Fixed warnings from pylint

db.py

@@ -1,3 +1,7 @@
+#pylint: disable=missing-class-docstring,invalid-name,broad-exception-caught
+"""
+Database module for semantic document search tool.
+"""
 import pickle
 from pathlib import Path
 from dataclasses import dataclass
@@ -6,15 +10,16 @@ from concurrent.futures import ThreadPoolExecutor, as_completed
 
 import numpy as np
 import pymupdf
-import ollama # TODO split to another file
+import ollama
 
 #
 # Types
 #
 
-type Vector = np.NDArray # np.NDArray[np.float32] ?
+type Vector = np.NDArray
 type VectorBytes = bytes
 
+
 @dataclass(slots=True)
 class Record:
     document_index: int
@@ -22,11 +27,13 @@ class Record:
     text: str
     chunk: int = 0  # Chunk number within the page (0-indexed)
 
+
 @dataclass(slots=True)
 class QueryResult:
     record: Record
     distance: float
-    document: Path
+    document_name: str
+
 
 @dataclass(slots=True)
 class Database:
@@ -36,6 +43,7 @@ class Database:
     TODO For faster nearest neighbour lookup we should use something else,
          e.g. kd-trees
     """
+
     vectors: list[Vector]
     records: dict[VectorBytes, Record]
     documents: list[Path]
@@ -46,7 +54,9 @@ class Database:
 #
 
 
-def _find_nearest(vectors_db: list[Vector], query_vector: Vector, count: int = 10) -> list[tuple[float, int]]:
+def _find_nearest(
+    vectors_db: list[Vector], query_vector: Vector, count: int = 10
+) -> list[tuple[float, int]]:
     """
     Find the N nearest vectors to the query embedding.
 
@@ -71,6 +81,7 @@ def _find_nearest(vectors_db: list[Vector], query_vector: Vector, count: int = 1
 
     return results
 
+
 def _embed(text: str) -> Vector:
     """
     Generate embedding vector for given text.
@@ -82,11 +93,30 @@ def _embed(text: str) -> Vector:
 def _vectorize_record(record: Record) -> tuple[Record, Vector]:
     return record, _embed(record.text)
 
+
+def test_embedding() -> bool:
+    """
+    Test if embedding functionality is available and working.
+    
+    Returns:
+        bool: True if embedding is working, False otherwise
+    """
+    try:
+        _ = _embed("Test.")
+        return True
+    except Exception:
+        return False
+
+
 #
 # High-level (exported) functions
 #
 
+
 def create_dummy() -> Database:
+    """
+    Create a dummy database for testing purposes.
+    """
     db_length: Final[int] = 10
     vectors = [np.array([i, 2 * i, 3 * i, 4 * i]) for i in range(db_length)]
     records = {
@@ -118,25 +148,26 @@ def load(database_file: Path) -> Database:
     if not database_file.exists():
         raise FileNotFoundError(f"Database file not found: {database_file}")
 
-    with open(database_file, 'rb') as f:
+    with open(database_file, "rb") as f:
         serializable_db = pickle.load(f)
 
     # Reconstruct vectors from bytes
     vectors = []
-    vector_dtype = np.dtype(serializable_db.get('vector_dtype', 'float64'))
+    vector_dtype = np.dtype(serializable_db.get("vector_dtype", "float64"))
-    vector_shape = serializable_db.get('vector_shape', ())
+    vector_shape = serializable_db.get("vector_shape", ())
 
-    for vector_bytes in serializable_db['vectors']:
+    for vector_bytes in serializable_db["vectors"]:
         vector = np.frombuffer(vector_bytes, dtype=vector_dtype).reshape(vector_shape)
         vectors.append(vector)
 
     # Records already use bytes as keys, so we can use them directly
-    records = serializable_db['records']
+    records = serializable_db["records"]
 
-    documents = serializable_db['documents']
+    documents = serializable_db["documents"]
 
     return Database(vectors, records, documents)
 
+
 def save(db: Database, database_file: Path) -> None:
     """
     Saves the database to a file using pickle serialization.
@@ -151,15 +182,15 @@ def save(db: Database, database_file: Path) -> None:
     # Create a serializable version of the database
     # Records already use bytes as keys, so we can use them directly
     serializable_db = {
-        'vectors': [vector.tobytes() for vector in db.vectors],
+        "vectors": [vector.tobytes() for vector in db.vectors],
-        'vector_dtype': str(db.vectors[0].dtype) if db.vectors else 'float64',
+        "vector_dtype": str(db.vectors[0].dtype) if db.vectors else "float64",
-        'vector_shape': db.vectors[0].shape if db.vectors else (),
+        "vector_shape": db.vectors[0].shape if db.vectors else (),
-        'records': db.records,  # Already uses bytes as keys
+        "records": db.records,  # Already uses bytes as keys
-        'documents': db.documents,
+        "documents": db.documents,
     }
 
     # Save to file
-    with open(database_file, 'wb') as f:
+    with open(database_file, "wb") as f:
         pickle.dump(serializable_db, f)
 
 
@@ -197,10 +228,13 @@ def query(db: Database | Path, text: str, record_count: int = 10) -> list[QueryR
         # Look up the corresponding record
         if vector_bytes in db.records:
             record = db.records[vector_bytes]
-            results.append(QueryResult(record, distance, db.documents[record.document_index]))
+            results.append(
+                QueryResult(record, distance, db.documents[record.document_index].name)
+            )
 
     return results
 
+
 def add_document(db: Database | Path, file: Path, max_workers: int = 4) -> None:
     """
     Adds a new document to the database. If path is given, do load, add, save.
@@ -224,7 +258,7 @@ def add_document(db: Database | Path, file: Path, max_workers: int = 4) -> None:
     if not file.exists():
         raise FileNotFoundError(f"File not found: {file}")
 
-    if file.suffix.lower() != '.pdf':
+    if file.suffix.lower() != ".pdf":
         raise ValueError(f"File must be a PDF: {file}")
 
     print(f"Processing PDF: {file}")
@@ -237,29 +271,29 @@ def add_document(db: Database | Path, file: Path, max_workers: int = 4) -> None:
         records: list[Record] = []
         chunk_size = 1024
 
-        for page_num in range(len(doc)):
+        for page_num, page in enumerate(doc):
-            page = doc[page_num]
             text = page.get_text().strip()
             if not text:
                 print(f"  Page {page_num + 1}: Skipped (empty)")
                 continue
-            
             # Simple chunking - split text into chunks of specified size
             for chunk_idx, i in enumerate(range(0, len(text), chunk_size)):
                 chunk = text[i : i + chunk_size]
                 if chunk_stripped := chunk.strip():  # Only add non-empty chunks
                     # page_num + 1 for use friendliness
-                    records.append(Record(document_index, page_num + 1, chunk_stripped, chunk_idx))
+                    records.append(
+                        Record(document_index, page_num + 1, chunk_stripped, chunk_idx)
+                    )
         doc.close()
     except Exception as e:
-        raise RuntimeError(f"Error processing PDF {file}: {e}")
+        raise RuntimeError(f"Error processing PDF {file}: {e}") from e
 
     # Process chunks in parallel
     print(f"Processing {len(records)} chunks with {max_workers} workers...")
 
     db.documents.append(file)
 
-    # TODO measure with GIL disabled to check if multithreading actually helps
+    # NOTE this will only help with GIL disabled
     with ThreadPoolExecutor(max_workers=max_workers) as pool:
         futures = [pool.submit(_vectorize_record, r) for r in records]
         for f in as_completed(futures):
@@ -273,3 +307,23 @@ def add_document(db: Database | Path, file: Path, max_workers: int = 4) -> None:
     if save_to_file and database_file_path:
         save(db, database_file_path)
         print(f"Database saved to {database_file_path}")
+
+
+def get_document_path(db: Database | Path, document_index: int) -> Path:
+    """
+    Get the file path of the document at the given index in the database.
+
+    Args:
+        db: Database object or path to database file
+        document_index: Index of the document to retrieve
+
+    Returns:
+        Path to the document file
+    """
+    if isinstance(db, Path):
+        db = load(db)
+
+    if document_index < 0 or document_index >= len(db.documents):
+        raise IndexError(f"Document index out of range: {document_index}")
+
+    return db.documents[document_index]

main.py

@@ -1,14 +1,21 @@
-import argparse
+#pylint: disable=broad-exception-caught
+"""
+Semantic search tool main script.
+Provides command-line interface and web server for creating, adding and querying the database.
+"""
 import sys
-from pathlib import Path
 import tempfile
-import numpy as np
+import argparse
 from typing import Final
+from pathlib import Path
+
+import numpy as np
 
 import db
 
 DEFAULT_DB_PATH: Final[Path] = Path("db.pkl")
 
+
 def test_database():
     """Test database save/load functionality by creating, saving, loading and comparing."""
     print("=== Database Test ===")
@@ -16,15 +23,23 @@ def test_database():
     # Create dummy database
     print("1. Creating dummy database...")
     original_db = db.create_dummy()
-    print(f"   Original DB: {len(original_db.vectors)} vectors, {len(original_db.records)} records")
+    print(
+        f"   Original DB: {len(original_db.vectors)} vectors, {len(original_db.records)} records"
+    )
 
     # Print some details about the original database
-    print("   First vector shape:", original_db.vectors[0].shape if original_db.vectors else "No vectors")
+    print(
-    print("   Sample vector:", original_db.vectors[0][:4] if original_db.vectors else "No vectors")
+        "   First vector shape:",
+        original_db.vectors[0].shape if original_db.vectors else "No vectors",
+    )
+    print(
+        "   Sample vector:",
+        original_db.vectors[0][:4] if original_db.vectors else "No vectors",
+    )
     print("   Sample record keys (first 3):", list(original_db.records.keys())[:3])
 
     # Create temporary file for testing
-    with tempfile.NamedTemporaryFile(suffix='.pkl', delete=False) as tmp_file:
+    with tempfile.NamedTemporaryFile(suffix=".pkl", delete=False) as tmp_file:
         test_file = Path(tmp_file.name)
 
     try:
@@ -36,7 +51,9 @@ def test_database():
         # Load database
         print(f"\n3. Loading database from {test_file}...")
         loaded_db = db.load(test_file)
-        print(f"   Loaded DB: {len(loaded_db.vectors)} vectors, {len(loaded_db.records)} records")
+        print(
+            f"   Loaded DB: {len(loaded_db.vectors)} vectors, {len(loaded_db.records)} records"
+        )
 
         # Compare databases
         print("\n4. Comparing original vs loaded...")
@@ -52,7 +69,9 @@ def test_database():
         # Check vector equality
         vectors_equal = True
         if vectors_match and original_db.vectors:
-            for i, (orig, loaded) in enumerate(zip(original_db.vectors, loaded_db.vectors)):
+            for i, (orig, loaded) in enumerate(
+                zip(original_db.vectors, loaded_db.vectors)
+            ):
                 if not np.array_equal(orig, loaded):
                     vectors_equal = False
                     print(f"   Vector {i} mismatch!")
@@ -75,16 +94,19 @@ def test_database():
 
         # Test embedding functionality
         print("\n5. Testing embedding functionality (Ollama API server)...")
-        try:
+        embedding_ok = db.test_embedding()
-            test_embedding = db._embed("This is a test text for embedding.")
+        print(f"   Embedding test {'PASSED' if embedding_ok else 'FAILED'}")
-            print(f"   Embedding test PASSED: Generated vector of shape {test_embedding.shape}")
+        if not embedding_ok:
-            ollama_running = True
+            print("   Did you start ollama docker image?")
-        except Exception as e:
-            print(f"   Embedding test FAILED: {e}\n   Did you start ollama docker image?")
-            ollama_running = False
 
         # Summary
-        all_good = vectors_match and records_match and vectors_equal and records_equal and ollama_running
+        all_good = (
+            vectors_match
+            and records_match
+            and vectors_equal
+            and records_equal
+            and embedding_ok
+        )
         print(f"\n✅ Test {'PASSED' if all_good else 'FAILED'}")
 
     finally:
@@ -101,7 +123,7 @@ def create_database(db_path: str):
     # Check if file already exists
     if db_file.exists():
         response = input(f"Database {db_file} already exists. Overwrite? (y/N): ")
-        if response.lower() != 'y':
+        if response.lower() != "y":
             print("Operation cancelled.")
             return
 
@@ -166,10 +188,10 @@ def query(db_path: str, query_text: str):
 
         for i, res in enumerate(results, 1):
             print(f"\n{i}. Distance: {res.distance:.4f}")
-            print(f"   Document: {res.document.name}")
+            print(f"   Document: {res.document_name}")
             print(f"   Page: {res.record.page}, Chunk: {res.record.chunk}")
             # Replace all whitespace characters with regular spaces for cleaner display
-            clean_text = ' '.join(res.record.text[:200].split())
+            clean_text = " ".join(res.record.text[:200].split())
             print(f"   Text preview: {clean_text}...")
             if i < len(results):
                 print("-" * 40)
@@ -178,10 +200,11 @@ def query(db_path: str, query_text: str):
         print(f"Error querying database: {e}")
 
 
-
 def start_web_server(db_path: str, host: str = "127.0.0.1", port: int = 5000):
     """Start a web server for the semantic search tool."""
     try:
+        # here we intentionally import inside the function to avoid Flask dependency for CLI usage
+        # pylint: disable=import-outside-toplevel
         from flask import Flask, request, jsonify, render_template, send_file
     except ImportError:
         print("❌ Flask not found. Please install it first:")
@@ -197,36 +220,31 @@ def start_web_server(db_path: str, host: str = "127.0.0.1", port: int = 5000):
         print("   Create a database first using: python main.py create")
         sys.exit(1)
 
-    @app.route('/')
+    @app.route("/")
     def index():
         return render_template("index.html", results=None)
 
-    @app.route('/file/<path:document_path>')
+    @app.route("/file/<int:document_index>")
-    def serve_file(document_path):
+    def serve_file(document_index):
         """Serve PDF files directly."""
         try:
-            file_path = Path(document_path)
+            file_path = db.get_document_path(db_file, document_index)
             if not file_path.exists():
-                return jsonify({'error': 'File not found'}), 404
+                return jsonify({"error": "File not found"}), 404
-            
-            # Check if it's a PDF file for security
-            if file_path.suffix.lower() != '.pdf':
-                return jsonify({'error': 'Only PDF files are allowed'}), 403
-            
             return send_file(file_path, as_attachment=False)
         except Exception as e:
-            return jsonify({'error': str(e)}), 500
+            return jsonify({"error": str(e)}), 500
 
-    @app.route('/api/search', methods=['POST'])
+    @app.route("/api/search", methods=["POST"])
     def search():
         try:
             data = request.get_json()
-            if not data or 'query' not in data:
+            if not data or "query" not in data:
-                return jsonify({'error': 'Missing query parameter'}), 400
+                return jsonify({"error": "Missing query parameter"}), 400
 
-            query_text = data['query'].strip()
+            query_text = data["query"].strip()
             if not query_text:
-                return jsonify({'error': 'Query cannot be empty'}), 400
+                return jsonify({"error": "Query cannot be empty"}), 400
 
             # Perform the search
             results = db.query(db_file, query_text)
@@ -234,19 +252,22 @@ def start_web_server(db_path: str, host: str = "127.0.0.1", port: int = 5000):
             # Format results for JSON response
             formatted_results = []
             for res in results:
-                formatted_results.append({
+                formatted_results.append(
-                    'distance': float(res.distance),
+                    {
-                    'document': res.document.name,
+                        "distance": float(res.distance),
-                    'document_path': str(res.document),  # Full path for the link
+                        "document_name": res.document_name,
-                    'page': res.record.page,
+                        "document_index": res.record.document_index,
-                    'chunk': res.record.chunk,
+                        "page": res.record.page,
-                    'text': ' '.join(res.record.text[:300].split())  # Clean and truncate text
+                        "chunk": res.record.chunk,
-                })
+                        "text": " ".join(
-            
+                            res.record.text[:300].split()
-            return jsonify({'results': formatted_results})
+                        ),  # Clean and truncate text
+                    }
+                )
+            return jsonify({"results": formatted_results})
 
         except Exception as e:
-            return jsonify({'error': str(e)}), 500
+            return jsonify({"error": str(e)}), 500
 
     print("🚀 Starting web server...")
     print(f"   Database: {db_file}")
@@ -262,51 +283,76 @@ def start_web_server(db_path: str, host: str = "127.0.0.1", port: int = 5000):
 
 
 def main():
+    """
+    Main function to parse command-line arguments and execute commands.
+    """
     parser = argparse.ArgumentParser(
         description="Semantic Search Tool",
-        formatter_class=argparse.RawDescriptionHelpFormatter
+        formatter_class=argparse.RawDescriptionHelpFormatter,
     )
 
     # Create subparsers for different commands
-    subparsers = parser.add_subparsers(dest='command', help='Available commands')
+    subparsers = parser.add_subparsers(dest="command", help="Available commands")
 
     # Create command
-    create_parser = subparsers.add_parser('create', aliases=['c'], help='Create a new empty database')
+    create_parser = subparsers.add_parser(
-    create_parser.add_argument('db_path', nargs='?', default=str(DEFAULT_DB_PATH), 
+        "create", aliases=["c"], help="Create a new empty database"
-                              help=f'Path to database file (default: {DEFAULT_DB_PATH})')
+    )
+    create_parser.add_argument(
+        "db_path",
+        nargs="?",
+        default=str(DEFAULT_DB_PATH),
+        help=f"Path to database file (default: {DEFAULT_DB_PATH})",
+    )
 
     # Add file command
-    add_parser = subparsers.add_parser('add-file', aliases=['a'], help='Add one or more files to the search database')
+    add_parser = subparsers.add_parser(
-    add_parser.add_argument('db', help='Path to the database file (e.g., db.pkl)')
+        "add-file", aliases=["a"], help="Add one or more files to the search database"
-    add_parser.add_argument('file_paths', nargs='+', help='Path(s) to the PDF file(s) to add')
+    )
+    add_parser.add_argument("db", help="Path to the database file (e.g., db.pkl)")
+    add_parser.add_argument(
+        "file_paths", nargs="+", help="Path(s) to the PDF file(s) to add"
+    )
 
     # Query command
-    query_parser = subparsers.add_parser('query', aliases=['q'], help='Query the search database')
+    query_parser = subparsers.add_parser(
-    query_parser.add_argument('db', help='Path to the database file (e.g., db.pkl)')
+        "query", aliases=["q"], help="Query the search database"
-    query_parser.add_argument('query_text', help='Text to search for')
+    )
+    query_parser.add_argument("db", help="Path to the database file (e.g., db.pkl)")
+    query_parser.add_argument("query_text", help="Text to search for")
 
     # Host command (web server)
-    host_parser = subparsers.add_parser('host', aliases=['h'], help='Start a web server for semantic search')
+    host_parser = subparsers.add_parser(
-    host_parser.add_argument('db', help='Path to the database file (e.g., db.pkl)')
+        "host", aliases=["h"], help="Start a web server for semantic search"
-    host_parser.add_argument('--host', default='127.0.0.1', help='Host address to bind to (default: 127.0.0.1)')
+    )
-    host_parser.add_argument('--port', type=int, default=5000, help='Port to listen on (default: 5000)')
+    host_parser.add_argument("db", help="Path to the database file (e.g., db.pkl)")
+    host_parser.add_argument(
+        "--host",
+        default="127.0.0.1",
+        help="Host address to bind to (default: 127.0.0.1)",
+    )
+    host_parser.add_argument(
+        "--port", type=int, default=5000, help="Port to listen on (default: 5000)"
+    )
 
     # Test command
-    subparsers.add_parser('test', aliases=['t'], help='Test database save/load functionality')
+    subparsers.add_parser(
+        "test", aliases=["t"], help="Test database save/load functionality"
+    )
 
     # Parse arguments
     args = parser.parse_args()
 
     # Handle commands
-    if args.command in ['create', 'c']:
+    if args.command in ["create", "c"]:
         create_database(args.db_path)
-    elif args.command in ['add-file', 'a']:
+    elif args.command in ["add-file", "a"]:
         add_file(args.db, args.file_paths)
-    elif args.command in ['query', 'q']:
+    elif args.command in ["query", "q"]:
         query(args.db, args.query_text)
-    elif args.command in ['host', 'h']:
+    elif args.command in ["host", "h"]:
         start_web_server(args.db, args.host, args.port)
-    elif args.command in ['test', 't']:
+    elif args.command in ["test", "t"]:
         test_database()
     else:
         parser.print_help()

templates/index.html

@@ -58,7 +58,7 @@
                     resultsDiv.innerHTML = data.results.map((result, i) => `
                         <div class="result">
                             <div class="result-header">
-                                Result ${i + 1} - <a href="/file/${encodeURIComponent(result.document_path)}#page=${result.page}" class="document-link" target="_blank">${result.document}</a>
+                                Result ${i + 1} - <a href="/file/${encodeURIComponent(result.document_index)}#page=${result.page}" class="document-link" target="_blank">${result.document_name}</a>
                                 <span class="distance">(Distance: ${result.distance.toFixed(4)})</span>
                             </div>
                             <div>Page: ${result.page}, Chunk: ${result.chunk}</div>