Anthropic Agent SDK

sference serves the Anthropic Messages API at POST /v1/messages, so the anthropic Python and TypeScript SDKs — and the Claude Agent SDK built on them — work with a base-URL change. Your agent loop then runs on open models with the same code.

Install

pip install -U anthropic

Point the client at sference

import os
from anthropic import Anthropic

client = Anthropic(
    base_url="https://api.sference.com",
    api_key=os.environ["SFERENCE_API_KEY"],   # sent as x-api-key
)

Authorization: Bearer works too — pass auth_token instead of api_key if you prefer.

message = client.messages.create(
    model="moonshotai/Kimi-K3",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Explain prefix caching."}],
)
print(message.content[0].text)

Model names are sference catalog ids. There are no claude-* aliases — a Claude model name returns 400.

Tool use

Anthropic's tool schema is served natively:

tools = [{
    "name": "get_weather",
    "description": "Return the current weather for a city.",
    "input_schema": {
        "type": "object",
        "properties": {"city": {"type": "string"}},
        "required": ["city"],
    },
}]

message = client.messages.create(
    model="zai-org/GLM-5.3",
    max_tokens=1024,
    tools=tools,
    messages=[{"role": "user", "content": "What is the weather in Ljubljana?"}],
)

for block in message.content:
    if block.type == "tool_use":
        result = get_weather(**block.input)
        # append the assistant turn and the tool_result, then call again

Extended thinking

Reasoning models stream thinking blocks that clients render normally, but signature is always empty — multi-turn thinking continuity is best-effort. See Extended thinking.

message = client.messages.create(
    model="moonshotai/Kimi-K3",
    max_tokens=4096,
    thinking={"type": "enabled", "budget_tokens": 2048},
    messages=[{"role": "user", "content": "Plan a migration."}],
)

Streaming

with client.messages.stream(
    model="zai-org/GLM-5.3",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Write a haiku about GPUs."}],
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

The SSE event sequence matches api.anthropic.com; the full list is on the Anthropic Messages API page.

The Claude Agent SDK

The Claude Agent SDK drives Claude Code's agent loop. Point it at sference and the loop runs on open models:

export ANTHROPIC_BASE_URL="https://api.sference.com"
export ANTHROPIC_AUTH_TOKEN="$SFERENCE_API_KEY"
export ANTHROPIC_MODEL="moonshotai/Kimi-K3"

For the CLI-level equivalent with hybrid routing — sference models in the /model picker, real Claude models passing through — use the launcher:

sference launch claude

See Claude Code for proxy mode, model recommendations, and known limits.

Cost control

/v1/messages is realtime only — flex, background, and batch live on the OpenAI-shaped endpoints. Two levers still apply:

• prompt_cache_key is not available on /v1/messages. Prefix caching is automatic; hits appear as cache_read_input_tokens in the usage block. Keep the stable part of the prompt first so it can be reused. See Prompt caching.
• max_queue_wait_s is accepted — bound the wait and fail over to another provider. See Max queue wait.
• For long background steps, use the OpenAI-shaped surfaces. A research or summarization step that nobody waits on can run on /v1/responses with background: true at 0.5 × list, while the interactive turn stays on /v1/messages.

Known limits

The complete compatibility surface is on the Anthropic Messages API page.