First commit

app.py

@@ -0,0 +1,139 @@
+import time
+from huggingface_hub import InferenceClient
+import gradio as gr
+
+# Initialize the inference client with the new LLM
+client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
+
+# Define the system prompt for enhancing user prompts
+SYSTEM_PROMPT = (
+    "You are a prompt enhancer and your work is to enhance the given prompt under 100 words "
+    "without changing the essence, only write the enhanced prompt and nothing else."
+)
+
+def format_prompt(message):
+    """
+    Format the input message using the system prompt and a timestamp to ensure uniqueness.
+    """
+    timestamp = time.time()
+    formatted = (
+        f"<s>[INST] SYSTEM: {SYSTEM_PROMPT} [/INST]"
+        f"[INST] {message} {timestamp} [/INST]"
+    )
+    return formatted
+
+def generate(message, max_new_tokens=256, temperature=0.9, top_p=0.95, repetition_penalty=1.0):
+    """
+    Generate an enhanced prompt using the new LLM.
+    This function yields intermediate results as they are generated.
+    """
+    temperature = float(temperature)
+    if temperature < 1e-2:
+        temperature = 1e-2
+    top_p = float(top_p)
+    generate_kwargs = {
+        "temperature": temperature,
+        "max_new_tokens": int(max_new_tokens),
+        "top_p": top_p,
+        "repetition_penalty": float(repetition_penalty),
+        "do_sample": True,
+    }
+    formatted_prompt = format_prompt(message)
+    stream = client.text_generation(
+        formatted_prompt,
+        **generate_kwargs,
+        stream=True,
+        details=True,
+        return_full_text=False,
+    )
+    output = ""
+    for response in stream:
+        token_text = response.token.text
+        output += token_text
+        yield output.strip('</s>')
+    return output.strip('</s>')
+
+# Markdown texts for credits and best practices
+CREDITS_MARKDOWN = """
+# Prompt Enhancer  
+Credits: Instructions and design inspired by [ruslanmv.com](https://ruslanmv.com).
+"""
+
+BEST_PRACTICES = """
+**Best Practices**  
+- Be specific and clear in your input prompt  
+- Use temperature 0.0 for consistent, focused results  
+- Increase temperature up to 1.0 for more creative variations  
+- Review and iterate on engineered prompts for optimal results  
+"""
+
+# Build the Gradio interface with the Ocean theme
+with gr.Blocks(theme=gr.themes.Ocean(), css=".gradio-container { max-width: 800px; margin: auto; }") as demo:
+    # Credits at the top
+    gr.Markdown(CREDITS_MARKDOWN)
+    
+    gr.Markdown(
+        "Enhance your prompt to under 100 words while preserving its essence. "
+        "Adjust the generation parameters as needed."
+    )
+    
+    with gr.Row():
+        with gr.Column(scale=1):
+            input_prompt = gr.Textbox(
+                label="Input Prompt",
+                placeholder="Enter your prompt here...",
+                lines=4,
+            )
+            max_tokens_slider = gr.Slider(
+                label="Max New Tokens",
+                minimum=50,
+                maximum=512,
+                step=1,
+                value=256,
+            )
+            temperature_slider = gr.Slider(
+                label="Temperature",
+                minimum=0.1,
+                maximum=2.0,
+                step=0.1,
+                value=0.9,
+            )
+            top_p_slider = gr.Slider(
+                label="Top-p (nucleus sampling)",
+                minimum=0.1,
+                maximum=1.0,
+                step=0.05,
+                value=0.95,
+            )
+            repetition_penalty_slider = gr.Slider(
+                label="Repetition Penalty",
+                minimum=1.0,
+                maximum=2.0,
+                step=0.05,
+                value=1.0,
+            )
+            generate_button = gr.Button("Enhance Prompt")
+        with gr.Column(scale=1):
+            output_prompt = gr.Textbox(
+                label="Enhanced Prompt",
+                lines=10,
+                interactive=True,
+            )
+    
+    # Best practices message at the bottom
+    gr.Markdown(BEST_PRACTICES)
+    
+    # Wire the button click to the generate function (streaming functionality is handled internally)
+    generate_button.click(
+        fn=generate,
+        inputs=[
+            input_prompt,
+            max_tokens_slider,
+            temperature_slider,
+            top_p_slider,
+            repetition_penalty_slider,
+        ],
+        outputs=output_prompt,
+    )
+
+demo.launch()