Update tools/orchestrator.py

tools/orchestrator.py

@@ -3,6 +3,7 @@ import json
 import re
 import logging
 import time
+from datetime import datetime
 from huggingface_hub import whoami
 
 from model_logic import call_model_stream, MODELS_BY_PROVIDER, get_default_model_display_name_for_provider
@@ -61,7 +62,11 @@ def orchestrate_and_respond(user_input: str, provider_name: str, model_display_n
     logger.info(f"ORCHESTRATOR [{request_id}]: Tool Decision: Action='{action_type}', Input='{action_input}'")
     
     yield "status", f"[Path: {action_type}]"
-    final_system_prompt = custom_system_prompt or prompts.DEFAULT_SYSTEM_PROMPT
+    
+    current_time_str = datetime.utcnow().strftime("%Y-%m-%d %H:%M:%S UTC")
+    base_system_prompt = custom_system_prompt or prompts.DEFAULT_SYSTEM_PROMPT
+    final_system_prompt = base_system_prompt.format(current_date_time=current_time_str)
+
     context_str = None
 
     if action_type == "create_huggingface_space":
@@ -70,7 +75,6 @@ def orchestrate_and_respond(user_input: str, provider_name: str, model_display_n
             try:
                 hf_token = os.getenv("HF_TOKEN")
                 if not hf_token: raise ValueError("Hugging Face token (HF_TOKEN) not found.")
-                
                 yield "status", "[Tool: Verifying user identity...]"
                 user_info = whoami(token=hf_token)
                 owner = user_info.get("name")
@@ -85,65 +89,46 @@ def orchestrate_and_respond(user_input: str, provider_name: str, model_display_n
                 ]
                 markdown_content = "".join(list(call_model_stream(provider_name, model_display_name, space_gen_messages, ui_api_key_override, 0.1, 4096)))
                 yield "status", "[Tool: Creating Space...]"
-                result = create_huggingface_space(
-                    owner=owner,
-                    space_name=action_input["space_name"],
-                    sdk=action_input["sdk"],
-                    markdown_content=markdown_content.strip()
-                )
+                result = create_huggingface_space(owner=owner, space_name=action_input["space_name"], sdk=action_input["sdk"], markdown_content=markdown_content.strip())
                 context_str = f"Tool Result (Create Space): {result.get('result') or result.get('error', 'Unknown outcome')}"
+                final_system_prompt += " The space building tool has completed. Inform the user about the result, providing any links or key information from the tool's output."
             except Exception as e:
                 context_str = f"Tool Failed: An error occurred during space creation process - {e}"
         else:
             context_str = "Tool Failed: Missing parameters for create_huggingface_space. Required: " + ", ".join(params)
-    elif action_type == "list_huggingface_space_files":
-        params = ["owner", "space_name"]
-        if all(p in action_input for p in params):
-            yield "status", "[Tool: Listing files...]"
-            result = list_huggingface_space_files(**action_input)
-            if "error" in result:
-                context_str = f"Tool Result (List Files): Error - {result['error']}"
-            else:
-                files_list = result.get("files", [])
-                files_str = "\n- ".join(files_list) if files_list else "No files found."
-                context_str = f"Tool Result (List Files):\nStatus: {result.get('status', 'OK')}\nFiles:\n- {files_str}"
-        else:
-            context_str = "Tool Failed: Missing parameters for list_huggingface_space_files. Required: " + ", ".join(params)
-    elif action_type == "get_huggingface_space_file_content":
-        params = ["owner", "space_name", "file_path"]
-        if all(p in action_input for p in params):
-            yield "status", "[Tool: Reading file content...]"
-            result = get_huggingface_space_file_content(**action_input)
-            if "error" in result:
-                context_str = f"Tool Result (Get Content): Error - {result['error']}"
-            else:
-                context_str = f"Tool Result (Get Content for '{action_input['file_path']}'):\nStatus: {result.get('status', 'OK')}\n```\n{result.get('content', '')}\n```"
-        else:
-            context_str = "Tool Failed: Missing parameters for get_huggingface_space_file_content. Required: " + ", ".join(params)
-    elif action_type == "update_huggingface_space_file":
-        params = ["owner", "space_name", "file_path", "new_content", "commit_message"]
+    elif action_type in ["list_huggingface_space_files", "get_huggingface_space_file_content", "update_huggingface_space_file"]:
+        tool_map = {
+            "list_huggingface_space_files": (list_huggingface_space_files, ["owner", "space_name"], "Listing files"),
+            "get_huggingface_space_file_content": (get_huggingface_space_file_content, ["owner", "space_name", "file_path"], "Reading file content"),
+            "update_huggingface_space_file": (update_huggingface_space_file, ["owner", "space_name", "file_path", "new_content", "commit_message"], "Updating file")
+        }
+        tool_func, params, status_msg = tool_map[action_type]
         if all(p in action_input for p in params):
-            yield "status", "[Tool: Updating file...]"
-            result = update_huggingface_space_file(**action_input)
-            context_str = f"Tool Result (Update File): {result.get('result') or result.get('error', 'Unknown outcome')}"
+            yield "status", f"[Tool: {status_msg}...]"
+            result = tool_func(**action_input)
+            context_str = f"Tool Result ({action_type}): {result}"
+            final_system_prompt += " A file operation tool has completed. Inform the user about the result, presenting the data clearly."
         else:
-            context_str = "Tool Failed: Missing parameters for update_huggingface_space_file. Required: " + ", ".join(params)
+            context_str = f"Tool Failed: Missing parameters for {action_type}. Required: " + ", ".join(params)
     elif action_type == "search_duckduckgo_and_report" and WEB_SEARCH_ENABLED:
         query = action_input.get("search_engine_query")
         if query:
             yield "status", f"[Web: '{query[:60]}'...]"
             results = search_and_scrape_duckduckgo(query, num_results=2)
             context_str = "Web Content:\n" + "\n".join([f"Source {i+1} ({r.get('url','N/A')}):\n{r.get('content', r.get('error', 'N/A'))[:3000]}\n---" for i, r in enumerate(results)])
+            final_system_prompt += " Generate a report/answer from the provided web content, history, & guidelines. Cite URLs as [Source X]."
     elif action_type == "scrape_url_and_report" and WEB_SEARCH_ENABLED:
         url = action_input.get("url")
         if url:
             yield "status", f"[Web: '{url[:60]}'...]"
             result = scrape_url(url)
             context_str = f"Web Content for {url}:\n{result.get('content', result.get('error', 'No content scraped.'))}"
+            final_system_prompt += " Summarize or answer questions based on the scraped web page content."
     elif action_type == "answer_using_conversation_memory":
         yield "status", "[Searching conversation memory...]"
         mems = retrieve_memories_semantic(f"User query: {user_input}\nContext:\n{history_str_for_prompt[-1000:]}", k=2)
         context_str = "Relevant Past Interactions:\n" + "\n".join([f"- User:{m.get('user_input','')}->AI:{m.get('bot_response','')} (Takeaway:{m.get('metrics',{}).get('takeaway','N/A')})" for m in mems]) if mems else "No relevant past interactions found."
+        final_system_prompt += " Respond using the provided Memory Context, your general knowledge, and the conversation history."
     
     final_user_prompt = prompts.get_final_response_prompt(history_str_for_prompt, initial_insights_ctx_str, user_input, context_str)
     final_llm_messages = [{"role": "system", "content": final_system_prompt}, {"role": "user", "content": final_user_prompt}]