### Summary
Update `ocr_only` strategy in `partition_pdf()`. This PR adds the
functionality to get accurate coordinate data when partitioning PDFs and
Images with the `ocr_only` strategy.
- Add functionality to perform OCR region grouping based on the OCR text
taken from `pytesseract.image_to_string()`
- Add functionality to get layout elements from OCR regions (ocr_layout)
for both `tesseract` and `paddle`
- Add functionality to determine the `source` of merged text regions
when merging text regions in `merge_text_regions()`
- Merge multiple test functions related to "ocr_only" strategy into
`test_partition_pdf_with_ocr_only_strategy()`
- This PR also fixes [issue
#1792](https://github.com/Unstructured-IO/unstructured/issues/1792)
### Evaluation
```
# Image
PYTHONPATH=. python examples/custom-layout-order/evaluate_natural_reading_order.py example-docs/double-column-A.jpg ocr_only xy-cut image
# PDF
PYTHONPATH=. python examples/custom-layout-order/evaluate_natural_reading_order.py example-docs/multi-column-2p.pdf ocr_only xy-cut pdf
```
### Test
- **Before update**
All elements have the same coordinate data
- **After update**
All elements have accurate coordinate data
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
This PR introduces `clean_pdfminer_inner_elements` , which deletes
pdfminer elements inside other detection origins such as YoloX or
detectron.
This function returns the clean document.
Also, the ingest-test fixtures were updated to reflect the new standard
output.
The best way to check that this function is working properly is check
the new test `test_clean_pdfminer_inner_elements` in
`test_unstructured/partition/utils/test_processing_elements.py`
---------
Co-authored-by: Roman Isecke <roman@unstructured.io>
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: rbiseck3 <rbiseck3@users.noreply.github.com>
Co-authored-by: Roman Isecke <136338424+rbiseck3@users.noreply.github.com>
### Description
* If the contents of a doc were updated by the process of
reading/downloading it, this was not being persisted. To fix this, the
data being passed around was updated to use a multiprocessing safe dict
rather than the json string. Now that dict is updated after the
`get_file` method is called.
* Wikipedia connector was updated to use a static filename rather than
one requiring a call to fetch data.
* The read config param `re_download` was not being leveraged by the
source node, this was fixed.
* Added fix: chunking and embedding order reversed so chunking runs
before embeddings
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: rbiseck3 <rbiseck3@users.noreply.github.com>
### Summary
A follow up ticket on
https://github.com/Unstructured-IO/unstructured/pull/1801, I forgot to
remove the lines that pass extract_tables to inference, and noted the
table regression if we only do one OCR for entire doc
**Tech details:**
* stop passing `extract_tables` parameter to inference
* added table extraction ingest test for image, which was skipped
before, and the "text_as_html" field contains the OCR output from the
table OCR refactor PR
* replaced `assert_called_once_with` with `call_args` so that the unit
tests don't need to test additional parameters
* added `error_margin` as ENV when comparing bounding boxes
of`ocr_region` with `table_element`
* added more tests for tables and noted the table regression in test for
partition pdf
### Test
* for stop passing `extract_tables` parameter to inference, run test
`test_partition_pdf_hi_res_ocr_mode_with_table_extraction` before this
branch and you will see warning like `Table OCR from get_tokens method
will be deprecated....`, which means it called the table OCR in
inference repo. This branch removed the warning.
Carrying `skip_infer_table_types` to `infer_table_structure` in
partition flow. Now PPT/X, DOC/X, etc. Table elements should not have a
`text_as_html` field.
Note: I've continued to exclude this var from partitioners that go
through html flow, I think if we've already got the html it doesn't make
sense to carry the infer variable along, since we're not 'infer-ing' the
html table in these cases.
TODO:
✅ add unit tests
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: amanda103 <amanda103@users.noreply.github.com>
**Executive Summary**
This PR adds the evaluation metrics to our current workflow. It verifies
the flow that when the code is pushed, the code will gets evaluate
against our gold standard and output into `.tsv` file.
**Technical Details**
- Adds evaluation metrics to the test-ingest workflow
- Make use of `structured-output` from `test-ingest` and compare to the
gold-standard uploaded in s3, and download into local when make
comparison. The current folder in-use is
`s3://utic-dev-tech-fixtures/small-cct`. This dir is editable in the
shell script.
- With this PR, only one file from one connector is use to compare.
**Misc**
- Not many overlapped files between test-ingest and gold-standard. More
files will be added.
**Outputs**
2 `.tsv` files are saved under `test_unstructured_ingest/metrics/`.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: Klaijan <Klaijan@users.noreply.github.com>
### Description
* Priority of this was to fix deserialization of ingest docs. Currently
the source metadata wasn't being persisted
* To help debug this, source metadata was added to the local ingest doc
as well.
* Unit test added to make sure the metadata itself was persisted.
* As part of serialization, it was forcing docs to fetch source metadata
if it hadn't already to add to the generated dict/json. This shouldn't
have happened if the underlying variable `_source_metadata` was `None`.
This way the doc can be serialized without any calls being made.
* Serialization was moved to the `to_dict` method to make it more
universal.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: rbiseck3 <rbiseck3@users.noreply.github.com>
### Description
Given that many of the options associated with the `Click` based cli
ingest commands are added dynamically from a number of configs, a check
was incorporated to make sure there were no duplicate entries to prevent
new configs from overwriting already added options.
### Issues that were found and fixes:
* duplicate api-key option set on Notion command conflicts with api key
used for unstructured api. Added notion prefix.
* retry logic configs had duplicates in biomed. Removed since this is
not handled by the pipeline.
**Executive Summary.** Introducing strict type-checking as preparation
for adding the chunk-overlap feature revealed a type mismatch for
regex-metadata between chunking tests and the (authoritative)
ElementMetadata definition. The implementation of regex-metadata aspects
of chunking passed the tests but did not produce the appropriate
behaviors in production where the actual data-structure was different.
This PR fixes these two bugs.
1. **Over-chunking.** The presence of `regex-metadata` in an element was
incorrectly being interpreted as a semantic boundary, leading to such
elements being isolated in their own chunks.
2. **Discarded regex-metadata.** regex-metadata present on the second or
later elements in a section (chunk) was discarded.
**Technical Summary**
The type of `ElementMetadata.regex_metadata` is `Dict[str,
List[RegexMetadata]]`. `RegexMetadata` is a `TypedDict` like `{"text":
"this matched", "start": 7, "end": 19}`.
Multiple regexes can be specified, each with a name like "mail-stop",
"version", etc. Each of those may produce its own set of matches, like:
```python
>>> element.regex_metadata
{
"mail-stop": [{"text": "MS-107", "start": 18, "end": 24}],
"version": [
{"text": "current: v1.7.2", "start": 7, "end": 21},
{"text": "supersedes: v1.7.0", "start": 22, "end": 40},
],
}
```
*Forensic analysis*
* The regex-metadata feature was added by Matt Robinson on 06/16/2023
commit: 4ea71683. The regex_metadata data structure is the same as when
it was added.
* The chunk-by-title feature was added by Matt Robinson on 08/29/2023
commit: f6a745a7. The mistaken regex-metadata data structure in the
tests is present in that commit.
Looks to me like a mis-remembering of the regex-metadata data-structure
and insufficient type-checking rigor (type-checker strictness level set
too low) to warn of the mistake.
**Over-chunking Behavior**
The over-chunking looked like this:
Chunking three elements with regex metadata should combine them into a
single chunk (`CompositeElement` object), subject to maximum size rules
(default 500 chars).
```python
elements: List[Element] = [
Title(
"Lorem Ipsum",
metadata=ElementMetadata(
regex_metadata={"ipsum": [RegexMetadata(text="Ipsum", start=6, end=11)]}
),
),
Text(
"Lorem ipsum dolor sit amet consectetur adipiscing elit.",
metadata=ElementMetadata(
regex_metadata={"dolor": [RegexMetadata(text="dolor", start=12, end=17)]}
),
),
Text(
"In rhoncus ipsum sed lectus porta volutpat.",
metadata=ElementMetadata(
regex_metadata={"ipsum": [RegexMetadata(text="ipsum", start=11, end=16)]}
),
),
]
chunks = chunk_by_title(elements)
assert chunks == [
CompositeElement(
"Lorem Ipsum\n\nLorem ipsum dolor sit amet consectetur adipiscing elit.\n\nIn rhoncus"
" ipsum sed lectus porta volutpat."
)
]
```
Observed behavior looked like this:
```python
chunks => [
CompositeElement('Lorem Ipsum')
CompositeElement('Lorem ipsum dolor sit amet consectetur adipiscing elit.')
CompositeElement('In rhoncus ipsum sed lectus porta volutpat.')
]
```
The fix changed the approach from breaking on any metadata field not in
a specified group (`regex_metadata` was missing from this group) to only
breaking on specified fields (whitelisting instead of blacklisting).
This avoids overchunking every time we add a new metadata field and is
also simpler and easier to understand. This change in approach is
discussed in more detail here #1790.
**Dropping regex-metadata Behavior**
Chunking this section:
```python
elements: List[Element] = [
Title(
"Lorem Ipsum",
metadata=ElementMetadata(
regex_metadata={"ipsum": [RegexMetadata(text="Ipsum", start=6, end=11)]}
),
),
Text(
"Lorem ipsum dolor sit amet consectetur adipiscing elit.",
metadata=ElementMetadata(
regex_metadata={
"dolor": [RegexMetadata(text="dolor", start=12, end=17)],
"ipsum": [RegexMetadata(text="ipsum", start=6, end=11)],
}
),
),
Text(
"In rhoncus ipsum sed lectus porta volutpat.",
metadata=ElementMetadata(
regex_metadata={"ipsum": [RegexMetadata(text="ipsum", start=11, end=16)]}
),
),
]
```
..should produce this regex_metadata on the single produced chunk:
```python
assert chunk == CompositeElement(
"Lorem Ipsum\n\nLorem ipsum dolor sit amet consectetur adipiscing elit.\n\nIn rhoncus"
" ipsum sed lectus porta volutpat."
)
assert chunk.metadata.regex_metadata == {
"dolor": [RegexMetadata(text="dolor", start=25, end=30)],
"ipsum": [
RegexMetadata(text="Ipsum", start=6, end=11),
RegexMetadata(text="ipsum", start=19, end=24),
RegexMetadata(text="ipsum", start=81, end=86),
],
}
```
but instead produced this:
```python
regex_metadata == {"ipsum": [{"text": "Ipsum", "start": 6, "end": 11}]}
```
Which is the regex-metadata from the first element only.
The fix was to remove the consolidation+adjustment process from inside
the "list-attribute-processing" loop (because regex-metadata is not a
list) and process regex metadata separately.
This pull request includes updated ingest test fixtures.
Please review and merge if appropriate.
Co-authored-by: benjats07 <benjats07@users.noreply.github.com>
### Description
Pivot from using the retry logic as a decorator as this posed too many
limitations on what can be passed in as a parameter at runtime. Moved
this to be a class approach and now that can be instantiated with
appropriate loggers leveraging the `--verbose` flag to set the log
level. This also mitigates how much new code is being forked from the
backoff library. The existing notion client that was using the previous
decorator has been refactored to use the new class approach and the
airtable connector was updated to support retry logic as well. Default
log handlers were introduced which applies to all instances of the retry
handler when it starts, backs off, and gives up.
A generic approach was added to configuring the retry parameters in the
CLI and was added to the running number of common configs across all CLI
commands.
Omitted CHANGELOG entry as this is mostly just a refactor of the retry
code. All other connectors will be updated to support retry in another
PR but this helps limit the number of changes to review in this one.
### Extra fixes
* Updated local and salesforce source connector to set `ingest_doc_cls`
in a `__post_init__` method since this variable can't be serialized.
### Testing
Both the airtable and notion ingest tests can be run locally. While they
might not pass due to text changes (to be expected when running
locally), the process can be viewed in the logs to validate.
Associated issue: #1488
### Summary
Some `OCR` elements with only spaces in the text have full-page width in
the bounding box, which causes the `xycut` sorting to not work as
expected. Now the logic to parse OCR results removes any elements with
only spaces (more than one space).
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
The current code assumes the first line of csv and tsv files are a
header line. Most csv and tsv files don't have a header line, and even
for those that do, dropping this line may not be the desired behavior.
Here is a snippet of code that demonstrates the current behavior and the
proposed fix
```
import pandas as pd
from lxml.html.soupparser import fromstring as soupparser_fromstring
c1 = """
Stanley Cups,,
Team,Location,Stanley Cups
Blues,STL,1
Flyers,PHI,2
Maple Leafs,TOR,13
"""
f = "./test.csv"
with open(f, 'w') as ff:
ff.write(c1)
print("Suggested Improvement Keep First Line")
table = pd.read_csv(f, header=None)
html_text = table.to_html(index=False, header=False, na_rep="")
text = soupparser_fromstring(html_text).text_content()
print(text)
print("\n\nOriginal Looses First Line")
table = pd.read_csv(f)
html_text = table.to_html(index=False, header=False, na_rep="")
text = soupparser_fromstring(html_text).text_content()
print(text)
```
---------
Co-authored-by: cragwolfe <crag@unstructured.io>
Co-authored-by: Yao You <theyaoyou@gmail.com>
Co-authored-by: Yao You <yao@unstructured.io>
### Summary
Closes#1714
Changes the default value for `languages` to `None` for elements that
don't have text or the language can't be detected.
### Testing
```
from unstructured.partition.auto import partition
filename = "example-docs/handbook-1p.docx"
elements = partition(filename=filename, detect_language_per_element=True)
# PageBreak elements don't have text and will be collected here
none_langs = [element for element in elements if element.metadata.languages is None]
none_langs[0].text
```
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: Coniferish <Coniferish@users.noreply.github.com>
Co-authored-by: cragwolfe <crag@unstructured.io>
PR to support schema changes introduced from [PR
232](https://github.com/Unstructured-IO/unstructured-inference/pull/232)
in `unstructured-inference`.
Specifically what needs to be supported is:
* Change to the way `LayoutElement` from `unstructured-inference` is
structured, specifically that this class is no longer a subclass of
`Rectangle`, and instead `LayoutElement` has a `bbox` property that
captures the location information and a `from_coords` method that allows
construction of a `LayoutElement` directly from coordinates.
* Removal of `LocationlessLayoutElement` since chipper now exports
bounding boxes, and if we need to support elements without bounding
boxes, we can make the `bbox` property mentioned above optional.
* Getting hierarchy data directly from the inference elements rather
than in post-processing
* Don't try to reorder elements received from chipper v2, as they should
already be ordered.
#### Testing:
The following demonstrates that the new version of chipper is inferring
hierarchy.
```python
from unstructured.partition.pdf import partition_pdf
elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res", model_name="chipper")
children = [el for el in elements if el.metadata.parent_id is not None]
print(children)
```
Also verify that running the traditional `hi_res` gives different
results:
```python
from unstructured.partition.pdf import partition_pdf
elements = partition_pdf("example-docs/layout-parser-paper-fast.pdf", strategy="hi_res")
```
---------
Co-authored-by: Sebastian Laverde Alfonso <lavmlk20201@gmail.com>
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: christinestraub <christinemstraub@gmail.com>
This PR:
- defines rbac_data as a SourceMetadata field,
- manages connections to an external api for obtaining rbac data with
ConnectorRBAC class,
- serializes rbac data and saves it to the disk,
- matches the rbac_data in the disk to each IngestDoc, using a common
field,
- forwards rbac data to Elements, via the partition() function
To test the changes, run `examples/ingest/sharepoint/ingest.sh` with the
relevant rbac & connector credentials
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: ahmetmeleq <ahmetmeleq@users.noreply.github.com>
Currently adding the embedding flag to any unstructured-ingest call
results in this failure:
```
2023-10-11 22:42:14,177 MainProcess ERROR 'b8a98c5d963a9dd75847a8f110cbf7c9'
multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
File "/Users/ryannikolaidis/.pyenv/versions/3.10.11/lib/python3.10/multiprocessing/pool.py", line 125, in worker
result = (True, func(*args, **kwds))
File "/Users/ryannikolaidis/.pyenv/versions/3.10.11/lib/python3.10/multiprocessing/pool.py", line 48, in mapstar
return list(map(*args))
File "/Users/ryannikolaidis/Development/unstructured/unstructured/unstructured/ingest/pipeline/copy.py", line 14, in run
ingest_doc_json = self.pipeline_context.ingest_docs_map[doc_hash]
File "<string>", line 2, in __getitem__
File "/Users/ryannikolaidis/.pyenv/versions/3.10.11/lib/python3.10/multiprocessing/managers.py", line 833, in _callmethod
raise convert_to_error(kind, result)
KeyError: 'b8a98c5d963a9dd75847a8f110cbf7c9'
"""
```
This is because the run method for the embedding node is not adding the
IngestDoc to the context map. This PR adds that logic and adds a test to
validate that the embeddings option works as expected.
NOTE: until https://github.com/Unstructured-IO/unstructured/pull/1719
goes in, the expected results include the duplicate element bug, however
currently this does at least prove that embeddings are generated and the
function doesn't error.
### Description
Set language to None by default. Update ingest test to use local file
used in language unit tests to validate.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: rbiseck3 <rbiseck3@users.noreply.github.com>
### Description
Add new parameter to map to `skip_infer_table_types` partition arg.
Applies to partition config which is set on all connectors.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: rbiseck3 <rbiseck3@users.noreply.github.com>
The current implementation removes elements from the beginning of the
element list and duplicates the list items
---------
Co-authored-by: Klaijan <klaijan@unstructured.io>
Co-authored-by: yuming <305248291@qq.com>
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: yuming-long <yuming-long@users.noreply.github.com>
### Summary
Closes#1534 and #1535
Detects document language using `langdetect` package.
Creates new kwargs for user to set the document language (`languages`)
or detect the language at the element level instead of the default
document level (`detect_language_per_element`)
---------
Co-authored-by: shreyanid <42684285+shreyanid@users.noreply.github.com>
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: Coniferish <Coniferish@users.noreply.github.com>
Co-authored-by: cragwolfe <crag@unstructured.io>
Co-authored-by: Austin Walker <austin@unstructured.io>
Adds data source properties to git connectors:
- data_created
- date_modified
- version
- record_locator
These properties are instantiated when supported by the connector.
Separates the logic between fetching the file from source and
`get_file`. Retrieves file metadata when any of the properties are
called.
Adds logic to check if file exists in the remote source. For connectors
that don't directly support it, adds exception handling to check any
issues while retrieving the file.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: rvztz <rvztz@users.noreply.github.com>
### Description
In order to add a retry strategy to the notion http calls, leveraging a
generic backoff library with some tweaks to pass in values from the CLI.
We’re probably unfairly (to the test) making a large volume of new
connections and requests to test services when all of our ingest tests
run across the full python test matrix and when a lot of PRs a firing at
once. Lets limit the full matrix run to a select few, but still have all
ingest tests run on python v3.10. This is done by checking the version
and skipping in ingest-test.sh.
Bonus: Bumps ingest test fixture workflow to use 3.10. This technically
shouldn't make a difference, but since we're making 3.10 the default of
the matrix strategy, it probably makes sense to use 3.10 for the ingest
fixture generation as well for consistency.
## Testing
-
[example](https://github.com/Unstructured-IO/unstructured/actions/runs/6460319121/job/17537900978?pr=1687)
running all tests in 3.10
-
[example](https://github.com/Unstructured-IO/unstructured/actions/runs/6460319121/job/17537899999?pr=1687)
skipping/running the expected tests in 3.8
When running test-ingest test fixtures locally (but not in CI), keep
output .json's and other workdir artifacts around for the convenience of
debugging.
**Test Instructions**
Run
bash -x ./test_unstructured_ingest/test-ingest-azure.sh
and witness output .json's are visible. Yay! Now, to instead clean up
output .json's and workdir, run:
UNSTRUCTURED_CLEANUP_DEV_FIXTURES=1 bash -x
./test_unstructured_ingest/test-ingest-azure.sh
and witness the files have been cleaned up. Yay!
## Summary
Second part of OCR refactor to move it from inference repo to
unstructured repo, first part is done in
https://github.com/Unstructured-IO/unstructured-inference/pull/231. This
PR adds OCR process logics to entire page OCR, and support two OCR
modes, "entire_page" or "individual_blocks".
The updated workflow for `Hi_res` partition:
* pass the document as data/filename to inference repo to get
`inferred_layout` (DocumentLayout)
* pass the document as data/filename to OCR module, which first open the
document (create temp file/dir as needed), and split the document by
pages (convert PDF pages to image pages for PDF file)
* if ocr mode is `"entire_page"`
* OCR the entire image
* merge the OCR layout with inferred page layout
* if ocr mode is `"individual_blocks"`
* from inferred page layout, find element with no extracted text, crop
the entire image by the bboxes of the element
* replace empty text element with the text obtained from OCR the cropped
image
* return all merged PageLayouts and form a DocumentLayout subject for
later on process
This PR also bump `unstructured-inference==0.7.2` since the branch relay
on OCR refactor from unstructured-inference.
## Test
```
from unstructured.partition.auto import partition
entrie_page_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="entire_page", ocr_languages="eng+kor", strategy="hi_res")
individual_blocks_ocr_mode_elements = partition(filename="example-docs/english-and-korean.png", ocr_mode="individual_blocks", ocr_languages="eng+kor", strategy="hi_res")
print([el.text for el in entrie_page_ocr_mode_elements])
print([el.text for el in individual_blocks_ocr_mode_elements])
```
latest output:
```
# entrie_page
['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'accounts.', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASUREWH HARUTOM|2] 팬 입니다. 팬 으 로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 불 공 평 함 을 LRU, 이 일 을 통해 저 희 의 의 혹 을 전 달 하여 귀 사 의 진지한 민 과 적극적인 답 변 을 받을 수 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were', 'successfully sent', '4. Use the hashtag of Haruto on your tweet to show that vou have sent vour email]', '메 고']
# individual_blocks
['RULES AND INSTRUCTIONS 1. Template for day 1 (korean) , for day 2 (English) for day 3 both English and korean. 2. Use all your accounts. use different emails to send. Its better to have many email', 'Note: Remember to write your own "OPENING MESSAGE" before you copy and paste the template. please always include [TREASURE HARUTO] for example:', '안녕하세요, 저 희 는 YGEAS 그룹 TREASURES HARUTOM| 2] 팬 입니다. 팬 으로서, HARUTO 씨 받 는 대 우 에 대해 의 구 심 과 habe ERO, 이 머 일 을 적극 저 희 의 ASS 전 달 하여 귀 사 의 진지한 고 2 있 기 를 바랍니다.', '3. CC Harutonations@gmail.com so we can keep track of how many emails were ciiccecefisliy cant', 'VULLESSIULY Set 4. Use the hashtag of Haruto on your tweet to show that you have sent your email']
```
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: yuming-long <yuming-long@users.noreply.github.com>
Co-authored-by: christinestraub <christinemstraub@gmail.com>
Co-authored-by: christinestraub <christinestraub@users.noreply.github.com>
### Description
As we add more and more steps to the pipeline (i.e. chunking, embedding,
table manipulation), it would help seperate the responsibility of each
of these into their own processes, running each in parallel using json
files to share data across. This will also help guarantee data is
serializable if this code was used in an actual pipeline. Following is a
flow diagram of the proposed changes. As part of this change:
* A parent pipeline class will be responsible for running each `node`,
which can optionally be run via multiprocessing if it supports it, or
not. Possible nodes at this moment:
* Doc factory: creates all the ingest docs via the source connector
* Source: reads/downloads all of the content to process to the local
filesystem to the location set by the `download_dir` parameter.
* Partition: runs partition on all of the downloaded content in json
format.
* Any number of reformat nodes that modify the partitioned content. This
can include chunking, embedding, etc.
* Write: push the final json into the destination via the destination
connector
* This pipeline relies on the information of the ingest docs to be
available via their serialization. An optimization was introduced with
the `IngestDocJsonMixin` which adds in all the `@property` fields to the
serialized json already being created via the `DataClassJsonMixin`
* For all intermediate steps (partitioning, reformatting), the content
is saved to a dedicated location on the local filesystem. Right now it's
set to `$HOME/.cache/unstructured/ingest/pipeline/STEP_NAME/`.
* Minor changes: made sense to move some of the config parameters
between the read and partition configs when I explicitly divided the
responsibility to download vs partition the content in the pipeline.
* The pipeline class only makes the doc factory, source and partition
nodes required, keeping with the logic that has been supported so far.
All reformatting nodes and write node are optional.
* Long term, there should also be some changes to the base configs
supported by the CLI to support pipeline specific configs, but for now
what exists was used to minimize changes in this PR.
* Final step to copy the final output to the location designated by the
`_output_filename` value of the ingest doc.
* Hashing occurs at each step by hashing the parameters of that step
(i.e. partition configs) along with the previous step via the filename
used. This allows each step to be the same _if_ all the parameters for
it have not changed and the content so far is the same.
* The only data that is shared and has writes to across processes is the
dictionary of ingest json data. This dict is created using the
`multiprocessing.manager.DictProxy` to make sure any interaction with it
is behind a lock.
### Minor refactors included:
* Utility methods added to extract configs from the click options
* Utility method to add common options to click commands.
* All writers moved to using the class approach which extracts a lot of
the common code so there's less copy-paste when new runners are added.
* Use `@property` for source metadata on base ingest doc to add logic to
call `update_source_metadata` if it's still `None` at the time it's
fetched.
### Additional bug fixes included
* Fsspec connectors were not serializable due to the `ingest_doc_cls`.
This was removed from the fields captured by the `@dataclass` decorator
and added in a `__post_init__` method.
* Various reddit connector params were missing. This doesn't have an
explicit ingest test at the moment so was never caught.
* Fsspec connector had the parent `update_source_metadata` misnamed as
`update_source_metadata_metadata` so it was never being called.
### Flow Diagram
Closes#1573.
### Summary
- update `shrink_bbox()` to keep top left rather than center
### Evaluation
Run the following command for this
[PDF](https://utic-dev-tech-fixtures.s3.us-east-2.amazonaws.com/pastebin/patent-11723901-page2.pdf).
```
PYTHONPATH=. python examples/custom-layout-order/evaluate_xy_cut_sorting.py <file_path> <strategy>
```
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
### Description
Exposes the endpoint url as an access kwarg when using the s3 filesystem
library via the fsspec abstraction. This allows for any non-aws data
providers that support the s3 protocol to be used with the s3 connector
(i.e. minio)
Closes out https://github.com/Unstructured-IO/unstructured/issues/950
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: rbiseck3 <rbiseck3@users.noreply.github.com>
- bump `unstructured-inference` to `0.6.6`
- specify default model name for element detection to be
`detectron2_onnx` to keep current behavior
- NOTE: the updated inference package by default would use yolox as
element detection model; this will be evaluated and enabled in a
separated PR
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: badGarnet <badGarnet@users.noreply.github.com>
Occasionally the es test can fail because the index fail to be created
on the first try. Experiments show adding timeout doesn't help but add
retry mitigates the issue. See history of commits in branch:
yao/bump-inference-to-0.6.6
https://github.com/Unstructured-IO/unstructured/pull/1563
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
Co-authored-by: badGarnet <badGarnet@users.noreply.github.com>
Fixes
docker exec unstructured-smoke-test /bin/bash -c
/home/notebook-user/test_unstructured_ingest/test-ingest-wikipedia.sh
/home/notebook-user/test_unstructured_ingest/test-ingest-wikipedia.sh:
line 10: python: command not found
in
https://github.com/Unstructured-IO/unstructured/blob/6ad4971/scripts/docker-smoke-test.sh#L43
that was preventing docker images from being built.
Closes GH Issue #1233.
### Summary
- add functionality to shrink all bounding boxes along x and y axes
(still centered around the same center point) before running xy-cut sort
### Evaluation
Run the followin gcommand for this
[PDF](https://utic-dev-tech-fixtures.s3.us-east-2.amazonaws.com/pastebin/patent-11723901-page2.pdf).
PYTHONPATH=. python examples/custom-layout-order/evaluate_xy_cut_sorting.py <file_path> <strategy>
- resolves an issue where occasionally deltalake writer results in
SIGABRT event though the writer finished writing table properly on linux
- this is first observed in ingest test
- Putting the writer into a process mitigates this problem by forcing
python to finish the deltalake rust backend to finish its tasks
## test
To test this it is best to setup an instance on a Linux system since the
problem has only been observed on Linux so far. Run
```bash
PYTHONPATH=. ./unstructured/ingest/main.py delta-table --num-processes 2 --metadata-exclude coordinates,filename,file_directory,metadata.data_source.date_processed,metadata.last_modified,metadata.date_created,metadata.detection_class_prob,metadata.parent_id,metadata.category_depth --table-uri ../tables/delta/ --preserve-downloads --verbose delta-table --write-column json_data --mode overwrite --table-uri file:///tmp/delta
```
Without this fix occasionally we'd encounter `SIGABTR`.
---------
Co-authored-by: ryannikolaidis <1208590+ryannikolaidis@users.noreply.github.com>
