Metadata-Version: 2.1
Name: marie-ai
Version: 3.0.26
Summary: Python library to Integrate AI-powered features into your applications
Home-page: https://github.com/marieai/marie-ai/
Download-URL: https://github.com/marieai/marie-ai/tags
Author: Marie AI
Author-email: hello@marieai.co
License: Apache 2.0
Project-URL: Documentation, https://docs.marieai.co
Project-URL: Source, https://github.com/marieai/marie-ai.git
Project-URL: Tracker, https://github.com/marieai/marie-ai/issues
Keywords: marie-ai ocr icr index elastic neural-network encoding embedding serving docker container image video audio deep-learning mlops
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Unix Shell
Classifier: Environment :: Console
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Database :: Database Engines/Servers
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Internet :: WWW/HTTP :: Indexing/Search
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Multimedia :: Video
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
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Provides-Extra: standard
Provides-Extra: core
Provides-Extra: numpy
Provides-Extra: protobuf
Provides-Extra: grpcio
Provides-Extra: grpcio-reflection
Provides-Extra: grpcio-health-checking
Provides-Extra: pyyaml
Provides-Extra: packaging
Provides-Extra: docarray
Provides-Extra: perf
Provides-Extra: prometheus_client
Provides-Extra: devel
Provides-Extra: psutil
Provides-Extra: uvloop
Provides-Extra: opentelemetry-instrumentation-grpc
Provides-Extra: opentelemetry-sdk
Provides-Extra: opentelemetry-exporter-otlp
Provides-Extra: opentelemetry-exporter-prometheus
Provides-Extra: opentelemetry-semantic-conventions
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Provides-Extra: opentelemetry-instrumentation-fastapi
Provides-Extra: opentelemetry-exporter-otlp-proto-grpc
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Provides-Extra: uvicorn[standard]
Provides-Extra: docker
Provides-Extra: pathspec
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Provides-Extra: requests
Provides-Extra: websockets
Provides-Extra: pydantic
Provides-Extra: python-multipart
Provides-Extra: aiofiles
Provides-Extra: aiohttp
Provides-Extra: aiostream
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Provides-Extra: pytest
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Provides-Extra: pytest-reraise
Provides-Extra: mock
Provides-Extra: requests-mock
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Provides-Extra: black
Provides-Extra: kubernetes
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Provides-Extra: pytest-lazy-fixture
Provides-Extra: cicd
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Provides-Extra: strawberry-graphql
Provides-Extra: watchfiles
Provides-Extra: urllib3
Provides-Extra: transformers
Provides-Extra: anyconfig
Provides-Extra: python-consul2
Provides-Extra: fastwer
Provides-Extra: matplotlib
Provides-Extra: albumentations
Provides-Extra: dominate
Provides-Extra: lmdb
Provides-Extra: natsort
Provides-Extra: celery
Provides-Extra: opencv-python
Provides-Extra: imagecodecs
Provides-Extra: imutils
Provides-Extra: PyPDF4
Provides-Extra: reportlab
Provides-Extra: pycocotools
Provides-Extra: nltk
Provides-Extra: timm
Provides-Extra: Wand
Provides-Extra: Cython
Provides-Extra: jsons
Provides-Extra: shapely
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Provides-Extra: onnx
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Provides-Extra: onnxruntime-gpu
Provides-Extra: onnxconverter_common
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Provides-Extra: pika
Provides-Extra: sentencepiece
Provides-Extra: Levenshtein
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Provides-Extra: patchify
Provides-Extra: colorcet
Provides-Extra: fast_pytorch_kmeans
Provides-Extra: all
License-File: LICENSE
License-File: NOTICE

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
# Marie-AI

Integrate AI-powered document pipeline into your applications

## Documentation

See the [MarieAI docs](https://docs.marieai.co).

## Installation

You don't need this source code unless you want to modify the package. If you just
want to use the package, just run:

```sh
pip install --upgrade marieai
```

Install from source with:

```sh
pip install -e .
```

Build docker container:

```sh
DOCKER_BUILDKIT=1 docker build . --build-arg PIP_TAG="standard" -f ./Dockerfiles/gpu.Dockerfile  -t marieai/marie:3.0-cuda 
```

## Command-line interface

This library additionally provides an `marie` command-line utility which makes it easy to interact with the API 
from your terminal. Run `marie -h` for usage.

## Example code

Examples of how to use this library to accomplish various tasks can be found in the MarieAI documentation. 
It contains code examples for:

* Document cleanup
* Optical character recognition (OCR)
* Document Classification
* Document Splitter
* Named Entity Recognition
* Form detection
* And more


## Run with default entrypoint

```shell
docker run --rm  -it marieai/marie:3.0.19-cuda
```

## Run the server with custom entrypoint

```shell
docker run --rm  -it --entrypoint /bin/bash  marieai/marie:3.0.19-cuda  
```

## Telemetry
https://telemetry.marieai.co/

TODO :MOVE TO DOCS

# S3 Cloud Storage
```shell
docker compose -f  docker-compose.s3.yml --project-directory . up  --build --remove-orphans
```

CrossFTP


## Configure AWS CLI Credentials.

```shell
vi ~/.aws/credentials
[marie] # this should be in the file
aws_access_key_id=your_access_key_id
aws_secret_access_key=your_secret_access_key
```

 

## Pull the Docker image.

```shell
docker pull zenko/cloudserver
```

## Create and start the container.


```sh
docker run --rm -it --name marie-s3-server -p 8000:8000 \
-e SCALITY_ACCESS_KEY_ID=MARIEACCESSKEY \
-e SCALITY_SECRET_ACCESS_KEY=MARIESECRETACCESSKEY \
-e S3DATA=multiple \
-e S3BACKEND=mem zenko/cloudserver
```

```
SCALITY_ACCESS_KEY_ID : Your AWS ACCESS KEY 
SCALITY_SECRET_ACCESS_KEY: Your AWS SECRET ACCESS KEY 
S3BACKEND: Currently using memory storage
```

## Verify Installation.

```shell
aws s3 mb s3://mybucket  --profile marie --endpoint-url http://localhost:8000 --region us-west-2
```

```shell
aws s3 ls --profile marie --endpoint-url http://localhost:8000
```

```shell
aws s3 cp some_file.txt s3://mybucket  --profile marie --endpoint-url http://localhost:8000
```


```shell
aws s3 --profile marie --endpoint-url=http://127.0.0.1:8000 ls --recursive s3://
```

# Production setup


Configuration for the S3 server will be stored in the following files:
https://towardsdatascience.com/10-lessons-i-learned-training-generative-adversarial-networks-gans-for-a-year-c9071159628
