Auto-update: Mon Jul 1 20:48:53 PDT 2024

This commit is contained in:
sanj 2024-07-01 20:48:53 -07:00
parent 79d139312a
commit acb5e0ccaa
16 changed files with 140 additions and 110 deletions

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@ -1,58 +1 @@
import requests
import os
import json
filename = 'location_log.json'
server = '!{!{ ENTER A PUBLIC URL TO YOUR SIJAPI INSTANCE }!}!'
api_key = '!{!{ ENTER YOUR GLOBAL_API_KEY HERE }!}!'
def upload_location_data(data):
headers = {
'Authorization': f'Bearer {api_key}',
'Content-Type': 'application/json'
}
try:
response = requests.post(f'{server}/locate', json=data, headers=headers)
if response.status_code == 200:
print('Location and weather updated successfully.')
os.remove(filename)
else:
print(f'Failed to post data. Status code: {response.status_code}')
print(response.text)
except requests.RequestException as e:
print(f'Error posting data: {e}')
if not os.path.exists(filename):
print('No data to upload.')
else:
try:
with open(filename, 'r') as f:
data = json.load(f)
# Ensure all datetime fields are correctly named and add default context if missing
for location in data:
if 'date' in location:
location['datetime'] = location.pop('date')
# Ensure context dictionary exists with all required keys
if 'context' not in location:
location['context'] = {
'action': 'manual',
'device_type': 'Pythonista',
'device_model': None,
'device_name': None,
'device_os': None
}
else:
context = location['context']
context.setdefault('action', 'manual')
context.setdefault('device_type', 'Pythonista')
context.setdefault('device_model', None)
context.setdefault('device_name', None)
context.setdefault('device_os', None)
upload_location_data(data)
except FileNotFoundError:
print(f'File {filename} not found.')
except json.JSONDecodeError:
print(f'Error decoding JSON from {filename}.')
except Exception as e:
print(f'Unexpected error: {e}')
how

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@ -1,3 +1,4 @@
# __init__.py
import os
import json
import yaml

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@ -1,4 +1,5 @@
#!/Users/sij/miniforge3/envs/api/bin/python
#__main__.py
from fastapi import FastAPI, Request, HTTPException, Response
from fastapi.responses import JSONResponse
from fastapi.middleware.cors import CORSMiddleware

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@ -1,3 +1,4 @@
# classes.py
import asyncio
import json
import math

58
sijapi/cli.py Normal file
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@ -0,0 +1,58 @@
# cli.py
import click
import asyncio
from datetime import datetime as dt_datetime, timedelta
# Import your async functions and dependencies
from your_main_app import build_daily_note_range_endpoint, loc
def async_command(f):
@click.command()
@click.pass_context
def wrapper(ctx, *args, **kwargs):
async def run():
return await f(*args, **kwargs)
return asyncio.run(run())
return wrapper
@click.group()
def cli():
"""CLI for your application."""
pass
@cli.command()
@click.argument('dt_start')
@click.argument('dt_end')
@async_command
async def bulk_note_range(dt_start: str, dt_end: str):
"""
Build daily notes for a date range.
DT_START and DT_END should be in YYYY-MM-DD format.
"""
try:
start_date = dt_datetime.strptime(dt_start, "%Y-%m-%d")
end_date = dt_datetime.strptime(dt_end, "%Y-%m-%d")
except ValueError:
click.echo("Error: Dates must be in YYYY-MM-DD format.")
return
if start_date > end_date:
click.echo("Error: Start date must be before or equal to end date.")
return
results = []
current_date = start_date
while current_date <= end_date:
formatted_date = await loc.dt(current_date)
result = await build_daily_note(formatted_date)
results.append(result)
current_date += timedelta(days=1)
click.echo("Generated notes for the following dates:")
for url in results:
click.echo(url)
if __name__ == '__main__':
cli()

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@ -1,22 +1,34 @@
from aura_sr import AuraSR
from PIL import Image
import torch
import os
aura_sr = AuraSR.from_pretrained("fal-ai/AuraSR")
# Set environment variables for MPS
os.environ['PYTORCH_MPS_HIGH_WATERMARK_RATIO'] = '0.0'
os.environ['PYTORCH_ENABLE_MPS_FALLBACK'] = '1'
# Initialize device as CPU for default
device = torch.device('cpu')
# Check if MPS is available
if torch.backends.mps.is_available():
if not torch.backends.mps.is_built():
print("MPS not available because the current PyTorch install was not built with MPS enabled.")
else:
device = torch.device('mps:0')
# Overwrite the default CUDA device with MPS
torch.cuda.default_stream = device
aura_sr = AuraSR.from_pretrained("fal-ai/AuraSR").to(device)
def load_image_from_path(file_path):
# Open image file
return Image.open(file_path)
def upscale_and_save(original_path):
# load the image from the path
original_image = load_image_from_path(original_path)
# upscale the image using the pretrained model
upscaled_image = aura_sr.upscale_4x(original_image)
# save the upscaled image back to the original path
# Overwrite the original image
upscaled_image.save(original_path)
# Now to use the function, provide the image path
# Insert your image path
upscale_and_save("/Users/sij/workshop/sijapi/sijapi/testbed/API__00482_ 2.png")

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@ -1,3 +1,4 @@
# logs.py
import os
import sys
from loguru import logger

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@ -1,6 +1,7 @@
'''
Uses whisper_cpp to create an OpenAI-compatible Whisper web service.
'''
# routers/asr.py
import os
import sys
import uuid

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@ -66,7 +66,7 @@ IG_VISION_LLM = os.getenv("IG_VISION_LLM")
IG_PROMPT_LLM = os.getenv("IG_PROMPT_LLM")
IG_IMG_GEN = os.getenv("IG_IMG_GEN", "ComfyUI")
IG_OUTPUT_PLATFORMS = os.getenv("IG_OUTPUT_PLATFORMS", "ig,ghost,obsidian").split(',')
SD_WORKFLOWS_DIR = os.path.join(COMFYUI_DIR, 'workflows')
IMG_WORKFLOWS_DIR = os.path.join(COMFYUI_DIR, 'workflows')
COMFYUI_OUTPUT_DIR = COMFYUI_DIR / 'output'
IG_PROFILES_DIR = os.path.join(BASE_DIR, 'profiles')
IG_PROFILE_DIR = os.path.join(IG_PROFILES_DIR, PROFILE)
@ -793,7 +793,7 @@ def load_json(json_payload, workflow):
if json_payload:
return json.loads(json_payload)
elif workflow:
workflow_path = os.path.join(SD_WORKFLOWS_DIR, f"{workflow}.json" if not workflow.endswith('.json') else workflow)
workflow_path = os.path.join(IMG_WORKFLOWS_DIR, f"{workflow}.json" if not workflow.endswith('.json') else workflow)
with open(workflow_path, 'r') as file:
return json.load(file)
else:

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@ -2,7 +2,7 @@
Image generation module using StableDiffusion and similar models by way of ComfyUI.
DEPENDS ON:
LLM module
COMFYUI_URL, COMFYUI_DIR, COMFYUI_OUTPUT_DIR, TS_SUBNET, TS_ADDRESS, DATA_DIR, SD_CONFIG_DIR, SD_IMAGE_DIR, SD_WORKFLOWS_DIR, LOCAL_HOSTS, API.URL, PHOTOPRISM_USER*, PHOTOPRISM_URL*, PHOTOPRISM_PASS*
COMFYUI_URL, COMFYUI_DIR, COMFYUI_OUTPUT_DIR, TS_SUBNET, TS_ADDRESS, DATA_DIR, IMG_CONFIG_DIR, IMG_DIR, IMG_WORKFLOWS_DIR, LOCAL_HOSTS, API.URL, PHOTOPRISM_USER*, PHOTOPRISM_URL*, PHOTOPRISM_PASS*
*unimplemented.
'''
@ -30,7 +30,7 @@ import shutil
# from photoprism.Photo import Photo
# from webdav3.client import Client
from sijapi.routers.llm import query_ollama
from sijapi import API, L, COMFYUI_URL, COMFYUI_OUTPUT_DIR, SD_CONFIG_PATH, SD_IMAGE_DIR, SD_WORKFLOWS_DIR
from sijapi import API, L, COMFYUI_URL, COMFYUI_OUTPUT_DIR, IMG_CONFIG_PATH, IMG_DIR, IMG_WORKFLOWS_DIR
img = APIRouter()
@ -86,7 +86,7 @@ async def workflow(prompt: str, scene: str = None, size: str = None, earlyout: s
width, height = map(int, size.split('x'))
L.DEBUG(f"Parsed width: {width}; parsed height: {height}")
workflow_path = Path(SD_WORKFLOWS_DIR) / scene_workflow['workflow']
workflow_path = Path(IMG_WORKFLOWS_DIR) / scene_workflow['workflow']
workflow_data = json.loads(workflow_path.read_text())
post = {
@ -104,7 +104,7 @@ async def workflow(prompt: str, scene: str = None, size: str = None, earlyout: s
print(f"Prompt ID: {prompt_id}")
max_size = max(width, height) if downscale_to_fit else None
destination_path = Path(destination_path).with_suffix(".jpg") if destination_path else SD_IMAGE_DIR / f"{prompt_id}.jpg"
destination_path = Path(destination_path).with_suffix(".jpg") if destination_path else IMG_DIR / f"{prompt_id}.jpg"
if earlyout:
asyncio.create_task(generate_and_save_image(prompt_id, saved_file_key, max_size, destination_path))
@ -132,7 +132,7 @@ async def generate_and_save_image(prompt_id, saved_file_key, max_size, destinati
def get_web_path(file_path: Path) -> str:
uri = file_path.relative_to(SD_IMAGE_DIR)
uri = file_path.relative_to(IMG_DIR)
web_path = f"{API.URL}/img/{uri}"
return web_path
@ -174,8 +174,8 @@ async def get_image(status_data, key):
async def save_as_jpg(image_data, prompt_id, max_size = None, quality = 100, destination_path: Path = None):
destination_path_png = (SD_IMAGE_DIR / prompt_id).with_suffix(".png")
destination_path_jpg = destination_path.with_suffix(".jpg") if destination_path else (SD_IMAGE_DIR / prompt_id).with_suffix(".jpg")
destination_path_png = (IMG_DIR / prompt_id).with_suffix(".png")
destination_path_jpg = destination_path.with_suffix(".jpg") if destination_path else (IMG_DIR / prompt_id).with_suffix(".jpg")
try:
destination_path_png.parent.mkdir(parents=True, exist_ok=True)
@ -224,16 +224,16 @@ def set_presets(workflow_data, preset_values):
def get_return_path(destination_path):
sd_dir = Path(SD_IMAGE_DIR)
sd_dir = Path(IMG_DIR)
if destination_path.parent.samefile(sd_dir):
return destination_path.name
else:
return str(destination_path)
def get_scene(scene):
with open(SD_CONFIG_PATH, 'r') as SD_CONFIG_file:
SD_CONFIG = yaml.safe_load(SD_CONFIG_file)
for scene_data in SD_CONFIG['scenes']:
with open(IMG_CONFIG_PATH, 'r') as IMG_CONFIG_file:
IMG_CONFIG = yaml.safe_load(IMG_CONFIG_file)
for scene_data in IMG_CONFIG['scenes']:
if scene_data['scene'] == scene:
L.DEBUG(f"Found scene for \"{scene}\".")
return scene_data
@ -246,9 +246,9 @@ def get_matching_scene(prompt):
prompt_lower = prompt.lower()
max_count = 0
scene_data = None
with open(SD_CONFIG_PATH, 'r') as SD_CONFIG_file:
SD_CONFIG = yaml.safe_load(SD_CONFIG_file)
for sc in SD_CONFIG['scenes']:
with open(IMG_CONFIG_PATH, 'r') as IMG_CONFIG_file:
IMG_CONFIG = yaml.safe_load(IMG_CONFIG_file)
for sc in IMG_CONFIG['scenes']:
count = sum(1 for trigger in sc['triggers'] if trigger in prompt_lower)
if count > max_count:
max_count = count
@ -259,7 +259,7 @@ def get_matching_scene(prompt):
return scene_data
else:
L.DEBUG(f"No matching scenes found, falling back to default scene.")
return SD_CONFIG['scenes'][0]
return IMG_CONFIG['scenes'][0]
@ -400,7 +400,7 @@ async def get_generation_options():
async def load_workflow(workflow_path: str, workflow:str):
workflow_path = workflow_path if workflow_path else os.path.join(SD_WORKFLOWS_DIR, f"{workflow}.json" if not workflow.endswith('.json') else workflow)
workflow_path = workflow_path if workflow_path else os.path.join(IMG_WORKFLOWS_DIR, f"{workflow}.json" if not workflow.endswith('.json') else workflow)
with open(workflow_path, 'r') as file:
return json.load(file)

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@ -1,6 +1,7 @@
'''
Interfaces with Ollama and creates an OpenAI-compatible relay API.
'''
# routers/llm.py
from fastapi import APIRouter, HTTPException, Request, Response, BackgroundTasks, File, Form, UploadFile
from fastapi.responses import StreamingResponse, JSONResponse, FileResponse
from datetime import datetime as dt_datetime

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@ -1,3 +1,4 @@
# routers/news.py
import os
import uuid
import asyncio
@ -90,7 +91,7 @@ async def download_and_save_article(article, site_name, earliest_date, bg_tasks:
try:
banner_url = article.top_image
if banner_url:
banner_image = download_file(banner_url, Path(OBSIDIAN_VAULT_DIR / OBSIDIAN_RESOURCES_DIR))
banner_image = download_file(banner_url, Path(OBSIDIAN_VAULT_DIR / OBSIDIAN_RESOURCES_DIR / f"{dt_datetime.now().strftime('%Y%m%d%H%M%S')}.jpg"))
if banner_image:
banner_markdown = f"![[{OBSIDIAN_RESOURCES_DIR}/{banner_image}]]"
except Exception as e:
@ -120,7 +121,7 @@ tags:
bg_tasks=bg_tasks,
text=tts_text,
voice=voice,
model="eleven_turbo_v2",
model="xtts2",
podcast=True,
title=audio_filename,
output_dir=Path(OBSIDIAN_VAULT_DIR) / OBSIDIAN_RESOURCES_DIR
@ -176,7 +177,7 @@ async def process_news_site(site, bg_tasks: BackgroundTasks):
earliest_date,
bg_tasks,
tts_mode=site.tts if hasattr(site, 'tts') else "off",
voice=site.tts if hasattr(site, 'tts') else DEFAULT_11L_VOICE
voice=site.voice if hasattr(site, 'voice') else DEFAULT_11L_VOICE
))
tasks.append(task)
@ -237,12 +238,11 @@ async def archive_post(
async def clip_get(
bg_tasks: BackgroundTasks,
url: str,
title: Optional[str] = Query(None),
encoding: str = Query('utf-8'),
tts: str = Query('summary'),
voice: str = Query(DEFAULT_VOICE)
):
markdown_filename = await process_article(bg_tasks, url, title, encoding, tts=tts, voice=voice)
parsed_content = await parse_article(url)
markdown_filename = await process_article(bg_tasks, parsed_content, tts, voice)
return {"message": "Clip saved successfully", "markdown_filename": markdown_filename}
@news.post("/note/add")

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@ -1,6 +1,7 @@
'''
Manages an Obsidian vault, in particular daily notes, using information and functionality drawn from the other routers, primarily calendar, email, ig, llm, rag, img, serve, time, tts, and weather.
'''
# routers/note.py
from fastapi import APIRouter, BackgroundTasks, File, UploadFile, Form, HTTPException, Response, Query, Path as FastAPIPath
from fastapi.responses import JSONResponse, PlainTextResponse
import os, re

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@ -30,7 +30,7 @@ from selenium.webdriver.support import expected_conditions as EC
from sijapi import (
L, LOGS_DIR, TS_ID, CASETABLE_PATH, COURTLISTENER_DOCKETS_URL, COURTLISTENER_API_KEY,
COURTLISTENER_BASE_URL, COURTLISTENER_DOCKETS_DIR, COURTLISTENER_SEARCH_DIR, ALERTS_DIR,
MAC_UN, MAC_PW, MAC_ID, TS_TAILNET, DATA_DIR, SD_IMAGE_DIR, PUBLIC_KEY, OBSIDIAN_VAULT_DIR
MAC_UN, MAC_PW, MAC_ID, TS_TAILNET, DATA_DIR, IMG_DIR, PUBLIC_KEY, OBSIDIAN_VAULT_DIR
)
from sijapi.utilities import bool_convert, sanitize_filename, assemble_journal_path
from sijapi.routers import loc, note
@ -44,7 +44,7 @@ async def get_pgp():
@serve.get("/img/{image_name}")
def serve_image(image_name: str):
image_path = os.path.join(SD_IMAGE_DIR, image_name)
image_path = os.path.join(IMG_DIR, image_name)
if os.path.exists(image_path):
return FileResponse(image_path)
else:

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@ -14,7 +14,7 @@ from typing import Optional, Union, List
from pydub import AudioSegment
from TTS.api import TTS
from pathlib import Path
from datetime import datetime
from datetime import datetime as dt_datetime
from time import time
import torch
import traceback
@ -66,21 +66,26 @@ async def list_11l_voices():
def select_voice(voice_name: str) -> str:
async def select_voice(voice_name: str) -> str:
try:
voice_file = VOICE_DIR / f"{voice_name}.wav"
L.DEBUG(f"select_voice received query to use voice: {voice_name}. Looking for {voice_file} inside {VOICE_DIR}.")
# Case Insensitive comparison
voice_name_lower = voice_name.lower()
L.DEBUG(f"Looking for {voice_name_lower}")
for item in VOICE_DIR.iterdir():
L.DEBUG(f"Checking {item.name.lower()}")
if item.name.lower() == f"{voice_name_lower}.wav":
L.DEBUG(f"select_voice received query to use voice: {voice_name}. Found {item} inside {VOICE_DIR}.")
return str(item)
L.ERR(f"Voice file not found")
raise HTTPException(status_code=404, detail="Voice file not found")
if voice_file.is_file():
return str(voice_file)
else:
raise HTTPException(status_code=404, detail="Voice file not found")
except Exception as e:
L.ERR(f"Voice file not found: {str(e)}")
return None
@tts.post("/tts")
@tts.post("/tts/speak")
@tts.post("/v1/audio/speech")
@ -132,13 +137,14 @@ async def generate_speech(
try:
model = model if model else await get_model(voice, voice_file)
title = title if title else "TTS audio"
output_path = output_dir / f"{dt_datetime.now().strftime('%Y%m%d%H%M%S')} {title}.wav"
if model == "eleven_turbo_v2":
L.INFO("Using ElevenLabs.")
audio_file_path = await elevenlabs_tts(model, text, voice, title, output_dir)
else: # if model == "xtts":
L.INFO("Using XTTS2")
audio_file_path = await local_tts(text, speed, voice, voice_file, podcast, bg_tasks, title, output_dir)
audio_file_path = await local_tts(text, speed, voice, voice_file, podcast, bg_tasks, title, output_path)
#else:
# raise HTTPException(status_code=400, detail="Invalid model specified")
@ -158,7 +164,7 @@ async def generate_speech(
async def get_model(voice: str = None, voice_file: UploadFile = None):
if voice_file or (voice and select_voice(voice)):
if voice_file or (voice and await select_voice(voice)):
return "xtts"
elif voice and await determine_voice_id(voice):
@ -220,7 +226,7 @@ async def elevenlabs_tts(model: str, input_text: str, voice: str, title: str = N
async with httpx.AsyncClient(timeout=httpx.Timeout(300.0)) as client: # 5 minutes timeout
response = await client.post(url, json=payload, headers=headers)
output_dir = output_dir if output_dir else TTS_OUTPUT_DIR
title = title if title else datetime.now().strftime("%Y%m%d%H%M%S")
title = title if title else dt_datetime.now().strftime("%Y%m%d%H%M%S")
filename = f"{sanitize_filename(title)}.mp3"
file_path = Path(output_dir) / filename
if response.status_code == 200:
@ -245,7 +251,9 @@ async def get_text_content(text: Optional[str], file: Optional[UploadFile]) -> s
async def get_voice_file_path(voice: str = None, voice_file: UploadFile = None) -> str:
if voice:
return select_voice(voice)
L.DEBUG(f"Looking for voice: {voice}")
selected_voice = await select_voice(voice)
return selected_voice
elif voice_file and isinstance(voice_file, UploadFile):
VOICE_DIR.mkdir(exist_ok=True)
@ -272,8 +280,9 @@ async def get_voice_file_path(voice: str = None, voice_file: UploadFile = None)
return str(new_file)
else:
L.DEBUG(f"{datetime.now().strftime('%Y%m%d%H%M%S')}: No voice specified or file provided, using default voice: {DEFAULT_VOICE}")
return select_voice(DEFAULT_VOICE)
L.DEBUG(f"{dt_datetime.now().strftime('%Y%m%d%H%M%S')}: No voice specified or file provided, using default voice: {DEFAULT_VOICE}")
selected_voice = await select_voice(DEFAULT_VOICE)
return selected_voice
@ -290,7 +299,7 @@ async def local_tts(
if output_path:
file_path = Path(output_path)
else:
datetime_str = datetime.now().strftime("%Y%m%d%H%M%S")
datetime_str = dt_datetime.now().strftime("%Y%m%d%H%M%S")
title = sanitize_filename(title) if title else "Audio"
filename = f"{datetime_str}_{title}.wav"
file_path = TTS_OUTPUT_DIR / filename

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@ -1,3 +1,4 @@
# utilities.py
import re
import os
from fastapi import Form