53 lines
2.0 KiB
Python
53 lines
2.0 KiB
Python
import os
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from typing import Optional
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from embedchain.config import BaseLlmConfig
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from embedchain.helpers.json_serializable import register_deserializable
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from embedchain.llm.base import BaseLlm
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@register_deserializable
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class MistralAILlm(BaseLlm):
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def __init__(self, config: Optional[BaseLlmConfig] = None):
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super().__init__(config)
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if not self.config.api_key and "MISTRAL_API_KEY" not in os.environ:
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raise ValueError("Please set the MISTRAL_API_KEY environment variable or pass it in the config.")
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def get_llm_model_answer(self, prompt):
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return MistralAILlm._get_answer(prompt=prompt, config=self.config)
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@staticmethod
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def _get_answer(prompt: str, config: BaseLlmConfig):
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try:
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from langchain_core.messages import HumanMessage, SystemMessage
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from langchain_mistralai.chat_models import ChatMistralAI
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except ModuleNotFoundError:
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raise ModuleNotFoundError(
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"The required dependencies for MistralAI are not installed."
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'Please install with `pip install --upgrade "embedchain[mistralai]"`'
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) from None
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api_key = config.api_key or os.getenv("MISTRAL_API_KEY")
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client = ChatMistralAI(mistral_api_key=api_key)
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messages = []
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if config.system_prompt:
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messages.append(SystemMessage(content=config.system_prompt))
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messages.append(HumanMessage(content=prompt))
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kwargs = {
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"model": config.model or "mistral-tiny",
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"temperature": config.temperature,
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"max_tokens": config.max_tokens,
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"top_p": config.top_p,
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}
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# TODO: Add support for streaming
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if config.stream:
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answer = ""
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for chunk in client.stream(**kwargs, input=messages):
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answer += chunk.content
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return answer
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else:
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response = client.invoke(**kwargs, input=messages)
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answer = response.content
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return answer
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