Update app.py

app.py

@@ -129,9 +129,23 @@ def process_user_interaction_gradio(user_input: str, provider_name: str, model_d
         yield "status", "<i>[LLM choosing best approach...]</i>"
         history_snippet = "\n".join([f"{msg['role']}: {msg['content'][:100]}" for msg in chat_history_for_prompt[-2:]])
         guideline_snippet = initial_insights_ctx_str[:200].replace('\n', ' ')
-        tool_sys_prompt = "You are a precise routing agent... Output JSON only. Example: {\"action\": \"search_duckduckgo_and_report\", \"action_input\": {\"search_engine_query\": \"query\"}}"
-        tool_user_prompt = f"User Query: \"{user_input}\nRecent History:\n{history_snippet}\nGuidelines: {guideline_snippet}...\nAvailable Actions: quick_respond, answer_using_conversation_memory, search_duckduckgo_and_report, scrape_url_and_report.\nSelect one action and input. Output JSON."
+        
+        # --- MODIFIED: Improved prompts for the tool-decision LLM ---
+        tool_sys_prompt = """You are a precise routing agent. Your job is to analyze the user's query and the conversation context, then select the single best action to provide an answer.
+Output ONLY a single, valid JSON object with "action" and "action_input" keys. Do not add any other text or explanations.
+
+Example: {"action": "search_duckduckgo_and_report", "action_input": {"search_engine_query": "latest AI research"}}
+
+Here are the available actions with descriptions of when to use them:
+- "quick_respond": Use for simple greetings, acknowledgements, or if the answer is obvious from the immediate context and requires no special tools.
+- "answer_using_conversation_memory": Use if the user's query refers to a previous conversation, asks you to "remember" or "recall" something, or seems like it could be answered by a past interaction you've had. This tool searches a database of your past conversations for relevant information.
+- "search_duckduckgo_and_report": Use for general knowledge questions, questions about current events, or when the user explicitly asks you to search the web for information.
+- "scrape_url_and_report": Use ONLY when the user provides a specific URL to read from.
+"""
+        tool_user_prompt = f"User Query: \"{user_input}\"\n\nRecent History:\n{history_snippet}\n\nGuidelines Snippet (for context):\n{guideline_snippet}...\n\nBased on the query and the action descriptions provided in the system prompt, select the single best action to take. Output the corresponding JSON object."
         tool_decision_messages = [{"role":"system", "content": tool_sys_prompt}, {"role":"user", "content": tool_user_prompt}]
+        # --- END OF MODIFICATION ---
+        
         tool_provider, tool_model_id = TOOL_DECISION_PROVIDER_ENV, TOOL_DECISION_MODEL_ID_ENV
         tool_model_display = next((dn for dn, mid in MODELS_BY_PROVIDER.get(tool_provider.lower(), {}).get("models", {}).items() if mid == tool_model_id), None)
         if not tool_model_display: tool_model_display = get_default_model_display_name_for_provider(tool_provider)