DebateForge/main.py at master · aaishwarymishra/DebateForge · GitHub

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import token
from importlib_metadata import metadata
from tkinter import Scale
from gradio import Interface, Textbox, Markdown, Slider, Chatbot, ChatMessage, Blocks, Row, Column, ClearButton, Button, Number,Label
from final_graph import create_final_graph, render_bettafish_report
from forum_graph import create_forum_graph
from graph_states import FinalState, ForumState
from langchain_core.callbacks import UsageMetadataCallbackHandler
import uuid
import time

graph = None
async def init_graph():
    global graph
    if graph is None:
        graph = await create_final_graph()

async def process_inputs(query, refinements, max_rounds):

    state = FinalState(
            query=query,
            vector_store="",
            query_limit=int(refinements),
            max_rounds=int(max_rounds),
            current_round=1,
            step=0,
            round_digests=[],
            running_mermaid_graph="",
            debate_history=[],
            final_report=None,
            messages = [],
            references = []
        )

    await init_graph()

    messages = []
    thread_id = str(uuid.uuid4())
    usage_callback = UsageMetadataCallbackHandler()
    config = {"configurable":{"thread_id":thread_id},"recursion_limit":100,"callbacks":[usage_callback]}
    step = 0
    current_round = 1
    current_round_md = "### Current Round: {current_round}"
    start_time = time.time()
    token_used = 0
    input_tokens = 0
    output_tokens = 0
    role = "user"
    status = "Searching the web for relevant information..."
    try:
        async for parent,child in graph.astream(state,config=config,stream_mode="updates",subgraphs=True):
            print("Parent:",parent)
            print("Child:",child,end="\n\n")
            if not parent or len(parent)==0:
                continue
            parent_node = parent[0].split(":")[0]
            curr_node = list(child.keys())[0]
            values = child.get(curr_node,{})
            if parent_node == "Research":
                if curr_node == "Query Refiner":
                    status = "Searching with refined queries..."
            elif parent_node == "Forum Graph":
                if curr_node == "Debate Supervisor":
                    step = values.get("step",step)
                    msgs = values.get("messages",[])

                    if step%2 == 0:
                        role = "assistant"
                    else:
                        role = "user"

                    if len(msgs)>0:
                        messages.append(ChatMessage(role=role,content=msgs[-1].content,metadata={"title":"Moderator Instructions"}))
                    status = "Analyzing and creating arguments..."
                elif curr_node == "Persona Agent":
                    msgs = values.get("messages",[])
                    if msgs:
                        tool_call = False
                        curr_message = msgs[-1]
                        if len(curr_message.content.strip()) == 0 and len(curr_message.tool_calls)>0:
                            tool_call = True

                        if not tool_call:
                            messages.append(ChatMessage(role=role,content=curr_message.content))
                        else:
                            messages.append(ChatMessage(role=role,content="Tool Call Made. Awaiting Response...",metadata={"title":"Fetching researched data"}))
                    status = "Engaging in debate..."
                elif curr_node == "Round Digest":
                    current_round += 1
                    status = "Preparing for next round..."

            for model, usage_data in usage_callback.usage_metadata.items():
                input_tokens += usage_data.get("input_tokens",0)
                output_tokens += usage_data.get("output_tokens",0)
                token_used += usage_data.get("total_tokens",0)

            total_time_taken = round((time.time()-start_time),2)
            yield messages, "" , status, current_round_md.format(current_round=current_round),total_time_taken,input_tokens,output_tokens, token_used

    except Exception as e:
        print("Error during running the graph:",e)
        yield messages, "" , f" An error occurred during the graph execution: {e} ", current_round_md.format(current_round=current_round),total_time_taken,input_tokens,output_tokens, token_used
        return

    try:

        snapshot = graph.get_state(config={"configurable":{"thread_id":thread_id}})
        if snapshot.values:
            report=render_bettafish_report(snapshot.values)
        else:
            report = "No state found. Did the graph finish?"


        yield messages, report , " Graph Execution Completed! Report Generated Below. ", current_round_md.format(current_round=current_round),total_time_taken,input_tokens,output_tokens, token_used

    except Exception as e:
        print("Error during report generation:",e)
        yield messages, "" , f" An error occurred during report generation: {e} ", current_round_md.format(current_round=current_round),total_time_taken,input_tokens,output_tokens, token_used
        return


with Blocks() as demo:
    Markdown("<div style='text-align:center;'> <h1> Strategic Debate Assistant </h1>  </div>")
    with Row():
        with Column():
            with Row():
                refinements = Slider(0, 3, label="Max Query Refinements", step=1, value=0)
                max_rounds = Slider(1, 10, label="Max Debate Rounds",step=1, value=1)
            query = Textbox(label="Enter your strategic question here", lines=2)
            with Row():
                ClearButton([query,refinements,max_rounds], value="Reset")
                submit_btn = Button("Submit",variant="primary")
            with Row():
                input_tokens = Number(label=" Input Tokens Used", value=0,interactive=False)
                output_tokens = Number(label="Output Tokens Used", value=0,interactive=False)
                total_tokens = Number(label="Total Tokens Used", value=0,interactive=False)
                total_time = Number(label="Total Time Taken (s)", value=0,interactive=False)
                label = Textbox(value=" Report will be generated below upon submission", label="Status", interactive=False )
        with Column():
            current_round = Markdown(label="Current round")
            chatbot = Chatbot(label="Debate Conversation")
    report_md = Markdown(label="Strategic Report")

    submit_btn.click(process_inputs, inputs=[query, refinements, max_rounds], outputs=[chatbot, report_md,label, current_round, total_time,input_tokens,output_tokens,total_tokens])


demo.launch()