3 Commits

Author SHA1 Message Date
Ahmet Melek
ca78dc737a
feat: extend ingest options to support multiple embedding modules, add deterministic ingest test for embeddings (#1918)
Closes #1782 

This PR:
- Extends ingest pipeline so that it is possible to select an embedding
provider from a range of providers
- Modifies the ingest embedding test to be a diff test, since the
embedding vectors are reproducible after supporting multiple providers

Additional info on the chosen provider for the test:
- Found `langchain.embeddings.HuggingFaceEmbeddings` to be deterministic
even when there's no seed set
- Took 6.84s to pass a unit test with the provider (without cache,
including model download)
- `langchain.embeddings.HuggingFaceEmbeddings` runs in local, making it
zero cost

For all these reasons, testing embedding modules with the Huggingface
model seems to be making sense

---------

Co-authored-by: cragwolfe <crag@unstructured.io>
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: ahmetmeleq <ahmetmeleq@users.noreply.github.com>
2023-11-06 12:26:12 +00:00
Mallori Harrell
00635744ed
feat: Adds local embedding model (#1619)
This PR adds a local embedding model option as an alternative to using
our OpenAI embedding brick. This brick uses LangChain's
HuggingFacEmbeddings.
2023-10-19 11:51:36 -05:00
ryannikolaidis
40523061ca
fix: _add_embeddings_to_elements bug resulting in duplicated elements (#1719)
Currently when the OpenAIEmbeddingEncoder adds embeddings to Elements in
`_add_embeddings_to_elements` it overwrites each Element's `to_dict`
method, mistakenly resulting in each Element having identical values
with the exception of the actual embedding value. This was due to the
way it leverages a nested `new_to_dict` method to overwrite. Instead,
this updates the original definition of Element itself to accommodate
the `embeddings` field when available. This also adds a test to validate
that values are not duplicated.
2023-10-12 21:47:32 +00:00