Create test.py

test.py

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+import streamlit as st
+from langchain.chains import LLMChain
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_google_genai import ChatGoogleGenerativeAI
+import os
+import google.generativeai as genai
+
+api_key = os.getenv("GEMINI_KEY2")
+
+# Define the Chat Prompt Template
+prompt = ChatPromptTemplate.from_messages(
+    [
+        (
+            "system",
+            "You are a helpful assistant that translates {input_language} to {output_language}.",
+        ),
+        ("human", "{input}"),
+    ]
+)
+
+# Initialize the Google Generative AI model
+llm = ChatGoogleGenerativeAI(
+    model="gemini-1.5-pro",
+    temperature=0.5,
+    max_tokens=None,
+    timeout=None,
+    max_retries=2,
+    api_key=api_key 
+)
+
+# Define the chain for translation
+translation_chain = LLMChain(prompt=prompt, llm=llm)
+
+# Function to translate text
+def translate_text(input_text, input_language, output_language):
+    try:
+        response = translation_chain({"input": input_text, "input_language": input_language, "output_language": output_language})
+        translation = response["text"].strip()
+    except Exception as e:
+        st.error(f"Error translating text to {output_language}: {e}")
+        translation = f"Sorry, we couldn't translate to {output_language} at the moment."
+    
+    return translation
+
+# Streamlit UI
+st.title("📝 Text Translation Bot with LangChain and Google Generative AI")
+
+# User input
+input_text = st.text_area("Enter text to translate:")
+
+# Language choices
+languages = ["Hindi", "Spanish", "German"]
+output_language = st.selectbox("Select output language:", languages)
+
+# Generate translation button
+if st.button("Translate"):
+    if input_text.strip():
+        st.write("Translating text, please wait...")
+        translated_text = translate_text(input_text, "English", output_language)
+        st.write("### Translated Text")
+        st.write(translated_text)
+    else:
+        st.warning("Please enter some text to translate.")