Enabled native function calling for O1 + added support for reasoning_effort config in the config. (#6256)

Co-authored-by: Engel Nyst <enyst@users.noreply.github.com>
This commit is contained in:
Alejandro Cuadron Lafuente 2025-01-16 15:53:11 +01:00 committed by GitHub
parent efe04baf34
commit 578291e961
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5 changed files with 34 additions and 4 deletions

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@ -23,6 +23,9 @@ workspace_base = "./workspace"
# Cache directory path
#cache_dir = "/tmp/cache"
# Reasoning effort for o1 models (low, medium, high, or not set)
#reasoning_effort = "medium"
# Debugging enabled
#debug = false

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@ -40,6 +40,7 @@ class LLMConfig:
drop_params: Drop any unmapped (unsupported) params without causing an exception.
modify_params: Modify params allows litellm to do transformations like adding a default message, when a message is empty.
disable_vision: If model is vision capable, this option allows to disable image processing (useful for cost reduction).
reasoning_effort: The effort to put into reasoning. This is a string that can be one of 'low', 'medium', 'high', or 'none'. Exclusive for o1 models.
caching_prompt: Use the prompt caching feature if provided by the LLM and supported by the provider.
log_completions: Whether to log LLM completions to the state.
log_completions_folder: The folder to log LLM completions to. Required if log_completions is True.
@ -79,6 +80,7 @@ class LLMConfig:
# Note: this setting is actually global, unlike drop_params
modify_params: bool = True
disable_vision: bool | None = None
reasoning_effort: str | None = None
caching_prompt: bool = True
log_completions: bool = False
log_completions_folder: str = os.path.join(LOG_DIR, 'completions')

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@ -6,7 +6,11 @@ from litellm import acompletion as litellm_acompletion
from openhands.core.exceptions import UserCancelledError
from openhands.core.logger import openhands_logger as logger
from openhands.llm.llm import LLM, LLM_RETRY_EXCEPTIONS
from openhands.llm.llm import (
LLM,
LLM_RETRY_EXCEPTIONS,
REASONING_EFFORT_SUPPORTED_MODELS,
)
from openhands.utils.shutdown_listener import should_continue
@ -55,6 +59,10 @@ class AsyncLLM(LLM):
elif 'messages' in kwargs:
messages = kwargs['messages']
# Set reasoning effort for models that support it
if self.config.model.lower() in REASONING_EFFORT_SUPPORTED_MODELS:
kwargs['reasoning_effort'] = self.config.reasoning_effort
# ensure we work with a list of messages
messages = messages if isinstance(messages, list) else [messages]

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@ -70,7 +70,15 @@ FUNCTION_CALLING_SUPPORTED_MODELS = [
'claude-3.5-haiku',
'claude-3-5-haiku-20241022',
'gpt-4o-mini',
'gpt-4o',
'o1-2024-12-17',
]
REASONING_EFFORT_SUPPORTED_MODELS = [
'o1-2024-12-17',
]
MODELS_WITHOUT_STOP_WORDS = [
'o1-mini',
]
@ -186,7 +194,8 @@ class LLM(RetryMixin, DebugMixin):
messages, kwargs['tools']
)
kwargs['messages'] = messages
kwargs['stop'] = STOP_WORDS
if self.config.model not in MODELS_WITHOUT_STOP_WORDS:
kwargs['stop'] = STOP_WORDS
mock_fncall_tools = kwargs.pop('tools')
# if we have no messages, something went very wrong
@ -205,6 +214,10 @@ class LLM(RetryMixin, DebugMixin):
'anthropic-beta': 'prompt-caching-2024-07-31',
}
# Set reasoning effort for models that support it
if self.config.model.lower() in REASONING_EFFORT_SUPPORTED_MODELS:
kwargs['reasoning_effort'] = self.config.reasoning_effort
# set litellm modify_params to the configured value
# True by default to allow litellm to do transformations like adding a default message, when a message is empty
# NOTE: this setting is global; unlike drop_params, it cannot be overridden in the litellm completion partial
@ -213,7 +226,6 @@ class LLM(RetryMixin, DebugMixin):
try:
# Record start time for latency measurement
start_time = time.time()
# we don't support streaming here, thus we get a ModelResponse
resp: ModelResponse = self._completion_unwrapped(*args, **kwargs)

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@ -5,6 +5,7 @@ from typing import Any
from openhands.core.exceptions import UserCancelledError
from openhands.core.logger import openhands_logger as logger
from openhands.llm.async_llm import LLM_RETRY_EXCEPTIONS, AsyncLLM
from openhands.llm.llm import REASONING_EFFORT_SUPPORTED_MODELS
class StreamingLLM(AsyncLLM):
@ -61,6 +62,10 @@ class StreamingLLM(AsyncLLM):
'The messages list is empty. At least one message is required.'
)
# Set reasoning effort for models that support it
if self.config.model.lower() in REASONING_EFFORT_SUPPORTED_MODELS:
kwargs['reasoning_effort'] = self.config.reasoning_effort
self.log_prompt(messages)
try: