1855 lines
50 KiB
JSON
1855 lines
50 KiB
JSON
{
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"openapi": "3.0.3",
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"info": {
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"title": "Text Generation Inference",
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"description": "Text Generation Webserver",
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"contact": {
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"name": "Olivier Dehaene"
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},
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"license": {
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"name": "Apache 2.0",
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"url": "https://www.apache.org/licenses/LICENSE-2.0"
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},
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"version": "2.0.0"
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},
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"paths": {
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"/": {
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"post": {
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"tags": [
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"Text Generation Inference"
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],
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"summary": "Generate tokens if `stream == false` or a stream of token if `stream == true`",
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"description": "Generate tokens if `stream == false` or a stream of token if `stream == true`",
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"operationId": "compat_generate",
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"requestBody": {
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/CompatGenerateRequest"
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}
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}
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},
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"required": true
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},
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"responses": {
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"200": {
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"description": "Generated Text",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/GenerateResponse"
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}
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},
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"text/event-stream": {
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"schema": {
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"$ref": "#/components/schemas/StreamResponse"
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}
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}
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}
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},
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"422": {
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"description": "Input validation error",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Input validation error"
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}
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}
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}
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},
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"424": {
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"description": "Generation Error",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Request failed during generation"
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}
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}
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}
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},
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"429": {
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"description": "Model is overloaded",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Model is overloaded"
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}
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}
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}
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},
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"500": {
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"description": "Incomplete generation",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Incomplete generation"
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}
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}
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}
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}
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}
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}
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},
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"/generate": {
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"post": {
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"tags": [
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"Text Generation Inference"
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],
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"summary": "Generate tokens",
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"description": "Generate tokens",
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"operationId": "generate",
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"requestBody": {
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/GenerateRequest"
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}
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}
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},
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"required": true
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},
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"responses": {
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"200": {
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"description": "Generated Text",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/GenerateResponse"
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}
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}
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}
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},
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"422": {
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"description": "Input validation error",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Input validation error"
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}
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}
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}
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},
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"424": {
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"description": "Generation Error",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Request failed during generation"
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}
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}
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}
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},
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"429": {
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"description": "Model is overloaded",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Model is overloaded"
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}
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}
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}
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},
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"500": {
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"description": "Incomplete generation",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Incomplete generation"
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}
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}
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}
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}
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}
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}
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},
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"/generate_stream": {
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"post": {
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"tags": [
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"Text Generation Inference"
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],
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"summary": "Generate a stream of token using Server-Sent Events",
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"description": "Generate a stream of token using Server-Sent Events",
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"operationId": "generate_stream",
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"requestBody": {
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/GenerateRequest"
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}
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}
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},
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"required": true
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},
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"responses": {
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"200": {
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"description": "Generated Text",
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"content": {
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"text/event-stream": {
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"schema": {
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"$ref": "#/components/schemas/StreamResponse"
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}
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}
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}
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},
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"422": {
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"description": "Input validation error",
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"content": {
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"text/event-stream": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Input validation error"
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}
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}
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}
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},
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"424": {
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"description": "Generation Error",
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"content": {
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"text/event-stream": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Request failed during generation"
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}
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}
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}
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},
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"429": {
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"description": "Model is overloaded",
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"content": {
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"text/event-stream": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Model is overloaded"
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}
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}
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}
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},
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"500": {
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"description": "Incomplete generation",
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"content": {
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"text/event-stream": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Incomplete generation"
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}
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}
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}
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}
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}
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}
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},
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"/health": {
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"get": {
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"tags": [
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"Text Generation Inference"
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],
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"summary": "Health check method",
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"description": "Health check method",
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"operationId": "health",
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"responses": {
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"200": {
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"description": "Everything is working fine"
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},
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"503": {
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"description": "Text generation inference is down",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "unhealthy",
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"error_type": "healthcheck"
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}
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}
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}
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}
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}
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}
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},
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"/info": {
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"get": {
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"tags": [
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"Text Generation Inference"
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],
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"summary": "Text Generation Inference endpoint info",
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"description": "Text Generation Inference endpoint info",
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"operationId": "get_model_info",
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"responses": {
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"200": {
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"description": "Served model info",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/Info"
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}
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}
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}
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}
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}
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}
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},
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"/metrics": {
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"get": {
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"tags": [
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"Text Generation Inference"
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],
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"summary": "Prometheus metrics scrape endpoint",
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"description": "Prometheus metrics scrape endpoint",
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"operationId": "metrics",
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"responses": {
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"200": {
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"description": "Prometheus Metrics",
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"content": {
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"text/plain": {
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"schema": {
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"type": "string"
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}
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}
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}
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}
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}
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}
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},
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"/tokenize": {
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"post": {
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"tags": [
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"Text Generation Inference"
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],
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"summary": "Tokenize inputs",
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"description": "Tokenize inputs",
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"operationId": "tokenize",
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"requestBody": {
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/GenerateRequest"
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}
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}
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},
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"required": true
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},
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"responses": {
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"200": {
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"description": "Tokenized ids",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/TokenizeResponse"
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}
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}
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}
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},
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"404": {
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"description": "No tokenizer found",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "No fast tokenizer available"
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}
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}
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}
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}
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}
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}
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},
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"/v1/chat/completions": {
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"post": {
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"tags": [
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"Text Generation Inference"
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],
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"summary": "Generate tokens",
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"description": "Generate tokens",
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"operationId": "chat_completions",
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"requestBody": {
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ChatRequest"
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}
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}
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},
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"required": true
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},
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"responses": {
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"200": {
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"description": "Generated Text",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ChatCompletionChunk"
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}
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}
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}
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},
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"422": {
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"description": "Input validation error",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Input validation error"
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}
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}
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}
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},
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"424": {
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"description": "Generation Error",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Request failed during generation"
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}
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}
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}
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},
|
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"429": {
|
|
"description": "Model is overloaded",
|
|
"content": {
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"application/json": {
|
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"schema": {
|
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"$ref": "#/components/schemas/ErrorResponse"
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},
|
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"example": {
|
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"error": "Model is overloaded"
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}
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}
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}
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},
|
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"500": {
|
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"description": "Incomplete generation",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ErrorResponse"
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},
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"example": {
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"error": "Incomplete generation"
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}
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}
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}
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}
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}
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}
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},
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"/v1/completions": {
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"post": {
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"tags": [
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"Text Generation Inference"
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],
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"summary": "Generate tokens",
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"description": "Generate tokens",
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"operationId": "completions",
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"requestBody": {
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/CompletionRequest"
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}
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}
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},
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"required": true
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},
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"responses": {
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"200": {
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"description": "Generated Text",
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/ChatCompletionChunk"
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}
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}
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}
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},
|
|
"422": {
|
|
"description": "Input validation error",
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/ErrorResponse"
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|
},
|
|
"example": {
|
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"error": "Input validation error"
|
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}
|
|
}
|
|
}
|
|
},
|
|
"424": {
|
|
"description": "Generation Error",
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/ErrorResponse"
|
|
},
|
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"example": {
|
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"error": "Request failed during generation"
|
|
}
|
|
}
|
|
}
|
|
},
|
|
"429": {
|
|
"description": "Model is overloaded",
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/ErrorResponse"
|
|
},
|
|
"example": {
|
|
"error": "Model is overloaded"
|
|
}
|
|
}
|
|
}
|
|
},
|
|
"500": {
|
|
"description": "Incomplete generation",
|
|
"content": {
|
|
"application/json": {
|
|
"schema": {
|
|
"$ref": "#/components/schemas/ErrorResponse"
|
|
},
|
|
"example": {
|
|
"error": "Incomplete generation"
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
},
|
|
"components": {
|
|
"schemas": {
|
|
"BestOfSequence": {
|
|
"type": "object",
|
|
"required": [
|
|
"generated_text",
|
|
"finish_reason",
|
|
"generated_tokens",
|
|
"prefill",
|
|
"tokens"
|
|
],
|
|
"properties": {
|
|
"finish_reason": {
|
|
"$ref": "#/components/schemas/FinishReason"
|
|
},
|
|
"generated_text": {
|
|
"type": "string",
|
|
"example": "test"
|
|
},
|
|
"generated_tokens": {
|
|
"type": "integer",
|
|
"format": "int32",
|
|
"example": 1,
|
|
"minimum": 0
|
|
},
|
|
"prefill": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/PrefillToken"
|
|
}
|
|
},
|
|
"seed": {
|
|
"type": "integer",
|
|
"format": "int64",
|
|
"example": 42,
|
|
"nullable": true,
|
|
"minimum": 0
|
|
},
|
|
"tokens": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/Token"
|
|
}
|
|
},
|
|
"top_tokens": {
|
|
"type": "array",
|
|
"items": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/Token"
|
|
}
|
|
}
|
|
}
|
|
}
|
|
},
|
|
"ChatCompletion": {
|
|
"type": "object",
|
|
"required": [
|
|
"id",
|
|
"object",
|
|
"created",
|
|
"model",
|
|
"system_fingerprint",
|
|
"choices",
|
|
"usage"
|
|
],
|
|
"properties": {
|
|
"choices": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/ChatCompletionComplete"
|
|
}
|
|
},
|
|
"created": {
|
|
"type": "integer",
|
|
"format": "int64",
|
|
"example": "1706270835",
|
|
"minimum": 0
|
|
},
|
|
"id": {
|
|
"type": "string"
|
|
},
|
|
"model": {
|
|
"type": "string",
|
|
"example": "mistralai/Mistral-7B-Instruct-v0.2"
|
|
},
|
|
"object": {
|
|
"type": "string"
|
|
},
|
|
"system_fingerprint": {
|
|
"type": "string"
|
|
},
|
|
"usage": {
|
|
"$ref": "#/components/schemas/Usage"
|
|
}
|
|
}
|
|
},
|
|
"ChatCompletionChoice": {
|
|
"type": "object",
|
|
"required": [
|
|
"index",
|
|
"delta"
|
|
],
|
|
"properties": {
|
|
"delta": {
|
|
"$ref": "#/components/schemas/ChatCompletionDelta"
|
|
},
|
|
"finish_reason": {
|
|
"type": "string",
|
|
"nullable": true
|
|
},
|
|
"index": {
|
|
"type": "integer",
|
|
"format": "int32",
|
|
"minimum": 0
|
|
},
|
|
"logprobs": {
|
|
"allOf": [
|
|
{
|
|
"$ref": "#/components/schemas/ChatCompletionLogprobs"
|
|
}
|
|
],
|
|
"nullable": true
|
|
}
|
|
}
|
|
},
|
|
"ChatCompletionChunk": {
|
|
"type": "object",
|
|
"required": [
|
|
"id",
|
|
"object",
|
|
"created",
|
|
"model",
|
|
"system_fingerprint",
|
|
"choices"
|
|
],
|
|
"properties": {
|
|
"choices": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/ChatCompletionChoice"
|
|
}
|
|
},
|
|
"created": {
|
|
"type": "integer",
|
|
"format": "int64",
|
|
"example": "1706270978",
|
|
"minimum": 0
|
|
},
|
|
"id": {
|
|
"type": "string"
|
|
},
|
|
"model": {
|
|
"type": "string",
|
|
"example": "mistralai/Mistral-7B-Instruct-v0.2"
|
|
},
|
|
"object": {
|
|
"type": "string"
|
|
},
|
|
"system_fingerprint": {
|
|
"type": "string"
|
|
}
|
|
}
|
|
},
|
|
"ChatCompletionComplete": {
|
|
"type": "object",
|
|
"required": [
|
|
"index",
|
|
"message",
|
|
"finish_reason"
|
|
],
|
|
"properties": {
|
|
"finish_reason": {
|
|
"type": "string"
|
|
},
|
|
"index": {
|
|
"type": "integer",
|
|
"format": "int32",
|
|
"minimum": 0
|
|
},
|
|
"logprobs": {
|
|
"allOf": [
|
|
{
|
|
"$ref": "#/components/schemas/ChatCompletionLogprobs"
|
|
}
|
|
],
|
|
"nullable": true
|
|
},
|
|
"message": {
|
|
"$ref": "#/components/schemas/Message"
|
|
}
|
|
}
|
|
},
|
|
"ChatCompletionDelta": {
|
|
"type": "object",
|
|
"required": [
|
|
"role"
|
|
],
|
|
"properties": {
|
|
"content": {
|
|
"type": "string",
|
|
"example": "What is Deep Learning?",
|
|
"nullable": true
|
|
},
|
|
"role": {
|
|
"type": "string",
|
|
"example": "user"
|
|
},
|
|
"tool_calls": {
|
|
"allOf": [
|
|
{
|
|
"$ref": "#/components/schemas/DeltaToolCall"
|
|
}
|
|
],
|
|
"nullable": true
|
|
}
|
|
}
|
|
},
|
|
"ChatCompletionLogprob": {
|
|
"type": "object",
|
|
"required": [
|
|
"token",
|
|
"logprob",
|
|
"top_logprobs"
|
|
],
|
|
"properties": {
|
|
"logprob": {
|
|
"type": "number",
|
|
"format": "float"
|
|
},
|
|
"token": {
|
|
"type": "string"
|
|
},
|
|
"top_logprobs": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/ChatCompletionTopLogprob"
|
|
}
|
|
}
|
|
}
|
|
},
|
|
"ChatCompletionLogprobs": {
|
|
"type": "object",
|
|
"required": [
|
|
"content"
|
|
],
|
|
"properties": {
|
|
"content": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/ChatCompletionLogprob"
|
|
}
|
|
}
|
|
}
|
|
},
|
|
"ChatCompletionTopLogprob": {
|
|
"type": "object",
|
|
"required": [
|
|
"token",
|
|
"logprob"
|
|
],
|
|
"properties": {
|
|
"logprob": {
|
|
"type": "number",
|
|
"format": "float"
|
|
},
|
|
"token": {
|
|
"type": "string"
|
|
}
|
|
}
|
|
},
|
|
"ChatRequest": {
|
|
"type": "object",
|
|
"required": [
|
|
"model",
|
|
"messages"
|
|
],
|
|
"properties": {
|
|
"frequency_penalty": {
|
|
"type": "number",
|
|
"format": "float",
|
|
"description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far,\ndecreasing the model's likelihood to repeat the same line verbatim.",
|
|
"example": "1.0",
|
|
"nullable": true
|
|
},
|
|
"logit_bias": {
|
|
"type": "array",
|
|
"items": {
|
|
"type": "number",
|
|
"format": "float"
|
|
},
|
|
"description": "UNUSED\nModify the likelihood of specified tokens appearing in the completion. Accepts a JSON object that maps tokens\n(specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically,\nthe bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model,\nbut values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should\nresult in a ban or exclusive selection of the relevant token.",
|
|
"nullable": true
|
|
},
|
|
"logprobs": {
|
|
"type": "boolean",
|
|
"description": "Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each\noutput token returned in the content of message.",
|
|
"example": "false",
|
|
"nullable": true
|
|
},
|
|
"max_tokens": {
|
|
"type": "integer",
|
|
"format": "int32",
|
|
"description": "The maximum number of tokens that can be generated in the chat completion.",
|
|
"example": "32",
|
|
"nullable": true,
|
|
"minimum": 0
|
|
},
|
|
"messages": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/Message"
|
|
},
|
|
"description": "A list of messages comprising the conversation so far.",
|
|
"example": "[{\"role\": \"user\", \"content\": \"What is Deep Learning?\"}]"
|
|
},
|
|
"model": {
|
|
"type": "string",
|
|
"description": "[UNUSED] ID of the model to use. See the model endpoint compatibility table for details on which models work with the Chat API.",
|
|
"example": "mistralai/Mistral-7B-Instruct-v0.2"
|
|
},
|
|
"n": {
|
|
"type": "integer",
|
|
"format": "int32",
|
|
"description": "UNUSED\nHow many chat completion choices to generate for each input message. Note that you will be charged based on the\nnumber of generated tokens across all of the choices. Keep n as 1 to minimize costs.",
|
|
"example": "2",
|
|
"nullable": true,
|
|
"minimum": 0
|
|
},
|
|
"presence_penalty": {
|
|
"type": "number",
|
|
"format": "float",
|
|
"description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far,\nincreasing the model's likelihood to talk about new topics",
|
|
"example": 0.1,
|
|
"nullable": true
|
|
},
|
|
"seed": {
|
|
"type": "integer",
|
|
"format": "int64",
|
|
"example": 42,
|
|
"nullable": true,
|
|
"minimum": 0
|
|
},
|
|
"stop": {
|
|
"type": "array",
|
|
"items": {
|
|
"type": "string"
|
|
},
|
|
"description": "Up to 4 sequences where the API will stop generating further tokens.",
|
|
"example": "null",
|
|
"nullable": true
|
|
},
|
|
"stream": {
|
|
"type": "boolean"
|
|
},
|
|
"temperature": {
|
|
"type": "number",
|
|
"format": "float",
|
|
"description": "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while\nlower values like 0.2 will make it more focused and deterministic.\n\nWe generally recommend altering this or `top_p` but not both.",
|
|
"example": 1.0,
|
|
"nullable": true
|
|
},
|
|
"tool_choice": {
|
|
"allOf": [
|
|
{
|
|
"$ref": "#/components/schemas/ToolType"
|
|
}
|
|
],
|
|
"nullable": true
|
|
},
|
|
"tool_prompt": {
|
|
"type": "string",
|
|
"description": "A prompt to be appended before the tools",
|
|
"example": "\"Based on the conversation, please choose the most appropriate tool to use: \"",
|
|
"nullable": true
|
|
},
|
|
"tools": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/Tool"
|
|
},
|
|
"description": "A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of\nfunctions the model may generate JSON inputs for.",
|
|
"example": "null",
|
|
"nullable": true
|
|
},
|
|
"top_logprobs": {
|
|
"type": "integer",
|
|
"format": "int32",
|
|
"description": "An integer between 0 and 5 specifying the number of most likely tokens to return at each token position, each with\nan associated log probability. logprobs must be set to true if this parameter is used.",
|
|
"example": "5",
|
|
"nullable": true,
|
|
"minimum": 0
|
|
},
|
|
"top_p": {
|
|
"type": "number",
|
|
"format": "float",
|
|
"description": "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the\ntokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.",
|
|
"example": 0.95,
|
|
"nullable": true
|
|
}
|
|
}
|
|
},
|
|
"CompatGenerateRequest": {
|
|
"type": "object",
|
|
"required": [
|
|
"inputs"
|
|
],
|
|
"properties": {
|
|
"inputs": {
|
|
"type": "string",
|
|
"example": "My name is Olivier and I"
|
|
},
|
|
"parameters": {
|
|
"$ref": "#/components/schemas/GenerateParameters"
|
|
},
|
|
"stream": {
|
|
"type": "boolean",
|
|
"default": "false"
|
|
}
|
|
}
|
|
},
|
|
"CompletionComplete": {
|
|
"type": "object",
|
|
"required": [
|
|
"index",
|
|
"text",
|
|
"finish_reason"
|
|
],
|
|
"properties": {
|
|
"finish_reason": {
|
|
"type": "string"
|
|
},
|
|
"index": {
|
|
"type": "integer",
|
|
"format": "int32",
|
|
"minimum": 0
|
|
},
|
|
"logprobs": {
|
|
"type": "array",
|
|
"items": {
|
|
"type": "number",
|
|
"format": "float"
|
|
},
|
|
"nullable": true
|
|
},
|
|
"text": {
|
|
"type": "string"
|
|
}
|
|
}
|
|
},
|
|
"CompletionCompleteChunk": {
|
|
"type": "object",
|
|
"required": [
|
|
"id",
|
|
"object",
|
|
"created",
|
|
"choices",
|
|
"model",
|
|
"system_fingerprint"
|
|
],
|
|
"properties": {
|
|
"choices": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/CompletionComplete"
|
|
}
|
|
},
|
|
"created": {
|
|
"type": "integer",
|
|
"format": "int64",
|
|
"minimum": 0
|
|
},
|
|
"id": {
|
|
"type": "string"
|
|
},
|
|
"model": {
|
|
"type": "string"
|
|
},
|
|
"object": {
|
|
"type": "string"
|
|
},
|
|
"system_fingerprint": {
|
|
"type": "string"
|
|
}
|
|
}
|
|
},
|
|
"CompletionRequest": {
|
|
"type": "object",
|
|
"required": [
|
|
"model",
|
|
"prompt"
|
|
],
|
|
"properties": {
|
|
"frequency_penalty": {
|
|
"type": "number",
|
|
"format": "float",
|
|
"description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far,\ndecreasing the model's likelihood to repeat the same line verbatim.",
|
|
"example": "1.0",
|
|
"nullable": true
|
|
},
|
|
"max_tokens": {
|
|
"type": "integer",
|
|
"format": "int32",
|
|
"description": "The maximum number of tokens that can be generated in the chat completion.",
|
|
"default": "32",
|
|
"nullable": true,
|
|
"minimum": 0
|
|
},
|
|
"model": {
|
|
"type": "string",
|
|
"description": "UNUSED\nID of the model to use. See the model endpoint compatibility table for details on which models work with the Chat API.",
|
|
"example": "mistralai/Mistral-7B-Instruct-v0.2"
|
|
},
|
|
"prompt": {
|
|
"type": "string",
|
|
"description": "The prompt to generate completions for.",
|
|
"example": "What is Deep Learning?"
|
|
},
|
|
"repetition_penalty": {
|
|
"type": "number",
|
|
"format": "float",
|
|
"nullable": true
|
|
},
|
|
"seed": {
|
|
"type": "integer",
|
|
"format": "int64",
|
|
"example": 42,
|
|
"nullable": true,
|
|
"minimum": 0
|
|
},
|
|
"stream": {
|
|
"type": "boolean"
|
|
},
|
|
"suffix": {
|
|
"type": "string",
|
|
"description": "The text to append to the prompt. This is useful for completing sentences or generating a paragraph of text.\nplease see the completion_template field in the model's tokenizer_config.json file for completion template.",
|
|
"nullable": true
|
|
},
|
|
"temperature": {
|
|
"type": "number",
|
|
"format": "float",
|
|
"description": "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while\nlower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or `top_p` but not both.",
|
|
"example": 1.0,
|
|
"nullable": true
|
|
},
|
|
"top_p": {
|
|
"type": "number",
|
|
"format": "float",
|
|
"description": "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the\ntokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.",
|
|
"example": 0.95,
|
|
"nullable": true
|
|
}
|
|
}
|
|
},
|
|
"DeltaToolCall": {
|
|
"type": "object",
|
|
"required": [
|
|
"index",
|
|
"id",
|
|
"type",
|
|
"function"
|
|
],
|
|
"properties": {
|
|
"function": {
|
|
"$ref": "#/components/schemas/Function"
|
|
},
|
|
"id": {
|
|
"type": "string"
|
|
},
|
|
"index": {
|
|
"type": "integer",
|
|
"format": "int32",
|
|
"minimum": 0
|
|
},
|
|
"type": {
|
|
"type": "string"
|
|
}
|
|
}
|
|
},
|
|
"Details": {
|
|
"type": "object",
|
|
"required": [
|
|
"finish_reason",
|
|
"generated_tokens",
|
|
"prefill",
|
|
"tokens"
|
|
],
|
|
"properties": {
|
|
"best_of_sequences": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/BestOfSequence"
|
|
},
|
|
"nullable": true
|
|
},
|
|
"finish_reason": {
|
|
"$ref": "#/components/schemas/FinishReason"
|
|
},
|
|
"generated_tokens": {
|
|
"type": "integer",
|
|
"format": "int32",
|
|
"example": 1,
|
|
"minimum": 0
|
|
},
|
|
"prefill": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/PrefillToken"
|
|
}
|
|
},
|
|
"seed": {
|
|
"type": "integer",
|
|
"format": "int64",
|
|
"example": 42,
|
|
"nullable": true,
|
|
"minimum": 0
|
|
},
|
|
"tokens": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/Token"
|
|
}
|
|
},
|
|
"top_tokens": {
|
|
"type": "array",
|
|
"items": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/Token"
|
|
}
|
|
}
|
|
}
|
|
}
|
|
},
|
|
"ErrorResponse": {
|
|
"type": "object",
|
|
"required": [
|
|
"error",
|
|
"error_type"
|
|
],
|
|
"properties": {
|
|
"error": {
|
|
"type": "string"
|
|
},
|
|
"error_type": {
|
|
"type": "string"
|
|
}
|
|
}
|
|
},
|
|
"FinishReason": {
|
|
"type": "string",
|
|
"enum": [
|
|
"length",
|
|
"eos_token",
|
|
"stop_sequence"
|
|
],
|
|
"example": "Length"
|
|
},
|
|
"Function": {
|
|
"type": "object",
|
|
"required": [
|
|
"arguments"
|
|
],
|
|
"properties": {
|
|
"arguments": {
|
|
"type": "string"
|
|
},
|
|
"name": {
|
|
"type": "string",
|
|
"nullable": true
|
|
}
|
|
}
|
|
},
|
|
"FunctionDefinition": {
|
|
"type": "object",
|
|
"required": [
|
|
"name",
|
|
"parameters"
|
|
],
|
|
"properties": {
|
|
"description": {
|
|
"type": "string",
|
|
"nullable": true
|
|
},
|
|
"name": {
|
|
"type": "string"
|
|
},
|
|
"parameters": {}
|
|
}
|
|
},
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{
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"$ref": "#/components/schemas/GrammarType"
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"photographer"
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"inputs"
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{
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"$ref": "#/components/schemas/Details"
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{
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],
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"json"
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},
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"value": {
|
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"description": "A string that represents a [JSON Schema](https://json-schema.org/).\n\nJSON Schema is a declarative language that allows to annotate JSON documents\nwith types and descriptions."
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}
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{
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"model_id",
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
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|
|
},
|
|
"Token": {
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|
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|
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|
"id",
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|
"text",
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|
"logprob",
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|
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|
|
],
|
|
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|
|
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|
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|
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|
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|
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|
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|
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|
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|
|
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|
|
"example": -0.34,
|
|
"nullable": true
|
|
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|
|
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|
|
"type": "boolean",
|
|
"example": "false"
|
|
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|
|
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|
|
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|
|
"example": "test"
|
|
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|
|
}
|
|
},
|
|
"TokenizeResponse": {
|
|
"type": "array",
|
|
"items": {
|
|
"$ref": "#/components/schemas/SimpleToken"
|
|
}
|
|
},
|
|
"Tool": {
|
|
"type": "object",
|
|
"required": [
|
|
"type",
|
|
"function"
|
|
],
|
|
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|
|
"function": {
|
|
"$ref": "#/components/schemas/FunctionDefinition"
|
|
},
|
|
"type": {
|
|
"type": "string",
|
|
"example": "function"
|
|
}
|
|
}
|
|
},
|
|
"ToolCall": {
|
|
"type": "object",
|
|
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|
|
"id",
|
|
"type",
|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
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|
|
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|
|
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|
|
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|
|
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|
|
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|
|
}
|
|
},
|
|
"ToolType": {
|
|
"oneOf": [
|
|
{
|
|
"type": "object",
|
|
"required": [
|
|
"FunctionName"
|
|
],
|
|
"properties": {
|
|
"FunctionName": {
|
|
"type": "string"
|
|
}
|
|
}
|
|
},
|
|
{
|
|
"type": "string",
|
|
"enum": [
|
|
"OneOf"
|
|
]
|
|
}
|
|
]
|
|
},
|
|
"Usage": {
|
|
"type": "object",
|
|
"required": [
|
|
"prompt_tokens",
|
|
"completion_tokens",
|
|
"total_tokens"
|
|
],
|
|
"properties": {
|
|
"completion_tokens": {
|
|
"type": "integer",
|
|
"format": "int32",
|
|
"minimum": 0
|
|
},
|
|
"prompt_tokens": {
|
|
"type": "integer",
|
|
"format": "int32",
|
|
"minimum": 0
|
|
},
|
|
"total_tokens": {
|
|
"type": "integer",
|
|
"format": "int32",
|
|
"minimum": 0
|
|
}
|
|
}
|
|
}
|
|
}
|
|
},
|
|
"tags": [
|
|
{
|
|
"name": "Text Generation Inference",
|
|
"description": "Hugging Face Text Generation Inference API"
|
|
}
|
|
]
|
|
}
|