Perform various data analysis on SEC 13-F and obtain some insights of fund activities such as number of holdings, AUM, and change of holdings between two quarters.
日本語の概要は準備中です。原文の説明を表示しています。
Google Text-to-Speech (gTTS) for converting text to audio. Use when creating audiobooks, podcasts, or speech synthesis from text. Handles long text by chunking at sentence boundaries and concatenating audio segments with pydub.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
gTTS is a Python library that converts text to speech using Google's Text-to-Speech API. It's free to use and doesn't require an API key.
pip install gtts pydub
pydub is useful for manipulating and concatenating audio files.
from gtts import gTTS
# Create speech
tts = gTTS(text="Hello, world!", lang='en')
# Save to file
tts.save("output.mp3")
# US English (default)
tts = gTTS(text="Hello", lang='en')
# British English
tts = gTTS(text="Hello", lang='en', tld='co.uk')
# Slow speech
tts = gTTS(text="Hello", lang='en', slow=True)
from gtts import gTTS
from pydub import AudioSegment
import tempfile
import os
import re
def chunk_text(text, max_chars=4500):
"""Split text into chunks at sentence boundaries."""
sentences = re.split(r'(?<=[.!?])\s+', text)
chunks = []
current_chunk = ""
for sentence in sentences:
if len(current_chunk) + len(sentence) < max_chars:
current_chunk += sentence + " "
else:
if current_chunk:
chunks.append(current_chunk.strip())
current_chunk = sentence + " "
if current_chunk:
chunks.append(current_chunk.strip())
return chunks
def text_to_audiobook(text, output_path):
"""Convert long text to a single audio file."""
chunks = chunk_text(text)
audio_segments = []
for i, chunk in enumerate(chunks):
# Create temp file for this chunk
with tempfile.NamedTemporaryFile(suffix='.mp3', delete=False) as tmp:
tmp_path = tmp.name
# Generate speech
tts = gTTS(text=chunk, lang='en', slow=False)
tts.save(tmp_path)
# Load and append
segment = AudioSegment.from_mp3(tmp_path)
audio_segments.append(segment)
# Cleanup
os.unlink(tmp_path)
# Concatenate all segments
combined = audio_segments[0]
for segment in audio_segments[1:]:
combined += segment
# Export
combined.export(output_path, format="mp3")
gTTS has a character limit per request (~5000 chars). For long documents:
If you prefer ffmpeg over pydub:
# Create file list
echo "file 'chunk1.mp3'" > files.txt
echo "file 'chunk2.mp3'" >> files.txt
# Concatenate
ffmpeg -f concat -safe 0 -i files.txt -c copy output.mp3
slow=False for natural speech speedまだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Perform various data analysis on SEC 13-F and obtain some insights of fund activities such as number of holdings, AUM, and change of holdings between two quarters.
日本語の概要は準備中です。原文の説明を表示しています。
AC branch pi-model power flow equations (P/Q and |S|) with transformer tap ratio and phase shift, matching `acopf-math-model.md` and MATPOWER branch fields. Use when computing branch flows in either direction, aggregating bus injections for nodal balance, checking MVA (rateA) limits, computing branch loading %, or debugging sign/units issues in AC power flow.
日本語の概要は準備中です。原文の説明を表示しています。
Redact text from PDF documents for blind review anonymization
日本語の概要は準備中です。原文の説明を表示しています。
Use when checking simplified ADA-derived plan-view bathroom accessibility constraints such as turning space, door clear width, toilet centerline, grab bars, and lavatory knee/toe clearance.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze failed GitHub Action jobs for a pull request.
日本語の概要は準備中です。原文の説明を表示しています。
Use when extracting plan-view architectural geometry from DXF files with semantic CAD layers, especially when outputs must normalize rooms, doors, fixtures, clearances, and grab bars into machine-checkable JSON.
日本語の概要は準備中です。原文の説明を表示しています。