Create app.py

app.py

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+import gradio as gr
+from llama_index.llms import Perplexity
+from llama_index.llms.base import ChatMessage
+
+# Define the main function for handling chat interactions.
+def chat_with_pplx_model(api_key, model_name, user_input, pre_prompt, system_message, temperature, max_tokens):
+    # Convert max_tokens to integer if it is not empty. This controls the length of the model's responses.
+    max_tokens = int(max_tokens) if max_tokens else None
+
+    # Prepend the pre-prompt text to the user input. This allows for setting a context or instructions.
+    full_user_input = f"{pre_prompt}\n{user_input}"
+
+    # Initialize the Perplexity model with the given parameters.
+    llm = Perplexity(
+        api_key=api_key, 
+        model_name=model_name, 
+        temperature=temperature,
+        max_tokens=max_tokens  # If max_tokens is None, the model uses its default value.
+    )
+    
+    # Prepare the chat messages for interaction with the model.
+    messages_dict = [
+        {"role": "system", "content": system_message},  # System message, like an initial greeting or instructions.
+        {"role": "user", "content": full_user_input}    # The actual user input, prepended with the pre_prompt.
+    ]
+    messages = [ChatMessage(**msg) for msg in messages_dict]
+    
+    # Get the response from the LLM.
+    response = llm.chat(messages)
+    return response
+
+# Gradio Interface components.
+api_key_input = gr.Textbox(label="API Key")  # Input for the API key.
+model_name_dropdown = gr.Dropdown(choices=["pplx-70b-online", "pplx-7b-online", "mixtral-8x7b-instruct"], label="LLM Model Name")  # Input for the model name.
+user_input = gr.Textbox(placeholder="Enter your input here", label="User Input")  # Input for user's message.
+pre_prompt_input = gr.Textbox(placeholder="Enter pre-prompt here", label="Pre-Prompt")  # Input for the pre-prompt text.
+system_message = gr.Textbox(placeholder="Enter system message here", label="System Message")  # Input for system message.
+temperature_slider = gr.Slider(minimum=0, maximum=2, step=0.01, label="Temperature")  # Slider to adjust the temperature.
+max_tokens_input = gr.Textbox(placeholder="Enter max tokens (optional)", label="Max Tokens")  # Input for max tokens.
+
+# Creating the Gradio interface.
+iface = gr.Interface(
+    fn=chat_with_pplx_model,
+    inputs=[api_key_input, model_name_dropdown, user_input, pre_prompt_input, system_message, temperature_slider, max_tokens_input],
+    outputs="text"
+)
+
+# Launching the interface.
+iface.launch(share=True)