语义记忆检索服务

# Using npm (recommended)
npm install -g aifbin-recall

# Using yarn
yarn global add aifbin-recall

# Using pnpm
pnpm add -g aifbin-recall

# Using Bun (Linux / macOS)
bun install -g aifbin-recall

git clone https://github.com/Terronex-dev/aifbin-recall.git
cd aifbin-recall
npm install
npm run build
npm link

aifbin-recall --version
# Output: 0.1.0

# Index a directory of .aif-bin files
aifbin-recall index ./memories --collection my-project

# Start the server
aifbin-recall serve

# Search via CLI
aifbin-recall search "what decisions did we make about the API?"

# Or query the HTTP API
curl "http://localhost:3847/search?q=API+decisions&collection=my-project"

aifbin-recall index ./memories \
  --collection my-project \
  --recursive \
  --db ~/.aifbin-recall/custom.db

aifbin-recall serve \
  --port 3847 \
  --host 0.0.0.0

aifbin-recall search "your query" \
  --collection my-project \
  --limit 10 \
  --model minilm

{
  "mcpServers": {
    "aifbin-recall": {
      "command": "aifbin-recall",
      "args": ["mcp"]
    }
  }
}

# GET request
curl "http://localhost:3847/search?q=your+query&collection=my-project&limit=10"

# POST request with options
curl -X POST http://localhost:3847/search \
  -H "Content-Type: application/json" \
  -d '{"query": "your query", "collection": "my-project", "limit": 10}'

{
  "results": [
    {
      "id": "chunk-uuid",
      "text": "The matched text content...",
      "score": 0.89,
      "vectorScore": 0.92,
      "keywordScore": 0.85,
      "sourceFile": "/path/to/file.aif-bin",
      "chunkIndex": 0,
      "metadata": {}
    }
  ]
}

server:
  port: 3847
  host: localhost

index:
  path: ~/.aifbin-recall/index.db
  
search:
  default_limit: 10
  hybrid_weight: 0.7  # 0 = keywords only, 1 = vectors only

embedding:
  model: minilm  # Options: minilm, mpnet, bge-small, bge-base, e5-small