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Update app.py
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app.py
CHANGED
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@@ -2,6 +2,8 @@ import json
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import uuid
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import asyncio
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import os
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from datetime import datetime, timedelta
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from urllib.parse import urlparse
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from fastapi import FastAPI, Query, BackgroundTasks
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@@ -9,22 +11,45 @@ from fastapi.responses import JSONResponse
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from rapidfuzz import process, fuzz
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from cryptography.fernet import Fernet
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# --- 1. SETUP
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# Note: Production me Fernet key ko environment variable se lena chahiye.
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SECRET_KEY = Fernet.generate_key()
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cipher_suite = Fernet(SECRET_KEY)
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# Logs
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LOG_DIR = "logs"
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os.makedirs(LOG_DIR, exist_ok=True)
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# --- 2. LOAD DATA FROM dataset.jsonl ---
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raw_data = []
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search_corpus = []
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global raw_data, search_corpus
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try:
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with open("dataset.jsonl", "r", encoding="utf-8") as f:
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@@ -33,7 +58,6 @@ def load_dataset():
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item = json.loads(line)
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raw_data.append(item)
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# Domain, title aur description nikal kar corpus me dalna
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domain = urlparse(item.get("url", "")).netloc
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text_to_search = f"{domain} {item.get('title', '')} {item.get('description', '')}"
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search_corpus.append(text_to_search.lower())
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@@ -41,16 +65,23 @@ def load_dataset():
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except FileNotFoundError:
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print("❌ ERROR: dataset.jsonl file not found in the directory!")
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#
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# ---
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async def log_query_encrypted(req_id: str, query: str):
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encrypted_q = cipher_suite.encrypt(query.encode()).decode()
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now = datetime.now()
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# Date ke hisaab se file ka naam banega (e.g., search_logs_2026-07-22.jsonl)
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date_str = now.strftime("%Y-%m-%d")
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log_file = os.path.join(LOG_DIR, f"search_logs_{date_str}.jsonl")
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@@ -60,43 +91,10 @@ async def log_query_encrypted(req_id: str, query: str):
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"timestamp": now.isoformat()
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}
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# File me append karna (Agar file nahi hai toh khud ban jayegi)
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with open(log_file, "a", encoding="utf-8") as f:
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f.write(json.dumps(log_entry) + "\n")
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# --- 4. OPTIMIZED 1 MONTH LOG CLEANUP ---
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async def cleanup_old_logs():
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while True:
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try:
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if os.path.exists(LOG_DIR):
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thirty_days_ago = datetime.now() - timedelta(days=30)
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# Folder ki saari files check karenge
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for filename in os.listdir(LOG_DIR):
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if filename.startswith("search_logs_") and filename.endswith(".jsonl"):
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# File ke naam se date nikalenge
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date_part = filename.replace("search_logs_", "").replace(".jsonl", "")
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try:
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file_date = datetime.strptime(date_part, "%Y-%m-%d")
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# Agar file 30 din se purani hai, toh puri file delete kar do
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if file_date < thirty_days_ago:
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os.remove(os.path.join(LOG_DIR, filename))
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print(f"🗑️ Deleted 1-month old log file: {filename}")
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except ValueError:
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pass
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except Exception as e:
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print("Cleanup Error:", e)
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# Har 24 ghante me ek baar check karega
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await asyncio.sleep(24 * 60 * 60)
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@app.on_event("startup")
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async def startup_event():
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# Background me cleanup task on startup
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asyncio.create_task(cleanup_old_logs())
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# --- 5. FAST AI / NLP LOGIC ---
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def check_self_harm(query: str) -> bool:
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harm_keywords = ["suicide", "kill myself", "die", "harm myself", "end my life", "suiside"]
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@@ -128,7 +126,7 @@ def ai_fallback_search(query: str):
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async def search(q: str = Query(..., description="Search query"), background_tasks: BackgroundTasks = BackgroundTasks()):
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req_id = str(uuid.uuid4())
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# Background Logging
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background_tasks.add_task(log_query_encrypted, req_id, q)
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# Self-Harm Check
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@@ -146,7 +144,7 @@ async def search(q: str = Query(..., description="Search query"), background_tas
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final_results = []
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# RapidFuzz search algorithm
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if search_corpus:
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results = process.extract(
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q.lower(),
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@@ -157,7 +155,7 @@ async def search(q: str = Query(..., description="Search query"), background_tas
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for match_str, score, index in results:
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if score > 40:
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result_item = raw_data[index].copy()
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result_item["match_score"] = round(score, 2)
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final_results.append(result_item)
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@@ -172,10 +170,15 @@ async def search(q: str = Query(..., description="Search query"), background_tas
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response_data["request_id"] = req_id
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# Adult Content
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if is_adult:
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response_data["safety_message"] = "you are safe you can do anything"
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headers = {"X-Safety-Message": "you are safe you can do anything"}
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return JSONResponse(content=response_data, headers=headers)
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return response_data
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import uuid
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import asyncio
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import os
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import uvicorn
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from contextlib import asynccontextmanager
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from datetime import datetime, timedelta
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from urllib.parse import urlparse
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from fastapi import FastAPI, Query, BackgroundTasks
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from rapidfuzz import process, fuzz
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from cryptography.fernet import Fernet
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# --- 1. SETUP & ENCRYPTION ---
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SECRET_KEY = Fernet.generate_key()
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cipher_suite = Fernet(SECRET_KEY)
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# Logs directory setup
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LOG_DIR = "logs"
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os.makedirs(LOG_DIR, exist_ok=True)
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# Global variables for dataset
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raw_data = []
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search_corpus = []
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# --- 2. OPTIMIZED CLEANUP TASK ---
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async def cleanup_old_logs():
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while True:
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try:
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if os.path.exists(LOG_DIR):
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thirty_days_ago = datetime.now() - timedelta(days=30)
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for filename in os.listdir(LOG_DIR):
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if filename.startswith("search_logs_") and filename.endswith(".jsonl"):
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date_part = filename.replace("search_logs_", "").replace(".jsonl", "")
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try:
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file_date = datetime.strptime(date_part, "%Y-%m-%d")
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if file_date < thirty_days_ago:
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os.remove(os.path.join(LOG_DIR, filename))
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print(f"🗑️ Deleted 1-month old log file: {filename}")
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except ValueError:
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pass
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except Exception as e:
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print("Cleanup Error:", e)
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# Har 24 ghante me ek baar check
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await asyncio.sleep(24 * 60 * 60)
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# --- 3. LIFESPAN (Replaces @app.on_event("startup")) ---
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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# a. Dataset Loading during startup
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global raw_data, search_corpus
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try:
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with open("dataset.jsonl", "r", encoding="utf-8") as f:
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item = json.loads(line)
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raw_data.append(item)
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domain = urlparse(item.get("url", "")).netloc
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text_to_search = f"{domain} {item.get('title', '')} {item.get('description', '')}"
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search_corpus.append(text_to_search.lower())
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except FileNotFoundError:
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print("❌ ERROR: dataset.jsonl file not found in the directory!")
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# b. Start background cleanup task
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cleanup_task = asyncio.create_task(cleanup_old_logs())
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yield # App jab tak chalegi, yaha yield rahega
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# c. App shutdown hone par task cancel karna
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cleanup_task.cancel()
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# Pass lifespan to FastAPI
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app = FastAPI(title="Fast Search API", lifespan=lifespan)
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# --- 4. DATE-BASED LOGGING & ENCRYPTION ---
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async def log_query_encrypted(req_id: str, query: str):
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encrypted_q = cipher_suite.encrypt(query.encode()).decode()
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now = datetime.now()
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date_str = now.strftime("%Y-%m-%d")
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log_file = os.path.join(LOG_DIR, f"search_logs_{date_str}.jsonl")
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"timestamp": now.isoformat()
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}
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with open(log_file, "a", encoding="utf-8") as f:
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f.write(json.dumps(log_entry) + "\n")
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# --- 5. FAST AI / NLP LOGIC ---
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def check_self_harm(query: str) -> bool:
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harm_keywords = ["suicide", "kill myself", "die", "harm myself", "end my life", "suiside"]
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async def search(q: str = Query(..., description="Search query"), background_tasks: BackgroundTasks = BackgroundTasks()):
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req_id = str(uuid.uuid4())
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# Background Logging
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background_tasks.add_task(log_query_encrypted, req_id, q)
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# Self-Harm Check
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final_results = []
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# RapidFuzz search algorithm
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if search_corpus:
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results = process.extract(
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q.lower(),
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for match_str, score, index in results:
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if score > 40:
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result_item = raw_data[index].copy()
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result_item["match_score"] = round(score, 2)
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final_results.append(result_item)
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response_data["request_id"] = req_id
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# Adult Content Safety Modification
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if is_adult:
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response_data["safety_message"] = "you are safe you can do anything"
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headers = {"X-Safety-Message": "you are safe you can do anything"}
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return JSONResponse(content=response_data, headers=headers)
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return response_data
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# --- 7. START SERVER FOR GRADIO SPACE ---
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# Ye block Gradio Space ko bata dega ki port 7860 par API continuously chalani hai.
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if __name__ == "__main__":
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uvicorn.run(app, host="0.0.0.0", port=7860)
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