Update endpoints.py

endpoints.py

@@ -1,5 +1,5 @@
 from fastapi import APIRouter, Depends, HTTPException, UploadFile, File, Query, Form, Path
-from fastapi.responses import StreamingResponse, JSONResponse
+from fastapi.responses import StreamingResponse, JSONResponse, FileResponse
 from fastapi.encoders import jsonable_encoder
 from typing import Optional, List
 from pydantic import BaseModel
@@ -14,6 +14,11 @@ from datetime import datetime
 from bson import ObjectId
 import asyncio
 from bson.errors import InvalidId
+import base64
+import os
+from pathlib import Path as PathLib
+import tempfile
+import subprocess
 
 # Define the ChatRequest model with an optional patient_id
 class ChatRequest(BaseModel):
@@ -45,7 +50,7 @@ def create_router(agent, logger, patients_collection, analysis_collection, users
             "status": "running",
             "timestamp": datetime.utcnow().isoformat(),
             "version": "2.6.0",
-            "features": ["chat", "voice-input", "voice-output", "patient-analysis", "report-upload"]
+            "features": ["chat", "voice-input", "voice-output", "patient-analysis", "report-upload", "patient-reports-pdf", "all-patients-reports-pdf"]
         }
 
     @router.get("/patients/analysis-results")
@@ -80,6 +85,248 @@ def create_router(agent, logger, patients_collection, analysis_collection, users
             logger.error(f"Error fetching analysis results: {e}")
             raise HTTPException(status_code=500, detail="Failed to retrieve analysis results")
 
+    @router.get("/patients/{patient_id}/analysis-reports/pdf")
+    async def get_patient_analysis_reports_pdf(
+        patient_id: str = Path(..., description="The ID of the patient"),
+        current_user: dict = Depends(get_current_user)
+    ):
+        logger.info(f"Generating PDF analysis reports for patient {patient_id} by {current_user['email']}")
+        try:
+            # Fetch patient details
+            patient = await patients_collection.find_one({"fhir_id": patient_id})
+            if not patient:
+                raise HTTPException(status_code=404, detail="Patient not found")
+
+            # Fetch all analyses for the patient
+            analyses = await analysis_collection.find({"patient_id": patient_id}).sort("timestamp", -1).to_list(length=None)
+            if not analyses:
+                raise HTTPException(status_code=404, detail="No analysis reports found for this patient")
+
+            # Creating LaTeX document
+            latex_content = r"""
+\documentclass[a4paper,12pt]{article}
+\usepackage[utf8]{inputenc}
+\usepackage[T1]{fontenc}
+\usepackage{lmodern}
+\usepackage{geometry}
+\geometry{margin=1in}
+\usepackage{enumitem}
+\usepackage{fancyhdr}
+\usepackage{lastpage}
+\usepackage{datetime}
+\pagestyle{fancy}
+\fancyhf{}
+\rhead{Patient Analysis Report}
+\lhead{\today}
+\cfoot{Page \thepage\ of \pageref{LastPage}}
+\begin{document}
+"""
+
+            # Adding patient information
+            patient_name = patient.get("full_name", "Unknown")
+            latex_content += f"""
+\\section*{{Analysis Reports for {patient_name} (ID: {patient_id})}}
+\\textbf{{Patient Name:}} {patient_name}\\\\
+\\textbf{{Patient ID:}} {patient_id}\\\\
+\\textbf{{Generated on:}} \\today\\\\
+"""
+
+            # Adding analysis reports
+            for idx, analysis in enumerate(analyses, 1):
+                timestamp = analysis.get("timestamp", datetime.utcnow()).strftime("%Y-%m-%d %H:%M:%S")
+                suicide_risk = analysis.get("suicide_risk", {})
+                risk_level = suicide_risk.get("level", "none").capitalize()
+                risk_score = suicide_risk.get("score", 0.0)
+                risk_factors = ", ".join(suicide_risk.get("factors", [])) or "None"
+                
+                latex_content += f"""
+\\subsection*{{Report {idx} - {timestamp}}}
+\\begin{{description}}
+    \\item[Risk Level:] {risk_level}
+    \\item[Risk Score:] {risk_score:.2f}
+    \\item[Risk Factors:] {risk_factors}
+"""
+
+                # Adding additional analysis details if available
+                if analysis.get("summary"):
+                    latex_content += f"    \\item[Summary:] {analysis['summary']}\n"
+                if analysis.get("recommendations"):
+                    recommendations = ", ".join(analysis["recommendations"]) if isinstance(analysis["recommendations"], list) else analysis["recommendations"]
+                    latex_content += f"    \\item[Recommendations:] {recommendations}\n"
+
+                latex_content += r"\end{description}\vspace{0.5cm}"
+
+            latex_content += r"\end{document}"
+
+            # Creating temporary directory for LaTeX compilation
+            with tempfile.TemporaryDirectory() as tmpdirname:
+                latex_file = PathLib(tmpdirname) / "report.tex"
+                pdf_file = PathLib(tmpdirname) / "report.pdf"
+
+                # Writing LaTeX content to file
+                with open(latex_file, "w", encoding="utf-8") as f:
+                    f.write(latex_content)
+
+                # Compiling LaTeX to PDF using pdflatex
+                try:
+                    subprocess.run(
+                        ["pdflatex", "-output-directory", tmpdirname, str(latex_file)],
+                        check=True,
+                        stdout=subprocess.PIPE,
+                        stderr=subprocess.PIPE,
+                        text=True
+                    )
+                except subprocess.CalledProcessError as e:
+                    logger.error(f"LaTeX compilation failed: {e.stderr}")
+                    raise HTTPException(status_code=500, detail="Failed to generate PDF report")
+
+                if not pdf_file.exists():
+                    raise HTTPException(status_code=500, detail="PDF generation failed")
+
+                # Reading the generated PDF
+                with open(pdf_file, "rb") as f:
+                    pdf_content = f.read()
+
+                # Returning the PDF as a response
+                return FileResponse(
+                    pdf_file,
+                    media_type="application/pdf",
+                    headers={"Content-Disposition": f"attachment; filename={patient_name.replace(' ', '_')}_{patient_id}_analysis_reports.pdf"}
+                )
+
+        except HTTPException:
+            raise
+        except Exception as e:
+            logger.error(f"Error generating PDF report for patient {patient_id}: {str(e)}")
+            raise HTTPException(status_code=500, detail=f"Failed to generate PDF report: {str(e)}")
+
+    @router.get("/patients/analysis-reports/all/pdf")
+    async def get_all_patients_analysis_reports_pdf(
+        current_user: dict = Depends(get_current_user)
+    ):
+        logger.info(f"Generating PDF analysis reports for all patients by {current_user['email']}")
+        try:
+            # Fetch all patients
+            patients = await patients_collection.find().to_list(length=None)
+            if not patients:
+                raise HTTPException(status_code=404, detail="No patients found")
+
+            # Creating LaTeX document
+            latex_content = r"""
+\documentclass[a4paper,12pt]{article}
+\usepackage[utf8]{inputenc}
+\usepackage[T1]{fontenc}
+\usepackage{lmodern}
+\usepackage{geometry}
+\geometry{margin=1in}
+\usepackage{enumitem}
+\usepackage{fancyhdr}
+\usepackage{lastpage}
+\usepackage{datetime}
+\pagestyle{fancy}
+\fancyhf{}
+\rhead{All Patients Analysis Reports}
+\lhead{\today}
+\cfoot{Page \thepage\ of \pageref{LastPage}}
+\begin{document}
+\section*{Analysis Reports for All Patients}
+\textbf{Generated on:} \today\\\\
+"""
+
+            # Flag to track if any analyses exist
+            has_analyses = False
+
+            # Iterate through each patient
+            for patient in patients:
+                patient_id = patient.get("fhir_id")
+                patient_name = patient.get("full_name", "Unknown")
+
+                # Fetch all analyses for the current patient
+                analyses = await analysis_collection.find({"patient_id": patient_id}).sort("timestamp", -1).to_list(length=None)
+                if not analyses:
+                    continue  # Skip patients with no analyses
+
+                has_analyses = True
+
+                # Adding patient section
+                latex_content += f"""
+\\section*{{Patient: {patient_name} (ID: {patient_id})}}
+\\textbf{{Patient Name:}} {patient_name}\\\\
+\\textbf{{Patient ID:}} {patient_id}\\\\
+"""
+
+                # Adding analysis reports for the patient
+                for idx, analysis in enumerate(analyses, 1):
+                    timestamp = analysis.get("timestamp", datetime.utcnow()).strftime("%Y-%m-%d %H:%M:%S")
+                    suicide_risk = analysis.get("suicide_risk", {})
+                    risk_level = suicide_risk.get("level", "none").capitalize()
+                    risk_score = suicide_risk.get("score", 0.0)
+                    risk_factors = ", ".join(suicide_risk.get("factors", [])) or "None"
+
+                    latex_content += f"""
+\\subsection*{{Report {idx} - {timestamp}}}
+\\begin{{description}}
+    \\item[Risk Level:] {risk_level}
+    \\item[Risk Score:] {risk_score:.2f}
+    \\item[Risk Factors:] {risk_factors}
+"""
+
+                    # Adding additional analysis details if available
+                    if analysis.get("summary"):
+                        latex_content += f"    \\item[Summary:] {analysis['summary']}\n"
+                    if analysis.get("recommendations"):
+                        recommendations = ", ".join(analysis["recommendations"]) if isinstance(analysis["recommendations"], list) else analysis["recommendations"]
+                        latex_content += f"    \\item[Recommendations:] {recommendations}\n"
+
+                    latex_content += r"\end{description}\vspace{0.5cm}"
+
+            latex_content += r"\end{document}"
+
+            if not has_analyses:
+                raise HTTPException(status_code=404, detail="No analysis reports found for any patients")
+
+            # Creating temporary directory for LaTeX compilation
+            with tempfile.TemporaryDirectory() as tmpdirname:
+                latex_file = PathLib(tmpdirname) / "all_reports.tex"
+                pdf_file = PathLib(tmpdirname) / "all_reports.pdf"
+
+                # Writing LaTeX content to file
+                with open(latex_file, "w", encoding="utf-8") as f:
+                    f.write(latex_content)
+
+                # Compiling LaTeX to PDF using pdflatex
+                try:
+                    subprocess.run(
+                        ["pdflatex", "-output-directory", tmpdirname, str(latex_file)],
+                        check=True,
+                        stdout=subprocess.PIPE,
+                        stderr=subprocess.PIPE,
+                        text=True
+                    )
+                except subprocess.CalledProcessError as e:
+                    logger.error(f"LaTeX compilation failed: {e.stderr}")
+                    raise HTTPException(status_code=500, detail="Failed to generate PDF report")
+
+                if not pdf_file.exists():
+                    raise HTTPException(status_code=500, detail="PDF generation failed")
+
+                # Reading the generated PDF
+                with open(pdf_file, "rb") as f:
+                    pdf_content = f.read()
+
+                # Returning the PDF as a response
+                return FileResponse(
+                    pdf_file,
+                    media_type="application/pdf",
+                    headers={"Content-Disposition": f"attachment; filename=all_patients_analysis_reports_{datetime.utcnow().strftime('%Y%m%d')}.pdf"}
+                )
+
+        except HTTPException:
+            raise
+        except Exception as e:
+            logger.error(f"Error generating PDF report for all patients: {str(e)}")
+            raise HTTPException(status_code=500, detail=f"Failed to generate PDF report: {str(e)}")
+
     @router.post("/chat-stream")
     async def chat_stream_endpoint(
         request: ChatRequest,