### Description:
NotionDB supports a number of common property types. I have found three
common types that are not included in notiondb loader. When programs
loaded them with notiondb, which will cause some metadata information
not to be passed to langchain. Therefore, I added three common types:
- date
- created_time
- last_edit_time.
### Issue:
no
### Dependencies:
No dependencies added :)
### Tag maintainer:
@rlancemartin, @eyurtsev
### Twitter handle:
@BJTUTC
Reverts langchain-ai/langchain#8610
this is actually an oversight - this merges all dfs into one df. we DO
NOT want to do this - the idea is we work and manipulate multiple dfs
This removes the use of the intermediate df list and directly
concatenates the dataframes if path is a list of strings. The pd.concat
function combines the dataframes efficiently, making it faster and more
memory-efficient compared to appending dataframes to a list.
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---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
- Description: this PR adds the support for arxiv identifier of the
ArxivAPIWrapper. I modified the `run()` and `load()` functions in
`arxiv.py`, using regex to recognize if the query is in the form of
arxiv identifier (see
[https://info.arxiv.org/help/find/index.html](https://info.arxiv.org/help/find/index.html)).
If so, it will directly search the paper corresponding to the arxiv
identifier. I also modified and added tests in `test_arxiv.py`.
- Issue: #9047
- Dependencies: N/A
- Tag maintainer: N/A
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
The new Fireworks and FireworksChat implementations are awesome! Added
in this PR https://github.com/langchain-ai/langchain/pull/11117 thank
you @ZixinYang
However, I think stop words were not plumbed correctly. I've made some
simple changes to do that, and also updated the notebook to be a bit
clearer with what's needed to use both new models.
---------
Co-authored-by: Taqi Jaffri <tjaffri@docugami.com>
The intermediate steps example in docs has an example on how to retrieve
and display the intermediate steps.
But the intermediate steps object is of type AgentAction which cannot be
passed to json.dumps (it raises an error).
I replaced it with Langchain's dumps function (from langchain.load.dump
import dumps) which is the preferred way to do so.
**Description:**
As long as `enforce_stop_tokens` returns a first occurrence, we can
speed up the execution by setting the optional `maxsplit` parameter to
1.
Tag maintainer:
@agola11
@hwchase17
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---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description:** New metadata fields were added to
`unstructured==0.10.15`, and our hosted api has been updated to reflect
this. When users call `partition_via_api` with an older version of the
library, they'll hit a parsing error related to the new fields.
Description
* Refactor Fireworks within Langchain LLMs.
* Remove FireworksChat within Langchain LLMs.
* Add ChatFireworks (which uses chat completion api) to Langchain chat
models.
* Users have to install `fireworks-ai` and register an api key to use
the api.
Issue - Not applicable
Dependencies - None
Tag maintainer - @rlancemartin @baskaryan
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- **Description:**: Adds LLM as a judge as an eval chain
- **Tag maintainer:** @hwchase17
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
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1. a test for the integration, preferably unit tests that do not rely on
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@baskaryan, @eyurtsev, @hwchase17.
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---------
Co-authored-by: William FH <13333726+hinthornw@users.noreply.github.com>
This enables bulk args like `chunk_size` to be passed down from the
ingest methods (from_text, from_documents) to be passed down to the bulk
API.
This helps alleviate issues where bulk importing a large amount of
documents into Elasticsearch was resulting in a timeout.
Contribution Shoutout
- @elastic
- [x] Updated Integration tests
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Fixed navbar:
- renamed several files, so ToC is sorted correctly
- made ToC items consistent: formatted several Titles
- added several links
- reformatted several docs to a consistent format
- renamed several files (removed `_example` suffix)
- added renamed files to the `docs/docs_skeleton/vercel.json`
Sometimes you don't want the LLM to be aware of the whole graph schema,
and want it to ignore parts of the graph when it is constructing Cypher
statements.
- **Description**: Adding retrievers for [kay.ai](https://kay.ai) and
SEC filings powered by Kay and Cybersyn. Kay provides context as a
service: it's an API built for RAG.
- **Issue**: N/A
- **Dependencies**: Just added a dep to the
[kay](https://pypi.org/project/kay/) package
- **Tag maintainer**: @baskaryan @hwchase17 Discussed in slack
- **Twtter handle:** [@vishalrohra_](https://twitter.com/vishalrohra_)
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
The huggingface pipeline in langchain (used for locally hosted models)
does not support batching. If you send in a batch of prompts, it just
processes them serially using the base implementation of _generate:
https://github.com/docugami/langchain/blob/master/libs/langchain/langchain/llms/base.py#L1004C2-L1004C29
This PR adds support for batching in this pipeline, so that GPUs can be
fully saturated. I updated the accompanying notebook to show GPU batch
inference.
---------
Co-authored-by: Taqi Jaffri <tjaffri@docugami.com>
