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Qdrant OCR search Cookbook #214
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| # OCR Search with Mistral and Qdrant | ||
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| This notebook demonstrates how to use **Mistral OCR** to extract text from documents, embed with **FastEmbed**, and store it in **Qdrant** for semantic search. | ||
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| --- | ||
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| ## What It Does | ||
| - Extracts text from scanned documents (PDFs, images) using Mistral OCR | ||
| - Creates embeddings of the recognized text | ||
| - Stores embeddings in Qdrant for scalable semantic search | ||
| - Lets you query with natural language and retrieve the most relevant passages | ||
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| --- | ||
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| ## Credentials | ||
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| You’ll need credentials for both **Mistral** and **Qdrant**. | ||
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| ### Qdrant Cloud | ||
| 1. Create a cluster at [Qdrant Cloud](https://cloud.qdrant.io) | ||
| 2. Generate an API key in the cluster’s **API Keys** section | ||
| 3. Export both the URL and the key: | ||
| ```bash | ||
| export QDRANT_URL="https://YOUR-CLUSTER-UUID.region.cloud.qdrant.io:6333" | ||
| export QDRANT_API_KEY="your_qdrant_key" | ||
| ``` | ||
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| ### Mistral | ||
| 1. Sign up at [Mistral](https://mistral.ai) | ||
| 2. Create an API key in the console | ||
| 3. Set it as an environment variable: | ||
| ```bash | ||
| export MISTRAL_API_KEY=your_mistral_key | ||
| ``` | ||
| --- | ||
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| ## Setup | ||
| Install dependencies: | ||
| ```bash | ||
| pip install mistralai qdrant-client python-dotenv | ||
| ``` | ||
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| Optionally, create a `.env` file: | ||
| ```bash | ||
| MISTRAL_API_KEY=your_mistral_key | ||
| QDRANT_URL=your_qdrant_url | ||
| QDRANT_API_KEY=your_qdrant_key # optional for local | ||
| ``` | ||
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| Run the notebook in this directory to see the full workflow. | ||
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| --- | ||
| ## Coming Soon | ||
| **Multimodal Search with Qdrant and Mistral** | ||
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Could you add details about setting up Qdrant Cloud and obtaining a Mistral API key at the beginning of the cookbook? That way, readers will have everything ready, and the flow will be smoother as they start working through it.