fewertokens

Python SDK for FewerTokens — a control-plane client for cross-family LLM routing.

The SDK asks FewerTokens which provider/model to use, then calls that model locally via LiteLLM with your provider keys. Usage is reported back asynchronously.

Install

pip install fewertokens

Quick start

from fewertokens import FewerTokens

ft = FewerTokens(
    api_key="ft_live_...",
    openai_api_key="sk-proj-...",      # Optional
    anthropic_api_key="sk-ant-...",    # Optional
    gemini_api_key="AIzaSy...",        # Optional
    base_url="https://api.fewertokens.in",
)

response = ft.chat.completions.create(
    messages=[{"role": "user", "content": "What is Python?"}],
)
print(response.content)
print(response.routing.provider, response.routing.model_used)
print(response.usage)

How it works

1. Route handshake — POST /v1/route with prompt text + available_providers
2. Local dispatch — litellm.completion / acompletion with the routed provider key
3. Telemetry — background POST /v1/telemetry with route_id + token usage (never blocks or raises)

Privacy & Security

🔒 Privacy & Security First:

• Zero Key Exposure: Your provider keys stay strictly in your client runtime's RAM memory and are never sent to FewerTokens servers.
• Direct Local Execution: Prompt content and response streams flow directly between your machine and LLM provider endpoints (OpenAI, Anthropic, Gemini, etc.). FewerTokens only processes prompt text for routing decisions (~20ms) and never sees or logs completion payloads.

Streaming

for chunk in ft.chat.completions.create(
    messages=[{"role": "user", "content": "Explain Docker"}],
    stream=True,
):
    print(chunk.content, end="", flush=True)

Async

response = await ft.chat.completions.acreate(
    messages=[{"role": "user", "content": "Hello!"}],
)

Notes

• At least one of openai_api_key, anthropic_api_key, or gemini_api_key is required.
• String shorthand: prompt="Hello" is accepted as an alternative to messages=.