CLI Reference

Run an AI app

Commands:
  subql-ai            Run an AI app                                        [default]
  subql-ai info       Get information on a project
  subql-ai embed-mdx  Creates a Lance db table with embeddings from MDX files
  subql-ai repl       Creates a CLI chat with a running app
  subql-ai publish    Publishes a project to IPFS so it can be easily distributed
  subql-ai init       Create a new project skeleton

Options:
      --version          Show version number                           [boolean]
      --help             Show help                                     [boolean]
  -p, --project          A path to a project file            [string] [required]
      --ipfsEndpoint     An endpoint to an IPFS gateway
          [string] [default: "https://unauthipfs.subquery.network/ipfs/api/v0/"]
      --ipfsAccessToken  A bearer authentication token to be used with the ipfs
                         endpoint                                       [string]
  -h, --host             The ollama RPC host
                                    [string] [default: "http://localhost:11434"]
  -i, --interface        The interface to interact with the app
                             [string] [choices: "cli", "http"] [default: "http"]
      --port             The port the http service runs on
                                                        [number] [default: 7827]
      --forceReload      If the project is from IPFS force reload it and don't
                         use the cached version       [boolean] [default: false]
      --toolTimeout      Set a limit for how long a tool can take to run, unit
                         is MS                         [number] [default: 10000]

subql-ai

Run an AI app.

subql-ai -p ./path/to/project.ts

info

Get information on a project.

subql-ai info -p ./path/to/project.ts

Example output

Project Information:
    Model:
      llama3.1
    Conifg:
      GRAPHQL_ENDPOINT: https://gateway.subquery.network/query/QmcoJLxSeBnGwtmtNmWFCRusXVTGjYWCK1LoujthZ2NyGP
        "type": "object",
        "properties": {
          "GRAPHQL_ENDPOINT": {
            "default": "https://gateway.subquery.network/query/QmcoJLxSeBnGwtmtNmWFCRusXVTGjYWCK1LoujthZ2NyGP",
            "type": "string"
          },
          "BASE_RPC": {
            "default": "https://gateway.subquery.network/rpc/base-full",
            "type": "string"
          },
          "BASE_SQT_ADDR": {
            "default": "0x858c50C3AF1913b0E849aFDB74617388a1a5340d",
            "type": "string"
          }
        },
        "required": [
          "GRAPHQL_ENDPOINT",
          "BASE_RPC",
          "BASE_SQT_ADDR"
        ]
      }
    Tools:
      TotalDelegation
      DelegatedIndexers
      UnclaimedDelegatorRewards
      CurrentDelegatorApy
      BetterIndexerApy
      TokenBalance
      SubqueryDocs
    System Prompt:

      You are an agent designed to help a user with their token delegation on the SubQuery Network.
      Given an input question, use the available tools to answer the users question quickly and concisely.
      You answer must use the result of the tools available.
      Do not mention that you used a tool or the name of a tool.
      If you need more information to answer the question, ask the user for more details.
      All token amounts are in SQT.

      If the question seems to be unrelated to the API, just return "I don't know" as the answer.

    Endpoints:
      gateway.subquery.network
    Vector Storage:
      Type: lancedb
      Path: ipfs://QmbELwJY7akcah3Ds5taT3KSN3aPG8xUv5poJ8crdhXrhx

embed-mdx

Creates a Lance db table with embeddings from MDX files

subql-ai embed-mdx -i ./path/to/dir/with/markdown -o ./db --table your-table-name

repl

When you have a running app you can run this in another terminal as a CLI interface for chatting with the App.

Type /bye to exit

subql-ai repl

publish

Publish your project to IPFS, this is how you can distribute your project

subql-ai publish -p ./path/to/project.ts

Info

You can use the --silent flag to only output the IPFS url. This is useful with CI pipelines.

example output

✔ Loaded project manifest
✔ Loaded project
✔ Generated project bundle
✔ Published project code
✔ Published vector db
✔ Published project to IPFS
ipfs://QmSejMf351cHqNTEbmJDziVLJ26r3hyepq1e6wbnejvgqM