mirror of
https://github.com/langgenius/dify.git
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389 lines
16 KiB
Python
389 lines
16 KiB
Python
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import decimal
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import json
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from typing import Optional, Union
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from gunicorn.config import User
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from core.callback_handler.entity.agent_loop import AgentLoop
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from core.callback_handler.entity.dataset_query import DatasetQueryObj
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from core.callback_handler.entity.llm_message import LLMMessage
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from core.callback_handler.entity.chain_result import ChainResult
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from core.constant import llm_constant
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from core.llm.llm_builder import LLMBuilder
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from core.llm.provider.llm_provider_service import LLMProviderService
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from core.prompt.prompt_builder import PromptBuilder
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from core.prompt.prompt_template import OutLinePromptTemplate
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from events.message_event import message_was_created
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from extensions.ext_database import db
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from extensions.ext_redis import redis_client
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from models.dataset import DatasetQuery
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from models.model import AppModelConfig, Conversation, Account, Message, EndUser, App, MessageAgentThought, MessageChain
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from models.provider import ProviderType, Provider
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class ConversationMessageTask:
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def __init__(self, task_id: str, app: App, app_model_config: AppModelConfig, user: Account,
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inputs: dict, query: str, streaming: bool,
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conversation: Optional[Conversation] = None, is_override: bool = False):
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self.task_id = task_id
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self.app = app
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self.tenant_id = app.tenant_id
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self.app_model_config = app_model_config
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self.is_override = is_override
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self.user = user
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self.inputs = inputs
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self.query = query
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self.streaming = streaming
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self.conversation = conversation
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self.is_new_conversation = False
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self.message = None
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self.model_dict = self.app_model_config.model_dict
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self.model_name = self.model_dict.get('name')
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self.mode = app.mode
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self.init()
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self._pub_handler = PubHandler(
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user=self.user,
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task_id=self.task_id,
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message=self.message,
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conversation=self.conversation,
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chain_pub=False, # disabled currently
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agent_thought_pub=False # disabled currently
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)
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def init(self):
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override_model_configs = None
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if self.is_override:
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override_model_configs = {
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"model": self.app_model_config.model_dict,
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"pre_prompt": self.app_model_config.pre_prompt,
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"agent_mode": self.app_model_config.agent_mode_dict,
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"opening_statement": self.app_model_config.opening_statement,
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"suggested_questions": self.app_model_config.suggested_questions_list,
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"suggested_questions_after_answer": self.app_model_config.suggested_questions_after_answer_dict,
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"more_like_this": self.app_model_config.more_like_this_dict,
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"user_input_form": self.app_model_config.user_input_form_list,
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}
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introduction = ''
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system_instruction = ''
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system_instruction_tokens = 0
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if self.mode == 'chat':
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introduction = self.app_model_config.opening_statement
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if introduction:
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prompt_template = OutLinePromptTemplate.from_template(template=PromptBuilder.process_template(introduction))
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prompt_inputs = {k: self.inputs[k] for k in prompt_template.input_variables if k in self.inputs}
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introduction = prompt_template.format(**prompt_inputs)
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if self.app_model_config.pre_prompt:
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pre_prompt = PromptBuilder.process_template(self.app_model_config.pre_prompt)
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system_message = PromptBuilder.to_system_message(pre_prompt, self.inputs)
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system_instruction = system_message.content
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llm = LLMBuilder.to_llm(self.tenant_id, self.model_name)
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system_instruction_tokens = llm.get_messages_tokens([system_message])
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if not self.conversation:
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self.is_new_conversation = True
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self.conversation = Conversation(
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app_id=self.app_model_config.app_id,
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app_model_config_id=self.app_model_config.id,
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model_provider=self.model_dict.get('provider'),
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model_id=self.model_name,
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override_model_configs=json.dumps(override_model_configs) if override_model_configs else None,
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mode=self.mode,
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name='',
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inputs=self.inputs,
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introduction=introduction,
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system_instruction=system_instruction,
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system_instruction_tokens=system_instruction_tokens,
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status='normal',
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from_source=('console' if isinstance(self.user, Account) else 'api'),
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from_end_user_id=(self.user.id if isinstance(self.user, EndUser) else None),
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from_account_id=(self.user.id if isinstance(self.user, Account) else None),
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)
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db.session.add(self.conversation)
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db.session.flush()
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self.message = Message(
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app_id=self.app_model_config.app_id,
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model_provider=self.model_dict.get('provider'),
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model_id=self.model_name,
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override_model_configs=json.dumps(override_model_configs) if override_model_configs else None,
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conversation_id=self.conversation.id,
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inputs=self.inputs,
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query=self.query,
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message="",
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message_tokens=0,
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message_unit_price=0,
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answer="",
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answer_tokens=0,
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answer_unit_price=0,
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provider_response_latency=0,
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total_price=0,
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currency=llm_constant.model_currency,
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from_source=('console' if isinstance(self.user, Account) else 'api'),
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from_end_user_id=(self.user.id if isinstance(self.user, EndUser) else None),
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from_account_id=(self.user.id if isinstance(self.user, Account) else None),
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agent_based=self.app_model_config.agent_mode_dict.get('enabled'),
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)
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db.session.add(self.message)
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db.session.flush()
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def append_message_text(self, text: str):
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self._pub_handler.pub_text(text)
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def save_message(self, llm_message: LLMMessage, by_stopped: bool = False):
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model_name = self.app_model_config.model_dict.get('name')
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message_tokens = llm_message.prompt_tokens
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answer_tokens = llm_message.completion_tokens
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message_unit_price = llm_constant.model_prices[model_name]['prompt']
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answer_unit_price = llm_constant.model_prices[model_name]['completion']
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total_price = self.calc_total_price(message_tokens, message_unit_price, answer_tokens, answer_unit_price)
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self.message.message = llm_message.prompt
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self.message.message_tokens = message_tokens
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self.message.message_unit_price = message_unit_price
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self.message.answer = llm_message.completion.strip() if llm_message.completion else ''
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self.message.answer_tokens = answer_tokens
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self.message.answer_unit_price = answer_unit_price
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self.message.provider_response_latency = llm_message.latency
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self.message.total_price = total_price
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self.update_provider_quota()
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db.session.commit()
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message_was_created.send(
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self.message,
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conversation=self.conversation,
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is_first_message=self.is_new_conversation
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)
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if not by_stopped:
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self._pub_handler.pub_end()
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def update_provider_quota(self):
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llm_provider_service = LLMProviderService(
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tenant_id=self.app.tenant_id,
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provider_name=self.message.model_provider,
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)
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provider = llm_provider_service.get_provider_db_record()
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if provider and provider.provider_type == ProviderType.SYSTEM.value:
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db.session.query(Provider).filter(
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Provider.tenant_id == self.app.tenant_id,
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Provider.quota_limit > Provider.quota_used
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).update({'quota_used': Provider.quota_used + 1})
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def init_chain(self, chain_result: ChainResult):
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message_chain = MessageChain(
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message_id=self.message.id,
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type=chain_result.type,
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input=json.dumps(chain_result.prompt),
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output=''
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)
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db.session.add(message_chain)
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db.session.flush()
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return message_chain
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def on_chain_end(self, message_chain: MessageChain, chain_result: ChainResult):
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message_chain.output = json.dumps(chain_result.completion)
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self._pub_handler.pub_chain(message_chain)
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def on_agent_end(self, message_chain: MessageChain, agent_model_name: str,
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agent_loop: AgentLoop):
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agent_message_unit_price = llm_constant.model_prices[agent_model_name]['prompt']
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agent_answer_unit_price = llm_constant.model_prices[agent_model_name]['completion']
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loop_message_tokens = agent_loop.prompt_tokens
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loop_answer_tokens = agent_loop.completion_tokens
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loop_total_price = self.calc_total_price(
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loop_message_tokens,
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agent_message_unit_price,
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loop_answer_tokens,
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agent_answer_unit_price
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)
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message_agent_loop = MessageAgentThought(
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message_id=self.message.id,
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message_chain_id=message_chain.id,
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position=agent_loop.position,
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thought=agent_loop.thought,
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tool=agent_loop.tool_name,
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tool_input=agent_loop.tool_input,
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observation=agent_loop.tool_output,
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tool_process_data='', # currently not support
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message=agent_loop.prompt,
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message_token=loop_message_tokens,
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message_unit_price=agent_message_unit_price,
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answer=agent_loop.completion,
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answer_token=loop_answer_tokens,
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answer_unit_price=agent_answer_unit_price,
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latency=agent_loop.latency,
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tokens=agent_loop.prompt_tokens + agent_loop.completion_tokens,
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total_price=loop_total_price,
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currency=llm_constant.model_currency,
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created_by_role=('account' if isinstance(self.user, Account) else 'end_user'),
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created_by=self.user.id
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)
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db.session.add(message_agent_loop)
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db.session.flush()
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self._pub_handler.pub_agent_thought(message_agent_loop)
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def on_dataset_query_end(self, dataset_query_obj: DatasetQueryObj):
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dataset_query = DatasetQuery(
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dataset_id=dataset_query_obj.dataset_id,
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content=dataset_query_obj.query,
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source='app',
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source_app_id=self.app.id,
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created_by_role=('account' if isinstance(self.user, Account) else 'end_user'),
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created_by=self.user.id
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)
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db.session.add(dataset_query)
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def calc_total_price(self, message_tokens, message_unit_price, answer_tokens, answer_unit_price):
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message_tokens_per_1k = (decimal.Decimal(message_tokens) / 1000).quantize(decimal.Decimal('0.001'),
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rounding=decimal.ROUND_HALF_UP)
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answer_tokens_per_1k = (decimal.Decimal(answer_tokens) / 1000).quantize(decimal.Decimal('0.001'),
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rounding=decimal.ROUND_HALF_UP)
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total_price = message_tokens_per_1k * message_unit_price + answer_tokens_per_1k * answer_unit_price
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return total_price.quantize(decimal.Decimal('0.0000001'), rounding=decimal.ROUND_HALF_UP)
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class PubHandler:
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def __init__(self, user: Union[Account | User], task_id: str,
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message: Message, conversation: Conversation,
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chain_pub: bool = False, agent_thought_pub: bool = False):
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self._channel = PubHandler.generate_channel_name(user, task_id)
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self._stopped_cache_key = PubHandler.generate_stopped_cache_key(user, task_id)
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self._task_id = task_id
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self._message = message
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self._conversation = conversation
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self._chain_pub = chain_pub
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self._agent_thought_pub = agent_thought_pub
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@classmethod
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def generate_channel_name(cls, user: Union[Account | User], task_id: str):
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user_str = 'account-' + user.id if isinstance(user, Account) else 'end-user-' + user.id
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return "generate_result:{}-{}".format(user_str, task_id)
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@classmethod
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def generate_stopped_cache_key(cls, user: Union[Account | User], task_id: str):
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user_str = 'account-' + user.id if isinstance(user, Account) else 'end-user-' + user.id
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return "generate_result_stopped:{}-{}".format(user_str, task_id)
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def pub_text(self, text: str):
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content = {
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'event': 'message',
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'data': {
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'task_id': self._task_id,
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'message_id': self._message.id,
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'text': text,
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'mode': self._conversation.mode,
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'conversation_id': self._conversation.id
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}
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}
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redis_client.publish(self._channel, json.dumps(content))
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if self._is_stopped():
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self.pub_end()
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raise ConversationTaskStoppedException()
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def pub_chain(self, message_chain: MessageChain):
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if self._chain_pub:
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content = {
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'event': 'chain',
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'data': {
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'task_id': self._task_id,
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'message_id': self._message.id,
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'chain_id': message_chain.id,
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'type': message_chain.type,
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'input': json.loads(message_chain.input),
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'output': json.loads(message_chain.output),
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'mode': self._conversation.mode,
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'conversation_id': self._conversation.id
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}
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}
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redis_client.publish(self._channel, json.dumps(content))
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if self._is_stopped():
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self.pub_end()
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raise ConversationTaskStoppedException()
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def pub_agent_thought(self, message_agent_thought: MessageAgentThought):
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if self._agent_thought_pub:
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content = {
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'event': 'agent_thought',
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'data': {
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'task_id': self._task_id,
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'message_id': self._message.id,
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'chain_id': message_agent_thought.message_chain_id,
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'agent_thought_id': message_agent_thought.id,
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'position': message_agent_thought.position,
|
||
|
|
'thought': message_agent_thought.thought,
|
||
|
|
'tool': message_agent_thought.tool,
|
||
|
|
'tool_input': message_agent_thought.tool_input,
|
||
|
|
'observation': message_agent_thought.observation,
|
||
|
|
'answer': message_agent_thought.answer,
|
||
|
|
'mode': self._conversation.mode,
|
||
|
|
'conversation_id': self._conversation.id
|
||
|
|
}
|
||
|
|
}
|
||
|
|
|
||
|
|
redis_client.publish(self._channel, json.dumps(content))
|
||
|
|
|
||
|
|
if self._is_stopped():
|
||
|
|
self.pub_end()
|
||
|
|
raise ConversationTaskStoppedException()
|
||
|
|
|
||
|
|
|
||
|
|
def pub_end(self):
|
||
|
|
content = {
|
||
|
|
'event': 'end',
|
||
|
|
}
|
||
|
|
|
||
|
|
redis_client.publish(self._channel, json.dumps(content))
|
||
|
|
|
||
|
|
@classmethod
|
||
|
|
def pub_error(cls, user: Union[Account | User], task_id: str, e):
|
||
|
|
content = {
|
||
|
|
'error': type(e).__name__,
|
||
|
|
'description': e.description if getattr(e, 'description', None) is not None else str(e)
|
||
|
|
}
|
||
|
|
|
||
|
|
channel = cls.generate_channel_name(user, task_id)
|
||
|
|
redis_client.publish(channel, json.dumps(content))
|
||
|
|
|
||
|
|
def _is_stopped(self):
|
||
|
|
return redis_client.get(self._stopped_cache_key) is not None
|
||
|
|
|
||
|
|
@classmethod
|
||
|
|
def stop(cls, user: Union[Account | User], task_id: str):
|
||
|
|
stopped_cache_key = cls.generate_stopped_cache_key(user, task_id)
|
||
|
|
redis_client.setex(stopped_cache_key, 600, 1)
|
||
|
|
|
||
|
|
|
||
|
|
class ConversationTaskStoppedException(Exception):
|
||
|
|
pass
|