app.py

import getpass
import os
import streamlit as st
from dotenv import load_dotenv
from langchain_core.output_parsers import StrOutputParser
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain_core.prompts import ChatPromptTemplate

# Load environment variables
load_dotenv()

# Instantiate the language model
llm = ChatGoogleGenerativeAI(
    model="gemini-1.5-pro",
    temperature=0,
    max_tokens=None,
    timeout=None,
    max_retries=2,
)

# Define the prompt template
prompt = ChatPromptTemplate.from_messages(
    [
        (
            "system",
            "You are a helpful assistant that translates {input_language} to {output_language}.",
        ),
        ("human", "{input}"),
    ]
)

# Streamlit UI
st.title('Langchain Demo With Gemini (Language Translator)')
st.write("Select the input and output languages, then enter a sentence to translate.")

# Language selection dropdowns
input_language = st.selectbox("Select input language", ["English", "German", "French", "Spanish"])
output_language = st.selectbox("Select output language", ["German", "English", "French", "Spanish", "Japanese","Hindi","Kannada","Telugu","Tamil"])

# Text input for the sentence to be translated
input_text = st.text_input("Enter the sentence to translate")

# Output parser
output_parser = StrOutputParser()

# Chain setup
chain = prompt | llm | output_parser

# Run the translation if text is provided
if input_text:
    result = chain.invoke(
        {
            "input_language": input_language,
            "output_language": output_language,
            "input": input_text,
        }
    )
    st.write("Translated Text:")
    st.write(result)