Initial commit

medical_scribe_gui_v3.py

@@ -0,0 +1,235 @@
+import os
+import sys
+import tkinter as tk
+from tkinter import filedialog, messagebox, ttk
+import threading
+import subprocess
+import time
+import ollama
+from fpdf import FPDF
+
+# Token HF
+HF_TOKEN = "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"
+
+# Dictionnaire de Prompts Enrichi
+PROMPT_TEMPLATES = {
+    "Contrôle T2A / Codage CIM-10": """Tu es un médecin DIM expert. Analyse cette réunion sur le codage CIM-10 et produis :
+1. Un tableau des phases (Avant/Pendant/Après contrôle).
+2. Une check-list des points d'attention (DP, DAS, Actes).
+3. Un modèle de fiche de synthèse pratique.
+Sois extrêmement rigoureux sur la terminologie PMSI/T2A.""",
+
+    "Consultation Standard": """Analyse cette consultation médicale et produis une synthèse :
+1. Motif et symptômes.
+2. Antécédents et Examen clinique.
+3. Diagnostic et Plan thérapeutique (ordonnance).""",
+
+    "Compte-rendu Opératoire": """Produis un compte-rendu chirurgical structuré :
+1. Indication et type d'intervention.
+2. Description technique détaillée.
+3. Matériel et incidents.
+4. Suites prévues.""",
+
+    "Lettre au Confrère": """Rédige une lettre de liaison formelle adressée à un confrère à partir de ce transcript.
+Format professionnel avec en-tête et conclusion standard.""",
+
+    "Prompt Personnalisé": "Tapez vos propres instructions ici..."
+}
+
+class PDF(FPDF):
+    def header(self):
+        self.set_font('Arial', 'B', 15)
+        self.cell(0, 10, 'Compte-rendu Médical IA', 0, 1, 'C')
+        self.ln(5)
+
+class MedicalScribeGUIv3:
+    def __init__(self, root):
+        self.root = root
+        self.root.title("Medical AI Scribe v3.0 - Expert Edition")
+        self.root.geometry("1000x900")
+        self.root.configure(bg="#eceff1")
+
+        # Variables
+        self.audio_path = tk.StringVar()
+        self.selected_model = tk.StringVar()
+        self.selected_template = tk.StringVar(value="Contrôle T2A / Codage CIM-10")
+        self.status_var = tk.StringVar(value="Prêt.")
+        self.progress_val = tk.DoubleVar(value=0)
+        self.last_summary_path = None
+        
+        self.current_process = None
+
+        self.setup_ui()
+        threading.Thread(target=self.load_ollama_models, daemon=True).start()
+
+    def setup_ui(self):
+        main_frame = tk.Frame(self.root, bg="#eceff1", padx=25, pady=25)
+        main_frame.pack(fill=tk.BOTH, expand=True)
+
+        # Titre
+        tk.Label(main_frame, text="MEDICAL AI SCRIBE EXPERT", font=("Segoe UI", 20, "bold"), bg="#eceff1", fg="#263238").pack(pady=(0, 20))
+
+        # Zone Fichier
+        f_frame = tk.LabelFrame(main_frame, text=" 1. Source Audio ", font=("Arial", 10, "bold"), bg="#eceff1", padx=10, pady=10)
+        f_frame.pack(fill="x", pady=10)
+        tk.Entry(f_frame, textvariable=self.audio_path, font=("Arial", 10), width=90).pack(side="left", padx=5)
+        tk.Button(f_frame, text="Parcourir", command=self.browse_file, bg="#607d8b", fg="white").pack(side="left", padx=5)
+
+        # Zone Configuration
+        c_frame = tk.LabelFrame(main_frame, text=" 2. Intelligence & Format ", font=("Arial", 10, "bold"), bg="#eceff1", padx=10, pady=10)
+        c_frame.pack(fill="x", pady=10)
+        
+        tk.Label(c_frame, text="Modèle Ollama:", bg="#eceff1").grid(row=0, column=0, sticky="w")
+        self.model_combo = ttk.Combobox(c_frame, textvariable=self.selected_model, width=40)
+        self.model_combo.grid(row=0, column=1, padx=10, pady=5, sticky="w")
+        self.model_combo.set("gpt-oss:120b-cloud")
+
+        tk.Label(c_frame, text="Type de document:", bg="#eceff1").grid(row=1, column=0, sticky="w")
+        self.template_combo = ttk.Combobox(c_frame, textvariable=self.selected_template, width=40, state="readonly")
+        self.template_combo['values'] = list(PROMPT_TEMPLATES.keys())
+        self.template_combo.grid(row=1, column=1, padx=10, pady=5, sticky="w")
+        self.template_combo.bind("<<ComboboxSelected>>", self.on_template_change)
+
+        # Prompt
+        tk.Label(main_frame, text="Instructions de synthèse:", font=("Arial", 10, "bold"), bg="#eceff1").pack(anchor="w", pady=(10, 0))
+        self.prompt_text = tk.Text(main_frame, height=6, font=("Arial", 10), padx=10, pady=10)
+        self.prompt_text.pack(fill="x", pady=5)
+        self.prompt_text.insert("1.0", PROMPT_TEMPLATES["Contrôle T2A / Codage CIM-10"])
+
+        # Progression
+        tk.Label(main_frame, text="Progression du traitement:", font=("Arial", 9), bg="#eceff1").pack(anchor="w", pady=(10, 0))
+        self.progress_bar = ttk.Progressbar(main_frame, variable=self.progress_val, maximum=100, mode='determinate')
+        self.progress_bar.pack(fill="x", pady=5)
+        self.status_label = tk.Label(main_frame, textvariable=self.status_var, font=("Arial", 10, "bold"), bg="#eceff1", fg="#1565c0")
+        self.status_label.pack()
+
+        # Boutons
+        btn_frame = tk.Frame(main_frame, bg="#eceff1")
+        btn_frame.pack(fill="x", pady=20)
+        
+        self.run_btn = tk.Button(btn_frame, text="LANCER LE PIPELINE", bg="#2e7d32", fg="white", font=("Arial", 12, "bold"), 
+                                width=25, pady=10, command=self.start_pipeline)
+        self.run_btn.pack(side="left", padx=5)
+        
+        self.stop_btn = tk.Button(btn_frame, text="STOP", bg="#c62828", fg="white", font=("Arial", 12, "bold"), 
+                                 width=10, pady=10, state="disabled", command=self.stop_pipeline)
+        self.stop_btn.pack(side="left", padx=5)
+
+        self.pdf_btn = tk.Button(btn_frame, text="EXPORTER PDF", bg="#f57c00", fg="white", font=("Arial", 12, "bold"), 
+                                width=15, pady=10, state="disabled", command=self.export_pdf)
+        self.pdf_btn.pack(side="right", padx=5)
+
+        # Logs
+        self.log_area = tk.Text(main_frame, height=12, bg="#212121", fg="#76ff03", font=("Consolas", 9), padx=10, pady=10)
+        self.log_area.pack(fill=tk.BOTH, expand=True)
+
+    def on_template_change(self, event):
+        self.prompt_text.delete("1.0", tk.END)
+        self.prompt_text.insert("1.0", PROMPT_TEMPLATES[self.selected_template.get()])
+
+    def browse_file(self):
+        fn = filedialog.askopenfilename(filetypes=[("Audio", "*.wav *.mp3 *.m4a *.flac")])
+        if fn: self.audio_path.set(fn)
+
+    def load_ollama_models(self):
+        try:
+            resp = ollama.list()
+            models = getattr(resp, 'models', []) if hasattr(resp, 'models') else resp.get('models', [])
+            names = [m.model if hasattr(m, 'model') else m.get('model', 'Unknown') for m in models]
+            if names: self.model_combo['values'] = names
+        except: pass
+
+    def log(self, msg):
+        self.log_area.insert(tk.END, str(msg) + "\n")
+        self.log_area.see(tk.END)
+        self.root.update_idletasks()
+
+    def start_pipeline(self):
+        if not self.audio_path.get(): return
+        self.run_btn.config(state="disabled")
+        self.stop_btn.config(state="normal")
+        self.pdf_btn.config(state="disabled")
+        self.log_area.delete("1.0", tk.END)
+        threading.Thread(target=self.run_worker, daemon=True).start()
+
+    def run_worker(self):
+        audio = self.audio_path.get()
+        model_name = self.selected_model.get()
+        prompt = self.prompt_text.get("1.0", tk.END).strip()
+        
+        try:
+            self.log("--- DÉMARRAGE DU MOTEUR EXPERT ---")
+            script_dir = os.path.dirname(os.path.abspath(__file__))
+            env = os.environ.copy()
+            env["HF_TOKEN"] = HF_TOKEN
+            
+            self.current_process = subprocess.Popen(
+                [sys.executable, os.path.join(script_dir, "medical_diarizer.py"), audio],
+                env=env, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True, bufsize=1
+            )
+            
+            for line in self.current_process.stdout:
+                line = line.strip()
+                if line.startswith("[STATUS] PROGRESS:"):
+                    try:
+                        val = int(line.split(":")[1])
+                        self.progress_val.set(val)
+                        self.status_var.set(f"Analyse en cours : {val}%")
+                    except: pass
+                else:
+                    self.log(line)
+            
+            self.current_process.wait()
+            transcript_file = audio.rsplit('.', 1)[0] + "_diarized.txt"
+            if not os.path.exists(transcript_file): raise Exception("Échec moteur.")
+
+            self.status_var.set("Génération de la synthèse IA...")
+            self.log("\n--- GÉNÉRATION DE LA SYNTHÈSE MÉDICALE ---")
+            import ollama
+            with open(transcript_file, "r") as f: content = f.read()
+            resp = ollama.chat(model=model_name, messages=[
+                {"role": "system", "content": prompt}, {"role": "user", "content": content}
+            ])
+            
+            self.last_summary_path = audio.rsplit('.', 1)[0] + "_final_summary.md"
+            with open(self.last_summary_path, "w") as f: f.write(resp['message']['content'])
+            
+            self.log("\n[OK] Synthèse générée avec succès.")
+            self.status_var.set("Terminé. Prêt pour export PDF.")
+            self.pdf_btn.config(state="normal")
+            messagebox.showinfo("Succès", "Traitement terminé !")
+            
+        except Exception as e:
+            self.log(f"\n[ERREUR] {e}")
+        finally:
+            self.run_btn.config(state="normal")
+            self.stop_btn.config(state="disabled")
+
+    def stop_pipeline(self):
+        if self.current_process:
+            self.current_process.terminate()
+            self.log("\n[STOP] Abandon.")
+            self.status_var.set("Prêt.")
+
+    def export_pdf(self):
+        if not self.last_summary_path or not os.path.exists(self.last_summary_path): return
+        try:
+            pdf = PDF()
+            pdf.add_page()
+            pdf.set_font("Arial", size=11)
+            with open(self.last_summary_path, 'r', encoding='utf-8') as f:
+                for line in f:
+                    clean_line = line.encode('latin-1', 'replace').decode('latin-1')
+                    pdf.multi_cell(0, 10, clean_line)
+            
+            pdf_path = self.last_summary_path.replace(".md", ".pdf")
+            pdf.output(pdf_path)
+            os.system(f"xdg-open '{pdf_path}'")
+            messagebox.showinfo("PDF", f"PDF généré et ouvert :\n{os.path.basename(pdf_path)}")
+        except Exception as e:
+            messagebox.showerror("Erreur PDF", str(e))
+
+if __name__ == "__main__":
+    root = tk.Tk()
+    MedicalScribeGUIv3(root)
+    root.mainloop()