| 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 |
|
|
