Update routers/transcription.py

routers/transcription.py

@@ -2,9 +2,71 @@ from fastapi import FastAPI, File, UploadFile , APIRouter , Request
 from fastapi.responses import JSONResponse
 from typing import List
 from controllers.transcription_controller import process_uploaded_files
+import openai
+import os
+
 
 router = APIRouter()
 
+client = OpenAI(
+  api_key=os.getenv('OPENAI_API_KEY')
+)
+
+CLINICAL_SUMMARY_PROMPT = """
+You are a clinical summarization engine for psychiatric case notes. Given a transcription of a doctor–patient conversation, extract all clinically relevant details valuable for both doctor and patient. Specifically, extract the following:
+
+- Patient Info: e.g., identifier, demographics.
+- Session Details: date, time, chief complaint, presenting symptoms.
+- History: psychiatric history and any other relevant medical history.
+- Mental Status Exam: appearance, behavior, speech, mood, affect, thought process, thought content, perception, cognition, insight, and judgment.
+- Assessment: clinician’s assessment/diagnosis.
+- Risk Assessment: any risks (e.g., suicidal ideation).
+- Treatment Plan: recommendations, follow-up plans.
+- Key Points: a list of critical details.
+
+For any missing data, use "N/A". Output only the JSON in the exact structure below without additional commentary.
+
+JSON Structure Example:
+{
+  "patient_info": {
+    "id": "N/A",
+    "demographics": "N/A"
+  },
+  "session_details": {
+    "date": "YYYY-MM-DD",
+    "time": "HH:MM",
+    "chief_complaint": "Summary of chief complaint",
+    "presenting_symptoms": "Summary of symptoms"
+  },
+  "history": {
+    "psychiatric": "Summary of psychiatric history",
+    "medical": "Summary of other medical history"
+  },
+  "mental_status_exam": {
+    "appearance": "Details of appearance",
+    "behavior": "Details of behavior",
+    "speech": "Details of speech",
+    "mood": "Details of mood",
+    "affect": "Details of affect",
+    "thought_process": "Details of thought process",
+    "thought_content": "Details of thought content",
+    "perception": "Details of perception",
+    "cognition": "Details of cognition",
+    "insight": "Details of insight",
+    "judgment": "Details of judgment"
+  },
+  "assessment": "Clinician's assessment and diagnosis",
+  "risk_assessment": "Risk factors (e.g., suicidal ideation)",
+  "treatment_plan": "Summary of treatment recommendations and follow-up plans",
+  "follow_up": "Next steps or appointment details",
+  "key_points": [
+    "Key point 1",
+    "Key point 2"
+  ]
+}
+"""
+
+
 @router.post("/transcribe")
 async def transcribe(files: List[UploadFile] = File(...)):
     results = await process_uploaded_files(files)
@@ -16,8 +78,22 @@ async def transcribe(files: List[UploadFile] = File(...)):
 async def transcribe(request:Request):
     body = await request.json()
     text = body.get('text')
-    result = 'This is a sample summary of the provided transcript.'+text
-    print("summarize")
-    print(result)
-    return JSONResponse(content={'summarized_results': result})
+    result = text
+
+    response = client.chat.completions.create(
+    messages=[
+        {"role": "system", "content": CLINICAL_SUMMARY_PROMPT},
+        {
+            "role": "user",
+            "content": f"I am providing you with the transcription of the recording of doctor and patient , follow the exact instructions given in the system prompt and generate the recording accordingly : \n {result}",
+        },
+        
+    ],
+        model="gpt-4o-mini",
+        response_format = { "type": "json_object" }
+    )
+    
+    print("summarized response")
+    print(response.choices[0].message.content)
+    return JSONResponse(content={'summarized_results': response.choices[0].message.content})