last commit gradio

app.py

@@ -1,135 +1,75 @@
-import os
 import gradio as gr
-import nltk
-from groq import Groq
-from sumy.parsers.plaintext import PlaintextParser
-from sumy.nlp.tokenizers import Tokenizer
-from sumy.summarizers.lsa import LsaSummarizer
-
-# Download tokenizer NLTK
-nltk.download('punkt')
-nltk.download('punkt_tab')
-
-# API Key Groq
-GROQ_API_KEY = "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"
-groq_client = Groq(api_key=GROQ_API_KEY)
-
-def save_to_file(content, filename):
-    with open(filename, 'w', encoding='utf-8') as file:
-        file.write(content)
-    return filename
-
-def transcribe_and_summarize_generate(audio_path):
-    # Transkripsi
-    with open(audio_path, "rb") as audio_file:
-        response = groq_client.audio.transcriptions.create(
-            model="whisper-large-v3",
-            file=audio_file,
-            response_format="text"
-        )
-    transcription = response
-
-    # Summarization LSA
-    parser = PlaintextParser.from_string(transcription, Tokenizer("english"))
-    summarizer = LsaSummarizer()
-    summary_sentences = summarizer(parser.document, 5)
-    summarized_text = " ".join([str(sentence) for sentence in summary_sentences])
-
-    # Token info
-    original_tokens = len(nltk.word_tokenize(transcription))
-    summarized_tokens = len(nltk.word_tokenize(summarized_text))
-    token_info = f"Asli: {original_tokens} token | Ringkasan: {summarized_tokens} token"
-
-    # SOAP
-    prompt_soap = f"""
-    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:
-    {transcription}
-
-    Tolong jangan tambahkan informasi tambahan selain yang berkaitan dengan diagnosis, obat, hasil lab, dan radiologi.
-    """
-    response_soap = groq_client.chat.completions.create(
-        model="llama3-8b-8192",
-        messages=[{"role": "user", "content": prompt_soap}]
+import os
+import requests
+from dotenv import load_dotenv
+
+load_dotenv()
+API_TRANSCRIBE = os.getenv("API_TRANSCRIBE")
+API_TEXT = os.getenv("API_TEXT")
+
+# ==== Function for backend calls ====
+def handle_audio(audio_file):
+    if audio_file is None:
+        return "-", "-", "-"
+    with open(audio_file, "rb") as f:
+        files = {"audio": f}
+        response = requests.post(API_TRANSCRIBE, files=files)
+        result = response.json()
+    return result.get("transcription", "-"), result.get("soap_content", "-"), result.get("tags_content", "-")
+
+def handle_text(dialogue):
+    if not dialogue.strip():
+        return "-", "-", "-"
+    response = requests.post(API_TEXT, json={"dialogue": dialogue})
+    result = response.json()
+    return dialogue, result.get("soap_content", "-"), result.get("tags_content", "-")
+
+# ==== Function to toggle inputs ====
+def toggle_inputs(choice):
+    return (
+        gr.update(visible=(choice == "Upload Audio")),
+        gr.update(visible=(choice == "Rekam Audio")),
+        gr.update(visible=(choice == "Input Teks")),
     )
-    soap_content = response_soap.choices[0].message.content
-
-    # Tags
-    prompt_tags = f"""
-    Identifikasi dan berikan luaran dalam bahasa Indonesia tags berikut dari percakapan dengan format:
-    Diagnosis:
-    Obat:
-    Hasil Lab:
-    Radiologi:
 
-    ### Percakapan:
-    {transcription}
+# ==== UI ====
+with gr.Blocks(title="SOAP AI Dropdown Input") as app:
+    gr.Markdown("## 🩺 SOAP AI — Pilih Jenis Input")
 
-    Tolong jangan tambahkan informasi tambahan selain yang berkaitan dengan diagnosis, obat, hasil lab, dan radiologi.
-    """
-    response_tags = groq_client.chat.completions.create(
-        model="llama3-8b-8192",
-        messages=[{"role": "user", "content": prompt_tags}]
+    input_choice = gr.Dropdown(
+        choices=["Upload Audio", "Input Teks"],
+        value="Upload Audio",
+        label="Pilih Metode Input"
     )
-    tags_content = response_tags.choices[0].message.content
 
-    # Save files
-    summarized_file = save_to_file(summarized_text, 'summarized_transcription.txt')
-    soap_file = save_to_file(soap_content, 'soap_summary.txt')
-    tags_file = save_to_file(tags_content, 'medical_tags.txt')
+    # Input fields (hidden by default except selected)
+    audio_upload = gr.Audio("microphone",label="🔊 Upload File Audio", type="filepath", visible=True)
+    text_input = gr.Textbox(label="📝 Masukkan Percakapan Dokter-Pasien", lines=6, visible=False)
 
-    return (
-        summarized_text,
-        soap_content,
-        tags_content,
-        token_info,
-        summarized_file,
-        soap_file,
-        tags_file,
-        audio_path
-    )
+    # Tombol proses
+    process_button = gr.Button("🚀 Proses ke SOAP")
 
-# Gradio UI
-with gr.Blocks(title="SOAP AI: Transkripsi dan Ringkasan Medis Otomatis") as app:
-    gr.Markdown("## 🧠 SOAP AI - Transkripsi, Ringkasan, dan Deteksi Medis Otomatis")
+    # Output
+    transcript_output = gr.Textbox(label="📝 Hasil Transkripsi", lines=3)
+    soap_output = gr.Textbox(label="📋 Ringkasan SOAP", lines=6)
+    tags_output = gr.Textbox(label="🏷️ Medical Tags", lines=6)
 
-    with gr.Row():
-        with gr.Column():
-            audio_input = gr.Audio("microphone", type="filepath", label="🎙️ Rekam Percakapan")
-            transcribe_button = gr.Button("🩺 Jalankan Proses Lengkap (Transkripsi + Ringkasan + SOAP + Tags)")
+    # === Events ===
+    input_choice.change(fn=toggle_inputs, inputs=input_choice,
+                        outputs=[audio_upload, text_input])
 
-        with gr.Column():
-            summarize_box = gr.Textbox(label="📄 Ringkasan LSA (5 Kalimat)", lines=5, interactive=False)
-            soap_box = gr.Textbox(label="📋 Ringkasan SOAP", lines=8, interactive=False)
-            tags_box = gr.Textbox(label="🏷️ Medical Tags", lines=6, interactive=False)
-            token_box = gr.Textbox(label="🔢 Token Info", interactive=False)
-
-    with gr.Row():
-        download_summary = gr.File(label="⬇️ Download Ringkasan LSA")
-        download_soap = gr.File(label="⬇️ Download SOAP")
-        download_tags = gr.File(label="⬇️ Download Tags")
-        download_audio = gr.File(label="⬇️ Download Audio")
+    process_button.click(
+        fn=handle_audio,
+        inputs=audio_upload,
+        outputs=[transcript_output, soap_output, tags_output],
+        show_progress="minimal"
+    )
 
-    transcribe_button.click(
-        transcribe_and_summarize_generate,
-        inputs=[audio_input],
-        outputs=[
-            summarize_box,
-            soap_box,
-            tags_box,
-            token_box,
-            download_summary,
-            download_soap,
-            download_tags,
-            download_audio
-        ]
+    process_button.click(
+        fn=handle_text,
+        inputs=text_input,
+        outputs=[transcript_output, soap_output, tags_output],
+        show_progress="minimal"
     )
 
-app.launch(share=True)
+app.launch()