Find numeric answers with Jev through repeated higher, lower, or exactly
decisions. Supply a question and bounds; the library calculates the guesses
using the official TypeSafe Python SDK.
Requires Python 3.10 or newer. Install from PyPI:
pip install jev-bisect
export TYPESAFE_API_KEY="your-typesafe-api-key"
python
from jev_bisect import bisect
result = bisect(
"How many slices in a pizza?",
min=0,
max=100,
)
print(result.answer)
print(result.turns)
min and max are required keyword arguments and must be finite numbers with
min < max. Omit last_guess or pass None to start at the midpoint.
To choose the first guess, supply an override such as
bisect(question, min=0, max=100, last_guess=25).
A result is returned only after Jev selects exactly. It contains answer,
turns, the final state, and history. Each history entry records the
state, choice, confidence, probabilities, and model version.
from jev_bisect import SearchConfig, bisect
result = bisect(
"What is pi?",
min=3,
max=4,
config=SearchConfig(precision=0.01, max_turns=10),
)
print(result.answer) # 3.14 if Jev makes the correct comparisons
| Field | Default | Meaning |
|---|---|---|
precision |
1 |
Smallest search increment; a positive finite int orfloat . |
max_turns |
20 |
Maximum evaluated guesses; an integer from 1 through 20. |
Omitting config or passing None uses these defaults. Both settings belong
in SearchConfig. Each evaluated guess counts as one turn, including the
initial midpoint. SDK retries are disabled for these calls.
Candidates are multiples of precision measured from zero: 1 searches
whole numbers, 0.01 searches hundredths, and 2.5 searches values such as
0, 2.5, and 5. Jev is instructed to round the answer to the nearest
multiple before comparing, with halfway values rounded away from zero.
Precision specifies search resolution, not significant digits or an error
tolerance.
After higher or lower, the current guess is excluded and the next guess
is the floor midpoint of the remaining candidates. For min=0, max=100 at
default precision, the choices higher, lower, exactly evaluate 50,
75, and 62. Rounding down also applies to negative numbers: the first
guess for min=-5, max=0 is -3.
Bounds snap inward to the candidate grid. With min=0.001, max=0.019 and
precision 0.01, the only candidate is 0.01. With min=0.1, max=5.9 and
precision 1, candidates are the integers 1 through 5. Any explicit
last_guess must be within the bounds and a multiple of precision.
Endpoints on the grid are reachable. A valid search may narrow internally to
one candidate, which still needs an exactly decision. Choose bounds that
contain the rounded answer; the search does not expand them. A large range
or fine precision may require more guesses than the configured limit, and
Jev can make incorrect comparisons.
Guesses use exact rational arithmetic and integer candidate indexes internally.
Whole-number increments, including 1.0, return integers; fractional increments
return floats. Trailing zeros are not preserved.
| Exception | Condition |
|---|---|
ValueError |
Invalid bounds ( bisect requiresmin < max ), config, question, model, or starting guess. |
SearchExhaustedError |
No candidate within bounds, no possible next guess, or a candidate cannot be represented as a float at the configured precision. |
MaxTurnsExceededError |
No exactly decision withinmax_turns . |
Failures during the model loop include the last evaluated state and completed
history; MaxTurnsExceededError also includes max_turns. Exhaustion before
any evaluation has state=None and empty history. SDK errors propagate.
from jev_bisect import MaxTurnsExceededError, SearchExhaustedError, bisect
try:
result = bisect("How many minutes are in three hours?", min=0, max=300)
except (MaxTurnsExceededError, SearchExhaustedError) as error:
print(error)
print(error.state, error.history)
else:
print(result.answer)
advance performs one step without an API call and returns a SearchState.
When last_guess is omitted, the choice applies to the bounds' midpoint.
Supply the returned bounds and guess for the next step, using the same config.
If the returned bounds are equal, pass last_guess to evaluate the remaining
candidate: exactly returns that state, while higher or lower raises
SearchExhaustedError. Without last_guess, advance requires min < max.
from jev_bisect import advance
state = advance("higher", min=0, max=100)
assert state.to_dict() == {"max": 100, "min": 51, "last_guess": 75}
state = advance("lower", min=state.min, max=state.max, last_guess=state.last_guess)
assert state.last_guess == 62
python
from typesafe_sdk import TypeSafeClient
from jev_bisect import bisect
with TypeSafeClient() as client:
result = bisect(
"How many centimeters are in three quarters of a meter?",
min=0,
max=100,
client=client,
model="jev-1.13.0",
)
The default model is jev-latest. A supplied
client remains open; otherwise, bisect creates and closes its own client on
success or error.
pip install -e '.[dev]'
pytest
ruff check .
python -m build
Tests use deterministic responses and a mock HTTP transport, requiring no API key or network requests.
Update version in pyproject.toml for each new release, then build and check
the wheel and source distribution:
pip install -e '.[dev,release]'
pytest
ruff check .
python -m build
python -m twine check --strict dist/*
These commands prepare files locally. When ready to publish, set
TWINE_USERNAME=__token__ and TWINE_PASSWORD to a PyPI API token, then upload
only the files for that release:
python -m twine upload dist/jev_bisect-0.1.0-py3-none-any.whl dist/jev_bisect-0.1.0.tar.gz
MIT; see LICENSE.