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fix: invalid new tool call creation logic during response handling in OAI-Compat model (#17781)

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This commit is contained in:
Vitor
2025-04-17 16:52:49 +08:00
committed by GitHub
parent b6b608219a
commit defd5520ea
3 changed files with 153 additions and 32 deletions
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86
api/core/model_runtime/model_providers/__base/large_language_model.py
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@@ -1,5 +1,6 @@
import logging
import time
import uuid
from collections.abc import Generator, Sequence
from typing import Optional, Union
@@ -24,6 +25,58 @@ from core.plugin.manager.model import PluginModelManager
logger = logging.getLogger(__name__)
def _gen_tool_call_id() -> str:
return f"chatcmpl-tool-{str(uuid.uuid4().hex)}"
def _increase_tool_call(
new_tool_calls: list[AssistantPromptMessage.ToolCall], existing_tools_calls: list[AssistantPromptMessage.ToolCall]
):
"""
Merge incremental tool call updates into existing tool calls.
:param new_tool_calls: List of new tool call deltas to be merged.
:param existing_tools_calls: List of existing tool calls to be modified IN-PLACE.
"""
def get_tool_call(tool_call_id: str):
"""
Get or create a tool call by ID
:param tool_call_id: tool call ID
:return: existing or new tool call
"""
if not tool_call_id:
return existing_tools_calls[-1]
_tool_call = next((_tool_call for _tool_call in existing_tools_calls if _tool_call.id == tool_call_id), None)
if _tool_call is None:
_tool_call = AssistantPromptMessage.ToolCall(
id=tool_call_id,
type="function",
function=AssistantPromptMessage.ToolCall.ToolCallFunction(name="", arguments=""),
)
existing_tools_calls.append(_tool_call)
return _tool_call
for new_tool_call in new_tool_calls:
# generate ID for tool calls with function name but no ID to track them
if new_tool_call.function.name and not new_tool_call.id:
new_tool_call.id = _gen_tool_call_id()
# get tool call
tool_call = get_tool_call(new_tool_call.id)
# update tool call
if new_tool_call.id:
tool_call.id = new_tool_call.id
if new_tool_call.type:
tool_call.type = new_tool_call.type
if new_tool_call.function.name:
tool_call.function.name = new_tool_call.function.name
if new_tool_call.function.arguments:
tool_call.function.arguments += new_tool_call.function.arguments
class LargeLanguageModel(AIModel):
"""
Model class for large language model.
@@ -109,44 +162,13 @@ class LargeLanguageModel(AIModel):
system_fingerprint = None
tools_calls: list[AssistantPromptMessage.ToolCall] = []
def increase_tool_call(new_tool_calls: list[AssistantPromptMessage.ToolCall]):
def get_tool_call(tool_name: str):
if not tool_name:
return tools_calls[-1]
tool_call = next(
(tool_call for tool_call in tools_calls if tool_call.function.name == tool_name), None
)
if tool_call is None:
tool_call = AssistantPromptMessage.ToolCall(
id="",
type="",
function=AssistantPromptMessage.ToolCall.ToolCallFunction(name=tool_name, arguments=""),
)
tools_calls.append(tool_call)
return tool_call
for new_tool_call in new_tool_calls:
# get tool call
tool_call = get_tool_call(new_tool_call.function.name)
# update tool call
if new_tool_call.id:
tool_call.id = new_tool_call.id
if new_tool_call.type:
tool_call.type = new_tool_call.type
if new_tool_call.function.name:
tool_call.function.name = new_tool_call.function.name
if new_tool_call.function.arguments:
tool_call.function.arguments += new_tool_call.function.arguments
for chunk in result:
if isinstance(chunk.delta.message.content, str):
content += chunk.delta.message.content
elif isinstance(chunk.delta.message.content, list):
content_list.extend(chunk.delta.message.content)
if chunk.delta.message.tool_calls:
increase_tool_call(chunk.delta.message.tool_calls)
_increase_tool_call(chunk.delta.message.tool_calls, tools_calls)
usage = chunk.delta.usage or LLMUsage.empty_usage()
system_fingerprint = chunk.system_fingerprint