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123 lines
4.8 KiB
Python
123 lines
4.8 KiB
Python
from __future__ import annotations
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import datetime
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from .. import stage, entities
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from langbot_plugin.api.entities.builtin.provider import message as provider_message
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import langbot_plugin.api.entities.events as events
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import langbot_plugin.api.entities.builtin.platform.message as platform_message
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import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
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@stage.stage_class('PreProcessor')
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class PreProcessor(stage.PipelineStage):
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"""请求预处理阶段
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签出会话、prompt、上文、模型、内容函数。
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改写：
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- session
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- prompt
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- messages
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- user_message
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- use_model
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- use_funcs
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"""
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async def process(
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self,
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query: pipeline_query.Query,
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stage_inst_name: str,
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) -> entities.StageProcessResult:
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"""处理"""
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selected_runner = query.pipeline_config['ai']['runner']['runner']
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session = await self.ap.sess_mgr.get_session(query)
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# 非 local-agent 时，llm_model 为 None
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llm_model = (
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await self.ap.model_mgr.get_model_by_uuid(query.pipeline_config['ai']['local-agent']['model'])
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if selected_runner == 'local-agent'
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else None
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)
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conversation = await self.ap.sess_mgr.get_conversation(
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query,
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session,
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query.pipeline_config['ai']['local-agent']['prompt'],
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query.pipeline_uuid,
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query.bot_uuid,
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)
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# 设置query
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query.session = session
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query.prompt = conversation.prompt.copy()
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query.messages = conversation.messages.copy()
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query.use_llm_model_uuid = llm_model.model_entity.uuid
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if selected_runner == 'local-agent':
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query.use_funcs = []
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if llm_model.model_entity.abilities.__contains__('func_call'):
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query.use_funcs = await self.ap.tool_mgr.get_all_tools()
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variables = {
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'session_id': f'{query.session.launcher_type.value}_{query.session.launcher_id}',
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'conversation_id': conversation.uuid,
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'msg_create_time': (
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int(query.message_event.time) if query.message_event.time else int(datetime.datetime.now().timestamp())
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),
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}
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query.variables.update(variables)
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# Check if this model supports vision, if not, remove all images
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# TODO this checking should be performed in runner, and in this stage, the image should be reserved
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if selected_runner == 'local-agent' and not llm_model.model_entity.abilities.__contains__('vision'):
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for msg in query.messages:
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if isinstance(msg.content, list):
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for me in msg.content:
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if me.type == 'image_url':
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msg.content.remove(me)
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content_list = []
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plain_text = ''
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qoute_msg = query.pipeline_config['trigger'].get('misc', '').get('combine-quote-message')
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for me in query.message_chain:
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if isinstance(me, platform_message.Plain):
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content_list.append(provider_message.ContentElement.from_text(me.text))
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plain_text += me.text
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elif isinstance(me, platform_message.Image):
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if selected_runner != 'local-agent' or llm_model.model_entity.abilities.__contains__('vision'):
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if me.base64 is not None:
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content_list.append(provider_message.ContentElement.from_image_base64(me.base64))
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elif isinstance(me, platform_message.Quote) and qoute_msg:
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for msg in me.origin:
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if isinstance(msg, platform_message.Plain):
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content_list.append(provider_message.ContentElement.from_text(msg.text))
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elif isinstance(msg, platform_message.Image):
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if selected_runner != 'local-agent' or llm_model.model_entity.abilities.__contains__('vision'):
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if msg.base64 is not None:
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content_list.append(provider_message.ContentElement.from_image_base64(msg.base64))
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query.variables['user_message_text'] = plain_text
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query.user_message = provider_message.Message(role='user', content=content_list)
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# =========== 触发事件 PromptPreProcessing
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event = events.PromptPreProcessing(
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session_name=f'{query.session.launcher_type.value}_{query.session.launcher_id}',
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default_prompt=query.prompt.messages,
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prompt=query.messages,
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query=query,
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)
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event_ctx = await self.ap.plugin_connector.emit_event(event)
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query.prompt.messages = event_ctx.event.default_prompt
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query.messages = event_ctx.event.prompt
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return entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
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