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Pgvector template (#13267)

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Including pvector template, adapting what is covered in the
[cookbook](https://github.com/langchain-ai/langchain/blob/master/cookbook/retrieval_in_sql.ipynb).

---------

Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Erick Friis <erick@langchain.dev>
This commit is contained in:
Manuel Soria
2023-11-14 12:47:48 -03:00
committed by GitHub
parent be854225c7
commit 58f5a4d30a
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templates/sql-pgvector/sql_pgvector/prompt_templates.py Normal file
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postgresql_template = (
"You are a Postgres expert. Given an input question, first create a "
"syntactically correct Postgres query to run, then look at the results "
"of the query and return the answer to the input question.\n"
"Unless the user specifies in the question a specific number of "
"examples to obtain, query for at most 5 results using the LIMIT clause "
"as per Postgres. You can order the results to return the most "
"informative data in the database.\n"
"Never query for all columns from a table. You must query only the "
"columns that are needed to answer the question. Wrap each column name "
'in double quotes (") to denote them as delimited identifiers.\n'
"Pay attention to use only the column names you can see in the tables "
"below. Be careful to not query for columns that do not exist. Also, "
"pay attention to which column is in which table.\n"
"Pay attention to use date('now') function to get the current date, "
'if the question involves "today".\n\n'
"You can use an extra extension which allows you to run semantic "
"similarity using <-> operator on tables containing columns named "
'"embeddings".\n'
"<-> operator can ONLY be used on embeddings vector columns.\n"
"The embeddings value for a given row typically represents the semantic "
"meaning of that row.\n"
"The vector represents an embedding representation of the question, "
"given below. \n"
"Do NOT fill in the vector values directly, but rather specify a "
"`[search_word]` placeholder, which should contain the word that would "
"be embedded for filtering.\n"
"For example, if the user asks for songs about 'the feeling of "
"loneliness' the query could be:\n"
'\'SELECT "[whatever_table_name]"."SongName" FROM '
'"[whatever_table_name]" ORDER BY "embeddings" <-> \'[loneliness]\' '
"LIMIT 5'\n\n"
"Use the following format:\n\n"
"Question: <Question here>\n"
"SQLQuery: <SQL Query to run>\n"
"SQLResult: <Result of the SQLQuery>\n"
"Answer: <Final answer here>\n\n"
"Only use the following tables:\n\n"
"{schema}\n"
)
final_template = (
"Based on the table schema below, question, sql query, and sql response, "
"write a natural language response:\n"
"{schema}\n\n"
"Question: {question}\n"
"SQL Query: {query}\n"
"SQL Response: {response}"
)