import os
import argparse
import gradio as gr
from difflib import Differ
from string import Template
from utils import load_prompt, setup_gemini_client
from configs.responses import SummaryResponses

def parse_args():
    parser = argparse.ArgumentParser()
    parser.add_argument("--ai-studio-api-key", type=str, default=os.getenv("GEMINI_API_KEY"))
    parser.add_argument("--vertexai", action="store_true", default=False)
    parser.add_argument("--vertexai-project", type=str, default="gcp-ml-172005")
    parser.add_argument("--vertexai-location", type=str, default="us-central1")
    parser.add_argument("--model", type=str, default="gemini-1.5-flash")

    parser.add_argument("--prompt-tmpl-path", type=str, default="configs/prompts.toml")
    parser.add_argument("--css-path", type=str, default="statics/styles.css")
    args = parser.parse_args()
    return args

def find_attached_file(filename, attached_files):
    for file in attached_files:
        if file['name'] == filename:
            return file
    return None

def echo(message, history, state):
    attached_file = None
    
    if message['files']:
        path_local = message['files'][0]
        filename = os.path.basename(path_local)

        attached_file = find_attached_file(filename, state["attached_files"])
        if attached_file is None: 
            path_gcp = client.files.upload(path=path_local)
            state["attached_files"].append({
                "name": filename,
                "path_local": path_local,
                "gcp_entity": path_gcp,
                "path_gcp": path_gcp.name,
                "mime_type=": path_gcp.mime_type,
                "expiration_time": path_gcp.expiration_time,
            })
            attached_file = path_gcp

    user_message = [message['text']]
    if attached_file: user_message.append(attached_file)

    chat_history = state['messages']
    chat_history = chat_history + user_message
    state['messages'] = chat_history

    response = client.models.generate_content(
        model="gemini-1.5-flash",
        contents=state['messages'],
    )
    model_response = response.text

    # make summary
    if state['summary'] != "":
        response = client.models.generate_content(
            model="gemini-1.5-flash",
            contents=[
                Template(
                    prompt_tmpl['summarization']['prompt']
                ).safe_substitute(
                    previous_summary=state['summary'], 
                    latest_conversation=str({"user": message['text'], "assistant": model_response})
                )
            ],
            config={'response_mime_type': 'application/json',
                'response_schema': SummaryResponses,
            },
        )

    if state['summary'] != "":
        prev_summary = state['summary_history'][-1]
    else:
        prev_summary = ""

    d = Differ()
    state['summary'] = (
        response.parsed.summary 
        if getattr(response.parsed, "summary", None) is not None 
        else response.text
    )
    state['summary_history'].append(
        response.parsed.summary 
        if getattr(response.parsed, "summary", None) is not None 
        else response.text
    )
    state['summary_diff_history'].append(
        [
            (token[2:], token[0] if token[0] != " " else None)
            for token in d.compare(prev_summary, state['summary'])
        ]
    )

    return (
        model_response, 
        state, 
        # state['summary'],
        state['summary_diff_history'][-1],
        state['summary_history'][-1],
        gr.Slider(
            maximum=len(state['summary_history']),
            value=len(state['summary_history']),
            visible=False if len(state['summary_history']) == 1 else True, interactive=True
        ),
    )

def change_view_toggle(view_toggle):
    if view_toggle == "Diff":
        return (
            gr.HighlightedText(visible=True),
            gr.Markdown(visible=False)
        )
    else:
        return (
            gr.HighlightedText(visible=False),
            gr.Markdown(visible=True)
        )        

def navigate_to_summary(summary_num, state):
    return (
        state['summary_diff_history'][summary_num-1],
        state['summary_history'][summary_num-1]
    )

def main(args):
    style_css = open(args.css_path, "r").read()

    global client, prompt_tmpl
    client = setup_gemini_client(args)
    prompt_tmpl = load_prompt(args)
    
    ## Gradio Blocks
    with gr.Blocks(css=style_css) as demo:
        # State per session
        state = gr.State({
            "messages": [],
            "attached_files": [],
            "summary": "",
            "summary_history": [],
            "summary_diff_history": []
        })

        with gr.Column():
            gr.Markdown("# Adaptive Summarization")
            gr.Markdown("AdaptSum stands for Adaptive Summarization. This project focuses on developing an LLM-powered system for dynamic summarization. Instead of generating entirely new summaries with each update, the system intelligently identifies and modifies only the necessary parts of the existing summary. This approach aims to create a more efficient and fluid summarization process within a continuous chat interaction with an LLM.")

        with gr.Column():
            with gr.Accordion("Adaptively Summarized Conversation", elem_id="adaptive-summary-accordion", open=False):
                with gr.Row(elem_id="view-toggle-btn-container"):
                    view_toggle_btn = gr.Radio(
                        choices=["Diff", "Markdown"],
                        value="Markdown",
                        interactive=True,
                        elem_id="view-toggle-btn"
                    )

                summary_diff = gr.HighlightedText(
                    label="Summary so far",
                    # value="No summary yet. As you chat with the assistant, the summary will be updated automatically.",
                    combine_adjacent=True,
                    show_legend=True,
                    color_map={"+": "red", "-": "green"},
                    elem_classes=["summary-window"],
                    visible=False
                )

                summary_md = gr.Markdown(
                    label="Summary so far",
                    value="No summary yet. As you chat with the assistant, the summary will be updated automatically.",
                    elem_classes=["summary-window"],
                    visible=True
                )

                summary_num = gr.Slider(label="summary history", minimum=1, maximum=1, step=1, show_reset_button=False, visible=False)

            view_toggle_btn.change(change_view_toggle, inputs=[view_toggle_btn], outputs=[summary_diff, summary_md])
            summary_num.release(navigate_to_summary, inputs=[summary_num, state], outputs=[summary_diff, summary_md])
        
        with gr.Column("chat-window", elem_id="chat-window"):
            gr.ChatInterface(
                multimodal=True,
                type="messages", 
                fn=echo, 
                additional_inputs=[state],
                additional_outputs=[state, summary_diff, summary_md, summary_num],
            )

    return demo

if __name__ == "__main__":
    args = parse_args()
    demo = main(args)
    demo.launch()