EchoVessel

EchoVessel is an open-source digital persona engine. You define or distill a persona from your own settings and source material, then run it as a long-lived companion that remembers, speaks, and grows with you — instead of resetting after every reply.

The core idea: a persona shouldn’t feel like a new tab every time you open it. It should feel continuous.

Why this exists

Most chat tools treat memory as a vector dump and identity as a system prompt. The result is responsive, but never present. EchoVessel asks a different question: what does it take for a digital persona to feel like the same person tomorrow as it was today? The answer turned out to be a system, not a feature — one where memory, voice, and behavior all serve the same continuity.

What it actually does

Five modules cooperating inside a single local daemon:

• memory — long-term persona memory, hierarchical (L1–L4)
• voice — text-to-speech, speech-to-text, voice cloning
• proactive — autonomous outreach with policy gates
• channels — pluggable transports (Web, Discord, more on the way)
• runtime — the daemon that ties everything together

Open the full architecture diagram →

Memory is the heart of it

Most “AI memory” is a search problem: find the most similar past chunk, paste it into the prompt. EchoVessel treats memory as a structure — four layers, each answering a different question about the persona’s relationship with you.

Layer	Question it answers	What it stores	Written when	Role at read time
L1 · core blocks	”Who am I right now?”	Short, stable text — persona, self, mood, user, relationship	Manually, on admin edits, or via import	Always injected into the prompt, unconditionally
L2 · recall messages	”What was literally said?”	Every user and persona message, verbatim, FTS5-indexed	On every turn, immediately	Ground-truth archive; expands context around L3 hits
L3 · events	”What happened in that conversation?”	One-line episodic facts, emotional impact, tags, embedding	When a session closes (extraction pass)	The primary target of vector retrieval
L4 · thoughts	”What do I believe about this person across many conversations?”	Longer-term observations distilled from many events	Reflection passes — after high-impact events or every 24h	Also vector-retrieved; keeps pointers back to source events

How a memory gets picked

When the persona is about to reply, every L3/L4 candidate gets ranked by a four-factor score:

score = 0.5 · recency + 3.0 · relevance + 2.0 · impact + 1.0 · relational_bonus

• recency — exponential decay with a 14-day half-life
• relevance — vector similarity to the current query, normalized to [0, 1]
• impact — |emotional_impact| / 10, so peak moments outweigh forgettable ones on ties
• relational_bonus — a flat +0.5 whenever a memory carries an identity-bearing, vulnerability, turning-point, commitment, or correction tag

A min_relevance floor (default 0.4) drops orthogonal matches before scoring, so a high-impact unrelated event cannot sneak in on the back of the impact weight. The shape of this formula owes a debt to the Stanford “Generative Agents” paper; the relational tag bonus is the part tailored to persona memory.

The hard problem isn’t storage. It’s deciding what to remember, how to represent it, and when it should wake up and influence the next reply.

Open the interactive memory diagram →

How a single message wakes the system up

Every message triggers a small choreography across layers: which memories surface, which get written, which get distilled into longer-term form. The companion runtime-flow page traces this turn-by-turn against a real conversation.

Open the runtime flow diagram →

Voice as identity

Voice isn’t a TTS afterthought. Each persona has its own voice (cloned or selected) that speaks across every channel — including native Discord voice messages, indistinguishable from the bubble a human friend would send.

Relationships without affection meters

EchoVessel doesn’t have a “likeability score.” A persona’s bond with you is visible in behavior — tone shifts, naming changes, deeper recall, more initiative — not a progress bar.

Local-first by default

Your persona lives on your machine. The data file sits in ~/.echovessel/memory.db. The embedder runs locally. The only network traffic is to the LLM endpoint you configure. No telemetry, no phone-home, no gradual creep into the cloud.

Ethics & open source

EchoVessel is for fictional characters, original characters, your own self-persona, consented digital counterparts, and creative or memorial reconstructions. It is not an impersonation tool for pretending to be a real person in external communication.

It stays open-source because digital presence and intimate computing tools should not belong only to closed commercial platforms.

Name

EchoVessel — carry an echo long enough for it to become presence.