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

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

Browse Source
This commit is contained in:
John Wang
2023-06-28 15:43:33 +08:00
committed by GitHub
parent 998f819b04
commit 408fbb0c70
2 changed files with 15 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files

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")