| from langchain_groq import ChatGroq | |
| from dotenv import load_dotenv | |
| from typing import Optional | |
| import os | |
| class LlamaModel: | |
| """ | |
| This class is used to interact with the Llama LLM models for text generation. | |
| Args: | |
| model: The name of the model to be used. Defaults to 'gemini-pro'. | |
| max_output_tokens: The maximum number of tokens to generate. Defaults to 1024. | |
| top_p: The probability of generating the next token. Defaults to 1.0. | |
| temperature: The temperature of the model. Defaults to 0.0. | |
| top_k: The number of top tokens to consider. Defaults to 5. | |
| """ | |
| def __init__(self, | |
| model: Optional[str] = 'llama3-70b-8192', | |
| ): | |
| load_dotenv() | |
| self.model = llm = ChatGroq(groq_api_key = os.getenv('groq_llama70_key'),model = model) | |
| def execute(self, prompt: str) -> str: | |
| try: | |
| response = self.model.invoke(prompt) | |
| res=response.content | |
| meta=response.response_metadata | |
| return {'text':res,'meta':meta} | |
| except Exception as e: | |
| return f"An error occurred: {e}" |