Discover LlamaIndex: Joint Text to SQL a...

BBP

Hi guys, I'm following the Text to SQL video (https://www.youtube.com/watch?v=ZIvcVJGtCrY) and I think it may be out of date.

At this part of the code:

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# Insert documents into vector index
# Each document has metadata of the city attached
for city, wiki_doc in zip(cities, wiki_docs):
    nodes = node_parser.get_nodes_from_documents([wiki_doc])
    # add metadata to each node
    for node in nodes:
        node.extra_info = {"title": city}
    vector_index.insert_nodes(nodes)

I get this error:

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python3 main.py
dict_keys(['city_stats'])
[('Toronto', 2930000, 'Canada'), ('Tokyo', 13960000, 'Japan'), ('Berlin', 3645000, 'Germany')]
Traceback (most recent call last):
  File "/home/bi-ai/ai/txt-to-sql/main.py", line 107, in <module>
    node.extra_info = {"title": city}
  File "pydantic/main.py", line 357, in pydantic.main.BaseModel.__setattr__
ValueError: "TextNode" object has no field "extra_info"

I think extra_info has been deprecated because when I hover over it, VSCode says "TO DO: DEPRECATED"

but I'm having trouble finding what it was replaced with. What should I use instead?

Sorry for the dumb question, I'm really new to the whole python ecosystem.

Please halp. Many thanks.

26 comments

BBP

Full code in my main.py so far:

LLogan M

node.metadata is what you are looking for 👍

BBP

bruh your turn around time is absolutely ruthless

LLogan M

LOL

BBP

thank you much GRC!! (Giga RAG Chad)

BBP

Sorry to bug you again about this @Logan M but perhaps something broke in the newer releases?

I copied the code exactly as is from the video--check out master branch below:

https://github.com/biphan380/txt-to-sql/tree/master

But I run into this error:

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ython3 main.py 
dict_keys(['city_stats'])
[('Toronto', 2930000, 'Canada'), ('Tokyo', 13960000, 'Japan'), ('Berlin', 3645000, 'Germany')]
Upserted vectors: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████| 17/17 [00:04<00:00,  4.15it/s]
Upserted vectors: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████| 18/18 [00:02<00:00,  7.85it/s]
Upserted vectors: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████| 11/11 [00:02<00:00,  4.62it/s]
<class 'llama_index.indices.struct_store.sql_query.NLStructStoreQueryEngine'>
Traceback (most recent call last):
  File "/home/bi-ai/ai/txt-to-sql/main.py", line 157, in <module>
    query_engine = SQLAutoVectorQueryEngine(
  File "/home/bi-ai/.local/lib/python3.10/site-packages/llama_index/query_engine/sql_vector_query_engine.py", line 94, in __init__
    raise ValueError(
ValueError: sql_query_tool.query_engine must be an instance of BaseSQLTableQueryEngine or NLSQLTableQueryEngine

BBP

so I tried to use the BaseSQLTableQueryEngine -- check out the playground branch here:

https://github.com/biphan380/txt-to-sql/commit/5a82d4b57438fae0f84749273752f0f44836ffc6

but I run into this:

Plain Text

python3 main.py 
dict_keys(['city_stats'])
[('Toronto', 2930000, 'Canada'), ('Tokyo', 13960000, 'Japan'), ('Berlin', 3645000, 'Germany')]
Traceback (most recent call last):
  File "/home/bi-ai/ai/txt-to-sql/main.py", line 99, in <module>
    sql_query_engine = BaseSQLTableQueryEngine([], sql_database, table_name="city_stats")
TypeError: Can't instantiate abstract class BaseSQLTableQueryEngine with abstract method _get_table_context

BBP

I understand the OO concepts of abstract classes, but am new to Python so finding a work around is taking a hot minute 😂

BBP

Any help is blessed ❤️

LLogan M

Yea that class isn't meant to be used directly 😅

Use the class that implements the abstract methods
https://github.com/jerryjliu/llama_index/blob/518783f712e97a26837fd1d212ce67f0c30f6c09/llama_index/indices/struct_store/sql_query.py#L319

LLogan M

Should work for you

BBP

ahhh the second option the error gives haha

BBP

ok gimme a hot min

BBP

Ser I made a bunch of commits to the playground branch and finally got results!

As you can see I sometimes get really good results, but I sometimes get "none is not an allowed value"

Can you give me some guidance on my how I can begin to make sense of why it's behaving this way?

LLogan M

I've lost some context on this maybe -- why is vector store query spec being used? Is this a sql-join query engine?

BBP

I'll be honest, I was just doing copy pasta from the txt-to-sql tutorial video, and the copy pasta was not working lol

BBP

so I tried to change some things

BBP

but yes, I believe it's supposed to be a sql-join query engine?

BBP

this video: https://www.youtube.com/watch?v=ZIvcVJGtCrY

LLogan M

Maybe just follow the example notebook for this instead 🙂

Just ran it and it seems to work ~~fine~~ ok-ish, would probably use gpt-4 for this though, gpt-3.5 sucks at this it seems haha
https://gpt-index.readthedocs.io/en/stable/examples/query_engine/SQLJoinQueryEngine.html#define-sqljoinqueryengine

Just noticed the notebook sets up a gpt-4 service context and doesn't use it :PSadge:

LLogan M

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from llama_index import set_global_service_context
set_global_service_context(service_context)

LLogan M

ah yea, using gpt-4 is a million times better lol

BBP

oh RIP, the video didn't have a link to the code so I just manually copy pasta 😂

BBP

glad I did it though , learned a lot

BBP

I'll check out this guide also!

BBP

thank you for carrying this chubby panda ser ❤️

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