Middleware

Pluggable middleware pipeline at three levels, from outermost to innermost:

Level	Wraps	Where	Use cases
App-level	The LLM call inside the agent loop	runtime.middleware	Mask secrets, inject RAG, filter content, modify prompts.
Module-level	Any module's execute call	tools.modules.<id>.middleware	Audit, retry, timeout, transform.
MCP-level	Raw MCP call_tool		Specialised MCP tool wrapping.

Pipeline pattern

All levels share the same protocol:

1. before hooks run in declaration order.
2. If any before returns a string, it short-circuits - no LLM / module call.
3. The actual call executes.
4. after hooks run in reverse order.

App-level middleware

runtime.middleware. Wraps every LLM call.

yaml

runtime:
  middleware:
    - mask_secrets:
        patterns: [password, api_key, token]
    - rag_inject:
        max_chunks: 5
        max_chars: 2000
        collection: my-docs
    - prompt_inject:
        system: "Always respond in French."
    - content_filter:
        block_patterns: ["DROP TABLE", "rm -rf /"]
    - response_filter:
        max_length: 5000
        mask_secrets: true

5 built-in app middlewares:

mask_secrets - SecretMaskMiddleware

Masks sensitive patterns (passwords, API keys, tokens) in user messages and LLM responses with [MASKED].

yaml

- mask_secrets:
    patterns: [password, api_key, secret_key]    # additional patterns
    replacement: "[MASKED]"                       # default
    mask_values: true                             # mask values, not just keys

Built-in patterns include: password, api_key, secret_key, token, bearer, sk-*, ghp_*, glpat-*.

prompt_inject - PromptInjectMiddleware

Dynamically inject content into the system prompt.

yaml

- prompt_inject:
    system: "Always respond in French."
    position: append              # append (default) | prepend

content_filter - ContentFilterMiddleware

Block messages containing dangerous patterns. Short-circuits the agent loop with a rejection message.

yaml

- content_filter:
    block_patterns: ["DROP TABLE", "rm -rf", "DELETE FROM"]
    rejection_message: "This request has been blocked for safety."

rag_inject - RagInjectMiddleware

Inject retrieval-augmented generation context before each LLM call. Retrieves relevant chunks from a knowledge base and appends / prepends them to the system prompt.

yaml

- rag_inject:
    max_chunks: 5
    max_chars: 2000
    position: append              # append | prepend
    collection: "my-docs"         # KB collection name

response_filter - ResponseFilterMiddleware

Filter or transform the LLM's response. Length cap + secret masking on output.

yaml

- response_filter:
    max_length: 5000              # truncate longer responses
    mask_secrets: true            # apply secret masking on output

Module-level middleware

tools.modules.<id>.middleware. Wraps the module's execute call.

yaml

tools:
  modules:
    filesystem:
      middleware:
        - audit:
            log_params: true
            log_result: false
        - retry:
            max_attempts: 3
            base_delay: 1.0
            backoff: exponential
        - timeout:
            seconds: 30.0

3 built-in module middlewares

audit - ModuleAuditMiddleware

Audit log per module call: module, action, duration, success / failure.

yaml

- audit:
    log_params: true              # log input parameters
    log_result: false             # log output result

retry - ModuleRetryMiddleware

Retry failed module calls with configurable backoff.

yaml

- retry:
    max_attempts: 3               # default 3
    base_delay: 1.0               # seconds
    backoff: exponential          # exponential | fixed

Exponential backoff doubles each attempt (1 s, 2 s, 4 s, ...), capped at 30 s.

timeout - ModuleTimeoutMiddleware

Per-call timeout.

yaml

- timeout:
    seconds: 30.0                 # default 30

MCP-level middleware

Wraps raw call_tool invocations on MCP servers. Used internally for caching, retries, and error normalisation.

Custom middleware

Load a custom class from a file or installed package.

From a local file

yaml

runtime:
  middleware:
    - custom:
        path: "./middlewares/my_middleware.ts"
        class: "MyAppMiddleware"
        config:
          key: value

The path is resolved relative to the app YAML location. The system also checks a middleware/ subdirectory if the file isn't found at the literal path.

From the built-in catalog

yaml

runtime:
  middleware:
    - mask_secrets:
        patterns: [password, api_key, token]

Writing a custom app middleware

Custom app middleware implements the middleware interface: a before method (called before the LLM call) and an after method (called after the LLM response). If before returns a string, the call is short-circuited.

Custom middleware is loaded from a local file or an installed package:

yaml

runtime:
  middleware:
    - custom:
        path: "./middlewares/my_middleware.ts"
        class: "MyAppMiddleware"
        config:
          key: value

Writing a custom module middleware

Custom module middleware wraps a module's execute call. Load it with the same custom: syntax used for app middleware:

Middleware resolution order

For each middleware name, resolution follows this order:

1. TOML registry - middleware packages registered via digitorn-middleware.toml.
2. Inline fallback - built-in classes hard-coded in

App-level fallback registry: mask_secrets, prompt_inject, content_filter, rag_inject, response_filter.

Module-level fallback registry: audit, retry, timeout.

Complete example

app.yaml

app:
  app_id: secure-assistant
  name: "Secure Assistant"

runtime:
  mode: conversation
  middleware:
    - mask_secrets:
        patterns: [database_password, stripe_key]
    - content_filter:
        block_patterns: ["DROP TABLE", "TRUNCATE", "rm -rf"]
    - rag_inject:
        max_chunks: 3
        collection: company-docs
    - prompt_inject:
        system: "You are a helpful assistant. Never reveal API keys."
    - response_filter:
        max_length: 10000
        mask_secrets: true

agents:
  - id: assistant
    role: assistant
    brain:
      provider: openai
      model: gpt-4o
      backend: openai_compat
      config: {api_key: "{{secret.OPENAI_API_KEY}}"}
    system_prompt: "You are a helpful assistant. Never reveal API keys."

tools:
  modules:
    filesystem:
      middleware:
        - audit: { log_params: true }
        - retry: { max_attempts: 2 }
    bash:
      middleware:
        - audit: { log_params: true }
        - timeout: { seconds: 60.0 }

Cross-references

• App-config block reference (runtime.middleware + tools.modules.<id>.middleware): App Configuration → runtime
• Hooks (different mechanism - fires on agent-loop events, not LLM calls): hooks.md
• Behaviour engine (per-tool runtime checks): Behavior Engine