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from langchain_core.prompts import ChatPromptTemplate | |
from langchain_core.output_parsers import StrOutputParser | |
from langchain_groq import ChatGroq | |
import streamlit as st | |
import os | |
from dotenv import load_dotenv | |
load_dotenv() | |
os.environ["GROQ_API_KEY"] = os.getenv("GROQ_API_KEY") | |
os.environ["LANGCHAIN_API_KEY"] = os.getenv("LANGCHAIN_API_KEY") | |
os.environ["LANGCHAIN_TRACING_V2"] = "true" | |
os.environ["LANGCHAIN_PROJECT"] = "sarcastic_bot" | |
# build a LLM chain | |
promptTemplate = ChatPromptTemplate.from_messages( | |
[ | |
("system", "Reply with {way} to all the questions"), | |
("user", "Question:{question}"), | |
] | |
) | |
model = ChatGroq(model="mixtral-8x7b-32768") | |
parser = StrOutputParser() | |
chain = promptTemplate|model|parser | |
#create streamlit | |
st.title("Sarcastic GROQ") | |
input_text = st.text_input("Ask you question mate!") | |
if input_text: | |
st.write(chain.invoke({"way": "sarcasm", "question": input_text})) |