merging docs for mistral

components/generators/daily_feed.py

@@ -45,25 +45,34 @@ BASE_PROMPT = (
 
 def summarize_topic(docs: List[str], topic: str) -> List[Dict]:
     feed = []
-    for doc in docs[:5]:
-        tail_prompt = f"Topic: {topic}\n\n{doc.strip()}"
-        print(f"\n📤 Prompt tail for LLaMA-3 8B:\n{tail_prompt[:300]}...\n")
-        summary_block = call_mistral(base_prompt=BASE_PROMPT, tail_prompt=tail_prompt)
-
-        if summary_block:
-            for line in summary_block.splitlines():
-                line = line.strip()
-                if line.startswith("-") or line.startswith("–"):
-                    clean_summary = line.lstrip("-–").strip()
-                    if clean_summary:
-                        feed.append({
-                            "summary": clean_summary,
-                            "image_url": "https://source.unsplash.com/800x600/?news",
-                            "article_link": f"https://google.com/search?q={topic.replace(' ', '+')}"
-                        })
+    if not docs:
+        return feed
+
+    # 🧠 Merge all docs with separators
+    merged_context = "\n\n---\n\n".join(doc.strip() for doc in docs)
+    tail_prompt = f"Topic: {topic}\n\n{merged_context}"
+
+    print(f"\n📤 Prompt tail for summarization:\n{tail_prompt[:500]}...\n")
+
+    # 🧠 Single call to summarizer
+    summary_block = call_mistral(base_prompt=BASE_PROMPT, tail_prompt=tail_prompt)
+
+    if summary_block:
+        for line in summary_block.splitlines():
+            line = line.strip()
+            if line.startswith("-") or line.startswith("–"):
+                clean_summary = line.lstrip("-–").strip()
+                if clean_summary:
+                    feed.append({
+                        "summary": clean_summary,
+                        "image_url": "https://source.unsplash.com/800x600/?news",
+                        "article_link": f"https://google.com/search?q={topic.replace(' ', '+')}"
+                    })
+
     return feed
 
 
+
 # ⚡ Generate and cache daily feed
 def generate_and_cache_daily_feed(documents: List[Document]):
     index = VectorStoreIndex.from_documents(documents)