Thanks to @tullytim we have a new Kafka source and destination
connector. It also works with hosted Kafka via Confluent.
Documentation will be added to the Docs repo.
### Summary
Closes#2959. Updates the dependency and CI to add support for Python
3.12.
The MongoDB ingest tests were disabled due to jobs like [this
one](https://github.com/Unstructured-IO/unstructured/actions/runs/9133383127/job/25116767333)
failing due to issues with the `bson` package. `bson` is a dependency
for the AstraDB connector, but `pymongo` does not work when `bson` is
installed from `pip`. This issue is documented by MongoDB
[here](https://pymongo.readthedocs.io/en/stable/installation.html). Spun
off #3049 to resolve this. Issue seems unrelated to Python 3.12, though
unsure why this didn't surface previously.
Disables the `argilla` tests because `argilla` does not yet support
Python 3.12. We can add the `argilla` tests back in once the PR
references below is merged. You can still use the `stage_for_argilla`
function if you're on `python<3.12` and you install `argilla` yourself.
- https://github.com/argilla-io/argilla/pull/4837
---------
Co-authored-by: Nicolò Boschi <boschi1997@gmail.com>
Thanks to @mogith-pn from Clarifai we have a new destination connector!
This PR intends to add Clarifai as a ingest destination connector.
Access via CLI and programmatic.
Documentation and Examples.
Integration test script.
Thanks to Eric Hare @erichare at DataStax we have a new destination
connector.
This Pull Request implements an integration with [Astra
DB](https://datastax.com) which allows for the Astra DB Vector Database
to be compatible with Unstructured's set of integrations.
To create your Astra account and authenticate with your
`ASTRA_DB_APPLICATION_TOKEN`, and `ASTRA_DB_API_ENDPOINT`, follow these
steps:
1. Create an account at https://astra.datastax.com
2. Login and create a new database
3. From the database page, in the right hand panel, you will find your
API Endpoint
4. Beneath that, you can create a Token to be used
Some notes about Astra DB:
- Astra DB is a Vector Database which allows for high-performance
database transactions, and enables modern GenAI apps [See
here](https://docs.datastax.com/en/astra/astra-db-vector/get-started/concepts.html)
- It supports similarity search via a number of methods [See
here](https://docs.datastax.com/en/astra/astra-db-vector/get-started/concepts.html#metrics)
- It also supports non-vector tables / collections
This PR:
- Moves ingest dependencies into local scopes to be able to import
ingest connector classes without the need of installing imported
external dependencies. This allows lightweight use of the classes (not
the instances. to use the instances as intended you'll still need the
dependencies).
- Upgrades the embed module dependencies from `langchain` to
`langchain-community` module (to pass CI [rather than introducing a
pin])
- Does pip-compile
- Does minor refactors in other files to pass `ruff 2.0` checks which
were introduced by pip-compile
Thanks to Ofer at Vectara, we now have a Vectara destination connector.
- There are no dependencies since it is all REST calls to API
-
---------
Co-authored-by: potter-potter <david.potter@gmail.com>
Adds OpenSearch as a source and destination.
Since OpenSearch is a fork of Elasticsearch, these connectors rely
heavily on inheriting the Elasticsearch connectors whenever possible.
- Adds OpenSearch source connector to be able to ingest documents from
OpenSearch.
- Adds OpenSearch destination connector to be able to ingest documents
from any supported source, embed them and write the embeddings /
documents into OpenSearch.
- Defines an example unstructured elements schema for users to be able
to setup their unstructured OpenSearch indexes easily.
---------
Co-authored-by: potter-potter <david.potter@gmail.com>
- Adds a destination connector to upload processed output into a
PostgreSQL/Sqlite database instance.
- Users are responsible to provide their instances. This PR includes a
couple of configuration examples.
- Defines the scripts required to setup a PostgreSQL instance with the
unstructured elements schema.
- Validates postgres/pgvector embedding storage and retrieval
---------
Co-authored-by: potter-potter <david.potter@gmail.com>
This PR intends to add [Qdrant](https://qdrant.tech/) as a supported
ingestion destination.
- Implements CLI and programmatic usage.
- Documentation update
- Integration test script
---
Clone of #2315 to run with CI secrets
---------
Co-authored-by: Anush008 <anushshetty90@gmail.com>
Co-authored-by: Roman Isecke <136338424+rbiseck3@users.noreply.github.com>
Closes https://github.com/Unstructured-IO/unstructured/issues/1842
Closes https://github.com/Unstructured-IO/unstructured/issues/2202
Closes https://github.com/Unstructured-IO/unstructured/issues/2203
This PR:
- Adds Elasticsearch destination connector to be able to ingest
documents from any supported source, embed them and write the embeddings
/ documents into Elasticsearch.
- Defines an example unstructured elements schema for users to be able
to setup their unstructured elasticsearch indexes easily.
- Includes parallelized upload and lazy processing for elasticsearch
destination connector.
- Rearranges elasticsearch test helpers to source, destination, and
common folders.
- Adds util functions to be able to batch iterables in a lazy way for
uploads
- Fixes a bug where removing the optional parameter `--fields` broke the
connector due to an integer processing error.
- Fixes a bug where using an [elasticsearch
config](8fa5cbf036/unstructured/ingest/connector/elasticsearch.py (L26-L35))
for a destination connector resulted in a serialization issue when
optional parameter `--fields` was not provided.
Adds Chroma (also known as ChromaDB) as a vector destination.
Currently Chroma is an in-memory single-process oriented library with
plans of a hosted and/or more production ready solution
-https://docs.trychroma.com/deployment
Though they now claim to support multiple Clients hitting the database
at once, I found that it was inconsistent. Sometimes multiprocessing
worked (maybe 1 out of 3 times) But the other times I would get
different errors. So I kept it single process.
---------
Co-authored-by: potter-potter <david.potter@gmail.com>
### Description
Given all the shell files that now exist in the repo, would be nice to
have linting/formatting around them (in addition to the existing
shellcheck which doesn't do anything to format the shell code). This PR
introduces `shfmt` to both check for changes and apply formatting when
the associated make targets are called.
### Description
Building off of PR
https://github.com/Unstructured-IO/unstructured/pull/2179, updating
fsspec based connectors to use better authentication field handling.
This PR adds in the following changes:
* Update the base classes to inherit from the enhanced json mixin
* Add in a new access config dataclass that should be used as a nest
dataclass in the connector configs
* Update the code extracting configs out of the cli options dictionary
to support the nested access config if it exists on the parent config
* Update all fsspec connectors with explicit access configs given what
each one's SDKs support
* Update the json mixin and enhanced field to support a name override
when serializing/deserializing from json/dicts. This allows a different
name to be used for the CLI option than what the name of the field is on
the dataclass.
* Update all the writes to use class-based approach and share the same
structure of the runner classes
* Above update allowed for better code to be used in the base source and
destination CLI commands
* Add in utility code around paring a flat dictionary (coming from the
click based options) into dataclass-based configs with potentially
nested dataclasses.
**Slightly unrelated changes:**
* session handle removed from pinecone connector as this was breaking
the serialization of the write config and didn't have any benefit as a
connection was never being shared, the index used simply makes a new
http call each time it's invoked.
* Dedicated write configs were created for all destination connectors to
better support serialization
* Refactor of Elasticsearch connector included, with update to ingest
test to use auth
**TODOs**
* Left a `#TODO` in the code but the way session handler is implemented
right now, it breaks serialization since it adds a generic variable
based on the library being used for a connector (i.e.
`googleapiclient.discovery.Resource`) which is not serializable. This
will need to be updated to omit that from serialization but still
support the current workflow.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: rbiseck3 <rbiseck3@users.noreply.github.com>
Closes#1781.
- Adds a Weaviate destination connector
- The connector receives a host for the weaviate instance and a weaviate
class name.
- Defines a weaviate schema for json elements.
- Defines the pre-processing to conform unstructured's schema to the
proposed weaviate schema.
### Description
Often times there are tests being skipped either due to missing env vars
or explicitly defined in the base script but these get lost in the logs.
This PR updates the scripts to leverage a custom error code if being
skipped due to missing env vars and this custom error code is being
caught by the base script and logs all files being skipped to a file. At
the end of the script, this file gets logged in the CI output.
### Description
Update any use of OpenAI for generating embeddings in the ingest tests
to use Huggingface
**Bonus Changes:**
* Remove duplicate delta table test
* Delete delta table destination directory at the beginning of the test
to make sure it doesn't exist and prevent the test from breaking.
### Description
This adds the basic implementation of pushing the generated json output
of partition to mongodb. None of this code provisions the mondo db
instance so things like adding a search index around the embedding
content must be done by the user. Any sort of schema validation would
also have to take place via user-specific configuration on the database.
This update makes no assumptions about the configuration of the database
itself.
### Description
Update all destination tests to match pattern:
* Don't omit any metadata to check full schema
* Move azure cognitive dest test from src to dest
* Split delta table test into seperate src and dest tests
* Fix azure cognitive search and add to dest tests being run (wasn't
being run originally)
### Description
This splits the source ingest tests from the destination ingest tests
since they share a different pattern:
* src tests pull data from a source and compare the partitioned content
to the expected results
* destingation tests leverage the local connector to produce results to
push to a destination and leverages overhead to create temporary
locations at those destinations to write to and delete when done.
Only the src tests create partitioned content that needs to be checked
so the update ingest test CI job only needs to run these.
