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88
gurt/api.py
88
gurt/api.py
@ -676,43 +676,77 @@ async def get_ai_response(cog: 'GurtCog', message: discord.Message, model_name:
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# Append tool response to history
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contents.append(Content(role="function", parts=[tool_response_part]))
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# Continue to the next loop iteration to see if AI calls another tool
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# Add an explicit instruction for the AI to proceed after the tool call
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contents.append(Content(role="user", parts=[Part.from_text(
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"(System Note: The requested tool action has been performed based on the function response above. "
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"Please now generate the final JSON response for the user, acknowledging the action if appropriate.)"
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)]))
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print("Added system note instructing AI to generate final response.")
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# Continue to the next loop iteration to see if AI calls another tool or generates the final response
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else:
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# No function call found in the response parts
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# No function call found in the response parts - AI likely provided the final response directly
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print("No further tool call requested by AI. Exiting loop.")
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break # Exit loop
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# --- After the loop ---
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# Check if a critical API error occurred *during* the loop
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if error_message:
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# An error occurred within the loop or initial API call
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print(f"Exited tool loop due to error: {error_message}")
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# Fallback logic might be needed here depending on the error
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print(f"Exited tool loop due to API error: {error_message}")
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if cog.bot.user.mentioned_in(message) or (message.reference and message.reference.resolved and message.reference.resolved.author == cog.bot.user):
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fallback_response = {"should_respond": True, "content": "...", "react_with_emoji": "❓"}
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fallback_response = {"should_respond": True, "content": "...", "react_with_emoji": "❓"}
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# Check if the loop hit the max iteration limit
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elif tool_calls_made >= max_tool_calls:
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error_message = f"Reached maximum tool call limit ({max_tool_calls}). Aborting further processing."
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error_message = f"Reached maximum tool call limit ({max_tool_calls}). Attempting to generate final response based on gathered context."
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print(error_message)
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# Potentially add a fallback response here too
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fallback_response = {"should_respond": True, "content": "Sorry, that got a bit complicated for me.", "react_with_emoji": "🤯"}
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# Proceed to attempt final JSON generation even if limit was hit
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# The 'last_response_obj' should hold the response from the last (limited) iteration
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if last_response_obj:
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# Attempt to parse JSON from the last response (less likely if limit hit)
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last_response_text_limit = _get_response_text(last_response_obj)
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if last_response_text_limit:
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print("Attempting to parse final JSON from the last loop response (limit hit)...")
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final_parsed_data = parse_and_validate_json_response(
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last_response_text_limit, RESPONSE_SCHEMA['schema'], "final response (from last loop iteration - limit hit)"
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)
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# If parsing failed, make the dedicated final call
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if final_parsed_data is None:
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print("Making dedicated final API call after hitting tool limit...")
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# (Final call logic is duplicated below, consider refactoring later)
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model_final_json = GenerativeModel(model_name or DEFAULT_MODEL, system_instruction=final_system_prompt)
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processed_response_schema = _preprocess_schema_for_vertex(RESPONSE_SCHEMA['schema'])
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generation_config_final_json = GenerationConfig(temperature=0.75, max_output_tokens=10000, response_mime_type="application/json", response_schema=processed_response_schema)
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# Append the last AI response before the final call
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if last_response_obj and last_response_obj.candidates: contents.append(last_response_obj.candidates[0].content)
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final_json_response_obj = await call_vertex_api_with_retry(cog=cog, model=model_final_json, contents=contents, generation_config=generation_config_final_json, safety_settings=STANDARD_SAFETY_SETTINGS, request_desc=f"Final JSON Generation (limit hit) for message {message.id}")
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if not final_json_response_obj or not final_json_response_obj.candidates: error_message += " | Final API call failed."
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else:
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final_response_text = _get_response_text(final_json_response_obj)
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final_parsed_data = parse_and_validate_json_response(final_response_text, RESPONSE_SCHEMA['schema'], "final response (dedicated call - limit hit)")
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if final_parsed_data is None: error_message += " | Failed to parse/validate final dedicated JSON."
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else: print("Successfully parsed final JSON response (after limit hit).")
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else:
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# Should not happen if limit was hit, but handle defensively
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error_message += " | No last response object available after hitting limit."
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fallback_response = {"should_respond": True, "content": "Sorry, that got too complicated.", "react_with_emoji": "🤯"}
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# Loop finished naturally (AI stopped calling tools)
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elif last_response_obj:
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# Loop finished naturally (AI didn't request more tools) or after the last successful tool call.
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# Now, make the FINAL call to get the structured JSON response.
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# Check if the *last* response from the loop *already* contained the final text answer
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# (This can happen if the AI decides to respond directly after the last tool call)
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# The last response object *should* contain the final answer or be parseable
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last_response_text = _get_response_text(last_response_obj)
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if last_response_text:
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print("Attempting to parse final JSON from the last loop response...")
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# Try parsing this text first
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final_parsed_data = parse_and_validate_json_response(
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last_response_text, RESPONSE_SCHEMA['schema'], "final response (from last loop iteration)"
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)
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print("Attempting to parse final JSON from the last natural loop response...")
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final_parsed_data = parse_and_validate_json_response(
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last_response_text, RESPONSE_SCHEMA['schema'], "final response (from last natural loop iteration)"
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)
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# If the last loop response didn't contain valid JSON, make a dedicated final call
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# If parsing the last natural response failed, make the dedicated final call
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if final_parsed_data is None:
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print("Last loop response did not contain valid final JSON. Making dedicated final API call...")
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print("Last natural loop response did not contain valid final JSON. Making dedicated final API call...")
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# Initialize a NEW model instance WITHOUT tools for the final call
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# This seems necessary for reliable JSON schema enforcement with Vertex AI currently
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@ -733,7 +767,7 @@ async def get_ai_response(cog: 'GurtCog', message: discord.Message, model_name:
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# Append the last AI response (which didn't have a tool call) to history before the final call
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if last_response_obj and last_response_obj.candidates:
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contents.append(last_response_obj.candidates[0].content)
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contents.append(last_response_obj.candidates[0].content)
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final_json_response_obj = await call_vertex_api_with_retry(
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cog=cog,
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@ -760,11 +794,11 @@ async def get_ai_response(cog: 'GurtCog', message: discord.Message, model_name:
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# Optional: Add re-prompt logic here if needed, similar to the old single-tool path
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# For simplicity now, just report the error.
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if cog.bot.user.mentioned_in(message) or (message.reference and message.reference.resolved and message.reference.resolved.author == cog.bot.user):
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fallback_response = {"should_respond": True, "content": "...", "react_with_emoji": "❓"}
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fallback_response = {"should_respond": True, "content": "...", "react_with_emoji": "❓"}
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# If parsing succeeded (either from last loop or dedicated call)
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elif final_parsed_data:
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print("Successfully parsed final JSON response.")
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print("Successfully parsed final JSON response.")
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else:
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@ -775,7 +809,7 @@ async def get_ai_response(cog: 'GurtCog', message: discord.Message, model_name:
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error_message = "Tool loop completed without a final response object."
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print(error_message)
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if cog.bot.user.mentioned_in(message) or (message.reference and message.reference.resolved and message.reference.resolved.author == cog.bot.user):
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fallback_response = {"should_respond": True, "content": "...", "react_with_emoji": "❓"}
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fallback_response = {"should_respond": True, "content": "...", "react_with_emoji": "❓"}
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except Exception as e:
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@ -786,7 +820,7 @@ async def get_ai_response(cog: 'GurtCog', message: discord.Message, model_name:
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final_parsed_data = None # Ensure final data is None on error
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# Add fallback if applicable
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if cog.bot.user.mentioned_in(message) or (message.reference and message.reference.resolved and message.reference.resolved.author == cog.bot.user):
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fallback_response = {"should_respond": True, "content": "...", "react_with_emoji": "❓"}
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fallback_response = {"should_respond": True, "content": "...", "react_with_emoji": "❓"}
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# Return dictionary structure remains the same, but initial_response is removed
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