Update app.py

app.py

@@ -1,17 +1,6 @@
-# main.py
-"""
-Financial Health Score Service (FastAPI)
-
-FINAL + CREDIT CARD VERSION:
-- Budget score
-- Transaction score
-- Credit card utilization & repayment score
-- GPT-4o-mini with JSON schema
-- Universal JSON parsing
-"""
-
 import json
 import os
+import time
 from datetime import datetime, timedelta
 
 from bson import ObjectId
@@ -20,6 +9,7 @@ from fastapi import FastAPI, HTTPException
 from openai import OpenAI
 from pydantic import BaseModel
 from pymongo import MongoClient
+from pymongo.errors import PyMongoError
 
 # ===========================
 # ENV SETUP
@@ -42,22 +32,51 @@ budget_collection = default_db["budgets"]
 transaction_collection = default_db["transactions"]
 currencies_collection = default_db["currencies"]
 creditcards_collection = default_db["creditcards"]
+api_logs_collection = default_db["api_logs"]
 
 openai = OpenAI(api_key=OPENAI_API_KEY)
 
 app = FastAPI(title="Financial Health Score Service")
 
-
 # ===========================
 # MODELS
 # ===========================
 class ScoreRequest(BaseModel):
     userId: str
 
-
 # ===========================
 # HELPERS
 # ===========================
+def ist_now():
+    return datetime.now().strftime("%d-%m-%Y %H:%M:%S:IST")
+
+
+def log_api_event(
+    *,
+    status: str,
+    response_time: float,
+    user_id: str | None = None,
+    error_message: str | None = None
+):
+    payload = {
+        "name": "Financial Health Score",
+        "status": status,
+        "date": ist_now(),
+        "response_time": round(response_time, 3),
+    }
+
+    if user_id:
+        payload["user_id"] = user_id
+
+    if error_message:
+        payload["error_message"] = error_message
+
+    try:
+        api_logs_collection.insert_one(payload)
+    except Exception:
+        pass  # logging must never break API
+
+
 def safe_number(v):
     try:
         return float(v)
@@ -102,17 +121,11 @@ def normalize_transactions(txns):
         currency_id = txn.get("currency")
 
         try:
-            if isinstance(currency_id, ObjectId):
-                doc = currencies_collection.find_one({"_id": currency_id})
-            else:
-                try:
-                    doc = currencies_collection.find_one({"_id": ObjectId(currency_id)})
-                except:
-                    doc = None
+            doc = currencies_collection.find_one({"_id": ObjectId(currency_id)})
             if doc:
                 currency_code = doc.get("code") or doc.get("currency")
         except:
-            currency_code = None
+            pass
 
         out.append({
             "type": txn.get("type"),
@@ -129,10 +142,10 @@ def normalize_creditcards(cards):
         try:
             start_date = c.get("billing_cycle", {}).get("start_date")
             end_date = c.get("billing_cycle", {}).get("end_date")
+            due_date = c.get("due_date")
+
             start_date = start_date.date().isoformat() if isinstance(start_date, datetime) else None
             end_date = end_date.date().isoformat() if isinstance(end_date, datetime) else None
-
-            due_date = c.get("due_date")
             due_date = due_date.date().isoformat() if isinstance(due_date, datetime) else None
         except:
             start_date = end_date = due_date = None
@@ -153,25 +166,12 @@ def normalize_creditcards(cards):
 def build_prompt(budgets, transactions, creditcards):
     return f"""
 You are a financial health scoring engine.
-
 Compute a score (0–100) considering:
-1. Budgets usage
-2. Spending patterns from recent transactions (last 30 days)
-3. Credit card health:
-   - utilization ratio (balance / credit_limit)
-   - due amount status
-   - repayment behavior
-   - risk from minimum-due payments
-   - future risk if due_date is near
-
-Scoring rules:
-- A lower credit utilization (<30%) increases score.
-- High utilization (>70%) lowers score sharply.
-- Overdue or large due amounts reduce score.
-- Good budget management increases score.
-- Overspending reduces score.
-- Make explanation short (2 sentences max).
-- MUST follow JSON schema.
+- Budget usage
+- Spending behavior
+- Credit card utilization and dues
+
+Return JSON only.
 
 Budgets:
 {json.dumps(budgets, indent=2)}
@@ -179,50 +179,87 @@ Budgets:
 Transactions:
 {json.dumps(transactions, indent=2)}
 
-CreditCards:
+Credit Cards:
 {json.dumps(creditcards, indent=2)}
 """
 
+# ===========================
+# HEALTH ENDPOINT
+# ===========================
+@app.get("/health")
+def health():
+    report = {
+        "service": "Financial Health Score Service",
+        "status": "healthy",
+        "checks": {}
+    }
+
+    try:
+        mongo_client.admin.command("ping")
+        report["checks"]["mongodb"] = "ok"
+    except PyMongoError as e:
+        report["checks"]["mongodb"] = f"fail: {e}"
+        report["status"] = "degraded"
+
+    try:
+        openai.models.list()
+        report["checks"]["openai"] = "ok"
+    except Exception as e:
+        report["checks"]["openai"] = f"fail: {e}"
+        report["status"] = "degraded"
+
+    report["timestamp"] = datetime.utcnow().isoformat()
+    return report
 
 # ===========================
-# ROUTES
+# FINANCIAL SCORE
 # ===========================
 @app.post("/financial-score")
 def financial_score(payload: ScoreRequest):
-    # Validate ID
+    start_time = time.time()
+
     try:
-        user_id = ObjectId(payload.userId)
+        user_oid = ObjectId(payload.userId)
     except:
+        log_api_event(
+            status="fail",
+            response_time=time.time() - start_time,
+            user_id=payload.userId,
+            error_message="Invalid userId"
+        )
         raise HTTPException(status_code=400, detail="Invalid userId")
 
-    # Fetch budgets
-    budgets_raw = list(budget_collection.find({"createdBy": user_id}))
-    budgets = normalize_budgets(budgets_raw)
-
-    # Fetch last 30 days transactions
-    thirty_days_ago = datetime.utcnow() - timedelta(days=30)
-    txns_raw = list(
-        transaction_collection.find(
-            {"user": user_id, "date": {"$gte": thirty_days_ago}}
-        ).sort("date", -1).limit(200)
-    )
-    transactions = normalize_transactions(txns_raw)
-
-    # Fetch credit cards
-    cards_raw = list(creditcards_collection.find({"user_id": user_id}))
-    creditcards = normalize_creditcards(cards_raw)
-
-    # No data
-    if not budgets and not transactions and not creditcards:
-        return {
-            "userId": payload.userId,
-            "score": 0,
-            "explanation": "No financial data found."
-        }
+    try:
+        budgets = normalize_budgets(
+            list(budget_collection.find({"createdBy": user_oid}))
+        )
 
-    prompt = build_prompt(budgets, transactions, creditcards)
+        txns = normalize_transactions(
+            list(
+                transaction_collection.find(
+                    {"user": user_oid, "date": {"$gte": datetime.utcnow() - timedelta(days=30)}}
+                ).sort("date", -1).limit(200)
+            )
+        )
+
+        cards = normalize_creditcards(
+            list(creditcards_collection.find({"user_id": user_oid}))
+        )
+
+        if not budgets and not txns and not cards:
+            log_api_event(
+                status="success",
+                response_time=time.time() - start_time,
+                user_id=payload.userId
+            )
+            return {
+                "status": "success",
+                "message": "No financial data found",
+                "userId": payload.userId,
+                "score": 0,
+                "explanation": "No financial data available."
+            }
 
-    try:
         response = openai.chat.completions.create(
             model="gpt-4o-mini",
             temperature=0.6,
@@ -236,51 +273,52 @@ def financial_score(payload: ScoreRequest):
                             "score": {"type": "number"},
                             "explanation": {"type": "string"}
                         },
-                        "required": ["score", "explanation"],
-                        "additionalProperties": False
+                        "required": ["score", "explanation"]
                     }
                 }
             },
             messages=[
                 {"role": "system", "content": "You calculate financial health."},
-                {"role": "user", "content": prompt}
+                {"role": "user", "content": build_prompt(budgets, txns, cards)}
             ]
         )
+
+        parsed = json.loads(response.choices[0].message.content)
+        score = max(0, min(100, int(float(parsed.get("score", 0)))))
+
+        log_api_event(
+            status="success",
+            response_time=time.time() - start_time,
+            user_id=payload.userId
+        )
+
+        return {
+            "status": "success",
+            "message": "Financial health score calculated successfully",
+            "userId": payload.userId,
+            "score": score,
+            "explanation": parsed.get("explanation")
+        }
+
     except Exception as exc:
-        raise HTTPException(status_code=502, detail=f"OpenAI request failed: {exc}")
+        log_api_event(
+            status="fail",
+            response_time=time.time() - start_time,
+            user_id=payload.userId,
+            error_message=str(exc)
+        )
+        raise HTTPException(status_code=502, detail=str(exc))
+
+
+
+
 
-    # UNIVERSAL JSON PARSING
-    try:
-        content = response.choices[0].message.content
 
-        if isinstance(content, list):
-            raw_json = content[0].get("text", content[0])
-        else:
-            raw_json = content
 
-        if not isinstance(raw_json, str):
-            raw_json = str(raw_json)
 
-        parsed = json.loads(raw_json)
 
-    except Exception as e:
-        raise HTTPException(
-            status_code=502,
-            detail=f"Could not parse JSON output: {e}"
-        )
 
-    score_val = parsed.get("score", 0)
-    try:
-        score_val = int(float(score_val))
-    except:
-        score_val = 0
-    score_val = max(0, min(100, score_val))
 
-    return {
-        "userId": payload.userId,
-        "score": score_val,
-        "explanation": parsed.get("explanation")
-    }
 
 
 
@@ -288,11 +326,12 @@ def financial_score(payload: ScoreRequest):
 # """
 # Financial Health Score Service (FastAPI)
 
-# FINAL VERSION:
-# - Uses GPT-4o-mini with JSON schema
-# - Universal-safe JSON parsing (supports all SDK formats)
-# - Correct OpenAI Chat Completions API
-# - Bulletproof error handling
+# FINAL + CREDIT CARD VERSION:
+# - Budget score
+# - Transaction score
+# - Credit card utilization & repayment score
+# - GPT-4o-mini with JSON schema
+# - Universal JSON parsing
 # """
 
 # import json
@@ -307,7 +346,7 @@ def financial_score(payload: ScoreRequest):
 # from pymongo import MongoClient
 
 # # ===========================
-# # ENV & CLIENT SETUP
+# # ENV SETUP
 # # ===========================
 # load_dotenv()
 
@@ -315,21 +354,19 @@ def financial_score(payload: ScoreRequest):
 # OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 
 # if not MONGO_URI:
-#     raise RuntimeError("❌ MONGO_URI missing in environment variables")
+#     raise RuntimeError("❌ MONGO_URI missing")
 
 # if not OPENAI_API_KEY:
-#     raise RuntimeError("❌ OPENAI_API_KEY missing in environment variables")
+#     raise RuntimeError("❌ OPENAI_API_KEY missing")
 
 # mongo_client = MongoClient(MONGO_URI)
 # default_db = mongo_client.get_default_database()
-# if default_db is None:
-#     raise RuntimeError("Unable to determine default database from MONGO_URI")
 
-# budget_collection = default_db["budget"]
+# budget_collection = default_db["budgets"]
 # transaction_collection = default_db["transactions"]
 # currencies_collection = default_db["currencies"]
+# creditcards_collection = default_db["creditcards"]
 
-# # OpenAI Client
 # openai = OpenAI(api_key=OPENAI_API_KEY)
 
 # app = FastAPI(title="Financial Health Score Service")
@@ -385,24 +422,17 @@ def financial_score(payload: ScoreRequest):
 #         date_val = txn.get("date")
 #         date_str = date_val.date().isoformat() if isinstance(date_val, datetime) else None
 
-#         # Resolve currency
 #         currency_code = None
 #         currency_id = txn.get("currency")
 
 #         try:
 #             if isinstance(currency_id, ObjectId):
 #                 doc = currencies_collection.find_one({"_id": currency_id})
-#             elif isinstance(currency_id, dict) and "$oid" in currency_id:
-#                 doc = currencies_collection.find_one({"_id": ObjectId(currency_id["$oid"])})
-#             elif isinstance(currency_id, str):
+#             else:
 #                 try:
 #                     doc = currencies_collection.find_one({"_id": ObjectId(currency_id)})
 #                 except:
-#                     doc = currencies_collection.find_one({"code": currency_id}) or \
-#                           currencies_collection.find_one({"currency": currency_id})
-#             else:
-#                 doc = None
-
+#                     doc = None
 #             if doc:
 #                 currency_code = doc.get("code") or doc.get("currency")
 #         except:
@@ -417,36 +447,73 @@ def financial_score(payload: ScoreRequest):
 #     return out
 
 
-# def build_prompt(budgets, transactions):
-#     return f"""
-# You are a financial wellness expert. Use the user's budgets and last 30 days of transactions
-# to compute a financial health score from 0 to 100.
+# def normalize_creditcards(cards):
+#     out = []
+#     for c in cards:
+#         try:
+#             start_date = c.get("billing_cycle", {}).get("start_date")
+#             end_date = c.get("billing_cycle", {}).get("end_date")
+#             start_date = start_date.date().isoformat() if isinstance(start_date, datetime) else None
+#             end_date = end_date.date().isoformat() if isinstance(end_date, datetime) else None
 
-# Rules:
-# - ALWAYS prefix currency amounts with currency code (e.g., "INR 10,000").
-# - Keep explanation short (1–2 sentences).
-# - Score must reflect spending, budget control, and overall balance.
-# - Respond ONLY in the JSON schema required below.
+#             due_date = c.get("due_date")
+#             due_date = due_date.date().isoformat() if isinstance(due_date, datetime) else None
+#         except:
+#             start_date = end_date = due_date = None
+
+#         out.append({
+#             "card_name": c.get("card_name"),
+#             "credit_limit": safe_number(c.get("credit_limit")),
+#             "current_balance": safe_number(c.get("current_balance")),
+#             "total_due_amount": safe_number(c.get("total_due_amount")),
+#             "minimum_due": safe_number(c.get("minimum_due")),
+#             "billing_cycle_start": start_date,
+#             "billing_cycle_end": end_date,
+#             "due_date": due_date,
+#         })
+#     return out
+
+
+# def build_prompt(budgets, transactions, creditcards):
+#     return f"""
+# You are a financial health scoring engine.
+
+# Compute a score (0–100) considering:
+# 1. Budgets usage
+# 2. Spending patterns from recent transactions (last 30 days)
+# 3. Credit card health:
+#    - utilization ratio (balance / credit_limit)
+#    - due amount status
+#    - repayment behavior
+#    - risk from minimum-due payments
+#    - future risk if due_date is near
+
+# Scoring rules:
+# - A lower credit utilization (<30%) increases score.
+# - High utilization (>70%) lowers score sharply.
+# - Overdue or large due amounts reduce score.
+# - Good budget management increases score.
+# - Overspending reduces score.
+# - Make explanation short (2 sentences max).
+# - MUST follow JSON schema.
 
 # Budgets:
 # {json.dumps(budgets, indent=2)}
 
 # Transactions:
 # {json.dumps(transactions, indent=2)}
+
+# CreditCards:
+# {json.dumps(creditcards, indent=2)}
 # """
 
 
 # # ===========================
 # # ROUTES
 # # ===========================
-# @app.get("/")
-# def root():
-#     return {"status": "Financial Health Score service running"}
-
-
 # @app.post("/financial-score")
 # def financial_score(payload: ScoreRequest):
-#     # Validate ObjectId
+#     # Validate ID
 #     try:
 #         user_id = ObjectId(payload.userId)
 #     except:
@@ -461,23 +528,24 @@ def financial_score(payload: ScoreRequest):
 #     txns_raw = list(
 #         transaction_collection.find(
 #             {"user": user_id, "date": {"$gte": thirty_days_ago}}
-#         ).sort("date", -1).limit(150)
+#         ).sort("date", -1).limit(200)
 #     )
 #     transactions = normalize_transactions(txns_raw)
 
-#     # If no data
-#     if not budgets and not transactions:
+#     # Fetch credit cards
+#     cards_raw = list(creditcards_collection.find({"user_id": user_id}))
+#     creditcards = normalize_creditcards(cards_raw)
+
+#     # No data
+#     if not budgets and not transactions and not creditcards:
 #         return {
 #             "userId": payload.userId,
 #             "score": 0,
-#             "explanation": "No budgets or recent transactions found."
+#             "explanation": "No financial data found."
 #         }
 
-#     prompt = build_prompt(budgets, transactions)
+#     prompt = build_prompt(budgets, transactions, creditcards)
 
-#     # ===========================
-#     # GPT-4o-mini WITH JSON SCHEMA
-#     # ===========================
 #     try:
 #         response = openai.chat.completions.create(
 #             model="gpt-4o-mini",
@@ -498,24 +566,20 @@ def financial_score(payload: ScoreRequest):
 #                 }
 #             },
 #             messages=[
-#                 {"role": "system", "content": "You are a financial scoring engine."},
+#                 {"role": "system", "content": "You calculate financial health."},
 #                 {"role": "user", "content": prompt}
 #             ]
 #         )
 #     except Exception as exc:
 #         raise HTTPException(status_code=502, detail=f"OpenAI request failed: {exc}")
 
-#     # ===========================
-#     # UNIVERSAL JSON PARSING (supports ALL SDK formats)
-#     # ===========================
+#     # UNIVERSAL JSON PARSING
 #     try:
 #         content = response.choices[0].message.content
 
-#         # Case A — list of dicts (new SDK)
 #         if isinstance(content, list):
 #             raw_json = content[0].get("text", content[0])
 #         else:
-#             # Case B — plain string (older SDK)
 #             raw_json = content
 
 #         if not isinstance(raw_json, str):
@@ -529,13 +593,11 @@ def financial_score(payload: ScoreRequest):
 #             detail=f"Could not parse JSON output: {e}"
 #         )
 
-#     # Score normalization
 #     score_val = parsed.get("score", 0)
 #     try:
 #         score_val = int(float(score_val))
 #     except:
 #         score_val = 0
-
 #     score_val = max(0, min(100, score_val))
 
 #     return {