Update to re-use the raw config base models in config.py as well

This commit is contained in:
Saba 2021-11-28 11:57:33 -05:00
parent 6292fe4481
commit da52433d89
3 changed files with 25 additions and 61 deletions

View file

@ -122,38 +122,38 @@ def chat(q: str):
return {'status': 'ok', 'response': gpt_response}
def initialize_search(config, regenerate, verbose):
def initialize_search(config: FullConfig, regenerate, verbose):
model = SearchModels()
search_config = SearchConfig()
# Initialize Org Notes Search
search_config.notes = TextSearchConfig.create_from_dictionary(config, ('content-type', 'org'), verbose)
search_config.notes = TextSearchConfig(config.content_type.org, verbose) if config.content_type.org else None
if search_config.notes:
model.notes_search = asymmetric.setup(search_config.notes, regenerate=regenerate)
# Initialize Org Music Search
search_config.music = TextSearchConfig.create_from_dictionary(config, ('content-type', 'music'), verbose)
search_config.music = TextSearchConfig(config.content_type.music, verbose) if config.content_type.music else None
if search_config.music:
model.music_search = asymmetric.setup(search_config.music, regenerate=regenerate)
# Initialize Ledger Search
search_config.ledger = TextSearchConfig.create_from_dictionary(config, ('content-type', 'ledger'), verbose)
search_config.ledger = TextSearchConfig(config.content_type.org, verbose) if config.content_type.ledger else None
if search_config.ledger:
model.ledger_search = symmetric_ledger.setup(search_config.ledger, regenerate=regenerate)
# Initialize Image Search
search_config.image = ImageSearchConfig.create_from_dictionary(config, ('content-type', 'image'), verbose)
search_config.image = ImageSearchConfig(config.content_type.image, verbose) if config.content_type.image else None
if search_config.image:
model.image_search = image_search.setup(search_config.image, regenerate=regenerate)
return model, search_config
def initialize_processor(config, verbose):
def initialize_processor(config: FullConfig, verbose):
processor_config = ProcessorConfig()
# Initialize Conversation Processor
processor_config.conversation = ConversationProcessorConfig.create_from_dictionary(config, ('processor', 'conversation'), verbose)
processor_config.conversation = ConversationProcessorConfig(config.processor.conversation, verbose)
# Load or Initialize Conversation History from Disk
conversation_logfile = processor_config.conversation.conversation_logfile

View file

@ -1,6 +1,7 @@
# Standard Packages
import argparse
import pathlib
import json
# External Packages
import yaml
@ -36,7 +37,7 @@ 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(args.config)
args.config = FullConfig.parse_raw(json.dumps(args.config))
if args.org_files:
args.config['content-type']['org']['input-files'] = args.org_files

View file

@ -6,6 +6,8 @@ from pathlib import Path
# Internal Packages
from src.utils.helpers import get_from_dict
from src.utils.rawconfig import TextSearchConfigTest, ImageSearchConfigTest, ProcessorConversationConfig
class SearchType(str, Enum):
Notes = "notes"
@ -43,49 +45,22 @@ class SearchModels():
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)
def __init__(self, text_search_config: TextSearchConfigTest, verbose: bool):
self.input_files = text_search_config.input_files
self.input_filter = text_search_config.input_filter
self.compressed_jsonl = Path(text_search_config.compressed_jsonl)
self.embeddings_file = Path(text_search_config.embeddings_file)
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
def __init__(self, image_search_config: ImageSearchConfigTest, verbose):
self.input_directory = Path(image_search_config.input_directory)
self.embeddings_file = Path(image_search_config.embeddings_file)
self.batch_size = image_search_config.batch_size
self.use_xmp_metadata = image_search_config.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():
@ -96,24 +71,12 @@ class SearchConfig():
class ConversationProcessorConfig():
def __init__(self, conversation_logfile, conversation_history, openai_api_key, verbose):
self.openai_api_key = openai_api_key
self.conversation_logfile = conversation_logfile
self.conversation_history = conversation_history
def __init__(self, processor_config: ProcessorConversationConfig, verbose: bool):
self.openai_api_key = processor_config.open_api_key
self.conversation_logfile = Path(processor_config.conversation_logfile)
self.conversation_history = Path(processor_config.conversation_history)
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'],
conversation_history = '',
conversation_logfile = Path(conversation_config['conversation-logfile']),
verbose = verbose)
@dataclass
class ProcessorConfig():
conversation: ConversationProcessorConfig = None