first version of ask

question.py

@@ -0,0 +1,56 @@
+# app/routes/question.py
+import os
+import requests
+from fastapi import APIRouter, Query
+from pydantic import BaseModel
+from typing import List
+from redis_client import redis_client as r
+from transformers import pipeline
+import re
+from dotenv import load_dotenv
+
+load_dotenv()
+
+GNEWS_API_KEY = os.getenv("GNEWS_API_KEY")
+
+router = APIRouter()
+
+qa_model = pipeline("text2text-generation", model="google/flan-t5-base")  # replace with your preferred model
+
+class QuestionInput(BaseModel):
+    question: str
+
+@router.post("/ask")
+async def ask_question(input: QuestionInput):
+    question = input.question
+
+    # Extract keywords (simple version)
+    keywords = re.findall(r"\b\w{4,}\b", question)
+    query_string = "+".join(keywords[:5])  # Limit to top 5 keywords
+
+    gnews_url = f"https://gnews.io/api/v4/search?q={query_string}&lang=en&max=3&expand=content&token={GNEWS_API_KEY}"
+    try:
+        response = requests.get(gnews_url, timeout=10)
+        response.raise_for_status()
+        articles = response.json().get("articles", [])
+    except Exception as e:
+        return {"error": f"GNews API error: {str(e)}"}
+
+    # Combine article content for context
+    context = "\n\n".join([
+        article.get("content") or article.get("description") or ""
+        for article in articles
+    ])
+
+    # Build prompt
+    prompt = f"Context:\n{context}\n\nQuestion: {question}\nAnswer:"
+    result = qa_model(prompt, max_length=256, do_sample=False)[0]['generated_text']
+
+    return {
+        "question": question,
+        "answer": result.strip(),
+        "sources": [
+            {"title": a["title"], "url": a["url"]}
+            for a in articles
+        ]
+    }

requirements.txt

@@ -2,4 +2,6 @@ fastapi
 uvicorn[standard]
 requests
 python-dotenv
-redis
+redis
+transformers
+torch