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Auto-update: Sat Jun 29 11:58:22 PDT 2024

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sanj 2024-06-29 11:58:22 -07:00
parent 7a064cd21d
commit f019d4ede0
16 changed files with 359 additions and 103 deletions
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13
sijapi/__init__.py
View file

@ -9,27 +9,22 @@ from dateutil import tz
from pathlib import Path
from pydantic import BaseModel
from typing import List, Optional
import traceback
import logging
from .logs import Logger
from .classes import AutoResponder, IMAPConfig, SMTPConfig, EmailAccount, EmailContact, IncomingEmail, Database, Geocoder
# from sijapi.config.config import load_config
# cfg = load_config()
from .classes import AutoResponder, IMAPConfig, SMTPConfig, EmailAccount, EmailContact, IncomingEmail, Database, Geocoder, APIConfig, Configuration
### Initial initialization
BASE_DIR = Path(__file__).resolve().parent
CONFIG_DIR = BASE_DIR / "config"
ENV_PATH = CONFIG_DIR / ".env"
LOGS_DIR = BASE_DIR / "logs"
# Create logger instance
L = Logger("Central", LOGS_DIR)
os.makedirs(LOGS_DIR, exist_ok=True)
load_dotenv(ENV_PATH)
### API essentials
API_CONFIG_PATH = CONFIG_DIR / "api.yaml"
SECRETS_CONFIG_PATH = CONFIG_DIR / "secrets.yaml"
API = APIConfig.load_from_yaml(API_CONFIG_PATH, SECRETS_CONFIG_PATH)
DB = Database.from_env()
ROUTERS = os.getenv('ROUTERS', '').split(',')
PUBLIC_SERVICES = os.getenv('PUBLIC_SERVICES', '').split(',')

14
sijapi/__main__.py
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@ -18,9 +18,8 @@ from dotenv import load_dotenv
from pathlib import Path
from datetime import datetime
import argparse
from . import L, LOGS_DIR, OBSIDIAN_VAULT_DIR
from . import L, API, OBSIDIAN_VAULT_DIR
from .logs import Logger
from .utilities import list_and_correct_impermissible_files
parser = argparse.ArgumentParser(description='Personal API.')
parser.add_argument('--debug', action='store_true', help='Set log level to L.INFO')
@ -106,6 +105,7 @@ async def handle_exception_middleware(request: Request, call_next):
def load_router(router_name):
router_file = ROUTER_DIR / f'{router_name}.py'
L.DEBUG(f"Attempting to load {router_name.capitalize()}...")
@ -127,15 +127,15 @@ def main(argv):
else:
L.CRIT(f"sijapi launched")
L.CRIT(f"{args._get_args}")
for router_name in ROUTERS:
load_router(router_name)
for module_name in API.MODULES.__fields__:
if getattr(API.MODULES, module_name):
load_router(module_name)
journal = OBSIDIAN_VAULT_DIR / "journal"
list_and_correct_impermissible_files(journal, rename=True)
config = Config()
config.keep_alive_timeout = 1200
config.bind = [HOST]
config.bind = [API.BIND]
asyncio.run(serve(api, config))
if __name__ == "__main__":
main(sys.argv[1:])

156
sijapi/classes.py
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@ -3,6 +3,8 @@ from typing import List, Optional, Any, Tuple, Dict, Union, Tuple
from datetime import datetime, timedelta, timezone
import asyncio
import json
import os
import re
import yaml
import math
from timezonefinder import TimezoneFinder
@ -15,6 +17,160 @@ from concurrent.futures import ThreadPoolExecutor
import reverse_geocoder as rg
from timezonefinder import TimezoneFinder
from srtm import get_data
from pathlib import Path
import yaml
from typing import Union, List, TypeVar, Type
from pydantic import BaseModel, create_model
from pydantic import BaseModel, Field
from typing import List, Dict
import yaml
from pathlib import Path
import os
from dotenv import load_dotenv
T = TypeVar('T', bound='Configuration')
class ModulesConfig(BaseModel):
asr: bool = Field(alias="asr")
calendar: bool = Field(alias="calendar")
email: bool = Field(alias="email")
health: bool = Field(alias="health")
hooks: bool = Field(alias="hooks")
llm: bool = Field(alias="llm")
locate: bool = Field(alias="locate")
note: bool = Field(alias="note")
sd: bool = Field(alias="sd")
serve: bool = Field(alias="serve")
time: bool = Field(alias="time")
tts: bool = Field(alias="tts")
weather: bool = Field(alias="weather")
class APIConfig(BaseModel):
BIND: str
PORT: int
URL: str
PUBLIC: List[str]
TRUSTED_SUBNETS: List[str]
MODULES: ModulesConfig
BaseTZ: Optional[str] = 'UTC'
KEYS: List[str]
@classmethod
def load_from_yaml(cls, config_path: Path, secrets_path: Path):
# Load main configuration
with open(config_path, 'r') as file:
config_data = yaml.safe_load(file)
print(f"Loaded main config: {config_data}") # Debug print
# Load secrets
try:
with open(secrets_path, 'r') as file:
secrets_data = yaml.safe_load(file)
print(f"Loaded secrets: {secrets_data}") # Debug print
except FileNotFoundError:
print(f"Secrets file not found: {secrets_path}")
secrets_data = {}
except yaml.YAMLError as e:
print(f"Error parsing secrets YAML: {e}")
secrets_data = {}
# Handle KEYS placeholder
if isinstance(config_data.get('KEYS'), list) and len(config_data['KEYS']) == 1:
placeholder = config_data['KEYS'][0]
if placeholder.startswith('{{') and placeholder.endswith('}}'):
key = placeholder[2:-2].strip() # Remove {{ }} and whitespace
parts = key.split('.')
if len(parts) == 2 and parts[0] == 'SECRET':
secret_key = parts[1]
if secret_key in secrets_data:
config_data['KEYS'] = secrets_data[secret_key]
print(f"Replaced KEYS with secret: {config_data['KEYS']}") # Debug print
else:
print(f"Secret key '{secret_key}' not found in secrets file")
else:
print(f"Invalid secret placeholder format: {placeholder}")
# Convert 'on'/'off' to boolean for MODULES if they are strings
for key, value in config_data['MODULES'].items():
if isinstance(value, str):
config_data['MODULES'][key] = value.lower() == 'on'
elif isinstance(value, bool):
config_data['MODULES'][key] = value
else:
raise ValueError(f"Invalid value for module {key}: {value}. Must be 'on', 'off', True, or False.")
return cls(**config_data)
class Configuration(BaseModel):
@classmethod
def load_config(cls: Type[T], yaml_path: Union[str, Path]) -> Union[T, List[T]]:
yaml_path = Path(yaml_path)
with yaml_path.open('r') as file:
config_data = yaml.safe_load(file)
# Load environment variables
load_dotenv()
# Resolve placeholders
config_data = cls.resolve_placeholders(config_data)
if isinstance(config_data, list):
return [cls.create_dynamic_model(**cfg) for cfg in config_data]
elif isinstance(config_data, dict):
return cls.create_dynamic_model(**config_data)
else:
raise ValueError(f"Unsupported YAML structure in {yaml_path}")
@classmethod
def resolve_placeholders(cls, data):
if isinstance(data, dict):
return {k: cls.resolve_placeholders(v) for k, v in data.items()}
elif isinstance(data, list):
return [cls.resolve_placeholders(v) for v in data]
elif isinstance(data, str):
return cls.resolve_string_placeholders(data)
else:
return data
@classmethod
def resolve_string_placeholders(cls, value):
pattern = r'\{\{\s*([^}]+)\s*\}\}'
matches = re.findall(pattern, value)
for match in matches:
parts = match.split('.')
if len(parts) == 2:
category, key = parts
if category == 'DIR':
replacement = str(Path(os.getenv(key, '')))
elif category == 'SECRET':
replacement = os.getenv(key, '')
else:
replacement = os.getenv(match, '')
value = value.replace('{{' + match + '}}', replacement)
return value
@classmethod
def create_dynamic_model(cls, **data):
for key, value in data.items():
if isinstance(value, dict):
data[key] = cls.create_dynamic_model(**value)
DynamicModel = create_model(
f'Dynamic{cls.__name__}',
__base__=cls,
**{k: (type(v), v) for k, v in data.items()}
)
return DynamicModel(**data)
class Config:
extra = "allow"
arbitrary_types_allowed = True
class Location(BaseModel):
latitude: float

31
sijapi/config/api.yaml-example Normal file
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@ -0,0 +1,31 @@
BIND: 0.0.0.0
PORT: 4444
URL: https://api.yourdomain.com
PUBLIC:
- /id
- /ip
- /health
- /img/
- /cl/dockets
- /cl/search
- /cd/alert
TRUSTED_SUBNETS:
- 127.0.0.1/32 # don't change this
- 192.168.50.0/24 # optionally set to your local subnet, or omit
- 100.11.11.0/24 # optionally set to your tailscale subnet, or omit
MODULES:
asr: on
calendar: on
email: on
health: on
hooks: on
llm: on
locate: on
note: on
sd: on
serve: on
time: on
tts: on
weather: on
TZ: 'America/Los_Angeles' # this is just for the initial config, and is dynamically updated based on location
KEYS: ['{{ SECRET.GLOBAL_API_KEYS }}'] # sourced from .env

20
sijapi/config/sd.yaml-example
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@ -2,35 +2,33 @@ scenes:
- scene: default
triggers:
- ""
API_PPrompt: "Highly-detailed image of "
API_SPrompt: ", masterpiece, subtle, nuanced, best quality, ultra detailed, ultra high resolution, 8k, documentary, american transcendental, cinematic, filmic, moody, dynamic lighting, realistic, wallpaper, landscape photography, professional, earthporn, eliot porter, frans lanting, daniel kordan, landscape photography, ultra detailed, earth tones, moody"
API_NPrompt: "3d, bad art, illustrated, deformed, blurry, duplicate, video game, render, anime, cartoon, fake, tiling, out of frame, bad art, bad anatomy, 3d render, nsfw, worst quality, low quality, text, watermark, Thomas Kinkade, sentimental, kitsch, kitschy, twee, commercial, holiday card, comic, cartoon"
API_PrePrompt: "Highly-detailed image of "
API_StylePrompt: ", masterpiece, subtle, nuanced, best quality, ultra detailed, ultra high resolution, 8k, documentary, american transcendental, cinematic, filmic, moody, dynamic lighting, realistic, wallpaper, landscape photography, professional, earthporn, eliot porter, frans lanting, daniel kordan, landscape photography, ultra detailed, earth tones, moody"
API_NegativePrompt: "3d, bad art, illustrated, deformed, blurry, duplicate, video game, render, anime, cartoon, fake, tiling, out of frame, bad art, bad anatomy, 3d render, nsfw, worst quality, low quality, text, watermark, Thomas Kinkade, sentimental, kitsch, kitschy, twee, commercial, holiday card, comic, cartoon"
llm_sys_msg: "You are a helpful AI who assists in refining prompts that will be used to generate highly realistic images. Upon receiving a prompt, you refine it by simplifying and distilling it to its essence, retaining the most visually evocative and distinct elements from what was provided. You may infer some visual details that were not provided in the prompt, so long as they are consistent with the prompt. Always use the most visually descriptive terms possible, and avoid any vague or abstract concepts. Do not include any words or descriptions based on other senses or emotions. Strive to show rather than tell. Space is limited, so be efficient with your words."
llm_pre_prompt: "Using the most visually descriptive sentence fragments, phrases, and words, distill this scene description to its essence, staying true to what it describes: "
workflows:
- workflow: default.json
size: 1024x768
- scene: wallpaper
triggers:
- wallpaper
API_PPrompt: "Stunning widescreen image of "
API_SPrompt: ", masterpiece, subtle, nuanced, best quality, ultra detailed, ultra high resolution, 8k, documentary, american transcendental, cinematic, filmic, moody, dynamic lighting, realistic, wallpaper, landscape photography, professional, earthporn, eliot porter, frans lanting, daniel kordan, landscape photography, ultra detailed, earth tones, moody"
API_NPrompt: "3d, bad art, illustrated, deformed, blurry, duplicate, video game, render, anime, cartoon, fake, tiling, out of frame, bad art, bad anatomy, 3d render, nsfw, worst quality, low quality, text, watermark, Thomas Kinkade, sentimental, kitsch, kitschy, twee, commercial, holiday card, comic, cartoon"
API_PrePrompt: "Stunning widescreen image of "
API_StylePrompt: ", masterpiece, subtle, nuanced, best quality, ultra detailed, ultra high resolution, 8k, documentary, american transcendental, cinematic, filmic, moody, dynamic lighting, realistic, wallpaper, landscape photography, professional, earthporn, eliot porter, frans lanting, daniel kordan, landscape photography, ultra detailed, earth tones, moody"
API_NegativePrompt: "3d, bad art, illustrated, deformed, blurry, duplicate, video game, render, anime, cartoon, fake, tiling, out of frame, bad art, bad anatomy, 3d render, nsfw, worst quality, low quality, text, watermark, Thomas Kinkade, sentimental, kitsch, kitschy, twee, commercial, holiday card, comic, cartoon"
llm_sys_msg: "You are a helpful AI who assists in generating prompts that will be used to generate highly realistic images. Always use the most visually descriptive terms possible, and avoid any vague or abstract concepts. Do not include any words or descriptions based on other senses or emotions. Strive to show rather than tell. Space is limited, so be efficient with your words."
llm_pre_prompt: "Using a series of words or sentence fragments separated by commas, describe a professional landscape photograph of a striking scene of nature. You can select any place on Earth that a young model from the Pacific Northwest is likely to travel to. Focus on describing the content and composition of the image. Only use words and phrases that are visually descriptive. This model is especially fond of wild and rugged places, mountains. She favors dark muted earth tones, dramatic lighting, and interesting juxtapositions between foreground and background, or center of frame and outer frame areas. Avoid cliche situations; instread strive for nuance and originality in composition and environment."
workflows:
- workflow: wallpaper.json
size: 1024x640
- scene: portrait
triggers:
- portrait
- profile
- headshot
API_PPrompt: "Highly-detailed portrait photo of "
API_SPrompt: "; attractive, cute, (((masterpiece))); ((beautiful lighting)), subdued, fine detail, extremely sharp, 8k, insane detail, dynamic lighting, cinematic, best quality, ultra detailed."
API_NPrompt: "canvas frame, 3d, bad art, illustrated, deformed, blurry, duplicate, bad anatomy, worst quality, low quality, watermark, FastNegativeV2, easynegative, epiCNegative, easynegative, verybadimagenegative_v1.3, nsfw, nude"
API_PrePrompt: "Highly-detailed portrait photo of "
API_StylePrompt: "; attractive, cute, (((masterpiece))); ((beautiful lighting)), subdued, fine detail, extremely sharp, 8k, insane detail, dynamic lighting, cinematic, best quality, ultra detailed."
API_NegativePrompt: "canvas frame, 3d, bad art, illustrated, deformed, blurry, duplicate, bad anatomy, worst quality, low quality, watermark, FastNegativeV2, easynegative, epiCNegative, easynegative, verybadimagenegative_v1.3, nsfw, nude"
llm_sys_msg: "You are a helpful AI who assists in refining prompts that will be used to generate highly realistic portrait photos. Upon receiving a prompt, you refine it by simplifying and distilling it to its essence, retaining the most visually evocative and distinct elements from what was provided, focusing in particular on the pictured individual's eyes, pose, and other distinctive features. You may infer some visual details that were not provided in the prompt, so long as they are consistent with the rest of the prompt. Always use the most visually descriptive terms possible, and avoid any vague or abstract concepts. Do not include any words or descriptions based on other senses or emotions. Strive to show rather than tell. Space is limited, so be efficient with your words. Remember that the final product will be a still image, and action verbs are not as helpful as simple descriptions of position, appearance, background, etc."
llm_pre_prompt: "Using the most visually descriptive sentence fragments, phrases, and words, distill this portrait photo to its essence: "
workflows:

3
sijapi/config/secrets.yaml-example Normal file
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@ -0,0 +1,3 @@
GLOBAL_API_KEYS:
- sk-YOUR-FIRST-API-KEY
- sk-YOUR-SECOND-API-KEY

6
sijapi/data/sd/workflows/default.json
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@ -10,7 +10,7 @@
},
"6": {
"inputs": {
"text": "API_PPrompt",
"text": "API_PrePrompt",
"clip": [
"4",
1
@ -23,7 +23,7 @@
},
"7": {
"inputs": {
"text": "API_NPrompt",
"text": "API_NegativePrompt",
"clip": [
"4",
1
@ -186,7 +186,7 @@
},
"21": {
"inputs": {
"text": "API_SPrompt",
"text": "API_StylePrompt",
"clip": [
"4",
1

6
sijapi/data/sd/workflows/landscape.json
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@ -10,7 +10,7 @@
},
"6": {
"inputs": {
"text": "API_PPrompt",
"text": "API_PrePrompt",
"clip": [
"4",
1
@ -23,7 +23,7 @@
},
"7": {
"inputs": {
"text": "API_NPrompt",
"text": "API_NegativePrompt",
"clip": [
"4",
1
@ -186,7 +186,7 @@
},
"21": {
"inputs": {
"text": "API_SPrompt",
"text": "API_StylePrompt",
"clip": [
"4",
1

6
sijapi/data/sd/workflows/selfie.json
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@ -118,7 +118,7 @@
},
"17": {
"inputs": {
"text": "API_PPrompt"
"text": "API_PrePrompt"
},
"class_type": "JWStringMultiline",
"_meta": {
@ -127,7 +127,7 @@
},
"18": {
"inputs": {
"text": "API_NPrompt"
"text": "API_NegativePrompt"
},
"class_type": "JWStringMultiline",
"_meta": {
@ -444,7 +444,7 @@
},
"96": {
"inputs": {
"text": "API_SPrompt"
"text": "API_StylePrompt"
},
"class_type": "JWStringMultiline",
"_meta": {

6
sijapi/data/sd/workflows/wallpaper.json
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@ -10,7 +10,7 @@
},
"6": {
"inputs": {
"text": "API_PPrompt",
"text": "API_PrePrompt",
"clip": [
"4",
1
@ -23,7 +23,7 @@
},
"7": {
"inputs": {
"text": "API_NPrompt",
"text": "API_NegativePrompt",
"clip": [
"4",
1
@ -186,7 +186,7 @@
},
"21": {
"inputs": {
"text": "API_SPrompt",
"text": "API_StylePrompt",
"clip": [
"4",
1

6
sijapi/data/sd/workflows/wallpaper_fast.json
View file

@ -10,7 +10,7 @@
},
"6": {
"inputs": {
"text": "API_PPrompt",
"text": "API_PrePrompt",
"clip": [
"4",
1
@ -23,7 +23,7 @@
},
"7": {
"inputs": {
"text": "API_NPrompt",
"text": "API_NegativePrompt",
"clip": [
"4",
1
@ -202,7 +202,7 @@
},
"21": {
"inputs": {
"text": "API_SPrompt",
"text": "API_StylePrompt",
"clip": [
"4",
1

60
sijapi/routers/dist.py Normal file
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@ -0,0 +1,60 @@
'''
WORK IN PROGRESS: This module will handle tasks related to multi-server environments.
'''
from fastapi import APIRouter, HTTPException
import asyncio
import logging
from sijapi.utilities import run_ssh_command
from sijapi import REBOOT_SCRIPT_PATH, HOST_CONFIG, API_CONFIG
dist = APIRouter()
logger = logging.getLogger(__name__)
@dist.get("/update-restart-others")
async def update_and_restart_others():
results = []
for server in API_CONFIG.servers:
if HOST_CONFIG.id != server.id:
try:
output, error = await run_ssh_command(server, f"bash {server.scripts.update_and_restart}")
results.append({"server": server.id, "status": "success", "output": output, "error": error})
except Exception as e:
results.append({"server": server.id, "status": "failed", "error": str(e)})
return {"message": "Update and restart process initiated for other servers.", "results": results}
@dist.get("/update-restart-self")
async def update_and_restart_self(safe: bool = True):
if safe and not await ensure_redundancy():
raise HTTPException(status_code=400, detail="Cannot safely restart: no redundancy available")
try:
process = await asyncio.create_subprocess_exec(
"bash", API_CONFIG.servers[HOST_CONFIG.id].scripts.update_and_restart,
stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE
)
stdout, stderr = await process.communicate()
logger.info(f"Update and restart initiated for self. Stdout: {stdout.decode()}. Stderr: {stderr.decode()}")
return {"message": "Update and restart process initiated for this server."}
except Exception as e:
logger.error(f"Failed to initiate update and restart for self: {str(e)}")
raise HTTPException(status_code=500, detail=f"Failed to initiate update and restart: {str(e)}")
@dist.get("/update-and-restart-all")
async def update_and_restart_all():
others_result = await update_and_restart_others()
self_result = await update_and_restart_self(safe=False)
return {"others": others_result, "self": self_result}
async def ensure_redundancy():
import aiohttp
redundancy = False
async with aiohttp.ClientSession() as session:
for server in API_CONFIG.servers:
if server.id != HOST_CONFIG.id:
try:
async with session.get(f"{server.protocol}://{server.ip}:{server.port}/health") as response:
if response.status // 100 == 2:
redundancy = True
break
except aiohttp.ClientError:
logger.warning(f"Failed to check health of server {server.id}")
return redundancy

42
sijapi/routers/ig.py
View file

@ -483,15 +483,15 @@ def update_prompt(workflow: dict, post: dict, positive: str, found_key=[None], p
for index, item in enumerate(value):
update_prompt(item, post, positive, found_key, current_path + [str(index)])
if value == "API_PPrompt":
if value == "API_PrePrompt":
workflow[key] = post.get(value, "") + positive
L.DEBUG(f"Updated API_PPrompt to: {workflow[key]}")
elif value == "API_SPrompt":
L.DEBUG(f"Updated API_PrePrompt to: {workflow[key]}")
elif value == "API_StylePrompt":
workflow[key] = post.get(value, "")
L.DEBUG(f"Updated API_SPrompt to: {workflow[key]}")
elif value == "API_NPrompt":
L.DEBUG(f"Updated API_StylePrompt to: {workflow[key]}")
elif value == "API_NegativePrompt":
workflow[key] = post.get(value, "")
L.DEBUG(f"Updated API_NPrompt to: {workflow[key]}")
L.DEBUG(f"Updated API_NegativePrompt to: {workflow[key]}")
elif key == "seed" or key == "noise_seed":
workflow[key] = random.randint(1000000000000, 9999999999999)
L.DEBUG(f"Updated seed to: {workflow[key]}")
@ -507,7 +507,7 @@ def update_prompt(workflow: dict, post: dict, positive: str, found_key=[None], p
return found_key[0]
def update_prompt_custom(workflow: dict, API_PPrompt: str, API_SPrompt: str, API_NPrompt: str, found_key=[None], path=None):
def update_prompt_custom(workflow: dict, API_PrePrompt: str, API_StylePrompt: str, API_NegativePrompt: str, found_key=[None], path=None):
if path is None:
path = []
@ -519,21 +519,21 @@ def update_prompt_custom(workflow: dict, API_PPrompt: str, API_SPrompt: str, API
if isinstance(value, dict):
if value.get('class_type') == 'SaveImage' and value.get('inputs', {}).get('filename_prefix') == 'API_':
found_key[0] = key
update_prompt(value, API_PPrompt, API_SPrompt, API_NPrompt, found_key, current_path)
update_prompt(value, API_PrePrompt, API_StylePrompt, API_NegativePrompt, found_key, current_path)
elif isinstance(value, list):
# Recursive call with updated path for each item in a list
for index, item in enumerate(value):
update_prompt(item, API_PPrompt, API_SPrompt, API_NPrompt, found_key, current_path + [str(index)])
update_prompt(item, API_PrePrompt, API_StylePrompt, API_NegativePrompt, found_key, current_path + [str(index)])
if value == "API_PPrompt":
workflow[key] = API_PPrompt
L.DEBUG(f"Updated API_PPrompt to: {workflow[key]}")
elif value == "API_SPrompt":
workflow[key] = API_SPrompt
L.DEBUG(f"Updated API_SPrompt to: {workflow[key]}")
elif value == "API_NPrompt":
workflow[key] = API_NPrompt
L.DEBUG(f"Updated API_NPrompt to: {workflow[key]}")
if value == "API_PrePrompt":
workflow[key] = API_PrePrompt
L.DEBUG(f"Updated API_PrePrompt to: {workflow[key]}")
elif value == "API_StylePrompt":
workflow[key] = API_StylePrompt
L.DEBUG(f"Updated API_StylePrompt to: {workflow[key]}")
elif value == "API_NegativePrompt":
workflow[key] = API_NegativePrompt
L.DEBUG(f"Updated API_NegativePrompt to: {workflow[key]}")
elif key == "seed" or key == "noise_seed":
workflow[key] = random.randint(1000000000000, 9999999999999)
L.DEBUG(f"Updated seed to: {workflow[key]}")
@ -682,9 +682,9 @@ def handle_custom_image(custom_post: str):
else:
workflow_name = args.workflow if args.workflow else "selfie"
post = {
"API_PPrompt": "",
"API_SPrompt": "; (((masterpiece))); (beautiful lighting:1), subdued, fine detail, extremely sharp, 8k, insane detail, dynamic lighting, cinematic, best quality, ultra detailed.",
"API_NPrompt": "canvas frame, 3d, ((bad art)), illustrated, deformed, blurry, duplicate, bad art, bad anatomy, worst quality, low quality, watermark, FastNegativeV2, (easynegative:0.5), epiCNegative, easynegative, verybadimagenegative_v1.3",
"API_PrePrompt": "",
"API_StylePrompt": "; (((masterpiece))); (beautiful lighting:1), subdued, fine detail, extremely sharp, 8k, insane detail, dynamic lighting, cinematic, best quality, ultra detailed.",
"API_NegativePrompt": "canvas frame, 3d, ((bad art)), illustrated, deformed, blurry, duplicate, bad art, bad anatomy, worst quality, low quality, watermark, FastNegativeV2, (easynegative:0.5), epiCNegative, easynegative, verybadimagenegative_v1.3",
"Vision_Prompt": "Write an upbeat Instagram description with emojis to accompany this selfie!",
"frequency": 2,
"ghost_tags": [

33
sijapi/routers/note.py
View file

@ -32,12 +32,43 @@ from pathlib import Path
from fastapi import APIRouter, Query, HTTPException
from sijapi import L, OBSIDIAN_VAULT_DIR, OBSIDIAN_RESOURCES_DIR, ARCHIVE_DIR, BASE_URL, OBSIDIAN_BANNER_SCENE, DEFAULT_11L_VOICE, DEFAULT_VOICE, GEO
from sijapi.routers import cal, loc, tts, llm, time, sd, weather, asr
from sijapi.utilities import assemble_journal_path, assemble_archive_path, convert_to_12_hour_format, sanitize_filename, convert_degrees_to_cardinal, HOURLY_COLUMNS_MAPPING
from sijapi.utilities import assemble_journal_path, assemble_archive_path, convert_to_12_hour_format, sanitize_filename, convert_degrees_to_cardinal, check_file_name, HOURLY_COLUMNS_MAPPING
from sijapi.classes import Location
note = APIRouter()
def list_and_correct_impermissible_files(root_dir, rename: bool = False):
"""List and correct all files with impermissible names."""
impermissible_files = []
for dirpath, _, filenames in os.walk(root_dir):
for filename in filenames:
if check_file_name(filename):
file_path = Path(dirpath) / filename
impermissible_files.append(file_path)
L.DEBUG(f"Impermissible file found: {file_path}")
# Sanitize the file name
new_filename = sanitize_filename(filename)
new_file_path = Path(dirpath) / new_filename
# Ensure the new file name does not already exist
if new_file_path.exists():
counter = 1
base_name, ext = os.path.splitext(new_filename)
while new_file_path.exists():
new_filename = f"{base_name}_{counter}{ext}"
new_file_path = Path(dirpath) / new_filename
counter += 1
# Rename the file
if rename:
os.rename(file_path, new_file_path)
L.DEBUG(f"Renamed: {file_path} -> {new_file_path}")
return impermissible_files
journal = OBSIDIAN_VAULT_DIR / "journal"
list_and_correct_impermissible_files(journal, rename=True)
### Daily Note Builder ###

12
sijapi/routers/sd.py
View file

@ -90,9 +90,9 @@ async def workflow(prompt: str, scene: str = None, size: str = None, style: str
workflow_data = json.loads(workflow_path.read_text())
post = {
"API_PPrompt": scene_data['API_PPrompt'] + image_concept + ', '.join(f"; (({trigger}))" for trigger in scene_data['triggers']),
"API_SPrompt": scene_data['API_SPrompt'],
"API_NPrompt": scene_data['API_NPrompt'],
"API_PrePrompt": scene_data['API_PrePrompt'] + image_concept + ', '.join(f"; (({trigger}))" for trigger in scene_data['triggers']),
"API_StylePrompt": scene_data['API_StylePrompt'],
"API_NegativePrompt": scene_data['API_NegativePrompt'],
"width": width,
"height": height
}
@ -406,7 +406,7 @@ async def load_workflow(workflow_path: str, workflow:str):
async def update_prompt_and_get_key(workflow: dict, post: dict, positive: str):
'''
Recurses through the workflow searching for and substituting the dynamic values for API_PPrompt, API_SPrompt, API_NPrompt, width, height, and seed (random integer).
Recurses through the workflow searching for and substituting the dynamic values for API_PrePrompt, API_StylePrompt, API_NegativePrompt, width, height, and seed (random integer).
Even more important, it finds and returns the key to the filepath where the file is saved, which we need to decipher status when generation is complete.
'''
found_key = [None]
@ -427,9 +427,9 @@ Even more important, it finds and returns the key to the filepath where the file
for index, item in enumerate(value):
update_recursive(item, current_path + [str(index)])
if value == "API_PPrompt":
if value == "API_PrePrompt":
workflow[key] = post.get(value, "") + positive
elif value in ["API_SPrompt", "API_NPrompt"]:
elif value in ["API_StylePrompt", "API_NegativePrompt"]:
workflow[key] = post.get(value, "")
elif key in ["seed", "noise_seed"]:
workflow[key] = random.randint(1000000000000, 9999999999999)

46
sijapi/utilities.py
View file

@ -6,6 +6,7 @@ import io
from io import BytesIO
import base64
import math
import paramiko
from dateutil import parser
from pathlib import Path
import filetype
@ -21,7 +22,6 @@ import pandas as pd
from scipy.spatial import cKDTree
from dateutil.parser import parse as dateutil_parse
from docx import Document
import asyncpg
from sshtunnel import SSHTunnelForwarder
from fastapi import Depends, HTTPException, Request, UploadFile
from fastapi.security.api_key import APIKeyHeader
@ -192,37 +192,6 @@ def check_file_name(file_name, max_length=255):
return needs_sanitization
def list_and_correct_impermissible_files(root_dir, rename: bool = False):
"""List and correct all files with impermissible names."""
impermissible_files = []
for dirpath, _, filenames in os.walk(root_dir):
for filename in filenames:
if check_file_name(filename):
file_path = Path(dirpath) / filename
impermissible_files.append(file_path)
L.DEBUG(f"Impermissible file found: {file_path}")
# Sanitize the file name
new_filename = sanitize_filename(filename)
new_file_path = Path(dirpath) / new_filename
# Ensure the new file name does not already exist
if new_file_path.exists():
counter = 1
base_name, ext = os.path.splitext(new_filename)
while new_file_path.exists():
new_filename = f"{base_name}_{counter}{ext}"
new_file_path = Path(dirpath) / new_filename
counter += 1
# Rename the file
if rename:
os.rename(file_path, new_file_path)
L.DEBUG(f"Renamed: {file_path} -> {new_file_path}")
return impermissible_files
def bool_convert(value: str = Form(None)):
return value.lower() in ["true", "1", "t", "y", "yes"]
@ -473,3 +442,16 @@ def load_geonames_data(path: str):
return data
async def run_ssh_command(server, command):
try:
ssh = paramiko.SSHClient()
ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())
ssh.connect(server.ssh.host, username=server.ssh.user, password=server.ssh.password)
stdin, stdout, stderr = ssh.exec_command(command)
output = stdout.read().decode()
error = stderr.read().decode()
ssh.close()
return output, error
except Exception as e:
L.ERR(f"SSH command failed for server {server.id}: {str(e)}")
raise