Update app.py

app.py

@@ -1,8 +1,6 @@
 import gradio as gr
 from gradio_client import Client
 import os
-import zipfile
-from huggingface_hub import HfApi
 import logging
 import time  # Import time module for adding delays
 
@@ -62,14 +60,6 @@ def process_text(file, prompt):
         file_path = file.name if hasattr(file, "name") else file
         chunks = segment_text(file_path)
         
-        # Initialize Hugging Face API
-        hf_api = HfApi(token=os.environ.get("HUGGINGFACE_TOKEN"))
-        if not hf_api.token:
-            raise ValueError("Hugging Face token not found in environment variables.")
-        
-        # Repository name on Hugging Face Hub
-        repo_name = "TeacherPuffy/book2"
-        
         # Process each chunk with a 15-second delay between API calls
         results = []
         for idx, chunk in enumerate(chunks):
@@ -80,27 +70,6 @@ def process_text(file, prompt):
                 results.append(result)
                 logger.info(f"Chunk {idx + 1} processed successfully.")
                 
-                # Save the result to a file
-                os.makedirs("outputs", exist_ok=True)
-                output_file = f"outputs/output_{idx}.txt"
-                with open(output_file, "w", encoding="utf-8") as f:
-                    f.write(result)
-                logger.info(f"Saved result to {output_file}")
-                
-                # Upload the chunk as an individual text file to Hugging Face
-                try:
-                    logger.info(f"Uploading chunk {idx + 1} to Hugging Face...")
-                    hf_api.upload_file(
-                        path_or_fileobj=output_file,
-                        path_in_repo=f"output_{idx}.txt",  # File name in the repository
-                        repo_id=repo_name,
-                        repo_type="dataset",
-                    )
-                    logger.info(f"Chunk {idx + 1} uploaded to Hugging Face successfully.")
-                except Exception as e:
-                    logger.error(f"Failed to upload chunk {idx + 1} to Hugging Face: {e}")
-                    raise gr.Error(f"Failed to upload chunk {idx + 1} to Hugging Face: {str(e)}")
-                
                 # Wait 15 seconds before the next API call
                 if idx < len(chunks) - 1:  # No need to wait after the last chunk
                     logger.info("Waiting 15 seconds before the next API call...")
@@ -110,19 +79,7 @@ def process_text(file, prompt):
                 logger.error(f"Failed to process chunk {idx + 1}: {e}")
                 raise gr.Error(f"Failed to process chunk {idx + 1}: {str(e)}")
         
-        # Create a ZIP file of all outputs
-        try:
-            logger.info("Creating ZIP file...")
-            with zipfile.ZipFile("outputs.zip", "w") as zipf:
-                for root, dirs, files in os.walk("outputs"):
-                    for file in files:
-                        zipf.write(os.path.join(root, file), file)
-            logger.info("ZIP file created successfully.")
-        except Exception as e:
-            logger.error(f"Failed to create ZIP file: {e}")
-            raise gr.Error(f"Failed to create ZIP file: {str(e)}")
-        
-        return "outputs.zip", "All chunks processed and uploaded to Hugging Face. ZIP file created."
+        return "All chunks processed successfully."
     
     except Exception as e:
         logger.error(f"An error occurred during processing: {e}")
@@ -135,14 +92,13 @@ with gr.Blocks() as demo:
         file_input = gr.File(label="Upload Text File")
         prompt_input = gr.Textbox(label="Enter Prompt")
     with gr.Row():
-        output_zip = gr.File(label="Download ZIP File")
         output_message = gr.Textbox(label="Status Message")
     submit_button = gr.Button("Submit")
     
     submit_button.click(
         process_text,
         inputs=[file_input, prompt_input],
-        outputs=[output_zip, output_message]
+        outputs=[output_message]
     )
 
 # Launch the Gradio app with a public link