Update app.py

app.py

@@ -4,6 +4,13 @@ import torch
 import gradio as gr
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
+title = """# 🙋🏻‍♂️ Welcome to Tonic's Salesforce/Xlam-7B-r"""
+description = """
+ Large Action Models (LAMs) are advanced large language models designed to enhance decision-making and translate user intentions into executable actions that interact with the world. LAMs autonomously plan and execute tasks to achieve specific goals, serving as the brains of AI agents. They have the potential to automate workflow processes across various domains, making them invaluable for a wide range of applications. 
+### Join us : 
+🌟TeamTonic🌟 is always making cool demos! Join our active builder's 🛠️community 👻 [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/GWpVpekp) On 🤗Huggingface:[MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Tonic-AI](https://github.com/tonic-ai) & contribute to🌟 [Build Tonic](https://git.tonic-ai.com/)🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
+"""
+
 # Load model and tokenizer
 model_name = "Salesforce/xLAM-7b-r"
 model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto", torch_dtype="auto", trust_remote_code=True)
@@ -87,7 +94,7 @@ iface = gr.Interface(
     inputs=[
         gr.Textbox(
             label="Available Tools (JSON format)",
-            lines=10,
+            lines=20,
             value=json.dumps([
                 {
                     "name": "get_weather",
@@ -126,9 +133,9 @@ iface = gr.Interface(
         ),
         gr.Textbox(label="User Query", lines=2, value="What's the weather like in New York in fahrenheit?")
     ],
-    outputs=gr.Textbox(label="Generated Response", lines=10),
-    title="xLAM-7b-r API Request Generator",
-    description="Enter available tools in JSON format and a user query to generate an API request or response.",
+    outputs=gr.Textbox(label="Generated Response", lines=5),
+    title=title,
+    description=description,
 )
 
 if __name__ == "__main__":