estel/dify
1
0
Fork 0
Code Issues Pull Requests Actions 1 Packages Projects Releases Wiki Activity

feat: advanced prompt backend (#1301)

Browse Source 
Co-authored-by: takatost <takatost@gmail.com>
This commit is contained in:
Garfield Dai
2023-10-12 23:13:10 +08:00
committed by GitHub
parent 2d1cb076c6
commit 42a5b3ec17
61 changed files with 767 additions and 581 deletions
Download Patch File Download Diff File Expand all files Collapse all files

22
api/core/conversation_message_task.py
View File

@@ -10,7 +10,7 @@ from core.model_providers.model_factory import ModelFactory
from core.model_providers.models.entity.message import to_prompt_messages, MessageType
from core.model_providers.models.llm.base import BaseLLM
from core.prompt.prompt_builder import PromptBuilder
from core.prompt.prompt_template import JinjaPromptTemplate
from core.prompt.prompt_template import PromptTemplateParser
from events.message_event import message_was_created
from extensions.ext_database import db
from extensions.ext_redis import redis_client
@@ -74,10 +74,10 @@ class ConversationMessageTask:
if self.mode == 'chat':
introduction = self.app_model_config.opening_statement
if introduction:
prompt_template = JinjaPromptTemplate.from_template(template=introduction)
prompt_inputs = {k: self.inputs[k] for k in prompt_template.input_variables if k in self.inputs}
prompt_template = PromptTemplateParser(template=introduction)
prompt_inputs = {k: self.inputs[k] for k in prompt_template.variable_keys if k in self.inputs}
try:
introduction = prompt_template.format(**prompt_inputs)
introduction = prompt_template.format(prompt_inputs)
except KeyError:
pass
@@ -150,12 +150,12 @@ class ConversationMessageTask:
message_tokens = llm_message.prompt_tokens
answer_tokens = llm_message.completion_tokens
message_unit_price = self.model_instance.get_tokens_unit_price(MessageType.HUMAN)
message_price_unit = self.model_instance.get_price_unit(MessageType.HUMAN)
message_unit_price = self.model_instance.get_tokens_unit_price(MessageType.USER)
message_price_unit = self.model_instance.get_price_unit(MessageType.USER)
answer_unit_price = self.model_instance.get_tokens_unit_price(MessageType.ASSISTANT)
answer_price_unit = self.model_instance.get_price_unit(MessageType.ASSISTANT)
message_total_price = self.model_instance.calc_tokens_price(message_tokens, MessageType.HUMAN)
message_total_price = self.model_instance.calc_tokens_price(message_tokens, MessageType.USER)
answer_total_price = self.model_instance.calc_tokens_price(answer_tokens, MessageType.ASSISTANT)
total_price = message_total_price + answer_total_price
@@ -163,7 +163,7 @@ class ConversationMessageTask:
self.message.message_tokens = message_tokens
self.message.message_unit_price = message_unit_price
self.message.message_price_unit = message_price_unit
self.message.answer = PromptBuilder.process_template(
self.message.answer = PromptTemplateParser.remove_template_variables(
llm_message.completion.strip()) if llm_message.completion else ''
self.message.answer_tokens = answer_tokens
self.message.answer_unit_price = answer_unit_price
@@ -226,15 +226,15 @@ class ConversationMessageTask:
def on_agent_end(self, message_agent_thought: MessageAgentThought, agent_model_instance: BaseLLM,
agent_loop: AgentLoop):
agent_message_unit_price = agent_model_instance.get_tokens_unit_price(MessageType.HUMAN)
agent_message_price_unit = agent_model_instance.get_price_unit(MessageType.HUMAN)
agent_message_unit_price = agent_model_instance.get_tokens_unit_price(MessageType.USER)
agent_message_price_unit = agent_model_instance.get_price_unit(MessageType.USER)
agent_answer_unit_price = agent_model_instance.get_tokens_unit_price(MessageType.ASSISTANT)
agent_answer_price_unit = agent_model_instance.get_price_unit(MessageType.ASSISTANT)
loop_message_tokens = agent_loop.prompt_tokens
loop_answer_tokens = agent_loop.completion_tokens
loop_message_total_price = agent_model_instance.calc_tokens_price(loop_message_tokens, MessageType.HUMAN)
loop_message_total_price = agent_model_instance.calc_tokens_price(loop_message_tokens, MessageType.USER)
loop_answer_total_price = agent_model_instance.calc_tokens_price(loop_answer_tokens, MessageType.ASSISTANT)
loop_total_price = loop_message_total_price + loop_answer_total_price