Delete app

app/__init__.py

@@ -1,9 +0,0 @@
-# app/__init__.py
-import os
-from .app import app
-
-# Load environment variables
-os.environ.setdefault("APP_ENV", "development")
-
-# Log environment
-print(f"Running in {os.environ['APP_ENV']} mode.")

app/app.py

@@ -1,189 +0,0 @@
-from fastapi import FastAPI, HTTPException
-from pydantic import BaseModel
-from typing import List, Dict
-from transformers import pipeline
-from itertools import groupby
-
-# Initialize the FastAPI app
-app = FastAPI()
-
-# Initialize the NER pipeline
-ner_pipeline = pipeline(
-    "ner",
-    model="dbmdz/bert-large-cased-finetuned-conll03-english",
-    grouped_entities=True
-)
-
-# Initialize the QA pipeline
-qa_pipeline = pipeline(
-    "question-answering",
-    model="deepset/roberta-base-squad2"
-)
-
-# Allowed domains for filtering
-allowed_domains = [
-    "clothing",
-    "fashion",
-    "shopping",
-    "accessories",
-    "sustainability",
-    "shoes",
-    "hats",
-    "shirts",
-    "dresses",
-    "pants",
-    "jeans",
-    "skirts",
-    "jackets",
-    "coats",
-    "t-shirts",
-    "sweaters",
-    "hoodies",
-    "activewear",
-    "formal wear",
-    "casual wear",
-    "sportswear",
-    "outerwear",
-    "swimwear",
-    "underwear",
-    "lingerie",
-    "socks",
-    "scarves",
-    "gloves",
-    "belts",
-    "ties",
-    "caps",
-    "beanies",
-    "boots",
-    "sandals",
-    "heels",
-    "sneakers",
-    "materials",
-    "cotton",
-    "polyester",
-    "wool",
-    "silk",
-    "leather",
-    "denim",
-    "linen",
-    "athleisure",
-    "ethnic wear",
-    "fashion trends",
-    "custom clothing",
-    "tailoring",
-    "sustainable materials",
-    "recycled clothing",
-    "fashion brands",
-    "streetwear"
-]
-
-# Pydantic models for structured response
-class Entity(BaseModel):
-    word: str
-    entity_group: str
-    score: float
-
-class NERResponse(BaseModel):
-    entities: List[Entity]
-
-class QAResponse(BaseModel):
-    question: str
-    answer: str
-    score: float
-
-class CombinedRequest(BaseModel):
-    text: str  # The input text prompt
-
-class CombinedResponse(BaseModel):
-    ner: NERResponse  # NER output
-    qa: QAResponse  # QA output
-
-# Function to check if the input text belongs to allowed domains
-def is_text_in_allowed_domain(text: str, domains: List[str]) -> bool:
-    for domain in domains:
-        if domain in text.lower():
-            return True
-    return False
-
-# Combined endpoint for NER and QA with domain filtering
-@app.post("/process/", response_model=CombinedResponse)
-async def process_request(request: CombinedRequest):
-    """
-    Process the input text for both NER and QA, returning both responses,
-    only if the text matches the allowed domains.
-    """
-    input_text = request.text
-
-    # Check if the input text belongs to the allowed domains
-    if not is_text_in_allowed_domain(input_text, allowed_domains):
-        raise HTTPException(
-            status_code=400,
-            detail=(
-                "The input text does not match the allowed domains. "
-                "Please provide a query related to clothing, fashion, or accessories."
-            )
-        )
-
-    # Perform Named Entity Recognition (NER)
-    ner_entities = ner_pipeline(input_text)
-
-    # Process the NER entities into the required format
-    formatted_entities = [
-        {
-            "word": entity["word"],
-            "entity_group": entity["entity_group"],
-            "score": float(entity["score"]),  # Convert numpy.float32 to Python float
-        }
-        for entity in ner_entities
-    ]
-    ner_response = {"entities": formatted_entities}
-
-    # Perform Question Answering (QA)
-    qa_result = qa_pipeline(question=input_text, context=input_text)
-    qa_result["score"] = float(qa_result["score"])  # Convert numpy.float32 to Python float
-
-    qa_response = {
-        "question": input_text,
-        "answer": qa_result["answer"],
-        "score": qa_result["score"]
-    }
-
-    # Return both NER and QA responses
-    return {"ner": ner_response, "qa": qa_response}
-
-
-# Root endpoint
-@app.get("/")
-async def root():
-    """
-    Root endpoint to confirm the server is running.
-    """
-    return {"message": "Welcome to the filtered NER and QA API!"}
-
-
-# JSon response
-
-# {
-#   "entities": [
-#     {
-#       "word": "Nike",
-#       "entity_group": "ORG",
-#       "score": 0.995
-#     },
-#     {
-#       "word": "running shoes",
-#       "entity_group": "PRODUCT",
-#       "score": 0.987
-#     },
-#     {
-#       "word": "outdoor activities",
-#       "entity_group": "ACTIVITY",
-#       "score": 0.960
-#     }
-#   ]
-# }
-# {
-#   "question": "Can you suggest comfortable Nike running shoes for outdoor activities?",
-#   "answer": "Nike Air Zoom Pegasus or React Infinity Run are great options for outdoor running.",
-#   "score": 0.978
-# }