app.py

import os
import gradio as gr
import transformers
import blackboxai

# Set up the Hugging Face Transformers library
model_name = "bert-base-uncased"
tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)
model = transformers.AutoModel.from_pretrained(model_name)

# Set up the Blackbox.ai API client
blackbox_client.Client.from_api_key(os.environ["BLACKBOX_API_KEY"])

# Define the user interface for the app
def run_model(input_text):
    # Tokenize the input text
    inputs = tokenizer(input_text, return_tensors="pt")

    # Run the model on the inputs
    outputs = model(**inputs)

    # Extract the last hidden state from the model outputs
    last_hidden_states = outputs.last_hidden_state

    # Return the last hidden state as a string
    return last_hidden_states.detach().numpy().tolist()

iface = gr.Interface(fn=run_model, inputs="text", outputs="text")

# Define the GitHub bot functions
def get_issues():
    # Code to get issues from the GitHub repository
    pass

def fix_issue(issue):
    # Code to fix the issue on the local fork
    pass

def push_fix():
    # Code to push the fix to the GitHub repository
    pass

def comment_on_issue(issue, result):
    # Code to comment on the issue with the result
    pass

# Define the main function to run the app and the bot
def main():
    # Run the app
    iface.launch()

    # Get the issues from the GitHub repository
    issues = get_issues()

    # Loop through the issues
    for issue in issues:
        # Fix the issue on the local fork
        fixed_issue = fix_issue(issue)

        # Run the model on the fixed issue
        result = run_model(fixed_issue)

        # Push the fix to the GitHub repository
        push_fix()

        # Comment on the issue with the result
        comment_on_issue(issue, result)

# Run the main function
if __name__ == "__main__":
    main()