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from langchain_core.prompts import ChatPromptTemplate | |
from langchain_core.output_parsers import StrOutputParser | |
from langchain import PromptTemplate, LLMChain | |
from langchain_groq import ChatGroq | |
import streamlit as st | |
import os | |
def get_response(input_text): | |
groq_api_key=os.getenv("GROK") | |
llm=ChatGroq(groq_api_key=groq_api_key, | |
model_name="mixtral-8x7b-32768") | |
prompt=ChatPromptTemplate.from_messages( | |
[ | |
("system","You are a therapist. Be like a friend to them. Ask about their day. Make them feel safe and heard. Dont tell them before hand if and only if specifically they ask you that they want to talk with a therapist then tell them to contact someone from our website. "), | |
("user","Question:{question}") | |
] | |
) | |
#prompt = PromptTemplate(template=prompt, input_variables=["question"]) | |
#llm_chain = LLMChain(prompt=prompt, llm=llm) | |
output_parser=StrOutputParser() | |
chain=prompt|llm|output_parser | |
response=chain.invoke({"question":input_text}) | |
return response | |
def main(): | |
st.title("Freud") | |
input_text=st.text_input("How are you Today?") | |
if st.button("Say"): | |
if input_text.strip() !="": | |
response=get_response(input_text) | |
st.write(response) | |
else: | |
st.warning("Please enter a question.") | |
if __name__=="__main__": | |
main() |