Create app.py

app.py

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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 environment variables
+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 respond to the user queries"),
+        ("user", "Question: {question}")
+    ]
+)
+
+# Streamlit app
+st.title('Langchain Demo With LLAMA2 API')
+input_text = st.text_input("Search the topic you want")
+
+# Ollama LLama2 LLM
+llm = Ollama(model="llama2")
+output_parser = StrOutputParser()
+chain = prompt | llm | output_parser
+
+# Display result when user inputs text
+if input_text:
+    response = chain.invoke({"question": input_text})
+    st.write(response)