gradio file

app.py

@@ -17,6 +17,14 @@ huggingface_client = InferenceClient(api_key=HF_API_KEY)
 # Load Faster Whisper model versi large
 model = faster_whisper.WhisperModel("turbo", device="cpu", compute_type="int8")
 
+# Daftar model yang dapat dipilih
+MODEL_OPTIONS = [
+    "mistralai/Mistral-7B-Instruct-v0.3",
+    "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
+    "mistralai/Mixtral-8x7B-Instruct-v0.1",
+    "Qwen/Qwen2.5-Coder-32B-Instruct"
+]
+
 def save_to_file(content, filename):
     with open(filename, 'w', encoding='utf-8') as file:
         file.write(content)
@@ -28,8 +36,8 @@ def transcribe_audio(audio_path):
     raw_transcription = " ".join(segment.text for segment in segments)
     return raw_transcription, save_to_file(raw_transcription, 'transcription_large.txt'), audio_path
 
-def generate_soap_summary(transcription_text):
-    """Membuat ringkasan SOAP dari teks transkripsi."""
+def generate_soap_summary(transcription_text, selected_model):
+    """Membuat ringkasan SOAP dari teks transkripsi menggunakan model yang dipilih."""
     template = """
     Anda adalah asisten medis yang membantu dokter dalam menyusun catatan SOAP berdasarkan percakapan dokter dan pasien.
     Ringkaskan dalam bentuk paragraf tanpa adanya bullet point dan gunakan bahasa Indonesia.
@@ -47,7 +55,7 @@ def generate_soap_summary(transcription_text):
     """
     messages = [{"role": "user", "content": template.format(dialogue=transcription_text)}]
     response = huggingface_client.chat.completions.create(
-        model="mistralai/Mixtral-8x7B-Instruct-v0.1",
+        model=selected_model,
         messages=messages,
         max_tokens=1000,
         stream=False
@@ -55,8 +63,8 @@ def generate_soap_summary(transcription_text):
     soap = response.choices[0].message.content.strip()
     return soap, save_to_file(soap, 'soap_summary.txt')
 
-def detect_medical_tags(transcription_text):
-    """Mendeteksi tags Diagnosis, Obat, Hasil Lab, dan Radiologi."""
+def detect_medical_tags(transcription_text, selected_model):
+    """Mendeteksi tags Diagnosis, Obat, Hasil Lab, dan Radiologi menggunakan model yang dipilih."""
     template = """
     Identifikasi dan berikan luaran dalam bahasa indonesia tags berikut dari percakapan:
     Diagnosis:
@@ -69,7 +77,7 @@ def detect_medical_tags(transcription_text):
     """
     messages = [{"role": "user", "content": template.format(dialogue=transcription_text)}]
     response = huggingface_client.chat.completions.create(
-        model="mistralai/Mixtral-8x7B-Instruct-v0.1",
+        model=selected_model,
         messages=messages,
         max_tokens=500,
         stream=False
@@ -83,6 +91,11 @@ with gr.Blocks(title="AI-based Medical SOAP Summarization and Tag Detection with
 
     with gr.Row():
         with gr.Column():
+            model_selector = gr.Dropdown(
+                choices=MODEL_OPTIONS,
+                value="mistralai/Mixtral-8x7B-Instruct-v0.1",
+                label="🔍 Pilih Model AI"
+            )
             audio_input = gr.Audio("microphone", type="filepath", label="🎙️ Rekam Suara")
             transcribe_button = gr.Button("🎧 Transkripsi dengan Whisper Large")
             transcription_edit_box = gr.Textbox(label="📄 Hasil Transkripsi (Faster Whisper Large) - Bisa Diedit", lines=12, interactive=True)
@@ -115,14 +128,14 @@ with gr.Blocks(title="AI-based Medical SOAP Summarization and Tag Detection with
     # Tombol SOAP
     soap_button.click(
         generate_soap_summary,
-        inputs=[transcription_edit_box],
+        inputs=[transcription_edit_box, model_selector],
         outputs=[soap_output, download_soap]
     )
 
     # Tombol Tags
     tags_button.click(
         detect_medical_tags,
-        inputs=[transcription_edit_box],
+        inputs=[transcription_edit_box, model_selector],
         outputs=[tags_output, download_tags]
     )