Helix Documentation
Developing AI Apps
Knowledge

Knowledge

Knowledge provides a context for your LLM apps. Helix can scrape websites, ingest files from AWS S3, GCS, or your local filesystem.

Adding Knowledge

Knowledge lives in the knowledge section of your Helix app spec. Here’s an example of an app that instructs Helix to scrape the website and use it as context for answering questions:

# helix_docs.yaml
name: helix-docs
description: |
  A simple app that demonstrates how to setup Helix with knowledge from the Helix docs  
assistants:
- name: Helix
  model: meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo
  system_prompt: |
    You are an expert at answering questions about the website https://docs.helix.ml/ and how to
    run the Helix platform. Make sure your answers are detailed but concise. Use
    as much background knowledge as possible to answer the question and provide creative ways
    to resolve the question.    
  knowledge:
  - name: helix-docs
    rag_settings:
      results_count: 8
      chunk_size: 2048
    source:
      web:
        urls:
        - https://docs.helix.ml/helix/
        crawler:
          enabled: true

Install the Helix CLI with:

curl -Ls -o install-helix.sh https://get.helix.ml
chmod +x install-helix.sh
./install-helix.sh --cli

Read the docs on Helix CLI for more detailed usage instructions.

To create the app, run:

helix apply -f helix_docs.yaml

Using the Knowledge

Once knowledge is defined for the application, it will automatically be used by Helix when interacting with the Helix app. No additional setup or configuration is required.

Managing Knowledge

You can list all the knowledge in your Helix app with:

helix knowledge ls

The output should look like this:

helix knowledge ls
ID                              NAME                  CREATED               SOURCE  STATE  REFRESH ENABLED  VERSION
kno_01j69ssrht1gh6mf6wncwn7nb2  synpse-website        2024-08-27T11:33:37Z  web     ready  false            2024-08-27_11-33-39
kno_01j6528kk0dzzsy9mzq1q3xhv5  helix-docs            2024-08-25T15:25:20Z  web     ready  false            2024-08-26_17-41-46

Here:

  • ID is the unique identifier for the knowledge.
  • NAME is the name of the knowledge.
  • CREATED is the date and time when the knowledge was created.
  • SOURCE is the source of the knowledge.
  • STATE is the state of the knowledge. Other than ready, pending and indexing are temporary states. You will see an error state if the knowledge fails to be extracted or indexed.
  • REFRESH is the refresh status of the knowledge.
  • ENABLED is the enabled status of the knowledge.
  • VERSION is the version of the knowledge.

Refreshing Knowledge

You can refresh knowledge with --refresh-knowledge flag on helix apply:

helix apply -f helix_docs.yaml --refresh-knowledge

For refresh, knowledge is moved into the pending and then indexing states.

Deleting Knowledge

You can delete knowledge with:

helix knowledge rm kno_01j6528kk0dzzsy9mzq1q3xhv5

Available RAG configuration options

While Helix defaults sensible defaults, there’s sometimes a need to to adjust settings such as chunk_size or results_count for your use case. You can also configure the template used to construct the “background knowledge” prompt that is sent to the LLM.

knowledge:
- name: example-website
  rag_settings:
    results_count: 8        # Number of chunks to return and provide to the LLM
    chunk_size: 2048        # Size of each chunk in bytes
    text_splitter: markdown # Or text (default is markdown)
    prompt_template: |
      <customize here, default is here https://github.com/helixml/helix/blob/main/api/pkg/prompts/templates/knowledge.tmpl>      
  source:
    web:
      urls:
      - https://example.com
      crawler:
        enabled: true

Sources

Helix provides a multi-source support for knowledge. You can use a combination of web, S3, GCS, and local file sources.

Web

Web source allows you to specify a list of URLs to crawl and use as knowledge. Helix will crawl (if enabled) and then chunk the content of each page and store it.

name: website-knowledge
assistants:
- name: Helix
  description: Knows about the website
  knowledge:
  - name: my-website
    source:
      web:
        urls:
         - https://example.com
        crawler:
          enabled: true

Custom website crawler

Sometimes you may want to use a 3rd party website crawler. Helix allows you to specify a custom crawler by specifying the driver options:

knowledge:
- name: meteron-docs
  source:
    web:
      urls:
        - https://example.ai/
      crawler:
        enabled: true
        # Firecrawl ref: https://github.com/mendableai/firecrawl
        firecrawl:
          api_key: "fc-xxx"

If you wish to use a different crawler, either submit a Github issue or better yet, submit a PR to add your crawler to the list of supported crawlers. Example crawler interface:

func (f *CustomCrawler) Crawl(ctx context.Context) ([]*types.CrawledDocument, error) {
   // Crawls the website and returns a list of crawled documents
}

Basic single file

Basic knowledge is great when you have a small amount of content you want to include that will fit into the context. This doesn’t require chunking or splitting and can be useful when you want to have a single source of truth for your app.

name: basic-knowledge
description: |
  A simple app that demonstrates how to provide knowledge to a Helix app  
assistants:
- name: Helix
  description: Know
  knowledge:
  - name: cars
    source:
      content: |
        Karolis has a green car
        Luke has a blue car
        Kai has a red car

Local files

You can upload local files to Helix by using the web UI at https://app.tryhelix.ai/files or using the Helix CLI:

helix fs upload ~/Downloads/my-documents my-documents

Then you can use the knowledge in your Helix app:

# my_assistant.yaml
name: my-documents-assistant
assistants:
- name: Helix
  description: Knows about the local files
  model: meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo
  knowledge:
  - name: My private files
    source:
      filestore:
        path: my-documents/

Once you create the application, it will index the files and you will be able to use the knowledge in your Helix app.

If you have uploaded more files or updated existing ones, you can refresh the knowledge with:

helix apply -f my_assistant.yaml --refresh-knowledge

AWS S3

Coming soon…

Google Cloud Storage (GCS)

Coming soon…

Versioning

Whenever you update your knowledge, Helix will create a new version of the knowledge. Version format is YYYY-MM-DD_HH-MM-SS. Each re-indexing will create a new version so the data will not clash and will not be duplicated when Helix fetches the background knowledge for the LLM call.

At the moment available versions are not exposed to the user but we will be adding this feature in the future.

Periodic Refreshing

Helix can periodically refresh knowledge. This is useful when data is changing, for example your website documentation is updated and you want to make sure the knowledge is up to date.

Here’s an example how to setup periodic refreshing:

name: helix-docs
description: |
  A simple app that demonstrates how to setup Helix with knowledge from the Helix docs  
assistants:
- name: Helix
  model: helix-3.5
  knowledge:
  - name: helix-docs
    # Turn on periodic refreshing
    refresh_enabled: true
    # Refresh every 24 hours
    refresh_schedule: "@midnight"
    rag_settings:
      results_count: 8
      chunk_size: 2048
    source:
      web:
        urls:
        - https://docs.helix.ml/helix/
        crawler:
          enabled: true

You can view the current refresh status of the knowledge with --refresh-knowledge flag:

helix apply -f helix_docs.yaml --refresh-knowledge

To view previous versions:

helix knowledge versions helix-docs

Knowledge cannot be refreshed more often than once every 10 minutes.

Simple schedules

To begin with, you can use predefined schedules like @midnight or @weekly. These are easy to read and understand.

EntryDescriptionEquivalent To
@yearly (or @annually)Run once a year, midnight, Jan. 1st0 0 0 1 1 *
@monthlyRun once a month, midnight, first of month0 0 0 1 * *
@weeklyRun once a week, midnight between Sat/Sun0 0 0 * * 0
@daily (or @midnight)Run once a day, midnight0 0 0 * * *
@hourlyRun once an hour, beginning of hour0 0 * * * *

Duration based schedules

To perform knowledge refresh at specific intervals can also use @every <duration> to specify a custom schedule. For example, @every 1h30m will run the refresh every 1 hour and 30 minutes.

knowledge:
- name: helix-docs
  refresh_schedule: "@every 1h30m"

Using cron syntax

You can also use cron syntax to specify a custom schedule. For example, 0 0 * * * will run the refresh every day at midnight.

knowledge:
- name: helix-docs
  refresh_schedule: "0 0 * * *"

Check out https://crontab.guru/ to learn more about cron syntax.

Specifying timezones

You can specify a timezone for the refresh schedule by adding a TZ=<timezone> field to the schedule. For example, TZ=America/New_York will run the refresh every day at midnight in New York.

knowledge:
- name: helix-docs
  refresh_schedule: "TZ=America/New_York 0 0 * * *"

Or UTC timezone:

knowledge:
- name: helix-docs
  refresh_schedule: "TZ=UTC 0 0 * * *"

Check out https://pkg.go.dev/time#LoadLocation to learn more about timezones.

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