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format code and remove max_input_tokens for ToolCallAgent

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This commit is contained in:
liangxinbing 2025-03-15 14:43:07 +08:00
parent 86399b97d6
commit 65a3898592
4 changed files with 66 additions and 40 deletions
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7
app/agent/toolcall.py
View File

@ -33,7 +33,6 @@ class ToolCallAgent(ReActAgent):
max_steps: int = 30
max_observe: Optional[Union[int, bool]] = None
max_input_tokens: Optional[int] = None
async def think(self) -> bool:
"""Process current state and decide next actions using tools"""
@ -51,13 +50,15 @@ class ToolCallAgent(ReActAgent):
tools=self.available_tools.to_params(),
tool_choice=self.tool_choices,
)
except ValueError as e:
except ValueError:
raise
except Exception as e:
# Check if this is a RetryError containing TokenLimitExceeded
if hasattr(e, "__cause__") and isinstance(e.__cause__, TokenLimitExceeded):
token_limit_error = e.__cause__
logger.error(f"🚨 Token limit error (from RetryError): {token_limit_error}")
logger.error(
f"🚨 Token limit error (from RetryError): {token_limit_error}"
)
self.memory.add_message(
Message.assistant_message(
f"Maximum token limit reached, cannot continue execution: {str(token_limit_error)}"

5
app/config.py
View File

@ -20,7 +20,10 @@ class LLMSettings(BaseModel):
base_url: str = Field(..., description="API base URL")
api_key: str = Field(..., description="API key")
max_tokens: int = Field(4096, description="Maximum number of tokens per request")
max_input_tokens: Optional[int] = Field(None, description="Maximum input tokens to use across all requests (None for unlimited)")
max_input_tokens: Optional[int] = Field(
None,
description="Maximum input tokens to use across all requests (None for unlimited)",
)
temperature: float = Field(1.0, description="Sampling temperature")
api_type: str = Field(..., description="AzureOpenai or Openai")
api_version: str = Field(..., description="Azure Openai version if AzureOpenai")

4
app/exceptions.py
View File

@ -4,10 +4,10 @@ class ToolError(Exception):
def __init__(self, message):
self.message = message
class OpenManusError(Exception):
"""Base exception for all OpenManus errors"""
pass
class TokenLimitExceeded(OpenManusError):
"""Exception raised when the token limit is exceeded"""
pass

40
app/llm.py
View File

@ -1,5 +1,6 @@
from typing import Dict, List, Optional, Union
import tiktoken
from openai import (
APIError,
AsyncAzureOpenAI,
@ -8,8 +9,12 @@ from openai import (
OpenAIError,
RateLimitError,
)
import tiktoken
from tenacity import retry, stop_after_attempt, wait_random_exponential, retry_if_exception_type
from tenacity import (
retry,
retry_if_exception_type,
stop_after_attempt,
wait_random_exponential,
)
from app.config import LLMSettings, config
from app.exceptions import TokenLimitExceeded
@ -54,7 +59,11 @@ class LLM:
# Add token counting related attributes
self.total_input_tokens = 0
self.max_input_tokens = llm_config.max_input_tokens if hasattr(llm_config, "max_input_tokens") else None
self.max_input_tokens = (
llm_config.max_input_tokens
if hasattr(llm_config, "max_input_tokens")
else None
)
# Initialize tokenizer
try:
@ -99,10 +108,14 @@ class LLM:
if "function" in tool_call:
# Function name
if "name" in tool_call["function"]:
token_count += self.count_tokens(tool_call["function"]["name"])
token_count += self.count_tokens(
tool_call["function"]["name"]
)
# Function arguments
if "arguments" in tool_call["function"]:
token_count += self.count_tokens(tool_call["function"]["arguments"])
token_count += self.count_tokens(
tool_call["function"]["arguments"]
)
# Calculate tokens for tool responses
if "name" in message and message["name"]:
@ -120,7 +133,9 @@ class LLM:
"""Update token counts"""
# Only track tokens if max_input_tokens is set
self.total_input_tokens += input_tokens
logger.info(f"Token usage: Input={input_tokens}, Cumulative Input={self.total_input_tokens}")
logger.info(
f"Token usage: Input={input_tokens}, Cumulative Input={self.total_input_tokens}"
)
def check_token_limit(self, input_tokens: int) -> bool:
"""Check if token limits are exceeded"""
@ -131,7 +146,10 @@ class LLM:
def get_limit_error_message(self, input_tokens: int) -> str:
"""Generate error message for token limit exceeded"""
if self.max_input_tokens is not None and (self.total_input_tokens + input_tokens) > self.max_input_tokens:
if (
self.max_input_tokens is not None
and (self.total_input_tokens + input_tokens) > self.max_input_tokens
):
return f"Request may exceed input token limit (Current: {self.total_input_tokens}, Needed: {input_tokens}, Max: {self.max_input_tokens})"
return "Token limit exceeded"
@ -187,7 +205,9 @@ class LLM:
@retry(
wait=wait_random_exponential(min=1, max=60),
stop=stop_after_attempt(6),
retry=retry_if_exception_type((OpenAIError, Exception, ValueError)), # Don't retry TokenLimitExceeded
retry=retry_if_exception_type(
(OpenAIError, Exception, ValueError)
), # Don't retry TokenLimitExceeded
)
async def ask(
self,
@ -299,7 +319,9 @@ class LLM:
@retry(
wait=wait_random_exponential(min=1, max=60),
stop=stop_after_attempt(6),
retry=retry_if_exception_type((OpenAIError, Exception, ValueError)), # Don't retry TokenLimitExceeded
retry=retry_if_exception_type(
(OpenAIError, Exception, ValueError)
), # Don't retry TokenLimitExceeded
)
async def ask_tool(
self,