srinuksv commited on
Commit
1378b3b
1 Parent(s): d776cdd

Update app.py

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Files changed (1) hide show
  1. app.py +58 -8
app.py CHANGED
@@ -1,15 +1,19 @@
1
  import os
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  import time
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- from fastapi import FastAPI
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  from fastapi.responses import HTMLResponse
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  from fastapi.staticfiles import StaticFiles
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  from llama_index.core import StorageContext, load_index_from_storage, VectorStoreIndex, SimpleDirectoryReader, ChatPromptTemplate, Settings
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  from llama_index.llms.huggingface import HuggingFaceInferenceAPI
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  from llama_index.embeddings.huggingface import HuggingFaceEmbedding
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  from pydantic import BaseModel
 
 
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  import datetime
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- from dotenv import load_dotenv
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- load_dotenv()
 
 
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  # Define Pydantic model for incoming request body
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  class MessageRequest(BaseModel):
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  message: str
@@ -18,9 +22,34 @@ class MessageRequest(BaseModel):
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  os.environ["HF_TOKEN"] = os.getenv("HF_TOKEN")
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  app = FastAPI()
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- app.mount("/static", StaticFiles(directory="static"), name="static")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  # Configure Llama index settings
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  Settings.llm = HuggingFaceInferenceAPI(
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  model_name="meta-llama/Meta-Llama-3-8B-Instruct",
@@ -89,10 +118,27 @@ def handle_query(query):
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  response ="Sorry, I couldn't find an answer."
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  current_chat_history.append((query, response))
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  return response
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- @app.get("/", response_class=HTMLResponse)
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- async def read_root():
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- with open("static/index.html") as f:
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- return f.read()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  @app.post("/chat/")
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  async def chat(request: MessageRequest):
@@ -106,5 +152,9 @@ async def chat(request: MessageRequest):
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  }
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  chat_history.append(message_data)
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  return {"response": response}
 
 
 
 
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  import os
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  import time
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+ from fastapi import FastAPI,Request
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  from fastapi.responses import HTMLResponse
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  from fastapi.staticfiles import StaticFiles
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  from llama_index.core import StorageContext, load_index_from_storage, VectorStoreIndex, SimpleDirectoryReader, ChatPromptTemplate, Settings
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  from llama_index.llms.huggingface import HuggingFaceInferenceAPI
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  from llama_index.embeddings.huggingface import HuggingFaceEmbedding
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  from pydantic import BaseModel
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+ from fastapi.responses import JSONResponse
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+ import uuid # for generating unique IDs
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  import datetime
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+ from fastapi.middleware.cors import CORSMiddleware
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+ from fastapi.templating import Jinja2Templates
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+
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+
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  # Define Pydantic model for incoming request body
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  class MessageRequest(BaseModel):
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  message: str
 
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  os.environ["HF_TOKEN"] = os.getenv("HF_TOKEN")
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  app = FastAPI()
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+ @app.middleware("http")
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+ async def add_security_headers(request: Request, call_next):
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+ response = await call_next(request)
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+ response.headers["Content-Security-Policy"] = "frame-ancestors *; frame-src *; object-src *;"
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+ response.headers["X-Frame-Options"] = "ALLOWALL"
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+ return response
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+
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+
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+ # Allow CORS requests from any domain
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+ app.add_middleware(
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+ CORSMiddleware,
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+ allow_origins=["*"],
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+ allow_credentials=True,
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+ allow_methods=["*"],
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+ allow_headers=["*"],
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+ )
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+
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+
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+ @app.get("/favicon.ico")
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+ async def favicon():
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+ return HTMLResponse("") # or serve a real favicon if you have one
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+
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+
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+ app.mount("/static", StaticFiles(directory="D:\SRUNU (1)\content\SRUNU\static"), name="static")
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+
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+ templates = Jinja2Templates(directory="static")
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  # Configure Llama index settings
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  Settings.llm = HuggingFaceInferenceAPI(
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  model_name="meta-llama/Meta-Llama-3-8B-Instruct",
 
118
  response ="Sorry, I couldn't find an answer."
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  current_chat_history.append((query, response))
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  return response
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+ @app.get("/ch/{id}", response_class=HTMLResponse)
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+ async def load_chat(request: Request, id: str):
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+ return templates.TemplateResponse("index.html", {"request": request, "user_id": id})
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+ # Route to save chat history
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+ @app.post("/hist/")
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+ async def save_chat_history(history: dict):
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+ # Logic to save chat history, using the `id` from the frontend
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+ print(history) # You can replace this with actual save logic
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+ return {"message": "Chat history saved"}
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+ @app.post("/webhook")
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+ async def receive_form_data(request: Request):
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+ form_data = await request.json()
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+
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+ # Generate a unique ID (for tracking user)
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+ unique_id = str(uuid.uuid4())
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+
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+ # Here you can do something with form_data like saving it to a database
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+ print("Received form data:", form_data)
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+
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+ # Send back the unique id to the frontend
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+ return JSONResponse({"id": unique_id})
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143
  @app.post("/chat/")
144
  async def chat(request: MessageRequest):
 
152
  }
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  chat_history.append(message_data)
154
  return {"response": response}
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+ @app.get("/")
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+ def read_root():
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+ return {"message": "Welcome to the API"}
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+
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