Configuration

Connect your Google Cloud credentials to power the proxy.

GCP Authentication
Dashboard Security
Type a PIN to lock this dashboard behind a password screen.
Connection Info
Proxy Base URL http://localhost:8000
OpenAI Endpoint /v1/chat/completions
Anthropic Endpoint /v1/messages
Supported Models
gemini-2.5-flash gemini-2.5-pro gemini-1.5-flash gemini-1.5-pro claude-* → auto-mapped

API Keys

Generate keys to authenticate proxy requests from your apps.

No API keys yet. Click New Key to generate one.

Playground

Test your proxy with a live streaming chat session.

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Live Logs

Real-time stream of all proxy requests via WebSocket.

0 requests
proxy.log
⬤ Listening for requests…

Integration Guide

Copy-paste snippets to connect any SDK to your proxy.

curl http://localhost:8000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "gemini-2.5-flash",
    "messages": [{"role": "user", "content": "Hello!"}],
    "stream": true
  }'
from anthropic import Anthropic

client = Anthropic(
    api_key="YOUR_API_KEY",
    base_url="http://localhost:8000"
)

stream = client.messages.stream(
    model="claude-3-5-sonnet",   # auto-mapped to gemini-2.5-pro
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello!"}]
)

with stream as s:
    for text in s.text_stream:
        print(text, end="", flush=True)
import Anthropic from '@anthropic-ai/sdk';

const client = new Anthropic({
    apiKey: 'YOUR_API_KEY',
    baseURL: 'http://localhost:8000',
});

const stream = client.messages.stream({
    model: 'claude-3-5-sonnet',  // auto-mapped to gemini-2.5-pro
    max_tokens: 1024,
    messages: [{ role: 'user', content: 'Hello!' }],
});

for await (const chunk of stream) {
    if (chunk.type === 'content_block_delta')
        process.stdout.write(chunk.delta.text);
}
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="http://localhost:8000/v1"
)

stream = client.chat.completions.create(
    model="gemini-2.5-flash",
    messages=[{"role": "user", "content": "Hello!"}],
    stream=True
)

for chunk in stream:
    print(chunk.choices[0].delta.content or "", end="")
import OpenAI from 'openai';

const openai = new OpenAI({
    apiKey: 'YOUR_API_KEY',
    baseURL: 'http://localhost:8000/v1',
});

const stream = await openai.chat.completions.create({
    model: 'gemini-2.5-flash',
    messages: [{ role: 'user', content: 'Hello!' }],
    stream: true,
});

for await (const chunk of stream) {
    process.stdout.write(chunk.choices[0]?.delta?.content || '');
}
from google import genai

client = genai.Client(
    api_key="YOUR_API_KEY",
    http_options={"api_endpoint": "http://localhost:8000"}
)

response = client.models.generate_content(
    model='gemini-2.5-flash',
    contents='Hello!',
)
print(response.text)