Update server.py

app/server.py

@@ -1,63 +1,35 @@
-#!/usr/bin/env python
+from pydantic import BaseModel, Field
-"""Example LangChain server exposes multiple runnables (LLMs in this case)."""
-
 from fastapi import FastAPI
 from fastapi.responses import RedirectResponse
-from langchain_anthropic import ChatAnthropic
-from langchain_openai import ChatOpenAI
-from langchain_google_genai import ChatGoogleGenerativeAI
-
 from langserve import add_routes
+from chain import build_chain
 
-import mlflow
+# Input API
+class QueryInput(BaseModel):
+    """쿼리 입력 모델"""
+    question: str = Field(..., description="사용자 질문")
+    temperature: float = 0.7
+    max_tokens: int = 1000
 
-import getpass
+app = FastAPI()
-import os
 
-os.environ["OPENAI_API_KEY"] = "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"
+rag_chain = build_chain()
-os.environ["GOOGLE_API_KEY"] = "AIzaSyDIO5PFKRV-kVjNzpsrOcC-KodUMO-VGAo"
 
-mlflow.set_tracking_uri("http://localhost:5000")
-mlflow.langchain.autolog()
-
-app = FastAPI(
-    title="LangChain Server",
-    version="1.0",
-    description="Spin up a simple api server using Langchain's Runnable interfaces",
-)
-
-llm = ChatGoogleGenerativeAI(
-    model="gemini-2.0-flash-001",
-    temperature=0,
-    max_tokens=None,
-    timeout=None,
-    max_retries=2,
-    # other params...
-)
-
-openai_llm = ChatOpenAI(
-    model="gpt-4o",
-    temperature=0,
-    max_tokens=None,
-    timeout=None,
-    max_retries=2,
-    # api_key="...",  # if you prefer to pass api key in directly instaed of using env vars
-    # base_url="...",
-    # organization="...",
-    # other params...
-)
-
-add_routes(
-    app,
-    llm,
-    path="/gemeni",
-)
 
 @app.get("/")
 async def redirect_root_to_docs():
-    return RedirectResponse("/gemeni/playground")
+    return RedirectResponse("/chat")
+
+
+# Edit this to add the chain you want to add
+add_routes(
+    app,
+    rag_chain,
+    path="/chat",
+    input_type=QueryInput
+)
 
 if __name__ == "__main__":
     import uvicorn
 
-    uvicorn.run(app, host="0.0.0.0", port=9000)
+    uvicorn.run(app, host="0.0.0.0", port=8000)