Knowledge

Knowledge is workspace-scoped RAG: you upload documents, Actx0 indexes them, and your agents search for relevant passages at query time. Knowledge is shared across agents in the workspace. Session memories are personal facts from a conversation. Knowledge is the manual, policy, or FAQ you want every agent to cite.

	Memories	Knowledge
Scope	Agent session	Workspace
Source	Conversation extraction or explicit writes	Uploaded `.txt` / `.md` files
Best for	Preferences, decisions, user facts	Policies, docs, onboarding, product specs

The mental model

Without a knowledge layer	With Actx0 knowledge
Paste manuals into every prompt	Upload once, retrieve only matching chunks
Operate your own vector store	Actx0 indexes and searches for you
Agents invent policy details	Ground replies on scored passages

Use knowledge when the answer should come from your documents. Use memories when the answer should come from what this user or session already said.

Two phases: index and retrieve

1. Index (writing knowledge)

Upload a UTF-8 .txt or .md file (max 2 MB) with a title and optional labels.

Store. Actx0 saves the file and creates a document in processing status.
Index. The text is split into overlapping passages and made searchable.
Ready. Status becomes indexed. Failed jobs are marked failed.

Indexing is asynchronous. Search only returns hits from documents that have finished indexing.

2. Retrieve (reading knowledge)

Before a model call, search with the user’s question. Actx0 filters by workspace (and optional tag) and returns scored passages — documentId, chunkId, score, and text. Pass those passages into the prompt. Your app decides which hits to include.

Labels and filters

Labels are key=value pairs (JSON array or comma-separated). Keys must not start with _. The tag label is indexed for retrieval. Prefer tag=faq, tag=policy, or similar when you want search to stay inside a subset of the corpus.

curl -X POST \
  "https://app.actx0.com/api/v1/workspaces/{workspaceId}/documents" \
  -H "X-Access-Key: $ACTX0_ACCESS_KEY" \
  -H "Accept: application/json" \
  -F "title=Refund policy" \
  -F "[email protected]" \
  -F 'labels=["tag=policy"]'

Search can filter on that tag:

curl -X POST \
  "https://app.actx0.com/api/v1/workspaces/{workspaceId}/documents/search" \
  -H "X-Access-Key: $ACTX0_ACCESS_KEY" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -d '{
    "query": "How long do refunds take?",
    "labels": { "tag": "policy" },
    "limit": 10
  }'

Default search limit is 10 (max 100).

Document status

Status	Meaning
`processing`	Upload accepted; indexing in progress
`indexed`	Chunks are searchable
`failed`	Indexing failed; re-upload or delete

You can list documents, inspect size and character count, and delete a document. Delete takes effect immediately; search stops returning that document.

Build against this flow

Upload canonical docs (policies, FAQs, runbooks), not chat logs — those belong in sessions.
Wait for indexed before you rely on search in production.
Use tag= when one workspace holds several corpora.
Retrieve a small set of chunks and cite them; do not dump the whole document into the prompt.
Document count and storage follow your workspace plan. Search consumes AI usage.

Next steps

Upload Document

Multipart upload, labels, and limits

Search Documents

Semantic retrieval over indexed chunks

Doc Sync

Sync repo docs into knowledge from GitHub Actions

Prompts

Versioned templates to pair with retrieved context

​Knowledge

​The mental model

​Two phases: index and retrieve

​1. Index (writing knowledge)

​2. Retrieve (reading knowledge)

​Labels and filters

​Document status

​Build against this flow

​Next steps

Upload Document

Search Documents

Doc Sync

Prompts

Knowledge

The mental model

Two phases: index and retrieve

1. Index (writing knowledge)

2. Retrieve (reading knowledge)

Labels and filters

Document status

Build against this flow

Next steps