Search

Search your stored conversations using semantic similarity. Find relevant sessions by meaning, not just exact keywords.

Prerequisites

PostgreSQL with pgvector For storing both conversation sessions and vector embeddings. Use tapes local up to bootstrap locally.

Embedding Provider Ollama (embeddinggemma) or OpenAI for generating embeddings from conversations

Search Guide

Step 1: Bootstrap local Postgres + Ollama

Pull the Postgres image (with pg_duckdb + pgvector preinstalled) and the Ollama container in one command. tapes local up also pulls embeddinggemma automatically.

tapes local up

Already have your own Postgres and Ollama running? Skip this step and supply your own DSN below.

Step 2: Run tapes with embeddings enabled

Start the tapes proxy and API against the local Postgres:

tapes serve \
  --postgres "postgres://tapes:tapes@localhost:5432/tapes?sslmode=disable" \
  --embedding-provider ollama \
  --embedding-target "http://localhost:11434" \
  --embedding-model embeddinggemma

Embeddings are written to the same Postgres database via pgvector. Override with --vector-store-target only if you want embeddings in a different database.

Step 3: Use your LLM through the proxy

Embeddings are generated automatically when an embedding provider is configured:

curl -X POST http://localhost:8080/api/chat \
  -H "Content-Type: application/json" \
  -d '{"model": "qwen3", "messages": [{"role": "user", "content": "How do I configure logging?"}]}'

Step 4: Search your sessions

Query your conversation history using natural language:

tapes search "logging configuration" \
  --postgres "postgres://tapes:tapes@localhost:5432/tapes?sslmode=disable" \
  --embedding-provider ollama \
  --embedding-target http://localhost:11434 \
  --embedding-model embeddinggemma

Understanding Results

Search results include:

Score Similarity score (higher = more relevant)

Hash Unique identifier for the matched conversation turn

Session ancestry Full conversation thread from root to matched message

Preview Snippet of the matched content

Next Steps

Once you've found a relevant conversation, use the checkout command to resume from that point. See the History guide for details on managing session history and resuming conversations.