YET ANOTEHR BOTCHED TRACK.

src/ai_client.py

@@ -679,28 +679,56 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str,
   for r_idx in range(MAX_TOOL_ROUNDS + 2):
    events.emit("request_start", payload={"provider": "gemini", "model": _model, "round": r_idx})
    if stream_callback:
-    resp = _gemini_chat.send_message_stream(payload)
+    # In 1.0.0, we use send_message with stream=True
+    config = types.GenerateContentConfig(
+     tools=[types.Tool(function_declarations=[types.FunctionDeclaration(**s) for s in mcp_client.get_tool_schemas()])] if enable_tools else [],
+     temperature=_temperature,
+     max_output_tokens=_max_tokens,
+    )
+    resp = _gemini_chat.send_message(payload, config=config, stream=True)
     txt_chunks: list[str] = []
+    calls = []
+    usage = {}
+    reason = "STOP"
+    final_resp = None
     for chunk in resp:
-     c_txt = chunk.text
-     if c_txt:
-      txt_chunks.append(c_txt)
-      stream_callback(c_txt)
+     if chunk.text:
+      txt_chunks.append(chunk.text)
+      stream_callback(chunk.text)
+     if chunk.candidates:
+      c = chunk.candidates[0]
+      if c.content and c.content.parts:
+       calls.extend([p.function_call for p in c.content.parts if p.function_call])
+      if hasattr(c, "finish_reason") and c.finish_reason:
+       reason = c.finish_reason.name
+     if chunk.usage_metadata:
+      usage = {
+       "input_tokens": chunk.usage_metadata.prompt_token_count,
+       "output_tokens": chunk.usage_metadata.candidates_token_count,
+       "total_tokens": chunk.usage_metadata.total_token_count,
+       "cache_read_input_tokens": getattr(chunk.usage_metadata, "cached_content_token_count", 0)
+      }
+     final_resp = chunk
     txt = "".join(txt_chunks)
-    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]
-    usage = {"input_tokens": getattr(resp.usage_metadata, "prompt_token_count", 0), "output_tokens": getattr(resp.usage_metadata, "candidates_token_count", 0)}
-    cached_tokens = getattr(resp.usage_metadata, "cached_content_token_count", None)
-    if cached_tokens: usage["cache_read_input_tokens"] = cached_tokens
+    # Final validation of response object for subsequent code
+    resp = final_resp 
    else:
-    resp = _gemini_chat.send_message(payload)
-    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)
-    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]
-    usage = {"input_tokens": getattr(resp.usage_metadata, "prompt_token_count", 0), "output_tokens": getattr(resp.usage_metadata, "candidates_token_count", 0)}
-    cached_tokens = getattr(resp.usage_metadata, "cached_content_token_count", None)
-    if cached_tokens: usage["cache_read_input_tokens"] = cached_tokens
-   if txt: all_text.append(txt)
-   events.emit("response_received", payload={"provider": "gemini", "model": _model, "usage": usage, "round": r_idx})
-   reason = resp.candidates[0].finish_reason.name if resp.candidates and hasattr(resp.candidates[0], "finish_reason") else "STOP"
+    config = types.GenerateContentConfig(
+     tools=[types.Tool(function_declarations=[types.FunctionDeclaration(**s) for s in mcp_client.get_tool_schemas()])] if enable_tools else [],
+     temperature=_temperature,
+     max_output_tokens=_max_tokens,
+    )
+    resp = _gemini_chat.send_message(payload, config=config)
+    txt = resp.text or ""
+    calls = [p.function_call for c in resp.candidates if getattr(c, "content", None) for p in c.content.parts if p.function_call]
+    usage = {
+     "input_tokens": getattr(resp.usage_metadata, "prompt_token_count", 0), 
+     "output_tokens": getattr(resp.usage_metadata, "candidates_token_count", 0),
+     "total_tokens": getattr(resp.usage_metadata, "total_token_count", 0),
+     "cache_read_input_tokens": getattr(resp.usage_metadata, "cached_content_token_count", 0)
+    }
+    reason = resp.candidates[0].finish_reason.name if (resp.candidates and hasattr(resp.candidates[0], "finish_reason")) else "STOP"
+
    _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})
    total_in = usage.get("input_tokens", 0)
    if total_in > _GEMINI_MAX_INPUT_TOKENS * 0.4 and _gemini_chat and _get_gemini_history_list(_gemini_chat):

src/app_controller.py

@@ -732,12 +732,12 @@ class AppController:
   self._set_status("fetching models...")
   def do_fetch() -> None:
    try:
-    models = ai_client.list_models(provider)
-    self.available_models = models
-    if self.current_model not in models and models:
-     self.current_model = models[0]
+    models_list = ai_client.list_models(provider)
+    self.available_models = models_list
+    if self.current_model not in models_list and models_list:
+     self.current_model = models_list[0]
      ai_client.set_provider(self._current_provider, self.current_model)
-    self._set_status(f"models loaded: {len(models)}")
+    self._set_status(f"models loaded: {len(models_list)}")
    except Exception as e:
     self._set_status(f"model fetch error: {e}")
   self.models_thread = threading.Thread(target=do_fetch, daemon=True)
@@ -843,6 +843,12 @@ class AppController:
     with self._pending_gui_tasks_lock:
      # These payloads already contain the 'action' field
      self._pending_gui_tasks.append(payload)
+   elif event_name == "response":
+    with self._pending_gui_tasks_lock:
+     self._pending_gui_tasks.append({
+       "action": "handle_ai_response",
+       "payload": payload
+      })
 
  def _handle_request_event(self, event: events.UserRequestEvent) -> None:
   """Processes a UserRequestEvent by calling the AI client."""