adding better gemini support

ai_client.py

@@ -33,7 +33,7 @@ MAX_TOOL_ROUNDS = 5
 # Kept well under the ~200k token API limit.
 _ANTHROPIC_CHUNK_SIZE = 180_000
 
-_ANTHROPIC_SYSTEM = (
+_SYSTEM_PROMPT = (
     "You are a helpful coding assistant with access to a PowerShell tool and MCP file tools (read_file, list_directory, search_files, get_file_summary). "
     "When asked to create or edit files, prefer targeted edits over full rewrites. "
     "Always explain what you are doing before invoking the tool.\n\n"
@@ -403,6 +403,7 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
             _gemini_chat = _gemini_client.chats.create(
                 model=_model,
                 config=types.GenerateContentConfig(
+                    system_instruction=_SYSTEM_PROMPT,
                     tools=[_gemini_tool_declaration()]
                 )
             )
@@ -429,16 +430,34 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
                 if hasattr(part, "function_call") and part.function_call is not None
             ]
 
-            _append_comms("IN", "response",            {
-                "round":      round_idx,
-                "text":       "\n".join(text_parts_raw),
-                "tool_calls": [{"name": fc.name, "args": dict(fc.args)} for fc in tool_calls],
+            usage_dict = {}
+            if hasattr(response, "usage_metadata") and response.usage_metadata:
+                meta = response.usage_metadata
+                if hasattr(meta, "prompt_token_count") and meta.prompt_token_count is not None:
+                    usage_dict["input_tokens"] = meta.prompt_token_count
+                if hasattr(meta, "candidates_token_count") and meta.candidates_token_count is not None:
+                    usage_dict["output_tokens"] = meta.candidates_token_count
+                if hasattr(meta, "cached_content_token_count") and meta.cached_content_token_count:
+                    usage_dict["cache_read_input_tokens"] = meta.cached_content_token_count
+
+            stop_reason = ""
+            if response.candidates and hasattr(response.candidates[0], "finish_reason"):
+                fr = response.candidates[0].finish_reason
+                stop_reason = str(fr.name) if hasattr(fr, "name") else str(fr)
+
+            _append_comms("IN", "response", {
+                "round":       round_idx,
+                "stop_reason": stop_reason,
+                "text":        "\n".join(text_parts_raw),
+                "tool_calls":  [{"name": fc.name, "args": dict(fc.args)} for fc in tool_calls],
+                "usage":       usage_dict,
             })
 
             if not tool_calls:
                 break
 
             function_responses = []
+            sent_results_log = []
             for fc in tool_calls:
                 fc_name = fc.name
                 fc_args = dict(fc.args)
@@ -452,6 +471,7 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
                             response={"output": output}
                         )
                     )
+                    sent_results_log.append({"tool_use_id": fc_name, "content": output})
                 elif fc_name == TOOL_NAME:
                     script = fc_args.get("script", "")
                     _append_comms("OUT", "tool_call", {
@@ -469,13 +489,29 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
                             response={"output": output}
                         )
                     )
+                    sent_results_log.append({"tool_use_id": TOOL_NAME, "content": output})
 
             if not function_responses:
                 break
 
-            # Refresh file context after tool calls
+            # Refresh file context after tool calls and inject as a text part
             if file_items:
                 file_items = _reread_file_items(file_items)
+                refreshed_ctx = _build_file_context_text(file_items)
+                if refreshed_ctx:
+                    refreshed_text = (
+                        "[FILES UPDATED — current contents below. "
+                        "Do NOT re-read these files with PowerShell.]\n\n"
+                        + refreshed_ctx
+                    )
+                    if hasattr(types.Part, "from_text"):
+                        function_responses.append(types.Part.from_text(text=refreshed_text))
+                    else:
+                        function_responses.append(types.Part(text=refreshed_text))
+
+            _append_comms("OUT", "tool_result_send", {
+                "results": sent_results_log
+            })
 
             response = _gemini_chat.send_message(function_responses)
 
@@ -599,7 +635,7 @@ def _send_anthropic(md_content: str, user_message: str, base_dir: str, file_item
                 system=[
                     {
                         "type": "text",
-                        "text": _ANTHROPIC_SYSTEM,
+                        "text": _SYSTEM_PROMPT,
                         "cache_control": {"type": "ephemeral"},
                     }
                 ],