mirror of
https://github.com/aljazceru/Auto-GPT.git
synced 2025-12-20 15:34:23 +01:00
* basic proxy (#54) * basic proxy (#55) * basic proxy * basic proxy * basic proxy * basic proxy * add back double quotes * add more specific files * write file * basic proxy * Put back double quotes
130 lines
3.9 KiB
Python
130 lines
3.9 KiB
Python
from __future__ import annotations
|
|
|
|
import openai
|
|
|
|
from autogpt.config import Config
|
|
from autogpt.llm.modelsinfo import COSTS
|
|
from autogpt.logs import logger
|
|
from autogpt.singleton import Singleton
|
|
|
|
|
|
class ApiManager(metaclass=Singleton):
|
|
def __init__(self):
|
|
self.total_prompt_tokens = 0
|
|
self.total_completion_tokens = 0
|
|
self.total_cost = 0
|
|
self.total_budget = 0
|
|
|
|
def reset(self):
|
|
self.total_prompt_tokens = 0
|
|
self.total_completion_tokens = 0
|
|
self.total_cost = 0
|
|
self.total_budget = 0.0
|
|
|
|
def create_chat_completion(
|
|
self,
|
|
messages: list, # type: ignore
|
|
model: str | None = None,
|
|
temperature: float = None,
|
|
max_tokens: int | None = None,
|
|
deployment_id=None,
|
|
) -> str:
|
|
"""
|
|
Create a chat completion and update the cost.
|
|
Args:
|
|
messages (list): The list of messages to send to the API.
|
|
model (str): The model to use for the API call.
|
|
temperature (float): The temperature to use for the API call.
|
|
max_tokens (int): The maximum number of tokens for the API call.
|
|
Returns:
|
|
str: The AI's response.
|
|
"""
|
|
cfg = Config()
|
|
if temperature is None:
|
|
temperature = cfg.temperature
|
|
if deployment_id is not None:
|
|
response = openai.ChatCompletion.create(
|
|
deployment_id=deployment_id,
|
|
model=model,
|
|
messages=messages,
|
|
temperature=temperature,
|
|
max_tokens=max_tokens,
|
|
api_key=cfg.openai_api_key,
|
|
)
|
|
else:
|
|
response = openai.ChatCompletion.create(
|
|
model=model,
|
|
messages=messages,
|
|
temperature=temperature,
|
|
max_tokens=max_tokens,
|
|
api_key=cfg.openai_api_key,
|
|
)
|
|
if not hasattr(response, "error"):
|
|
logger.debug(f"Response: {response}")
|
|
prompt_tokens = response.usage.prompt_tokens
|
|
completion_tokens = response.usage.completion_tokens
|
|
self.update_cost(prompt_tokens, completion_tokens, model)
|
|
return response
|
|
|
|
def update_cost(self, prompt_tokens, completion_tokens, model):
|
|
"""
|
|
Update the total cost, prompt tokens, and completion tokens.
|
|
|
|
Args:
|
|
prompt_tokens (int): The number of tokens used in the prompt.
|
|
completion_tokens (int): The number of tokens used in the completion.
|
|
model (str): The model used for the API call.
|
|
"""
|
|
self.total_prompt_tokens += prompt_tokens
|
|
self.total_completion_tokens += completion_tokens
|
|
self.total_cost += (
|
|
prompt_tokens * COSTS[model]["prompt"]
|
|
+ completion_tokens * COSTS[model]["completion"]
|
|
) / 1000
|
|
logger.debug(f"Total running cost: ${self.total_cost:.3f}")
|
|
|
|
def set_total_budget(self, total_budget):
|
|
"""
|
|
Sets the total user-defined budget for API calls.
|
|
|
|
Args:
|
|
total_budget (float): The total budget for API calls.
|
|
"""
|
|
self.total_budget = total_budget
|
|
|
|
def get_total_prompt_tokens(self):
|
|
"""
|
|
Get the total number of prompt tokens.
|
|
|
|
Returns:
|
|
int: The total number of prompt tokens.
|
|
"""
|
|
return self.total_prompt_tokens
|
|
|
|
def get_total_completion_tokens(self):
|
|
"""
|
|
Get the total number of completion tokens.
|
|
|
|
Returns:
|
|
int: The total number of completion tokens.
|
|
"""
|
|
return self.total_completion_tokens
|
|
|
|
def get_total_cost(self):
|
|
"""
|
|
Get the total cost of API calls.
|
|
|
|
Returns:
|
|
float: The total cost of API calls.
|
|
"""
|
|
return self.total_cost
|
|
|
|
def get_total_budget(self):
|
|
"""
|
|
Get the total user-defined budget for API calls.
|
|
|
|
Returns:
|
|
float: The total budget for API calls.
|
|
"""
|
|
return self.total_budget
|