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hi!
This is pretty straight-forward: The sdist package does not contain the
license file (which is needed by e.g. conda) because the package is
built from the subdir and can't see the license.
I _copied_ the license but since I'm unfamiliar with the projects
direction, I'm not sure that's correct.
thanks!
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Fixes: #8207
Description:
Pinecone returns scores (not distances) with cosine similarity. The
values according to the docs are [-1, 1], although I could never
reproduce negative values.
This PR ensures that the score returned from Pinecone is preserved,
rather than inverted, so the most relevant documents can be filtered (eg
when using similarity thresholds)
I'll leave this as a draft PR as I couldn't run the tests (my pinecone
account might not be enough - some errors were being thrown around
namespaces) so hopefully someone who _can_ will pick this up.
Maintainers:
@rlancemartin, @eyurtsev
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** Fixed a serialization issue in the add_texts method
of the Matching Engine Vector Store caused by a typo, leading to an
attempt to serialize the json module itself.
- **Issue:** #12154
- **Dependencies:** ./.
- **Tag maintainer:**
- **Description:** Refine Weaviate tutorial and add an example for
Retrieval-Augmented Generation (RAG)
- **Issue:** (not applicable),
- **Dependencies:** none
- **Tag maintainer:** @baskaryan <!--
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- **Twitter handle:** @helloiamleonie
Co-authored-by: Leonie <leonie@Leonies-MBP-2.fritz.box>
Due to the possibility of external inputs including UUIDs, there may be
additional values in **kwargs, while Weaviate's `__init__` method does
not support passing extra **kwarg parameters.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
When calling max_marginal_relevance_search from PGVector the filter
param is not carried over to max_marginal_relevance_search_by_vector
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** Uses `endpoint_url` if provided with a boto3 session.
When running dynamodb locally, credentials are required even if invalid.
With this change, it will be possible to pass a boto3 session with
credentials and specify an endpoint_url
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
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Replace this entire comment with:
- **Description:** Add MyScaleWithoutJSON which allows user to wrap
columns into Document's Metadata
- **Tag maintainer:** @baskaryan
**Description**
Bumps the Momento dependency to the latest version and refactors the
usage of `SearchHit` in the Momento Vector Index (MVI) vector store
integration. This change is a one liner where we use the preferred
attribute `score` to read the query-document similarity instead of
`distance`. The latest versions of Momento clients will use this
attribute going forward.
**Dependencies**
Updated the Momento dependency to latest version.
**Tests**
💚 I re-ran the existing MVI integration tests
(`tests/integration_tests/vectorstores/test_momento_vector_index.py`)
and they pass.
**Review**
cc @baskaryan @eyurtsev
On the [Defining Custom
Tools](https://python.langchain.com/docs/modules/agents/tools/custom_tools)
page, there's a 'Subclassing the BaseTool class' paragraph under the
'Completely New Tools - String Input and Output' header. Also there's
another 'Subclassing the BaseTool' paragraph under no header, which I
think may belong to the 'Custom Structured Tools' header.
Another thing is, there's a 'Using the tool decorator' and a 'Using the
decorator' paragraph, I think should belong to 'Completely New Tools -
String Input and Output' and 'Custom Structured Tools' separately.
This PR moves those paragraphs to corresponding headers.
**Description**
the ollama api now supports passing system prompt and template directly
instead of modifying the model file , but the ollama integration in
langchain did not have this change updated . The update just adds these
two parameters to it ( there are 2 more parameters that are pending to
be updated, I was not sure about their utility wrt to langchain )
Refer :
8713ac23a8
**Issue** : None Applicable
**Dependencies** : None Changed
**Twitter handle** : https://twitter.com/violetto96
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
added Parallel Function Calling for Structured Data Extraction notebook
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---------
Co-authored-by: Erick Friis <erick@langchain.dev>
`_get_kwarg_value` function is useless, one can rely on python builtin
functionalities to do the exact same thing.
- **Description:** Removed `_get_kwarg_value`. Helps with code
readability.
- **Issue:** the issue # it fixes (if applicable),
- **Twitter handle:** @Guillem_96
Improve CSV reader which can't call .strip() on NoneType if there are
less cells in the row compared to the header
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- **Description:**
I have a CSV file as followed
```
headerA,headerB,headerC
v1A,v1B,v1C,
v2A,v2B
v3A,v3B,v3C
```
In this case, row 2 is missing a value, which results in reading a None
type. The strip() method can not be called on None, hence raising. In
this PR I am making the change to only call strip if the value if not
None.
- **Issue:** the issue # it fixes (if applicable),
- **Dependencies:** any dependencies required for this change,
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We updated MyScale free knowledge base, where you can try your RAG with
36 million paragraphs from wikipedia and 2 million paragraphs from
ArXiv.
The pod has two tables
```sql
CREATE TABLE default.ChatArXiv (
`abstract` String,
`id` String,
`vector` Array(Float32),
`metadata` Object('JSON'),
`pubdate` DateTime,
`title` String,
`categories` Array(String),
`authors` Array(String),
`comment` String,
`primary_category` String,
VECTOR INDEX vec_idx vector TYPE MSTG('metric_type=Cosine'),
CONSTRAINT vec_len CHECK length(vector) = 768)
ENGINE = ReplacingMergeTree ORDER BY id;
CREATE TABLE wiki.Wikipedia (
`id` String,
`title` String,
`text` String,
`url` String,
`wiki_id` UInt64,
`views` Float32,
`paragraph_id` UInt64,
`langs` UInt32,
`emb` Array(Float32),
VECTOR INDEX emb_idx emb TYPE MSTG('metric_type=Cosine'),
CONSTRAINT emb_len CHECK length(emb) = 768)
ENGINE = ReplacingMergeTree ORDER BY id;
```
You can connect those two tables using credentials below (just the same
to the old one)
URL: `msc-4a9e710a.us-east-1.aws.staging.myscale.cloud`
Port: `443`
Username: `chatdata`
Password: `myscale_rocks`
It's FREE and you can also use it with
ChatData: https://github.com/myscale/ChatData
Retrieval-QA-Benchmark:
https://github.com/myscale/Retrieval-QA-Benchmark
... and also LangChain!
Request for review @baskaryan
**Description:** This is like the rag-conversation template in many
ways. What's different is:
- support for a timescale vector store.
- support for time-based filters.
- support for metadata filters.
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---------
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** Changed the fleet_context documentation to use
`context.download_embeddings()` from the latest release from our
package. More details here:
https://github.com/fleet-ai/context/tree/main#api
- **Issue:** n/a
- **Dependencies:** n/a
- **Tag maintainer:** @baskaryan
- **Twitter handle:** @andrewthezhou
Added a Docusaurus Loader
Issue: #6353
I had to implement this for working with the Ionic documentation, and
wanted to open this up as a draft to get some guidance on building this
out further. I wasn't sure if having it be a light extension of the
SitemapLoader was in the spirit of a proper feature for the library --
but I'm grateful for the opportunities Langchain has given me and I'd
love to build this out properly for the sake of the community.
Any feedback welcome!
- **Description:** `AzureMLChatOnlineEndpoint` object from
langchain/chat_models/azureml_endpoint.py safe to print
without having any secrets included in raw format in the string
representation.
- **Issue:** #12165,
- **Tag maintainer:** @eyurtsev
---------
Co-authored-by: Faysal Bougamale <faysal.bougamale@horiba.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
- Adding documentation to the runnable.
- Documentation is not organized in the best way for the runnable; i.e.,
in
terms of LCEL vs. other standard methods, will follow up with more
edits.
