autogen/autogen/oai/openai_utils.py

382 lines
15 KiB
Python

import os
import json
import tempfile
from pathlib import Path
from typing import List, Optional, Dict, Set, Union
import logging
from dotenv import find_dotenv, load_dotenv
NON_CACHE_KEY = ["api_key", "api_base", "api_type", "api_version"]
def get_key(config):
"""Get a unique identifier of a configuration.
Args:
config (dict or list): A configuration.
Returns:
tuple: A unique identifier which can be used as a key for a dict.
"""
copied = False
for key in NON_CACHE_KEY:
if key in config:
config, copied = config.copy() if not copied else config, True
config.pop(key)
# if isinstance(config, dict):
# return tuple(get_key(x) for x in sorted(config.items()))
# if isinstance(config, list):
# return tuple(get_key(x) for x in config)
# return config
return json.dumps(config, sort_keys=True)
def get_config_list(
api_keys: List, api_bases: Optional[List] = None, api_type: Optional[str] = None, api_version: Optional[str] = None
) -> List[Dict]:
"""Get a list of configs for openai api calls.
Args:
api_keys (list): The api keys for openai api calls.
api_bases (list, optional): The api bases for openai api calls.
api_type (str, optional): The api type for openai api calls.
api_version (str, optional): The api version for openai api calls.
"""
config_list = []
for i, api_key in enumerate(api_keys):
if not api_key.strip():
continue
config = {"api_key": api_key}
if api_bases:
config["api_base"] = api_bases[i]
if api_type:
config["api_type"] = api_type
if api_version:
config["api_version"] = api_version
config_list.append(config)
return config_list
def config_list_openai_aoai(
key_file_path: Optional[str] = ".",
openai_api_key_file: Optional[str] = "key_openai.txt",
aoai_api_key_file: Optional[str] = "key_aoai.txt",
aoai_api_base_file: Optional[str] = "base_aoai.txt",
exclude: Optional[str] = None,
) -> List[Dict]:
"""Get a list of configs for openai + azure openai api calls.
Args:
key_file_path (str, optional): The path to the key files.
openai_api_key_file (str, optional): The file name of the openai api key.
aoai_api_key_file (str, optional): The file name of the azure openai api key.
aoai_api_base_file (str, optional): The file name of the azure openai api base.
exclude (str, optional): The api type to exclude, "openai" or "aoai".
Returns:
list: A list of configs for openai api calls.
"""
if "OPENAI_API_KEY" not in os.environ and exclude != "openai":
try:
with open(f"{key_file_path}/{openai_api_key_file}") as key_file:
os.environ["OPENAI_API_KEY"] = key_file.read().strip()
except FileNotFoundError:
logging.info(
"To use OpenAI API, please set OPENAI_API_KEY in os.environ "
"or create key_openai.txt in the specified path, or specify the api_key in config_list."
)
if "AZURE_OPENAI_API_KEY" not in os.environ and exclude != "aoai":
try:
with open(f"{key_file_path}/{aoai_api_key_file}") as key_file:
os.environ["AZURE_OPENAI_API_KEY"] = key_file.read().strip()
except FileNotFoundError:
logging.info(
"To use Azure OpenAI API, please set AZURE_OPENAI_API_KEY in os.environ "
"or create key_aoai.txt in the specified path, or specify the api_key in config_list."
)
if "AZURE_OPENAI_API_BASE" not in os.environ and exclude != "aoai":
try:
with open(f"{key_file_path}/{aoai_api_base_file}") as key_file:
os.environ["AZURE_OPENAI_API_BASE"] = key_file.read().strip()
except FileNotFoundError:
logging.info(
"To use Azure OpenAI API, please set AZURE_OPENAI_API_BASE in os.environ "
"or create base_aoai.txt in the specified path, or specify the api_base in config_list."
)
aoai_config = (
get_config_list(
# Assuming Azure OpenAI api keys in os.environ["AZURE_OPENAI_API_KEY"], in separated lines
api_keys=os.environ.get("AZURE_OPENAI_API_KEY", "").split("\n"),
# Assuming Azure OpenAI api bases in os.environ["AZURE_OPENAI_API_BASE"], in separated lines
api_bases=os.environ.get("AZURE_OPENAI_API_BASE", "").split("\n"),
api_type="azure",
api_version="2023-07-01-preview", # change if necessary
)
if exclude != "aoai"
else []
)
openai_config = (
get_config_list(
# Assuming OpenAI API_KEY in os.environ["OPENAI_API_KEY"]
api_keys=os.environ.get("OPENAI_API_KEY", "").split("\n"),
# "api_type": "open_ai",
# "api_base": "https://api.openai.com/v1",
)
if exclude != "openai"
else []
)
config_list = openai_config + aoai_config
return config_list
def config_list_from_models(
key_file_path: Optional[str] = ".",
openai_api_key_file: Optional[str] = "key_openai.txt",
aoai_api_key_file: Optional[str] = "key_aoai.txt",
aoai_api_base_file: Optional[str] = "base_aoai.txt",
exclude: Optional[str] = None,
model_list: Optional[list] = None,
) -> List[Dict]:
"""Get a list of configs for api calls with models in the model list.
Args:
key_file_path (str, optional): The path to the key files.
openai_api_key_file (str, optional): The file name of the openai api key.
aoai_api_key_file (str, optional): The file name of the azure openai api key.
aoai_api_base_file (str, optional): The file name of the azure openai api base.
exclude (str, optional): The api type to exclude, "openai" or "aoai".
model_list (list, optional): The model list.
Returns:
list: A list of configs for openai api calls.
"""
config_list = config_list_openai_aoai(
key_file_path,
openai_api_key_file,
aoai_api_key_file,
aoai_api_base_file,
exclude,
)
if model_list:
config_list = [{**config, "model": model} for model in model_list for config in config_list]
return config_list
def config_list_gpt4_gpt35(
key_file_path: Optional[str] = ".",
openai_api_key_file: Optional[str] = "key_openai.txt",
aoai_api_key_file: Optional[str] = "key_aoai.txt",
aoai_api_base_file: Optional[str] = "base_aoai.txt",
exclude: Optional[str] = None,
) -> List[Dict]:
"""Get a list of configs for gpt-4 followed by gpt-3.5 api calls.
Args:
key_file_path (str, optional): The path to the key files.
openai_api_key_file (str, optional): The file name of the openai api key.
aoai_api_key_file (str, optional): The file name of the azure openai api key.
aoai_api_base_file (str, optional): The file name of the azure openai api base.
exclude (str, optional): The api type to exclude, "openai" or "aoai".
Returns:
list: A list of configs for openai api calls.
"""
return config_list_from_models(
key_file_path,
openai_api_key_file,
aoai_api_key_file,
aoai_api_base_file,
exclude,
model_list=["gpt-4", "gpt-3.5-turbo"],
)
def filter_config(config_list, filter_dict):
"""Filter the config list by provider and model.
Args:
config_list (list): The config list.
filter_dict (dict, optional): The filter dict with keys corresponding to a field in each config,
and values corresponding to lists of acceptable values for each key.
Returns:
list: The filtered config list.
"""
if filter_dict:
config_list = [
config for config in config_list if all(config.get(key) in value for key, value in filter_dict.items())
]
return config_list
def config_list_from_json(
env_or_file: str,
file_location: Optional[str] = "",
filter_dict: Optional[Dict[str, Union[List[Union[str, None]], Set[Union[str, None]]]]] = None,
) -> List[Dict]:
"""Get a list of configs from a json parsed from an env variable or a file.
Args:
env_or_file (str): The env variable name or file name.
file_location (str, optional): The file location.
filter_dict (dict, optional): The filter dict with keys corresponding to a field in each config,
and values corresponding to lists of acceptable values for each key.
e.g.,
```python
filter_dict = {
"api_type": ["open_ai", None], # None means a missing key is acceptable
"model": ["gpt-3.5-turbo", "gpt-4"],
}
```
Returns:
list: A list of configs for openai api calls.
"""
json_str = os.environ.get(env_or_file)
if json_str:
config_list = json.loads(json_str)
else:
try:
with open(os.path.join(file_location, env_or_file)) as json_file:
config_list = json.load(json_file)
except FileNotFoundError:
return []
return filter_config(config_list, filter_dict)
def get_config(
api_key: str, api_base: Optional[str] = None, api_type: Optional[str] = None, api_version: Optional[str] = None
) -> Dict:
"""
Construct a configuration dictionary with the provided API configurations.
Appending the additional configurations to the config only if they're set
example:
>> model_api_key_map={
"gpt-4": "OPENAI_API_KEY",
"gpt-3.5-turbo": {
"api_key_env_var": "ANOTHER_API_KEY",
"api_type": "aoai",
"api_version": "v2",
"api_base": "https://api.someotherapi.com"
}
}
Args:
api_key (str): The API key used for authenticating API requests.
api_base (str, optional): The base URL of the API. Defaults to None.
api_type (str, optional): The type or kind of API. Defaults to None.
api_version (str, optional): The API version. Defaults to None.
Returns:
Dict: A dictionary containing the API configurations.
"""
config = {"api_key": api_key}
if api_base:
config["api_base"] = api_base
if api_type:
config["api_type"] = api_type
if api_version:
config["api_version"] = api_version
return config
def config_list_from_dotenv(
dotenv_file_path: Optional[str] = None, model_api_key_map: Optional[dict] = None, filter_dict: Optional[dict] = None
) -> List[Dict[str, Union[str, Set[str]]]]:
"""
Load API configurations from a specified .env file or environment variables and construct a list of configurations.
This function will:
- Load API keys from a provided .env file or from existing environment variables.
- Create a configuration dictionary for each model using the API keys and additional configurations.
- Filter and return the configurations based on provided filters.
model_api_key_map will default to `{"gpt-4": "OPENAI_API_KEY", "gpt-3.5-turbo": "OPENAI_API_KEY"}` if none
Args:
dotenv_file_path (str, optional): The path to the .env file. Defaults to None.
model_api_key_map (str/dict, optional): A dictionary mapping models to their API key configurations.
If a string is provided as configuration, it is considered as an environment
variable name storing the API key.
If a dict is provided, it should contain at least 'api_key_env_var' key,
and optionally other API configurations like 'api_base', 'api_type', and 'api_version'.
Defaults to a basic map with 'gpt-4' and 'gpt-3.5-turbo' mapped to 'OPENAI_API_KEY'.
filter_dict (dict, optional): A dictionary containing the models to be loaded.
Containing a 'model' key mapped to a set of model names to be loaded.
Defaults to None, which loads all found configurations.
Returns:
List[Dict[str, Union[str, Set[str]]]]: A list of configuration dictionaries for each model.
Raises:
FileNotFoundError: If the specified .env file does not exist.
TypeError: If an unsupported type of configuration is provided in model_api_key_map.
"""
if dotenv_file_path:
dotenv_path = Path(dotenv_file_path)
if dotenv_path.exists():
load_dotenv(dotenv_path)
else:
logging.warning(f"The specified .env file {dotenv_path} does not exist.")
else:
dotenv_path = find_dotenv()
if not dotenv_path:
logging.warning("No .env file found. Loading configurations from environment variables.")
load_dotenv(dotenv_path)
# Ensure the model_api_key_map is not None to prevent TypeErrors during key assignment.
model_api_key_map = model_api_key_map or {}
# Ensure default models are always considered
default_models = ["gpt-4", "gpt-3.5-turbo"]
for model in default_models:
# Only assign default API key if the model is not present in the map.
# If model is present but set to invalid/empty, do not overwrite.
if model not in model_api_key_map:
model_api_key_map[model] = "OPENAI_API_KEY"
env_var = []
# Loop over the models and create configuration dictionaries
for model, config in model_api_key_map.items():
if isinstance(config, str):
api_key_env_var = config
config_dict = get_config(api_key=os.getenv(api_key_env_var))
elif isinstance(config, dict):
api_key = os.getenv(config.get("api_key_env_var", "OPENAI_API_KEY"))
config_without_key_var = {k: v for k, v in config.items() if k != "api_key_env_var"}
config_dict = get_config(api_key=api_key, **config_without_key_var)
else:
logging.warning(f"Unsupported type {type(config)} for model {model} configuration")
if not config_dict["api_key"] or config_dict["api_key"].strip() == "":
logging.warning(
f"API key not found or empty for model {model}. Please ensure path to .env file is correct."
)
continue # Skip this configuration and continue with the next
# Add model to the configuration and append to the list
config_dict["model"] = model
env_var.append(config_dict)
fd, temp_name = tempfile.mkstemp()
try:
with os.fdopen(fd, "w+") as temp:
env_var_str = json.dumps(env_var)
temp.write(env_var_str)
temp.flush()
# Assuming config_list_from_json is a valid function from your code
config_list = config_list_from_json(env_or_file=temp_name, filter_dict=filter_dict)
finally:
# The file is deleted after using its name (to prevent windows build from breaking)
os.remove(temp_name)
if len(config_list) == 0:
logging.error("No configurations loaded.")
return []
logging.info(f"Models available: {[config['model'] for config in config_list]}")
return config_list