Update app.py

app.py

@@ -55,22 +55,22 @@ def segment_text(file_path):
     logger.info(f"Segmented text into {len(chunks)} chunks.")
     return chunks
 
-# Function to process the text file and make parallel API calls
+# Function to process the text file and make API calls
 def process_text(file, prompt):
     try:
         logger.info("Starting text processing...")
         
         # Segment the text file into chunks
-        chunks = segment_text(file.name)
+        file_path = file.name if hasattr(file, "name") else file
+        chunks = segment_text(file_path)
         
-        # Perform two parallel API calls for each chunk
+        # Perform API calls for each chunk
         results = []
         for idx, chunk in enumerate(chunks):
             logger.info(f"Processing chunk {idx + 1}/{len(chunks)}")
             try:
-                result1 = call_api(f"{prompt}\n\n{chunk}")
-                result2 = call_api(f"{prompt}\n\n{chunk}")
-                results.extend([result1, result2])
+                result = call_api(f"{prompt}\n\n{chunk}")
+                results.append(result)
                 logger.info(f"Chunk {idx + 1} processed successfully.")
             except Exception as e:
                 logger.error(f"Failed to process chunk {idx + 1}: {e}")
@@ -87,7 +87,9 @@ def process_text(file, prompt):
         # Upload to Hugging Face dataset
         try:
             logger.info("Uploading results to Hugging Face dataset...")
-            hf_api = HfApi(token=os.environ["HUGGINGFACE_TOKEN"])
+            hf_api = HfApi(token=os.environ.get("HUGGINGFACE_TOKEN"))
+            if not hf_api.token:
+                raise ValueError("Hugging Face token not found in environment variables.")
             dataset = Dataset.from_dict({"text": results})
             dataset.push_to_hub("TeacherPuffy/book")  # Updated dataset name
             logger.info("Results uploaded to Hugging Face dataset successfully.")
@@ -115,7 +117,7 @@ def process_text(file, prompt):
 
 # Gradio interface
 with gr.Blocks() as demo:
-    gr.Markdown("## Text File Processor with Parallel API Calls")
+    gr.Markdown("## Text File Processor with API Calls")
     with gr.Row():
         file_input = gr.File(label="Upload Text File")
         prompt_input = gr.Textbox(label="Enter Prompt")