Removed the dependencies contained in `test.txt`, `dev.txt`, and
`constraints.txt` from the things that get installed in the docker
image. In order to keep testing the image (running the tests), I added a
step to the `docker-test` make target to install `test.txt` and
`dev.txt`. Thus we presumably get a smaller image (probably not much
smaller), reduce the dependency chain or our images, and have less
exposure to vulnerabilities while still testing as robustly as before.
Incidentally, I removed the `Dockerfile` for our ubuntu image, since it
made reference to non-existent make targets, which tells me it's stale
and wasn't being used.
### Review:
- Reviewer should ensure the dev and test dependencies are not being
installed in the docker image. One way to check is to check the logs in
CI, and note, e.g. that
[this](https://github.com/Unstructured-IO/unstructured/actions/runs/14112971425/job/39536304012#step:3:1700)
is the first reference to `pytest` in the docker build and test logs,
after the image build is completed.
- Reviewer should ensure docker image is still being tested in CI and is
passing.
This PR allows passing down both `ocr_agent` and `table_ocr_agent` as
parameters to specify the `OCRAgent` class for the page and tables, if
any, respectively. Both are default to using `tesseract`, consistent
with the present default behavior.
We used to rely on env variables to specify the agents but os env can be
changed during runtime outside of the caller's control. This method of
passing down the variables ensures that specification is independent of
env changes.
## testing
Using `example-docs/img/layout-parser-paper-with-table.jpg` and run
partition with two different settings. Note that this test requires
`paddleocr` extra.
```python
from unstructured.partition.auto import partition
from unstructured.partition.utils.constants import OCR_AGENT_TESSERACT, OCR_AGENT_PADDLE
elements = partition(f, strategy="hi_res", skip_infer_table_types=[], ocr_agent=OCR_AGENT_TESSERACT, table_ocr_agent=OCR_AGENT_PADDLE)
elements_alt = partition(f, strategy="hi_res", skip_infer_table_types=[], ocr_agent=OCR_AGENT_PADDLE, table_ocr_agent=OCR_AGENT_TESSERACT)
```
we should see both finish and slight differences in the table element's
text attribute.
## NOTE
`test_unstructured_ingest/expected-structured-output-html` contains all
test HTML fixtures. Original JSON files, from which these HTML fixtures
are generated, were taken from
`test_unstructured_ingest/expected-structured-output`
I noticed that `make tidy` wasn't working in my development environment.
This happens if you, a developer, forget to follow the specific
instructions in `README.md` and install exactly the right versions of
the necessary tools, including a *quite old* version of Ruff. This
version will nonetheless warn you:
warning: `ruff <path>` is deprecated. Use `ruff check <path>` instead.
So this fixes that, in order to future-proof and avoid confusion!
This PR refactors the data structure for `list[LayoutElement]` and
`list[TextRegion]` used in partition pdf/image files.
- new data structure replaces a list of objects with one object with
`numpy` array to store data
- this only affects partition internal steps and it doesn't change input
or output signature of `partition` function itself, i.e., `partition`
still returns `list[Element]`
- internally `list[LayoutElement]` -> `LayoutElements`;
`list[TextRegion]` -> `TextRegions`
- current refactor stops before clean up pdfminer elements inside
inferred layout elements -> the algorithm of clean up needs to be
refactored before the data structure refactor can move forward. So
current refactor converts the array data structure into list data
structure with `element_array.as_list()` call. This is the last step
before turning `list[LayoutElement]` into `list[Element]` as return
- a future PR will update this last step so that we build
`list[Element]` from `LayoutElements` data structure instead.
The goal of this PR is to replace the data structure as much as possible
without changing underlying logic. There are a few places where the
slicing or filtering logic was simple enough to be converted into vector
data structure operations. Those are refactored to be vector based. As a
result there is some small improvements observed in ingest test. This is
likely because the vector operations cleaned up some previous
inconsistency in data types and operations.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: badGarnet <badGarnet@users.noreply.github.com>
### Description
Alternative to https://github.com/Unstructured-IO/unstructured/pull/3572
but maintaining all ingest tests, running them by pulling in the latest
version of unstructured-ingest.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: rbiseck3 <rbiseck3@users.noreply.github.com>
Co-authored-by: Christine Straub <christinemstraub@gmail.com>
Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
**Summary**
In preparation for pluggable auto-partitioners simplify metadata as
discussed.
**Additional Context**
- Pluggable auto-partitioners requires partitioners to have a consistent
call signature. An arbitrary partitioner provided at runtime needs to
have a call signature that is known and consistent. Basically
`partition_x(filename, *, file, **kwargs)`.
- The current `auto.partition()` is highly coupled to each distinct
file-type partitioner, deciding which arguments to forward to each.
- This is driven by the existence of "delegating" partitioners, those
that convert their file-type and then call a second partitioner to do
the actual partitioning. Both the delegating and proxy partitioners are
decorated with metadata-post-processing decorators and those decorators
are not idempotent. We call the situation where those decorators would
run twice "double-decorating". For example, EPUB converts to HTML and
calls `partition_html()` and both `partition_epub()` and
`partition_html()` are decorated.
- The way double-decorating has been avoided in the past is to avoid
sending the arguments the metadata decorators are sensitive to to the
proxy partitioner. This is very obscure, complex to reason about,
error-prone, and just overall not a viable strategy. The better solution
is to not decorate delegating partitioners and let the proxy partitioner
handle all the metadata.
- This first step in preparation for that is part of simplifying the
metadata processing by removing unused or unwanted legacy parameters.
- `date_from_file_object` is a misnomer because a file-object never
contains last-modified data.
- It can never produce useful results in the API where last-modified
information must be provided by `metadata_last_modified`.
- It is an undocumented parameter so not in use.
- Using it can produce incorrect metadata.
This PR adds the requirement files for base and extras for the ingest
cache's hash key.
- The current workflow uses only the ingest requirements to generate
hash key for the gitaction cache
- Sometimes only base or extra requirements (like extra-pdf.txt) updated
but not any ingest requirements -> this would mean the ingest test would
fetch a cache with outdated non-ingest dependencies
- When we generate new ingest cache we actually do check first base and
extra requirements and generate a base env before layer on top the
ingest dependencies.
- This PR allows the ingest step to recognize changes to non-ingest
dependency changes and trigger new cache generation when either ingest
or base/extra requirement files changes.
This PR also bumps the setup python action version in cache actions; it
also adds installation of `virtualenv` for the ingest cache action to
avoid errors like
https://github.com/Unstructured-IO/unstructured/actions/runs/10905551870/job/30265057515?pr=3641#step:3:111
### Summary
Updates the file detection logic for OLE files to check the storage
content of the file to more reliable differentiate between DOC, PPT, XLS
and MSG files. This corrects a bug that caused file type detection to be
incorrect in cases where the `filetype` library guessed and incorrect
MIME type, such as `'application/vnd.ms-excel'` for a `.msg` file.
As part of this work, the `"msg"` extra was removed because the
`python-oxmsg` package is now a base dependency.
### Testing
Using a test `.msg` file that returns `'application/vnd.ms-excel'` from
`filetype.guess_mime`.
```python
from unstructured.file_utils.filetype import detect_filetype
filename = "test-file.msg"
detect_filetype(filename=filename) # result should be FileType.MSG
```
This PR reverts `pytesseract` dependency to `unstructured.pytesseract`
fork due to the unavailability of some recent release versions of
`pytesseract` on PyPI.
This PR also addresses an issue encountered during the publication of
`unstructured==0.15.4` to PyPI. The error was due to the fact that PyPI
does not allow direct dependencies from Version Control System URLs like
GitHub in the `install_requires` or `extras_require` sections of the
`setup.py` file.
### Summary
Addresses
[CVE-2024-39705](https://nvd.nist.gov/vuln/detail/CVE-2024-39705) by
updating to `nltk==3.8.2` and closes#3511. This CVE had previously been
mitigated in #3361.
---------
Co-authored-by: Christine Straub <christinemstraub@gmail.com>
This PR aims to remove "unstructured.paddlepaddle" fork. Previously, we
used `unstructured.paddlepaddle` fork to support
`unstructured.paddleocr` on arm64 architecture. But currently,
`unstructured.paddleocr` with `unstructured.paddlepaddle` fails to work
on `arm64` architecture. Also, `unstructured.paddleocr` with the latest
version of the original `paddlepaddle` works on both `amd64` and `arm64`
architectures.
### Testing
```
os.environ["OCR_AGENT"] = "unstructured.partition.utils.ocr_models.paddle_ocr.OCRAgentPaddle"
elements = partition_pdf(
filename=<file_path>,
strategy="hi_res",
infer_table_structure=True,
)
```
### Summary
Adds a CI check to ensure that packages added as dependencies are
appropriately licensed. All of the `.txt` files in the `requirements`
directory are checked with the exception of:
- `constraints.txt`, since those are not installed and are instead
conditions on the other dependency files
- `dev.txt`, since those are for local development and not shipped as
part of the `unstructured` package
- `extra-pdf-image.txt` - the `extra-pdf-image.in` since checking
`extra-pdf-image.txt` pulls in NVIDIA GPU related packages with an
`Other/Proprietary` license type, and there's not a good way to exclude
those without adding `Other/Proprietary` to the allowed licenses list.
### Testing
The new `check-licenses` job should pass in CI.
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**
Extract as much mechanical refactoring from the HTML parser change-over
into the PR as possible. This leaves the next PR focused on installing
the new parser and the ingest-test impact.
**Reviewers:** Commits are well groomed and reviewing commit-by-commit
is probably easier.
**Additional Context**
This PR introduces the rewritten HTML parser. Its general design is
recursive, consistent with the recursive structure of HTML (tree of
elements). It also adds the unit tests for that parser but it does not
_install_ the parser. So the behavior of `partition_html()` is unchanged
by this PR. The next PR in this series will do that and handle the
ingest and other unit test changes required to reflect the dozen or so
bug-fixes the new parser provides.
**Summary**
Clean `tests_unstructured/partition/test_html.py` in preparation for
broader refactor of HTML partitioner to follow. That refactor will
address a cluster of bugs.
Temporarily remove blank lines in tests so reordering tests in following
commit is easier to follow. Those will go back in after that.
**Summary**
`partition_msg()` previously used the `msg_parser` library for parsing
Outlook MSG email files (.msg files). The `msg_parser` library is
unmaintained and has several major shortcomings such as not being able
to parse MSG files with 8-bit encoded strings and not reliably
extracting attachments.
Use the new and permissively licenced `python-oxmsg` library instead.
**Additional Context**
For reviewability purposes, this PR temporarily places the new
`partition_msg()` implementation in `new_msg.py` and references that
implementation from `msg.py`. `new_msg.py` will be renamed to `msg.py`
in a closely following PR. This avoids a very messy interleaving of
hunks in a diff between the old and re-written `partition_msg()`
implementation.
Fixes#2481Fixes#3006
This PR changes two `python` commands in `Makefile` to use `python3` to
be consistent with other make commands. This makes it more explicit on
which python to use when the makefile is used outside of a controlled
virtualenv where only one python exists.
**Summary**
Some partitioner test modules are placed in directories by themselves or
with one other test module. This unnecessarily obscures where to find
the test module corresponding to a partitiner.
Move partitioner test modules to mirror the directory structure of
`unstructured/partition`.
### 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>
### Summary
Updates the `Dockerfile` to use the Chainguard `wolfi-base` image to
reduce CVEs. Also adds a step in the docker publish job that scans the
images and checks for CVEs before publishing. The job will fail if there
are high or critical vulnerabilities.
### Testing
Run `make docker-run-dev` and then `python3.11` once you're in. And that
point, you can try:
```python
from unstructured.partition.auto import partition
elements = partition(filename="example-docs/DA-1p.pdf", skip_infer_table_types=["pdf"])
elements
```
Stop the container once you're done.
**Reviewers:** Likely quicker to review commit-by-commit.
**Summary**
In preparation for adding a PPTX `Picture` shape _sub-partitioner_,
extract management of PPTX partitioning-run options to a separate
`_PptxPartitioningOptions` object similar to those used in chunking and
XLSX partitioning. This provides several benefits:
- Extract code dealing with applying defaults and computing derived
values from the main partitioning code, leaving it less cluttered and
focused on the partitioning algorithm itself.
- Allow the options set to be passed to helper objects, prominently
including sub-partitioners, without requiring a long list of parameters
or requiring the caller to couple itself to the particular option values
the helper object requires.
- Allow options behaviors to be thoroughly and efficiently tested in
isolation.
### Description
* The `consistent-deps.sh` was fixed to take into account the ingest
dependencies, causing some errors to show up. New constriants were added
to make that script pass.
* Update all requirements without constraint on pydantic, allowing the
latest version to be pulled in.
* `pikepdf` is causing a conflict but there's a fix on their `main`
branch, just need for the next release to be published. Opened up a
question here to see if we can get that out any sooner: [Do releases
happen on a
schedule?](https://github.com/pikepdf/pikepdf/discussions/574). For now
added `lxml<5` to the constraints.
A couple optimizations:
* `constraints.in` renamed to `constraints.txt` since the whole point is
all dependencies are already pinned and the file never gets compiled
* `constraints.txt` moved to a `requirements/deps` directory as this
never gets compiled by `pip-compile`
* Other dependency files updated to reference the new location of
`base.in` and `constraints.txt`
* make file updated since it was originally written to avoid the
`base.in` and `constraints.in` file
### Description
This PR resolved the following open issue:
[bug/bedrock-encoder-not-supported-in-ingest](https://github.com/Unstructured-IO/unstructured/issues/2319).
To do so, the following changes were made:
* All aws configs were added as input parameters to the CLI
* These were mapped to the bedrock embedder when an embedder is
generated via `get_embedder`
* An ingest test was added to call the aws bedrock service
* Requirements for boto were bumped because the first version to
introduce the bedrock runtime, which is required to hit the bedrock
service, was introduced in version `1.34.63`, which was ahead of the
version of boto pinned.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: rbiseck3 <rbiseck3@users.noreply.github.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.
**Summary**
Add `include_orig_elements: bool = True` as a new chunking option. This
PR does not implement _adding_ original elements to chunks, only
accepting this parameter as a chunking option and assigning `True` to it
as a default value when it is omitted as a keyword argument.
Note this will need to be added in other repositories as well in order
to fully support this new option by all access methods. In particular it
will need to be added in `unstructured-api` in order to become available
via the SDKs.
**Summary**
Some typing modernization in `elements.py` which will get changes to add
the `orig_elements` metadata field.
Also some additions to `unit_util.py` to enable simplified mocking that
will be required in the next PR.
### Description
Currently the requirements associated with an extra in the `setup.py` is
being dynamically generated using the `load_requirements()` method in
the same file. This is being passed in all the `.in` files which then
get read line by line to generate the requirements associated with an
extra. Unless the `.in` file itself has a version pin, this will never
respect the `.txt` files being generated by `pip-compile`. This fix
updates all the inputs to `load_requirements()` to use the `.txt` files
themselves.
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
I accidentally added Vectara to setup and makefile. But there are no
dependencies for Vectara
This removes Vectara from those files.
---------
Co-authored-by: potter-potter <david.potter@gmail.com>
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>
### Description
This adds in a destination connector to write content to the Databricks
Unity Catalog Volumes service. Currently there is an internal account
that can be used for testing manually but there is not dedicated account
to use for testing so this is not being added to the automated ingest
tests that get run in the CI.
To test locally:
```shell
#!/usr/bin/env bash
path="testpath/$(uuidgen)"
PYTHONPATH=. python ./unstructured/ingest/main.py local \
--num-processes 4 \
--output-dir azure-test \
--strategy fast \
--verbose \
--input-path example-docs/fake-memo.pdf \
--recursive \
databricks-volumes \
--catalog "utic-dev-tech-fixtures" \
--volume "small-pdf-set" \
--volume-path "$path" \
--username "$DATABRICKS_USERNAME" \
--password "$DATABRICKS_PASSWORD" \
--host "$DATABRICKS_HOST"
```
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>
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.
Adds source connector for SFTP which uses fsspec and paramiko via
fsspec. Paramiko is the standard sftp package for python used in pysftp
etc...
```
--username foo \
--password bar \
--remote-url sftp://localhost:47474/upload/
```
Will only download a specifically requested file if it has an extension.
(i.e. `--remote-url sftp://localhost:47474/upload/bob.zip`) It will
treat any other remote_url as a folder path. This is intentional.
---------
Co-authored-by: potter-potter <david.potter@gmail.com>
