theroyallab/tabbyAPI
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patch pydantic config into old config

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- convert pydantic to dict to avoid errors with current files
- fix formatting
This commit is contained in:
TerminalMan
2024-09-06 14:31:28 +01:00
parent 36e991c16e
commit 8e9344642e
2 changed files with 26 additions and 13 deletions
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30
common/args.py
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@@ -5,6 +5,7 @@ from typing import get_origin, get_args, Optional, Union, List
from pydantic import BaseModel from pydantic import BaseModel
from common.tabby_config import config from common.tabby_config import config
def str_to_bool(value): def str_to_bool(value):
"""Converts a string into a boolean value""" """Converts a string into a boolean value"""
@@ -40,34 +41,43 @@ def init_argparser():
for field_name, field_type in config.__annotations__.items(): for field_name, field_type in config.__annotations__.items():
# Get the sub-model type (e.g., ModelA, ModelB) # Get the sub-model type (e.g., ModelA, ModelB)
sub_model = field_type.__base__ sub_model = field_type.__base__
# Create argument group for the sub-model # Create argument group for the sub-model
group = parser.add_argument_group(field_name, description=f"Arguments for {field_name}") group = parser.add_argument_group(
field_name, description=f"Arguments for {field_name}"
)
# Loop through each field in the sub-model (e.g., ModelA, ModelB) # Loop through each field in the sub-model (e.g., ModelA, ModelB)
for sub_field_name, sub_field_type in field_type.__annotations__.items(): for sub_field_name, sub_field_type in field_type.__annotations__.items():
field = field_type.__fields__[sub_field_name] field = field_type.__fields__[sub_field_name]
help_text = field.description if field.description else "No description available" help_text = (
field.description if field.description else "No description available"
)
# Handle Optional types or other generic types # Handle Optional types or other generic types
origin = get_origin(sub_field_type) origin = get_origin(sub_field_type)
if origin is Union: # Check if the type is Union (which includes Optional) if origin is Union: # Check if the type is Union (which includes Optional)
sub_field_type = next(t for t in get_args(sub_field_type) if t is not type(None)) sub_field_type = next(
elif origin is List : sub_field_type = get_args(sub_field_type)[0] t for t in get_args(sub_field_type) if t is not type(None)
)
elif origin is List:
sub_field_type = get_args(sub_field_type)[0]
# Map Pydantic types to argparse types # Map Pydantic types to argparse types
print(sub_field_type, type(sub_field_type)) print(sub_field_type, type(sub_field_type))
if isinstance(sub_field_type, type) and issubclass(sub_field_type, (int, float, str, bool)): if isinstance(sub_field_type, type) and issubclass(
sub_field_type, (int, float, str, bool)
):
arg_type = sub_field_type arg_type = sub_field_type
else: else:
arg_type = str # Default to string for unknown types arg_type = str # Default to string for unknown types
# Add the argument for each field in the sub-model # Add the argument for each field in the sub-model
group.add_argument(f"--{sub_field_name}", type=arg_type, help=help_text) group.add_argument(f"--{sub_field_name}", type=arg_type, help=help_text)
return parser return parser
def convert_args_to_dict(args: argparse.Namespace, parser: argparse.ArgumentParser): def convert_args_to_dict(args: argparse.Namespace, parser: argparse.ArgumentParser):
"""Broad conversion of surface level arg groups to dictionaries""" """Broad conversion of surface level arg groups to dictionaries"""
@@ -81,4 +91,4 @@ def convert_args_to_dict(args: argparse.Namespace, parser: argparse.ArgumentPars
arg_groups[group.title] = group_dict arg_groups[group.title] = group_dict
return arg_groups return arg_groups

9
main.py
View File

@@ -69,12 +69,14 @@ async def entrypoint_async():
model_path = pathlib.Path(config.model.model_dir) model_path = pathlib.Path(config.model.model_dir)
model_path = model_path / model_name model_path = model_path / model_name
await model.load_model(model_path.resolve(), **config.model) # TODO: remove model_dump()
await model.load_model(model_path.resolve(), **config.model.model_dump())
# Load loras after loading the model # Load loras after loading the model
if config.lora.loras: if config.lora.loras:
lora_dir = pathlib.Path(config.lora.lora_dir) lora_dir = pathlib.Path(config.lora.lora_dir)
await model.container.load_loras(lora_dir.resolve(), **config.lora) # TODO: remove model_dump()
await model.container.load_loras(lora_dir.resolve(), **config.lora.model_dump())
# If an initial embedding model name is specified, create a separate container # If an initial embedding model name is specified, create a separate container
# and load the model # and load the model
@@ -84,7 +86,8 @@ async def entrypoint_async():
embedding_model_path = embedding_model_path / embedding_model_name embedding_model_path = embedding_model_path / embedding_model_name
try: try:
await model.load_embedding_model(embedding_model_path, **config.embeddings) # TODO: remove model_dump()
await model.load_embedding_model(embedding_model_path, **config.embeddings.model_dump())
except ImportError as ex: except ImportError as ex:
logger.error(ex.msg) logger.error(ex.msg)