wehub-resource-sync
44 lines
1.6 KiB
Markdown
44 lines
1.6 KiB
Markdown
# Build a multi-agent hotel booking crew using DeepSeek-R1
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In this tutorial we are building a 100% local multi-agent hotel booking crew. It find the cheapest and best hotels for you and uses DeepSeek-R1 running locally.
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It features [Browserbase](https://dub.sh/bb1) to create a headless browser tool for the agents and CrewAI for multi-agent orchestration.
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### Setup
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To sync dependencies, run:
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```sh
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uv sync
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```
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### Environment Variables
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You need to set up the following environment variables:
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```sh
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BROWSERBASE_API_KEY=...
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OPENAI_API_KEY=... (not required for locally running)
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```
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[Get your browser base API key here](https://dub.sh/bb1)
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OpenAI API key needed only when you are running app_openai.py. app.py uses a locally running DeepSeek with Ollama. ([how to setup local llm](https://ollama.com/library/deepseek-r1))
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Ensure these variables are configured correctly before running the application use `.env.example` as reference and create your own `.env` file.
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Run the streamlit app using `streamlit run app.py`
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---
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## 📬 Stay Updated with Our Newsletter!
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**Get a FREE Data Science eBook** 📖 with 150+ essential lessons in Data Science when you subscribe to our newsletter! Stay in the loop with the latest tutorials, insights, and exclusive resources. [Subscribe now!](https://join.dailydoseofds.com)
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[](https://join.dailydoseofds.com)
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---
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## Contribution
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Contributions are welcome! Please fork the repository and submit a pull request with your improvements.
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