changes v17

question.py

@@ -33,6 +33,11 @@ def extract_last_keywords(raw: str, max_keywords=6):
             return parts
     return []
 
+def is_relevant(article, keywords):
+    text = f"{article.get('title', '')} {article.get('content', '')}".lower()
+    return any(kw.lower() in text for kw in keywords)
+
+
 def mistral_generate(prompt: str, max_new_tokens=128):
     payload = {
         "inputs": prompt,
@@ -93,10 +98,12 @@ async def ask_question(input: QuestionInput):
 
     print("Fetched articles:", articles)
 
+    relevant_articles = [a for a in articles if is_relevant(a, keywords)]
+
     context = "\n\n".join([
-        article.get("content") or article.get("description") or ""
-        for article in articles
-    ])[:1500]
+        a.get("content") or ""
+        for a in relevant_articles
+    ])[:15000]
 
     if not context.strip():
         return {
@@ -107,9 +114,11 @@ async def ask_question(input: QuestionInput):
 
     # Step 3: Ask Mistral to answer using the context
     answer_prompt = (
-        f"<s>[INST] You are a news aggregator and generate responses like one. Say things like you already know it and you're informing the user. Use the context below to answer the question. "
-        f"If not enough information is available, say 'Cannot answer'.\n\n"
-        f"Context:\n{context}\n\nQuestion: {question} [/INST]"
+        f"You are a concise news assistant. Answer the user's question clearly using the context below if relevant. "
+        f"If the context is not helpful, you may rely on your own knowledge, but do not mention the context or question again.\n\n"
+        f"Context:\n{context}\n\n"
+        f"Question: {question}\n\n"
+        f"Answer:"
     )
     answer = mistral_generate(answer_prompt, max_new_tokens=256)
     if not answer: