Create app.py

app.py

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+import os
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_openai import ChatOpenAI
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain_core.prompts import MessagesPlaceholder
+from langchain.memory import ConversationBufferWindowMemory
+from operator import itemgetter
+from langchain_core.runnables import RunnableLambda,RunnablePassthrough
+
+genai_key = os.getenv("gen_key")
+
+model = ChatGoogleGenerativeAI(temperature=0,model='gemini-1.5-pro',max_output_tokens=150,convert_system_message_to_human=True,api_key=genai_key)
+
+prompt=ChatPromptTemplate.from_messages([
+     ("system","you are a good assistant"),
+     MessagesPlaceholder(variable_name="history"),
+     ("human","{input}")])
+
+
+memory=ConversationBufferWindowMemory(k=3,return_messages=True)
+
+chain=(RunnablePassthrough.assign(history=RunnableLambda(memory.load_memory_variables)|
+       itemgetter("history"))|prompt|model)
+
+# Streamlit interface
+st.title("chat bot")
+st.write("Enter your input text:")
+
+# User input
+user_input = st.text_area("Input Text")
+
+# Generate and display the response
+if st.button("Generate Response"):
+    res = chain.invoke({"input": user_input})
+    st.write("Generated Response:")
+    st.write(res.content)
+
+        # Save the context
+    memory.save_context({"input": user_input}, {"output": res.content})
+
+        # Display the conversation history
+    #st.write("Conversation History:")
+    #for msg in memory.buffer:
+    #    st.write(f"{msg['role']}: {msg['content']}")
+
+    # Optionally, you can also add a button to reset the conversation history
+if st.button("End Conversation"):
+    st.write("Conversation ended.")
+    memory.clear()
+
+