Closed vp999 closed 11 months ago
🤖
Hello,
The issue you're experiencing seems to be related to the conversion of natural language queries to SQL. In the LlamaIndex codebase, the NLStructStoreQueryEngine class is responsible for this conversion. It uses the llm_predictor
to convert the natural language query into SQL, and then attempts to run this SQL query. If the conversion from natural language to SQL is not accurate, it could result in invalid SQL being executed, leading to an OperationalError.
As for the warnings about not being able to load the OpenAI model, it's likely because the llm_predictor
object, which is used to convert natural language queries to SQL and to synthesize responses, is not able to load the required model. This could be due to a variety of reasons such as the model file not being found, insufficient resources to load the model, or the model being incompatible with the version of the library being used.
There are two similar issues that have been solved in the LlamaIndex repository:
Bug: text-to-SQL example fails with the new LlamaCPP fallback which was closed by a pull request: Improve SQL query parsing
Bug: sqlite3.Warning: You can only execute one statement at a time in NLSQLTableQueryEngine The suggested solution is to update to the latest version of llama-index. The issue has been addressed in the latest codebase. Relevant PR: https://github.com/jerryjliu/llama_index/pull/6782
As for the SQLStructStoreIndex.from_documents
method, I wasn't able to find specific documentation within the repository. However, based on the method name and typical usage in similar frameworks, it's likely that this method is used to create an instance of the SQLStructStoreIndex class from a list of documents, where each document is a structured data item that can be indexed and queried.
I hope this helps! If you have any other questions or need further clarification, feel free to ask.
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🤖
Hello,
The issue you're experiencing seems to be related to the conversion of natural language queries to SQL. In the LlamaIndex codebase, the NLStructStoreQueryEngine class is responsible for this conversion. It uses the
llm_predictor
to convert the natural language query into SQL, and then attempts to run this SQL query. If the conversion from natural language to SQL is not accurate, it could result in invalid SQL being executed, leading to an OperationalError.As for the warnings about not being able to load the OpenAI model, it's likely because the
llm_predictor
object, which is used to convert natural language queries to SQL and to synthesize responses, is not able to load the required model. This could be due to a variety of reasons such as the model file not being found, insufficient resources to load the model, or the model being incompatible with the version of the library being used.There are two similar issues that have been solved in the LlamaIndex repository:
- Bug: text-to-SQL example fails with the new LlamaCPP fallback which was closed by a pull request: Improve SQL query parsing
- Bug: sqlite3.Warning: You can only execute one statement at a time in NLSQLTableQueryEngine The suggested solution is to update to the latest version of llama-index. The issue has been addressed in the latest codebase. Relevant PR: Remove usage of stop token in Prompt, SQL gen #6782
As for the
SQLStructStoreIndex.from_documents
method, I wasn't able to find specific documentation within the repository. However, based on the method name and typical usage in similar frameworks, it's likely that this method is used to create an instance of the SQLStructStoreIndex class from a list of documents, where each document is a structured data item that can be indexed and queried.I hope this helps! If you have any other questions or need further clarification, feel free to ask.
Sources
- [Bug]: text-to-SQL example fails with the new LlamaCPP fallback
- [Bug]: sqlite3.Warning: You can only execute one statement at a time in NLSQLTableQueryEngine
- llama_index/indices/struct_store/sql_query.py
- benchmarks/struct_indices/spider/generate_sql.py
- docs/examples/index_structs/struct_indices/SQLIndexDemo.ipynb
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I tried synthesize_response=False as parameter to index.as_query_engine. got same results also tried with adding instruction_str as parameter to index.as_query_engine. got same results.
any other ideas??
🤖
Hello,
Based on the context provided, it seems like the issue you're encountering is due to the SQL execution code receiving natural language text in addition to SQL text. This is causing an OperationalError because the SQL execution code is designed to handle SQL queries, not natural language text.
To resolve this issue, you should ensure that only SQL queries are passed to the SQL execution code. This can be done by using the NLStructStoreQueryEngine class instead of the SQLStructStoreQueryEngine class. The NLStructStoreQueryEngine class is designed to handle natural language queries. It extracts the SQL from the natural language query and then runs the SQL over the SQLStructStoreIndex.
Here's how you can use the NLStructStoreQueryEngine class:
from llama_index.indices.struct_store.sql_query import NLStructStoreQueryEngine
# Initialize the NLStructStoreQueryEngine
engine = NLStructStoreQueryEngine(index)
# Use the engine to execute a natural language query
response = engine._query(query_bundle)
In this code, index
is an instance of SQLStructStoreIndex and query_bundle
is an instance of QueryBundle containing the natural language query. The _query
method of the NLStructStoreQueryEngine class will extract the SQL from the natural language query and execute it, returning the result.
Additionally, when initializing the SQLStructStoreIndex, you can specify the query mode to be either SQL or natural language (NL) using the as_query_engine
method. If you want to use natural language queries, you can set the query mode to NL as follows:
from llama_index.indices.struct_store.sql import SQLQueryMode, SQLStructStoreIndex
# Initialize the SQLStructStoreIndex
index = SQLStructStoreIndex(...)
# Set the query mode to NL
engine = index.as_query_engine(query_mode=SQLQueryMode.NL)
This will return an instance of NLStructStoreQueryEngine, which you can then use to execute natural language queries.
Regarding the SQLStructStoreIndex.from_documents()
method, I wasn't able to find specific information within the repository. However, typically, such a method would be used to create an instance of SQLStructStoreIndex from a list of documents.
I hope this helps! If you have any other questions, feel free to ask.
Best, Dosu
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Help me be more useful! Please leave a 👍 if this is helpful and 👎 if it is irrelevant.
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@vp999 Llama2 isn't great at text to SQL. You can try modifying the default text to SQL prompt to improve performance or use a better model (GPT-3.5 or GPT-4)
@vp999 Llama2 isn't great at text to SQL. You can try modifying the default text to SQL prompt to improve performance or use a better model (GPT-3.5 or GPT-4)
due to security restriction i cant call cloud apis..
i see few others faced similar issue , and it is getting fixed in https://github.com/jerryjliu/llama_index/pull/7283/commits/5f6f89ed0e89e15013173fe4840218a17ae2cb6c so closing this thread now
i see few others faced similar issue , and it is getting fixed in 5f6f89e so closing this thread now
It says This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
?
I'm using 0.10.24 and that fix is not there.
Bug Description
I was trying to use SQLStructStoreIndex as query engine to interact with sqllite database. The code is erroring out because the database sql execution code is recieving the natural langauge text in addition to sql text.
Version
0.8.5.post1
Steps to Reproduce
do not set open api token , this way it uses llama2 as local default
sql_database = SQLDatabase.from_uri("sqlite:///database/chinook.db")
index = SQLStructStoreIndex.from_documents( [], sql_database=sql_database,) query_engine = index.as_query_engine()
query_engine.query("who are the top selling artists?")
output error : OperationalError: (sqlite3.OperationalError) near "Question": syntax error [SQL: Question: Who are the top selling artists?
SQLQuery: SELECT ArtistId, Name, SUM(UnitPrice * Quantity) AS TotalSales FROM invoices JOIN invoice_items ON invoices.InvoiceId = invoice_items.InvoiceId JOIN tracks ON invoice_items.TrackId = tracks.TrackId JOIN artists ON tracks.ArtistId = artists.ArtistId GROUP BY ArtistId, Name ORDER BY TotalSales DESC;] (Background on this error at: https://sqlalche.me/e/20/e3q8)
Relevant Logs/Tracbacks