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checkpoint: finished test curation

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This commit is contained in:
Edward R. Gonzalez
2026-02-25 21:58:18 -05:00
parent e0b9ab997a
commit 56025a84e9
33 changed files with 546 additions and 356 deletions
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163
ai_client.py
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@@ -20,6 +20,7 @@ import difflib
import threading
from pathlib import Path
import os
import project_manager
import file_cache
import mcp_client
import anthropic
@@ -44,6 +45,13 @@ def set_model_params(temp: float, max_tok: int, trunc_limit: int = 8000):
_max_tokens = max_tok
_history_trunc_limit = trunc_limit
def get_history_trunc_limit() -> int:
return _history_trunc_limit
def set_history_trunc_limit(val: int):
global _history_trunc_limit
_history_trunc_limit = val
_gemini_client = None
_gemini_chat = None
_gemini_cache = None
@@ -800,11 +808,10 @@ def _send_gemini_cli(md_content: str, user_message: str, base_dir: str,
try:
if _gemini_cli_adapter is None:
_gemini_cli_adapter = GeminiCliAdapter(binary_path="gemini")
events.emit("request_start", payload={"provider": "gemini_cli", "model": _model, "round": 0})
mcp_client.configure(file_items or [], [base_dir])
# If it's a new session (session_id is None), we should ideally send the context.
# For now, following the simple pattern:
payload = user_message
if _gemini_cli_adapter.session_id is None:
# Prepend context and discussion history to the first message
@@ -814,23 +821,104 @@ def _send_gemini_cli(md_content: str, user_message: str, base_dir: str,
full_prompt += user_message
payload = full_prompt
_append_comms("OUT", "request", {"message": f"[CLI] [msg {len(payload)}]"})
result_text = _gemini_cli_adapter.send(payload)
usage = _gemini_cli_adapter.last_usage or {}
latency = _gemini_cli_adapter.last_latency
events.emit("response_received", payload={"provider": "gemini_cli", "model": _model, "usage": usage, "latency": latency, "round": 0})
_append_comms("IN", "response", {
"round": 0,
"stop_reason": "STOP",
"text": result_text,
"tool_calls": [],
"usage": usage
})
return result_text
all_text = []
_cumulative_tool_bytes = 0
for r_idx in range(MAX_TOOL_ROUNDS + 2):
events.emit("request_start", payload={"provider": "gemini_cli", "model": _model, "round": r_idx})
_append_comms("OUT", "request", {"message": f"[CLI] [round {r_idx}] [msg {len(payload)}]"})
resp_data = _gemini_cli_adapter.send(payload)
txt = resp_data.get("text", "")
if txt: all_text.append(txt)
calls = resp_data.get("tool_calls", [])
usage = _gemini_cli_adapter.last_usage or {}
latency = _gemini_cli_adapter.last_latency
events.emit("response_received", payload={"provider": "gemini_cli", "model": _model, "usage": usage, "latency": latency, "round": r_idx})
# Clean up the tool calls format to match comms log expectation
log_calls = []
for c in calls:
log_calls.append({"name": c.get("name"), "args": c.get("args")})
_append_comms("IN", "response", {
"round": r_idx,
"stop_reason": "TOOL_USE" if calls else "STOP",
"text": txt,
"tool_calls": log_calls,
"usage": usage
})
# If there's text and we're not done, push it to the history immediately
# so it appears as a separate entry in the GUI.
if txt and calls and comms_log_callback:
# Use kind='history_add' to push a new entry into the disc_entries list
comms_log_callback({
"ts": project_manager.now_ts(),
"direction": "IN",
"kind": "history_add",
"payload": {
"role": "AI",
"content": txt
}
})
if not calls or r_idx > MAX_TOOL_ROUNDS:
break
tool_results_for_cli = []
for i, fc in enumerate(calls):
name = fc.get("name")
args = fc.get("args", {})
call_id = fc.get("id")
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, "id": call_id, "args": args})
out = mcp_client.dispatch(name, args)
elif name == TOOL_NAME:
scr = args.get("script", "")
_append_comms("OUT", "tool_call", {"name": TOOL_NAME, "id": call_id, "script": scr})
out = _run_script(scr, base_dir)
else:
out = f"ERROR: unknown tool '{name}'"
if i == len(calls) - 1:
if file_items:
file_items, changed = _reread_file_items(file_items)
ctx = _build_file_diff_text(changed)
if ctx:
out += f"\n\n[SYSTEM: FILES UPDATED]\n\n{ctx}"
if r_idx == MAX_TOOL_ROUNDS:
out += "\n\n[SYSTEM: MAX ROUNDS. PROVIDE FINAL ANSWER.]"
out = _truncate_tool_output(out)
_cumulative_tool_bytes += len(out)
tool_results_for_cli.append({
"role": "tool",
"tool_call_id": call_id,
"name": name,
"content": out
})
_append_comms("IN", "tool_result", {"name": name, "id": call_id, "output": out})
events.emit("tool_execution", payload={"status": "completed", "tool": name, "result": out, "round": r_idx})
if _cumulative_tool_bytes > _MAX_TOOL_OUTPUT_BYTES:
_append_comms("OUT", "request", {"message": f"[TOOL OUTPUT BUDGET EXCEEDED: {_cumulative_tool_bytes} bytes]"})
# We should ideally tell the model here, but for CLI we just append to payload
# For Gemini CLI, we send the tool results as a JSON array of messages (or similar)
# The adapter expects a string, so we'll pass the JSON string of the results.
payload = json.dumps(tool_results_for_cli)
# Return only the text from the last round, because intermediate
# text chunks were already pushed to history via comms_log_callback.
final_text = all_text[-1] if all_text else "(No text returned)"
return final_text
except Exception as e:
# Basic error classification for CLI
raise ProviderError("unknown", "gemini_cli", e)
@@ -1348,6 +1436,7 @@ def get_history_bleed_stats(md_content: str | None = None) -> dict:
"percentage": percentage,
}
elif _provider == "gemini":
effective_limit = _history_trunc_limit if _history_trunc_limit > 0 else _GEMINI_MAX_INPUT_TOKENS
if _gemini_chat:
try:
_ensure_gemini_client()
@@ -1368,7 +1457,7 @@ def get_history_bleed_stats(md_content: str | None = None) -> dict:
print("[DEBUG] Gemini count_tokens skipped: no history or md_content")
return {
"provider": "gemini",
"limit": _GEMINI_MAX_INPUT_TOKENS,
"limit": effective_limit,
"current": 0,
"percentage": 0,
}
@@ -1379,12 +1468,11 @@ def get_history_bleed_stats(md_content: str | None = None) -> dict:
contents=history
)
current_tokens = resp.total_tokens
limit_tokens = _GEMINI_MAX_INPUT_TOKENS
percentage = (current_tokens / limit_tokens) * 100 if limit_tokens > 0 else 0
percentage = (current_tokens / effective_limit) * 100 if effective_limit > 0 else 0
print(f"[DEBUG] Gemini current_tokens={current_tokens}, percentage={percentage:.4f}%")
return {
"provider": "gemini",
"limit": limit_tokens,
"limit": effective_limit,
"current": current_tokens,
"percentage": percentage,
}
@@ -1400,12 +1488,11 @@ def get_history_bleed_stats(md_content: str | None = None) -> dict:
contents=[types.Content(role="user", parts=[types.Part.from_text(text=md_content)])]
)
current_tokens = resp.total_tokens
limit_tokens = _GEMINI_MAX_INPUT_TOKENS
percentage = (current_tokens / limit_tokens) * 100 if limit_tokens > 0 else 0
percentage = (current_tokens / effective_limit) * 100 if effective_limit > 0 else 0
print(f"[DEBUG] Gemini (MD ONLY) current_tokens={current_tokens}, percentage={percentage:.4f}%")
return {
"provider": "gemini",
"limit": limit_tokens,
"limit": effective_limit,
"current": current_tokens,
"percentage": percentage,
}
@@ -1415,10 +1502,28 @@ def get_history_bleed_stats(md_content: str | None = None) -> dict:
return {
"provider": "gemini",
"limit": _GEMINI_MAX_INPUT_TOKENS,
"limit": effective_limit,
"current": 0,
"percentage": 0,
}
elif _provider == "gemini_cli":
effective_limit = _history_trunc_limit if _history_trunc_limit > 0 else _GEMINI_MAX_INPUT_TOKENS
# For Gemini CLI, we don't have direct count_tokens access without making a call,
# so we report the limit and current usage from the last run if available.
limit_tokens = effective_limit
current_tokens = 0
if _gemini_cli_adapter and _gemini_cli_adapter.last_usage:
# Stats from CLI use 'input_tokens' or 'input'
u = _gemini_cli_adapter.last_usage
current_tokens = u.get("input_tokens") or u.get("input", 0)
percentage = (current_tokens / limit_tokens) * 100 if limit_tokens > 0 else 0
return {
"provider": "gemini_cli",
"limit": limit_tokens,
"current": current_tokens,
"percentage": percentage,
}
# Default empty state
return {