Enable max inner product for approximate retrieval strategy. For exact
strategy we lack the necessary `maxInnerProduct` function in the
Painless scripting language, this is why we do not add it there.
Similarity docs:
https://www.elastic.co/guide/en/elasticsearch/reference/current/dense-vector.html#dense-vector-params
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Joe McElroy <joseph.mcelroy@elastic.co>
Implement similarity function selector for ElasticsearchStore. The
scores coming back from Elasticsearch are already similarities (not
distances) and they are already normalized (see
[docs](https://www.elastic.co/guide/en/elasticsearch/reference/current/dense-vector.html#dense-vector-params)).
Hence we leave the scores untouched and just forward them.
This fixes#11539.
However, in hybrid mode (when keyword search and vector search are
involved) Elasticsearch currently returns no scores. This PR adds an
error message around this fact. We need to think a bit more to come up
with a solution for this case.
This PR also corrects a small error in the Elasticsearch integration
test.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:**
In this PR, I am adding a `PolygonLastQuote` Tool, which can be used to
get the latest price quote for a given ticker / stock.
Additionally, I've added a Polygon Toolkit, which we can use to
encapsulate future tools that we build for Polygon.
**Twitter handle:** [@virattt](https://twitter.com/virattt)
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
fixed multi-query template for Vectara
added self-query template for Vectara
Also added prompt_name parameter to summarization
CC @efriis
**Twitter handle:** @ofermend
- **Description:** Some text-generation models on huggingface repeat the
prompt in their generated response, but not all do! The tests use "gpt2"
which DOES repeat the prompt and as such, the HuggingFaceHub class is
hardcoded to remove the first few characters of the response (to match
the len(prompt)). However, if you are using a model (such as the very
popular "meta-llama/Llama-2-7b-chat-hf") that DOES NOT repeat the prompt
in it's generated text, then the beginning of the generated text will be
cut off. This code change fixes that bug by first checking whether the
prompt is repeated in the generated response and removing it
conditionally.
- **Issue:** #16232
- **Dependencies:** N/A
- **Twitter handle:** N/A
* Removed some env vars not used in langchain package IT
* Added Astra DB env vars in langchain package, used for cache tests
* Added conftest.py to load env vars in langchain_community IT
* Added .env.example in langchain_community IT
The timeout function comes in handy when you want to kill longrunning
queries.
The value sanitization removes all lists that are larger than 128
elements. The idea here is to remove embedding properties from results.
- **Description:** As Shell tool is very versatile, while integrating it
into applications as openai functions, developers have no clue about
what command is being executed using the ShellTool. All one can see is:
Summarising my feature request:
1. There's no visibility about what command was executed.
2. There's no mechanism to prevent a command to be executed using
ShellTool, like a y/n human input which can be accepted from user to
proceed with executing the command.,
- **Issue:** the issue #15931 it fixes if applicable,
- **Dependencies:** There isn't any dependancy,
- **Twitter handle:** @krishnashed
- **Description:** Made a small fix for the `SQLDatabase` highlighted in
an issue. The issue pertains to switching schema for different SQL
engines.
- **Issue:** #16023
@baskaryan
- **Description:** This handles the cohere response when documents
aren't included in the response
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** N/A
**Description:**
Implement `adelete` function from `VectorStore` in `Qdrant` to support
other asynchronous flows such as async indexing (`aindex`) which
requires `adelete` to be implemented. Since `Qdrant` can be passed an
async qdrant client, this can be supported easily.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
This PR addresses an issue in OpenAIWhisperParserLocal where requesting
CUDA without availability leads to an AttributeError #15143
Changes:
- Refactored Logic for CUDA Availability: The initialization now
includes a check for CUDA availability. If CUDA is not available, the
code falls back to using the CPU. This ensures seamless operation
without manual intervention.
- Parameterizing Batch Size and Chunk Size: The batch_size and
chunk_size are now configurable parameters, offering greater flexibility
and optimization options based on the specific requirements of the use
case.
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
**Description:** This new feature enhances the flexibility of pipeline
integration, particularly when working with RESTful APIs.
``JsonRequestsWrapper`` allows for the decoding of JSON output, instead
of the only option for text output.
---------
Co-authored-by: Zhichao HAN <hanzhichao2000@hotmail.com>
Fixed the issue mentioned in #15698 for SlackGetChannel Tool.
@baskaryan.
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** add deprecated warning for ErnieBotChat and
ErnieEmbeddings.
- These two classes **lack maintenance** and do not use the sdk provided
by qianfan, which means hard to implement some key feature like
streaming.
- The alternative `langchain_community.chat_models.QianfanChatEndpoint`
and `langchain_community.embeddings.QianfanEmbeddingsEndpoint` can
completely replace these two classes, only need to change configuration
items.
- **Issue:** None,
- **Dependencies:** None,
- **Twitter handle:** None
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
**Description**: `zip` is iterator that will only produce result once,
so the previous code will cause the `embeddings` to be an empty list.
**Issue**: I could not find a related issue.
**Dependencies**: this PR does not introduce or affect dependencies.
---------
Co-authored-by: Bagatur <baskaryan@gmail.com>
- **Description:** docs update following the changes introduced in
#15879
<!-- 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.
-->
BigQuery vector search lets you use GoogleSQL to do semantic search,
using vector indexes for fast but approximate results, or using brute
force for exact results.
This PR:
1. Add `metadata[_job_ib]` in Document returned by any similarity search
2. Add `explore_job_stats` to enable users to explore job statistics and
better the debuggability
3. Set the minimum row limit for running create vector index.
## Description
In this update, I addressed the missing implementation for
atransform_document, which is the asynchronous counterpart of
transform_document in Doctran.
### Usage Example:
```py
# Instantiate DoctranPropertyExtractor with specified properties
property_extractor = DoctranPropertyExtractor(properties=properties)
# Asynchronously extract properties from a list of documents
extracted_document = await property_extractor.atransform_documents(
documents, properties=properties
)
# Display metadata of the first extracted document
print(json.dumps(extracted_document[0].metadata, indent=2))
```
## Issue
- Pull request #14525 has caused a break in the aforementioned code.
Instead of removing an asynchronous implementation of a function,
consider implementing a synchronous version alongside it.
- **Description:** Added parenthesis in return statement of
aembed_query() funtion to fix 'coroutine' object is not subscriptable
error.
- **Dependencies:** NA
Co-authored-by: H161961 <Raunak.Raunak@Honeywell.com>
## Feature
- Follow parameter structure as per official documentation
- top level parameters (e.g. model, system, template) will be passed as
top level parameters
- other parameters will be sent in options unless options is provided
## Tests
- Test if top level parameters handled properly
- Test if parameters that are not top level parameters are handled as
options
- Test if options is provided, it will be passed as is
**Description:** Added the new gpt-3.5-turbo-1106 for **finetuned** cost
calculation,
**Issue:** no issue found open
By the information in OpenAI the pricing is the same as the older model
(0613)
- **Description:** Added a `PolygonAPIWrapper` and an initial
`get_last_quote` endpoint, which allows us to get the last price quote
for a given `ticker`. Once merged, I can add a Polygon tool in `tools/`
for agents to use.
- **Twitter handle:** [@virattt](https://twitter.com/virattt)
The Polygon.io Stocks API provides REST endpoints that let you query the
latest market data from all US stock exchanges.
