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app.py

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+import streamlit as st
+from gradio_client import Client
+
+# Constants
+TITLE = "Llama2 70B Chatbot"
+DESCRIPTION = """
+This Space demonstrates model [Llama-2-70b-chat-hf](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf) by Meta, 
+a Llama 2 model with 70B parameters fine-tuned for chat instructions. 
+"""
+
+# Initialize client
+client = Client("https://ysharma-explore-llamav2-with-tgi.hf.space/")
+
+# Prediction function
+def predict(message, system_prompt="", temperature=0.9, max_new_tokens=4096):
+    return client.predict(
+			message,	# str in 'Message' Textbox component
+            system_prompt,	# str in 'Optional system prompt' Textbox component
+			temperature,	# int | float (numeric value between 0.0 and 1.0)
+			max_new_tokens,	# int | float (numeric value between 0 and 4096)
+			0.3,	# int | float (numeric value between 0.0 and 1)
+			1,	# int | float (numeric value between 1.0 and 2.0)
+			api_name="/chat"
+    )
+
+# Streamlit UI
+st.title(TITLE)
+st.write(DESCRIPTION)
+
+# Input fields
+message = st.text_area("Enter your message:", "")
+system_prompt = st.text_area("Optional system prompt:", "")
+temperature = st.slider("Temperature", min_value=0.0, max_value=1.0, value=0.9, step=0.05)
+max_new_tokens = st.slider("Max new tokens", min_value=0, max_value=4096, value=4096, step=64)
+
+if st.button("Predict"):
+    response = predict(message, system_prompt, temperature, max_new_tokens)
+    st.write("Response:", response)
+

requirements.txt

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+gradio-client==0.0.4