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.gitignore

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+.env

Dockerfile

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+FROM python:3.10
+
+WORKDIR /code
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+EXPOSE 7860
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from fastapi import FastAPI
+from pydantic import BaseModel
+from typing import List
+from langchain_community.tools.tavily_search import TavilySearchResults
+import os
+from langgraph.prebuilt import create_react_agent
+from langchain_openai import AzureChatOpenAI
+from dotenv import load_dotenv
+load_dotenv()
+os.environ['AZURE_OPENAI_API_KEY'] = os.getenv('AZURE_OPENAI_API_KEY')
+os.environ['OPENAI_API_VERSION'] = os.getenv('OPENAI_API_VERSION')
+os.environ['AZURE_OPENAI_ENDPOINT'] = os.getenv('AZURE_OPENAI_ENDPOINT')
+os.environ['TAVILY_API_KEY'] = os.getenv('TAVILY_API_KEY')
+
+MODEL_NAME = [
+   "gpt-4o"
+]
+
+tool = TavilySearchResults(max_results=5)
+
+tools = [tool, ]
+
+app = FastAPI()
+
+class RequestState(BaseModel):
+    model_name: str
+    system_prompt: str
+    messages: List[str]
+
+@app.post("/chat")
+def chat_endpoint(request: RequestState):
+    """API Endpoint to chat with bot"""
+    if request.model_name not in MODEL_NAME:
+        return {"error": "Model not found"}
+    
+    llm = AzureChatOpenAI(
+    azure_deployment="gpt-4o", 
+    temperature=0,
+    max_tokens=None,
+    timeout=None,
+    max_retries=2,
+)
+    agent = create_react_agent(llm, tools=tools, prompt=request.system_prompt)
+    state = {"messages": request.messages}
+    result = agent.invoke(state)
+    return result
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)

requirements.txt

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+python-dotenv
+langchain
+langchain-core
+langchain-community
+langchain-openai
+fastapi
+uvicorn
+langgraph
+tavily-python