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honcho
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(feat) Updaate deriver prompt and sampling parameters

This commit is contained in:
3un01a 2026-02-04 12:37:13 -08:00
parent e93e57175e
commit 535b486378
4 changed files with 80 additions and 0 deletions
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5
pyproject.toml
View File

@ -93,6 +93,11 @@ asyncio_default_fixture_loop_scope = "session"
addopts = "--strict-markers --cov=src/ --cov=sdks/python/src/honcho --cov-report=term-missing --ignore=tests/alembic"
testpaths = ["tests"]
pythonpath = ["src"]
filterwarnings = [
"ignore::DeprecationWarning:cashews.*:",
"ignore::DeprecationWarning:websockets.*:",
"ignore::DeprecationWarning:uvicorn.*:",
]
[tool.coverage.report]
exclude_lines = [

3
src/config.py
View File

@ -251,6 +251,9 @@ class DeriverSettings(BackupLLMSettingsMixin, HonchoSettings):
PROVIDER: SupportedProviders = "google"
MODEL: str = "gemini-2.5-flash-lite"
TEMPERATURE: float | None = None
TOP_P: float | None = None
REPETITION_PENALTY: float | None = None
NO_REPEAT_NGRAM_SIZE: int | None = None
# Whether to deduplicate documents when creating them
DEDUPLICATE: bool = True

3
src/deriver/deriver.py
View File

@ -131,6 +131,9 @@ async def process_representation_tasks_batch(
response_model=PromptRepresentation,
json_mode=True,
temperature=settings.DERIVER.TEMPERATURE,
top_p=settings.DERIVER.TOP_P,
repetition_penalty=settings.DERIVER.REPETITION_PENALTY,
no_repeat_ngram_size=settings.DERIVER.NO_REPEAT_NGRAM_SIZE,
stop_seqs=[" \n", "\n\n\n\n"],
thinking_budget_tokens=settings.DERIVER.THINKING_BUDGET_TOKENS,
max_input_tokens=settings.DERIVER.MAX_INPUT_TOKENS,

69
src/utils/clients.py
View File

@ -573,6 +573,9 @@ async def _stream_final_response(
response_model: type[BaseModel] | None,
json_mode: bool,
temperature: float | None,
top_p: float | None,
repetition_penalty: float | None,
no_repeat_ngram_size: int | None,
stop_seqs: list[str] | None,
reasoning_effort: ReasoningEffortType,
verbosity: VerbosityType,
@ -616,6 +619,9 @@ async def _stream_final_response(
response_model,
json_mode,
_get_effective_temperature(temperature),
top_p,
repetition_penalty,
no_repeat_ngram_size,
stop_seqs,
reasoning_effort,
verbosity,
@ -643,6 +649,9 @@ async def _execute_tool_loop(
response_model: type[BaseModel] | None,
json_mode: bool,
temperature: float | None,
top_p: float | None,
repetition_penalty: float | None,
no_repeat_ngram_size: int | None,
stop_seqs: list[str] | None,
reasoning_effort: ReasoningEffortType,
verbosity: VerbosityType,
@ -745,6 +754,9 @@ async def _execute_tool_loop(
response_model,
json_mode,
_get_effective_temperature(temperature),
top_p,
repetition_penalty,
no_repeat_ngram_size,
stop_seqs,
gpt5_reasoning_effort,
gpt5_verbosity,
@ -808,6 +820,9 @@ async def _execute_tool_loop(
response_model=response_model,
json_mode=json_mode,
temperature=temperature,
top_p=top_p,
repetition_penalty=repetition_penalty,
no_repeat_ngram_size=no_repeat_ngram_size,
stop_seqs=stop_seqs,
reasoning_effort=reasoning_effort,
verbosity=verbosity,
@ -941,6 +956,9 @@ async def _execute_tool_loop(
response_model=response_model,
json_mode=json_mode,
temperature=temperature,
top_p=top_p,
repetition_penalty=repetition_penalty,
no_repeat_ngram_size=no_repeat_ngram_size,
stop_seqs=stop_seqs,
reasoning_effort=reasoning_effort,
verbosity=verbosity,
@ -977,6 +995,9 @@ async def _execute_tool_loop(
response_model,
json_mode,
_get_effective_temperature(temperature),
top_p,
repetition_penalty,
no_repeat_ngram_size,
stop_seqs,
reasoning_effort,
verbosity,
@ -1182,6 +1203,9 @@ async def honcho_llm_call(
response_model: type[M],
json_mode: bool = False,
temperature: float | None = None,
top_p: float | None = None,
repetition_penalty: float | None = None,
no_repeat_ngram_size: int | None = None,
stop_seqs: list[str] | None = None,
reasoning_effort: Literal["low", "medium", "high", "minimal"]
| None = None, # OpenAI only
@ -1211,6 +1235,9 @@ async def honcho_llm_call(
response_model: None = None,
json_mode: bool = False,
temperature: float | None = None,
top_p: float | None = None,
repetition_penalty: float | None = None,
no_repeat_ngram_size: int | None = None,
stop_seqs: list[str] | None = None,
reasoning_effort: Literal["low", "medium", "high", "minimal"]
| None = None, # OpenAI only
@ -1240,6 +1267,9 @@ async def honcho_llm_call(
response_model: type[BaseModel] | None = None,
json_mode: bool = False,
temperature: float | None = None,
top_p: float | None = None,
repetition_penalty: float | None = None,
no_repeat_ngram_size: int | None = None,
stop_seqs: list[str] | None = None,
reasoning_effort: Literal["low", "medium", "high", "minimal"]
| None = None, # OpenAI only
@ -1269,6 +1299,9 @@ async def honcho_llm_call(
response_model: type[BaseModel] | None = None,
json_mode: bool = False,
temperature: float | None = None,
top_p: float | None = None,
repetition_penalty: float | None = None,
no_repeat_ngram_size: int | None = None,
stop_seqs: list[str] | None = None,
reasoning_effort: Literal["low", "medium", "high", "minimal"]
| None = None, # OpenAI only
@ -1422,6 +1455,9 @@ async def honcho_llm_call(
response_model,
json_mode,
_get_effective_temperature(temperature),
top_p,
repetition_penalty,
no_repeat_ngram_size,
stop_seqs,
gpt5_reasoning_effort,
gpt5_verbosity,
@ -1439,6 +1475,9 @@ async def honcho_llm_call(
response_model,
json_mode,
_get_effective_temperature(temperature),
top_p,
repetition_penalty,
no_repeat_ngram_size,
stop_seqs,
gpt5_reasoning_effort,
gpt5_verbosity,
@ -1522,6 +1561,9 @@ async def honcho_llm_call(
response_model=response_model,
json_mode=json_mode,
temperature=temperature,
top_p=top_p,
repetition_penalty=repetition_penalty,
no_repeat_ngram_size=no_repeat_ngram_size,
stop_seqs=stop_seqs,
reasoning_effort=reasoning_effort,
verbosity=verbosity,
@ -1559,6 +1601,9 @@ async def honcho_llm_call_inner(
response_model: type[M],
json_mode: bool = False,
temperature: float | None = None,
top_p: float | None = None,
repetition_penalty: float | None = None,
no_repeat_ngram_size: int | None = None,
stop_seqs: list[str] | None = None,
reasoning_effort: Literal["low", "medium", "high", "minimal"]
| None = None, # OpenAI only
@ -1580,6 +1625,9 @@ async def honcho_llm_call_inner(
response_model: None = None,
json_mode: bool = False,
temperature: float | None = None,
top_p: float | None = None,
repetition_penalty: float | None = None,
no_repeat_ngram_size: int | None = None,
stop_seqs: list[str] | None = None,
reasoning_effort: Literal["low", "medium", "high", "minimal"]
| None = None, # OpenAI only
@ -1601,6 +1649,9 @@ async def honcho_llm_call_inner(
response_model: type[BaseModel] | None = None,
json_mode: bool = False,
temperature: float | None = None,
top_p: float | None = None,
repetition_penalty: float | None = None,
no_repeat_ngram_size: int | None = None,
stop_seqs: list[str] | None = None,
reasoning_effort: Literal["low", "medium", "high", "minimal"]
| None = None, # OpenAI only
@ -1621,6 +1672,9 @@ async def honcho_llm_call_inner(
response_model: type[BaseModel] | None = None,
json_mode: bool = False,
temperature: float | None = None,
top_p: float | None = None,
repetition_penalty: float | None = None,
no_repeat_ngram_size: int | None = None,
stop_seqs: list[str] | None = None,
reasoning_effort: Literal["low", "medium", "high", "minimal"]
| None = None, # OpenAI only
@ -1865,6 +1919,21 @@ async def honcho_llm_call_inner(
if temperature is not None and "gpt-5" not in model:
openai_params["temperature"] = temperature
# Add generation parameters for explicit control
if top_p is not None:
openai_params["top_p"] = top_p
# Add vLLM-specific parameters only for vLLM provider
# These are not standard OpenAI API parameters and must be passed via extra_body
if provider == "vllm":
extra_body: dict[str, Any] = {}
if repetition_penalty is not None:
extra_body["repetition_penalty"] = repetition_penalty
if no_repeat_ngram_size is not None:
extra_body["no_repeat_ngram_size"] = no_repeat_ngram_size
if extra_body:
openai_params["extra_body"] = extra_body
if "gpt-5" in model:
openai_params["max_completion_tokens"] = params["max_tokens"]
if reasoning_effort: