Files
t6_mem0/embedchain/llm/mistralai.py
2024-07-04 11:40:56 -07:00

73 lines
3.2 KiB
Python

import os
from typing import Any, Optional
from embedchain.config import BaseLlmConfig
from embedchain.helpers.json_serializable import register_deserializable
from embedchain.llm.base import BaseLlm
@register_deserializable
class MistralAILlm(BaseLlm):
def __init__(self, config: Optional[BaseLlmConfig] = None):
super().__init__(config)
if not self.config.api_key and "MISTRAL_API_KEY" not in os.environ:
raise ValueError("Please set the MISTRAL_API_KEY environment variable or pass it in the config.")
def get_llm_model_answer(self, prompt) -> tuple[str, Optional[dict[str, Any]]]:
if self.config.token_usage:
response, token_info = self._get_answer(prompt, self.config)
model_name = "mistralai/" + self.config.model
if model_name not in self.config.model_pricing_map:
raise ValueError(
f"Model {model_name} not found in `model_prices_and_context_window.json`. \
You can disable token usage by setting `token_usage` to False."
)
total_cost = (
self.config.model_pricing_map[model_name]["input_cost_per_token"] * token_info["prompt_tokens"]
) + self.config.model_pricing_map[model_name]["output_cost_per_token"] * token_info["completion_tokens"]
response_token_info = {
"prompt_tokens": token_info["prompt_tokens"],
"completion_tokens": token_info["completion_tokens"],
"total_tokens": token_info["prompt_tokens"] + token_info["completion_tokens"],
"total_cost": round(total_cost, 10),
"cost_currency": "USD",
}
return response, response_token_info
return self._get_answer(prompt, self.config)
@staticmethod
def _get_answer(prompt: str, config: BaseLlmConfig):
try:
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_mistralai.chat_models import ChatMistralAI
except ModuleNotFoundError:
raise ModuleNotFoundError(
"The required dependencies for MistralAI are not installed."
'Please install with `pip install --upgrade "embedchain[mistralai]"`'
) from None
api_key = config.api_key or os.getenv("MISTRAL_API_KEY")
client = ChatMistralAI(mistral_api_key=api_key)
messages = []
if config.system_prompt:
messages.append(SystemMessage(content=config.system_prompt))
messages.append(HumanMessage(content=prompt))
kwargs = {
"model": config.model or "mistral-tiny",
"temperature": config.temperature,
"max_tokens": config.max_tokens,
"top_p": config.top_p,
}
# TODO: Add support for streaming
if config.stream:
answer = ""
for chunk in client.stream(**kwargs, input=messages):
answer += chunk.content
return answer
else:
chat_response = client.invoke(**kwargs, input=messages)
if config.token_usage:
return chat_response.content, chat_response.response_metadata["token_usage"]
return chat_response.content