Delete app.py

app.py

@@ -1,147 +0,0 @@
-from fastapi import FastAPI, HTTPException, UploadFile, File
-from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import FileResponse, StreamingResponse
-from pydantic import BaseModel
-import os
-
-from inference.predictor import CreditRiskPredictor
-from advisor_bot import generate_advice
-from chatbot_advisor import ask_chatbot
-from utility import STT, TTS
-
-
-# ================== APP INIT ================== #
-
-app = FastAPI(title="RiskGuard AI - Credit Risk Engine")
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-# ================== LOAD MODEL ON START ================== #
-
-predictor = CreditRiskPredictor()
-
-# ================== SCHEMAS ================== #
-
-class CreditRiskInput(BaseModel):
-    age: int
-    income: float
-    loan_amount: float
-    loan_tenure_months: int
-    avg_dpd_per_delinquency: float
-    delinquency_ratio: float
-    credit_utilization_ratio: float
-    num_open_accounts: int
-    residence_type: str
-    loan_purpose: str
-    loan_type: str
-
-
-class CreditRiskOutput(BaseModel):
-    probability: float
-    credit_score: int
-    rating: str
-    advisor_response: str | None = None
-
-
-class ChatMessage(BaseModel):
-    thread_id: str
-    message: str
-    probability: float
-    credit_score: int
-    rating: str
-    advisor_reply: str
-
-
-class TTSRequest(BaseModel):
-    text: str
-
-
-# ================== HEALTH ================== #
-
-@app.get("/")
-def root():
-    return {"status": "RiskGuard AI API is running."}
-
-
-# ================== CREDIT RISK ================== #
-
-@app.post("/predict_credit_risk", response_model=CreditRiskOutput)
-def predict_credit_risk(input_data: CreditRiskInput):
-    try:
-        input_dict = input_data.dict()
-
-        probability, credit_score, rating = predictor.predict(input_dict)
-
-        advisor_reply = generate_advice(
-            probability=probability,
-            credit_score=credit_score,
-            rating=rating
-        )
-
-        return CreditRiskOutput(
-            probability=probability,
-            credit_score=credit_score,
-            rating=rating,
-            advisor_response=advisor_reply
-        )
-
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-
-# ================== CHAT STREAM ================== #
-
-@app.post("/chat")
-async def chat(message_data: ChatMessage):
-
-    async def event_generator():
-        for chunk in ask_chatbot(
-            message_data.probability,
-            message_data.credit_score,
-            message_data.rating,
-            message_data.advisor_reply,
-            message_data.message,
-            message_data.thread_id
-        ):
-            yield chunk
-
-    return StreamingResponse(event_generator(), media_type="text/plain")
-
-
-# ================== TTS ================== #
-
-@app.post("/tts")
-async def generate_tts(request: TTSRequest):
-    try:
-        if not request.text.strip():
-            raise HTTPException(status_code=400, detail="Text is empty")
-
-        audio_path = await TTS(text=request.text)
-
-        if not os.path.exists(audio_path):
-            raise HTTPException(status_code=500, detail="Audio file not created")
-
-        return FileResponse(
-            path=audio_path,
-            media_type="audio/mpeg",
-            filename="speech.mp3"
-        )
-
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-
-# ================== STT ================== #
-
-@app.post("/stt")
-async def transcribe_audio(file: UploadFile = File(...)):
-    try:
-        return await STT(file)
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))