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README.md
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title: AI Class Tutor -- Dev
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description: An LLM based AI class tutor with RAG on DL4DS course
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emoji: πΆ
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colorFrom: red
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sdk: docker
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app_port: 7860
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---
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# DL4DS Tutor π
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![License](https://img.shields.io/github/license/edubotics-ai/edubot-core)
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![GitHub stars](https://img.shields.io/github/stars/edubotics-ai/edubot-core)
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![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)
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Hugging Face [Space](https://huggingface.co/spaces/dl4ds/dl4ds_tutor). It is pushed automatically from the `main` branch of this repo by this
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[Actions Workflow](https://github.com/DL4DS/dl4ds_tutor/blob/main/.github/workflows/push_to_hf_space.yml) upon a push to `main`.
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[Space](https://huggingface.co/spaces/dl4ds/tutor_dev). It is pushed automatically from the `dev_branch` branch of this repo by this
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[Actions Workflow](https://github.com/DL4DS/dl4ds_tutor/blob/dev_branch/.github/workflows/push_to_hf_space_prototype.yml) upon a push to `dev_branch`.
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1. **Clone the Repository**
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```bash
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git clone https://github.com/edubotics-ai/edubot-core
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```
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2. Create your app in the apps folder. (An example is the `apps/ai_tutor` app)
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```
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cd apps
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mkdir your_app
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```
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2. **Put your data under the `apps/your_app/storage/data` directory**
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- Add URLs in the `urls.txt` file.
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- Add other PDF files in the `apps/your_app/storage/data` directory.
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3. **To test Data Loading (Optional)**
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```bash
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cd apps/your_app
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python -m edubotics_core.dataloader.data_loader --links "your_pdf_link" --config_file config/config.yml --project_config_file config/project_config.yml
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```
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4. **Create the Vector Database**
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```bash
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cd apps/your_app
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python -m edubotics_core.vectorstore.store_manager --config_file config/config.yml --project_config_file config/project_config.yml
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```
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6. **Run the FastAPI App**
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```bash
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cd apps/your_app
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uvicorn app:app --port 7860
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```
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## Documentation
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## Docker
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docker build --tag dev -f Dockerfile.dev .
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docker run -it --rm -p 7860:7860 dev
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```
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##
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# edubotics-core
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## Welcome to edubotics-core by Edubotics AI! π
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![PyPI](https://img.shields.io/pypi/v/edubotics-core.svg)
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![GitHub stars](https://img.shields.io/github/stars/edubotics-ai/edubot-core.svg)
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![License](https://img.shields.io/github/license/edubotics-ai/edubot-core.svg)
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![PyPI Downloads](https://img.shields.io/pypi/dm/edubotics-core.svg)
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[![GitHub Contributors](https://img.shields.io/github/contributors/edubotics-ai/edubot-core)](https://github.com/edubotics-ai/edubot-core/graphs/contributors)
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**Empower Education with AI: Create Intelligent Chatbots Quickly and Efficiently π**
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edubotics-core is an open-source Python library that allows developers to build LLM-based chatbots efficiently. It provides a comprehensive set of core modules for vector storage, retrieval, processing, with more to come.
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## π Installation
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You can install edubotics-core using pip:
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```bash
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pip install edubotics-core
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```
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Full documentation can be found [here](https://edubotics-ai.github.io/edubot-core/).
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## β¨ Key Features
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- Modular and Extensible: Easily create, modify, and extend to the core modules.
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## π Applications
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To see the full extent of what edubotics-core can do, check out the app templates we have built:
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- [Edubotics AI Tutor](https://github.com/edubotics-ai/edubot-app): A Digital AI Teaching Assistant setup for the [DS598](https://dl4ds.github.io/sp2024/) course at Boston University.
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## π Contributing
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We welcome contributions to edubotics-core! If you're interested in contributing, please check out our [contributing guidelines](CONTRIBUTING.md) for more details.
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## π License
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edubotics-core is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.
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