jalr/tabbyAPI-ollama
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

fix model names

Browse source
This commit is contained in:
TerminalMan 2024-09-12 17:00:07 +01:00
parent 05f1c3e293
commit 8b48f00271
2 changed files with 38 additions and 35 deletions
Download patch file Download diff file Expand all files Collapse all files

52
common/config_models.py
View file

@ -4,13 +4,13 @@ from typing import List, Optional, Union
from common.utils import unwrap from common.utils import unwrap
class config_config_model(BaseModel): class ConfigConfig(BaseModel):
config: Optional[str] = Field( config: Optional[str] = Field(
None, description=("Path to an overriding config.yml file") None, description=("Path to an overriding config.yml file")
) )
class network_config_model(BaseModel): class NetworkConfig(BaseModel):
host: Optional[str] = Field("127.0.0.1", description=("The IP to host on")) host: Optional[str] = Field("127.0.0.1", description=("The IP to host on"))
port: Optional[int] = Field(5000, description=("The port to host on")) port: Optional[int] = Field(5000, description=("The port to host on"))
disable_auth: Optional[bool] = Field( disable_auth: Optional[bool] = Field(
@ -28,7 +28,7 @@ class network_config_model(BaseModel):
) )
class logging_config_model(BaseModel): class LoggingConfig(BaseModel):
log_prompt: Optional[bool] = Field(False, description=("Enable prompt logging")) log_prompt: Optional[bool] = Field(False, description=("Enable prompt logging"))
log_generation_params: Optional[bool] = Field( log_generation_params: Optional[bool] = Field(
False, description=("Enable generation parameter logging") False, description=("Enable generation parameter logging")
@ -36,7 +36,7 @@ class logging_config_model(BaseModel):
log_requests: Optional[bool] = Field(False, description=("Enable request logging")) log_requests: Optional[bool] = Field(False, description=("Enable request logging"))
class model_config_model(BaseModel): class ModelConfig(BaseModel):
model_dir: str = Field( model_dir: str = Field(
"models", "models",
description=( description=(
@ -171,8 +171,10 @@ class model_config_model(BaseModel):
), ),
) )
model_config = ConfigDict(protected_namespaces=())
class draft_model_config_model(BaseModel):
class DraftModelConfig(BaseModel):
draft_model_dir: Optional[str] = Field( draft_model_dir: Optional[str] = Field(
"models", "models",
description=( description=(
@ -209,18 +211,18 @@ class draft_model_config_model(BaseModel):
) )
class lora_instance_model(BaseModel): class LoraInstanceModel(BaseModel):
name: str = Field(..., description=("Name of the LoRA model")) name: str = Field(..., description=("Name of the LoRA model"))
scaling: float = Field( scaling: float = Field(
1.0, description=("Scaling factor for the LoRA model (default: 1.0)") 1.0, description=("Scaling factor for the LoRA model (default: 1.0)")
) )
class lora_config_model(BaseModel): class LoraConfig(BaseModel):
lora_dir: Optional[str] = Field( lora_dir: Optional[str] = Field(
"loras", description=("Directory to look for LoRAs (default: 'loras')") "loras", description=("Directory to look for LoRAs (default: 'loras')")
) )
loras: Optional[List[lora_instance_model]] = Field( loras: Optional[List[LoraInstanceModel]] = Field(
None, None,
description=( description=(
"List of LoRAs to load and associated scaling factors (default scaling:" "List of LoRAs to load and associated scaling factors (default scaling:"
@ -229,13 +231,13 @@ class lora_config_model(BaseModel):
) )
class sampling_config_model(BaseModel): class SamplingConfig(BaseModel):
override_preset: Optional[str] = Field( override_preset: Optional[str] = Field(
None, description=("Select a sampler override preset") None, description=("Select a sampler override preset")
) )
class developer_config_model(BaseModel): class DeveloperConfig(BaseModel):
unsafe_launch: Optional[bool] = Field( unsafe_launch: Optional[bool] = Field(
False, description=("Skip Exllamav2 version check") False, description=("Skip Exllamav2 version check")
) )
@ -257,7 +259,7 @@ class developer_config_model(BaseModel):
) )
class embeddings_config_model(BaseModel): class EmbeddingsConfig(BaseModel):
embedding_model_dir: Optional[str] = Field( embedding_model_dir: Optional[str] = Field(
"models", "models",
description=( description=(
@ -276,18 +278,20 @@ class embeddings_config_model(BaseModel):
) )
class tabby_config_model(BaseModel): class TabbyConfigModel(BaseModel):
config: config_config_model = Field(default_factory=config_config_model) config: ConfigConfig = Field(default_factory=ConfigConfig.model_construct)
network: network_config_model = Field(default_factory=network_config_model) network: NetworkConfig = Field(default_factory=NetworkConfig.model_construct)
logging: logging_config_model = Field(default_factory=logging_config_model) logging: LoggingConfig = Field(default_factory=LoggingConfig.model_construct)
model: model_config_model = Field(default_factory=model_config_model) model: ModelConfig = Field(default_factory=ModelConfig.model_construct)
draft_model: draft_model_config_model = Field( draft_model: DraftModelConfig = Field(
default_factory=draft_model_config_model default_factory=DraftModelConfig.model_construct
)
lora: LoraConfig = Field(default_factory=LoraConfig.model_construct)
sampling: SamplingConfig = Field(default_factory=SamplingConfig.model_construct)
developer: DeveloperConfig = Field(default_factory=DeveloperConfig.model_construct)
embeddings: EmbeddingsConfig = Field(
default_factory=EmbeddingsConfig.model_construct
) )
lora: lora_config_model = Field(default_factory=lora_config_model)
sampling: sampling_config_model = Field(default_factory=sampling_config_model)
developer: developer_config_model = Field(default_factory=developer_config_model)
embeddings: embeddings_config_model = Field(default_factory=embeddings_config_model)
@model_validator(mode="before") @model_validator(mode="before")
def set_defaults(cls, values): def set_defaults(cls, values):
@ -297,11 +301,11 @@ class tabby_config_model(BaseModel):
values[field_name] = cls.__annotations__[field_name](**default_instance) values[field_name] = cls.__annotations__[field_name](**default_instance)
return values return values
model_config = ConfigDict(validate_assignment=True) model_config = ConfigDict(validate_assignment=True, protected_namespaces=())
def generate_config_file(filename="config_sample.yml", indentation=2): def generate_config_file(filename="config_sample.yml", indentation=2):
schema = tabby_config_model.model_json_schema() schema = TabbyConfigModel.model_json_schema()
def dump_def(id: str, indent=2): def dump_def(id: str, indent=2):
yaml = "" yaml = ""

21
common/tabby_config.py
View file

@ -5,11 +5,10 @@ from typing import Optional
from os import getenv from os import getenv
from common.utils import unwrap, merge_dicts from common.utils import unwrap, merge_dicts
from common.config_models import tabby_config_model from common.config_models import TabbyConfigModel
import common.config_models
class TabbyConfig(tabby_config_model): class TabbyConfig(TabbyConfigModel):
# Persistent defaults # Persistent defaults
# TODO: make this pydantic? # TODO: make this pydantic?
model_defaults: dict = {} model_defaults: dict = {}
@ -26,11 +25,11 @@ class TabbyConfig(tabby_config_model):
merged_config = merge_dicts(*configs) merged_config = merge_dicts(*configs)
for field in tabby_config_model.model_fields.keys(): # validate and update config
value = unwrap(merged_config.get(field), {}) merged_config_model = TabbyConfigModel.model_validate(merged_config)
model = getattr(common.config_models, f"{field}_config_model") for field in TabbyConfigModel.model_fields.keys():
value = getattr(merged_config_model, field)
setattr(self, field, model.parse_obj(value)) setattr(self, field, value)
# Set model defaults dict once to prevent on-demand reconstruction # Set model defaults dict once to prevent on-demand reconstruction
# TODO: clean this up a bit # TODO: clean this up a bit
@ -71,7 +70,7 @@ class TabbyConfig(tabby_config_model):
config = self._from_file(pathlib.Path(config_override)) config = self._from_file(pathlib.Path(config_override))
return config # Return early if loading from file return config # Return early if loading from file
for key in tabby_config_model.model_fields.keys(): for key in TabbyConfigModel.model_fields.keys():
override = args.get(key) override = args.get(key)
if override: if override:
if key == "logging": if key == "logging":
@ -86,10 +85,10 @@ class TabbyConfig(tabby_config_model):
config = {} config = {}
for field_name in tabby_config_model.model_fields.keys(): for field_name in TabbyConfigModel.model_fields.keys():
section_config = {} section_config = {}
for sub_field_name in getattr( for sub_field_name in getattr(
tabby_config_model(), field_name TabbyConfigModel(), field_name
).model_fields.keys(): ).model_fields.keys():
setting = getenv(f"TABBY_{field_name}_{sub_field_name}".upper(), None) setting = getenv(f"TABBY_{field_name}_{sub_field_name}".upper(), None)
if setting is not None: if setting is not None: