Create app.py

app.py

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+import gradio as gr
+from langgraph.graph import StateGraph, MessagesState, START, END
+from langgraph.types import Command
+from langchain_core.messages import BaseMessage, HumanMessage
+from langgraph.prebuilt import create_react_agent
+from langchain_anthropic import ChatAnthropic
+
+# Define your LangGraph agents and nodes
+llm = ChatAnthropic(model="claude-3-5-sonnet-latest")
+
+def make_system_prompt(suffix: str) -> str:
+    return (
+        "You are a helpful AI assistant, collaborating with other assistants."
+        " Use the provided tools to progress towards answering the question."
+        " If you are unable to fully answer, that's OK, another assistant with different tools "
+        " will help where you left off. Execute what you can to make progress."
+        " If you or any of the other assistants have the final answer or deliverable,"
+        " prefix your response with FINAL ANSWER so the team knows to stop."
+        f"\n{suffix}"
+    )
+
+# Research agent and node
+def research_node(state: MessagesState) -> Command[str]:
+    agent = create_react_agent(
+        llm,
+        tools=[],  # Define your tools if needed
+        state_modifier=make_system_prompt("You can only do research.")
+    )
+    result = agent.invoke(state)
+    goto = END if "FINAL ANSWER" in result["messages"][-1].content else "chart_generator"
+    result["messages"][-1] = HumanMessage(
+        content=result["messages"][-1].content, name="researcher"
+    )
+    return Command(update={"messages": result["messages"]}, goto=goto)
+
+# Chart generator agent and node
+def chart_node(state: MessagesState) -> Command[str]:
+    agent = create_react_agent(
+        llm,
+        tools=[],  # Define your tools if needed
+        state_modifier=make_system_prompt("You can only generate charts.")
+    )
+    result = agent.invoke(state)
+    goto = END if "FINAL ANSWER" in result["messages"][-1].content else "researcher"
+    result["messages"][-1] = HumanMessage(
+        content=result["messages"][-1].content, name="chart_generator"
+    )
+    return Command(update={"messages": result["messages"]}, goto=goto)
+
+# Initialize the LangGraph workflow
+workflow = StateGraph(MessagesState)
+workflow.add_node("researcher", research_node)
+workflow.add_node("chart_generator", chart_node)
+workflow.add_edge(START, "researcher")
+workflow.add_edge("researcher", "chart_generator")
+workflow.add_edge("chart_generator", END)
+graph = workflow.compile()
+
+# Define the function to run the graph
+def run_langgraph(user_input):
+    # Start with user input
+    events = graph.stream(
+        {"messages": [("user", user_input)]},
+        {"recursion_limit": 150}
+    )
+    # Collect outputs from the workflow
+    output = []
+    for event in events:
+        output.append(event)
+    # Return the final output
+    return output[-1]["messages"][-1].content if output else "No output generated"
+
+# Create Gradio interface
+def process_input(user_input):
+    result = run_langgraph(user_input)
+    return result
+
+interface = gr.Interface(
+    fn=process_input,
+    inputs="text",
+    outputs="text",
+    title="LangGraph Research Automation",
+    description="Enter your research task (e.g., 'Get GDP data for the USA over the past 5 years and create a chart.')."
+)
+
+# Launch the Gradio interface
+if __name__ == "__main__":
+    interface.launch()