refactor utils

app.py

@@ -17,15 +17,15 @@ from fastapi.middleware.cors import CORSMiddleware
 # MongoDB imports
 from pymongo.errors import PyMongoError, ConnectionFailure, ServerSelectionTimeoutError
 
-from utils.rotator import APIKeyRotator
-from utils.parser import parse_pdf_bytes, parse_docx_bytes
+from utils.api.rotator import APIKeyRotator
+from utils.ingestion.parser import parse_pdf_bytes, parse_docx_bytes
 from utils.caption import BlipCaptioner
-from utils.chunker import build_cards_from_pages
-from utils.embeddings import EmbeddingClient
-from utils.rag import RAGStore, ensure_indexes
-from utils.router import select_model, generate_answer_with_model
-from utils.summarizer import cheap_summarize
-from utils.common import trim_text
+from utils.ingestion.chunker import build_cards_from_pages
+from utils.rag.embeddings import EmbeddingClient
+from utils.rag.rag import RAGStore, ensure_indexes
+from utils.api.router import select_model, generate_answer_with_model
+from utils.service.summarizer import cheap_summarize
+from utils.service.common import trim_text
 from utils.logger import get_logger
 import re
 
@@ -645,7 +645,7 @@ async def generate_report(
     file_summary = doc_sum.get("summary", "")
 
     # Chain-of-thought style two-step with Gemini
-    from utils.router import GEMINI_MED, GEMINI_PRO
+    from utils.api.router import GEMINI_MED, GEMINI_PRO
     
     # Step 1: Content filtering and relevance assessment based on user instructions
     if instructions.strip():
@@ -734,7 +734,7 @@ async def generate_report_pdf(
     """
     Generate a PDF from report content using the PDF utility module
     """
-    from utils.pdf import generate_report_pdf as generate_pdf
+    from utils.service.pdf import generate_report_pdf as generate_pdf
     from fastapi.responses import Response
     
     try:
@@ -775,7 +775,7 @@ Return only the variations, one per line, no numbering or extra text."""
         
         user_prompt = f"Original question: {question}\n\nGenerate query variations:"
         
-        from utils.router import generate_answer_with_model
+        from utils.api.router import generate_answer_with_model
         selection = {"provider": "nvidia", "model": "meta/llama-3.1-8b-instruct"}
         response = await generate_answer_with_model(selection, sys_prompt, user_prompt, None, nvidia_rotator)
         
@@ -866,7 +866,7 @@ async def _chat_impl(
     """
     import sys
     from memo.core import get_memory_system
-    from utils.router import NVIDIA_SMALL  # reuse default name
+    from utils.api.router import NVIDIA_SMALL  # reuse default name
     memory = get_memory_system()
     logger.info("[CHAT] User Q/chat: %s", trim_text(question, 15).replace("\n", " "))
 
@@ -956,7 +956,7 @@ async def _chat_impl(
             numbered = [{"id": i+1, "text": s} for i, s in enumerate(recent3)]
             user = f"Question: {question}\nCandidates:\n{json.dumps(numbered, ensure_ascii=False)}\nSelect any related items and output ONLY their 'text' values concatenated."
             try:
-                from utils.rotator import robust_post_json
+                from utils.api.rotator import robust_post_json
                 key = nvidia_rotator.get_key()
                 url = "https://integrate.api.nvidia.com/v1/chat/completions"
                 payload = {

memo/context.py

@@ -9,7 +9,7 @@ import numpy as np
 from typing import List, Dict, Any, Tuple, Optional
 
 from utils.logger import get_logger
-from utils.embeddings import EmbeddingClient
+from utils.rag.embeddings import EmbeddingClient
 
 logger = get_logger("CONTEXT_MANAGER", __name__)
 

memo/core.py

@@ -10,7 +10,7 @@ import asyncio
 from typing import List, Dict, Any, Optional, Tuple
 
 from utils.logger import get_logger
-from utils.embeddings import EmbeddingClient
+from utils.rag.embeddings import EmbeddingClient
 from memo.legacy import MemoryLRU
 from memo.persistent import PersistentMemory
 

memo/history.py

@@ -10,7 +10,7 @@ from typing import List, Dict, Any, Tuple, Optional
 from utils.logger import get_logger
 from memo.nvidia import summarize_qa, files_relevance, related_recent_context
 from memo.context import semantic_context, get_legacy_context
-from utils.embeddings import EmbeddingClient
+from utils.rag.embeddings import EmbeddingClient
 
 logger = get_logger("HISTORY_MANAGER", __name__)
 

memo/nvidia.py

@@ -10,7 +10,7 @@ import json
 from typing import List, Dict, Any
 
 from utils.logger import get_logger
-from utils.rotator import robust_post_json
+from utils.api.rotator import robust_post_json
 
 logger = get_logger("NVIDIA_INTEGRATION", __name__)
 

memo/persistent.py

@@ -11,7 +11,7 @@ from typing import List, Dict, Any, Optional, Tuple
 from datetime import datetime, timezone
 
 from utils.logger import get_logger
-from utils.embeddings import EmbeddingClient
+from utils.rag.embeddings import EmbeddingClient
 
 logger = get_logger("PERSISTENT_MEMORY", __name__)
 

utils/README.md

@@ -102,8 +102,8 @@ Core utilities for the EdSummariser RAG system providing document processing, re
 
 ```python
 # Basic RAG usage
-from utils.rag import RAGStore
-from utils.embeddings import EmbeddingClient
+from utils.rag.rag import RAGStore
+from utils.rag.embeddings import EmbeddingClient
 
 rag = RAGStore(mongo_uri, db_name)
 embedder = EmbeddingClient()

utils/{caption.py → ingestion/caption.py}

@@ -2,7 +2,7 @@
 from typing import Optional
 from PIL import Image
 import logging
-from .logger import get_logger
+from utils.logger import get_logger
 
 # Use transformers BLIP base (CPU friendly)
 try:

utils/{chunker.py → ingestion/chunker.py}

@@ -1,9 +1,9 @@
 # ────────────────────────────── utils/chunker.py ──────────────────────────────
 import re
 from typing import List, Dict, Any
-from .summarizer import cheap_summarize, clean_chunk_text
-from .common import split_sentences, slugify
-from .logger import get_logger
+from utils.service.summarizer import cheap_summarize, clean_chunk_text
+from utils.service.common import split_sentences, slugify
+from utils.logger import get_logger
 
 # Enhanced semantic chunker with overlap and better structure:
 # - Split by headings / numbered sections if present

utils/{parser.py → ingestion/parser.py}

@@ -4,7 +4,7 @@ import fitz  # PyMuPDF
 from docx import Document
 from PIL import Image
 import numpy as np
-from .logger import get_logger
+from utils.logger import get_logger
 
 logger = get_logger("PARSER", __name__)
 

utils/{common.py → service/common.py}

@@ -1,6 +1,6 @@
 import re
 import unicodedata
-from .logger import get_logger
+from utils.logger import get_logger
 
 logger = get_logger("COMMON", __name__)
 

utils/{summarizer.py → service/summarizer.py}

@@ -1,8 +1,8 @@
 import os
 import asyncio
 from typing import List
-from .logger import get_logger
-from utils.rotator import robust_post_json, APIKeyRotator
+from utils.logger import get_logger
+from utils.api.rotator import robust_post_json, APIKeyRotator
 
 logger = get_logger("SUM", __name__)