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fix: title, summary, suggested questions generate (#476)

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John Wang 2023-06-28 15:43:33 +08:00 committed by GitHub
parent 998f819b04
commit 408fbb0c70
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2 changed files with 15 additions and 12 deletions
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19
api/core/generator/llm_generator.py
View File

@ -2,7 +2,7 @@ import logging
from langchain import PromptTemplate
from langchain.chat_models.base import BaseChatModel
from langchain.schema import HumanMessage, OutputParserException
from langchain.schema import HumanMessage, OutputParserException, BaseMessage
from core.constant import llm_constant
from core.llm.llm_builder import LLMBuilder
@ -23,10 +23,10 @@ class LLMGenerator:
@classmethod
def generate_conversation_name(cls, tenant_id: str, query, answer):
prompt = CONVERSATION_TITLE_PROMPT
prompt = prompt.format(query=query, answer=answer)
prompt = prompt.format(query=query)
llm: StreamableOpenAI = LLMBuilder.to_llm(
tenant_id=tenant_id,
model_name=generate_base_model,
model_name='gpt-3.5-turbo',
max_tokens=50
)
@ -40,11 +40,12 @@ class LLMGenerator:
@classmethod
def generate_conversation_summary(cls, tenant_id: str, messages):
max_tokens = 200
model = 'gpt-3.5-turbo'
prompt = CONVERSATION_SUMMARY_PROMPT
prompt_with_empty_context = prompt.format(context='')
prompt_tokens = TokenCalculator.get_num_tokens(generate_base_model, prompt_with_empty_context)
rest_tokens = llm_constant.max_context_token_length[generate_base_model] - prompt_tokens - max_tokens
prompt_tokens = TokenCalculator.get_num_tokens(model, prompt_with_empty_context)
rest_tokens = llm_constant.max_context_token_length[model] - prompt_tokens - max_tokens
context = ''
for message in messages:
@ -52,14 +53,14 @@ class LLMGenerator:
continue
message_qa_text = "Human:" + message.query + "\nAI:" + message.answer + "\n"
if rest_tokens - TokenCalculator.get_num_tokens(generate_base_model, context + message_qa_text) > 0:
if rest_tokens - TokenCalculator.get_num_tokens(model, context + message_qa_text) > 0:
context += message_qa_text
prompt = prompt.format(context=context)
llm: StreamableOpenAI = LLMBuilder.to_llm(
tenant_id=tenant_id,
model_name=generate_base_model,
model_name=model,
max_tokens=max_tokens
)
@ -102,7 +103,7 @@ class LLMGenerator:
llm: StreamableOpenAI = LLMBuilder.to_llm(
tenant_id=tenant_id,
model_name=generate_base_model,
model_name='gpt-3.5-turbo',
temperature=0,
max_tokens=256
)
@ -114,6 +115,8 @@ class LLMGenerator:
try:
output = llm(query)
if isinstance(output, BaseMessage):
output = output.content
questions = output_parser.parse(output)
except Exception:
logging.exception("Error generating suggested questions after answer")

8
api/core/prompt/prompts.py
View File

@ -1,5 +1,5 @@
CONVERSATION_TITLE_PROMPT = (
"Human:{{query}}\n-----\n"
"Human:{query}\n-----\n"
"Help me summarize the intent of what the human said and provide a title, the title should not exceed 20 words.\n"
"If the human said is conducted in Chinese, you should return a Chinese title.\n"
"If the human said is conducted in English, you should return an English title.\n"
@ -19,7 +19,7 @@ CONVERSATION_SUMMARY_PROMPT = (
INTRODUCTION_GENERATE_PROMPT = (
"I am designing a product for users to interact with an AI through dialogue. "
"The Prompt given to the AI before the conversation is:\n\n"
"```\n{{prompt}}\n```\n\n"
"```\n{prompt}\n```\n\n"
"Please generate a brief introduction of no more than 50 words that greets the user, based on this Prompt. "
"Do not reveal the developer's motivation or deep logic behind the Prompt, "
"but focus on building a relationship with the user:\n"
@ -27,13 +27,13 @@ INTRODUCTION_GENERATE_PROMPT = (
MORE_LIKE_THIS_GENERATE_PROMPT = (
"-----\n"
"{{original_completion}}\n"
"{original_completion}\n"
"-----\n\n"
"Please use the above content as a sample for generating the result, "
"and include key information points related to the original sample in the result. "
"Try to rephrase this information in different ways and predict according to the rules below.\n\n"
"-----\n"
"{{prompt}}\n"
"{prompt}\n"
)
SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT = (