add chat

src/blackbox/chat.py

@@ -0,0 +1,103 @@
+from typing import Any, Coroutine
+
+from fastapi import Request, Response, status
+from fastapi.responses import JSONResponse
+from .blackbox import Blackbox
+
+import requests
+import json
+from openai import OpenAI
+import re
+
+from injector import singleton
+@singleton
+class Chat(Blackbox):
+    
+    def __call__(self, *args, **kwargs):
+        return self.processing(*args, **kwargs)
+
+    def valid(self, *args, **kwargs) -> bool:
+        data = args[0]
+        return isinstance(data, list)
+
+    # model_name有 Qwen1.5-14B-Chat , internlm2-chat-20b
+    def processing(self, model_name, prompt, template, context: list, temperature, top_p, n, max_tokens)  -> str:
+        if context == None:
+            context = []
+
+        # gpt-4， gpt-3.5-turbo
+        if re.search(r"gpt", model_name):
+            url = 'https://api.openai.com/v1/completions' 
+            key = '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'
+        else:
+            url = 'http://120.196.116.194:48892/v1/chat/completions'
+            key = 'YOUR_API_KEY'
+              
+        prompt_template = [
+           {"role": "system", "content": template},
+        ]
+
+        chat_inputs={
+            "model": model_name,
+            "messages": prompt_template + context + [
+                {
+                    "role": "user",
+                    "content": prompt
+                }
+            ],
+            "temperature": temperature,
+            "top_p": top_p,
+            "n": n,
+            "max_tokens": max_tokens,
+            "stream": False,
+        }
+
+        header = {
+            'Content-Type': 'application/json',
+            'Authorization': "Bearer " + key
+        }
+
+        fastchat_response = requests.post(url, json=chat_inputs, headers=header)
+
+        return fastchat_response.json()["choices"][0]["message"]["content"]
+    
+    async def fast_api_handler(self, request: Request) -> Response:
+        try:
+            data = await request.json()
+        except:
+            return JSONResponse(content={"error": "json parse error"}, status_code=status.HTTP_400_BAD_REQUEST)
+
+        user_model_name = data.get("model_name")
+        user_context = data.get("context")
+        user_question = data.get("question")
+        user_template = data.get("template")
+        user_temperature = data.get("temperature")
+        user_top_p = data.get("top_p")
+        user_n = data.get("n")
+        user_max_tokens = data.get("max_tokens")
+        
+
+        if user_question is None:
+            return JSONResponse(content={"error": "question is required"}, status_code=status.HTTP_400_BAD_REQUEST)
+
+        if user_model_name is None or user_model_name.isspace() or user_model_name == "":
+            user_model_name = "Qwen1.5-14B-Chat"
+
+        if user_template is None or user_template.isspace():
+            user_template = ""
+        
+        if user_temperature is None or user_temperature == "":
+            user_temperature = 0.7
+
+        if user_top_p is None or user_top_p == "":
+            user_top_p = 1
+
+        if user_n is None or user_n == "":
+            user_n = 1
+        
+        if user_max_tokens is None or user_max_tokens == "":
+            user_max_tokens = 1024
+
+
+        return JSONResponse(content={"response": self.processing(user_model_name, user_question, user_template, user_context, 
+        user_temperature, user_top_p, user_n, user_max_tokens)}, status_code=status.HTTP_200_OK)