basemode
Make chat-tuned LLMs continue text instead of answering it.
basemode provides raw text continuation through the terminal, an async Python
API, and an OpenAI-compatible completions server. It selects a prompting method
for each model and repairs common artifacts at the join between the prompt and
the generated text.
The problem
Ask a chat model to continue a passage and it may answer with an introduction, quote the continuation, or offer to revise it:
> The ship rounded the headland and
I'd be happy to help continue this passage! Here's one possibility:
"The ship rounded the headland and the harbour opened before them..."
Would you like me to continue in a different style?
With basemode, the same prefix produces continuation text directly:
$ basemode "The ship rounded the headland and"
The ship rounded the headland and the wind dropped all at once, as though
the cliffs had swallowed it. Sails that had been drum-tight for three days
went slack, and in the sudden quiet the crew could hear water moving along
the hull.
Install
pip install basemode
Requires Python 3.11 or later. Set the relevant provider key in the environment
or a .env file, or save it with basemode keys set PROVIDER.
Quickstart
# Continue a prefix
basemode "The ship rounded the headland and"
# Parallel continuations
basemode "The ship rounded the headland and" -n 3
# Or just ask a question, like `llm`
basemode ask "why is the sky blue?" -m claude-haiku-4-5
cat notes.md | basemode ask "summarise this"
# Inspect selected strategy and pricing metadata
basemode info claude-sonnet-4-6
# Compare prompting methods and save the best result
basemode bench claude-sonnet-4-6 --save
# Show only key-configured models
basemode models --available
Set a default model with basemode default MODEL. Without one, generation uses
gpt-4o-mini. See the installation guide
for provider-key names and source installation.
Commands
basemode --help
basemode run --help
basemode models --help
basemode info --help
basemode strategies --help
basemode run: stream one or more continuations; this is the default commandbasemode ask: ask a question and stream a normal chat answer (stdin is prepended)basemode models: list known models and filter by provider or availabilitybasemode info: inspect a model's normalized ID, strategy, quirks, price, and local healthbasemode bench: compare strategies using live requests and optionally pin the winnerbasemode verify: collect durable compatibility evidence with bounded live probesbasemode serve: expose an OpenAI-compatible/v1/completionsendpointbasemode keys,default, andrate: manage local preferences
How strategy selection works
Different models respond to different prompt shapes: native completion,
assistant prefill, a system instruction, few-shot examples, or FIM tokens.
basemode chooses in this order:
- A strategy supplied for the current call.
- A local pin saved by
basemode bench --save. - The strategy recorded in the verified-model registry.
- A model-name heuristic.
basemode info MODEL reports the selected strategy and its source. bench
compares strategies on prose, technical writing, poetry, and dialogue, then
scores assistant preambles, refusals, echoed prefixes, chat turns, and stray
formatting.
basemode bench claude-opus-5 --samples # compare
basemode bench claude-opus-5 --save # pin the winner for this model
┏━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┓
┃ Strategy ┃ Score ┃ Flags / error ┃ Mean s ┃
┡━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━┩
│ few_shot │ 0.93 │ quoted │ 2.07 │
│ system │ 0.75 │ empty │ 2.24 │
│ prefill │ 0.00 │ BadRequestError: ... │ 0.30 │
└──────────┴───────┴──────────────────────┴────────┘
See Strategies for the prompt shapes, scoring rules, and override behavior.
Server
basemode serve exposes POST /v1/completions for clients that support the
classic OpenAI completions API, including
Tapestry Loom.
pip install 'basemode[server]'
basemode serve --port 8080
Set the client endpoint to http://127.0.0.1:8080/v1/completions. Responses
are synchronous JSON; streaming and logprobs are not supported. The
CLI reference
lists accepted fields.
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)
Documentation and development
The documentation covers configuration, strategy behavior, model evidence, and the complete CLI and Python APIs. To build it locally:
make docs-serve
For repository setup and test commands, see the agent quickstart.
Verified models
The registry currently contains 297 model endpoints with a tested prompt strategy. The full model table lists prices, release dates, strategies, and compatibility quirks. It is generated from the same registry used at runtime.
Metadata
Release files for basemode 0.1.50
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| basemode-0.1.50.tar.gz | 1.2 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| basemode-0.1.50-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.1 MB
Release files / basemode-0.1.50.tar.gz
| Download URL | basemode-0.1.50.tar.gz |
|---|---|
| Size | 1.2 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / basemode-0.1.50-py3-none-any.whl
| Download URL | basemode-0.1.50-py3-none-any.whl |
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| Size | 890.5 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
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