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feat: upgrade langchain (#430)

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Co-authored-by: jyong <718720800@qq.com>
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John Wang 2023-06-25 16:49:14 +08:00 • committed by GitHub
commit 3241e4015b
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91 changed files with 2703 additions and 3153 deletions
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19
api/core/prompt/prompts.py
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@ -1,5 +1,3 @@
from llama_index import QueryKeywordExtractPrompt
CONVERSATION_TITLE_PROMPT = (
"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"
@ -45,23 +43,6 @@ SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT = (
"[\"question1\",\"question2\",\"question3\"]\n"
)
QUERY_KEYWORD_EXTRACT_TEMPLATE_TMPL = (
"A question is provided below. Given the question, extract up to {max_keywords} "
"keywords from the text. Focus on extracting the keywords that we can use "
"to best lookup answers to the question. Avoid stopwords."
"I am not sure which language the following question is in. "
"If the user asked the question in Chinese, please return the keywords in Chinese. "
"If the user asked the question in English, please return the keywords in English.\n"
"---------------------\n"
"{question}\n"
"---------------------\n"
"Provide keywords in the following comma-separated format: 'KEYWORDS: <keywords>'\n"
)
QUERY_KEYWORD_EXTRACT_TEMPLATE = QueryKeywordExtractPrompt(
QUERY_KEYWORD_EXTRACT_TEMPLATE_TMPL
)
RULE_CONFIG_GENERATE_TEMPLATE = """Given MY INTENDED AUDIENCES and HOPING TO SOLVE using a language model, please select \
the model prompt that best suits the input.
You will be provided with the prompt, variables, and an opening statement.