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b792da53ba623fd326f1aeaa18060a862a85986d
ComfyAssets-ComfyUI_PromptM…/database/operations.py
T
Vito Sansevero 1f422d2c43 fix: restore through SQLite's backup API, close_all for shared files, safer output scans 
restore_from_file copied the uploaded file over the live database and deleted
its WAL while other PromptModel instances (nodes, image monitor, queue hook)
still held connections, which corrupts on POSIX and fails on Windows. It now
copies pages through the online backup API into the live connection so every
open handle sees the new content. PromptDatabase.close_all() closes the
connections of every thread, which tests need before deleting a database.
Output scans skip symlinked files, filesystem entries get a stable digest id
instead of a per-process hash(), and thumbnail streaming stops when the
client disconnects.
2026-10-08 18:01:34 -07:00

2024 lines
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"""
Database operations for KikoTextEncode prompt storage and retrieval.
"""
import sqlite3
import json
import datetime
import os
from typing import Optional, List, Dict, Any
from .models import PromptModel, normalize_image_path, utc_now_iso
# Import logging system
try:
from ..utils.logging_config import get_logger
except ImportError:
import sys
current_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0, current_dir)
from utils.logging_config import get_logger
# Subquery to fetch tags from junction table, embedded in SELECT statements
TAG_SUBQUERY = (
"(SELECT GROUP_CONCAT(t.name, '|||') "
"FROM prompt_tags pt JOIN tags t ON pt.tag_id = t.id "
"WHERE pt.prompt_id = prompts.id) AS _tag_list"
)
# Server-side sort orders, keyed by the value the UI sends. Only these strings ever
# reach ORDER BY; unknown keys fall back to DEFAULT_SORT.
# last_used_at is NULL until the prompt has run, so "IS NULL" first keeps
# never-run prompts after every run one (SQLite sorts NULL first in DESC).
SORT_ORDERS = {
"last_used_desc": "last_used_at IS NULL, last_used_at DESC, id DESC",
"created_desc": "created_at DESC, id DESC",
"created_asc": "created_at ASC, id ASC",
"run_count_desc": (
"run_count DESC, last_used_at IS NULL, last_used_at DESC, id DESC"
),
"rating_desc": "rating IS NULL, rating DESC, id DESC",
"rating_asc": "rating IS NULL, rating ASC, id DESC",
"text_asc": "text COLLATE NOCASE ASC, id ASC",
"text_desc": "text COLLATE NOCASE DESC, id DESC",
}
DEFAULT_SORT = "created_desc"
def order_by_clause(sort: Optional[str]) -> str:
"""Return a whitelisted ORDER BY expression for a UI sort key."""
return SORT_ORDERS.get(sort or DEFAULT_SORT, SORT_ORDERS[DEFAULT_SORT])
LIKE_ESCAPE = "\\"
def escape_like(term: str) -> str:
"""Escape LIKE wildcards in user text; use with ``LIKE ? ESCAPE '\\'``."""
return (
term.replace(LIKE_ESCAPE, LIKE_ESCAPE + LIKE_ESCAPE)
.replace("%", LIKE_ESCAPE + "%")
.replace("_", LIKE_ESCAPE + "_")
)
def _resolve_db_path(db_path: Optional[str] = None) -> str:
"""Resolve the database path from config, falling back to defaults.
When no explicit path is given, reads PromptManagerConfig.DEFAULT_DB_PATH
(set via config.json). Relative paths are resolved against the extension
root directory so the database location is predictable regardless of the
process working directory (important for Docker deployments).
Args:
db_path: Explicit database path, or None to use config/default.
Returns:
Absolute path to the SQLite database file.
"""
extension_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
if db_path is None:
try:
from py.config import PromptManagerConfig
db_path = PromptManagerConfig.DEFAULT_DB_PATH
except Exception:
db_path = "prompts.db"
if not os.path.isabs(db_path):
db_path = os.path.join(extension_root, db_path)
# Ensure parent directory exists for custom paths
parent = os.path.dirname(db_path)
if parent:
os.makedirs(parent, exist_ok=True)
return db_path
class PromptDatabase:
"""Database operations class for managing prompts."""
def __init__(self, db_path: Optional[str] = None):
"""
Initialize the database operations.
Args:
db_path: Path to the SQLite database file. If None, resolves from
config.json or defaults to prompts.db in the extension root.
"""
self.logger = get_logger("prompt_manager.database")
db_path = _resolve_db_path(db_path)
self.logger.debug(f"Initializing database operations with path: {db_path}")
self.model = PromptModel(db_path)
self.logger.debug("Database operations initialized successfully")
def close(self) -> None:
"""Close the calling thread's database connection (see PromptModel.close)."""
self.model.close()
def close_all(self) -> None:
"""Close every thread's connection (see PromptModel.close_all)."""
self.model.close_all()
def save_prompt(
self,
text: str,
category: Optional[str] = None,
tags: Optional[List[str]] = None,
rating: Optional[int] = None,
notes: Optional[str] = None,
prompt_hash: Optional[str] = None,
) -> int:
"""
Save a new prompt to the database.
Args:
text: The prompt text
category: Optional category
tags: List of tags
rating: Rating 1-5
notes: Optional notes
prompt_hash: SHA256 hash of the prompt
Returns:
int: The ID of the saved prompt
Raises:
ValueError: If required parameters are invalid
sqlite3.Error: If database operation fails
"""
if not text or not text.strip():
raise ValueError("Prompt text cannot be empty")
if rating is not None and (rating < 1 or rating > 5):
raise ValueError("Rating must be between 1 and 5")
self.logger.debug(
f"Saving prompt: text_length={len(text)}, category={category}, "
f"tags={tags}, rating={rating}"
)
try:
with self.model.get_connection() as conn:
cursor = conn.execute(
"""
INSERT INTO prompts (
text, category, tags, rating, notes, hash, created_at,
updated_at
) VALUES (?, ?, NULL, ?, ?, ?, ?, ?)
""",
(
text.strip(),
category,
rating,
notes,
prompt_hash,
datetime.datetime.now(datetime.timezone.utc).isoformat(),
datetime.datetime.now(datetime.timezone.utc).isoformat(),
),
)
prompt_id = cursor.lastrowid
if tags:
self._sync_prompt_tags(conn, prompt_id, tags)
conn.commit()
self.logger.debug(f"Successfully saved prompt with ID: {prompt_id}")
return prompt_id
except sqlite3.IntegrityError:
# Another caller inserted the same hash between the caller's
# duplicate check and this INSERT (the with-block rolled back).
existing = self.get_prompt_by_hash(prompt_hash) if prompt_hash else None
if existing is None:
raise
self.logger.debug(
f"Prompt with hash {prompt_hash} was saved concurrently; "
f"returning existing ID {existing['id']}"
)
return existing["id"]
def record_prompt_use(self, prompt_id: int, times: int = 1) -> bool:
"""
Count runs of a prompt and mark it as most recently used.
Args:
prompt_id: The prompt ID
times: Number of runs to add (queued runs counted on first save)
Returns:
True if the prompt exists and was updated
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
"UPDATE prompts SET run_count = run_count + ?, last_used_at = ?"
" WHERE id = ?",
(max(1, int(times)), utc_now_iso(), prompt_id),
)
conn.commit()
return cursor.rowcount > 0
def get_prompt_by_id(self, prompt_id: int) -> Optional[Dict[str, Any]]:
"""
Get a prompt by its ID.
Args:
prompt_id: The prompt ID
Returns:
Dict containing prompt data or None if not found
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
f"SELECT prompts.*, {TAG_SUBQUERY} FROM prompts WHERE id = ?",
(prompt_id,),
)
row = cursor.fetchone()
return self._row_to_dict(row) if row else None
def get_prompt_by_hash(self, prompt_hash: str) -> Optional[Dict[str, Any]]:
"""
Get a prompt by its hash.
Args:
prompt_hash: SHA256 hash of the prompt
Returns:
Dict containing prompt data or None if not found
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
f"SELECT prompts.*, {TAG_SUBQUERY} FROM prompts WHERE hash = ?",
(prompt_hash,),
)
row = cursor.fetchone()
return self._row_to_dict(row) if row else None
def search_prompts(
self,
text: Optional[str] = None,
category: Optional[str] = None,
tags: Optional[List[str]] = None,
rating_min: Optional[int] = None,
rating_max: Optional[int] = None,
date_from: Optional[str] = None,
date_to: Optional[str] = None,
folder: Optional[str] = None,
limit: int = 100,
offset: int = 0,
tag_partial: bool = False,
sort: Optional[str] = None,
) -> List[Dict[str, Any]]:
"""
Search prompts with various filters.
Args:
text: Text to search for in prompt content
category: Filter by category
tags: Filter by tags (must contain all specified tags)
rating_min: Minimum rating filter
rating_max: Maximum rating filter
date_from: Start date filter (ISO format)
date_to: End date filter (ISO format)
folder: Filter by subfolder name in generated image paths
limit: Maximum number of results
offset: Number of results to skip
tag_partial: Use LIKE matching for tags instead of exact match
sort: Sort key from SORT_ORDERS (default: newest first)
Returns:
List of dictionaries containing prompt data
"""
query_parts = [f"SELECT prompts.*, {TAG_SUBQUERY} FROM prompts WHERE 1=1"]
params = []
if text:
query_parts.append("AND text LIKE ? ESCAPE '\\'")
params.append(f"%{escape_like(text)}%")
if category:
query_parts.append("AND category = ?")
params.append(category)
if tags:
for tag in tags:
if tag_partial:
query_parts.append(
"AND prompts.id IN ("
" SELECT pt.prompt_id FROM prompt_tags pt"
" JOIN tags t ON pt.tag_id = t.id"
" WHERE t.name LIKE ? ESCAPE '\\')"
)
params.append(f"%{escape_like(tag)}%")
else:
query_parts.append(
"AND prompts.id IN ("
" SELECT pt.prompt_id FROM prompt_tags pt"
" JOIN tags t ON pt.tag_id = t.id WHERE t.name = ?)"
)
params.append(tag)
if folder:
# Escape LIKE wildcards in the folder name
safe_folder = (
folder.replace("\\", "\\\\").replace("%", "\\%").replace("_", "\\_")
)
query_parts.append(
"AND prompts.id IN ("
" SELECT DISTINCT prompt_id FROM generated_images"
" WHERE image_path LIKE ? ESCAPE '\\'"
" OR image_path LIKE ? ESCAPE '\\'"
" OR image_path LIKE ? ESCAPE '\\'"
")"
)
# Pattern 1: folder between forward slashes (Unix + normalized Windows)
params.append(f"%/{safe_folder}/%")
# Pattern 2: folder between backslashes (Windows native)
params.append(f"%\\\\{safe_folder}\\\\%")
# Pattern 3: folder at start of a relative path
params.append(f"{safe_folder}/%")
if rating_min is not None:
query_parts.append("AND rating >= ?")
params.append(rating_min)
if rating_max is not None:
query_parts.append("AND rating <= ?")
params.append(rating_max)
if date_from:
query_parts.append("AND created_at >= ?")
params.append(date_from)
if date_to:
query_parts.append("AND created_at <= ?")
params.append(date_to)
query_parts.append(f"ORDER BY {order_by_clause(sort)} LIMIT ? OFFSET ?")
params.extend([limit, offset])
query = " ".join(query_parts)
with self.model.get_connection() as conn:
cursor = conn.execute(query, params)
rows = cursor.fetchall()
prompts = [self._row_to_dict(row) for row in rows]
if prompts:
prompt_ids = [p["id"] for p in prompts]
self._attach_preview_images(conn, prompts, prompt_ids)
return prompts
def get_recent_prompts(
self, limit: int = 10, offset: int = 0, sort: Optional[str] = None
) -> Dict[str, Any]:
"""
Get the most recent prompts with pagination support.
Args:
limit: Maximum number of prompts to return
offset: Number of prompts to skip (for pagination)
sort: Sort key from SORT_ORDERS (default: newest first)
Returns:
Dictionary containing prompt data and pagination info
"""
with self.model.get_connection() as conn:
# Get total count
cursor = conn.execute("SELECT COUNT(*) FROM prompts")
row = cursor.fetchone()
total_count = (row[0] if row else 0) or 0
# Get paginated results
cursor = conn.execute(
f"SELECT prompts.*, {TAG_SUBQUERY} FROM prompts"
f" ORDER BY {order_by_clause(sort)} LIMIT ? OFFSET ?",
(limit, offset),
)
rows = cursor.fetchall()
prompts = [self._row_to_dict(row) for row in rows]
if prompts:
prompt_ids = [p["id"] for p in prompts]
self._attach_preview_images(conn, prompts, prompt_ids)
return {
"prompts": prompts,
"total": total_count,
"limit": limit,
"offset": offset,
"has_more": (offset + limit) < total_count,
"page": (offset // limit) + 1,
"total_pages": (total_count + limit - 1) // limit, # Ceiling division
}
def get_prompts_by_category(
self, category: str, limit: int = 100
) -> List[Dict[str, Any]]:
"""
Get all prompts in a specific category.
Args:
category: The category name
limit: Maximum number of prompts to return
Returns:
List of dictionaries containing prompt data
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
f"SELECT prompts.*, {TAG_SUBQUERY} FROM prompts WHERE category = ? "
"ORDER BY created_at DESC LIMIT ?",
(category, limit),
)
rows = cursor.fetchall()
return [self._row_to_dict(row) for row in rows]
def get_top_rated_prompts(self, limit: int = 10) -> List[Dict[str, Any]]:
"""
Get the highest rated prompts.
Args:
limit: Maximum number of prompts to return
Returns:
List of dictionaries containing prompt data
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
f"""
SELECT prompts.*, {TAG_SUBQUERY} FROM prompts
WHERE rating IS NOT NULL
ORDER BY rating DESC, created_at DESC
LIMIT ?
""",
(limit,),
)
rows = cursor.fetchall()
return [self._row_to_dict(row) for row in rows]
def update_prompt_metadata(
self,
prompt_id: int,
category: Optional[str] = None,
tags: Optional[List[str]] = None,
rating: Optional[int] = None,
notes: Optional[str] = None,
) -> bool:
"""
Update metadata for an existing prompt.
Args:
prompt_id: The prompt ID
category: New category
tags: New tags list
rating: New rating
notes: New notes
Returns:
bool: True if update was successful, False otherwise
"""
updates = []
params = []
if category is not None:
updates.append("category = ?")
params.append(category)
if rating is not None:
if rating < 1 or rating > 5:
raise ValueError("Rating must be between 1 and 5")
updates.append("rating = ?")
params.append(rating)
if notes is not None:
updates.append("notes = ?")
params.append(notes)
if not updates and tags is None:
return False
with self.model.get_connection() as conn:
if updates:
updates.append("updated_at = ?")
params.append(datetime.datetime.now(datetime.timezone.utc).isoformat())
params.append(prompt_id)
query = f"UPDATE prompts SET {', '.join(updates)} WHERE id = ?"
conn.execute(query, params)
if tags is not None:
self._sync_prompt_tags(conn, prompt_id, tags)
conn.execute(
"UPDATE prompts SET updated_at = ? WHERE id = ?",
(
datetime.datetime.now(datetime.timezone.utc).isoformat(),
prompt_id,
),
)
conn.commit()
return True
def delete_prompt(self, prompt_id: int) -> bool:
"""
Delete a prompt by its ID.
Args:
prompt_id: The prompt ID to delete
Returns:
bool: True if deletion was successful, False otherwise
"""
with self.model.get_connection() as conn:
# First delete related images to avoid foreign key constraint
conn.execute(
"DELETE FROM generated_images WHERE prompt_id = ?", (prompt_id,)
)
# Then delete the prompt
cursor = conn.execute("DELETE FROM prompts WHERE id = ?", (prompt_id,))
conn.commit()
return cursor.rowcount > 0
def delete_prompts_by_category(self, category: str) -> int:
"""Delete all prompts with the given category.
Returns:
Number of prompts deleted.
"""
with self.model.get_connection() as conn:
# Get IDs first for cascade cleanup
ids = [
r[0]
for r in conn.execute(
"SELECT id FROM prompts WHERE category = ?", (category,)
).fetchall()
]
if not ids:
return 0
placeholders = ",".join("?" * len(ids))
conn.execute(
f"DELETE FROM generated_images WHERE prompt_id IN ({placeholders})",
ids,
)
conn.execute(
f"DELETE FROM prompt_tags WHERE prompt_id IN ({placeholders})",
ids,
)
cursor = conn.execute(
f"DELETE FROM prompts WHERE id IN ({placeholders})",
ids,
)
conn.commit()
return cursor.rowcount
def get_all_categories(self) -> List[str]:
"""
Get all unique categories from the database.
Returns:
List of category names
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
"SELECT DISTINCT TRIM(category) as category FROM prompts WHERE "
"category IS NOT NULL AND TRIM(category) != '' ORDER BY category"
)
return [row["category"] for row in cursor.fetchall()]
def get_prompt_subfolders(
self,
root_dirs: Optional[List[str]] = None,
include_ancestors: bool = False,
) -> List[str]:
"""
Get distinct subfolder paths from generated_images.
Extracts the directory portion of image_path, made relative to
root_dirs if provided. Returns sorted unique folder names.
Args:
root_dirs: Gallery root directories for computing relative paths
include_ancestors: If True, also include all ancestor path segments
so that hierarchical tree navigation works. For example, a path
``2026/08-Aug/2026-08-06`` also adds ``2026`` and ``2026/08-Aug``.
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
"SELECT DISTINCT image_path FROM generated_images "
"WHERE image_path IS NOT NULL AND image_path != ''"
)
folders = set()
for row in cursor.fetchall():
image_path = row["image_path"]
parent = os.path.dirname(image_path)
if not parent:
continue
made_relative = False
if root_dirs:
for root in root_dirs:
try:
rel = os.path.relpath(parent, root)
if not rel.startswith(".."):
if rel != ".":
folders.add(rel)
made_relative = True
break
except ValueError:
continue
if not made_relative:
# Preserve full relative-style path instead of collapsing
# to just the basename, which loses hierarchy and creates
# ambiguity (e.g. foo/bar and baz/bar both become "bar").
folders.add(parent)
if include_ancestors:
ancestors = set()
for folder in folders:
parts = folder.replace("\\", "/").split("/")
for i in range(1, len(parts)):
ancestors.add("/".join(parts[:i]))
folders.update(ancestors)
return sorted(folders)
def get_all_tags(self) -> List[str]:
"""
Get all unique tags that are in use (linked to at least one prompt).
Returns:
Sorted list of tag names
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
"SELECT DISTINCT t.name AS tag "
"FROM prompt_tags pt "
"JOIN tags t ON pt.tag_id = t.id "
"ORDER BY t.name"
)
return [row["tag"] for row in cursor.fetchall()]
def get_tags_with_counts(
self,
limit: int = 50,
offset: int = 0,
search: Optional[str] = None,
sort: str = "alpha_asc",
) -> Dict[str, Any]:
"""
Get all unique tags with their usage counts via junction table.
Args:
limit: Maximum number of tags to return
offset: Number of tags to skip
search: Optional case-insensitive substring filter
sort: Sort order - alpha_asc, alpha_desc, count_desc, count_asc
Returns:
Dict with tags list, total count, and pagination info
"""
search_clause = ""
params: list = []
if search:
search_clause = "HAVING t.name LIKE ? ESCAPE '\\'"
params.append(f"%{escape_like(search)}%")
sort_map = {
"alpha_desc": "tag COLLATE NOCASE DESC",
"count_desc": "count DESC, tag COLLATE NOCASE ASC",
"count_asc": "count ASC, tag COLLATE NOCASE ASC",
}
order = sort_map.get(sort, "tag COLLATE NOCASE ASC")
with self.model.get_connection() as conn:
count_sql = (
"SELECT COUNT(*) as total FROM ("
" SELECT t.name AS tag, COUNT(*) AS count"
" FROM prompt_tags pt JOIN tags t ON pt.tag_id = t.id"
f" GROUP BY t.name {search_clause}"
")"
)
cursor = conn.execute(count_sql, params)
row = cursor.fetchone()
total = (row[0] if row else 0) or 0
data_sql = (
"SELECT t.name AS tag, COUNT(*) AS count"
" FROM prompt_tags pt JOIN tags t ON pt.tag_id = t.id"
f" GROUP BY t.name {search_clause}"
f" ORDER BY {order}"
" LIMIT ? OFFSET ?"
)
cursor = conn.execute(data_sql, params + [limit, offset])
tags = [
{"name": row["tag"], "count": row["count"]} for row in cursor.fetchall()
]
return {
"tags": tags,
"total": total,
"limit": limit,
"offset": offset,
"has_more": (offset + limit) < total,
}
def get_prompts_by_tags(
self, tags: List[str], mode: str = "and", limit: int = 20, offset: int = 0
) -> Dict[str, Any]:
"""
Get prompts that match the given tags with AND/OR filtering.
Uses junction table for precise tag matching and a batched image
fetch to avoid N+1 queries.
Args:
tags: List of tag names to filter by
mode: 'and' (must have all tags) or 'or' (must have any tag)
limit: Maximum number of prompts to return
offset: Number of prompts to skip
Returns:
Dict with prompts list (including preview images), total count, pagination
"""
if not tags:
return {
"prompts": [],
"total": 0,
"limit": limit,
"offset": offset,
"has_more": False,
}
with self.model.get_connection() as conn:
placeholders = ",".join(["?"] * len(tags))
if mode == "and":
where_clause = (
"prompts.id IN ("
" SELECT pt.prompt_id FROM prompt_tags pt"
" JOIN tags t ON pt.tag_id = t.id"
f" WHERE t.name IN ({placeholders})"
" GROUP BY pt.prompt_id"
f" HAVING COUNT(DISTINCT t.name) = ?"
")"
)
tag_params = list(tags) + [len(tags)]
else:
where_clause = (
"prompts.id IN ("
" SELECT pt.prompt_id FROM prompt_tags pt"
" JOIN tags t ON pt.tag_id = t.id"
f" WHERE t.name IN ({placeholders})"
")"
)
tag_params = list(tags)
cursor = conn.execute(
f"SELECT COUNT(*) FROM prompts WHERE {where_clause}",
tag_params,
)
row = cursor.fetchone()
total = (row[0] if row else 0) or 0
cursor = conn.execute(
f"SELECT prompts.*, {TAG_SUBQUERY} FROM prompts WHERE {where_clause} "
"ORDER BY created_at DESC LIMIT ? OFFSET ?",
tag_params + [limit, offset],
)
rows = cursor.fetchall()
prompts = [self._row_to_dict(row) for row in rows]
if prompts:
prompt_ids = [p["id"] for p in prompts]
self._attach_preview_images(conn, prompts, prompt_ids)
return {
"prompts": prompts,
"total": total,
"limit": limit,
"offset": offset,
"has_more": (offset + limit) < total,
}
def rename_tag_all_prompts(self, old_name: str, new_name: str) -> Dict[str, Any]:
"""
Rename a tag across all prompts that use it.
With junction tables this is a single UPDATE or a merge operation.
Args:
old_name: Current tag name
new_name: New tag name
Returns:
Dict with success status and affected_count
"""
if not old_name or not old_name.strip():
raise ValueError("Old tag name cannot be empty")
if not new_name or not new_name.strip():
raise ValueError("New tag name cannot be empty")
old_name = old_name.strip()
new_name = new_name.strip()
with self.model.get_connection() as conn:
cursor = conn.execute("SELECT id FROM tags WHERE name = ?", (old_name,))
old_tag = cursor.fetchone()
if not old_tag:
return {"success": True, "affected_count": 0, "skipped_count": 0}
old_tag_id = old_tag["id"]
# Count affected prompts before the operation
cursor = conn.execute(
"SELECT COUNT(*) as c FROM prompt_tags WHERE tag_id = ?", (old_tag_id,)
)
affected = cursor.fetchone()["c"]
cursor = conn.execute("SELECT id FROM tags WHERE name = ?", (new_name,))
existing_new = cursor.fetchone()
if existing_new:
# Target tag exists — merge: move links, handle conflicts, delete old
new_tag_id = existing_new["id"]
conn.execute(
"UPDATE OR IGNORE prompt_tags SET tag_id = ? WHERE tag_id = ?",
(new_tag_id, old_tag_id),
)
# Delete remaining links (conflicts = prompt already had the target tag)
conn.execute("DELETE FROM prompt_tags WHERE tag_id = ?", (old_tag_id,))
conn.execute("DELETE FROM tags WHERE id = ?", (old_tag_id,))
else:
# Simple rename
conn.execute(
"UPDATE tags SET name = ? WHERE id = ?", (new_name, old_tag_id)
)
conn.commit()
self.logger.info(
f"Renamed tag '{old_name}' -> '{new_name}' in {affected} prompts"
)
return {"success": True, "affected_count": affected, "skipped_count": 0}
def delete_tag_all_prompts(self, tag_name: str) -> Dict[str, Any]:
"""
Remove a tag from all prompts that use it.
With junction tables, deleting from the tags table cascades to prompt_tags.
Args:
tag_name: Tag name to remove
Returns:
Dict with success status and affected_count
"""
if not tag_name or not tag_name.strip():
raise ValueError("Tag name cannot be empty")
tag_name = tag_name.strip()
with self.model.get_connection() as conn:
cursor = conn.execute("SELECT id FROM tags WHERE name = ?", (tag_name,))
tag_row = cursor.fetchone()
if not tag_row:
return {"success": True, "affected_count": 0, "skipped_count": 0}
tag_id = tag_row["id"]
cursor = conn.execute(
"SELECT COUNT(*) as c FROM prompt_tags WHERE tag_id = ?", (tag_id,)
)
affected = cursor.fetchone()["c"]
# CASCADE delete handles prompt_tags entries
conn.execute("DELETE FROM tags WHERE id = ?", (tag_id,))
conn.commit()
self.logger.info(f"Deleted tag '{tag_name}' from {affected} prompts")
return {"success": True, "affected_count": affected, "skipped_count": 0}
def merge_tags(self, source_tags: List[str], target_tag: str) -> Dict[str, Any]:
"""
Merge one or more source tags into a target tag across all prompts.
With junction tables, this is UPDATE + DELETE per source tag.
Args:
source_tags: List of tag names to merge from
target_tag: Tag name to merge into
Returns:
Dict with success status, affected_count, and tags_merged
"""
if not source_tags:
raise ValueError("Source tags list cannot be empty")
if not target_tag or not target_tag.strip():
raise ValueError("Target tag cannot be empty")
target_tag = target_tag.strip()
source_tags = [t.strip() for t in source_tags if t.strip()]
affected = 0
tags_merged = 0
with self.model.get_connection() as conn:
# Ensure target tag exists
conn.execute("INSERT OR IGNORE INTO tags (name) VALUES (?)", (target_tag,))
cursor = conn.execute("SELECT id FROM tags WHERE name = ?", (target_tag,))
target_id = cursor.fetchone()["id"]
for src_tag in source_tags:
cursor = conn.execute("SELECT id FROM tags WHERE name = ?", (src_tag,))
src_row = cursor.fetchone()
if not src_row:
continue
src_id = src_row["id"]
cursor = conn.execute(
"SELECT COUNT(*) as c FROM prompt_tags WHERE tag_id = ?", (src_id,)
)
src_count = cursor.fetchone()["c"]
if src_count > 0:
# Move links from source to target (ignore conflicts)
conn.execute(
"UPDATE OR IGNORE prompt_tags SET tag_id = ? WHERE tag_id = ?",
(target_id, src_id),
)
# Delete remaining (conflicts = prompt already had target tag)
conn.execute("DELETE FROM prompt_tags WHERE tag_id = ?", (src_id,))
tags_merged += 1
affected += src_count
# Delete the source tag
conn.execute("DELETE FROM tags WHERE id = ?", (src_id,))
conn.commit()
self.logger.info(
f"Merged {tags_merged} tags into '{target_tag}', affected {affected} "
"prompts"
)
return {
"success": True,
"affected_count": affected,
"tags_merged": tags_merged,
"skipped_count": 0,
}
def get_untagged_prompts_count(self) -> int:
"""
Get the count of prompts that have no tags.
Returns:
Number of untagged prompts
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
"SELECT COUNT(*) as total FROM prompts "
"WHERE NOT EXISTS (SELECT 1 FROM prompt_tags WHERE prompt_id = "
"prompts.id)"
)
return cursor.fetchone()["total"]
def get_untagged_prompts(self, limit: int = 20, offset: int = 0) -> Dict[str, Any]:
"""
Get prompts that have no tags, with pagination.
Uses batched image fetch to avoid N+1 queries.
Args:
limit: Maximum number of prompts to return
offset: Number of prompts to skip
Returns:
Dict with prompts list, total count, and pagination
"""
with self.model.get_connection() as conn:
where = (
"NOT EXISTS (SELECT 1 FROM prompt_tags WHERE prompt_id = prompts.id)"
)
cursor = conn.execute(
f"SELECT COUNT(*) as total FROM prompts WHERE {where}"
)
total = cursor.fetchone()["total"]
cursor = conn.execute(
f"SELECT prompts.*, {TAG_SUBQUERY} FROM prompts WHERE {where} "
"ORDER BY created_at DESC LIMIT ? OFFSET ?",
(limit, offset),
)
rows = cursor.fetchall()
prompts = [self._row_to_dict(row) for row in rows]
if prompts:
prompt_ids = [p["id"] for p in prompts]
self._attach_preview_images(conn, prompts, prompt_ids)
return {
"prompts": prompts,
"total": total,
"limit": limit,
"offset": offset,
"has_more": (offset + limit) < total,
}
def _attach_preview_images(
self,
conn: sqlite3.Connection,
prompts: List[Dict[str, Any]],
prompt_ids: List[int],
) -> None:
"""Batch-fetch up to 3 preview images + counts for a list of prompts."""
id_placeholders = ",".join(["?"] * len(prompt_ids))
img_cursor = conn.execute(
f"""SELECT * FROM (
SELECT id, prompt_id, image_path, filename,
generation_time, width, height, format,
ROW_NUMBER() OVER (
PARTITION BY prompt_id ORDER BY generation_time DESC
) AS rn
FROM generated_images
WHERE prompt_id IN ({id_placeholders})
) WHERE rn <= 3""",
prompt_ids,
)
images_by_prompt: Dict[int, list] = {}
for img_row in img_cursor.fetchall():
pid = img_row["prompt_id"]
images_by_prompt.setdefault(pid, []).append(dict(img_row))
cnt_cursor = conn.execute(
f"SELECT prompt_id, COUNT(*) as cnt FROM generated_images "
f"WHERE prompt_id IN ({id_placeholders}) GROUP BY prompt_id",
prompt_ids,
)
counts_by_prompt = {
row["prompt_id"]: row["cnt"] for row in cnt_cursor.fetchall()
}
for prompt in prompts:
pid = prompt["id"]
prompt["images"] = images_by_prompt.get(pid, [])
prompt["image_count"] = counts_by_prompt.get(pid, 0)
def _ensure_tags(
self, conn: sqlite3.Connection, tag_names: List[str]
) -> Dict[str, int]:
"""Ensure tag names exist in tags table, return name->id mapping."""
if not tag_names:
return {}
for name in tag_names:
conn.execute("INSERT OR IGNORE INTO tags (name) VALUES (?)", (name,))
placeholders = ",".join(["?"] * len(tag_names))
cursor = conn.execute(
f"SELECT id, name FROM tags WHERE name IN ({placeholders})",
list(tag_names),
)
return {row["name"]: row["id"] for row in cursor.fetchall()}
def _sync_prompt_tags(
self, conn: sqlite3.Connection, prompt_id: int, tags: List[str]
) -> None:
"""Replace all junction table entries for a prompt."""
conn.execute("DELETE FROM prompt_tags WHERE prompt_id = ?", (prompt_id,))
if tags:
tag_map = self._ensure_tags(conn, tags)
for tag_name in tags:
tag_id = tag_map.get(tag_name)
if tag_id:
conn.execute(
"INSERT OR IGNORE INTO prompt_tags (prompt_id, tag_id) "
"VALUES (?, ?)",
(prompt_id, tag_id),
)
def _get_prompt_tags(self, conn: sqlite3.Connection, prompt_id: int) -> List[str]:
"""Get tag names for a prompt from junction table."""
cursor = conn.execute(
"SELECT t.name FROM prompt_tags pt "
"JOIN tags t ON pt.tag_id = t.id "
"WHERE pt.prompt_id = ?",
(prompt_id,),
)
return [row["name"] for row in cursor.fetchall()]
def _row_to_dict(self, row: sqlite3.Row) -> Dict[str, Any]:
"""
Convert a database row to a dictionary with parsed JSON fields.
Args:
row: SQLite row object
Returns:
Dictionary representation of the row
"""
data = dict(row)
# Parse tags from junction table subquery result (preferred)
if "_tag_list" in data and data["_tag_list"]:
data["tags"] = data["_tag_list"].split("|||")
del data["_tag_list"]
elif "_tag_list" in data:
# TAG_SUBQUERY present but NULL (no tags)
data["tags"] = []
del data["_tag_list"]
elif data.get("tags"):
# Fallback: parse legacy JSON column
try:
parsed = json.loads(data["tags"])
if isinstance(parsed, list):
data["tags"] = parsed
elif isinstance(parsed, str):
data["tags"] = [t.strip() for t in parsed.split(",") if t.strip()]
else:
data["tags"] = []
except (json.JSONDecodeError, TypeError):
data["tags"] = []
else:
data["tags"] = []
return data
def export_prompts(self, file_path: str, format: str = "json") -> bool:
"""
Export all prompts to a file.
Args:
file_path: Path to save the export file
format: Export format ("json" or "csv")
Returns:
bool: True if export was successful, False otherwise
"""
try:
prompts = self.search_prompts(limit=10000) # Get all prompts
if format.lower() == "json":
with open(file_path, "w", encoding="utf-8") as f:
json.dump(prompts, f, indent=2, ensure_ascii=False)
elif format.lower() == "csv":
import csv
if prompts:
with open(file_path, "w", newline="", encoding="utf-8") as f:
writer = csv.DictWriter(f, fieldnames=prompts[0].keys())
writer.writeheader()
for prompt in prompts:
# Convert lists to strings for CSV
row = prompt.copy()
if isinstance(row.get("tags"), list):
row["tags"] = ", ".join(row["tags"])
writer.writerow(row)
else:
raise ValueError(f"Unsupported export format: {format}")
return True
except Exception as e:
self.logger.error(f"Error exporting prompts: {e}")
return False
def cleanup_duplicates(self) -> int:
"""
Remove duplicate prompts based on text content, preserving all image links.
Merges metadata and transfers images to the retained prompt.
Returns:
int: Number of duplicates removed
"""
self.logger.info("Starting duplicate cleanup process with image preservation")
try:
with self.model.get_connection() as conn:
# Find duplicates by text content (case-insensitive)
# Note: Removed ORDER BY from GROUP_CONCAT for SQLite compatibility
# We'll sort the IDs manually after fetching
cursor = conn.execute("""
SELECT LOWER(TRIM(text)) as normalized_text, COUNT(*) as count,
GROUP_CONCAT(id) as ids,
GROUP_CONCAT(created_at) as created_dates
FROM prompts
GROUP BY LOWER(TRIM(text))
HAVING COUNT(*) > 1
""")
duplicates = cursor.fetchall()
self.logger.debug(
f"Found {len(duplicates)} groups of duplicate prompts"
)
total_removed = 0
total_images_transferred = 0
for duplicate in duplicates:
ids = duplicate["ids"].split(",")
created_dates = duplicate["created_dates"].split(",")
# Sort IDs by created_at date to keep the oldest
id_date_pairs = list(zip(ids, created_dates))
id_date_pairs.sort(key=lambda x: x[1]) # Sort by date
sorted_ids = [int(pair[0]) for pair in id_date_pairs]
# Keep the oldest one (first), merge and delete the rest
primary_id = sorted_ids[0] # Keep the oldest
duplicate_ids = sorted_ids[1:]
self.logger.debug(
f"Merging duplicates: keeping {primary_id}, removing "
f"{duplicate_ids}"
)
# Get primary prompt details
cursor = conn.execute(
"SELECT * FROM prompts WHERE id = ?", (primary_id,)
)
primary_prompt = cursor.fetchone()
if not primary_prompt:
continue
# Collect and merge metadata from all duplicates
merged_metadata = self._merge_duplicate_metadata(
conn, primary_id, duplicate_ids
)
# Transfer all images from duplicates to primary prompt
images_transferred = self._transfer_images_to_primary(
conn, primary_id, duplicate_ids
)
total_images_transferred += images_transferred
# Update primary prompt with merged metadata
if merged_metadata:
self._update_primary_with_merged_metadata(
conn, primary_id, merged_metadata
)
# Delete duplicate prompts (images already transferred)
for duplicate_id in duplicate_ids:
conn.execute(
"DELETE FROM prompts WHERE id = ?", (duplicate_id,)
)
total_removed += 1
self.logger.debug(f"Removed duplicate prompt {duplicate_id}")
conn.commit()
if total_removed > 0:
self.logger.info(
f"Removed {total_removed} duplicate prompts, transferred "
f"{total_images_transferred} images"
)
else:
self.logger.info("No duplicate prompts found")
return total_removed
except Exception as e:
self.logger.error(f"Error cleaning up duplicates: {e}", exc_info=True)
return 0
# Gallery-related methods
def link_image_to_prompt(
self, prompt_id: str, image_path: str, metadata: Optional[Dict[str, Any]] = None
) -> int:
"""
Link a generated image to a prompt.
Args:
prompt_id: ID of the prompt that generated this image
image_path: Full path to the image file
metadata: Optional metadata about the image
Returns:
int: The ID of the created image record
"""
# Validate that prompt_id is a valid integer and exists in prompts table
try:
# Convert prompt_id to integer if it's a string number
if isinstance(prompt_id, str) and prompt_id.isdigit():
prompt_id_int = int(prompt_id)
elif isinstance(prompt_id, int):
prompt_id_int = prompt_id
else:
# Handle temporary IDs like "temp_123456" - skip linking
if isinstance(prompt_id, str) and prompt_id.startswith("temp_"):
self.logger.debug(
f"Skipping image linking for temporary prompt ID: {prompt_id}"
)
return 0
else:
self.logger.warning(
f"Invalid prompt_id format: {prompt_id}, skipping image linking"
)
return 0
# Verify the prompt exists in the database
with self.model.get_connection() as conn:
cursor = conn.execute(
"SELECT id FROM prompts WHERE id = ?", (prompt_id_int,)
)
if not cursor.fetchone():
self.logger.warning(
f"Prompt ID {prompt_id_int} not found in database, skipping "
"image linking"
)
return 0
# Proceed with linking
filename = os.path.basename(image_path)
file_path = normalize_image_path(image_path)
file_info = metadata.get("file_info", {}) if metadata else {}
# INSERT OR IGNORE skips a file already linked to this prompt
# (same prompt_id + normalised full path)
cursor = conn.execute(
"""
INSERT OR IGNORE INTO generated_images
(prompt_id, image_path, filename, file_path, file_size, width,
height, format, workflow_data, prompt_metadata, parameters)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
""",
(
prompt_id_int,
image_path,
filename,
file_path,
file_info.get("size"),
(
file_info.get("dimensions", [None, None])[0]
if file_info.get("dimensions")
else None
),
(
file_info.get("dimensions", [None, None])[1]
if file_info.get("dimensions")
else None
),
file_info.get("format"),
json.dumps(metadata.get("workflow", {}) if metadata else {}),
json.dumps(metadata.get("prompt", {}) if metadata else {}),
json.dumps(metadata.get("parameters", {}) if metadata else {}),
),
)
conn.commit()
if cursor.rowcount == 0:
self.logger.debug(
f"Image {file_path} already linked to prompt {prompt_id_int}"
)
return 0
return cursor.lastrowid
except Exception as e:
self.logger.error(f"Error linking image to prompt {prompt_id}: {e}")
return 0
def get_prompt_images(self, prompt_id: str) -> List[Dict[str, Any]]:
"""
Get all images associated with a prompt.
Args:
prompt_id: The prompt ID
Returns:
List of image records
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
"""
SELECT * FROM generated_images
WHERE prompt_id = ?
ORDER BY generation_time DESC
""",
(prompt_id,),
)
return [self._image_row_to_dict(row) for row in cursor.fetchall()]
def get_recent_images(
self, limit: int = 50, offset: int = 0
) -> List[Dict[str, Any]]:
"""
Get recently generated images across all prompts, newest first.
Args:
limit: Maximum number of images to return
offset: Number of newest images to skip (paging)
Returns:
List of image records with prompt text
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
"""
SELECT gi.*, p.text as prompt_text
FROM generated_images gi
LEFT JOIN prompts p ON gi.prompt_id = p.id
ORDER BY gi.generation_time DESC
LIMIT ? OFFSET ?
""",
(int(limit), max(0, int(offset))),
)
return [self._image_row_to_dict(row) for row in cursor.fetchall()]
def get_all_images(
self,
limit: int = 0,
offset: int = 0,
) -> List[Dict[str, Any]]:
"""
Get generated images with their linked prompts.
Args:
limit: Maximum number of images to return (0 = all).
offset: Number of images to skip.
Returns:
List of image records with prompt text and tags
"""
sql = (
"SELECT gi.*, p.text as prompt_text, "
"(SELECT GROUP_CONCAT(t.name, '|||') FROM prompt_tags pt "
"JOIN tags t ON pt.tag_id = t.id WHERE pt.prompt_id = p.id) AS "
"_prompt_tags_list "
"FROM generated_images gi "
"INNER JOIN prompts p ON gi.prompt_id = p.id "
"WHERE gi.image_path IS NOT NULL AND gi.image_path != '' "
"ORDER BY gi.generation_time DESC"
)
params: list = []
if limit > 0:
sql += " LIMIT ? OFFSET ?"
params = [limit, offset]
with self.model.get_connection() as conn:
cursor = conn.execute(sql, params)
rows = cursor.fetchall()
result = []
for row in rows:
data = self._image_row_to_dict(row)
if row["_prompt_tags_list"]:
data["prompt_tags"] = row["_prompt_tags_list"].split("|||")
else:
data["prompt_tags"] = []
result.append(data)
return result
def search_images_by_prompt(
self, search_term: str, limit: Optional[int] = None, offset: int = 0
) -> List[Dict[str, Any]]:
"""
Search images by prompt text, newest first.
Args:
search_term: Text to search for in prompt content
limit: Maximum number of images to return (None for no limit)
offset: Number of newest matches to skip (paging)
Returns:
List of image records with prompt text
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
"""
SELECT gi.*, p.text as prompt_text
FROM generated_images gi
JOIN prompts p ON gi.prompt_id = p.id
WHERE p.text LIKE ? ESCAPE '\\'
ORDER BY gi.generation_time DESC
LIMIT ? OFFSET ?
""",
(
f"%{escape_like(search_term)}%",
-1 if limit is None else int(limit),
max(0, int(offset)),
),
)
return [self._image_row_to_dict(row) for row in cursor.fetchall()]
def get_image_by_id(self, image_id: int) -> Optional[Dict[str, Any]]:
"""
Get an image record by its ID.
Args:
image_id: The image ID
Returns:
Image record or None if not found
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
"SELECT * FROM generated_images WHERE id = ?", (image_id,)
)
row = cursor.fetchone()
return self._image_row_to_dict(row) if row else None
def delete_image(self, image_id: int) -> bool:
"""
Delete an image record by its ID.
Args:
image_id: The image ID to delete
Returns:
bool: True if deletion was successful
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
"DELETE FROM generated_images WHERE id = ?", (image_id,)
)
conn.commit()
return cursor.rowcount > 0
def cleanup_missing_images(self) -> int:
"""
Remove image records where the actual file no longer exists.
Returns:
int: Number of orphaned records removed
"""
removed_count = 0
with self.model.get_connection() as conn:
cursor = conn.execute("SELECT id, image_path FROM generated_images")
images = cursor.fetchall()
for image in images:
if not os.path.exists(image["image_path"]):
conn.execute(
"DELETE FROM generated_images WHERE id = ?", (image["id"],)
)
removed_count += 1
conn.commit()
return removed_count
def _clean_nan_values(self, obj: Any) -> Any:
"""
Recursively clean NaN values from nested data structures.
Args:
obj: The object to clean (dict, list, or scalar)
Returns:
Cleaned object with NaN values replaced by None
"""
if isinstance(obj, dict):
return {key: self._clean_nan_values(value) for key, value in obj.items()}
elif isinstance(obj, list):
return [self._clean_nan_values(item) for item in obj]
elif isinstance(obj, float) and str(obj) == "nan":
return None
else:
return obj
def _merge_duplicate_metadata(
self, conn: sqlite3.Connection, primary_id: int, duplicate_ids: List[int]
) -> Dict[str, Any]:
"""
Merge metadata from duplicate prompts, prioritizing non-empty values.
Args:
conn: Database connection
primary_id: ID of the prompt to keep
duplicate_ids: List of duplicate prompt IDs
Returns:
Dict containing merged metadata
"""
try:
cursor = conn.execute(
"SELECT category, rating, notes FROM prompts WHERE id = ?",
(primary_id,),
)
primary_data = cursor.fetchone()
if not primary_data:
return {}
merged = {
"category": primary_data["category"],
"tags": self._get_prompt_tags(conn, primary_id),
"rating": primary_data["rating"],
"notes": primary_data["notes"] or "",
}
for dup_id in duplicate_ids:
cursor = conn.execute(
"SELECT category, rating, notes FROM prompts WHERE id = ?",
(dup_id,),
)
dup_data = cursor.fetchone()
if not dup_data:
continue
if not merged["category"] and dup_data["category"]:
merged["category"] = dup_data["category"]
dup_tags = self._get_prompt_tags(conn, dup_id)
for tag in dup_tags:
if tag not in merged["tags"]:
merged["tags"].append(tag)
if dup_data["rating"] and (
not merged["rating"] or dup_data["rating"] > merged["rating"]
):
merged["rating"] = dup_data["rating"]
if dup_data["notes"] and dup_data["notes"].strip():
if merged["notes"]:
merged["notes"] += f" | {dup_data['notes']}"
else:
merged["notes"] = dup_data["notes"]
return merged
except Exception as e:
self.logger.error(f"Error merging metadata: {e}", exc_info=True)
return {}
def _transfer_images_to_primary(
self, conn: sqlite3.Connection, primary_id: int, duplicate_ids: List[int]
) -> int:
"""
Transfer all images from duplicate prompts to the primary prompt.
Args:
conn: Database connection
primary_id: ID of the prompt to keep
duplicate_ids: List of duplicate prompt IDs
Returns:
Number of images transferred
"""
transferred_count = 0
try:
for dup_id in duplicate_ids:
# Update all images to point to primary prompt
cursor = conn.execute(
"UPDATE generated_images SET prompt_id = ? WHERE prompt_id = ?",
(primary_id, dup_id),
)
transferred_count += cursor.rowcount
if cursor.rowcount > 0:
self.logger.debug(
f"Transferred {cursor.rowcount} images from prompt {dup_id} "
f"to {primary_id}"
)
return transferred_count
except Exception as e:
self.logger.error(f"Error transferring images: {e}", exc_info=True)
return 0
def _update_primary_with_merged_metadata(
self, conn: sqlite3.Connection, primary_id: int, merged_metadata: Dict[str, Any]
) -> None:
"""
Update the primary prompt with merged metadata.
Args:
conn: Database connection
primary_id: ID of the prompt to update
merged_metadata: Merged metadata dictionary
"""
try:
conn.execute(
"""
UPDATE prompts
SET category = ?, rating = ?, notes = ?, updated_at = ?
WHERE id = ?
""",
(
merged_metadata.get("category"),
merged_metadata.get("rating"),
merged_metadata.get("notes"),
datetime.datetime.now(datetime.timezone.utc).isoformat(),
primary_id,
),
)
self._sync_prompt_tags(conn, primary_id, merged_metadata.get("tags", []))
self.logger.debug(
f"Updated primary prompt {primary_id} with merged metadata"
)
except Exception as e:
self.logger.error(
f"Error updating primary prompt metadata: {e}", exc_info=True
)
# ------------------------------------------------------------------
# Methods extracted from api.py raw SQL (Fix 3.1)
# ------------------------------------------------------------------
def get_statistics(self) -> Dict[str, Any]:
"""Get comprehensive database statistics."""
with self.model.get_connection() as conn:
cursor = conn.execute("SELECT COUNT(*) FROM prompts")
row = cursor.fetchone()
total_prompts = (row[0] if row else 0) or 0
cursor = conn.execute(
"SELECT COUNT(DISTINCT TRIM(category)) FROM prompts "
"WHERE category IS NOT NULL AND TRIM(category) != ''"
)
row = cursor.fetchone()
total_categories = (row[0] if row else 0) or 0
cursor = conn.execute(
"SELECT AVG(rating) FROM prompts WHERE rating IS NOT NULL"
)
row = cursor.fetchone()
avg_rating = row[0] if row else None
cursor = conn.execute(
"SELECT COUNT(*) FROM tags t "
"WHERE EXISTS (SELECT 1 FROM prompt_tags pt WHERE pt.tag_id = t.id)"
)
row = cursor.fetchone()
total_tags = (row[0] if row else 0) or 0
cursor = conn.execute("SELECT COUNT(*) FROM generated_images")
row = cursor.fetchone()
total_images = (row[0] if row else 0) or 0
cursor = conn.execute(
"SELECT COUNT(DISTINCT prompt_id) FROM generated_images"
)
row = cursor.fetchone()
images_with_prompts = (row[0] if row else 0) or 0
avg = round(avg_rating, 2) if avg_rating else None
return {
"total_prompts": total_prompts,
"total_categories": total_categories,
"average_rating": avg,
"avg_rating": avg,
"total_tags": total_tags,
"total_images": total_images,
"images_with_prompts": images_with_prompts,
}
def update_prompt_text(self, prompt_id: int, new_text: str) -> bool:
"""Update only the text of a prompt.
Returns:
True if a row was updated.
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
"UPDATE prompts SET text = ?, updated_at = ? WHERE id = ?",
(
new_text,
datetime.datetime.now(datetime.timezone.utc).isoformat(),
prompt_id,
),
)
conn.commit()
return cursor.rowcount > 0
def update_prompt_rating(self, prompt_id: int, rating: int) -> bool:
"""Update only the rating of a prompt.
Returns:
True if a row was updated.
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
"UPDATE prompts SET rating = ?, updated_at = ? WHERE id = ?",
(
rating,
datetime.datetime.now(datetime.timezone.utc).isoformat(),
prompt_id,
),
)
conn.commit()
return cursor.rowcount > 0
def set_prompt_tags(self, prompt_id: int, tags: List[str]) -> None:
"""Overwrite the tags list for a prompt via junction table."""
with self.model.get_connection() as conn:
self._sync_prompt_tags(conn, prompt_id, tags)
conn.execute(
"UPDATE prompts SET updated_at = ? WHERE id = ?",
(datetime.datetime.now(datetime.timezone.utc).isoformat(), prompt_id),
)
conn.commit()
def bulk_delete_prompts(self, prompt_ids: List[int]) -> int:
"""Delete multiple prompts and their associated images.
Returns:
Number of prompts actually deleted.
"""
count = 0
with self.model.get_connection() as conn:
for pid in prompt_ids:
conn.execute("DELETE FROM generated_images WHERE prompt_id = ?", (pid,))
cursor = conn.execute("DELETE FROM prompts WHERE id = ?", (pid,))
if cursor.rowcount > 0:
count += 1
conn.commit()
return count
def bulk_add_tags(self, prompt_ids: List[int], new_tags: List[str]) -> int:
"""Add tags to multiple prompts via junction table (skipping duplicates).
Returns:
Number of prompts that were actually modified.
"""
count = 0
with self.model.get_connection() as conn:
tag_map = self._ensure_tags(conn, new_tags)
now = datetime.datetime.now(datetime.timezone.utc).isoformat()
for pid in prompt_ids:
cursor = conn.execute("SELECT id FROM prompts WHERE id = ?", (pid,))
if not cursor.fetchone():
continue
added = False
for tag_name in new_tags:
tag_id = tag_map.get(tag_name)
if tag_id:
cursor = conn.execute(
"INSERT OR IGNORE INTO prompt_tags (prompt_id, tag_id) "
"VALUES (?, ?)",
(pid, tag_id),
)
if cursor.rowcount > 0:
added = True
if added:
conn.execute(
"UPDATE prompts SET updated_at = ? WHERE id = ?", (now, pid)
)
count += 1
conn.commit()
return count
def bulk_set_category(self, prompt_ids: List[int], category: str) -> int:
"""Set category on multiple prompts.
Returns:
Number of prompts actually updated.
"""
count = 0
now = datetime.datetime.now(datetime.timezone.utc).isoformat()
with self.model.get_connection() as conn:
for pid in prompt_ids:
cursor = conn.execute(
"UPDATE prompts SET category = ?, updated_at = ? WHERE id = ?",
(category, now, pid),
)
if cursor.rowcount > 0:
count += 1
conn.commit()
return count
def get_image_prompt_info(self, image_path: str) -> Optional[Dict[str, Any]]:
"""Look up prompt + image metadata for a given image path.
Returns a dict with prompt_id, text, category, tags, rating, notes,
workflow_data, prompt_metadata, generation_time — or None.
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
"""SELECT gi.prompt_id, p.text, p.category, p.rating, p.notes,
gi.workflow_data, gi.prompt_metadata, gi.generation_time
FROM generated_images gi
JOIN prompts p ON gi.prompt_id = p.id
WHERE gi.image_path = ? OR gi.file_path = ?
OR gi.image_path LIKE ? ESCAPE '\\'""",
(
image_path,
normalize_image_path(image_path),
f"%{escape_like(os.path.basename(image_path))}",
),
)
row = cursor.fetchone()
if not row:
return None
tags = self._get_prompt_tags(conn, row[0])
try:
workflow = json.loads(row[5]) if row[5] else None
except (json.JSONDecodeError, TypeError):
workflow = None
try:
prompt_meta = json.loads(row[6]) if row[6] else None
except (json.JSONDecodeError, TypeError):
prompt_meta = None
return {
"prompt_id": row[0],
"text": row[1],
"category": row[2],
"tags": tags,
"rating": row[3],
"notes": row[4],
"workflow_data": workflow,
"prompt_metadata": prompt_meta,
"generation_time": row[7],
}
def get_prompt_id_for_image(self, image_path: str) -> Optional[int]:
"""Return the prompt_id linked to an image, or None."""
with self.model.get_connection() as conn:
cursor = conn.execute(
"SELECT prompt_id FROM generated_images"
" WHERE image_path = ? OR file_path = ?",
(image_path, normalize_image_path(image_path)),
)
row = cursor.fetchone()
return row[0] if row else None
def check_hash_duplicates(self) -> List[Dict[str, Any]]:
"""Find prompts sharing the same hash.
Returns list of dicts with 'hash' and 'count'.
"""
with self.model.get_connection() as conn:
cursor = conn.execute(
"SELECT hash, COUNT(*) as count FROM prompts "
"WHERE hash IS NOT NULL GROUP BY hash HAVING COUNT(*) > 1"
)
return [dict(row) for row in cursor.fetchall()]
def prune_orphaned_prompts(self) -> int:
"""Delete prompts with no linked images and no __protected__ tag.
Returns number of prompts removed.
"""
with self.model.get_connection() as conn:
cursor = conn.execute("""
SELECT p.id FROM prompts p
LEFT JOIN generated_images gi ON p.id = gi.prompt_id
WHERE gi.prompt_id IS NULL
AND NOT EXISTS (
SELECT 1 FROM prompt_tags pt
JOIN tags t ON pt.tag_id = t.id
WHERE pt.prompt_id = p.id AND t.name = '__protected__'
)
""")
orphaned = [row["id"] for row in cursor.fetchall()]
if not orphaned:
return 0
placeholders = ",".join(["?"] * len(orphaned))
cursor = conn.execute(
f"DELETE FROM prompts WHERE id IN ({placeholders})", orphaned
)
conn.commit()
return cursor.rowcount
def check_consistency(self) -> List[str]:
"""Run consistency checks and return a list of issue descriptions."""
issues: List[str] = []
with self.model.get_connection() as conn:
# Check for orphaned prompt_tags entries
cursor = conn.execute("""
SELECT pt.prompt_id, pt.tag_id FROM prompt_tags pt
LEFT JOIN prompts p ON pt.prompt_id = p.id
WHERE p.id IS NULL
""")
for ref in cursor.fetchall():
issues.append(
"prompt_tags entry references non-existent prompt "
f"{ref['prompt_id']}"
)
# Check for orphaned image entries
cursor = conn.execute("""
SELECT gi.id, gi.prompt_id FROM generated_images gi
LEFT JOIN prompts p ON gi.prompt_id = p.id
WHERE p.id IS NULL
""")
for ref in cursor.fetchall():
issues.append(
f"Image {ref['id']} references non-existent prompt "
f"{ref['prompt_id']}"
)
return issues
def _image_row_to_dict(self, row: sqlite3.Row) -> Dict[str, Any]:
"""
Convert an image database row to a dictionary with parsed JSON fields.
Args:
row: SQLite row object
Returns:
Dictionary representation of the row
"""
data = dict(row)
# Parse JSON fields
for field in ["workflow_data", "prompt_metadata", "parameters"]:
if data.get(field):
try:
parsed_data = json.loads(data[field])
data[field] = self._clean_nan_values(parsed_data)
except (json.JSONDecodeError, TypeError):
data[field] = {}
else:
data[field] = {}
return data
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