Multi-Model-Agent / tools.py
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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
)