working app

.gitignore

@@ -0,0 +1,36 @@
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+*.egg-info/
+*.egg
+
+# Virtual Environment
+chatbot-env/
+venv/
+ENV/
+env/
+env.bak/
+
+# Environment variables
+.env
+
+# IDE specific files
+.idea/
+.vscode/
+*.swp
+*.swo
+
+# Distribution / packaging
+dist/
+build/
+*.egg-info/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# Local development settings
+*.log
+.DS_Store

app.py

@@ -0,0 +1,40 @@
+import gradio as gr
+from backend import backend_chat
+from langchain_core.messages import HumanMessage, BaseMessage, AIMessage
+
+
+def respond(message: str, history: list[dict]):
+    """
+    message: the latest user input
+    history: openai-style list of dicts with keys 'role' and 'content'
+    """
+
+    backend_history = []
+    for msg in history:
+        if msg["role"] == "user":
+            backend_history.append(HumanMessage(content=msg["content"]))
+        elif msg["role"] == "assistant":
+            backend_history.append(AIMessage(content=msg["content"]))
+   
+    updated_backend_history = backend_chat(backend_history, message)
+    latest_assistant = None
+    for msg in reversed(updated_backend_history):
+        if not isinstance(msg, HumanMessage):
+            latest_assistant = msg
+            break
+
+    if latest_assistant is None:
+        return "Sorry, I couldn't generate a response."
+    return latest_assistant.content
+
+def main():
+    demo = gr.ChatInterface(
+        fn=respond,
+        type="messages",
+        title="ChatBot",
+        description="Chatbot using langgraph backend and Memory Checkpointing",
+    )
+    demo.launch()
+
+if __name__ == "__main__":
+    main()

backend.py

@@ -0,0 +1,47 @@
+# backend.py
+
+from langgraph.graph import StateGraph, START, END
+from typing import TypedDict, Annotated, List
+from dotenv import load_dotenv
+from langgraph.checkpoint.memory import InMemorySaver
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain_core.messages import BaseMessage, HumanMessage
+from langgraph.graph.message import add_messages
+
+load_dotenv()
+THREAD_ID = "1"
+
+gen_llm = ChatGoogleGenerativeAI(model='gemini-2.5-flash')
+
+class ChatBotState(TypedDict):
+    messages: Annotated[List[BaseMessage], add_messages]
+
+def chat_node(state: ChatBotState) -> ChatBotState:
+    messages = state['messages']
+    response = gen_llm.invoke(messages)
+    # depending on design, maybe response returns BaseMessage or list
+    return {'messages': [response]}
+
+# build graph
+graph = StateGraph(ChatBotState)
+graph.add_node('chat_node', chat_node)
+graph.add_edge(START, 'chat_node')
+graph.add_edge('chat_node', END)
+checkpointer = InMemorySaver()
+chatbot = graph.compile(checkpointer=checkpointer)
+
+def backend_chat(history: List[BaseMessage], user_text: str) -> List[BaseMessage]:
+    if history is None:
+        history = []
+    history.append(HumanMessage(content=user_text))
+    state = {'messages': history}
+    config = {
+        "configurable": {
+            "thread_id": THREAD_ID
+        }
+    }
+    result_state = chatbot.invoke(state, config=config)
+    new_messages = result_state.get('messages', [])
+    # append new messages (assistant responses) to history
+    history.extend(new_messages)
+    return history

requirements.txt

@@ -0,0 +1,5 @@
+langgraph
+langchain
+langchain-google-genai
+python-dotenv
+gradio