fix: bridge tool-calls in copilot-acp adapter
Enable Hermes tool execution through the copilot-acp adapter by:
- Passing tool schemas and tool_choice into the ACP prompt text
- Instructing ACP backend to emit <tool_call>{...}</tool_call> blocks
- Parsing XML tool-call blocks and bare JSON fallback back into
Hermes-compatible SimpleNamespace tool call objects
- Setting finish_reason='tool_calls' when tool calls are extracted
- Cleaning tool-call markup from response text
Fix duplicate tool call extraction when both XML block and bare JSON
regexes matched the same content (XML blocks now take precedence).
Cherry-picked from PR #4536 by MestreY0d4-Uninter. Stripped heuristic
fallback system (auto-synthesized tool calls from prose) and
Portuguese-language patterns — tool execution should be model-decided,
not heuristic-guessed.
This commit is contained in:
MestreY0d4-Uninter
committed by
Teknium
Teknium
parent
d3d5b895f6
commit
6c12999b8c
@@ -11,6 +11,7 @@ from __future__ import annotations
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import json
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import os
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import queue
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import re
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import shlex
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import subprocess
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import threading
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@@ -23,6 +24,9 @@ from typing import Any
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ACP_MARKER_BASE_URL = "acp://copilot"
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_DEFAULT_TIMEOUT_SECONDS = 900.0
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_TOOL_CALL_BLOCK_RE = re.compile(r"<tool_call>\s*(\{.*?\})\s*</tool_call>", re.DOTALL)
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_TOOL_CALL_JSON_RE = re.compile(r"\{\s*\"id\"\s*:\s*\"[^\"]+\"\s*,\s*\"type\"\s*:\s*\"function\"\s*,\s*\"function\"\s*:\s*\{.*?\}\s*\}", re.DOTALL)
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def _resolve_command() -> str:
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return (
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@@ -50,15 +54,50 @@ def _jsonrpc_error(message_id: Any, code: int, message: str) -> dict[str, Any]:
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}
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def _format_messages_as_prompt(messages: list[dict[str, Any]], model: str | None = None) -> str:
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def _format_messages_as_prompt(
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messages: list[dict[str, Any]],
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model: str | None = None,
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tools: list[dict[str, Any]] | None = None,
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tool_choice: Any = None,
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) -> str:
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sections: list[str] = [
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"You are being used as the active ACP agent backend for Hermes.",
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"Use your own ACP capabilities and respond directly in natural language.",
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"Do not emit OpenAI tool-call JSON.",
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"Use ACP capabilities to complete tasks.",
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"IMPORTANT: If you take an action with a tool, you MUST output tool calls using <tool_call>{...}</tool_call> blocks with JSON exactly in OpenAI function-call shape.",
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"If no tool is needed, answer normally.",
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]
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if model:
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sections.append(f"Hermes requested model hint: {model}")
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if isinstance(tools, list) and tools:
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tool_specs: list[dict[str, Any]] = []
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for t in tools:
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if not isinstance(t, dict):
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continue
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fn = t.get("function") or {}
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if not isinstance(fn, dict):
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continue
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name = fn.get("name")
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if not isinstance(name, str) or not name.strip():
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continue
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tool_specs.append(
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{
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"name": name.strip(),
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"description": fn.get("description", ""),
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"parameters": fn.get("parameters", {}),
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}
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)
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if tool_specs:
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sections.append(
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"Available tools (OpenAI function schema). "
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"When using a tool, emit ONLY <tool_call>{...}</tool_call> with one JSON object "
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"containing id/type/function{name,arguments}. arguments must be a JSON string.\n"
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+ json.dumps(tool_specs, ensure_ascii=False)
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)
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if tool_choice is not None:
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sections.append(f"Tool choice hint: {json.dumps(tool_choice, ensure_ascii=False)}")
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transcript: list[str] = []
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for message in messages:
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if not isinstance(message, dict):
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@@ -114,6 +153,80 @@ def _render_message_content(content: Any) -> str:
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return str(content).strip()
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def _extract_tool_calls_from_text(text: str) -> tuple[list[SimpleNamespace], str]:
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if not isinstance(text, str) or not text.strip():
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return [], ""
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extracted: list[SimpleNamespace] = []
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consumed_spans: list[tuple[int, int]] = []
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def _try_add_tool_call(raw_json: str) -> None:
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try:
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obj = json.loads(raw_json)
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except Exception:
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return
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if not isinstance(obj, dict):
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return
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fn = obj.get("function")
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if not isinstance(fn, dict):
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return
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fn_name = fn.get("name")
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if not isinstance(fn_name, str) or not fn_name.strip():
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return
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fn_args = fn.get("arguments", "{}")
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if not isinstance(fn_args, str):
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fn_args = json.dumps(fn_args, ensure_ascii=False)
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call_id = obj.get("id")
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if not isinstance(call_id, str) or not call_id.strip():
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call_id = f"acp_call_{len(extracted)+1}"
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extracted.append(
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SimpleNamespace(
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id=call_id,
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call_id=call_id,
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response_item_id=None,
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type="function",
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function=SimpleNamespace(name=fn_name.strip(), arguments=fn_args),
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)
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)
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for m in _TOOL_CALL_BLOCK_RE.finditer(text):
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raw = m.group(1)
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_try_add_tool_call(raw)
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consumed_spans.append((m.start(), m.end()))
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# Only try bare-JSON fallback when no XML blocks were found.
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if not extracted:
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for m in _TOOL_CALL_JSON_RE.finditer(text):
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raw = m.group(0)
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_try_add_tool_call(raw)
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consumed_spans.append((m.start(), m.end()))
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if not consumed_spans:
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return extracted, text.strip()
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consumed_spans.sort()
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merged: list[tuple[int, int]] = []
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for start, end in consumed_spans:
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if not merged or start > merged[-1][1]:
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merged.append((start, end))
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else:
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merged[-1] = (merged[-1][0], max(merged[-1][1], end))
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parts: list[str] = []
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cursor = 0
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for start, end in merged:
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if cursor < start:
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parts.append(text[cursor:start])
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cursor = max(cursor, end)
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if cursor < len(text):
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parts.append(text[cursor:])
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cleaned = "\n".join(p.strip() for p in parts if p and p.strip()).strip()
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return extracted, cleaned
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def _ensure_path_within_cwd(path_text: str, cwd: str) -> Path:
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candidate = Path(path_text)
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if not candidate.is_absolute():
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@@ -190,14 +303,23 @@ class CopilotACPClient:
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model: str | None = None,
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messages: list[dict[str, Any]] | None = None,
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timeout: float | None = None,
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tools: list[dict[str, Any]] | None = None,
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tool_choice: Any = None,
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**_: Any,
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) -> Any:
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prompt_text = _format_messages_as_prompt(messages or [], model=model)
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prompt_text = _format_messages_as_prompt(
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messages or [],
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model=model,
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tools=tools,
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tool_choice=tool_choice,
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)
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response_text, reasoning_text = self._run_prompt(
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prompt_text,
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timeout_seconds=float(timeout or _DEFAULT_TIMEOUT_SECONDS),
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)
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tool_calls, cleaned_text = _extract_tool_calls_from_text(response_text)
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usage = SimpleNamespace(
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prompt_tokens=0,
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completion_tokens=0,
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@@ -205,13 +327,14 @@ class CopilotACPClient:
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prompt_tokens_details=SimpleNamespace(cached_tokens=0),
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)
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assistant_message = SimpleNamespace(
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content=response_text,
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tool_calls=[],
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content=cleaned_text,
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tool_calls=tool_calls,
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reasoning=reasoning_text or None,
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reasoning_content=reasoning_text or None,
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reasoning_details=None,
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)
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choice = SimpleNamespace(message=assistant_message, finish_reason="stop")
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finish_reason = "tool_calls" if tool_calls else "stop"
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choice = SimpleNamespace(message=assistant_message, finish_reason=finish_reason)
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return SimpleNamespace(
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choices=[choice],
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usage=usage,
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