Configure your client

You signed up, you have a key. Now you need to point your client at ByteSpike instead of a model vendor’s own gateway. The whole gateway lives at https://llm.bytespike.ai — every protocol, every model. Pick the protocol that matches your client, set two env vars, and you’re done.

1. Get an API key

Sign in to console.bytespike.ai/keys and Create key. Pick the routing group (claude-default for Claude models, gemini-default for Gemini, or default to route everything — see Models for what’s in each group). The plaintext is shown once at creation — store it. Format: sk-byts-….

Treat the key like a database password. Each key binds to one routing group; create separate keys for each model family you want to reach instead of trying to put one key everywhere.

2. Pick a protocol

Three protocols hit the same gateway. Pick whichever your client speaks natively — billing, throttling, and credit accounting are identical across all three. The URL you use depends on whether you’re driving an SDK (which auto-appends the endpoint path) or hand-rolling curl / REST (where you write the full path yourself).

SDK base URL

Set this as ANTHROPIC_BASE_URL / OPENAI_BASE_URL / Gemini client endpoint. The SDK appends /v1/messages, /chat/completions, or /models/{model}:generateContent for you.

Protocol	SDK base URL	Typical clients
Anthropic Messages	`https://llm.bytespike.ai`	Claude Code, Claude Desktop, Anthropic SDK
OpenAI Chat Completions	`https://llm.bytespike.ai/v1`	OpenAI SDK, Cherry Studio, NextChat, LobeChat
Gemini Native	`https://llm.bytespike.ai/v1beta`	Google AI Studio examples, vertex-compat clients

Full endpoint (curl / REST) [#full-endpoint]

If you’re calling the gateway with curl or any client that needs the literal request URL, use the full endpoint instead. This is what the console’s Keys → EndpointBanner copies.

Protocol	Full endpoint
Anthropic	`https://llm.bytespike.ai/v1/messages`
OpenAI	`https://llm.bytespike.ai/v1/chat/completions`
Gemini	`https://llm.bytespike.ai/v1beta/models/{model}:generateContent`

Gemini’s path needs the model id baked into the URL (e.g. gemini-3.1-pro:generateContent); the other two take the model in the JSON body.

3. Set the env vars

Anthropic Messages
OpenAI Chat Completions
Gemini Native

For Claude Code and the Anthropic SDK, two env vars are all you need:

export ANTHROPIC_BASE_URL=https://llm.bytespike.ai
export ANTHROPIC_API_KEY=sk-byts-...

Any client that reads these standard vars (Claude Code, Anthropic Python / TypeScript SDK, third-party clients) picks them up transparently. Then call any Anthropic-compatible model:

import anthropic
client = anthropic.Anthropic()  # reads env vars
msg = client.messages.create(
    model="claude-sonnet-4-6",
    max_tokens=1024,
    messages=[{"role": "user", "content": "hi"}],
)

Or, with the full endpoint via curl:

curl https://llm.bytespike.ai/v1/messages \
  -H "x-api-key: sk-byts-..." \
  -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d '{
    "model": "claude-sonnet-4-6",
    "max_tokens": 64,
    "messages": [{"role": "user", "content": "hi"}]
  }'

OpenAI’s SDK takes the base URL as a constructor arg:

from openai import OpenAI
client = OpenAI(
    base_url="https://llm.bytespike.ai/v1",
    api_key="sk-byts-...",
)
r = client.chat.completions.create(
    model="gemini-3-1-pro",      # any ByteSpike model id works
    messages=[{"role": "user", "content": "hi"}],
)

Or with env vars on most OpenAI-compat clients:

export OPENAI_BASE_URL=https://llm.bytespike.ai/v1
export OPENAI_API_KEY=sk-byts-...

Full endpoint via curl:

curl https://llm.bytespike.ai/v1/chat/completions \
  -H "Authorization: Bearer sk-byts-..." \
  -H "content-type: application/json" \
  -d '{
    "model": "gpt-5-4",
    "messages": [{"role": "user", "content": "hi"}]
  }'

Google’s native protocol passes the key as a query param:

curl "https://llm.bytespike.ai/v1beta/models/gemini-3.1-pro:generateContent?key=sk-byts-..." \
  -H "content-type: application/json" \
  -d '{
    "contents": [{"parts": [{"text": "hi"}]}]
  }'

Vertex/AI-Studio SDKs that read GEMINI_API_KEY and let you override the endpoint will work the same way.

4. Pick a model

One key calls every model regardless of which vendor originally made it. You don’t need a separate Anthropic / OpenAI / Google / DeepSeek subscription — ByteSpike serves them all through one endpoint. Common model IDs (full catalog at Console → Models or via GET /v1/models):

Family	Use these ids
Claude	`claude-opus-4-8`, `claude-sonnet-4-6`, `claude-haiku-4-5`
GPT-5	`gpt-5-5`, `gpt-5-4`, `gpt-5-4-mini`, `gpt-5-4-nano`, `gpt-5-2`
Gemini	`gemini-3-1-pro`, `gemini-3-5-flash`, `gemini-2-5-flash`
DeepSeek	`deepseek-v4-pro`, `deepseek-v4-flash`, `deepseek-v3-2`, `deepseek-v3-anthropic`
Kimi / GLM / MiniMax / Doubao	`kimi-k2-6`, `glm-5-1`, `minimax-m2-7`, `doubao-seed-2-0-pro`
Image	`seedream-4-5`, `seedream-v5lite`, `nano-banana`, `nano-banana-v2`, `gpt-image-2`
Video	`sora2`, `sora2-pro`, `veo3-1`, `veo3-1-fast`, `seedance-pro`, `seedance-1-5-pro`

A model id is the same string regardless of which protocol you use — claude-sonnet-4-6 works on Anthropic Messages, OpenAI Chat Completions, and Gemini Native.

5. Client-specific setup

Claude Code (CLI / agent)

Claude Code reads ANTHROPIC_BASE_URL and ANTHROPIC_API_KEY automatically. Add to your shell profile:

# ~/.zshrc or ~/.bashrc
export ANTHROPIC_BASE_URL=https://llm.bytespike.ai
export ANTHROPIC_API_KEY=sk-byts-...

Then claude calls every Anthropic-protocol model through ByteSpike.

Claude Desktop

Open Settings → Developer → Edit Config. Add the env vars under your OS’s section. Restart the app for the change to take.

Cherry Studio

Settings → Model Providers → Add Provider → “OpenAI Compatible”. Base URL: https://llm.bytespike.ai/v1. API key: your ByteSpike key. Then any of the model ids from the table above works.

NextChat / ChatGPT-Next-Web

Settings → Custom Endpoint. API URL: https://llm.bytespike.ai/v1. API Key: your ByteSpike key. Model: any of the ids above.

OpenAI SDK (Python / TypeScript)

Pass base_url / baseURL in the client constructor. The model string is the only thing that changes per call.Python:

from openai import OpenAI
OpenAI(base_url="https://llm.bytespike.ai/v1", api_key="sk-byts-...")

TypeScript:

import OpenAI from "openai"
new OpenAI({ baseURL: "https://llm.bytespike.ai/v1", apiKey: "sk-byts-..." })

6. Verify the wiring

Hit /v1/models to confirm the key is live and see what your account can actually call:

curl https://llm.bytespike.ai/v1/models \
  -H "Authorization: Bearer sk-byts-..."

The response is a JSON array of model objects. data[].id should include every model your tier exposes. If the list is short and you expected more, check console.bytespike.ai/account — your allowed_models may be capped by an org default or admin policy.

Errors come back in the protocol’s native shape. A 401 means the key is wrong; a 403 means the key is fine but the model isn’t on your tier; a 402 means out of credits — top up at console.bytespike.ai/billing.

Next steps

Authentication — full header reference + key management
Models — per-model rate cards and capability tags
Error handling — retry semantics + status codes

​1. Get an API key

​2. Pick a protocol

​SDK base URL

​Full endpoint (curl / REST) [#full-endpoint]

​3. Set the env vars

​4. Pick a model

​5. Client-specific setup

​6. Verify the wiring

​Next steps

1. Get an API key

2. Pick a protocol

SDK base URL

Full endpoint (curl / REST) [#full-endpoint]

3. Set the env vars

4. Pick a model

5. Client-specific setup

6. Verify the wiring

Next steps