Configure, use dynamically instantiated SearchType enum on app start

The SearchType is now dynamically populated with core and configured
plugin types

Use the new dynamic SearchType enum from state.py across codebase

src/khoj/configure.py

@@ -2,6 +2,7 @@
 import sys
 import logging
 import json
+from enum import Enum
 
 # External Packages
 import schedule
@@ -14,7 +15,7 @@ from khoj.processor.org_mode.org_to_jsonl import OrgToJsonl
 from khoj.search_type import image_search, text_search
 from khoj.utils.config import SearchType, SearchModels, ProcessorConfigModel, ConversationProcessorConfigModel
 from khoj.utils import state
-from khoj.utils.helpers import LRU, resolve_absolute_path
+from khoj.utils.helpers import LRU, resolve_absolute_path, merge_dicts
 from khoj.utils.rawconfig import FullConfig, ProcessorConfig
 from khoj.search_filter.date_filter import DateFilter
 from khoj.search_filter.word_filter import WordFilter
@@ -40,8 +41,9 @@ def configure_server(args, required=False):
     # Initialize Processor from Config
     state.processor_config = configure_processor(args.config.processor)
 
-    # Initialize the search model from Config
+    # Initialize the search type and model from Config
     state.search_index_lock.acquire()
+    state.SearchType = configure_search_types(state.config)
     state.model = configure_search(state.model, state.config, args.regenerate)
     state.search_index_lock.release()
 
@@ -54,9 +56,19 @@ def update_search_index():
     logger.info("Search Index updated via Scheduler")
 
 
-def configure_search(model: SearchModels, config: FullConfig, regenerate: bool, t: SearchType = None):
+def configure_search_types(config: FullConfig):
+    # Extract core search types
+    core_search_types = {e.name: e.value for e in SearchType}
+    # Extract configured plugin search types
+    plugin_search_types = {plugin_type: plugin_type for plugin_type in config.content_type.plugins.keys()}
+
+    # Dynamically generate search type enum by merging core search types with configured plugin search types
+    return Enum("SearchType", merge_dicts(core_search_types, plugin_search_types))
+
+
+def configure_search(model: SearchModels, config: FullConfig, regenerate: bool, t: state.SearchType = None):
     # Initialize Org Notes Search
-    if (t == SearchType.Org or t == None) and config.content_type.org:
+    if (t == state.SearchType.Org or t == None) and config.content_type.org:
         # Extract Entries, Generate Notes Embeddings
         model.orgmode_search = text_search.setup(
             OrgToJsonl,
@@ -67,7 +79,7 @@ def configure_search(model: SearchModels, config: FullConfig, regenerate: bool,
         )
 
     # Initialize Org Music Search
-    if (t == SearchType.Music or t == None) and config.content_type.music:
+    if (t == state.SearchType.Music or t == None) and config.content_type.music:
         # Extract Entries, Generate Music Embeddings
         model.music_search = text_search.setup(
             OrgToJsonl,
@@ -78,7 +90,7 @@ def configure_search(model: SearchModels, config: FullConfig, regenerate: bool,
         )
 
     # Initialize Markdown Search
-    if (t == SearchType.Markdown or t == None) and config.content_type.markdown:
+    if (t == state.SearchType.Markdown or t == None) and config.content_type.markdown:
         # Extract Entries, Generate Markdown Embeddings
         model.markdown_search = text_search.setup(
             MarkdownToJsonl,
@@ -89,7 +101,7 @@ def configure_search(model: SearchModels, config: FullConfig, regenerate: bool,
         )
 
     # Initialize Ledger Search
-    if (t == SearchType.Ledger or t == None) and config.content_type.ledger:
+    if (t == state.SearchType.Ledger or t == None) and config.content_type.ledger:
         # Extract Entries, Generate Ledger Embeddings
         model.ledger_search = text_search.setup(
             BeancountToJsonl,
@@ -100,7 +112,7 @@ def configure_search(model: SearchModels, config: FullConfig, regenerate: bool,
         )
 
     # Initialize Image Search
-    if (t == SearchType.Image or t == None) and config.content_type.image:
+    if (t == state.SearchType.Image or t == None) and config.content_type.image:
         # Extract Entries, Generate Image Embeddings
         model.image_search = image_search.setup(
             config.content_type.image, search_config=config.search_type.image, regenerate=regenerate

src/khoj/routers/api.py

@@ -12,10 +12,9 @@ from khoj.configure import configure_processor, configure_search
 from khoj.search_type import image_search, text_search
 from khoj.utils.helpers import timer
 from khoj.utils.rawconfig import FullConfig, SearchResponse
-from khoj.utils.config import SearchType
+from khoj.utils.state import SearchType
 from khoj.utils import state, constants
 
-
 # Initialize Router
 api = APIRouter()
 logger = logging.getLogger(__name__)

src/khoj/routers/api_beta.py

@@ -17,7 +17,7 @@ from khoj.processor.conversation.gpt import (
     understand,
     summarize,
 )
-from khoj.utils.config import SearchType
+from khoj.utils.state import SearchType
 from khoj.utils.helpers import get_from_dict, resolve_absolute_path
 from khoj.utils import state
 

src/khoj/utils/state.py

@@ -8,6 +8,7 @@ import torch
 from pathlib import Path
 
 # Internal Packages
+from khoj.utils import config as utils_config
 from khoj.utils.config import SearchModels, ProcessorConfigModel
 from khoj.utils.helpers import LRU
 from khoj.utils.rawconfig import FullConfig
@@ -23,6 +24,7 @@ port: int = None
 cli_args: List[str] = None
 query_cache = LRU()
 search_index_lock = threading.Lock()
+SearchType = utils_config.SearchType
 
 if torch.cuda.is_available():
     # Use CUDA GPU