Update app.py

app.py

@@ -1,17 +1,24 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
+from gradio_client import Client
+from PIL import Image
+import requests
+from io import BytesIO
+import streamlit as st
 
 # Initialize the HuggingFace Inference Client with the specified model
-client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.2")
+client_mistral = InferenceClient("mistralai/Mistral-7B-Instruct-v0.2")
+# Initialize the Playground AI client
+client_playground = Client("https://playgroundai-playground-v2-5.hf.space/--replicas/c9ozb/")
 
-def format_prompt(message, logo_request):
+def format_prompt(logo_request):
     system_prompt = """
     You are an advanced language model designed to create detailed and creative image prompts for logo generation. Based on the user's input, generate an elaborate and descriptive image prompt that can be used to create a high-quality logo. Ensure that the prompt is clear, imaginative, and provides specific details that will guide the logo creation process effectively.
     """
     prompt = f"<s>[SYS] {system_prompt} [/SYS][INST] {logo_request} [/INST]</s>"
     return prompt
 
-def generate(logo_request, temperature=0.9, max_new_tokens=512, top_p=0.95, repetition_penalty=1.0):
+def generate_improved_prompt(logo_request, temperature=0.9, max_new_tokens=512, top_p=0.95, repetition_penalty=1.0):
     temperature = float(temperature)
     if temperature < 1e-2:
         temperature = 1e-2
@@ -26,14 +33,40 @@ def generate(logo_request, temperature=0.9, max_new_tokens=512, top_p=0.95, repe
         "seed": 42,
     }
 
-    formatted_prompt = format_prompt("", logo_request)
-    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
+    formatted_prompt = format_prompt(logo_request)
+    stream = client_mistral.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
     output = ""
 
     for response in stream:
         output += response.token.text
         yield output
 
+def generate_image(prompt, negative_prompt="", use_negative_prompt=False, seed=0, width=1024, height=1024, guidance_scale=7.5, randomize_seed=True):
+    result = client_playground.predict(
+        prompt,
+        negative_prompt,
+        use_negative_prompt,
+        seed,
+        width,
+        height,
+        guidance_scale,
+        randomize_seed,
+        api_name="/run"
+    )
+
+    # Extract the image URL from the result
+    image_path = result[0][0]["image"]
+    image_url = "https://playgroundai-playground-v2-5.hf.space/--replicas/c9ozb/file=" + image_path
+    
+    # Fetch and display the result image
+    response = requests.get(image_url)
+    
+    if response.headers['Content-Type'].startswith('image'):
+        img = Image.open(BytesIO(response.content))
+        return img
+    else:
+        return None
+
 css = """
 #mkd {
     height: 500px; 
@@ -52,7 +85,7 @@ with gr.Blocks(css=css) as gpt:
             generate_button = gr.Button("Generate")
             output_area = gr.Textbox(label="AI Response", interactive=False, lines=10)
             generate_button.click(
-                fn=generate,
+                fn=generate_improved_prompt,
                 inputs=[logo_input],
                 outputs=output_area
             )
@@ -60,7 +93,7 @@ with gr.Blocks(css=css) as gpt:
     gr.Markdown("""
     ---
     ### Meta Information
-    **Project Title**: Logo Prompt Generator
+    **Project Title**: Magic AI Website Logo Creator
     
     **Github**: [https://github.com/pacnimo/gpt-prompt-generator](https://github.com/pacnimo/)
     
@@ -70,3 +103,23 @@ with gr.Blocks(css=css) as gpt:
     """) # Meta, project description, and footer added here
 
 gpt.launch(debug=True)
+
+st.title("Image Generation using API")
+
+# Streamlit app input fields
+prompt = st.text_input("Enter prompt:", "")
+negative_prompt = st.text_input("Enter negative prompt:", "")
+use_negative_prompt = st.checkbox("Use negative prompt", False)
+seed = st.number_input("Seed (0-2147483647):", value=0, min_value=0, max_value=2147483647)
+width = st.slider("Width:", 1024, 1536)
+height = st.slider("Height:", 1024, 1536)
+guidance_scale = st.slider("Guidance Scale:", 3.0, 20.0, 0.1)
+randomize_seed = st.checkbox("Randomize seed", True)
+
+if st.button("Generate Image"):
+    with st.spinner("Generating image..."):
+        img = generate_image(prompt, negative_prompt, use_negative_prompt, seed, width, height, guidance_scale, randomize_seed)
+        if img:
+            st.image(img, caption="Generated Image")
+        else:
+            st.error("The content retrieved is not an image.")