Add LLM filtering pattern, .env.example, and workflows/lib

- Add .env.example with LLM_API_URL, LLM_MODEL, LLM_API_KEY
- Add .gitignore to exclude .env
- Add Pattern 5 (LLM filtering) to notebook-patterns.md
- Track workflows/lib with llm_call helper using mirascope
- Update README with LLM setup step and updated project structure

README.md

@@ -33,6 +33,14 @@ The goal is to use [opencode](https://opencode.ai) (or any LLM-powered coding to
 
 Replace `xxxxx` with your actual LiteLLM API key.
 
+4. **(Optional) LLM filtering in workflows** — if your workflows need to classify or score entities via an LLM, copy `.env.example` to `.env` and fill in your key:
+
+```bash
+cp .env.example .env
+```
+
+The `workflows/lib` module provides an `llm_call` helper (using [mirascope](https://mirascope.io)) for structured LLM calls — see Pattern 5 in `docs/notebook-patterns.md`.
+
 ## Quickstart
 
 1. Run `opencode` from the project root
@@ -60,11 +68,15 @@ It also includes API base URLs, a translation table mapping natural-language que
 ```
 internalai-agent/
 ├── AGENTS.md                        # LLM agent routing guide (entry point)
+├── .env.example                     # LLM credentials template
 ├── docs/
 │   ├── company-context.md           # Monadical org, tools, key concepts
 │   ├── contactdb-api.md             # ContactDB REST API reference
 │   ├── dataindex-api.md             # DataIndex REST API reference
 │   ├── connectors-and-sources.md    # Connector → entity type mappings
 │   └── notebook-patterns.md         # Marimo notebook templates and patterns
-└── workflows/                       # Generated analysis notebooks go here
+└── workflows/
+    └── lib/                         # Shared helpers for notebooks
+        ├── __init__.py
+        └── llm.py                   # llm_call() — structured LLM calls via mirascope
 ```