langchain-perplexity

import os from langchain_perplexity import ChatPerplexity from langchain_core.prompts import ChatPromptTemplate # Set your Perplexity API key as an environment variable # It's recommended to load this from a .env file or similar in production os.environ["PERPLEXITY_API_KEY"] = os.environ.get("PERPLEXITY_API_KEY", "your_perplexity_api_key_here") # Initialize the chat model chat = ChatPerplexity(model="sonar") # Define a prompt template prompt = ChatPromptTemplate.from_messages([ ("system", "You are a helpful assistant."), ("human", "{input}") ]) # Create a chain chain = prompt | chat # Invoke the chain with a question response = chain.invoke({"input": "What breakthroughs in fusion energy have been announced this year?"}) print(response.content) # Example with Pro Search (requires 'sonar-pro' model and WebSearchOptions) # from langchain_perplexity import WebSearchOptions # pro_chat = ChatPerplexity( # model="sonar-pro", # # web_search_options=WebSearchOptions(search_type="pro") # Uncomment if specific search_type needed # ) # pro_response = pro_chat.invoke("How does the electoral college work?") # print(pro_response.content)