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import gradio as gr |
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from langchain_core.messages import HumanMessage, messages_to_dict |
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from langgraph.graph import StateGraph, END |
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from agents.agents_nodes import agent_node, format_output, tool_node |
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from utils.state_utils import AgentState |
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def create_interface(): |
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graph = StateGraph(AgentState) |
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graph.add_node("agent", agent_node) |
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graph.add_node("tool", tool_node) |
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graph.add_node("format", format_output) |
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graph.set_entry_point("agent") |
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graph.add_edge("agent", "tool") |
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graph.add_edge("tool", "format") |
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graph.add_edge("format", END) |
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app = graph.compile() |
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def process_query(query: str) -> dict: |
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try: |
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inputs = {"messages": [HumanMessage(content=query)]} |
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result = app.invoke(inputs) |
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return result |
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except Exception as e: |
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return {"error": f"Execution error: {str(e)}"} |
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with gr.Blocks(title="Time Value of Money Calculator") as interface: |
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gr.Markdown("## Time Value of Money Calculator") |
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gr.Markdown("Enter natural language queries about present/future value calculations") |
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with gr.Row(): |
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input_text = gr.Textbox( |
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label="Financial Question", |
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placeholder="E.g.: Present value of $3000 in 5 years at 8% interest?", |
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lines=3 |
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) |
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output_json = gr.JSON(label="Result") |
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submit_btn = gr.Button("Calculate") |
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submit_btn.click( |
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fn=process_query, |
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inputs=input_text, |
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outputs=output_json |
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) |
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return interface |
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