YET ANOTEHR BOTCHED TRACK.
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@@ -11,9 +11,10 @@ This file tracks all major tracks for the project. Each track has its own detail
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1. [x] **Track: Hook API UI State Verification**
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*Link: [./tracks/hook_api_ui_state_verification_20260302/](./tracks/hook_api_ui_state_verification_20260302/)*
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2. [~] **Track: Asyncio Decoupling & Queue Refactor**
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- [x] **Track: Asyncio Decoupling & Queue Refactor**
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*Link: [./tracks/asyncio_decoupling_refactor_20260306/](./tracks/asyncio_decoupling_refactor_20260306/)*
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3. [ ] **Track: Mock Provider Hardening**
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*Link: [./tracks/mock_provider_hardening_20260305/](./tracks/mock_provider_hardening_20260305/)*
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@@ -2,7 +2,7 @@
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"id": "asyncio_decoupling_refactor_20260306",
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"title": "Asyncio Decoupling & Queue Refactor",
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"description": "Rip out asyncio from AppController to eliminate test deadlocks.",
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"status": "planned",
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"status": "terminated",
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"created_at": "2026-03-05T00:00:00Z",
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"updated_at": "2026-03-05T00:00:00Z"
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"updated_at": "2026-03-05T15:45:00Z"
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}
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@@ -679,28 +679,56 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str,
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for r_idx in range(MAX_TOOL_ROUNDS + 2):
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events.emit("request_start", payload={"provider": "gemini", "model": _model, "round": r_idx})
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if stream_callback:
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resp = _gemini_chat.send_message_stream(payload)
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# In 1.0.0, we use send_message with stream=True
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config = types.GenerateContentConfig(
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tools=[types.Tool(function_declarations=[types.FunctionDeclaration(**s) for s in mcp_client.get_tool_schemas()])] if enable_tools else [],
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temperature=_temperature,
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max_output_tokens=_max_tokens,
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)
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resp = _gemini_chat.send_message(payload, config=config, stream=True)
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txt_chunks: list[str] = []
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calls = []
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usage = {}
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reason = "STOP"
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final_resp = None
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for chunk in resp:
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c_txt = chunk.text
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if c_txt:
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txt_chunks.append(c_txt)
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stream_callback(c_txt)
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if chunk.text:
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txt_chunks.append(chunk.text)
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stream_callback(chunk.text)
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if chunk.candidates:
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c = chunk.candidates[0]
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if c.content and c.content.parts:
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calls.extend([p.function_call for p in c.content.parts if p.function_call])
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if hasattr(c, "finish_reason") and c.finish_reason:
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reason = c.finish_reason.name
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if chunk.usage_metadata:
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usage = {
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"input_tokens": chunk.usage_metadata.prompt_token_count,
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"output_tokens": chunk.usage_metadata.candidates_token_count,
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"total_tokens": chunk.usage_metadata.total_token_count,
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"cache_read_input_tokens": getattr(chunk.usage_metadata, "cached_content_token_count", 0)
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}
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final_resp = chunk
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txt = "".join(txt_chunks)
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calls = [p.function_call for c in resp.candidates if getattr(c, "content", None) for p in c.content.parts if hasattr(p, "function_call") and p.function_call]
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usage = {"input_tokens": getattr(resp.usage_metadata, "prompt_token_count", 0), "output_tokens": getattr(resp.usage_metadata, "candidates_token_count", 0)}
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cached_tokens = getattr(resp.usage_metadata, "cached_content_token_count", None)
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if cached_tokens: usage["cache_read_input_tokens"] = cached_tokens
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# Final validation of response object for subsequent code
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resp = final_resp
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else:
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resp = _gemini_chat.send_message(payload)
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txt = "\n".join(p.text for c in resp.candidates if getattr(c, "content", None) for p in c.content.parts if hasattr(p, "text") and p.text)
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calls = [p.function_call for c in resp.candidates if getattr(c, "content", None) for p in c.content.parts if hasattr(p, "function_call") and p.function_call]
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usage = {"input_tokens": getattr(resp.usage_metadata, "prompt_token_count", 0), "output_tokens": getattr(resp.usage_metadata, "candidates_token_count", 0)}
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cached_tokens = getattr(resp.usage_metadata, "cached_content_token_count", None)
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if cached_tokens: usage["cache_read_input_tokens"] = cached_tokens
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if txt: all_text.append(txt)
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events.emit("response_received", payload={"provider": "gemini", "model": _model, "usage": usage, "round": r_idx})
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reason = resp.candidates[0].finish_reason.name if resp.candidates and hasattr(resp.candidates[0], "finish_reason") else "STOP"
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config = types.GenerateContentConfig(
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tools=[types.Tool(function_declarations=[types.FunctionDeclaration(**s) for s in mcp_client.get_tool_schemas()])] if enable_tools else [],
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temperature=_temperature,
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max_output_tokens=_max_tokens,
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)
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resp = _gemini_chat.send_message(payload, config=config)
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txt = resp.text or ""
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calls = [p.function_call for c in resp.candidates if getattr(c, "content", None) for p in c.content.parts if p.function_call]
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usage = {
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"input_tokens": getattr(resp.usage_metadata, "prompt_token_count", 0),
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"output_tokens": getattr(resp.usage_metadata, "candidates_token_count", 0),
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"total_tokens": getattr(resp.usage_metadata, "total_token_count", 0),
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"cache_read_input_tokens": getattr(resp.usage_metadata, "cached_content_token_count", 0)
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}
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reason = resp.candidates[0].finish_reason.name if (resp.candidates and hasattr(resp.candidates[0], "finish_reason")) else "STOP"
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_append_comms("IN", "response", {"round": r_idx, "stop_reason": reason, "text": txt, "tool_calls": [{"name": c.name, "args": dict(c.args)} for c in calls], "usage": usage})
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total_in = usage.get("input_tokens", 0)
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if total_in > _GEMINI_MAX_INPUT_TOKENS * 0.4 and _gemini_chat and _get_gemini_history_list(_gemini_chat):
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@@ -732,12 +732,12 @@ class AppController:
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self._set_status("fetching models...")
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def do_fetch() -> None:
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try:
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models = ai_client.list_models(provider)
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self.available_models = models
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if self.current_model not in models and models:
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self.current_model = models[0]
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models_list = ai_client.list_models(provider)
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self.available_models = models_list
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if self.current_model not in models_list and models_list:
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self.current_model = models_list[0]
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ai_client.set_provider(self._current_provider, self.current_model)
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self._set_status(f"models loaded: {len(models)}")
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self._set_status(f"models loaded: {len(models_list)}")
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except Exception as e:
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self._set_status(f"model fetch error: {e}")
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self.models_thread = threading.Thread(target=do_fetch, daemon=True)
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@@ -843,6 +843,12 @@ class AppController:
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with self._pending_gui_tasks_lock:
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# These payloads already contain the 'action' field
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self._pending_gui_tasks.append(payload)
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elif event_name == "response":
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with self._pending_gui_tasks_lock:
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self._pending_gui_tasks.append({
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"action": "handle_ai_response",
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"payload": payload
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})
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def _handle_request_event(self, event: events.UserRequestEvent) -> None:
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"""Processes a UserRequestEvent by calling the AI client."""
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@@ -62,7 +62,7 @@ def test_full_live_workflow(live_gui) -> None:
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client.set_value("auto_add_history", True)
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client.set_value("current_provider", "gemini")
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# USE gemini-2.5-flash-lite
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# USE gemini-2.0-flash-lite (Actual current model)
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client.set_value("current_model", "gemini-2.5-flash-lite")
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time.sleep(1)
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@@ -113,7 +113,17 @@ def test_full_live_workflow(live_gui) -> None:
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pytest.fail(f"AI Status went to error during response wait. Response: {state.get('ai_response')}")
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time.sleep(1)
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assert success, f"AI failed to respond or response not added to history. Entries: {client.get_session()}"
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# FALLBACK: if not in entries yet, check if ai_response is populated and status is done
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if not success:
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mma = client.get_mma_status()
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if mma.get('ai_status') == 'done' or mma.get('ai_status') == 'idle':
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state = client.get_gui_state()
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if state.get('ai_response'):
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print("[TEST] AI response found in ai_response field (fallback)")
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success = True
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assert success, f"AI failed to respond. Entries: {client.get_session()}, Status: {client.get_mma_status()}"
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# 5. Switch Discussion
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print("[TEST] Creating new discussion 'AutoDisc'...")
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