HOFchain - The HOF Cognitive Chain-of-thought Prompter

HOFchain is a Python library designed to simplify the process of higher-order functional cognitive computing for Natural Language Understanding (NLU) based code generation. This library integrates functionalities for parsing input, generating code, planning tasks, and more, enabling an end-to-end solution for automating software development tasks from natural language specifications.

Features

• NLU Parsing: Extracts intent and entities from natural language input.
• Code Generation: Generates code templates based on extracted intent and entities.
• Task Planning: Plans and organizes development tasks.
• Test Generation: Creates unit tests for the generated code.
• Deployment Scripts: Generates deployment scripts for deploying the generated code.

Installation

To install HOFchain, simply clone the repository and install the dependencies:

git clone https://github.com/yourusername/HOFchain.git
cd HOFchain
pip install -r requirements.txt

Usage

Here’s an example of how to use HOFchain to generate a REST API from a natural language specification:

from HOFchain import (
    parse_input, generate_code_template, plan_tasks,
    generate_tests, generate_deployment_script
)

# Input text from user
input_text = "Create a REST API with endpoints for user registration and login."

# Step 1: Parse Input
intent, entities = parse_input(input_text)
print("Intent:", intent)
print("Entities:", entities)

# Step 2: Generate Code Template
code_template = generate_code_template(intent, entities)
print("Generated Code Template:", code_template)

# Step 3: Plan Tasks
tasks = plan_tasks(intent, entities)
print("Planned Tasks:", tasks)

# Step 4: Generate Tests
tests = generate_tests(intent, entities)
print("Generated Tests:", tests)

# Step 5: Generate Deployment Script
deployment_script = generate_deployment_script(intent, entities)
print("Generated Deployment Script:", deployment_script)

API Reference

NLU Parsing

extract_intent(input_text: str) -> str

Extracts the intent from the input text.

extract_entities(input_text: str) -> dict

Extracts relevant entities from the input text.

parse_input(input_text: str) -> tuple

Parses the input text to extract intent and entities.

Code Generation

generate_code_template(intent: str, entities: dict) -> str

Generates a code template based on the intent and entities.

Task Planning

plan_tasks(intent: str, entities: dict) -> list

Plans and organizes development tasks based on the intent and entities.

Test Generation

generate_tests(intent: str, entities: dict) -> list

Generates unit tests for the generated code based on the intent and entities.

Deployment Scripts

generate_deployment_script(intent: str, entities: dict) -> str

Generates deployment scripts for deploying the generated code.

Contributing

Contributions are welcome! Please fork the repository and submit a pull request for any changes or improvements.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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Example Output

Here’s an example output for the provided usage:

Intent

create_api

Entities

{'endpoints': ['user registration', 'login']}

Generated Code Template

from flask import Flask

app = Flask(__name__)

# Define endpoints

@app.route('/user_registration', methods=['GET', 'POST'])
def user_registration():
    return "user registration endpoint"

@app.route('/login', methods=['GET', 'POST'])
def login():
    return "login endpoint"

if __name__ == "__main__":
    app.run(debug=True)

Planned Tasks

[
    {"task": "Define endpoints", "details": {"endpoints": ["user registration", "login"]}},
    {"task": "Implement endpoints", "details": {"endpoints": ["user registration", "login"]}},
    {"task": "Test endpoints", "details": {"endpoints": ["user registration", "login"]}}
]

Generated Tests

def test_user_registration():
    response = client.get('/user_registration')
    assert response.status_code == 200

def test_login():
    response = client.get('/login')
    assert response.status_code == 200

Generated Deployment Script

# Dockerfile
FROM python:3.8-slim

COPY . /app
WORKDIR /app
RUN pip install -r requirements.txt
CMD ["python", "app.py"]

Contact

For questions or support, please open an issue on the GitHub repository or contact [email protected]

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