Update app.py

app.py

@@ -1,4 +1,3 @@
-
 import gradio as gr
 import openai
 from openai import OpenAI
@@ -12,8 +11,12 @@ from datetime import datetime
 from sqlmodel import SQLModel, Field, create_engine, Session, select
 from typing import Optional
 import glob
+import re
+import matplotlib.pyplot as plt
+import io
+import base64
 
-# === Clean temp audio files ===
+# === Temp file cleanup ===
 for pattern in ["/tmp/*.wav", "/tmp/*.mp3"]:
     for filepath in glob.glob(pattern):
         try:
@@ -21,22 +24,23 @@ for pattern in ["/tmp/*.wav", "/tmp/*.mp3"]:
         except Exception as e:
             print(f"Could not delete {filepath}: {e}")
 
-# === Environment Setup ===
+# === Environment setup ===
 os.environ["HF_HOME"] = "/tmp/hf"
 os.environ["TRANSFORMERS_CACHE"] = "/tmp/hf"
 os.environ["XDG_CACHE_HOME"] = "/tmp/hf"
 os.environ["MPLCONFIGDIR"] = "/tmp/matplotlib"
 db_path = "/tmp/chatter_sessions.db"
 openai.api_key = os.getenv("OPENAI_API_KEY")
-client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+client = OpenAI(api_key=openai.api_key)
 
-# === Language Codes ===
+# === Language codes ===
 LANG_CODES = {
     "English": "en", "Spanish": "es", "Hindi": "hi", "French": "fr", "German": "de",
     "Arabic": "ar", "Chinese": "zh", "Portuguese": "pt", "Japanese": "ja", "Korean": "ko"
 }
+CATEGORIES = ["Clarity", "Structure", "Fluency", "Content Relevance", "Tone & Expression", "Average"]
 
-# === SQLModel with nickname support ===
+# === SQLModel setup ===
 class SessionEntry(SQLModel, table=True):
     id: Optional[int] = Field(default=None, primary_key=True)
     user: str
@@ -68,7 +72,7 @@ def fetch_user_sessions(user):
     session.close()
     return results
 
-# === Load Whisper ===
+# === Whisper ===
 model = WhisperModel("base", compute_type="int8")
 
 def convert_to_wav(input_file):
@@ -81,7 +85,7 @@ def transcribe_audio(audio_path):
     segments, _ = model.transcribe(audio_path)
     return " ".join([segment.text for segment in segments])
 
-# === GPT Feedback ===
+# === GPT-4 Feedback ===
 def generate_feedback(transcript, language):
     prompt = f"""You are a communication coach. Please respond in [language={language}].
 Evaluate the user's speech on:
@@ -124,6 +128,41 @@ Transcript:
     )
     return response.choices[0].message.content
 
+def parse_scores(feedback):
+    scores = {}
+    for cat in CATEGORIES[:-1]:  # Skip "Average" for now
+        match = re.search(fr"{cat}:\s*(\d+)/10", feedback)
+        scores[cat] = int(match.group(1)) if match else None
+    values = [s for s in scores.values() if s is not None]
+    scores["Average"] = round(sum(values)/len(values), 2) if values else None
+    return scores
+
+def generate_user_chart(user, metric):
+    sessions = fetch_user_sessions(user)
+    if not sessions or metric not in CATEGORIES:
+        return None
+
+    session_ids = list(range(1, len(sessions) + 1))
+    scores = []
+    for s in sessions:
+        parsed = parse_scores(s.feedback)
+        scores.append(parsed.get(metric, 0))
+
+    fig, ax = plt.subplots()
+    ax.plot(session_ids, scores, marker='o', label=metric)
+    ax.set_title(f"{metric} Score Over Time for {user}")
+    ax.set_xlabel("Session")
+    ax.set_ylabel("Score (0–10)")
+    ax.set_ylim(0, 10)
+    ax.grid(True)
+    ax.legend()
+
+    buf = io.BytesIO()
+    plt.savefig(buf, format="png")
+    plt.close(fig)
+    buf.seek(0)
+    return f"data:image/png;base64,{base64.b64encode(buf.read()).decode()}"
+
 def tutor_feedback(audio_file, language, nickname):
     if not audio_file or not os.path.exists(audio_file):
         return "", "No audio received.", None, "", []
@@ -170,7 +209,12 @@ with gr.Blocks(css="light_mode_chatter_owl.css") as app:
     example_box = gr.Textbox(label="🗣 Suggested Improvement", visible=True, placeholder="Click to generate improved speech...")
     history_table = gr.Dataframe(headers=["🕒 Timestamp", "🌐 Language", "📝 Transcript (Preview)", "📋 Feedback (Preview)"])
 
-    # Interactions
+    with gr.Row():
+        chart_metric = gr.Dropdown(label="📈 Choose Metric to Visualize", choices=CATEGORIES, value="Average")
+        view_chart = gr.Button("📊 Show Progress Chart")
+
+    chart_output = gr.Image(label="📉 Your Progress")
+
     audio_input.change(fn=tutor_feedback,
                        inputs=[audio_input, language_dropdown, nickname_box],
                        outputs=[transcript_box, feedback_box, audio_output, hidden_transcript, history_table])
@@ -183,7 +227,11 @@ with gr.Blocks(css="light_mode_chatter_owl.css") as app:
                        inputs=[hidden_transcript, language_dropdown],
                        outputs=example_box)
 
-# === Launch App ===
+    view_chart.click(fn=generate_user_chart,
+                     inputs=[nickname_box, chart_metric],
+                     outputs=chart_output)
+
+# === Launch ===
 if __name__ == "__main__":
     print("✅ App is launching...")
     app.launch(server_name="0.0.0.0", server_port=7860, debug=True)