Create app.py

app.py

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+import gradio as gr
+from gradio_client import Client
+import os
+import zipfile
+from datasets import Dataset
+from huggingface_hub import HfApi
+
+# Initialize the Gradio client
+client = Client("MiniMaxAI/MiniMax-Text-01")
+
+# Function to call the API and get the result
+def call_api(prompt):
+    result = client.predict(
+        message=prompt,
+        max_tokens=12800,
+        temperature=0.1,
+        top_p=0.9,
+        api_name="/chat"
+    )
+    return result
+
+# Function to segment the text file into chunks of 3000 words
+def segment_text(file_path):
+    with open(file_path, "r") as f:
+        text = f.read()
+    words = text.split()
+    chunks = [" ".join(words[i:i + 3000]) for i in range(0, len(words), 3000)]
+    return chunks
+
+# Function to process the text file and make parallel API calls
+def process_text(file, prompt):
+    # Segment the text file into chunks
+    chunks = segment_text(file.name)
+    
+    # Perform two parallel API calls for each chunk
+    results = []
+    for chunk in chunks:
+        result1 = call_api(f"{prompt}\n\n{chunk}")
+        result2 = call_api(f"{prompt}\n\n{chunk}")
+        results.extend([result1, result2])
+    
+    # Save results as individual text files
+    os.makedirs("outputs", exist_ok=True)
+    for idx, result in enumerate(results):
+        with open(f"outputs/output_{idx}.txt", "w") as f:
+            f.write(result)
+    
+    # Upload to Hugging Face dataset
+    hf_api = HfApi(token=os.environ["HUGGINGFACE_TOKEN"])
+    dataset = Dataset.from_dict({"text": results})
+    dataset.push_to_hub("your_huggingface_username/your_dataset_name")
+    
+    # Create a 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)
+    
+    return "outputs.zip", "Results uploaded to Hugging Face dataset and ZIP file created."
+
+# Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("## Text File Processor with Parallel API Calls")
+    with gr.Row():
+        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]
+    )
+
+# Launch the Gradio app
+demo.launch()