Commit Graph

455 Commits (b0896210c7d6c298002a6c074eba34384ce9b0e7)

Author SHA1 Message Date
Lance Martin 17ae2998e7
Update Ollama docs (#9220)
Based on discussion w/ team.
1 year ago
Krish Dholakia 49f1d8477c
Adding ChatLiteLLM model (#9020)
Description: Adding a langchain integration for the LiteLLM library 
Tag maintainer: @hwchase17, @baskaryan
Twitter handle: @krrish_dh / @Berri_AI

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Emmanuel Gautier f11e5442d6
docs: update LlamaCpp input args (#9173)
This PR only updates the LlamaCpp args documentation. The input arg has
been flattened.
1 year ago
Massimiliano Pronesti d95eeaedbe
feat(llms): support vLLM's OpenAI-compatible server (#9179)
This PR aims at supporting [vLLM's OpenAI-compatible server
feature](https://vllm.readthedocs.io/en/latest/getting_started/quickstart.html#openai-compatible-server),
i.e. allowing to call vLLM's LLMs like if they were OpenAI's.

I've also udpated the related notebook providing an example usage. At
the moment, vLLM only supports the `Completion` API.
1 year ago
Michael Goin 621da3c164
Adds DeepSparse as an LLM (#9184)
Adds [DeepSparse](https://github.com/neuralmagic/deepsparse) as an LLM
backend. DeepSparse supports running various open-source sparsified
models hosted on [SparseZoo](https://sparsezoo.neuralmagic.com/) for
performance gains on CPUs.

Twitter handles: @mgoin_ @neuralmagic


---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Bagatur 0fa69d8988
Bagatur/zep python 1.0 (#9186)
Co-authored-by: Daniel Chalef <131175+danielchalef@users.noreply.github.com>
1 year ago
Harrison Chase 8d69dacdf3
multiple retreival in parralel (#9174) 1 year ago
UmerHA 8aab39e3ce
Added SmartGPT workflow (issue #4463) (#4816)
# Added SmartGPT workflow by providing SmartLLM wrapper around LLMs
Edit:
As @hwchase17 suggested, this should be a chain, not an LLM. I have
adapted the PR.

It is used like this:
```
from langchain.prompts import PromptTemplate
from langchain.chains import SmartLLMChain
from langchain.chat_models import ChatOpenAI

hard_question = "I have a 12 liter jug and a 6 liter jug. I want to measure 6 liters. How do I do it?"
hard_question_prompt = PromptTemplate.from_template(hard_question)

llm = ChatOpenAI(model_name="gpt-4")
prompt = PromptTemplate.from_template(hard_question)
chain = SmartLLMChain(llm=llm, prompt=prompt, verbose=True)

chain.run({})
```


Original text: 
Added SmartLLM wrapper around LLMs to allow for SmartGPT workflow (as in
https://youtu.be/wVzuvf9D9BU). SmartLLM can be used wherever LLM can be
used. E.g:

```
smart_llm = SmartLLM(llm=OpenAI())
smart_llm("What would be a good company name for a company that makes colorful socks?")
```
or
```
smart_llm = SmartLLM(llm=OpenAI())
prompt = PromptTemplate(
    input_variables=["product"],
    template="What is a good name for a company that makes {product}?",
)
chain = LLMChain(llm=smart_llm, prompt=prompt)
chain.run("colorful socks")
```

SmartGPT consists of 3 steps:

1. Ideate - generate n possible solutions ("ideas") to user prompt
2. Critique - find flaws in every idea & select best one
3. Resolve - improve upon best idea & return it

Fixes #4463

## Who can review?

Community members can review the PR once tests pass. Tag
maintainers/contributors who might be interested:

- @hwchase17
- @agola11

Twitter: [@UmerHAdil](https://twitter.com/@UmerHAdil) | Discord:
RicChilligerDude#7589

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Bagatur 45741bcc1b
Bagatur/vectara nit (#9140)
Co-authored-by: Ofer Mendelevitch <ofer@vectara.com>
1 year ago
Dominick DEV 9b64932e55
Add LangChain utility for real-time crypto exchange prices (#4501)
This commit adds the LangChain utility which allows for the real-time
retrieval of cryptocurrency exchange prices. With LangChain, users can
easily access up-to-date pricing information by running the command
".run(from_currency, to_currency)". This new feature provides a
convenient way to stay informed on the latest exchange rates and make
informed decisions when trading crypto.


---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Joshua Sundance Bailey eaa505fb09
Create ArcGISLoader & example notebook (#8873)
- Description: Adds the ArcGISLoader class to
`langchain.document_loaders`
  - Allows users to load data from ArcGIS Online, Portal, and similar
- Users can authenticate with `arcgis.gis.GIS` or retrieve public data
anonymously
  - Uses the `arcgis.features.FeatureLayer` class to retrieve the data
  - Defines the most relevant keywords arguments and accepts `**kwargs`
- Dependencies: Using this class requires `arcgis` and, optionally,
`bs4.BeautifulSoup`.

Tagging maintainers:
  - DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Hai The Dude e4418d1b7e
Added new use case docs for Web Scraping, Chromium loader, BS4 transformer (#8732)
- Description: Added a new use case category called "Web Scraping", and
a tutorial to scrape websites using OpenAI Functions Extraction chain to
the docs.
  - Tag maintainer:@baskaryan @hwchase17 ,
- Twitter handle: https://www.linkedin.com/in/haiphunghiem/ (I'm on
LinkedIn mostly)

---------

Co-authored-by: Lance Martin <lance@langchain.dev>
1 year ago
niklub 16af5f8690
Add LabelStudio integration (#8880)
This PR introduces [Label Studio](https://labelstud.io/) integration
with LangChain via `LabelStudioCallbackHandler`:

- sending data to the Label Studio instance
- labeling dataset for supervised LLM finetuning
- rating model responses
- tracking and displaying chat history
- support for custom data labeling workflow

### Example

```
chat_llm = ChatOpenAI(callbacks=[LabelStudioCallbackHandler(mode="chat")])
chat_llm([
    SystemMessage(content="Always use emojis in your responses."),
        HumanMessage(content="Hey AI, how's your day going?"),
    AIMessage(content="🤖 I don't have feelings, but I'm running smoothly! How can I help you today?"),
        HumanMessage(content="I'm feeling a bit down. Any advice?"),
    AIMessage(content="🤗 I'm sorry to hear that. Remember, it's okay to seek help or talk to someone if you need to. 💬"),
        HumanMessage(content="Can you tell me a joke to lighten the mood?"),
    AIMessage(content="Of course! 🎭 Why did the scarecrow win an award? Because he was outstanding in his field! 🌾"),
        HumanMessage(content="Haha, that was a good one! Thanks for cheering me up."),
    AIMessage(content="Always here to help! 😊 If you need anything else, just let me know."),
        HumanMessage(content="Will do! By the way, can you recommend a good movie?"),
])
```

<img width="906" alt="image"
src="https://github.com/langchain-ai/langchain/assets/6087484/0a1cf559-0bd3-4250-ad96-6e71dbb1d2f3">


### Dependencies
- [label-studio](https://pypi.org/project/label-studio/)
- [label-studio-sdk](https://pypi.org/project/label-studio-sdk/)

https://twitter.com/labelstudiohq

---------

Co-authored-by: nik <nik@heartex.net>
1 year ago
Bagatur 8cb2594562
Bagatur/dingo (#9079)
Co-authored-by: gary <1625721671@qq.com>
1 year ago
Manuel Soria 31cfc00845
Code understanding use case (#8801)
Code understanding docs

---------

Co-authored-by: Manuel Soria <manuel.soria@greyscaleai.com>
Co-authored-by: Lance Martin <lance@langchain.dev>
1 year ago
Alvaro Bartolome f7ae183f40
`ArgillaCallbackHandler` to properly use default values for `api_url` and `api_key` (#9113)
As of the recent PR at #9043, after some testing we've realised that the
default values were not being used for `api_key` and `api_url`. Besides
that, the default for `api_key` was set to `argilla.apikey`, but since
the default values are intended for people using the Argilla Quickstart
(easy to run and setup), the defaults should be instead `owner.apikey`
if using Argilla 1.11.0 or higher, or `admin.apikey` if using a lower
version of Argilla.

Additionally, we've removed the f-string replacements from the
docstrings.

---------

Co-authored-by: Gabriel Martin <gabriel@argilla.io>
1 year ago
Bagatur 0e5d09d0da
dalle nb fix (#9125) 1 year ago
Francisco Ingham 9249d305af
tagging docs refactor (#8722)
refactor of tagging use case according to new format

---------

Co-authored-by: Lance Martin <lance@langchain.dev>
1 year ago
Ashutosh Sanzgiri 991b448dfc
minor edits (#9093)
Description:

Minor edit to PR#845

Thanks!
1 year ago
Chenyu Zhao c0acbdca1b
Update Fireworks model names (#9085) 1 year ago
Charles Lanahan a2588d6c57
Update openai embeddings notebook with correct embedding model in section 2 (#5831)
In second section it looks like a copy/paste from the first section and
doesn't include the specific embedding model mentioned in the example so
I added it for clarity.
---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Josh Phillips 5fc07fa524
change id column type to uuid to match function (#7456)
The table creation process in these examples commands do not match what
the recently updated functions in these example commands is looking for.
This change updates the type in the table creation command.
Issue Number for my report of the doc problem #7446
@rlancemartin and @eyurtsev I believe this is your area
Twitter: @j1philli

Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Bidhan Roy 02430e25b6
BagelDB (bageldb.ai), VectorStore integration. (#8971)
- **Description**: [BagelDB](bageldb.ai) a collaborative vector
database. Integrated the bageldb PyPi package with langchain with
related tests and code.

  - **Issue**: Not applicable.
  - **Dependencies**: `betabageldb` PyPi package.
  - **Tag maintainer**: @rlancemartin, @eyurtsev, @baskaryan
  - **Twitter handle**: bageldb_ai (https://twitter.com/BagelDB_ai)
  
We ran `make format`, `make lint` and `make test` locally.

Followed the contribution guideline thoroughly
https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md

---------

Co-authored-by: Towhid1 <nurulaktertowhid@gmail.com>
1 year ago
Harrison Chase bb6fbf4c71
openai adapters (#8988)
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Nuno Campos <nuno@boringbits.io>
1 year ago
Piyush Jain 8eea46ed0e
Bedrock embeddings async methods (#9024)
## Description
This PR adds the `aembed_query` and `aembed_documents` async methods for
improving the embeddings generation for large documents. The
implementation uses asyncio tasks and gather to achieve concurrency as
there is no bedrock async API in boto3.

### Maintainers
@agola11 
@aarora79  

### Open questions
To avoid throttling from the Bedrock API, should there be an option to
limit the concurrency of the calls?
1 year ago
Eugene Yurtsev a5a4c53280
RedisStore: Update init and Documentation updates (#9044)
* Update Redis Store to support init from parameters
* Update notebook to show how to use redis store, and some fixes in
documentation
1 year ago
Blake (Yung Cher Ho) 8d351bfc20
Takeoff integration (#9045)
## Description:
This PR adds the Titan Takeoff Server to the available LLMs in
LangChain.

Titan Takeoff is an inference server created by
[TitanML](https://www.titanml.co/) that allows you to deploy large
language models locally on your hardware in a single command. Most
generative model architectures are included, such as Falcon, Llama 2,
GPT2, T5 and many more.

Read more about Titan Takeoff here:
-
[Blog](https://medium.com/@TitanML/introducing-titan-takeoff-6c30e55a8e1e)
- [Docs](https://docs.titanml.co/docs/titan-takeoff/getting-started)

#### Testing
As Titan Takeoff runs locally on port 8000 by default, no network access
is needed. Responses are mocked for testing.

- [x] Make Lint
- [x] Make Format
- [x] Make Test

#### Dependencies
No new dependencies are introduced. However, users will need to install
the titan-iris package in their local environment and start the Titan
Takeoff inferencing server in order to use the Titan Takeoff
integration.

Thanks for your help and please let me know if you have any questions.

cc: @hwchase17 @baskaryan
1 year ago
Eugene Yurtsev 5e05ba2140
Add embeddings cache (#8976)
This PR adds the ability to temporarily cache or persistently store
embeddings. 

A notebook has been included showing how to set up the cache and how to
use it with a vectorstore.
1 year ago
Lance Martin 2380492c8e
API use case (#8546)
Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Luca Foppiano dfb93dd2b5
Improved grobid documentation (#9025)
- Description: Improvement in the Grobid loader documentation, typos and
suggesting to use the docker image instead of installing Grobid in local
(the documentation was also limited to Mac, while docker allow running
in any platform)
  - Tag maintainer: @rlancemartin, @eyurtsev
  - Twitter handle: @whitenoise
1 year ago
Piyush Jain 3b51817706
Updating port and ssl use in sample notebook (#8995)
## Description
This PR updates the sample notebook to use the default port (8182) and
the ssl for the Neptune database connection.
1 year ago
Jerzy Czopek 539672a7fd
Feature/fix azureopenai model mappings (#8621)
This pull request aims to ensure that the `OpenAICallbackHandler` can
properly calculate the total cost for Azure OpenAI chat models. The
following changes have resolved this issue:

- The `model_name` has been added to the ChatResult llm_output. Without
this, the default values of `gpt-35-turbo` were applied. This was
causing the total cost for Azure OpenAI's GPT-4 to be significantly
inaccurate.
- A new parameter `model_version` has been added to `AzureChatOpenAI`.
Azure does not include the model version in the response. With the
addition of `model_name`, this is not a significant issue for GPT-4
models, but it's an issue for GPT-3.5-Turbo. Version 0301 (default) of
GPT-3.5-Turbo on Azure has a flat rate of 0.002 per 1k tokens for both
prompt and completion. However, version 0613 introduced a split in
pricing for prompt and completion tokens.
- The `OpenAICallbackHandler` implementation has been updated with the
proper model names, versions, and cost per 1k tokens.

Unit tests have been added to ensure the functionality works as
expected; the Azure ChatOpenAI notebook has been updated with examples.

Maintainers: @hwchase17, @baskaryan

Twitter handle: @jjczopek

---------

Co-authored-by: Jerzy Czopek <jerzy.czopek@avanade.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Harrison Chase 7de6a1b78e
parent document retriever (#8941) 1 year ago
arjunbansal a2681f950d
add instructions on integrating Log10 (#8938)
- Description: Instruction for integration with Log10: an [open
source](https://github.com/log10-io/log10) proxiless LLM data management
and application development platform that lets you log, debug and tag
your Langchain calls
  - Tag maintainer: @baskaryan
  - Twitter handle: @log10io @coffeephoenix

Several examples showing the integration included
[here](https://github.com/log10-io/log10/tree/main/examples/logging) and
in the PR
1 year ago
Aarav Borthakur 3f64b8a761
Integrate Rockset as a chat history store (#8940)
Description: Adds Rockset as a chat history store
Dependencies: no changes
Tag maintainer: @hwchase17

This PR passes linting and testing. 

I added a test for the integration and an example notebook showing its
use.
1 year ago
Bagatur 0a1be1d501
document lcel fallbacks (#8942) 1 year ago
Molly Cantillon 99b5a7226c
Weaviate: adding auth example + fixing spelling in ReadME (#8939)
Added basic auth example to Weaviate notebook @baskaryan
1 year ago
Joe Reuter 8f0cd91d57
Airbyte based loaders (#8586)
This PR adds 8 new loaders:
* `AirbyteCDKLoader` This reader can wrap and run all python-based
Airbyte source connectors.
* Separate loaders for the most commonly used APIs:
  * `AirbyteGongLoader`
  * `AirbyteHubspotLoader`
  * `AirbyteSalesforceLoader`
  * `AirbyteShopifyLoader`
  * `AirbyteStripeLoader`
  * `AirbyteTypeformLoader`
  * `AirbyteZendeskSupportLoader`

## Documentation and getting started
I added the basic shape of the config to the notebooks. This increases
the maintenance effort a bit, but I think it's worth it to make sure
people can get started quickly with these important connectors. This is
also why I linked the spec and the documentation page in the readme as
these two contain all the information to configure a source correctly
(e.g. it won't suggest using oauth if that's avoidable even if the
connector supports it).

## Document generation
The "documents" produced by these loaders won't have a text part
(instead, all the record fields are put into the metadata). If a text is
required by the use case, the caller needs to do custom transformation
suitable for their use case.

## Incremental sync
All loaders support incremental syncs if the underlying streams support
it. By storing the `last_state` from the reader instance away and
passing it in when loading, it will only load updated records.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Harrison Chase 7543a3d70e
Harrison/image (#845)
Co-authored-by: Ashutosh Sanzgiri <sanzgiri@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Leonid Ganeline 33a2f58fbf
`tensoflow_datasets` document loader (#8721)
This PR adds `tensoflow_datasets` document loader
1 year ago
Leonid Ganeline 2d078c7767
`PubMed` document loader (#8893)
- added `PubMed Document Loader` artifacts; ut-s; examples 
- fixed `PubMed utility`; ut-s

@hwchase17
1 year ago
Seif 6327eecdaf
Fix typo in Vectara docs (#8925)
Fixed a typo in the Vectara docs description.
1 year ago
David vonThenen bf4a112aa6
Fixes to the Nebula LLM Integration (#8918)
This addresses some issues with introducing the Nebula LLM to LangChain
in this PR:
https://github.com/langchain-ai/langchain/pull/8876

This fixes the following:
- Removes `SYMBLAI` from variable names
- Fixes bug with `Bearer` for the API KEY


Thanks again in advance for your help!
cc: @hwchase17, @baskaryan

---------

Co-authored-by: dvonthenen <david.vonthenen@gmail.com>
1 year ago
Josh Hart 6116cbf0de
Fix imports in awslambda docs (#8916)
Minor doc fix to awslambda tool notebook. 

Add missing import for initialize_agent to awslambda agent example

Co-authored-by: Josh Hart <josharj@amazon.com>
1 year ago
Maurits de Groot 61c2d918c6
Fixed inaccurate import in integrations:providers:bedrock documentation (#8915)
Description:
Fixed inaccurate import in integrations:providers:bedrock documentation

In the current version of the bedrock documentation, page
https://python.langchain.com/docs/integrations/providers/bedrock it
states that the import is from langchain import Bedrock

This has been changed to from langchain.llms.bedrock import Bedrock as
stated in https://python.langchain.com/docs/integrations/llms/bedrock

Issue:
Not applicable

Dependencies
No dependencies required

Tag maintainer
@baskaryan

Twitter handle:
Not applicable
1 year ago
Manuel Soria e74a605379
SQL use case docs (#8513) 1 year ago
Jacob Lee fa30a57034
Adds Ollama as an LLM (#8829)
Adds Ollama as an LLM. Ollama can run various open source models locally
e.g. Llama 2 and Vicuna, automatically configuring and GPU-optimizing
them.

@rlancemartin @hwchase17

---------

Co-authored-by: Lance Martin <lance@langchain.dev>
1 year ago
Ash Vardanian 1f9124ceaa
Add: USearch Vector Store (#8835)
## Description

I am excited to propose an integration with USearch, a lightweight
vector-search engine available for both Python and JavaScript, among
other languages.

## Dependencies

It introduces a new PyPi dependency - `usearch`. I am unsure if it must
be added to the Poetry file, as this would make the PR too clunky.
Please let me know.

## Profiles

- Maintainers: @ashvardanian @davvard
- Twitter handles: @ashvardanian @unum_cloud

---------

Co-authored-by: Davit Vardanyan <78792753+davvard@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
1 year ago
Leonid Kuligin b52a3785c9
Allow to specify a custom loader for GcsFileLoader (#8868)
Co-authored-by: Leonid Kuligin <kuligin@google.com>
1 year ago
Jeffrey Wang ff44fe4e16
Change default Metaphor search example to use prompt optimizer (#8890)
- fix install command
- change example notebook to use Metaphor autoprompt by default

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1 year ago