Create app.py

app.py

@@ -0,0 +1,60 @@
+import gradio as gr
+import os
+from langchain_openai import ChatOpenAI
+
+# Set up the SambaNova Chat API client
+api_key = os.environ.get("FEATHERLESS_API_KEY")
+llm = ChatOpenAI(
+    base_url="https://api.featherless.ai/v1/",
+    api_key=api_key,
+    streaming=True,
+    model="Qwen/Qwen3-32B",
+)
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "system", "content": system_message}]
+
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+
+    messages.append({"role": "user", "content": message})
+
+    # Update the ChatOpenAI instance with the current parameters
+    llm.max_tokens = max_tokens
+    llm.temperature = temperature
+    llm.top_p = top_p
+
+    response = ""
+    for chunk in llm.stream(messages):
+        token = chunk.content
+        response += token
+        yield response
+
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=2.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=0.95,
+            step=0.05,
+            label="Top-p (nucleus sampling)",
+        ),
+    ],
+)
+
+if __name__ == "__main__":
+    demo.launch()