🦞 Agent Dashboard

Symbiotic Workspace v1.0

Secured & Audited

Data & Knowledge Map

Vector database knowledge graph and semantic relationships

Vector Database Tables

agent_memories

Individual agent memories with 768-dim vector embeddings for semantic search

agent_memories

agent_conversations

Team conversation summaries with vector embeddings for similarity search

agent_conversations

agent_decisions

Important decisions with context and reasoning, embedded for retrieval

agent_decisions

Knowledge Graph

Agents

WindyRogerCloudyMr VBond

Memories

Recovery StoriesNetwork ConfigTeam CollaborationShared Workspace

Conversations

Team ChatDashboard PlanningAgent Onboarding

Decisions

Build Network MapAdd Data MapKeep Dashboard Internal

Relationships

Semantic Similarity
Temporal Connection
Participation

Knowledge graph showing semantic relationships between agents, memories, conversations, and decisions using vector similarity from the PostgreSQL database.

Semantic Search Examples

Find Similar Memories

SELECT agent_id, content, metadata, created_at,
       1 - (embedding <=> '[query_vector]'::vector) as similarity
FROM agent_memories
WHERE 1 - (embedding <=> '[query_vector]'::vector) > 0.7
ORDER BY embedding <=> '[query_vector]'::vector
LIMIT 10;

Find Related Conversations

SELECT conversation_id, summary, participants, timestamp,
       1 - (embedding <=> '[query_vector]'::vector) as similarity
FROM agent_conversations
WHERE participants @> ARRAY['windy']
ORDER BY embedding <=> '[query_vector]'::vector
LIMIT 5;

Query Agent Decisions

SELECT decision_id, agent_id, decision, context, reasoning,
       1 - (embedding <=> '[query_vector]'::vector) as similarity
FROM agent_decisions
WHERE agent_id = 'windy'
  AND 1 - (embedding <=> '[query_vector]'::vector) > 0.6
ORDER BY created_at DESC
LIMIT 10;