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https://github.com/langchain-ai/langchain-teacher
Teach LangChain using LangChain!
https://github.com/langchain-ai/langchain-teacher
Last synced: 5 days ago
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Teach LangChain using LangChain!
- Host: GitHub
- URL: https://github.com/langchain-ai/langchain-teacher
- Owner: langchain-ai
- Created: 2023-07-23T03:03:59.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2023-10-20T23:20:11.000Z (about 1 year ago)
- Last Synced: 2024-12-13T10:45:37.343Z (9 days ago)
- Language: Python
- Homepage: https://lang-teacher.streamlit.app/
- Size: 233 KB
- Stars: 238
- Watchers: 7
- Forks: 87
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
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README
# LangChain-Teacher
## Description
LangChain-Teacher's goal is to facilitate interactive learning of LangChain, enabling users to begin with the Python-based LangChain through a chat-based learning interface. The app offers two teaching styles: Instructional, which provides step-by-step instructions, and Interactive lessons with questions, which prompts users with questions to assess their understanding.
The hosted version of the app is on Streamlit Cloud at [lang-teacher.streamlit.app](https://lang-teacher.streamlit.app/)
## How Does This Work?
The core of the teaching process is driven by the prompts defined in `get_prompt.py`. This module creates lessons based on the content available in the `lc_guides` folder, where lessons are stored as `.txt` files.
To give a bit more context:
- The prompt, combined with the lesson content from the `.txt` file, is sent to a Language Learning Model (LLM) to assist in generating bite-sized lessons.
- The chat memory helps LLM retain information about previous instructions and add new ones to the conversation.
- This showcases the power of prompt templates and how prompt engineering could be used in the development of LLM applications.
## Getting Started
This Streamlit app guides users through lessons using a chat-based interface. To get started, follow these steps:
### Prerequisites
- Python 3.10 or higher
### Installation
1. Clone the repository from GitHub or create a GitHub Codespace:
```
git clone https://github.com/hwchase17/langchain-teacher.git
```
Change directory to the langchain-teacher directory
```
cd langchain-teacher
```
2. Install the required dependencies listed in `requirements.txt`:
```
pip install -r requirements.txt
```
3. Create a `.env` file in the root directory and add the following environment variables:
```
OPENAI_API_KEY=
LANGCHAIN_ENDPOINT=
LANGCHAIN_API_KEY=
LANGCHAIN_TRACING_V2=
LANGCHAIN_PROJECT=
```
An example `.env` file is provided as `.env-example`. If you're not using LangSmith, you only need to set the `OPENAI_API_KEY` variable.
4. Run the Streamlit app using the command:
```
streamlit run lc_main.py
```
If using `dotenv` to manage environment variables, use the following command:
```
dotenv streamlit run lc_main.py
```
## Additional Files and Branches
- The initial version of the app used a getting started guide at guide.txt together with the main.py file to run the streamlit app. You can also run the initial version of the app using the command:
```
streamlit run main.py
```
- There is also a tutor for LangChain expression language with lesson files in the `lcel` folder and the `lcel.py` file to run the streamlit app.
- The `supervisor-model` branch in this repository implements a `SequentialChain` to supervise responses from students and teachers. This approach aims to ensure that questions are on-topic by the students and that the responses are accordingly as well by the teacher model.
## Future Work
- [ ] **Integration with LangSmith Hub**: Integrate prompts directly into the [LangSmith Hub](https://smith.langchain.com/).
- [ ] **Expanding Lesson Library**: Continuously add new lessons to create a comprehensive learning resource.
- [ ] **Token Usage Improvement**: Currently the prompt sent to the LLM is quite large as it takes the prompt and the lesson. Could be improved further.
## Contributions
Please feel free to add more lessons/examples/use cases. We would love for langchain-teacher to be the first stop for any new learner. You can contribute by creating pull requests or raising issues.
## License
This project is licensed under the [MIT License](LICENSE).