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Update app.py
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app.py
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@@ -1,16 +1,15 @@
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from fastapi import FastAPI, UploadFile, File, HTTPException
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from tools import update_retriever
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from chatbot import app as app_graph
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from langchain_core.messages import HumanMessage
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import os
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from fastapi.responses import StreamingResponse, FileResponse
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from fastapi.middleware.cors import CORSMiddleware
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from pydantic import BaseModel
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from utils import TTS, STT
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# =====================================================
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# APP SETUP
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# =====================================================
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app = FastAPI()
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@@ -22,80 +21,48 @@ app.add_middleware(
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allow_headers=["*"],
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)
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# =====================================================
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# MODELS
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# =====================================================
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class TTSRequest(BaseModel):
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text: str
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UPLOAD_DIR = "/data/uploads"
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os.makedirs(UPLOAD_DIR, exist_ok=True)
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# =====================================================
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# HEALTH CHECK
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# =====================================================
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@app.get("/")
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def health():
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return {
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# =====================================================
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# FILE UPLOAD (RAG)
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# =====================================================
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@app.post("/upload")
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async def upload_file(file: UploadFile = File(...)):
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file_path = os.path.join(UPLOAD_DIR, file.filename)
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with open(file_path, "wb") as f:
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f.write(await file.read())
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# Update vector store
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update_retriever(file_path)
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# 🔥 Rebuild LangGraph so RAG becomes active
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rebuild_graph()
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return {
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"status": "success",
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"filename": file.filename
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}
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# =====================================================
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# CHAT ENDPOINT (STREAMING)
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# =====================================================
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@app.post("/chat")
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async def chat(message: str, session_id: str = "default"):
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async def event_generator():
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buffer = ""
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async for chunk in app_graph.astream(
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{"messages": [HumanMessage(content=message)]},
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config={"configurable": {"thread_id": session_id}},
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stream_mode="messages"
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):
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if
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buffer += msg.content
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# Flush every ~150 characters (prevents broken tokens)
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if len(buffer) > 150:
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yield f"data: {buffer.strip()}\n\n"
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buffer = ""
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if buffer:
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yield f"data: {buffer.strip()}\n\n"
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return StreamingResponse(
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event_generator(),
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@@ -104,14 +71,9 @@ async def chat(message: str, session_id: str = "default"):
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no",
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"Access-Control-Allow-Origin": "*",
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},
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)
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# =====================================================
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# STT
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# =====================================================
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@app.post("/stt")
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async def transcribe_audio(file: UploadFile = File(...)):
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raise HTTPException(status_code=500, detail=str(e))
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# =====================================================
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# TTS
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# =====================================================
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@app.post("/tts")
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async def generate_tts(request: TTSRequest):
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try:
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@@ -143,4 +101,4 @@ async def generate_tts(request: TTSRequest):
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)
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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from fastapi import FastAPI, UploadFile, File, HTTPException
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from tools import create_rag_tool, update_retriever
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from chatbot import app as app_graph
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from langchain_core.messages import HumanMessage
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import os
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from fastapi.responses import StreamingResponse, FileResponse
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from langchain_core.messages import AIMessage
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from fastapi.middleware.cors import CORSMiddleware
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import asyncio
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from pydantic import BaseModel
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from utils import TTS, STT
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app = FastAPI()
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allow_headers=["*"],
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)
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class TTSRequest(BaseModel):
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text: str
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UPLOAD_DIR = "uploads"
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@app.get("/")
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def health():
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return {'Status' : 'The api is live and running'}
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@app.post("/upload")
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async def upload_file(file: UploadFile = File(...)):
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os.makedirs(UPLOAD_DIR, exist_ok=True)
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file_path = os.path.join(UPLOAD_DIR, file.filename)
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with open(file_path, "wb") as f:
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f.write(await file.read())
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update_retriever(file_path)
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return {
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"status": "success",
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"filename": file.filename
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}
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@app.post("/chat")
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async def chat(message: str, session_id: str = "default"):
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async def event_generator():
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async for chunk in app_graph.astream(
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{"messages": [HumanMessage(content=message)]},
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config={"configurable": {"thread_id": session_id}},
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stream_mode="messages"
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):
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if len(chunk) >= 1:
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message_chunk = chunk[0] if isinstance(chunk, tuple) else chunk
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if hasattr(message_chunk, 'content') and message_chunk.content:
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data = str(message_chunk.content).replace("\n", "\\n")
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yield f"data: {data}\n\n"
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await asyncio.sleep(0.01)
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return StreamingResponse(
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event_generator(),
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"Cache-Control": "no-cache",
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"Connection": "keep-alive",
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"X-Accel-Buffering": "no",
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},
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)
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# ---------------- STT ---------------- #
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@app.post("/stt")
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async def transcribe_audio(file: UploadFile = File(...)):
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raise HTTPException(status_code=500, detail=str(e))
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@app.post("/tts")
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async def generate_tts(request: TTSRequest):
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try:
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)
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except Exception as e:
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raise HTTPException(status_code=500, detail=str(e))
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