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import os
import gradio as gr
from openai import OpenAI
# --- Configuration ---
# Read from environment for safety. Set OPENAI_API_KEY before running.
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
if not OPENAI_API_KEY:
raise RuntimeError(
"Missing OPENAI_API_KEY. Set it in your environment: "
"export OPENAI_API_KEY='sk-...' (Linux/Mac) or "
"setx OPENAI_API_KEY \"sk-...\" (Windows)"
)
# Optional: override base URL if you use a proxy/self-hosted gateway.
# For the standard OpenAI endpoint you can omit base_url entirely.
client = OpenAI(
api_key=OPENAI_API_KEY,
base_url=os.getenv("OPENAI_BASE_URL", "https://api.openai.com/v1")
)
# Default system prompt and model; adjust as desired.
DEFAULT_SYSTEM_PROMPT = "You are a helpful, concise assistant."
DEFAULT_MODEL = os.getenv("OPENAI_MODEL", "gpt-5-chat-latest") # use a current chat model
def chat_fn(message, history, system_prompt, temperature, max_tokens):
"""
Gradio ChatInterface passes:
- message: current user message (str)
- history: list[tuple[str,str]] of (user, assistant) turns
We convert to OpenAI's chat message format and call the Chat Completions API.
"""
# Build messages: system + alternating user/assistant + latest user
messages = [{"role": "system", "content": system_prompt.strip() or DEFAULT_SYSTEM_PROMPT}]
for user_msg, assistant_msg in history:
if user_msg:
messages.append({"role": "user", "content": user_msg})
if assistant_msg:
messages.append({"role": "assistant", "content": assistant_msg})
messages.append({"role": "user", "content": message})
resp = client.chat.completions.create(
model=DEFAULT_MODEL,
messages=messages,
temperature=temperature,
max_tokens=max_tokens if max_tokens and max_tokens > 0 else None,
)
reply = resp.choices[0].message.content
return reply
with gr.Blocks(title="OpenAI Chat (Gradio)") as demo:
gr.Markdown("## OpenAI Chatbot\nEnter a message below to chat.")
with gr.Row():
system_prompt = gr.Textbox(
label="System prompt",
value=DEFAULT_SYSTEM_PROMPT,
lines=2
)
with gr.Row():
temperature = gr.Slider(0.0, 2.0, value=0.7, step=0.1, label="Temperature")
max_tokens = gr.Slider(64, 4096, value=512, step=32, label="Max tokens (response)")
chat = gr.ChatInterface(
fn=lambda msg, hist: chat_fn(msg, hist, system_prompt.value, temperature.value, int(max_tokens.value)),
type="messages", # keeps history as list of tuples
title="OpenAI Chatbot",
retry_btn="Retry",
undo_btn="Remove last",
clear_btn="Clear",
submit_btn="Send"
)
if __name__ == "__main__":
# You can set server_name="0.0.0.0" if deploying in a container.
demo.launch()
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