feat(app-instance): 集成Beaver后端并更新配置管理
集成新的Beaver后端服务到应用实例中，替换原有的nanobot实现。 主要变更包括： - 在Dockerfile和环境配置中添加Beaver相关路径和配置变量 - 更新工作目录结构从.nanobot到.beaver - 实现Beaver引擎加载器，支持配置文件加载和工具组装 - 添加内置工具如ListDirectoryTool、ReadFileTool、SearchFilesTool - 更新消息处理流程，支持通道适配器和网关模式 - 重构技能系统，支持显式工具提示和嵌入式检索 - 改进错误处理和生命周期管理 此变更使应用实例能够使用统一的Beaver后端进行AI代理运行时管理。
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"""Configuration models and loaders."""
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from .loader import default_config_path, load_config
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from .schema import AgentDefaultsConfig, BeaverConfig, EmbeddingConfig, ProviderConfig
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__all__ = [
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"AgentDefaultsConfig",
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"BeaverConfig",
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"EmbeddingConfig",
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"ProviderConfig",
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"default_config_path",
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"load_config",
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]
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127
app-instance/backend/beaver/foundation/config/loader.py
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127
app-instance/backend/beaver/foundation/config/loader.py
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"""Config loader for per-sandbox Beaver runtime settings."""
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from __future__ import annotations
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import json
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import os
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from pathlib import Path
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from typing import Any
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from .schema import AgentDefaultsConfig, BeaverConfig, EmbeddingConfig, ProviderConfig
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def default_config_path(*, workspace: str | Path | None = None) -> Path:
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"""Resolve the default config path for a single-user sandbox instance.
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Priority:
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1. `BEAVER_CONFIG_PATH`
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2. `NANOBOT_CONFIG_PATH` for compatibility during migration
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3. `BEAVER_HOME/config.json`
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4. `NANOBOT_HOME/config.json` for migration compatibility
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5. `<workspace>/.beaver/config.json`
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6. `./.beaver/config.json`
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"""
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explicit = os.getenv("BEAVER_CONFIG_PATH") or os.getenv("NANOBOT_CONFIG_PATH")
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if explicit:
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return Path(explicit).expanduser()
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beaver_home = os.getenv("BEAVER_HOME")
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if beaver_home:
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return Path(beaver_home).expanduser() / "config.json"
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nanobot_home = os.getenv("NANOBOT_HOME")
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if nanobot_home:
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return Path(nanobot_home).expanduser() / "config.json"
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root = Path(workspace).expanduser() if workspace is not None else Path.cwd()
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return root / ".beaver" / "config.json"
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def load_config(
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*,
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workspace: str | Path | None = None,
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config_path: str | Path | None = None,
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) -> BeaverConfig:
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"""Load backend config; missing config is treated as an empty config."""
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path = Path(config_path).expanduser() if config_path is not None else default_config_path(workspace=workspace)
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if not path.exists():
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return BeaverConfig(config_path=path)
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data = json.loads(path.read_text(encoding="utf-8"))
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if not isinstance(data, dict):
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raise ValueError(f"Beaver config must be a JSON object: {path}")
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return BeaverConfig(
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agents_defaults=_parse_agent_defaults(data),
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providers=_parse_providers(data.get("providers")),
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embedding=_parse_embedding(data),
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config_path=path,
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)
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def _parse_agent_defaults(data: dict[str, Any]) -> AgentDefaultsConfig:
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agents = _as_dict(data.get("agents"))
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defaults = _as_dict(agents.get("defaults"))
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return AgentDefaultsConfig(
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workspace=_string(defaults.get("workspace") or data.get("workspace")),
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model=_string(defaults.get("model") or data.get("model")),
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provider=_string(defaults.get("provider") or data.get("provider")),
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embedding_model=_string(defaults.get("embeddingModel") or defaults.get("embedding_model") or data.get("embeddingModel")),
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)
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def _parse_providers(raw: Any) -> dict[str, ProviderConfig]:
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providers: dict[str, ProviderConfig] = {}
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for name, payload in _as_dict(raw).items():
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if not isinstance(payload, dict):
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continue
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providers[str(name)] = ProviderConfig(
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api_key=_string(payload.get("apiKey") or payload.get("api_key")),
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api_base=_string(payload.get("apiBase") or payload.get("api_base") or payload.get("baseUrl") or payload.get("base_url")),
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extra_headers=_string_dict(payload.get("extraHeaders") or payload.get("extra_headers") or payload.get("headers")),
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request_timeout_seconds=_float(
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payload.get("requestTimeoutSeconds")
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or payload.get("request_timeout_seconds")
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or payload.get("timeout")
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),
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)
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return providers
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def _parse_embedding(data: dict[str, Any]) -> EmbeddingConfig:
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raw = _as_dict(data.get("embedding") or data.get("embeddings"))
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return EmbeddingConfig(
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provider=_string(raw.get("provider") or raw.get("provider_name")),
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model=_string(raw.get("model") or data.get("embeddingModel") or data.get("embedding_model")),
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api_key=_string(raw.get("apiKey") or raw.get("api_key")),
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api_base=_string(raw.get("apiBase") or raw.get("api_base") or raw.get("baseUrl") or raw.get("base_url")),
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extra_headers=_string_dict(raw.get("extraHeaders") or raw.get("extra_headers") or raw.get("headers")),
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request_timeout_seconds=_float(
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raw.get("requestTimeoutSeconds") or raw.get("request_timeout_seconds") or raw.get("timeout")
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),
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)
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def _as_dict(value: Any) -> dict[str, Any]:
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return value if isinstance(value, dict) else {}
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def _string(value: Any) -> str | None:
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if value is None:
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return None
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value = str(value).strip()
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return value or None
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def _string_dict(value: Any) -> dict[str, str]:
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if not isinstance(value, dict):
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return {}
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return {str(key): str(item) for key, item in value.items() if item is not None}
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def _float(value: Any) -> float | None:
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if value in (None, ""):
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return None
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return float(value)
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136
app-instance/backend/beaver/foundation/config/schema.py
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136
app-instance/backend/beaver/foundation/config/schema.py
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"""Runtime configuration schema for Beaver sandbox instances."""
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from __future__ import annotations
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Any
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@dataclass(slots=True)
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class ProviderConfig:
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"""One configured LLM provider profile."""
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api_key: str | None = None
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api_base: str | None = None
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extra_headers: dict[str, str] = field(default_factory=dict)
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request_timeout_seconds: float | None = None
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@dataclass(slots=True)
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class AgentDefaultsConfig:
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"""Default agent settings for this sandbox instance."""
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workspace: str | None = None
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model: str | None = None
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provider: str | None = None
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embedding_model: str | None = None
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@dataclass(slots=True)
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class EmbeddingConfig:
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"""Optional dedicated embedding model settings."""
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provider: str | None = None
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model: str | None = None
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api_key: str | None = None
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api_base: str | None = None
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extra_headers: dict[str, str] = field(default_factory=dict)
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request_timeout_seconds: float | None = None
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@dataclass(slots=True)
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class BeaverConfig:
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"""Config loaded once per backend sandbox instance."""
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agents_defaults: AgentDefaultsConfig = field(default_factory=AgentDefaultsConfig)
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providers: dict[str, ProviderConfig] = field(default_factory=dict)
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embedding: EmbeddingConfig = field(default_factory=EmbeddingConfig)
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config_path: Path | None = None
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@property
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def default_model(self) -> str | None:
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return _clean(self.agents_defaults.model)
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@property
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def default_embedding_model(self) -> str:
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return _clean(self.embedding.model) or _clean(self.agents_defaults.embedding_model) or "text-embedding-v4"
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def resolve_provider_target(
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self,
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*,
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model: str | None = None,
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provider_name: str | None = None,
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) -> dict[str, Any]:
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"""Resolve model/provider credentials from instance config.
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Request-level model/provider overrides are allowed, but credentials are still
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read from backend config, not from Web/channel payloads.
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"""
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resolved_model = _clean(model) or self.default_model
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resolved_provider = _clean(provider_name) or self._infer_provider(resolved_model)
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provider_cfg = self.providers.get(resolved_provider or "") if resolved_provider else None
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payload: dict[str, Any] = {
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"model": resolved_model,
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"provider_name": resolved_provider,
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}
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if provider_cfg is not None:
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payload.update(
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{
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"api_key": provider_cfg.api_key,
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"api_base": provider_cfg.api_base,
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"extra_headers": dict(provider_cfg.extra_headers),
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"request_timeout_seconds": provider_cfg.request_timeout_seconds,
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}
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)
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return {key: value for key, value in payload.items() if value not in (None, "", {})}
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def resolve_embedding_target(self) -> dict[str, Any] | None:
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"""Return an explicit embedding target when configured."""
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has_explicit_embedding = any(
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[
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_clean(self.embedding.provider),
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_clean(self.embedding.api_key),
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_clean(self.embedding.api_base),
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self.embedding.extra_headers,
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self.embedding.request_timeout_seconds is not None,
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]
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)
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if not has_explicit_embedding:
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return None
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provider_cfg = self.providers.get(_clean(self.embedding.provider) or "")
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payload: dict[str, Any] = {
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"provider": _clean(self.embedding.provider),
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"model": self.default_embedding_model,
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"api_key": _clean(self.embedding.api_key) or (provider_cfg.api_key if provider_cfg else None),
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"api_base": _clean(self.embedding.api_base) or (provider_cfg.api_base if provider_cfg else None),
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"extra_headers": self.embedding.extra_headers or (dict(provider_cfg.extra_headers) if provider_cfg else {}),
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"request_timeout_seconds": self.embedding.request_timeout_seconds
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or (provider_cfg.request_timeout_seconds if provider_cfg else None),
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}
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return {key: value for key, value in payload.items() if value not in (None, "", {})}
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def _infer_provider(self, model: str | None) -> str | None:
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configured_provider = _clean(self.agents_defaults.provider)
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if configured_provider:
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return configured_provider
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if model and "/" in model:
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prefix = model.split("/", 1)[0]
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if prefix in self.providers:
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return prefix
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if len(self.providers) == 1:
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return next(iter(self.providers))
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return None
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def _clean(value: str | None) -> str | None:
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if value is None:
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return None
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value = str(value).strip()
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return value or None
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