Fixing build yet another time

backend.py

@@ -24,8 +24,7 @@ from bert import analyze_with_clinicalBert, classify_disease_and_severity, extra
 from disease_links import diseases as disease_links
 from disease_steps import disease_next_steps
 from disease_support import disease_doctor_specialty, disease_home_care
-import datetime
-from typing import Optional, List 
+from past_reports import router as reports_router, db_fetch_reports
 
 model = genai.GenerativeModel('gemini-1.5-flash')
 df = pd.read_csv("measurement.csv")
@@ -43,7 +42,21 @@ api = APIRouter(prefix="/api")
 app.include_router(api)
 
 
+'''app.add_middleware(
+    CORSMiddleware,
+    allow_origins=[
+        "http://localhost:8002"
+        "http://localhost:9000"
+        "http://localhost:5501"
+    ],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)'''
+
+
 app.mount("/app", StaticFiles(directory="web", html=True), name="web")
+app.include_router(reports_router)
 
 app.add_middleware(
     CORSMiddleware,
@@ -82,15 +95,13 @@ try:
 except Exception as e:
     raise RuntimeError(f"Failed to configure Firebase: {e}")
 
+class ChatRequest(BaseModel):
+    user_id: Optional[str] = "anonymous"
+    question: str
 
 class ChatResponse(BaseModel):
     answer: str
 
-
-class ChatRequest(BaseModel):
-    question: str
-    user_id: Optional[str] = "anonymous"
-
 class ReportData(BaseModel):
     user_id: str
     reportDate: Optional[str] = None
@@ -158,16 +169,7 @@ def ocr_text_from_image(image_bytes: bytes) -> str:
     print(response_text)
 
     return response_text
-
-@app.post("/chat/", response_model=ChatResponse)
-async def chat_endpoint(request: ChatRequest):
-    """
-    Chatbot endpoint that answers questions based on the last analyzed document and user history.
-    """
-    global EXTRACTED_TEXT_CACHE
-    if not EXTRACTED_TEXT_CACHE:
-        raise HTTPException(status_code=400, detail="Please provide a document context by analyzing text first.")
-    
+def get_past_reports_from_firestore(user_id: str):
     try:
         reports_ref = db.collection('users').document(request.user_id).collection('reports')
         docs = reports_ref.order_by('timestamp', direction=firestore.Query.DESCENDING).limit(10).stream()
@@ -178,8 +180,35 @@ async def chat_endpoint(request: ChatRequest):
             history_text += f"Report from {report_data.get('timestamp', 'N/A')}:\n{report_data.get('ocr_text', 'No OCR text found')}\n\n"
     except Exception as e:
         history_text = "No past reports found for this user."
-    
+    return history_text
+
+def get_past_reports_from_sqllite(user_id: str):
+    try:
+        reports = db_fetch_reports(user_id=user_id, limit=10, offset=0)
+        
+        history_text = ""
+        for report in reports:
+            history_text += f"Report from {report.get('report_date', 'N/A')}:\n{report.get('ocr_text', 'No OCR text found')}\n\n"
+    except Exception as e:
+        history_text = "No past reports found for this user."
+    return history_text
+
+@app.post("/chat/", response_model=ChatResponse)
+async def chat_endpoint(request: ChatRequest):
+    """
+    Chatbot endpoint that answers questions based on the last analyzed document and user history.
+    """
+    print("Received chat request for user:", request.user_id)
+    #history_text = get_past_reports_from_firestore(request.user_id)
+    history_text = get_past_reports_from_sqllite(request.user_id)
+
     full_document_text = EXTRACTED_TEXT_CACHE + "\n\n" + "PAST REPORTS:\n" + history_text
+
+    if not full_document_text:
+        raise HTTPException(status_code=400, detail="No past reports or current data exists for this user")
+    
+    
+   
     
     try:
         full_prompt = system_prompt_chat.format(
@@ -205,6 +234,7 @@ async def analyze(
     filename = file.filename.lower()
     detected_diseases = set()
     ocr_full = ""
+    print("Received request for file:", filename)
     if filename.endswith(".pdf"):
         pdf_bytes = await file.read()
         image_bytes_list = extract_images_from_pdf_bytes(pdf_bytes)
@@ -225,22 +255,19 @@ async def analyze(
         return {"message": "Gemini model not available; please use BERT model."}
 
     found_diseases = extract_non_negated_keywords(ocr_full)
-    print(f"CALLING FOUND DISEASES: {found_diseases}")
     past = detect_past_diseases(ocr_full)
-    print(f"CALLING PAST DISEASES: {past}")
 
     for disease in found_diseases:
         if disease in past:    
             severity = classify_disease_and_severity(disease)
             detected_diseases.add(((f"{disease}(detected as historical condition, but still under risk.)"), severity))
-            print(f"DETECTED DISEASES(PAST): {detected_diseases}")
         else:
             severity = classify_disease_and_severity(disease)
             detected_diseases.add((disease, severity))
-            print(f"DETECTED DISEASES: {detected_diseases}")
+           
         
-    print("OCR TEXT:", ocr_text)
-    print("Detected diseases:", found_diseases)
+   
+    print("Detected diseases:", detected_diseases)
     ranges = analyze_measurements(ocr_full, df)
 
 
@@ -274,7 +301,6 @@ async def analyze(
         next_steps_range = disease_next_steps.get(condition.lower(), ['Consult a doctor'])
         specialist_range = disease_doctor_specialty.get(condition.lower(), "General Practitioner")
         home_care_range = disease_home_care.get(condition.lower(), [])
-        print(f"HELLO!: {measurement}")
                     
         condition_version = condition.upper()    
         severity_version = severity.upper()
@@ -288,12 +314,11 @@ async def analyze(
             "info_link": link_range
         })
                             
-    print(ocr_full)
+    
     ranges = analyze_measurements(ocr_full, df)
     print(analyze_measurements(ocr_full, df))
     # print ("Ranges is being printed", ranges)
     historical_med_data = detect_past_diseases(ocr_full)
-    print("***End of Code***")
     
     return {
         "ocr_text": ocr_full.strip(),

web/analyzer.html

@@ -190,6 +190,8 @@
       </ul>
     </nav>
 
+    <!--Shared helpers (API base + query params) -->
+    <script src="script.js"></script>
     <script>
       const hamburger = document.getElementById("hamburger");
       const mobileMenu = document.getElementById("mobile-menu");
@@ -470,7 +472,7 @@
 
           let data;
           try {
-            const res = await fetch("http://localhost:9000/analyze/", {
+            const res = await fetch(api("analyze/"), {
               method: "POST",
               body: formData,
             });
@@ -512,11 +514,18 @@
           }
 
           if (currentUser) {
-            await saveAnalysis(currentUser.uid, {
+            /*await saveAnalysis(currentUser.uid, {
               reportDate: date,
               ocr_text: extractedText,
               resolutions: recs,
               measurements: findings,
+            });*/
+            await postReportToBackend({
+              user_id: currentUser.email,
+              report_date: new Date(),
+              ocr_text: extractedText,
+              anomalies: JSON.stringify(recs),
+              measurements: JSON.stringify(findings),
             });
           }
 
@@ -525,7 +534,7 @@
 
         async function postReportToBackend(report) {
           try {
-            const response = await fetch('http://localhost:9000/save_report/', {
+            const response = await fetch(api('save_report/'), {
               method: 'POST',
               headers: {
                 'Content-Type': 'application/json',
@@ -559,7 +568,7 @@
           chat.scrollTop = chat.scrollHeight;
           
           try {
-            const response = await fetch("http://localhost:9000/chat/", {
+            const response = await fetch(api('chat/'), {
               method: "POST",
               headers: {
                 "Content-Type": "application/json",

web/past_data.html

@@ -114,8 +114,31 @@
     onAuthStateChanged(auth, async (user) => {
       if (user) {
         statusEl.textContent = `Signed in as ${user.email || user.uid}`;
+
+        async function getPastReports() {
+          try {
+            const url = api('reports/', { user_id: user.email });
+            const response = await fetch(url, {
+              method: 'GET',
+              headers: {
+                'Content-Type': 'application/json',
+              },
+            });
+            if (!response.ok) {
+              throw new Error(`HTTP error! status: ${response.status}`);
+            }
+            const data = await response.json();
+            console.log('Report successfully sent to backend:', data);
+            recsEl.innerHTML = data.map(doc => renderAnalysis(doc)).join("");
+          } catch (error) {
+            console.error('Error sending report to backend:', error);
+            recsEl.innerHTML = '<p class="text-sm text-gray-500">No saved analyses yet.</p>';
+          }
+        }
+       getPastReports();
+        
         
-        try {
+       /* try {
           const q = query(
             collection(db, "users", user.uid, "analyses"),
             orderBy("createdAt", "desc")
@@ -150,7 +173,7 @@
         } catch (error) {
           console.error('Error fetching analyses:', error);
           recsEl.innerHTML = '<p class="text-sm text-red-500">Error loading analyses.</p>';
-        }
+        }*/
         
       } else {
         statusEl.textContent = "Not signed in.";

web/script.js

@@ -27,6 +27,7 @@
           : API_BASE + (path.startsWith("/") ? path : "/" + path);
   
       const url = new URL(full);
+      console.log("Calling api :",url);
       if (params && typeof params === "object") {
         for (const [k, v] of Object.entries(params)) {
           if (v === undefined || v === null) continue;