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"""
Transformation logic from OpenAI /v1/chat/completion format to Mistral's /chat/completion format.
Why separate file? Make it easy to see how transformation works
Docs - https://docs.mistral.ai/api/
"""
from typing import List, Literal, Optional, Tuple, Union
from litellm.litellm_core_utils.prompt_templates.common_utils import (
handle_messages_with_content_list_to_str_conversion,
strip_none_values_from_message,
)
from litellm.llms.openai.chat.gpt_transformation import OpenAIGPTConfig
from litellm.secret_managers.main import get_secret_str
from litellm.types.llms.mistral import MistralToolCallMessage
from litellm.types.llms.openai import AllMessageValues
class MistralConfig(OpenAIGPTConfig):
"""
Reference: https://docs.mistral.ai/api/
The class `MistralConfig` provides configuration for the Mistral's Chat API interface. Below are the parameters:
- `temperature` (number or null): Defines the sampling temperature to use, varying between 0 and 2. API Default - 0.7.
- `top_p` (number or null): An alternative to sampling with temperature, used for nucleus sampling. API Default - 1.
- `max_tokens` (integer or null): This optional parameter helps to set the maximum number of tokens to generate in the chat completion. API Default - null.
- `tools` (list or null): A list of available tools for the model. Use this to specify functions for which the model can generate JSON inputs.
- `tool_choice` (string - 'auto'/'any'/'none' or null): Specifies if/how functions are called. If set to none the model won't call a function and will generate a message instead. If set to auto the model can choose to either generate a message or call a function. If set to any the model is forced to call a function. Default - 'auto'.
- `stop` (string or array of strings): Stop generation if this token is detected. Or if one of these tokens is detected when providing an array
- `random_seed` (integer or null): The seed to use for random sampling. If set, different calls will generate deterministic results.
- `safe_prompt` (boolean): Whether to inject a safety prompt before all conversations. API Default - 'false'.
- `response_format` (object or null): An object specifying the format that the model must output. Setting to { "type": "json_object" } enables JSON mode, which guarantees the message the model generates is in JSON. When using JSON mode you MUST also instruct the model to produce JSON yourself with a system or a user message.
"""
temperature: Optional[int] = None
top_p: Optional[int] = None
max_tokens: Optional[int] = None
tools: Optional[list] = None
tool_choice: Optional[Literal["auto", "any", "none"]] = None
random_seed: Optional[int] = None
safe_prompt: Optional[bool] = None
response_format: Optional[dict] = None
stop: Optional[Union[str, list]] = None
def __init__(
self,
temperature: Optional[int] = None,
top_p: Optional[int] = None,
max_tokens: Optional[int] = None,
tools: Optional[list] = None,
tool_choice: Optional[Literal["auto", "any", "none"]] = None,
random_seed: Optional[int] = None,
safe_prompt: Optional[bool] = None,
response_format: Optional[dict] = None,
stop: Optional[Union[str, list]] = None,
) -> None:
locals_ = locals().copy()
for key, value in locals_.items():
if key != "self" and value is not None:
setattr(self.__class__, key, value)
@classmethod
def get_config(cls):
return super().get_config()
def get_supported_openai_params(self, model: str) -> List[str]:
return [
"stream",
"temperature",
"top_p",
"max_tokens",
"tools",
"tool_choice",
"seed",
"stop",
"response_format",
]
def _map_tool_choice(self, tool_choice: str) -> str:
if tool_choice == "auto" or tool_choice == "none":
return tool_choice
elif tool_choice == "required":
return "any"
else: # openai 'tool_choice' object param not supported by Mistral API
return "any"
def map_openai_params(
self,
non_default_params: dict,
optional_params: dict,
model: str,
drop_params: bool,
) -> dict:
for param, value in non_default_params.items():
if param == "max_tokens":
optional_params["max_tokens"] = value
if param == "tools":
optional_params["tools"] = value
if param == "stream" and value is True:
optional_params["stream"] = value
if param == "temperature":
optional_params["temperature"] = value
if param == "top_p":
optional_params["top_p"] = value
if param == "stop":
optional_params["stop"] = value
if param == "tool_choice" and isinstance(value, str):
optional_params["tool_choice"] = self._map_tool_choice(
tool_choice=value
)
if param == "seed":
optional_params["extra_body"] = {"random_seed": value}
if param == "response_format":
optional_params["response_format"] = value
return optional_params
def _get_openai_compatible_provider_info(
self, api_base: Optional[str], api_key: Optional[str]
) -> Tuple[Optional[str], Optional[str]]:
# mistral is openai compatible, we just need to set this to custom_openai and have the api_base be https://api.mistral.ai
api_base = (
api_base
or get_secret_str("MISTRAL_AZURE_API_BASE") # for Azure AI Mistral
or "https://api.mistral.ai/v1"
) # type: ignore
# if api_base does not end with /v1 we add it
if api_base is not None and not api_base.endswith(
"/v1"
): # Mistral always needs a /v1 at the end
api_base = api_base + "/v1"
dynamic_api_key = (
api_key
or get_secret_str("MISTRAL_AZURE_API_KEY") # for Azure AI Mistral
or get_secret_str("MISTRAL_API_KEY")
)
return api_base, dynamic_api_key
def _transform_messages(
self, messages: List[AllMessageValues], model: str
) -> List[AllMessageValues]:
"""
- handles scenario where content is list and not string
- content list is just text, and no images
- if image passed in, then just return as is (user-intended)
- if `name` is passed, then drop it for mistral API: https://github.com/BerriAI/litellm/issues/6696
Motivation: mistral api doesn't support content as a list
"""
## 1. If 'image_url' in content, then return as is
for m in messages:
_content_block = m.get("content")
if _content_block and isinstance(_content_block, list):
for c in _content_block:
if c.get("type") == "image_url":
return messages
## 2. If content is list, then convert to string
messages = handle_messages_with_content_list_to_str_conversion(messages)
## 3. Handle name in message
new_messages: List[AllMessageValues] = []
for m in messages:
m = MistralConfig._handle_name_in_message(m)
m = MistralConfig._handle_tool_call_message(m)
m = strip_none_values_from_message(m) # prevents 'extra_forbidden' error
new_messages.append(m)
return new_messages
@classmethod
def _handle_name_in_message(cls, message: AllMessageValues) -> AllMessageValues:
"""
Mistral API only supports `name` in tool messages
If role == tool, then we keep `name`
Otherwise, we drop `name`
"""
_name = message.get("name") # type: ignore
if _name is not None and message["role"] != "tool":
message.pop("name", None) # type: ignore
return message
@classmethod
def _handle_tool_call_message(cls, message: AllMessageValues) -> AllMessageValues:
"""
Mistral API only supports tool_calls in Messages in `MistralToolCallMessage` spec
"""
_tool_calls = message.get("tool_calls")
mistral_tool_calls: List[MistralToolCallMessage] = []
if _tool_calls is not None and isinstance(_tool_calls, list):
for _tool in _tool_calls:
_tool_call_message = MistralToolCallMessage(
id=_tool.get("id"),
type="function",
function=_tool.get("function"), # type: ignore
)
mistral_tool_calls.append(_tool_call_message)
message["tool_calls"] = mistral_tool_calls # type: ignore
return message
|
