重构capability层
This commit is contained in:
puke
puke
@@ -4,9 +4,9 @@ ReelForge Services
|
||||
Unified service layer providing simplified access to capabilities.
|
||||
"""
|
||||
|
||||
from reelforge.services.base import BaseService
|
||||
from reelforge.services.llm import LLMService
|
||||
from reelforge.services.tts import TTSService
|
||||
from reelforge.services.comfy_base_service import ComfyBaseService
|
||||
from reelforge.services.llm_service import LLMService
|
||||
from reelforge.services.tts_service import TTSService
|
||||
from reelforge.services.image import ImageService
|
||||
from reelforge.services.video import VideoService
|
||||
from reelforge.services.narration_generator import NarrationGeneratorService
|
||||
@@ -16,7 +16,7 @@ from reelforge.services.storyboard_processor import StoryboardProcessorService
|
||||
from reelforge.services.video_generator import VideoGeneratorService
|
||||
|
||||
__all__ = [
|
||||
"BaseService",
|
||||
"ComfyBaseService",
|
||||
"LLMService",
|
||||
"TTSService",
|
||||
"ImageService",
|
||||
|
||||
@@ -1,85 +0,0 @@
|
||||
"""
|
||||
Base service class for all capability services
|
||||
"""
|
||||
|
||||
from abc import ABC, abstractmethod
|
||||
from typing import Any, Optional
|
||||
|
||||
from reelforge.core.config_manager import ConfigManager
|
||||
|
||||
|
||||
class BaseService(ABC):
|
||||
"""
|
||||
Base service class for all capability services
|
||||
|
||||
Provides callable interface and basic properties:
|
||||
- Direct call: result = await service(...)
|
||||
- Active capability: service.active
|
||||
- Available IDs: service.available
|
||||
|
||||
Usage:
|
||||
result = await reelforge.llm("Hello world")
|
||||
print(f"Using: {reelforge.llm.active}")
|
||||
print(f"Available: {reelforge.llm.available}")
|
||||
"""
|
||||
|
||||
def __init__(self, config_manager: ConfigManager, capability_type: str):
|
||||
"""
|
||||
Initialize service
|
||||
|
||||
Args:
|
||||
config_manager: ConfigManager instance
|
||||
capability_type: Type of capability (llm, tts, etc.)
|
||||
"""
|
||||
self._config_manager = config_manager
|
||||
self._capability_type = capability_type
|
||||
|
||||
@abstractmethod
|
||||
async def __call__(self, **kwargs) -> Any:
|
||||
"""
|
||||
Make service callable directly
|
||||
|
||||
This is the main entry point for using the service.
|
||||
Subclasses MUST implement this with specific signatures.
|
||||
|
||||
Example:
|
||||
answer = await reelforge.llm(prompt="Hello")
|
||||
"""
|
||||
pass
|
||||
|
||||
@property
|
||||
def active(self) -> Optional[str]:
|
||||
"""
|
||||
Get active capability ID
|
||||
|
||||
Returns:
|
||||
Active capability ID (e.g., "call") or None if not set
|
||||
|
||||
Example:
|
||||
print(f"Using LLM: {reelforge.llm.active}")
|
||||
"""
|
||||
return self._config_manager.get_active(self._capability_type)
|
||||
|
||||
@property
|
||||
def available(self) -> list[str]:
|
||||
"""
|
||||
List available capability IDs
|
||||
|
||||
Returns:
|
||||
List of capability IDs
|
||||
|
||||
Example:
|
||||
print(f"Available LLMs: {reelforge.llm.available}")
|
||||
"""
|
||||
return self._config_manager.get_available_ids(self._capability_type)
|
||||
|
||||
def __repr__(self) -> str:
|
||||
"""String representation"""
|
||||
active = self.active or "none"
|
||||
available = ", ".join(self.available) if self.available else "none"
|
||||
return (
|
||||
f"<{self.__class__.__name__} "
|
||||
f"active={active!r} "
|
||||
f"available=[{available}]>"
|
||||
)
|
||||
|
||||
191
reelforge/services/comfy_base_service.py
Normal file
191
reelforge/services/comfy_base_service.py
Normal file
@@ -0,0 +1,191 @@
|
||||
"""
|
||||
ComfyUI Base Service - Common logic for ComfyUI-based services
|
||||
"""
|
||||
|
||||
import os
|
||||
from pathlib import Path
|
||||
from typing import Optional, List, Dict, Any
|
||||
|
||||
from comfykit import ComfyKit
|
||||
from loguru import logger
|
||||
|
||||
|
||||
class ComfyBaseService:
|
||||
"""
|
||||
Base service for ComfyUI workflow-based capabilities
|
||||
|
||||
Provides common functionality for TTS, Image, and other ComfyUI-based services.
|
||||
|
||||
Subclasses should define:
|
||||
- WORKFLOW_PREFIX: Prefix for workflow files (e.g., "image_", "tts_")
|
||||
- DEFAULT_WORKFLOW: Default workflow filename (e.g., "image_default.json")
|
||||
- WORKFLOWS_DIR: Directory containing workflows (default: "workflows")
|
||||
"""
|
||||
|
||||
WORKFLOW_PREFIX: str = "" # Must be overridden by subclass
|
||||
DEFAULT_WORKFLOW: str = "" # Must be overridden by subclass
|
||||
WORKFLOWS_DIR: str = "workflows"
|
||||
|
||||
def __init__(self, config: dict, service_name: str):
|
||||
"""
|
||||
Initialize ComfyUI base service
|
||||
|
||||
Args:
|
||||
config: Full application config dict
|
||||
service_name: Service name in config (e.g., "tts", "image")
|
||||
"""
|
||||
self.config = config.get(service_name, {})
|
||||
self.service_name = service_name
|
||||
self._workflows_cache: Optional[List[str]] = None
|
||||
|
||||
def _scan_workflows(self) -> List[str]:
|
||||
"""
|
||||
Scan workflows/{prefix}*.json files
|
||||
|
||||
Returns:
|
||||
List of workflow filenames
|
||||
Example: ["image_default.json", "image_flux.json"]
|
||||
"""
|
||||
workflows = []
|
||||
workflows_dir = Path(self.WORKFLOWS_DIR)
|
||||
|
||||
if not workflows_dir.exists():
|
||||
logger.warning(f"Workflows directory not found: {workflows_dir}")
|
||||
return workflows
|
||||
|
||||
# Scan for {prefix}_*.json files
|
||||
for file in workflows_dir.glob(f"{self.WORKFLOW_PREFIX}*.json"):
|
||||
workflows.append(file.name)
|
||||
logger.debug(f"Found {self.service_name} workflow: {file.name}")
|
||||
|
||||
return sorted(workflows)
|
||||
|
||||
def _get_default_workflow(self) -> str:
|
||||
"""
|
||||
Get default workflow name from config or use DEFAULT_WORKFLOW
|
||||
|
||||
Returns:
|
||||
Default workflow filename
|
||||
"""
|
||||
return self.config.get("default_workflow", self.DEFAULT_WORKFLOW)
|
||||
|
||||
def _resolve_workflow(self, workflow: Optional[str] = None) -> str:
|
||||
"""
|
||||
Resolve workflow to actual workflow path
|
||||
|
||||
Args:
|
||||
workflow: Workflow filename (e.g., "image_default.json")
|
||||
Can also be:
|
||||
- Absolute path: "/path/to/workflow.json"
|
||||
- Relative path: "custom/workflow.json"
|
||||
- URL: "http://..."
|
||||
- RunningHub ID: "12345"
|
||||
|
||||
Returns:
|
||||
Workflow file path or identifier
|
||||
|
||||
Raises:
|
||||
ValueError: If workflow not found
|
||||
"""
|
||||
# 1. If not specified, use default
|
||||
if workflow is None:
|
||||
workflow = self._get_default_workflow()
|
||||
|
||||
# 2. If it's an absolute path, URL, or looks like RunningHub ID, use as-is
|
||||
if (workflow.startswith("/") or
|
||||
workflow.startswith("http://") or
|
||||
workflow.startswith("https://") or
|
||||
workflow.isdigit()):
|
||||
logger.debug(f"Using workflow identifier: {workflow}")
|
||||
return workflow
|
||||
|
||||
# 3. If it's just a filename, look in workflows/ directory
|
||||
workflow_path = Path(self.WORKFLOWS_DIR) / workflow
|
||||
|
||||
if not workflow_path.exists():
|
||||
# List available workflows for error message
|
||||
available = self._scan_workflows()
|
||||
available_str = ", ".join(available) if available else "none"
|
||||
raise ValueError(
|
||||
f"Workflow '{workflow}' not found at {workflow_path}. "
|
||||
f"Available workflows: {available_str}\n"
|
||||
f"Please create: {workflow_path}"
|
||||
)
|
||||
|
||||
logger.info(f"🎬 Using {self.service_name} workflow: {workflow}")
|
||||
return str(workflow_path)
|
||||
|
||||
def _prepare_comfykit_config(
|
||||
self,
|
||||
comfyui_url: Optional[str] = None,
|
||||
runninghub_api_key: Optional[str] = None,
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Prepare ComfyKit configuration
|
||||
|
||||
Args:
|
||||
comfyui_url: ComfyUI URL (optional, overrides config)
|
||||
runninghub_api_key: RunningHub API key (optional, overrides config)
|
||||
|
||||
Returns:
|
||||
ComfyKit configuration dict
|
||||
"""
|
||||
kit_config = {}
|
||||
|
||||
# ComfyUI URL (priority: param > config > env > default)
|
||||
final_comfyui_url = (
|
||||
comfyui_url
|
||||
or self.config.get("comfyui_url")
|
||||
or os.getenv("COMFYUI_BASE_URL")
|
||||
or "http://127.0.0.1:8188"
|
||||
)
|
||||
kit_config["comfyui_url"] = final_comfyui_url
|
||||
|
||||
# RunningHub API key (priority: param > config > env)
|
||||
final_rh_key = (
|
||||
runninghub_api_key
|
||||
or self.config.get("runninghub_api_key")
|
||||
or os.getenv("RUNNINGHUB_API_KEY")
|
||||
)
|
||||
if final_rh_key:
|
||||
kit_config["runninghub_api_key"] = final_rh_key
|
||||
|
||||
logger.debug(f"ComfyKit config: {kit_config}")
|
||||
return kit_config
|
||||
|
||||
def list_workflows(self) -> List[str]:
|
||||
"""
|
||||
List all available workflows
|
||||
|
||||
Returns:
|
||||
List of workflow filenames (sorted alphabetically)
|
||||
|
||||
Example:
|
||||
workflows = service.list_workflows()
|
||||
# ['image_default.json', 'image_flux.json']
|
||||
"""
|
||||
return self._scan_workflows()
|
||||
|
||||
@property
|
||||
def available(self) -> List[str]:
|
||||
"""
|
||||
List available workflows
|
||||
|
||||
Returns:
|
||||
List of available workflow filenames
|
||||
|
||||
Example:
|
||||
print(f"Available workflows: {service.available}")
|
||||
"""
|
||||
return self.list_workflows()
|
||||
|
||||
def __repr__(self) -> str:
|
||||
"""String representation"""
|
||||
default = self._get_default_workflow()
|
||||
available = ", ".join(self.available) if self.available else "none"
|
||||
return (
|
||||
f"<{self.__class__.__name__} "
|
||||
f"default={default!r} "
|
||||
f"available=[{available}]>"
|
||||
)
|
||||
|
||||
@@ -1,42 +1,37 @@
|
||||
"""
|
||||
Image Generation Service - Workflow-based, no capability layer
|
||||
|
||||
This service directly uses ComfyKit to execute workflows without going through
|
||||
the capability abstraction layer. This is because workflow files themselves
|
||||
already provide sufficient abstraction and flexibility.
|
||||
Image Generation Service - ComfyUI Workflow-based implementation
|
||||
"""
|
||||
|
||||
import os
|
||||
from pathlib import Path
|
||||
from typing import Optional, List, Dict
|
||||
from typing import Optional
|
||||
|
||||
from comfykit import ComfyKit
|
||||
from loguru import logger
|
||||
|
||||
from reelforge.services.comfy_base_service import ComfyBaseService
|
||||
|
||||
class ImageService:
|
||||
|
||||
class ImageService(ComfyBaseService):
|
||||
"""
|
||||
Image generation service - Workflow-based
|
||||
|
||||
Directly uses ComfyKit to execute workflows. No capability abstraction needed
|
||||
since workflow itself is already the abstraction.
|
||||
Uses ComfyKit to execute image generation workflows.
|
||||
|
||||
Usage:
|
||||
# Use default preset (workflows/image_default.json)
|
||||
# Use default workflow (workflows/image_default.json)
|
||||
image_url = await reelforge.image(prompt="a cat")
|
||||
|
||||
# Use specific preset
|
||||
image_url = await reelforge.image(preset="flux", prompt="a cat")
|
||||
# Use specific workflow
|
||||
image_url = await reelforge.image(
|
||||
prompt="a cat",
|
||||
workflow="image_flux.json"
|
||||
)
|
||||
|
||||
# List available presets
|
||||
presets = reelforge.image.list_presets()
|
||||
|
||||
# Get preset path
|
||||
path = reelforge.image.get_preset_path("flux")
|
||||
# List available workflows
|
||||
workflows = reelforge.image.list_workflows()
|
||||
"""
|
||||
|
||||
PRESET_PREFIX = "image_"
|
||||
DEFAULT_PRESET = "default"
|
||||
WORKFLOW_PREFIX = "image_"
|
||||
DEFAULT_WORKFLOW = "image_default.json"
|
||||
WORKFLOWS_DIR = "workflows"
|
||||
|
||||
def __init__(self, config: dict):
|
||||
@@ -46,105 +41,11 @@ class ImageService:
|
||||
Args:
|
||||
config: Full application config dict
|
||||
"""
|
||||
self.config = config.get("image", {})
|
||||
self._presets_cache: Optional[Dict[str, str]] = None
|
||||
|
||||
def _scan_presets(self) -> Dict[str, str]:
|
||||
"""
|
||||
Scan workflows/image_*.json files
|
||||
|
||||
Returns:
|
||||
Dict mapping preset name to workflow path
|
||||
Example: {"default": "workflows/image_default.json", "flux": "workflows/image_flux.json"}
|
||||
"""
|
||||
if self._presets_cache is not None:
|
||||
return self._presets_cache
|
||||
|
||||
presets = {}
|
||||
workflows_dir = Path(self.WORKFLOWS_DIR)
|
||||
|
||||
if not workflows_dir.exists():
|
||||
logger.warning(f"Workflows directory not found: {workflows_dir}")
|
||||
return presets
|
||||
|
||||
# Scan for image_*.json files
|
||||
for file in workflows_dir.glob(f"{self.PRESET_PREFIX}*.json"):
|
||||
# Extract preset name: "image_flux.json" -> "flux"
|
||||
preset_name = file.stem.replace(self.PRESET_PREFIX, "")
|
||||
presets[preset_name] = str(file)
|
||||
logger.debug(f"Found image preset: {preset_name} -> {file}")
|
||||
|
||||
self._presets_cache = presets
|
||||
return presets
|
||||
|
||||
def _get_default_preset(self) -> str:
|
||||
"""
|
||||
Get default preset name from config or use "default"
|
||||
|
||||
Priority:
|
||||
1. config.yaml: image.default
|
||||
2. "default"
|
||||
"""
|
||||
return self.config.get("default", self.DEFAULT_PRESET)
|
||||
|
||||
def _resolve_workflow(
|
||||
self,
|
||||
preset: Optional[str] = None,
|
||||
workflow: Optional[str] = None
|
||||
) -> str:
|
||||
"""
|
||||
Resolve preset/workflow to actual workflow path
|
||||
|
||||
Args:
|
||||
preset: Preset name (e.g., "flux", "default")
|
||||
workflow: Full workflow path (for backward compatibility)
|
||||
|
||||
Returns:
|
||||
Workflow file path
|
||||
|
||||
Raises:
|
||||
ValueError: If preset not found or no workflows available
|
||||
"""
|
||||
# 1. If explicit workflow path provided, use it
|
||||
if workflow:
|
||||
logger.debug(f"Using explicit workflow: {workflow}")
|
||||
return workflow
|
||||
|
||||
# 2. Scan available presets
|
||||
presets = self._scan_presets()
|
||||
|
||||
if not presets:
|
||||
raise ValueError(
|
||||
f"No workflow presets found in {self.WORKFLOWS_DIR}/ directory. "
|
||||
f"Please create at least one workflow file: {self.WORKFLOWS_DIR}/{self.PRESET_PREFIX}default.json"
|
||||
)
|
||||
|
||||
# 3. Determine which preset to use
|
||||
if preset:
|
||||
# Use specified preset
|
||||
target_preset = preset
|
||||
else:
|
||||
# Use default preset
|
||||
target_preset = self._get_default_preset()
|
||||
|
||||
# 4. Lookup preset
|
||||
if target_preset not in presets:
|
||||
available = ", ".join(sorted(presets.keys()))
|
||||
raise ValueError(
|
||||
f"Preset '{target_preset}' not found. "
|
||||
f"Available presets: {available}\n"
|
||||
f"Please create: {self.WORKFLOWS_DIR}/{self.PRESET_PREFIX}{target_preset}.json"
|
||||
)
|
||||
|
||||
workflow_path = presets[target_preset]
|
||||
logger.info(f"🎨 Using image preset: {target_preset} ({workflow_path})")
|
||||
|
||||
return workflow_path
|
||||
super().__init__(config, service_name="image")
|
||||
|
||||
async def __call__(
|
||||
self,
|
||||
prompt: str,
|
||||
preset: Optional[str] = None,
|
||||
workflow: Optional[str] = None,
|
||||
# ComfyUI connection (optional overrides)
|
||||
comfyui_url: Optional[str] = None,
|
||||
@@ -164,8 +65,7 @@ class ImageService:
|
||||
|
||||
Args:
|
||||
prompt: Image generation prompt
|
||||
preset: Preset name (default: from config or "default")
|
||||
workflow: Full workflow path (backward compatible)
|
||||
workflow: Workflow filename (default: from config or "image_default.json")
|
||||
comfyui_url: ComfyUI URL (optional, overrides config)
|
||||
runninghub_api_key: RunningHub API key (optional, overrides config)
|
||||
width: Image width
|
||||
@@ -181,26 +81,29 @@ class ImageService:
|
||||
Generated image URL/path
|
||||
|
||||
Examples:
|
||||
# Simplest: use default preset (workflows/image_default.json)
|
||||
# Simplest: use default workflow (workflows/image_default.json)
|
||||
image_url = await reelforge.image(prompt="a beautiful cat")
|
||||
|
||||
# Use specific preset
|
||||
image_url = await reelforge.image(preset="flux", prompt="a cat")
|
||||
# Use specific workflow
|
||||
image_url = await reelforge.image(
|
||||
prompt="a cat",
|
||||
workflow="image_flux.json"
|
||||
)
|
||||
|
||||
# With additional parameters
|
||||
image_url = await reelforge.image(
|
||||
preset="flux",
|
||||
prompt="a cat",
|
||||
workflow="image_flux.json",
|
||||
width=1024,
|
||||
height=1024,
|
||||
steps=20,
|
||||
seed=42
|
||||
)
|
||||
|
||||
# Backward compatible: direct workflow path
|
||||
# With absolute path
|
||||
image_url = await reelforge.image(
|
||||
workflow="workflows/custom.json",
|
||||
prompt="a cat"
|
||||
prompt="a cat",
|
||||
workflow="/path/to/custom.json"
|
||||
)
|
||||
|
||||
# With custom ComfyUI server
|
||||
@@ -210,30 +113,13 @@ class ImageService:
|
||||
)
|
||||
"""
|
||||
# 1. Resolve workflow path
|
||||
workflow_path = self._resolve_workflow(preset=preset, workflow=workflow)
|
||||
workflow_path = self._resolve_workflow(workflow=workflow)
|
||||
|
||||
# 2. Prepare ComfyKit config
|
||||
kit_config = {}
|
||||
|
||||
# ComfyUI URL (priority: param > config > env > default)
|
||||
final_comfyui_url = (
|
||||
comfyui_url
|
||||
or self.config.get("comfyui_url")
|
||||
or os.getenv("COMFYUI_BASE_URL")
|
||||
or "http://127.0.0.1:8188"
|
||||
kit_config = self._prepare_comfykit_config(
|
||||
comfyui_url=comfyui_url,
|
||||
runninghub_api_key=runninghub_api_key
|
||||
)
|
||||
kit_config["comfyui_url"] = final_comfyui_url
|
||||
|
||||
# RunningHub API key (priority: param > config > env)
|
||||
final_rh_key = (
|
||||
runninghub_api_key
|
||||
or self.config.get("runninghub_api_key")
|
||||
or os.getenv("RUNNINGHUB_API_KEY")
|
||||
)
|
||||
if final_rh_key:
|
||||
kit_config["runninghub_api_key"] = final_rh_key
|
||||
|
||||
logger.debug(f"ComfyKit config: {kit_config}")
|
||||
|
||||
# 3. Build workflow parameters
|
||||
workflow_params = {"prompt": prompt}
|
||||
@@ -283,74 +169,3 @@ class ImageService:
|
||||
except Exception as e:
|
||||
logger.error(f"Image generation error: {e}")
|
||||
raise
|
||||
|
||||
def list_presets(self) -> List[str]:
|
||||
"""
|
||||
List all available image presets
|
||||
|
||||
Returns:
|
||||
List of preset names (sorted alphabetically)
|
||||
|
||||
Example:
|
||||
presets = reelforge.image.list_presets()
|
||||
# ['anime', 'default', 'flux', 'sd15']
|
||||
"""
|
||||
return sorted(self._scan_presets().keys())
|
||||
|
||||
def get_preset_path(self, preset: str) -> Optional[str]:
|
||||
"""
|
||||
Get workflow path for a preset
|
||||
|
||||
Args:
|
||||
preset: Preset name
|
||||
|
||||
Returns:
|
||||
Workflow file path, or None if not found
|
||||
|
||||
Example:
|
||||
path = reelforge.image.get_preset_path("flux")
|
||||
# 'workflows/image_flux.json'
|
||||
"""
|
||||
return self._scan_presets().get(preset)
|
||||
|
||||
@property
|
||||
def active(self) -> str:
|
||||
"""
|
||||
Get active preset name
|
||||
|
||||
This property is provided for compatibility with other services
|
||||
that use the capability layer.
|
||||
|
||||
Returns:
|
||||
Active preset name
|
||||
|
||||
Example:
|
||||
print(f"Using preset: {reelforge.image.active}")
|
||||
"""
|
||||
return self._get_default_preset()
|
||||
|
||||
@property
|
||||
def available(self) -> List[str]:
|
||||
"""
|
||||
List available presets
|
||||
|
||||
This property is provided for compatibility with other services
|
||||
that use the capability layer.
|
||||
|
||||
Returns:
|
||||
List of available preset names
|
||||
|
||||
Example:
|
||||
print(f"Available presets: {reelforge.image.available}")
|
||||
"""
|
||||
return self.list_presets()
|
||||
|
||||
def __repr__(self) -> str:
|
||||
"""String representation"""
|
||||
active = self.active
|
||||
available = ", ".join(self.available) if self.available else "none"
|
||||
return (
|
||||
f"<ImageService "
|
||||
f"active={active!r} "
|
||||
f"available=[{available}]>"
|
||||
)
|
||||
|
||||
@@ -1,97 +0,0 @@
|
||||
"""
|
||||
LLM (Large Language Model) Service
|
||||
"""
|
||||
|
||||
from typing import Optional
|
||||
|
||||
from reelforge.services.base import BaseService
|
||||
|
||||
|
||||
class LLMService(BaseService):
|
||||
"""
|
||||
LLM (Large Language Model) service
|
||||
|
||||
Provides unified access to various LLM providers (Qwen, OpenAI, DeepSeek, Ollama, etc.)
|
||||
|
||||
Usage:
|
||||
# Direct call (recommended)
|
||||
answer = await reelforge.llm("Explain atomic habits")
|
||||
|
||||
# With parameters
|
||||
answer = await reelforge.llm(
|
||||
prompt="Explain atomic habits in 3 sentences",
|
||||
temperature=0.7,
|
||||
max_tokens=2000
|
||||
)
|
||||
|
||||
# Explicit call syntax
|
||||
answer = await reelforge.llm.call(prompt="Hello")
|
||||
|
||||
# Check active LLM
|
||||
print(f"Using: {reelforge.llm.active}")
|
||||
|
||||
# List available LLMs
|
||||
print(f"Available: {reelforge.llm.available}")
|
||||
"""
|
||||
|
||||
def __init__(self, router):
|
||||
super().__init__(router, "llm")
|
||||
|
||||
async def __call__(
|
||||
self,
|
||||
prompt: str,
|
||||
api_key: Optional[str] = None,
|
||||
base_url: Optional[str] = None,
|
||||
model: Optional[str] = None,
|
||||
temperature: Optional[float] = None,
|
||||
max_tokens: Optional[int] = None,
|
||||
**kwargs
|
||||
) -> str:
|
||||
"""
|
||||
Generate text using LLM
|
||||
|
||||
Args:
|
||||
prompt: The prompt to generate from
|
||||
api_key: API key (optional, uses config if not provided)
|
||||
base_url: Base URL (optional, uses config if not provided)
|
||||
model: Model name (optional, uses config if not provided)
|
||||
temperature: Sampling temperature (0.0-2.0). Lower is more deterministic.
|
||||
max_tokens: Maximum tokens to generate
|
||||
**kwargs: Additional provider-specific parameters
|
||||
|
||||
Returns:
|
||||
Generated text
|
||||
|
||||
Examples:
|
||||
# Use config from config.yaml
|
||||
answer = await reelforge.llm("Explain atomic habits")
|
||||
|
||||
# Override with custom parameters
|
||||
answer = await reelforge.llm(
|
||||
"Explain the concept of atomic habits in 3 sentences",
|
||||
api_key="sk-custom-key",
|
||||
base_url="https://api.custom.com/v1",
|
||||
model="custom-model",
|
||||
temperature=0.7,
|
||||
max_tokens=500
|
||||
)
|
||||
"""
|
||||
params = {"prompt": prompt}
|
||||
|
||||
# Add optional LLM parameters (will override config if provided)
|
||||
if api_key is not None:
|
||||
params["api_key"] = api_key
|
||||
if base_url is not None:
|
||||
params["base_url"] = base_url
|
||||
if model is not None:
|
||||
params["model"] = model
|
||||
|
||||
if temperature is not None:
|
||||
params["temperature"] = temperature
|
||||
if max_tokens is not None:
|
||||
params["max_tokens"] = max_tokens
|
||||
|
||||
params.update(kwargs)
|
||||
|
||||
return await self._config_manager.call(self._capability_type, **params)
|
||||
|
||||
184
reelforge/services/llm_service.py
Normal file
184
reelforge/services/llm_service.py
Normal file
@@ -0,0 +1,184 @@
|
||||
"""
|
||||
LLM (Large Language Model) Service - Direct OpenAI SDK implementation
|
||||
"""
|
||||
|
||||
import os
|
||||
from typing import Optional
|
||||
|
||||
from openai import AsyncOpenAI
|
||||
from loguru import logger
|
||||
|
||||
|
||||
class LLMService:
|
||||
"""
|
||||
LLM (Large Language Model) service
|
||||
|
||||
Direct implementation using OpenAI SDK. No capability layer needed.
|
||||
|
||||
Supports all OpenAI SDK compatible providers:
|
||||
- OpenAI (gpt-4o, gpt-4o-mini, gpt-3.5-turbo)
|
||||
- Alibaba Qwen (qwen-max, qwen-plus, qwen-turbo)
|
||||
- Anthropic Claude (claude-sonnet-4-5, claude-opus-4, claude-haiku-4)
|
||||
- DeepSeek (deepseek-chat)
|
||||
- Moonshot Kimi (moonshot-v1-8k, moonshot-v1-32k, moonshot-v1-128k)
|
||||
- Ollama (llama3.2, qwen2.5, mistral, codellama) - FREE & LOCAL!
|
||||
- Any custom provider with OpenAI-compatible API
|
||||
|
||||
Usage:
|
||||
# Direct call
|
||||
answer = await reelforge.llm("Explain atomic habits")
|
||||
|
||||
# With parameters
|
||||
answer = await reelforge.llm(
|
||||
prompt="Explain atomic habits in 3 sentences",
|
||||
temperature=0.7,
|
||||
max_tokens=2000
|
||||
)
|
||||
"""
|
||||
|
||||
def __init__(self, config: dict):
|
||||
"""
|
||||
Initialize LLM service
|
||||
|
||||
Args:
|
||||
config: Full application config dict
|
||||
"""
|
||||
self.config = config.get("llm", {})
|
||||
self._client: Optional[AsyncOpenAI] = None
|
||||
|
||||
def _get_config_value(self, key: str, default=None):
|
||||
"""
|
||||
Get config value from config file
|
||||
|
||||
Args:
|
||||
key: Config key name
|
||||
default: Default value if not found
|
||||
|
||||
Returns:
|
||||
Config value
|
||||
"""
|
||||
return self.config.get(key, default)
|
||||
|
||||
def _create_client(
|
||||
self,
|
||||
api_key: Optional[str] = None,
|
||||
base_url: Optional[str] = None,
|
||||
) -> AsyncOpenAI:
|
||||
"""
|
||||
Create OpenAI client
|
||||
|
||||
Args:
|
||||
api_key: API key (optional, uses config if not provided)
|
||||
base_url: Base URL (optional, uses config if not provided)
|
||||
|
||||
Returns:
|
||||
AsyncOpenAI client instance
|
||||
"""
|
||||
# Get API key (priority: parameter > config)
|
||||
final_api_key = (
|
||||
api_key
|
||||
or self._get_config_value("api_key")
|
||||
or "dummy-key" # Ollama doesn't need real key
|
||||
)
|
||||
|
||||
# Get base URL (priority: parameter > config)
|
||||
final_base_url = (
|
||||
base_url
|
||||
or self._get_config_value("base_url")
|
||||
)
|
||||
|
||||
# Create client
|
||||
client_kwargs = {"api_key": final_api_key}
|
||||
if final_base_url:
|
||||
client_kwargs["base_url"] = final_base_url
|
||||
|
||||
return AsyncOpenAI(**client_kwargs)
|
||||
|
||||
async def __call__(
|
||||
self,
|
||||
prompt: str,
|
||||
api_key: Optional[str] = None,
|
||||
base_url: Optional[str] = None,
|
||||
model: Optional[str] = None,
|
||||
temperature: float = 0.7,
|
||||
max_tokens: int = 2000,
|
||||
**kwargs
|
||||
) -> str:
|
||||
"""
|
||||
Generate text using LLM
|
||||
|
||||
Args:
|
||||
prompt: The prompt to generate from
|
||||
api_key: API key (optional, uses config if not provided)
|
||||
base_url: Base URL (optional, uses config if not provided)
|
||||
model: Model name (optional, uses config if not provided)
|
||||
temperature: Sampling temperature (0.0-2.0). Lower is more deterministic.
|
||||
max_tokens: Maximum tokens to generate
|
||||
**kwargs: Additional provider-specific parameters
|
||||
|
||||
Returns:
|
||||
Generated text
|
||||
|
||||
Examples:
|
||||
# Use config from config.yaml
|
||||
answer = await reelforge.llm("Explain atomic habits")
|
||||
|
||||
# Override with custom parameters
|
||||
answer = await reelforge.llm(
|
||||
prompt="Explain atomic habits in 3 sentences",
|
||||
api_key="sk-custom-key",
|
||||
base_url="https://api.custom.com/v1",
|
||||
model="custom-model",
|
||||
temperature=0.7,
|
||||
max_tokens=500
|
||||
)
|
||||
"""
|
||||
# Create client (new instance each time to support parameter overrides)
|
||||
client = self._create_client(api_key=api_key, base_url=base_url)
|
||||
|
||||
# Get model (priority: parameter > config)
|
||||
final_model = (
|
||||
model
|
||||
or self._get_config_value("model")
|
||||
or "gpt-3.5-turbo" # Default fallback
|
||||
)
|
||||
|
||||
logger.debug(f"LLM call: model={final_model}, base_url={client.base_url}")
|
||||
|
||||
try:
|
||||
response = await client.chat.completions.create(
|
||||
model=final_model,
|
||||
messages=[{"role": "user", "content": prompt}],
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
**kwargs
|
||||
)
|
||||
|
||||
result = response.choices[0].message.content
|
||||
logger.debug(f"LLM response length: {len(result)} chars")
|
||||
|
||||
return result
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"LLM call error (model={final_model}, base_url={client.base_url}): {e}")
|
||||
raise
|
||||
|
||||
@property
|
||||
def active(self) -> str:
|
||||
"""
|
||||
Get active model name
|
||||
|
||||
Returns:
|
||||
Active model name
|
||||
|
||||
Example:
|
||||
print(f"Using model: {reelforge.llm.active}")
|
||||
"""
|
||||
return self._get_config_value("model", "gpt-3.5-turbo")
|
||||
|
||||
def __repr__(self) -> str:
|
||||
"""String representation"""
|
||||
model = self.active
|
||||
base_url = self._get_config_value("base_url", "default")
|
||||
return f"<LLMService model={model!r} base_url={base_url!r}>"
|
||||
|
||||
@@ -123,7 +123,8 @@ class StoryboardProcessorService:
|
||||
# Call TTS
|
||||
audio_path = await self.core.tts(
|
||||
text=frame.narration,
|
||||
voice=config.voice_id
|
||||
voice=config.voice_id,
|
||||
rate="+20%",
|
||||
)
|
||||
|
||||
frame.audio_path = audio_path
|
||||
|
||||
@@ -1,103 +0,0 @@
|
||||
"""
|
||||
TTS (Text-to-Speech) Service
|
||||
"""
|
||||
|
||||
import base64
|
||||
import uuid
|
||||
from typing import Optional
|
||||
|
||||
from reelforge.services.base import BaseService
|
||||
from reelforge.utils.os_util import get_temp_path, save_bytes_to_file
|
||||
|
||||
|
||||
class TTSService(BaseService):
|
||||
"""
|
||||
TTS (Text-to-Speech) service
|
||||
|
||||
Provides unified access to various TTS providers (Edge TTS, Azure TTS, etc.)
|
||||
Returns path to saved audio file.
|
||||
|
||||
Usage:
|
||||
# Direct call (auto-generate temp path)
|
||||
audio_path = await reelforge.tts("Hello world")
|
||||
# Returns: "temp/abc123def456.mp3"
|
||||
|
||||
# With voice parameter
|
||||
audio_path = await reelforge.tts(
|
||||
text="你好，世界",
|
||||
voice="zh-CN-YunjianNeural"
|
||||
)
|
||||
|
||||
# Specify custom output path
|
||||
audio_path = await reelforge.tts(
|
||||
text="Hello",
|
||||
output_path="output/greeting.mp3"
|
||||
)
|
||||
|
||||
# Check active TTS
|
||||
print(f"Using: {reelforge.tts.active}")
|
||||
"""
|
||||
|
||||
def __init__(self, router):
|
||||
super().__init__(router, "tts")
|
||||
|
||||
async def __call__(
|
||||
self,
|
||||
text: str,
|
||||
voice: Optional[str] = None,
|
||||
rate: Optional[str] = None,
|
||||
output_path: Optional[str] = None,
|
||||
**kwargs
|
||||
) -> str:
|
||||
"""
|
||||
Convert text to speech and save to file
|
||||
|
||||
Args:
|
||||
text: Text to convert to speech
|
||||
voice: Voice ID (uses default if not specified)
|
||||
rate: Speech rate (e.g., "+0%", "+50%", "-20%")
|
||||
output_path: Output file path (default: temp/<uuid>.mp3)
|
||||
**kwargs: Additional provider-specific parameters
|
||||
|
||||
Returns:
|
||||
Path to saved audio file (str)
|
||||
|
||||
Example:
|
||||
# Auto-generate path
|
||||
audio_path = await reelforge.tts("Hello world")
|
||||
# Returns: "temp/abc123def456.mp3"
|
||||
|
||||
# Specify custom path
|
||||
audio_path = await reelforge.tts(
|
||||
"你好，世界",
|
||||
voice="zh-CN-YunjianNeural",
|
||||
output_path="output/greeting.mp3"
|
||||
)
|
||||
"""
|
||||
params = {"text": text}
|
||||
if voice is not None:
|
||||
params["voice"] = voice
|
||||
if rate is not None:
|
||||
params["rate"] = rate
|
||||
params.update(kwargs)
|
||||
|
||||
# Call capability and get base64-encoded audio
|
||||
audio_base64 = await self._config_manager.call(self._capability_type, **params)
|
||||
|
||||
# Decode base64 to bytes
|
||||
if isinstance(audio_base64, str):
|
||||
audio_data = base64.b64decode(audio_base64)
|
||||
else:
|
||||
audio_data = audio_base64
|
||||
|
||||
# Generate output path if not specified
|
||||
if output_path is None:
|
||||
# Generate UUID without hyphens for filename
|
||||
file_uuid = uuid.uuid4().hex
|
||||
output_path = get_temp_path(f"{file_uuid}.mp3")
|
||||
|
||||
# Save to file
|
||||
saved_path = save_bytes_to_file(audio_data, output_path)
|
||||
|
||||
return saved_path
|
||||
|
||||
311
reelforge/services/tts_service.py
Normal file
311
reelforge/services/tts_service.py
Normal file
@@ -0,0 +1,311 @@
|
||||
"""
|
||||
TTS (Text-to-Speech) Service - Dual implementation (Edge TTS + ComfyUI)
|
||||
"""
|
||||
|
||||
import uuid
|
||||
from typing import Optional
|
||||
|
||||
from comfykit import ComfyKit
|
||||
from loguru import logger
|
||||
|
||||
from reelforge.services.comfy_base_service import ComfyBaseService
|
||||
from reelforge.utils.os_util import get_temp_path
|
||||
|
||||
|
||||
class TTSService(ComfyBaseService):
|
||||
"""
|
||||
TTS (Text-to-Speech) service - Dual implementation
|
||||
|
||||
Supports two TTS methods:
|
||||
1. Edge TTS (default) - Free, local SDK, no workflow needed
|
||||
2. ComfyUI Workflow - Workflow-based, requires ComfyUI setup
|
||||
|
||||
Usage:
|
||||
# Use default (edge-tts)
|
||||
audio_path = await reelforge.tts(text="Hello, world!")
|
||||
|
||||
# Explicitly use edge-tts
|
||||
audio_path = await reelforge.tts(
|
||||
text="你好，世界！",
|
||||
workflow="edge"
|
||||
)
|
||||
|
||||
# Use ComfyUI workflow
|
||||
audio_path = await reelforge.tts(
|
||||
text="Hello",
|
||||
workflow="tts_comfyui.json"
|
||||
)
|
||||
|
||||
# List available workflows
|
||||
workflows = reelforge.tts.list_workflows()
|
||||
"""
|
||||
|
||||
WORKFLOW_PREFIX = "tts_"
|
||||
DEFAULT_WORKFLOW = "edge" # Default to edge-tts
|
||||
WORKFLOWS_DIR = "workflows"
|
||||
|
||||
# Built-in providers (not workflow files)
|
||||
BUILTIN_PROVIDERS = ["edge", "edge-tts"]
|
||||
|
||||
def __init__(self, config: dict):
|
||||
"""
|
||||
Initialize TTS service
|
||||
|
||||
Args:
|
||||
config: Full application config dict
|
||||
"""
|
||||
super().__init__(config, service_name="tts")
|
||||
|
||||
def _resolve_workflow(self, workflow: Optional[str] = None) -> str:
|
||||
"""
|
||||
Resolve workflow to actual workflow path or provider name
|
||||
|
||||
Args:
|
||||
workflow: Workflow filename or provider name (e.g., "edge", "tts_default.json")
|
||||
|
||||
Returns:
|
||||
Workflow file path or provider name
|
||||
"""
|
||||
# 1. If not specified, use default
|
||||
if workflow is None:
|
||||
workflow = self._get_default_workflow()
|
||||
|
||||
# 2. If it's a built-in provider, return as-is
|
||||
if workflow in self.BUILTIN_PROVIDERS:
|
||||
logger.debug(f"Using built-in TTS provider: {workflow}")
|
||||
return workflow
|
||||
|
||||
# 3. Otherwise, treat as workflow file (use parent logic)
|
||||
return super()._resolve_workflow(workflow)
|
||||
|
||||
async def __call__(
|
||||
self,
|
||||
text: str,
|
||||
workflow: Optional[str] = None,
|
||||
# ComfyUI connection (optional overrides, only for workflow mode)
|
||||
comfyui_url: Optional[str] = None,
|
||||
runninghub_api_key: Optional[str] = None,
|
||||
# Common TTS parameters (work for both edge-tts and workflows)
|
||||
voice: Optional[str] = None,
|
||||
rate: Optional[str] = None,
|
||||
volume: Optional[str] = None,
|
||||
pitch: Optional[str] = None,
|
||||
**params
|
||||
) -> str:
|
||||
"""
|
||||
Generate speech using edge-tts or ComfyUI workflow
|
||||
|
||||
Args:
|
||||
text: Text to convert to speech
|
||||
workflow: Workflow filename or provider name (default: "edge")
|
||||
- "edge" or "edge-tts": Use local edge-tts SDK
|
||||
- "tts_xxx.json": Use ComfyUI workflow
|
||||
- Absolute path/URL/RunningHub ID: Also supported
|
||||
comfyui_url: ComfyUI URL (only for workflow mode)
|
||||
runninghub_api_key: RunningHub API key (only for workflow mode)
|
||||
voice: Voice ID
|
||||
rate: Speech rate (e.g., "+0%", "+50%", "-20%")
|
||||
volume: Speech volume (e.g., "+0%")
|
||||
pitch: Speech pitch (e.g., "+0Hz")
|
||||
**params: Additional parameters
|
||||
|
||||
Returns:
|
||||
Generated audio file path
|
||||
|
||||
Examples:
|
||||
# Simplest: use default (edge-tts)
|
||||
audio_path = await reelforge.tts(text="Hello, world!")
|
||||
|
||||
# Explicitly use edge-tts with parameters
|
||||
audio_path = await reelforge.tts(
|
||||
text="你好，世界！",
|
||||
workflow="edge",
|
||||
voice="zh-CN-XiaoxiaoNeural",
|
||||
rate="+20%"
|
||||
)
|
||||
|
||||
# Use ComfyUI workflow
|
||||
audio_path = await reelforge.tts(
|
||||
text="Hello",
|
||||
workflow="tts_default.json"
|
||||
)
|
||||
|
||||
# With absolute path
|
||||
audio_path = await reelforge.tts(
|
||||
text="Hello",
|
||||
workflow="/path/to/custom_tts.json"
|
||||
)
|
||||
"""
|
||||
# 1. Resolve workflow path or provider
|
||||
workflow_or_provider = self._resolve_workflow(workflow=workflow)
|
||||
|
||||
# 2. Determine execution path
|
||||
if workflow_or_provider in self.BUILTIN_PROVIDERS:
|
||||
# Use edge-tts
|
||||
return await self._call_edge_tts(
|
||||
text=text,
|
||||
voice=voice,
|
||||
rate=rate,
|
||||
volume=volume,
|
||||
pitch=pitch,
|
||||
**params
|
||||
)
|
||||
else:
|
||||
# Use ComfyUI workflow
|
||||
return await self._call_comfyui_workflow(
|
||||
workflow_path=workflow_or_provider,
|
||||
text=text,
|
||||
comfyui_url=comfyui_url,
|
||||
runninghub_api_key=runninghub_api_key,
|
||||
voice=voice,
|
||||
rate=rate,
|
||||
volume=volume,
|
||||
pitch=pitch,
|
||||
**params
|
||||
)
|
||||
|
||||
async def _call_edge_tts(
|
||||
self,
|
||||
text: str,
|
||||
voice: Optional[str] = None,
|
||||
rate: Optional[str] = None,
|
||||
volume: Optional[str] = None,
|
||||
pitch: Optional[str] = None,
|
||||
**params
|
||||
) -> str:
|
||||
"""
|
||||
Generate speech using edge-tts SDK
|
||||
|
||||
Args:
|
||||
text: Text to convert to speech
|
||||
voice: Voice ID (default: zh-CN-YunjianNeural)
|
||||
rate: Speech rate (default: +0%)
|
||||
volume: Speech volume (default: +0%)
|
||||
pitch: Speech pitch (default: +0Hz)
|
||||
**params: Additional parameters (e.g., retry_count, retry_delay)
|
||||
|
||||
Returns:
|
||||
Generated audio file path
|
||||
"""
|
||||
from reelforge.utils.tts_util import edge_tts
|
||||
|
||||
logger.info(f"🎙️ Using edge-tts (local SDK)")
|
||||
|
||||
# Generate temp file path
|
||||
output_path = get_temp_path(f"{uuid.uuid4().hex}.mp3")
|
||||
|
||||
# Call edge-tts with output_path to save directly
|
||||
try:
|
||||
audio_bytes = await edge_tts(
|
||||
text=text,
|
||||
voice=voice or "zh-CN-YunjianNeural",
|
||||
rate=rate or "+0%",
|
||||
volume=volume or "+0%",
|
||||
pitch=pitch or "+0Hz",
|
||||
output_path=output_path,
|
||||
**params
|
||||
)
|
||||
|
||||
logger.info(f"✅ Generated audio (edge-tts): {output_path}")
|
||||
return output_path
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Edge TTS generation error: {e}")
|
||||
raise
|
||||
|
||||
async def _call_comfyui_workflow(
|
||||
self,
|
||||
workflow_path: str,
|
||||
text: str,
|
||||
comfyui_url: Optional[str] = None,
|
||||
runninghub_api_key: Optional[str] = None,
|
||||
voice: Optional[str] = None,
|
||||
rate: Optional[str] = None,
|
||||
volume: Optional[str] = None,
|
||||
pitch: Optional[str] = None,
|
||||
**params
|
||||
) -> str:
|
||||
"""
|
||||
Generate speech using ComfyUI workflow
|
||||
|
||||
Args:
|
||||
workflow_path: Path to workflow file
|
||||
text: Text to convert to speech
|
||||
comfyui_url: ComfyUI URL
|
||||
runninghub_api_key: RunningHub API key
|
||||
voice: Voice ID (workflow-specific)
|
||||
rate: Speech rate (workflow-specific)
|
||||
volume: Speech volume (workflow-specific)
|
||||
pitch: Speech pitch (workflow-specific)
|
||||
**params: Additional workflow parameters
|
||||
|
||||
Returns:
|
||||
Generated audio file path/URL
|
||||
"""
|
||||
logger.info(f"🎙️ Using ComfyUI workflow: {workflow_path}")
|
||||
|
||||
# 1. Prepare ComfyKit config
|
||||
kit_config = self._prepare_comfykit_config(
|
||||
comfyui_url=comfyui_url,
|
||||
runninghub_api_key=runninghub_api_key
|
||||
)
|
||||
|
||||
# 2. Build workflow parameters
|
||||
workflow_params = {"text": text}
|
||||
|
||||
# Add optional TTS parameters
|
||||
if voice is not None:
|
||||
workflow_params["voice"] = voice
|
||||
if rate is not None:
|
||||
workflow_params["rate"] = rate
|
||||
if volume is not None:
|
||||
workflow_params["volume"] = volume
|
||||
if pitch is not None:
|
||||
workflow_params["pitch"] = pitch
|
||||
|
||||
# Add any additional parameters
|
||||
workflow_params.update(params)
|
||||
|
||||
logger.debug(f"Workflow parameters: {workflow_params}")
|
||||
|
||||
# 3. Execute workflow
|
||||
try:
|
||||
kit = ComfyKit(**kit_config)
|
||||
|
||||
logger.info(f"Executing TTS workflow: {workflow_path}")
|
||||
result = await kit.execute(workflow_path, workflow_params)
|
||||
|
||||
# 4. Handle result
|
||||
if result.status != "completed":
|
||||
error_msg = result.msg or "Unknown error"
|
||||
logger.error(f"TTS generation failed: {error_msg}")
|
||||
raise Exception(f"TTS generation failed: {error_msg}")
|
||||
|
||||
# ComfyKit result can have audio files in different output types
|
||||
# Try to get audio file path from result
|
||||
audio_path = None
|
||||
|
||||
# Check for audio files in result.audios (if available)
|
||||
if hasattr(result, 'audios') and result.audios:
|
||||
audio_path = result.audios[0]
|
||||
# Check for files in result.files
|
||||
elif hasattr(result, 'files') and result.files:
|
||||
audio_path = result.files[0]
|
||||
# Check in outputs dictionary
|
||||
elif hasattr(result, 'outputs') and result.outputs:
|
||||
# Try to find audio file in outputs
|
||||
for key, value in result.outputs.items():
|
||||
if isinstance(value, str) and any(value.endswith(ext) for ext in ['.mp3', '.wav', '.flac']):
|
||||
audio_path = value
|
||||
break
|
||||
|
||||
if not audio_path:
|
||||
logger.error("No audio file generated")
|
||||
raise Exception("No audio file generated by workflow")
|
||||
|
||||
logger.info(f"✅ Generated audio (ComfyUI): {audio_path}")
|
||||
return audio_path
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"TTS generation error: {e}")
|
||||
raise
|
||||
Reference in New Issue
Block a user