Ramis
12dbf69431
Reframe README around the real bottleneck (human coordination, not engineering ability) with the "five-minute meeting" cost story; rewrite the demo script to match. Update gemini/livekit/mongodb/digitalocean specs to reflect shipped code (Gemini Live agent, TTS, embeddings, Lyria via Interactions API; current API routes; hermes_jobs collections). Add hermes.md. Rename graph.md -> cont_learning.md. Remove outdated/dead docs (agent-learning scaffolding, graph-discovery, handoffs, superpowers, idea/plan/demo-setup) and the bundled LiveKit starter under examples/. Rewire CLAUDE.md doc-first gate off the deleted PLAN.md. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LuV8W8oNYRsDWKoqK8Mkqc
119 lines
4.6 KiB
Markdown
119 lines
4.6 KiB
Markdown
# Gemini Integration Spec
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Status: active / matches code.
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PodMan uses Gemini for five jobs, all through the `@google/genai` SDK
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(`GoogleGenAI`) with a single `GEMINI_API_KEY` (`GOOGLE_API_KEY` /
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`GOOGLE_GENERATIVE_AI_API_KEY` also accepted):
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1. **Vision** — turn screen frames into structured work context.
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2. **Embeddings** — vector recall over past coordination events.
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3. **TTS voice** — spoken urgent escalations over LiveKit.
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4. **Live conversation** — a real-time voice agent teammates talk to.
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5. **GenMedia (Lyria)** — a per-pod background score.
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Collision detection and intervention text are **deterministic in code**, not
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Gemini calls. PodMan does not ask Gemini "is this a conflict?" — that is decided
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by `backend/src/collision/detector.ts` from fused vision + git truth. This is a
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deliberate reliability choice for the live demo.
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---
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## 1. Vision — screen understanding
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**Model:** `GEMINI_VISION_MODEL` (default `gemini-2.0-flash`)
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**Code:** `backend/src/vision/gemini.ts` → `analyzeFrame()`
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**Trigger:** the LiveKit agent samples a JPEG frame from each engineer's
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screen-share track (not an HTTP upload — frames arrive over LiveKit).
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**Input:** a single base64 JPEG, sampled at low media resolution.
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**Output:** structured JSON via `responseJsonSchema` (no markdown parsing):
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```ts
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{
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currentFile: string, // open file path, e.g. src/auth/session.ts
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currentSymbol: string, // function/class under the cursor
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activity: string, // editing | reading | debugging | terminal | PR review
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hasUnpushedChanges: boolean, // dirty git gutter / modified markers visible
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confidence: number // 0..1
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}
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```
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**Latency/cost levers (in code):**
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- `thinkingConfig: { thinkingBudget: 0 }` — minimal thinking for the ambient loop.
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- `mediaResolution: MEDIA_RESOLUTION_LOW` — smaller image tokens.
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- Missing `confidence` defaults to `0.5`.
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**Demo reliability:** large editor font, single window, visible file tab. This is
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the primary lever for clean reads.
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---
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## 2. Embeddings — semantic recall
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**Model:** `GEMINI_EMBEDDING_MODEL` (default `gemini-embedding-001`, 768 dims)
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**Code:** `backend/src/memory/vectors.ts`
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Each collision is embedded into a short memory text (`file`, `symbol`,
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`engineers`, `severity`, unpushed flag) and stored on the `collisions` document.
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On a new collision PodMan embeds the query and runs MongoDB Atlas `$vectorSearch`
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(index `collision_embedding`) to recall similar past events and their outcomes.
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**Provider order:** Voyage (`VOYAGE_API_KEY`, `voyage-4-lite`) is tried first when
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present; Gemini embeddings are the fallback. Without either, recall degrades to
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exact signature/file matching — the demo still works.
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---
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## 3. TTS voice — urgent escalation over LiveKit
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**Model:** `GEMINI_LIVE_MODEL` (default `gemini-3.1-flash-tts-preview`)
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**Default voice:** `GEMINI_TTS_VOICE` (default `Charon`)
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**Code:** `backend/src/voice/live.ts` → `speak()` / `speakInRoom()`
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Flow: a short, natural voice line is generated for a critical collision, returned
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as audio, and published as a LiveKit microphone-source audio track. The track is
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held for the audio duration plus tail/hold so browsers do not cut playout short.
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Browser audio must be unlocked by a user gesture first. The frontend always
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renders the `VOICE_CUE` text as a fallback. See `docs/livekit.md` for delivery.
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---
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## 4. Live conversation — real-time voice agent
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**Model:** `GEMINI_CONVERSATION_MODEL` (default `gemini-3.1-flash-live-preview`)
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**Code:** `agents/podman-live-conversation/agent.py` (Python LiveKit Agents,
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`google.realtime.RealtimeModel`)
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A teammate can start a live, streaming speech-to-speech session with PodMan. The
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agent answers using **function tools** rather than guessing, including:
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- `get_active_pod_context`, `get_recent_changes`, `search_team_memory`
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- `search_repo`, `repo_recent_commits`, `repo_find_commits` (repo + git history)
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- `record_conversation_note`
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- `delegate_to_hermes`, `abort_active_hermes_job` (hands work to the async Hermes
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job runner — see `docs/hermes.md`)
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Started/stopped via `POST /api/pods/:id/live-conversation/start` and `.../stop`.
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---
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## 5. GenMedia — Lyria background score
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**Model:** `lyria-3-clip-preview` (override with `GEMINI_MUSIC_MODEL`)
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**Endpoint:** Gemini **Interactions API** (`/v1beta/interactions`)
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**Code:** `backend/src/voice/music.ts`
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A pod-specific ~30s clip is generated through the Interactions API, cached in
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MongoDB, and served via `GET /api/pods/:id/music` to play as ambient room audio.
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---
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## Cooldown
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Per-pod cooldown (`NUDGE_COOLDOWN_MS`, default 180000 ms / 3 min) gates repeated
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interventions. Implemented in `backend/src/memory/policy.ts`, not in Gemini.
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