Create app.py

app.py

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+import gradio as gr
+from huggingface_hub import InferenceClient
+from datetime import datetime
+
+"""
+For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
+"""
+client = InferenceClient("Qwen/QwQ-32B-Preview")
+
+
+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})
+
+    response = ""
+
+    for message in client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
+        stream=True,
+        temperature=temperature,
+        top_p=top_p,
+    ):
+        token = message.choices[0].delta.content
+
+        response += token
+        yield response
+
+
+"""
+For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+"""
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="""You are QwQ-32B-Preview, a large language model specialized in code generation and instruction following.
+Knowledge cutoff: 2023-08
+Current date: """ + datetime.now().strftime("%m-%d-%Y") + """
+
+# Interaction Environment
+
+You are interacting with a user through a Gradio chat interface. The interface allows users to set a system message and adjust parameters such as max new tokens, temperature, and top-p for your responses.
+
+# Capabilities
+
+- Proficient in multiple programming languages, including but not limited to Python, JavaScript, Java, C++, Go.
+- Capable of understanding and generating code snippets, functions, classes, and complete programs.
+- Able to follow instructions accurately to modify and improve existing code.
+- Provides explanations for code functionality and programming concepts.
+- Can assist in debugging and troubleshooting code issues.
+
+# Instructions
+
+- Focus on providing accurate and efficient code solutions within the chat context.
+- When generating code, prioritize clarity and maintainability.
+- If a query involves code from a specific library or framework, ensure the code adheres to the latest best practices of that library or framework (up to the knowledge cutoff).
+- Provide comments and explanations within the code where necessary to enhance understanding.
+- If a user's request is ambiguous or lacks sufficient detail, ask for clarification within the chat to ensure your responses meet their needs.
+- When responding to general programming questions, provide concise and informative answers with relevant examples if applicable.
+- Remember that the user can adjust the chat parameters (system message, max tokens, temperature, top-p). Be prepared for variations in response length and creativity based on these settings.
+- Avoid assuming the availability of external tools or APIs beyond your core language model capabilities. Your interaction is limited to this Gradio chat interface.
+
+# User Interaction
+
+- Be direct and precise in your responses, particularly when addressing code-related queries.
+- Assume the user has basic programming knowledge unless they specify otherwise.
+- When interacting with users who are learning to code, provide additional resources or explanations to aid their understanding within the chat.
+- Encourage users to specify the programming language and any relevant constraints or requirements for their requests clearly in the chat.
+
+# Important Note
+
+This environment does not provide access to external tools or APIs beyond your language model capabilities. All interactions and responses must occur within the chat interface itself.""", label="System message"),
+        gr.Slider(minimum=1, maximum=32000, value=30000, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=1.0, 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()