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https://github.com/Mintplex-Labs/langchain-python.git
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Jon Luo
8a35811556
The current prompt specifically instructs the LLM to use the `LIMIT` clause. This will cause issues with MS SQL Server, which uses `SELECT TOP` instead of `LIMIT`. The generated SQL will use `LIMIT`; the instruction to "always limit... using the LIMIT clause" seems to override the "create a syntactically correct mssql query to run" portion. Reported here: https://github.com/hwchase17/langchain/issues/1103#issuecomment-1441144224 I don't have access to a SQL Server instance to test, but removing that part of the prompt in OpenAI Playground results in the correct `SELECT TOP` syntax, whereas keeping it in results in the `LIMIT` clause, even when instructing it to generate syntactically correct mssql. It's also still correctly using `LIMIT` in my MariaDB database. I think in this case we can assume that the model will select the appropriate method based on the dialect specified. In general, it would be nice to be able to test a suite of SQL dialects for things like dialect-specific syntax and other issues we've run into in the past, but I'm not quite sure how to best approach that yet.
41 lines
1.6 KiB
Python
41 lines
1.6 KiB
Python
# flake8: noqa
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from langchain.prompts.base import CommaSeparatedListOutputParser
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from langchain.prompts.prompt import PromptTemplate
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_DEFAULT_TEMPLATE = """Given an input question, first create a syntactically correct {dialect} query to run, then look at the results of the query and return the answer. Unless the user specifies in his question a specific number of examples he wishes to obtain, always limit your query to at most {top_k} results. You can order the results by a relevant column to return the most interesting examples in the database.
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Never query for all the columns from a specific table, only ask for a the few relevant columns given the question.
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Pay attention to use only the column names that you can see in the schema description. Be careful to not query for columns that do not exist. Also, pay attention to which column is in which table.
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Use the following format:
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Question: "Question here"
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SQLQuery: "SQL Query to run"
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SQLResult: "Result of the SQLQuery"
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Answer: "Final answer here"
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Only use the tables listed below.
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{table_info}
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Question: {input}"""
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PROMPT = PromptTemplate(
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input_variables=["input", "table_info", "dialect", "top_k"],
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template=_DEFAULT_TEMPLATE,
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)
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_DECIDER_TEMPLATE = """Given the below input question and list of potential tables, output a comma separated list of the table names that may be necessary to answer this question.
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Question: {query}
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Table Names: {table_names}
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Relevant Table Names:"""
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DECIDER_PROMPT = PromptTemplate(
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input_variables=["query", "table_names"],
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template=_DECIDER_TEMPLATE,
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output_parser=CommaSeparatedListOutputParser(),
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)
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