Update main.py

main.py

@@ -2,7 +2,25 @@ import gradio as gr
 from huggingface_hub import InferenceClient
 
 client = InferenceClient(model='mistralai/Mistral-7B-Instruct-v0.2')
+# from fastapi import FastAPI
+# from fastapi.staticfiles import StaticFiles
+# from fastapi.responses import FileResponse
+# from transformers import pipeline
+
+# app = FastAPI()
+
+# pipe_flan = pipeline("text2text-generation", model="google/flan-t5-small")
 
+# @app.get("/infer_t5")
+# def t5(input):
+#     output = pipe_flan(input)
+#     return {"output": output[0]["generated_text"]}
+
+# app.mount("/", StaticFiles(directory="static", html=True), name="static")
+
+# @app.get("/")
+# def index() -> FileResponse:
+#     return FileResponse(path="/app/static/index.html", media_type="text/html")
 #from langchain import HuggingFaceHub
 #import os
 #from langchain.vectorstores import Chroma
@@ -86,23 +104,3 @@ demo = gr.ChatInterface(
 
 if __name__ == "__main__":
     demo.launch(share=True)
-
-# from fastapi import FastAPI
-# from fastapi.staticfiles import StaticFiles
-# from fastapi.responses import FileResponse
-# from transformers import pipeline
-
-# app = FastAPI()
-
-# pipe_flan = pipeline("text2text-generation", model="google/flan-t5-small")
-
-# @app.get("/infer_t5")
-# def t5(input):
-#     output = pipe_flan(input)
-#     return {"output": output[0]["generated_text"]}
-
-# app.mount("/", StaticFiles(directory="static", html=True), name="static")
-
-# @app.get("/")
-# def index() -> FileResponse:
-#     return FileResponse(path="/app/static/index.html", media_type="text/html")