Spaces:
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Paused
File size: 2,710 Bytes
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import json
import gradio as gr
from openai import OpenAI
from datetime import datetime
ENV_API_KEY = os.getenv("LLMAPI_KEY") # backup if user doesn't provide
DEFAULT_ENDPOINT = "https://api.llmapi.ai/v1"
DEFAULT_MODEL = "deepseek-v4-flash-0731"
def run_llm(endpoint: str, api_key: str, model: str, prompt: str):
endpoint = (endpoint or "").strip().rstrip("/")
api_key = (api_key or "").strip()
model = (model or "").strip()
prompt = (prompt or "").strip()
if not endpoint:
return ("Missing endpoint (e.g. https://api.llmapi.ai/v1).", None)
key = api_key or (ENV_API_KEY or "").strip()
if not key:
return ("Missing API key. Provide one in the form or set Spaces secret env LLMAPI_KEY.", None)
if not model:
return ("Missing model (e.g. deepseek-v4-flash-0731).", None)
if not prompt:
return ("Missing prompt.", None)
client = OpenAI(base_url=endpoint, api_key=key)
try:
resp = client.chat.completions.create(
model=model,
messages=[{"role": "user", "content": prompt}],
)
content = resp.choices[0].message.content
# Build a JSON download payload (complete-ish)
payload = {
"created_at_utc": datetime.utcnow().isoformat() + "Z",
"request": {
"base_url": endpoint,
"model": model,
"messages": [{"role": "user", "content": prompt}],
},
"response": resp.model_dump() if hasattr(resp, "model_dump") else str(resp),
}
# Write to a file for Gradio download
filename = "result.json"
with open(filename, "w", encoding="utf-8") as f:
json.dump(payload, f, ensure_ascii=False, indent=2)
return (content, filename)
except Exception as e:
return (f"Error: {e}", None)
with gr.Blocks() as demo:
gr.Markdown("# Custom LLM Endpoint (user-provided)")
with gr.Row():
endpoint = gr.Textbox(label="Endpoint (base_url)", value=DEFAULT_ENDPOINT)
api_key = gr.Textbox(
label="API Key (optional - uses env LLMAPI_KEY as backup)",
type="password",
placeholder="Leave blank to use env LLMAPI_KEY",
)
model = gr.Textbox(label="Model", value=DEFAULT_MODEL)
prompt = gr.Textbox(label="Prompt", lines=6, placeholder="Type your prompt here...")
run_btn = gr.Button("Send")
out_text = gr.Textbox(label="Response", lines=10)
out_file = gr.File(label="Download results as JSON")
run_btn.click(
fn=run_llm,
inputs=[endpoint, api_key, model, prompt],
outputs=[out_text, out_file],
)
demo.launch()
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