Files
ComfyAssets-ComfyUI_PromptM…/prompt_search_list.py
T

186 lines
5.8 KiB
Python

"""
PromptSearchList: A ComfyUI node that searches prompts and outputs results as a list.
This node enables batch processing workflows by outputting prompt texts with
OUTPUT_IS_LIST=True, allowing direct connection to nodes that accept list inputs.
"""
from typing import Any, Dict, List, Tuple
try:
from .utils.logging_config import get_logger
except ImportError:
import os
import sys
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from utils.logging_config import get_logger
try:
from comfy.comfy_types import IO, ComfyNodeABC, InputTypeDict
except ImportError:
class ComfyNodeABC:
pass
class IO:
STRING = "STRING"
INT = "INT"
InputTypeDict = dict
try:
from .database.operations import PromptDatabase
except ImportError:
import os
import sys
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from database.operations import PromptDatabase
class PromptSearchList(ComfyNodeABC):
"""
A ComfyUI node that searches the prompt database and outputs matching
prompts as a list for batch processing workflows.
Features:
- Search by text content
- Filter by category, tags, and minimum rating
- Outputs as OUTPUT_IS_LIST for batch node compatibility
- Read-only operation (no database writes)
"""
def __init__(self):
self.logger = get_logger("prompt_search_list.node")
self.logger.debug("Initializing PromptSearchList node")
self.db = PromptDatabase()
@classmethod
def INPUT_TYPES(cls) -> InputTypeDict:
return {
"required": {},
"optional": {
"text": (
IO.STRING,
{
"default": "",
"tooltip": "Search text to match against prompt content",
},
),
"category": (
IO.STRING,
{
"default": "",
"tooltip": "Filter by specific category",
},
),
"tags": (
IO.STRING,
{
"default": "",
"tooltip": "Comma-separated list of tags to filter by",
},
),
"min_rating": (
IO.INT,
{
"default": 0,
"min": 0,
"max": 5,
"tooltip": "Minimum rating (0-5) to include in results",
},
),
"limit": (
IO.INT,
{
"default": 50,
"min": 1,
"max": 1000,
"tooltip": "Maximum number of results to return",
},
),
},
}
RETURN_TYPES = (IO.STRING,)
RETURN_NAMES = ("prompts",)
OUTPUT_IS_LIST = (True,)
OUTPUT_TOOLTIPS = ("List of prompt texts matching the search criteria.",)
FUNCTION = "search"
CATEGORY = "🫶 ComfyAssets/🧠 Prompts"
DESCRIPTION = (
"Searches the prompt database and outputs matching prompts as a list. "
"Use this node to retrieve stored prompts for batch processing workflows. "
"Connect to nodes that accept list inputs like String OutputList or batch processors."
)
def search(
self,
text: str = "",
category: str = "",
tags: str = "",
min_rating: int = 0,
limit: int = 50,
) -> Tuple[List[str]]:
"""
Search for prompts matching the given criteria.
Args:
text: Search text to match against prompt content
category: Filter by specific category
tags: Comma-separated list of tags to filter by
min_rating: Minimum rating (0-5) to include
limit: Maximum number of results to return
Returns:
Tuple containing a list of prompt text strings
"""
try:
# Parse tags from comma-separated string
tags_list = None
if tags and tags.strip():
tags_list = [tag.strip() for tag in tags.split(",") if tag.strip()]
# Perform search
results = self.db.search_prompts(
text=text.strip() if text and text.strip() else None,
category=category.strip() if category and category.strip() else None,
tags=tags_list,
rating_min=min_rating if min_rating > 0 else None,
limit=limit,
)
# Extract just the prompt text from results
prompt_texts = [r["text"] for r in results if r.get("text")]
self.logger.debug(
f"Search returned {len(prompt_texts)} prompts "
f"(text='{text[:20]}...' if text else '', category='{category}', "
f"tags={tags_list}, min_rating={min_rating}, limit={limit})"
)
# Return empty list if no results (not an error)
if not prompt_texts:
self.logger.info("Search returned no results")
return ([],)
return (prompt_texts,)
except Exception as e:
self.logger.error(f"Search error: {e}", exc_info=True)
# Return empty list on error to avoid breaking workflows
return ([],)
@classmethod
def IS_CHANGED(cls, text="", category="", tags="", min_rating=0, limit=50):
"""
Always re-execute to get fresh results from the database.
The database contents may have changed since the last execution,
so we always return a unique value to trigger re-execution.
"""
import time
return time.time()