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--- |
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license: llama2 |
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datasets: |
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- Intel/neuralchat_dataset_preprocessed |
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language: |
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- en |
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pipeline_tag: image-to-text |
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--- |
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# ScriptSculptor 🌳 |
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## Introduction 🚀 |
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Welcome to our project! Developed with Intel Cloud Developer and love during the thrilling TreeHacks competition. |
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This guide is your compass for navigating through the features, setup, and usage of our application. |
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## Installation 🛠️ |
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To get started, install the required packages using pip: |
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```sh |
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pip3 install langchain predictionguard duckdb |
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``` |
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## Setup 🔑 |
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You will need an API key from predictionguard which can be found at https://www.predictionguard.com/. Ensure you have the necessary tokens and environment variables set: |
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```python |
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pg_access_token = "your_token_here" |
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os.environ['PREDICTIONGUARD_TOKEN'] = pg_access_token |
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``` |
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#### 📈 Example |
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```markdown |
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## Example |
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def test(): |
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present_code = """ |
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from flask import Flask, jsonify |
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import sqlite3 |
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app = Flask(__name__)""" |
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question = "could you add api" |
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method = "GET" |
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path = "example/path" |
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api_name = "blah blah" |
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sql_schema = "\ |
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CREATE TABLE users (\ |
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user_id INTEGER PRIMARY KEY,\ |
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user_name VARCHAR(255)\ |
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);\ |
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\ |
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CREATE TABLE sleep (\ |
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user_id INTEGER,\ |
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time_stamp TIMESTAMP,\ |
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bpm INTEGER,\ |
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FOREIGN KEY (user_id) REFERENCES users(user_id)\ |
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);" |
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flask_code = text2flask(present_code, question, method, path, api_name, sql_schema) |
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print(flask_code) |
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``` |
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## Contributions 🙌 |
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Contributions are welcome! If you have ideas or improvements, please fork the repo and submit a pull request. 🌳 |
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## Acknowledgements 🎉 |
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Big thanks to everyone who participated in the hackathon, our mentors, and the open-source community! 🌟 |
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