gradio file

app.py

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+import os
+import faster_whisper
+import gradio as gr
+from dotenv import load_dotenv
+from huggingface_hub import InferenceClient
+
+# Load API key dari .env
+load_dotenv()
+HF_API_KEY = os.getenv("HF_API_KEY")
+
+if not HF_API_KEY:
+    raise ValueError("API Key Hugging Face tidak ditemukan. Pastikan file .env berisi HF_API_KEY.")
+
+# Inisialisasi klien API Hugging Face
+huggingface_client = InferenceClient(api_key=HF_API_KEY)
+
+# Load Faster Whisper model versi large
+model = faster_whisper.WhisperModel("turbo", device="cpu", compute_type="int8")
+
+def save_to_file(content, filename):
+    with open(filename, 'w', encoding='utf-8') as file:
+        file.write(content)
+    return filename
+
+def transcribe_audio(audio_path):
+    """Transkripsi audio menggunakan Faster Whisper tanpa koreksi model Hugging Face."""
+    segments, _ = model.transcribe(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."""
+    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.
+    Harap buat ringkasan dalam format berikut:
+
+    Subjective:
+    Objective:
+    Assessment:
+    Plan:
+
+    ### Percakapan:
+    {dialogue}
+
+    ### Catatan SOAP:
+    """
+    messages = [{"role": "user", "content": template.format(dialogue=transcription_text)}]
+    response = huggingface_client.chat.completions.create(
+        model="mistralai/Mixtral-8x7B-Instruct-v0.1",
+        messages=messages,
+        max_tokens=1000,
+        stream=False
+    )
+    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."""
+    template = """
+    Identifikasi dan berikan luaran dalam bahasa indonesia tags berikut dari percakapan:
+    Diagnosis:
+    Obat:
+    Hasil Lab:
+    Radiologi:
+
+    ### Percakapan:
+    {dialogue}
+    """
+    messages = [{"role": "user", "content": template.format(dialogue=transcription_text)}]
+    response = huggingface_client.chat.completions.create(
+        model="mistralai/Mixtral-8x7B-Instruct-v0.1",
+        messages=messages,
+        max_tokens=500,
+        stream=False
+    )
+    tags = response.choices[0].message.content.strip()
+    return tags, save_to_file(tags, 'medical_tags.txt')
+
+# Antarmuka Gradio
+with gr.Blocks(title="AI-based Medical SOAP Summarization and Tag Detection with Faster Whisper Large") as app:
+    gr.Markdown("## Medical SOAP Summarization and Tag Detection with Faster Whisper Large")
+
+    with gr.Row():
+        with gr.Column():
+            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)
+            update_transcription_button = gr.Button("💾 Simpan Hasil Edit")
+            soap_button = gr.Button("📝 Buat SOAP")
+            tags_button = gr.Button("🏷️ Deteksi Tags")
+
+        with gr.Column():
+            soap_output = gr.Textbox(label="📃 Hasil SOAP", lines=10, interactive=False)
+            tags_output = gr.Textbox(label="🏷️ Hasil Tags Diagnosis, Obat, Hasil Lab, Radiologi", lines=10, interactive=False)
+            download_audio = gr.File(label="⬇️ Download Rekaman")
+            download_transcription = gr.File(label="⬇️ Download Transkripsi")
+            download_soap = gr.File(label="⬇️ Download SOAP")
+            download_tags = gr.File(label="⬇️ Download Tags")
+
+    # Tombol Transkripsi
+    transcribe_button.click(
+        transcribe_audio,
+        inputs=[audio_input],
+        outputs=[transcription_edit_box, download_transcription, download_audio]
+    )
+
+    # Tombol Simpan Hasil Edit
+    update_transcription_button.click(
+        lambda text: (text, save_to_file(text, 'user_edited_transcription.txt')),
+        inputs=[transcription_edit_box],
+        outputs=[transcription_edit_box, download_transcription]
+    )
+
+    # Tombol SOAP
+    soap_button.click(
+        generate_soap_summary,
+        inputs=[transcription_edit_box],
+        outputs=[soap_output, download_soap]
+    )
+
+    # Tombol Tags
+    tags_button.click(
+        detect_medical_tags,
+        inputs=[transcription_edit_box],
+        outputs=[tags_output, download_tags]
+    )
+
+# Jalankan aplikasi
+app.launch()