Synced repo using 'sync_with_huggingface' Github Action

app.py

@@ -1,101 +1,10 @@
-import gradio as gr
-from transformers import pipeline
-from flake8.api import legacy as flake8
-import autopep8
-
-# Initialize the pipeline for text generation
-pipe = pipeline("text-generation", model="replit/replit-code-v1_5-3b", trust_remote_code=True)
-
-def generate_code(prompt, max_length=100, num_return_sequences=1):
-    try:
-        # Use the pipeline to generate code
-        results = pipe(prompt, max_length=max_length, num_return_sequences=num_return_sequences)
-        # Format the generated results
-        return "\n\n".join([res["generated_text"] for res in results])
-    except Exception as e:
-        return f"An error occurred: {str(e)}"
-
-def lint_code(code: str) -> tuple[str, str]:
-    """
-    Lint the provided Python code using Flake8 and auto-fix it with autopep8.
-    Returns the fixed code and the linting report.
-    """
-    try:
-        # Run Flake8 for linting, ignoring line-length violations (E501)
-        style_guide = flake8.get_style_guide(ignore=["E501"])
-        
-        # Directly check code content
-        report = style_guide.check_code(code)
-        
-        # Auto-fix the code with autopep8
-        fixed_code = autopep8.fix_code(code)
-        
-        # Generate the linting report
-        lint_report = "\n".join(msg for msg in report.get_statistics())
-        
-        return fixed_code, lint_report
-    except Exception as e:
-        return code, f"An error occurred during linting: {str(e)}"
-
-def process_file(file) -> tuple[str, str]:
-    """
-    Process the uploaded file, decode its content, and lint it.
-    Returns the fixed code and linting report.
-    """
-    try:
-        # Read the file content and decode it to a string
-        with file as f:
-            code = f.read().decode("utf-8")
-        
-        # Lint the code and get the report
-        return lint_code(code)
-    except Exception as e:
-        return "", f"An error occurred while processing the file: {str(e)}"
-
-def handle_input(code: str, file) -> tuple[str, str]:
-    """
-    Handle both code inputs: either text or file.
-    If a file is provided, process the file. Otherwise, process the pasted code.
-    """
-    if file:
-        return process_file(file)
-    return lint_code(code)
-
-# Gradio interface
-with gr.Blocks() as interface:
-    gr.Markdown("### PyLint Pro: AI Code Generation Tool")
-    
-    # Input fields
-    prompt_input = gr.Textbox(label="Code Prompt", placeholder="Enter your code snippet or logic...")
-    max_length_input = gr.Slider(label="Max Length", minimum=10, maximum=500, value=100)
-    num_return_sequences_input = gr.Slider(label="Number of Outputs", minimum=1, maximum=5, value=1)
-    
-    # Output
-    output_box = gr.Textbox(label="Generated Code", placeholder="The generated code will appear here...", lines=10)
-
-    # Button to trigger code generation
-    generate_button = gr.Button("Generate Code")
-    
-    # Define interaction
-    generate_button.click(
-        generate_code,
-        inputs=[prompt_input, max_length_input, num_return_sequences_input],
-        outputs=output_box,
-    )
-
-    # Existing linting interface
-    gr.Markdown("### Python Code Linter")
-    code_input = gr.Textbox(lines=20, placeholder="Paste your Python code here...", label="Python Code")
-    file_input = gr.File(label="Upload a Python (.py) file", file_types=[".py"])
-    linted_code_output = gr.Textbox(label="Linted Code", lines=20)
-    lint_report_output = gr.Textbox(label="Linting Report")
-    lint_button = gr.Button("Lint Code")
-    lint_button.click(
-        handle_input,
-        inputs=[code_input, file_input],
-        outputs=[linted_code_output, lint_report_output],
-    )
-
-# Launch the interface
-if __name__ == "__main__":
-    interface.launch()
+fastapi==0.95.2
+uvicorn==0.22.0
+transformers==4.38.0
+torch==2.2.0
+pydantic==1.10.13
+gradio==3.1.4
+datasets==2.13.1
+huggingface_hub==0.16.4
+flake8==6.0.0
+autopep8==2.0.2