Delete app.py

app.py

@@ -1,130 +0,0 @@
-import gradio as gr
-import spaces
-import PyPDF2
-import docx
-import io
-import os
-from typing import Optional
-from huggingface_hub import InferenceClient
-from prompts import SYSTEM_PROMPT, PROMPTS
-
-def extract_text_from_file(file) -> str:
-    """Extract text from uploaded files"""
-    if file is None:
-        return ""
-    
-    file_path = file.name
-    text = ""
-    
-    try:
-        if file_path.endswith('.pdf'):
-            with open(file_path, 'rb') as f:
-                reader = PyPDF2.PdfReader(f)
-                for page in reader.pages:
-                    text += page.extract_text() + "\n"
-        
-        elif file_path.endswith('.docx'):
-            doc = docx.Document(file_path)
-            for paragraph in doc.paragraphs:
-                text += paragraph.text + "\n"
-        
-        elif file_path.endswith('.txt'):
-            with open(file_path, 'r', encoding='utf-8') as f:
-                text = f.read()
-    except Exception as e:
-        return f"Error reading file: {str(e)}"
-    
-    return text
-
-@spaces.GPU
-def process_document(document, operation_type, text_input):
-    """Main processing function using Cerebras Llama through HuggingFace"""
-    
-    # Extract text from file or use text input
-    if document is not None:
-        text = extract_text_from_file(document)
-    else:
-        text = text_input
-    
-    if not text.strip():
-        return "Please provide either a document or text input."
-    
-    # Get the appropriate prompt
-    prompt = PROMPTS.get(operation_type, "")
-    
-    # Create the client with Cerebras provider
-    try:
-        client = InferenceClient(
-            "meta-llama/Llama-3.3-70B-Instruct",
-            provider="cerebras",
-            token=os.getenv("HF_TOKEN"),
-        )
-        
-        # Create conversation messages
-        messages = [
-            {"role": "system", "content": SYSTEM_PROMPT},
-            {"role": "user", "content": f"{prompt}\n\nDocument content:\n{text}"}
-        ]
-        
-        # Generate response using chat completion
-        response = client.chat_completion(
-            messages=messages,
-            max_tokens=3000,
-            temperature=0.1,
-            stream=False
-        )
-        
-        return response.choices[0].message.content
-        
-    except Exception as e:
-        return f"Error: {str(e)}\n\nPlease ensure:\n1. HF_TOKEN is set in settings\n2. You have Pro access to use Cerebras inference\n3. The Cerebras/Llama integration is enabled in your account"
-
-# Create the Gradio interface
-with gr.Blocks(title="Study Assistant", theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 📚 Study Assistant - Document Analysis Tool")
-    gr.Markdown("Upload a document or paste text, then select the type of analysis you want to perform.")
-    gr.Markdown("*Powered by Meta Llama-3.3-70B via Cerebras on HuggingFace*")
-    
-    with gr.Row():
-        with gr.Column():
-            document = gr.File(
-                label="Upload Document",
-                file_types=[".pdf", ".docx", ".txt"],
-                file_count="single"
-            )
-            text_input = gr.Textbox(
-                label="Or paste text directly",
-                lines=5,
-                placeholder="Paste your text here if you don't want to upload a file..."
-            )
-            
-        with gr.Column():
-            operation_type = gr.Dropdown(
-                choices=["Summary", "Outline", "Analysis", "Study Guide", "Table", "Questions"],
-                label="Select Operation",
-                value="Summary"
-            )
-            process_btn = gr.Button("🚀 Process Document", variant="primary", size="lg")
-    
-    output = gr.Textbox(
-        label="Output",
-        lines=20,
-        show_copy_button=True
-    )
-    
-    gr.Markdown("---")
-    gr.Markdown("### Tips:")
-    gr.Markdown("- Supported formats: PDF, DOCX, TXT")
-    gr.Markdown("- Maximum file size: 200MB")
-    gr.Markdown("- Text can be pasted directly if you don't have a file")
-    gr.Markdown("- Uses HuggingFace Pro account with Cerebras access")
-    
-    process_btn.click(
-        fn=process_document,
-        inputs=[document, operation_type, text_input],
-        outputs=output,
-        show_progress=True
-    )
-
-if __name__ == "__main__":
-    demo.launch()