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feat: intercept literal [tool_calls] arrays in generated text and map to actual function calls

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2026-05-06 17:27:10 +08:00
parent cca9c99e22
commit 5911e4322e
2 changed files with 68 additions and 1 deletions
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55
app/main.py
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@@ -44,6 +44,7 @@ from .http.tool_bridge import (
_anthropic_tool_result_block,
_anthropic_tool_use_block,
_extract_function_call_event_from_text,
_extract_tool_calls_from_text,
_forced_tool_fallback_event,
_json_string,
_openai_forced_tool_name,
@@ -656,10 +657,52 @@ async def v1_chat_completions(req: ChatCompletionsRequest, request: Request):
continue
buffered_text_parts.append(text)
completion_tokens_holder["n"] += estimate_tokens(text)
full_text = "".join(buffered_text_parts)
if req.tools:
if "[tool_calls]".startswith(full_text) or "[tool_calls]" in full_text:
continue
if forced_tool_name and not saw_tool_call:
continue
yield _text_payload(text)
# Yield all buffered text
text_to_yield = "".join(buffered_text_parts)
buffered_text_parts.clear()
yield _text_payload(text_to_yield)
if buffered_text_parts and not saw_tool_call:
merged_text = "".join(buffered_text_parts)
extracted_tool_calls = _extract_tool_calls_from_text(merged_text)
if extracted_tool_calls:
saw_tool_call = True
for i, tc in enumerate(extracted_tool_calls):
tool_id = str(tc.get("id") or f"call_inferred_{i}")
tool_call_indexes[tool_id] = i
payload = {
"id": completion_id,
"object": "chat.completion.chunk",
"created": created,
"model": model,
"choices": [
{
"index": 0,
"delta": {
"tool_calls": [
{
"index": i,
**_openai_tool_call(tc, forced_id=tool_id),
}
]
},
"finish_reason": None,
}
],
}
yield f"data: {json.dumps(payload, ensure_ascii=False)}\n\n"
buffered_text_parts.clear()
if buffered_text_parts and forced_tool_name and not saw_tool_call:
merged_text = "".join(buffered_text_parts)
inferred = _extract_function_call_event_from_text(
@@ -808,6 +851,16 @@ async def v1_chat_completions(req: ChatCompletionsRequest, request: Request):
tool_id = str(item.get("id") or f"call_{idx}")
tool_calls.append(_openai_tool_call(item, forced_id=tool_id))
saw_tool_call = True
if not saw_tool_call:
extracted_tool_calls = _extract_tool_calls_from_text(message_content)
if extracted_tool_calls:
for idx, tc in enumerate(extracted_tool_calls):
tool_id = str(tc.get("id") or f"call_inferred_{idx}")
tool_calls.append(_openai_tool_call(tc, forced_id=tool_id))
saw_tool_call = True
message_content = ""
if not saw_tool_call and forced_tool_name:
inferred = _extract_function_call_event_from_text(
message_content,