Update src/main.py

src/main.py

@@ -1,45 +1,45 @@
-import base64
-import os
-from fastapi import FastAPI, Header, HTTPException, Body
-from src.processor import get_text_from_file
-from src.analyzer import run_analysis
-
-app = FastAPI()
-API_KEY = os.getenv("API_KEY", "sk_track2_987654321")
-
-@app.post("/api/document-analyze")
-async def analyze_document(x_api_key: str = Header(None), data: dict = Body(...)):
-    # 1. Auth Check (401 Unauthorized)
-    if x_api_key != API_KEY:
-        raise HTTPException(status_code=401, detail="Unauthorized")
-
-    # 2. Extract Base64
-    try:
-        file_b64 = data.get("fileBase64")
-        file_name = data.get("fileName")
-        file_type = data.get("fileType") # pdf/docx/image
-        
-        # Decode Base64 string to bytes
-        file_bytes = base64.b64decode(file_b64)
-        
-        # Extract text using your existing processor
-        text = get_text_from_file(file_bytes, f"test.{file_type}")
-        
-        # Run AI analysis
-        result = run_analysis(text)
-        
-        # 3. Return exactly what the rubric asks for
-        return {
-            "status": "success",
-            "fileName": file_name,
-            "summary": result["summary"],
-            "entities": {
-                "names": [e["text"] for e in result["entities"] if e["label"] == "PERSON"],
-                "organizations": [e["text"] for e in result["entities"] if e["label"] == "ORG"],
-                "dates": [e["text"] for e in result["entities"] if e["label"] == "DATE"],
-                "amounts": [e["text"] for e in result["entities"] if e["label"] == "MONEY"]
-            },
-            "sentiment": result["sentiment"]
-        }
-    except Exception as e:
+import base64
+import os
+from fastapi import FastAPI, Header, HTTPException, Body
+# FIX: Match the function name in processor.py
+from src.processor import get_text_from_base64 
+from src.analyzer import run_analysis
+
+app = FastAPI()
+API_KEY = os.getenv("API_KEY", "sk_track2_987654321")
+
+@app.post("/api/document-analyze")
+async def analyze_document(x_api_key: str = Header(None), data: dict = Body(...)):
+    # 1. Auth Check
+    if x_api_key != API_KEY:
+        raise HTTPException(status_code=401, detail="Unauthorized")
+
+    try:
+        file_b64 = data.get("fileBase64")
+        file_name = data.get("fileName")
+        file_type = data.get("fileType") # pdf/docx/image
+        
+        # Decode Base64 string to bytes
+        file_bytes = base64.b64decode(file_b64)
+        
+        # FIX: Call the correct function name here too
+        text = get_text_from_base64(file_bytes, file_type)
+        
+        # Run AI analysis
+        result = run_analysis(text)
+        
+        # 3. Return exactly what the rubric asks for
+        return {
+            "status": "success",
+            "fileName": file_name,
+            "summary": result["summary"],
+            "entities": {
+                "names": result["entities"].get("names", []),
+                "organizations": result["entities"].get("organizations", []),
+                "dates": result["entities"].get("dates", []),
+                "amounts": result["entities"].get("amounts", [])
+            },
+            "sentiment": result["sentiment"]
+        }
+    except Exception as e:
         return {"status": "error", "message": str(e)}