basemode 0.1.4

Make any LLM do raw text continuation

basemode

Make any LLM do raw text continuation.

basemode coerces chat-tuned models into clean next-token continuation mode (instead of assistant-style replies), with strategy selection handled per model/provider.

Install

pip install basemode

Set provider keys via environment variables or .env (for example OPENAI_API_KEY, ANTHROPIC_API_KEY, OPENROUTER_API_KEY, GEMINI_API_KEY, GROQ_API_KEY, TOGETHER_API_KEY).

Quickstart

# Single continuation (default model if configured, else fallback)
basemode "The ship rounded the headland and"

# Parallel continuations
basemode "The ship rounded the headland and" -n 3

# Inspect selected strategy and pricing metadata
basemode info claude-sonnet-4-6

# Show only key-configured models
basemode models --available

CLI

basemode --help
basemode run --help
basemode models --help
basemode info --help
basemode strategies --help

Useful commands:

• basemode run (default): stream continuation text
• basemode models: list models (supports --verified and --json for picker UIs)
• basemode providers: list provider IDs
• basemode info: show normalized model + prompt strategy + pricing metadata
• basemode default: get/set your default model
• basemode keys: manage stored API keys

Python API

from basemode import continue_text, branch_text

async for token in continue_text(
    "The ship rounded the headland and",
    model="gpt-4o-mini",
    max_tokens=120,
):
    print(token, end="", flush=True)

async for idx, token in branch_text(
    "The ship rounded the headland and",
    model="gpt-4o-mini",
    n=3,
    max_tokens=80,
):
    print(idx, token, end="", flush=True)

Docs

Full docs are in docs/ and can be served with MkDocs:

make docs-serve

Then open http://localhost:8001.

Integration Health Checks

Run live provider checks (real APIs, key-aware skips):

uv run pytest -m integration tests/test_integration.py -q

This writes a machine-readable report to dist/integration/provider_health.json with per-model status, latency, token estimates, and estimated USD cost.

Verified Models

Single generated table, refreshed by CI.

Model	Input cost (/1M)	Output cost (/1M)	Release date	Prompt method	Reliability
anthropic/claude-haiku-4-5-20251001	$1.00	$5.00	2025-10-01	prefill	✓
anthropic/claude-opus-4-1-20250805	$15.00	$75.00	2025-08-05	prefill	✓
anthropic/claude-opus-4-20250514	$15.00	$75.00	2025-05-22	prefill	✓
anthropic/claude-opus-4-5-20251101	$5.00	$25.00	2025-11-24	prefill	✓
anthropic/claude-opus-4-6	$5.00	$25.00	2026-02-05	system	✓
anthropic/claude-opus-4-7	$5.00	$25.00	2026-04-16	system	✓
anthropic/claude-sonnet-4-20250514	$3.00	$15.00	2025-05-22	prefill	✓
anthropic/claude-sonnet-4-5-20250929	$3.00	$15.00	2025-09-29	prefill	✓
anthropic/claude-sonnet-4-6	$3.00	$15.00	2026-02-17	system	✓
gemini/gemini-2.5-flash	$0.30	$2.50	2025-06-17	system	⚠
gemini/gemini-2.5-pro	$1.25	$10.00	2025-06-17	system	⚠
gemini/gemma-4-26b-a4b-it	$0.07	$0.35	2026-04-03	system	⚠
gemini/gemma-4-31b-it	$0.13	$0.38	2026-04-02	system	⚠
moonshot/kimi-k2-0905-preview	$0.60	$2.50	2025-07-11	system	⚠
moonshot/kimi-k2.5	$0.60	$3.00	2026-01-27	system	⚠
openai/gpt-4o-mini	$0.15	$0.60	2024-07-18	system	⚠
openai/gpt-5.4-mini	$0.75	$4.50	2026-03-17	system	✓
openrouter/moonshotai/kimi-k2.6	$0.60	$2.80	2026-04-20	system	⚠
zai/glm-4.7	$0.60	$2.20	2025-12-22	system	✓
zai/glm-5	$1.00	$3.20	2026-02-11	system	✓

Legend: ✓ = LiteLLM pricing present and release date available; ⚠ = missing/approximate field or known issue.