feat: bound agent facet label proposals
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@@ -0,0 +1,277 @@
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{
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"$defs": {
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"FacetLabelProposal": {
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"additionalProperties": false,
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"properties": {
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"definition": {
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"maxLength": 500,
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"minLength": 1,
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"title": "Definition",
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"type": "string"
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},
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"facet": {
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"enum": [
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"tags",
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"audience",
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"use_for",
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"domain"
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],
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"title": "Facet",
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"type": "string"
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},
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"schema_version": {
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"const": 1,
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"default": 1,
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"title": "Schema Version",
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"type": "integer"
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},
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"value": {
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"maxLength": 100,
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"minLength": 1,
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"title": "Value",
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"type": "string"
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}
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},
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"required": [
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"facet",
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"value",
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"definition"
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],
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"title": "FacetLabelProposal",
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"type": "object"
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},
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"Locator": {
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"additionalProperties": false,
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"properties": {
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"block_id": {
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"maxLength": 128,
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"minLength": 1,
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"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
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"title": "Block Id",
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"type": "string"
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},
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"end": {
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"exclusiveMinimum": 0,
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"title": "End",
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"type": "integer"
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},
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"kind": {
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"enum": [
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"text_span",
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"pdf_page_span",
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"transcript_timestamp_span"
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],
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"title": "Kind",
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"type": "string"
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},
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"page": {
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"anyOf": [
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{
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"minimum": 1,
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"type": "integer"
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},
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{
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"type": "null"
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}
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],
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"default": null,
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"title": "Page"
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},
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"schema_version": {
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"const": 1,
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"default": 1,
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"title": "Schema Version",
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"type": "integer"
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},
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"start": {
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"minimum": 0,
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"title": "Start",
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"type": "integer"
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},
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"time_end_ms": {
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"anyOf": [
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{
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"minimum": 0,
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"type": "integer"
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},
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{
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"type": "null"
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}
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],
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"default": null,
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"title": "Time End Ms"
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},
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"time_start_ms": {
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"anyOf": [
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{
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"minimum": 0,
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"type": "integer"
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},
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{
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"type": "null"
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}
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],
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"default": null,
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"title": "Time Start Ms"
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}
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},
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"required": [
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"kind",
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"block_id",
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"start",
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"end"
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],
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"title": "Locator",
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"type": "object"
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}
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},
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"additionalProperties": false,
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"properties": {
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"candidate_audience": {
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"default": [],
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"items": {
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"maxLength": 100,
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"minLength": 1,
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"type": "string"
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},
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"maxItems": 3,
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"title": "Candidate Audience",
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"type": "array"
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},
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"candidate_domain": {
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"default": [],
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"items": {
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"maxLength": 100,
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"minLength": 1,
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"type": "string"
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},
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"maxItems": 3,
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"title": "Candidate Domain",
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"type": "array"
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},
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"candidate_facet_labels": {
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"default": [],
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"items": {
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"$ref": "#/$defs/FacetLabelProposal"
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},
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"maxItems": 14,
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"title": "Candidate Facet Labels",
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"type": "array"
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},
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"candidate_tags": {
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"default": [],
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"items": {
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"maxLength": 100,
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"minLength": 1,
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"type": "string"
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},
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"maxItems": 5,
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"title": "Candidate Tags",
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"type": "array"
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},
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"candidate_use_for": {
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"default": [],
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"items": {
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"maxLength": 100,
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"minLength": 1,
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"type": "string"
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},
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"maxItems": 3,
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"title": "Candidate Use For",
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"type": "array"
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},
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"excerpt": {
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"maxLength": 4000,
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"minLength": 1,
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"title": "Excerpt",
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"type": "string"
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},
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"extraction_id": {
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"pattern": "^[a-f0-9]{64}$",
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"title": "Extraction Id",
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"type": "string"
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},
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"lens": {
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"enum": [
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"technical",
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"conceptual",
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"cultural-historical",
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"financial-market"
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],
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"title": "Lens",
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"type": "string"
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},
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"locator": {
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"$ref": "#/$defs/Locator"
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},
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"project_id": {
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"maxLength": 128,
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"minLength": 1,
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"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
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"title": "Project Id",
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"type": "string"
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},
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"relevance": {
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"default": "borderline",
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"enum": [
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"borderline",
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"low"
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],
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"title": "Relevance",
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"type": "string"
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},
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"relevance_rationale": {
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"maxLength": 2000,
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"minLength": 1,
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"title": "Relevance Rationale",
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"type": "string"
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},
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"review_id": {
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"maxLength": 128,
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"minLength": 1,
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"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
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"title": "Review Id",
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"type": "string"
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},
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"run_id": {
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"maxLength": 128,
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"minLength": 1,
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"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
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"title": "Run Id",
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"type": "string"
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},
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"schema_version": {
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"const": 1,
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"default": 1,
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"title": "Schema Version",
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"type": "integer"
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},
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"source_revision_id": {
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"maxLength": 128,
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"minLength": 1,
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"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
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"title": "Source Revision Id",
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"type": "string"
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},
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"summary": {
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"maxLength": 2000,
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"minLength": 1,
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"title": "Summary",
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"type": "string"
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}
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},
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"required": [
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"review_id",
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"project_id",
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"run_id",
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"source_revision_id",
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"extraction_id",
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"locator",
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"excerpt",
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"lens",
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"summary",
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"relevance_rationale"
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],
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"title": "IngestReviewCreate",
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"type": "object"
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}
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@@ -0,0 +1,66 @@
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{
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"additionalProperties": false,
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"properties": {
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"decision": {
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"enum": [
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"include",
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"exclude",
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"defer"
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],
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"title": "Decision",
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"type": "string"
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},
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"decision_id": {
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"maxLength": 128,
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"minLength": 1,
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"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
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"title": "Decision Id",
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"type": "string"
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},
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"guidance_rule": {
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"anyOf": [
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{
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"maxLength": 1000,
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"type": "string"
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},
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{
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"type": "null"
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}
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],
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"default": null,
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"title": "Guidance Rule"
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},
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"rationale": {
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"maxLength": 2000,
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"minLength": 1,
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"title": "Rationale",
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"type": "string"
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},
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"review_id": {
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"maxLength": 128,
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"minLength": 1,
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"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
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"title": "Review Id",
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"type": "string"
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},
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"save_as_guidance": {
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"default": false,
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"title": "Save As Guidance",
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"type": "boolean"
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},
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"schema_version": {
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"const": 1,
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||||
"default": 1,
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||||
"title": "Schema Version",
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"type": "integer"
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}
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},
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"required": [
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"decision_id",
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"review_id",
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"decision",
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"rationale"
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],
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"title": "IngestReviewDecision",
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"type": "object"
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}
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@@ -0,0 +1,479 @@
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{
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"$defs": {
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"JevFacetOptionScore": {
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"additionalProperties": false,
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"properties": {
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"label": {
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"maxLength": 100,
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"minLength": 1,
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"title": "Label",
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"type": "string"
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},
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"label_id": {
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"anyOf": [
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{
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||||
"maxLength": 128,
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||||
"minLength": 1,
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||||
"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
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"type": "string"
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},
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{
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"type": "null"
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||||
}
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],
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"default": null,
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"title": "Label Id"
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},
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"probability": {
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"maximum": 1,
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"minimum": 0,
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"title": "Probability",
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"type": "number"
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},
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"schema_version": {
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"const": 1,
|
||||
"default": 1,
|
||||
"title": "Schema Version",
|
||||
"type": "integer"
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||||
}
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},
|
||||
"required": [
|
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"label",
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"probability"
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],
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||||
"title": "JevFacetOptionScore",
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"type": "object"
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||||
},
|
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"JevFacetResolution": {
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"additionalProperties": false,
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"properties": {
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||||
"added_to_project": {
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||||
"default": false,
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"title": "Added To Project",
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"type": "boolean"
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||||
},
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"choice_confidence": {
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"maximum": 1,
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"minimum": 0,
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"title": "Choice Confidence",
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"type": "number"
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},
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"facet": {
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"enum": [
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"tags",
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"audience",
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"use_for",
|
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"domain"
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],
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"title": "Facet",
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"type": "string"
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},
|
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"fit_probability": {
|
||||
"maximum": 1,
|
||||
"minimum": 0,
|
||||
"title": "Fit Probability",
|
||||
"type": "number"
|
||||
},
|
||||
"new_probability": {
|
||||
"maximum": 1,
|
||||
"minimum": 0,
|
||||
"title": "New Probability",
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||||
"type": "number"
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||||
},
|
||||
"option_probabilities": {
|
||||
"default": [],
|
||||
"items": {
|
||||
"$ref": "#/$defs/JevFacetOptionScore"
|
||||
},
|
||||
"maxItems": 6,
|
||||
"title": "Option Probabilities",
|
||||
"type": "array"
|
||||
},
|
||||
"rank": {
|
||||
"maximum": 20,
|
||||
"minimum": 1,
|
||||
"title": "Rank",
|
||||
"type": "integer"
|
||||
},
|
||||
"schema_version": {
|
||||
"const": 1,
|
||||
"default": 1,
|
||||
"title": "Schema Version",
|
||||
"type": "integer"
|
||||
},
|
||||
"selected_label": {
|
||||
"anyOf": [
|
||||
{
|
||||
"maxLength": 100,
|
||||
"minLength": 1,
|
||||
"type": "string"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"default": null,
|
||||
"title": "Selected Label"
|
||||
},
|
||||
"selected_label_id": {
|
||||
"anyOf": [
|
||||
{
|
||||
"maxLength": 128,
|
||||
"minLength": 1,
|
||||
"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
|
||||
"type": "string"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"default": null,
|
||||
"title": "Selected Label Id"
|
||||
},
|
||||
"selected_new_label": {
|
||||
"default": false,
|
||||
"title": "Selected New Label",
|
||||
"type": "boolean"
|
||||
},
|
||||
"value": {
|
||||
"maxLength": 100,
|
||||
"minLength": 1,
|
||||
"title": "Value",
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"facet",
|
||||
"value",
|
||||
"fit_probability",
|
||||
"new_probability",
|
||||
"choice_confidence",
|
||||
"rank"
|
||||
],
|
||||
"title": "JevFacetResolution",
|
||||
"type": "object"
|
||||
},
|
||||
"JevFacetScore": {
|
||||
"additionalProperties": false,
|
||||
"properties": {
|
||||
"facet": {
|
||||
"enum": [
|
||||
"tags",
|
||||
"audience",
|
||||
"use_for",
|
||||
"domain"
|
||||
],
|
||||
"title": "Facet",
|
||||
"type": "string"
|
||||
},
|
||||
"probability": {
|
||||
"maximum": 1,
|
||||
"minimum": 0,
|
||||
"title": "Probability",
|
||||
"type": "number"
|
||||
},
|
||||
"schema_version": {
|
||||
"const": 1,
|
||||
"default": 1,
|
||||
"title": "Schema Version",
|
||||
"type": "integer"
|
||||
},
|
||||
"value": {
|
||||
"maxLength": 100,
|
||||
"minLength": 1,
|
||||
"title": "Value",
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"facet",
|
||||
"value",
|
||||
"probability"
|
||||
],
|
||||
"title": "JevFacetScore",
|
||||
"type": "object"
|
||||
},
|
||||
"Locator": {
|
||||
"additionalProperties": false,
|
||||
"properties": {
|
||||
"block_id": {
|
||||
"maxLength": 128,
|
||||
"minLength": 1,
|
||||
"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
|
||||
"title": "Block Id",
|
||||
"type": "string"
|
||||
},
|
||||
"end": {
|
||||
"exclusiveMinimum": 0,
|
||||
"title": "End",
|
||||
"type": "integer"
|
||||
},
|
||||
"kind": {
|
||||
"enum": [
|
||||
"text_span",
|
||||
"pdf_page_span",
|
||||
"transcript_timestamp_span"
|
||||
],
|
||||
"title": "Kind",
|
||||
"type": "string"
|
||||
},
|
||||
"page": {
|
||||
"anyOf": [
|
||||
{
|
||||
"minimum": 1,
|
||||
"type": "integer"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"default": null,
|
||||
"title": "Page"
|
||||
},
|
||||
"schema_version": {
|
||||
"const": 1,
|
||||
"default": 1,
|
||||
"title": "Schema Version",
|
||||
"type": "integer"
|
||||
},
|
||||
"start": {
|
||||
"minimum": 0,
|
||||
"title": "Start",
|
||||
"type": "integer"
|
||||
},
|
||||
"time_end_ms": {
|
||||
"anyOf": [
|
||||
{
|
||||
"minimum": 0,
|
||||
"type": "integer"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"default": null,
|
||||
"title": "Time End Ms"
|
||||
},
|
||||
"time_start_ms": {
|
||||
"anyOf": [
|
||||
{
|
||||
"minimum": 0,
|
||||
"type": "integer"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"default": null,
|
||||
"title": "Time Start Ms"
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"kind",
|
||||
"block_id",
|
||||
"start",
|
||||
"end"
|
||||
],
|
||||
"title": "Locator",
|
||||
"type": "object"
|
||||
}
|
||||
},
|
||||
"additionalProperties": false,
|
||||
"properties": {
|
||||
"created_at": {
|
||||
"format": "date-time",
|
||||
"title": "Created At",
|
||||
"type": "string"
|
||||
},
|
||||
"excerpt": {
|
||||
"maxLength": 4000,
|
||||
"minLength": 1,
|
||||
"title": "Excerpt",
|
||||
"type": "string"
|
||||
},
|
||||
"extraction_id": {
|
||||
"pattern": "^[a-f0-9]{64}$",
|
||||
"title": "Extraction Id",
|
||||
"type": "string"
|
||||
},
|
||||
"jev_facet_resolutions": {
|
||||
"default": [],
|
||||
"items": {
|
||||
"$ref": "#/$defs/JevFacetResolution"
|
||||
},
|
||||
"maxItems": 20,
|
||||
"title": "Jev Facet Resolutions",
|
||||
"type": "array"
|
||||
},
|
||||
"jev_facet_scores": {
|
||||
"default": [],
|
||||
"items": {
|
||||
"$ref": "#/$defs/JevFacetScore"
|
||||
},
|
||||
"maxItems": 20,
|
||||
"title": "Jev Facet Scores",
|
||||
"type": "array"
|
||||
},
|
||||
"jev_lens": {
|
||||
"anyOf": [
|
||||
{
|
||||
"enum": [
|
||||
"technical",
|
||||
"conceptual",
|
||||
"cultural-historical",
|
||||
"financial-market"
|
||||
],
|
||||
"type": "string"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"default": null,
|
||||
"title": "Jev Lens"
|
||||
},
|
||||
"jev_lens_confidence": {
|
||||
"anyOf": [
|
||||
{
|
||||
"maximum": 1,
|
||||
"minimum": 0,
|
||||
"type": "number"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"default": null,
|
||||
"title": "Jev Lens Confidence"
|
||||
},
|
||||
"jev_model": {
|
||||
"anyOf": [
|
||||
{
|
||||
"maxLength": 100,
|
||||
"type": "string"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"default": null,
|
||||
"title": "Jev Model"
|
||||
},
|
||||
"jev_relation_probability": {
|
||||
"anyOf": [
|
||||
{
|
||||
"maximum": 1,
|
||||
"minimum": 0,
|
||||
"type": "number"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"default": null,
|
||||
"title": "Jev Relation Probability"
|
||||
},
|
||||
"lens": {
|
||||
"enum": [
|
||||
"technical",
|
||||
"conceptual",
|
||||
"cultural-historical",
|
||||
"financial-market"
|
||||
],
|
||||
"title": "Lens",
|
||||
"type": "string"
|
||||
},
|
||||
"locator": {
|
||||
"$ref": "#/$defs/Locator"
|
||||
},
|
||||
"project_id": {
|
||||
"maxLength": 128,
|
||||
"minLength": 1,
|
||||
"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
|
||||
"title": "Project Id",
|
||||
"type": "string"
|
||||
},
|
||||
"relevance": {
|
||||
"default": "borderline",
|
||||
"enum": [
|
||||
"borderline",
|
||||
"low"
|
||||
],
|
||||
"title": "Relevance",
|
||||
"type": "string"
|
||||
},
|
||||
"relevance_rationale": {
|
||||
"maxLength": 2000,
|
||||
"minLength": 1,
|
||||
"title": "Relevance Rationale",
|
||||
"type": "string"
|
||||
},
|
||||
"review_id": {
|
||||
"maxLength": 128,
|
||||
"minLength": 1,
|
||||
"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
|
||||
"title": "Review Id",
|
||||
"type": "string"
|
||||
},
|
||||
"run_id": {
|
||||
"maxLength": 128,
|
||||
"minLength": 1,
|
||||
"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
|
||||
"title": "Run Id",
|
||||
"type": "string"
|
||||
},
|
||||
"schema_version": {
|
||||
"const": 1,
|
||||
"default": 1,
|
||||
"title": "Schema Version",
|
||||
"type": "integer"
|
||||
},
|
||||
"source_revision_id": {
|
||||
"maxLength": 128,
|
||||
"minLength": 1,
|
||||
"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
|
||||
"title": "Source Revision Id",
|
||||
"type": "string"
|
||||
},
|
||||
"status": {
|
||||
"default": "needs-user-review",
|
||||
"enum": [
|
||||
"needs-user-review",
|
||||
"included",
|
||||
"excluded",
|
||||
"deferred"
|
||||
],
|
||||
"title": "Status",
|
||||
"type": "string"
|
||||
},
|
||||
"submitted_by": {
|
||||
"maxLength": 128,
|
||||
"minLength": 1,
|
||||
"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
|
||||
"title": "Submitted By",
|
||||
"type": "string"
|
||||
},
|
||||
"summary": {
|
||||
"maxLength": 2000,
|
||||
"minLength": 1,
|
||||
"title": "Summary",
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"review_id",
|
||||
"project_id",
|
||||
"run_id",
|
||||
"source_revision_id",
|
||||
"extraction_id",
|
||||
"locator",
|
||||
"excerpt",
|
||||
"lens",
|
||||
"summary",
|
||||
"relevance_rationale",
|
||||
"submitted_by",
|
||||
"created_at"
|
||||
],
|
||||
"title": "IngestReviewItem",
|
||||
"type": "object"
|
||||
}
|
||||
@@ -1,5 +1,151 @@
|
||||
{
|
||||
"$defs": {
|
||||
"ProjectFacetLabel": {
|
||||
"additionalProperties": false,
|
||||
"properties": {
|
||||
"aliases": {
|
||||
"default": [],
|
||||
"items": {
|
||||
"maxLength": 100,
|
||||
"minLength": 1,
|
||||
"type": "string"
|
||||
},
|
||||
"maxItems": 20,
|
||||
"title": "Aliases",
|
||||
"type": "array"
|
||||
},
|
||||
"canonical_label": {
|
||||
"maxLength": 100,
|
||||
"minLength": 1,
|
||||
"title": "Canonical Label",
|
||||
"type": "string"
|
||||
},
|
||||
"created_at": {
|
||||
"format": "date-time",
|
||||
"title": "Created At",
|
||||
"type": "string"
|
||||
},
|
||||
"definition": {
|
||||
"maxLength": 500,
|
||||
"minLength": 1,
|
||||
"title": "Definition",
|
||||
"type": "string"
|
||||
},
|
||||
"facet": {
|
||||
"enum": [
|
||||
"tags",
|
||||
"audience",
|
||||
"use_for",
|
||||
"domain"
|
||||
],
|
||||
"title": "Facet",
|
||||
"type": "string"
|
||||
},
|
||||
"jev_fit_probability": {
|
||||
"anyOf": [
|
||||
{
|
||||
"maximum": 1,
|
||||
"minimum": 0,
|
||||
"type": "number"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"default": null,
|
||||
"title": "Jev Fit Probability"
|
||||
},
|
||||
"jev_model": {
|
||||
"anyOf": [
|
||||
{
|
||||
"maxLength": 100,
|
||||
"type": "string"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"default": null,
|
||||
"title": "Jev Model"
|
||||
},
|
||||
"jev_new_probability": {
|
||||
"anyOf": [
|
||||
{
|
||||
"maximum": 1,
|
||||
"minimum": 0,
|
||||
"type": "number"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"default": null,
|
||||
"title": "Jev New Probability"
|
||||
},
|
||||
"label_id": {
|
||||
"maxLength": 128,
|
||||
"minLength": 1,
|
||||
"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
|
||||
"title": "Label Id",
|
||||
"type": "string"
|
||||
},
|
||||
"merged_into": {
|
||||
"anyOf": [
|
||||
{
|
||||
"maxLength": 128,
|
||||
"minLength": 1,
|
||||
"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
|
||||
"type": "string"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"default": null,
|
||||
"title": "Merged Into"
|
||||
},
|
||||
"origin_review_id": {
|
||||
"anyOf": [
|
||||
{
|
||||
"maxLength": 128,
|
||||
"minLength": 1,
|
||||
"pattern": "^[a-zA-Z0-9][a-zA-Z0-9._:-]*$",
|
||||
"type": "string"
|
||||
},
|
||||
{
|
||||
"type": "null"
|
||||
}
|
||||
],
|
||||
"default": null,
|
||||
"title": "Origin Review Id"
|
||||
},
|
||||
"schema_version": {
|
||||
"const": 1,
|
||||
"default": 1,
|
||||
"title": "Schema Version",
|
||||
"type": "integer"
|
||||
},
|
||||
"status": {
|
||||
"default": "active",
|
||||
"enum": [
|
||||
"active",
|
||||
"merged",
|
||||
"retired"
|
||||
],
|
||||
"title": "Status",
|
||||
"type": "string"
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"label_id",
|
||||
"facet",
|
||||
"canonical_label",
|
||||
"definition",
|
||||
"created_at"
|
||||
],
|
||||
"title": "ProjectFacetLabel",
|
||||
"type": "object"
|
||||
},
|
||||
"ProjectStatus": {
|
||||
"enum": [
|
||||
"active",
|
||||
@@ -38,6 +184,15 @@
|
||||
"title": "Description",
|
||||
"type": "string"
|
||||
},
|
||||
"facet_labels": {
|
||||
"default": [],
|
||||
"items": {
|
||||
"$ref": "#/$defs/ProjectFacetLabel"
|
||||
},
|
||||
"maxItems": 2000,
|
||||
"title": "Facet Labels",
|
||||
"type": "array"
|
||||
},
|
||||
"key_questions": {
|
||||
"items": {
|
||||
"type": "string"
|
||||
|
||||
@@ -230,6 +230,18 @@
|
||||
"path": "schemas/ExtractionRecord.schema.json",
|
||||
"sha256": "5b7c6c8a46696736ef90fca1b1eac6d17dd9918ed12e9c212a776651b0c31937"
|
||||
},
|
||||
{
|
||||
"path": "schemas/IngestReviewCreate.schema.json",
|
||||
"sha256": "0db108b90265d2089ce8df3d2734865a13f7abb1dfba85058b9bbec5fcac426d"
|
||||
},
|
||||
{
|
||||
"path": "schemas/IngestReviewDecision.schema.json",
|
||||
"sha256": "5f62ad3fd8035130cb5e31141eeef1f83acc55727246bc7bf82b43fca6697a9f"
|
||||
},
|
||||
{
|
||||
"path": "schemas/IngestReviewItem.schema.json",
|
||||
"sha256": "5cf759227279a87552bc2f43d4545a68c00a8702afce87b2088bc6f276a85f27"
|
||||
},
|
||||
{
|
||||
"path": "schemas/KnowledgeNode.schema.json",
|
||||
"sha256": "62efb24c24967c2339c1ba605fa498ffa54459b027b6236421f30f2c4f9437ce"
|
||||
@@ -240,7 +252,7 @@
|
||||
},
|
||||
{
|
||||
"path": "schemas/ProjectRecord.schema.json",
|
||||
"sha256": "f69f0987b556f3aa9aa71d310a890cb4a46de790360356b31aae572659c6f1eb"
|
||||
"sha256": "bba7461c640c05734f668fd1568b6a80b2c9569e81c3efd289875aff46a168da"
|
||||
},
|
||||
{
|
||||
"path": "schemas/ProposalReceipt.schema.json",
|
||||
|
||||
+4
-4
@@ -10,7 +10,7 @@
|
||||
"contract_id": "gewu.service.v1",
|
||||
"contract_version": 1,
|
||||
"path": "contracts/service-v1.json",
|
||||
"sha256": "5e6eabc607788638c1e71bb8eb4a294d33cdd4c623e70d533e4e9f0c9b730bc1",
|
||||
"sha256": "a0120520aadb73fee08138b7b60a5ee05b82823e028ec1bc644ead6637920668",
|
||||
"scope": "Generated local MCP tool input schemas and v1 record schemas; native host workflows remain NOT RUN."
|
||||
}
|
||||
],
|
||||
@@ -190,7 +190,7 @@
|
||||
"compatible_checkpoint_contracts": [
|
||||
"gewu.local-checkpoint@0.1.0"
|
||||
],
|
||||
"sha256": "3985cc41a7405ce9076f57229d63380cb18fb57c1c6b615a7014e717d6172eb6",
|
||||
"sha256": "39d559dbc43b14cff6816a92bc95e337128b4eacea899d12cd71becbd441cc12",
|
||||
"hash_encoding": "utf8-no-bom-lf"
|
||||
},
|
||||
{
|
||||
@@ -435,7 +435,7 @@
|
||||
"compatible_checkpoint_contracts": [
|
||||
"gewu.local-checkpoint@0.1.0"
|
||||
],
|
||||
"sha256": "5e6eabc607788638c1e71bb8eb4a294d33cdd4c623e70d533e4e9f0c9b730bc1",
|
||||
"sha256": "a0120520aadb73fee08138b7b60a5ee05b82823e028ec1bc644ead6637920668",
|
||||
"hash_encoding": "utf8-no-bom-lf"
|
||||
},
|
||||
{
|
||||
@@ -516,6 +516,6 @@
|
||||
"snapshot": {
|
||||
"algorithm": "sha256",
|
||||
"scope": "modules array serialized as UTF-8 JSON with sorted keys and compact separators",
|
||||
"digest": "1f782aee6890de50e3928e7edc14eb2f959d8e0e05641cbd16d12b2edb3211d1"
|
||||
"digest": "f00e1677c0abafd42b8d70d14847a1044ba43917424cda7c4b18b5494a959385"
|
||||
}
|
||||
}
|
||||
@@ -8,6 +8,10 @@ Read the pack's [evidence](../../protocols/EVIDENCE.md), [scope](../../protocols
|
||||
|
||||
Inputs are the selected source(s), explicit project and the user's research objective. Use `get_project_context` for the project's north star, key questions, watch list, taxonomy extensions, research lenses and saved ingest guidance. Every project defaults to four research lenses: technical, conceptual, cultural-historical and financial-market. Treat these as coverage prompts, not quotas. Verify the supported tool/schema contract, including `ingest_review_create` when borderline-review intake is available. Use the connector for local byte transfer; it returns a typed source metadata candidate without exposing the selected path or bytes. Selected `.vtt` and `.srt` files produce timestamped transcript cues; cite exact cue start/end times and the quote span. A declared NotebookLM export label is metadata only and is not export verification. For text explicitly pasted by the user, use `source_capture_text` with a stable capture ID and source key; it accepts UTF-8 plain text or Markdown up to 1 MB, archives and extracts it, and returns a typed candidate marked `capture_method=pasted-text`. Retry uncertain calls with the same capture ID and identical inputs; changed input under that ID conflicts. It does not register the candidate. `source_capture_url` fetches only operator-allowlisted public hosts and stages supported text, Markdown, HTML or PDF bytes; it also returns a source metadata candidate but does not register it. Submit candidates with the normal typed proposal flow, and use `capture-failed` candidates only as bookmarks, never as factual evidence. URL source IDs follow the sanitized URL; local source IDs follow the connector's configured file ID; pasted-text source IDs are derived from the supplied stable key and revision IDs include the content digest. PDF extraction currently requires Linux bubblewrap, Poppler and prlimit. Unsupported formats and unavailable parsers must be reported without inventing an extraction. If the service is unavailable, report the blocked stage and only prepare an unaccepted local draft when that work was requested.
|
||||
|
||||
Extract useful atomic assertions, problems, techniques or cases with their conditions across all four lenses where the source contains relevant material. Consider cultural history, philosophical context and market/financial evidence as project data when they explain the project's origins, concepts, adoption, audience, costs or viability; they are not automatically peripheral. First try to connect uncertain material to the north star, a key question, a saved rule or one of the lenses. Exclude only clearly unrelated material, unavailable evidence, or material the user explicitly excluded. Do not defer a section merely because its relevance is indirect, non-technical or historical. Continue normal evidence-backed proposal evaluation/submission for all plausible useful findings. Also submit a bounded `ingest_review_create` follow-up flag with the exact extraction excerpt/locator, lens, summary and reason when a human should review the relevance or categorization; this flag is persisted for notification/filtering and must not block or change proposal submission. Include the same evidence-backed candidate `tags`, `audience`, `use_for` and `domain` labels you proposed for the associated knowledge, up to five per facet (20 total); reuse project vocabulary when suitable and omit uncertain candidates. If available, Jev assesses relevance, lens and each proposed facet label in one advisory call. Use these probabilities to focus human review; they are not a gate, evidence assessment, or instruction to silently rewrite accepted knowledge. When a reviewer decides, record the feedback and apply reusable project guidance only when the reviewer explicitly opts in. Preserve the service's exact source/extraction/location bindings. Map each factual field to evidence; assess semantic support separately. Record clear exclusions and genuinely skipped/deferred sections. Optimize for useful coverage rather than maximum note count.
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Extract useful atomic assertions, problems, techniques or cases with their conditions across all four lenses where the source contains relevant material. Consider cultural history, philosophical context and market/financial evidence as project data when they explain the project's origins, concepts, adoption, audience, costs or viability; they are not automatically peripheral. First try to connect uncertain material to the north star, a key question, a saved rule or one of the lenses. Exclude only clearly unrelated material, unavailable evidence, or material the user explicitly excluded. Do not defer a section merely because its relevance is indirect, non-technical or historical. Continue normal evidence-backed proposal evaluation/submission for all plausible useful findings. When a human should review relevance or categorization, submit a bounded `ingest_review_create` flag with the exact extraction excerpt/locator, lens, summary and reason before finalizing the associated proposal facets. This persists for notification/filtering and never blocks the evidence-backed proposal flow.
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For `tags`, `audience`, `use_for` and `domain`, inspect the `facet_labels` catalog returned by `get_project_context`. Reuse a canonical project label when its meaning fits; do not create spelling, phrasing or singular/plural variants. Propose only useful, evidence-backed labels, with at most five tags and three labels in each other facet (14 total). Prefer `candidate_facet_labels` entries shaped as `{facet, value, definition}` so a genuinely new concept has a concise, distinguishing definition (500 characters max). Legacy `candidate_tags`, `candidate_audience`, `candidate_use_for` and `candidate_domain` fields remain valid for labels that do not need a definition. Leave uncertain labels out. Jev compares agent-proposed candidates with the closest project labels and chooses an existing label or the `new_label` option; it does not invent the proposed label text. The backend may add only a distinct new candidate that Jev ranks in that facet's configured top N (tags: up to five; other facets: up to three) and that clears its fit, new-label and confidence thresholds. An existing-label match is reused rather than duplicated. For the associated proposal, use Jev's selected canonical existing label for that facet. Use a new candidate as a project vocabulary label only when `added_to_project` is true; otherwise omit it from the proposal facets and leave its evidence-backed finding intact. Treat returned `jev_facet_resolutions` as the recorded decision; never claim a label was added unless `added_to_project` is true. Label promotion requires the server's local embedding model and Jev configuration; without them the candidate remains only a review signal. Label decisions only normalize facets; they do not gate evidence assessment, proposal submission or acceptance.
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If available, Jev also assesses relevance and lens in the same advisory call. Use the saved scores to focus human review; they are not evidence assessment or an instruction to silently rewrite accepted knowledge. When a reviewer decides, record the feedback and apply reusable project guidance only when the reviewer explicitly opts in. Preserve the service's exact source/extraction/location bindings. Map each factual field to evidence; assess semantic support separately. Record clear exclusions and genuinely skipped/deferred sections. Optimize for useful coverage rather than maximum note count.
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Submit bounded bundles under the affected project/shared policies. Repair actionable findings without weakening evidence, changing scope to evade policy or assuming owner authority. Resume uncertain calls through status lookup. Report accepted node IDs and receipts, pending/rejected work, archive/extraction limits and actual coverage. A successful upload or schema check is not a completed ingestion.
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Reference in new issue
Block a user