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feat(ai_client): Emit API lifecycle and tool execution events

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Edward R. Gonzalez
2026-02-23 16:31:48 -05:00
parent c44026c06c
commit 20ebab55a0
2 changed files with 106 additions and 0 deletions
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12
ai_client.py
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@@ -19,6 +19,7 @@ from pathlib import Path
import file_cache
import mcp_client
import google.genai
from google.genai import types
from events import EventEmitter
_provider: str = "gemini"
@@ -620,6 +621,7 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
r["output"] = val
for r_idx in range(MAX_TOOL_ROUNDS + 2):
events.emit("request_start", payload={"provider": "gemini", "model": _model, "round": r_idx})
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)
if txt: all_text.append(txt)
@@ -629,6 +631,8 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
cached_tokens = getattr(resp.usage_metadata, "cached_content_token_count", None)
if cached_tokens:
usage["cache_read_input_tokens"] = cached_tokens
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"
_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})
@@ -662,6 +666,7 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
f_resps, log = [], []
for i, fc in enumerate(calls):
name, args = fc.name, dict(fc.args)
events.emit("tool_execution", payload={"status": "started", "tool": name, "args": args, "round": r_idx})
if name in mcp_client.TOOL_NAMES:
_append_comms("OUT", "tool_call", {"name": name, "args": args})
out = mcp_client.dispatch(name, args)
@@ -681,6 +686,7 @@ def _send_gemini(md_content: str, user_message: str, base_dir: str, file_items:
f_resps.append(types.Part.from_function_response(name=name, response={"output": out}))
log.append({"tool_use_id": name, "content": out})
events.emit("tool_execution", payload={"status": "completed", "tool": name, "result": out, "round": r_idx})
_append_comms("OUT", "tool_result_send", {"results": log})
payload = f_resps
@@ -998,6 +1004,7 @@ def _send_anthropic(md_content: str, user_message: str, base_dir: str, file_item
def _strip_private_keys(history):
return [{k: v for k, v in m.items() if not k.startswith("_")} for m in history]
events.emit("request_start", payload={"provider": "anthropic", "model": _model, "round": round_idx})
response = _anthropic_client.messages.create(
model=_model,
max_tokens=_max_tokens,
@@ -1036,6 +1043,8 @@ def _send_anthropic(md_content: str, user_message: str, base_dir: str, file_item
if cache_read is not None:
usage_dict["cache_read_input_tokens"] = cache_read
events.emit("response_received", payload={"provider": "anthropic", "model": _model, "usage": usage_dict, "round": round_idx})
_append_comms("IN", "response", {
"round": round_idx,
"stop_reason": response.stop_reason,
@@ -1059,6 +1068,7 @@ def _send_anthropic(md_content: str, user_message: str, base_dir: str, file_item
b_name = getattr(block, "name", None)
b_id = getattr(block, "id", "")
b_input = getattr(block, "input", {})
events.emit("tool_execution", payload={"status": "started", "tool": b_name, "args": b_input, "round": round_idx})
if b_name in mcp_client.TOOL_NAMES:
_append_comms("OUT", "tool_call", {"name": b_name, "id": b_id, "args": b_input})
output = mcp_client.dispatch(b_name, b_input)
@@ -1068,6 +1078,7 @@ def _send_anthropic(md_content: str, user_message: str, base_dir: str, file_item
"tool_use_id": b_id,
"content": output,
})
events.emit("tool_execution", payload={"status": "completed", "tool": b_name, "result": output, "round": round_idx})
elif b_name == TOOL_NAME:
script = b_input.get("script", "")
_append_comms("OUT", "tool_call", {
@@ -1086,6 +1097,7 @@ def _send_anthropic(md_content: str, user_message: str, base_dir: str, file_item
"tool_use_id": b_id,
"content": output,
})
events.emit("tool_execution", payload={"status": "completed", "tool": b_name, "result": output, "round": round_idx})
# Refresh file context after tool calls — only inject CHANGED files
if file_items:

94
tests/test_api_events.py
View File

@@ -18,3 +18,97 @@ def test_event_emission():
ai_client.events.emit("request_start", payload={"model": "test"})
mock_callback.assert_called_once_with(payload={"model": "test"})
def test_send_emits_events():
from unittest.mock import patch, MagicMock
# We need to mock _ensure_gemini_client and the chat object it creates
with patch("ai_client._ensure_gemini_client"), \
patch("ai_client._gemini_client") as mock_client, \
patch("ai_client._gemini_chat") as mock_chat:
# Setup mock response
mock_response = MagicMock()
mock_response.candidates = []
# Explicitly set usage_metadata as a mock with integer values
mock_usage = MagicMock()
mock_usage.prompt_token_count = 10
mock_usage.candidates_token_count = 5
mock_usage.cached_content_token_count = None
mock_response.usage_metadata = mock_usage
mock_chat.send_message.return_value = mock_response
mock_client.chats.create.return_value = mock_chat
ai_client.set_provider("gemini", "gemini-flash")
start_callback = MagicMock()
response_callback = MagicMock()
ai_client.events.on("request_start", start_callback)
ai_client.events.on("response_received", response_callback)
# We need to bypass the context changed check or set it up
ai_client.send("context", "message")
assert start_callback.called
assert response_callback.called
# Check payload
args, kwargs = start_callback.call_args
assert kwargs['payload']['provider'] == 'gemini'
def test_send_emits_tool_events():
from unittest.mock import patch, MagicMock
with patch("ai_client._ensure_gemini_client"), \
patch("ai_client._gemini_client") as mock_client, \
patch("ai_client._gemini_chat") as mock_chat, \
patch("mcp_client.dispatch") as mock_dispatch:
# 1. Setup mock response with a tool call
mock_fc = MagicMock()
mock_fc.name = "read_file"
mock_fc.args = {"path": "test.txt"}
mock_response_with_tool = MagicMock()
mock_response_with_tool.candidates = [MagicMock()]
mock_part = MagicMock()
mock_part.text = "tool call text"
mock_part.function_call = mock_fc
mock_response_with_tool.candidates[0].content.parts = [mock_part]
mock_response_with_tool.candidates[0].finish_reason.name = "STOP"
# Setup mock usage
mock_usage = MagicMock()
mock_usage.prompt_token_count = 10
mock_usage.candidates_token_count = 5
mock_usage.cached_content_token_count = None
mock_response_with_tool.usage_metadata = mock_usage
# 2. Setup second mock response (final answer)
mock_response_final = MagicMock()
mock_response_final.candidates = []
mock_response_final.usage_metadata = mock_usage
mock_chat.send_message.side_effect = [mock_response_with_tool, mock_response_final]
mock_dispatch.return_value = "file content"
ai_client.set_provider("gemini", "gemini-flash")
tool_callback = MagicMock()
ai_client.events.on("tool_execution", tool_callback)
ai_client.send("context", "message")
# Should be called twice: once for 'started', once for 'completed'
assert tool_callback.call_count == 2
# Check 'started' call
args, kwargs = tool_callback.call_args_list[0]
assert kwargs['payload']['status'] == 'started'
assert kwargs['payload']['tool'] == 'read_file'
# Check 'completed' call
args, kwargs = tool_callback.call_args_list[1]
assert kwargs['payload']['status'] == 'completed'
assert kwargs['payload']['result'] == 'file content'