# ai-bot A plaintext Matrix bot user (`@ai:vojo.chat`, display name **Vojo AI**) that answers xAI Grok completions in its rooms: `@`-mentions in group rooms and every message in a 1:1. It runs as a **Synapse application service** — Synapse pushes event transactions to the bot's HTTP endpoint; the bot speaks the Matrix CS-API back over plain HTTP (no Olm/Megolm — Vojo rooms are unencrypted by default) and calls the xAI OpenAI-compatible Chat Completions API. Authentication is the appservice `as_token`/`hs_token` (from the registration) — non-expiring, so there is **no token rotation and no stored password**. It is a **separate server-side service**, deployed next to Synapse. It lives in this repo (alongside `apps/widget-*`) but ships nothing to the web client. > Branding: user-facing name is **Vojo AI** with a generic icon. "Grok" appears > only as the factual attribution ("powered by Grok, xAI") and as the real model > id — never as the product name or logo (xAI Brand Guidelines). Design source of truth: `docs/plans/grok_bot.md`. Privacy/152-ФЗ pre-launch gating lives there (§6) and is **not** closed by this code. ## Layout ``` apps/ai-bot/ ├── main.go # entrypoint, lifecycle, `check-config` subcommand ├── config.go # env parsing + validation + redacted summary ├── bot.go # event handling, classification, limiter wiring ├── appservice.go # HTTP transaction-push server (hs_token auth, txn idempotency) ├── matrix.go # CS-API client as the appservice user (as_token + ?user_id=) ├── registration.go # generate + read registration.yaml (tokens, mautrix idiom) ├── events.go # Matrix event types + decoders ├── mentions.go # m.mentions + pill/reply fallbacks (F29/F30) ├── context.go # provider-neutral message-window assembly (trigger + bot replies) ├── llm.go # provider-neutral types + LLMClient interface (no vendor names) ├── httpllm.go # shared OpenAI-compatible chat/completions transport + retry (F6) ├── provider_xai.go # thin xAI/Grok adapter over the shared transport ├── provider_gemini.go # Gemini adapter: OpenAI-compat client + native v1beta grounding ├── pricing.go # per-model price table (priceFor) + CostBreakdown ├── router.go # cascade router: Layer-0 heuristic + optional Layer-1 Gemini classifier ├── cascade.go # generate(): route dispatch with degrade-to-grok_direct ├── web.go # WebProvider: grok_web_search (Live Search) | gemini_grounding + cap guard ├── telemetry.go # request_log analytics row + async emit + retention trim ├── store.go # Postgres (vojo_ai): spend ledger (+reservation/components), dedup, request_log, grounding cap ├── messages.go # language-free emoji status reactions ├── markdown.go # markdown → org.matrix.custom.html for the reply's formatted_body ├── util.go # bounded dedup set + small hash ├── prompts/system_ru.txt ├── Dockerfile # CGO-free static build → distroless, EXPOSE 8009 └── .env.example ``` ## Configuration All via environment (see `.env.example`). Required: `HOMESERVER_URL`, `BOT_MXID`, `AS_TOKEN`, `HS_TOKEN`, `XAI_API_KEY`, `ALLOWED_SERVERS`, `AI_BOT_DATABASE_URL`. `AS_ADDR` (default `:8009`) is the transaction-push listen address — it must match the `url` port in the registration. The model is env-configurable (`XAI_MODEL`, default `grok-4.20-0309-non-reasoning`). `grok-4.3` is the newer unified model (same price, 1M context): one model with a `reasoning_effort` dial. If you switch `XAI_MODEL=grok-4.3`, set `GROK_REASONING_EFFORT=none` to keep the default voice fast/cheap — otherwise the API defaults to `low` and reasons on **every** reply. `GROK_REASONING_EFFORT` (accepted: `none|low|medium|high`, default empty = not sent) is applied to the normal Grok voice (grok_direct + web synthesis); leave it **empty** for `grok-4.20-non-reasoning`, which rejects the param. The reason_then_grok route always uses `high` regardless. ### Database The bot keeps its **operational state** — appservice transaction + event dedup, the daily spend ledger, and the encrypted-room warned set — in a dedicated Postgres database `vojo_ai` on the shared server, mirroring the per-service bridge databases (each bridge owns its own role + DB). It stores **no message content**: the room timeline is canonical in Synapse, and the bot's xAI context window is the in-memory buffer in `bot.go`. The schema is created/migrated on startup (a `schema_version` table + idempotent `CREATE TABLE IF NOT EXISTS`), so a fresh `vojo_ai` needs no manual DDL — just the role + database: ```sql -- once, as the Postgres superuser (e.g. `docker exec vojo-postgres-1 psql -U synapse -d postgres`): CREATE ROLE vojo_ai LOGIN PASSWORD '<32-char secret>'; -- least privilege; NOT a superuser CREATE DATABASE vojo_ai OWNER vojo_ai; ``` Point the bot at it with `AI_BOT_DATABASE_URL` (libpq/pgx DSN). Inside the docker network the host is the `postgres` service; `sslmode=disable` matches Synapse and the bridges on the internal network: ``` AI_BOT_DATABASE_URL=postgres://vojo_ai:@postgres:5432/vojo_ai?sslmode=disable ``` The hard USD ceiling is priced from the **API-returned token usage** times the per-model price table (`XAI_PRICE_*_PER_M`, `GEMINI_PRICE_*_PER_M`), so a price change only needs those constants updated — it can't silently blow the cap. The ceiling is enforced with an optimistic **reservation** (`reserved_usd`): a request's estimated max-cost is booked at admission and settled to the real cost afterward, so a burst of concurrent requests can't slip past `DAILY_USD_CEILING` (it would otherwise, since the USD only lands after each call). ### Operator accounting (Phase 1, on by default) - `REQUEST_BUDGET_SECONDS` (default 180) — overall per-request deadline shared by all model calls, so a slow/retried call (or a cascade) can't accrete minutes. - `GROK_PROMPT_CACHE` (default false) — Grok caches prompt prefixes automatically; this toggle only adds the `x-grok-conv-id` routing header (a per-room id) to raise the cache hit rate. There is no `prompt_cache` body param (verified on docs.x.ai). - `TELEMETRY_ENABLED` (default false) — write a `request_log` analytics row per engaged request (route, per-component $, latency, degrade/ceiling reasons). The write is async and isolated — its failure never drops a reply. `TELEMETRY_STORE_TEXT` (default false) additionally keeps the query text (for offline eval); `TELEMETRY_RETENTION_DAYS` (default 30) time-trims old rows. Turn telemetry on to MEASURE the base before enabling any cascade layer. ### Observability — logs & per-request trace The bot logs with the Go stdlib `log/slog` to **stderr**; `LOG_LEVEL` (`debug|info|warn|error`, default `info`) and `LOG_FORMAT` (`text|json`, default `text`) control it. Set `LOG_FORMAT=json` in prod so a collector (Fluent Bit / Vector / Filebeat) can tail the container's stdout and ship the lines to OpenSearch / Loki — the bot itself never talks to a log backend (12-factor: it just writes structured lines). - **Trace id (always on, no content).** Every handled event gets a fresh `trace_id` (a random 16-byte / 32-hex value — the W3C/OpenTelemetry trace-id shape, so the `trace_id` field maps straight onto an OTel trace id later; full distributed tracing would still need a span id + `traceparent` propagation). It is minted once at the **per-event handler** and stamped into the request `context`, then attached to **every** log line for that request — through the per-room goroutine and down to the HTTP call to the model — so you can grep one `trace_id` to get the whole trail. (The appservice transaction-push logs sit above the per-event handler and carry no `trace_id`; they correlate by their Synapse txn id instead, since one transaction fans out to many events.) The Matrix `event_id` is logged on the entry/skip lines too, and is the `request_log.ID`, so logs ↔ telemetry correlate. - **Routing / selection (DEBUG, no flag — metadata only).** At `LOG_LEVEL=debug` the router's verdict (`route decided`: route, source, confidence, needs_web) and the final outcome (`generation outcome`: route actually run, fallback, degrade reason, per-stage ms, $) are logged. No message content — safe to leave on while debugging routing. - **Model request/response bodies (gated per-user, DEBUG).** `LOG_BODIES_USERS` is a comma-separated **allowlist of sender mxids** whose full model request/response bodies are logged (`llm exchange`). Empty (default) = **nobody** — message content never enters the logs. It is a **double gate**: a sender must be on the allowlist AND `LOG_LEVEL=debug` must be set. Bodies are truncated to a fixed ~4 KB cap. Only the request/response **bodies** are logged — never the URL or any header — so the API key cannot leak on either transport. Use it to debug your own traffic, e.g. `LOG_BODIES_USERS=@heaven:vojo.chat`. **Note:** once on, these lines contain cleartext message content + the model's reply + the sender mxid (personal data) — so if you ship them to OpenSearch/Loki, apply retention and access control at that sink accordingly. `TELEMETRY_*` (below) is the separate **analytics** path (a `request_log` row per request); the logs above are the **debug** path. They share the `trace_id`/`event_id` correlation keys but are independent — telemetry can be off while debug logging is on, and vice versa. ### Cascade (Phase 2-4) — behind flags, **default OFF** (every layer off == today's bot) All optional; an unset env is exactly today's single grok_direct call. Any layer off or failing **degrades to grok_direct** (never silence). Do **not** enable in prod until the offline-eval gate (misroute < 2-3% AND measured saving > the second provider's cost; see `docs/plans/ai_backend_build_plan.md` §9). | Env | Default | Meaning | |---|---|---| | `ROUTER_ENABLED` | false | Layer-0 heuristic router (else everything → grok_direct) | | `ROUTER_CLASSIFIER_ENABLED` | false | Layer-1 Gemini classifier on uncertain cases (requires `ROUTER_ENABLED` + Gemini key) | | `TRIVIAL_OFFLOAD_ENABLED` | false | answer trivial messages with Gemini (requires Gemini key) | | `WEB_ENABLED` | false | web_then_grok route (Gemini/Grok fetches fresh facts, **Grok stays the voice**) | | `WEB_PROVIDER` | `grok_web_search` | `grok_web_search` (xAI Agent Tools `web_search` on the Responses API, $5/1k calls, no Gemini key) or `gemini_grounding` (**cheapest**: Gemini does the fetch via native v1beta `google_search`, Grok voices it — ~$0.0013/query, validated on `gemini-2.5-flash-lite`; the F-EXT-3 "Gemini-3 only" caveat is the OpenAI-compat endpoint, native v1beta works on 2.5). Requires `GEMINI_API_KEY`. | | `WEB_GROUNDING_DAILY_CAP` | 450 | durable per-day cap for `gemini_grounding` before degrading (keep < the 500/day free grounding RPD; guards the per-1k overage) | | `REASONING_ENABLED` | false | manual "think harder" route on `REASONING_TRIGGER` | | `REASONING_TRIGGER` | `подумай глубже` | trigger phrase | | `REASONING_MODEL` | `grok-4.3` | a **reasoning-capable** model (the default `grok-4.20-non-reasoning` rejects `reasoning_effort`) | | `REASONING_EFFORT` | `high` | the reasoning_effort the "think harder" route sends (`none|low|medium|high`) | | `GEMINI_API_KEY` / `_FILE` | — | required only when a Gemini-using layer is on (fail-fast at startup otherwise) | | `GEMINI_MODEL` | `gemini-2.5-flash-lite` | cheap model for trivial/classifier | | `GEMINI_BASE_URL` | `…/v1beta/openai` | OpenAI-compat endpoint (native grounding endpoint derived from it) | ## One-time setup (appservice registration) Like the mautrix bridges (e.g. telegram), the bot **generates its own registration** (random `as_token`/`hs_token`) and reads its tokens back from that same file — the single source of truth shared with Synapse, no hand-copying. 1. Generate it (writes `REGISTRATION_PATH`, default `/data/registration.yaml`): ```bash docker compose run --rm ai-bot generate-registration ``` 2. Bind-mount that same file into the Synapse container (e.g. as `/data/ai-registration.yaml`) and add it to `homeserver.yaml`: ```yaml app_service_config_files: - /data/ai-registration.yaml ``` 3. **Restart Synapse** (it caches AS configs at startup). Synapse auto-creates `@ai:vojo.chat` from `sender_localpart` — no `register_new_matrix_user`. The bot reads `REGISTRATION_PATH` for its tokens (no env `AS_TOKEN`/`HS_TOKEN` needed) and sets its own display name (`BOT_DISPLAY_NAME`, default "Vojo AI") on startup. The bot writes/reads `/data`, so that dir must be owned by the image's runtime uid (distroless nonroot = **65532**): `sudo chown -R 65532:65532 ~/vojo/ai-bot`. ## Run ```bash go run . check-config # local config smoke test (no homeserver contact) go run . # real run (needs env + a reachable homeserver) ``` ### Image & secrets model The image is **config-less** (a `.dockerignore` keeps `.env`, `state/` and VCS out of the build context; the Dockerfile copies only the binary + `prompts/`). Build locally and ship like the mautrix bridges (VS Code task **Deploy AI bot** = `docker build -t ai-bot:custom` → `docker save | ssh docker load`), then run on the server with config + secrets supplied at runtime. Config and secrets are **separated**: non-secret config in `ai-bot.env` (`env_file`); the appservice tokens live in the generated `registration.yaml` (read via `REGISTRATION_PATH`); the only remaining standalone secret is the xAI key (`XAI_API_KEY_FILE`). Compose stanza (add to `~/vojo/docker-compose.yml`; the **service key `ai-bot`** must match the registration `url` host `http://ai-bot:8009`): ```yaml ai-bot: image: ai-bot:custom container_name: vojo-ai-bot restart: unless-stopped depends_on: [synapse, postgres] # needs both up before it starts env_file: ./ai-bot/ai-bot.env # config incl. AI_BOT_DATABASE_URL (chmod 600 — embeds the DB password) environment: REGISTRATION_PATH: /data/registration.yaml # tokens (generated; shared with Synapse) STATE_DIR: /data/state # runtime dir (the operational store is now in Postgres) XAI_API_KEY_FILE: /data/secrets/xai_api_key # the one standalone secret volumes: - ./ai-bot:/data # owned by uid 65532 (see setup) ``` Also bind-mount the same registration into Synapse and restart it: ```yaml synapse: volumes: - ./ai-bot/registration.yaml:/data/ai-registration.yaml:ro ``` `HOMESERVER_URL` must use the Synapse **service name** (`http://synapse:8008`), not `localhost`. Synapse and the bot must share a docker network (same compose project does this) so Synapse can push to `http://ai-bot:8009`. ## Verification status Compile-level + unit-tested locally: - ✅ `go vet` clean, `gofmt` clean, static CGO-free build. - ✅ `go test` — appservice transaction handling (hs_token auth → 403 on bad token, txnId idempotency / no re-dispatch, legacy `?access_token=`, user query 200/404); mention detection (m.mentions, empty-`{}` F29, no-body-fallback F30, pill, reply-to-bot); DM classification (invited+joined==2, F3: 2 joined + 1 invited is **not** a 1:1); group-vs-DM context minimisation (groups never leak third-party content); USD pricing; **markdown → HTML rendering** (escaping, safe-URL allowlist, false-positive guards, oversize/adversarial fallbacks). - ✅ `check-config` reads env + loads the system prompt. The store-backed tests (appservice transaction handling + the dedup/limiter/warned store in `store_test.go`, including the concurrent per-user-cap guarantee and restart-durability) need a throwaway Postgres via `AI_BOT_TEST_DATABASE_URL`; they **skip** when it is unset, so `go test ./...` stays green without one. To run them: ```bash docker run -d --name pg -e POSTGRES_PASSWORD=p -p 5432:5432 postgres:16 # … create role+db vojo_ai, then: AI_BOT_TEST_DATABASE_URL=postgres://vojo_ai:…@localhost:5432/vojo_ai?sslmode=disable go test ./... ``` Deferred to a live homeserver + xAI key + a loaded registration (runtime ✔): - Synapse pushes transactions → bot replies (`authenticated as @ai:vojo.chat` in logs); - invite from `:vojo.chat` → join, foreign-server invite → leave (F11); - `@`-mention / 1:1 message → `m.notice` reply with reply (and thread, F27) relation, carrying a `formatted_body` (org.matrix.custom.html) when the answer has markdown; - encrypted room → exactly one notice, **not** repeated after restart (F5); - per-user cap → silent drop; global USD ceiling → one notice/room/day; - a retried transaction (lost 200) is processed at most once (txn dedup).