mirror of
https://github.com/kennethreitz/instructor.git
synced 2026-06-05 22:50:18 +00:00
Jason
73 lines
3.4 KiB
Markdown
73 lines
3.4 KiB
Markdown
# Citation with Extraction
|
|
|
|
This repository contains a FastAPI application that uses GPT-4 to answer questions based on a given context and extract relevant facts with correct and exact citations. The extracted facts are returned as JSON events using Server-Sent Events (SSE).
|
|
|
|
## How it Works
|
|
|
|
The FastAPI app defines an endpoint `/extract` that accepts a POST request with JSON data containing a `context` and a `query`. The `context` represents the text from which the question is being asked, and the `query` is the question itself.
|
|
|
|
The app leverages GPT-4, an advanced language model, to generate answers to the questions and extract relevant facts. It ensures that the extracted facts include direct quotes from the given context.
|
|
|
|
## Example Usage
|
|
|
|
To use the `/extract` endpoint, send a POST request with `curl` or any HTTP client with the following format:
|
|
|
|
```bash
|
|
curl -X POST -H "Content-Type: application/json" -d '{
|
|
"context": "My name is Jason Liu, and I grew up in Toronto Canada but I was born in China.I went to an arts highschool but in university I studied Computational Mathematics and physics. As part of coop I worked at many companies including Stitchfix, Facebook. I also started the Data Science club at the University of Waterloo and I was the president of the club for 2 years.",
|
|
"query": "What did the author do in school?"
|
|
}' -N http://localhost:8000/extract
|
|
```
|
|
|
|
```sh
|
|
data: {'body': 'In school, the author went to an arts high school.', 'spans': [(91, 106)], 'citation': ['arts highschool']}
|
|
data: {'body': 'In university, the author studied Computational Mathematics and physics.', 'spans': [(135, 172)], 'citation': ['Computational Mathematics and physics']}
|
|
```
|
|
|
|
Replace `http://localhost:8000` with the actual URL of your FastAPI app if it's running on a different host and port. The API will respond with Server-Sent Events (SSE) containing the extracted facts in real-time.
|
|
|
|
## Bring your own API key
|
|
|
|
If you have your own api key but dont want to try deploying it yourself you're welcome to use my
|
|
modal isntance here, this code is public and I do not store your key.
|
|
|
|
```bash
|
|
curl -X 'POST' \
|
|
'https://jxnl--rag-citation-fastapi-app.modal.run/extract' \
|
|
-H 'accept: */*' \
|
|
-H 'Content-Type: application/json' \
|
|
-H 'Authorization: Bearer <OPENAI_API_KEY>' \
|
|
-d '{
|
|
"context": "My name is Jason Liu, and I grew up in Toronto Canada but I was born in China.I went to an arts highschool but in university I studied Computational Mathematics and physics. As part of coop I worked at many companies including Stitchfix, Facebook. I also started the Data Science club at the University of Waterloo and I was the president of the club for 2 years.",
|
|
"query": "What did the author do in school?"
|
|
}'
|
|
```
|
|
|
|
|
|
## Requirements
|
|
|
|
To run this application, ensure you have the following Python packages installed:
|
|
|
|
```bash
|
|
pip install -r requirements.txt
|
|
```
|
|
|
|
## Running the App
|
|
|
|
To run the FastAPI app, execute the following command:
|
|
|
|
```bash
|
|
uvicorn main:app --reload
|
|
```
|
|
|
|
This will start the server, and the `/extract` endpoint will be available at `http://localhost:8000/extract`.
|
|
|
|
## Note
|
|
|
|
Ensure that you have a valid API key for GPT-4 from OpenAI. If you don't have one, you can obtain it from the OpenAI website.
|
|
|
|
Please use this application responsibly and be mindful of any usage limits or restrictions from OpenAI's API usage policy.
|
|
|
|
## License
|
|
|
|
This project is licensed under the [MIT License](LICENSE). Feel free to use, modify, and distribute it as you see fit. |