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<p align="center">
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<img src="colivara-image.png" alt="ColiVara" width=650px>
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</p>
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# ColiVara
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**State of the Art Retrieval - with a delightful developer experience**
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[![codecov](https://codecov.io/gh/tjmlabs/ColiVara/branch/main/graph/badge.svg)](https://codecov.io/gh/tjmlabs/ColiVara) [![Tests](https://github.com/tjmlabs/ColiVara/actions/workflows/test.yml/badge.svg)](https://github.com/tjmlabs/Colivara/actions/workflows/test.yml)
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[![Discord](https://dcbadge.limes.pink/api/server/https://discord.gg/DtGRxWuj8y)](https://discord.gg/DtGRxWuj8y)
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Colivara is a suite of services that allows you to store, search, and retrieve documents based on their **_visual_** embedding. ColiVara has state of the art retrieval performance on both text and visual documents, offering superior multimodal understanding and control.
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[![codecov](https://codecov.io/gh/tjmlabs/ColiVara/branch/main/graph/badge.svg)](https://codecov.io/gh/tjmlabs/ColiVara) [![Tests](https://github.com/tjmlabs/ColiVara/actions/workflows/test.yml/badge.svg)](https://github.com/tjmlabs/Colivara/actions/workflows/test.yml)
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It is a web-first implementation of the **ColPali** paper using ColQwen2 as the LLM model. It works exactly like RAG from the end-user standpoint - but using vision models instead of chunking and text-processing for documents.
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**No OCR, no text extraction, no broken tables, or missing images. What you see, is what you get.**
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### Cloud Quickstart:
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### Quickstart:
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1. Get a free API Key from the [ColiVara Website](https://colivara.com).
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```bash
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pip install colivara-py
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```
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or in Typescript
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or
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```bash
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npm install colivara-ts
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```
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3. Index a document. Colivara accepts a file url, or base64 encoded file, or a file path. We support over 100 file formats including PDF, DOCX, PPTX, and more. We will also automatically take a screenshot of URLs (webpages) and index them.
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3. Index a document (a file url, base64 encoded file, or path). It supports over 100 file formats including PDF, DOCX, PPTX, and more.
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```python
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from colivara_py import ColiVara
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client = ColiVara(api_key="your_api_key")
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client = ColiVara(api_key=os.environ.get("COLIVARA_API_KEY"), # default and can be omitted
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base_url="https://api.colivara.com" # default and can be omitted
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)
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# Upload a document to the default_collection
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document = client.upsert_document(
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name="sample_document",
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# You can use a file path, base64 encoded file, or a URL
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document_url="https://example.com/sample.pdf",
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# optional - add metadata
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metadata={"author": "John Doe"},
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# optional - specify a collection
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collection_name="user_1_collection",
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# optional - wait for the document to index. Webhooks are also supported.
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wait=True
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name="sample_document",
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document_url="https://example.com/sample.pdf", # You can use a file path, base64 encoded file, or a URL
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metadata={"author": "John Doe"}, # optional - add metadata
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collection_name="user_1_collection", # optional - specify a collection
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wait=True # optional - wait for indexing (supports Webhooks)
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)
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```
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or
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docker-compose exec web mypy .
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```
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## Support
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For support, join our Discord community where you can:
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- Get help with setup and configuration
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- Report bugs and request features
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- Connect with other ColiVara users
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- Stay updated on new releases and announcements
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Click the badge below to join:
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[![Discord](https://dcbadge.limes.pink/api/server/https://discord.gg/DtGRxWuj8y)](https://discord.gg/DtGRxWuj8y)
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## License
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This project is licensed under Functional Source License, Version 1.1, Apache 2.0 Future License. See the [LICENSE.md](LICENSE.md) file for details.

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