Created
September 18, 2024 06:48
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Usage of llama-3.1-sonar-small-128k-online
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| import os | |
| import sys | |
| from dotenv import load_dotenv | |
| from langchain_community.chat_models import ChatPerplexity | |
| from langchain_core.prompts import ChatPromptTemplate | |
| from langchain_core.output_parsers import StrOutputParser | |
| # Load environment variables | |
| load_dotenv() | |
| # Set up the Perplexity API client | |
| chat = ChatPerplexity( | |
| model="llama-3.1-sonar-small-128k-online", | |
| temperature=0, | |
| pplx_api_key=os.getenv("PPLX_API_KEY"), | |
| ) | |
| def evaluate_text(file_path, prompt): | |
| # Read the file content | |
| with open(file_path, "r", encoding="utf-8") as file: | |
| file_content = file.read() | |
| # Create a prompt template | |
| prompt_template = ChatPromptTemplate.from_messages( | |
| [ | |
| ("system", "You are a helpful assistant."), | |
| ("human", "{prompt}\n\n{file_content}"), | |
| ] | |
| ) | |
| # Create a runnable sequence | |
| chain = prompt_template | chat | StrOutputParser() | |
| # Invoke the chain | |
| return chain.invoke({"prompt": prompt, "file_content": file_content}) | |
| if __name__ == "__main__": | |
| if len(sys.argv) != 3: | |
| print("Usage: python script_name.py <prompt> <path_to_text_file>") | |
| sys.exit(1) | |
| prompt = sys.argv[1] | |
| file_path = sys.argv[2] | |
| # Make the API call and get the evaluation | |
| evaluation = evaluate_text(file_path, prompt) | |
| # Print the evaluation | |
| print(evaluation) |
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