switch to gemini-flash-lite-2.5

README.md

@@ -13,7 +13,7 @@ An asynchronous transactional data cleaning, validation, and LLM powered categor
 
 - Reads multi format dates and handles missing transaction IDs by auto generating unique fallbacks, and parses messy amounts with currency signs and commas cleanly.
 - Offloads validation, spend conversion, and analysis to a Celery background worker backed by Redis.
-- Integrates with the Google GenAI SDK (`gemini-3.5-flash`) using structured output schemas to categorize transaction records into database-defined custom categories.
+- Integrates with the Google GenAI SDK (`gemini-2.5-flash-lite` 75% cheaper than `gemini-3.5-flash-lite with no tangible decrease in performance) using structured output schemas to categorize transaction records into database-defined custom categories.
 - Uses Redis caching with a 24-hour TTL to store live exchange rates, falling back to a hardcoded rate of `93.0` if offline.
 - Statistical Anomaly Detection:
   - Flags transactions exceeding 3 times the account's median spend as statistical outliers.

app/worker.py

@@ -70,7 +70,7 @@ async def classify_transactions_batch(
             interaction = await loop.run_in_executor(
                 None,
                 lambda: client.interactions.create(
-                    model="gemini-3.5-flash",
+                    model="gemini-2.5-flash-lite",
                     input=input_prompt,
                     response_format={
                         "type": "text",