xinyin025/LangBot
1
0
Fork 0
mirror of https://github.com/langbot-app/LangBot.git synced 2026-08-13 06:00:58 +00:00
Code Issues Packages Projects Releases Wiki Activity

fix:del some print ,and amend respback on stream judge ,and del in dingtalk this is_stream_output_supported() use

Browse Source
This commit is contained in:
Dong_master
2025-07-29 23:09:02 +08:00
parent 8f8c8ff367
commit 307f6acd8c
11 changed files with 101 additions and 188 deletions
Download Patch File Download Diff File Expand all files Collapse all files
pkg/provider/runners/dashscopeapi.py
-4
View File
@@ -185,8 +185,6 @@ class DashScopeAPIRunner(runner.RequestRunner):
# 将参考资料替换到文本中
pending_content = self._replace_references(pending_content, references_dict)
yield llm_entities.Message(
role='assistant',
content=pending_content,
@@ -261,13 +259,11 @@ class DashScopeAPIRunner(runner.RequestRunner):
role='assistant',
content=pending_content,
is_final=is_final,
)
# 保存当前会话的session_id用于下次对话的语境
query.session.using_conversation.uuid = stream_output.get('session_id')
else:
for chunk in response:
if chunk.get('status_code') != 200:
pkg/provider/runners/difysvapi.py
-2
View File
@@ -148,7 +148,6 @@ class DifyServiceAPIRunner(runner.RequestRunner):
if mode == 'workflow':
if chunk['event'] == 'node_finished':
if not is_stream:
if chunk['data']['node_type'] == 'answer':
yield llm_entities.Message(
role='assistant',
@@ -274,7 +273,6 @@ class DifyServiceAPIRunner(runner.RequestRunner):
content=self._try_convert_thinking(pending_agent_message),
)
if chunk['event'] == 'agent_thought':
if chunk['tool'] != '' and chunk['observation'] != '': # 工具调用结果，跳过
continue
pkg/provider/runners/localagent.py
+25 -29
View File
@@ -1,7 +1,6 @@
from __future__ import annotations
import json
from ssl import ALERT_DESCRIPTION_BAD_CERTIFICATE_HASH_VALUE
import typing
from .. import runner
@@ -15,26 +14,27 @@ class LocalAgentRunner(runner.RequestRunner):
class ToolCallTracker:
"""工具调用追踪器"""
def __init__(self):
self.active_calls: dict[str,dict] = {}
self.active_calls: dict[str, dict] = {}
self.completed_calls: list[llm_entities.ToolCall] = []
async def run(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message | llm_entities.MessageChunk, None]:
async def run(
self, query: core_entities.Query
) -> typing.AsyncGenerator[llm_entities.Message | llm_entities.MessageChunk, None]:
"""运行请求"""
pending_tool_calls = []
req_messages = query.prompt.messages.copy() + query.messages.copy() + [query.user_message]
try:
# print(await query.adapter.is_stream_output_supported())
is_stream = await query.adapter.is_stream_output_supported()
except AttributeError:
is_stream = False
# while True:
# pass
if not is_stream:
# 非流式输出，直接请求
# print(123)
msg = await query.use_llm_model.requester.invoke_llm(
query,
query.use_llm_model,
@@ -44,7 +44,6 @@ class LocalAgentRunner(runner.RequestRunner):
)
yield msg
final_msg = msg
print(final_msg)
else:
# 流式输出，需要处理工具调用
tool_calls_map: dict[str, llm_entities.ToolCall] = {}
@@ -55,29 +54,28 @@ class LocalAgentRunner(runner.RequestRunner):
query.use_funcs,
stream=is_stream,
extra_args=query.use_llm_model.model_entity.extra_args,
):
):
yield msg
# if msg.tool_calls:
# for tool_call in msg.tool_calls:
# if tool_call.id not in tool_calls_map:
# tool_calls_map[tool_call.id] = llm_entities.ToolCall(
# id=tool_call.id,
# type=tool_call.type,
# function=llm_entities.FunctionCall(
# name=tool_call.function.name if tool_call.function else '',
# arguments=''
# ),
# )
# if tool_call.function and tool_call.function.arguments:
# # 流式处理中，工具调用参数可能分多个chunk返回，需要追加而不是覆盖
# tool_calls_map[tool_call.id].function.arguments += tool_call.function.arguments
if msg.tool_calls:
for tool_call in msg.tool_calls:
if tool_call.id not in tool_calls_map:
tool_calls_map[tool_call.id] = llm_entities.ToolCall(
id=tool_call.id,
type=tool_call.type,
function=llm_entities.FunctionCall(
name=tool_call.function.name if tool_call.function else '',
arguments=''
),
)
if tool_call.function and tool_call.function.arguments:
# 流式处理中，工具调用参数可能分多个chunk返回，需要追加而不是覆盖
tool_calls_map[tool_call.id].function.arguments += tool_call.function.arguments
final_msg = llm_entities.Message(
role=msg.role,
content=msg.all_content,
tool_calls=list(tool_calls_map.values()),
)
pending_tool_calls = final_msg.tool_calls
req_messages.append(final_msg)
@@ -117,8 +115,8 @@ class LocalAgentRunner(runner.RequestRunner):
req_messages,
query.use_funcs,
stream=is_stream,
extra_args=query.use_llm_model.model_entity.extra_args,
):
extra_args=query.use_llm_model.model_entity.extra_args,
):
yield msg
if msg.tool_calls:
for tool_call in msg.tool_calls:
@@ -127,8 +125,7 @@ class LocalAgentRunner(runner.RequestRunner):
id=tool_call.id,
type=tool_call.type,
function=llm_entities.FunctionCall(
name=tool_call.function.name if tool_call.function else '',
arguments=''
name=tool_call.function.name if tool_call.function else '', arguments=''
),
)
if tool_call.function and tool_call.function.arguments:
@@ -140,7 +137,6 @@ class LocalAgentRunner(runner.RequestRunner):
tool_calls=list(tool_calls_map.values()),
)
else:
print("非流式")
# 处理完所有调用，再次请求
msg = await query.use_llm_model.requester.invoke_llm(
query,