add glm-47 and deepseek-v32

## Motivation

Add documentation to help AI coding agents (Claude Code, Cursor, GitHub
Copilot, etc.) understand the exo codebase and contribute effectively.

## Changes

- Add `AGENTS.md` with guidance for AI agents working on the codebase
- Add symlink `CLAUDE.md -> AGENTS.md` for backwards compatibility with
Claude Code

## Why It Works

`AGENTS.md` is becoming a standard convention for AI agent instructions.
The symlink ensures Claude Code (which looks for `CLAUDE.md`) continues
to work while supporting the broader `AGENTS.md` convention.

## Test Plan

### Manual Testing
- Verified symlink works correctly

### Automated Testing
- N/A (documentation only)

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>

AGENTS.md

@@ -0,0 +1,96 @@
+# AGENTS.md
+
+This file provides guidance to AI coding agents when working with code in this repository.
+
+## Project Overview
+
+exo is a distributed AI inference system that connects multiple devices into a cluster. It enables running large language models across multiple machines using MLX as the inference backend and libp2p for peer-to-peer networking.
+
+## Build & Run Commands
+
+```bash
+# Build the dashboard (required before running exo)
+cd dashboard && npm install && npm run build && cd ..
+
+# Run exo (starts both master and worker with API at http://localhost:52415)
+uv run exo
+
+# Run with verbose logging
+uv run exo -v   # or -vv for more verbose
+
+# Run tests (excludes slow tests by default)
+uv run pytest
+
+# Run all tests including slow tests
+uv run pytest -m ""
+
+# Run a specific test file
+uv run pytest src/exo/shared/tests/test_election.py
+
+# Run a specific test function
+uv run pytest src/exo/shared/tests/test_election.py::test_function_name
+
+# Type checking (strict mode)
+uv run basedpyright
+
+# Linting
+uv run ruff check
+
+# Format code (using nix)
+nix fmt
+```
+
+## Architecture
+
+### Node Composition
+A single exo `Node` (src/exo/main.py) runs multiple components:
+- **Router**: libp2p-based pub/sub messaging via Rust bindings (exo_pyo3_bindings)
+- **Worker**: Handles inference tasks, downloads models, manages runner processes
+- **Master**: Coordinates cluster state, places model instances across nodes
+- **Election**: Bully algorithm for master election
+- **API**: FastAPI server for OpenAI-compatible chat completions
+
+### Message Flow
+Components communicate via typed pub/sub topics (src/exo/routing/topics.py):
+- `GLOBAL_EVENTS`: Master broadcasts indexed events to all workers
+- `LOCAL_EVENTS`: Workers send events to master for indexing
+- `COMMANDS`: Workers/API send commands to master
+- `ELECTION_MESSAGES`: Election protocol messages
+- `CONNECTION_MESSAGES`: libp2p connection updates
+
+### Event Sourcing
+The system uses event sourcing for state management:
+- `State` (src/exo/shared/types/state.py): Immutable state object
+- `apply()` (src/exo/shared/apply.py): Pure function that applies events to state
+- Master indexes events and broadcasts; workers apply indexed events
+
+### Key Type Hierarchy
+- `src/exo/shared/types/`: Pydantic models for all shared types
+  - `events.py`: Event types (discriminated union)
+  - `commands.py`: Command types
+  - `tasks.py`: Task types for worker execution
+  - `state.py`: Cluster state model
+
+### Rust Components
+Rust code in `rust/` provides:
+- `networking`: libp2p networking (gossipsub, peer discovery)
+- `exo_pyo3_bindings`: PyO3 bindings exposing Rust to Python
+- `system_custodian`: System-level operations
+
+### Dashboard
+Svelte 5 + TypeScript frontend in `dashboard/`. Build output goes to `dashboard/build/` and is served by the API.
+
+## Code Style Requirements
+
+From .cursorrules:
+- Strict, exhaustive typing - never bypass the type-checker
+- Use `Literal[...]` for enum-like sets, `typing.NewType` for primitives
+- Pydantic models with `frozen=True` and `strict=True`
+- Pure functions with injectable effect handlers for side-effects
+- Descriptive names - no abbreviations or 3-letter acronyms
+- Catch exceptions only where you can handle them meaningfully
+- Use `@final` and immutability wherever applicable
+
+## Testing
+
+Tests use pytest-asyncio with `asyncio_mode = "auto"`. Tests are in `tests/` subdirectories alongside the code they test. The `EXO_TESTS=1` env var is set during tests.

CLAUDE.md

@@ -0,0 +1 @@
+AGENTS.md

src/exo/shared/models/model_cards.py

@@ -70,34 +70,36 @@ MODEL_CARDS: dict[str, ModelCard] = {
             supports_tensor=True,
         ),
     ),
-    # "deepseek-v3.2": ModelCard(
-    #     short_id="deepseek-v3.2",
-    #     model_id=ModelId("mlx-community/DeepSeek-V3.2-8bit"),
-    #     name="DeepSeek V3.2 (8-bit)",
-    #     description="""DeepSeek V3.2 is a large language model trained on the DeepSeek V3.2 dataset.""",
-    #     tags=[],
-    #     metadata=ModelMetadata(
-    #         model_id=ModelId("mlx-community/DeepSeek-V3.2-8bit"),
-    #         pretty_name="DeepSeek V3.2 (8-bit)",
-    #         storage_size=Memory.from_kb(754706307),
-    #         n_layers=61,
-    #         hidden_size=7168,
-    #     ),
-    # ),
-    # "deepseek-v3.2-4bit": ModelCard(
-    #     short_id="deepseek-v3.2-4bit",
-    #     model_id=ModelId("mlx-community/DeepSeek-V3.2-4bit"),
-    #     name="DeepSeek V3.2 (4-bit)",
-    #     description="""DeepSeek V3.2 is a large language model trained on the DeepSeek V3.2 dataset.""",
-    #     tags=[],
-    #     metadata=ModelMetadata(
-    #         model_id=ModelId("mlx-community/DeepSeek-V3.2-4bit"),
-    #         pretty_name="DeepSeek V3.2 (4-bit)",
-    #         storage_size=Memory.from_kb(754706307 // 2),  # TODO !!!!!
-    #         n_layers=61,
-    #         hidden_size=7168,
-    #     ),
-    # ),
+    "deepseek-v3.2": ModelCard(
+        short_id="deepseek-v3.2",
+        model_id=ModelId("mlx-community/DeepSeek-V3.2-8bit"),
+        name="DeepSeek V3.2 (8-bit)",
+        description="""DeepSeek V3.2 is a large language model trained on the DeepSeek V3.2 dataset.""",
+        tags=[],
+        metadata=ModelMetadata(
+            model_id=ModelId("mlx-community/DeepSeek-V3.2-8bit"),
+            pretty_name="DeepSeek V3.2 (8-bit)",
+            storage_size=Memory.from_kb(754706307),
+            n_layers=61,
+            hidden_size=7168,
+            supports_tensor=True,
+        ),
+    ),
+    "deepseek-v3.2-4bit": ModelCard(
+        short_id="deepseek-v3.2-4bit",
+        model_id=ModelId("mlx-community/DeepSeek-V3.2-4bit"),
+        name="DeepSeek V3.2 (4-bit)",
+        description="""DeepSeek V3.2 is a large language model trained on the DeepSeek V3.2 dataset.""",
+        tags=[],
+        metadata=ModelMetadata(
+            model_id=ModelId("mlx-community/DeepSeek-V3.2-4bit"),
+            pretty_name="DeepSeek V3.2 (4-bit)",
+            storage_size=Memory.from_kb(754706307 // 2),  # TODO !!!!!
+            n_layers=61,
+            hidden_size=7168,
+            supports_tensor=True,
+        ),
+    ),
     # deepseek r1
     # "deepseek-r1-0528-4bit": ModelCard(
     #     short_id="deepseek-r1-0528-4bit",
@@ -554,6 +556,36 @@ MODEL_CARDS: dict[str, ModelCard] = {
             supports_tensor=True,
         ),
     ),
+    "glm-4.7-4bit": ModelCard(
+        short_id="glm-4.7-4bit",
+        model_id=ModelId("mlx-community/GLM-4.7-4bit"),
+        name="GLM 4.7 4bit",
+        description="GLM 4.7 4bit",
+        tags=[],
+        metadata=ModelMetadata(
+            model_id=ModelId("mlx-community/GLM-4.7-4bit"),
+            pretty_name="GLM 4.7 4bit",
+            storage_size=Memory.from_bytes(198556925568),
+            n_layers=91,
+            hidden_size=5120,
+            supports_tensor=True,
+        ),
+    ),
+    "glm-4.7-8bit-gs32": ModelCard(
+        short_id="glm-4.7-8bit-gs32",
+        model_id=ModelId("mlx-community/GLM-4.7-8bit-gs32"),
+        name="GLM 4.7 8bit (gs32)",
+        description="GLM 4.7 8bit (gs32)",
+        tags=[],
+        metadata=ModelMetadata(
+            model_id=ModelId("mlx-community/GLM-4.7-8bit-gs32"),
+            pretty_name="GLM 4.7 8bit (gs32)",
+            storage_size=Memory.from_bytes(396963397248),
+            n_layers=91,
+            hidden_size=5120,
+            supports_tensor=True,
+        ),
+    ),
     # "devstral-2-123b-instruct-2512-8bit": ModelCard(
     #     short_id="devstral-2-123b-instruct-2512-8bit",
     #     model_id=ModelId("mlx-community/Devstral-2-123B-Instruct-2512-8bit"),

tests/headless_runner.py

@@ -89,6 +89,10 @@ async def assert_downloads():
     await sd.ensure_shard(
         await build_full_shard(MODEL_CARDS["gpt-oss-20b-4bit"].model_id)
     )
+    await sd.ensure_shard(await build_full_shard(MODEL_CARDS["deepseek-v3.2"].model_id))
+    await sd.ensure_shard(
+        await build_full_shard(MODEL_CARDS["glm-4.7-8bit-gs32"].model_id)
+    )
 
 
 async def ring_backend(test: Tests):