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honcho
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chore: code review

This commit is contained in:
Benjamin McCormick 2025-11-11 17:42:25 -05:00
parent 3186d2ce39
commit d58c36d100
4 changed files with 155 additions and 138 deletions
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32
.env.template
View File

@ -89,14 +89,18 @@ LLM_ANTHROPIC_API_KEY=your-anthropic-api-key-here
# DERIVER_WORKING_REPRESENTATION_MAX_OBSERVATIONS=100
# DERIVER_REPRESENTATION_BATCH_MAX_TOKENS=4096
# DERIVER_MAX_INPUT_TOKENS=23000
# DERIVER_BACKUP_PROVIDER=
# DERIVER_BACKUP_MODEL=
# =============================================================================
# Peer Card Configuration
# =============================================================================
# ENABLED=true
# PROVIDER=openai
# MODEL=gpt-5-nano-2025-08-07
# MAX_OUTPUT_TOKENS=4000
# PEER_CARD_ENABLED=true
# PEER_CARD_PROVIDER=openai
# PEER_CARD_MODEL=gpt-5-nano-2025-08-07
# PEER_CARD_MAX_OUTPUT_TOKENS=4000
# PEER_CARD_BACKUP_PROVIDER=
# PEER_CARD_BACKUP_MODEL=
# =============================================================================
# Dialectic Settings
@ -111,6 +115,8 @@ LLM_ANTHROPIC_API_KEY=your-anthropic-api-key-here
# DIALECTIC_SEMANTIC_SEARCH_MAX_DISTANCE=0.85
# DIALECTIC_THINKING_BUDGET_TOKENS=1024
# DIALECTIC_CONTEXT_WINDOW_SIZE=100000
# DIALECTIC_BACKUP_PROVIDER=
# DIALECTIC_BACKUP_MODEL=
# =============================================================================
# Summary Settings
@ -119,10 +125,26 @@ LLM_ANTHROPIC_API_KEY=your-anthropic-api-key-here
# SUMMARY_MESSAGES_PER_SHORT_SUMMARY=20
# SUMMARY_MESSAGES_PER_LONG_SUMMARY=60
# SUMMARY_PROVIDER=google
# SUMMARY_MODEL=gemini-1.5-flash-latest
# SUMMARY_MODEL=gemini-2.5-flash
# SUMMARY_MAX_TOKENS_SHORT=1000
# SUMMARY_MAX_TOKENS_LONG=2000
# SUMMARY_THINKING_BUDGET_TOKENS=512
# SUMMARY_BACKUP_PROVIDER=
# SUMMARY_BACKUP_MODEL=
# =============================================================================
# Dream Settings
# =============================================================================
# DREAM_ENABLED=true
# DREAM_DOCUMENT_THRESHOLD=50
# DREAM_IDLE_TIMEOUT_MINUTES=60
# DREAM_MIN_HOURS_BETWEEN_DREAMS=8
# DREAM_ENABLED_TYPES=["consolidate"]
# DREAM_PROVIDER=openai
# DREAM_MODEL=gpt-4o-mini-2024-07-18
# DREAM_MAX_TOKENS=2000
# DREAM_BACKUP_PROVIDER=
# DREAM_BACKUP_MODEL=
# =============================================================================
# Webhook Settings

25
config.toml.example
View File

@ -63,9 +63,11 @@ WORKERS = 1
POLLING_SLEEP_INTERVAL_SECONDS = 1.0
STALE_SESSION_TIMEOUT_MINUTES = 5
PROVIDER = "google"
MODEL = "gemini-2.0-flash-lite"
MODEL = "gemini-2.5-flash-lite"
MAX_OUTPUT_TOKENS = 2500
THINKING_BUDGET_TOKENS = 1024 # only applied when using Anthropic
# BACKUP_PROVIDER = "google"
# BACKUP_MODEL = "gemini-2.5-flash-lite"
WORKING_REPRESENTATION_MAX_OBSERVATIONS = 100
REPRESENTATION_BATCH_MAX_TOKENS = 4096
@ -77,6 +79,8 @@ ENABLED = true
PROVIDER = "openai"
MODEL = "gpt-5-nano-2025-08-07"
MAX_OUTPUT_TOKENS = 4000
# BACKUP_PROVIDER = "google"
# BACKUP_MODEL = "gemini-2.5-flash-lite"
# Dialectic settings
[dialectic]
@ -90,6 +94,8 @@ SEMANTIC_SEARCH_TOP_K = 10
SEMANTIC_SEARCH_MAX_DISTANCE = 0.85
THINKING_BUDGET_TOKENS = 1024
CONTEXT_WINDOW_SIZE = 100000
# BACKUP_PROVIDER = "google"
# BACKUP_MODEL = "gemini-2.5-flash"
# Summary settings
[summary]
@ -97,10 +103,25 @@ ENABLED = true
MESSAGES_PER_SHORT_SUMMARY = 20
MESSAGES_PER_LONG_SUMMARY = 60
PROVIDER = "google"
MODEL = "gemini-1.5-flash-latest"
MODEL = "gemini-2.5-flash"
MAX_TOKENS_SHORT = 1000
MAX_TOKENS_LONG = 2000
THINKING_BUDGET_TOKENS = 512
# BACKUP_PROVIDER = "google"
# BACKUP_MODEL = "gemini-2.5-flash"
# Dream settings
[dream]
ENABLED = true
DOCUMENT_THRESHOLD = 50
IDLE_TIMEOUT_MINUTES = 60
MIN_HOURS_BETWEEN_DREAMS = 8
ENABLED_TYPES = ["consolidate"]
PROVIDER = "openai"
MODEL = "gpt-4o-mini-2024-07-18"
MAX_OUTPUT_TOKENS = 2000
# BACKUP_PROVIDER = "google"
# BACKUP_MODEL = "gemini-2.5-flash"
# Webhook settings
[webhook]

85
src/config.py
View File

@ -128,6 +128,26 @@ class HonchoSettings(BaseSettings):
)
class BackupLLMSettingsMixin:
"""Mixin class for settings that support backup LLM provider configuration.
Provides backup provider and model fields along with validation to ensure
both fields are set together or both are None.
"""
BACKUP_PROVIDER: SupportedProviders | None = None
BACKUP_MODEL: str | None = None
@model_validator(mode="after")
def _validate_backup_configuration(self):
"""Ensure both backup fields are set together or both are None."""
if (self.BACKUP_PROVIDER is None) != (self.BACKUP_MODEL is None):
raise ValueError(
"BACKUP_PROVIDER and BACKUP_MODEL must both be set or both be None"
)
return self
class DBSettings(HonchoSettings):
model_config = SettingsConfigDict(env_prefix="DB_", extra="ignore") # pyright: ignore
@ -191,7 +211,7 @@ class LLMSettings(HonchoSettings):
DEFAULT_MAX_TOKENS: Annotated[int, Field(default=1000, gt=0, le=100_000)] = 2500
class DeriverSettings(HonchoSettings):
class DeriverSettings(BackupLLMSettingsMixin, HonchoSettings):
model_config = SettingsConfigDict(env_prefix="DERIVER_", extra="ignore") # pyright: ignore
WORKERS: Annotated[int, Field(default=1, gt=0, le=100)] = 1
@ -207,8 +227,6 @@ class DeriverSettings(HonchoSettings):
PROVIDER: SupportedProviders = "google"
MODEL: str = "gemini-2.5-flash-lite"
BACKUP_PROVIDER: SupportedProviders | None = None
BACKUP_MODEL: str | None = None
MAX_OUTPUT_TOKENS: Annotated[int, Field(default=10_000, gt=0, le=100_000)] = 10_000
# Thinking budget tokens are only applied when using Anthropic as provider
@ -230,15 +248,6 @@ class DeriverSettings(HonchoSettings):
MAX_INPUT_TOKENS: Annotated[int, Field(default=23000, gt=0, le=23000)] = 23000
@model_validator(mode="after")
def validate_backup_configuration(self):
"""Ensure both backup fields are set together or both are None."""
if (self.BACKUP_PROVIDER is None) != (self.BACKUP_MODEL is None):
raise ValueError(
"BACKUP_PROVIDER and BACKUP_MODEL must both be set or both be None"
)
return self
@model_validator(mode="after")
def validate_batch_tokens_vs_context_limit(self):
if self.REPRESENTATION_BATCH_MAX_TOKENS > self.MAX_INPUT_TOKENS:
@ -248,35 +257,22 @@ class DeriverSettings(HonchoSettings):
return self
class PeerCardSettings(HonchoSettings):
class PeerCardSettings(BackupLLMSettingsMixin, HonchoSettings):
model_config = SettingsConfigDict(env_prefix="PEER_CARD_", extra="ignore") # pyright: ignore
ENABLED: bool = True
PROVIDER: SupportedProviders = "openai"
MODEL: str = "gpt-5-nano-2025-08-07"
BACKUP_PROVIDER: SupportedProviders | None = None
BACKUP_MODEL: str | None = None
# Note: peer cards should be very short, but GPT-5 models need output tokens for thinking which cannot be turned off...
MAX_OUTPUT_TOKENS: Annotated[int, Field(default=4000, gt=1000, le=10_000)] = 4000
@model_validator(mode="after")
def validate_backup_configuration(self):
"""Ensure both backup fields are set together or both are None."""
if (self.BACKUP_PROVIDER is None) != (self.BACKUP_MODEL is None):
raise ValueError(
"BACKUP_PROVIDER and BACKUP_MODEL must both be set or both be None"
)
return self
class DialecticSettings(HonchoSettings):
class DialecticSettings(BackupLLMSettingsMixin, HonchoSettings):
model_config = SettingsConfigDict(env_prefix="DIALECTIC_", extra="ignore") # pyright: ignore
PROVIDER: SupportedProviders = "anthropic"
MODEL: str = "claude-sonnet-4-20250514"
BACKUP_PROVIDER: SupportedProviders | None = None
BACKUP_MODEL: str | None = None
PERFORM_QUERY_GENERATION: bool = False
QUERY_GENERATION_PROVIDER: SupportedProviders = "groq"
@ -295,17 +291,8 @@ class DialecticSettings(HonchoSettings):
int, Field(default=100_000, gt=10_000, le=200_000)
] = 100_000
@model_validator(mode="after")
def validate_backup_configuration(self):
"""Ensure both backup fields are set together or both are None."""
if (self.BACKUP_PROVIDER is None) != (self.BACKUP_MODEL is None):
raise ValueError(
"BACKUP_PROVIDER and BACKUP_MODEL must both be set or both be None"
)
return self
class SummarySettings(HonchoSettings):
class SummarySettings(BackupLLMSettingsMixin, HonchoSettings):
model_config = SettingsConfigDict(env_prefix="SUMMARY_", extra="ignore") # pyright: ignore
ENABLED: bool = True
@ -315,22 +302,11 @@ class SummarySettings(HonchoSettings):
PROVIDER: SupportedProviders = "openai"
MODEL: str = "gpt-4o-mini-2024-07-18"
BACKUP_PROVIDER: SupportedProviders | None = None
BACKUP_MODEL: str | None = None
MAX_TOKENS_SHORT: Annotated[int, Field(default=1000, gt=0, le=10_000)] = 1000
MAX_TOKENS_LONG: Annotated[int, Field(default=4000, gt=0, le=20_000)] = 4000
THINKING_BUDGET_TOKENS: Annotated[int, Field(default=512, gt=0, le=2000)] = 512
@model_validator(mode="after")
def validate_backup_configuration(self):
"""Ensure both backup fields are set together or both are None."""
if (self.BACKUP_PROVIDER is None) != (self.BACKUP_MODEL is None):
raise ValueError(
"BACKUP_PROVIDER and BACKUP_MODEL must both be set or both be None"
)
return self
class WebhookSettings(HonchoSettings):
model_config = SettingsConfigDict(env_prefix="WEBHOOK_", extra="ignore") # pyright: ignore
@ -346,7 +322,7 @@ class MetricsSettings(HonchoSettings):
NAMESPACE: str = "honcho"
class DreamSettings(HonchoSettings):
class DreamSettings(BackupLLMSettingsMixin, HonchoSettings):
model_config = SettingsConfigDict(env_prefix="DREAM_", extra="ignore") # pyright: ignore
ENABLED: bool = True
@ -358,19 +334,8 @@ class DreamSettings(HonchoSettings):
# LLM settings for dream processing
PROVIDER: SupportedProviders = "openai"
MODEL: str = "gpt-4o-mini-2024-07-18"
BACKUP_PROVIDER: SupportedProviders | None = None
BACKUP_MODEL: str | None = None
MAX_OUTPUT_TOKENS: Annotated[int, Field(default=2000, gt=0, le=10_000)] = 2000
@model_validator(mode="after")
def validate_backup_configuration(self):
"""Ensure both backup fields are set together or both are None."""
if (self.BACKUP_PROVIDER is None) != (self.BACKUP_MODEL is None):
raise ValueError(
"BACKUP_PROVIDER and BACKUP_MODEL must both be set or both be None"
)
return self
class AppSettings(HonchoSettings):
# No env_prefix for app-level settings

151
src/utils/clients.py
View File

@ -208,53 +208,92 @@ async def honcho_llm_call(
Raises:
ValueError: If provider is not configured
"""
# Extract provider/model from settings, with backup support
attempt = _current_attempt.get()
# Set attempt counter to 1 for first call (tenacity uses 1-indexed attempts)
_current_attempt.set(1)
# Use backup if: (1) we're retrying, (2) backup is configured, (3) backup client exists
use_backup = (
attempt > 0
and llm_settings.BACKUP_PROVIDER is not None
and llm_settings.BACKUP_MODEL is not None
and llm_settings.BACKUP_PROVIDER in CLIENTS
)
if (
use_backup
and llm_settings.BACKUP_PROVIDER is not None
and llm_settings.BACKUP_MODEL is not None
async def _call_with_provider_selection() -> (
HonchoLLMCallResponse[Any] | AsyncIterator[HonchoLLMCallStreamChunk]
):
provider = llm_settings.BACKUP_PROVIDER
model = llm_settings.BACKUP_MODEL
logger.info(
f"Retry attempt {attempt}: switching from "
+ f"{llm_settings.PROVIDER}/{llm_settings.MODEL} to "
+ f"backup {provider}/{model}"
)
"""
Inner function that selects provider/model based on current attempt.
This function is retried, so provider selection happens on each attempt.
"""
attempt = _current_attempt.get()
# Filter out incompatible parameters when using backup
if provider != "anthropic" and thinking_budget_tokens:
logger.warning(
f"thinking_budget_tokens not supported by {provider}, ignoring"
# Use backup on final retry attempt (when attempt == retry_attempts)
if (
attempt == retry_attempts
and llm_settings.BACKUP_PROVIDER is not None
and llm_settings.BACKUP_MODEL is not None
and llm_settings.BACKUP_PROVIDER in CLIENTS
):
provider: SupportedProviders = llm_settings.BACKUP_PROVIDER
model: str = llm_settings.BACKUP_MODEL
logger.info(
f"Final retry attempt {attempt}: switching from "
+ f"{llm_settings.PROVIDER}/{llm_settings.MODEL} to "
+ f"backup {provider}/{model}"
)
thinking_budget_tokens = None
if model and "gpt-5" not in model and (reasoning_effort or verbosity):
logger.warning(
"reasoning_effort/verbosity only supported by GPT-5 models, ignoring"
# Filter out incompatible parameters when using backup
thinking_budget = thinking_budget_tokens
gpt5_reasoning_effort = reasoning_effort
gpt5_verbosity = verbosity
if provider != "anthropic" and thinking_budget:
logger.warning(
f"thinking_budget_tokens not supported by {provider}, ignoring"
)
thinking_budget = None
if "gpt-5" not in model and (gpt5_reasoning_effort or gpt5_verbosity):
logger.warning(
"reasoning_effort/verbosity only supported by GPT-5 models, ignoring"
)
gpt5_reasoning_effort = None
gpt5_verbosity = None
else:
provider = llm_settings.PROVIDER
model = llm_settings.MODEL
thinking_budget = thinking_budget_tokens
gpt5_reasoning_effort = reasoning_effort
gpt5_verbosity = verbosity
# Validate client exists
client = CLIENTS.get(provider)
if not client:
raise ValueError(f"Missing client for {provider}")
if stream:
return await honcho_llm_call_inner(
provider,
model,
prompt,
max_tokens,
response_model,
json_mode,
stop_seqs,
gpt5_reasoning_effort,
gpt5_verbosity,
thinking_budget,
True, # type: ignore[arg-type]
)
else:
return await honcho_llm_call_inner(
provider,
model,
prompt,
max_tokens,
response_model,
json_mode,
stop_seqs,
gpt5_reasoning_effort,
gpt5_verbosity,
thinking_budget,
False, # type: ignore[arg-type]
)
reasoning_effort = None
verbosity = None
else:
provider = llm_settings.PROVIDER
model = llm_settings.MODEL
# Validate client exists
client = CLIENTS.get(provider)
if not client:
raise ValueError(f"Missing client for {provider}")
decorated = honcho_llm_call_inner
decorated = _call_with_provider_selection
# apply tracking
if track_name:
@ -279,37 +318,7 @@ async def honcho_llm_call(
before_sleep=before_retry_callback,
)(decorated)
# Reset attempt counter at start
_current_attempt.set(0)
if stream:
return await decorated(
provider,
model,
prompt,
max_tokens,
response_model,
json_mode,
stop_seqs,
reasoning_effort,
verbosity,
thinking_budget_tokens,
True,
)
else:
return await decorated(
provider,
model,
prompt,
max_tokens,
response_model,
json_mode,
stop_seqs,
reasoning_effort,
verbosity,
thinking_budget_tokens,
False,
)
return await decorated()
@overload