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Dockerfile

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+FROM python:3.10-slim
+
+WORKDIR /code
+
+COPY app /code/app
+
+RUN pip install --upgrade pip
+RUN pip install -r /code/app/requirements.txt
+
+EXPOSE 8000
+
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]

app/main.py

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+import os
+import nltk
+import uvicorn
+from fastapi import FastAPI, File, UploadFile
+from pydantic import BaseModel
+from groq import Groq
+from dotenv import load_dotenv
+
+load_dotenv()
+
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+groq_client = Groq(api_key=GROQ_API_KEY)
+
+def transcribe_audio(audio_path: str):
+    with open(audio_path, "rb") as audio_file:
+        response = groq_client.audio.transcriptions.create(
+            model="whisper-large-v3",
+            file=audio_file,
+            response_format="text"
+        )
+    return response
+
+def summarize_soap(dialogue: str):
+    prompt_soap = f"""
+    Anda adalah asisten medis yang membantu dokter dalam menyusun catatan SOAP berdasarkan percakapan dokter dan pasien.
+    Ringkaskan dalam bentuk paragraf tanpa bullet point dan gunakan bahasa Indonesia.
+    Harap buat ringkasan dalam format berikut:
+    Subjective:
+    Objective:
+    Assessment:
+    Plan:
+    ### Percakapan:
+    {dialogue}
+    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}]
+    )
+    return response_soap.choices[0].message.content
+
+def detect_medical_tags(dialogue: str):
+    prompt_tags = f"""
+    Identifikasi dan berikan luaran dalam bahasa Indonesia tags berikut dari percakapan dengan format:
+    Diagnosis:
+    Obat:
+    Hasil Lab:
+    Radiologi:
+    ### Percakapan:
+    {dialogue}
+    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}]
+    )
+    return response_tags.choices[0].message.content
+
+app = FastAPI(title="Medical Transcription Pipeline (Groq API)")
+
+@app.get("/")
+async def root():
+    return {
+        "message": "🚀 SOAP AI FastAPI is running. Use /full_process or /soap_tags to interact"
+    }
+
+@app.post("/full_process")
+async def full_process(audio: UploadFile = File(...)):
+    try:
+        filename = audio.filename
+        temp_audio_path = f"/tmp/temp_{filename}"
+        with open(temp_audio_path, "wb") as f:
+            f.write(await audio.read())
+
+        transcription = transcribe_audio(temp_audio_path)
+
+        soap_content = summarize_soap(transcription)
+        tags_content = detect_medical_tags(transcription)
+
+        os.remove(temp_audio_path)
+
+        return {
+            "transcription": transcription,
+            "soap_content": soap_content,
+            "tags_content": tags_content
+        }
+    except Exception as e:
+        return {"error": str(e)}
+
+class TranscriptionInput(BaseModel):
+    dialogue: str
+
+@app.post("/soap_tags")
+async def soap_tags(data: TranscriptionInput):
+    transcript_text = data.dialogue
+
+    soap_content = summarize_soap(transcript_text)
+    tags_content = detect_medical_tags(transcript_text)
+
+    return {
+        "soap_content": soap_content,
+        "tags_content": tags_content
+    }
+
+if __name__ == "__main__":
+    uvicorn.run("main:app", host="0.0.0.0", port=8000, reload=True)

app/requirements.txt

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+fastapi==0.115.8
+faster_whisper==1.1.1
+huggingface_hub==0.28.1
+soundfile==0.13.1
+sumy==0.11.0
+nltk==3.9.1
+uvicorn==0.34.0
+groq==0.18.0
+python-multipart
+python-dotenv