Update llm_node.py

llm_node.py

@@ -1,32 +1,30 @@
 from langchain_community.llms import HuggingFaceHub
 
-def llm_node(question):
-    # Initialize the Hugging Face model
+def llm_node(question, search_result):
+    # Initialize Hugging Face model (free)
     llm = HuggingFaceHub(
-        repo_id="HuggingFaceH4/zephyr-7b-beta",  # You can replace with e.g., mistralai/Mistral-7B-Instruct-v0.2
+        repo_id="HuggingFaceH4/zephyr-7b-beta",  # You can swap with mistral or mixtral if needed
         model_kwargs={
-            "temperature": 0.1,          # Keep responses deterministic
-            "max_new_tokens": 500        # Allow for longer outputs if needed
+            "temperature": 0.1,
+            "max_new_tokens": 500
         }
     )
 
-    # Craft the prompt carefully for exact-match outputs
+    # Build prompt combining search + question
     prompt = f"""You are solving a GAIA benchmark evaluation question.
 
-⚠️ VERY IMPORTANT:
-- ONLY return the final answer, exactly as required.
-- DO NOT include explanations, prefixes, or notes.
-- Format the answer exactly as asked (e.g., comma-separated, plural, in requested order).
-- If the question asks for a list, give only the list, no intro.
-
 Here’s the question:
-
 {question}
 
-Your direct answer:"""
+Here’s retrieved information:
+{search_result}
+
+⚠️ VERY IMPORTANT:
+- ONLY return the final answer, exactly as required.
+- Do NOT include explanations, prefixes, or notes.
+- If the question asks for a list, give only the list, in the requested format.
+
+Your answer:"""
 
-    # Run the model
     response = llm.invoke(prompt)
-    
-    # Clean up whitespace or stray characters
     return response.strip()