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feat: add supports for gemini-3 series thought signature (#3698)

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* feat: add supports for gemini-3 series thought signature

* feat: refactor tools_call_extra_content to use a dictionary for better structure
This commit is contained in:
Soulter
2025-11-19 18:54:56 +08:00
committed by GitHub
parent cd2556ab94
commit afb56cf707
5 changed files with 70 additions and 46 deletions
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astrbot/core/agent/message.py
+7
View File
@@ -119,6 +119,13 @@ class ToolCall(BaseModel):
"""The ID of the tool call."""
function: FunctionBody
"""The function body of the tool call."""
extra_content: dict[str, Any] | None = None
"""Extra metadata for the tool call."""
def model_dump(self, **kwargs: Any) -> dict[str, Any]:
if self.extra_content is None:
kwargs.setdefault("exclude", set()).add("extra_content")
return super().model_dump(**kwargs)
class ToolCallPart(BaseModel):
astrbot/core/db/po.py
+7 -13
View File
@@ -3,13 +3,7 @@ from dataclasses import dataclass, field
from datetime import datetime, timezone
from typing import TypedDict
from sqlmodel import (
JSON,
Field,
SQLModel,
Text,
UniqueConstraint,
)
from sqlmodel import JSON, Field, SQLModel, Text, UniqueConstraint
class PlatformStat(SQLModel, table=True):
@@ -18,7 +12,7 @@ class PlatformStat(SQLModel, table=True):
Note: In astrbot v4, we moved `platform` table to here.
"""
__tablename__ = "platform_stats"
__tablename__ = "platform_stats" # type: ignore
id: int = Field(primary_key=True, sa_column_kwargs={"autoincrement": True})
timestamp: datetime = Field(nullable=False)
@@ -37,7 +31,7 @@ class PlatformStat(SQLModel, table=True):
class ConversationV2(SQLModel, table=True):
__tablename__ = "conversations"
__tablename__ = "conversations" # type: ignore
inner_conversation_id: int = Field(
primary_key=True,
@@ -74,7 +68,7 @@ class Persona(SQLModel, table=True):
It can be used to customize the behavior of LLMs.
"""
__tablename__ = "personas"
__tablename__ = "personas" # type: ignore
id: int | None = Field(
primary_key=True,
@@ -104,7 +98,7 @@ class Persona(SQLModel, table=True):
class Preference(SQLModel, table=True):
"""This class represents preferences for bots."""
__tablename__ = "preferences"
__tablename__ = "preferences" # type: ignore
id: int | None = Field(
default=None,
@@ -140,7 +134,7 @@ class PlatformMessageHistory(SQLModel, table=True):
or platform-specific messages.
"""
__tablename__ = "platform_message_history"
__tablename__ = "platform_message_history" # type: ignore
id: int | None = Field(
primary_key=True,
@@ -167,7 +161,7 @@ class Attachment(SQLModel, table=True):
Attachments can be images, files, or other media types.
"""
__tablename__ = "attachments"
__tablename__ = "attachments" # type: ignore
inner_attachment_id: int | None = Field(
primary_key=True,
astrbot/core/provider/entities.py
+22 -9
View File
@@ -211,6 +211,8 @@ class LLMResponse:
"""Tool call names."""
tools_call_ids: list[str] = field(default_factory=list)
"""Tool call IDs."""
tools_call_extra_content: dict[str, dict[str, Any]] = field(default_factory=dict)
"""Tool call extra content. tool_call_id -> extra_content dict"""
reasoning_content: str = ""
"""The reasoning content extracted from the LLM, if any."""
@@ -233,6 +235,7 @@ class LLMResponse:
tools_call_args: list[dict[str, Any]] | None = None,
tools_call_name: list[str] | None = None,
tools_call_ids: list[str] | None = None,
tools_call_extra_content: dict[str, dict[str, Any]] | None = None,
raw_completion: ChatCompletion
| GenerateContentResponse
| AnthropicMessage
@@ -256,6 +259,8 @@ class LLMResponse:
tools_call_name = []
if tools_call_ids is None:
tools_call_ids = []
if tools_call_extra_content is None:
tools_call_extra_content = {}
self.role = role
self.completion_text = completion_text
@@ -263,6 +268,7 @@ class LLMResponse:
self.tools_call_args = tools_call_args
self.tools_call_name = tools_call_name
self.tools_call_ids = tools_call_ids
self.tools_call_extra_content = tools_call_extra_content
self.raw_completion = raw_completion
self.is_chunk = is_chunk
@@ -288,16 +294,19 @@ class LLMResponse:
"""Convert to OpenAI tool calls format. Deprecated, use to_openai_to_calls_model instead."""
ret = []
for idx, tool_call_arg in enumerate(self.tools_call_args):
ret.append(
{
"id": self.tools_call_ids[idx],
"function": {
"name": self.tools_call_name[idx],
"arguments": json.dumps(tool_call_arg),
},
"type": "function",
payload = {
"id": self.tools_call_ids[idx],
"function": {
"name": self.tools_call_name[idx],
"arguments": json.dumps(tool_call_arg),
},
)
"type": "function",
}
if self.tools_call_extra_content.get(self.tools_call_ids[idx]):
payload["extra_content"] = self.tools_call_extra_content[
self.tools_call_ids[idx]
]
ret.append(payload)
return ret
def to_openai_to_calls_model(self) -> list[ToolCall]:
@@ -311,6 +320,10 @@ class LLMResponse:
name=self.tools_call_name[idx],
arguments=json.dumps(tool_call_arg),
),
# the extra_content will not serialize if it's None when calling ToolCall.model_dump()
extra_content=self.tools_call_extra_content.get(
self.tools_call_ids[idx]
),
),
)
return ret
astrbot/core/provider/sources/gemini_source.py
+25 -8
View File
@@ -290,13 +290,24 @@ class ProviderGoogleGenAI(Provider):
parts = [types.Part.from_text(text=content)]
append_or_extend(gemini_contents, parts, types.ModelContent)
elif not native_tool_enabled and "tool_calls" in message:
parts = [
types.Part.from_function_call(
parts = []
for tool in message["tool_calls"]:
part = types.Part.from_function_call(
name=tool["function"]["name"],
args=json.loads(tool["function"]["arguments"]),
)
for tool in message["tool_calls"]
]
# we should set thought_signature back to part if exists
# for more info about thought_signature, see:
# https://ai.google.dev/gemini-api/docs/thought-signatures
if "extra_content" in tool:
ts_bs64 = (
tool["extra_content"]
.get("google", {})
.get("thought_signature")
)
if ts_bs64:
part.thought_signature = base64.b64decode(ts_bs64)
parts.append(part)
append_or_extend(gemini_contents, parts, types.ModelContent)
else:
logger.warning("assistant 角色的消息内容为空，已添加空格占位")
@@ -393,10 +404,15 @@ class ProviderGoogleGenAI(Provider):
llm_response.role = "tool"
llm_response.tools_call_name.append(part.function_call.name)
llm_response.tools_call_args.append(part.function_call.args)
# gemini 返回的 function_call.id 可能为 None
llm_response.tools_call_ids.append(
part.function_call.id or part.function_call.name,
)
# function_call.id might be None, use name as fallback
tool_call_id = part.function_call.id or part.function_call.name
llm_response.tools_call_ids.append(tool_call_id)
# extra_content
if part.thought_signature:
ts_bs64 = base64.b64encode(part.thought_signature).decode("utf-8")
llm_response.tools_call_extra_content[tool_call_id] = {
"google": {"thought_signature": ts_bs64}
}
elif (
part.inline_data
and part.inline_data.mime_type
@@ -435,6 +451,7 @@ class ProviderGoogleGenAI(Provider):
contents=conversation,
config=config,
)
logger.debug(f"genai result: {result}")
if not result.candidates:
logger.error(f"请求失败, 返回的 candidates 为空: {result}")
astrbot/core/provider/sources/openai_source.py
+9 -16
View File
@@ -8,7 +8,7 @@ import re
from collections.abc import AsyncGenerator
from openai import AsyncAzureOpenAI, AsyncOpenAI
from openai._exceptions import NotFoundError, UnprocessableEntityError
from openai._exceptions import NotFoundError
from openai.lib.streaming.chat._completions import ChatCompletionStreamState
from openai.types.chat.chat_completion import ChatCompletion
from openai.types.chat.chat_completion_chunk import ChatCompletionChunk
@@ -279,6 +279,7 @@ class ProviderOpenAIOfficial(Provider):
args_ls = []
func_name_ls = []
tool_call_ids = []
tool_call_extra_content_dict = {}
for tool_call in choice.message.tool_calls:
if isinstance(tool_call, str):
# workaround for #1359
@@ -296,11 +297,16 @@ class ProviderOpenAIOfficial(Provider):
args_ls.append(args)
func_name_ls.append(tool_call.function.name)
tool_call_ids.append(tool_call.id)
# gemini-2.5 / gemini-3 series extra_content handling
extra_content = getattr(tool_call, "extra_content", None)
if extra_content is not None:
tool_call_extra_content_dict[tool_call.id] = extra_content
llm_response.role = "tool"
llm_response.tools_call_args = args_ls
llm_response.tools_call_name = func_name_ls
llm_response.tools_call_ids = tool_call_ids
llm_response.tools_call_extra_content = tool_call_extra_content_dict
# specially handle finish reason
if choice.finish_reason == "content_filter":
raise Exception(
@@ -353,7 +359,7 @@ class ProviderOpenAIOfficial(Provider):
payloads = {"messages": context_query, **model_config}
# xAI 原生搜索参数（最小侵入地在此处注入）
# xAI origin search tool inject
self._maybe_inject_xai_search(payloads, **kwargs)
return payloads, context_query
@@ -475,12 +481,6 @@ class ProviderOpenAIOfficial(Provider):
self.client.api_key = chosen_key
llm_response = await self._query(payloads, func_tool)
break
except UnprocessableEntityError as e:
logger.warning(f"不可处理的实体错误：{e}，尝试删除图片。")
# 尝试删除所有 image
new_contexts = await self._remove_image_from_context(context_query)
payloads["messages"] = new_contexts
context_query = new_contexts
except Exception as e:
last_exception = e
(
@@ -545,12 +545,6 @@ class ProviderOpenAIOfficial(Provider):
async for response in self._query_stream(payloads, func_tool):
yield response
break
except UnprocessableEntityError as e:
logger.warning(f"不可处理的实体错误：{e}，尝试删除图片。")
# 尝试删除所有 image
new_contexts = await self._remove_image_from_context(context_query)
payloads["messages"] = new_contexts
context_query = new_contexts
except Exception as e:
last_exception = e
(
@@ -646,4 +640,3 @@ class ProviderOpenAIOfficial(Provider):
with open(image_url, "rb") as f:
image_bs64 = base64.b64encode(f.read()).decode("utf-8")
return "data:image/jpeg;base64," + image_bs64
return ""