diff --git a/.gitignore b/.gitignore index a4b8d2d6..c763b375 100644 --- a/.gitignore +++ b/.gitignore @@ -3,4 +3,6 @@ __pycache__ .emacs.desktop* tests/data/.* src/.data -.vscode \ No newline at end of file +.vscode +*.gz +*.pt \ No newline at end of file diff --git a/environment.yml b/environment.yml index aedf5358..e56ebe26 100644 --- a/environment.yml +++ b/environment.yml @@ -13,4 +13,6 @@ dependencies: - pytest=6.* - pillow=8.* - torchvision=0.* - - openai=0.* \ No newline at end of file + - openai=0.* + - pydantic=1.* + - jinja2=3.0.* diff --git a/src/main.py b/src/main.py index be812bbc..bfd6fafb 100644 --- a/src/main.py +++ b/src/main.py @@ -1,26 +1,49 @@ # Standard Packages -import sys -import json +import sys, json, yaml from typing import Optional # External Packages import uvicorn -from fastapi import FastAPI +from fastapi import FastAPI, Request +from fastapi.responses import HTMLResponse +from fastapi.staticfiles import StaticFiles +from fastapi.templating import Jinja2Templates # Internal Packages from src.search_type import asymmetric, symmetric_ledger, image_search from src.utils.helpers import get_absolute_path from src.utils.cli import cli -from src.utils.config import SearchType, SearchModels, TextSearchConfig, ImageSearchConfig, SearchConfig, ProcessorConfig, ConversationProcessorConfig +from src.utils.config import SearchType, SearchModels, ProcessorConfigModel, ConversationProcessorConfigModel +from src.utils.rawconfig import FullConfig from src.processor.conversation.gpt import converse, message_to_log, message_to_prompt, understand - # Application Global State model = SearchModels() -search_config = SearchConfig() -processor_config = ProcessorConfig() +processor_config = ProcessorConfigModel() +config = {} +config_file = "" +verbose = 0 app = FastAPI() +app.mount("/views", StaticFiles(directory="views"), name="views") +templates = Jinja2Templates(directory="views/") + +@app.get('/ui', response_class=HTMLResponse) +def ui(request: Request): + return templates.TemplateResponse("config.html", context={'request': request}) + +@app.get('/config', response_model=FullConfig) +def config(): + return config + +@app.post('/config') +async def config(updated_config: FullConfig): + global config + config = updated_config + with open(config_file, 'w') as outfile: + yaml.dump(yaml.safe_load(config.json(by_alias=True)), outfile) + outfile.close() + return config @app.get('/search') def search(q: str, n: Optional[int] = 5, t: Optional[SearchType] = None): @@ -60,7 +83,7 @@ def search(q: str, n: Optional[int] = 5, t: Optional[SearchType] = None): return image_search.collate_results( hits, model.image_search.image_names, - search_config.image.input_directory, + config.content_type.image.input_directory, results_count) else: @@ -69,22 +92,7 @@ def search(q: str, n: Optional[int] = 5, t: Optional[SearchType] = None): @app.get('/regenerate') def regenerate(t: Optional[SearchType] = None): - if (t == SearchType.Notes or t == None) and search_config.notes: - # Extract Entries, Generate Embeddings - model.notes_search = asymmetric.setup(search_config.notes, regenerate=True) - - if (t == SearchType.Music or t == None) and search_config.music: - # Extract Entries, Generate Song Embeddings - model.music_search = asymmetric.setup(search_config.music, regenerate=True) - - if (t == SearchType.Ledger or t == None) and search_config.ledger: - # Extract Entries, Generate Embeddings - model.ledger_search = symmetric_ledger.setup(search_config.ledger, regenerate=True) - - if (t == SearchType.Image or t == None) and search_config.image: - # Extract Images, Generate Embeddings - model.image_search = image_search.setup(search_config.image, regenerate=True) - + initialize_search(regenerate=True, t=t) return {'status': 'ok', 'message': 'regeneration completed'} @@ -105,37 +113,40 @@ def chat(q: str): return {'status': 'ok', 'response': gpt_response} -def initialize_search(config, regenerate, verbose): +def initialize_search(config: FullConfig, regenerate: bool, t: SearchType = None): model = SearchModels() - search_config = SearchConfig() # Initialize Org Notes Search - search_config.notes = TextSearchConfig.create_from_dictionary(config, ('content-type', 'org'), verbose) - if search_config.notes: - model.notes_search = asymmetric.setup(search_config.notes, regenerate=regenerate) + if (t == SearchType.Notes or t == None) and config.content_type.org: + # Extract Entries, Generate Notes Embeddings + model.notes_search = asymmetric.setup(config.content_type.org, regenerate=regenerate, verbose=verbose) # Initialize Org Music Search - search_config.music = TextSearchConfig.create_from_dictionary(config, ('content-type', 'music'), verbose) - if search_config.music: - model.music_search = asymmetric.setup(search_config.music, regenerate=regenerate) + if (t == SearchType.Music or t == None) and config.content_type.music: + # Extract Entries, Generate Music Embeddings + model.music_search = asymmetric.setup(config.content_type.music, regenerate=regenerate, verbose=verbose) # Initialize Ledger Search - search_config.ledger = TextSearchConfig.create_from_dictionary(config, ('content-type', 'ledger'), verbose) - if search_config.ledger: - model.ledger_search = symmetric_ledger.setup(search_config.ledger, regenerate=regenerate) + if (t == SearchType.Ledger or t == None) and config.content_type.ledger: + # Extract Entries, Generate Ledger Embeddings + model.ledger_search = symmetric_ledger.setup(config.content_type.ledger, regenerate=regenerate, verbose=verbose) # Initialize Image Search - search_config.image = ImageSearchConfig.create_from_dictionary(config, ('content-type', 'image'), verbose) - if search_config.image: - model.image_search = image_search.setup(search_config.image, regenerate=regenerate) + if (t == 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, regenerate=regenerate, verbose=verbose) - return model, search_config + return model -def initialize_processor(config, verbose): +def initialize_processor(config: FullConfig): + if not config.processor: + return + + processor_config = ProcessorConfigModel() + # Initialize Conversation Processor - processor_config = ProcessorConfig() - processor_config.conversation = ConversationProcessorConfig.create_from_dictionary(config, ('processor', 'conversation'), verbose) + processor_config.conversation = ConversationProcessorConfigModel(config.processor.conversation, verbose) conversation_logfile = processor_config.conversation.conversation_logfile if processor_config.conversation.verbose: @@ -180,12 +191,21 @@ def shutdown_event(): if __name__ == '__main__': # Load config from CLI args = cli(sys.argv[1:]) + + # Stores the file path to the config file. + config_file = args.config_file - # Initialize Search from Config - model, search_config = initialize_search(args.config, args.regenerate, args.verbose) + # Store the verbose flag + verbose = args.verbose + + # Store the raw config data. + config = args.config + + # Initialize the search model from Config + model = initialize_search(args.config, args.regenerate) # Initialize Processor from Config - processor_config = initialize_processor(args.config, args.verbose) + processor_config = initialize_processor(args.config) # Start Application Server if args.socket: diff --git a/src/search_type/asymmetric.py b/src/search_type/asymmetric.py index fc4e72e4..bdf7ddff 100644 --- a/src/search_type/asymmetric.py +++ b/src/search_type/asymmetric.py @@ -14,7 +14,8 @@ from sentence_transformers import SentenceTransformer, CrossEncoder, util # Internal Packages from src.utils.helpers import get_absolute_path, resolve_absolute_path from src.processor.org_mode.org_to_jsonl import org_to_jsonl -from src.utils.config import TextSearchModel, TextSearchConfig +from src.utils.config import TextSearchModel +from src.utils.rawconfig import TextSearchConfig def initialize_model(): @@ -58,7 +59,7 @@ def compute_embeddings(entries, bi_encoder, embeddings_file, regenerate=False, v corpus_embeddings = bi_encoder.encode([entry[0] for entry in entries], convert_to_tensor=True, show_progress_bar=True) torch.save(corpus_embeddings, get_absolute_path(embeddings_file)) if verbose > 0: - print(f"Computed embeddings and save them to {embeddings_file}") + print(f"Computed embeddings and saved them to {embeddings_file}") return corpus_embeddings @@ -148,22 +149,22 @@ def collate_results(hits, entries, count=5): in hits[0:count]] -def setup(config: TextSearchConfig, regenerate: bool) -> TextSearchModel: +def setup(config: TextSearchConfig, regenerate: bool, verbose: bool) -> TextSearchModel: # Initialize Model bi_encoder, cross_encoder, top_k = initialize_model() # Map notes in Org-Mode files to (compressed) JSONL formatted file if not resolve_absolute_path(config.compressed_jsonl).exists() or regenerate: - org_to_jsonl(config.input_files, config.input_filter, config.compressed_jsonl, config.verbose) + org_to_jsonl(config.input_files, config.input_filter, config.compressed_jsonl, verbose) # Extract Entries - entries = extract_entries(config.compressed_jsonl, config.verbose) + entries = extract_entries(config.compressed_jsonl, verbose) top_k = min(len(entries), top_k) # top_k hits can't be more than the total entries in corpus # Compute or Load Embeddings - corpus_embeddings = compute_embeddings(entries, bi_encoder, config.embeddings_file, regenerate=regenerate, verbose=config.verbose) + corpus_embeddings = compute_embeddings(entries, bi_encoder, config.embeddings_file, regenerate=regenerate, verbose=verbose) - return TextSearchModel(entries, corpus_embeddings, bi_encoder, cross_encoder, top_k, verbose=config.verbose) + return TextSearchModel(entries, corpus_embeddings, bi_encoder, cross_encoder, top_k, verbose=verbose) if __name__ == '__main__': diff --git a/src/search_type/image_search.py b/src/search_type/image_search.py index 95acc801..34a38a9e 100644 --- a/src/search_type/image_search.py +++ b/src/search_type/image_search.py @@ -10,9 +10,10 @@ from tqdm import trange import torch # Internal Packages -from src.utils.helpers import get_absolute_path, resolve_absolute_path +from src.utils.helpers import resolve_absolute_path import src.utils.exiftool as exiftool -from src.utils.config import ImageSearchModel, ImageSearchConfig +from src.utils.config import ImageSearchModel +from src.utils.rawconfig import ImageSearchConfig def initialize_model(): @@ -153,7 +154,7 @@ def collate_results(hits, image_names, image_directory, count=5): in hits[0:count]] -def setup(config: ImageSearchConfig, regenerate: bool) -> ImageSearchModel: +def setup(config: ImageSearchConfig, regenerate: bool, verbose: bool) -> ImageSearchModel: # Initialize Model encoder = initialize_model() @@ -170,13 +171,13 @@ def setup(config: ImageSearchConfig, regenerate: bool) -> ImageSearchModel: batch_size=config.batch_size, regenerate=regenerate, use_xmp_metadata=config.use_xmp_metadata, - verbose=config.verbose) + verbose=verbose) return ImageSearchModel(image_names, image_embeddings, image_metadata_embeddings, encoder, - config.verbose) + verbose) if __name__ == '__main__': diff --git a/src/search_type/symmetric_ledger.py b/src/search_type/symmetric_ledger.py index 4d091371..20d2293f 100644 --- a/src/search_type/symmetric_ledger.py +++ b/src/search_type/symmetric_ledger.py @@ -1,9 +1,6 @@ # Standard Packages import json -import time import gzip -import os -import sys import re import argparse import pathlib @@ -15,11 +12,12 @@ from sentence_transformers import SentenceTransformer, CrossEncoder, util # Internal Packages from src.utils.helpers import get_absolute_path, resolve_absolute_path from src.processor.ledger.beancount_to_jsonl import beancount_to_jsonl -from src.utils.config import TextSearchModel, TextSearchConfig +from src.utils.config import TextSearchModel +from src.utils.rawconfig import TextSearchConfig def initialize_model(): - "Initialize model for symetric semantic search. That is, where query of similar size to results" + "Initialize model for symmetric semantic search. That is, where query of similar size to results" torch.set_num_threads(4) bi_encoder = SentenceTransformer('sentence-transformers/paraphrase-MiniLM-L6-v2') # The encoder encodes all entries to use for semantic search top_k = 30 # Number of entries we want to retrieve with the bi-encoder @@ -55,7 +53,7 @@ def compute_embeddings(entries, bi_encoder, embeddings_file, regenerate=False, v corpus_embeddings = bi_encoder.encode(entries, convert_to_tensor=True, show_progress_bar=True) torch.save(corpus_embeddings, get_absolute_path(embeddings_file)) if verbose > 0: - print(f"Computed embeddings and save them to {embeddings_file}") + print(f"Computed embeddings and saved them to {embeddings_file}") return corpus_embeddings @@ -143,7 +141,7 @@ def collate_results(hits, entries, count=5): in hits[0:count]] -def setup(config: TextSearchConfig, regenerate: bool) -> TextSearchModel: +def setup(config: TextSearchConfig, regenerate: bool, verbose: bool) -> TextSearchModel: # Initialize Model bi_encoder, cross_encoder, top_k = initialize_model() @@ -156,9 +154,9 @@ def setup(config: TextSearchConfig, regenerate: bool) -> TextSearchModel: top_k = min(len(entries), top_k) # Compute or Load Embeddings - corpus_embeddings = compute_embeddings(entries, bi_encoder, config.embeddings_file, regenerate=regenerate, verbose=config.verbose) + corpus_embeddings = compute_embeddings(entries, bi_encoder, config.embeddings_file, regenerate=regenerate, verbose=verbose) - return TextSearchModel(entries, corpus_embeddings, bi_encoder, cross_encoder, top_k, verbose=config.verbose) + return TextSearchModel(entries, corpus_embeddings, bi_encoder, cross_encoder, top_k, verbose=verbose) if __name__ == '__main__': diff --git a/src/utils/cli.py b/src/utils/cli.py index 6891463a..aa58af8d 100644 --- a/src/utils/cli.py +++ b/src/utils/cli.py @@ -1,12 +1,14 @@ # Standard Packages import argparse import pathlib +import json # External Packages import yaml # Internal Packages -from src.utils.helpers import is_none_or_empty, get_absolute_path, resolve_absolute_path, get_from_dict, merge_dicts +from src.utils.helpers import is_none_or_empty, get_absolute_path, resolve_absolute_path, merge_dicts +from src.utils.rawconfig import FullConfig def cli(args=None): if is_none_or_empty(args): @@ -35,12 +37,15 @@ def cli(args=None): with open(get_absolute_path(args.config_file), 'r', encoding='utf-8') as config_file: config_from_file = yaml.safe_load(config_file) args.config = merge_dicts(priority_dict=config_from_file, default_dict=args.config) + args.config = FullConfig.parse_obj(args.config) + else: + args.config = FullConfig.parse_obj(args.config) if args.org_files: - args.config['content-type']['org']['input-files'] = args.org_files + args.config.content_type.org.input_files = args.org_files if args.org_filter: - args.config['content-type']['org']['input-filter'] = args.org_filter + args.config.content_type.org.input_filter = args.org_filter return args diff --git a/src/utils/config.py b/src/utils/config.py index 01665e9d..830ec3ce 100644 --- a/src/utils/config.py +++ b/src/utils/config.py @@ -4,7 +4,7 @@ from dataclasses import dataclass from pathlib import Path # Internal Packages -from src.utils.helpers import get_from_dict +from src.utils.rawconfig import ConversationProcessorConfig class SearchType(str, Enum): @@ -42,80 +42,15 @@ class SearchModels(): image_search: ImageSearchModel = None -class TextSearchConfig(): - def __init__(self, input_files, input_filter, compressed_jsonl, embeddings_file, verbose): - self.input_files = input_files - self.input_filter = input_filter - self.compressed_jsonl = Path(compressed_jsonl) - self.embeddings_file = Path(embeddings_file) +class ConversationProcessorConfigModel(): + def __init__(self, processor_config: ConversationProcessorConfig, verbose: bool): + self.openai_api_key = processor_config.open_api_key + self.conversation_logfile = Path(processor_config.conversation_logfile) + self.chat_log = '' + self.meta_log = [] + self.conversation_history = Path(processor_config.conversation_history) self.verbose = verbose - - def create_from_dictionary(config, key_tree, verbose): - text_config = get_from_dict(config, *key_tree) - search_enabled = text_config and ('input-files' in text_config or 'input-filter' in text_config) - if not search_enabled: - return None - - return TextSearchConfig( - input_files = text_config['input-files'], - input_filter = text_config['input-filter'], - compressed_jsonl = Path(text_config['compressed-jsonl']), - embeddings_file = Path(text_config['embeddings-file']), - verbose = verbose) - - -class ImageSearchConfig(): - def __init__(self, input_directory, embeddings_file, batch_size, use_xmp_metadata, verbose): - self.input_directory = input_directory - self.embeddings_file = Path(embeddings_file) - self.batch_size = batch_size - self.use_xmp_metadata = use_xmp_metadata - self.verbose = verbose - - def create_from_dictionary(config, key_tree, verbose): - image_config = get_from_dict(config, *key_tree) - search_enabled = image_config and 'input-directory' in image_config - if not search_enabled: - return None - - return ImageSearchConfig( - input_directory = Path(image_config['input-directory']), - embeddings_file = Path(image_config['embeddings-file']), - batch_size = image_config['batch-size'], - use_xmp_metadata = {'yes': True, 'no': False}[image_config['use-xmp-metadata']], - verbose = verbose) - - @dataclass -class SearchConfig(): - notes: TextSearchConfig = None - ledger: TextSearchConfig = None - music: TextSearchConfig = None - image: ImageSearchConfig = None - - -class ConversationProcessorConfig(): - def __init__(self, conversation_logfile, chat_log, meta_log, openai_api_key, verbose): - self.openai_api_key = openai_api_key - self.conversation_logfile = conversation_logfile - self.chat_log = chat_log - self.meta_log = meta_log - self.verbose = verbose - - def create_from_dictionary(config, key_tree, verbose): - conversation_config = get_from_dict(config, *key_tree) - if not conversation_config: - return None - - return ConversationProcessorConfig( - openai_api_key = conversation_config['openai-api-key'], - chat_log = '', - meta_log = [], - conversation_logfile = Path(conversation_config['conversation-logfile']), - verbose = verbose) - - -@dataclass -class ProcessorConfig(): - conversation: ConversationProcessorConfig = None \ No newline at end of file +class ProcessorConfigModel(): + conversation: ConversationProcessorConfigModel = None diff --git a/src/utils/helpers.py b/src/utils/helpers.py index b9f60ef0..e2a3b1fe 100644 --- a/src/utils/helpers.py +++ b/src/utils/helpers.py @@ -4,6 +4,8 @@ import pathlib def is_none_or_empty(item): return item == None or (hasattr(item, '__iter__') and len(item) == 0) +def to_snake_case_from_dash(item: str): + return item.replace('_', '-') def get_absolute_path(filepath): return str(pathlib.Path(filepath).expanduser().absolute()) diff --git a/src/utils/rawconfig.py b/src/utils/rawconfig.py new file mode 100644 index 00000000..a8a0df57 --- /dev/null +++ b/src/utils/rawconfig.py @@ -0,0 +1,62 @@ +# System Packages +from pathlib import Path +from typing import List, Optional + +# External Packages +from pydantic import BaseModel + +# Internal Packages +from src.utils.helpers import to_snake_case_from_dash + +class ConfigBase(BaseModel): + class Config: + alias_generator = to_snake_case_from_dash + allow_population_by_field_name = True + +class SearchConfig(ConfigBase): + input_files: Optional[List[str]] + input_filter: Optional[str] + embeddings_file: Optional[Path] + +class TextSearchConfig(ConfigBase): + compressed_jsonl: Optional[Path] + input_files: Optional[List[str]] + input_filter: Optional[str] + embeddings_file: Optional[Path] + +class ImageSearchConfig(ConfigBase): + use_xmp_metadata: Optional[str] + batch_size: Optional[int] + input_directory: Optional[Path] + input_filter: Optional[str] + embeddings_file: Optional[Path] + +class ContentTypeConfig(ConfigBase): + org: Optional[TextSearchConfig] + ledger: Optional[TextSearchConfig] + image: Optional[ImageSearchConfig] + music: Optional[TextSearchConfig] + +class AsymmetricConfig(ConfigBase): + encoder: Optional[str] + cross_encoder: Optional[str] + +class ImageSearchTypeConfig(ConfigBase): + encoder: Optional[str] + +class SearchTypeConfig(ConfigBase): + asymmetric: Optional[AsymmetricConfig] + image: Optional[ImageSearchTypeConfig] + +class ConversationProcessorConfig(ConfigBase): + open_api_key: Optional[str] + conversation_logfile: Optional[str] + conversation_history: Optional[str] + +class ProcessorConfigModel(ConfigBase): + conversation: Optional[ConversationProcessorConfig] + +class FullConfig(ConfigBase): + content_type: Optional[ContentTypeConfig] + search_type: Optional[SearchTypeConfig] + processor: Optional[ProcessorConfigModel] diff --git a/tests/conftest.py b/tests/conftest.py index 246f5a44..fcff1510 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -3,8 +3,8 @@ import pytest from pathlib import Path # Internal Packages -from src.utils.config import SearchConfig, TextSearchConfig, ImageSearchConfig from src.search_type import asymmetric, image_search +from src.utils.rawconfig import ContentTypeConfig, ImageSearchConfig, TextSearchConfig @pytest.fixture(scope='session') @@ -12,44 +12,40 @@ def model_dir(tmp_path_factory): model_dir = tmp_path_factory.mktemp('data') # Generate Image Embeddings from Test Images - search_config = SearchConfig() + search_config = ContentTypeConfig() search_config.image = ImageSearchConfig( input_directory = Path('tests/data'), embeddings_file = model_dir.joinpath('.image_embeddings.pt'), batch_size = 10, - use_xmp_metadata = False, - verbose = 2) + use_xmp_metadata = False) - image_search.setup(search_config.image, regenerate=False) + image_search.setup(search_config.image, regenerate=False, verbose=True) # Generate Notes Embeddings from Test Notes - search_config.notes = TextSearchConfig( + search_config.org = TextSearchConfig( input_files = [Path('tests/data/main_readme.org'), Path('tests/data/interface_emacs_readme.org')], input_filter = None, compressed_jsonl = model_dir.joinpath('.notes.jsonl.gz'), - embeddings_file = model_dir.joinpath('.note_embeddings.pt'), - verbose = 0) + embeddings_file = model_dir.joinpath('.note_embeddings.pt')) - asymmetric.setup(search_config.notes, regenerate=False) + asymmetric.setup(search_config.notes, regenerate=False, verbose=True) return model_dir @pytest.fixture(scope='session') def search_config(model_dir): - search_config = SearchConfig() - search_config.notes = TextSearchConfig( + search_config = ContentTypeConfig() + search_config.org = TextSearchConfig( input_files = [Path('tests/data/main_readme.org'), Path('tests/data/interface_emacs_readme.org')], input_filter = None, compressed_jsonl = model_dir.joinpath('.notes.jsonl.gz'), - embeddings_file = model_dir.joinpath('.note_embeddings.pt'), - verbose = 2) + embeddings_file = model_dir.joinpath('.note_embeddings.pt')) search_config.image = ImageSearchConfig( input_directory = Path('tests/data'), embeddings_file = Path('tests/data/.image_embeddings.pt'), batch_size = 10, - use_xmp_metadata = False, - verbose = 2) + use_xmp_metadata = False) return search_config diff --git a/tests/test_asymmetric_search.py b/tests/test_asymmetric_search.py index 2d84e336..92535b28 100644 --- a/tests/test_asymmetric_search.py +++ b/tests/test_asymmetric_search.py @@ -8,7 +8,7 @@ from src.search_type import asymmetric def test_asymmetric_setup(search_config): # Act # Regenerate notes embeddings during asymmetric setup - notes_model = asymmetric.setup(search_config.notes, regenerate=True) + notes_model = asymmetric.setup(search_config.org, regenerate=True) # Assert assert len(notes_model.entries) == 10 @@ -18,7 +18,7 @@ def test_asymmetric_setup(search_config): # ---------------------------------------------------------------------------------------------------- def test_asymmetric_search(search_config): # Arrange - model.notes_search = asymmetric.setup(search_config.notes, regenerate=False) + model.notes_search = asymmetric.setup(search_config.org, regenerate=False) query = "How to git install application?" # Act diff --git a/tests/test_cli.py b/tests/test_cli.py index de2f9753..58808fb4 100644 --- a/tests/test_cli.py +++ b/tests/test_cli.py @@ -40,7 +40,7 @@ def test_cli_config_from_file(): assert actual_args.config_file == Path('tests/data/config.yml') assert actual_args.regenerate == True assert actual_args.config is not None - assert actual_args.config['content-type']['org']['input-files'] == ['~/first_from_config.org', '~/second_from_config.org'] + assert actual_args.config.content_type.org.input_files == ['~/first_from_config.org', '~/second_from_config.org'] assert actual_args.verbose == 3 @@ -54,7 +54,7 @@ def test_cli_config_from_cmd_args(): assert actual_args.org_files == ['first.org'] assert actual_args.config_file is None assert actual_args.config is not None - assert actual_args.config['content-type']['org']['input-files'] == ['first.org'] + assert actual_args.config.content_type.org.input_files == ['first.org'] # ---------------------------------------------------------------------------------------------------- @@ -67,4 +67,4 @@ def test_cli_config_from_cmd_args_override_config_file(): assert actual_args.org_files == ['first.org'] assert actual_args.config_file == Path('tests/data/config.yml') assert actual_args.config is not None - assert actual_args.config['content-type']['org']['input-files'] == ['first.org'] + assert actual_args.config.content_type.org.input_files == ['first.org'] diff --git a/tests/test_client.py b/tests/test_client.py index cbf0e0c3..bf8815fa 100644 --- a/tests/test_client.py +++ b/tests/test_client.py @@ -5,15 +5,16 @@ from pathlib import Path from fastapi.testclient import TestClient # Internal Packages -from src.main import app, model, search_config as main_search_config +from src.main import app, model, config from src.search_type import asymmetric, image_search from src.utils.helpers import resolve_absolute_path +from src.utils.rawconfig import FullConfig # Arrange # ---------------------------------------------------------------------------------------------------- client = TestClient(app) - +config = FullConfig() # Test # ---------------------------------------------------------------------------------------------------- @@ -31,7 +32,7 @@ def test_search_with_invalid_search_type(): # ---------------------------------------------------------------------------------------------------- def test_search_with_valid_search_type(search_config): # Arrange - main_search_config.image = search_config.image + config.content_type.image = search_config.image for search_type in ["notes", "ledger", "music", "image"]: # Act response = client.get(f"/search?q=random&t={search_type}") @@ -51,7 +52,7 @@ def test_regenerate_with_invalid_search_type(): # ---------------------------------------------------------------------------------------------------- def test_regenerate_with_valid_search_type(search_config): # Arrange - main_search_config.image = search_config.image + config.content_type.image = search_config.image for search_type in ["notes", "ledger", "music", "image"]: # Act response = client.get(f"/regenerate?t={search_type}") @@ -62,7 +63,7 @@ def test_regenerate_with_valid_search_type(search_config): # ---------------------------------------------------------------------------------------------------- def test_image_search(search_config): # Arrange - main_search_config.image = search_config.image + config.content_type.image = search_config.image model.image_search = image_search.setup(search_config.image, regenerate=False) query_expected_image_pairs = [("brown kitten next to fallen plant", "kitten_park.jpg"), ("a horse and dog on a leash", "horse_dog.jpg"), diff --git a/views/config.html b/views/config.html new file mode 100644 index 00000000..befa8e24 --- /dev/null +++ b/views/config.html @@ -0,0 +1,12 @@ + +
+