Commit Graph

11 Commits

Author SHA1 Message Date
Casey Clements
6e9a8b188f
mongodb: Add Hybrid and Full-Text Search Retrievers, release 0.2.0 (#25057)
## Description

This pull-request extends the existing vector search strategies of
MongoDBAtlasVectorSearch to include Hybrid (Reciprocal Rank Fusion) and
Full-text via new Retrievers.

There is a small breaking change in the form of the `prefilter` kwarg to
search. For this, and because we have now added a great deal of
features, including programmatic Index creation/deletion since 0.1.0, we
plan to bump the version to 0.2.0.

### Checklist
* Unit tests have been extended
* formatting has been applied
* One mypy error remains which will either go away in CI or be
simplified.

---------

Signed-off-by: Casey Clements <casey.clements@mongodb.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
2024-08-07 20:10:29 +00:00
Isaac Francisco
a72fddbf8d
[docs]: vector store integration pages (#24858)
Co-authored-by: Erick Friis <erick@langchain.dev>
2024-08-06 17:20:27 +00:00
Casey Clements
db3ceb4d0a
partners/mongodb: Improved search index commands (#24745)
Hardens index commands with try/except for free clusters and optional
waits for syncing and tests.

[efriis](https://github.com/efriis) These are the upgrades to the search
index commands (CRUD) that I mentioned.

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
2024-08-01 20:16:32 +00:00
Casey Clements
a47f69a120
partners/mongodb : Significant MongoDBVectorSearch ID enhancements (#23535)
## Description

This pull-request improves the treatment of document IDs in
`MongoDBAtlasVectorSearch`.

Class method signatures of add_documents, add_texts, delete, and
from_texts
now include an `ids:Optional[List[str]]` keyword argument permitting the
user
greater control. 
Note that, as before, IDs may also be inferred from
`Document.metadata['_id']`
if present, but this is no longer required,
IDs can also optionally be returned from searches.

This PR closes the following JIRA issues.

* [PYTHON-4446](https://jira.mongodb.org/browse/PYTHON-4446)
MongoDBVectorSearch delete / add_texts function rework
* [PYTHON-4435](https://jira.mongodb.org/browse/PYTHON-4435) Add support
for "Indexing"
* [PYTHON-4534](https://jira.mongodb.org/browse/PYTHON-4534) Ensure
datetimes are json-serializable

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
2024-07-17 13:26:20 -07:00
Philippe PRADOS
26cee2e878
partners[patch]: MongoDB vectorstore to return and accept string IDs (#23818)
The mongdb have some errors.
- `add_texts() -> List` returns a list of `ObjectId`, and not a list of
string
- `delete()` with `id` never remove chunks.

---------

Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
2024-07-03 14:14:08 -04:00
Jib
c0fcf76e93
LangChain-MongoDB: [Experimental] Driver-side index creation helper (#19359)
## Description
Created a helper method to make vector search indexes via client-side
pymongo.

**Recent Update** -- Removed error suppressing/overwriting layer in
favor of letting the original exception provide information.

## ToDo's
- [x] Make _wait_untils for integration test delete index
functionalities.
- [x] Add documentation for its use. Highlight it's experimental
- [x] Post Integration Test Results in a screenshot
- [x] Get review from MongoDB internal team (@shaneharvey, @blink1073 ,
@NoahStapp , @caseyclements)



- [x] **Add tests and docs**: If you're adding a new integration, please
include
1. Added new integration tests. Not eligible for unit testing since the
operation is Atlas Cloud specific.
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.

![image](https://github.com/langchain-ai/langchain/assets/2887713/a3fc8ee1-e04c-4976-accc-fea0eeae028a)


- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
2024-06-26 15:07:28 -04:00
Jib
f369495fa0
mongodb: [performance] Increase DEFAULT_INSERT_BATCH_SIZE to 100,000 and introduce sizing constraints (#19608) 2024-05-14 22:11:26 +00:00
Jib
a97473c846
mongodb[patch]: Make ObjectId JSON-serializable on generation (#21394) 2024-05-14 11:52:29 -07:00
Erick Friis
91a2ea5cd6
chroma, mongodb: fix docstrings (#21629) 2024-05-13 21:27:43 +00:00
Jib
866d6408af
mongodb[patch]: Remove embedding retrieval from mongodb payload (#19035)
## Description
Returning the embedding is not necessary in the vector search
functionality unless specified as a debugging step. This change defaults
the behavior such that the server _only_ returns the embedding key if
explicitly requested, such as in the case of
`max_marginal_relevance_search`.


- [x] **Add tests and docs**: If you're adding a new integration, please
include
* Added `test_from_documents_no_embedding_return`


- [x] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
2024-03-18 19:43:50 +00:00
Jib
72bfc1d3db
mongodb[minor]: MongoDB Partner Package -- Porting MongoDBAtlasVectorSearch (#17652)
This PR migrates the existing MongoDBAtlasVectorSearch abstraction from
the `langchain_community` section to the partners package section of the
codebase.
- [x] Run the partner package script as advised in the partner-packages
documentation.
- [x] Add Unit Tests
- [x] Migrate Integration Tests
- [x] Refactor `MongoDBAtlasVectorStore` (autogenerated) to
`MongoDBAtlasVectorSearch`
- [x] ~Remove~ deprecate the old `langchain_community` VectorStore
references.

## Additional Callouts
- Implemented the `delete` method
- Included any missing async function implementations
  - `amax_marginal_relevance_search_by_vector`
  - `adelete` 
- Added new Unit Tests that test for functionality of
`MongoDBVectorSearch` methods
- Removed [`del
res[self._embedding_key]`](e0c81e1cb0/libs/community/langchain_community/vectorstores/mongodb_atlas.py (L218))
in `_similarity_search_with_score` function as it would make the
`maximal_marginal_relevance` function fail otherwise. The `Document`
needs to store the embedding key in metadata to work.

Checklist:

- [x] PR title: Please title your PR "package: description", where
"package" is whichever of langchain, community, core, experimental, etc.
is being modified. Use "docs: ..." for purely docs changes, "templates:
..." for template changes, "infra: ..." for CI changes.
  - Example: "community: add foobar LLM"
- [x] PR message
- [x] Pass lint and test: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified to check that you're
passing lint and testing. See contribution guidelines for more
information on how to write/run tests, lint, etc:
https://python.langchain.com/docs/contributing/
- [x] Add tests and docs: If you're adding a new integration, please
include
1. Existing tests supplied in docs/docs do not change. Updated
docstrings for new functions like `delete`
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory. (This already exists)

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

---------

Co-authored-by: Steven Silvester <steven.silvester@ieee.org>
Co-authored-by: Erick Friis <erick@langchain.dev>
2024-02-29 23:09:48 +00:00