Upload server.py

app/server.py

@@ -0,0 +1,58 @@
+#!/usr/bin/env python
+"""Example LangChain server exposes multiple runnables (LLMs in this case)."""
+
+from fastapi import FastAPI
+from langchain_anthropic import ChatAnthropic
+from langchain_openai import ChatOpenAI
+from langchain_google_genai import ChatGoogleGenerativeAI
+
+from langserve import add_routes
+
+import mlflow
+
+import getpass
+import os
+
+os.environ["OPENAI_API_KEY"] = "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"
+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",
+)
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(app, host="0.0.0.0", port=9000)