69 Commits

Author SHA1 Message Date
461d1300ad Refactor app instance to Keycloak SSO 2026-06-15 15:54:39 +08:00
fc9fd93c36 feat: 支持多语言提示词本地化和界面优化
- 添加 prompt_locale 参数支持简体中文、繁体中文和英文提示词本地化
- 移除内置 agents 配置以简化系统架构
- 更新 ContextBuilder 使用动态提示词模板而非硬编码内容
- 在 AgentLoop、Web 接口和 AgentService 中传递 locale 参数
- 添加输出语言指令确保用户界面内容按指定语言生成
- 扩展前端 LanguageSwitcher 组件支持三种语言选项
- 优化 Header 和侧边栏组件的响应式布局和文本截断处理
- 更新测试用例验证不同语言环境下的提示词正确性
2026-06-10 16:11:05 +08:00
9cc3334ea7 ```
feat(app-instance): 添加Outlook MCP调用超时配置选项

新增OUTLOOK_MCP_CALL_TIMEOUT_SECONDS环境变量,默认值为60秒,
用于控制后端等待Outlook MCP调用的超时时间。

在create-instance.sh脚本中添加了相应的命令行参数解析和处理逻辑,
同时更新了deploy-control组件的相关配置和测试用例。

BREAKING CHANGE: 新增配置项可能需要现有部署进行相应调整。
```
2026-06-09 14:23:37 +08:00
dc4c6f313d fix(providers): avoid chat template body for vllm mistral 2026-06-09 13:19:09 +08:00
9e2c02a333 feat(skills-ui): show replay eval coverage 2026-06-08 13:38:10 +08:00
b9171998b9 feat(skill-learning): gate publish on replay confidence 2026-06-08 13:36:55 +08:00
64d789a3d0 feat(skill-learning): produce replay eval reports 2026-06-08 13:35:58 +08:00
cc1bf85517 feat(skill-learning): run replay arms through agent loop 2026-06-08 13:33:53 +08:00
4c8bc53d33 feat(skill-learning): add surrogate tool evaluator 2026-06-08 13:33:02 +08:00
70014c0f70 feat(engine): allow replay tool executor injection 2026-06-08 13:32:14 +08:00
eb69bb168a feat(skill-learning): add replay tool policy 2026-06-08 13:31:13 +08:00
7287e93f87 feat(skill-learning): select replay eval cases 2026-06-08 13:30:00 +08:00
a925f0e77f feat(skill-learning): preserve base skill during synthesis 2026-06-08 13:28:41 +08:00
6dc580ab26 feat(skill-learning): add draft preservation checks 2026-06-08 13:27:10 +08:00
3a16dc283d feat(skill-learning): extend eval report payload 2026-06-08 13:26:12 +08:00
0fd4df3c17 docs: plan skill replay eval implementation 2026-06-08 11:26:07 +08:00
f46a435bab docs: refine skill replay case selection 2026-06-08 10:46:35 +08:00
a28254c6b8 docs: design skill replay eval 2026-06-08 10:29:39 +08:00
0cf4f44346 提交修改 2026-06-08 10:19:57 +08:00
e0bc6c55b0 chore: update external connector deployment flow 2026-06-05 17:27:05 +08:00
2c5205b06e feat: 添加MinIO文件系统支持并优化外部连接器功能
- 添加MinIO用户文件系统配置选项(BEAVER_MINIO_ROOT_USER等)
- 更新外部连接器配置结构,包括BASE_URL和认证令牌设置
- 改进connector provider支持更多类型(official, feishu_bot等)
- 实现Mistral模型推理模式支持reasoning_effort参数
- 增强外部连接器策略配置和运行时配置管理
- 添加connector bridge事件验证和安全保护机制
- 优化任务路由逻辑,区分simple_chat和new_task场景
- 更新初始技能工具提示配置,分离authoring admin功能
2026-06-05 11:46:40 +08:00
236ac19789 test: add pytest asyncio dependency 2026-06-03 16:34:37 +08:00
ba2417c7f2 merge: personal user filesystem minio integration 2026-06-03 16:32:29 +08:00
f3655c86c9 merge: channel runtime v1 2026-06-03 16:23:07 +08:00
c3d84b904a feat: implement channel runtime connectors 2026-06-03 16:22:44 +08:00
ee972441f5 docs: harden external connector implementation plans 2026-06-03 10:32:50 +08:00
d335199a64 docs: add external connector implementation plans 2026-06-03 09:24:06 +08:00
feeaccc0e3 docs: tighten external connector contract 2026-06-03 09:12:30 +08:00
cf35edb4ca docs: decouple external connector sidecar design 2026-06-02 18:05:46 +08:00
e0a4862af8 docs: add openclaw sidecar connector design 2026-06-02 17:59:57 +08:00
c3a0aef104 docs: tighten channel connector API plan 2026-06-02 16:07:01 +08:00
b25713a141 docs: refine channel connectors foundation plan 2026-06-02 15:51:16 +08:00
d74a1c9c12 docs: add channel connectors foundation plan 2026-06-02 15:37:36 +08:00
834d4e1e2f docs: add channel connector pairing design 2026-06-02 15:17:46 +08:00
6a6ddc21c0 docs: design terminal websocket channel 2026-06-01 16:41:19 +08:00
826db8ec2e ```
feat(llm): 添加 Hermes Gateway LLM 设计文档
```
2026-06-01 16:05:15 +08:00
33a9845566 ```
feat(engine): 添加技能查看工具并优化异步任务管理

- 添加SkillViewTool到引擎加载器中,增强技能管理功能
- 在AgentLoop中引入_active_direct_task来跟踪活跃任务
- 实现直接任务执行时的同步处理逻辑
- 更新工具实例化方式以支持依赖注入

feat(config): 增加智能体运行时参数配置支持

- 扩展AgentDefaultsConfig添加max_tokens和temperature字段
- 实现配置解析函数_first_config_value处理多个配置源
- 支持通过Web API动态更新智能体运行时参数
- 添加前端页面配置表单和验证逻辑

refactor(provider): 统一最大令牌数参数类型为可选整型

- 将所有LLM提供者的max_tokens参数改为int | None类型
- 为AnthropicProvider实现模型特定的最大令牌数默认值
- 调整参数传递逻辑,优先级:调用参数 > 配置文件 > 模型默认值
- 移除硬编码的默认值,改用条件判断

feat(process): 增强事件投影功能

- 添加工具调用开始/结束事件的映射逻辑
- 实现技能激活事件的识别和展示
- 添加辅助函数处理工具调用名称和参数提取
- 优化运行记录关联逻辑,提升事件匹配准确性

fix(web): 更新网络请求客户端信任环境设置

- 将WebFetchTool和WebSearchTool的trust_env参数设为True
- 确保HTTP客户端能够正确使用系统代理配置
- 修复可能的网络连接问题

test: 添加配置加载和事件投影相关测试

- 新增智能体默认参数配置测试用例
- 实现API配置持久化和重载测试
- 添加技能卡片和工具事件的投影测试
```
2026-05-27 13:37:06 +08:00
55b39563a0 test: cover task detail live timeline updates 2026-05-26 13:49:31 +08:00
41ac87e322 feat: make task detail timeline first 2026-05-26 13:48:18 +08:00
542b23ef6e fix: tighten task detail component interactions 2026-05-26 12:48:27 +08:00
9002d1206f feat: add task detail timeline components 2026-05-26 12:30:22 +08:00
dd9f40b38c fix: allow user task timeline actor 2026-05-26 12:24:50 +08:00
96562877cc fix: align agent timeline event contract 2026-05-26 12:20:33 +08:00
f58a57e5b8 test: cover failed task team timeline projection 2026-05-26 12:13:20 +08:00
362aae9b12 feat: enrich task process timeline events 2026-05-26 12:09:57 +08:00
29d175222d fix: make acceptance timeline dedupe robust 2026-05-26 12:04:12 +08:00
2e4f8541ee fix: dedupe task timeline milestones 2026-05-26 11:59:49 +08:00
a1164dc49a fix: harden task timeline model 2026-05-26 11:52:46 +08:00
7b638b083a feat: add task timeline model 2026-05-26 11:28:57 +08:00
6e9e74d1ee feat(engine): 添加运行时上下文支持并重构工具迭代限制
添加 RuntimeContext 类用于捕获模型运行时的日期时间信息,
包括UTC时间、本地时间和时区信息,并在系统提示中显示这些信息。

同时增加最大上下文消息数和工具迭代次数的配置选项,
将验证服务从引擎加载器中移除,并更新相关的数据结构和接口。

BREAKING CHANGE: 移除了验证服务,相关字段被替换为证据状态和接受状态。

- 添加 RuntimeContext 类和相关渲染方法
- 增加 max_context_messages 和 max_tool_iterations 配置
- 移除 ValidationService 相关代码
- 更新消息记录中的验证状态字段
- 添加原始工具调用检测和回退处理
2026-05-26 11:18:35 +08:00
16347caf5e Add task detail live execution design 2026-05-26 10:55:16 +08:00
030bce8a60 feat(litellm): 添加 reasoning_content 支持并强制禁用思考模式
- 在 LiteLLMProvider 中添加 "reasoning_content" 到允许的消息键集合中
- 修改 _apply_thinking_mode 方法以强制禁用思考模式,不再基于模型名称判断
- 总是设置 enable_thinking 为 False 并添加 thinking.type: disabled 配置
- 更新相关测试用例验证新的思考模式行为

fix(web): 修复非运行状态下的直接处理逻辑

- 创建 _run_web_direct 辅助函数来处理代理服务的直接提交/处理逻辑
- 当代理服务未运行时使用 process_direct 而不是 submit_direct
- 更新 REST 和 WebSocket 接口以使用新的处理逻辑
- 添加相应的单元测试验证非运行状态下使用直接处理

test(config): 添加代理配置重载功能的测试

- 添加 test_reload_agent_config_updates_booted_loop_config 测试函数
- 验证配置文件更新后代理循环能够正确加载新配置
- 测试模型、API 基础地址和 API 密钥的更新

chore(frontend): 默认禁用前端思考模式偏好

- 将前端思考模式存储的默认值从 true 改为 false
- 确保窗口未定义时返回 false 而不是 true
- 更新本地存储缺失时的默认行为为禁用思考模式
2026-05-22 17:43:21 +08:00
c671b66043 feat(frontend): restore session progress sidebar 2026-05-22 14:34:45 +08:00
e061961a79 merge agent team evidence validation work 2026-05-22 11:51:05 +08:00
8068d86760 chore(engine): compact llm request snapshots 2026-05-22 11:40:21 +08:00
4022db8887 feat(team): run parallel nodes with isolated loops 2026-05-22 11:39:17 +08:00
c53e221117 feat(engine): finalize after tool iteration limit 2026-05-22 11:37:02 +08:00
b808f5cbc2 feat(task): route validation status to review states 2026-05-22 11:35:46 +08:00
0adc04806c feat(task): synthesize and validate from evidence 2026-05-22 11:33:39 +08:00
60605a74e0 feat(team): preserve node run evidence 2026-05-22 11:30:19 +08:00
3ff2e2ce11 fix(task): complete evidence rendering contract 2026-05-22 11:28:19 +08:00
0ace09b984 feat(task): add structured run evidence 2026-05-22 11:15:10 +08:00
c3c4df306b fix(task): reject unknown validation status payloads 2026-05-22 11:04:28 +08:00
5446614828 test(task): strengthen validation status semantics 2026-05-22 11:00:53 +08:00
2fd618da9c feat(task): add validation status semantics 2026-05-22 10:55:45 +08:00
28a2627b1f docs: plan task evidence validation implementation 2026-05-22 10:47:03 +08:00
249087e943 docs: clarify validation acceptance compatibility 2026-05-22 10:41:23 +08:00
8bff282892 docs: clarify task validation status semantics 2026-05-22 10:35:30 +08:00
3a3e848a78 docs: design task evidence validation refactor 2026-05-22 10:30:35 +08:00
359 changed files with 27578 additions and 15301 deletions

0
.codex
View File

View File

@ -1,30 +1,24 @@
# Shared values used by the root deployment flow in README.md
# Standalone app-instance defaults
PROJECT_ROOT=/home/ivan/xuan/beaver_project
BEAVER_NET=beaver-instance-edge
BEAVER_PROXY_CONTAINER_NAME=beaver-router-proxy
BEAVER_PUBLIC_URL=http://172.19.0.245:18080
BEAVER_HOST_IP=172.19.0.245
BEAVER_HOST_PORT=18080
BEAVER_DEPLOY_TOKEN=change-me
BEAVER_AUTHZ_INTERNAL_TOKEN=change-me
BEAVER_SERVER_IP=127.0.0.1
BEAVER_BASE_DOMAIN=localhost
BEAVER_PROVIDER=openai
BEAVER_MODEL=openai/gpt-5
BEAVER_API_KEY=sk-xxxxxxxx
BEAVER_API_BASE=
# Per-instance Beaver backend config. In Docker app-instance this should point
# to the mounted single-user sandbox config, not to frontend env.
BEAVER_HOME=/root/.beaver
BEAVER_CONFIG_PATH=/root/.beaver/config.json
BEAVER_WORKSPACE=/root/.beaver/workspace
# Must be reachable from app-instance containers.
BEAVER_AUTHZ_URL=http://beaver-authz-service:19090
BEAVER_OUTLOOK_MCP_URL=
BEAVER_OUTLOOK_MCP_SERVER_ID=outlook_mcp
# Keycloak SSO
BEAVER_KEYCLOAK_ISSUER=https://keycloak.bwgdi.com/realms/beaver
BEAVER_KEYCLOAK_CLIENT_ID=beaver-agnet
BEAVER_KEYCLOAK_REDIRECT_URI=http://172.19.0.245:18080/auth/callback
BEAVER_KEYCLOAK_POST_LOGOUT_REDIRECT_URI=http://172.19.0.245:18080/logout/callback
# Must be reachable from auth-portal and authz-service containers.
BEAVER_DEPLOY_URL=http://beaver-deploy-control:8090
# Model provider settings used when generating config.json with run-standalone.sh
BEAVER_PROVIDER=openai
BEAVER_MODEL=openai/gpt-5
BEAVER_API_KEY=
BEAVER_API_BASE=
# Optional runtime limits
BEAVER_USER_FILES_MAX_UPLOAD_BYTES=5368709120

1
.gitignore vendored
View File

@ -21,6 +21,7 @@ sessions/
**/.ruff_cache/
**/.mypy_cache/
**/.cache/
**/.codegraph/
**/.venv/
**/dist/
**/build/

12
AGENTS.md Normal file
View File

@ -0,0 +1,12 @@
# Repository Instructions
This branch is scoped to the standalone `app-instance` package.
Useful entry points:
- `app-instance/README.md`
- `app-instance/run-standalone.sh`
- `app-instance/backend`
- `app-instance/frontend`
The repository no longer owns the old auth portal, authz service, deploy control plane, router proxy, or per-user instance orchestration.

411
DESIGN.md
View File

@ -1,411 +0,0 @@
# DESIGN.md
## Brand
**Beaver — Taupe**
A calm editorial UI system focused on rhythm, hierarchy, and soft neutral contrast.
Designed for AI-native tools, dashboards, and minimalist productivity software.
The interface emphasizes:
- Spacious layouts
- Soft grayscale surfaces
- Typography-first hierarchy
- Rounded geometry
- Quiet shadows
- Dense information with low visual noise
The visual tone should feel:
- thoughtful
- mature
- calm
- premium
- architectural
- editorial
Avoid:
- saturated colors
- hard borders
- sharp corners
- excessive gradients
- loud shadows
- playful illustration-heavy UI
---
# Colors
## Core Palette
| Token | Hex | Usage |
|---|---|---|
| background | `#F5F3F1` | Main app background |
| foreground | `#0B0B0B` | Primary text |
| primary | `#1D1715` | Primary actions |
| secondary | `#E5E2DF` | Secondary surfaces |
| muted | `#DDD9D6` | Muted backgrounds |
| accent | `#CAC5C0` | Borders / subtle emphasis |
---
## Neutral Scale
| Token | Hex |
|---|---|
| zinc-50 | `#F7F5F4` |
| zinc-100 | `#ECE8E5` |
| zinc-200 | `#D8D2CE` |
| zinc-300 | `#B8AEA8` |
| zinc-400 | `#8B7E77` |
| zinc-500 | `#6A5E58` |
| zinc-600 | `#4F4642` |
| zinc-700 | `#342E2B` |
---
## Semantic Colors
### Taupe
| Step | Hex |
|---|---|
| taupe-100 | `#E7E2DE` |
| taupe-300 | `#B8AEA8` |
| taupe-500 | `#8B7E77` |
| taupe-700 | `#5F5550` |
### Sage
| Step | Hex |
|---|---|
| sage-100 | `#E3E8E2` |
| sage-300 | `#B7C2B5` |
| sage-500 | `#869683` |
| sage-700 | `#657162` |
### Slate
| Step | Hex |
|---|---|
| slate-100 | `#E4E7EB` |
| slate-300 | `#BCC4CE` |
| slate-500 | `#8C96A3` |
| slate-700 | `#697281` |
---
# Typography
## Philosophy
Typography drives hierarchy.
The system should feel like a modern editorial publication mixed with a productivity dashboard.
Large headings use elegant serif typography.
UI and body copy use neutral grotesk sans-serif typography.
---
## Font Stack
### Serif
```css
font-family: "Lora", Georgia, serif;
```
Used for:
- hero titles
- article headings
- marketing emphasis
- editorial sections
---
### Sans
```css
font-family: "Public Sans", Inter, sans-serif;
```
Used for:
- UI
- labels
- forms
- dashboards
- buttons
- navigation
---
## Type Scale
| Style | Size | Weight | Line Height |
|---|---|---|---|
| h1 | 48px | 600 | 1.1 |
| h2 | 36px | 600 | 1.15 |
| h3 | 28px | 500 | 1.2 |
| body-lg | 18px | 400 | 1.7 |
| body | 16px | 400 | 1.6 |
| small | 14px | 400 | 1.5 |
| mono | 13px | 500 | 1.4 |
---
# Radius
Rounded geometry should feel soft but architectural.
| Token | Radius |
|---|---|
| xs | 4px |
| sm | 8px |
| md | 12px |
| lg | 16px |
| xl | 24px |
| full | 999px |
Cards should primarily use:
```css
border-radius: 16px;
```
---
# Shadows
Shadows should be subtle and diffused.
Avoid strong elevation.
## Soft
```css
box-shadow:
0 1px 2px rgba(0,0,0,0.04),
0 6px 24px rgba(0,0,0,0.03);
```
## Floating
```css
box-shadow:
0 12px 40px rgba(0,0,0,0.06);
```
---
# Grid
## Layout
- 12-column grid
- Max width: `1280px`
- Horizontal padding: `32px`
- Large whitespace between sections
---
## Content Widths
| Type | Width |
|---|---|
| reading | 720px |
| dashboard | 1280px |
| modal | 480px |
| form | 560px |
---
# Spacing
Base unit:
```txt
4px
```
Spacing scale:
| Token | Value |
|---|---|
| 1 | 4px |
| 2 | 8px |
| 3 | 12px |
| 4 | 16px |
| 5 | 20px |
| 6 | 24px |
| 8 | 32px |
| 10 | 40px |
| 12 | 48px |
| 16 | 64px |
Use generous vertical rhythm.
Sections should breathe.
---
# Components
## Buttons
### Primary
- Dark background
- White text
- Pill radius
- Minimal shadow
```css
background: #1D1715;
color: white;
border-radius: 999px;
height: 40px;
padding: 0 16px;
```
### Secondary
```css
background: #ECE8E5;
color: #1D1715;
```
### Ghost
Transparent background with subtle hover fill.
---
## Cards
Cards are soft containers with quiet separation.
```css
background: rgba(255,255,255,0.7);
border: 1px solid rgba(0,0,0,0.04);
border-radius: 16px;
```
Avoid heavy borders.
---
## Inputs
Inputs should feel invisible until focused.
```css
background: #F7F5F4;
border: 1px solid transparent;
```
Focus:
```css
border-color: #8B7E77;
box-shadow: 0 0 0 3px rgba(139,126,119,0.12);
```
---
## Charts
Charts should use muted earthy tones.
Preferred palette:
- taupe
- sage
- slate
Avoid:
- neon colors
- bright blue dashboards
- rainbow charts
---
# Motion
Motion should be restrained and smooth.
Preferred easing:
```css
cubic-bezier(0.22, 1, 0.36, 1)
```
Preferred duration:
| Type | Duration |
|---|---|
| hover | 150ms |
| panel | 250ms |
| modal | 350ms |
---
# Layout Skeleton
Application layout:
- Left sidebar
- Large content canvas
- Floating top toolbar
- Soft dashboard cards
- Spacious internal padding
The UI should always feel:
- breathable
- editorial
- premium
- calm
Never dense or overly enterprise-looking.
---
# Design Keywords
Use these words when generating UI:
- editorial
- taupe
- soft neutral
- premium minimal
- typography-first
- architectural spacing
- calm dashboard
- quiet luxury
- modern serif
- subtle shadows
- muted grayscale
- sophisticated SaaS
---
# AI Agent Instructions
When generating UI:
1. Prioritize whitespace over density
2. Typography should create hierarchy
3. Use muted neutral palettes
4. Prefer soft cards over hard sections
5. Avoid excessive color usage
6. Keep interactions subtle
7. Use serif fonts sparingly for emphasis
8. Maintain premium visual restraint
9. Design should feel timeless rather than trendy
10. Every screen should feel breathable

198
README.md
View File

@ -1,183 +1,75 @@
# Beaver Project
# Beaver App Instance
`Beaver Project` 是一套单机 Docker 部署的多实例运行环境:
This branch contains a standalone Beaver app instance for an external orchestrator to deploy.
- 用户先进入独立的 `auth-portal` 完成注册或登录。
- 注册会触发 `authz-service` 调用 `deploy-control`
- `deploy-control` 在同一台机器上创建一个独立的 `app-instance` 容器。
- `router-proxy` 按实例域名把流量转发到对应容器。
The app instance is a single Docker image that runs:
当前推荐的最小部署方式是一台 Linux / WSL2 Ubuntu 机器加 Docker。生产域名和 HTTPS 可以放在项目外层的 Nginx、Caddy、Traefik 或云负载均衡上。
- Next.js frontend
- FastAPI backend
- Nginx reverse proxy
## 组件
Authentication is delegated to Keycloak. This repository does not maintain local user registration, passwords, per-user instance routing, or deployment orchestration.
| 目录 | 职责 | 默认端口 |
| --- | --- | --- |
| `auth-portal/` | 用户登录、注册、模型配置引导入口 | `3081` |
| `authz-service/` | AuthZ 服务,负责账号和 backend 身份编排 | `19090` |
| `deploy-control/` | 部署控制面,调用 Docker 创建和管理实例 | `8090` |
| `router-proxy/` | 统一实例入口代理,按 Host 分发到实例容器 | `8088` |
| `app-instance/` | 单用户运行实例,容器内包含前端、后端和 Nginx | 容器内 `8080` |
## Runtime Contract
公网环境通常只暴露:
The external orchestrator is responsible for:
- `auth-portal`: `3081`,或外层代理后的 `https://portal.example.com`
- `router-proxy`: `8088`,或外层代理后的 `https://<slug>.apps.example.com`
- Building or pulling the app image
- Providing a mounted Beaver home directory
- Providing `config.json`
- Choosing the public host and port
- Registering the public callback URL and post-logout callback URL in Keycloak
- Managing lifecycle, routing, TLS, and scaling
不要直接把 `deploy-control:8090``authz-service:19090` 暴露到公网。
## 请求链路
注册:
The app instance exposes container port `8080`:
```text
Browser
-> auth-portal
-> authz-service POST /portal/register
-> deploy-control POST /api/instances/register
-> app-instance/create-instance.sh
-> app-instance POST /api/auth/register
-> authz-service /oauth/register or /backends/register
-> auth-portal provider onboarding
-> deploy-control POST /api/instances/configure-provider
/ frontend
/api backend API
/ws backend WebSocket
```
登录:
## Keycloak
Default IdP settings:
```text
Browser
-> auth-portal
-> deploy-control POST /api/instances/resolve
-> app-instance POST /api/auth/login
-> app-instance frontend URL
issuer: https://keycloak.bwgdi.com/realms/beaver
client_id: beaver-agnet
```
## 快速开始
For the current plain-IP deployment, register these values in Keycloak:
本机完整流程见:
```text
web_origin: http://172.19.0.245:18080
redirect_uri: http://172.19.0.245:18080/auth/callback
post_logout_redirect_uri: http://172.19.0.245:18080/logout/callback
```
- [部署指南.md](./部署指南.md)
The app validates Keycloak JWT issuer, signature, expiry, audience/azp, and nonce where applicable. The Keycloak `sub` claim is used as the application user ID.
域名、HTTPS、公网反向代理说明见
- [域名配置指引.md](./域名配置指引.md)
最小配置变量:
## Build
```bash
export PROJECT_ROOT=/home/ivan/xuan/beaver_project
export BEAVER_NET=beaver-instance-edge
export BEAVER_PROXY_CONTAINER_NAME=beaver-router-proxy
export BEAVER_DEPLOY_TOKEN="$(openssl rand -hex 32)"
export BEAVER_AUTHZ_INTERNAL_TOKEN="$(openssl rand -hex 32)"
export BEAVER_BASE_DOMAIN=localhost
export BEAVER_AUTHZ_URL='http://beaver-authz-service:19090'
export BEAVER_DEPLOY_URL='http://beaver-deploy-control:8090'
export BEAVER_OUTLOOK_MCP_URL=''
export BEAVER_OUTLOOK_MCP_SERVER_ID='outlook_mcp'
cd app-instance
docker build -t beaver/app-instance:keycloak-login .
```
启动顺序:
1. 创建运行目录。
2. 构建四个镜像。
3. 创建共享 Docker network。
4. 启动 `router-proxy`
5. 启动 `authz-service`
6. 启动 `deploy-control`
7. 启动 `auth-portal`
8. 打开 `http://127.0.0.1:3081/register` 测试注册。
## 关键配置关系
`DEPLOY_API_TOKEN``DEPLOY_CONTROL_API_TOKEN` 必须相等:
- `auth-portal` / `authz-service``DEPLOY_API_TOKEN` 请求 `deploy-control`
- `deploy-control``DEPLOY_CONTROL_API_TOKEN` 校验请求。
`AUTHZ_ISSUER` 在这套单机部署里要写容器网络地址:
```text
http://beaver-authz-service:19090
```
不要写成 `http://127.0.0.1:19090`,因为新创建的 `app-instance` 容器里的 `127.0.0.1` 指向它自己,不是 AuthZ 容器。
`DEPLOY_PUBLIC_*` 决定新实例展示给用户的 URL
## Run Locally
```bash
DEPLOY_PUBLIC_SCHEME=http
DEPLOY_PUBLIC_BASE_DOMAIN=localhost
DEPLOY_PUBLIC_PORT=8088
cd app-instance
./run-standalone.sh --build --replace
```
本机测试时实例 URL 形如:
The script prints the `web_origin`, `redirect_uri`, and `post_logout_redirect_uri` values that must be configured in Keycloak.
```text
http://alice.localhost:8088
```
## Useful Paths
正式 HTTPS 域名通常改成:
- `app-instance/` - app image, frontend, backend, runtime helper script, app tests
- `skills/` - reusable skill content retained for product/runtime packaging
- `agents/` - agent registry retained for runtime packaging
- `docs/` - product and architecture documentation
- `AGENTS.md` - local coding-agent instructions
```bash
DEPLOY_PUBLIC_SCHEME=https
DEPLOY_PUBLIC_BASE_DOMAIN=apps.example.com
DEPLOY_PUBLIC_PORT=443
```
实例 URL 形如:
```text
https://alice.apps.example.com
```
前提是你已经在项目外层把 `*.apps.example.com``80/443` 流量转发到 `router-proxy:8088`
## 模型配置方式
当前版本不会在注册创建实例时写入模型 provider、model 或 API key。
流程是:
1. 注册先创建一个不含模型凭证的实例。
2. `auth-portal` 进入模型配置引导页。
3. 用户确认后Portal 调用 `deploy-control /api/instances/configure-provider`
4. `deploy-control` 写入该实例的 `config.json` 并重启对应容器。
如果用户跳过引导,实例仍会创建成功,但后续需要在实例内补齐 provider 配置后才能正常调用模型。
## 持久化目录
至少保留:
```text
authz-service/runtime/data
app-instance/runtime/instances
app-instance/runtime/registry
router-proxy/runtime/conf.d
```
不要在需要保留账号、实例或配置时删除这些目录。
## 模板文件
可参考这些环境变量模板:
- [`.env.example`](./.env.example)
- [`auth-portal/src/.env.example`](./auth-portal/src/.env.example)
- [`authz-service/.env.example`](./authz-service/.env.example)
- [`deploy-control/.env.example`](./deploy-control/.env.example)
- [`router-proxy/.env.example`](./router-proxy/.env.example)
这些模板不会被脚本自动加载。你可以手动 `export`,也可以在 `docker run` 时使用 `--env-file`
## 子项目文档
- [`app-instance/README.md`](./app-instance/README.md)
- [`auth-portal/src/README.md`](./auth-portal/src/README.md)
- [`authz-service/README.md`](./authz-service/README.md)
- [`deploy-control/README.md`](./deploy-control/README.md)
- [`router-proxy/README.md`](./router-proxy/README.md)
See `app-instance/README.md` for the app-specific contract and environment variables.

View File

@ -1,4 +1,5 @@
runtime/
.env
backend/.git/
backend/.venv/
backend/.pytest_cache/
@ -13,4 +14,3 @@ frontend/node_modules/
frontend/.next/
frontend/.next-dev/
frontend/tsconfig.tsbuildinfo

28
app-instance/.env.example Normal file
View File

@ -0,0 +1,28 @@
# Docker image/runtime
IMAGE_NAME=beaver/app-instance:keycloak
CONTAINER_NAME=beaver-app-instance
HOST_IP=172.19.0.245
HOST_PORT=18080
HOST_BIND_IP=0.0.0.0
DATA_DIR=runtime/standalone
DOCKER_NETWORK=
# Beaver model config rendered into runtime/standalone/beaver-home/config.json
BEAVER_PROVIDER=custom
BEAVER_MODEL=
BEAVER_API_KEY=
BEAVER_API_BASE=
# Keycloak public client
KEYCLOAK_ISSUER=https://keycloak.bwgdi.com/realms/beaver
KEYCLOAK_CLIENT_ID=beaver-agnet
KEYCLOAK_REDIRECT_URI=
KEYCLOAK_POST_LOGOUT_REDIRECT_URI=
# Build mirrors
NPM_REGISTRY=https://registry.npmmirror.com
NPM_FETCH_RETRIES=5
NPM_FETCH_RETRY_MIN_TIMEOUT=20000
NPM_FETCH_RETRY_MAX_TIMEOUT=120000
APT_MIRROR=https://mirrors.tuna.tsinghua.edu.cn/debian
PYPI_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple

View File

@ -20,11 +20,15 @@ RUN --mount=type=cache,target=/root/.npm \
COPY frontend/ ./
ARG NEXT_PUBLIC_AUTH_PORTAL_URL=""
ARG NEXT_PUBLIC_AUTH_PORTAL_PORT="3081"
ARG NEXT_PUBLIC_KEYCLOAK_ISSUER="https://keycloak.bwgdi.com/realms/beaver"
ARG NEXT_PUBLIC_KEYCLOAK_CLIENT_ID="beaver-agnet"
ARG NEXT_PUBLIC_KEYCLOAK_REDIRECT_URI=""
ARG NEXT_PUBLIC_KEYCLOAK_POST_LOGOUT_REDIRECT_URI=""
ENV NEXT_PUBLIC_AUTH_PORTAL_URL=${NEXT_PUBLIC_AUTH_PORTAL_URL}
ENV NEXT_PUBLIC_AUTH_PORTAL_PORT=${NEXT_PUBLIC_AUTH_PORTAL_PORT}
ENV NEXT_PUBLIC_KEYCLOAK_ISSUER=${NEXT_PUBLIC_KEYCLOAK_ISSUER}
ENV NEXT_PUBLIC_KEYCLOAK_CLIENT_ID=${NEXT_PUBLIC_KEYCLOAK_CLIENT_ID}
ENV NEXT_PUBLIC_KEYCLOAK_REDIRECT_URI=${NEXT_PUBLIC_KEYCLOAK_REDIRECT_URI}
ENV NEXT_PUBLIC_KEYCLOAK_POST_LOGOUT_REDIRECT_URI=${NEXT_PUBLIC_KEYCLOAK_POST_LOGOUT_REDIRECT_URI}
# API / WS 走同域反代,不在构建时写死实例地址。
RUN npm run build
@ -39,7 +43,6 @@ ENV DEBIAN_FRONTEND=noninteractive \
BEAVER_HOME=/root/.beaver \
BEAVER_CONFIG_PATH=/root/.beaver/config.json \
BEAVER_WORKSPACE=/root/.beaver/workspace \
BEAVER_AUTH_FILE=/root/.beaver/web_auth_users.json \
PORT=3000 \
HOSTNAME=127.0.0.1
@ -47,8 +50,12 @@ ARG NPM_REGISTRY="https://registry.npmmirror.com"
ARG NPM_FETCH_RETRIES="5"
ARG NPM_FETCH_RETRY_MIN_TIMEOUT="20000"
ARG NPM_FETCH_RETRY_MAX_TIMEOUT="120000"
ARG APT_MIRROR="https://mirrors.tuna.tsinghua.edu.cn/debian"
ARG PYPI_INDEX_URL="https://pypi.tuna.tsinghua.edu.cn/simple"
RUN apt-get update && \
RUN find /etc/apt -type f \( -name "*.list" -o -name "*.sources" \) -exec \
sed -i "s|http://deb.debian.org/debian-security|${APT_MIRROR}-security|g; s|http://deb.debian.org/debian|${APT_MIRROR}|g; s|http://security.debian.org/debian-security|${APT_MIRROR}-security|g" {} + && \
apt-get update && \
apt-get install -y --no-install-recommends curl ca-certificates gnupg git nginx dumb-init && \
mkdir -p /etc/apt/keyrings && \
curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg && \
@ -63,7 +70,7 @@ WORKDIR /opt/app/backend
COPY backend/pyproject.toml backend/README.md ./
COPY backend/beaver/ ./beaver/
RUN uv pip install --system --no-cache .
RUN uv pip install --system --no-cache --index-url "${PYPI_INDEX_URL}" ".[channels]"
WORKDIR /opt/app/frontend
COPY --from=frontend-builder /build/frontend/next.config.js ./

View File

@ -1,118 +1,56 @@
# app-instance
实例应用单元:
- 一个 Docker 容器里同时运行前端、后端和 Nginx 反代
- 前端走 `/`
- 后端 API 走 `/api`
- WebSocket 走 `/ws`
体 app instance一个 Docker 容器内运行前端、后端和 Nginx。这个目录只提供干净的应用实例不再负责用户注册登录、实例编排、注册表或反向代理路由。
## 关键文件
- `Dockerfile`
- 统一镜像构建入口
- `entrypoint.sh`
- 容器内启动前端、后端、Nginx
- `create-instance.sh`
- 创建实例目录、生成配置、启动容器、写注册表
- `remove-instance.sh`
- 删除容器、移除注册表、可选清理实例目录
- `list-instances.sh`
- 查看当前注册实例
- `instance-registry.py`
- 维护 `runtime/registry/instances.json`
- `Dockerfile`: 统一镜像构建入口
- `entrypoint.sh`: 容器内启动前端、后端、Nginx
- `run-standalone.sh`: 从 `.env` 读取参数,构建并运行单体容器
- `.env.example`: 可复制的部署参数模板
## 注册表
## Keycloak SSO
默认注册表路径
当前登录交给 Keycloak
- issuer: `https://keycloak.bwgdi.com/realms/beaver`
- client_id: `beaver-agnet`
- flow: Authorization Code + PKCE S256
- password grant: disabled
- client secret: none
应用需要在 Keycloak client 中配置:
- `redirect_uri`: `http://<host-ip>:<host-port>/auth/callback`
- `post_logout_redirect_uri`: `http://<host-ip>:<host-port>/logout/callback`
- `web_origin`: `http://<host-ip>:<host-port>`
默认单机部署示例:
```text
runtime/registry/instances.json
redirect_uri: http://172.19.0.245:18080/auth/callback
post_logout_redirect_uri: http://172.19.0.245:18080/logout/callback
web_origin: http://172.19.0.245:18080
```
每条记录至少包含:
- `instance_id`
- `instance_slug`
- `container_name`
- `host_port`
- `public_url`
- `instance_root`
- `image_name`
## 常用命令
### 1. 构建镜像
## 部署
```bash
docker build -t beaver/app-instance:latest .
cp .env.example .env
./run-standalone.sh --build --replace
```
### 2. 创建实例
脚本会输出当前需要填到 Keycloak 的 `redirect_uri``post_logout_redirect_uri``web_origin`
```bash
./create-instance.sh \
--image beaver/app-instance:latest \
--instance-id demo-001 \
--auth-username admin \
--auth-password 123456 \
--api-key 'your-api-key'
```
## 数据目录
可选参数
- `--host-port`
- `--public-url`
- `--username`
- `--email`
- `--instance-host`
- `--authz-base-url`
- `--backend-id`
- `--client-id`
- `--client-secret`
- `--network`
- `--host-bind-ip`
- `--build`
- `--replace`
### 3. 查看实例
```bash
./list-instances.sh
./list-instances.sh --json
```
### 4. 删除实例
```bash
./remove-instance.sh --instance-id demo-001
```
如果要把实例目录也一并清掉:
```bash
./remove-instance.sh --instance-id demo-001 --purge-data
```
## 目录约定
默认实例数据目录:
默认数据目录
```text
runtime/instances/<instance-slug>/
runtime/standalone/beaver-home/
```
其中会生成
```text
runtime/instances/<instance-slug>/
└── beaver-home
├── config.json
├── web_auth_users.json
└── workspace/
```
这个目录是单用户 sandbox 的配置与数据边界。容器内会把它挂到:
容器内挂载到
```text
/root/.beaver/
@ -125,28 +63,4 @@ BEAVER_CONFIG_PATH=/root/.beaver/config.json
BEAVER_WORKSPACE=/root/.beaver/workspace
```
所以模型 `provider/api_key/api_base/model` 配一次即可Web / channel 请求不需要、也不应该携带 API Key
## 当前状态
这层已经支持:
- 统一镜像构建
- 镜像内安装并启动新的 `beaver` 后端
- 实例创建
- 实例删除
- 实例列表
- 基于注册表的端口分配
- 为 deploy-control / router-proxy 记录用户名和实例 host
## 生产注意
- 实例容器的宿主机端口默认只绑定 `127.0.0.1`
- 外部访问应统一走 `router-proxy`
- 如果你确实要把单个实例端口直接暴露到公网,再显式传 `--host-bind-ip 0.0.0.0`
下一步可以继续接:
- portal 调用创建实例
- URL 分配和反向代理
- 实例续期 / 停用 / 启用
模型 provider、API key、workspace 数据都在这个目录下维护

View File

@ -0,0 +1,4 @@
{
"agents": [],
"version": 1
}

View File

@ -18,8 +18,9 @@ if TYPE_CHECKING:
class TeamGraphScheduler:
"""Execute sequence, parallel, and DAG team graphs."""
def __init__(self, runner: LocalAgentRunner) -> None:
def __init__(self, runner: LocalAgentRunner, *, max_parallel_team_nodes: int = 3) -> None:
self.runner = runner
self.max_parallel_team_nodes = max(1, int(max_parallel_team_nodes))
async def run(
self,
@ -96,7 +97,18 @@ class TeamGraphScheduler:
nodes: list[ExecutionNode],
**kwargs,
) -> list[NodeRunResult]:
return list(await asyncio.gather(*(self._run_node(node, dependency_outputs={}, **kwargs) for node in nodes)))
semaphore = asyncio.Semaphore(self.max_parallel_team_nodes)
async def run_one(node: ExecutionNode) -> NodeRunResult:
async with semaphore:
return await self._run_node(
node,
dependency_outputs={},
execution_mode="isolated_loop",
**kwargs,
)
return list(await asyncio.gather(*(run_one(node) for node in nodes)))
async def _run_dag(
self,
@ -164,6 +176,7 @@ class TeamGraphScheduler:
inherited_pinned_skill_contexts: list["SkillContext"],
allow_candidate_generation: bool,
dependency_outputs: dict[str, str],
execution_mode: str = "shared_loop",
) -> NodeRunResult:
try:
pinned = self._merge_pinned(inherited_pinned_skills, node.inherited_pinned_skills)
@ -189,6 +202,7 @@ class TeamGraphScheduler:
envelope,
provider_bundle=node_provider_bundle,
allow_candidate_generation=allow_candidate_generation,
execution_mode=execution_mode,
)
except asyncio.CancelledError:
raise
@ -241,7 +255,7 @@ class TeamGraphScheduler:
failed = [item for item in results if not item.success]
if failed:
failure_lines = [
f"- {item.node_id}: {item.error or item.finish_reason}"
f"- {item.node_id}: {item.error or item.finish_reason} evidence={'yes' if item.evidence else 'no'}"
for item in failed
]
summary_parts.append("Failed nodes:\n" + "\n".join(failure_lines))

View File

@ -6,6 +6,7 @@ from uuid import uuid4
from beaver.engine import AgentLoop
from beaver.engine.providers import ProviderBundle
from beaver.tasks.evidence import EvidenceBuilder
from .models import DelegationEnvelope, NodeRunResult
@ -22,6 +23,7 @@ class LocalAgentRunner:
*,
provider_bundle: ProviderBundle | None = None,
allow_candidate_generation: bool = False,
execution_mode: str = "shared_loop",
) -> NodeRunResult:
if provider_bundle is not None and (envelope.agent.model or envelope.agent.provider_name):
raise ValueError(
@ -29,7 +31,14 @@ class LocalAgentRunner:
"build a node-specific provider bundle instead."
)
child_session_id = self._child_session_id(envelope)
runner = self.loop.submit_direct if self.loop.is_running else self.loop.process_direct
target_loop = self.loop
if execution_mode == "isolated_loop":
target_loop = AgentLoop(profile=self.loop.profile, loader=self.loop.loader)
runner = (
target_loop.process_direct
if execution_mode == "isolated_loop"
else (self.loop.submit_direct if self.loop.is_running else self.loop.process_direct)
)
result = await runner(
envelope.task,
session_id=child_session_id,
@ -47,6 +56,13 @@ class LocalAgentRunner:
pinned_skill_contexts=envelope.inherited_pinned_skill_contexts,
allow_candidate_generation=allow_candidate_generation,
)
loaded = target_loop.boot()
evidence = EvidenceBuilder(loaded.session_manager).build_run_evidence(
result.session_id,
result.run_id,
result.output_text,
result.finish_reason,
)
success = result.finish_reason == "stop"
return NodeRunResult(
node_id=envelope.node_id or envelope.agent.name,
@ -56,6 +72,7 @@ class LocalAgentRunner:
session_id=result.session_id,
finish_reason=result.finish_reason,
error=None if success else (result.output_text or result.finish_reason),
evidence=evidence,
)
@staticmethod

View File

@ -7,6 +7,7 @@ from typing import TYPE_CHECKING, Any, Literal
if TYPE_CHECKING:
from beaver.engine.context import SkillContext
from beaver.tasks.evidence import RunEvidence
TeamStrategy = Literal[
@ -116,6 +117,7 @@ class NodeRunResult:
session_id: str | None = None
finish_reason: str = "stop"
error: str | None = None
evidence: "RunEvidence | None" = None
def to_dict(self) -> dict[str, Any]:
return {
@ -126,6 +128,7 @@ class NodeRunResult:
"session_id": self.session_id,
"finish_reason": self.finish_reason,
"error": self.error,
"evidence": self.evidence.to_dict() if self.evidence is not None else None,
}

View File

@ -15,7 +15,9 @@ class AgentRegistry:
self.path = self.workspace / "agents" / "registry.json"
self.path.parent.mkdir(parents=True, exist_ok=True)
if not self.path.exists():
self._write_agents(_builtin_agents())
self._write_agents([])
else:
self._drop_legacy_builtin_agents()
def list_agents(self, *, include_disabled: bool = True) -> list[RegisteredAgent]:
agents = self._read_agents()
@ -125,72 +127,14 @@ class AgentRegistry:
payload = {"version": 1, "agents": [agent.to_dict() for agent in agents]}
self.path.write_text(json.dumps(payload, ensure_ascii=False, indent=2, sort_keys=True) + "\n", encoding="utf-8")
def _drop_legacy_builtin_agents(self) -> None:
agents = self._read_agents()
migrated = [agent for agent in agents if agent.source != "builtin"]
if len(migrated) != len(agents):
self._write_agents(migrated)
def _terms(text: str) -> set[str]:
normalized = "".join(ch.lower() if ch.isalnum() else " " for ch in text)
return {part for part in normalized.split() if part}
def _builtin_agents() -> list[RegisteredAgent]:
return [
RegisteredAgent(
agent_id="researcher",
name="researcher",
display_name="Researcher",
role="research",
description="Finds facts, references, constraints, and implementation options.",
system_prompt="You are a research specialist. Gather concise evidence and tradeoffs for the parent task.",
capabilities=["research", "analysis", "source review", "requirements"],
tags=["planning", "research"],
priority=50,
source="builtin",
),
RegisteredAgent(
agent_id="implementer",
name="implementer",
display_name="Implementer",
role="implementation",
description="Builds scoped implementation slices and proposes concrete changes.",
system_prompt="You are an implementation specialist. Produce practical, scoped implementation output.",
capabilities=["implementation", "coding", "refactor", "integration"],
tags=["coding", "build"],
priority=45,
source="builtin",
),
RegisteredAgent(
agent_id="reviewer",
name="reviewer",
display_name="Reviewer",
role="review",
description="Reviews plans, code, outputs, and risks before final synthesis.",
system_prompt="You are a review specialist. Focus on defects, missing requirements, and risks.",
capabilities=["review", "quality", "risk", "verification"],
tags=["review", "quality"],
priority=45,
source="builtin",
),
RegisteredAgent(
agent_id="tester",
name="tester",
display_name="Tester",
role="testing",
description="Designs and executes verification checks for task outputs.",
system_prompt="You are a testing specialist. Identify focused checks and report pass/fail evidence.",
capabilities=["testing", "verification", "regression", "qa"],
tags=["test", "quality"],
priority=40,
source="builtin",
),
RegisteredAgent(
agent_id="documenter",
name="documenter",
display_name="Documenter",
role="documentation",
description="Writes and reconciles user-facing and internal documentation updates.",
system_prompt="You are a documentation specialist. Produce concise docs aligned with the implementation.",
capabilities=["documentation", "explanation", "migration notes", "release notes"],
tags=["docs", "communication"],
priority=35,
source="builtin",
),
]

View File

@ -4,6 +4,7 @@ from .builder import (
ContextBuildInput,
ContextBuildResult,
ContextBuilder,
RuntimeContext,
SessionContext,
SkillContext,
)
@ -12,6 +13,7 @@ __all__ = [
"ContextBuildInput",
"ContextBuildResult",
"ContextBuilder",
"RuntimeContext",
"SessionContext",
"SkillContext",
]

View File

@ -27,13 +27,7 @@ from dataclasses import dataclass, field
from typing import Any
from beaver.memory.curated.snapshot import MemorySnapshot
BEAVER_USER_ASSISTANT_IDENTITY_PROMPT = (
"You are 海狸 (Beaver), an AI assistant developed by 博维资讯系统有限公司. "
"When communicating with users, keep this identity consistent. "
"If users ask who you are, say that you are 海狸 (Beaver), 博维资讯系统有限公司研发的 AI 助手."
)
from beaver.prompts import get_main_agent_prompt
@dataclass(slots=True)
@ -76,10 +70,25 @@ class SessionContext:
model: str | None = None
user_id: str | None = None
channel: str | None = None
channel_kind: str | None = None
account_id: str | None = None
peer_id: str | None = None
peer_type: str | None = None
chat_id: str | None = None
thread_id: str | None = None
parent_session_id: str | None = None
@dataclass(slots=True)
class RuntimeContext:
"""Per-run runtime facts that should be visible to the model."""
utc_datetime: str
local_datetime: str
timezone: str | None = None
utc_offset: str | None = None
@dataclass(slots=True)
class ContextBuildInput:
"""一次上下文构建所需的全部输入。
@ -98,11 +107,13 @@ class ContextBuildInput:
"""
base_system_prompt: str = ""
prompt_locale: str | None = None
history: list[dict[str, Any]] = field(default_factory=list)
current_user_input: str | list[dict[str, Any]] | None = None
memory_snapshot: MemorySnapshot | None = None
activated_skills: list[SkillContext] = field(default_factory=list)
session_context: SessionContext | None = None
runtime_context: RuntimeContext | None = None
execution_context: str | None = None
extra_sections: list[str] = field(default_factory=list)
@ -143,9 +154,10 @@ class ContextBuilder:
1. Beaver user-facing assistant identity
2. base system prompt
3. session metadata
4. execution context
5. frozen memory snapshot
6. extra sections
4. runtime date/time
5. execution context
6. frozen memory snapshot
7. extra sections
这样设计的原因:
- 身份与总规则要最靠前
@ -154,7 +166,7 @@ class ContextBuilder:
- activated skill 正文放到显式消息里,避免 system prompt 持续膨胀
"""
sections: list[str] = [BEAVER_USER_ASSISTANT_IDENTITY_PROMPT]
sections: list[str] = [get_main_agent_prompt(build_input.prompt_locale)]
base_system_prompt = (build_input.base_system_prompt or "").strip()
if base_system_prompt:
@ -164,6 +176,10 @@ class ContextBuilder:
if session_section:
sections.append(session_section)
runtime_section = self._render_runtime_section(build_input.runtime_context)
if runtime_section:
sections.append(runtime_section)
execution_context = (build_input.execution_context or "").strip()
if execution_context:
sections.append(f"# Execution Context\n\n{execution_context}")
@ -338,8 +354,18 @@ class ContextBuilder:
rows.append(f"User ID: {session_context.user_id}")
if session_context.channel:
rows.append(f"Channel: {session_context.channel}")
if session_context.channel_kind:
rows.append(f"Channel Kind: {session_context.channel_kind}")
if session_context.account_id:
rows.append(f"Account ID: {session_context.account_id}")
if session_context.peer_id:
rows.append(f"Peer ID: {session_context.peer_id}")
if session_context.peer_type:
rows.append(f"Peer Type: {session_context.peer_type}")
if session_context.chat_id:
rows.append(f"Chat ID: {session_context.chat_id}")
if session_context.thread_id:
rows.append(f"Thread ID: {session_context.thread_id}")
if session_context.parent_session_id:
rows.append(f"Parent Session ID: {session_context.parent_session_id}")
@ -347,6 +373,31 @@ class ContextBuilder:
return None
return "# Current Session\n\n" + "\n".join(rows)
def _render_runtime_section(self, runtime_context: RuntimeContext | None) -> str | None:
"""Render date/time facts captured for the current model run."""
if runtime_context is None:
return None
rows: list[str] = []
if runtime_context.utc_datetime:
rows.append(f"Current UTC time: {runtime_context.utc_datetime}")
if runtime_context.local_datetime:
rows.append(f"Current local time: {runtime_context.local_datetime}")
if runtime_context.timezone:
rows.append(f"Local timezone: {runtime_context.timezone}")
if runtime_context.utc_offset:
rows.append(f"Local UTC offset: {runtime_context.utc_offset}")
if not rows:
return None
return (
"# Current Date and Time\n\n"
+ "\n".join(rows)
+ "\n\nUse this section as authoritative for relative date/time references such as "
'"today", "tomorrow", "now", "this week", and "next month".'
)
def build_skill_activation_messages(self, activated_skills: list[SkillContext]) -> list[dict[str, str]]:
"""把已激活 skill 转成显式消息。

View File

@ -24,7 +24,7 @@ from beaver.skills.learning.eval import SkillDraftEvaluator
from beaver.skills.publisher import SkillPublisher
from beaver.skills.reviews import ReviewService
from beaver.skills.specs import SkillSpecStore
from beaver.tasks import TaskExecutionPlanner, TaskService, ValidationService
from beaver.tasks import TaskExecutionPlanner, TaskService
from beaver.tasks.skill_resolver import TaskSkillResolver
from beaver.skills import SkillAssembler, SkillsLoader
from beaver.tools import ObjectBackedTool, ToolAssembler, ToolExecutor, ToolRegistry
@ -44,6 +44,7 @@ from beaver.tools.builtins import (
SpawnTool,
SessionSearchTool,
SkillManageTool,
SkillViewTool,
SkillsListTool,
TerminalTool,
TodoTool,
@ -97,7 +98,6 @@ class EngineLoadResult:
task_skill_resolver: TaskSkillResolver | None = None
task_service: TaskService | None = None
task_execution_planner: TaskExecutionPlanner | None = None
validation_service: ValidationService | None = None
mcp_manager: MCPConnectionManager | None = None
mcp_report: dict[str, dict] = field(default_factory=dict)
closeables: list[tuple[str, Callable[[], None]]] = field(default_factory=list, repr=False)
@ -172,7 +172,6 @@ class EngineLoader:
task_skill_resolver: TaskSkillResolver | None = None,
task_service: TaskService | None = None,
task_execution_planner: TaskExecutionPlanner | None = None,
validation_service: ValidationService | None = None,
) -> None:
self.config = config or load_config(workspace=workspace, config_path=config_path)
configured_workspace = self.config.agents_defaults.workspace
@ -198,7 +197,6 @@ class EngineLoader:
self._task_skill_resolver = task_skill_resolver
self._task_service = task_service
self._task_execution_planner = task_execution_planner
self._validation_service = validation_service
def load(self) -> EngineLoadResult:
"""装配当前主链需要的最小 runtime 对象。"""
@ -235,16 +233,17 @@ class EngineLoader:
ObjectBackedTool(UserFilesCopyToWorkspaceTool()),
ObjectBackedTool(UserFilesPublishOutputTool()),
ObjectBackedTool(WebFetchTool()),
ObjectBackedTool(WebSearchTool()),
ObjectBackedTool(TerminalTool()),
ObjectBackedTool(ProcessTool()),
ObjectBackedTool(ExecuteCodeTool()),
ObjectBackedTool(TodoTool()),
ObjectBackedTool(ClarifyTool()),
ObjectBackedTool(SendMessageTool()),
ObjectBackedTool(DelegateTool()),
ObjectBackedTool(SpawnTool()),
SkillsListTool(),
ObjectBackedTool(WebSearchTool()),
ObjectBackedTool(TerminalTool()),
ObjectBackedTool(ProcessTool()),
ObjectBackedTool(ExecuteCodeTool()),
ObjectBackedTool(TodoTool()),
ObjectBackedTool(ClarifyTool()),
ObjectBackedTool(SendMessageTool()),
ObjectBackedTool(DelegateTool()),
ObjectBackedTool(SpawnTool()),
SkillsListTool(),
ObjectBackedTool(SkillViewTool(loader=skills_loader)),
SkillManageTool(),
CronTool(),
]
@ -288,7 +287,6 @@ class EngineLoader:
)
task_service = self._task_service or TaskService(workspace / "tasks")
task_execution_planner = self._task_execution_planner or TaskExecutionPlanner(task_skill_resolver=task_skill_resolver)
validation_service = self._validation_service or ValidationService()
mcp_manager = MCPConnectionManager(
self.config.tools.mcp_servers,
authz_config=self.config.authz,
@ -323,7 +321,6 @@ class EngineLoader:
task_skill_resolver=task_skill_resolver,
task_service=task_service,
task_execution_planner=task_execution_planner,
validation_service=validation_service,
mcp_manager=mcp_manager,
)
if self._session_manager is None:

View File

@ -4,12 +4,16 @@ from __future__ import annotations
import asyncio
import json
import os
import re
from dataclasses import dataclass, field
from datetime import datetime, timezone
from typing import Any
from uuid import uuid4
from zoneinfo import ZoneInfo, ZoneInfoNotFoundError
from beaver.engine.context import ContextBuildInput, SessionContext, SkillContext
from beaver.engine.context import ContextBuildInput, RuntimeContext, SessionContext, SkillContext
from beaver.foundation.events import ChannelIdentity
from beaver.memory.runs import RunRecord, SkillEffectRecord
from beaver.skills.learning import RunReceiptContext
from beaver.skills.catalog.utils import strip_frontmatter
@ -26,6 +30,17 @@ TOOL_FAILURE_GUIDANCE_PROMPT = (
"Use available materials, state uncertainty clearly, and provide partial confirmed results."
)
RAW_TOOL_CALL_FALLBACK = (
"The run reached the configured tool-call limit before producing a reliable final answer. "
"The model attempted another tool call instead of answering, so the raw tool call was suppressed. "
"Please request a revision to continue the task."
)
_RAW_TOOL_CALL_RE = re.compile(
r"^\s*<tool_call\b[\s\S]*?</tool_call>\s*$|^\s*<function=[^>]+>[\s\S]*?</function>\s*$",
re.IGNORECASE,
)
@dataclass(slots=True)
class AgentProfile:
@ -34,9 +49,10 @@ class AgentProfile:
name: str = "default"
system_prompt: str = ""
default_model: str = "gpt-4.1-mini"
max_tokens: int = 4096
max_tokens: int | None = None
max_context_messages: int = 1000
temperature: float = 0.2
max_tool_iterations: int = 8
max_tool_iterations: int = 30
@dataclass(slots=True)
@ -74,6 +90,7 @@ class AgentLoop:
self.loaded: EngineLoadResult | None = None
self.runtime_services: dict[str, Any] = {}
self._run_queue: asyncio.Queue[_DirectRunRequest | None] | None = None
self._active_direct_task: asyncio.Task[Any] | None = None
self._running = False
self._stop_requested = False
@ -115,6 +132,8 @@ class AgentLoop:
if item.future.cancelled():
continue
previous_direct_task = self._active_direct_task
self._active_direct_task = asyncio.current_task()
try:
result = await self._process_direct_impl(item.task, **item.kwargs)
except asyncio.CancelledError:
@ -127,6 +146,8 @@ class AgentLoop:
else:
if not item.future.done():
item.future.set_result(result)
finally:
self._active_direct_task = previous_direct_task
finally:
if self._run_queue is not None:
while True:
@ -168,6 +189,9 @@ class AgentLoop:
if self._stop_requested:
raise RuntimeError("AgentLoop.submit_direct() is not accepting new tasks after stop()")
if asyncio.current_task() is self._active_direct_task:
return await self._process_direct_impl(task, **kwargs)
future: asyncio.Future[AgentRunResult] = asyncio.get_running_loop().create_future()
await self._run_queue.put(_DirectRunRequest(task=task, kwargs=dict(kwargs), future=future))
return await future
@ -200,6 +224,7 @@ class AgentLoop:
title: str | None = None,
execution_context: str | None = None,
skill_selection_context: str | None = None,
prompt_locale: str | None = None,
model: str | None = None,
provider_name: str | None = None,
api_key: str | None = None,
@ -223,8 +248,10 @@ class AgentLoop:
attempt_index: int | None = None,
pinned_skill_names: list[str] | None = None,
pinned_skill_contexts: list[SkillContext] | None = None,
tool_executor_override: Any = None,
allow_candidate_generation: bool = False,
intent_agent_decision: dict[str, Any] | None = None,
channel_identity: ChannelIdentity | None = None,
) -> AgentRunResult:
"""跑通最小 direct run 主链。
@ -249,6 +276,7 @@ class AgentLoop:
title=title,
execution_context=execution_context,
skill_selection_context=skill_selection_context,
prompt_locale=prompt_locale,
model=model,
provider_name=provider_name,
api_key=api_key,
@ -272,8 +300,10 @@ class AgentLoop:
attempt_index=attempt_index,
pinned_skill_names=pinned_skill_names,
pinned_skill_contexts=pinned_skill_contexts,
tool_executor_override=tool_executor_override,
allow_candidate_generation=allow_candidate_generation,
intent_agent_decision=intent_agent_decision,
channel_identity=channel_identity,
)
async def _process_direct_impl(
@ -286,6 +316,7 @@ class AgentLoop:
title: str | None = None,
execution_context: str | None = None,
skill_selection_context: str | None = None,
prompt_locale: str | None = None,
model: str | None = None,
provider_name: str | None = None,
api_key: str | None = None,
@ -309,8 +340,10 @@ class AgentLoop:
attempt_index: int | None = None,
pinned_skill_names: list[str] | None = None,
pinned_skill_contexts: list[SkillContext] | None = None,
tool_executor_override: Any = None,
allow_candidate_generation: bool = False,
intent_agent_decision: dict[str, Any] | None = None,
channel_identity: ChannelIdentity | None = None,
) -> AgentRunResult:
"""真正执行一轮 direct run 的内部实现。
@ -327,6 +360,7 @@ class AgentLoop:
tool_registry = self._require_loaded("tool_registry")
tool_assembler = self._require_loaded("tool_assembler")
tool_executor = self._require_loaded("tool_executor")
effective_tool_executor = tool_executor_override or tool_executor
skills_loader = self._require_loaded("skills_loader")
skill_assembler = self._require_loaded("skill_assembler")
skill_learning_service = self._require_loaded("skill_learning_service")
@ -348,7 +382,7 @@ class AgentLoop:
resolved_request_timeout_seconds = configured_provider.get("request_timeout_seconds")
resolved_embedding_model = embedding_model or config.default_embedding_model
resolved_embedding_target = embedding_target or config.resolve_embedding_target()
resolved_max_tokens = max_tokens or self.profile.max_tokens
resolved_max_tokens = self.profile.max_tokens if max_tokens is None else max_tokens
resolved_temperature = self.profile.temperature if temperature is None else temperature
resolved_max_tool_iterations = (
self.profile.max_tool_iterations if max_tool_iterations is None else max_tool_iterations
@ -446,7 +480,7 @@ class AgentLoop:
*(pinned_skill_contexts or []),
*self._load_pinned_skill_contexts(skills_loader, pinned_skill_names or []),
]
if not include_skill_assembly or thinking_enabled is False:
if not include_skill_assembly:
activated_skills = self._merge_skill_contexts(pinned_skills, [])
else:
skill_query = skill_selection_context or task
@ -512,8 +546,6 @@ class AgentLoop:
if not include_tools:
selected_tool_specs = []
elif thinking_enabled is False:
selected_tool_specs = tool_registry.list_specs()
else:
selected_tool_specs = await tool_assembler.assemble(
task_description=task,
@ -543,7 +575,11 @@ class AgentLoop:
build_input = ContextBuildInput(
base_system_prompt=self.profile.system_prompt,
history=session_manager.get_history(resolved_session_id),
prompt_locale=prompt_locale,
history=session_manager.get_history(
resolved_session_id,
max_messages=max(1, self.profile.max_context_messages),
),
current_user_input=task,
memory_snapshot=memory_snapshot,
activated_skills=activated_skills,
@ -552,8 +588,16 @@ class AgentLoop:
source=source,
model=resolved_model,
user_id=user_id,
channel=channel_identity.channel_id if channel_identity else None,
channel_kind=channel_identity.kind if channel_identity else None,
account_id=channel_identity.account_id if channel_identity else None,
peer_id=channel_identity.peer_id if channel_identity else None,
peer_type=channel_identity.peer_type if channel_identity else None,
chat_id=channel_identity.peer_id if channel_identity else None,
thread_id=channel_identity.thread_id if channel_identity else None,
parent_session_id=parent_session_id,
),
runtime_context=self._current_runtime_context(),
execution_context=execution_context,
extra_sections=[TOOL_FAILURE_GUIDANCE_PROMPT],
)
@ -643,36 +687,39 @@ class AgentLoop:
while True:
chat_kwargs: dict[str, Any] = {
"messages": messages,
"tools": tool_schemas,
"tools": tool_schemas if include_tools else None,
"model": final_model,
"max_tokens": resolved_max_tokens,
"temperature": resolved_temperature,
}
if thinking_enabled is not None:
chat_kwargs["thinking_enabled"] = thinking_enabled
message_char_length = len(json.dumps(messages, ensure_ascii=False, default=str))
tool_schema_char_length = len(json.dumps(tool_schemas, ensure_ascii=False, default=str))
tool_names = [
str(tool.get("function", {}).get("name") or tool.get("name") or "tool")
for tool in (tool_schemas or [])
if isinstance(tool, dict)
]
snapshot_payload = {
"iteration": iterations,
"provider_name": final_provider_name,
"model": final_model,
"message_count": len(messages),
"tool_names": tool_names,
"message_char_length": message_char_length,
"tool_schema_char_length": tool_schema_char_length,
"max_tokens": resolved_max_tokens,
"temperature": resolved_temperature,
"thinking_enabled": thinking_enabled,
}
session_manager.append_message(
resolved_session_id,
run_id=resolved_run_id,
role="system",
event_type="llm_request_snapshotted",
event_payload={
"iteration": iterations,
"provider_name": final_provider_name,
"model": final_model,
"messages": messages,
"tools": tool_schemas,
"max_tokens": resolved_max_tokens,
"temperature": resolved_temperature,
"thinking_enabled": thinking_enabled,
},
content=json.dumps(
{
"messages": messages,
"tools": tool_schemas,
},
ensure_ascii=False,
default=str,
),
event_payload=snapshot_payload,
content=json.dumps(snapshot_payload, ensure_ascii=False, default=str),
context_visible=False,
source=source,
title=title,
@ -696,6 +743,7 @@ class AgentLoop:
tool_calls=assistant_tool_calls or None,
finish_reason=response.finish_reason,
reasoning=response.reasoning_content,
context_visible=not bool(assistant_tool_calls),
source=source,
title=title,
model=final_model,
@ -710,12 +758,24 @@ class AgentLoop:
if not response.has_tool_calls:
final_text = response.content or ""
final_finish_reason = response.finish_reason or "stop"
if self._looks_like_raw_tool_call(final_text):
final_text = RAW_TOOL_CALL_FALLBACK
final_finish_reason = "invalid_tool_call_text"
else:
final_finish_reason = response.finish_reason or "stop"
break
if iterations >= resolved_max_tool_iterations:
final_text = response.content or "Tool loop stopped after reaching the configured iteration limit."
final_finish_reason = "max_tool_iterations"
finalized = await self._finalize_after_tool_limit(
provider=provider,
messages=messages,
model=final_model,
max_tokens=resolved_max_tokens,
temperature=resolved_temperature,
thinking_enabled=thinking_enabled,
)
final_text = finalized or RAW_TOOL_CALL_FALLBACK
final_finish_reason = "max_tool_iterations_finalized" if finalized else "max_tool_iterations"
session_manager.append_message(
resolved_session_id,
run_id=resolved_run_id,
@ -737,7 +797,7 @@ class AgentLoop:
iterations += 1
for tool_call in response.tool_calls:
result = await tool_executor.execute_tool_call(tool_call, context=tool_context)
result = await effective_tool_executor.execute_tool_call(tool_call, context=tool_context)
session_manager.append_message(
resolved_session_id,
run_id=resolved_run_id,
@ -859,6 +919,56 @@ class AgentLoop:
raise RuntimeError(f"Engine loader did not provide required dependency {field_name!r}")
return value
@staticmethod
async def _finalize_after_tool_limit(
*,
provider: Any,
messages: list[dict[str, Any]],
model: str,
max_tokens: int | None,
temperature: float,
thinking_enabled: bool | None,
) -> str:
final_messages = AgentLoop._with_system_guidance(
messages,
(
"The configured tool iteration budget is exhausted. Do not call tools. "
"Produce the best final answer from the existing conversation and tool results. "
"State uncertainty explicitly."
),
)
kwargs: dict[str, Any] = {
"messages": final_messages,
"tools": None,
"model": model,
"max_tokens": max_tokens,
"temperature": temperature,
}
if thinking_enabled is not None:
kwargs["thinking_enabled"] = thinking_enabled
response = await provider.chat(**kwargs)
if response.has_tool_calls:
return ""
content = (response.content or "").strip()
if AgentLoop._looks_like_raw_tool_call(content):
return ""
return content
@staticmethod
def _looks_like_raw_tool_call(content: str | None) -> bool:
if not content:
return False
return bool(_RAW_TOOL_CALL_RE.match(content))
@staticmethod
def _with_system_guidance(messages: list[dict[str, Any]], guidance: str) -> list[dict[str, Any]]:
copied = [dict(message) for message in messages]
if copied and copied[0].get("role") == "system":
existing = str(copied[0].get("content") or "").strip()
copied[0]["content"] = "\n\n".join(part for part in (existing, guidance.strip()) if part)
return copied
return [{"role": "system", "content": guidance.strip()}, *copied]
@staticmethod
def _load_pinned_skill_contexts(skills_loader: Any, skill_names: list[str]) -> list[SkillContext]:
contexts: list[SkillContext] = []
@ -1092,3 +1202,49 @@ class AgentLoop:
@staticmethod
def _utc_now() -> str:
return datetime.now(timezone.utc).isoformat()
@staticmethod
def _current_runtime_context() -> RuntimeContext:
utc_now = datetime.now(timezone.utc)
timezone_name = AgentLoop._configured_timezone_name()
local_now = datetime.now().astimezone()
rendered_timezone = local_now.tzname()
if timezone_name:
try:
local_now = utc_now.astimezone(ZoneInfo(timezone_name))
rendered_timezone = timezone_name
except ZoneInfoNotFoundError:
rendered_timezone = local_now.tzname() or timezone_name
return RuntimeContext(
utc_datetime=utc_now.isoformat(),
local_datetime=local_now.isoformat(),
timezone=rendered_timezone,
utc_offset=AgentLoop._format_utc_offset(local_now),
)
@staticmethod
def _configured_timezone_name() -> str | None:
for value in (os.getenv("BEAVER_RUNTIME_TIMEZONE"), os.getenv("TZ")):
cleaned = (value or "").strip()
if cleaned:
return cleaned
try:
timezone_file = "/etc/timezone"
if os.path.exists(timezone_file):
with open(timezone_file, encoding="utf-8") as file:
cleaned = file.read().strip()
if cleaned:
return cleaned
except OSError:
return None
return None
@staticmethod
def _format_utc_offset(value: datetime) -> str | None:
raw = value.strftime("%z")
if not raw:
return None
return f"{raw[:3]}:{raw[3:]}"

View File

@ -43,7 +43,7 @@ class AnthropicProvider(LLMProvider):
messages: list[dict[str, Any]],
tools: list[dict[str, Any]] | None = None,
model: str | None = None,
max_tokens: int = 4096,
max_tokens: int | None = None,
temperature: float = 0.7,
thinking_enabled: bool | None = None,
) -> LLMResponse:
@ -57,9 +57,14 @@ class AnthropicProvider(LLMProvider):
"model": model or self.default_model,
"system": system_prompt or "",
"messages": anthropic_messages,
"max_tokens": max(1, max_tokens),
"temperature": temperature,
}
resolved_max_tokens = (
_default_max_tokens_for_model(model or self.default_model)
if max_tokens is None
else max(1, max_tokens)
)
kwargs["max_tokens"] = resolved_max_tokens
if tools:
kwargs["tools"] = _convert_tools(tools)
@ -100,6 +105,17 @@ class AnthropicProvider(LLMProvider):
return self.default_model
def _default_max_tokens_for_model(model: str) -> int:
"""Return a conservative native output ceiling for Anthropic Messages."""
normalized = model.lower().replace("_", "-")
if "sonnet-4" in normalized or "opus-4" in normalized or "3-7" in normalized or "3.7" in normalized:
return 64_000
if "haiku" in normalized:
return 4_096
return 8_192
def _convert_messages(messages: list[dict[str, Any]]) -> tuple[str, list[dict[str, Any]]]:
system_prompt = ""
converted: list[dict[str, Any]] = []

View File

@ -88,7 +88,7 @@ class LLMProvider(ABC):
messages: list[dict[str, Any]],
tools: list[dict[str, Any]] | None = None,
model: str | None = None,
max_tokens: int = 4096,
max_tokens: int | None = None,
temperature: float = 0.7,
thinking_enabled: bool | None = None,
) -> LLMResponse:

View File

@ -56,7 +56,7 @@ class FallbackProviderChain(LLMProvider):
messages: list[dict],
tools: list[dict] | None = None,
model: str | None = None,
max_tokens: int = 4096,
max_tokens: int | None = None,
temperature: float = 0.7,
thinking_enabled: bool | None = None,
) -> LLMResponse:
@ -115,7 +115,7 @@ class FallbackProviderChain(LLMProvider):
messages: list[dict],
tools: list[dict] | None,
model: str,
max_tokens: int,
max_tokens: int | None,
temperature: float,
thinking_enabled: bool | None,
) -> LLMResponse:

View File

@ -39,7 +39,7 @@ class OpenAICodexProvider(LLMProvider):
messages: list[dict[str, Any]],
tools: list[dict[str, Any]] | None = None,
model: str | None = None,
max_tokens: int = 4096,
max_tokens: int | None = None,
temperature: float = 0.7,
thinking_enabled: bool | None = None,
) -> LLMResponse:

View File

@ -47,7 +47,7 @@ class CustomProvider(LLMProvider):
messages: list[dict[str, Any]],
tools: list[dict[str, Any]] | None = None,
model: str | None = None,
max_tokens: int = 4096,
max_tokens: int | None = None,
temperature: float = 0.7,
thinking_enabled: bool | None = None,
) -> LLMResponse:
@ -55,9 +55,10 @@ class CustomProvider(LLMProvider):
kwargs: dict[str, Any] = {
"model": model or self.default_model,
"messages": self.sanitize_empty_content(messages),
"max_tokens": max(1, max_tokens),
"temperature": temperature,
}
if max_tokens is not None:
kwargs["max_tokens"] = max(1, max_tokens)
if tools:
kwargs.update(tools=tools, tool_choice="auto")
try:

View File

@ -3,9 +3,11 @@
from __future__ import annotations
from contextlib import contextmanager
from ipaddress import ip_address
import json
import os
from typing import Any
from urllib.parse import urlsplit
from .base import LLMProvider, LLMResponse, ToolCallRequest
from .registry import find_by_model, find_by_name, find_gateway
@ -23,7 +25,24 @@ except ModuleNotFoundError: # pragma: no cover
litellm = None # type: ignore[assignment]
acompletion = None # type: ignore[assignment]
_ALLOWED_MSG_KEYS = frozenset({"role", "content", "tool_calls", "tool_call_id", "name"})
_ALLOWED_MSG_KEYS = frozenset({"role", "content", "tool_calls", "tool_call_id", "name", "reasoning_content"})
def _looks_like_local_vllm_api_base(api_base: str | None) -> bool:
if not api_base:
return False
lowered = api_base.lower()
if "vllm" in lowered or "localhost" in lowered:
return True
host = urlsplit(lowered).hostname or ""
if host in {"127.0.0.1", "::1", "0.0.0.0"}:
return True
try:
parsed_host = ip_address(host)
except ValueError:
return False
return parsed_host.is_private or parsed_host.is_loopback
class LiteLLMProvider(LLMProvider):
@ -119,13 +138,23 @@ class LiteLLMProvider(LLMProvider):
@staticmethod
def _sanitize_messages(messages: list[dict[str, Any]]) -> list[dict[str, Any]]:
sanitized = []
system_contents: list[str] = []
for message in messages:
clean = {key: value for key, value in message.items() if key in _ALLOWED_MSG_KEYS}
if clean.get("role") == "system":
content = clean.get("content")
if isinstance(content, str) and content.strip():
system_contents.append(content.strip())
elif content is not None:
system_contents.append(str(content))
continue
if clean.get("role") == "assistant" and "content" not in clean:
clean["content"] = None
if isinstance(clean.get("tool_calls"), list):
clean["tool_calls"] = LiteLLMProvider._sanitize_tool_calls(clean["tool_calls"])
sanitized.append(clean)
if system_contents:
sanitized.insert(0, {"role": "system", "content": "\n\n".join(system_contents)})
return sanitized
@staticmethod
@ -175,23 +204,34 @@ class LiteLLMProvider(LLMProvider):
kwargs["provider"] = provider_payload
def _apply_thinking_mode(self, original_model: str, resolved_model: str, kwargs: dict[str, Any], enabled: bool | None) -> None:
if enabled is None:
return
model_key = f"{original_model} {resolved_model}".lower()
if "qwen" not in model_key:
if self._uses_mistral_reasoning_parser(original_model, resolved_model):
if enabled is not None:
extra_body = dict(kwargs.get("extra_body") or {})
extra_body["reasoning_effort"] = "high" if enabled else "none"
kwargs["extra_body"] = extra_body
return
extra_body = dict(kwargs.get("extra_body") or {})
chat_template_kwargs = dict(extra_body.get("chat_template_kwargs") or {})
chat_template_kwargs["enable_thinking"] = bool(enabled)
chat_template_kwargs["enable_thinking"] = False
extra_body["chat_template_kwargs"] = chat_template_kwargs
extra_body["thinking"] = {"type": "disabled"}
kwargs["extra_body"] = extra_body
def _uses_mistral_reasoning_parser(self, original_model: str, resolved_model: str) -> bool:
model_names = f"{original_model} {resolved_model}".lower()
if "mistral" not in model_names:
return False
if self.provider_name == "vllm":
return True
return self.provider_name in {"openai", "custom"} and _looks_like_local_vllm_api_base(self.api_base)
async def chat(
self,
messages: list[dict[str, Any]],
tools: list[dict[str, Any]] | None = None,
model: str | None = None,
max_tokens: int = 4096,
max_tokens: int | None = None,
temperature: float = 0.7,
thinking_enabled: bool | None = None,
) -> LLMResponse:
@ -204,10 +244,11 @@ class LiteLLMProvider(LLMProvider):
kwargs: dict[str, Any] = {
"model": resolved_model,
"messages": sanitized_messages,
"max_tokens": max(1, max_tokens),
"temperature": temperature,
"timeout": self.request_timeout_seconds or 45.0,
}
if max_tokens is not None:
kwargs["max_tokens"] = max(1, max_tokens)
if self.api_key:
kwargs["api_key"] = self.api_key
if self.api_base:

View File

@ -84,8 +84,10 @@ class MessageRecord:
payload["task_id"] = self.event_payload.get("task_id")
if self.event_payload.get("task_status"):
payload["task_status"] = self.event_payload.get("task_status")
if self.event_payload.get("validation_status"):
payload["validation_status"] = self.event_payload.get("validation_status")
if self.event_payload.get("evidence_status"):
payload["evidence_status"] = self.event_payload.get("evidence_status")
if self.event_payload.get("acceptance_state"):
payload["acceptance_state"] = self.event_payload.get("acceptance_state")
if self.event_payload.get("feedback_state"):
payload["feedback_state"] = self.event_payload.get("feedback_state")
if self.event_payload.get("feedback_error"):

View File

@ -13,6 +13,7 @@ from .schema import (
AuthzConfig,
BackendIdentityConfig,
BeaverConfig,
ChannelConfig,
EmbeddingConfig,
MCPServerConfig,
ProviderConfig,
@ -73,6 +74,7 @@ def load_config(
embedding=_parse_embedding(data),
tools=_parse_tools(data.get("tools")),
authz=_parse_authz(data.get("authz")),
channels=_parse_channels(data.get("channels")),
backend_identity=_parse_backend_identity(data.get("backend_identity") or data.get("backendIdentity")),
config_path=path,
)
@ -86,6 +88,25 @@ def _parse_agent_defaults(data: dict[str, Any]) -> AgentDefaultsConfig:
model=_string(defaults.get("model") or data.get("model")),
provider=_string(defaults.get("provider") or data.get("provider")),
embedding_model=_string(defaults.get("embeddingModel") or defaults.get("embedding_model") or data.get("embeddingModel")),
max_tokens=_int(_first_config_value(
defaults.get("maxTokens"),
defaults.get("max_tokens"),
data.get("maxTokens"),
data.get("max_tokens"),
)),
temperature=_float(_first_config_value(defaults.get("temperature"), data.get("temperature"))),
max_context_messages=_int(
defaults.get("maxContextMessages")
or defaults.get("max_context_messages")
or data.get("maxContextMessages")
or data.get("max_context_messages")
),
max_tool_iterations=_int(_first_config_value(
defaults.get("maxToolIterations"),
defaults.get("max_tool_iterations"),
data.get("maxToolIterations"),
data.get("max_tool_iterations"),
)),
)
@ -177,6 +198,48 @@ def _parse_authz(raw: Any) -> AuthzConfig:
)
def _parse_channels(raw: Any) -> dict[str, ChannelConfig]:
channels: dict[str, ChannelConfig] = {}
for channel_id, payload in _as_dict(raw).items():
cleaned_id = str(channel_id).strip()
if not cleaned_id:
continue
channels[cleaned_id] = _parse_channel_config(payload)
return channels
def _parse_channel_config(payload: Any) -> ChannelConfig:
data = _as_dict(payload)
return ChannelConfig(
enabled=_bool(data.get("enabled"), default=False),
kind=_string(data.get("kind")) or "",
mode=_string(data.get("mode")) or "webhook",
account_id=_string(data.get("accountId") or data.get("account_id")) or "",
display_name=_string(data.get("displayName") or data.get("display_name")) or "",
config=_normalize_config_map(data.get("config")),
secrets=_string_dict(data.get("secrets")),
)
def _normalize_config_map(value: Any) -> dict[str, Any]:
if not isinstance(value, dict):
return {}
return {
_camel_to_snake_key(str(key)): item
for key, item in value.items()
if str(key).strip()
}
def _camel_to_snake_key(value: str) -> str:
result: list[str] = []
for char in value:
if char.isupper() and result:
result.append("_")
result.append(char.lower())
return "".join(result)
def _parse_backend_identity(raw: Any) -> BackendIdentityConfig:
data = _as_dict(raw)
return BackendIdentityConfig(
@ -192,6 +255,13 @@ def _as_dict(value: Any) -> dict[str, Any]:
return value if isinstance(value, dict) else {}
def _first_config_value(*values: Any) -> Any:
for value in values:
if value not in (None, ""):
return value
return None
def _string(value: Any) -> str | None:
if value is None:
return None
@ -217,6 +287,13 @@ def _float(value: Any) -> float | None:
return float(value)
def _int(value: Any) -> int | None:
parsed = _float(value)
if parsed is None:
return None
return int(parsed)
def _bool(value: Any, *, default: bool) -> bool:
if isinstance(value, bool):
return value

View File

@ -25,6 +25,10 @@ class AgentDefaultsConfig:
model: str | None = None
provider: str | None = None
embedding_model: str | None = None
max_tokens: int | None = None
temperature: float | None = None
max_context_messages: int | None = None
max_tool_iterations: int | None = None
@dataclass(slots=True)
@ -87,6 +91,19 @@ class AuthzConfig:
outlook_mcp_url: str = ""
@dataclass(slots=True)
class ChannelConfig:
"""One configured channel adapter instance."""
enabled: bool = False
kind: str = ""
mode: str = "webhook"
account_id: str = ""
display_name: str = ""
config: dict[str, Any] = field(default_factory=dict)
secrets: dict[str, str] = field(default_factory=dict)
@dataclass(slots=True)
class BackendIdentityConfig:
"""This backend's AuthZ client identity."""
@ -107,6 +124,7 @@ class BeaverConfig:
embedding: EmbeddingConfig = field(default_factory=EmbeddingConfig)
tools: ToolsConfig = field(default_factory=ToolsConfig)
authz: AuthzConfig = field(default_factory=AuthzConfig)
channels: dict[str, ChannelConfig] = field(default_factory=dict)
backend_identity: BackendIdentityConfig = field(default_factory=BackendIdentityConfig)
config_path: Path | None = None

View File

@ -1,5 +1,5 @@
"""Event contracts and dispatch helpers."""
from .message_bus import InboundMessage, MessageBus, OutboundMessage
from .message_bus import ChannelIdentity, InboundMessage, MessageBus, OutboundMessage
__all__ = ["InboundMessage", "MessageBus", "OutboundMessage"]
__all__ = ["ChannelIdentity", "InboundMessage", "MessageBus", "OutboundMessage"]

View File

@ -9,12 +9,58 @@ from typing import Any
from uuid import uuid4
@dataclass(slots=True)
class ChannelIdentity:
"""Normalized channel routing identity.
`channel_id` is the Beaver adapter instance id, not the platform kind.
"""
channel_id: str
kind: str
account_id: str
peer_id: str
thread_id: str | None = None
peer_type: str = "unknown"
user_id: str | None = None
message_id: str | None = None
def validation_error(self) -> str | None:
if not self.channel_id.strip():
return "channel_id is required"
if not self.account_id.strip():
return "account_id is required"
if not self.peer_id.strip():
return "peer_id is required"
return None
def session_id(self) -> str:
parts = [self.channel_id, self.account_id, self.peer_id]
if self.thread_id:
parts.append(self.thread_id)
return ":".join(_clean_session_part(part) for part in parts)
def dedupe_key(self) -> str | None:
if not self.message_id:
return None
return f"{self.session_id()}:{_clean_session_part(self.message_id)}"
def _clean_session_part(value: str) -> str:
cleaned = str(value).strip()
if not cleaned:
return "unknown"
return cleaned.replace(":", "_")
@dataclass(slots=True)
class InboundMessage:
"""A minimal inbound message accepted by the gateway bridge."""
channel: str
content: str
content_type: str = "text"
channel_identity: ChannelIdentity | None = None
session_id: str | None = None
user_id: str | None = None
title: str | None = None
@ -35,6 +81,8 @@ class OutboundMessage:
content: str
session_id: str | None
finish_reason: str
content_type: str = "text"
channel_identity: ChannelIdentity | None = None
message_id: str = field(default_factory=lambda: str(uuid4()))
run_id: str | None = None
provider_name: str | None = None

View File

@ -1,7 +1,17 @@
"""Channel interfaces."""
from .base import ChannelAdapter
from .base import ChannelInboundSink
from .external_connector import ExternalConnectorChannel
from .manager import ChannelManager
from .memory import MemoryChannelAdapter
from .terminal_websocket import TerminalWebSocketAdapter
__all__ = ["ChannelAdapter", "ChannelManager", "MemoryChannelAdapter"]
__all__ = [
"ChannelAdapter",
"ChannelInboundSink",
"ExternalConnectorChannel",
"ChannelManager",
"MemoryChannelAdapter",
"TerminalWebSocketAdapter",
]

View File

@ -2,16 +2,17 @@
from __future__ import annotations
from typing import Protocol
from typing import Any, Protocol
from beaver.foundation.events import MessageBus, OutboundMessage
from beaver.foundation.events import InboundMessage, OutboundMessage
class ChannelAdapter(Protocol):
"""Minimal contract every gateway channel must implement."""
"""Minimal contract every runtime channel adapter must implement."""
name: str
bus: MessageBus
channel_id: str
kind: str
mode: str
async def start(self) -> None:
"""Prepare the channel before messages are routed."""
@ -22,3 +23,9 @@ class ChannelAdapter(Protocol):
async def send(self, message: OutboundMessage) -> None:
"""Deliver an outbound message to the concrete channel."""
class ChannelInboundSink(Protocol):
"""Runtime callback used by adapters to submit normalized inbound messages."""
async def accept_inbound(self, message: InboundMessage) -> Any:
"""Accept a normalized inbound message from an adapter."""

View File

@ -0,0 +1,29 @@
"""Channel connection setup layer."""
from .connectors import ChannelConnector, ChannelConnectorRegistry
from .dedupe import ConnectorMessageDedupeRecord, DedupeBeginResult, MessageDedupeStore
from .external import ExternalConnectorBase, FeishuConnector, WeixinConnector
from .models import ChannelConnection, ChannelRuntimeSpec, PairingSession, ValidationResult
from .sidecar_client import ConnectorSidecarClient
from .store import ChannelConnectionStore, CredentialStore, PairingTokenStore
from .telegram import TelegramConnector
__all__ = [
"ChannelConnector",
"ChannelConnectorRegistry",
"ConnectorMessageDedupeRecord",
"DedupeBeginResult",
"MessageDedupeStore",
"ExternalConnectorBase",
"FeishuConnector",
"WeixinConnector",
"ConnectorSidecarClient",
"ChannelConnection",
"ChannelRuntimeSpec",
"PairingSession",
"ValidationResult",
"ChannelConnectionStore",
"CredentialStore",
"PairingTokenStore",
"TelegramConnector",
]

View File

@ -0,0 +1,93 @@
"""Channel connector registry."""
from __future__ import annotations
from typing import Protocol
from beaver.foundation.config.schema import ChannelConfig
from .models import ChannelRuntimeSpec, ValidationResult
from .store import ChannelConnectionStore, CredentialStore
class ChannelConnector(Protocol):
kind: str
async def validate(self, connection_id: str) -> ValidationResult:
...
async def materialize_runtime(self, connection_id: str) -> ChannelRuntimeSpec:
...
async def revoke(self, connection_id: str) -> None:
...
class ChannelConnectorRegistry:
def __init__(self, *, connection_store: ChannelConnectionStore, credential_store: CredentialStore) -> None:
self.connection_store = connection_store
self.credential_store = credential_store
self._connectors: dict[str, ChannelConnector] = {}
def register(self, connector: ChannelConnector) -> None:
kind = connector.kind.strip()
if not kind:
raise ValueError("Connector kind is required")
if kind in self._connectors:
raise ValueError(f"Connector already registered: {kind}")
self._connectors[kind] = connector
def connectors(self) -> list[dict[str, str]]:
return [{"kind": kind} for kind in sorted(self._connectors)]
def connector_for_kind(self, kind: str) -> ChannelConnector:
return self._connector(kind)
async def validate(self, connection_id: str) -> ValidationResult:
connection = self.connection_store.get(connection_id)
connector = self._connector(connection.kind)
result = await connector.validate(connection_id)
self.connection_store.update_status(
connection_id,
status=result.status,
last_error=result.error,
)
return result
async def materialize_runtime(self, connection_id: str) -> ChannelRuntimeSpec:
connection = self.connection_store.get(connection_id)
return await self._connector(connection.kind).materialize_runtime(connection_id)
async def materialize_connected_runtime_specs(self) -> list[ChannelRuntimeSpec]:
specs: list[ChannelRuntimeSpec] = []
for connection in self.connection_store.list():
if connection.status not in {"connected", "running"}:
continue
specs.append(await self._connector(connection.kind).materialize_runtime(connection.connection_id))
return specs
async def materialize_channel_configs(self) -> dict[str, ChannelConfig]:
channels: dict[str, ChannelConfig] = {}
for spec in await self.materialize_connected_runtime_specs():
secrets = self.credential_store.get(spec.secrets_ref) if spec.secrets_ref else {}
channels[spec.channel_id] = ChannelConfig(
enabled=True,
kind=spec.kind,
mode=spec.mode,
account_id=spec.account_id,
display_name=spec.display_name,
config=dict(spec.config),
secrets=secrets,
)
return channels
async def revoke(self, connection_id: str) -> None:
connection = self.connection_store.get(connection_id)
await self._connector(connection.kind).revoke(connection_id)
self.connection_store.revoke(connection_id)
def _connector(self, kind: str) -> ChannelConnector:
connector = self._connectors.get(kind)
if connector is None:
raise KeyError(f"Connector not registered: {kind}")
return connector

View File

@ -0,0 +1,144 @@
"""Bridge event dedupe store for external connector retries."""
from __future__ import annotations
import json
from dataclasses import asdict, dataclass
from datetime import datetime, timezone
from pathlib import Path
from threading import Lock
from typing import Any
def _iso_now() -> str:
return datetime.now(timezone.utc).isoformat()
def _parse_iso(value: str) -> datetime:
return datetime.fromisoformat(value.replace("Z", "+00:00"))
@dataclass(slots=True)
class ConnectorMessageDedupeRecord:
dedupe_key: str
connection_id: str
event_id: str
status: str
first_seen_at: str
updated_at: str
delivery_attempts: int
message_id: str | None = None
last_error: str | None = None
def to_dict(self) -> dict[str, Any]:
return asdict(self)
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "ConnectorMessageDedupeRecord":
return cls(
dedupe_key=str(data.get("dedupe_key") or ""),
connection_id=str(data.get("connection_id") or ""),
event_id=str(data.get("event_id") or ""),
status=str(data.get("status") or "processing"),
first_seen_at=str(data.get("first_seen_at") or _iso_now()),
updated_at=str(data.get("updated_at") or _iso_now()),
delivery_attempts=int(data.get("delivery_attempts") or 0),
message_id=str(data["message_id"]) if data.get("message_id") is not None else None,
last_error=str(data["last_error"]) if data.get("last_error") is not None else None,
)
@dataclass(slots=True)
class DedupeBeginResult:
should_process: bool
dedupe_key: str
status: str
http_status: int
retry_after_seconds: int | None
record: ConnectorMessageDedupeRecord
class MessageDedupeStore:
def __init__(self, path: Path, *, processing_ttl_seconds: int = 60) -> None:
self.path = Path(path)
self.processing_ttl_seconds = int(processing_ttl_seconds)
self._lock = Lock()
def begin(self, *, connection_id: str, event_id: str, delivery_attempt: int) -> DedupeBeginResult:
dedupe_key = f"{connection_id}:{event_id}"
now = _iso_now()
with self._lock:
data = self._load()
raw = data["records"].get(dedupe_key)
if isinstance(raw, dict):
record = ConnectorMessageDedupeRecord.from_dict(raw)
if record.status == "completed":
return DedupeBeginResult(False, dedupe_key, record.status, 200, None, record)
if record.status == "processing" and not self._is_stale(record, now):
return DedupeBeginResult(False, dedupe_key, record.status, 409, 5, record)
record.status = "processing"
record.updated_at = now
record.delivery_attempts = max(record.delivery_attempts + 1, int(delivery_attempt))
record.last_error = None
else:
record = ConnectorMessageDedupeRecord(
dedupe_key=dedupe_key,
connection_id=connection_id,
event_id=event_id,
status="processing",
first_seen_at=now,
updated_at=now,
delivery_attempts=max(1, int(delivery_attempt)),
)
data["records"][dedupe_key] = record.to_dict()
self._save(data)
return DedupeBeginResult(True, dedupe_key, record.status, 200, None, record)
def complete(self, dedupe_key: str, *, message_id: str | None) -> ConnectorMessageDedupeRecord:
return self._mark(dedupe_key, status="completed", message_id=message_id, error=None)
def fail(self, dedupe_key: str, *, error: str) -> ConnectorMessageDedupeRecord:
return self._mark(dedupe_key, status="failed", message_id=None, error=error)
def _mark(
self,
dedupe_key: str,
*,
status: str,
message_id: str | None,
error: str | None,
) -> ConnectorMessageDedupeRecord:
with self._lock:
data = self._load()
raw = data["records"].get(dedupe_key)
if not isinstance(raw, dict):
raise KeyError(dedupe_key)
record = ConnectorMessageDedupeRecord.from_dict(raw)
record.status = status
record.updated_at = _iso_now()
record.message_id = message_id or record.message_id
record.last_error = error
data["records"][dedupe_key] = record.to_dict()
self._save(data)
return record
def _is_stale(self, record: ConnectorMessageDedupeRecord, now: str) -> bool:
age = (_parse_iso(now) - _parse_iso(record.updated_at)).total_seconds()
return age >= self.processing_ttl_seconds
def _load(self) -> dict[str, Any]:
if not self.path.exists():
return {"records": {}}
try:
data = json.loads(self.path.read_text(encoding="utf-8"))
except (OSError, json.JSONDecodeError):
return {"records": {}}
if not isinstance(data, dict) or not isinstance(data.get("records"), dict):
return {"records": {}}
return data
def _save(self, data: dict[str, Any]) -> None:
self.path.parent.mkdir(parents=True, exist_ok=True)
tmp_path = self.path.with_name(f"{self.path.name}.tmp")
tmp_path.write_text(json.dumps(data, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
tmp_path.replace(self.path)

View File

@ -0,0 +1,210 @@
"""Sidecar-backed channel connectors."""
from __future__ import annotations
import os
from typing import Any
from .models import ChannelRuntimeSpec, ValidationResult
from .sidecar_client import ConnectorSidecarClient
from .store import ChannelConnectionStore, CredentialStore
POLICY_CONFIG_KEYS = {
"allowFrom",
"groupAllowFrom",
"requireMentionInGroups",
"respondToMentionAll",
"dmMode",
"maxMessageChars",
"textBatchDelayMs",
"textBatchMaxMessages",
"textBatchMaxChars",
}
class ExternalConnectorBase:
kind = ""
capabilities: list[str] = []
def __init__(
self,
*,
connection_store: ChannelConnectionStore,
credential_store: CredentialStore,
sidecar_client: ConnectorSidecarClient | Any,
sidecar_base_url: str,
) -> None:
self.connection_store = connection_store
self.credential_store = credential_store
self.sidecar_client = sidecar_client
self.sidecar_base_url = sidecar_base_url
self.callback_base_url = _callback_base_url()
async def start_session(
self,
*,
display_name: str,
owner_user_id: str | None,
options: dict[str, Any],
) -> dict[str, Any]:
runtime_config = {"sidecarBaseUrl": self.sidecar_base_url}
runtime_config.update(_policy_runtime_config(options))
connection = self.connection_store.create(
kind=self.kind,
mode="sidecar",
display_name=display_name or self.kind,
account_id="",
owner_user_id=owner_user_id,
auth_type="connector_session",
runtime_config=runtime_config,
capabilities=list(self.capabilities),
)
connection = self.connection_store.update_status(connection.connection_id, status="pairing", last_error=None)
payload = {
"kind": self.kind,
"connectionId": connection.connection_id,
"channelId": connection.channel_id,
"displayName": connection.display_name,
"callbackBaseUrl": self.callback_base_url,
"options": dict(options),
}
view = dict(await self.sidecar_client.start_session(payload))
connection.pairing_session_id = str(view.get("sessionId") or "")
connection = self.connection_store.update(connection)
connection = self._apply_session_view(connection, view)
view["connectionId"] = connection.connection_id
view["channelId"] = connection.channel_id
return view
async def poll_session(self, session_id: str) -> dict[str, Any]:
view = dict(await self.sidecar_client.get_session(session_id))
connection = self._connection_for_session(session_id)
connection = self._apply_session_view(connection, view)
view["connectionId"] = connection.connection_id
view["channelId"] = connection.channel_id
return view
def _apply_session_view(self, connection: Any, view: dict[str, Any]) -> Any:
status = str(view.get("status") or "")
if status == "connected":
connection.account_id = str(view.get("accountId") or connection.account_id)
connection.display_name = str(view.get("displayName") or connection.display_name)
metadata = view.get("metadata") if isinstance(view.get("metadata"), dict) else {}
state_ref = metadata.get("stateRef")
if state_ref:
connection.credentials_ref = self.credential_store.put(kind=self.kind, values={"stateRef": state_ref})
self.connection_store.update(connection)
self.connection_store.update_status(connection.connection_id, status="connected", last_error=None)
elif status in {"expired", "error", "cancelled"}:
self.connection_store.update_status(
connection.connection_id,
status="error",
last_error=str(view.get("error") or status),
)
return self.connection_store.get(connection.connection_id)
async def validate(self, connection_id: str) -> ValidationResult:
connection = self.connection_store.get(connection_id)
if connection.status in {"connected", "running"}:
return ValidationResult(
ok=True,
status="connected",
account_id=connection.account_id,
display_name=connection.display_name,
)
return ValidationResult(ok=False, status=connection.status, error=connection.last_error)
async def materialize_runtime(self, connection_id: str) -> ChannelRuntimeSpec:
connection = self.connection_store.get(connection_id)
if connection.status not in {"connected", "running"}:
raise ValueError(f"Connection is not connected: {connection.connection_id}")
return ChannelRuntimeSpec(
channel_id=connection.channel_id,
kind="external_connector",
mode="http",
account_id=connection.account_id,
display_name=connection.display_name,
config={
"platformKind": self.kind,
"connectionId": connection.connection_id,
**dict(connection.runtime_config),
"sidecarBaseUrl": connection.runtime_config.get("sidecarBaseUrl") or self.sidecar_base_url,
},
secrets_ref=None,
)
async def revoke(self, connection_id: str) -> None:
await self.sidecar_client.logout(connection_id)
def _connection_for_session(self, session_id: str):
for connection in self.connection_store.list():
if connection.pairing_session_id == session_id:
return connection
raise KeyError(session_id)
class WeixinConnector(ExternalConnectorBase):
kind = "weixin"
capabilities = ["receive_text", "send_text", "receive_media", "direct_messages"]
class FeishuConnector(ExternalConnectorBase):
kind = "feishu"
capabilities = ["receive_text", "send_text", "receive_media", "groups"]
def _policy_runtime_config(options: dict[str, Any]) -> dict[str, Any]:
result: dict[str, Any] = {}
for key in POLICY_CONFIG_KEYS:
if key not in options:
continue
value = options[key]
if key in {"allowFrom", "groupAllowFrom"}:
items = _string_list(value)
if items:
result[key] = items
continue
if key in {"maxMessageChars", "textBatchDelayMs", "textBatchMaxMessages", "textBatchMaxChars"}:
number = _positive_int(value)
if number is not None:
result[key] = number
continue
if key in {"requireMentionInGroups", "respondToMentionAll"}:
result[key] = _bool(value)
continue
text = str(value or "").strip()
if text:
result[key] = text
return result
def _callback_base_url() -> str:
for name in ("EXTERNAL_CONNECTOR_CALLBACK_BASE_URL", "BEAVER_CONNECTOR_CALLBACK_BASE_URL"):
value = os.environ.get(name, "").strip()
if value:
return value.rstrip("/")
return ""
def _string_list(value: Any) -> list[str]:
if isinstance(value, str):
raw_items = value.replace("\n", ",").split(",")
elif isinstance(value, list):
raw_items = value
else:
raw_items = []
return [str(item).strip() for item in raw_items if str(item).strip()]
def _positive_int(value: Any) -> int | None:
try:
number = int(value)
except (TypeError, ValueError):
return None
return number if number > 0 else None
def _bool(value: Any) -> bool:
if isinstance(value, bool):
return value
return str(value).strip().lower() in {"1", "true", "yes", "on"}

View File

@ -0,0 +1,117 @@
"""Channel connection setup models."""
from __future__ import annotations
from dataclasses import asdict, dataclass, field
from datetime import datetime, timezone
from typing import Any
CONNECTION_STATUSES = {"draft", "pairing", "connected", "running", "degraded", "error", "revoked"}
def iso_now() -> str:
return datetime.now(timezone.utc).isoformat()
@dataclass(slots=True)
class ChannelConnection:
connection_id: str
owner_user_id: str | None
channel_id: str
kind: str
mode: str
display_name: str
account_id: str
status: str
auth_type: str
credentials_ref: str | None = None
connector_ref: str | None = None
pairing_session_id: str | None = None
runtime_config: dict[str, Any] = field(default_factory=dict)
capabilities: list[str] = field(default_factory=list)
created_at: str = field(default_factory=iso_now)
updated_at: str = field(default_factory=iso_now)
last_seen_at: str | None = None
last_error: str | None = None
def to_dict(self) -> dict[str, Any]:
return asdict(self)
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "ChannelConnection":
return cls(
connection_id=str(data.get("connection_id") or ""),
owner_user_id=_optional_string(data.get("owner_user_id")),
channel_id=str(data.get("channel_id") or ""),
kind=str(data.get("kind") or ""),
mode=str(data.get("mode") or ""),
display_name=str(data.get("display_name") or ""),
account_id=str(data.get("account_id") or ""),
status=str(data.get("status") or "draft"),
auth_type=str(data.get("auth_type") or ""),
credentials_ref=_optional_string(data.get("credentials_ref")),
connector_ref=_optional_string(data.get("connector_ref")),
pairing_session_id=_optional_string(data.get("pairing_session_id")),
runtime_config=dict(data.get("runtime_config") or {}),
capabilities=[str(item) for item in data.get("capabilities") or []],
created_at=str(data.get("created_at") or iso_now()),
updated_at=str(data.get("updated_at") or iso_now()),
last_seen_at=_optional_string(data.get("last_seen_at")),
last_error=_optional_string(data.get("last_error")),
)
@dataclass(slots=True)
class PairingSession:
pairing_session_id: str
kind: str
scope: str
token: str
status: str
expires_at_ms: int
created_at_ms: int
def to_dict(self) -> dict[str, Any]:
return asdict(self)
@classmethod
def from_dict(cls, data: dict[str, Any]) -> "PairingSession":
return cls(
pairing_session_id=str(data.get("pairing_session_id") or ""),
kind=str(data.get("kind") or ""),
scope=str(data.get("scope") or ""),
token=str(data.get("token") or ""),
status=str(data.get("status") or "pending"),
expires_at_ms=int(data.get("expires_at_ms") or 0),
created_at_ms=int(data.get("created_at_ms") or 0),
)
@dataclass(slots=True)
class ChannelRuntimeSpec:
channel_id: str
kind: str
mode: str
account_id: str
display_name: str
config: dict[str, Any] = field(default_factory=dict)
secrets_ref: str | None = None
external_endpoint: str | None = None
@dataclass(slots=True)
class ValidationResult:
ok: bool
status: str
account_id: str | None = None
display_name: str | None = None
error: str | None = None
metadata: dict[str, Any] = field(default_factory=dict)
def _optional_string(value: Any) -> str | None:
if value is None:
return None
text = str(value).strip()
return text or None

View File

@ -0,0 +1,39 @@
"""HTTP client for the generic external connector sidecar."""
from __future__ import annotations
from typing import Any
import httpx
class ConnectorSidecarClient:
def __init__(self, *, base_url: str, token: str, timeout_seconds: float = 20.0) -> None:
self.base_url = base_url.rstrip("/")
self.token = token
self.timeout_seconds = float(timeout_seconds)
async def get_connectors(self) -> list[dict[str, Any]]:
return await self._request("GET", "/connectors")
async def start_session(self, payload: dict[str, Any]) -> dict[str, Any]:
return await self._request("POST", "/connector-sessions", json=payload)
async def get_session(self, session_id: str) -> dict[str, Any]:
return await self._request("GET", f"/connector-sessions/{session_id}")
async def cancel_session(self, session_id: str) -> dict[str, Any]:
return await self._request("POST", f"/connector-sessions/{session_id}/cancel", json={})
async def logout(self, connection_id: str) -> dict[str, Any]:
return await self._request("POST", f"/connections/{connection_id}/logout", json={})
async def send(self, payload: dict[str, Any]) -> dict[str, Any]:
return await self._request("POST", "/send", json=payload)
async def _request(self, method: str, path: str, *, json: dict[str, Any] | None = None) -> Any:
headers = {"Authorization": f"Bearer {self.token}"} if self.token else {}
async with httpx.AsyncClient(timeout=self.timeout_seconds) as client:
response = await client.request(method, f"{self.base_url}{path}", json=json, headers=headers)
response.raise_for_status()
return response.json()

View File

@ -0,0 +1,222 @@
"""Persistent channel connection stores."""
from __future__ import annotations
import json
import time
from pathlib import Path
from threading import Lock
from typing import Any
from uuid import uuid4
from .models import CONNECTION_STATUSES, ChannelConnection, PairingSession, iso_now
class ChannelConnectionStore:
def __init__(self, path: Path) -> None:
self.path = Path(path)
self._lock = Lock()
def create(
self,
*,
kind: str,
mode: str,
display_name: str,
account_id: str,
owner_user_id: str | None,
auth_type: str,
runtime_config: dict[str, Any] | None = None,
capabilities: list[str] | None = None,
credentials_ref: str | None = None,
) -> ChannelConnection:
with self._lock:
data = self._load()
connection_id = f"conn_{uuid4().hex}"
channel_id = f"{_slug(kind)}-{uuid4().hex[:8]}"
now = iso_now()
connection = ChannelConnection(
connection_id=connection_id,
owner_user_id=owner_user_id,
channel_id=channel_id,
kind=kind,
mode=mode,
display_name=display_name or channel_id,
account_id=account_id,
status="draft",
auth_type=auth_type,
credentials_ref=credentials_ref,
runtime_config=runtime_config or {},
capabilities=capabilities or [],
created_at=now,
updated_at=now,
)
data["connections"][connection_id] = connection.to_dict()
self._save(data)
return connection
def get(self, connection_id: str) -> ChannelConnection:
data = self._load()
raw = data["connections"].get(connection_id)
if not isinstance(raw, dict):
raise KeyError(connection_id)
return ChannelConnection.from_dict(raw)
def list(self) -> list[ChannelConnection]:
data = self._load()
return [ChannelConnection.from_dict(item) for item in data["connections"].values() if isinstance(item, dict)]
def update(self, connection: ChannelConnection) -> ChannelConnection:
with self._lock:
data = self._load()
if connection.connection_id not in data["connections"]:
raise KeyError(connection.connection_id)
connection.updated_at = iso_now()
data["connections"][connection.connection_id] = connection.to_dict()
self._save(data)
return connection
def update_status(self, connection_id: str, *, status: str, last_error: str | None) -> ChannelConnection:
if status not in CONNECTION_STATUSES:
raise ValueError(f"Unsupported connection status: {status}")
connection = self.get(connection_id)
connection.status = status
connection.last_error = last_error
if status in {"connected", "running"}:
connection.last_seen_at = iso_now()
return self.update(connection)
def revoke(self, connection_id: str) -> ChannelConnection:
return self.update_status(connection_id, status="revoked", last_error=None)
def _load(self) -> dict[str, Any]:
if not self.path.exists():
return {"connections": {}}
try:
data = json.loads(self.path.read_text(encoding="utf-8"))
except (OSError, json.JSONDecodeError):
return {"connections": {}}
if not isinstance(data, dict) or not isinstance(data.get("connections"), dict):
return {"connections": {}}
return data
def _save(self, data: dict[str, Any]) -> None:
self.path.parent.mkdir(parents=True, exist_ok=True)
tmp_path = self.path.with_name(f"{self.path.name}.tmp")
tmp_path.write_text(json.dumps(data, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
tmp_path.replace(self.path)
class CredentialStore:
def __init__(self, path: Path) -> None:
self.path = Path(path)
self._lock = Lock()
def put(self, *, kind: str, values: dict[str, Any]) -> str:
cleaned = {str(key): str(value) for key, value in values.items() if str(key).strip() and str(value).strip()}
ref = f"cred_{uuid4().hex}"
with self._lock:
data = self._load()
data["credentials"][ref] = {"kind": kind, "values": cleaned, "created_at": iso_now()}
self._save(data)
return ref
def get(self, ref: str) -> dict[str, str]:
data = self._load()
item = data["credentials"].get(ref)
if not isinstance(item, dict):
raise KeyError(ref)
values = item.get("values")
if not isinstance(values, dict):
return {}
return {str(key): str(value) for key, value in values.items()}
def redacted(self, ref: str | None) -> dict[str, str]:
if not ref:
return {}
try:
values = self.get(ref)
except KeyError:
return {}
return {key: "***" for key in values}
def _load(self) -> dict[str, Any]:
if not self.path.exists():
return {"credentials": {}}
try:
data = json.loads(self.path.read_text(encoding="utf-8"))
except (OSError, json.JSONDecodeError):
return {"credentials": {}}
if not isinstance(data, dict) or not isinstance(data.get("credentials"), dict):
return {"credentials": {}}
return data
def _save(self, data: dict[str, Any]) -> None:
self.path.parent.mkdir(parents=True, exist_ok=True)
tmp_path = self.path.with_name(f"{self.path.name}.tmp")
tmp_path.write_text(json.dumps(data, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
tmp_path.replace(self.path)
class PairingTokenStore:
def __init__(self, path: Path) -> None:
self.path = Path(path)
self._lock = Lock()
def create(self, *, kind: str, ttl_seconds: int, scope: str) -> PairingSession:
now_ms = _now_ms()
session = PairingSession(
pairing_session_id=f"pair_{uuid4().hex}",
kind=kind,
scope=scope,
token=f"pair_{uuid4().hex}",
status="pending",
expires_at_ms=now_ms + int(ttl_seconds * 1000),
created_at_ms=now_ms,
)
with self._lock:
data = self._load()
data["sessions"][session.pairing_session_id] = session.to_dict()
self._save(data)
return session
def consume(self, token: str, *, expected_kind: str) -> PairingSession | None:
with self._lock:
data = self._load()
for key, raw in data["sessions"].items():
session = PairingSession.from_dict(raw)
if session.token != token or session.kind != expected_kind:
continue
if session.status != "pending" or session.expires_at_ms <= _now_ms():
return None
session.status = "consumed"
data["sessions"][key] = session.to_dict()
self._save(data)
return session
return None
def _load(self) -> dict[str, Any]:
if not self.path.exists():
return {"sessions": {}}
try:
data = json.loads(self.path.read_text(encoding="utf-8"))
except (OSError, json.JSONDecodeError):
return {"sessions": {}}
if not isinstance(data, dict) or not isinstance(data.get("sessions"), dict):
return {"sessions": {}}
return data
def _save(self, data: dict[str, Any]) -> None:
self.path.parent.mkdir(parents=True, exist_ok=True)
tmp_path = self.path.with_name(f"{self.path.name}.tmp")
tmp_path.write_text(json.dumps(data, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
tmp_path.replace(self.path)
def _now_ms() -> int:
return int(time.time() * 1000)
def _slug(value: str) -> str:
text = "".join(char if char.isalnum() else "-" for char in str(value).strip().lower())
return "-".join(part for part in text.split("-") if part) or "channel"

View File

@ -0,0 +1,92 @@
"""Telegram channel connector."""
from __future__ import annotations
from collections.abc import Callable
from typing import Any
from .models import ChannelRuntimeSpec, ValidationResult
from .store import ChannelConnectionStore, CredentialStore
class TelegramConnector:
kind = "telegram"
def __init__(
self,
*,
connection_store: ChannelConnectionStore,
credential_store: CredentialStore,
client_factory: Callable[[str], Any] | None = None,
) -> None:
self.connection_store = connection_store
self.credential_store = credential_store
self.client_factory = client_factory or _default_client_factory
async def validate(self, connection_id: str) -> ValidationResult:
connection = self.connection_store.get(connection_id)
token = self._bot_token(connection.credentials_ref)
try:
client = self.client_factory(token)
raw = await client.get_me()
bot_id = _value(raw, "id")
username = _value(raw, "username")
first_name = _value(raw, "first_name") or "Telegram Bot"
account_id = f"telegram:{bot_id}" if bot_id else connection.account_id
display_name = f"{first_name} (@{username})" if username else first_name
connection.account_id = account_id
connection.display_name = display_name
connection.capabilities = ["receive_text", "send_text", "receive_media", "groups"]
self.connection_store.update(connection)
return ValidationResult(
ok=True,
status="connected",
account_id=account_id,
display_name=display_name,
metadata={"username": username} if username else {},
)
except Exception as exc:
return ValidationResult(ok=False, status="error", error=str(exc))
async def materialize_runtime(self, connection_id: str) -> ChannelRuntimeSpec:
connection = self.connection_store.get(connection_id)
if connection.status not in {"connected", "running"}:
raise ValueError(f"Connection is not connected: {connection.connection_id}")
return ChannelRuntimeSpec(
channel_id=connection.channel_id,
kind=connection.kind,
mode=connection.mode,
account_id=connection.account_id,
display_name=connection.display_name,
config=dict(connection.runtime_config),
secrets_ref=connection.credentials_ref,
)
async def revoke(self, connection_id: str) -> None:
# Telegram bot tokens do not have a Beaver-managed platform revoke action.
# The registry owns local connection state transitions.
return None
def _bot_token(self, credentials_ref: str | None) -> str:
if not credentials_ref:
raise ValueError("Telegram credentials are missing")
token = self.credential_store.get(credentials_ref).get("botToken")
if not token:
raise ValueError("botToken is required")
return token
def _value(raw: Any, key: str) -> str:
if isinstance(raw, dict):
value = raw.get(key)
else:
value = getattr(raw, key, None)
return str(value).strip() if value is not None else ""
def _default_client_factory(token: str) -> Any:
try:
from telegram import Bot
except ImportError as exc: # pragma: no cover - optional live dependency
raise RuntimeError("Install beaver-backend[telegram] to validate Telegram connections") from exc
return Bot(token=token)

View File

@ -0,0 +1,97 @@
"""Generic runtime channel backed by an external connector sidecar."""
from __future__ import annotations
import hashlib
from typing import Any
from beaver.foundation.events import OutboundMessage
from beaver.interfaces.channels.connections.sidecar_client import ConnectorSidecarClient
class ExternalConnectorChannel:
def __init__(
self,
*,
channel_id: str,
platform_kind: str,
connection_id: str,
account_id: str,
display_name: str,
sidecar_client: ConnectorSidecarClient | Any,
) -> None:
self.channel_id = channel_id
self.kind = "external_connector"
self.mode = "http"
self.platform_kind = platform_kind
self.connection_id = connection_id
self.account_id = account_id
self.display_name = display_name or channel_id
self.sidecar_client = sidecar_client
self.started = False
async def start(self) -> None:
self.started = True
async def stop(self) -> None:
self.started = False
async def send(self, message: OutboundMessage) -> None:
identity = message.channel_identity
if identity is None:
raise ValueError("channel_identity is required for external connector sends")
metadata = {
"inboundMessageId": identity.message_id,
"sessionId": message.session_id,
}
context_token = _context_token(message)
if context_token:
metadata["contextToken"] = context_token
payload = {
"requestId": _request_id(message),
"connectionId": self.connection_id,
"channelId": self.channel_id,
"kind": self.platform_kind,
"target": {
"peerId": identity.peer_id,
"peerType": identity.peer_type,
"threadId": identity.thread_id,
},
"content": message.content,
"metadata": metadata,
}
await self.sidecar_client.send(payload)
def _request_id(message: OutboundMessage) -> str:
identity = message.channel_identity
channel = message.channel or (identity.channel_id if identity else "unknown")
session_id = message.session_id or (identity.session_id() if identity else "unknown")
message_id = str(message.message_id or "").strip()
if not message_id:
basis = "|".join(
[
message.content,
identity.message_id if identity and identity.message_id else "",
identity.peer_id if identity else "",
message.finish_reason,
]
)
message_id = hashlib.sha256(basis.encode("utf-8")).hexdigest()[:24]
return f"out_{channel}:{session_id}:{message_id}"
def _context_token(message: OutboundMessage) -> str | None:
inbound_metadata = message.metadata.get("inbound_metadata")
if isinstance(inbound_metadata, dict):
value = _clean_optional(inbound_metadata.get("contextToken") or inbound_metadata.get("context_token"))
if value:
return value
return _clean_optional(message.metadata.get("contextToken") or message.metadata.get("context_token"))
def _clean_optional(value: Any) -> str | None:
if value is None:
return None
text = str(value).strip()
return text or None

View File

@ -0,0 +1,116 @@
"""Generic fixed-schema text webhook channel adapter."""
from __future__ import annotations
import asyncio
from typing import Any
from beaver.foundation.events import ChannelIdentity, InboundMessage, OutboundMessage
from beaver.interfaces.channels.base import ChannelInboundSink
class GenericWebhookAdapter:
def __init__(
self,
*,
channel_id: str,
kind: str,
mode: str,
account_id: str,
display_name: str = "",
inbound_sink: ChannelInboundSink,
response_timeout_seconds: float = 1800,
) -> None:
self.channel_id = channel_id
self.kind = kind
self.mode = mode
self.account_id = account_id
self.display_name = display_name or channel_id
self.inbound_sink = inbound_sink
self.response_timeout_seconds = max(1.0, float(response_timeout_seconds))
self.started = False
self._pending: dict[str, asyncio.Future[OutboundMessage]] = {}
async def start(self) -> None:
self.started = True
async def stop(self) -> None:
self.started = False
for future in list(self._pending.values()):
if not future.done():
future.cancel()
self._pending.clear()
async def handle_webhook_payload(self, payload: dict[str, Any]) -> dict[str, Any]:
text = str(payload.get("text") or "").strip()
peer_id = str(payload.get("peer_id") or "").strip()
message_id = str(payload.get("message_id") or "").strip()
thread_id = str(payload.get("thread_id") or "").strip() or None
peer_type = str(payload.get("peer_type") or "unknown").strip() or "unknown"
user_id = str(payload.get("user_id") or "").strip() or None
if not text:
return {"ok": False, "error": "text is required"}
if not peer_id:
return {"ok": False, "error": "peer_id is required"}
if not message_id:
return {"ok": False, "error": "message_id is required"}
identity = ChannelIdentity(
channel_id=self.channel_id,
kind=self.kind,
account_id=self.account_id,
peer_id=peer_id,
thread_id=thread_id,
peer_type=peer_type,
user_id=user_id,
message_id=message_id,
)
inbound = InboundMessage(
channel=self.channel_id,
content=text,
user_id=user_id,
channel_identity=identity,
metadata={"webhook": {"peer_type": peer_type}},
)
future = asyncio.get_running_loop().create_future()
self._pending[inbound.message_id] = future
accept = await self.inbound_sink.accept_inbound(inbound)
if not accept.accepted:
self._pending.pop(inbound.message_id, None)
record = accept.record or {}
return {
"ok": accept.error is None,
"duplicate": accept.duplicate,
"pending": accept.pending,
"session_id": accept.session_id,
"status": record.get("status"),
"run_id": record.get("run_id"),
"reply": record.get("reply"),
"error": accept.error or record.get("error"),
}
try:
outbound = await asyncio.wait_for(future, timeout=self.response_timeout_seconds)
except asyncio.TimeoutError:
self._pending.pop(inbound.message_id, None)
return {
"ok": True,
"duplicate": False,
"pending": True,
"session_id": accept.session_id,
}
return {
"ok": outbound.finish_reason != "error",
"duplicate": False,
"pending": False,
"session_id": outbound.session_id,
"run_id": outbound.run_id,
"reply": outbound.content,
"error": outbound.metadata.get("error"),
}
async def send(self, message: OutboundMessage) -> None:
future = self._pending.pop(message.message_id, None)
if future is None or future.done():
message.metadata["delivery_status"] = "unclaimed"
return
future.set_result(message)

View File

@ -3,6 +3,7 @@
from __future__ import annotations
import asyncio
from collections.abc import Awaitable, Callable
from contextlib import suppress
from beaver.foundation.events import MessageBus, OutboundMessage
@ -20,13 +21,17 @@ class ChannelManager:
self.started = False
def register(self, channel: ChannelAdapter) -> None:
if self.started:
raise RuntimeError("Cannot register channels after ChannelManager.start()")
if channel.name in self.channels:
raise ValueError(f"Channel already registered: {channel.name}")
if channel.bus is not self.bus:
raise ValueError("Channel must share the same MessageBus as ChannelManager")
self.channels[channel.name] = channel
if channel.channel_id in self.channels:
raise ValueError(f"Channel already registered: {channel.channel_id}")
self.channels[channel.channel_id] = channel
def unregister(self, channel_id: str) -> ChannelAdapter | None:
return self.channels.pop(channel_id, None)
def replace_registered(self, channel: ChannelAdapter) -> ChannelAdapter | None:
old = self.channels.get(channel.channel_id)
self.channels[channel.channel_id] = channel
return old
async def start(self) -> None:
started: list[ChannelAdapter] = []
@ -53,7 +58,13 @@ class ChannelManager:
if errors:
raise RuntimeError(f"Failed to stop {len(errors)} channel(s)") from errors[0]
async def dispatch_outbound(self, stop_event: asyncio.Event) -> None:
async def dispatch_outbound(
self,
stop_event: asyncio.Event,
*,
on_delivered: Callable[[OutboundMessage], Awaitable[None]] | None = None,
on_failed: Callable[[OutboundMessage, Exception | None], Awaitable[None]] | None = None,
) -> None:
"""Route bus outbound messages until stopped and the queue is drained."""
while True:
@ -68,9 +79,16 @@ class ChannelManager:
channel = self.channels.get(message.channel)
if channel is None:
self.undeliverable.append(message)
if on_failed is not None:
await on_failed(message, None)
continue
try:
await channel.send(message)
except Exception: # pragma: no cover - defensive channel isolation
except Exception as exc: # pragma: no cover - defensive channel isolation
self.undeliverable.append(message)
if on_failed is not None:
await on_failed(message, exc)
else:
if on_delivered is not None:
await on_delivered(message)

View File

@ -4,15 +4,27 @@ from __future__ import annotations
from typing import Any
from beaver.foundation.events import InboundMessage, MessageBus, OutboundMessage
from beaver.foundation.events import ChannelIdentity, InboundMessage, OutboundMessage
from beaver.interfaces.channels.base import ChannelInboundSink
class MemoryChannelAdapter:
"""A local channel that stores outbound messages in memory."""
def __init__(self, bus: MessageBus, *, name: str = "memory") -> None:
self.name = name
self.bus = bus
def __init__(
self,
inbound_sink: ChannelInboundSink,
*,
channel_id: str = "memory-dev",
kind: str = "memory",
mode: str = "webhook",
account_id: str = "memory",
) -> None:
self.channel_id = channel_id
self.kind = kind
self.mode = mode
self.account_id = account_id
self.inbound_sink = inbound_sink
self.started = False
self.sent_messages: list[OutboundMessage] = []
@ -36,12 +48,24 @@ class MemoryChannelAdapter:
model: str | None = None,
provider_name: str | None = None,
embedding_model: str | None = None,
peer_id: str = "default",
thread_id: str | None = None,
message_id: str | None = None,
metadata: dict[str, Any] | None = None,
) -> InboundMessage:
"""Publish a text message from this channel into the shared bus."""
identity = ChannelIdentity(
channel_id=self.channel_id,
kind=self.kind,
account_id=self.account_id,
peer_id=peer_id,
thread_id=thread_id,
user_id=user_id,
message_id=message_id,
)
message = InboundMessage(
channel=self.name,
channel=self.channel_id,
content=content,
session_id=session_id,
user_id=user_id,
@ -50,9 +74,10 @@ class MemoryChannelAdapter:
model=model,
provider_name=provider_name,
embedding_model=embedding_model,
channel_identity=identity,
metadata=metadata or {},
)
await self.bus.publish_inbound(message)
await self.inbound_sink.accept_inbound(message)
return message
async def publish_external_text(
@ -73,9 +98,6 @@ class MemoryChannelAdapter:
the shared gateway bus.
"""
session_parts = [self.name, chat_id]
if thread_id:
session_parts.append(thread_id)
metadata = {
"chat_id": chat_id,
"message_id": message_id,
@ -84,8 +106,10 @@ class MemoryChannelAdapter:
}
return await self.publish_text(
content,
session_id=":".join(str(part) for part in session_parts if str(part)),
user_id=user_id,
title=title,
peer_id=chat_id,
thread_id=thread_id,
message_id=message_id,
metadata=metadata,
)

View File

@ -0,0 +1 @@
"""Platform channel adapters."""

View File

@ -0,0 +1,138 @@
"""Shared helpers for platform channel adapters."""
from __future__ import annotations
from dataclasses import dataclass
from typing import Any
from beaver.foundation.events import ChannelIdentity, InboundMessage, OutboundMessage
@dataclass(slots=True)
class OutboundTarget:
peer_id: str | None
thread_id: str | None = None
peer_type: str = "unknown"
user_id: str | None = None
class PlatformDeliveryError(RuntimeError):
"""Raised when a platform client rejects a delivery."""
def config_bool(config: dict[str, Any], key: str, *, default: bool = False) -> bool:
value = config.get(key)
if value is None:
return default
if isinstance(value, bool):
return value
if isinstance(value, (int, float)):
return bool(value)
text = str(value).strip().lower()
if text in {"1", "true", "yes", "on"}:
return True
if text in {"0", "false", "no", "off"}:
return False
return default
def config_list(config: dict[str, Any], key: str) -> list[str]:
value = config.get(key)
if value is None:
return []
if isinstance(value, str):
return [part.strip() for part in value.split(",") if part.strip()]
if isinstance(value, (list, tuple, set)):
return [str(item).strip() for item in value if str(item).strip()]
text = str(value).strip()
return [text] if text else []
def chunk_text(text: str, *, max_chars: int) -> list[str]:
if max_chars <= 0:
raise ValueError("max_chars must be positive")
if not text:
return [""]
return [text[index : index + max_chars] for index in range(0, len(text), max_chars)]
def compact_media_summary(media_type: str, *, file_name: str | None = None) -> str:
label = str(media_type or "attachment").strip() or "attachment"
if file_name:
return f"[{label}: {file_name}]"
return f"[{label}]"
def target_from_session_id(session_id: str | None) -> OutboundTarget:
if not session_id:
return OutboundTarget(peer_id=None)
parts = str(session_id).split(":")
if len(parts) < 3:
return OutboundTarget(peer_id=None)
thread_id = parts[3] if len(parts) > 3 and parts[3] else None
return OutboundTarget(peer_id=parts[2] or None, thread_id=thread_id)
def outbound_target(message: OutboundMessage) -> OutboundTarget:
identity = message.channel_identity
if identity is None:
return target_from_session_id(message.session_id)
return OutboundTarget(
peer_id=identity.peer_id,
thread_id=identity.thread_id,
peer_type=identity.peer_type,
user_id=identity.user_id,
)
def mark_unclaimed(message: OutboundMessage) -> None:
message.metadata["delivery_status"] = "unclaimed"
def build_inbound_message(
*,
channel_id: str,
kind: str,
account_id: str,
peer_id: str,
content: str,
message_id: str | None,
peer_type: str,
user_id: str | None = None,
thread_id: str | None = None,
metadata: dict[str, Any] | None = None,
) -> InboundMessage:
identity = ChannelIdentity(
channel_id=channel_id,
kind=kind,
account_id=account_id,
peer_id=peer_id,
thread_id=thread_id,
peer_type=peer_type,
user_id=user_id,
message_id=message_id,
)
return InboundMessage(
channel=channel_id,
content=content,
session_id=identity.session_id(),
user_id=user_id,
message_id=message_id or "",
channel_identity=identity,
metadata=metadata or {},
)
def allowed_by_policy(
*,
policy: str | None,
identifier: str | None,
allowlist: list[str],
default: str = "open",
) -> bool:
effective = (policy or default).strip().lower()
if effective == "disabled":
return False
if effective == "allowlist":
return bool(identifier and identifier in allowlist)
return True

View File

@ -0,0 +1,207 @@
"""Feishu/Lark channel adapter."""
from __future__ import annotations
import json
from collections.abc import Callable
from typing import Any
from beaver.foundation.events import InboundMessage, OutboundMessage
from beaver.interfaces.channels.base import ChannelInboundSink
from .base import (
build_inbound_message,
chunk_text,
compact_media_summary,
config_bool,
config_list,
mark_unclaimed,
outbound_target,
)
EventRecorder = Callable[..., None]
class FeishuAdapter:
"""Feishu/Lark bot adapter with injectable client support."""
KIND = "feishu"
def __init__(
self,
*,
channel_id: str,
kind: str,
mode: str,
account_id: str,
display_name: str | None,
inbound_sink: ChannelInboundSink,
secrets: dict[str, Any] | None = None,
config: dict[str, Any] | None = None,
event_recorder: EventRecorder | None = None,
client: Any | None = None,
) -> None:
self.channel_id = channel_id
self.kind = kind
self.mode = mode
self.account_id = account_id
self.display_name = display_name
self.inbound_sink = inbound_sink
self.secrets = secrets or {}
self.config = config or {}
self.event_recorder = event_recorder
self._client = client
self.max_message_chars = int(self.config.get("maxMessageChars") or 4096)
async def start(self) -> None:
if self._client is not None:
return
if self.mode not in {"websocket", "webhook"}:
raise ValueError(f"Unsupported feishu mode: {self.mode}")
self._client = self._build_client()
async def stop(self) -> None:
close = getattr(self._client, "close", None)
if close is not None:
result = close()
if hasattr(result, "__await__"):
await result
async def handle_event_payload(self, payload: dict[str, Any]) -> None:
message = self._normalize_payload(payload)
if message is None:
return
await self.inbound_sink.accept_inbound(message)
async def send(self, message: OutboundMessage) -> None:
target = outbound_target(message)
if not target.peer_id:
mark_unclaimed(message)
return
client = self._require_client()
for chunk in chunk_text(message.content, max_chars=self.max_message_chars):
await client.send_text(receive_id_type="chat_id", receive_id=target.peer_id, text=chunk)
def _normalize_payload(self, payload: dict[str, Any]) -> InboundMessage | None:
event = payload.get("event") if isinstance(payload.get("event"), dict) else payload
message = event.get("message") if isinstance(event.get("message"), dict) else {}
sender = event.get("sender") if isinstance(event.get("sender"), dict) else {}
peer_id = _string_or_none(message.get("chat_id"))
if not peer_id:
return None
message_id = _string_or_none(message.get("message_id"))
message_type = str(message.get("message_type") or "unknown")
chat_type = str(message.get("chat_type") or "unknown")
peer_type = "dm" if chat_type == "p2p" else "group"
user_id = _sender_open_id(sender)
if peer_type == "dm" and not self._dm_allowed(user_id or peer_id):
return None
if peer_type == "group" and not self._group_allowed(peer_id, user_id):
return None
if peer_type == "group" and config_bool(self.config, "requireMentionInGroups", default=False):
if not self._message_mentions_bot(message):
return None
content = self._message_content(message_type, message)
if not content:
return None
metadata = {
"chat_id": peer_id,
"message_id": message_id,
"chat_type": chat_type,
"message_type": message_type,
}
return build_inbound_message(
channel_id=self.channel_id,
kind=self.kind,
account_id=self.account_id,
peer_id=peer_id,
peer_type=peer_type,
user_id=user_id,
message_id=message_id,
content=content,
metadata=metadata,
)
def _message_content(self, message_type: str, message: dict[str, Any]) -> str:
content = _parse_json_object(message.get("content"))
if message_type == "text":
return str(content.get("text") or "").strip()
file_name = _string_or_none(content.get("file_name") or content.get("name"))
return compact_media_summary(message_type, file_name=file_name)
def _message_mentions_bot(self, message: dict[str, Any]) -> bool:
bot_open_id = _string_or_none(self.config.get("botOpenId"))
if not bot_open_id:
return False
mentions = message.get("mentions")
if not isinstance(mentions, list):
return False
for mention in mentions:
if not isinstance(mention, dict):
continue
mention_id = mention.get("id") if isinstance(mention.get("id"), dict) else {}
if _string_or_none(mention_id.get("open_id")) == bot_open_id:
return True
return False
def _dm_allowed(self, identifier: str | None) -> bool:
allowlist = config_list(self.config, "allowFrom")
if not allowlist:
return True
return bool(identifier and identifier in allowlist)
def _group_allowed(self, peer_id: str | None, user_id: str | None) -> bool:
allowlist = config_list(self.config, "groupAllowFrom")
if not allowlist:
return True
return bool((peer_id and peer_id in allowlist) or (user_id and user_id in allowlist))
def _require_client(self) -> Any:
if self._client is None:
self._client = self._build_client()
return self._client
def _build_client(self) -> Any:
self._require_secret("appId")
self._require_secret("appSecret")
try:
import lark_oapi # noqa: F401
except ImportError as exc: # pragma: no cover - optional live dependency
raise RuntimeError("Install beaver-backend[feishu] to enable FeishuAdapter") from exc
raise RuntimeError("Feishu live client is not configured for direct construction")
def _require_secret(self, key: str) -> str:
value = self.secrets.get(key)
if not value:
raise ValueError(f"{key} is required")
return str(value)
def _parse_json_object(value: Any) -> dict[str, Any]:
if isinstance(value, dict):
return value
if not isinstance(value, str):
return {}
try:
parsed = json.loads(value)
except json.JSONDecodeError:
return {}
return parsed if isinstance(parsed, dict) else {}
def _sender_open_id(sender: dict[str, Any]) -> str | None:
sender_id = sender.get("sender_id") if isinstance(sender.get("sender_id"), dict) else {}
return _string_or_none(sender_id.get("open_id"))
def _string_or_none(value: Any) -> str | None:
if value is None:
return None
text = str(value).strip()
return text or None

View File

@ -0,0 +1,206 @@
"""QQ Bot channel adapter."""
from __future__ import annotations
from collections.abc import Callable
from typing import Any
from beaver.foundation.events import InboundMessage, OutboundMessage
from beaver.interfaces.channels.base import ChannelInboundSink
from .base import (
allowed_by_policy,
build_inbound_message,
chunk_text,
compact_media_summary,
config_list,
mark_unclaimed,
outbound_target,
)
EventRecorder = Callable[..., None]
class QQBotAdapter:
"""QQ Bot API adapter with injectable client support."""
KIND = "qqbot"
def __init__(
self,
*,
channel_id: str,
kind: str,
mode: str,
account_id: str,
display_name: str | None,
inbound_sink: ChannelInboundSink,
secrets: dict[str, Any] | None = None,
config: dict[str, Any] | None = None,
event_recorder: EventRecorder | None = None,
client: Any | None = None,
) -> None:
self.channel_id = channel_id
self.kind = kind
self.mode = mode
self.account_id = account_id
self.display_name = display_name
self.inbound_sink = inbound_sink
self.secrets = secrets or {}
self.config = config or {}
self.event_recorder = event_recorder
self._client = client
self.max_message_chars = int(self.config.get("maxMessageChars") or 2000)
async def start(self) -> None:
if self._client is not None:
return
if self.mode != "websocket":
raise ValueError(f"Unsupported qqbot mode: {self.mode}")
self._client = self._build_client()
async def stop(self) -> None:
close = getattr(self._client, "close", None)
if close is not None:
result = close()
if hasattr(result, "__await__"):
await result
async def handle_event_payload(self, payload: dict[str, Any]) -> None:
message = self._normalize_payload(payload)
if message is None:
return
await self.inbound_sink.accept_inbound(message)
async def send(self, message: OutboundMessage) -> None:
target = outbound_target(message)
if not target.peer_id:
mark_unclaimed(message)
return
client = self._require_client()
platform_message_id = message.channel_identity.message_id if message.channel_identity else None
for chunk in chunk_text(message.content, max_chars=self.max_message_chars):
await client.send_text(
peer_type=target.peer_type,
peer_id=target.peer_id,
content=chunk,
message_id=platform_message_id,
)
def _normalize_payload(self, payload: dict[str, Any]) -> InboundMessage | None:
event_type = str(payload.get("t") or payload.get("type") or "")
data = payload.get("d") if isinstance(payload.get("d"), dict) else payload
author = data.get("author") if isinstance(data.get("author"), dict) else {}
route = self._route(event_type, data, author)
if route is None:
return None
peer_id, peer_type, user_id, thread_id = route
if peer_type == "dm":
if not allowed_by_policy(
policy=self.config.get("dmPolicy"),
identifier=user_id or peer_id,
allowlist=config_list(self.config, "allowFrom"),
default="open",
):
return None
elif peer_type == "group":
if not allowed_by_policy(
policy=self.config.get("groupPolicy"),
identifier=peer_id,
allowlist=config_list(self.config, "groupAllowFrom"),
default="open",
):
return None
message_id = _string_or_none(data.get("id"))
content = str(data.get("content") or "").strip()
media_entries = self._media_entries(data)
if media_entries:
content = "\n".join([part for part in [content, *media_entries] if part]).strip()
if not content:
return None
metadata = {
"event_type": event_type,
"message_id": message_id,
"peer_type": peer_type,
}
if media_entries:
metadata["media"] = media_entries
return build_inbound_message(
channel_id=self.channel_id,
kind=self.kind,
account_id=self.account_id,
peer_id=peer_id,
thread_id=thread_id,
peer_type=peer_type,
user_id=user_id,
message_id=message_id,
content=content,
metadata=metadata,
)
def _route(
self,
event_type: str,
data: dict[str, Any],
author: dict[str, Any],
) -> tuple[str, str, str | None, str | None] | None:
if event_type == "C2C_MESSAGE_CREATE":
peer_id = _string_or_none(author.get("user_openid"))
if not peer_id:
return None
return peer_id, "dm", peer_id, None
if event_type == "GROUP_AT_MESSAGE_CREATE":
peer_id = _string_or_none(data.get("group_openid"))
if not peer_id:
return None
return peer_id, "group", _string_or_none(author.get("member_openid")), None
if data.get("guild_id") and data.get("channel_id"):
peer_id = _string_or_none(data.get("channel_id"))
if not peer_id:
return None
return peer_id, "channel", _string_or_none(author.get("id")), _string_or_none(data.get("guild_id"))
return None
def _media_entries(self, data: dict[str, Any]) -> list[str]:
entries: list[str] = []
attachments = data.get("attachments")
if not isinstance(attachments, list):
return entries
for attachment in attachments:
if not isinstance(attachment, dict):
continue
media_type = str(attachment.get("content_type") or attachment.get("type") or "attachment")
entries.append(compact_media_summary(media_type, file_name=_string_or_none(attachment.get("filename"))))
return entries
def _require_client(self) -> Any:
if self._client is None:
self._client = self._build_client()
return self._client
def _build_client(self) -> Any:
self._require_secret("appId")
self._require_secret("clientSecret")
try:
import aiohttp # noqa: F401
except ImportError as exc: # pragma: no cover - optional live dependency
raise RuntimeError("Install beaver-backend[qqbot] to enable QQBotAdapter") from exc
raise RuntimeError("QQBot live client is not configured for direct construction")
def _require_secret(self, key: str) -> str:
value = self.secrets.get(key)
if not value:
raise ValueError(f"{key} is required")
return str(value)
def _string_or_none(value: Any) -> str | None:
if value is None:
return None
text = str(value).strip()
return text or None

View File

@ -0,0 +1,244 @@
"""Telegram channel adapter."""
from __future__ import annotations
from collections.abc import Awaitable, Callable
from typing import Any
from beaver.foundation.events import InboundMessage, OutboundMessage
from beaver.interfaces.channels.base import ChannelInboundSink
from .base import (
build_inbound_message,
chunk_text,
compact_media_summary,
config_bool,
config_list,
mark_unclaimed,
outbound_target,
)
EventRecorder = Callable[..., None]
class TelegramAdapter:
"""Telegram Bot API adapter with injectable client support."""
KIND = "telegram"
def __init__(
self,
*,
channel_id: str,
kind: str,
mode: str,
account_id: str,
display_name: str | None,
inbound_sink: ChannelInboundSink,
secrets: dict[str, Any] | None = None,
config: dict[str, Any] | None = None,
event_recorder: EventRecorder | None = None,
client: Any | None = None,
application_factory: Callable[[], Any] | None = None,
) -> None:
self.channel_id = channel_id
self.kind = kind
self.mode = mode
self.account_id = account_id
self.display_name = display_name
self.inbound_sink = inbound_sink
self.secrets = secrets or {}
self.config = config or {}
self.event_recorder = event_recorder
self._client = client
self._application_factory = application_factory
self._application: Any | None = None
self.max_message_chars = int(self.config.get("maxMessageChars") or 4096)
async def start(self) -> None:
if self._client is not None:
return
if self.mode == "polling":
self._application = self._build_application()
await self._application.initialize()
await self._application.start()
if getattr(self._application, "updater", None) is not None:
await self._application.updater.start_polling()
self._client = self._application.bot
return
if self.mode == "webhook":
self._client = self._build_bot()
return
raise ValueError(f"Unsupported telegram mode: {self.mode}")
async def stop(self) -> None:
if self._application is None:
return
updater = getattr(self._application, "updater", None)
if updater is not None:
await updater.stop()
await self._application.stop()
await self._application.shutdown()
self._application = None
async def handle_update_payload(self, payload: dict[str, Any]) -> None:
message = self._normalize_payload(payload)
if message is None:
return
await self.inbound_sink.accept_inbound(message)
async def send(self, message: OutboundMessage) -> None:
target = outbound_target(message)
if not target.peer_id:
mark_unclaimed(message)
return
client = self._require_client()
kwargs: dict[str, Any] = {"chat_id": target.peer_id}
if target.thread_id:
kwargs["message_thread_id"] = int(target.thread_id) if str(target.thread_id).isdigit() else target.thread_id
for chunk in chunk_text(message.content, max_chars=self.max_message_chars):
await client.send_message(**kwargs, text=chunk)
def _normalize_payload(self, payload: dict[str, Any]) -> InboundMessage | None:
data = payload.get("message") or payload.get("edited_message")
if not isinstance(data, dict):
return None
chat = data.get("chat") if isinstance(data.get("chat"), dict) else {}
sender = data.get("from") if isinstance(data.get("from"), dict) else {}
peer_id = _string_or_none(chat.get("id"))
if not peer_id:
return None
chat_type = str(chat.get("type") or "unknown")
peer_type = self._peer_type(chat_type)
user_id = _string_or_none(sender.get("id"))
message_id = _string_or_none(data.get("message_id"))
thread_id = _string_or_none(data.get("message_thread_id"))
content = str(data.get("text") or data.get("caption") or "").strip()
media_entries = self._media_entries(data)
if media_entries:
content = "\n".join([part for part in [content, *media_entries] if part]).strip()
if not content:
return None
if peer_type in {"group", "channel"} and not self._group_allowed(peer_id, user_id):
return None
if peer_type == "dm" and not self._dm_allowed(user_id or peer_id):
return None
if peer_type in {"group", "channel"} and config_bool(self.config, "requireMentionInGroups", default=False):
gated = self._strip_required_mention(content)
if gated is None:
return None
content = gated
metadata = {
"chat_id": peer_id,
"message_id": message_id,
"chat_type": chat_type,
}
if media_entries:
metadata["media"] = media_entries
return build_inbound_message(
channel_id=self.channel_id,
kind=self.kind,
account_id=self.account_id,
peer_id=peer_id,
thread_id=thread_id,
peer_type=peer_type,
user_id=user_id,
message_id=message_id,
content=content,
metadata=metadata,
)
def _media_entries(self, data: dict[str, Any]) -> list[str]:
entries: list[str] = []
if data.get("photo"):
entries.append(compact_media_summary("photo"))
for media_type in ("document", "audio", "video"):
value = data.get(media_type)
if isinstance(value, dict):
entries.append(compact_media_summary(media_type, file_name=_string_or_none(value.get("file_name"))))
return entries
def _strip_required_mention(self, content: str) -> str | None:
username = str(self.config.get("botUsername") or "").strip().lstrip("@")
if not username:
return None
mention = f"@{username}"
if mention not in content:
return None
return content.replace(mention, "", 1).strip()
def _dm_allowed(self, identifier: str | None) -> bool:
allowlist = config_list(self.config, "allowFrom")
if not allowlist:
return True
return bool(identifier and identifier in allowlist)
def _group_allowed(self, peer_id: str | None, user_id: str | None) -> bool:
allowlist = config_list(self.config, "groupAllowFrom")
if not allowlist:
return True
return bool((peer_id and peer_id in allowlist) or (user_id and user_id in allowlist))
def _peer_type(self, chat_type: str) -> str:
if chat_type == "private":
return "dm"
if chat_type in {"group", "supergroup"}:
return "group"
if chat_type == "channel":
return "channel"
return chat_type or "unknown"
def _require_client(self) -> Any:
if self._client is None:
self._client = self._build_bot()
return self._client
def _build_bot(self) -> Any:
token = self._require_secret("botToken")
try:
from telegram import Bot
except ImportError as exc: # pragma: no cover - optional live dependency
raise RuntimeError("Install beaver-backend[telegram] to enable TelegramAdapter") from exc
return Bot(token=token)
def _build_application(self) -> Any:
if self._application_factory is not None:
return self._application_factory()
token = self._require_secret("botToken")
try:
from telegram.ext import Application
except ImportError as exc: # pragma: no cover - optional live dependency
raise RuntimeError("Install beaver-backend[telegram] to enable TelegramAdapter") from exc
async def handle(update: Any, context: Any) -> None:
if hasattr(update, "to_dict"):
await self.handle_update_payload(update.to_dict())
application = Application.builder().token(token).build()
try:
from telegram.ext import MessageHandler, filters
application.add_handler(MessageHandler(filters.ALL, handle))
except Exception:
pass
return application
def _require_secret(self, key: str) -> str:
value = self.secrets.get(key)
if not value:
raise ValueError(f"{key} is required")
return str(value)
def _string_or_none(value: Any) -> str | None:
if value is None:
return None
text = str(value).strip()
return text or None

View File

@ -0,0 +1,180 @@
"""Weixin channel adapter."""
from __future__ import annotations
from collections.abc import Callable
from typing import Any
from beaver.foundation.events import InboundMessage, OutboundMessage
from beaver.interfaces.channels.base import ChannelInboundSink
from .base import (
allowed_by_policy,
build_inbound_message,
chunk_text,
compact_media_summary,
config_list,
mark_unclaimed,
outbound_target,
)
EventRecorder = Callable[..., None]
class WeixinAdapter:
"""Tencent iLink-style Weixin adapter with injectable client support."""
KIND = "weixin"
def __init__(
self,
*,
channel_id: str,
kind: str,
mode: str,
account_id: str,
display_name: str | None,
inbound_sink: ChannelInboundSink,
secrets: dict[str, Any] | None = None,
config: dict[str, Any] | None = None,
event_recorder: EventRecorder | None = None,
client: Any | None = None,
) -> None:
self.channel_id = channel_id
self.kind = kind
self.mode = mode
self.account_id = account_id
self.display_name = display_name
self.inbound_sink = inbound_sink
self.secrets = secrets or {}
self.config = config or {}
self.event_recorder = event_recorder
self._client = client
self.max_message_chars = int(self.config.get("maxMessageChars") or 2000)
async def start(self) -> None:
if self._client is not None:
return
if self.mode != "polling":
raise ValueError(f"Unsupported weixin mode: {self.mode}")
self._client = self._build_client()
async def stop(self) -> None:
close = getattr(self._client, "close", None)
if close is not None:
result = close()
if hasattr(result, "__await__"):
await result
async def handle_message_payload(self, payload: dict[str, Any]) -> None:
message = self._normalize_payload(payload)
if message is None:
return
await self.inbound_sink.accept_inbound(message)
async def send(self, message: OutboundMessage) -> None:
target = outbound_target(message)
if not target.peer_id:
mark_unclaimed(message)
return
client = self._require_client()
context_token = self._context_token(message)
for chunk in chunk_text(message.content, max_chars=self.max_message_chars):
await client.send_text(peer_id=target.peer_id, text=chunk, context_token=context_token)
def _normalize_payload(self, payload: dict[str, Any]) -> InboundMessage | None:
sender_id = _string_or_none(payload.get("from") or payload.get("from_user"))
room_id = _string_or_none(payload.get("room_id") or payload.get("roomId"))
message_id = _string_or_none(payload.get("id") or payload.get("message_id"))
message_type = str(payload.get("type") or payload.get("message_type") or "text")
if room_id:
peer_id = room_id
peer_type = "group"
user_id = sender_id
if not allowed_by_policy(
policy=self.config.get("groupPolicy"),
identifier=peer_id,
allowlist=config_list(self.config, "groupAllowFrom"),
default="disabled",
):
return None
else:
peer_id = sender_id
peer_type = "dm"
user_id = sender_id
if not allowed_by_policy(
policy=self.config.get("dmPolicy"),
identifier=peer_id,
allowlist=config_list(self.config, "allowFrom"),
default="open",
):
return None
if not peer_id:
return None
content = self._content(message_type, payload)
if not content:
return None
metadata = {
"message_id": message_id,
"message_type": message_type,
}
context_token = _string_or_none(payload.get("context_token") or payload.get("contextToken"))
if context_token:
metadata["context_token"] = context_token
if room_id:
metadata["room_id"] = room_id
return build_inbound_message(
channel_id=self.channel_id,
kind=self.kind,
account_id=self.account_id,
peer_id=peer_id,
peer_type=peer_type,
user_id=user_id,
message_id=message_id,
content=content,
metadata=metadata,
)
def _content(self, message_type: str, payload: dict[str, Any]) -> str:
if message_type == "text":
return str(payload.get("text") or payload.get("content") or "").strip()
file_name = _string_or_none(payload.get("file_name") or payload.get("filename"))
return compact_media_summary(message_type, file_name=file_name)
def _context_token(self, message: OutboundMessage) -> str | None:
inbound_metadata = message.metadata.get("inbound_metadata")
if isinstance(inbound_metadata, dict):
value = _string_or_none(inbound_metadata.get("context_token"))
if value:
return value
return _string_or_none(message.metadata.get("context_token"))
def _require_client(self) -> Any:
if self._client is None:
self._client = self._build_client()
return self._client
def _build_client(self) -> Any:
self._require_secret("token")
try:
import aiohttp # noqa: F401
except ImportError as exc: # pragma: no cover - optional live dependency
raise RuntimeError("Install beaver-backend[weixin] to enable WeixinAdapter") from exc
raise RuntimeError("Weixin live client is not configured for direct construction")
def _require_secret(self, key: str) -> str:
value = self.secrets.get(key)
if not value:
raise ValueError(f"{key} is required")
return str(value)
def _string_or_none(value: Any) -> str | None:
if value is None:
return None
text = str(value).strip()
return text or None

View File

@ -0,0 +1,526 @@
"""Channel runtime host for adapter lifecycle and bus-first routing."""
from __future__ import annotations
import asyncio
from dataclasses import dataclass
from datetime import datetime, timezone
from pathlib import Path
from typing import Any
from beaver.foundation.config.schema import ChannelConfig
from beaver.foundation.events import InboundMessage, MessageBus, OutboundMessage
from beaver.interfaces.channels.base import ChannelAdapter
from beaver.interfaces.channels.manager import ChannelManager
from beaver.interfaces.channels.state import ChannelDedupeStore, ChannelEventLog
from beaver.services.agent_service import AgentService
def _iso_now() -> str:
return datetime.now(timezone.utc).isoformat()
def _channel_capabilities(kind: str, mode: str) -> list[str]:
if kind == "webhook":
return ["receive_text", "send_text", "sync_webhook_response"]
if kind == "terminal" and mode == "websocket":
return ["receive_text", "send_text", "persistent_connection"]
if kind in {"feishu", "qqbot", "telegram"}:
return ["receive_text", "send_text", "receive_media", "groups"]
if kind == "weixin":
return ["receive_text", "send_text", "receive_media", "direct_messages"]
return []
@dataclass(slots=True)
class ChannelAcceptResult:
accepted: bool
duplicate: bool = False
pending: bool = False
rejected: bool = False
session_id: str | None = None
dedupe_key: str | None = None
record: dict[str, Any] | None = None
error: str | None = None
class ChannelRuntime:
"""Own channel adapters, state, and the inbound/outbound bus bridge."""
def __init__(
self,
*,
service: AgentService,
workspace: Path,
channels: dict[str, ChannelConfig],
bus: MessageBus | None = None,
) -> None:
self.service = service
self.workspace = Path(workspace)
self.bus = bus or MessageBus()
self.manager = ChannelManager(self.bus)
self.channel_configs = dict(channels)
self.adapters: dict[str, ChannelAdapter] = {}
self.states: dict[str, dict[str, Any]] = {}
state_dir = self.workspace / "state" / "channels"
retention = self._default_dedupe_retention_hours()
self.dedupe = ChannelDedupeStore(state_dir / "dedupe.json", retention_hours=retention)
self.events = ChannelEventLog(state_dir / "events.jsonl")
self._bridge_task: asyncio.Task[None] | None = None
self._dispatch_task: asyncio.Task[None] | None = None
self._stop_event = asyncio.Event()
self._dispatch_stop_event = asyncio.Event()
self._lifecycle_lock = asyncio.Lock()
async def start(self) -> None:
self._stop_event.clear()
self._dispatch_stop_event.clear()
for channel_id, cfg in self.channel_configs.items():
if not cfg.enabled:
self.states[channel_id] = {"state": "disabled", "last_error": None}
continue
try:
adapter = self._build_adapter(channel_id, cfg)
self.adapters[channel_id] = adapter
self.manager.register(adapter)
await adapter.start()
self.states[channel_id] = {
"state": "running",
"last_error": None,
"started_at": _iso_now(),
}
self.events.record(channel_id=channel_id, kind="adapter_started")
except Exception as exc: # pragma: no cover - defensive startup isolation
self.states[channel_id] = {"state": "error", "last_error": str(exc)}
self.events.record(
channel_id=channel_id,
kind="adapter_error",
status="error",
error=str(exc),
)
self._bridge_task = asyncio.create_task(self._bridge_inbound_to_agent())
self._dispatch_task = asyncio.create_task(
self.manager.dispatch_outbound(
self._dispatch_stop_event,
on_delivered=self._record_outbound_delivered,
on_failed=self._record_outbound_failed,
)
)
async def stop(self) -> None:
self._stop_event.set()
if self._bridge_task is not None:
self._bridge_task.cancel()
try:
await self._bridge_task
except asyncio.CancelledError:
pass
self._dispatch_stop_event.set()
if self._dispatch_task is not None:
try:
await asyncio.wait_for(self._dispatch_task, timeout=1.0)
except asyncio.TimeoutError:
self._dispatch_task.cancel()
try:
await self._dispatch_task
except asyncio.CancelledError:
pass
await self.manager.stop()
for channel_id in self.adapters:
self.events.record(channel_id=channel_id, kind="adapter_stopped")
async def add_channel(self, channel_id: str, config: ChannelConfig) -> None:
async with self._lifecycle_lock:
current = self.channel_configs.get(channel_id)
if current == config and channel_id in self.adapters:
return
if not config.enabled:
await self._remove_channel_locked(channel_id)
self.channel_configs[channel_id] = config
self.states[channel_id] = {"state": "disabled", "last_error": None}
return
adapter = self._build_adapter(channel_id, config)
await adapter.start()
old_adapter = self.adapters.get(channel_id)
self.manager.replace_registered(adapter)
self.adapters[channel_id] = adapter
self.channel_configs[channel_id] = config
self.states[channel_id] = {"state": "running", "last_error": None, "started_at": _iso_now()}
self.events.record(channel_id=channel_id, kind="adapter_started")
if old_adapter is not None and old_adapter is not adapter:
await old_adapter.stop()
async def remove_channel(self, channel_id: str) -> None:
async with self._lifecycle_lock:
await self._remove_channel_locked(channel_id)
async def _remove_channel_locked(self, channel_id: str) -> None:
adapter = self.adapters.pop(channel_id, None)
self.manager.unregister(channel_id)
self.channel_configs.pop(channel_id, None)
if adapter is not None:
await adapter.stop()
self.events.record(channel_id=channel_id, kind="adapter_stopped")
self.states[channel_id] = {"state": "removed", "last_error": None}
async def accept_inbound(self, message: InboundMessage) -> ChannelAcceptResult:
identity = message.channel_identity
if identity is None:
self.events.record(
channel_id=message.channel,
kind="inbound_rejected",
status="error",
error="channel_identity is required",
)
return ChannelAcceptResult(
accepted=False,
rejected=True,
error="channel_identity is required",
)
validation_error = identity.validation_error()
if validation_error:
self.events.record(
channel_id=identity.channel_id,
kind="inbound_rejected",
status="error",
error=validation_error,
)
return ChannelAcceptResult(accepted=False, rejected=True, error=validation_error)
expected_session_id = identity.session_id()
if message.session_id != expected_session_id:
self.events.record(
channel_id=identity.channel_id,
kind="session_id_normalized",
session_id=expected_session_id,
message_id=identity.message_id,
)
message.session_id = expected_session_id
message.channel = identity.channel_id
dedupe_key = identity.dedupe_key()
if dedupe_key:
write = self.dedupe.mark_processing(
dedupe_key=dedupe_key,
session_id=expected_session_id,
message_id=identity.message_id or "",
)
if not write.created:
record = write.record or {}
self.events.record(
channel_id=identity.channel_id,
kind="inbound_duplicate",
session_id=expected_session_id,
message_id=identity.message_id,
status=str(record.get("status") or "processing"),
)
return ChannelAcceptResult(
accepted=False,
duplicate=True,
pending=record.get("status") == "processing",
session_id=expected_session_id,
dedupe_key=dedupe_key,
record=record,
)
self.events.record(
channel_id=identity.channel_id,
kind="inbound_accepted",
session_id=expected_session_id,
message_id=identity.message_id,
text=message.content,
)
await self.bus.publish_inbound(message)
return ChannelAcceptResult(
accepted=True,
session_id=expected_session_id,
dedupe_key=dedupe_key,
)
def statuses(self) -> list[dict[str, Any]]:
items: list[dict[str, Any]] = []
recent = self.events.recent(limit=500)
last_by_channel = {event["channel_id"]: event for event in recent if event.get("channel_id")}
for channel_id, cfg in self.channel_configs.items():
state = self.states.get(channel_id, {"state": "configured", "last_error": None})
capabilities = _channel_capabilities(cfg.kind, cfg.mode)
webhook_url = None
websocket_url = None
connected_peers = 0
if cfg.kind == "webhook":
webhook_url = f"/api/channels/{channel_id}/webhook"
elif cfg.kind == "terminal" and cfg.mode == "websocket":
websocket_url = f"/api/channels/{channel_id}/ws"
adapter = self.adapters.get(channel_id)
if adapter is not None and hasattr(adapter, "status_extra"):
extra = adapter.status_extra() # type: ignore[attr-defined]
connected_peers = int(extra.get("connected_peers") or 0)
items.append(
{
"channel_id": channel_id,
"name": channel_id,
"kind": cfg.kind,
"mode": cfg.mode,
"display_name": cfg.display_name or channel_id,
"enabled": cfg.enabled,
"state": state.get("state", "configured"),
"account_id": cfg.account_id,
"last_error": state.get("last_error"),
"started_at": state.get("started_at"),
"last_event_at": last_by_channel.get(channel_id, {}).get("created_at"),
"capabilities": capabilities,
"webhook_url": webhook_url,
"websocket_url": websocket_url,
"connected_peers": connected_peers,
}
)
return items
def recent_events(self, channel_id: str, *, limit: int = 100) -> list[dict[str, Any]]:
return self.events.recent(channel_id=channel_id, limit=limit)
def record_event(
self,
*,
channel_id: str,
kind: str,
session_id: str | None = None,
message_id: str | None = None,
run_id: str | None = None,
status: str = "ok",
error: str | None = None,
metadata: dict[str, Any] | None = None,
) -> None:
self.events.record(
channel_id=channel_id,
kind=kind,
session_id=session_id,
message_id=message_id,
run_id=run_id,
status=status,
error=error,
metadata=metadata,
)
def _build_adapter(self, channel_id: str, cfg: ChannelConfig) -> ChannelAdapter:
if cfg.kind == "webhook" and cfg.mode == "webhook":
from beaver.interfaces.channels.generic_webhook import GenericWebhookAdapter
return GenericWebhookAdapter(
channel_id=channel_id,
kind=cfg.kind,
mode=cfg.mode,
account_id=cfg.account_id,
display_name=cfg.display_name,
inbound_sink=self,
response_timeout_seconds=float(cfg.config.get("response_timeout_seconds") or 1800),
)
if cfg.kind == "terminal" and cfg.mode == "websocket":
from beaver.interfaces.channels.terminal_websocket import TerminalWebSocketAdapter
return TerminalWebSocketAdapter(
channel_id=channel_id,
kind=cfg.kind,
mode=cfg.mode,
account_id=cfg.account_id,
display_name=cfg.display_name,
inbound_sink=self,
event_recorder=self.record_event,
heartbeat_seconds=float(cfg.config.get("heartbeat_seconds") or 30),
max_message_chars=int(cfg.config.get("max_message_chars") or 20000),
)
if cfg.kind == "telegram" and cfg.mode in {"polling", "webhook"}:
from beaver.interfaces.channels.platforms.telegram import TelegramAdapter
return TelegramAdapter(
channel_id=channel_id,
kind=cfg.kind,
mode=cfg.mode,
account_id=cfg.account_id,
display_name=cfg.display_name,
inbound_sink=self,
secrets=cfg.secrets,
config=cfg.config,
event_recorder=self.record_event,
)
if cfg.kind == "feishu" and cfg.mode in {"websocket", "webhook"}:
from beaver.interfaces.channels.platforms.feishu import FeishuAdapter
return FeishuAdapter(
channel_id=channel_id,
kind=cfg.kind,
mode=cfg.mode,
account_id=cfg.account_id,
display_name=cfg.display_name,
inbound_sink=self,
secrets=cfg.secrets,
config=cfg.config,
event_recorder=self.record_event,
)
if cfg.kind == "qqbot" and cfg.mode == "websocket":
from beaver.interfaces.channels.platforms.qqbot import QQBotAdapter
return QQBotAdapter(
channel_id=channel_id,
kind=cfg.kind,
mode=cfg.mode,
account_id=cfg.account_id,
display_name=cfg.display_name,
inbound_sink=self,
secrets=cfg.secrets,
config=cfg.config,
event_recorder=self.record_event,
)
if cfg.kind == "weixin" and cfg.mode == "polling":
from beaver.interfaces.channels.platforms.weixin import WeixinAdapter
return WeixinAdapter(
channel_id=channel_id,
kind=cfg.kind,
mode=cfg.mode,
account_id=cfg.account_id,
display_name=cfg.display_name,
inbound_sink=self,
secrets=cfg.secrets,
config=cfg.config,
event_recorder=self.record_event,
)
if cfg.kind == "external_connector" and cfg.mode == "http":
import os
from beaver.interfaces.channels.connections.sidecar_client import ConnectorSidecarClient
from beaver.interfaces.channels.external_connector import ExternalConnectorChannel
base_url = str(cfg.config.get("sidecarBaseUrl") or os.getenv("EXTERNAL_CONNECTOR_BASE_URL") or "").strip()
token = os.getenv("EXTERNAL_CONNECTOR_TOKEN", "")
platform_kind = str(cfg.config.get("platformKind") or "").strip()
connection_id = str(cfg.config.get("connectionId") or "").strip()
if not base_url:
raise ValueError("external connector sidecarBaseUrl is required")
if not platform_kind:
raise ValueError("external connector platformKind is required")
if not connection_id:
raise ValueError("external connector connectionId is required")
return ExternalConnectorChannel(
channel_id=channel_id,
platform_kind=platform_kind,
connection_id=connection_id,
account_id=cfg.account_id,
display_name=cfg.display_name,
sidecar_client=ConnectorSidecarClient(base_url=base_url, token=token),
)
raise ValueError(f"Unsupported channel kind/mode: {cfg.kind}/{cfg.mode}")
async def _bridge_inbound_to_agent(self) -> None:
current_inbound: InboundMessage | None = None
while not self._stop_event.is_set():
try:
current_inbound = await asyncio.wait_for(self.bus.consume_inbound(), timeout=0.25)
except asyncio.TimeoutError:
continue
except asyncio.CancelledError:
raise
inbound = current_inbound
identity = inbound.channel_identity
try:
self.events.record(
channel_id=inbound.channel,
kind="direct_run_started",
session_id=inbound.session_id,
message_id=identity.message_id if identity else inbound.message_id,
)
outbound = await self.service.handle_inbound_message(inbound)
except asyncio.CancelledError:
outbound = AgentService.build_outbound_error(
inbound,
detail="Channel runtime stopped before completing the inbound message",
finish_reason="cancelled",
)
self._mark_dedupe_result(inbound, outbound)
await self.bus.publish_outbound(outbound)
current_inbound = None
raise
except Exception as exc:
self.events.record(
channel_id=inbound.channel,
kind="direct_run_failed",
session_id=inbound.session_id,
message_id=identity.message_id if identity else inbound.message_id,
status="error",
error=str(exc),
)
outbound = AgentService.build_outbound_error(
inbound,
detail=str(exc),
finish_reason="error",
)
else:
self.events.record(
channel_id=outbound.channel,
kind="direct_run_finished",
session_id=outbound.session_id,
message_id=identity.message_id if identity else inbound.message_id,
run_id=outbound.run_id,
)
self._mark_dedupe_result(inbound, outbound)
await self.bus.publish_outbound(outbound)
current_inbound = None
def _mark_dedupe_result(self, inbound: InboundMessage, outbound: OutboundMessage) -> None:
identity = inbound.channel_identity
dedupe_key = identity.dedupe_key() if identity else None
if not dedupe_key:
return
cfg = self.channel_configs.get(identity.channel_id)
max_reply_chars = int((cfg.config if cfg else {}).get("max_cached_reply_chars") or 20000)
max_error_chars = int((cfg.config if cfg else {}).get("max_cached_error_chars") or 4000)
if outbound.finish_reason == "error":
self.dedupe.mark_error(
dedupe_key=dedupe_key,
error=outbound.content,
max_error_chars=max_error_chars,
)
else:
self.dedupe.mark_done(
dedupe_key=dedupe_key,
run_id=outbound.run_id,
reply=outbound.content,
max_reply_chars=max_reply_chars,
)
async def _record_outbound_delivered(self, message: OutboundMessage) -> None:
kind = "outbound_unclaimed" if message.metadata.get("delivery_status") == "unclaimed" else "outbound_delivered"
self.events.record(
channel_id=message.channel,
kind=kind,
session_id=message.session_id,
message_id=message.channel_identity.message_id if message.channel_identity else message.message_id,
run_id=message.run_id,
)
async def _record_outbound_failed(self, message: OutboundMessage, exc: Exception | None) -> None:
self.events.record(
channel_id=message.channel,
kind="outbound_delivery_failed",
session_id=message.session_id,
message_id=message.channel_identity.message_id if message.channel_identity else message.message_id,
run_id=message.run_id,
status="error",
error=str(exc) if exc else "channel not registered",
)
def _default_dedupe_retention_hours(self) -> int:
for cfg in self.channel_configs.values():
value = cfg.config.get("dedupe_retention_hours")
if value is not None:
return int(value)
return 48

View File

@ -0,0 +1,198 @@
"""Persistent channel runtime state."""
from __future__ import annotations
import json
import time
from dataclasses import dataclass
from datetime import datetime, timezone
from pathlib import Path
from threading import Lock
from typing import Any
from uuid import uuid4
def _now_ms() -> int:
return int(time.time() * 1000)
def _iso_now() -> str:
return datetime.now(timezone.utc).isoformat()
@dataclass(slots=True)
class DedupeWriteResult:
created: bool
record: dict[str, Any] | None = None
class ChannelDedupeStore:
def __init__(self, path: Path, *, retention_hours: int = 48) -> None:
self.path = path
self.retention_ms = max(1, int(retention_hours)) * 60 * 60 * 1000
self._lock = Lock()
def get(self, dedupe_key: str) -> dict[str, Any] | None:
with self._lock:
data = self._load()
self._prune_unlocked(data, _now_ms())
record = data["records"].get(dedupe_key)
self._save(data)
return record
def mark_processing(self, *, dedupe_key: str, session_id: str, message_id: str) -> DedupeWriteResult:
with self._lock:
data = self._load()
now_ms = _now_ms()
self._prune_unlocked(data, now_ms)
existing = data["records"].get(dedupe_key)
if existing is not None:
self._save(data)
return DedupeWriteResult(created=False, record=existing)
record = {
"dedupe_key": dedupe_key,
"status": "processing",
"session_id": session_id,
"message_id": message_id,
"run_id": None,
"reply": None,
"error": None,
"created_at_ms": now_ms,
"updated_at_ms": now_ms,
}
data["records"][dedupe_key] = record
self._save(data)
return DedupeWriteResult(created=True, record=record)
def mark_done(
self,
*,
dedupe_key: str,
run_id: str | None,
reply: str,
max_reply_chars: int,
) -> None:
self._mark_result(
dedupe_key=dedupe_key,
status="done",
run_id=run_id,
reply=reply[: max(0, int(max_reply_chars))],
error=None,
)
def mark_error(self, *, dedupe_key: str, error: str, max_error_chars: int) -> None:
self._mark_result(
dedupe_key=dedupe_key,
status="error",
run_id=None,
reply=None,
error=error[: max(0, int(max_error_chars))],
)
def _mark_result(
self,
*,
dedupe_key: str,
status: str,
run_id: str | None,
reply: str | None,
error: str | None,
) -> None:
with self._lock:
data = self._load()
record = data["records"].get(dedupe_key)
if record is None:
record = {"dedupe_key": dedupe_key, "created_at_ms": _now_ms()}
data["records"][dedupe_key] = record
record.update(
{
"status": status,
"run_id": run_id,
"reply": reply,
"error": error,
"updated_at_ms": _now_ms(),
}
)
self._save(data)
def _load(self) -> dict[str, Any]:
if not self.path.exists():
return {"records": {}}
try:
data = json.loads(self.path.read_text(encoding="utf-8"))
except (OSError, json.JSONDecodeError):
return {"records": {}}
if not isinstance(data, dict) or not isinstance(data.get("records"), dict):
return {"records": {}}
return data
def _save(self, data: dict[str, Any]) -> None:
self.path.parent.mkdir(parents=True, exist_ok=True)
tmp_path = self.path.with_name(f"{self.path.name}.tmp")
tmp_path.write_text(json.dumps(data, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
tmp_path.replace(self.path)
def _prune_unlocked(self, data: dict[str, Any], now_ms: int) -> None:
records = data.get("records", {})
expired_before = now_ms - self.retention_ms
for key, record in list(records.items()):
updated_at_ms = int(record.get("updated_at_ms") or record.get("created_at_ms") or 0)
if updated_at_ms < expired_before:
records.pop(key, None)
class ChannelEventLog:
def __init__(self, path: Path) -> None:
self.path = path
self._lock = Lock()
def record(
self,
*,
channel_id: str,
kind: str,
session_id: str | None = None,
message_id: str | None = None,
run_id: str | None = None,
status: str = "ok",
error: str | None = None,
text: str | None = None,
metadata: dict[str, Any] | None = None,
) -> dict[str, Any]:
entry = {
"event_id": uuid4().hex,
"channel_id": channel_id,
"kind": kind,
"session_id": session_id,
"message_id": message_id,
"run_id": run_id,
"status": status,
"error": error,
"text_preview": (text or "")[:120] if text else None,
"text_length": len(text) if text else 0,
"metadata": metadata or {},
"created_at": _iso_now(),
}
with self._lock:
self.path.parent.mkdir(parents=True, exist_ok=True)
with self.path.open("a", encoding="utf-8") as handle:
handle.write(json.dumps(entry, ensure_ascii=False) + "\n")
return entry
def recent(self, *, channel_id: str | None = None, limit: int = 100) -> list[dict[str, Any]]:
if not self.path.exists():
return []
lines = self.path.read_text(encoding="utf-8").splitlines()
items: list[dict[str, Any]] = []
for line in reversed(lines):
try:
item = json.loads(line)
except json.JSONDecodeError:
continue
if channel_id and item.get("channel_id") != channel_id:
continue
items.append(item)
if len(items) >= max(1, int(limit)):
break
return list(reversed(items))

View File

@ -0,0 +1,301 @@
"""Text-only terminal WebSocket channel adapter."""
from __future__ import annotations
from collections.abc import Callable
from contextlib import suppress
from dataclasses import dataclass, field
from typing import Any
from beaver.foundation.events import ChannelIdentity, InboundMessage, OutboundMessage
from beaver.interfaces.channels.base import ChannelInboundSink
try:
from fastapi import WebSocket
from starlette.websockets import WebSocketDisconnect
except ModuleNotFoundError: # pragma: no cover - import-only fallback
class WebSocketDisconnect(Exception):
"""Fallback disconnect exception for skeleton import environments."""
class WebSocket: # type: ignore[override]
"""Fallback websocket annotation shim."""
def _clean(value: Any) -> str:
return str(value or "").strip()
@dataclass(slots=True)
class TerminalConnection:
websocket: WebSocket
peer_id: str
session_id: str
thread_id: str | None = None
user_id: str | None = None
device_name: str = ""
capabilities: list[str] = field(default_factory=list)
class TerminalWebSocketAdapter:
"""Accept text terminal websocket frames and deliver final assistant replies."""
def __init__(
self,
*,
channel_id: str,
kind: str,
mode: str,
account_id: str,
display_name: str = "",
inbound_sink: ChannelInboundSink,
event_recorder: Callable[..., None] | None = None,
heartbeat_seconds: float = 30,
max_message_chars: int = 20000,
) -> None:
self.channel_id = channel_id
self.kind = kind
self.mode = mode
self.account_id = account_id
self.display_name = display_name or channel_id
self.inbound_sink = inbound_sink
self.event_recorder = event_recorder
self.heartbeat_seconds = max(1.0, float(heartbeat_seconds))
self.max_message_chars = max(1, int(max_message_chars))
self.started = False
self._connections_by_session: dict[str, TerminalConnection] = {}
self._session_by_peer: dict[str, str] = {}
async def start(self) -> None:
self.started = True
async def stop(self) -> None:
self.started = False
for connection in list(self._connections_by_session.values()):
with suppress(Exception):
await connection.websocket.close(code=1001)
self._connections_by_session.clear()
self._session_by_peer.clear()
def status_extra(self) -> dict[str, Any]:
return {"connected_peers": len(self._connections_by_session)}
async def handle_websocket(self, websocket: WebSocket) -> None:
await websocket.accept()
connection: TerminalConnection | None = None
try:
while True:
try:
payload = await websocket.receive_json()
except WebSocketDisconnect:
break
except ValueError:
await websocket.send_json({"type": "error", "error": "Invalid websocket JSON payload"})
continue
if not isinstance(payload, dict):
await websocket.send_json({"type": "error", "error": "Websocket payload must be a JSON object"})
continue
frame_type = _clean(payload.get("type")).lower()
if frame_type == "ping":
await websocket.send_json({"type": "pong"})
continue
if frame_type == "connect":
connection = await self._handle_connect(websocket, payload, current=connection)
continue
if frame_type == "message":
if connection is None:
await websocket.send_json({"type": "error", "error": "connect is required before message"})
continue
await self._handle_message(websocket, connection, payload)
continue
await websocket.send_json(
{
"type": "error",
"error": f"Unsupported websocket frame type: {frame_type or '<empty>'}",
}
)
finally:
if connection is not None:
self._remove_connection(connection)
self._record(
kind="terminal_disconnected",
session_id=connection.session_id,
metadata={"peer_id": connection.peer_id, "device_name": connection.device_name},
)
async def _handle_connect(
self,
websocket: WebSocket,
payload: dict[str, Any],
*,
current: TerminalConnection | None,
) -> TerminalConnection | None:
peer_id = _clean(payload.get("peer_id"))
if not peer_id:
await websocket.send_json({"type": "error", "error": "peer_id is required"})
return current
thread_id = _clean(payload.get("thread_id")) or None
user_id = _clean(payload.get("user_id")) or None
device_name = _clean(payload.get("device_name"))
capabilities = [str(item) for item in payload.get("capabilities") or [] if item is not None]
identity = ChannelIdentity(
channel_id=self.channel_id,
kind=self.kind,
account_id=self.account_id,
peer_id=peer_id,
thread_id=thread_id,
peer_type="terminal",
user_id=user_id,
)
session_id = identity.session_id()
connection = TerminalConnection(
websocket=websocket,
peer_id=peer_id,
session_id=session_id,
thread_id=thread_id,
user_id=user_id,
device_name=device_name,
capabilities=capabilities,
)
if current is not None and current.session_id != session_id:
self._remove_connection(current)
old = self._connections_by_session.get(session_id)
if old is not None and old.websocket is not websocket:
with suppress(Exception):
await old.websocket.close(code=1000)
self._connections_by_session[session_id] = connection
self._session_by_peer[peer_id] = session_id
self._record(
kind="terminal_connected",
session_id=session_id,
metadata={"peer_id": peer_id, "device_name": device_name, "capabilities": capabilities},
)
await websocket.send_json(
{
"type": "connected",
"channel_id": self.channel_id,
"session_id": session_id,
}
)
return connection
async def _handle_message(
self,
websocket: WebSocket,
connection: TerminalConnection,
payload: dict[str, Any],
) -> None:
message_id = _clean(payload.get("message_id"))
text = _clean(payload.get("text"))
if not message_id:
await websocket.send_json({"type": "error", "error": "message_id is required"})
return
if not text:
await websocket.send_json({"type": "error", "error": "text is required"})
return
if len(text) > self.max_message_chars:
await websocket.send_json(
{
"type": "error",
"error": f"text exceeds max_message_chars ({self.max_message_chars})",
}
)
return
thread_id = _clean(payload.get("thread_id")) or connection.thread_id
user_id = _clean(payload.get("user_id")) or connection.user_id
identity = ChannelIdentity(
channel_id=self.channel_id,
kind=self.kind,
account_id=self.account_id,
peer_id=connection.peer_id,
thread_id=thread_id,
peer_type="terminal",
user_id=user_id,
message_id=message_id,
)
inbound = InboundMessage(
channel=self.channel_id,
content=text,
content_type="text",
user_id=user_id,
channel_identity=identity,
metadata={
"terminal": {
"peer_id": connection.peer_id,
"device_name": connection.device_name,
"capabilities": connection.capabilities,
}
},
)
accept = await self.inbound_sink.accept_inbound(inbound)
ack: dict[str, Any] = {
"type": "ack",
"message_id": message_id,
"session_id": accept.session_id or identity.session_id(),
"accepted": accept.accepted,
}
if accept.duplicate:
ack["duplicate"] = True
ack["pending"] = accept.pending
record = accept.record or {}
if record.get("reply"):
ack["reply"] = record["reply"]
if accept.error or record.get("error"):
ack["error"] = accept.error or record.get("error")
await websocket.send_json(ack)
async def send(self, message: OutboundMessage) -> None:
session_id = message.session_id
if not session_id and message.channel_identity is not None:
session_id = message.channel_identity.session_id()
connection = self._connections_by_session.get(session_id or "")
if connection is None:
message.metadata["delivery_status"] = "unclaimed"
return
payload = {
"type": "message",
"role": "assistant",
"message_id": message.channel_identity.message_id if message.channel_identity else message.message_id,
"run_id": message.run_id,
"text": message.content,
"finish_reason": message.finish_reason,
}
try:
await connection.websocket.send_json(payload)
except Exception:
message.metadata["delivery_status"] = "unclaimed"
self._remove_connection(connection)
def _remove_connection(self, connection: TerminalConnection) -> None:
current = self._connections_by_session.get(connection.session_id)
if current is connection:
self._connections_by_session.pop(connection.session_id, None)
if self._session_by_peer.get(connection.peer_id) == connection.session_id:
self._session_by_peer.pop(connection.peer_id, None)
def _record(
self,
*,
kind: str,
session_id: str | None = None,
message_id: str | None = None,
status: str = "ok",
error: str | None = None,
metadata: dict[str, Any] | None = None,
) -> None:
if self.event_recorder is None:
return
self.event_recorder(
channel_id=self.channel_id,
kind=kind,
session_id=session_id,
message_id=message_id,
status=status,
error=error,
metadata=metadata,
)

File diff suppressed because it is too large Load Diff

View File

@ -0,0 +1,152 @@
"""Keycloak OIDC token verification for the Beaver web app."""
from __future__ import annotations
from dataclasses import dataclass
import os
import time
from typing import Any
import jwt
from jwt import PyJWKClient
try:
from fastapi import HTTPException
except ModuleNotFoundError: # pragma: no cover
class HTTPException(Exception): # type: ignore[override]
def __init__(self, status_code: int, detail: str) -> None:
super().__init__(detail)
self.status_code = status_code
self.detail = detail
DEFAULT_KEYCLOAK_ISSUER = "https://keycloak.bwgdi.com/realms/beaver"
DEFAULT_KEYCLOAK_CLIENT_ID = "beaver-agnet"
@dataclass(frozen=True, slots=True)
class KeycloakAuthConfig:
issuer: str
client_id: str
token_url: str
jwks_url: str
@classmethod
def from_env(cls) -> "KeycloakAuthConfig":
issuer = _clean_base_url(os.getenv("BEAVER_KEYCLOAK_ISSUER") or DEFAULT_KEYCLOAK_ISSUER)
client_id = (os.getenv("BEAVER_KEYCLOAK_CLIENT_ID") or DEFAULT_KEYCLOAK_CLIENT_ID).strip()
token_url = (
os.getenv("BEAVER_KEYCLOAK_TOKEN_URL", "").strip()
or f"{issuer}/protocol/openid-connect/token"
)
jwks_url = (
os.getenv("BEAVER_KEYCLOAK_JWKS_URL", "").strip()
or f"{issuer}/protocol/openid-connect/certs"
)
return cls(issuer=issuer, client_id=client_id, token_url=token_url, jwks_url=jwks_url)
@dataclass(frozen=True, slots=True)
class KeycloakIdentity:
user_id: str
username: str
email: str = ""
name: str = ""
realm_roles: tuple[str, ...] = ()
client_roles: tuple[str, ...] = ()
def extract_bearer_token(authorization: str | None) -> str:
if not authorization:
raise HTTPException(status_code=401, detail="Missing Authorization header")
prefix = "bearer "
if not authorization.lower().startswith(prefix):
raise HTTPException(status_code=401, detail="Invalid Authorization header")
token = authorization[len(prefix):].strip()
if not token:
raise HTTPException(status_code=401, detail="Invalid token")
return token
class KeycloakTokenVerifier:
def __init__(self, *, config: KeycloakAuthConfig) -> None:
self.config = config
self._jwks_client = PyJWKClient(config.jwks_url)
def verify(self, token: str, *, expected_nonce: str | None = None) -> KeycloakIdentity:
try:
signing_key = self._jwks_client.get_signing_key_from_jwt(token).key
claims = jwt.decode(
token,
signing_key,
algorithms=["RS256"],
issuer=self.config.issuer,
options={
"require": ["exp", "iat", "iss"],
"verify_aud": False,
},
)
except Exception as exc: # noqa: BLE001 - normalize JWT/JWKS failures for HTTP callers
raise HTTPException(status_code=401, detail=f"Invalid token: {exc}") from exc
return self.validate_claims(claims, expected_nonce=expected_nonce)
def validate_claims(self, claims: dict[str, Any], *, expected_nonce: str | None = None) -> KeycloakIdentity:
now = int(time.time())
issuer = str(claims.get("iss") or "")
if issuer != self.config.issuer:
raise HTTPException(status_code=401, detail="Invalid token issuer")
exp = _int_claim(claims, "exp")
iat = _int_claim(claims, "iat")
if exp <= now:
raise HTTPException(status_code=401, detail="Token expired")
if iat > now + 120:
raise HTTPException(status_code=401, detail="Token issued in the future")
if not _matches_client(claims.get("aud"), self.config.client_id) and claims.get("azp") != self.config.client_id:
raise HTTPException(status_code=401, detail="Invalid token audience")
if expected_nonce is not None and claims.get("nonce") != expected_nonce:
raise HTTPException(status_code=401, detail="Invalid token nonce")
user_id = str(claims.get("sub") or "").strip()
if not user_id:
raise HTTPException(status_code=401, detail="Token subject is required")
username = (
str(claims.get("preferred_username") or "").strip()
or str(claims.get("email") or "").strip()
or user_id
)
return KeycloakIdentity(
user_id=user_id,
username=username,
email=str(claims.get("email") or "").strip(),
name=str(claims.get("name") or "").strip(),
realm_roles=_roles_from(claims.get("realm_access")),
client_roles=_roles_from((claims.get("resource_access") or {}).get(self.config.client_id) if isinstance(claims.get("resource_access"), dict) else None),
)
def _clean_base_url(value: str) -> str:
return value.strip().rstrip("/")
def _int_claim(claims: dict[str, Any], key: str) -> int:
try:
return int(claims[key])
except (KeyError, TypeError, ValueError) as exc:
raise HTTPException(status_code=401, detail=f"Token {key} claim is required") from exc
def _matches_client(audience: Any, client_id: str) -> bool:
if isinstance(audience, str):
return audience == client_id
if isinstance(audience, list):
return client_id in {str(item) for item in audience}
return False
def _roles_from(value: Any) -> tuple[str, ...]:
if not isinstance(value, dict):
return ()
roles = value.get("roles")
if not isinstance(roles, list):
return ()
return tuple(str(role) for role in roles if str(role).strip())

View File

@ -1,11 +1,25 @@
"""Web request and response schemas."""
from .chat import (
WebChatAcceptanceRequest,
WebChatAcceptanceResponse,
WebChatFeedbackRequest,
WebChatFeedbackResponse,
WebChatRequest,
WebChatResponse,
WebErrorResponse,
WebAgentConfigRequest,
WebAgentConfigResponse,
WebChannelConfigRequest,
WebChannelConfigResponse,
WebChannelConnectionCreateRequest,
WebChannelConnectionResponse,
WebChannelConnectionUpdateRequest,
WebChannelValidationResponse,
WebConnectorBridgeEventRequest,
WebConnectorBridgeEventResponse,
WebConnectorSessionCreateRequest,
WebConnectorSessionResponse,
WebProviderConfigRequest,
WebProviderConfigResponse,
WebProviderTarget,
@ -13,11 +27,25 @@ from .chat import (
)
__all__ = [
"WebChatAcceptanceRequest",
"WebChatAcceptanceResponse",
"WebChatFeedbackRequest",
"WebChatFeedbackResponse",
"WebChatRequest",
"WebChatResponse",
"WebErrorResponse",
"WebAgentConfigRequest",
"WebAgentConfigResponse",
"WebChannelConfigRequest",
"WebChannelConfigResponse",
"WebChannelConnectionCreateRequest",
"WebChannelConnectionResponse",
"WebChannelConnectionUpdateRequest",
"WebChannelValidationResponse",
"WebConnectorBridgeEventRequest",
"WebConnectorBridgeEventResponse",
"WebConnectorSessionCreateRequest",
"WebConnectorSessionResponse",
"WebProviderConfigRequest",
"WebProviderConfigResponse",
"WebProviderTarget",

View File

@ -55,6 +55,7 @@ class WebChatRequest(BaseModel):
user_id: str | None = None
title: str | None = None
execution_context: str | None = None
prompt_locale: str | None = None
model: str | None = None
provider_name: str | None = None
embedding_model: str | None = None
@ -82,11 +83,34 @@ class WebChatResponse(BaseModel):
usage: dict[str, Any] = Field(default_factory=dict)
task_id: str | None = None
task_status: str | None = None
evidence_status: str | None = None
acceptance_state: str | None = None
validation_result: dict[str, Any] | None = None
class WebChatAcceptanceRequest(BaseModel):
"""User acceptance on the latest assistant result in chat."""
session_id: str
run_id: str
acceptance_type: str
comment: str | None = None
class WebChatAcceptanceResponse(BaseModel):
"""Acceptance recording result."""
session_id: str
run_id: str
task_id: str
task_status: str
acceptance_type: str
feedback_type: str
learning_candidates: list[dict[str, Any]] = Field(default_factory=list)
class WebChatFeedbackRequest(BaseModel):
"""Feedback on the latest assistant result in chat."""
"""Backward-compatible feedback payload."""
session_id: str
run_id: str
@ -94,15 +118,8 @@ class WebChatFeedbackRequest(BaseModel):
comment: str | None = None
class WebChatFeedbackResponse(BaseModel):
"""Feedback recording result."""
session_id: str
run_id: str
task_id: str
task_status: str
feedback_type: str
learning_candidates: list[dict[str, Any]] = Field(default_factory=list)
class WebChatFeedbackResponse(WebChatAcceptanceResponse):
"""Backward-compatible feedback response."""
class WebProviderConfigRequest(BaseModel):
@ -123,6 +140,127 @@ class WebProviderConfigResponse(BaseModel):
enabled: bool
class WebChannelConfigRequest(BaseModel):
"""Channel config update from the settings page."""
enabled: bool = False
kind: str
mode: str
account_id: str | None = None
display_name: str | None = None
config: dict[str, Any] = Field(default_factory=dict)
secrets: dict[str, str | None] = Field(default_factory=dict)
class WebChannelConfigResponse(BaseModel):
"""Channel config update result."""
ok: bool
channel_id: str
restart_required: bool
channel: dict[str, Any]
class WebChannelConnectionCreateRequest(BaseModel):
"""Create a channel connection from the setup UI."""
kind: str
mode: str
display_name: str | None = Field(default=None, alias="displayName")
owner_user_id: str | None = Field(default=None, alias="ownerUserId")
auth_type: str = Field(default="token", alias="authType")
account_id: str | None = Field(default=None, alias="accountId")
config: dict[str, Any] = Field(default_factory=dict)
secrets: dict[str, str | None] = Field(default_factory=dict)
class WebChannelConnectionResponse(BaseModel):
"""Channel connection response with redacted credentials."""
connection: dict[str, Any]
credentials: dict[str, str] = Field(default_factory=dict)
class WebChannelConnectionUpdateRequest(BaseModel):
"""Update editable channel connection setup fields."""
display_name: str | None = Field(default=None, alias="displayName")
account_id: str | None = Field(default=None, alias="accountId")
config: dict[str, Any] | None = None
secrets: dict[str, str | None] | None = None
class WebChannelValidationResponse(BaseModel):
"""Connector validation response."""
ok: bool
status: str
account_id: str | None = None
display_name: str | None = None
error: str | None = None
metadata: dict[str, Any] = Field(default_factory=dict)
connection: dict[str, Any]
class WebConnectorBridgeEventRequest(BaseModel):
"""Inbound connector bridge event from the external sidecar."""
event_id: str = Field(alias="eventId")
timestamp: str
delivery_attempt: int = Field(default=1, alias="deliveryAttempt")
connection_id: str = Field(alias="connectionId")
channel_id: str = Field(alias="channelId")
kind: str
account_id: str = Field(alias="accountId")
peer_id: str = Field(alias="peerId")
peer_type: str = Field(default="unknown", alias="peerType")
user_id: str | None = Field(default=None, alias="userId")
thread_id: str | None = Field(default=None, alias="threadId")
message_id: str = Field(alias="messageId")
message_type: str = Field(default="text", alias="messageType")
content: str
metadata: dict[str, Any] = Field(default_factory=dict)
class WebConnectorBridgeEventResponse(BaseModel):
"""Connector bridge event accept/dedupe response."""
accepted: bool
duplicate: bool = False
pending: bool = False
retry_after_seconds: int | None = Field(default=None, alias="retryAfterSeconds")
class WebConnectorSessionCreateRequest(BaseModel):
"""Start a connector-managed onboarding session."""
kind: str
display_name: str | None = Field(default=None, alias="displayName")
owner_user_id: str | None = Field(default=None, alias="ownerUserId")
options: dict[str, Any] = Field(default_factory=dict)
class WebConnectorSessionResponse(BaseModel):
"""Connector session view plus optional connection view."""
session: dict[str, Any]
connection: dict[str, Any] | None = None
class WebAgentConfigRequest(BaseModel):
"""Agent runtime defaults update from the settings page."""
max_tokens: int | None = None
temperature: float
max_tool_iterations: int
class WebAgentConfigResponse(BaseModel):
"""Agent runtime defaults update result."""
ok: bool
class WebStatusResponse(BaseModel):
"""Web 宿主层状态响应。"""

View File

@ -227,6 +227,15 @@ class SkillDraftEvalReport:
cases: list[dict[str, Any]] = field(default_factory=list)
status: str = "completed"
created_at: str = ""
eval_version: str = "heuristic-v1"
mode: str = "heuristic"
execution_coverage: float = 0.0
surrogate_coverage: float = 0.0
blocked_coverage: float = 0.0
confidence: str = "low"
case_reports: list[dict[str, Any]] = field(default_factory=list)
tool_mode_summary: dict[str, Any] = field(default_factory=dict)
preservation_report: dict[str, Any] | None = None
def to_dict(self) -> dict[str, Any]:
return {
@ -244,6 +253,17 @@ class SkillDraftEvalReport:
"cases": [dict(item) for item in self.cases],
"status": self.status,
"created_at": self.created_at,
"eval_version": self.eval_version,
"mode": self.mode,
"execution_coverage": self.execution_coverage,
"surrogate_coverage": self.surrogate_coverage,
"blocked_coverage": self.blocked_coverage,
"confidence": self.confidence,
"case_reports": [dict(item) for item in self.case_reports],
"tool_mode_summary": dict(self.tool_mode_summary),
"preservation_report": (
dict(self.preservation_report) if self.preservation_report is not None else None
),
}
@classmethod
@ -263,6 +283,23 @@ class SkillDraftEvalReport:
cases=[dict(item) for item in payload.get("cases") or [] if isinstance(item, dict)],
status=str(payload.get("status") or "completed"),
created_at=str(payload.get("created_at") or ""),
eval_version=str(payload.get("eval_version") or "heuristic-v1"),
mode=str(payload.get("mode") or "heuristic"),
execution_coverage=_bounded_float(payload.get("execution_coverage"), default=0.0),
surrogate_coverage=_bounded_float(payload.get("surrogate_coverage"), default=0.0),
blocked_coverage=_bounded_float(payload.get("blocked_coverage"), default=0.0),
confidence=str(payload.get("confidence") or "low"),
case_reports=[
dict(item)
for item in payload.get("case_reports") or []
if isinstance(item, dict)
],
tool_mode_summary=dict(payload.get("tool_mode_summary") or {}),
preservation_report=(
dict(payload["preservation_report"])
if isinstance(payload.get("preservation_report"), dict)
else None
),
)
@ -272,6 +309,15 @@ def _optional_str(value: Any) -> str | None:
return str(value)
def _bounded_float(value: Any, *, default: float = 0.0) -> float:
if value in (None, ""):
return default
try:
return max(0.0, min(1.0, float(value)))
except (TypeError, ValueError):
return default
def _summarize_evidence(payload: dict[str, Any]) -> str:
evidence = payload.get("evidence")
if isinstance(evidence, dict):

View File

@ -0,0 +1,5 @@
"""Prompt templates used by Beaver runtime components."""
from .main_agent import get_main_agent_prompt
__all__ = ["get_main_agent_prompt"]

View File

@ -0,0 +1,55 @@
"""Locale-aware main agent prompt loading."""
from __future__ import annotations
from functools import lru_cache
from pathlib import Path
DEFAULT_MAIN_AGENT_PROMPT_LOCALE = "zh-Hans"
_PROMPT_FILES = {
"zh-Hans": "zh-Hans.md",
"zh-Hant": "zh-Hant.md",
"en": "en.md",
}
_LOCALE_ALIASES = {
"zh": "zh-Hans",
"zh-cn": "zh-Hans",
"zh-hans": "zh-Hans",
"zh-sg": "zh-Hans",
"zh-hant": "zh-Hant",
"zh-tw": "zh-Hant",
"zh-hk": "zh-Hant",
"zh-mo": "zh-Hant",
"en": "en",
"en-us": "en",
"en-gb": "en",
}
def get_main_agent_prompt(locale: str | None = None) -> str:
"""Return the main-agent identity prompt for a prompt locale."""
prompt_locale = normalize_main_agent_prompt_locale(locale)
return _load_main_agent_prompt(prompt_locale)
def normalize_main_agent_prompt_locale(locale: str | None = None) -> str:
cleaned = (locale or DEFAULT_MAIN_AGENT_PROMPT_LOCALE).strip()
if not cleaned:
return DEFAULT_MAIN_AGENT_PROMPT_LOCALE
normalized = _LOCALE_ALIASES.get(cleaned.lower())
if normalized:
return normalized
return cleaned if cleaned in _PROMPT_FILES else DEFAULT_MAIN_AGENT_PROMPT_LOCALE
@lru_cache(maxsize=len(_PROMPT_FILES))
def _load_main_agent_prompt(locale: str) -> str:
filename = _PROMPT_FILES.get(locale, _PROMPT_FILES[DEFAULT_MAIN_AGENT_PROMPT_LOCALE])
path = Path(__file__).with_name("main_agent") / filename
if not path.exists():
fallback_path = Path(__file__).with_name("main_agent") / _PROMPT_FILES[DEFAULT_MAIN_AGENT_PROMPT_LOCALE]
return fallback_path.read_text(encoding="utf-8").strip()
return path.read_text(encoding="utf-8").strip()

View File

@ -0,0 +1,7 @@
You are Beaver, an AI assistant developed by Boway Information Systems Co., Ltd.
When communicating with users, keep this identity consistent. If users ask who you are, say that you are Beaver, an AI assistant developed by Boway Information Systems Co., Ltd.
# Language
Use English for user-facing replies, task titles, summaries, plans, and final reports while this prompt is active. If the user explicitly asks for another language, follow that request.

View File

@ -0,0 +1,7 @@
你是海狸 (Beaver),博维资讯系统有限公司研发的 AI 助手。
与用户沟通时,保持这个身份一致。用户问你是谁时,说明你是海狸 (Beaver),博维资讯系统有限公司研发的 AI 助手。
# 语言
使用简体中文进行面向用户的回复、任务标题、摘要、计划和最终报告。若用户明确要求其他语言,则按用户要求执行。

View File

@ -0,0 +1,7 @@
你是海狸 (Beaver),博維資訊系統有限公司研發的 AI 助手。
與使用者溝通時,保持這個身份一致。使用者問你是誰時,說明你是海狸 (Beaver),博維資訊系統有限公司研發的 AI 助手。
# 語言
使用繁體中文進行面向使用者的回覆、任務標題、摘要、計劃和最終報告。若使用者明確要求其他語言,則按使用者要求執行。

View File

@ -22,7 +22,17 @@ from beaver.engine import AgentLoop, AgentProfile, AgentRunResult, EngineLoader
from beaver.engine.providers import make_provider_bundle
from beaver.foundation.events import InboundMessage, OutboundMessage
from beaver.foundation.models import CronJob, CronRunRecord
from beaver.tasks import MainAgentRouter, TaskExecutionPlan, TaskRecord, ValidationResult
from beaver.prompts.main_agent import normalize_main_agent_prompt_locale
from beaver.tasks import (
EvidenceBuilder,
MainAgentRouter,
RunEvidence,
TaskEvidencePacket,
TaskExecutionPlan,
TaskRecord,
render_task_evidence,
)
from beaver.tasks.service import normalize_acceptance_type
NOTIFICATION_SESSION_ID = "notify:default:scheduled"
@ -51,11 +61,27 @@ class AgentService:
) -> None:
self.profile = profile or AgentProfile()
self.loader = loader or EngineLoader(workspace=workspace, config_path=config_path)
self._apply_configured_profile_defaults()
self._loop: AgentLoop | None = None
self._run_task: asyncio.Task[None] | None = None
self._main_agent_router = MainAgentRouter()
self._runtime_services: dict[str, Any] = {}
def _apply_configured_profile_defaults(self) -> None:
defaults = self.loader.config.agents_defaults
self.profile.max_tokens = None
self.profile.temperature = 0.2
self.profile.max_context_messages = 1000
self.profile.max_tool_iterations = 30
if defaults.max_tokens is not None:
self.profile.max_tokens = max(1, defaults.max_tokens)
if defaults.temperature is not None:
self.profile.temperature = defaults.temperature
if defaults.max_context_messages is not None:
self.profile.max_context_messages = max(1, defaults.max_context_messages)
if defaults.max_tool_iterations is not None:
self.profile.max_tool_iterations = max(0, defaults.max_tool_iterations)
def create_loop(self) -> AgentLoop:
"""创建并缓存当前 service 使用的 AgentLoop。"""
@ -223,7 +249,7 @@ class AgentService:
Scheduled jobs are product-level Tasks, not hidden one-off agent turns.
This entry bypasses the main-agent classifier and forces Task mode so
every trigger produces a TaskRecord, validation, feedback state, and a
every trigger produces a TaskRecord, evidence, acceptance state, and a
run_id that the scheduled-task history can link to.
"""
@ -271,9 +297,9 @@ class AgentService:
result.run_id,
{
"message_type": "scheduled_reply",
"scheduled_job_id": job.id,
"scheduled_run_id": run.scheduled_run_id,
"cron_job_name": job.name,
"scheduled_job_id": cron_job_id,
"scheduled_run_id": scheduled_run_id,
"cron_job_name": cron_job_name,
"mode": "notification",
},
)
@ -394,15 +420,15 @@ class AgentService:
},
)
async def submit_feedback(
async def submit_acceptance(
self,
*,
session_id: str,
run_id: str,
feedback_type: str,
acceptance_type: str,
comment: str | None = None,
) -> dict[str, Any]:
"""Record chat feedback for the internal task linked to a run."""
"""Record user acceptance for the internal task linked to a run."""
loaded = self.create_loop().boot()
task_service = self._require_loaded(loaded, "task_service")
@ -410,32 +436,31 @@ class AgentService:
if task is None or task.session_id != session_id:
raise ValueError(f"No internal task found for run_id={run_id!r}")
normalized = feedback_type.strip().lower()
if normalized not in {"satisfied", "revise", "abandon"}:
raise ValueError("feedback_type must be one of: satisfied, revise, abandon")
normalized = normalize_acceptance_type(acceptance_type)
legacy_feedback_type = "satisfied" if normalized == "accept" else normalized
already_recorded = any(
item.get("run_id") == run_id and item.get("feedback_type") == normalized
item.get("run_id") == run_id and item.get("acceptance_type") == normalized
for item in task.feedback
)
conflicting_feedback = next(
conflicting_acceptance = next(
(
item
for item in task.feedback
if item.get("run_id") == run_id and item.get("feedback_type") != normalized
if item.get("run_id") == run_id and item.get("acceptance_type") != normalized
),
None,
)
if conflicting_feedback is not None:
if conflicting_acceptance is not None:
raise ValueError(
f"Feedback for run_id={run_id!r} was already recorded as "
f"{conflicting_feedback.get('feedback_type')!r}"
f"Acceptance for run_id={run_id!r} was already recorded as "
f"{conflicting_acceptance.get('acceptance_type')!r}"
)
if task.status in {"closed", "abandoned"} and not already_recorded:
raise ValueError(f"Task {task.task_id} is already finalized as {task.status!r}")
updated = task if already_recorded else task_service.add_feedback(
updated = task if already_recorded else task_service.add_acceptance(
task.task_id,
feedback_type=normalized,
acceptance_type=normalized,
comment=comment,
run_id=run_id,
)
@ -446,7 +471,8 @@ class AgentService:
{
"task_id": updated.task_id,
"task_status": updated.status,
"feedback_state": normalized,
"acceptance_state": normalized,
"feedback_state": legacy_feedback_type,
},
)
if not already_recorded:
@ -454,10 +480,11 @@ class AgentService:
session_id,
run_id=run_id,
role="system",
event_type="task_feedback_recorded",
event_type="task_acceptance_recorded",
event_payload={
"task_id": task.task_id,
"feedback_type": normalized,
"acceptance_type": normalized,
"feedback_type": legacy_feedback_type,
"comment": comment,
"task_status": updated.status,
},
@ -466,35 +493,36 @@ class AgentService:
)
generated_candidates = []
validation = ValidationResult.from_dict(updated.validation_result)
if not already_recorded:
run_memory_store = self._require_loaded(loaded, "run_memory_store")
feedback_payload = {
"feedback_type": normalized,
acceptance_payload = {
"acceptance_type": normalized,
"feedback_type": legacy_feedback_type,
"comment": comment or "",
"task_status": updated.status,
"final_accepted_run_id": updated.metadata.get("final_accepted_run_id"),
}
run_memory_store.update_run_record(
run_id,
success=normalized == "satisfied",
feedback=feedback_payload,
success=normalized == "accept",
feedback=acceptance_payload,
)
run_memory_store.update_skill_effects_for_run(
run_id,
success=normalized == "satisfied",
feedback_score=self._feedback_score_for_learning(normalized, validation),
success=normalized == "accept",
feedback_score=self._acceptance_score_for_learning(normalized),
notes=(comment or normalized).strip(),
)
skill_learning_service = self._require_loaded(loaded, "skill_learning_service")
skill_learning_service.rescore_skill_versions()
if already_recorded:
generated_candidates = []
elif normalized == "satisfied" and validation is not None and validation.accepted:
elif normalized == "accept":
generated_candidates = [
item.to_dict()
for item in skill_learning_service.build_learning_candidates_for_task(
updated.task_id,
trigger_run_id=run_id,
final_accepted_run_id=run_id,
)
]
elif normalized == "abandon":
@ -505,7 +533,8 @@ class AgentService:
event_type="task_failure_evidence_recorded",
event_payload={
"task_id": updated.task_id,
"feedback_type": normalized,
"acceptance_type": normalized,
"feedback_type": legacy_feedback_type,
"comment": comment or "",
"task_status": updated.status,
"durable_memory_written": False,
@ -519,10 +548,28 @@ class AgentService:
"run_id": run_id,
"task_id": updated.task_id,
"task_status": updated.status,
"feedback_type": normalized,
"acceptance_type": normalized,
"feedback_type": legacy_feedback_type,
"learning_candidates": generated_candidates,
}
async def submit_feedback(
self,
*,
session_id: str,
run_id: str,
feedback_type: str,
comment: str | None = None,
) -> dict[str, Any]:
"""Backward-compatible wrapper for older clients."""
return await self.submit_acceptance(
session_id=session_id,
run_id=run_id,
acceptance_type=feedback_type,
comment=comment,
)
async def _process_with_main_agent(
self,
message: str,
@ -558,6 +605,8 @@ class AgentService:
if active_task is not None and decision.short_title and not active_task.metadata.get("short_title"):
active_task.metadata["short_title"] = decision.short_title
task_service.store.upsert_task(active_task)
if active_task is not None and (decision.action == "simple_chat" or decision.starts_new_task):
await self._accept_active_task_for_new_topic(active_task)
if active_task is not None and decision.closes_task:
task_service.close_task(active_task.task_id, reason=decision.reason)
return await runner(message, **kwargs)
@ -574,6 +623,7 @@ class AgentService:
session_id=session_id,
description=message,
metadata={
"prompt_locale": normalize_main_agent_prompt_locale(kwargs.get("prompt_locale")),
"router_reason": decision.reason,
**({"short_title": decision.short_title} if decision.short_title else {}),
},
@ -582,7 +632,7 @@ class AgentService:
else active_task
)
if active_task is not None and decision.action == "revise_task" and task.task_id == active_task.task_id:
task = self._record_revision_feedback_for_task(
task = self._record_revision_acceptance_for_task(
loaded,
task=task,
session_id=session_id,
@ -590,7 +640,21 @@ class AgentService:
)
return await self._run_task_mode(message, runner=runner, kwargs=kwargs, task=task)
def _record_revision_feedback_for_task(
async def _accept_active_task_for_new_topic(self, task: TaskRecord) -> None:
"""Accept a completed active Task before routing an unrelated new topic."""
if task.status != "awaiting_acceptance":
return
run_id = next((item for item in reversed(task.run_ids) if item), None)
if not run_id:
return
await self.submit_acceptance(
session_id=task.session_id,
run_id=run_id,
acceptance_type="accept",
)
def _record_revision_acceptance_for_task(
self,
loaded: Any,
*,
@ -598,9 +662,9 @@ class AgentService:
session_id: str,
comment: str,
) -> TaskRecord:
"""Mark the latest feedback-eligible run as revised before continuing a task."""
"""Mark the latest acceptance-eligible run as revised before continuing a task."""
if task.status not in {"awaiting_feedback", "needs_revision"}:
if task.status not in {"awaiting_acceptance", "needs_revision"}:
return task
run_id = next((item for item in reversed(task.run_ids) if item), None)
if not run_id:
@ -608,15 +672,15 @@ class AgentService:
existing = next((item for item in task.feedback if item.get("run_id") == run_id), None)
if existing is not None:
if existing.get("feedback_type") != "revise":
if existing.get("acceptance_type") != "revise":
return task
updated = task
already_recorded = True
else:
task_service = self._require_loaded(loaded, "task_service")
updated = task_service.add_feedback(
updated = task_service.add_acceptance(
task.task_id,
feedback_type="revise",
acceptance_type="revise",
comment=comment,
run_id=run_id,
)
@ -629,6 +693,7 @@ class AgentService:
{
"task_id": updated.task_id,
"task_status": updated.status,
"acceptance_state": "revise",
"feedback_state": "revise",
},
)
@ -639,9 +704,10 @@ class AgentService:
session_id,
run_id=run_id,
role="system",
event_type="task_feedback_recorded",
event_type="task_acceptance_recorded",
event_payload={
"task_id": updated.task_id,
"acceptance_type": "revise",
"feedback_type": "revise",
"comment": comment,
"task_status": updated.status,
@ -650,12 +716,12 @@ class AgentService:
content=comment,
context_visible=False,
)
validation = ValidationResult.from_dict(updated.validation_result)
run_memory_store = self._require_loaded(loaded, "run_memory_store")
run_memory_store.update_run_record(
run_id,
success=False,
feedback={
"acceptance_type": "revise",
"feedback_type": "revise",
"comment": comment,
"task_status": updated.status,
@ -664,7 +730,7 @@ class AgentService:
run_memory_store.update_skill_effects_for_run(
run_id,
success=False,
feedback_score=self._feedback_score_for_learning("revise", validation),
feedback_score=self._acceptance_score_for_learning("revise"),
notes=comment.strip() or "revise",
)
skill_learning_service = self._require_loaded(loaded, "skill_learning_service")
@ -681,181 +747,190 @@ class AgentService:
) -> AgentRunResult:
loaded = self.create_loop().boot()
task_service = self._require_loaded(loaded, "task_service")
validation_service = self._require_loaded(loaded, "validation_service")
task_execution_planner = self._require_loaded(loaded, "task_execution_planner")
session_manager = self._require_loaded(loaded, "session_manager")
run_memory_store = self._require_loaded(loaded, "run_memory_store")
last_result: AgentRunResult | None = None
latest_validation: ValidationResult | None = None
base_execution_context = kwargs.get("execution_context")
prompt_locale = kwargs.get("prompt_locale") or task.metadata.get("prompt_locale")
output_language_instruction = self._output_language_instruction(prompt_locale)
provider_bundle = kwargs.get("provider_bundle") or self._make_provider_bundle_for_task(loaded, kwargs)
kwargs = dict(kwargs)
team_provider_bundle_factory = kwargs.pop("team_provider_bundle_factory", None)
kwargs["provider_bundle"] = provider_bundle
for attempt_index in (1, 2):
task_service.start_run(task.task_id, user_message=message, attempt_index=attempt_index)
plan = await task_execution_planner.plan(
attempt_index = int(task.metadata.get("latest_attempt_index") or 0) + 1
task_service.start_run(task.task_id, user_message=message, attempt_index=attempt_index)
plan = await task_execution_planner.plan(
task=task,
user_message=message,
attempt_index=attempt_index,
provider_bundle=provider_bundle,
)
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_execution_planned",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
**plan.to_event_payload(),
},
)
team_summaries: list[str] = []
team_execution_context = ""
team_result: TeamRunResult | None = None
if plan.is_team:
team_result, team_error = await self._run_team_for_task(
plan,
task=task,
user_message=message,
attempt_index=attempt_index,
latest_validation=latest_validation,
provider_bundle=provider_bundle,
parent_session_id=kwargs["session_id"],
provider_bundle_factory=team_provider_bundle_factory
or self._build_team_provider_bundle_factory(loaded, kwargs),
)
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_execution_planned",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
**plan.to_event_payload(),
},
)
team_summaries: list[str] = []
team_execution_context = ""
if plan.is_team:
team_result, team_error = await self._run_team_for_task(
plan,
task=task,
parent_session_id=kwargs["session_id"],
provider_bundle_factory=team_provider_bundle_factory
or self._build_team_provider_bundle_factory(loaded, kwargs),
if team_result is not None:
team_summaries = [self._team_summary_for_validation(team_result)]
team_packet = TaskEvidencePacket(
task_id=task.task_id,
attempt_index=attempt_index,
main_run=None,
team_runs=self._team_run_evidence(team_result),
team_node_results=list(team_result.node_results),
final_output="",
)
team_execution_context = self._join_context(
self._team_execution_context(plan, team_result),
"Rendered team evidence:\n" + render_task_evidence(team_packet),
)
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_team_run_completed" if team_result.success else "task_team_run_failed",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"plan_mode": plan.mode,
"strategy": plan.graph.strategy if plan.graph else None,
"node_ids": [node.node_id for node in plan.graph.nodes] if plan.graph else [],
"team_run_ids": team_result.run_ids,
"team_success": team_result.success,
"node_results": self._team_node_results_for_event(plan, team_result),
"reason": plan.reason,
"error": None if team_result.success else "one or more team nodes failed",
},
)
else:
team_summaries = [f"Team execution failed: {team_error}"]
team_execution_context = self._failed_team_execution_context(plan, team_error or "unknown error")
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_team_run_failed",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"plan_mode": plan.mode,
"strategy": plan.graph.strategy if plan.graph else None,
"node_ids": [node.node_id for node in plan.graph.nodes] if plan.graph else [],
"team_run_ids": [],
"team_success": False,
"reason": plan.reason,
"error": team_error,
},
)
if team_result is not None:
team_summaries = [self._team_summary_for_validation(team_result)]
team_execution_context = self._team_execution_context(plan, team_result)
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_team_run_completed" if team_result.success else "task_team_run_failed",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"plan_mode": plan.mode,
"strategy": plan.graph.strategy if plan.graph else None,
"node_ids": [node.node_id for node in plan.graph.nodes] if plan.graph else [],
"team_run_ids": team_result.run_ids,
"team_success": team_result.success,
"node_results": self._team_node_results_for_event(plan, team_result),
"reason": plan.reason,
"error": None if team_result.success else "one or more team nodes failed",
},
)
else:
team_summaries = [f"Team execution failed: {team_error}"]
team_execution_context = self._failed_team_execution_context(plan, team_error or "unknown error")
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_team_run_failed",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"plan_mode": plan.mode,
"strategy": plan.graph.strategy if plan.graph else None,
"node_ids": [node.node_id for node in plan.graph.nodes] if plan.graph else [],
"team_run_ids": [],
"team_success": False,
"reason": plan.reason,
"error": team_error,
},
)
attempt_kwargs = dict(kwargs)
attempt_kwargs.update(
{
"task_id": task.task_id,
"task_mode": True,
"attempt_index": attempt_index,
"allow_candidate_generation": False,
}
)
if attempt_index == 2 and latest_validation is not None:
revision_context = latest_validation.recommended_revision_prompt.strip()
if revision_context:
attempt_kwargs["execution_context"] = self._join_context(
base_execution_context,
f"Task validation revision request:\n{revision_context}",
team_execution_context,
)
elif team_execution_context:
attempt_kwargs["execution_context"] = self._join_context(base_execution_context, team_execution_context)
attempt_kwargs["skill_selection_context"] = self._build_skill_selection_context(
task=task,
user_message=message,
attempt_index=attempt_index,
latest_validation=latest_validation,
plan=plan,
team_summaries=team_summaries,
)
attempt_kwargs = dict(kwargs)
attempt_kwargs.update(
{
"task_id": task.task_id,
"task_mode": True,
"attempt_index": attempt_index,
"allow_candidate_generation": False,
}
)
attempt_kwargs["execution_context"] = self._join_context(
base_execution_context,
output_language_instruction,
team_execution_context,
)
if plan.is_team and team_execution_context:
attempt_kwargs["include_tools"] = False
attempt_kwargs["max_tool_iterations"] = 0
attempt_kwargs["skill_selection_context"] = self._build_skill_selection_context(
task=task,
user_message=message,
attempt_index=attempt_index,
plan=plan,
team_summaries=team_summaries,
)
result = await runner(message, **attempt_kwargs)
last_result = result
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_synthesis_completed",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"main_run_id": result.run_id,
"plan_mode": plan.mode,
"strategy": plan.graph.strategy if plan.graph else None,
},
)
task = task_service.append_run(
task.task_id,
result.run_id,
skill_names=self._skill_names_for_run(loaded, result.run_id),
)
validation = await validation_service.validate_task_result(
task=task,
user_message=message,
final_output=result.output_text,
transcript_excerpt=self._run_excerpt(session_manager, result.session_id, result.run_id),
tool_summaries=self._tool_summaries(session_manager, result.session_id, result.run_id),
team_summaries=team_summaries,
provider_bundle=provider_bundle,
)
latest_validation = validation
task = task_service.record_validation(task.task_id, result.run_id, validation)
run_memory_store.update_run_record(result.run_id, validation_result=validation.to_dict())
session_manager.update_latest_assistant_event_payload(
result.session_id,
result.run_id,
{
"task_id": task.task_id,
"task_status": task.status,
"validation_status": "passed" if validation.accepted else "failed",
},
)
session_manager.append_message(
result.session_id,
run_id=result.run_id,
role="system",
event_type="task_validation_snapshotted",
event_payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"validation_result": validation.to_dict(),
"retry_scheduled": not validation.accepted and attempt_index == 1,
},
content=validation.recommended_revision_prompt or None,
context_visible=False,
)
if not validation.accepted and attempt_index == 1:
session_manager.set_run_context_visible(result.session_id, result.run_id, False)
result.task_id = task.task_id
result.task_status = task.status
result.validation_result = validation.to_dict()
if validation.accepted or attempt_index == 2:
return result
if last_result is None: # pragma: no cover - defensive
raise RuntimeError("Task mode did not produce a run result")
return last_result
result = await runner(message, **attempt_kwargs)
self._append_task_observation(
session_manager,
task.session_id,
event_type="task_synthesis_completed",
payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"main_run_id": result.run_id,
"plan_mode": plan.mode,
"strategy": plan.graph.strategy if plan.graph else None,
},
)
task = task_service.append_run(
task.task_id,
result.run_id,
skill_names=self._skill_names_for_run(loaded, result.run_id),
)
evidence_packet = self._build_task_evidence_packet(
session_manager=session_manager,
task=task,
attempt_index=attempt_index,
result=result,
team_result=team_result,
)
evidence_text = render_task_evidence(evidence_packet)
evidence_debug = {
"evidence_run_ids": [
item.run_id for item in [evidence_packet.main_run, *evidence_packet.team_runs] if item is not None
],
"evidence_session_ids": [
item.session_id
for item in [evidence_packet.main_run, *evidence_packet.team_runs]
if item is not None
],
"tool_result_count": sum(
len(item.tool_results)
for item in [evidence_packet.main_run, *evidence_packet.team_runs]
if item is not None
),
"evidence_length": len(evidence_text),
}
session_manager.update_latest_assistant_event_payload(
result.session_id,
result.run_id,
{
"task_id": task.task_id,
"task_status": task.status,
"evidence_status": "recorded",
},
)
session_manager.append_message(
result.session_id,
run_id=result.run_id,
role="system",
event_type="task_evidence_recorded",
event_payload={
"task_id": task.task_id,
"attempt_index": attempt_index,
"evidence_debug": evidence_debug,
},
content=None,
context_visible=False,
)
result.task_id = task.task_id
result.task_status = task.status
result.validation_result = None
return result
async def _run_team_for_task(
self,
@ -911,6 +986,24 @@ class AgentService:
"short_title": decision.short_title,
}
@staticmethod
def _output_language_instruction(prompt_locale: str | None) -> str:
locale = normalize_main_agent_prompt_locale(prompt_locale)
if locale == "en":
return (
"Output language: English. Use English for user-facing task titles, summaries, plans, "
"and final answers unless the user explicitly requests another language."
)
if locale == "zh-Hant":
return (
"輸出語言:繁體中文。除非使用者明確要求其他語言,所有面向使用者的任務標題、摘要、"
"計劃與最終回答都使用繁體中文。"
)
return (
"输出语言:简体中文。除非用户明确要求其他语言,所有面向用户的任务标题、摘要、"
"计划与最终回答都使用简体中文。"
)
@staticmethod
def _skill_names_for_run(loaded: Any, run_id: str) -> list[str]:
store = getattr(loaded, "run_memory_store", None)
@ -922,12 +1015,10 @@ class AgentService:
return []
@staticmethod
def _feedback_score_for_learning(feedback_type: str, validation: ValidationResult | None) -> float:
if feedback_type == "satisfied":
if validation is not None:
return max(0.0, min(1.0, float(validation.score)))
def _acceptance_score_for_learning(acceptance_type: str) -> float:
if acceptance_type == "accept":
return 1.0
if feedback_type == "revise":
if acceptance_type == "revise":
return 0.5
return 0.0
@ -937,12 +1028,11 @@ class AgentService:
task: TaskRecord,
user_message: str,
attempt_index: int,
latest_validation: ValidationResult | None = None,
plan: TaskExecutionPlan | None = None,
team_summaries: list[str] | None = None,
) -> str:
phase = f"attempt_{attempt_index}"
if latest_validation is not None:
if task.feedback and task.feedback[-1].get("acceptance_type") == "revise":
phase = f"revision_attempt_{attempt_index}"
elif plan is not None and plan.is_team:
phase = f"team_synthesis_attempt_{attempt_index}"
@ -963,24 +1053,14 @@ class AgentService:
)
else:
sections.append("Previously activated skills:\nNone")
if latest_validation is not None:
validation_lines = [
f"accepted: {latest_validation.accepted}",
f"score: {latest_validation.score}",
]
if latest_validation.issues:
validation_lines.append("issues:\n" + "\n".join(f"- {item}" for item in latest_validation.issues))
if latest_validation.missing_requirements:
validation_lines.append(
"missing requirements:\n"
+ "\n".join(f"- {item}" for item in latest_validation.missing_requirements)
)
if latest_validation.recommended_revision_prompt:
validation_lines.append(
"recommended revision:\n"
+ latest_validation.recommended_revision_prompt
)
sections.append("Validation feedback:\n" + "\n".join(validation_lines))
if task.feedback:
history_lines = []
for item in task.feedback[-5:]:
kind = item.get("acceptance_type") or item.get("feedback_type")
comment = item.get("comment") or ""
run_id = item.get("run_id") or ""
history_lines.append(f"- {kind} run={run_id}: {comment}".strip())
sections.append("Task acceptance history:\n" + "\n".join(history_lines))
if plan is not None:
plan_lines = [
f"mode: {plan.mode}",
@ -1083,6 +1163,36 @@ class AgentService:
payloads.append(payload)
return payloads
@staticmethod
def _team_run_evidence(result: TeamRunResult | None) -> list[RunEvidence]:
if result is None:
return []
return [node.evidence for node in result.node_results if node.evidence is not None]
def _build_task_evidence_packet(
self,
*,
session_manager: Any,
task: TaskRecord,
attempt_index: int,
result: AgentRunResult,
team_result: TeamRunResult | None,
) -> TaskEvidencePacket:
main_run = EvidenceBuilder(session_manager).build_run_evidence(
result.session_id,
result.run_id,
result.output_text,
result.finish_reason,
)
return TaskEvidencePacket(
task_id=task.task_id,
attempt_index=attempt_index,
main_run=main_run,
team_runs=self._team_run_evidence(team_result),
team_node_results=list(team_result.node_results) if team_result is not None else [],
final_output=result.output_text,
)
@staticmethod
def _team_execution_context(plan: TaskExecutionPlan, result: TeamRunResult) -> str:
node_lines = [
@ -1168,17 +1278,19 @@ class AgentService:
async def handle_inbound_message(self, inbound: InboundMessage) -> OutboundMessage:
"""把 bus inbound 映射成标准 runtime 调用,并返回结构化 outbound。"""
channel_identity = inbound.channel_identity
try:
result = await self.submit_direct(
inbound.content,
session_id=inbound.session_id,
source=f"gateway:{inbound.channel}",
user_id=inbound.user_id,
user_id=inbound.user_id or (channel_identity.user_id if channel_identity else None),
title=inbound.title,
execution_context=inbound.execution_context,
model=inbound.model,
provider_name=inbound.provider_name,
embedding_model=inbound.embedding_model,
channel_identity=channel_identity,
)
except Exception as exc:
return self.build_outbound_error(
@ -1214,12 +1326,15 @@ class AgentService:
finish_reason=result.finish_reason,
provider_name=result.provider_name,
model=result.model,
content_type=inbound.content_type,
channel_identity=inbound.channel_identity,
usage=dict(result.usage),
metadata={
"inbound_metadata": dict(inbound.metadata),
"task_id": getattr(result, "task_id", None),
"task_status": getattr(result, "task_status", None),
"validation_result": getattr(result, "validation_result", None),
"evidence_status": "recorded" if getattr(result, "task_id", None) else None,
"validation_result": None,
},
)
@ -1238,6 +1353,8 @@ class AgentService:
session_id=inbound.session_id,
content=detail,
finish_reason=finish_reason,
content_type=inbound.content_type,
channel_identity=inbound.channel_identity,
metadata={"error": detail, "inbound_metadata": dict(inbound.metadata)},
)

View File

@ -50,10 +50,11 @@ class SessionProcessProjector:
for record in records:
payload = dict(record.event_payload or {})
task_id = payload.get("task_id")
run_record_for_event = run_records.get(str(record.run_id)) if record.run_id else None
task_id = payload.get("task_id") or getattr(run_record_for_event, "task_id", None)
if not task_id:
continue
attempt_index = int(payload.get("attempt_index") or 1)
attempt_index = int(payload.get("attempt_index") or getattr(run_record_for_event, "attempt_index", None) or 1)
root_run_id = f"task:{task_id}:attempt:{attempt_index}"
created_at = _timestamp(record.timestamp)
root = runs.setdefault(
@ -73,15 +74,70 @@ class SessionProcessProjector:
},
)
if record.event_type == "task_execution_planned":
if record.event_type == "assistant_message_added" and record.tool_calls:
run_id = record.run_id or root_run_id
parent_run_id = root_run_id if run_id != root_run_id else None
for index, tool_call in enumerate(record.tool_calls):
if not isinstance(tool_call, dict):
continue
tool_name = _tool_call_name(tool_call)
add_event(
event_id=f"{_event_id(record, 'tool-call')}:{index}",
run_id=run_id,
parent_run_id=parent_run_id,
kind="tool_call_started",
actor_type="tool",
actor_id=tool_name,
actor_name=tool_name,
text=f"Calling tool: {tool_name}.",
created_at=created_at,
status="running",
metadata={
"task_id": task_id,
"attempt_index": attempt_index,
"timeline_type": "tool_call",
"tool_name": tool_name,
"tool_call_id": tool_call.get("id"),
"arguments": _tool_call_arguments(tool_call),
},
)
elif record.event_type == "tool_result_recorded":
run_id = record.run_id or root_run_id
parent_run_id = root_run_id if run_id != root_run_id else None
tool_name = str(record.tool_name or payload.get("tool_name") or "tool")
add_event(
event_id=_event_id(record, "tool-result"),
run_id=run_id,
parent_run_id=parent_run_id,
kind="tool_call_finished",
actor_type="tool",
actor_id=tool_name,
actor_name=tool_name,
text=_truncate(str(record.content or payload.get("error") or "")),
created_at=created_at,
status="done" if payload.get("success", True) else "error",
metadata={
**dict(payload),
"task_id": task_id,
"attempt_index": attempt_index,
"timeline_type": "tool_result",
"tool_name": tool_name,
"tool_call_id": record.tool_call_id,
"result_summary": _truncate(str(record.content or payload.get("error") or "")),
},
)
elif record.event_type == "task_execution_planned":
plan_mode = payload.get("plan_mode") or "single"
strategy = payload.get("strategy") or "single"
node_ids = payload.get("node_ids") or []
root["title"] = f"{payload.get('plan_mode', 'single')} plan: {strategy}"
root["title"] = f"{plan_mode} plan: {strategy}"
root["summary"] = payload.get("reason") or ""
root["metadata"] = {
**root.get("metadata", {}),
"plan_mode": payload.get("plan_mode"),
"strategy": payload.get("strategy"),
"plan_mode": plan_mode,
"strategy": strategy,
"node_ids": node_ids,
"skill_queries": payload.get("skill_queries") or [],
"selected_skill_names": payload.get("selected_skill_names") or [],
@ -92,36 +148,65 @@ class SessionProcessProjector:
add_event(
event_id=_event_id(record, "planned"),
run_id=root_run_id,
kind="run_started",
kind="task_planned",
actor_type="system",
actor_id="task",
actor_name="Task Planner",
text=f"Planned {payload.get('plan_mode')} execution via {strategy}. {payload.get('reason') or ''}".strip(),
text=f"Beaver planned {plan_mode} execution via {strategy}. {payload.get('reason') or ''}".strip(),
created_at=created_at,
status="running",
metadata=root["metadata"],
metadata={
**root["metadata"],
"timeline_type": "plan",
"user_summary": f"Beaver will use {plan_mode} execution for this task.",
},
)
selected_skill_names = [
str(item)
for item in payload.get("selected_skill_names") or []
if str(item).strip()
]
if selected_skill_names:
add_event(
event_id=_event_id(record, "skills"),
run_id=root_run_id,
kind="skill_selected",
actor_type="system",
actor_id="skill-selector",
actor_name="Skill Selector",
text=f"Selected skill guidance: {', '.join(selected_skill_names)}.",
created_at=created_at,
status="done",
metadata={
"task_id": task_id,
"attempt_index": attempt_index,
"timeline_type": "skill",
"skill_names": selected_skill_names,
"reason": payload.get("reason") or "Selected from task planning context.",
},
)
elif record.event_type in {"task_team_run_completed", "task_team_run_failed"}:
team_success = bool(payload.get("team_success"))
root["status"] = "running"
team_run_ids = payload.get("team_run_ids") or []
root["metadata"] = {
**root.get("metadata", {}),
"team_success": team_success,
"team_run_ids": payload.get("team_run_ids") or [],
"team_run_ids": team_run_ids,
"team_error": payload.get("error"),
}
add_event(
event_id=_event_id(record, "team"),
run_id=root_run_id,
kind="run_status",
kind="agent_team_created",
actor_type="system",
actor_id="team",
actor_name="Task Team",
text=payload.get("error") or ("Team completed" if team_success else "Team completed with failed nodes"),
created_at=created_at,
status="done" if team_success else "error",
metadata=dict(payload),
metadata={**dict(payload), "timeline_type": "agent_team", "team_run_ids": team_run_ids},
)
node_results = payload.get("node_results") or []
for item in node_results:
@ -192,20 +277,26 @@ class SessionProcessProjector:
event_id=f"{_event_id(record, 'node')}:{item.get('node_id')}",
run_id=str(node_run_id),
parent_run_id=root_run_id,
kind="run_finished",
kind="agent_finished",
actor_type="agent",
actor_id=str(item.get("node_id") or "sub-agent"),
actor_name=str(item.get("node_id") or "Sub-agent"),
text=_truncate(str(item.get("output_text") or item.get("error") or "")),
created_at=created_at,
status=status,
metadata=dict(item),
metadata={
**dict(item),
"task_id": task_id,
"attempt_index": attempt_index,
"timeline_type": "agent_progress",
},
)
elif record.event_type == "task_synthesis_completed":
main_run_id = str(payload.get("main_run_id") or "")
if main_run_id:
run_record = run_records.get(main_run_id)
activated_skill_names = _activated_skill_names(run_record)
runs[main_run_id] = {
"run_id": main_run_id,
"parent_run_id": root_run_id,
@ -219,8 +310,32 @@ class SessionProcessProjector:
"started_at": run_record.started_at if run_record is not None else created_at,
"finished_at": run_record.ended_at if run_record is not None else created_at,
"summary": _truncate(run_record.task_text if run_record is not None else ""),
"metadata": {"task_id": task_id, "attempt_index": attempt_index},
"metadata": {
"task_id": task_id,
"attempt_index": attempt_index,
"skill_names": activated_skill_names,
},
}
if activated_skill_names:
add_event(
event_id=_event_id(record, "synthesis-skills"),
run_id=main_run_id,
parent_run_id=root_run_id,
kind="skill_selected",
actor_type="system",
actor_id="skill-selector",
actor_name="Skill Selector",
text=f"Selected skill guidance: {', '.join(activated_skill_names)}.",
created_at=created_at,
status="done",
metadata={
"task_id": task_id,
"attempt_index": attempt_index,
"timeline_type": "skill",
"skill_names": activated_skill_names,
"activation_reasons": _activated_skill_reasons(run_record),
},
)
add_event(
event_id=_event_id(record, "synthesis"),
run_id=main_run_id,
@ -235,27 +350,46 @@ class SessionProcessProjector:
metadata=dict(payload),
)
elif record.event_type == "task_validation_snapshotted":
validation = payload.get("validation_result") if isinstance(payload.get("validation_result"), dict) else {}
accepted = bool(validation.get("accepted"))
root["status"] = "done" if accepted or attempt_index == 2 else "waiting"
root["finished_at"] = created_at if root["status"] == "done" else None
elif record.event_type == "task_evidence_recorded":
root["status"] = "waiting"
root["finished_at"] = None
add_event(
event_id=_event_id(record, "validation"),
event_id=_event_id(record, "evidence"),
run_id=record.run_id or root_run_id,
parent_run_id=root_run_id if record.run_id else None,
kind="run_status",
kind="task_result_ready",
actor_type="system",
actor_id="validator",
actor_name="Validator",
text=(
f"Validation {'passed' if accepted else 'failed'} "
f"(score={validation.get('score')})."
+ (" Retry scheduled." if payload.get("retry_scheduled") else "")
),
actor_id="evidence-recorder",
actor_name="Evidence",
text="The task result is ready for user acceptance.",
created_at=created_at,
status="done" if accepted else "error",
metadata=dict(payload),
status="done",
metadata={**dict(payload), "timeline_type": "result"},
)
elif record.event_type == "task_acceptance_recorded":
acceptance_type = str(payload.get("acceptance_type") or payload.get("feedback_type") or "")
if acceptance_type == "accept":
root["status"] = "done"
root["finished_at"] = created_at
elif acceptance_type == "abandon":
root["status"] = "cancelled"
root["finished_at"] = created_at
else:
root["status"] = "waiting"
root["finished_at"] = None
add_event(
event_id=_event_id(record, "acceptance"),
run_id=record.run_id or root_run_id,
parent_run_id=root_run_id if record.run_id else None,
kind="task_acceptance_recorded",
actor_type="user",
actor_id="user-acceptance",
actor_name="User Acceptance",
text=f"User acceptance recorded: {acceptance_type or 'unknown'}.",
created_at=created_at,
status="done",
metadata={**dict(payload), "timeline_type": "acceptance"},
)
return {
@ -281,3 +415,49 @@ def _truncate(text: str, limit: int = 800) -> str:
if len(cleaned) <= limit:
return cleaned
return cleaned[: limit - 1] + "..."
def _activated_skill_names(run_record: Any | None) -> list[str]:
if run_record is None:
return []
names = []
for receipt in getattr(run_record, "activated_skills", []) or []:
skill_name = str(getattr(receipt, "skill_name", "") or "").strip()
if skill_name:
names.append(skill_name)
return list(dict.fromkeys(names))
def _activated_skill_reasons(run_record: Any | None) -> list[str]:
if run_record is None:
return []
reasons = []
for receipt in getattr(run_record, "activated_skills", []) or []:
reason = str(getattr(receipt, "activation_reason", "") or "").strip()
if reason:
reasons.append(reason)
return reasons
def _tool_call_name(tool_call: dict[str, Any]) -> str:
function_payload = tool_call.get("function")
if isinstance(function_payload, dict):
name = function_payload.get("name")
if name:
return str(name)
for key in ("name", "tool_name"):
value = tool_call.get(key)
if value:
return str(value)
return "tool"
def _tool_call_arguments(tool_call: dict[str, Any]) -> Any:
function_payload = tool_call.get("function")
if isinstance(function_payload, dict) and "arguments" in function_payload:
return function_payload.get("arguments")
if "arguments" in tool_call:
return tool_call.get("arguments")
if "args" in tool_call:
return tool_call.get("args")
return None

View File

@ -16,10 +16,10 @@ if TYPE_CHECKING:
class TeamService:
"""Internal service for Beaver-native multi-agent execution."""
def __init__(self, loop: AgentLoop) -> None:
def __init__(self, loop: AgentLoop, *, max_parallel_team_nodes: int = 3) -> None:
self.loop = loop
self.runner = LocalAgentRunner(loop)
self.scheduler = TeamGraphScheduler(self.runner)
self.scheduler = TeamGraphScheduler(self.runner, max_parallel_team_nodes=max_parallel_team_nodes)
async def run_team(
self,

View File

@ -32,16 +32,23 @@ When there is an active task, do not force every new user message into that task
- Choose `revise_task` when the user asks to change, correct, refine, expand, reformat, or redo the latest active task result.
- Choose `continue_task` for neutral follow-up questions or additional next steps that still belong to the active task.
- Choose `new_task` when the user asks for clearly unrelated work.
- Choose `simple_chat` for unrelated lightweight conversation. This starts a new topic and the previous task will be accepted automatically.
- Choose `new_task` when the user asks for clearly unrelated work that needs Task capabilities. This starts a new topic and the previous task will be accepted automatically.
- Choose `close_task` when the user says the task is satisfactory or finished, such as "可以了", "就这样", or "that's good".
- Choose `abandon_task` when the user says to stop, cancel, or no longer do the active task.
Do not classify unrelated lightweight conversation as `revise_task` merely because
the active task is awaiting acceptance. A revision must ask to change or correct
the active task result.
Examples with an active weather task:
- "再详细一点" -> `revise_task`
- "加上明后天穿衣建议" -> `revise_task`
- "顺便查一下深圳" -> `continue_task`
- "帮我写一个采购合同" -> `new_task`
- "吃饭没" -> `simple_chat`
- "我在冰岛" -> `simple_chat`
- "可以了" -> `close_task`
- "不用了" -> `abandon_task`

View File

@ -1,5 +1,6 @@
"""Skill learning loop helpers."""
from .case_selection import select_replay_cases
from .evidence import EvidencePacket, EvidenceSelector
from .eval import SkillDraftEvaluator
from .missing_skill import (
@ -9,11 +10,15 @@ from .missing_skill import (
MissingSkillSynthesizer,
)
from .pipeline import SkillLearningPipelineService
from .preservation import check_preservation
from .replay import ReplayArmRequest, ReplayRunner, ReplayToolExecutor, ReplayToolPolicy, classify_tool_mode
from .service import RunReceiptContext, SkillLearningService
from .surrogate import SurrogateToolEvaluator
from .synthesizer import SkillDraftSynthesizer
from .worker import SkillLearningWorker, SkillLearningWorkerConfig, SkillLearningWorkerResult
__all__ = [
"select_replay_cases",
"EvidencePacket",
"EvidenceSelector",
"SkillDraftEvaluator",
@ -23,6 +28,13 @@ __all__ = [
"MissingSkillSynthesizer",
"RunReceiptContext",
"SkillLearningPipelineService",
"check_preservation",
"ReplayToolExecutor",
"ReplayToolPolicy",
"ReplayArmRequest",
"ReplayRunner",
"classify_tool_mode",
"SurrogateToolEvaluator",
"SkillDraftSynthesizer",
"SkillLearningService",
"SkillLearningWorker",

View File

@ -0,0 +1,109 @@
"""Historical replay case selection for skill draft evaluation."""
from __future__ import annotations
from typing import Any
from beaver.memory.runs import RunRecord
from beaver.memory.skills import SkillLearningCandidate
MAX_REPLAY_CASES = 10
def select_replay_cases(candidate: SkillLearningCandidate, runs: list[RunRecord]) -> list[dict[str, Any]]:
accepted = [record for record in runs if _is_accepted(record)]
if candidate.kind == "revise_skill":
selected = _select_revise(candidate, accepted)
elif candidate.kind == "merge_skills":
selected = _select_merge(candidate, accepted)
else:
selected = _select_new(candidate, accepted)
return [_case_payload(candidate, record) for record in selected[:MAX_REPLAY_CASES]]
def _select_revise(candidate: SkillLearningCandidate, runs: list[RunRecord]) -> list[RunRecord]:
target = candidate.related_skill_names[0] if candidate.related_skill_names else ""
version = str(candidate.evidence.get("skill_version") or "")
matches = [
record
for record in runs
if any(
receipt.skill_name == target and (not version or receipt.skill_version == version)
for receipt in record.activated_skills
)
]
return _recent_diverse(matches)
def _select_merge(candidate: SkillLearningCandidate, runs: list[RunRecord]) -> list[RunRecord]:
targets = set(candidate.related_skill_names)
matches = [
record
for record in runs
if targets and targets.issubset({receipt.skill_name for receipt in record.activated_skills})
]
return _recent_diverse(matches)
def _select_new(candidate: SkillLearningCandidate, runs: list[RunRecord]) -> list[RunRecord]:
source_ids = set(candidate.source_run_ids)
if source_ids:
matches = [record for record in runs if record.run_id in source_ids]
else:
theme = str(candidate.evidence.get("theme") or "").lower().strip()
matches = [record for record in runs if theme and theme in record.task_text.lower()]
return _recent_diverse(matches)
def _case_payload(candidate: SkillLearningCandidate, record: RunRecord) -> dict[str, Any]:
baseline_skill_names = []
if candidate.kind == "revise_skill":
baseline_skill_names = list(candidate.related_skill_names[:1])
elif candidate.kind == "merge_skills":
baseline_skill_names = list(candidate.related_skill_names)
return {
"run_id": record.run_id,
"task_id": record.task_id,
"session_id": record.session_id,
"task_text": record.task_text,
"baseline_skill_names": baseline_skill_names,
"candidate_skill_name": candidate.draft_skill_name,
"accepted_score": _score(record),
}
def _recent_diverse(runs: list[RunRecord]) -> list[RunRecord]:
sorted_runs = sorted(runs, key=lambda item: (item.started_at, item.run_id), reverse=True)
result: list[RunRecord] = []
seen_tasks: set[str] = set()
for record in sorted_runs:
task_key = record.task_id or record.task_text
if task_key in seen_tasks and len(sorted_runs) > MAX_REPLAY_CASES:
continue
seen_tasks.add(task_key)
result.append(record)
if len(result) >= MAX_REPLAY_CASES:
break
if len(result) < min(len(sorted_runs), MAX_REPLAY_CASES):
seen_run_ids = {record.run_id for record in result}
result.extend(record for record in sorted_runs if record.run_id not in seen_run_ids)
return result[:MAX_REPLAY_CASES]
def _is_accepted(record: RunRecord) -> bool:
feedback = record.feedback or {}
acceptance = feedback.get("acceptance_type")
if acceptance is None and feedback.get("feedback_type") == "satisfied":
acceptance = "accept"
return bool(record.success) and acceptance == "accept"
def _score(record: RunRecord) -> float:
validation = record.validation_result or {}
value = validation.get("score") if isinstance(validation, dict) else None
if value is not None:
try:
return max(0.0, min(1.0, float(value)))
except (TypeError, ValueError):
pass
return 0.8 if record.success else 0.4

View File

@ -4,17 +4,28 @@ from __future__ import annotations
from uuid import uuid4
from beaver.engine.context import SkillContext
from beaver.engine.providers import ProviderBundle
from beaver.memory.runs import RunMemoryStore
from beaver.memory.skills import SkillDraftEvalReport, SkillLearningCandidate
from beaver.skills.learning.case_selection import select_replay_cases
from beaver.skills.learning.preservation import check_preservation
from beaver.skills.learning.replay import ReplayArmRequest, ReplayRunner
from beaver.skills.learning.surrogate import SurrogateToolEvaluator
from beaver.skills.specs import SkillDraft
class SkillDraftEvaluator:
"""Builds a bounded eval report without writing user-visible sessions."""
def __init__(self, run_store: RunMemoryStore) -> None:
def __init__(
self,
run_store: RunMemoryStore,
*,
surrogate_evaluator: SurrogateToolEvaluator | None = None,
) -> None:
self.run_store = run_store
self.surrogate_evaluator = surrogate_evaluator or SurrogateToolEvaluator()
async def evaluate(
self,
@ -22,11 +33,30 @@ class SkillDraftEvaluator:
candidate: SkillLearningCandidate,
draft: SkillDraft,
provider_bundle: ProviderBundle | None,
replay_runner: ReplayRunner | None = None,
) -> SkillDraftEvalReport:
if provider_bundle is None or provider_bundle.main_provider is None:
return self._skipped(candidate, draft)
runs_by_id = {record.run_id: record for record in self.run_store.list_runs()}
runs = self.run_store.list_runs()
replay_cases = select_replay_cases(candidate, runs)
if replay_runner is not None and replay_cases:
return await self._evaluate_replay(
candidate=candidate,
draft=draft,
replay_cases=replay_cases,
provider_bundle=provider_bundle,
replay_runner=replay_runner,
)
return self._evaluate_heuristic(candidate, draft, runs)
def _evaluate_heuristic(
self,
candidate: SkillLearningCandidate,
draft: SkillDraft,
runs: list,
) -> SkillDraftEvalReport:
runs_by_id = {record.run_id: record for record in runs}
cases: list[dict] = []
for run_id in candidate.source_run_ids[:8]:
record = runs_by_id.get(run_id)
@ -78,6 +108,78 @@ class SkillDraftEvaluator:
created_at=_utc_now(),
)
async def _evaluate_replay(
self,
*,
candidate: SkillLearningCandidate,
draft: SkillDraft,
replay_cases: list[dict],
provider_bundle: ProviderBundle,
replay_runner: ReplayRunner,
) -> SkillDraftEvalReport:
case_reports: list[dict] = []
legacy_cases: list[dict] = []
for case in replay_cases:
baseline = await replay_runner.run_arm(
ReplayArmRequest(
case_id=f"{case['run_id']}:baseline",
arm="baseline",
task_text=str(case["task_text"]),
pinned_skill_names=list(case.get("baseline_skill_names") or []),
pinned_skill_contexts=[],
provider_bundle=provider_bundle,
model_settings={"max_tool_iterations": 4, "temperature": 0.0},
)
)
candidate_arm = await replay_runner.run_arm(
ReplayArmRequest(
case_id=f"{case['run_id']}:candidate",
arm="candidate",
task_text=str(case["task_text"]),
pinned_skill_names=[],
pinned_skill_contexts=[_draft_skill_context(draft)],
provider_bundle=provider_bundle,
model_settings={"max_tool_iterations": 4, "temperature": 0.0},
)
)
surrogate = await self.surrogate_evaluator.evaluate(
task_text=str(case["task_text"]),
baseline=baseline,
candidate=candidate_arm,
)
baseline_score = surrogate["baseline_score"]
candidate_score = surrogate["candidate_score"]
case_report = {
"run_id": case["run_id"],
"task_id": case.get("task_id"),
"session_id": case.get("session_id"),
"baseline": baseline,
"candidate": candidate_arm,
"baseline_score": baseline_score,
"candidate_score": candidate_score,
"delta": round(candidate_score - baseline_score, 4),
"execution_coverage": _arm_mode_coverage(baseline, candidate_arm, "executed"),
"surrogate_coverage": _arm_mode_coverage(baseline, candidate_arm, "surrogate"),
"blocked_tool_count": _arm_mode_count(baseline, candidate_arm, "blocked"),
"confidence": surrogate["confidence"],
"tool_calls": [*baseline.get("tool_calls", []), *candidate_arm.get("tool_calls", [])],
"artifacts": [*baseline.get("artifacts", []), *candidate_arm.get("artifacts", [])],
"side_effects": [*baseline.get("side_effects", []), *candidate_arm.get("side_effects", [])],
"validator_notes": list(surrogate.get("notes") or []),
}
case_reports.append(case_report)
legacy_cases.append(
{
"run_id": case["run_id"],
"session_id": case.get("session_id") or "",
"baseline_score": baseline_score,
"candidate_score": candidate_score,
"delta": round(candidate_score - baseline_score, 4),
}
)
preservation_report = _preservation_report(candidate, draft)
return _report_from_case_reports(candidate, draft, case_reports, legacy_cases, preservation_report)
def _skipped(self, candidate: SkillLearningCandidate, draft: SkillDraft) -> SkillDraftEvalReport:
return SkillDraftEvalReport(
report_id=uuid4().hex,
@ -115,6 +217,108 @@ def _candidate_score(baseline: float, draft: SkillDraft) -> float:
return min(1.0, max(0.75, baseline + 0.05))
def _draft_skill_context(draft: SkillDraft) -> SkillContext:
tool_hints = draft.proposed_frontmatter.get("tools")
return SkillContext(
name=f"draft:{draft.skill_name}",
content=draft.proposed_content,
version=draft.draft_id,
content_hash="draft",
activation_reason="skill_replay_eval_candidate",
tool_hints=[str(item) for item in tool_hints if str(item).strip()] if isinstance(tool_hints, list) else [],
)
def _preservation_report(candidate: SkillLearningCandidate, draft: SkillDraft) -> dict | None:
if candidate.kind not in {"revise_skill", "merge_skills"}:
return None
base_content = str(candidate.evidence.get("base_content") or "") if isinstance(candidate.evidence, dict) else ""
if not base_content.strip():
return None
return check_preservation(base_content=base_content, draft_content=draft.proposed_content)
def _report_from_case_reports(
candidate: SkillLearningCandidate,
draft: SkillDraft,
case_reports: list[dict],
legacy_cases: list[dict],
preservation_report: dict | None,
) -> SkillDraftEvalReport:
baseline_avg = sum(item["baseline_score"] for item in legacy_cases) / len(legacy_cases)
candidate_avg = sum(item["candidate_score"] for item in legacy_cases) / len(legacy_cases)
regressions = [item for item in legacy_cases if item["candidate_score"] < item["baseline_score"]]
improved = [item for item in legacy_cases if item["candidate_score"] > item["baseline_score"]]
unchanged = len(legacy_cases) - len(regressions) - len(improved)
execution, surrogate, blocked = _coverage(case_reports)
confidence = _confidence(execution, surrogate, blocked, [item.get("confidence") for item in case_reports])
score_delta = candidate_avg - baseline_avg
passed = candidate_avg >= 0.75 and not (regressions and score_delta <= 0) and blocked < 1.0
return SkillDraftEvalReport(
report_id=uuid4().hex,
skill_name=draft.skill_name,
draft_id=draft.draft_id,
candidate_id=candidate.candidate_id,
passed=passed,
baseline_score_avg=round(baseline_avg, 4),
candidate_score_avg=round(candidate_avg, 4),
score_delta=round(score_delta, 4),
regression_count=len(regressions),
improved_count=len(improved),
unchanged_count=unchanged,
cases=legacy_cases,
status="completed",
created_at=_utc_now(),
eval_version="replay-v1",
mode="replay",
execution_coverage=execution,
surrogate_coverage=surrogate,
blocked_coverage=blocked,
confidence=confidence,
case_reports=case_reports,
tool_mode_summary={"executed": execution, "surrogate": surrogate, "blocked": blocked},
preservation_report=preservation_report,
)
def _coverage(case_reports: list[dict]) -> tuple[float, float, float]:
counts = {"executed": 0, "surrogate": 0, "blocked": 0}
for report in case_reports:
for call in report.get("tool_calls") or []:
if isinstance(call, dict) and call.get("mode") in counts:
counts[str(call["mode"])] += 1
total = sum(counts.values())
if total == 0:
return 1.0, 0.0, 0.0
return (
round(counts["executed"] / total, 4),
round(counts["surrogate"] / total, 4),
round(counts["blocked"] / total, 4),
)
def _confidence(execution: float, surrogate: float, blocked: float, case_confidences: list[object]) -> str:
if blocked > 0.0:
return "low"
if execution >= 0.75 and surrogate <= 0.25:
return "high"
if execution >= 0.25 or "medium" in case_confidences:
return "medium"
return "low"
def _arm_mode_coverage(baseline: dict, candidate: dict, mode: str) -> float:
calls = [*baseline.get("tool_calls", []), *candidate.get("tool_calls", [])]
if not calls:
return 1.0 if mode == "executed" else 0.0
return round(sum(1 for call in calls if isinstance(call, dict) and call.get("mode") == mode) / len(calls), 4)
def _arm_mode_count(baseline: dict, candidate: dict, mode: str) -> int:
calls = [*baseline.get("tool_calls", []), *candidate.get("tool_calls", [])]
return sum(1 for call in calls if isinstance(call, dict) and call.get("mode") == mode)
def _utc_now() -> str:
from datetime import datetime, timezone

View File

@ -8,6 +8,7 @@ from beaver.engine.providers import ProviderBundle
from beaver.memory.skills import SkillDraftEvalReport, SkillDraftSafetyReport, SkillLearningCandidate, SkillLearningStore
from beaver.skills.drafts import DraftService
from beaver.skills.learning.eval import SkillDraftEvaluator
from beaver.skills.learning.replay import ReplayRunner
from beaver.skills.learning.service import SkillLearningService
from beaver.skills.learning.safety import SkillDraftSafetyChecker
from beaver.skills.publisher import SkillPublisher
@ -285,11 +286,17 @@ class SkillLearningPipelineService:
draft_id: str,
*,
provider_bundle: ProviderBundle | None,
replay_runner: ReplayRunner | None = None,
) -> SkillDraftEvalReport:
draft = self.get_draft(skill_name, draft_id)
candidate = self.get_candidate(candidate_id)
evaluator = self.evaluator or SkillDraftEvaluator(self.learning_service.run_store)
report = await evaluator.evaluate(candidate=candidate, draft=draft, provider_bundle=provider_bundle)
report = await evaluator.evaluate(
candidate=candidate,
draft=draft,
provider_bundle=provider_bundle,
replay_runner=replay_runner,
)
self.learning_store.write_eval_report(report)
if report.status == "skipped_provider_unavailable":
status = "draft_ready"
@ -330,6 +337,14 @@ class SkillLearningPipelineService:
eval_report = self.get_eval_report(draft.skill_name, draft.draft_id)
if eval_report is not None and eval_report.status != "skipped_provider_unavailable" and not eval_report.passed:
raise ValueError("Draft eval report did not pass")
if eval_report is not None and eval_report.mode == "replay":
if eval_report.confidence == "low":
raise ValueError("Draft replay eval has low confidence and requires revision before publish")
if eval_report.blocked_coverage >= 1.0:
raise ValueError("Draft replay eval blocked all important tool calls")
preservation = eval_report.preservation_report or {}
if preservation.get("passed") is False:
raise ValueError("Draft preservation check did not pass")
def _mark_candidate_by_draft(
self,

View File

@ -0,0 +1,53 @@
"""Preservation checks for skill revision drafts."""
from __future__ import annotations
import re
from typing import Any
def check_preservation(*, base_content: str, draft_content: str) -> dict[str, Any]:
base_sections = _sections(base_content)
draft_sections = _sections(draft_content)
preserved: list[str] = []
changed: list[str] = []
dropped: list[str] = []
for heading, body in base_sections.items():
draft_body = draft_sections.get(heading)
if draft_body is None:
dropped.append(heading)
continue
preserved.append(heading)
if _normalize(body) != _normalize(draft_body):
changed.append(heading)
risk_level = "high" if dropped else "low"
return {
"passed": not dropped,
"risk_level": risk_level,
"preserved_sections": preserved,
"changed_sections": changed,
"dropped_sections": dropped,
}
def _sections(content: str) -> dict[str, str]:
current = "body"
sections: dict[str, list[str]] = {current: []}
for line in (content or "").splitlines():
match = re.match(r"^#{1,6}\s+(.+?)\s*$", line)
if match:
current = match.group(1).strip()
sections.setdefault(current, [])
continue
sections.setdefault(current, []).append(line)
return {
heading: "\n".join(lines).strip()
for heading, lines in sections.items()
if "\n".join(lines).strip()
}
def _normalize(value: str) -> str:
return re.sub(r"\s+", " ", value or "").strip().lower()

View File

@ -0,0 +1,203 @@
"""Replay execution helpers for skill draft evaluation."""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Any, Literal
from uuid import uuid4
from beaver.tools.base import ToolContext, ToolResult, ToolSpec
from beaver.tools.registry.tool_registry import ToolRegistry
from beaver.tools.runtime.executor import ToolExecutor
ToolExecutionMode = Literal["executed", "surrogate", "blocked"]
@dataclass(slots=True)
class ReplayToolPolicy:
safe_toolsets: set[str] = field(default_factory=lambda: {"filesystem", "user_files", "core", "web", "search"})
surrogate_transports: set[str] = field(default_factory=lambda: {"mcp", "connector"})
destructive_terms: tuple[str, ...] = (
"delete",
"remove",
"destroy",
"revoke",
"permission",
"credential",
"payment",
"pay",
)
external_write_terms: tuple[str, ...] = (
"send",
"post",
"publish",
"create",
"update",
"invite",
"reply",
"forward",
)
class ReplayToolExecutor:
def __init__(
self,
inner: ToolExecutor,
*,
registry: ToolRegistry,
policy: ReplayToolPolicy | None = None,
) -> None:
self.inner = inner
self.registry = registry
self.policy = policy or ReplayToolPolicy()
self.traces: list[dict[str, Any]] = []
async def execute(
self,
tool_name: str,
arguments: dict[str, Any] | None,
*,
context: ToolContext | None = None,
) -> ToolResult:
tool = self.registry.get(tool_name)
spec = tool.spec if tool is not None else ToolSpec(
name=tool_name,
description="unregistered tool",
input_schema={"type": "object", "properties": {}},
toolset="unknown",
)
mode = classify_tool_mode(spec, self.policy)
trace = {
"trace_id": uuid4().hex,
"tool_name": tool_name,
"mode": mode,
"arguments": dict(arguments or {}),
"schema": dict(spec.input_schema),
"toolset": spec.toolset,
"metadata": dict(spec.metadata),
"classification_reason": _classification_reason(spec, mode),
}
if mode == "executed":
result = await self.inner.execute(tool_name, arguments or {}, context=context)
trace["result"] = {
"success": result.success,
"error": result.error,
"content": result.content[:2000],
}
self.traces.append(trace)
return result
if mode == "surrogate":
trace["result"] = {
"success": True,
"error": "replay_surrogate",
"content": "Tool call recorded for surrogate evaluation.",
}
self.traces.append(trace)
return ToolResult(
success=True,
content="Tool call recorded for surrogate evaluation.",
tool_name=tool_name,
error="replay_surrogate",
raw_output=trace,
)
trace["result"] = {
"success": False,
"error": "replay_blocked",
"content": "Tool call blocked by replay policy.",
}
self.traces.append(trace)
return ToolResult(
success=False,
content="Tool call blocked by replay policy.",
tool_name=tool_name,
error="replay_blocked",
raw_output=trace,
)
async def execute_tool_call(self, tool_call: Any, *, context: ToolContext | None = None) -> ToolResult:
tool_name, arguments = ToolExecutor._normalize_tool_call(tool_call)
return await self.execute(tool_name, arguments, context=context)
def classify_tool_mode(spec: ToolSpec, policy: ReplayToolPolicy | None = None) -> ToolExecutionMode:
policy = policy or ReplayToolPolicy()
name = spec.name.lower()
toolset = spec.toolset.lower()
metadata = {str(key).lower(): str(value).lower() for key, value in spec.metadata.items()}
if any(term in name for term in policy.destructive_terms):
return "blocked"
if toolset in policy.safe_toolsets:
return "executed"
if metadata.get("transport") in policy.surrogate_transports or toolset in {"mcp", "connector", "external"}:
if any(term in name for term in policy.external_write_terms):
return "surrogate"
return "executed"
return "surrogate"
def _classification_reason(spec: ToolSpec, mode: ToolExecutionMode) -> str:
return f"{spec.name} classified as {mode} from toolset={spec.toolset} metadata={spec.metadata}"
@dataclass(slots=True)
class ReplayArmRequest:
case_id: str
arm: str
task_text: str
pinned_skill_names: list[str] = field(default_factory=list)
pinned_skill_contexts: list[Any] = field(default_factory=list)
provider_bundle: Any | None = None
model_settings: dict[str, Any] = field(default_factory=dict)
class ReplayRunner:
def __init__(self, *, agent_loop: Any, policy: ReplayToolPolicy | None = None) -> None:
self.agent_loop = agent_loop
self.policy = policy or ReplayToolPolicy()
async def run_arm(self, request: ReplayArmRequest) -> dict[str, Any]:
loaded = self.agent_loop.boot()
replay_executor = ReplayToolExecutor(
loaded.tool_executor,
registry=loaded.tool_registry,
policy=self.policy,
)
result = await self.agent_loop.process_direct(
request.task_text,
provider_bundle=request.provider_bundle,
include_skill_assembly=False,
include_tools=True,
pinned_skill_names=request.pinned_skill_names,
pinned_skill_contexts=request.pinned_skill_contexts,
max_tool_iterations=int(request.model_settings.get("max_tool_iterations") or 4),
temperature=float(request.model_settings.get("temperature") or 0.0),
source="skill_replay_eval",
tool_executor_override=replay_executor,
)
return {
"case_id": request.case_id,
"arm": request.arm,
"session_id": result.session_id,
"run_id": result.run_id,
"task_text": request.task_text,
"finish_reason": result.finish_reason,
"final_answer": result.output_text,
"tool_calls": list(replay_executor.traces),
"artifacts": [],
"side_effects": _side_effects_from_traces(replay_executor.traces),
}
def _side_effects_from_traces(traces: list[dict[str, Any]]) -> list[dict[str, Any]]:
effects: list[dict[str, Any]] = []
for trace in traces:
if trace.get("mode") in {"surrogate", "blocked"}:
effects.append(
{
"tool_name": trace.get("tool_name"),
"mode": trace.get("mode"),
"arguments": trace.get("arguments"),
"classification_reason": trace.get("classification_reason"),
}
)
return effects

View File

@ -69,15 +69,24 @@ class SkillLearningService:
existing_ids.add(candidate.candidate_id)
return candidates
def build_learning_candidates_for_task(self, task_id: str, *, trigger_run_id: str) -> list[SkillLearningCandidate]:
"""Build candidates scoped to a single validated and satisfied Task run."""
def build_learning_candidates_for_task(
self,
task_id: str,
*,
final_accepted_run_id: str | None = None,
trigger_run_id: str | None = None,
) -> list[SkillLearningCandidate]:
"""Build candidates from a user-accepted Task and all of its runs."""
final_accepted_run_id = final_accepted_run_id or trigger_run_id
if not final_accepted_run_id:
return []
runs = [record for record in self.run_store.list_runs() if record.task_id == task_id]
trigger_run = next((record for record in runs if record.run_id == trigger_run_id), None)
if trigger_run is None or not self._is_confirmed_positive_run(trigger_run):
final_run = next((record for record in runs if record.run_id == final_accepted_run_id), None)
if final_run is None or not self._is_task_accepted_run(final_run):
return []
source_runs = [record for record in runs if self._is_confirmed_positive_run(record)]
source_runs = sorted(runs, key=lambda item: (item.started_at, item.run_id))
if not source_runs:
return []
@ -100,11 +109,16 @@ class SkillLearningService:
source_session_ids=source_session_ids,
related_skill_names=[],
reason=f"Task {task_id} completed successfully without a published skill; consider extracting reusable guidance.",
evidence={"task_id": task_id, "trigger_run_id": trigger_run_id, "theme": self._task_theme(trigger_run.task_text)},
evidence={
"task_id": task_id,
"final_accepted_run_id": final_accepted_run_id,
"source_run_ids": source_run_ids,
"theme": self._task_theme(final_run.task_text),
},
status="open",
priority=1,
confidence=0.8,
trigger_reason="validation_accepted_and_user_satisfied",
trigger_reason="task_accepted",
)
)
else:
@ -137,13 +151,14 @@ class SkillLearningService:
),
evidence={
"task_id": task_id,
"trigger_run_id": trigger_run_id,
"final_accepted_run_id": final_accepted_run_id,
"source_run_ids": source_run_ids,
"skill_version": receipt.skill_version,
},
status="open",
priority=1,
confidence=0.7,
trigger_reason="validation_accepted_and_user_satisfied",
trigger_reason="task_accepted",
)
)
@ -190,7 +205,13 @@ class SkillLearningService:
)
if candidate.kind == "merge_skills":
target_name = self._suggest_skill_name(candidate, packet)
payload = await self.synthesizer.synthesize_merge(candidate, packet, provider, model)
payload = await self.synthesizer.synthesize_merge(
candidate,
packet,
provider,
model,
base_skill=self._merged_base_skill_snapshot(candidate.related_skill_names),
)
return self.draft_service.create_merge_draft(
skill_name=target_name,
base_version=None,
@ -202,7 +223,13 @@ class SkillLearningService:
)
target_skill = candidate.related_skill_names[0]
base_version = candidate.evidence.get("skill_version")
payload = await self.synthesizer.synthesize_revision(candidate, packet, provider, model)
payload = await self.synthesizer.synthesize_revision(
candidate,
packet,
provider,
model,
base_skill=self._base_skill_snapshot(target_skill, base_version),
)
return self.draft_service.create_revision_draft(
skill_name=target_skill,
base_version=base_version,
@ -213,6 +240,46 @@ class SkillLearningService:
evidence_refs=[{"run_id": item} for item in candidate.source_run_ids],
)
def _base_skill_snapshot(self, skill_name: str, version: str | None) -> dict[str, Any] | None:
loaded = self.draft_service.store.read_published_skill(skill_name, version)
if loaded is None:
return None
return {
"skill_name": loaded.version.skill_name,
"version": loaded.version.version,
"frontmatter": dict(loaded.version.frontmatter),
"content": loaded.content,
"summary": loaded.version.summary,
"tool_hints": list(loaded.version.tool_hints),
}
def _merged_base_skill_snapshot(self, skill_names: list[str]) -> dict[str, Any] | None:
snapshots = [
snapshot
for name in skill_names
if (snapshot := self._base_skill_snapshot(name, None)) is not None
]
if not snapshots:
return None
return {
"skill_name": "merge:" + ",".join(str(item["skill_name"]) for item in snapshots),
"version": "mixed",
"frontmatter": {"merged_skills": [item["frontmatter"] for item in snapshots]},
"content": "\n\n".join(
f"<!-- base skill: {item['skill_name']} {item['version']} -->\n{item['content']}"
for item in snapshots
),
"summary": "\n".join(str(item["summary"]) for item in snapshots if item.get("summary")),
"tool_hints": list(
dict.fromkeys(
tool
for item in snapshots
for tool in item.get("tool_hints", [])
if str(tool).strip()
)
),
}
def rescore_skill_versions(self) -> list[SkillPerformanceSnapshot]:
snapshots: list[SkillPerformanceSnapshot] = []
grouped: dict[tuple[str, str], list[SkillEffectRecord]] = {}
@ -269,7 +336,7 @@ class SkillLearningService:
groups.setdefault(key, []).append(record)
candidates: list[SkillLearningCandidate] = []
for theme, runs in groups.items():
successful = [record for record in runs if self._is_confirmed_positive_run(record)]
successful = [record for record in runs if self._is_task_accepted_run(record)]
if len(successful) < 2:
continue
if any(record.activated_skills for record in successful):
@ -290,7 +357,7 @@ class SkillLearningService:
def _build_merge_candidates(self) -> list[SkillLearningCandidate]:
pair_counts: dict[tuple[str, str], list[RunRecord]] = {}
for record in self.run_store.list_runs():
if not self._is_confirmed_positive_run(record):
if not self._is_task_accepted_run(record):
continue
unique = sorted({receipt.skill_name for receipt in record.activated_skills})
for pair in combinations(unique, 2):
@ -351,14 +418,15 @@ class SkillLearningService:
return effects
@staticmethod
def _is_confirmed_positive_run(record: RunRecord) -> bool:
validation = record.validation_result or {}
def _is_task_accepted_run(record: RunRecord) -> bool:
feedback = record.feedback or {}
acceptance_type = feedback.get("acceptance_type")
if acceptance_type is None and feedback.get("feedback_type") == "satisfied":
acceptance_type = "accept"
return (
bool(record.success)
and bool(record.task_id)
and validation.get("accepted") is True
and feedback.get("feedback_type") == "satisfied"
and acceptance_type == "accept"
)
@staticmethod

View File

@ -0,0 +1,53 @@
"""Surrogate evaluation for replay tool calls that cannot execute safely."""
from __future__ import annotations
from typing import Any
class SurrogateToolEvaluator:
async def evaluate(self, *, task_text: str, baseline: dict[str, Any], candidate: dict[str, Any]) -> dict[str, Any]:
baseline_score = _score_arm(task_text, baseline)
candidate_score = _score_arm(task_text, candidate)
surrogate_count = _mode_count(baseline, "surrogate") + _mode_count(candidate, "surrogate")
blocked_count = _mode_count(baseline, "blocked") + _mode_count(candidate, "blocked")
confidence = "low" if blocked_count else ("medium" if surrogate_count <= 2 else "low")
return {
"baseline_score": baseline_score,
"candidate_score": candidate_score,
"delta": round(candidate_score - baseline_score, 4),
"surrogate_tool_count": surrogate_count,
"blocked_tool_count": blocked_count,
"confidence": confidence,
"notes": [
"Surrogate score is based on intended tool calls, schemas, arguments, and task relevance.",
],
}
def _score_arm(task_text: str, arm: dict[str, Any]) -> float:
calls = [item for item in arm.get("tool_calls") or [] if isinstance(item, dict)]
if not calls:
return 0.5
scores = [_score_call(task_text, call) for call in calls]
return round(sum(scores) / len(scores), 4)
def _score_call(task_text: str, call: dict[str, Any]) -> float:
if call.get("mode") == "blocked":
return 0.2
if call.get("mode") == "executed":
result = call.get("result") if isinstance(call.get("result"), dict) else {}
return 0.85 if result.get("success") is not False else 0.35
arguments = dict(call.get("arguments") or {})
if not arguments:
return 0.45
non_empty = sum(1 for value in arguments.values() if str(value).strip())
completeness = non_empty / max(1, len(arguments))
argument_text = " ".join(str(value).lower() for value in arguments.values())
relevance = 0.15 if any(token and token in argument_text for token in task_text.lower().split()[:16]) else 0.0
return round(min(0.9, 0.5 + 0.3 * completeness + relevance), 4)
def _mode_count(arm: dict[str, Any], mode: str) -> int:
return sum(1 for item in arm.get("tool_calls") or [] if isinstance(item, dict) and item.get("mode") == mode)

View File

@ -17,8 +17,9 @@ class SkillDraftSynthesizer:
evidence_packet: EvidencePacket,
provider: LLMProvider,
model: str,
base_skill: dict[str, Any] | None = None,
) -> dict[str, Any]:
return await self._synthesize(candidate, evidence_packet, provider, model, "revise")
return await self._synthesize(candidate, evidence_packet, provider, model, "revise", base_skill=base_skill)
async def synthesize_new_skill(
self,
@ -27,7 +28,7 @@ class SkillDraftSynthesizer:
provider: LLMProvider,
model: str,
) -> dict[str, Any]:
return await self._synthesize(candidate, evidence_packet, provider, model, "new")
return await self._synthesize(candidate, evidence_packet, provider, model, "new", base_skill=None)
async def synthesize_merge(
self,
@ -35,8 +36,9 @@ class SkillDraftSynthesizer:
evidence_packet: EvidencePacket,
provider: LLMProvider,
model: str,
base_skill: dict[str, Any] | None = None,
) -> dict[str, Any]:
return await self._synthesize(candidate, evidence_packet, provider, model, "merge")
return await self._synthesize(candidate, evidence_packet, provider, model, "merge", base_skill=base_skill)
async def _synthesize(
self,
@ -45,15 +47,18 @@ class SkillDraftSynthesizer:
provider: LLMProvider,
model: str,
action: str,
*,
base_skill: dict[str, Any] | None,
) -> dict[str, Any]:
prompt = self._build_prompt(candidate, evidence_packet, action)
prompt = self._build_prompt(candidate, evidence_packet, action, base_skill=base_skill)
response = await provider.chat(
messages=[
{
"role": "system",
"content": (
"You synthesize Beaver skill drafts from execution evidence. "
"Return only JSON with keys: frontmatter, content, change_reason."
"Return only JSON with keys: frontmatter, content, change_reason, "
"preserved_sections, changed_sections, dropped_sections."
),
},
{"role": "user", "content": prompt},
@ -69,11 +74,30 @@ class SkillDraftSynthesizer:
return self._fallback_payload(candidate, evidence_packet, action)
@staticmethod
def _build_prompt(candidate: SkillLearningCandidate, evidence_packet: EvidencePacket, action: str) -> str:
def _build_prompt(
candidate: SkillLearningCandidate,
evidence_packet: EvidencePacket,
action: str,
base_skill: dict[str, Any] | None = None,
) -> str:
tool_names = _coerce_string_list(evidence_packet.metadata.get("tool_names"))
tool_section = ", ".join(tool_names) if tool_names else "none observed"
selected_tool_names = _coerce_string_list(evidence_packet.metadata.get("selected_tool_names"))
selected_tool_section = ", ".join(selected_tool_names) if selected_tool_names else "none recorded"
base_section = ""
if base_skill:
base_section = (
"\n\nBase skill snapshot:\n"
f"- skill_name: {base_skill.get('skill_name')}\n"
f"- version: {base_skill.get('version')}\n"
f"- frontmatter: {json.dumps(base_skill.get('frontmatter') or {}, ensure_ascii=False, sort_keys=True)}\n"
f"- tool_hints: {base_skill.get('tool_hints') or []}\n"
f"- summary: {base_skill.get('summary') or ''}\n"
"Base skill content:\n"
f"{base_skill.get('content') or ''}\n"
"Preserve existing instructions unless the evidence requires a change. "
"If any section is changed or dropped, explain it in changed_sections or dropped_sections."
)
return (
f"Action: {action}\n"
f"Candidate kind: {candidate.kind}\n"
@ -83,11 +107,13 @@ class SkillDraftSynthesizer:
f"Run-selected tool names: {selected_tool_section}\n"
f"Task summaries:\n- " + "\n- ".join(evidence_packet.task_summaries)
+ "\n\nSession excerpts:\n" + "\n\n".join(evidence_packet.session_excerpts)
+ base_section
+ "\n\nReturn JSON only. The frontmatter object must include:"
+ "\n- description: a concise skill description"
+ "\n- tools: an explicit JSON array of exact tool names this skill needs. "
+ "Prefer called tool names when the workflow depends on them; use run-selected tool names only when clearly required. "
+ "Use [] only when no tool is required."
+ "\nThe JSON may include preserved_sections, changed_sections, and dropped_sections arrays."
)
@staticmethod
@ -111,6 +137,9 @@ class SkillDraftSynthesizer:
"frontmatter": frontmatter,
"content": content_value.strip(),
"change_reason": str(payload.get("change_reason") or ""),
"preserved_sections": _coerce_string_list(payload.get("preserved_sections")),
"changed_sections": _coerce_string_list(payload.get("changed_sections")),
"dropped_sections": _coerce_string_list(payload.get("dropped_sections")),
}
@staticmethod
@ -124,6 +153,9 @@ class SkillDraftSynthesizer:
"frontmatter": frontmatter,
"content": str(payload.get("content") or "").strip(),
"change_reason": str(payload.get("change_reason") or ""),
"preserved_sections": _coerce_string_list(payload.get("preserved_sections")),
"changed_sections": _coerce_string_list(payload.get("changed_sections")),
"dropped_sections": _coerce_string_list(payload.get("dropped_sections")),
}
@staticmethod
@ -138,6 +170,9 @@ class SkillDraftSynthesizer:
},
"content": f"# {title}\n\n## Evidence\n\n{content}\n",
"change_reason": candidate.reason or f"Fallback {action} synthesis.",
"preserved_sections": [],
"changed_sections": [],
"dropped_sections": [],
}

View File

@ -1,22 +1,27 @@
"""Internal task tracking for automatic Main Agent task mode."""
from .models import MainAgentDecision, TaskEvent, TaskRecord, ValidationResult
from .evidence import EvidenceBuilder, RunEvidence, TaskEvidencePacket, ToolEvidence, render_task_evidence
from .models import MainAgentDecision, TaskEvent, TaskRecord, ValidationResult, ValidationStatus
from .planner import TaskExecutionPlan, TaskExecutionPlanner
from .router import MainAgentRouter
from .service import TaskService
from .skill_resolver import SkillResolutionReport, TaskSkillResolver
from .validation import ValidationService
__all__ = [
"EvidenceBuilder",
"MainAgentDecision",
"MainAgentRouter",
"RunEvidence",
"TaskEvent",
"TaskEvidencePacket",
"TaskExecutionPlan",
"TaskExecutionPlanner",
"TaskRecord",
"TaskService",
"SkillResolutionReport",
"TaskSkillResolver",
"ToolEvidence",
"ValidationResult",
"ValidationService",
"ValidationStatus",
"render_task_evidence",
]

View File

@ -0,0 +1,183 @@
"""Structured evidence for task synthesis and validation."""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Any
@dataclass(slots=True)
class ToolEvidence:
tool_name: str
tool_call_id: str | None
content: str
event_payload: dict[str, Any] = field(default_factory=dict)
url: str | None = None
title: str | None = None
created_at: str | None = None
def to_dict(self) -> dict[str, Any]:
return {
"tool_name": self.tool_name,
"tool_call_id": self.tool_call_id,
"content": self.content,
"event_payload": dict(self.event_payload),
"url": self.url,
"title": self.title,
"created_at": self.created_at,
}
@dataclass(slots=True)
class RunEvidence:
run_id: str
session_id: str
output_text: str
finish_reason: str
transcript: list[dict[str, Any]] = field(default_factory=list)
tool_results: list[ToolEvidence] = field(default_factory=list)
warnings: list[str] = field(default_factory=list)
def to_dict(self) -> dict[str, Any]:
return {
"run_id": self.run_id,
"session_id": self.session_id,
"output_text": self.output_text,
"finish_reason": self.finish_reason,
"transcript": list(self.transcript),
"tool_results": [item.to_dict() for item in self.tool_results],
"warnings": list(self.warnings),
}
@dataclass(slots=True)
class TaskEvidencePacket:
task_id: str
attempt_index: int
main_run: RunEvidence | None
team_runs: list[RunEvidence] = field(default_factory=list)
team_node_results: list[Any] = field(default_factory=list)
final_output: str = ""
def to_dict(self) -> dict[str, Any]:
return {
"task_id": self.task_id,
"attempt_index": self.attempt_index,
"main_run": self.main_run.to_dict() if self.main_run else None,
"team_runs": [item.to_dict() for item in self.team_runs],
"team_node_results": [
item.to_dict() if hasattr(item, "to_dict") else dict(item)
for item in self.team_node_results
],
"final_output": self.final_output,
}
class EvidenceBuilder:
def __init__(self, session_manager: Any) -> None:
self.session_manager = session_manager
def build_run_evidence(
self,
session_id: str,
run_id: str,
output_text: str,
finish_reason: str,
) -> RunEvidence:
events = self.session_manager.get_run_event_records(session_id, run_id)
transcript: list[dict[str, Any]] = []
tool_results: list[ToolEvidence] = []
warnings: list[str] = []
for event in events:
payload = dict(event.event_payload or {})
transcript.append(
{
"role": event.role,
"event_type": event.event_type,
"content": event.content,
"tool_name": event.tool_name,
"tool_call_id": event.tool_call_id,
"finish_reason": event.finish_reason,
"event_payload": payload,
}
)
if event.event_type == "tool_result_recorded":
tool_results.append(
ToolEvidence(
tool_name=event.tool_name or "tool",
tool_call_id=event.tool_call_id,
content=event.content or "",
event_payload=payload,
url=_optional_str(payload.get("url")),
title=_optional_str(payload.get("title")),
created_at=_optional_str(payload.get("created_at")),
)
)
if finish_reason and finish_reason != "stop":
warnings.append(f"finish_reason={finish_reason}")
return RunEvidence(
run_id=run_id,
session_id=session_id,
output_text=output_text,
finish_reason=finish_reason,
transcript=transcript,
tool_results=tool_results,
warnings=warnings,
)
def render_task_evidence(packet: TaskEvidencePacket) -> str:
sections = [
f"Task evidence packet: task_id={packet.task_id} attempt={packet.attempt_index}",
f"Final output:\n{packet.final_output}",
]
if packet.main_run is not None:
sections.append("Main run evidence:\n" + render_run_evidence(packet.main_run))
if packet.team_runs:
sections.append(
"Team run evidence:\n"
+ "\n\n".join(render_run_evidence(item) for item in packet.team_runs)
)
if packet.team_node_results:
lines = []
for item in packet.team_node_results:
lines.append(
f"- {getattr(item, 'node_id', '')}: success={getattr(item, 'success', False)} "
f"finish_reason={getattr(item, 'finish_reason', '')} error={getattr(item, 'error', '') or ''}"
)
sections.append("Team node results:\n" + "\n".join(lines))
return "\n\n".join(section for section in sections if section.strip())
def render_run_evidence(evidence: RunEvidence) -> str:
lines = [
f"run_id={evidence.run_id}",
f"session_id={evidence.session_id}",
f"finish_reason={evidence.finish_reason}",
]
if evidence.output_text:
lines.append(f"output:\n{evidence.output_text}")
if evidence.warnings:
lines.append("warnings:\n" + "\n".join(f"- {item}" for item in evidence.warnings))
if evidence.tool_results:
lines.append(
"tool_results:\n"
+ "\n\n".join(_render_tool_evidence(item) for item in evidence.tool_results)
)
return "\n".join(lines)
def _render_tool_evidence(item: ToolEvidence) -> str:
header = f"- tool={item.tool_name} call_id={item.tool_call_id or ''}"
metadata = []
if item.url:
metadata.append(f"url={item.url}")
if item.title:
metadata.append(f"title={item.title}")
if item.created_at:
metadata.append(f"created_at={item.created_at}")
return "\n".join([header, *metadata, item.content])
def _optional_str(value: Any) -> str | None:
return str(value) if value is not None else None

View File

@ -1,33 +1,70 @@
"""Models for internal task tracking and validation."""
"""Models for internal task tracking and user acceptance."""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Any
from typing import Any, Literal
TASK_OPEN_STATUSES = {"open", "running", "validating", "awaiting_feedback", "needs_revision"}
ValidationStatus = Literal["accepted", "rejected", "insufficient_evidence", "validator_error"]
VALIDATION_STATUSES = {"accepted", "rejected", "insufficient_evidence", "validator_error"}
TASK_OPEN_STATUSES = {"open", "running", "awaiting_acceptance", "needs_revision"}
LEGACY_STATUS_MAP = {
"validating": "running",
"awaiting_feedback": "awaiting_acceptance",
"needs_review": "awaiting_acceptance",
}
@dataclass(slots=True)
class ValidationResult:
passed: bool
score: float
status: ValidationStatus = "rejected"
score: float = 0.0
issues: list[str] = field(default_factory=list)
missing_requirements: list[str] = field(default_factory=list)
evidence_gaps: list[str] = field(default_factory=list)
recommended_revision_prompt: str = ""
validator: str = "heuristic"
def __init__(
self,
*,
status: ValidationStatus | None = None,
passed: bool | None = None,
score: float = 0.0,
issues: list[str] | None = None,
missing_requirements: list[str] | None = None,
evidence_gaps: list[str] | None = None,
recommended_revision_prompt: str = "",
validator: str = "heuristic",
) -> None:
if status is not None and status not in VALIDATION_STATUSES:
raise ValueError(f"unknown validation status: {status}")
self.status = status or ("accepted" if passed and score >= 0.75 else "rejected")
self.score = max(0.0, min(1.0, float(score or 0.0)))
self.issues = list(issues or [])
self.missing_requirements = list(missing_requirements or [])
self.evidence_gaps = list(evidence_gaps or [])
self.recommended_revision_prompt = recommended_revision_prompt
self.validator = validator
@property
def passed(self) -> bool:
return self.status == "accepted"
@property
def accepted(self) -> bool:
return self.passed and self.score >= 0.75
return self.status == "accepted"
def to_dict(self) -> dict[str, Any]:
return {
"status": self.status,
"passed": self.passed,
"score": self.score,
"issues": list(self.issues),
"missing_requirements": list(self.missing_requirements),
"evidence_gaps": list(self.evidence_gaps),
"recommended_revision_prompt": self.recommended_revision_prompt,
"validator": self.validator,
"accepted": self.accepted,
@ -37,11 +74,17 @@ class ValidationResult:
def from_dict(cls, payload: dict[str, Any] | None) -> "ValidationResult | None":
if not isinstance(payload, dict):
return None
raw_status = payload.get("status")
if "status" in payload and raw_status not in VALIDATION_STATUSES:
raise ValueError(f"unknown validation status: {raw_status}")
status: ValidationStatus | None = raw_status if "status" in payload else None
return cls(
passed=bool(payload.get("passed")),
status=status,
passed=bool(payload.get("passed")) if "status" not in payload else None,
score=float(payload.get("score", 0.0) or 0.0),
issues=[str(item) for item in payload.get("issues") or []],
missing_requirements=[str(item) for item in payload.get("missing_requirements") or []],
evidence_gaps=[str(item) for item in payload.get("evidence_gaps") or []],
recommended_revision_prompt=str(payload.get("recommended_revision_prompt") or ""),
validator=str(payload.get("validator") or "unknown"),
)
@ -73,6 +116,14 @@ class TaskRecord:
def is_open(self) -> bool:
return self.status in TASK_OPEN_STATUSES
@property
def is_execution_active(self) -> bool:
return self.status == "running"
@property
def requires_user_action(self) -> bool:
return self.status in {"awaiting_acceptance", "needs_revision"}
def to_dict(self) -> dict[str, Any]:
return {
"task_id": self.task_id,
@ -91,6 +142,7 @@ class TaskRecord:
"satisfaction": self.satisfaction,
"run_ids": list(self.run_ids),
"skill_names": list(self.skill_names),
"acceptance": list(self.feedback),
"feedback": list(self.feedback),
"validation_result": self.validation_result,
"metadata": dict(self.metadata),
@ -106,7 +158,7 @@ class TaskRecord:
goal=str(payload.get("goal") or payload.get("description") or ""),
constraints=[str(item) for item in payload.get("constraints") or []],
priority=int(payload.get("priority", 0) or 0),
status=str(payload.get("status") or "open"),
status=LEGACY_STATUS_MAP.get(str(payload.get("status") or "open"), str(payload.get("status") or "open")),
creator=str(payload.get("creator") or "main-agent"),
created_at=str(payload.get("created_at") or ""),
updated_at=str(payload.get("updated_at") or ""),
@ -115,7 +167,11 @@ class TaskRecord:
satisfaction=_optional_float(payload.get("satisfaction")),
run_ids=[str(item) for item in payload.get("run_ids") or []],
skill_names=[str(item) for item in payload.get("skill_names") or []],
feedback=[dict(item) for item in payload.get("feedback") or [] if isinstance(item, dict)],
feedback=[
_normalize_acceptance_entry(dict(item))
for item in (payload.get("acceptance") or payload.get("feedback") or [])
if isinstance(item, dict)
],
validation_result=dict(payload["validation_result"]) if isinstance(payload.get("validation_result"), dict) else None,
metadata=dict(payload.get("metadata") or {}),
)
@ -180,3 +236,13 @@ def _optional_float(value: Any) -> float | None:
if value in (None, ""):
return None
return float(value)
def _normalize_acceptance_entry(entry: dict[str, Any]) -> dict[str, Any]:
if entry.get("acceptance_type") is None and entry.get("feedback_type") is not None:
feedback_type = str(entry.get("feedback_type") or "")
entry["acceptance_type"] = "accept" if feedback_type == "satisfied" else feedback_type
if entry.get("feedback_type") is None and entry.get("acceptance_type") is not None:
acceptance_type = str(entry.get("acceptance_type") or "")
entry["feedback_type"] = "satisfied" if acceptance_type == "accept" else acceptance_type
return entry

View File

@ -10,7 +10,7 @@ from typing import Any, Literal
from beaver.coordinator.models import AgentDescriptor, ExecutionGraph, ExecutionNode
from beaver.engine.providers import ProviderBundle
from .models import TaskRecord, ValidationResult
from .models import TaskRecord
from .skill_resolver import SkillResolutionReport, TaskSkillResolver
@ -76,7 +76,6 @@ class TaskExecutionPlanner:
task: TaskRecord,
user_message: str,
attempt_index: int,
latest_validation: ValidationResult | None = None,
provider_bundle: ProviderBundle | None = None,
timeout_seconds: float = 30.0,
) -> TaskExecutionPlan:
@ -105,7 +104,6 @@ class TaskExecutionPlanner:
task=task,
user_message=user_message,
attempt_index=attempt_index,
latest_validation=latest_validation,
),
},
],
@ -230,14 +228,10 @@ class TaskExecutionPlanner:
task: TaskRecord,
user_message: str,
attempt_index: int,
latest_validation: ValidationResult | None,
) -> str:
validation_note = ""
if latest_validation is not None:
validation_note = (
"\nPrevious validation issues:\n"
+ json.dumps(latest_validation.to_dict(), ensure_ascii=False)
)
history_note = ""
if task.feedback:
history_note = "\nRelevant task history:\n" + json.dumps(task.feedback[-5:], ensure_ascii=False)
return (
"Decide execution mode for this internal Task attempt.\n"
"Use mode=team only when independent research, review, implementation slices, or staged checks "
@ -254,7 +248,7 @@ class TaskExecutionPlanner:
f"Task goal:\n{task.goal}\n\n"
f"Current user request:\n{user_message}\n\n"
f"Attempt index: {attempt_index}\n"
f"{validation_note}"
f"{history_note}"
)
@staticmethod

View File

@ -161,6 +161,9 @@ class MainAgentRouter:
"Critical policy:\n"
"- If there is an active Task, choose continue_task or revise_task unless the user's topic is completely unrelated "
"to that Task or the user explicitly closes/abandons it.\n"
"- With an active Task, choose simple_chat for unrelated lightweight conversation and new_task for unrelated work "
"that needs Task capabilities. Either decision starts a new topic.\n"
"- An unrelated lightweight conversation must not be classified as revise_task merely because the active Task is awaiting acceptance.\n"
"- Choose revise_task when the active Task is awaiting feedback or needs revision and the user asks for changes "
"such as '改一下', '加上', '删除', '换成', '再详细点', '格式改成', '不要', or equivalent wording.\n"
"- Choose continue_task for neutral follow-up questions or additional next steps that do not imply dissatisfaction with the previous result.\n"

View File

@ -7,7 +7,7 @@ from pathlib import Path
from typing import Any
from uuid import uuid4
from .models import TaskEvent, TaskRecord, ValidationResult
from .models import TaskEvent, TaskRecord
from .store import TaskStore
@ -77,6 +77,8 @@ class TaskService:
payload = task.to_dict()
payload["short_title"] = self.ensure_short_title(task).metadata.get("short_title")
payload["is_open"] = task.is_open
payload["is_execution_active"] = task.is_execution_active
payload["requires_user_action"] = task.requires_user_action
return payload
def ensure_short_title(self, task: TaskRecord) -> TaskRecord:
@ -103,18 +105,70 @@ class TaskService:
for name in skill_names or []:
if name not in task.skill_names:
task.skill_names.append(name)
task.status = "awaiting_acceptance"
task.updated_at = self._now()
self.store.upsert_task(task)
self._event(task, "run_completed", run_id=run_id, payload={"skill_names": skill_names or []})
self._event(task, "evidence_recorded", run_id=run_id, payload={"skill_names": skill_names or []})
return task
def record_validation(self, task_id: str, run_id: str, validation: ValidationResult) -> TaskRecord:
def add_acceptance(
self,
task_id: str,
*,
acceptance_type: str,
comment: str | None = None,
run_id: str | None = None,
) -> TaskRecord:
task = self._require(task_id)
task.status = "awaiting_feedback"
task.updated_at = self._now()
task.validation_result = validation.to_dict()
now = self._now()
normalized = normalize_acceptance_type(acceptance_type)
matching_acceptance = any(
item.get("run_id") == run_id and item.get("acceptance_type") == normalized
for item in task.feedback
)
conflicting_acceptance = next(
(
item
for item in task.feedback
if item.get("run_id") == run_id and item.get("acceptance_type") != normalized
),
None,
)
if conflicting_acceptance is not None:
raise ValueError(
f"Acceptance for run_id={run_id!r} was already recorded as "
f"{conflicting_acceptance.get('acceptance_type')!r}"
)
if task.status in {"closed", "abandoned"} and not matching_acceptance:
raise ValueError(f"Task {task.task_id} is already finalized as {task.status!r}")
if matching_acceptance:
return task
entry = {
"acceptance_type": normalized,
"feedback_type": "satisfied" if normalized == "accept" else normalized,
"comment": comment or "",
"run_id": run_id,
"created_at": now,
}
task.feedback.append(entry)
if normalized == "revise":
task.status = "needs_revision"
elif normalized == "abandon":
task.status = "abandoned"
task.closed_at = now
task.close_reason = comment or "abandoned"
elif normalized == "accept":
task.status = "closed"
task.closed_at = now
task.close_reason = "accepted"
task.satisfaction = 1.0
if run_id:
task.metadata["final_accepted_run_id"] = run_id
task.updated_at = now
self.store.upsert_task(task)
self._event(task, "validated", run_id=run_id, payload=validation.to_dict())
self._event(task, f"acceptance_{normalized}", run_id=run_id, payload=entry)
return task
def add_feedback(
@ -125,52 +179,12 @@ class TaskService:
comment: str | None = None,
run_id: str | None = None,
) -> TaskRecord:
task = self._require(task_id)
now = self._now()
matching_feedback = any(
item.get("run_id") == run_id and item.get("feedback_type") == feedback_type
for item in task.feedback
return self.add_acceptance(
task_id,
acceptance_type=feedback_type,
comment=comment,
run_id=run_id,
)
conflicting_feedback = next(
(
item
for item in task.feedback
if item.get("run_id") == run_id and item.get("feedback_type") != feedback_type
),
None,
)
if conflicting_feedback is not None:
raise ValueError(
f"Feedback for run_id={run_id!r} was already recorded as "
f"{conflicting_feedback.get('feedback_type')!r}"
)
if task.status in {"closed", "abandoned"} and not matching_feedback:
raise ValueError(f"Task {task.task_id} is already finalized as {task.status!r}")
if matching_feedback:
return task
entry = {
"feedback_type": feedback_type,
"comment": comment or "",
"run_id": run_id,
"created_at": now,
}
task.feedback.append(entry)
if feedback_type == "revise":
task.status = "needs_revision"
elif feedback_type == "abandon":
task.status = "abandoned"
task.closed_at = now
task.close_reason = comment or "abandoned"
elif feedback_type == "satisfied":
task.status = "closed"
task.closed_at = now
task.close_reason = "satisfied"
task.satisfaction = 1.0
task.updated_at = now
self.store.upsert_task(task)
self._event(task, f"feedback_{feedback_type}", run_id=run_id, payload=entry)
return task
def close_task(self, task_id: str, *, reason: str = "closed") -> TaskRecord:
task = self._require(task_id)
@ -245,3 +259,12 @@ def short_task_title(text: str) -> str:
if len(words) <= 4:
return cleaned[:40]
return " ".join(words[:4])[:40]
def normalize_acceptance_type(value: str) -> str:
normalized = (value or "").strip().lower()
if normalized == "satisfied":
return "accept"
if normalized not in {"accept", "revise", "abandon"}:
raise ValueError("acceptance_type must be one of: accept, revise, abandon")
return normalized

View File

@ -1,138 +0,0 @@
"""Automatic validation for internal Task mode."""
from __future__ import annotations
import json
from typing import Any
from beaver.engine.providers import ProviderBundle
from .models import TaskRecord, ValidationResult
class ValidationService:
async def validate_task_result(
self,
*,
task: TaskRecord,
user_message: str,
final_output: str,
transcript_excerpt: str = "",
tool_summaries: list[str] | None = None,
team_summaries: list[str] | None = None,
provider_bundle: ProviderBundle | None = None,
) -> ValidationResult:
provider = None
model = None
if provider_bundle is not None:
provider = provider_bundle.auxiliary_provider or provider_bundle.main_provider
runtime = provider_bundle.auxiliary_runtime or provider_bundle.main_runtime
model = getattr(runtime, "model", None)
if provider is not None:
try:
return await self._validate_with_provider(
provider=provider,
model=model,
task=task,
user_message=user_message,
final_output=final_output,
transcript_excerpt=transcript_excerpt,
tool_summaries=tool_summaries or [],
team_summaries=team_summaries or [],
)
except Exception as exc:
return ValidationResult(
passed=False,
score=0.0,
issues=[f"Validator failed: {exc}"],
missing_requirements=["A valid automatic validation result is required before accepting the task."],
recommended_revision_prompt=(
"Review the task result again because automatic validation failed, "
"then provide a corrected final answer that explicitly satisfies the task goal."
),
validator="llm_error",
)
return self._heuristic_validate(final_output)
async def _validate_with_provider(
self,
*,
provider: Any,
model: str | None,
task: TaskRecord,
user_message: str,
final_output: str,
transcript_excerpt: str,
tool_summaries: list[str],
team_summaries: list[str],
) -> ValidationResult:
prompt = (
"Validate whether the assistant output satisfies the task. "
"Return only compact JSON with keys: passed, score, issues, "
"missing_requirements, recommended_revision_prompt.\n\n"
f"Task goal:\n{task.goal}\n\n"
f"Current user request:\n{user_message}\n\n"
f"Transcript excerpt:\n{transcript_excerpt[:2500]}\n\n"
f"Tool summaries:\n{json.dumps(tool_summaries[:12], ensure_ascii=False)}\n\n"
f"Team summaries:\n{json.dumps(team_summaries[:12], ensure_ascii=False)}\n\n"
f"Assistant final output:\n{final_output[:4000]}"
)
response = await provider.chat(
messages=[
{"role": "system", "content": "You are a strict task result validator."},
{"role": "user", "content": prompt},
],
tools=None,
model=model,
max_tokens=4096,
temperature=0.0,
)
payload = self._parse_json_object(response.content or "")
return ValidationResult(
passed=bool(payload.get("passed")),
score=max(0.0, min(1.0, float(payload.get("score", 0.0) or 0.0))),
issues=[str(item) for item in payload.get("issues") or []],
missing_requirements=[str(item) for item in payload.get("missing_requirements") or []],
recommended_revision_prompt=str(payload.get("recommended_revision_prompt") or ""),
validator="llm",
)
@staticmethod
def _heuristic_validate(final_output: str) -> ValidationResult:
text = final_output.strip()
if not text:
return ValidationResult(
passed=False,
score=0.0,
issues=["Assistant output is empty."],
missing_requirements=["A non-empty result is required."],
recommended_revision_prompt="Produce a complete, non-empty answer for the task.",
validator="heuristic",
)
lowered = text.lower()
if "run failed before completion" in lowered or "tool loop stopped" in lowered:
return ValidationResult(
passed=False,
score=0.35,
issues=["The run did not complete cleanly."],
missing_requirements=["A successful final result is required."],
recommended_revision_prompt="Retry the task and address the failure before returning the final answer.",
validator="heuristic",
)
return ValidationResult(passed=True, score=0.85, validator="heuristic")
@staticmethod
def _parse_json_object(text: str) -> dict[str, Any]:
cleaned = text.strip()
if cleaned.startswith("```"):
cleaned = cleaned.strip("`")
if cleaned.lower().startswith("json"):
cleaned = cleaned[4:].strip()
start = cleaned.find("{")
end = cleaned.rfind("}")
if start >= 0 and end >= start:
cleaned = cleaned[start : end + 1]
payload = json.loads(cleaned)
if not isinstance(payload, dict):
raise ValueError("validator response must be a JSON object")
return payload

View File

@ -51,7 +51,7 @@ class WebFetchTool:
try:
safe_url = _safe_url(url)
limit = max(1000, min(int(max_chars or 12000), 50000))
async with httpx.AsyncClient(timeout=20, follow_redirects=True, trust_env=False) as client:
async with httpx.AsyncClient(timeout=20, follow_redirects=True, trust_env=True) as client:
response = await client.get(
safe_url,
headers={"User-Agent": "Mozilla/5.0 Beaver/1.0"},
@ -96,7 +96,7 @@ class WebSearchTool:
raise ValueError("query is required")
bounded = max(1, min(int(limit or 5), 10))
url = f"https://duckduckgo.com/html/?q={quote_plus(query)}"
async with httpx.AsyncClient(timeout=20, follow_redirects=True, trust_env=False) as client:
async with httpx.AsyncClient(timeout=20, follow_redirects=True, trust_env=True) as client:
response = await client.get(url, headers={"User-Agent": "Mozilla/5.0 Beaver/1.0"})
response.raise_for_status()
html = response.text

View File

@ -886,11 +886,9 @@ tool_hints:
<div class="panel">
<h3>Beaver 平台部署层</h3>
<ul>
<li><span class="code">auth-portal</span>:用户入口、登录注册</li>
<li><span class="code">authz-service</span>授权服务和后端身份</li>
<li><span class="code">deploy-control</span>:创建和管理单用户实例</li>
<li><span class="code">router-proxy</span>:按 Host 转发到实例。</li>
<li>每个用户一个 <span class="code">app-instance</span>Docker 容器隔离 + per-instance workspace。</li>
<li><span class="code">Keycloak OIDC</span>:用户入口、SSO 登录与登出</li>
<li><span class="code">app-instance</span>单体应用容器,内置前端、后端和 Nginx</li>
<li>外部编排系统负责部署和访问入口,当前应用不维护实例注册表</li>
</ul>
</div>
<div class="panel">

View File

@ -13,6 +13,7 @@ dependencies = [
"litellm>=1.79.0,<2.0.0",
"minio>=7.2.0,<8.0.0",
"openai>=1.79.0,<2.0.0",
"PyJWT[crypto]>=2.9.0,<3.0.0",
"pydantic>=2.12.0,<3.0.0",
"python-multipart>=0.0.20,<1.0.0",
"typer>=0.20.0,<1.0.0",
@ -22,6 +23,24 @@ dependencies = [
[project.optional-dependencies]
dev = [
"pytest>=9.0.0,<10.0.0",
"pytest-asyncio>=1.0.0,<2.0.0",
]
telegram = [
"python-telegram-bot>=22.0,<23.0",
]
feishu = [
"lark-oapi>=1.4.22,<2.0.0",
]
qqbot = [
"aiohttp>=3.9.0,<4.0.0",
]
weixin = [
"aiohttp>=3.9.0,<4.0.0",
]
channels = [
"python-telegram-bot>=22.0,<23.0",
"lark-oapi>=1.4.22,<2.0.0",
"aiohttp>=3.9.0,<4.0.0",
]
[project.scripts]

View File

@ -0,0 +1,47 @@
import asyncio
from contextlib import suppress
from typing import Any
from beaver.engine import AgentLoop, AgentRunResult, EngineLoader
def _run_result(run_id: str, output_text: str) -> AgentRunResult:
return AgentRunResult(
session_id="web:test",
run_id=run_id,
output_text=output_text,
finish_reason="stop",
tool_iterations=0,
)
def test_running_loop_handles_reentrant_submit_direct(tmp_path) -> None:
async def run_case() -> None:
loop = AgentLoop(loader=EngineLoader(workspace=tmp_path))
calls: list[str] = []
async def fake_process_direct(task: str, **kwargs: Any) -> AgentRunResult:
calls.append(task)
if task == "outer":
return await loop.submit_direct("inner", session_id="web:test")
return _run_result(task, "inner completed")
loop._process_direct_impl = fake_process_direct # type: ignore[method-assign]
loop_task = asyncio.create_task(loop.run())
await asyncio.sleep(0)
try:
result = await asyncio.wait_for(loop.submit_direct("outer", session_id="web:test"), timeout=1)
finally:
await loop.stop()
with suppress(asyncio.TimeoutError):
await asyncio.wait_for(loop_task, timeout=1)
if not loop_task.done():
loop_task.cancel()
with suppress(asyncio.CancelledError):
await loop_task
assert result.output_text == "inner completed"
assert calls == ["outer", "inner"]
asyncio.run(run_case())

View File

@ -0,0 +1,71 @@
from __future__ import annotations
from pathlib import Path
from types import SimpleNamespace
import pytest
from beaver.engine.loader import EngineLoader
from beaver.engine.loop import AgentLoop
from beaver.engine.providers.base import LLMProvider, LLMResponse, ToolCallRequest
from beaver.engine.providers.factory import ProviderBundle
from beaver.skills.learning.replay import ReplayToolExecutor, ReplayToolPolicy
class ToolCallingProvider(LLMProvider):
def __init__(self) -> None:
super().__init__()
self.calls = 0
async def chat(
self,
messages: list[dict],
tools: list[dict] | None = None,
model: str | None = None,
max_tokens: int | None = None,
temperature: float = 0.7,
thinking_enabled: bool | None = None,
) -> LLMResponse:
self.calls += 1
if self.calls == 1:
return LLMResponse(
content="",
tool_calls=[
ToolCallRequest(
id="call-1",
name="read_file",
arguments={"path": "README.md"},
)
],
)
return LLMResponse(content="done")
def get_default_model(self) -> str:
return "stub"
@pytest.mark.asyncio
async def test_process_direct_uses_replay_tool_executor(tmp_path: Path) -> None:
loop = AgentLoop(loader=EngineLoader(workspace=tmp_path))
loaded = loop.boot()
provider = ToolCallingProvider()
runtime = SimpleNamespace(model="stub", provider_name="stub")
replay_executor = ReplayToolExecutor(
loaded.tool_executor,
registry=loaded.tool_registry,
policy=ReplayToolPolicy(),
)
result = await loop.process_direct(
"Read the README.",
provider_bundle=ProviderBundle(main_runtime=runtime, main_provider=provider), # type: ignore[arg-type]
include_skill_assembly=False,
pinned_skill_names=[],
tool_executor_override=replay_executor,
max_tool_iterations=2,
source="skill_replay_eval",
)
assert result.output_text == "done"
assert replay_executor.traces
assert replay_executor.traces[0]["tool_name"] == "read_file"

View File

@ -1,5 +1,7 @@
from __future__ import annotations
import json
from beaver.coordinator.models import AgentDescriptor, ExecutionGraph, ExecutionNode
from beaver.coordinator.registry import AgentRegistry, RegisteredAgent, TargetResolver
from beaver.tasks import TaskRecord
@ -20,22 +22,64 @@ def _task() -> TaskRecord:
)
def test_registry_seeds_builtin_agents_and_filters_disabled(tmp_path) -> None:
def test_registry_starts_empty_and_filters_disabled(tmp_path) -> None:
registry = AgentRegistry(tmp_path)
assert {agent.agent_id for agent in registry.list_active_agents()} >= {
"researcher",
"implementer",
"reviewer",
"tester",
"documenter",
}
assert registry.list_agents() == []
registry.upsert_agent(
RegisteredAgent(
agent_id="tester",
name="tester",
display_name="Tester",
role="testing",
description="Runs checks.",
system_prompt="test",
)
)
registry.disable_agent("tester")
assert "tester" not in {agent.agent_id for agent in registry.list_active_agents()}
def test_registry_drops_legacy_builtin_agents(tmp_path) -> None:
registry_path = tmp_path / "agents" / "registry.json"
registry_path.parent.mkdir(parents=True)
registry_path.write_text(
json.dumps(
{
"version": 1,
"agents": [
{
"agent_id": "researcher",
"name": "researcher",
"display_name": "Researcher",
"role": "research",
"description": "legacy builtin",
"system_prompt": "research",
"source": "builtin",
},
{
"agent_id": "workspace-agent",
"name": "workspace-agent",
"display_name": "Workspace Agent",
"role": "workspace",
"description": "user configured",
"system_prompt": "work",
"source": "workspace",
},
],
}
)
+ "\n",
encoding="utf-8",
)
registry = AgentRegistry(tmp_path)
assert [agent.agent_id for agent in registry.list_agents()] == ["workspace-agent"]
def test_resolver_selects_registered_agent_by_role_and_capabilities(tmp_path) -> None:
registry = AgentRegistry(tmp_path)
registry.upsert_agent(
@ -88,4 +132,3 @@ def test_resolver_falls_back_to_ephemeral_agent_when_no_match(tmp_path) -> None:
assert resolved.nodes[0].agent.name == "rare"
assert resolved.nodes[0].agent.metadata["resolution"] == "fallback_ephemeral"
assert reports[0].fallback_used is True

View File

@ -45,6 +45,18 @@ class RecordingProvider(LLMProvider):
return "stub-model"
class BlockingProvider(RecordingProvider):
def __init__(self, content: str, started: asyncio.Event, release: asyncio.Event) -> None:
super().__init__([_response(content)])
self.started = started
self.release = release
async def chat(self, *args, **kwargs) -> LLMResponse:
self.started.set()
await self.release.wait()
return await super().chat(*args, **kwargs)
class StubSkillAssembler:
def __init__(self, activated_skills: list[SkillContext] | None = None) -> None:
self.activated_skills = list(activated_skills or [])
@ -153,6 +165,26 @@ def test_local_agent_runner_uses_shared_loop_and_records_parent_task(tmp_path: P
assert child_session["parent_session_id"] == "session-root"
def test_team_node_preserves_evidence_when_finish_reason_is_not_stop(tmp_path: Path) -> None:
loop = _loop(tmp_path)
provider = RecordingProvider([_response("partial evidence", finish_reason="max_tool_iterations")])
envelope = DelegationEnvelope(
parent_task_id="task-parent",
parent_session_id="session-root",
parent_run_id="run-root",
agent=AgentDescriptor(name="researcher", role="research"),
task="research the requested topic",
node_id="research",
)
result = asyncio.run(LocalAgentRunner(loop).run(envelope, provider_bundle=_bundle(provider)))
assert result.success is False
assert result.evidence is not None
assert result.evidence.output_text == "partial evidence"
assert result.evidence.finish_reason == "max_tool_iterations"
def test_pinned_skill_is_injected_into_delegated_run(tmp_path: Path) -> None:
_publish_skill(
tmp_path,
@ -278,6 +310,57 @@ def test_team_parallel_runs_all_nodes(tmp_path: Path) -> None:
assert [item.output_text for item in result.node_results] == ["one", "two", "three"]
def test_team_parallel_starts_nodes_concurrently_with_isolated_loops(tmp_path: Path) -> None:
loop = _loop(tmp_path)
first_started = asyncio.Event()
second_started = asyncio.Event()
release = asyncio.Event()
providers = {
"one": BlockingProvider("one", first_started, release),
"two": BlockingProvider("two", second_started, release),
}
graph = ExecutionGraph(
strategy="parallel",
nodes=[
ExecutionNode("one", "task one", AgentDescriptor(name="one")),
ExecutionNode("two", "task two", AgentDescriptor(name="two")),
],
)
async def run_case():
loop_task = asyncio.create_task(loop.run())
await asyncio.sleep(0)
task = asyncio.create_task(
TeamService(loop).run_team(
graph,
parent_task_id=None,
parent_session_id="session-root",
parent_run_id="run-root",
provider_bundle_factory=lambda node: _bundle(providers[node.node_id]),
)
)
try:
await asyncio.wait_for(first_started.wait(), timeout=1)
await asyncio.wait_for(second_started.wait(), timeout=1)
release.set()
return await task
finally:
release.set()
if not task.done():
task.cancel()
try:
await task
except asyncio.CancelledError:
pass
await loop.stop()
await loop_task
result = asyncio.run(run_case())
assert result.success is True
assert [item.node_id for item in result.node_results] == ["one", "two"]
def test_parallel_node_factory_error_is_normalized_and_keeps_completed_runs(tmp_path: Path) -> None:
loop = _loop(tmp_path)
loaded = loop.boot()
@ -438,7 +521,7 @@ def test_team_summary_lists_only_failed_nodes_when_all_nodes_fail(tmp_path: Path
)
assert result.success is False
assert result.summary == "Failed nodes:\n- one: one down\n- two: two down"
assert result.summary == "Failed nodes:\n- one: one down evidence=no\n- two: two down evidence=no"
def test_graph_structure_errors_still_raise(tmp_path: Path) -> None:

View File

@ -0,0 +1,84 @@
from __future__ import annotations
from fastapi.testclient import TestClient
from beaver.interfaces.web.app import create_app
from beaver.services.agent_service import AgentService
def test_channel_connection_api_creates_updates_lists_and_revokes(tmp_path) -> None:
config_path = tmp_path / "config.json"
config_path.write_text(
'{"agents": {"defaults": {"workspace": "%s"}}, "providers": {}}' % str(tmp_path),
encoding="utf-8",
)
service = AgentService(config_path=config_path)
app = create_app(service=service, manage_service_lifecycle=False)
try:
with TestClient(app) as client:
created = client.post(
"/api/channel-connections",
json={
"kind": "telegram",
"mode": "polling",
"displayName": "Telegram Main",
"authType": "token",
"secrets": {"botToken": "token-1"},
"config": {"maxMessageChars": 4096, "requireMentionInGroups": True},
},
)
assert created.status_code == 200
body = created.json()
connection_id = body["connection"]["connection_id"]
assert body["connection"]["kind"] == "telegram"
assert body["connection"]["status"] == "draft"
assert "credentials_ref" not in body["connection"]
assert body["connection"]["runtime_config"] == {
"max_message_chars": 4096,
"require_mention_in_groups": True,
}
assert body["credentials"] == {"botToken": "***"}
patched = client.patch(
f"/api/channel-connections/{connection_id}",
json={
"displayName": "Telegram Ops",
"config": {"maxMessageChars": 2048},
"secrets": {"botToken": "token-2"},
},
)
assert patched.status_code == 200
assert patched.json()["connection"]["display_name"] == "Telegram Ops"
assert patched.json()["connection"]["runtime_config"] == {"max_message_chars": 2048}
assert patched.json()["credentials"] == {"botToken": "***"}
listed = client.get("/api/channel-connections")
assert listed.status_code == 200
assert listed.json()[0]["connection_id"] == connection_id
assert "credentials_ref" not in listed.json()[0]
revoked = client.post(f"/api/channel-connections/{connection_id}/revoke")
assert revoked.status_code == 200
assert revoked.json()["connection"]["status"] == "revoked"
finally:
service.close()
def test_channel_connectors_api_lists_registered_connectors(tmp_path) -> None:
config_path = tmp_path / "config.json"
config_path.write_text(
'{"agents": {"defaults": {"workspace": "%s"}}, "providers": {}}' % str(tmp_path),
encoding="utf-8",
)
service = AgentService(config_path=config_path)
app = create_app(service=service, manage_service_lifecycle=False)
try:
with TestClient(app) as client:
response = client.get("/api/channel-connectors")
finally:
service.close()
assert response.status_code == 200
assert response.json() == [{"kind": "feishu"}, {"kind": "telegram"}, {"kind": "weixin"}]

View File

@ -0,0 +1,63 @@
from __future__ import annotations
from beaver.interfaces.channels.connections import (
ChannelConnectionStore,
CredentialStore,
PairingTokenStore,
)
def test_channel_connection_store_creates_updates_lists_and_revokes(tmp_path) -> None:
store = ChannelConnectionStore(tmp_path / "connections.json")
created = store.create(
kind="telegram",
mode="polling",
display_name="Telegram Main",
account_id="telegram:bot-main",
owner_user_id="user-1",
auth_type="token",
runtime_config={"max_message_chars": 4096},
capabilities=["receive_text", "send_text"],
)
updated = store.update_status(created.connection_id, status="connected", last_error=None)
revoked = store.revoke(created.connection_id)
assert created.connection_id
assert created.channel_id.startswith("telegram-")
assert created.status == "draft"
assert updated.status == "connected"
assert revoked.status == "revoked"
assert store.get(created.connection_id).status == "revoked"
assert [item.connection_id for item in store.list()] == [created.connection_id]
def test_credential_store_saves_values_by_reference_and_redacts_views(tmp_path) -> None:
store = CredentialStore(tmp_path / "credentials.json")
ref = store.put(kind="telegram", values={"botToken": "secret-token", "empty": ""})
assert ref.startswith("cred_")
assert store.get(ref) == {"botToken": "secret-token"}
assert store.redacted(ref) == {"botToken": "***"}
def test_pairing_token_store_uses_one_time_expiring_tokens(tmp_path) -> None:
store = PairingTokenStore(tmp_path / "pairing.json")
session = store.create(kind="terminal", ttl_seconds=60, scope="channel:pair")
consumed = store.consume(session.token, expected_kind="terminal")
reused = store.consume(session.token, expected_kind="terminal")
assert session.status == "pending"
assert consumed is not None
assert consumed.status == "consumed"
assert reused is None
def test_pairing_token_store_rejects_expired_tokens(tmp_path) -> None:
store = PairingTokenStore(tmp_path / "pairing.json")
session = store.create(kind="weixin", ttl_seconds=-1, scope="channel:pair")
assert store.consume(session.token, expected_kind="weixin") is None

View File

@ -0,0 +1,164 @@
from __future__ import annotations
import asyncio
from beaver.foundation.config.schema import ChannelConfig
from beaver.interfaces.channels.connections import (
ChannelConnectionStore,
ChannelConnectorRegistry,
ChannelRuntimeSpec,
CredentialStore,
ValidationResult,
)
class FakeConnector:
kind = "fake"
def __init__(self) -> None:
self.validated: list[str] = []
self.revoked: list[str] = []
async def validate(self, connection_id: str) -> ValidationResult:
self.validated.append(connection_id)
return ValidationResult(ok=True, status="connected", account_id="fake-account", display_name="Fake")
async def materialize_runtime(self, connection_id: str) -> ChannelRuntimeSpec:
return ChannelRuntimeSpec(
channel_id="fake-channel",
kind="fake",
mode="webhook",
account_id="fake-account",
display_name="Fake",
config={"enabled": True},
)
async def revoke(self, connection_id: str) -> None:
self.revoked.append(connection_id)
return None
def test_connector_registry_dispatches_by_kind(tmp_path) -> None:
async def run() -> None:
connection_store = ChannelConnectionStore(tmp_path / "connections.json")
credential_store = CredentialStore(tmp_path / "credentials.json")
connector = FakeConnector()
registry = ChannelConnectorRegistry(connection_store=connection_store, credential_store=credential_store)
registry.register(connector)
connection = connection_store.create(
kind="fake",
mode="webhook",
display_name="Fake",
account_id="fake-account",
owner_user_id=None,
auth_type="token",
)
result = await registry.validate(connection.connection_id)
spec = await registry.materialize_runtime(connection.connection_id)
assert result.ok is True
assert connector.validated == [connection.connection_id]
assert spec.channel_id == "fake-channel"
asyncio.run(run())
def test_connector_registry_materializes_channel_configs_with_credentials(tmp_path) -> None:
async def run() -> None:
connection_store = ChannelConnectionStore(tmp_path / "connections.json")
credential_store = CredentialStore(tmp_path / "credentials.json")
credentials_ref = credential_store.put(kind="telegram", values={"botToken": "token-1"})
connection = connection_store.create(
kind="fake",
mode="webhook",
display_name="Connected",
account_id="connected",
owner_user_id=None,
auth_type="token",
credentials_ref=credentials_ref,
)
connection_store.update_status(connection.connection_id, status="connected", last_error=None)
class CredentialAwareConnector(FakeConnector):
async def materialize_runtime(self, connection_id: str) -> ChannelRuntimeSpec:
stored = connection_store.get(connection_id)
return ChannelRuntimeSpec(
channel_id="fake-channel",
kind="fake",
mode="webhook",
account_id="fake-account",
display_name="Fake",
config={"enabled": True},
secrets_ref=stored.credentials_ref,
)
registry = ChannelConnectorRegistry(connection_store=connection_store, credential_store=credential_store)
registry.register(CredentialAwareConnector())
configs = await registry.materialize_channel_configs()
assert isinstance(configs["fake-channel"], ChannelConfig)
assert configs["fake-channel"].enabled is True
assert configs["fake-channel"].secrets == {"botToken": "token-1"}
asyncio.run(run())
def test_connector_registry_materializes_only_connected_connections(tmp_path) -> None:
async def run() -> None:
connection_store = ChannelConnectionStore(tmp_path / "connections.json")
credential_store = CredentialStore(tmp_path / "credentials.json")
registry = ChannelConnectorRegistry(connection_store=connection_store, credential_store=credential_store)
registry.register(FakeConnector())
draft = connection_store.create(
kind="fake",
mode="webhook",
display_name="Draft",
account_id="draft",
owner_user_id=None,
auth_type="token",
)
connected = connection_store.create(
kind="fake",
mode="webhook",
display_name="Connected",
account_id="connected",
owner_user_id=None,
auth_type="token",
)
connection_store.update_status(connected.connection_id, status="connected", last_error=None)
specs = await registry.materialize_connected_runtime_specs()
assert [spec.channel_id for spec in specs] == ["fake-channel"]
assert connection_store.get(draft.connection_id).status == "draft"
asyncio.run(run())
def test_connector_registry_revoke_calls_connector_and_updates_store(tmp_path) -> None:
async def run() -> None:
connection_store = ChannelConnectionStore(tmp_path / "connections.json")
credential_store = CredentialStore(tmp_path / "credentials.json")
connector = FakeConnector()
registry = ChannelConnectorRegistry(connection_store=connection_store, credential_store=credential_store)
registry.register(connector)
connection = connection_store.create(
kind="fake",
mode="webhook",
display_name="Fake",
account_id="fake-account",
owner_user_id=None,
auth_type="token",
)
connection_store.update_status(connection.connection_id, status="connected", last_error=None)
await registry.revoke(connection.connection_id)
assert connector.revoked == [connection.connection_id]
assert connection_store.get(connection.connection_id).status == "revoked"
asyncio.run(run())

View File

@ -0,0 +1,414 @@
import asyncio
import json
from fastapi.testclient import TestClient
from beaver.foundation.config.schema import ChannelConfig
from beaver.foundation.events import ChannelIdentity, InboundMessage, OutboundMessage
from beaver.foundation.events import MessageBus
from beaver.interfaces.channels.generic_webhook import GenericWebhookAdapter
from beaver.interfaces.channels.runtime import ChannelRuntime
from beaver.interfaces.channels.state import ChannelDedupeStore, ChannelEventLog
from beaver.interfaces.web.app import _self_restart_enabled, create_app
from beaver.services.agent_service import AgentService
def test_channel_identity_builds_stable_session_id() -> None:
identity = ChannelIdentity(
channel_id="webhook-dev",
kind="webhook",
account_id="local",
peer_id="demo-user",
thread_id="main",
peer_type="dm",
message_id="msg-1",
)
assert identity.session_id() == "webhook-dev:local:demo-user:main"
assert identity.dedupe_key() == "webhook-dev:local:demo-user:main:msg-1"
def test_channel_identity_requires_routing_fields() -> None:
identity = ChannelIdentity(channel_id="webhook-dev", kind="webhook", account_id="", peer_id="demo")
assert identity.validation_error() == "account_id is required"
def test_messages_carry_channel_identity() -> None:
identity = ChannelIdentity(
channel_id="webhook-dev",
kind="webhook",
account_id="local",
peer_id="demo-user",
message_id="msg-1",
)
inbound = InboundMessage(channel="webhook-dev", content="hello", channel_identity=identity)
outbound = OutboundMessage(
channel="webhook-dev",
content="ok",
session_id=identity.session_id(),
finish_reason="stop",
channel_identity=identity,
)
assert inbound.channel_identity is identity
assert outbound.channel_identity is identity
def test_dedupe_store_tracks_processing_and_done(tmp_path) -> None:
store = ChannelDedupeStore(tmp_path / "dedupe.json", retention_hours=48)
created = store.mark_processing(
dedupe_key="webhook-dev:local:demo:msg-1",
session_id="webhook-dev:local:demo",
message_id="msg-1",
)
duplicate = store.mark_processing(
dedupe_key="webhook-dev:local:demo:msg-1",
session_id="webhook-dev:local:demo",
message_id="msg-1",
)
assert created.created is True
assert duplicate.created is False
assert duplicate.record is not None
assert duplicate.record["status"] == "processing"
store.mark_done(
dedupe_key="webhook-dev:local:demo:msg-1",
run_id="run-1",
reply="hello" * 10000,
max_reply_chars=20,
)
done = store.get("webhook-dev:local:demo:msg-1")
assert done is not None
assert done["status"] == "done"
assert done["reply"] == "hellohellohellohello"
def test_channel_event_log_writes_recent_events(tmp_path) -> None:
log = ChannelEventLog(tmp_path / "events.jsonl")
log.record(
channel_id="webhook-dev",
kind="inbound_accepted",
session_id="webhook-dev:local:demo",
message_id="msg-1",
status="ok",
text="hello world",
)
events = log.recent(channel_id="webhook-dev", limit=10)
assert len(events) == 1
assert events[0]["kind"] == "inbound_accepted"
assert events[0]["text_preview"] == "hello world"
assert "raw_channel_payload" not in json.dumps(events[0])
class FakeAgentService:
is_running = True
async def handle_inbound_message(self, inbound):
return OutboundMessage(
message_id=inbound.message_id,
channel=inbound.channel,
content=f"echo:{inbound.content}",
session_id=inbound.session_id,
finish_reason="stop",
run_id="run-1",
channel_identity=inbound.channel_identity,
)
class SlowFakeAgentService(FakeAgentService):
async def handle_inbound_message(self, inbound):
await asyncio.sleep(0.05)
return await super().handle_inbound_message(inbound)
def test_channel_runtime_accept_inbound_normalizes_session_and_dedupes(tmp_path) -> None:
async def run() -> None:
bus = MessageBus()
runtime = ChannelRuntime(
service=FakeAgentService(),
bus=bus,
workspace=tmp_path,
channels={},
)
identity = ChannelIdentity(
channel_id="webhook-dev",
kind="webhook",
account_id="local",
peer_id="demo",
message_id="msg-1",
)
result = await runtime.accept_inbound(
InboundMessage(
channel="webhook-dev",
content="hello",
session_id="wrong",
channel_identity=identity,
)
)
duplicate = await runtime.accept_inbound(
InboundMessage(
channel="webhook-dev",
content="hello",
channel_identity=identity,
)
)
queued = await bus.consume_inbound()
assert result.accepted is True
assert queued.session_id == "webhook-dev:local:demo"
assert duplicate.accepted is False
assert duplicate.duplicate is True
asyncio.run(run())
def test_generic_webhook_adapter_waits_for_outbound_reply(tmp_path) -> None:
async def run() -> None:
bus = MessageBus()
runtime = ChannelRuntime(
service=FakeAgentService(),
bus=bus,
workspace=tmp_path,
channels={},
)
adapter = GenericWebhookAdapter(
channel_id="webhook-dev",
kind="webhook",
mode="webhook",
account_id="local",
display_name="Webhook Dev",
inbound_sink=runtime,
response_timeout_seconds=1,
)
runtime.manager.register(adapter)
await runtime.start()
try:
response = await adapter.handle_webhook_payload(
{
"peer_id": "demo",
"message_id": "msg-1",
"text": "hello",
"peer_type": "dm",
}
)
finally:
await runtime.stop()
assert response["ok"] is True
assert response["reply"] == "echo:hello"
assert response["session_id"] == "webhook-dev:local:demo"
asyncio.run(run())
def test_generic_webhook_records_unclaimed_outbound_after_timeout(tmp_path) -> None:
async def run() -> None:
bus = MessageBus()
runtime = ChannelRuntime(
service=SlowFakeAgentService(),
bus=bus,
workspace=tmp_path,
channels={},
)
adapter = GenericWebhookAdapter(
channel_id="webhook-dev",
kind="webhook",
mode="webhook",
account_id="local",
display_name="Webhook Dev",
inbound_sink=runtime,
response_timeout_seconds=1,
)
adapter.response_timeout_seconds = 0.01
runtime.manager.register(adapter)
await runtime.start()
try:
response = await adapter.handle_webhook_payload(
{
"peer_id": "demo",
"message_id": "msg-1",
"text": "hello",
"peer_type": "dm",
}
)
await asyncio.sleep(0.1)
events = runtime.recent_events("webhook-dev", limit=20)
finally:
await runtime.stop()
assert response["pending"] is True
assert any(event["kind"] == "outbound_unclaimed" for event in events)
asyncio.run(run())
def test_channel_runtime_starts_enabled_generic_webhook_and_reports_status(tmp_path) -> None:
async def run() -> None:
runtime = ChannelRuntime(
service=FakeAgentService(),
workspace=tmp_path,
channels={
"webhook-dev": ChannelConfig(
enabled=True,
kind="webhook",
mode="webhook",
account_id="local",
display_name="Webhook Dev",
config={"response_timeout_seconds": 1800},
),
"off": ChannelConfig(
enabled=False,
kind="webhook",
mode="webhook",
account_id="local",
),
},
)
await runtime.start()
try:
statuses = runtime.statuses()
finally:
await runtime.stop()
by_id = {item["channel_id"]: item for item in statuses}
assert by_id["webhook-dev"]["state"] == "running"
assert by_id["webhook-dev"]["webhook_url"] == "/api/channels/webhook-dev/webhook"
assert by_id["off"]["state"] == "disabled"
asyncio.run(run())
def test_channel_runtime_builds_platform_adapters_without_starting_networks(tmp_path) -> None:
runtime = ChannelRuntime(
service=FakeAgentService(),
workspace=tmp_path,
channels={},
)
cases = {
"telegram-main": ChannelConfig(enabled=True, kind="telegram", mode="polling", account_id="bot-main"),
"feishu-main": ChannelConfig(enabled=True, kind="feishu", mode="websocket", account_id="tenant-main"),
"qq-main": ChannelConfig(enabled=True, kind="qqbot", mode="websocket", account_id="qq-main"),
"weixin-main": ChannelConfig(enabled=True, kind="weixin", mode="polling", account_id="wx-main"),
}
for channel_id, cfg in cases.items():
adapter = runtime._build_adapter(channel_id, cfg)
assert adapter.channel_id == channel_id
assert adapter.kind == cfg.kind
assert adapter.mode == cfg.mode
def test_channel_runtime_reports_platform_capabilities(tmp_path) -> None:
runtime = ChannelRuntime(
service=FakeAgentService(),
workspace=tmp_path,
channels={
"telegram-main": ChannelConfig(enabled=True, kind="telegram", mode="polling", account_id="bot-main"),
"weixin-main": ChannelConfig(enabled=True, kind="weixin", mode="polling", account_id="wx-main"),
},
)
by_id = {item["channel_id"]: item for item in runtime.statuses()}
assert by_id["telegram-main"]["capabilities"] == [
"receive_text",
"send_text",
"receive_media",
"groups",
]
assert by_id["weixin-main"]["capabilities"] == [
"receive_text",
"send_text",
"receive_media",
"direct_messages",
]
def test_channel_runtime_platform_start_failure_does_not_stop_other_channels(tmp_path) -> None:
async def run() -> None:
runtime = ChannelRuntime(
service=FakeAgentService(),
workspace=tmp_path,
channels={
"telegram-main": ChannelConfig(
enabled=True,
kind="telegram",
mode="polling",
account_id="bot-main",
secrets={},
),
"off": ChannelConfig(
enabled=False,
kind="weixin",
mode="polling",
account_id="wx-main",
),
},
)
await runtime.start()
try:
by_id = {item["channel_id"]: item for item in runtime.statuses()}
finally:
await runtime.stop()
assert by_id["telegram-main"]["state"] == "error"
assert "botToken" in by_id["telegram-main"]["last_error"]
assert by_id["off"]["state"] == "disabled"
asyncio.run(run())
def test_web_app_status_exposes_configured_channel(tmp_path) -> None:
config_path = tmp_path / "config.json"
workspace = tmp_path / "workspace"
workspace.mkdir()
config_path.write_text(
json.dumps(
{
"agents": {"defaults": {"workspace": str(workspace), "model": "openai/gpt-5"}},
"providers": {},
"channels": {
"webhook-dev": {
"enabled": True,
"kind": "webhook",
"mode": "webhook",
"accountId": "local",
"displayName": "Webhook Dev",
}
},
}
),
encoding="utf-8",
)
service = AgentService(config_path=config_path)
app = create_app(service=service, manage_service_lifecycle=False)
with TestClient(app) as client:
payload = client.get("/api/status").json()
service.close()
assert payload["channels"][0]["channel_id"] == "webhook-dev"
assert payload["channels"][0]["state"] == "running"
assert payload["channels"][0]["webhook_url"] == "/api/channels/webhook-dev/webhook"
assert payload["runtime_controls"]["self_restart"] is True
def test_self_restart_env_defaults_enabled(monkeypatch) -> None:
monkeypatch.delenv("BEAVER_ENABLE_SELF_RESTART", raising=False)
assert _self_restart_enabled() is True
def test_self_restart_env_can_disable(monkeypatch) -> None:
monkeypatch.setenv("BEAVER_ENABLE_SELF_RESTART", "0")
assert _self_restart_enabled() is False

View File

@ -0,0 +1,119 @@
from __future__ import annotations
import asyncio
from beaver.foundation.config.schema import ChannelConfig
from beaver.foundation.events import MessageBus, OutboundMessage
from beaver.interfaces.channels.runtime import ChannelRuntime
class FakeService:
async def handle_inbound_message(self, inbound):
return OutboundMessage(channel=inbound.channel, content="ok", session_id=inbound.session_id, finish_reason="stop")
def test_runtime_add_channel_starts_new_channel_after_runtime_start(tmp_path) -> None:
async def run() -> None:
runtime = ChannelRuntime(service=FakeService(), workspace=tmp_path, channels={}, bus=MessageBus())
await runtime.start()
try:
await runtime.add_channel(
"webhook-dev",
ChannelConfig(enabled=True, kind="webhook", mode="webhook", account_id="acct"),
)
assert "webhook-dev" in runtime.adapters
assert runtime.states["webhook-dev"]["state"] == "running"
finally:
await runtime.stop()
asyncio.run(run())
def test_runtime_add_channel_noops_for_same_config(tmp_path) -> None:
async def run() -> None:
cfg = ChannelConfig(enabled=True, kind="webhook", mode="webhook", account_id="acct")
runtime = ChannelRuntime(service=FakeService(), workspace=tmp_path, channels={}, bus=MessageBus())
await runtime.start()
try:
await runtime.add_channel("webhook-dev", cfg)
first = runtime.adapters["webhook-dev"]
await runtime.add_channel("webhook-dev", cfg)
assert runtime.adapters["webhook-dev"] is first
finally:
await runtime.stop()
asyncio.run(run())
def test_runtime_replacement_failure_keeps_old_channel(tmp_path) -> None:
async def run() -> None:
good = ChannelConfig(enabled=True, kind="webhook", mode="webhook", account_id="acct")
bad = ChannelConfig(enabled=True, kind="missing", mode="http", account_id="acct")
runtime = ChannelRuntime(service=FakeService(), workspace=tmp_path, channels={}, bus=MessageBus())
await runtime.start()
try:
await runtime.add_channel("webhook-dev", good)
old = runtime.adapters["webhook-dev"]
try:
await runtime.add_channel("webhook-dev", bad)
except ValueError:
pass
else:
raise AssertionError("Expected ValueError")
assert runtime.adapters["webhook-dev"] is old
assert runtime.channel_configs["webhook-dev"] == good
assert runtime.states["webhook-dev"]["state"] == "running"
finally:
await runtime.stop()
asyncio.run(run())
def test_runtime_remove_channel_stops_and_unregisters(tmp_path) -> None:
async def run() -> None:
runtime = ChannelRuntime(service=FakeService(), workspace=tmp_path, channels={}, bus=MessageBus())
await runtime.start()
try:
await runtime.add_channel(
"webhook-dev",
ChannelConfig(enabled=True, kind="webhook", mode="webhook", account_id="acct"),
)
await runtime.remove_channel("webhook-dev")
assert "webhook-dev" not in runtime.adapters
assert "webhook-dev" not in runtime.manager.channels
assert runtime.states["webhook-dev"]["state"] == "removed"
finally:
await runtime.stop()
asyncio.run(run())
def test_runtime_builds_external_connector_channel(tmp_path, monkeypatch) -> None:
async def run() -> None:
monkeypatch.setenv("EXTERNAL_CONNECTOR_TOKEN", "connector-token")
runtime = ChannelRuntime(service=FakeService(), workspace=tmp_path, channels={}, bus=MessageBus())
await runtime.start()
try:
await runtime.add_channel(
"weixin-main",
ChannelConfig(
enabled=True,
kind="external_connector",
mode="http",
account_id="weixin:me",
display_name="Weixin Main",
config={
"platformKind": "weixin",
"connectionId": "conn_1",
"sidecarBaseUrl": "http://external-connector:8787",
},
),
)
adapter = runtime.adapters["weixin-main"]
assert adapter.kind == "external_connector"
assert adapter.mode == "http"
assert getattr(adapter, "platform_kind") == "weixin"
finally:
await runtime.stop()
asyncio.run(run())

View File

@ -1,9 +1,14 @@
import json
import asyncio
from fastapi.testclient import TestClient
from beaver.engine import AgentLoop, EngineLoader
from beaver.engine.providers import make_provider_bundle
from beaver.engine.providers.litellm import LiteLLMProvider
from beaver.foundation.config import load_config
from beaver.interfaces.web.app import create_app, _reload_agent_config
from beaver.services.agent_service import AgentService
def test_load_config_reads_current_instance_shape(tmp_path) -> None:
@ -42,6 +47,44 @@ def test_load_config_reads_current_instance_shape(tmp_path) -> None:
assert target["extra_headers"] == {"X-Test": "1"}
def test_config_loader_reads_channels(tmp_path) -> None:
config_path = tmp_path / "config.json"
config_path.write_text(
json.dumps(
{
"agents": {"defaults": {"model": "openai/gpt-5"}},
"channels": {
"webhook-dev": {
"enabled": True,
"kind": "webhook",
"mode": "webhook",
"accountId": "local",
"displayName": "Webhook Dev",
"config": {
"responseTimeoutSeconds": 1800,
"dedupeRetentionHours": 48,
},
"secrets": {"ignored_for_status": "secret-value"},
}
},
}
),
encoding="utf-8",
)
config = load_config(config_path=config_path)
channel = config.channels["webhook-dev"]
assert channel.enabled is True
assert channel.kind == "webhook"
assert channel.mode == "webhook"
assert channel.account_id == "local"
assert channel.display_name == "Webhook Dev"
assert channel.config["response_timeout_seconds"] == 1800
assert channel.config["dedupe_retention_hours"] == 48
assert channel.secrets == {"ignored_for_status": "secret-value"}
def test_provider_resolution_ignores_custom_and_disabled_overrides(tmp_path) -> None:
config_path = tmp_path / "config.json"
config_path.write_text(
@ -124,6 +167,236 @@ def test_agent_loop_config_drives_provider_bundle(tmp_path) -> None:
loop.close()
def test_reload_agent_config_updates_booted_loop_config(tmp_path) -> None:
workspace = tmp_path / "workspace"
config_path = tmp_path / "config.json"
config_path.write_text(
json.dumps(
{
"agents": {"defaults": {"workspace": str(workspace), "model": "old-model"}},
"providers": {"openai": {"apiKey": "sk-test", "apiBase": "https://old.example.com/v1"}},
}
),
encoding="utf-8",
)
service = AgentService(config_path=config_path)
loaded = service.create_loop().boot()
assert loaded.config.default_model == "old-model"
config_path.write_text(
json.dumps(
{
"agents": {"defaults": {"workspace": str(workspace), "model": "new-model"}},
"providers": {"openai": {"apiKey": "sk-test", "apiBase": "https://new.example.com/v1"}},
}
),
encoding="utf-8",
)
_reload_agent_config(service, config_path)
target = service.create_loop().boot().config.resolve_provider_target()
assert target["model"] == "new-model"
assert target["api_base"] == "https://new.example.com/v1"
assert target["api_key"] == "sk-test"
service.close()
def test_reload_agent_config_keeps_running_service_when_old_mcp_close_fails(tmp_path) -> None:
async def run_case() -> None:
workspace = tmp_path / "workspace"
config_path = tmp_path / "config.json"
config_path.write_text(
json.dumps(
{
"agents": {"defaults": {"workspace": str(workspace), "model": "old-model"}},
"providers": {"openai": {"apiKey": "sk-test", "apiBase": "https://old.example.com/v1"}},
}
),
encoding="utf-8",
)
service = AgentService(config_path=config_path)
await service.start()
class FailingMCPManager:
async def close(self) -> None:
raise RuntimeError("Attempted to exit cancel scope in a different task than it was entered in")
loaded = service.create_loop().boot()
loaded.mcp_manager = FailingMCPManager()
config_path.write_text(
json.dumps(
{
"agents": {"defaults": {"workspace": str(workspace), "model": "new-model"}},
"providers": {"openai": {"apiKey": "sk-test", "apiBase": "https://new.example.com/v1"}},
}
),
encoding="utf-8",
)
loop = asyncio.get_running_loop()
unhandled: list[dict[str, object]] = []
previous_handler = loop.get_exception_handler()
loop.set_exception_handler(lambda _loop, context: unhandled.append(context))
try:
_reload_agent_config(service, config_path)
await asyncio.sleep(0)
target = service.create_loop().boot().config.resolve_provider_target()
assert service.is_running is True
assert target["model"] == "new-model"
assert target["api_base"] == "https://new.example.com/v1"
assert unhandled == []
finally:
loop.set_exception_handler(previous_handler)
await service.shutdown(force=True)
asyncio.run(run_case())
def test_agent_defaults_include_runtime_controls(tmp_path) -> None:
config_path = tmp_path / "config.json"
config_path.write_text(
json.dumps(
{
"agents": {
"defaults": {
"maxTokens": 12345,
"temperature": 0.4,
"maxToolIterations": 9,
}
}
}
),
encoding="utf-8",
)
config = load_config(config_path=config_path)
service = AgentService(config_path=config_path)
assert config.agents_defaults.max_tokens == 12345
assert config.agents_defaults.temperature == 0.4
assert config.agents_defaults.max_tool_iterations == 9
assert service.profile.max_tokens == 12345
assert service.profile.temperature == 0.4
assert service.profile.max_tool_iterations == 9
service.close()
def test_agent_config_api_persists_and_reloads_defaults(tmp_path) -> None:
config_path = tmp_path / "config.json"
config_path.write_text(json.dumps({"agents": {"defaults": {}}}), encoding="utf-8")
service = AgentService(config_path=config_path)
app = create_app(service=service, manage_service_lifecycle=False)
with TestClient(app) as client:
response = client.post(
"/api/agent-config",
json={"max_tokens": 8192, "temperature": 0.6, "max_tool_iterations": 12},
)
status = client.get("/api/status")
saved = json.loads(config_path.read_text(encoding="utf-8"))
defaults = saved["agents"]["defaults"]
assert response.status_code == 200
assert response.json() == {"ok": True}
assert defaults["maxTokens"] == 8192
assert defaults["temperature"] == 0.6
assert defaults["maxToolIterations"] == 12
assert service.profile.max_tokens == 8192
assert service.profile.temperature == 0.6
assert service.profile.max_tool_iterations == 12
assert status.json()["max_tokens"] == 8192
assert status.json()["temperature"] == 0.6
assert status.json()["max_tool_iterations"] == 12
service.close()
def test_agent_config_api_accepts_zero_temperature_and_iterations(tmp_path) -> None:
config_path = tmp_path / "config.json"
service = AgentService(config_path=config_path)
app = create_app(service=service, manage_service_lifecycle=False)
with TestClient(app) as client:
response = client.post(
"/api/agent-config",
json={"max_tokens": None, "temperature": 0, "max_tool_iterations": 0},
)
config = load_config(config_path=config_path)
assert response.status_code == 200
assert config.agents_defaults.max_tokens is None
assert config.agents_defaults.temperature == 0
assert config.agents_defaults.max_tool_iterations == 0
assert service.profile.max_tokens is None
assert service.profile.temperature == 0
assert service.profile.max_tool_iterations == 0
service.close()
def test_channel_config_api_persists_and_masks_secrets(tmp_path) -> None:
config_path = tmp_path / "config.json"
config_path.write_text(
json.dumps(
{
"agents": {"defaults": {"model": "openai/gpt-5"}},
"channels": {
"telegram-main": {
"enabled": False,
"kind": "telegram",
"mode": "polling",
"accountId": "bot-main",
"displayName": "Telegram Main",
"secrets": {"botToken": "1234567890abcdef"},
"config": {"requireMentionInGroups": True},
}
},
}
),
encoding="utf-8",
)
service = AgentService(config_path=config_path)
app = create_app(service=service, manage_service_lifecycle=False)
with TestClient(app) as client:
before = client.get("/api/channels/telegram-main/config")
response = client.post(
"/api/channels/telegram-main/config",
json={
"enabled": True,
"kind": "telegram",
"mode": "polling",
"account_id": "bot-main",
"display_name": "Telegram Primary",
"secrets": {"botToken": ""},
"config": {
"requireMentionInGroups": False,
"allowFrom": ["1001", "1002"],
"maxMessageChars": 3000,
},
},
)
saved = json.loads(config_path.read_text(encoding="utf-8"))
channel = saved["channels"]["telegram-main"]
assert before.status_code == 200
assert before.json()["secrets"] == {"botToken": "1234••••cdef"}
assert response.status_code == 200
assert response.json()["ok"] is True
assert response.json()["restart_required"] is True
assert response.json()["channel"]["display_name"] == "Telegram Primary"
assert response.json()["channel"]["secrets"] == {"botToken": "1234••••cdef"}
assert channel["enabled"] is True
assert channel["displayName"] == "Telegram Primary"
assert channel["secrets"]["botToken"] == "1234567890abcdef"
assert channel["config"]["allowFrom"] == ["1001", "1002"]
assert load_config(config_path=config_path).channels["telegram-main"].enabled is True
service.close()
def test_openai_compatible_qwen_config_keeps_openai_provider() -> None:
bundle = make_provider_bundle(
model="qwen-plus",

View File

@ -0,0 +1,51 @@
from __future__ import annotations
from beaver.interfaces.channels.connections import MessageDedupeStore
def test_message_dedupe_store_completes_and_dedupes_completed(tmp_path) -> None:
store = MessageDedupeStore(tmp_path / "message_dedupe.json")
first = store.begin(connection_id="conn_1", event_id="evt_1", delivery_attempt=1)
store.complete(first.dedupe_key, message_id="msg_1")
duplicate = store.begin(connection_id="conn_1", event_id="evt_1", delivery_attempt=2)
assert first.should_process is True
assert duplicate.should_process is False
assert duplicate.status == "completed"
assert duplicate.http_status == 200
def test_message_dedupe_store_returns_conflict_for_active_processing(tmp_path) -> None:
store = MessageDedupeStore(tmp_path / "message_dedupe.json", processing_ttl_seconds=60)
store.begin(connection_id="conn_1", event_id="evt_1", delivery_attempt=1)
duplicate = store.begin(connection_id="conn_1", event_id="evt_1", delivery_attempt=2)
assert duplicate.should_process is False
assert duplicate.status == "processing"
assert duplicate.http_status == 409
assert duplicate.retry_after_seconds == 5
def test_message_dedupe_store_reprocesses_stale_processing(tmp_path) -> None:
store = MessageDedupeStore(tmp_path / "message_dedupe.json", processing_ttl_seconds=0)
store.begin(connection_id="conn_1", event_id="evt_1", delivery_attempt=1)
stale = store.begin(connection_id="conn_1", event_id="evt_1", delivery_attempt=2)
assert stale.should_process is True
assert stale.status == "processing"
assert stale.record.delivery_attempts == 2
def test_message_dedupe_store_reprocesses_failed_records(tmp_path) -> None:
store = MessageDedupeStore(tmp_path / "message_dedupe.json")
first = store.begin(connection_id="conn_1", event_id="evt_1", delivery_attempt=1)
store.fail(first.dedupe_key, error="runtime rejected")
retry = store.begin(connection_id="conn_1", event_id="evt_1", delivery_attempt=2)
assert retry.should_process is True
assert retry.record.delivery_attempts == 2
assert retry.record.last_error is None

View File

@ -0,0 +1,51 @@
from __future__ import annotations
from beaver.engine.context import ContextBuildInput, ContextBuilder, RuntimeContext, SessionContext
def test_context_builder_injects_current_date_and_time() -> None:
result = ContextBuilder().build_messages(
ContextBuildInput(
base_system_prompt="Follow user requests.",
current_user_input="今天几号?",
session_context=SessionContext(session_id="web:alpha", source="web", model="stub-model"),
runtime_context=RuntimeContext(
utc_datetime="2026-05-26T01:10:00+00:00",
local_datetime="2026-05-26T09:10:00+08:00",
timezone="Asia/Shanghai",
utc_offset="+08:00",
),
)
)
system_prompt = result.messages[0]["content"]
assert "# Current Date and Time" in system_prompt
assert "Current UTC time: 2026-05-26T01:10:00+00:00" in system_prompt
assert "Current local time: 2026-05-26T09:10:00+08:00" in system_prompt
assert "Local timezone: Asia/Shanghai" in system_prompt
assert "Local UTC offset: +08:00" in system_prompt
assert '"today", "tomorrow", "now", "this week", and "next month"' in system_prompt
assert result.messages[-1] == {"role": "user", "content": "今天几号?"}
def test_context_builder_uses_simplified_main_agent_prompt_by_default() -> None:
system_prompt = ContextBuilder().build_system_prompt(ContextBuildInput())
assert "你是海狸 (Beaver)" in system_prompt
assert "博维资讯系统有限公司研发的 AI 助手" in system_prompt
assert "使用简体中文进行面向用户的回复" in system_prompt
def test_context_builder_uses_traditional_main_agent_prompt_for_zh_hant() -> None:
system_prompt = ContextBuilder().build_system_prompt(ContextBuildInput(prompt_locale="zh-Hant"))
assert "你是海狸 (Beaver)" in system_prompt
assert "博維資訊系統有限公司研發的 AI 助手" in system_prompt
assert "使用繁體中文進行面向使用者的回覆" in system_prompt
def test_context_builder_uses_english_main_agent_prompt_for_en() -> None:
system_prompt = ContextBuilder().build_system_prompt(ContextBuildInput(prompt_locale="en"))
assert "You are Beaver, an AI assistant developed by Boway Information Systems Co., Ltd." in system_prompt
assert "Use English for user-facing replies" in system_prompt

View File

@ -0,0 +1,193 @@
from __future__ import annotations
from fastapi.testclient import TestClient
from beaver.interfaces.channels.connections import ChannelConnectionStore
from beaver.interfaces.web.app import create_app
from beaver.services.agent_service import AgentService
def _app(tmp_path, monkeypatch):
monkeypatch.setenv("BEAVER_BRIDGE_TOKEN", "bridge-token")
config_path = tmp_path / "config.json"
config_path.write_text(
'{"agents": {"defaults": {"workspace": "%s"}}, "providers": {}}' % str(tmp_path),
encoding="utf-8",
)
service = AgentService(config_path=config_path)
app = create_app(service=service, manage_service_lifecycle=False)
return app, service
def _connected_connection(tmp_path):
state_dir = tmp_path / "state" / "channel_connections"
store = ChannelConnectionStore(state_dir / "connections.json")
connection = store.create(
kind="weixin",
mode="sidecar",
display_name="Weixin Main",
account_id="weixin:me",
owner_user_id=None,
auth_type="connector_session",
)
store.update_status(connection.connection_id, status="connected", last_error=None)
return connection
def _connection_with_status(tmp_path, status: str):
state_dir = tmp_path / "state" / "channel_connections"
store = ChannelConnectionStore(state_dir / "connections.json")
connection = store.create(
kind="feishu",
mode="sidecar",
display_name="Feishu Main",
account_id="feishu:app-1",
owner_user_id=None,
auth_type="connector_session",
)
store.update_status(connection.connection_id, status=status, last_error=None)
return connection
def _payload(connection, *, event_id: str = "evt-1", delivery_attempt: int = 1) -> dict:
return {
"eventId": event_id,
"timestamp": "2026-06-02T09:30:00Z",
"deliveryAttempt": delivery_attempt,
"connectionId": connection.connection_id,
"channelId": connection.channel_id,
"kind": "weixin",
"accountId": "weixin:me",
"peerId": "peer-1",
"peerType": "dm",
"userId": "sender-1",
"threadId": None,
"messageId": "msg-1",
"messageType": "text",
"content": "hello",
"metadata": {},
}
def test_bridge_endpoint_accepts_valid_event(tmp_path, monkeypatch) -> None:
app, service = _app(tmp_path, monkeypatch)
try:
with TestClient(app) as client:
connection = _connected_connection(tmp_path)
response = client.post(
"/api/channel-connector-bridge/events",
headers={"Authorization": "Bearer bridge-token"},
json=_payload(connection),
)
assert response.status_code == 200
assert response.json()["accepted"] is True
finally:
service.close()
def test_bridge_endpoint_rejects_invalid_token(tmp_path, monkeypatch) -> None:
app, service = _app(tmp_path, monkeypatch)
try:
with TestClient(app) as client:
connection = _connected_connection(tmp_path)
response = client.post(
"/api/channel-connector-bridge/events",
headers={"Authorization": "Bearer wrong"},
json=_payload(connection),
)
assert response.status_code == 401
finally:
service.close()
def test_bridge_endpoint_rejects_connection_identity_mismatch(tmp_path, monkeypatch) -> None:
app, service = _app(tmp_path, monkeypatch)
try:
with TestClient(app) as client:
connection = _connected_connection(tmp_path)
payload = _payload(connection)
payload["channelId"] = "forged-channel"
payload["kind"] = "feishu"
payload["accountId"] = "feishu:attacker"
response = client.post(
"/api/channel-connector-bridge/events",
headers={"Authorization": "Bearer bridge-token"},
json=payload,
)
assert response.status_code == 403
assert "does not match connection" in response.json()["detail"]
finally:
service.close()
def test_bridge_endpoint_rejects_inactive_connection(tmp_path, monkeypatch) -> None:
app, service = _app(tmp_path, monkeypatch)
try:
with TestClient(app) as client:
connection = _connection_with_status(tmp_path, "pairing")
response = client.post(
"/api/channel-connector-bridge/events",
headers={"Authorization": "Bearer bridge-token"},
json={
**_payload(connection),
"kind": "feishu",
"accountId": "feishu:app-1",
},
)
assert response.status_code == 409
assert "not connected" in response.json()["detail"]
finally:
service.close()
def test_bridge_endpoint_rejects_empty_or_oversized_content(tmp_path, monkeypatch) -> None:
app, service = _app(tmp_path, monkeypatch)
try:
with TestClient(app) as client:
connection = _connection_with_status(tmp_path, "connected")
blank = client.post(
"/api/channel-connector-bridge/events",
headers={"Authorization": "Bearer bridge-token"},
json={
**_payload(connection, event_id="blank"),
"kind": "feishu",
"accountId": "feishu:app-1",
"content": " ",
},
)
too_long = client.post(
"/api/channel-connector-bridge/events",
headers={"Authorization": "Bearer bridge-token"},
json={
**_payload(connection, event_id="too-long"),
"kind": "feishu",
"accountId": "feishu:app-1",
"content": "x" * 20001,
},
)
assert blank.status_code == 400
assert too_long.status_code == 413
finally:
service.close()
def test_bridge_endpoint_dedupes_repeated_event(tmp_path, monkeypatch) -> None:
app, service = _app(tmp_path, monkeypatch)
try:
with TestClient(app) as client:
connection = _connected_connection(tmp_path)
first = client.post(
"/api/channel-connector-bridge/events",
headers={"Authorization": "Bearer bridge-token"},
json=_payload(connection),
)
second = client.post(
"/api/channel-connector-bridge/events",
headers={"Authorization": "Bearer bridge-token"},
json=_payload(connection, delivery_attempt=2),
)
assert first.status_code == 200
assert second.status_code in {200, 409}
assert second.json()["duplicate"] is True
finally:
service.close()

View File

@ -0,0 +1,114 @@
from __future__ import annotations
import asyncio
from beaver.foundation.events import ChannelIdentity, OutboundMessage
from beaver.interfaces.channels.external_connector import ExternalConnectorChannel, _request_id
class FakeSidecarClient:
def __init__(self) -> None:
self.sent: list[dict] = []
async def send(self, payload: dict) -> dict:
self.sent.append(payload)
return {"ok": True, "providerMessageId": "provider-1"}
def test_external_connector_channel_sends_with_target_and_request_id() -> None:
async def run() -> None:
client = FakeSidecarClient()
channel = ExternalConnectorChannel(
channel_id="weixin-main",
platform_kind="weixin",
connection_id="conn_1",
account_id="weixin:me",
display_name="Weixin Main",
sidecar_client=client,
)
message = OutboundMessage(
channel="weixin-main",
content="reply",
session_id="s1",
finish_reason="stop",
message_id="out-msg-1",
channel_identity=ChannelIdentity(
channel_id="weixin-main",
kind="weixin",
account_id="weixin:me",
peer_id="peer-1",
peer_type="dm",
thread_id=None,
user_id="sender-1",
message_id="in-msg-1",
),
metadata={"inbound_metadata": {"contextToken": "ctx-1"}},
)
await channel.send(message)
assert client.sent == [
{
"requestId": "out_weixin-main:s1:out-msg-1",
"connectionId": "conn_1",
"channelId": "weixin-main",
"kind": "weixin",
"target": {"peerId": "peer-1", "peerType": "dm", "threadId": None},
"content": "reply",
"metadata": {"inboundMessageId": "in-msg-1", "sessionId": "s1", "contextToken": "ctx-1"},
}
]
asyncio.run(run())
def test_external_connector_request_id_falls_back_when_message_id_is_none_or_blank() -> None:
identity = ChannelIdentity(
channel_id="weixin-main",
kind="weixin",
account_id="weixin:me",
peer_id="peer-1",
peer_type="dm",
message_id="in-msg-1",
)
first = OutboundMessage(
channel="weixin-main",
content="same reply",
session_id="s1",
finish_reason="stop",
message_id=None, # type: ignore[arg-type]
channel_identity=identity,
)
second = OutboundMessage(
channel="weixin-main",
content="same reply",
session_id="s1",
finish_reason="stop",
message_id="",
channel_identity=identity,
)
assert _request_id(first) == _request_id(second)
assert _request_id(first).startswith("out_weixin-main:s1:")
def test_external_connector_channel_requires_identity() -> None:
async def run() -> None:
channel = ExternalConnectorChannel(
channel_id="weixin-main",
platform_kind="weixin",
connection_id="conn_1",
account_id="weixin:me",
display_name="Weixin Main",
sidecar_client=FakeSidecarClient(),
)
message = OutboundMessage(channel="weixin-main", content="reply", session_id="s1", finish_reason="stop")
try:
await channel.send(message)
except ValueError as exc:
assert "channel_identity is required" in str(exc)
else:
raise AssertionError("Expected ValueError")
asyncio.run(run())

Some files were not shown because too many files have changed in this diff Show More