Merge PR #1555: fix: merge tool_calls from multiple choices in LiteLLM response

This commit is contained in:
Re-bin
2026-03-06 07:16:20 +00:00

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@@ -8,6 +8,7 @@ from typing import Any
import json_repair
import litellm
from litellm import acompletion
from loguru import logger
from nanobot.providers.base import LLMProvider, LLMResponse, ToolCallRequest
from nanobot.providers.registry import find_by_model, find_gateway
@@ -255,20 +256,37 @@ class LiteLLMProvider(LLMProvider):
"""Parse LiteLLM response into our standard format."""
choice = response.choices[0]
message = choice.message
content = message.content
finish_reason = choice.finish_reason
# Some providers (e.g. GitHub Copilot) split content and tool_calls
# across multiple choices. Merge them so tool_calls are not lost.
raw_tool_calls = []
for ch in response.choices:
msg = ch.message
if hasattr(msg, "tool_calls") and msg.tool_calls:
raw_tool_calls.extend(msg.tool_calls)
if ch.finish_reason in ("tool_calls", "stop"):
finish_reason = ch.finish_reason
if not content and msg.content:
content = msg.content
if len(response.choices) > 1:
logger.debug("LiteLLM response has {} choices, merged {} tool_calls",
len(response.choices), len(raw_tool_calls))
tool_calls = []
if hasattr(message, "tool_calls") and message.tool_calls:
for tc in message.tool_calls:
# Parse arguments from JSON string if needed
args = tc.function.arguments
if isinstance(args, str):
args = json_repair.loads(args)
for tc in raw_tool_calls:
# Parse arguments from JSON string if needed
args = tc.function.arguments
if isinstance(args, str):
args = json_repair.loads(args)
tool_calls.append(ToolCallRequest(
id=_short_tool_id(),
name=tc.function.name,
arguments=args,
))
tool_calls.append(ToolCallRequest(
id=_short_tool_id(),
name=tc.function.name,
arguments=args,
))
usage = {}
if hasattr(response, "usage") and response.usage:
@@ -280,11 +298,11 @@ class LiteLLMProvider(LLMProvider):
reasoning_content = getattr(message, "reasoning_content", None) or None
thinking_blocks = getattr(message, "thinking_blocks", None) or None
return LLMResponse(
content=message.content,
content=content,
tool_calls=tool_calls,
finish_reason=choice.finish_reason or "stop",
finish_reason=finish_reason or "stop",
usage=usage,
reasoning_content=reasoning_content,
thinking_blocks=thinking_blocks,