SQLDatabaseChain - Utilizing Prompt Templates

[BrettlyCD]

I'm currently using a SQLDatabaseChain with the standard template from the documentation:

sql_agent_prompt_template = 
"""You are an expert data analyst. Given an input question, first create a syntactically correct {dialect} query to run, then look at the results of the query and describe the answer.
Use the following format:

Question: Question here
SQLQuery: SQL Query to run
SQLResult: Result of the SQLQuery
Answer: Final answer here

Only use the following tables:
{table_info}

Question: {input}"""

In the docs and other threads I've seen online, it doesn't look like running the chain requires you to specify the input variables when running, but I have been running it in this way:

sql_prompt = PromptTemplate(input_variables=["input", "table_info", "dialect"], template=sql_agent_prompt_template)

db_chain = SQLDatabaseChain.from_llm(llm, db, prompt=sql_prompt, verbose=True)

db_chain.run(sql_prompt.format(input="<question>", table_info="<table>", dialect="sqlite"))

This works, but is harder to scale. Is it not necessary to include the sql_prompt.format() in the run command?

And if not, how is it forming an accurate prompt? I notice when I change the structure of the prompt, the chain errors - is this because this specific template is structured to succeed on the chain?

Thank you for helping me understand better!

[dosubot[bot]]

Answer generated by a 🤖

Answer

I understand that you're using the SQLDatabaseChain with a standard template and you're manually formatting the prompt before running the chain. You're wondering if this step is necessary and how the prompt is formed if you don't manually format it. You've also noticed that changing the structure of the prompt causes errors and you're curious about why this happens.

Let me clarify this for you. When you're using the run method of the SQLDatabaseChain, it's not necessary to manually format the prompt. The PromptTemplate object you've created and passed to the SQLDatabaseChain constructor takes care of this for you. It uses the input_variables you've specified to map the variables in the template to the corresponding values in the context when the chain is run.

The errors you're seeing when you change the structure of the prompt are likely because both the SQLDatabaseChain and the language model it uses are expecting a specific format. The prompt structure you're using is designed to work well with the language model and the SQLDatabaseChain. If you alter the structure of the prompt, the language model might struggle to generate the correct output, and the SQLDatabaseChain might have difficulty parsing the output.

Here's how you can run the chain without manually formatting the prompt:

sql_prompt = PromptTemplate(input_variables=["input", "table_info", "dialect"], template=sql_agent_prompt_template)

db_chain = SQLDatabaseChain.from_llm(llm, db, prompt=sql_prompt, verbose=True)

db_chain.run(input="<question>", table_info="<table>", dialect="sqlite")

In this example, the run method is called with the input variables as keyword arguments. The PromptTemplate object uses these arguments to format the prompt.

This is one potential solution based on my understanding of your issue. If you find this answer helpful and believe it's not covered by the existing documentation, I encourage you to make a pull request to update the documentation. This could be beneficial for other users who might encounter the same issue.

Sources

• langchain/chains/sql_database/prompt.py

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