Kuniaki Shimizu kun432

AIユーザ:

Instruction: Set up a Python environment with necessary libraries for stock market data analysis and trading. Input: Use libraries such as pandas, NumPy, matplotlib, and a brokerage API (like Alpaca or Interactive Brokers). AIアシスタント:

Solution: To set up a Python environment suitable for stock market data analysis and trading, you'll need to install several essential libraries, including pandas, NumPy, matplotlib for data handling and visualization, and a brokerage API client such as alpaca-trade-api for interacting with Alpaca’s trading platform.

Here’s a step-by-step guide to setting up your environment:

Following the procedures below

https://gist.github.com/kun432/a8d7238c9c1fd738aed5f7d7771ba4a5

except:

using LLMWhisperer as text extractor instead of Llama Parse

Checking exisiting Unstract

Environment Info

$ docker version
Client:
 Version:           27.1.1
 API version:       1.46
 Go version:        go1.21.12

	┏━ Message ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
	┃ ┃
	┃ テクノロジー業界の巨人（AAPL、GOOGL、MSFT）の業績を比較してください: ┃
	┃ 1. 3社の財務データを取得してください ┃
	┃ 2. テクノロジー業界に影響を与える最近のニュースを分析してください ┃
	┃ 3. 比較指標と相関関係を計算してください ┃
	┃ 4. ポートフォリオの配分比率を推奨してください ┃
	┃ ┃
	┗━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┛
	┏━ Reasoning step 1 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

	services:
	chunker:
	command:
	- chunker-recursive
	- -p
	- pulsar://pulsar:6650
	- --chunk-size
	- '1000'
	- --chunk-overlap
	- '200'