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from langchain_groq import ChatGroq | |
from langchain.chains import LLMChain | |
from langchain.prompts import PromptTemplate | |
from langchain.tools import Tool | |
import os | |
# summeriser | |
GROQ_API_KEY = os.getenv("GROQ_API_KEY") | |
if not GROQ_API_KEY: | |
raise ValueError("GROQ_API_KEY environment variable is not set.") | |
# Initialize ChatGroq for summarization | |
summarizer_llm = ChatGroq( | |
temperature=0.7, | |
model="llama3-8b-8192", | |
api_key=GROQ_API_KEY, | |
streaming=True, | |
verbose=True | |
) | |
# Define a prompt template for summarization | |
summarization_prompt = PromptTemplate( | |
input_variables=["text"], | |
template="Summarize the following content: {text}" | |
) | |
# Create the summarization chain | |
summarization_chain = LLMChain( | |
llm=summarizer_llm, | |
prompt=summarization_prompt | |
) | |
# Define the summarizer tool | |
def summarize_content_tool(text: str) -> str: | |
return summarization_chain.run(text=text) | |
summarizer_tool = Tool( | |
name="summarizer", | |
description="Summarizes content using a language model.", | |
func=summarize_content_tool | |
) | |