image-to-text en dataset:Intel/neuralchat_dataset_preprocessed license:llama2 region:us
---
license: llama2
datasets:
- Intel/neuralchat_dataset_preprocessed
language:
- en
pipeline_tag: image-to-text
---

# ScriptSculptor 🌳

## Introduction 🚀
Welcome to our project! Developed with Intel Cloud Developer and love during the thrilling TreeHacks competition. 
This guide is your compass for navigating through the features, setup, and usage of our application. 


## Installation 🛠️
To get started, install the required packages using pip:

```sh
pip3 install langchain predictionguard duckdb
```

## Setup 🔑

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:

```python
pg_access_token = "your_token_here"
os.environ['PREDICTIONGUARD_TOKEN'] = pg_access_token
```


#### 📈 Example

```markdown
## Example
def test():
    present_code = """
    from flask import Flask, jsonify
    import sqlite3
    app = Flask(__name__)"""

    question = "could you add api"
    method = "GET"
    path = "example/path"
    api_name = "blah blah"
    sql_schema = "\
    CREATE TABLE users (\
        user_id INTEGER PRIMARY KEY,\
        user_name VARCHAR(255)\
    );\
    \
    CREATE TABLE sleep (\
        user_id INTEGER,\
        time_stamp TIMESTAMP,\
        bpm INTEGER,\
        FOREIGN KEY (user_id) REFERENCES users(user_id)\
    );"

    flask_code = text2flask(present_code, question, method, path, api_name, sql_schema)
    print(flask_code)
```



## Contributions 🙌

Contributions are welcome! If you have ideas or improvements, please fork the repo and submit a pull request. 🌳

## Acknowledgements 🎉

Big thanks to everyone who participated in the hackathon, our mentors, and the open-source community! 🌟




