Release v2.3.0 — remove AI Chat UI from README, bump to stable

Phase out AI Chat UI references from README while keeping the code.
Update CI badge and star history URLs to goldspanlabs org.
Bump version from 2.3.0b5 to 2.3.0 stable release.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

Author: michaelchu

README.md

@@ -1,16 +1,16 @@
 ![Badge](https://hitscounter.dev/api/hit?url=https%3A%2F%2Fgithub.com%2Fmichaelchu%2Foptopsy&label=Visitors&icon=suitcase-lg&color=%239ec5fe&message=&style=flat&tz=Canada%2FEastern)
 ![Badge](https://hitscounter.dev/api/hit?url=https%3A%2F%2Fmichaelchu.github.io%2Foptopsy%2F&label=Docs&icon=github&color=%23d2f4ea&message=&style=flat&tz=Canada%2FEastern)
-[![CI](https://github.com/michaelchu/optopsy/actions/workflows/ci.yml/badge.svg)](https://github.com/michaelchu/optopsy/actions/workflows/ci.yml)
+[![CI](https://github.com/goldspanlabs/optopsy/actions/workflows/ci.yml/badge.svg)](https://github.com/goldspanlabs/optopsy/actions/workflows/ci.yml)
 [![PyPI version](https://badge.fury.io/py/optopsy.svg)](https://badge.fury.io/py/optopsy)
 [![Python](https://img.shields.io/pypi/pyversions/optopsy)](https://pypi.org/project/optopsy/)
 
 
 
 <img src="docs/assets/logo.png" alt="Optopsy" width="150">
 
-An AI-powered research and backtesting tool for options strategies.
+A nimble backtesting and statistics library for options strategies.
 
-Optopsy combines a Python backtesting engine with an optional conversational AI interface that fetches data from online or local sources, runs strategies, and interprets results — so you can go from *"How do 45-DTE iron condors on SPX perform with a 50% profit target and 2x stop loss vs holding to expiration?"* to detailed performance statistics in seconds, not spreadsheets.
+Optopsy is a Python backtesting engine that lets you go from *"How do 45-DTE iron condors on SPX perform with a 50% profit target and 2x stop loss vs holding to expiration?"* to detailed performance statistics in seconds, not spreadsheets.
 
 [Full Documentation](https://michaelchu.github.io/optopsy/) | [API Reference](https://michaelchu.github.io/optopsy/api-reference/) | [Examples](https://michaelchu.github.io/optopsy/examples/)
 
@@ -33,106 +33,22 @@ Optopsy combines a Python backtesting engine with an optional conversational AI
 - **Live Data Providers** - Fetch options chains and stock prices directly from supported data sources (e.g. EODHD)
 - **Smart Caching** - Automatic local caching of fetched data with gap detection for efficient re-fetches
 - **Plugin System** - Extend with custom strategies, signals, and data providers via entry points
-- **AI Chat UI** - Interactive AI-powered chat interface with conversation starters, settings panel, and result caching
 
 ## Installation
 
 ```bash
 # Core library only (latest stable release)
 pip install optopsy
 
-# With Data CLI (download & cache market data, no Chainlit needed)
+# With Data CLI (download & cache market data)
 pip install optopsy[data]
-
-# With AI Chat UI (beta — requires pre-release, includes data package)
-pip install --pre optopsy[ui]
 ```
 
 **Requirements:** Python 3.12-3.13, Pandas 2.0+, NumPy 1.26+
 
-## AI Chat UI (Beta)
-
-An AI-powered chat interface that lets you fetch data, run backtests, and interpret results using natural language.
-
-![AI Chat UI](docs/images/example.gif)
-
-### Setup & Configuration
-
-Install the beta pre-release with the `ui` extra:
-
-```bash
-pip install --pre optopsy[ui]
-```
-
-Configure your environment variables in a `.env` file at the project root (the app auto-loads it):
-
-```env
-ANTHROPIC_API_KEY=sk-ant-...       # or OPENAI_API_KEY for OpenAI models
-EODHD_API_KEY=your-key-here        # enables live data downloads (optional)
-OPTOPSY_MODEL=anthropic/claude-haiku-4-5-20251001  # override the default model (optional)
-```
-
-At minimum you need an LLM API key (`ANTHROPIC_API_KEY` or `OPENAI_API_KEY`). Set `EODHD_API_KEY` to enable downloading historical options data directly from [EODHD](https://eodhd.com/). The `OPTOPSY_MODEL` variable accepts any [LiteLLM model string](https://docs.litellm.ai/docs/providers) if you want to use a different model.
-
-### Downloading Data
-
-The recommended workflow is to download data first via the CLI, then use the chat agent to analyze it:
-
-```bash
-# Download historical options data (requires EODHD_API_KEY)
-optopsy-chat download SPY
-optopsy-chat download SPY AAPL TSLA    # multiple symbols
-optopsy-chat download SPY -v           # verbose/debug output
-```
-
-> **Note:** If developing with `uv`, prefix commands with `uv run` (e.g., `uv run optopsy-chat download SPY`).
-
-Data is stored locally as Parquet files at `~/.optopsy/cache/`. Re-running the download command only fetches new data since your last download — it won't re-download what you already have. A Rich progress display shows download progress in the terminal.
-
-Once downloaded, the chat agent can query this data instantly without needing to re-fetch. Stock price history (via yfinance) is also cached locally and fetched automatically when the agent needs it for charting or signal analysis — no manual download required.
-
-### Cache Management
-
-```bash
-optopsy-chat cache size              # show per-symbol disk usage
-optopsy-chat cache clear             # clear all cached data
-optopsy-chat cache clear SPY         # clear specific symbol
-```
-
-### Launching the Chat
-
-```bash
-optopsy-chat                         # launch (opens browser)
-optopsy-chat run --port 9000         # custom port
-optopsy-chat run --headless          # don't open browser
-optopsy-chat run --debug             # enable debug logging
-```
-
-### What the Agent Can Do
-
-- **Run any of the 38 strategies** — ask in plain English (e.g. *"Run iron condors on SPY with 30-45 DTE"*) and the agent picks the right function and parameters
-- **Fetch live options data** — pull options chains from EODHD and cache them locally for fast repeat access
-- **Fetch stock price history** — automatically download OHLCV data via yfinance for charting and signal analysis
-- **Load & preview CSV data** — drag-and-drop a CSV into the chat or point to a file on disk; inspect shape, columns, date ranges, and sample rows
-- **Scan & compare strategies** — run up to 50 strategy/parameter combinations in one call and get a ranked leaderboard
-- **Suggest parameters** — analyze your dataset's DTE and OTM% distributions and recommend sensible starting ranges
-- **Build entry/exit signals** — compose 80+ technical analysis signals (momentum, overlap, volatility, trend, volume, IV rank, calendar) with AND/OR logic
-- **Simulate trades** — run chronological simulations with starting capital, position limits, and a full equity curve with metrics (win rate, profit factor, max drawdown, etc.)
-- **Create interactive charts** — generate Plotly charts (line, bar, scatter, histogram, heatmap, candlestick with indicator overlays) from results, simulations, or raw data
-- **Multi-dataset sessions** — load multiple symbols, run the same strategy across each, and compare side-by-side
-- **Session memory** — the agent tracks all strategy runs and results so it can reference prior analysis without re-running
-
-### Data Providers
-
-EODHD is the built-in data provider for downloading historical options and stock data. The provider system is pluggable — you can build custom providers by subclassing `DataProvider` in `optopsy/data/providers/` to integrate your own data sources.
-
-> **Note:** The download and cache commands are also available via the standalone `optopsy-data` CLI (`pip install optopsy[data]`) without the Chainlit dependency. See [Data Management](https://michaelchu.github.io/optopsy/data/) for details.
-
-See the [Chat UI documentation](https://michaelchu.github.io/optopsy/chat-ui/) for more details.
-
 ## Data Management
 
-Optopsy includes a standalone data CLI for downloading and caching historical market data — no chat UI or Chainlit required.
+Optopsy includes a standalone data CLI for downloading and caching historical market data.
 
 ```bash
 pip install optopsy[data]
@@ -234,13 +150,12 @@ The simulator works with all 38 strategies. It selects one trade per entry date,
 - [Parameters](https://michaelchu.github.io/optopsy/parameters/) - Configuration options reference
 - [Entry Signals](https://michaelchu.github.io/optopsy/entry-signals/) - Technical analysis signal filters
 - [Data Management](https://michaelchu.github.io/optopsy/data/) - Standalone data CLI and caching
-- [Chat UI](https://michaelchu.github.io/optopsy/chat-ui/) - AI-powered chat interface
 - [Examples](https://michaelchu.github.io/optopsy/examples/) - Common use cases and recipes
 - [API Reference](https://michaelchu.github.io/optopsy/api-reference/) - Complete function documentation
 
 ## Star History
 
-[![Star History Chart](https://app.repohistory.com/api/svg?repo=michaelchu/optopsy&type=Date&background=FFFFFF&color=62C3F8)](https://app.repohistory.com/star-history)
+[![Star History Chart](https://app.repohistory.com/api/svg?repo=goldspanlabs/optopsy&type=Date&background=FFFFFF&color=62C3F8)](https://app.repohistory.com/star-history)
 
 ## Disclaimer
 

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "optopsy"
-version = "2.3.0b5"
+version = "2.3.0"
 description = "A nimble backtesting and statistics library for options strategies"
 readme = "README.md"
 license = "AGPL-3.0-or-later"