75 lines
2.8 KiB
Markdown
75 lines
2.8 KiB
Markdown
# Design Decisions
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This file records architectural choices and the alternatives considered.
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New entries are added when a design decision is resolved (not when options
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are brainstormed). Unresolved questions live in DESIGN.md §10.
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---
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## Why Mattermost Plugin vs Bot Account
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**Context:** AI assistants in Mattermost can be implemented as plugins
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(running inside the Mattermost server process) or as bot accounts
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(independent services using the REST API and WebSocket).
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**Alternatives considered:**
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1. **Plugin** — hooks into slash commands, message hooks, KV store, System
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Console config UI, and the plugin lifecycle. No separate process to
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manage. Deployment is a single `.tar.gz` upload.
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2. **Bot account** — separate service, more language freedom, but requires
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managing OAuth tokens, WebSocket reconnection, a separate process with
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its own lifecycle, and the bot account itself in Mattermost.
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**Outcome:** Plugin chosen for v0.1.0 because:
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- Single deployment artifact
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- Built-in config UI via System Console
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- No bot account to create and maintain
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- KV store for persistence without a database
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- Simpler for the target audience (self-hosted teams)
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**Trade-off:** Plugin runs inside the Mattermost process — bugs can affect
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server stability. Mitigated by standard isolation practices (panic recovery,
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goroutine lifecycle management).
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---
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## Why Ollama
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**Context:** Backend LLM provider for the plugin.
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**Alternatives considered:**
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1. **Ollama** — Single binary, simple REST API, streaming, model management,
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self-hosted (data never leaves the infrastructure). Community Edition
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friendly.
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2. **OpenAI / Anthropic API** — SaaS, API key required, data leaves the
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network, ongoing API costs. Not aligned with self-hosted Mattermost
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ethos.
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3. **Local inference (llama.cpp, etc.)** — More complex to set up and
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manage. Ollama wraps this with a clean API.
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**Outcome:** Ollama. It matches the self-hosted, no-data-leaves paradigm of
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Mattermost Community Edition and provides the simplest API surface for a
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plugin to consume.
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---
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## Why Per-Channel Per-User Context (Proposed)
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**Context:** When a user sends `/ai <prompt>`, should the plugin remember
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previous exchanges?
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**Alternatives considered:**
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1. **Per-user global** — Context follows the user across channels. Simple
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but confusing: context from a #general question leaks into #dev.
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2. **Per-channel per-user** — Each user gets separate context in each
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channel. Natural mapping: different channels are different topics.
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3. **No context** — Stateless. Simplest but every prompt is isolated;
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users can't have a conversation.
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**Outcome (proposed):** Per-channel per-user. Marked as D2 in DESIGN.md —
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not final until v0.1.0 implementation.
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---
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*This file follows the template from the `project-docs` skill.*
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