7.3 KiB
scriptorium
Scriptorium is a generic prompt-definition execution engine written in Go.
Given named input artifacts and a prompt definition, Scriptorium:
- Loads the prompt definition.
- Resolves input artifact references.
- Renders prompt messages from templates.
- Calls an OpenAI-compatible LLM endpoint.
- Validates output if configured.
- Optionally performs bounded structured-output repair.
- Returns a generated artifact plus run metadata.
Where Scriptorium Fits
Scriptorium is not an orchestrator.
In the D&D workflow:
- Narratio orchestrates the full pipeline.
- WhisperX transcribes audio.
- Seriatim merges transcripts.
- Audita polishes transcripts.
- Scriptorium generates final artifacts from prepared inputs.
D&D-specific behavior belongs in profiles, schemas, fixtures, and caller inputs, not in core Go logic.
Core Concepts
- Prompt definition: YAML config for templates, inputs, output format, and validation behavior.
- Execution profile: conceptual runtime config (endpoint/model/timeouts/auth source). In this transition, execution settings are supplied as run-time overrides.
- Named inputs: logical names (for example
transcript,glossary) mapped to artifact references. - Artifact refs: currently
fileandinlineare supported. - Template variables: key/value vars passed at run time and referenced as
{{.var_name}}. - Execution target: endpoint/model plus generation/runtime parameters (
temperature,max_tokens,top_p,timeout_seconds,reasoning_effort,api_key_env). - Output format:
text,markdown, orjson. - Validation mode:
none,basic,json,json_schema. - Repair attempts: bounded retries for structured modes (
json,json_schema) when output validation fails.
Build and Test
go build -o scriptorium ./cmd/scriptorium
go test ./...
CLI Usage
scriptorium run
Required flags:
--prompt-dir--profile-dir--prompt--input(repeatablename=path)
Common optional flags:
--profile(execution profile selector; falls back to promptdefault_profile)--var(repeatablename=value)--out--llm-base-url--model--api-key-env--temperature--max-tokens--schema-dir--timeout
Current transitional behavior: execution-profile loading is not implemented yet, so run-time execution settings must be supplied via overrides. In practice, provide at least endpoint and model (--llm-base-url and --model).
Example:
export SCRIPTORIUM_API_KEY="your-key"
go run ./cmd/scriptorium run \
--prompt-dir ./prompts \
--profile-dir ./profiles \
--prompt generic.markdown_summary \
--profile local-fast \
--input transcript=./examples/fixtures/transcript.md \
--input glossary=./examples/fixtures/glossary.yml \
--llm-base-url http://localhost:8000/v1 \
--model gpt-4o-mini \
--api-key-env SCRIPTORIUM_API_KEY \
--out ./out.md
Output behavior:
- Artifact content goes to stdout unless
--outis set. - Summaries and errors are written to stderr.
- Exit code
2means the run succeeded but validation status isfailed.
scriptorium serve
Starts HTTP API.
Required flags:
--prompt-dir--profile-dir
Common optional flags:
--addr(default:8080)--schema-dir(default.)--model--timeout(default10m)
HTTP API
Endpoint:
POST /v1/runs
No built-in authentication is provided by the server itself. Deploy behind a trusted boundary or gateway.
Request example:
{
"prompt_id": "generic.structured_events",
"prompt_version": "1.0.0",
"profile_id": "local-default",
"inputs": {
"transcript": {"type": "file", "uri": "./examples/fixtures/transcript.md"},
"glossary": {"type": "file", "uri": "./examples/fixtures/glossary.yml"}
},
"vars": {
"session_date": "2026-05-04"
},
"model": {
"endpoint": "http://localhost:8000/v1",
"model": "gpt-4o-mini",
"temperature": 0.0,
"max_tokens": 600,
"top_p": 1.0,
"timeout_seconds": 120,
"api_key_env": "SCRIPTORIUM_API_KEY"
}
}
Response shape:
{
"artifact": {
"name": "output",
"content_type": "application/json",
"body": "{...}",
"uri": "",
"size": 123,
"hash": "..."
},
"validation": {
"status": "passed",
"mode": "json_schema",
"errors": [],
"schema_path": "structured_events.schema.json",
"repair_attempts": 0,
"is_valid": true
},
"metadata": {
"run_id": "xxxxxxxx-xxxx-4xxx-8xxx-xxxxxxxxxxxx",
"prompt_id": "generic.structured_events",
"prompt_version": "1.0.0",
"prompt_hash": "...",
"rendered_prompt_hash": "...",
"selected_profile_id": "local-default",
"model_name": "gpt-4o-mini",
"endpoint": "http://localhost:8000/v1",
"model_params": {
"endpoint": "http://localhost:8000/v1",
"model": "gpt-4o-mini",
"temperature": 0,
"max_tokens": 600,
"top_p": 1,
"timeout_seconds": 120,
"api_key_env": "SCRIPTORIUM_API_KEY"
},
"input_hashes": {"transcript": "...", "glossary": "..."},
"usage": {"prompt_tokens": 10, "completion_tokens": 20, "total_tokens": 30},
"start_time": "...",
"end_time": "...",
"duration_ms": 1523,
"validation_mode": "json_schema",
"validation_status": "passed",
"repair_attempts_used": 0
},
"raw_model_output": "{...}"
}
Validation content failures return 200 with validation.status = "failed" and preserve raw_model_output.
Error response shape:
{
"error": {
"code": "artifact_read_failed",
"message": "failed to read input artifact"
}
}
Prompt Definition Authoring
Minimal Markdown prompt definition
id: generic.markdown_summary
version: "1.0.0"
default_profile: local-default
inputs:
- name: transcript
required: true
templates:
- role: system
content: "You are a concise assistant."
- role: user
content: |
Summarize:
{{input "transcript"}}
output_format: markdown
validation:
validation_mode: basic
Structured JSON prompt definition with schema validation
id: generic.structured_events
version: "1.0.0"
default_profile: local-default
inputs:
- name: transcript
required: true
templates:
- role: system
content: "Return only JSON."
- role: user
content: |
Extract events from:
{{input "transcript"}}
output_format: json
validation:
format: json
validation_mode: json_schema
schema_path: structured_events.schema.json
repair_attempts: 1
repair_attempts is strictly bounded and only applies to structured validation modes.
Validation Modes
none: skipped validation result.basic: fails for empty/whitespace output.json: output must parse as JSON.json_schema: output must parse as JSON and satisfy configured schema.
Validation content failures are returned in the structured result; raw model output is preserved.
Examples
- Prompt definitions:
prompts/ - Execution profiles:
profiles/ - Schemas:
schemas/ - Fixtures:
examples/fixtures/ - Local experimentation:
local-test/
Development Notes
- Core follows ports-and-adapters and remains domain-generic.
- Domain/usecase packages do not depend on HTTP/CLI wire DTOs.
- To add a new LLM adapter: implement
internal/llm.Client. - To add a new artifact reader: extend
internal/artifact.Readerrouting. - To add a new validation mode: extend
internal/validateand preserve run semantics.