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honcho
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chore: cleanup config, remove noisy logs

This commit is contained in:
Benjamin McCormick 2026-02-04 17:37:48 -05:00
parent 498dcb1e9f
commit dbb1f8cddb
8 changed files with 7 additions and 30 deletions
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2
.env.template
View File

@ -99,6 +99,8 @@ LLM_ANTHROPIC_API_KEY=your-anthropic-api-key-here
# DERIVER_PROVIDER=google
# DERIVER_MODEL=gemini-2.5-flash-lite
# DERIVER_TEMPERATURE=
# DERIVER_TOP_P=
# DERIVER_REPETITION_PENALTY=
# DERIVER_DEDUPLICATE=true
# DERIVER_MAX_OUTPUT_TOKENS=4096
# DERIVER_THINKING_BUDGET_TOKENS=1024

4
config.toml.example
View File

@ -76,7 +76,9 @@ STALE_SESSION_TIMEOUT_MINUTES = 5
# QUEUE_ERROR_RETENTION_SECONDS = 2592000 # 30 days
PROVIDER = "google"
MODEL = "gemini-2.5-flash-lite"
# TEMPERATURE = 0.0
# TEMPERATURE = 0.7
# TOP_P = 0.9
# REPETITION_PENALTY = 1.15
# BACKUP_PROVIDER = "anthropic"
# BACKUP_MODEL = "claude-haiku-4-5"
DEDUPLICATE = true

2
docs/v3/contributing/configuration.mdx
View File

@ -372,6 +372,8 @@ DERIVER_MAX_OUTPUT_TOKENS=4096
DERIVER_THINKING_BUDGET_TOKENS=1024
DERIVER_MAX_INPUT_TOKENS=23000 # Maximum input tokens for deriver
DERIVER_TEMPERATURE= # Optional temperature override (unset by default)
DERIVER_TOP_P= # Optional nucleus sampling override (unset by default)
DERIVER_REPETITION_PENALTY= # Optional repetition penalty override (unset by default)
# Backup provider (optional, must set both or neither)
# DERIVER_BACKUP_PROVIDER=anthropic

5
pyproject.toml
View File

@ -93,11 +93,6 @@ 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 = [

1
src/config.py
View File

@ -253,7 +253,6 @@ class DeriverSettings(BackupLLMSettingsMixin, HonchoSettings):
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

1
src/deriver/deriver.py
View File

@ -133,7 +133,6 @@ async def process_representation_tasks_batch(
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,

2
src/utils/agent_tools.py
View File

@ -1723,13 +1723,11 @@ async def create_tool_executor(
Returns:
String result describing what was done
"""
logger.info(f"[tool call] {tool_name} {tool_input}")
try:
handler = _TOOL_HANDLERS.get(tool_name)
if handler:
result = await handler(ctx, tool_input)
logger.info(f"[tool result] {tool_name} {result}")
return result
return f"Unknown tool: {tool_name}"

20
src/utils/clients.py
View File

@ -575,7 +575,6 @@ async def _stream_final_response(
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,
@ -621,7 +620,6 @@ async def _stream_final_response(
_get_effective_temperature(temperature),
top_p,
repetition_penalty,
no_repeat_ngram_size,
stop_seqs,
reasoning_effort,
verbosity,
@ -651,7 +649,6 @@ async def _execute_tool_loop(
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,
@ -756,7 +753,6 @@ async def _execute_tool_loop(
_get_effective_temperature(temperature),
top_p,
repetition_penalty,
no_repeat_ngram_size,
stop_seqs,
gpt5_reasoning_effort,
gpt5_verbosity,
@ -822,7 +818,6 @@ async def _execute_tool_loop(
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,
@ -958,7 +953,6 @@ async def _execute_tool_loop(
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,
@ -997,7 +991,6 @@ async def _execute_tool_loop(
_get_effective_temperature(temperature),
top_p,
repetition_penalty,
no_repeat_ngram_size,
stop_seqs,
reasoning_effort,
verbosity,
@ -1205,7 +1198,6 @@ async def honcho_llm_call(
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
@ -1237,7 +1229,6 @@ async def honcho_llm_call(
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
@ -1269,7 +1260,6 @@ async def honcho_llm_call(
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
@ -1301,7 +1291,6 @@ async def honcho_llm_call(
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
@ -1457,7 +1446,6 @@ async def honcho_llm_call(
_get_effective_temperature(temperature),
top_p,
repetition_penalty,
no_repeat_ngram_size,
stop_seqs,
gpt5_reasoning_effort,
gpt5_verbosity,
@ -1477,7 +1465,6 @@ async def honcho_llm_call(
_get_effective_temperature(temperature),
top_p,
repetition_penalty,
no_repeat_ngram_size,
stop_seqs,
gpt5_reasoning_effort,
gpt5_verbosity,
@ -1563,7 +1550,6 @@ async def honcho_llm_call(
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,
@ -1603,7 +1589,6 @@ async def honcho_llm_call_inner(
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
@ -1627,7 +1612,6 @@ async def honcho_llm_call_inner(
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
@ -1651,7 +1635,6 @@ async def honcho_llm_call_inner(
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
@ -1674,7 +1657,6 @@ async def honcho_llm_call_inner(
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
@ -1929,8 +1911,6 @@ async def honcho_llm_call_inner(
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