Quick Start

Get up and running with Hindsight in 60 seconds.

Clients

Python

TypeScript

Go

CLI

HTTP

Start the API Server

pip (API only)

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

Docker (Full Experience)

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

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

Python

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")

Node.js

npm install @vectorize-io/hindsight-client

import { HindsightClient } from '@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');

CLI

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"

Go

go get github.com/vectorize-io/hindsight/hindsight-clients/go

cfg := hindsight.NewConfiguration()
cfg.Servers = hindsight.ServerConfigurations{
	{URL: "http://localhost:8888"},
}
client := hindsight.NewAPIClient(cfg)
ctx := context.Background()

// Retain a memory
retainReq := hindsight.RetainRequest{
	Items: []hindsight.MemoryItem{
		{Content: "Alice works at Google"},
	},
}
client.MemoryAPI.RetainMemories(ctx, "my-bank").RetainRequest(retainReq).Execute()

// Recall memories
recallReq := hindsight.RecallRequest{
	Query: "What does Alice do?",
}
resp, _, _ := client.MemoryAPI.RecallMemories(ctx, "my-bank").RecallRequest(recallReq).Execute()
for _, r := range resp.Results {
	fmt.Println(r.Text)
}

// Reflect - generate response
reflectReq := hindsight.ReflectRequest{
	Query: "Tell me about Alice",
}
answer, _, _ := client.MemoryAPI.Reflect(ctx, "my-bank").ReflectRequest(reflectReq).Execute()
fmt.Println(answer.GetText())

---

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

---

Integrations

Browse all supported integrations in the Integrations Hub.

Next Steps

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