Commit Graph

16 Commits (e6f0cee896592b25523f00a726f731538f704802)

Author SHA1 Message Date
Abdul 82102c99b3
langchain[patch]: Running SQLDatabaseChain adds prefix "SQLQuery:\n" (#14058)
- **Issue:** https://github.com/langchain-ai/langchain/issues/12077

---------

Co-authored-by: Abdul Kader Maliyakkal <maliyakk@amazon.com>
10 months ago
Qihui Xie 57ade13b2b
fix llm_inputs duplication problem in intermediate_steps in SQLDatabaseChain (#10279)
Use `.copy()` to fix the bug that the first `llm_inputs` element is
overwritten by the second `llm_inputs` element in `intermediate_steps`.

***Problem description:***
In [line 127](

c732d8fffd/libs/experimental/langchain_experimental/sql/base.py (L127C17-L127C17)),
the `llm_inputs` of the sql generation step is appended as the first
element of `intermediate_steps`:
```
            intermediate_steps.append(llm_inputs)  # input: sql generation
```

However, `llm_inputs` is a mutable dict, it is updated in [line
179](https://github.com/langchain-ai/langchain/blob/master/libs/experimental/langchain_experimental/sql/base.py#L179)
for the final answer step:
```
                llm_inputs["input"] = input_text
```
Then, the updated `llm_inputs` is appended as another element of
`intermediate_steps` in [line
180](c732d8fffd/libs/experimental/langchain_experimental/sql/base.py (L180)):
```
                intermediate_steps.append(llm_inputs)  # input: final answer
```

As a result, the final `intermediate_steps` returned in [line
189](c732d8fffd/libs/experimental/langchain_experimental/sql/base.py (L189C43-L189C43))
actually contains two same `llm_inputs` elements, i.e., the `llm_inputs`
for the sql generation step overwritten by the one for final answer step
by mistake. Users are not able to get the actual `llm_inputs` for the
sql generation step from `intermediate_steps`

Simply calling `.copy()` when appending `llm_inputs` to
`intermediate_steps` can solve this problem.
12 months ago
Predrag Gruevski c9986bc3a9
Tweak type hints to match dependency's behavior. (#11355)
Needs #11353 to merge first, and a new `langchain` to be published with
those changes.
12 months ago
Mohammad Mohtashim 3bddd708f7
Add memory to sql chain (#8597)
continuation of PR #8550

@hwchase17 please see and merge. And also close the PR #8550.

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
12 months ago
Nuno Campos 7b13292e35
Remove python eval from vector sql db chain (#10937)
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1 year ago
Aashish Saini 1b050b98f5
Corrected some spelling mistakes and grammatical errors (#10791)
Corrected some spelling mistakes and grammatical errors
CC: @baskaryan, @eyurtsev, @hwchase17.

---------

Co-authored-by: Ishita Chauhan <136303787+IshitaChauhanShortHillsAI@users.noreply.github.com>
Co-authored-by: Aashish Saini <141953346+AashishSainiShorthillsAI@users.noreply.github.com>
Co-authored-by: ManpreetShorthillsAI <142380984+ManpreetShorthillsAI@users.noreply.github.com>
Co-authored-by: AryamanJaiswalShorthillsAI <142397527+AryamanJaiswalShorthillsAI@users.noreply.github.com>
Co-authored-by: Adarsh Shrivastav <142413097+AdarshKumarShorthillsAI@users.noreply.github.com>
Co-authored-by: Vishal <141389263+VishalYadavShorthillsAI@users.noreply.github.com>
Co-authored-by: ChetnaGuptaShorthillsAI <142381084+ChetnaGuptaShorthillsAI@users.noreply.github.com>
Co-authored-by: PankajKumarShorthillsAI <142473460+PankajKumarShorthillsAI@users.noreply.github.com>
Co-authored-by: AbhishekYadavShorthillsAI <142393903+AbhishekYadavShorthillsAI@users.noreply.github.com>
Co-authored-by: AmitSinghShorthillsAI <142410046+AmitSinghShorthillsAI@users.noreply.github.com>
Co-authored-by: Md Nazish Arman <142379599+MdNazishArmanShorthillsAI@users.noreply.github.com>
Co-authored-by: KamalSharmaShorthillsAI <142474019+KamalSharmaShorthillsAI@users.noreply.github.com>
Co-authored-by: Lakshya <lakshyagupta87@yahoo.com>
Co-authored-by: Aayush <142384656+AayushShorthillsAI@users.noreply.github.com>
Co-authored-by: AnujMauryaShorthillsAI <142393269+AnujMauryaShorthillsAI@users.noreply.github.com>
Co-authored-by: ishita <chauhanishita5356@gmail.com>
1 year ago
Harrison Chase 12ff780089
move embeddings to schema (#10696) 1 year ago
Harrison Chase 5442d2b1fa
Harrison/stop importing from init (#10690) 1 year ago
Hedeer El Showk 9749f8ebae
database -> db in from_llm (#10667)
**Description:** Renamed argument `database` in
`SQLDatabaseSequentialChain.from_llm()` to `db`,

I realize it's tiny and a bit of a nitpick but for consistency with
SQLDatabaseChain (and all the others actually) I thought it should be
renamed. Also got me while working and using it today.

✔️ Please make sure your PR is passing linting and
testing before submitting. Run `make format`, `make lint` and `make
test` to check this locally.
1 year ago
刘 方瑞 890ed775a3
Resolve: VectorSearch enabled SQLChain? (#10177)
Squashed from #7454 with updated features

We have separated the `SQLDatabseChain` from `VectorSQLDatabseChain` and
put everything into `experimental/`.

Below is the original PR message from #7454.

-------

We have been working on features to fill up the gap among SQL, vector
search and LLM applications. Some inspiring works like self-query
retrievers for VectorStores (for example
[Weaviate](https://python.langchain.com/en/latest/modules/indexes/retrievers/examples/weaviate_self_query.html)
and
[others](https://python.langchain.com/en/latest/modules/indexes/retrievers/examples/self_query.html))
really turn those vector search databases into a powerful knowledge
base! 🚀🚀

We are thinking if we can merge all in one, like SQL and vector search
and LLMChains, making this SQL vector database memory as the only source
of your data. Here are some benefits we can think of for now, maybe you
have more 👀:

With ALL data you have: since you store all your pasta in the database,
you don't need to worry about the foreign keys or links between names
from other data source.
Flexible data structure: Even if you have changed your schema, for
example added a table, the LLM will know how to JOIN those tables and
use those as filters.
SQL compatibility: We found that vector databases that supports SQL in
the marketplace have similar interfaces, which means you can change your
backend with no pain, just change the name of the distance function in
your DB solution and you are ready to go!

### Issue resolved:
- [Feature Proposal: VectorSearch enabled
SQLChain?](https://github.com/hwchase17/langchain/issues/5122)

### Change made in this PR:
- An improved schema handling that ignore `types.NullType` columns 
- A SQL output Parser interface in `SQLDatabaseChain` to enable Vector
SQL capability and further more
- A Retriever based on `SQLDatabaseChain` to retrieve data from the
database for RetrievalQAChains and many others
- Allow `SQLDatabaseChain` to retrieve data in python native format
- Includes PR #6737 
- Vector SQL Output Parser for `SQLDatabaseChain` and
`SQLDatabaseChainRetriever`
- Prompts that can implement text to VectorSQL
- Corresponding unit-tests and notebook

### Twitter handle: 
- @MyScaleDB

### Tag Maintainer:
Prompts / General: @hwchase17, @baskaryan
DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev

### Dependencies:
No dependency added
1 year ago
Programmers Emperor 872d829201
Update __init__.py (#9955)
Add SQLDatabaseSequentialChain Class to __init__.py so it can be
accessed and used

<!-- Thank you for contributing to LangChain!

Replace this entire comment with:
- Description: SQLDatabaseSequentialChain is not found when importing
Langchain_experimental package, when I open __init__.py
Langchain_expermental.sql, I found that SQLDatabaseSequentialChain is
imported and add to __all__ list
- Issue: SQLDatabaseSequentialChain is not found in
Langchain_experimental package
  - Dependencies: None,
  - Tag maintainer: None,
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Please make sure your PR is passing linting and testing before
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If you're adding a new integration, please include:
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1 year ago
Predrag Gruevski eb3d1fa93c
Add security warning to experimental `SQLDatabaseChain` class. (#9867)
The most reliable way to not have a chain run an undesirable SQL command
is to not give it database permissions to run that command. That way the
database itself performs the rule enforcement, so it's much easier to
configure and use properly than anything we could add in ourselves.
1 year ago
Nuno Campos c0d67420e5
Use a submodule for pydantic v1 compat (#9371)
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1 year ago
Eugene Yurtsev 2673b3a314
Create pydantic v1 namespace in langchain (#9254)
Create pydantic v1 namespace in langchain experimental
1 year ago
Harrison Chase 1b0bfa54cf cr 1 year ago
Harrison Chase aa0e69bc98
Harrison/official pre release (#8106) 1 year ago