feat: Add core AI service for LLM interaction, configuration, response parsing, and JSON repair.

app/services/ai_service.py

@@ -6,9 +6,11 @@ import time
 from typing import Any, TypedDict
 
 from litellm import acompletion
+import litellm
 from pydantic import ValidationError
 from tenacity import retry, retry_if_exception_type, stop_after_attempt, wait_exponential
 
+
 from app import models
 from app.ai_schema import (
     PROMPT_VERSION,
@@ -21,6 +23,11 @@ from app.database import SessionLocal
 from app.utils.image import encode_image
 from app.utils.text import clean_text
 
+# Suppress Litellm verbose logging to avoid Pydantic serialization warnings
+litellm.suppress_debug_info = True
+litellm.set_verbose = False
+litellm.drop_params = True
+
 # Default configuration (can be overridden by DB settings)
 DEFAULT_PROVIDER = "ollama"
 DEFAULT_MODEL = "google/gemini-flash-1.5"
@@ -283,7 +290,9 @@ class AIService:
 
             # If content is empty and we used response_format, try again without it
             if not content and "response_format" in kwargs:
-                logger.warning(f"Model {config['model']} returned empty content with JSON mode. Retrying without response_format.")
+                logger.warning(
+                    f"Model {config['model']} returned empty content with JSON mode. Retrying without response_format."
+                )
                 del kwargs["response_format"]
                 response = await acompletion(**kwargs)
                 content = response.choices[0].message.content
@@ -348,7 +357,8 @@ class AIService:
 
                 # Extract all potential prices from text for debugging
                 import re
-                price_patterns = re.findall(r'\d+[,\.]\d{2}\s*€', cleaned_text)
+
+                price_patterns = re.findall(r"\d+[,\.]\d{2}\s*€", cleaned_text)
                 if price_patterns:
                     logger.info(f"Prices found in text: {price_patterns[:10]}")  # First 10 prices
                 else: