fleet-memory/hindsight-docs/docs/developer/api/quickstart.md

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Quick Start

Get up and running with Hindsight in 60 seconds.

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Start the API Server

pip install hindsight-api
export OPENAI_API_KEY=sk-xxx
export HINDSIGHT_API_LLM_API_KEY=$OPENAI_API_KEY

hindsight-api

API available at http://localhost:8888

export OPENAI_API_KEY=sk-xxx

docker run --rm -it --pull always -p 8888:8888 -p 9999:9999 \
  -e HINDSIGHT_API_LLM_API_KEY=$OPENAI_API_KEY \
  -v $HOME/.hindsight-docker:/home/hindsight/.pg0 \
  ghcr.io/vectorize-io/hindsight:latest

• API: http://localhost:8888
• Control Plane (Web UI): http://localhost:9999

:::tip LLM Provider Hindsight requires an LLM with structured output support. Recommended: Groq with gpt-oss-20b for fast, cost-effective inference. See LLM Providers for more details. :::

---

Use the Client

pip install hindsight-client

from hindsight_client import Hindsight

client = Hindsight(base_url="http://localhost:8888")

# Retain: Store information
client.retain(bank_id="my-bank", content="Alice works at Google as a software engineer")

# Recall: Search memories
client.recall(bank_id="my-bank", query="What does Alice do?")

# Reflect: Generate disposition-aware response
client.reflect(bank_id="my-bank", query="Tell me about Alice")

npm install @vectorize-io/hindsight-client

const { HindsightClient } = require('@vectorize-io/hindsight-client');

const client = new HindsightClient({ baseUrl: 'http://localhost:8888' });

// Retain: Store information
await client.retain('my-bank', 'Alice works at Google as a software engineer');

// Recall: Search memories
await client.recall('my-bank', 'What does Alice do?');

// Reflect: Generate response
await client.reflect('my-bank', 'Tell me about Alice');

curl -fsSL https://hindsight.vectorize.io/get-cli | bash

# Retain: Store information
hindsight memory retain my-bank "Alice works at Google as a software engineer"

# Recall: Search memories
hindsight memory recall my-bank "What does Alice do?"

# Reflect: Generate response
hindsight memory reflect my-bank "Tell me about Alice"

---

What's Happening

Operation	What it does
Retain	Content is processed, facts are extracted, entities are identified and linked in a knowledge graph
Recall	Four search strategies (semantic, keyword, graph, temporal) run in parallel to find relevant memories
Reflect	Retrieved memories are used to generate a disposition-aware response

---

Next Steps

• Retain — Advanced options for storing memories
• Recall — Search and retrieval strategies
• Reflect — Disposition-aware reasoning
• Memory Banks — Configure disposition and background
• Server Deployment — Docker Compose, Helm, and production setup