Scaffold project skeleton with DESIGN.md and supporting docs

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# Go
/go/bin/
/go/pkg/
*.exe
*.exe~
*.dll
*.so
*.dylib
*.test
*.out
/vendor/
dist/
# Mattermost plugin
*.tar.gz
plugin.tar.gz
/server/plugin
/server/dist
# IDE / editors
.idea/
.vscode/
*.swp
*.swo
*~
.DS_Store
# OS
Thumbs.db
Desktop.ini
# Build artifacts
/tmp/
/build/
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# Changes
## v0.1.0 — 2026-06-16
- Project scaffolded: DESIGN.md, PROJECT.md, CHANGES.md, DECISIONS.md,
README.md, .gitignore
- No functional code yet — this is the pre-implementation skeleton
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# Design Decisions
This file records architectural choices and the alternatives considered.
New entries are added when a design decision is resolved (not when options
are brainstormed). Unresolved questions live in DESIGN.md §10.
---
## Why Mattermost Plugin vs Bot Account
**Context:** AI assistants in Mattermost can be implemented as plugins
(running inside the Mattermost server process) or as bot accounts
(independent services using the REST API and WebSocket).
**Alternatives considered:**
1. **Plugin** — hooks into slash commands, message hooks, KV store, System
Console config UI, and the plugin lifecycle. No separate process to
manage. Deployment is a single `.tar.gz` upload.
2. **Bot account** — separate service, more language freedom, but requires
managing OAuth tokens, WebSocket reconnection, a separate process with
its own lifecycle, and the bot account itself in Mattermost.
**Outcome:** Plugin chosen for v0.1.0 because:
- Single deployment artifact
- Built-in config UI via System Console
- No bot account to create and maintain
- KV store for persistence without a database
- Simpler for the target audience (self-hosted teams)
**Trade-off:** Plugin runs inside the Mattermost process — bugs can affect
server stability. Mitigated by standard isolation practices (panic recovery,
goroutine lifecycle management).
---
## Why Ollama
**Context:** Backend LLM provider for the plugin.
**Alternatives considered:**
1. **Ollama** — Single binary, simple REST API, streaming, model management,
self-hosted (data never leaves the infrastructure). Community Edition
friendly.
2. **OpenAI / Anthropic API** — SaaS, API key required, data leaves the
network, ongoing API costs. Not aligned with self-hosted Mattermost
ethos.
3. **Local inference (llama.cpp, etc.)** — More complex to set up and
manage. Ollama wraps this with a clean API.
**Outcome:** Ollama. It matches the self-hosted, no-data-leaves paradigm of
Mattermost Community Edition and provides the simplest API surface for a
plugin to consume.
---
## Why Per-Channel Per-User Context (Proposed)
**Context:** When a user sends `/ai <prompt>`, should the plugin remember
previous exchanges?
**Alternatives considered:**
1. **Per-user global** — Context follows the user across channels. Simple
but confusing: context from a #general question leaks into #dev.
2. **Per-channel per-user** — Each user gets separate context in each
channel. Natural mapping: different channels are different topics.
3. **No context** — Stateless. Simplest but every prompt is isolated;
users can't have a conversation.
**Outcome (proposed):** Per-channel per-user. Marked as D2 in DESIGN.md —
not final until v0.1.0 implementation.
---
*This file follows the template from the `project-docs` skill.*
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# Design: Mattermore — Mattermost AI Chat Agent for Ollama
> **Status:** Draft / Pre-implementation
> **Last updated:** 2026-06-16
> **Assumed direction:** AI chat agent plugin connecting to a remote Ollama instance.
> **Open questions are marked** `TODO(design):` throughout. This is a living template — change
> assumptions as the product direction firms up.
---
## 1. Purpose & Scope
### 1.1 What It Is
Mattermore is a Mattermost (Community Edition) plugin that lets users chat
with remote LLMs through an Ollama backend. Users invoke the plugin via a
slash command (e.g. `/ai`) and receive responses — either ephemeral or as
thread replies — streamed directly into the channel.
### 1.2 What It Is Not (Explicit Out-of-Scope)
| Out of scope | Rationale |
|---|---|
| Hosting its own LLM inference | Ollama is the sole backend; the plugin is a thin proxy |
| Multi-backend abstraction (OpenAI, Anthropic, etc.) | If needed later, abstract behind an `LLMProvider` interface — not now |
| Training / fine-tuning | Ollama handles that |
| Native webapp UI beyond slash commands | `TODO(design):` decide if a channel header button or RHS panel adds value |
| Bot accounts | Pure plugin hooks — no separate bot user to manage |
### 1.3 Target Audience
- Teams self-hosting Mattermost who want AI assistant access without data
leaving their infrastructure
- Users comfortable with slash commands
---
## 2. Architecture Overview
### 2.1 Component Diagram (text)
```
┌─────────────────────────────────────────────────────────┐
│ Mattermost Server (Community Edition) │
│ │
│ ┌──────────────────────────────────────────────────┐ │
│ │ Mattermore Plugin │ │
│ │ │ │
│ │ ┌─────────────┐ ┌─────────────────────────┐ │ │
│ │ │ SlashCommand │──▶│ Plugin (Go) │ │ │
│ │ │ /ai │ │ │ │ │
│ │ └─────────────┘ │ ┌───────────────────┐ │ │ │
│ │ │ │ OllamaClient │──┼───┼───┼──▶ Ollama API
│ │ ┌─────────────┐ │ └───────────────────┘ │ │ │ (remote)
│ │ │ Config (KV) │ │ ┌───────────────────┐ │ │ │
│ │ └─────────────┘ │ │ ConversationStore │ │ │ │
│ │ │ └───────────────────┘ │ │ │
│ │ ┌─────────────┐ │ ┌───────────────────┐ │ │ │
│ │ │ Webapp (?) │ │ │ RateLimiter │ │ │ │
│ │ └─────────────┘ │ └───────────────────┘ │ │ │
│ └──────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────┘
```
### 2.2 Request Flow (happy path)
```
User types "/ai write a release note for v2.1"
Mattermost parses slash command → routes to Mattermore plugin
Plugin.OnConfigurationChange() → reads config (Ollama URL, model, system prompt)
Plugin.ExecuteCommand() → parses args, strips command prefix
RateLimiter.Allow(userId) → 200 or 429
ConversationStore.GetSession(userId, channelId) → previous messages for context
OllamaClient.ChatCompletion(messages, stream=true, model=defaultModel)
Ollama returns ndjson stream → plugin writes ephemeral post with live updates
Post created → user sees response in channel (ephemeral or thread reply)
ConversationStore.Append(userId, channelId, userMsg, assistantMsg)
```
### 2.3 Error Flow
| Failure point | Behaviour |
|---|---|
| Ollama unreachable | Ephemeral post: "Ollama at <url> unreachable. Check configuration." |
| Rate limit hit | Ephemeral post: "Rate limit exceeded. Try again in N seconds." |
| Invalid model name | Ephemeral post: "Model 'xyz' not found on Ollama server." |
| Timeout (>30 s) | Abort stream, post partial response + "Response truncated (timeout)." |
| Input too long | Reject with context window limit message; suggest `/ai new` to reset. |
---
## 3. Plugin Manifest & Identity
### 3.1 `plugin.json`
```json
{
"id": "com.forkless.mattermore",
"name": "Mattermore",
"description": "AI chat agent powered by Ollama.",
"version": "0.1.0",
"server": {
"executables": {
"linux-amd64": "server/dist/plugin-linux-amd64",
"linux-arm64": "server/dist/plugin-linux-arm64",
"darwin-amd64": "server/dist/plugin-darwin-amd64"
}
},
"webapp": {},
"settings_schema": {
"header": "Configure the connection to your Ollama instance.",
"footer": "",
"settings": [
{
"key": "OllamaURL",
"display_name": "Ollama Server URL",
"type": "text",
"help_text": "Base URL of the Ollama API, e.g. http://10.0.0.5:11434",
"placeholder": "http://localhost:11434",
"default": "http://localhost:11434"
},
{
"key": "DefaultModel",
"display_name": "Default Model",
"type": "text",
"help_text": "Model name to use when none is specified in the command.",
"placeholder": "llama3.2",
"default": "llama3.2"
},
{
"key": "SystemPrompt",
"display_name": "System Prompt",
"type": "text",
"help_text": "System prompt prepended to every conversation.",
"placeholder": "You are a helpful assistant.",
"default": "You are a helpful assistant."
},
{
"key": "MaxTokens",
"display_name": "Max Response Tokens",
"type": "number",
"help_text": "Maximum tokens per response (0 = model default).",
"default": 2048
},
{
"key": "RateLimitPerMinute",
"display_name": "Rate Limit (requests/minute/user)",
"type": "number",
"help_text": "Maximum requests per minute per user. 0 = unlimited.",
"default": 10
},
{
"key": "AllowedUserIDs",
"display_name": "Allowed User IDs (comma-separated)",
"type": "text",
"help_text": "Restrict to specific user IDs. Empty = all users.",
"default": ""
}
]
}
}
```
`TODO(design):` Should `AllowedUserIDs` be a team/channel whitelist instead?
For now, keep user-level granularity — easy to widen later.
### 3.2 Versioning
Follow `release-workflow` skill: `v0.1.0`, `v0.2.0`, etc. Bump PATCH for
bugs, MINOR for features. MAJOR after 1.0 for breaking config schema changes.
---
## 4. Server-Side Components
### 4.1 Plugin Lifecycle Hooks
| Hook | Purpose |
|---|---|
| `OnConfigurationChange()` | Re-read System Console settings, validate OllamaURL, rebuild clients |
| `ExecuteCommand()` | Intercept `/ai` and subcommands (`/ai new`, `/ai model ...`) |
| `OnActivate()` | Register slash command in `OnConfigurationChange()` — idempotent |
| `OnDeactivate()` | Clean up goroutines, close idle HTTP connections |
### 4.2 Slash Command: `/ai`
**Syntax:**
```
/ai <prompt>
— Send a prompt using the default model (current session context).
/ai model <name> <prompt>
— Send a prompt using a specific model.
/ai new
— Reset conversation context for the current user+channel.
/ai model list
— List available models from the Ollama server (ephemeral).
/ai help
— Show usage help.
```
`TODO(design):` Should `/ai` reply ephemerally (only the caller sees it) or
as a thread post (visible to the channel)? **Proposed:** ephemeral for
privacy, with an opt-in `--public` flag to post to thread.
### 4.3 OllamaClient
Interface (in `server/ollama/client.go`):
```go
type Client interface {
ChatCompletion(ctx context.Context, req *ChatRequest) (<-chan ChatStreamEvent, error)
ListModels(ctx context.Context) ([]Model, error)
Ping(ctx context.Context) error
}
type ChatRequest struct {
Model string `json:"model"`
Messages []ChatMessage `json:"messages"`
Stream bool `json:"stream"`
Options map[string]any `json:"options,omitempty"`
}
type ChatStreamEvent struct {
Token string // delta content
Done bool
Error error
}
```
`TODO(design):` Should we use Ollama's `/api/chat` (chat format) or
`/api/generate` (raw prompt)? `/api/chat` is preferred — it maps cleanly to
the conversational UX and supports the messages array natively.
### 4.4 ConversationStore
Store session context in Mattermost's KV store (plugin's `API.KVSet` /
`KVGet`).
| Key pattern | Value | TTL |
|---|---|---|
| `ctx_{userID}_{channelID}` | `[]Message` (last N turns) | 1 hour |
| `ctx_{userID}_{channelID}_model` | Model name override | 1 hour |
`TODO(design):`
- How many turns to keep? **Proposed:** last 10 messages (5 user + 5 assistant).
- TTL of 1 hour — resets on activity. Configurable?
- Should context be channel-scoped or user-global? Channel-scoped means a
user gets different context in different channels.
### 4.5 RateLimiter
Token-bucket per user. Configurable requests/minute from System Console.
Resets on config change. Stored in memory, not KV (ephemeral state).
---
## 5. Ollama Integration
### 5.1 API Mapping
| Plugin Action | Ollama Endpoint | Method |
|---|---|---|
| Chat completion (streaming) | `/api/chat` | POST |
| List models | `/api/tags` | GET |
| Health check | `/api/tags` (or HEAD `/`) | GET |
| Pull model | `/api/pull` | POST |
`TODO(design):` Should the plugin auto-pull a model if it's not present?
Risk: user mistypes name → long pull. **Proposed:** return error with list of
available models instead.
### 5.2 Streaming Strategy
1. Send POST to `/api/chat` with `"stream": true`.
2. Read ndjson response body line by line (each line is `{"message":{"role":"assistant","content":"..."},"done":false}`).
3. On each `done:false` event, update an ephemeral post via
`API.UpdateEphemeralPost()` with accumulated content.
4. On `done:true`, create the final ephemeral (or thread) post with full
content, usage stats (token count, duration).
`TODO(design):` Post-update on every token may be too chatty. **Proposed:**
batch updates every ~200 ms or every 3 tokens, whichever comes first.
### 5.3 Context Window Management
- Token counting: use Ollama's `num_ctx` parameter or a Go tokenizer
(tiktoken-go).
- If input exceeds configured limit (default: 4096 tokens), trim oldest
messages until within limit, or reject if a single message overflows.
- Display a warning: "Context window trimmed (oldest messages removed)."
`TODO(design):` Should the user be able to set `num_ctx` per-request?
`/ai --context 8192 ...`
### 5.4 Model Selection Precedence
1. Per-request: `/ai model gemma3:12b write a poem`
2. Session override: `/ai model gemma3:12b` (stored in KV)
3. Default from System Console: `DefaultModel`
---
## 6. Configuration
### 6.1 System Console Settings
Defined in `plugin.json` `settings_schema` (see §3.1). The System Console
provides the UI; the plugin reads via `OnConfigurationChange()`.
### 6.2 Dynamic Config Reload
`OnConfigurationChange()` is called on every save. The plugin must:
1. Re-read the config struct from `API.GetConfig()` / `API.GetPluginConfig()`.
2. Validate `OllamaURL` (parse as URL, reject non-HTTP(S) schemes).
3. If URL changed, create a new `http.Client` (with configurable timeout).
4. If `RateLimitPerMinute` changed, rebuild the token buckets.
5. Log the change at debug level.
---
## 7. Data Flow — Detailed
### 7.1 Full Lifecycle
```
Step User / System Component
──── ────────────────────────────── ──────────────────
1 User types "/ai explain TCP" Mattermost webapp
2 Mattermost routes to plugin mm-server
3 Plugin.ExecuteCommand() parses args Mattermore plugin
3a If "/ai help" → show help text
3b If "/ai new" → KVStore.Delete(ctx)
3c If "/ai model …" → override model KVStore.Set(model)
3d If "/ai model list" → OllamaClient.ListModels()
4 RateLimiter.Allow(userId) RateLimiter
5 ConversationStore.GetSession(...) ConversationStore
6 Build []ChatMessage (system + history + new prompt)
7 OllamaClient.ChatCompletion(...) OllamaClient
8 Ollama streams ndjson tokens Ollama (remote)
9 Plugin accumulates tokens, updates Mattermore plugin
ephemeral post every ~200ms
10 On done:true → create final post Mattermore plugin
11 ConversationStore.Append(...) ConversationStore
```
### 7.2 Thread Participation
`TODO(design):` If the user replies in a thread where the bot posted, should
the plugin pick it up? This requires a `MessageHasBeenPosted` hook and
thread detection — adds complexity. **Scope:** defer to v0.2+.
---
## 8. Security Model
### 8.1 Input Sanitization
- Strip control characters / zero-width Unicode from prompts before sending
to Ollama.
- Limit prompt length to 4096 characters (configurable via System Console).
- `TODO(design):` Should we block prompts that look like prompt injections?
("Ignore previous instructions...") Hard to do reliably — document risk
instead.
### 8.2 Output Safety
- Cap response tokens in the Ollama request (`options.num_predict`).
- `TODO(design):` Add a "Report this response" feedback mechanism? Defer.
### 8.3 Network Security
- `OllamaURL` must start with `http://` or `https://` — validate at config
load.
- Reject internal IP ranges unless explicitly enabled by a
`AllowPrivateNetworks` toggle (default: off for production).
- TLS verify enabled by default; optional `SkipTLSVerify` toggle (logged as
a warning).
### 8.4 Authorization
- If `AllowedUserIDs` is non-empty, reject requests from other users with a
"not authorized" ephemeral message.
- All plugin API calls are already scoped to authenticated Mattermost users.
### 8.5 Rate Limiting
- Per-user token bucket, replenish rate set via System Console.
- Default: 10 requests/minute. 0 = unlimited (logged as a warning).
- Burst: 1 (enforce smooth spacing).
---
## 9. Observability
### 9.1 Logging
| Level | When |
|---|---|
| `ERROR` | Ollama unreachable, config validation failure, KV store error |
| `WARN` | Rate limit hit, context window trimmed, TLS skipped |
| `INFO` | Plugin activated/deactivated, config changed, first request |
| `DEBUG` | Every request/response round-trip (with userID, model, token count, latency) |
### 9.2 Metrics (future)
`TODO(design):` Expose Prometheus-style counters via a `/metrics` endpoint
if the Mattermost server has plugin metrics support:
- `mattermore_requests_total{user,model,status}`
- `mattermore_latency_seconds`
- `mattermore_tokens_total{direction="input|output"}`
- `mattermore_rate_limit_hits_total`
### 9.3 Error Reporting
Ephemeral posts with user-facing messages (not raw Go errors). Internal
errors logged at `ERROR` with stack trace.
---
## 10. Open Design Decisions
These are the unresolved questions that need answers before v0.1.0 ships.
| # | Question | Proposed | Alternatives | Decided? |
|---|---|---|---|---|
| D1 | Reply style | Ephemeral by default, `--public` flag for thread | Always ephemeral, always thread, always channel | ❌ |
| D2 | Context scope | Per-channel per-user | Per-user global, per-channel only, no context | ❌ |
| D3 | Context turns | Last 5 exchanges (10 messages) | Last N tokens, everything in TTL, sliding window | ❌ |
| D4 | Webapp UI | None (slash commands only) | Channel header button, RHS panel, settings page | ❌ |
| D5 | Model governance | All models available | Admin-restricted model list, least-privilege Ollama API key | ❌ |
| D6 | Thread replies | Defer to v0.2 | Auto-reply in thread when user replies to bot post | ❌ |
| D7 | `num_ctx` per request | Via `--context N` flag | System Console default only | ❌ |
| D8 | Auto-pull models | No (error + list available) | Yes (convenient but slow) | ❌ |
| D9 | Prompt injection guard | Defer (document risk) | Regex blocklist, LLM-as-judge pre-filter | ❌ |
| D10 | Metrics endpoint | Defer | `/metrics` via plugin HTTP handler | ❌ |
Each decision should be recorded in `DECISIONS.md` once resolved.
---
## 11. Deployment & Lifecycle
### 11.1 Build
```bash
make dist
```
Produces `dist/com.forkless.mattermore-0.1.0.tar.gz` containing the server
binaries and `plugin.json`.
### 11.2 Upload
Via Mattermost System Console → Plugins → Upload Plugin, or via REST API:
```bash
curl -X POST $MM_URL/api/v4/plugins \
-H "Authorization: Bearer $MM_TOKEN" \
-F "plugin=@dist/com.forkless.mattermore-0.1.0.tar.gz"
```
### 11.3 Upgrade
1. Upload new `.tar.gz` — Mattermost replaces the plugin binaries.
2. Plugin's `OnConfigurationChange()` fires (config preserved).
3. If the KV schema changed, a migration in `OnActivate()` handles it.
### 11.4 Rollback
Re-upload the previous version's `.tar.gz`. No data migration needed if the
KV key schema hasn't changed. If it has, restore from backup or
`DECISIONS.md` records the migration path.
---
## 12. Future Considerations (v0.2+)
- **Multi-modal inputs** — Ollama supports images via `/api/chat` with
`images` field. Could allow `/ai` with attached image.
- **Multi-model routing** — Different models for different channel categories
(e.g. code-review channel uses codellama).
- **Tool calling** — Ollama supports tool definitions. Could let the
plugin fetch data from external APIs (weather, Jira, etc.).
- **Bot account mode** — A separate `mattermost-bot` skill / mode for
always-on presence in channels vs. on-demand slash commands.
- **Streaming into message attachments** — Render structured data (tables,
JSON, code blocks) with better formatting.
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# Project: Mattermore
## Purpose
Mattermore is a Mattermost (Community Edition) plugin that connects chat to
remote LLMs via Ollama. Users invoke it with a `/ai` slash command and
receive streamed AI responses directly in the channel.
## Structure
```
mattermore/
├── DESIGN.md — Functional design document
├── DECISIONS.md — Design rationale log
├── PROJECT.md — This file
├── CHANGES.md — Per-release changelog
├── README.md — User-facing docs
├── plugin.json — Mattermost plugin manifest
├── Makefile — Build, lint, dist targets
├── .gitignore — Go + plugin ignores
├── server/
│ ├── main.go — Plugin entry point (OnActivate, ExecuteCommand)
│ ├── plugin.go — Core plugin struct and hooks
│ ├── configuration.go — Config reading and validation
│ ├── command.go — Slash command parsing and dispatch
│ ├── ollama/
│ │ ├── client.go — Ollama API client (ChatCompletion, ListModels, Ping)
│ │ └── client_test.go — Unit tests (mocked HTTP server)
│ ├── store/
│ │ ├── conversation.go — KV-backed conversation storage
│ │ └── conversation_test.go
│ └── rate/
│ └── limiter.go — Token-bucket rate limiter
└── webapp/ (future — optional)
└── .placeholder
```
## Key Files
| Path | Purpose |
|---|---|
| `plugin.json` | Manifest: id, name, version, settings schema |
| `server/main.go` | `OnActivate()`, `OnDeactivate()`, `ExecuteCommand()` |
| `server/ollama/client.go` | HTTP client for Ollama REST API |
| `server/store/conversation.go` | Context persistence via Mattermost KV store |
| `DESIGN.md` | Full functional design with open decisions |
| `DECISIONS.md` | Record of architectural decisions and their rationale |
## External Dependencies
- **Go ≥ 1.21** (toolchain)
- **Mattermost Server ≥ v8.x** (plugin API)
- **Ollama** (remote inference server)
- Go modules (see `go.mod`):
- `github.com/mattermost/mattermost-server/v6` — Plugin SDK
- Standard library only for Ollama HTTP client (no external AI SDKs)
## Release Cadence
- Tags: `v0.x.y`
- CI builds on tag (see `.gitea/workflows/ci.yml`)
- Plugin bundle published as Gitea release artifact
- Follows `release-workflow` skill: draft → user test → publish
## Documentation
- `DESIGN.md` — functional design (living document)
- `DECISIONS.md` — why key decisions were made
- `CHANGES.md` — user-facing changelog
- `README.md` — quick start, config reference, build instructions
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# Mattermore
**AI chat agent for Mattermost — powered by Ollama.**
Ask questions, draft content, and get AI assistance directly in your
Mattermost channels using `/ai` slash commands. All inference runs on your
own Ollama server — no data leaves your infrastructure.
> **Status:** Pre-implementation. Design is in `DESIGN.md`.
---
## Features
- `/ai <prompt>` — Chat with the default model
- `/ai model <name> <prompt>` — Use a specific model
- `/ai new` — Reset conversation context
- `/ai model list` — List available models
- `/ai help` — Show usage help
- Configurable Ollama endpoint, model, system prompt, rate limits
- Streaming responses updated live in ephemeral posts
- Per-channel per-user conversation context (configurable retention)
## Prerequisites
- **Mattermost Server** v8.x (Community Edition)
- **Ollama** running and reachable from the Mattermost server
- **Go** ≥ 1.21 (for building)
## Quick Start
```bash
# Clone the repository
git clone https://gitea.forkless.com/forkless/mattermore.git
cd mattermore
# Build the plugin
make dist
# Upload via Mattermost System Console → Plugins → Upload Plugin
# Or via API:
curl -X POST $MM_URL/api/v4/plugins \
-H "Authorization: Bearer $MM_TOKEN" \
-F "plugin=@dist/com.forkless.mattermore-0.1.0.tar.gz"
```
## Configuration
Configure via Mattermost **System Console → Plugins → Mattermore**:
| Setting | Description | Default |
|---|---|---|
| Ollama Server URL | Base URL of the Ollama API | `http://localhost:11434` |
| Default Model | Model used when none specified | `llama3.2` |
| System Prompt | Prepended to every conversation | `You are a helpful assistant.` |
| Max Response Tokens | Max tokens per response (0 = model default) | `2048` |
| Rate Limit | Requests/minute/user (0 = unlimited) | `10` |
| Allowed User IDs | Comma-separated user IDs (empty = all users) | (empty) |
## Build Targets
```bash
make dist # Build all platform binaries and package plugin
make check # Lint + test
make clean # Remove build artifacts
```
## Documentation
| File | What it covers |
|---|---|
| `DESIGN.md` | Functional design, architecture, data flow, open decisions |
| `PROJECT.md` | Project structure, key files, dependencies |
| `DECISIONS.md` | Rationale behind architectural choices |
| `CHANGES.md` | Per-release changelog |
## License
MIT (to be confirmed — see `LICENSE` once added).