Update app.py

app.py

@@ -13,7 +13,8 @@ import moviepy.editor as mp
 from groq import Groq
 from langchain_groq import ChatGroq
 from langchain.agents import AgentExecutor, create_tool_calling_agent
-from langchain_tavily_search import TavilySearchResults
+# --- CORRECTED TAVILY IMPORT ---
+from langchain_tavily import TavilySearchResults
 from langchain_core.prompts import ChatPromptTemplate
 from langchain.tools import Tool
 
@@ -77,7 +78,6 @@ class LangChainAgent:
     def __init__(self, groq_api_key: str, tavily_api_key: str):
         self.llm = ChatGroq(model_name="llama3-70b-8192", groq_api_key=groq_api_key, temperature=0.0)
 
-        # Updated tools with much more specific descriptions
         self.tools = [
             TavilySearchResults(
                 name="web_search",
@@ -97,7 +97,6 @@ class LangChainAgent:
             ),
         ]
         
-        # Updated, rule-based system prompt
         prompt = ChatPromptTemplate.from_messages([
             ("system", (
                 "You are a powerful problem-solving agent. Your goal is to answer the user's question accurately. "
@@ -119,11 +118,10 @@ class LangChainAgent:
         self.agent_executor = AgentExecutor(agent=agent, tools=self.tools, verbose=True, handle_parsing_errors=True)
 
     def __call__(self, question: str, task_id: str) -> str:
-        # The agent sometimes needs the URL directly, so let's extract it if present.
         urls = re.findall(r'https?://[^\s]+', question)
         input_for_agent = {"input": question, "task_id": task_id}
         if urls:
-            input_for_agent['video_url'] = urls[0] # Pass the URL if found
+            input_for_agent['video_url'] = urls[0]
             
         try:
             response = self.agent_executor.invoke(input_for_agent)
@@ -131,7 +129,7 @@ class LangChainAgent:
         except Exception as e:
             return f"Agent execution failed with an error: {e}"
 
-# --- Main Application Logic (Unchanged) ---
+# --- Main Application Logic ---
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     space_id = os.getenv("SPACE_ID")
     if not profile: return "Please Login to Hugging Face with the button.", None
@@ -172,7 +170,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         return final_status, pd.DataFrame(results_log)
     except Exception as e: return f"Submission Failed: {e}", pd.DataFrame(results_log)
 
-# --- Gradio Interface (Unchanged) ---
+# --- Gradio Interface ---
 with gr.Blocks() as demo:
     gr.Markdown("# Ultimate Agent Runner (Search + Audio + Video)")
     gr.Markdown("This agent can search, transcribe audio files, and transcribe YouTube videos.")