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from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser
from langchain_community.llms import Ollama
import streamlit as st
import os
from dotenv import load_dotenv
load_dotenv()
os.environ["LANGCHAIN_TRACING_V2"]="true"
os.environ["LANGCHAIN_API_KEY"]=os.getenv("LANGCHAIN_API_KEY")
## Prompt Template
prompt=ChatPromptTemplate.from_messages(
[
("system","You are a helpful assistant. Please response to the user queries"),
("user","Question:{question}")
]
)
## streamlit framework
st.title('Langchain Demo With LLAMA2 API')
input_text=st.text_input("Search the topic u want")
# ollama LLAma2 LLm
llm=Ollama(model="llama2")
output_parser=StrOutputParser()
chain=prompt|llm|output_parser
if input_text:
st.write(chain.invoke({"question":input_text})) |