Commit Graph

151 Commits (0b33abc8b1fdd0eb269b776f6390d6f59d1f1432)

Author SHA1 Message Date
Nejc Habjan b4fa847a90
community[minor]: add exclude parameter to DirectoryLoader (#17316)
- **Description:** adds an `exclude` parameter to the DirectoryLoader
class, based on similar behavior in GenericLoader
- **Issue:** discussed in
https://github.com/langchain-ai/langchain/discussions/9059 and I think
in some other issues that I cannot find at the moment 🙇
  - **Dependencies:** None
  - **Twitter handle:** don't have one sorry! Just https://github/nejch

---------

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
7 months ago
Bagatur 8f14234afb
infra: ignore flakey lua test (#17618) 7 months ago
morgana 9d7ca7df6e
community[patch]: update copy of metadata in rockset vectorstore integration (#17612)
- **Description:** This fixes an issue with working with RecordManager.
RecordManager was generating new hashes on documents because `add_texts`
was modifying the metadata directly. Additionally moved some tests to
unit tests since that was a more appropriate home.
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** `@_morgan_adams_`
7 months ago
Moshe Berchansky 20a56fe0a2
community[minor]: Add QuantizedEmbedders (#17391)
**Description:** 
* adding Quantized embedders using optimum-intel and
intel-extension-for-pytorch.
* added mdx documentation and example notebooks 
* added embedding import testing.

**Dependencies:** 
optimum = {extras = ["neural-compressor"], version = "^1.14.0", optional
= true}
intel_extension_for_pytorch = {version = "^2.2.0", optional = true}

Dependencies have been added to pyproject.toml for the community lib.  

**Twitter handle:** @peter_izsak

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Amir Karbasi bccc9241ea
community[patch]: Resolve KuzuQAChain API Changes (#16885)
- **Description:** Updates to the Kuzu API had broken this
functionality. These updates resolve those issues and add a new test to
demonstrate the updates.
- **Issue:** #11874
- **Dependencies:** No new dependencies
- **Twitter handle:** @amirk08


Test results:
```
tests/integration_tests/graphs/test_kuzu.py::TestKuzu::test_query_no_params PASSED                                   [ 33%]
tests/integration_tests/graphs/test_kuzu.py::TestKuzu::test_query_params PASSED                                      [ 66%]
tests/integration_tests/graphs/test_kuzu.py::TestKuzu::test_refresh_schema PASSED                                    [100%]

=================================================== slowest 5 durations =================================================== 
0.53s call     tests/integration_tests/graphs/test_kuzu.py::TestKuzu::test_refresh_schema
0.34s call     tests/integration_tests/graphs/test_kuzu.py::TestKuzu::test_query_no_params
0.28s call     tests/integration_tests/graphs/test_kuzu.py::TestKuzu::test_query_params
0.03s teardown tests/integration_tests/graphs/test_kuzu.py::TestKuzu::test_refresh_schema
0.02s teardown tests/integration_tests/graphs/test_kuzu.py::TestKuzu::test_query_params
==================================================== 3 passed in 1.27s ==================================================== 
```
7 months ago
Christophe Bornet 789cd5198d
community[patch]: Use astrapy built-in pagination prefetch in AstraDBLoader (#17569) 7 months ago
Christophe Bornet ff1f985a2a
community: Fix some mypy types in cassandra doc loader (#17570)
Thank you!
7 months ago
nvpranak 91bcc9c5c9
community[minor]: Nemo embeddings(#16206)
This PR is adding support for NVIDIA NeMo embeddings issue #16095.

---------

Co-authored-by: Praveen Nakshatrala <pnakshatrala@gmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
wulixuan c776cfc599
community[minor]: integrate with model Yuan2.0 (#15411)
1. integrate with
[`Yuan2.0`](https://github.com/IEIT-Yuan/Yuan-2.0/blob/main/README-EN.md)
2. update `langchain.llms`
3. add a new doc for [Yuan2.0
integration](docs/docs/integrations/llms/yuan2.ipynb)

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
volodymyr-memsql e36bc379f2
community[patch]: Add vector index support to SingleStoreDB VectorStore (#17308)
This pull request introduces support for various Approximate Nearest
Neighbor (ANN) vector index algorithms in the VectorStore class,
starting from version 8.5 of SingleStore DB. Leveraging this enhancement
enables users to harness the power of vector indexing, significantly
boosting search speed, particularly when handling large sets of vectors.

---------

Co-authored-by: Volodymyr Tkachuk <vtkachuk-ua@singlestore.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Kate Silverstein 0bc4a9b3fc
community[minor]: Adds Llamafile as an LLM (#17431)
* **Description:** Adds a simple LLM implementation for interacting with
[llamafile](https://github.com/Mozilla-Ocho/llamafile)-based models.
* **Dependencies:** N/A
* **Issue:** N/A

**Detail**
[llamafile](https://github.com/Mozilla-Ocho/llamafile) lets you run LLMs
locally from a single file on most computers without installing any
dependencies.

To use the llamafile LLM implementation, the user needs to:

1. Download a llamafile e.g.
https://huggingface.co/jartine/TinyLlama-1.1B-Chat-v1.0-GGUF/resolve/main/TinyLlama-1.1B-Chat-v1.0.Q5_K_M.llamafile?download=true
2. Make the file executable.
3. Run the llamafile in 'server mode'. (All llamafiles come packaged
with a lightweight server; by default, the server listens at
`http://localhost:8080`.)


```bash
wget https://url/of/model.llamafile
chmod +x model.llamafile
./model.llamafile --server --nobrowser
```

Now, the user can invoke the LLM via the LangChain client:

```python
from langchain_community.llms.llamafile import Llamafile

llm = Llamafile()

llm.invoke("Tell me a joke.")
```
7 months ago
Qihui Xie 5738143d4b
add mongodb_store (#13801)
# Add MongoDB storage
  - **Description:** 
  Add MongoDB Storage as an option for large doc store. 

Example usage: 
```Python
# Instantiate the MongodbStore with a MongoDB connection
from langchain.storage import MongodbStore

mongo_conn_str = "mongodb://localhost:27017/"
mongodb_store = MongodbStore(mongo_conn_str, db_name="test-db",
                                collection_name="test-collection")

# Set values for keys
doc1 = Document(page_content='test1')
doc2 = Document(page_content='test2')
mongodb_store.mset([("key1", doc1), ("key2", doc2)])

# Get values for keys
values = mongodb_store.mget(["key1", "key2"])
# [doc1, doc2]

# Iterate over keys
for key in mongodb_store.yield_keys():
    print(key)

# Delete keys
mongodb_store.mdelete(["key1", "key2"])
 ```

  - **Dependencies:**
  Use `mongomock` for integration test.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
7 months ago
wulixuan 5d06797905
community[minor]: integrate chat models with Yuan2.0 (#16575)
1. integrate chat models with
[`Yuan2.0`](https://github.com/IEIT-Yuan/Yuan-2.0/blob/main/README-EN.md)
2. add a new doc for [Yuan2.0
integration](docs/docs/integrations/llms/yuan2.ipynb)
 
Yuan2.0 is a new generation Fundamental Large Language Model developed
by IEIT System. We have published all three models, Yuan 2.0-102B, Yuan
2.0-51B, and Yuan 2.0-2B.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Ian Gregory e5472b5eb8
Framework for supporting more languages in LanguageParser (#13318)
## Description

I am submitting this for a school project as part of a team of 5. Other
team members are @LeilaChr, @maazh10, @Megabear137, @jelalalamy. This PR
also has contributions from community members @Harrolee and @Mario928.

Initial context is in the issue we opened (#11229).

This pull request adds:

- Generic framework for expanding the languages that `LanguageParser`
can handle, using the
[tree-sitter](https://github.com/tree-sitter/py-tree-sitter#py-tree-sitter)
parsing library and existing language-specific parsers written for it
- Support for the following additional languages in `LanguageParser`:
  - C
  - C++
  - C#
  - Go
- Java (contributed by @Mario928
https://github.com/ThatsJustCheesy/langchain/pull/2)
  - Kotlin
  - Lua
  - Perl
  - Ruby
  - Rust
  - Scala
- TypeScript (contributed by @Harrolee
https://github.com/ThatsJustCheesy/langchain/pull/1)

Here is the [design
document](https://docs.google.com/document/d/17dB14cKCWAaiTeSeBtxHpoVPGKrsPye8W0o_WClz2kk)
if curious, but no need to read it.

## Issues

- Closes #11229
- Closes #10996
- Closes #8405

## Dependencies

`tree_sitter` and `tree_sitter_languages` on PyPI. We have tried to add
these as optional dependencies.

## Documentation

We have updated the list of supported languages, and also added a
section to `source_code.ipynb` detailing how to add support for
additional languages using our framework.

## Maintainer

- @hwchase17 (previously reviewed
https://github.com/langchain-ai/langchain/pull/6486)

Thanks!!

## Git commits

We will gladly squash any/all of our commits (esp merge commits) if
necessary. Let us know if this is desirable, or if you will be
squash-merging anyway.

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Replace this entire comment with:
  - **Description:** a description of the change, 
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---------

Co-authored-by: Maaz Hashmi <mhashmi373@gmail.com>
Co-authored-by: LeilaChr <87657694+LeilaChr@users.noreply.github.com>
Co-authored-by: Jeremy La <jeremylai511@gmail.com>
Co-authored-by: Megabear137 <zubair.alnoor27@gmail.com>
Co-authored-by: Lee Harrold <lhharrold@sep.com>
Co-authored-by: Mario928 <88029051+Mario928@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
7 months ago
Sridhar Ramaswamy 9f1cbbc6ed
community[minor]: Add pebblo safe document loader (#16862)
- **Description:** Pebblo opensource project enables developers to
safely load data to their Gen AI apps. It identifies semantic topics and
entities found in the loaded data and summarizes them in a
developer-friendly report.
  - **Dependencies:** none
  - **Twitter handle:** srics

@hwchase17
7 months ago
mhavey 1bbb64d956
community[minor], langchian[minor]: Add Neptune Rdf graph and chain (#16650)
**Description**: This PR adds a chain for Amazon Neptune graph database
RDF format. It complements the existing Neptune Cypher chain. The PR
also includes a Neptune RDF graph class to connect to, introspect, and
query a Neptune RDF graph database from the chain. A sample notebook is
provided under docs that demonstrates the overall effect: invoking the
chain to make natural language queries against Neptune using an LLM.

**Issue**: This is a new feature
 
**Dependencies**: The RDF graph class depends on the AWS boto3 library
if using IAM authentication to connect to the Neptune database.

---------

Co-authored-by: Piyush Jain <piyushjain@duck.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Andreas Motl 1fdd9bd980
community/SQLDatabase: Generalize and trim software tests (#16659)
- **Description:** Improve test cases for `SQLDatabase` adapter
component, see
[suggestion](https://github.com/langchain-ai/langchain/pull/16655#pullrequestreview-1846749474).
  - **Depends on:** GH-16655
  - **Addressed to:** @baskaryan, @cbornet, @eyurtsev

_Remark: This PR is stacked upon GH-16655, so that one will need to go
in first._

Edit: Thank you for bringing in GH-17191, @eyurtsev. This is a little
aftermath, improving/streamlining the corresponding test cases.
7 months ago
Chris f9f5626ca4
community[patch]: Fix github search issues and PRs PaginatedList has no len() error (#16806)
**Description:** 
Bugfix: Langchain_community's GitHub Api wrapper throws a TypeError when
searching for issues and/or PRs (the `search_issues_and_prs` method).
This is because PyGithub's PageinatedList type does not support the
len() method. See https://github.com/PyGithub/PyGithub/issues/1476

![image](https://github.com/langchain-ai/langchain/assets/8849021/57390b11-ed41-4f48-ba50-f3028610789c)
  **Dependencies:** None 
  **Twitter handle**: @ChrisKeoghNZ
  
I haven't registered an issue as it would take me longer to fill the
template out than to make the fix, but I'm happy to if that's deemed
essential.

I've added a simple integration test to cover this as there were no
existing unit tests and it was going to be tricky to set them up.

Co-authored-by: Chris Keogh <chris.keogh@xero.com>
7 months ago
morgana 722aae4fd1
community: add delete method to rocksetdb vectorstore to support recordmanager (#17030)
- **Description:** This adds a delete method so that rocksetdb can be
used with `RecordManager`.
  - **Issue:** N/A
  - **Dependencies:** N/A
  - **Twitter handle:** `@_morgan_adams_`

---------

Co-authored-by: Rockset API Bot <admin@rockset.io>
7 months ago
yin1991 37ef6ac113
community[patch]: Add Pagination to GitHubIssuesLoader for Efficient GitHub Issues Retrieval (#16934)
- **Description:** Add Pagination to GitHubIssuesLoader for Efficient
GitHub Issues Retrieval
- **Issue:** [the issue # it fixes if
applicable,](https://github.com/langchain-ai/langchain/issues/16864)

---------

Co-authored-by: root <root@ip-172-31-46-160.ap-southeast-1.compute.internal>
Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Spencer Kelly 54fa78c887
community[patch]: fixed vector similarity filtering (#16967)
**Description:** changed filtering so that failed filter doesn't add
document to results. Currently filtering is entirely broken and all
documents are returned whether or not they pass the filter.

fixes issue introduced in
https://github.com/langchain-ai/langchain/pull/16190
7 months ago
Abhijeeth Padarthi 584b647b96
community[minor]: AWS Athena Document Loader (#15625)
- **Description:** Adds the document loader for [AWS
Athena](https://aws.amazon.com/athena/), a serverless and interactive
analytics service.
  - **Dependencies:** Added boto3 as a dependency
7 months ago
david-tempelmann 93da18b667
community[minor]: Add mmr and similarity_score_threshold retrieval to DatabricksVectorSearch (#16829)
- **Description:** This PR adds support for `search_types="mmr"` and
`search_type="similarity_score_threshold"` to retrievers using
`DatabricksVectorSearch`,
  - **Issue:** 
  - **Dependencies:**
  - **Twitter handle:**

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
7 months ago
Erick Friis 3a2eb6e12b
infra: add print rule to ruff (#16221)
Added noqa for existing prints. Can slowly remove / will prevent more
being intro'd
8 months ago
Quang Hoa 54c1fb3f25
community[patch]: Make some functions work with Milvus (#10695)
**Description**
Make some functions work with Milvus:
1. get_ids: Get primary keys by field in the metadata
2. delete: Delete one or more entities by ids
3. upsert: Update/Insert one or more entities

**Issue**
None
**Dependencies**
None
**Tag maintainer:**
@hwchase17 
**Twitter handle:**
None

---------

Co-authored-by: HoaNQ9 <hoanq.1811@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
8 months ago
kYLe c9999557bf
community[patch]: Modify LLMs/Anyscale work with OpenAI API v1 (#14206)
<!-- Thank you for contributing to LangChain!

Replace this entire comment with:
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- **Description:** 
1. Modify LLMs/Anyscale to work with OAI v1
2. Get rid of openai_ prefixed variables in Chat_model/ChatAnyscale
3. Modify `anyscale_api_base` to `anyscale_base_url` to follow OAI name
convention (reverted)

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
8 months ago
Bagatur 65e97c9b53
infra: mv SQLDatabase tests to community (#17276) 8 months ago
Armin Stepanyan 641efcf41c
community: add runtime kwargs to HuggingFacePipeline (#17005)
This PR enables changing the behaviour of huggingface pipeline between
different calls. For example, before this PR there's no way of changing
maximum generation length between different invocations of the chain.
This is desirable in cases, such as when we want to scale the maximum
output size depending on a dynamic prompt size.

Usage example:

```python
from langchain_community.llms.huggingface_pipeline import HuggingFacePipeline
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline

model_id = "gpt2"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
hf = HuggingFacePipeline(pipeline=pipe)

hf("Say foo:", pipeline_kwargs={"max_new_tokens": 42})
```

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
8 months ago
Scott Nath a32798abd7
community: Add you.com utility, update you retriever integration docs (#17014)
<!-- Thank you for contributing to LangChain!

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whichever of langchain, community, core, experimental, etc. is being
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- **Description: changes to you.com files** 
    - general cleanup
- adds community/utilities/you.py, moving bulk of code from retriever ->
utility
    - removes `snippet` as endpoint
    - adds `news` as endpoint
    - adds more tests

<s>**Description: update community MAKE file** 
    - adds `integration_tests`
    - adds `coverage`</s>

- **Issue:** the issue # it fixes if applicable,
- [For New Contributors: Update Integration
Documentation](https://github.com/langchain-ai/langchain/issues/15664#issuecomment-1920099868)
- **Dependencies:** n/a
- **Twitter handle:** @scottnath
- **Mastodon handle:** scottnath@mastodon.social

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
8 months ago
Liang Zhang 7306600e2f
community[patch]: Support SerDe transform functions in Databricks LLM (#16752)
**Description:** Databricks LLM does not support SerDe the
transform_input_fn and transform_output_fn. After saving and loading,
the LLM will be broken. This PR serialize these functions into a hex
string using pickle, and saving the hex string in the yaml file. Using
pickle to serialize a function can be flaky, but this is a simple
workaround that unblocks many use cases. If more sophisticated SerDe is
needed, we can improve it later.

Test:
Added a simple unit test.
I did manual test on Databricks and it works well.
The saved yaml looks like:
```
llm:
      _type: databricks
      cluster_driver_port: null
      cluster_id: null
      databricks_uri: databricks
      endpoint_name: databricks-mixtral-8x7b-instruct
      extra_params: {}
      host: e2-dogfood.staging.cloud.databricks.com
      max_tokens: null
      model_kwargs: null
      n: 1
      stop: null
      task: null
      temperature: 0.0
      transform_input_fn: 80049520000000000000008c085f5f6d61696e5f5f948c0f7472616e73666f726d5f696e7075749493942e
      transform_output_fn: null
```

@baskaryan

```python
from langchain_community.embeddings import DatabricksEmbeddings
from langchain_community.llms import Databricks
from langchain.chains import RetrievalQA
from langchain.document_loaders import TextLoader
from langchain.text_splitter import CharacterTextSplitter
from langchain.vectorstores import FAISS
import mlflow

embeddings = DatabricksEmbeddings(endpoint="databricks-bge-large-en")

def transform_input(**request):
  request["messages"] = [
    {
      "role": "user",
      "content": request["prompt"]
    }
  ]
  del request["prompt"]
  return request

llm = Databricks(endpoint_name="databricks-mixtral-8x7b-instruct", transform_input_fn=transform_input)

persist_dir = "faiss_databricks_embedding"

# Create the vector db, persist the db to a local fs folder
loader = TextLoader("state_of_the_union.txt")
documents = loader.load()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
docs = text_splitter.split_documents(documents)
db = FAISS.from_documents(docs, embeddings)
db.save_local(persist_dir)

def load_retriever(persist_directory):
    embeddings = DatabricksEmbeddings(endpoint="databricks-bge-large-en")
    vectorstore = FAISS.load_local(persist_directory, embeddings)
    return vectorstore.as_retriever()

retriever = load_retriever(persist_dir)
retrievalQA = RetrievalQA.from_llm(llm=llm, retriever=retriever)
with mlflow.start_run() as run:
    logged_model = mlflow.langchain.log_model(
        retrievalQA,
        artifact_path="retrieval_qa",
        loader_fn=load_retriever,
        persist_dir=persist_dir,
    )

# Load the retrievalQA chain
loaded_model = mlflow.pyfunc.load_model(logged_model.model_uri)
print(loaded_model.predict([{"query": "What did the president say about Ketanji Brown Jackson"}]))

```
8 months ago
Neli Hateva 9bb5157a3d
langchain[patch], community[patch]: Fixes in the Ontotext GraphDB Graph and QA Chain (#17239)
- **Description:** Fixes in the Ontotext GraphDB Graph and QA Chain
related to the error handling in case of invalid SPARQL queries, for
which `prepareQuery` doesn't throw an exception, but the server returns
400 and the query is indeed invalid
  - **Issue:** N/A
  - **Dependencies:** N/A
  - **Twitter handle:** @OntotextGraphDB
8 months ago
ByeongUk Choi b88329e9a5
community[patch]: Implement Unique ID Enforcement in FAISS (#17244)
**Description:**
Implemented unique ID validation in the FAISS component to ensure all
document IDs are distinct. This update resolves issues related to
non-unique IDs, such as inconsistent behavior during deletion processes.
8 months ago
Luiz Ferreira 34d2daffb3
community[patch]: Fix chat openai unit test (#17124)
- **Description:** 
Actually the test named `test_openai_apredict` isn't testing the
apredict method from ChatOpenAI.
  - **Twitter handle:**
  https://twitter.com/OAlmofadas
8 months ago
Frank ef082c77b1
community[minor]: add github file loader to load any github file content b… (#15305)
### Description
support load any github file content based on file extension.  

Why not use [git
loader](https://python.langchain.com/docs/integrations/document_loaders/git#load-existing-repository-from-disk)
?
git loader clones the whole repo even only interested part of files,
that's too heavy. This GithubFileLoader only downloads that you are
interested files.

### Twitter handle
my twitter: @shufanhaotop

---------

Co-authored-by: Hao Fan <h_fan@apple.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
8 months ago
Ryan Kraus f027696b5f
community: Added new Utility runnables for NVIDIA Riva. (#15966)
**Please tag this issue with `nvidia_genai`**

- **Description:** Added new Runnables for integration NVIDIA Riva into
LCEL chains for Automatic Speech Recognition (ASR) and Text To Speech
(TTS).
- **Issue:** N/A
- **Dependencies:** To use these runnables, the NVIDIA Riva client
libraries are required. It they are not installed, an error will be
raised instructing how to install them. The Runnables can be safely
imported without the riva client libraries.
- **Twitter handle:** N/A

All of the Riva Runnables are inside a single folder in the Utilities
module. In this folder are four files:
- common.py - Contains all code that is common to both TTS and ASR
- stream.py - Contains a class representing an audio stream that allows
the end user to put data into the stream like a queue.
- asr.py - Contains the RivaASR runnable
- tts.py - Contains the RivaTTS runnable

The following Python function is an example of creating a chain that
makes use of both of these Runnables:

```python
def create(
    config: Configuration,
    audio_encoding: RivaAudioEncoding,
    sample_rate: int,
    audio_channels: int = 1,
) -> Runnable[ASRInputType, TTSOutputType]:
    """Create a new instance of the chain."""
    _LOGGER.info("Instantiating the chain.")

    # create the riva asr client
    riva_asr = RivaASR(
        url=str(config.riva_asr.service.url),
        ssl_cert=config.riva_asr.service.ssl_cert,
        encoding=audio_encoding,
        audio_channel_count=audio_channels,
        sample_rate_hertz=sample_rate,
        profanity_filter=config.riva_asr.profanity_filter,
        enable_automatic_punctuation=config.riva_asr.enable_automatic_punctuation,
        language_code=config.riva_asr.language_code,
    )

    # create the prompt template
    prompt = PromptTemplate.from_template("{user_input}")

    # model = ChatOpenAI()
    model = ChatNVIDIA(model="mixtral_8x7b")  # type: ignore

    # create the riva tts client
    riva_tts = RivaTTS(
        url=str(config.riva_asr.service.url),
        ssl_cert=config.riva_asr.service.ssl_cert,
        output_directory=config.riva_tts.output_directory,
        language_code=config.riva_tts.language_code,
        voice_name=config.riva_tts.voice_name,
    )

    # construct and return the chain
    return {"user_input": riva_asr} | prompt | model | riva_tts  # type: ignore
```

The following code is an example of creating a new audio stream for
Riva:

```python
input_stream = AudioStream(maxsize=1000)
# Send bytes into the stream
for chunk in audio_chunks:
    await input_stream.aput(chunk)
input_stream.close()
```

The following code is an example of how to execute the chain with
RivaASR and RivaTTS

```python
output_stream = asyncio.Queue()
while not input_stream.complete:
    async for chunk in chain.astream(input_stream):
        output_stream.put(chunk)    
```

Everything should be async safe and thread safe. Audio data can be put
into the input stream while the chain is running without interruptions.

---------

Co-authored-by: Hayden Wolff <hwolff@nvidia.com>
Co-authored-by: Hayden Wolff <hwolff@Haydens-Laptop.local>
Co-authored-by: Hayden Wolff <haydenwolff99@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
8 months ago
Bagatur 6e2ed9671f
infra: fix breebs test lint (#17075) 8 months ago
Alex Boury 334b6ebdf3
community[minor]: Breebs docs retriever (#16578)
- **Description:** Implementation of breeb retriever with integration
tests ->
libs/community/tests/integration_tests/retrievers/test_breebs.py and
documentation (notebook) ->
docs/docs/integrations/retrievers/breebs.ipynb.
  - **Dependencies:** None
8 months ago
Harrison Chase 4eda647fdd
infra: add -p to mkdir in lint steps (#17013)
Previously, if this did not find a mypy cache then it wouldnt run

this makes it always run

adding mypy ignore comments with existing uncaught issues to unblock other prs

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
8 months ago
Killinsun - Ryota Takeuchi bcfce146d8
community[patch]: Correct the calling to collection_name in qdrant (#16920)
## Description

In #16608, the calling `collection_name` was wrong.
I made a fix for it. 
Sorry for the inconvenience!

## Issue

https://github.com/langchain-ai/langchain/issues/16962

## Dependencies

N/A



<!-- Thank you for contributing to LangChain!

Please title your PR "<package>: <description>", where <package> is
whichever of langchain, community, core, experimental, etc. is being
modified.

Replace this entire comment with:
  - **Description:** a description of the change, 
  - **Issue:** the issue # it fixes if applicable,
  - **Dependencies:** any dependencies required for this change,
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!

Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` from the root
of the package you've modified to check this locally.

See contribution guidelines for more information on how to write/run
tests, lint, etc: https://python.langchain.com/docs/contributing/

If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.

If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
 -->

---------

Co-authored-by: Kumar Shivendu <kshivendu1@gmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
8 months ago
Erick Friis b1a847366c
community: revert SQL Stores (#16912)
This reverts commit cfc225ecb3.


https://github.com/langchain-ai/langchain/pull/15909#issuecomment-1922418097

These will have existed in langchain-community 0.0.16 and 0.0.17.
8 months ago
Christophe Bornet af8c5c185b
langchain[minor],community[minor]: Add async methods in BaseLoader (#16634)
Adds:
* methods `aload()` and `alazy_load()` to interface `BaseLoader`
* implementation for class `MergedDataLoader `
* support for class `BaseLoader` in async function `aindex()` with unit
tests

Note: this is compatible with existing `aload()` methods that some
loaders already had.

**Twitter handle:** @cbornet_

---------

Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
8 months ago
Christophe Bornet 744070ee85
Add async methods for the AstraDB VectorStore (#16391)
- **Description**: fully async versions are available for astrapy 0.7+.
For older astrapy versions or if the user provides a sync client without
an async one, the async methods will call the sync ones wrapped in
`run_in_executor`
  - **Twitter handle:** cbornet_
8 months ago
baichuan-assistant f8f2649f12
community: Add Baichuan LLM to community (#16724)
Replace this entire comment with:
- **Description:** Add Baichuan LLM to integration/llm, also updated
related docs.

Co-authored-by: BaiChuanHelper <wintergyc@WinterGYCs-MacBook-Pro.local>
8 months ago
thiswillbeyourgithub 1d082359ee
community: add support for callable filters in FAISS (#16190)
- **Description:**
Filtering in a FAISS vectorstores is very inflexible and doesn't allow
that many use case. I think supporting callable like this enables a lot:
regular expressions, condition on multiple keys etc. **Note** I had to
manually alter a test. I don't understand if it was falty to begin with
or if there is something funky going on.
- **Issue:** None
- **Dependencies:** None
- **Twitter handle:** None

Signed-off-by: thiswillbeyourgithub <26625900+thiswillbeyourgithub@users.noreply.github.com>
8 months ago
Volodymyr Machula 32c5be8b73
community[minor]: Connery Tool and Toolkit (#14506)
## Summary

This PR implements the "Connery Action Tool" and "Connery Toolkit".
Using them, you can integrate Connery actions into your LangChain agents
and chains.

Connery is an open-source plugin infrastructure for AI.

With Connery, you can easily create a custom plugin with a set of
actions and seamlessly integrate them into your LangChain agents and
chains. Connery will handle the rest: runtime, authorization, secret
management, access management, audit logs, and other vital features.
Additionally, Connery and our community offer a wide range of
ready-to-use open-source plugins for your convenience.

Learn more about Connery:

- GitHub: https://github.com/connery-io/connery-platform
- Documentation: https://docs.connery.io
- Twitter: https://twitter.com/connery_io

## TODOs

- [x] API wrapper
   - [x] Integration tests
- [x] Connery Action Tool
   - [x] Docs
   - [x] Example
   - [x] Integration tests
- [x] Connery Toolkit
  - [x] Docs
  - [x] Example
- [x] Formatting (`make format`)
- [x] Linting (`make lint`)
- [x] Testing (`make test`)
8 months ago
Harrison Chase 8457c31c04
community[patch]: activeloop ai tql deprecation (#14634)
Co-authored-by: AdkSarsen <adilkhan@activeloop.ai>
8 months ago
Neli Hateva c95facc293
langchain[minor], community[minor]: Implement Ontotext GraphDB QA Chain (#16019)
- **Description:** Implement Ontotext GraphDB QA Chain
  - **Issue:** N/A
  - **Dependencies:** N/A
  - **Twitter handle:** @OntotextGraphDB
8 months ago
Jael Gu a1aa3a657c
community[patch]: Milvus supports add & delete texts by ids (#16256)
# Description

To support [langchain
indexing](https://python.langchain.com/docs/modules/data_connection/indexing)
as requested by users, vectorstore Milvus needs to support:
- document addition by id (`add_documents` method with `ids` argument)
- delete by id (`delete` method with `ids` argument)

Example usage:

```python
from langchain.indexes import SQLRecordManager, index
from langchain.schema import Document
from langchain_community.vectorstores import Milvus
from langchain_openai import OpenAIEmbeddings

collection_name = "test_index"
embedding = OpenAIEmbeddings()
vectorstore = Milvus(embedding_function=embedding, collection_name=collection_name)

namespace = f"milvus/{collection_name}"
record_manager = SQLRecordManager(
    namespace, db_url="sqlite:///record_manager_cache.sql"
)
record_manager.create_schema()

doc1 = Document(page_content="kitty", metadata={"source": "kitty.txt"})
doc2 = Document(page_content="doggy", metadata={"source": "doggy.txt"})

index(
    [doc1, doc1, doc2],
    record_manager,
    vectorstore,
    cleanup="incremental",  # None, "incremental", or "full"
    source_id_key="source",
)
```

# Fix issues

Fix https://github.com/milvus-io/milvus/issues/30112

---------

Signed-off-by: Jael Gu <mengjia.gu@zilliz.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
8 months ago
Benito Geordie f3fdc5c5da
community: Added integrations for ThirdAI's NeuralDB with Retriever and VectorStore frameworks (#15280)
**Description:** Adds ThirdAI NeuralDB retriever and vectorstore
integration. NeuralDB is a CPU-friendly and fine-tunable text retrieval
engine.
8 months ago
Christophe Bornet 2e3af04080
Use Postponed Evaluation of Annotations in Astra and Cassandra doc loaders (#16694)
Minor/cosmetic change
8 months ago