Merge pull request #847 from RockChinQ/version/3.3

Release: 3.3
This commit is contained in:
Junyan Qin 2024-07-28 20:57:26 +08:00 committed by GitHub
commit 78d98c40b1
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35 changed files with 599 additions and 86 deletions

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@ -8,7 +8,7 @@ from . import entities, operator, errors
from ..config import manager as cfg_mgr
# 引入所有算子以便注册
from .operators import func, plugin, default, reset, list as list_cmd, last, next, delc, resend, prompt, cmd, help, version, update
from .operators import func, plugin, default, reset, list as list_cmd, last, next, delc, resend, prompt, cmd, help, version, update, ollama, model
class CommandManager:

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@ -0,0 +1,86 @@
from __future__ import annotations
import typing
from .. import operator, entities, cmdmgr, errors
@operator.operator_class(
name="model",
help='显示和切换模型列表',
usage='!model\n!model show <模型名>\n!model set <模型名>',
privilege=2
)
class ModelOperator(operator.CommandOperator):
"""Model命令"""
async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
content = '模型列表:\n'
model_list = self.ap.model_mgr.model_list
for model in model_list:
content += f"\n名称: {model.name}\n"
content += f"请求器: {model.requester.name}\n"
content += f"\n当前对话使用模型: {context.query.use_model.name}\n"
content += f"新对话默认使用模型: {self.ap.provider_cfg.data.get('model')}\n"
yield entities.CommandReturn(text=content.strip())
@operator.operator_class(
name="show",
help='显示模型详情',
privilege=2,
parent_class=ModelOperator
)
class ModelShowOperator(operator.CommandOperator):
"""Model Show命令"""
async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
model_name = context.crt_params[0]
model = None
for _model in self.ap.model_mgr.model_list:
if model_name == _model.name:
model = _model
break
if model is None:
yield entities.CommandReturn(error=errors.CommandError(f"未找到模型 {model_name}"))
else:
content = f"模型详情\n"
content += f"名称: {model.name}\n"
if model.model_name is not None:
content += f"请求模型名称: {model.model_name}\n"
content += f"请求器: {model.requester.name}\n"
content += f"密钥组: {model.token_mgr.provider}\n"
content += f"支持视觉: {model.vision_supported}\n"
content += f"支持工具: {model.tool_call_supported}\n"
yield entities.CommandReturn(text=content.strip())
@operator.operator_class(
name="set",
help='设置默认使用模型',
privilege=2,
parent_class=ModelOperator
)
class ModelSetOperator(operator.CommandOperator):
"""Model Set命令"""
async def execute(self, context: entities.ExecuteContext) -> typing.AsyncGenerator[entities.CommandReturn, None]:
model_name = context.crt_params[0]
model = None
for _model in self.ap.model_mgr.model_list:
if model_name == _model.name:
model = _model
break
if model is None:
yield entities.CommandReturn(error=errors.CommandError(f"未找到模型 {model_name}"))
else:
self.ap.provider_cfg.data['model'] = model_name
await self.ap.provider_cfg.dump_config()
yield entities.CommandReturn(text=f"已设置当前使用模型为 {model_name},重置会话以生效")

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@ -0,0 +1,121 @@
from __future__ import annotations
import json
import typing
import traceback
import ollama
from .. import operator, entities, errors
@operator.operator_class(
name="ollama",
help="ollama平台操作",
usage="!ollama\n!ollama show <模型名>\n!ollama pull <模型名>\n!ollama del <模型名>"
)
class OllamaOperator(operator.CommandOperator):
async def execute(
self, context: entities.ExecuteContext
) -> typing.AsyncGenerator[entities.CommandReturn, None]:
try:
content: str = '模型列表:\n'
model_list: list = ollama.list().get('models', [])
for model in model_list:
content += f"名称: {model['name']}\n"
content += f"修改时间: {model['modified_at']}\n"
content += f"大小: {bytes_to_mb(model['size'])}MB\n\n"
yield entities.CommandReturn(text=f"{content.strip()}")
except ollama.ResponseError as e:
yield entities.CommandReturn(error=errors.CommandError(f"无法获取模型列表,请确认 Ollama 服务正常"))
def bytes_to_mb(num_bytes):
mb: float = num_bytes / 1024 / 1024
return format(mb, '.2f')
@operator.operator_class(
name="show",
help="ollama模型详情",
privilege=2,
parent_class=OllamaOperator
)
class OllamaShowOperator(operator.CommandOperator):
async def execute(
self, context: entities.ExecuteContext
) -> typing.AsyncGenerator[entities.CommandReturn, None]:
content: str = '模型详情:\n'
try:
show: dict = ollama.show(model=context.crt_params[0])
model_info: dict = show.get('model_info', {})
ignore_show: str = 'too long to show...'
for key in ['license', 'modelfile']:
show[key] = ignore_show
for key in ['tokenizer.chat_template.rag', 'tokenizer.chat_template.tool_use']:
model_info[key] = ignore_show
content += json.dumps(show, indent=4)
yield entities.CommandReturn(text=content.strip())
except ollama.ResponseError as e:
yield entities.CommandReturn(error=errors.CommandError(f"无法获取模型详情,请确认 Ollama 服务正常"))
@operator.operator_class(
name="pull",
help="ollama模型拉取",
privilege=2,
parent_class=OllamaOperator
)
class OllamaPullOperator(operator.CommandOperator):
async def execute(
self, context: entities.ExecuteContext
) -> typing.AsyncGenerator[entities.CommandReturn, None]:
try:
model_list: list = ollama.list().get('models', [])
if context.crt_params[0] in [model['name'] for model in model_list]:
yield entities.CommandReturn(text="模型已存在")
return
except ollama.ResponseError as e:
yield entities.CommandReturn(error=errors.CommandError(f"无法获取模型列表,请确认 Ollama 服务正常"))
return
on_progress: bool = False
progress_count: int = 0
try:
for resp in ollama.pull(model=context.crt_params[0], stream=True):
total: typing.Any = resp.get('total')
if not on_progress:
if total is not None:
on_progress = True
yield entities.CommandReturn(text=resp.get('status'))
else:
if total is None:
on_progress = False
completed: typing.Any = resp.get('completed')
if isinstance(completed, int) and isinstance(total, int):
percentage_completed = (completed / total) * 100
if percentage_completed > progress_count:
progress_count += 10
yield entities.CommandReturn(
text=f"下载进度: {completed}/{total} ({percentage_completed:.2f}%)")
except ollama.ResponseError as e:
yield entities.CommandReturn(text=f"拉取失败: {e.error}")
@operator.operator_class(
name="del",
help="ollama模型删除",
privilege=2,
parent_class=OllamaOperator
)
class OllamaDelOperator(operator.CommandOperator):
async def execute(
self, context: entities.ExecuteContext
) -> typing.AsyncGenerator[entities.CommandReturn, None]:
try:
ret: str = ollama.delete(model=context.crt_params[0])['status']
except ollama.ResponseError as e:
ret = f"{e.error}"
yield entities.CommandReturn(text=ret)

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@ -20,7 +20,7 @@ class VersionCommand(operator.CommandOperator):
try:
if await self.ap.ver_mgr.is_new_version_available():
reply_str += "\n\n有新版本可用, 使用 !update 更新"
reply_str += "\n\n有新版本可用"
except:
pass

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@ -9,6 +9,7 @@ from ..provider.session import sessionmgr as llm_session_mgr
from ..provider.modelmgr import modelmgr as llm_model_mgr
from ..provider.sysprompt import sysprompt as llm_prompt_mgr
from ..provider.tools import toolmgr as llm_tool_mgr
from ..provider import runnermgr
from ..config import manager as config_mgr
from ..audit.center import v2 as center_mgr
from ..command import cmdmgr
@ -33,6 +34,8 @@ class Application:
tool_mgr: llm_tool_mgr.ToolManager = None
runner_mgr: runnermgr.RunnerManager = None
# ======= 配置管理器 =======
command_cfg: config_mgr.ConfigManager = None

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@ -3,7 +3,7 @@ from __future__ import annotations
import abc
import typing
from ..core import app
from . import app
preregistered_migrations: list[typing.Type[Migration]] = []

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@ -0,0 +1,23 @@
from __future__ import annotations
from .. import migration
@migration.migration_class("ollama-requester-config", 10)
class MsgTruncatorConfigMigration(migration.Migration):
"""迁移"""
async def need_migrate(self) -> bool:
"""判断当前环境是否需要运行此迁移"""
return 'ollama-chat' not in self.ap.provider_cfg.data['requester']
async def run(self):
"""执行迁移"""
self.ap.provider_cfg.data['requester']['ollama-chat'] = {
"base-url": "http://127.0.0.1:11434",
"args": {},
"timeout": 600
}
await self.ap.provider_cfg.dump_config()

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@ -0,0 +1,21 @@
from __future__ import annotations
from .. import migration
@migration.migration_class("command-prefix-config", 11)
class CommandPrefixConfigMigration(migration.Migration):
"""迁移"""
async def need_migrate(self) -> bool:
"""判断当前环境是否需要运行此迁移"""
return 'command-prefix' not in self.ap.command_cfg.data
async def run(self):
"""执行迁移"""
self.ap.command_cfg.data['command-prefix'] = [
"!", ""
]
await self.ap.command_cfg.dump_config()

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@ -0,0 +1,19 @@
from __future__ import annotations
from .. import migration
@migration.migration_class("runner-config", 12)
class RunnerConfigMigration(migration.Migration):
"""迁移"""
async def need_migrate(self) -> bool:
"""判断当前环境是否需要运行此迁移"""
return 'runner' not in self.ap.provider_cfg.data
async def run(self):
"""执行迁移"""
self.ap.provider_cfg.data['runner'] = 'local-agent'
await self.ap.provider_cfg.dump_config()

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@ -13,6 +13,7 @@ from ...provider.session import sessionmgr as llm_session_mgr
from ...provider.modelmgr import modelmgr as llm_model_mgr
from ...provider.sysprompt import sysprompt as llm_prompt_mgr
from ...provider.tools import toolmgr as llm_tool_mgr
from ...provider import runnermgr
from ...platform import manager as im_mgr
@stage.stage_class("BuildAppStage")
@ -81,6 +82,11 @@ class BuildAppStage(stage.BootingStage):
llm_tool_mgr_inst = llm_tool_mgr.ToolManager(ap)
await llm_tool_mgr_inst.initialize()
ap.tool_mgr = llm_tool_mgr_inst
runner_mgr_inst = runnermgr.RunnerManager(ap)
await runner_mgr_inst.initialize()
ap.runner_mgr = runner_mgr_inst
im_mgr_inst = im_mgr.PlatformManager(ap=ap)
await im_mgr_inst.initialize()
ap.platform_mgr = im_mgr_inst

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@ -3,9 +3,10 @@ from __future__ import annotations
import importlib
from .. import stage, app
from ...config import migration
from ...config.migrations import m001_sensitive_word_migration, m002_openai_config_migration, m003_anthropic_requester_cfg_completion, m004_moonshot_cfg_completion
from ...config.migrations import m005_deepseek_cfg_completion, m006_vision_config, m007_qcg_center_url, m008_ad_fixwin_config_migrate, m009_msg_truncator_cfg
from .. import migration
from ..migrations import m001_sensitive_word_migration, m002_openai_config_migration, m003_anthropic_requester_cfg_completion, m004_moonshot_cfg_completion
from ..migrations import m005_deepseek_cfg_completion, m006_vision_config, m007_qcg_center_url, m008_ad_fixwin_config_migrate, m009_msg_truncator_cfg
from ..migrations import m010_ollama_requester_config, m011_command_prefix_config, m012_runner_config
@stage.stage_class("MigrationStage")

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@ -10,7 +10,7 @@ import mirai
from .. import handler
from ... import entities
from ....core import entities as core_entities
from ....provider import entities as llm_entities
from ....provider import entities as llm_entities, runnermgr
from ....plugin import events
@ -71,7 +71,9 @@ class ChatMessageHandler(handler.MessageHandler):
try:
async for result in self.runner(query):
runner = self.ap.runner_mgr.get_runner()
async for result in runner.run(query):
query.resp_messages.append(result)
self.ap.logger.info(f'对话({query.query_id})响应: {self.cut_str(result.readable_str())}')
@ -108,64 +110,3 @@ class ChatMessageHandler(handler.MessageHandler):
response_seconds=int(time.time() - start_time),
retry_times=-1,
)
async def runner(
self,
query: core_entities.Query,
) -> typing.AsyncGenerator[llm_entities.Message, None]:
"""执行一个请求处理过程中的LLM接口请求、函数调用的循环
这是临时处理方案后续可能改为使用LangChain或者自研的工作流处理器
"""
await query.use_model.requester.preprocess(query)
pending_tool_calls = []
req_messages = query.prompt.messages.copy() + query.messages.copy() + [query.user_message]
# 首次请求
msg = await query.use_model.requester.call(query.use_model, req_messages, query.use_funcs)
yield msg
pending_tool_calls = msg.tool_calls
req_messages.append(msg)
# 持续请求,只要还有待处理的工具调用就继续处理调用
while pending_tool_calls:
for tool_call in pending_tool_calls:
try:
func = tool_call.function
parameters = json.loads(func.arguments)
func_ret = await self.ap.tool_mgr.execute_func_call(
query, func.name, parameters
)
msg = llm_entities.Message(
role="tool", content=json.dumps(func_ret, ensure_ascii=False), tool_call_id=tool_call.id
)
yield msg
req_messages.append(msg)
except Exception as e:
# 工具调用出错,添加一个报错信息到 req_messages
err_msg = llm_entities.Message(
role="tool", content=f"err: {e}", tool_call_id=tool_call.id
)
yield err_msg
req_messages.append(err_msg)
# 处理完所有调用,再次请求
msg = await query.use_model.requester.call(query.use_model, req_messages, query.use_funcs)
yield msg
pending_tool_calls = msg.tool_calls
req_messages.append(msg)

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@ -42,7 +42,9 @@ class Processor(stage.PipelineStage):
self.ap.logger.info(f"处理 {query.launcher_type.value}_{query.launcher_id} 的请求({query.query_id}): {message_text}")
async def generator():
if message_text.startswith('!') or message_text.startswith(''):
cmd_prefix = self.ap.command_cfg.data['command-prefix']
if any(message_text.startswith(prefix) for prefix in cmd_prefix):
async for result in self.cmd_handler.handle(query):
yield result
else:

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@ -146,9 +146,9 @@ class PlatformManager:
if len(self.adapters) == 0:
self.ap.logger.warning('未运行平台适配器,请根据文档配置并启用平台适配器。')
async def send(self, event: mirai.MessageEvent, msg: mirai.MessageChain, adapter: msadapter.MessageSourceAdapter, check_quote=True, check_at_sender=True):
async def send(self, event: mirai.MessageEvent, msg: mirai.MessageChain, adapter: msadapter.MessageSourceAdapter):
if check_at_sender and self.ap.platform_cfg.data['at-sender'] and isinstance(event, GroupMessage):
if self.ap.platform_cfg.data['at-sender'] and isinstance(event, GroupMessage):
msg.insert(
0,
@ -160,7 +160,7 @@ class PlatformManager:
await adapter.reply_message(
event,
msg,
quote_origin=True if self.ap.platform_cfg.data['quote-origin'] and check_quote else False
quote_origin=True if self.ap.platform_cfg.data['quote-origin'] else False
)
async def run(self):

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@ -3,6 +3,7 @@ from __future__ import annotations
import typing
import abc
import pydantic
import mirai
from . import events
from ..provider.tools import entities as tools_entities
@ -165,12 +166,55 @@ class EventContext:
}
"""
# ========== 插件可调用的 API ==========
def add_return(self, key: str, ret):
"""添加返回值"""
if key not in self.__return_value__:
self.__return_value__[key] = []
self.__return_value__[key].append(ret)
async def reply(self, message_chain: mirai.MessageChain):
"""回复此次消息请求
Args:
message_chain (mirai.MessageChain): YiriMirai库的消息链若用户使用的不是 YiriMirai 适配器程序也能自动转换为目标消息链
"""
await self.host.ap.platform_mgr.send(
event=self.event.query.message_event,
msg=message_chain,
adapter=self.event.query.adapter,
)
async def send_message(
self,
target_type: str,
target_id: str,
message: mirai.MessageChain
):
"""主动发送消息
Args:
target_type (str): 目标类型`person``group`
target_id (str): 目标ID
message (mirai.MessageChain): YiriMirai库的消息链若用户使用的不是 YiriMirai 适配器程序也能自动转换为目标消息链
"""
await self.event.query.adapter.send_message(
target_type=target_type,
target_id=target_id,
message=message
)
def prevent_postorder(self):
"""阻止后续插件执行"""
self.__prevent_postorder__ = True
def prevent_default(self):
"""阻止默认行为"""
self.__prevent_default__ = True
# ========== 以下是内部保留方法,插件不应调用 ==========
def get_return(self, key: str) -> list:
"""获取key的所有返回值"""
if key in self.__return_value__:
@ -183,14 +227,6 @@ class EventContext:
return self.__return_value__[key][0]
return None
def prevent_default(self):
"""阻止默认行为"""
self.__prevent_default__ = True
def prevent_postorder(self):
"""阻止后续插件执行"""
self.__prevent_postorder__ = True
def is_prevented_default(self):
"""是否阻止默认行为"""
return self.__prevent_default__
@ -199,6 +235,7 @@ class EventContext:
"""是否阻止后序插件执行"""
return self.__prevent_postorder__
def __init__(self, host: APIHost, event: events.BaseEventModel):
self.eid = EventContext.eid

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@ -95,7 +95,7 @@ class Message(pydantic.BaseModel):
for ce in self.content:
if ce.type == 'text':
mc.append(mirai.Plain(ce.text))
elif ce.type == 'image':
elif ce.type == 'image_url':
if ce.image_url.url.startswith("http"):
mc.append(mirai.Image(url=ce.image_url.url))
else: # base64

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@ -0,0 +1,105 @@
from __future__ import annotations
import asyncio
import os
import typing
from typing import Union, Mapping, Any, AsyncIterator
import async_lru
import ollama
from .. import api, entities, errors
from ... import entities as llm_entities
from ...tools import entities as tools_entities
from ....core import app
from ....utils import image
REQUESTER_NAME: str = "ollama-chat"
@api.requester_class(REQUESTER_NAME)
class OllamaChatCompletions(api.LLMAPIRequester):
"""Ollama平台 ChatCompletion API请求器"""
client: ollama.AsyncClient
request_cfg: dict
def __init__(self, ap: app.Application):
super().__init__(ap)
self.ap = ap
self.request_cfg = self.ap.provider_cfg.data['requester'][REQUESTER_NAME]
async def initialize(self):
os.environ['OLLAMA_HOST'] = self.request_cfg['base-url']
self.client = ollama.AsyncClient(
timeout=self.request_cfg['timeout']
)
async def _req(self,
args: dict,
) -> Union[Mapping[str, Any], AsyncIterator[Mapping[str, Any]]]:
return await self.client.chat(
**args
)
async def _closure(self, req_messages: list[dict], use_model: entities.LLMModelInfo,
user_funcs: list[tools_entities.LLMFunction] = None) -> (
llm_entities.Message):
args: Any = self.request_cfg['args'].copy()
args["model"] = use_model.name if use_model.model_name is None else use_model.model_name
messages: list[dict] = req_messages.copy()
for msg in messages:
if 'content' in msg and isinstance(msg["content"], list):
text_content: list = []
image_urls: list = []
for me in msg["content"]:
if me["type"] == "text":
text_content.append(me["text"])
elif me["type"] == "image_url":
image_url = await self.get_base64_str(me["image_url"]['url'])
image_urls.append(image_url)
msg["content"] = "\n".join(text_content)
msg["images"] = [url.split(',')[1] for url in image_urls]
args["messages"] = messages
resp: Mapping[str, Any] | AsyncIterator[Mapping[str, Any]] = await self._req(args)
message: llm_entities.Message = await self._make_msg(resp)
return message
async def _make_msg(
self,
chat_completions: Union[Mapping[str, Any], AsyncIterator[Mapping[str, Any]]]) -> llm_entities.Message:
message: Any = chat_completions.pop('message', None)
if message is None:
raise ValueError("chat_completions must contain a 'message' field")
message.update(chat_completions)
ret_msg: llm_entities.Message = llm_entities.Message(**message)
return ret_msg
async def call(
self,
model: entities.LLMModelInfo,
messages: typing.List[llm_entities.Message],
funcs: typing.List[tools_entities.LLMFunction] = None,
) -> llm_entities.Message:
req_messages: list = []
for m in messages:
msg_dict: dict = m.dict(exclude_none=True)
content: Any = msg_dict.get("content")
if isinstance(content, list):
if all(isinstance(part, dict) and part.get('type') == 'text' for part in content):
msg_dict["content"] = "\n".join(part["text"] for part in content)
req_messages.append(msg_dict)
try:
return await self._closure(req_messages, model)
except asyncio.TimeoutError:
raise errors.RequesterError('请求超时')
@async_lru.alru_cache(maxsize=128)
async def get_base64_str(
self,
original_url: str,
) -> str:
base64_image: str = await image.qq_image_url_to_base64(original_url)
return f"data:image/jpeg;base64,{base64_image}"

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@ -6,7 +6,7 @@ from . import entities
from ...core import app
from . import token, api
from .apis import chatcmpl, anthropicmsgs, moonshotchatcmpl, deepseekchatcmpl
from .apis import chatcmpl, anthropicmsgs, moonshotchatcmpl, deepseekchatcmpl, ollamachat
FETCH_MODEL_LIST_URL = "https://api.qchatgpt.rockchin.top/api/v2/fetch/model_list"

40
pkg/provider/runner.py Normal file
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@ -0,0 +1,40 @@
from __future__ import annotations
import abc
import typing
from ..core import app, entities as core_entities
from . import entities as llm_entities
preregistered_runners: list[typing.Type[RequestRunner]] = []
def runner_class(name: str):
"""注册一个请求运行器
"""
def decorator(cls: typing.Type[RequestRunner]) -> typing.Type[RequestRunner]:
cls.name = name
preregistered_runners.append(cls)
return cls
return decorator
class RequestRunner(abc.ABC):
"""请求运行器
"""
name: str = None
ap: app.Application
def __init__(self, ap: app.Application):
self.ap = ap
async def initialize(self):
pass
@abc.abstractmethod
async def run(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
"""运行请求
"""
pass

27
pkg/provider/runnermgr.py Normal file
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@ -0,0 +1,27 @@
from __future__ import annotations
from . import runner
from ..core import app
from .runners import localagent
class RunnerManager:
ap: app.Application
using_runner: runner.RequestRunner
def __init__(self, ap: app.Application):
self.ap = ap
async def initialize(self):
for r in runner.preregistered_runners:
if r.name == self.ap.provider_cfg.data['runner']:
self.using_runner = r(self.ap)
await self.using_runner.initialize()
break
def get_runner(self) -> runner.RequestRunner:
return self.using_runner

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@ -0,0 +1,70 @@
from __future__ import annotations
import json
import typing
from .. import runner
from ...core import app, entities as core_entities
from .. import entities as llm_entities
@runner.runner_class("local-agent")
class LocalAgentRunner(runner.RequestRunner):
"""本地Agent请求运行器
"""
async def run(self, query: core_entities.Query) -> typing.AsyncGenerator[llm_entities.Message, None]:
"""运行请求
"""
await query.use_model.requester.preprocess(query)
pending_tool_calls = []
req_messages = query.prompt.messages.copy() + query.messages.copy() + [query.user_message]
# 首次请求
msg = await query.use_model.requester.call(query.use_model, req_messages, query.use_funcs)
yield msg
pending_tool_calls = msg.tool_calls
req_messages.append(msg)
# 持续请求,只要还有待处理的工具调用就继续处理调用
while pending_tool_calls:
for tool_call in pending_tool_calls:
try:
func = tool_call.function
parameters = json.loads(func.arguments)
func_ret = await self.ap.tool_mgr.execute_func_call(
query, func.name, parameters
)
msg = llm_entities.Message(
role="tool", content=json.dumps(func_ret, ensure_ascii=False), tool_call_id=tool_call.id
)
yield msg
req_messages.append(msg)
except Exception as e:
# 工具调用出错,添加一个报错信息到 req_messages
err_msg = llm_entities.Message(
role="tool", content=f"err: {e}", tool_call_id=tool_call.id
)
yield err_msg
req_messages.append(err_msg)
# 处理完所有调用,再次请求
msg = await query.use_model.requester.call(query.use_model, req_messages, query.use_funcs)
yield msg
pending_tool_calls = msg.tool_calls
req_messages.append(msg)

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@ -15,3 +15,4 @@ websockets
urllib3
psutil
async-lru
ollama

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@ -1,3 +1,7 @@
{
"privilege": {}
"privilege": {},
"command-prefix": [
"!",
""
]
}

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@ -37,11 +37,17 @@
"base-url": "https://api.deepseek.com",
"args": {},
"timeout": 120
},
"ollama-chat": {
"base-url": "http://127.0.0.1:11434",
"args": {},
"timeout": 600
}
},
"model": "gpt-3.5-turbo",
"prompt-mode": "normal",
"prompt": {
"default": ""
}
},
"runner": "local-agent"
}