Update app.py

app.py

@@ -1,34 +1,116 @@
 import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer
+import time
+import random
 
-model_cache = {}
+# Load the model and tokenizer
+model_id = "Tech-Meld/Hajax_Chat_1.0"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
 
-def load_model():
-    model_id = "Tech-Meld/Hajax_Chat_1.0"
-    tokenizer = AutoTokenizer.from_pretrained(model_id)
-    model = AutoModelForCausalLM.from_pretrained(model_id)
-    return model, tokenizer
+# --- Functions ---
 
-def get_response(input_text, model, tokenizer):
+def get_response(input_text, temperature, top_p, top_k, max_length):
     inputs = tokenizer.encode(input_text + tokenizer.eos_token, return_tensors='pt')
-    outputs = model.generate(inputs, max_length=1000, pad_token_id=tokenizer.eos_token_id)
+    outputs = model.generate(
+        inputs,
+        max_length=max_length,
+        pad_token_id=tokenizer.eos_token_id,
+        temperature=temperature,
+        top_p=top_p,
+        top_k=top_k,
+    )
     response = tokenizer.decode(outputs[:, inputs.shape[-1]:][0], skip_special_tokens=True)
     return response
 
-def chat(input_text):
-    global model_cache
-    if "model" not in model_cache:
-        model_cache["model"], model_cache["tokenizer"] = load_model()
-    model = model_cache["model"]
-    tokenizer = model_cache["tokenizer"]
-    response = get_response(input_text, model, tokenizer)
-    return response
+def analyze_text(text):
+    num_tokens = len(tokenizer.tokenize(text))
+    return {
+        "Number of characters": len(text),
+        "Number of words": len(text.split()),
+        "Number of tokens": num_tokens,
+    }
+
+# --- Interface ---
+
+css = """
+.gradio-container {
+  background-color: #f0f0f0; /* Light background for the container */
+}
+
+.gradio-interface {
+  background-color: rgba(255, 255, 255, 0.8); /* Translucent white background */
+  border-radius: 15px; /* Rounded corners */
+  padding: 20px;
+  box-shadow: 0 0 10px rgba(0, 0, 0, 0.2); /* Subtle shadow */
+}
+
+.gradio-button {
+  background-color: #4CAF50; /* Green button color */
+  color: white;
+  border: none;
+  padding: 10px 20px;
+  text-align: center;
+  text-decoration: none;
+  display: inline-block;
+  font-size: 16px;
+  margin: 4px 2px;
+  cursor: pointer;
+  border-radius: 5px; /* Rounded corners */
+}
+
+.gradio-button:hover {
+  background-color: #3e8e41; /* Darker green on hover */
+}
+
+.gradio-text-area {
+  resize: vertical; /* Allow vertical resizing for text areas */
+}
+"""
 
 iface = gr.Interface(
-    chat,
-    "text",
-    "text",
+    fn=get_response,
+    inputs=[
+        gr.Textbox(label="Your message:", lines=5, placeholder="Enter your message here...", show_label=True),
+        gr.Slider(label="Temperature", minimum=0.1, maximum=1.0, step=0.1, value=0.7),
+        gr.Slider(label="Top p", minimum=0.1, maximum=1.0, step=0.1, value=0.9),
+        gr.Slider(label="Top k", minimum=1, maximum=100, step=1, value=50),
+        gr.Slider(label="Max length", minimum=10, maximum=1000, step=10, value=250),
+    ],
+    outputs=[
+        gr.TextArea(label="AI Response:", lines=10),
+        gr.Label(label="Text Analysis", elem_id="analysis"),
+    ],
     title="Chat with AI",
-    description="Type your message and press Enter to chat with the AI.",
+    description="Engage in a conversation with our advanced AI model. Customize the response using various parameters.",
+    theme="default",  # Use a custom theme to override the default Gradio styling
+    css=css,  # Apply the CSS styles defined earlier
+    layout="vertical",
+    allow_flagging="never",
 )
-iface.launch()
+
+# --- Dynamic Background ---
+
+def update_background():
+    while True:
+        r = random.randint(0, 255)
+        g = random.randint(0, 255)
+        b = random.randint(0, 255)
+        iface.root.style.background_color = f"rgb({r}, {g}, {b})"  # Set dynamic background color
+        time.sleep(1)  # Update every second
+
+# Start a separate thread to update the background color
+gr.Interface.update(update_background, inputs=[], outputs=[], live=True)
+
+# --- Analysis Logic ---
+
+def update_analysis(response):
+    analysis = analyze_text(response)
+    analysis_str = f"Number of characters: {analysis['Number of characters']}\n" \
+                  f"Number of words: {analysis['Number of words']}\n" \
+                  f"Number of tokens: {analysis['Number of tokens']}"
+    iface.update(analysis=analysis_str, live=True)  # Update analysis section with the generated data
+
+iface.outputs[0].postprocess = update_analysis  # Update analysis after every response
+
+iface.launch(debug=True)