update

agent.py

@@ -27,7 +27,7 @@ class State(TypedDict):
 
 def get_llm():
     os.getenv("GROQ_API_KEY")
-    # return init_chat_model("llama-3.3-70b-versatile", model_provider="groq")
+    #return init_chat_model("llama-3.3-70b-versatile", model_provider="groq")
 
     return init_chat_model("gemini-2.0-flash", model_provider="google_genai")
 
@@ -143,7 +143,8 @@ def get_graph(llm):
         """
         print("\n-------------------- Tool (Tavily) has been called --------------------\n")
         print("The query is: ", query)
-        docs = tavily_retriever.invoke(query)
+        # docs = tavily_retriever.invoke(query)
+        docs = TavilySearchResults(max_results=3).invoke({'query': query})
         serialized = "\n\n".join(
             (f"\nContent:\n{doc.page_content}")
             for doc in docs
@@ -157,10 +158,11 @@ def get_graph(llm):
 
         Args:
             query: The search query."""
+        print("\n-------------------- Tool (Tavily) has been called --------------------\n")
         search_docs = TavilySearchResults(max_results=3).invoke({'query': query})
         formatted_search_docs = "\n\n---\n\n".join(
             [
-                f'<Document source="{doc.metadata["source"]}" page="{doc.metadata.get("page", "")}"/>\n{doc.page_content}\n</Document>'
+                f'URL: {doc["url"]}\nTitle= {doc["title"]}\nContent: {doc["content"]}'
                 for doc in search_docs
             ])
         return {"web_results": formatted_search_docs}

app.py

@@ -126,8 +126,8 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     answers_payload = []
     print(f"Running agent on {len(questions_data)} questions...")
     for item in questions_data:
-        print("Waiting for 10 seconds...")
-        time.sleep(10)
+        print("Waiting for 12 seconds...")
+        time.sleep(12)
         task_id = item.get("task_id")
         question_text = item.get("question")
         content_type = None