spoken_module.py

import gradio as gr
import uuid
import os
import matplotlib.pyplot as plt
from gtts import gTTS
from openai import OpenAI
from app_utils import (
    LANG_CODES, save_to_db, fetch_user_sessions,
    convert_to_wav, transcribe_audio,
    parse_scores_from_feedback, generate_progress_summary,
    build_score_comparison_data, render_score_chart,
    build_trend_data, render_trend_chart
)

client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

def generate_feedback(transcript, language, goal="general improvement", focus_areas=None, previous_transcript=None):
    focus_str = ", ".join(focus_areas) if focus_areas else "Clarity, Structure, Fluency, Content Relevance, and Tone"
    history_section = f"\n\nFor reference, their previous transcript was:\n{previous_transcript}" if previous_transcript else ""

    prompt = f"""
You are a supportive communication coach helping a learner whose goal is: **{goal}**.
First, return a JSON object of scores (0–10) for these areas:
{focus_str}
Then provide a clear and friendly evaluation:
For each area:
- Repeat the score (0–10)
- Explain why the user got that score
Then provide:
- A detailed summary of strengths and improvement areas.
- One motivational line to end with. Do not specifically add motivational keyword, just add the line.
Transcript:
{history_section}
""".strip()

    response = client.chat.completions.create(
        model="gpt-4",
        messages=[
            {"role": "system", "content": f"You are a warm and constructive communication coach responding in {language}."},
            {"role": "user", "content": prompt}
        ],
        temperature=0.7
    )
    feedback = response.choices[0].message.content

    try:
        split_idx = feedback.index('}') + 1
        feedback_clean = feedback[split_idx:].strip()
    except:
        feedback_clean = feedback

    return feedback, feedback_clean

def generate_example_response(transcript, language):
    prompt = f"""Rewrite this speech to make it more polished, fluent, and confident.
Keep the meaning and tone the same, but improve clarity and structure.
Transcript:
{transcript}
"""
    response = client.chat.completions.create(
        model="gpt-4",
        messages=[
            {"role": "system", "content": f"Reply in {language}. Provide only the improved version of the speech."},
            {"role": "user", "content": prompt}
        ]
    )
    return response.choices[0].message.content

def render_empty_chart(title):
    fig, ax = plt.subplots()
    ax.set_title(title)
    ax.text(0.5, 0.5, "No scores yet.\nSpeak again to generate progress!", ha='center', va='center', fontsize=12)
    ax.axis('off')
    return fig

def spoken_dashboard(nickname_input):
    with gr.Column() as spoken_panel:
        gr.Markdown("""
        <div id="header" style="text-align: center;">
            <h2>🦉 Meet <strong>Chatter the Owl</strong></h2>
            <p>Speak in your chosen language and get personalized feedback and progress tracking.</p>
        </div>
        """)

        with gr.Row():
            language_dropdown = gr.Dropdown(label="🌍 Language", choices=list(LANG_CODES.keys()), value="English")
            goal_dropdown = gr.Dropdown(label="🎯 Goal", choices=["Interview preparation", "Public speaking", "Class presentation", "General improvement"], value="General improvement")
            focus_checkboxes = gr.CheckboxGroup(label="🧠 Focus Areas", choices=["Clarity", "Structure", "Fluency", "Tone", "Content Relevance"], value=["Clarity", "Structure", "Fluency", "Tone", "Content Relevance"])

        with gr.Row():
            audio_input = gr.Audio(type="filepath", label="🎙 Speak or Upload Audio")
            audio_output = gr.Audio(label="🔊 Chatter's Response", type="filepath")

        transcript_box = gr.Textbox(label="📖 Transcript", interactive=False)
        feedback_box = gr.Textbox(label="💡 Feedback", interactive=False)
        hidden_transcript = gr.Textbox(visible=False)

        with gr.Row():
            try_again = gr.Button("🔁 Try Again")
            show_example = gr.Button("🎯 Show Me an Example")

        example_box = gr.Textbox(label="🗣 Suggested Improvement", visible=True)
        history_table = gr.Dataframe(headers=["🕒 Timestamp", "🌐 Language", "📄 Transcript", "💬 Feedback"])

        with gr.Row():
            with gr.Column(scale=1):
                gr.Dropdown(
                    choices=[""],
                    label="📊 Score Comparison",
                    interactive=False,
                    show_label=True
                )
                score_chart = gr.Plot()
        
            with gr.Column(scale=1):
                trend_category_dropdown = gr.Dropdown(
                    label="📈 Track Progress In",
                    choices=["Clarity", "Structure", "Fluency", "Tone", "Content Relevance"],
                    value="Tone"
                )
                trend_chart = gr.Plot(label="Progress Over Time")


        milestone_box = gr.Markdown(visible=False)

        def tutor_feedback(audio_file, language, goal, focus_areas, trend_category, nickname):
            if not audio_file:
                return "", "No audio received.", None, "", [], render_empty_chart("📊 Score Comparison"), render_empty_chart("📈 Progress Over Time"), gr.update(visible=False)

            if hasattr(nickname, "value"):
                nickname = nickname.value

            wav_path = convert_to_wav(audio_file)
            transcript = transcribe_audio(wav_path)
            previous_sessions = fetch_user_sessions(nickname)
            previous_transcript = previous_sessions[-1].transcript if previous_sessions else None
            previous_feedback = previous_sessions[-1].feedback if previous_sessions else None

            full_feedback, feedback_clean = generate_feedback(transcript, language, goal, focus_areas, previous_transcript)

            if previous_feedback:
                feedback_clean += generate_progress_summary(full_feedback, previous_feedback)

            milestone = ""
            session_count = len(previous_sessions) + 1
            if session_count in [3, 5, 10]:
                milestone = f"🎉 Congrats on completing **{session_count} sessions**!"
                feedback_clean += f"\n\n{milestone}"

            lang_code = LANG_CODES.get(language, "en")
            tts = gTTS(feedback_clean, lang=lang_code)
            mp3_path = f"/tmp/{uuid.uuid4()}.mp3"
            tts.save(mp3_path)

            save_to_db(nickname, transcript, full_feedback, language)
            sessions = fetch_user_sessions(nickname)
            session_table = [[s.timestamp, s.language, s.transcript[:40], s.feedback[:40]] for s in sessions]

            score_plot = render_score_chart(build_score_comparison_data(full_feedback, previous_feedback)) if previous_feedback else render_empty_chart("📊 Score Comparison")
            dates, trend_scores = build_trend_data(sessions, trend_category)
            trend_plot = render_trend_chart(dates, trend_scores, trend_category) if trend_scores else render_empty_chart(f"📈 {trend_category} Progress")

            return transcript, feedback_clean, mp3_path, transcript, session_table, score_plot, trend_plot, gr.update(visible=bool(milestone), value=milestone)

        audio_input.change(
            fn=tutor_feedback,
            inputs=[audio_input, language_dropdown, goal_dropdown, focus_checkboxes, trend_category_dropdown, nickname_input],
            outputs=[transcript_box, feedback_box, audio_output, hidden_transcript, history_table, score_chart, trend_chart, milestone_box],
            show_progress="minimal"
        )

        try_again.click(fn=lambda: ("", "", None, "", "", render_empty_chart("📊 Score Comparison"), render_empty_chart("📈 Progress Over Time"), gr.update(visible=False)),
                        inputs=None,
                        outputs=[transcript_box, feedback_box, audio_output, hidden_transcript, example_box, score_chart, trend_chart, milestone_box])

        show_example.click(fn=generate_example_response,
                           inputs=[hidden_transcript, language_dropdown],
                           outputs=example_box)

        def update_trend_chart(trend_category, nickname):
            if hasattr(nickname, "value"):
                nickname = nickname.value
            sessions = fetch_user_sessions(nickname)
            dates, trend_scores = build_trend_data(sessions, trend_category)
            if trend_scores:
                return render_trend_chart(dates, trend_scores, trend_category)
            return render_empty_chart(f"📈 {trend_category} Progress")

        trend_category_dropdown.change(
            fn=update_trend_chart,
            inputs=[trend_category_dropdown, nickname_input],
            outputs=[trend_chart]
        )

    return spoken_panel