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openai-compatible-api-playground/.gitignore

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+__pycache__/
+*.pyc
+.env
+.venv/
+venv/
+

openai-compatible-api-playground/README.md

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+---
+title: VeloKey OpenAI-Compatible API Playground
+emoji: 🔑
+colorFrom: blue
+colorTo: green
+sdk: gradio
+sdk_version: 4.44.1
+app_file: app.py
+pinned: true
+license: mit
+short_description: Test VeloKey's OpenAI-compatible AI model API from Hugging Face
+tags:
+  - openai-compatible
+  - ai-api
+  - llm
+  - gradio
+  - api-playground
+---
+
+# VeloKey OpenAI-Compatible API Playground
+
+Test VeloKey's OpenAI-compatible AI model API directly from a Hugging Face Space.
+
+This demo lets you:
+
+- Send a chat completion request to `https://api.velokey.ai/v1/chat/completions`
+- Use your own VeloKey API key without storing it in the Space
+- Choose or enter a model ID available to your account
+- Inspect the raw JSON response for debugging
+- List models available through `GET /v1/models`
+
+## How to use
+
+1. Get a VeloKey API key from [velokey.ai/console/keys](https://velokey.ai/console/keys?ref=huggingface-space).
+2. Paste the key into the API key field.
+3. Click **List available models** if you are not sure which model ID to use.
+4. Enter a prompt and click **Run chat completion**.
+
+Your API key is only used for the request you send from this app. Do not paste production secrets into third-party apps unless you understand the risk.
+
+## Resources
+
+- [VeloKey website](https://velokey.ai?ref=huggingface-space)
+- [API documentation](https://docs.velokey.ai/api/introduction)
+- [Model catalog](https://velokey.ai/model?ref=huggingface-space)
+- [Pricing](https://velokey.ai/pricing?ref=huggingface-space)
+- [Get API key](https://velokey.ai/console/keys?ref=huggingface-space)

openai-compatible-api-playground/app.py

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+from __future__ import annotations
+
+import json
+import time
+from typing import Any
+
+import gradio as gr
+import requests
+
+
+BASE_URL = "https://api.velokey.ai/v1"
+CHAT_COMPLETIONS_URL = f"{BASE_URL}/chat/completions"
+MODELS_URL = f"{BASE_URL}/models"
+
+MODEL_EXAMPLES = [
+    "gpt-5.5",
+    "claude-sonnet-4-6",
+    "gemini-3-pro-preview",
+    "deepseek-v4-pro",
+    "qwen3.7-max",
+]
+
+DEFAULT_SYSTEM_PROMPT = "You are a concise assistant for developers."
+DEFAULT_USER_PROMPT = "Explain what an OpenAI-compatible API gateway is in two sentences."
+
+
+def _headers(api_key: str) -> dict[str, str]:
+    return {
+        "Authorization": f"Bearer {api_key.strip()}",
+        "Content-Type": "application/json",
+        "User-Agent": "velokey-huggingface-playground/1.0",
+    }
+
+
+def _format_json(data: Any) -> str:
+    return json.dumps(data, ensure_ascii=False, indent=2)
+
+
+def _request_json(method: str, url: str, api_key: str, **kwargs: Any) -> tuple[int, Any, float]:
+    start = time.perf_counter()
+    response = requests.request(
+        method,
+        url,
+        headers=_headers(api_key),
+        timeout=60,
+        **kwargs,
+    )
+    elapsed_ms = (time.perf_counter() - start) * 1000
+
+    try:
+        body: Any = response.json()
+    except ValueError:
+        body = response.text
+
+    return response.status_code, body, elapsed_ms
+
+
+def list_models(api_key: str) -> tuple[str, str]:
+    if not api_key.strip():
+        return "Paste a VeloKey API key first.", ""
+
+    try:
+        status, body, elapsed_ms = _request_json("GET", MODELS_URL, api_key)
+    except requests.RequestException as exc:
+        return f"Request failed: {exc}", ""
+
+    if status >= 400:
+        return f"Model list request returned HTTP {status}.", _format_json(body)
+
+    model_ids: list[str] = []
+    if isinstance(body, dict) and isinstance(body.get("data"), list):
+        for item in body["data"]:
+            if isinstance(item, dict) and item.get("id"):
+                model_ids.append(str(item["id"]))
+    elif isinstance(body, list):
+        for item in body:
+            if isinstance(item, dict) and item.get("id"):
+                model_ids.append(str(item["id"]))
+
+    if model_ids:
+        preview = "\n".join(model_ids[:30])
+        if len(model_ids) > 30:
+            preview += f"\n...and {len(model_ids) - 30} more"
+        summary = f"Found {len(model_ids)} model IDs in {elapsed_ms:.0f} ms."
+        return summary, preview
+
+    return f"Request succeeded in {elapsed_ms:.0f} ms, but no model IDs were recognized.", _format_json(body)
+
+
+def run_chat_completion(
+    api_key: str,
+    model: str,
+    system_prompt: str,
+    user_prompt: str,
+    temperature: float,
+    max_tokens: int,
+) -> tuple[str, str, str]:
+    if not api_key.strip():
+        return "Paste a VeloKey API key first.", "", ""
+    if not model.strip():
+        return "Enter a model ID available to your VeloKey account.", "", ""
+    if not user_prompt.strip():
+        return "Enter a user prompt.", "", ""
+
+    messages: list[dict[str, str]] = []
+    if system_prompt.strip():
+        messages.append({"role": "system", "content": system_prompt.strip()})
+    messages.append({"role": "user", "content": user_prompt.strip()})
+
+    payload = {
+        "model": model.strip(),
+        "messages": messages,
+        "temperature": temperature,
+        "max_tokens": max_tokens,
+    }
+
+    try:
+        status, body, elapsed_ms = _request_json("POST", CHAT_COMPLETIONS_URL, api_key, json=payload)
+    except requests.RequestException as exc:
+        return f"Request failed: {exc}", "", _format_json(payload)
+
+    if status >= 400:
+        return f"Chat completion returned HTTP {status}.", _format_json(body), _format_json(payload)
+
+    answer = ""
+    if isinstance(body, dict):
+        choices = body.get("choices")
+        if isinstance(choices, list) and choices:
+            first = choices[0]
+            if isinstance(first, dict):
+                message = first.get("message")
+                if isinstance(message, dict):
+                    content = message.get("content")
+                    if isinstance(content, str):
+                        answer = content
+                if not answer and isinstance(first.get("text"), str):
+                    answer = str(first["text"])
+
+    if not answer:
+        answer = "Request succeeded, but the response format did not include choices[0].message.content."
+
+    status_line = f"HTTP {status} in {elapsed_ms:.0f} ms"
+    return status_line, answer, _format_json(body)
+
+
+with gr.Blocks(
+    title="VeloKey OpenAI-Compatible API Playground",
+    theme=gr.themes.Soft(primary_hue="blue", secondary_hue="green"),
+    css="""
+    .resource-links a { margin-right: 0.75rem; }
+    .hint { color: #4b5563; font-size: 0.95rem; }
+    """,
+) as demo:
+    gr.Markdown(
+        """
+        # VeloKey OpenAI-Compatible API Playground
+
+        Test a VeloKey chat completion request from Hugging Face using your own API key.
+
+        <p class="resource-links">
+          <a href="https://velokey.ai?ref=huggingface-space" target="_blank">Website</a>
+          <a href="https://docs.velokey.ai/api/introduction" target="_blank">API docs</a>
+          <a href="https://velokey.ai/model?ref=huggingface-space" target="_blank">Models</a>
+          <a href="https://velokey.ai/pricing?ref=huggingface-space" target="_blank">Pricing</a>
+          <a href="https://velokey.ai/console/keys?ref=huggingface-space" target="_blank">Get API key</a>
+        </p>
+        """
+    )
+
+    with gr.Row():
+        api_key_input = gr.Textbox(
+            label="VeloKey API key",
+            type="password",
+            placeholder="vk-...",
+            scale=2,
+        )
+        model_input = gr.Dropdown(
+            label="Model ID",
+            choices=MODEL_EXAMPLES,
+            value=MODEL_EXAMPLES[0],
+            allow_custom_value=True,
+            scale=2,
+        )
+
+    with gr.Row():
+        list_models_button = gr.Button("List available models", variant="secondary")
+        model_status = gr.Textbox(label="Model list status", interactive=False)
+
+    available_models = gr.Textbox(
+        label="Available model IDs",
+        lines=8,
+        interactive=False,
+        placeholder="Click List available models to query GET /v1/models.",
+    )
+
+    with gr.Accordion("Prompt settings", open=True):
+        system_prompt_input = gr.Textbox(
+            label="System prompt",
+            value=DEFAULT_SYSTEM_PROMPT,
+            lines=2,
+        )
+        user_prompt_input = gr.Textbox(
+            label="User prompt",
+            value=DEFAULT_USER_PROMPT,
+            lines=5,
+        )
+        with gr.Row():
+            temperature_input = gr.Slider(
+                label="Temperature",
+                minimum=0,
+                maximum=2,
+                step=0.1,
+                value=0.7,
+            )
+            max_tokens_input = gr.Slider(
+                label="Max tokens",
+                minimum=16,
+                maximum=2048,
+                step=16,
+                value=512,
+            )
+
+    run_button = gr.Button("Run chat completion", variant="primary")
+
+    with gr.Row():
+        status_output = gr.Textbox(label="Status", interactive=False)
+        answer_output = gr.Textbox(label="Assistant response", lines=10, interactive=False)
+
+    raw_json_output = gr.Code(label="Raw JSON response", language="json", lines=18)
+
+    gr.Markdown(
+        """
+        <p class="hint">
+        API keys are submitted with each request and are not saved by this app. For production apps,
+        keep your VeloKey API key on your own backend, not in browser-side code.
+        </p>
+        """
+    )
+
+    list_models_button.click(
+        fn=list_models,
+        inputs=[api_key_input],
+        outputs=[model_status, available_models],
+    )
+
+    run_button.click(
+        fn=run_chat_completion,
+        inputs=[
+            api_key_input,
+            model_input,
+            system_prompt_input,
+            user_prompt_input,
+            temperature_input,
+            max_tokens_input,
+        ],
+        outputs=[status_output, answer_output, raw_json_output],
+    )
+
+
+if __name__ == "__main__":
+    demo.launch()

openai-compatible-api-playground/requirements.txt

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+gradio==4.44.1
+huggingface_hub==0.25.2
+requests==2.32.5