feat: improve update_docs for openapi schema (#2169)
* feat: add pre commit step to force schema update when router changes * fix: prefer improved update_doc and start server and compare * fix: adjust typo * fix: adjust revert typo * fix: update workflow to use update_doc md command * feat: improve workflow to check openapi schema too * fix: adjust timeout for CI * fix: adjust raise condition and install server in ci * fix: install protoc before server * feat: improve update doc and add command to print router schema * fix: adjust autodoc workflow * fix: explicitly install protoc and python * fix: alllow trailing space in openapi schema diff
This commit is contained in:
drbh
GitHub
parent
0759ec495e
commit
571530dd9a
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@ -11,10 +11,30 @@ jobs:
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- name: Checkout code
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uses: actions/checkout@v2
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- name: Set up Rust
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uses: actions-rs/toolchain@v1
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with:
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profile: minimal
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toolchain: stable
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- name: Install Protocol Buffers compiler
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run: |
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sudo apt-get update
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sudo apt-get install -y protobuf-compiler libprotobuf-dev
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- name: Install Launcher
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id: install-launcher
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run: cargo install --path launcher/
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- name: Check launcher Docs are up-to-date
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- name: Install router
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id: install-router
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run: cargo install --path router/
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- name: Set up Python
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uses: actions/setup-python@v2
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with:
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python-version: '3.x'
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- name: Check that documentation is up-to-date
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run: |
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echo text-generation-launcher --help
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python update_doc.py --check
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@ -10,7 +10,7 @@
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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": "2.0.1"
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"version": "2.1.1-dev0"
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},
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"paths": {
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"/": {
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@ -19,7 +19,6 @@
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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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@ -108,7 +107,6 @@
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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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@ -192,7 +190,6 @@
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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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@ -276,7 +273,6 @@
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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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@ -305,7 +301,6 @@
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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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@ -327,7 +322,6 @@
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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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@ -349,7 +343,6 @@
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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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@ -394,7 +387,6 @@
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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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@ -483,7 +475,6 @@
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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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@ -626,7 +617,6 @@
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"type": "object",
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"required": [
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"id",
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"object",
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"created",
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"model",
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"system_fingerprint",
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@ -653,9 +643,6 @@
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"type": "string",
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"example": "mistralai/Mistral-7B-Instruct-v0.2"
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},
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"object": {
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"type": "string"
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},
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"system_fingerprint": {
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"type": "string"
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},
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@ -697,7 +684,6 @@
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"type": "object",
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"required": [
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"id",
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"object",
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"created",
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"model",
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"system_fingerprint",
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@ -723,9 +709,6 @@
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"type": "string",
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"example": "mistralai/Mistral-7B-Instruct-v0.2"
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},
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"object": {
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"type": "string"
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},
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"system_fingerprint": {
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"type": "string"
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}
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@ -756,34 +739,19 @@
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"nullable": true
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},
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"message": {
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"$ref": "#/components/schemas/Message"
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"$ref": "#/components/schemas/OutputMessage"
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}
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}
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},
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"ChatCompletionDelta": {
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"type": "object",
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"required": [
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"role"
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],
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"properties": {
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"content": {
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"type": "string",
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"example": "What is Deep Learning?",
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"nullable": true
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"oneOf": [
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{
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"$ref": "#/components/schemas/TextMessage"
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},
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"role": {
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"type": "string",
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"example": "user"
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},
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"tool_calls": {
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"allOf": [
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{
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"$ref": "#/components/schemas/DeltaToolCall"
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}
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],
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"nullable": true
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{
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"$ref": "#/components/schemas/ToolCallDelta"
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}
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}
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]
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},
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"ChatCompletionLogprob": {
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"type": "object",
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@ -903,6 +871,15 @@
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"example": 0.1,
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"nullable": true
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},
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"response_format": {
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"allOf": [
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{
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"$ref": "#/components/schemas/GrammarType"
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}
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],
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"default": "null",
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"nullable": true
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},
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"seed": {
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"type": "integer",
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"format": "int64",
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@ -1021,7 +998,6 @@
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"type": "object",
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"required": [
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"id",
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"object",
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"created",
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"choices",
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"model",
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@ -1045,9 +1021,6 @@
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"model": {
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"type": "string"
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},
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"object": {
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"type": "string"
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},
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"system_fingerprint": {
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"type": "string"
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}
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@ -1081,12 +1054,7 @@
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"example": "mistralai/Mistral-7B-Instruct-v0.2"
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},
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"prompt": {
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"type": "array",
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"items": {
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"type": "string"
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},
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"description": "The prompt to generate completions for.",
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"example": "What is Deep Learning?"
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"$ref": "#/components/schemas/Prompt"
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},
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"repetition_penalty": {
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"type": "number",
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@ -1100,6 +1068,15 @@
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"nullable": true,
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"minimum": 0
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},
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"stop": {
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"type": "array",
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"items": {
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"type": "string"
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},
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"description": "Up to 4 sequences where the API will stop generating further tokens.",
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"example": "null",
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"nullable": true
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},
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"stream": {
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"type": "boolean"
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},
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@ -1121,15 +1098,6 @@
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"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.",
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"example": 0.95,
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"nullable": true
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},
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"stop": {
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"type": "array",
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"items": {
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"type": "string"
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},
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"description": "Up to 4 sequences where the API will stop generating further tokens.",
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"example": "null",
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"nullable": true
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}
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}
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},
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@ -1272,8 +1240,16 @@
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"GenerateParameters": {
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"type": "object",
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"properties": {
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"adapter_id": {
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"type": "string",
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"description": "Lora adapter id",
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"default": "null",
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"example": "null",
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"nullable": true
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},
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"best_of": {
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"type": "integer",
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"description": "Generate best_of sequences and return the one if the highest token logprobs.",
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"default": "null",
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"example": 1,
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"nullable": true,
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@ -1282,20 +1258,24 @@
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},
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"decoder_input_details": {
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"type": "boolean",
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"description": "Whether to return decoder input token logprobs and ids.",
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"default": "false"
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},
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"details": {
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"type": "boolean",
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"description": "Whether to return generation details.",
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"default": "true"
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},
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"do_sample": {
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"type": "boolean",
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"description": "Activate logits sampling.",
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"default": "false",
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"example": true
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},
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"frequency_penalty": {
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"type": "number",
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"format": "float",
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"description": "The parameter for frequency penalty. 1.0 means no penalty\nPenalize new tokens based on their existing frequency in the text so far,\ndecreasing the model's likelihood to repeat the same line verbatim.",
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"default": "null",
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"example": 0.1,
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"nullable": true,
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@ -1313,6 +1293,7 @@
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"max_new_tokens": {
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"type": "integer",
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"format": "int32",
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"description": "Maximum number of tokens to generate.",
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"default": "100",
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"example": "20",
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"nullable": true,
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@ -1321,6 +1302,7 @@
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"repetition_penalty": {
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"type": "number",
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"format": "float",
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"description": "The parameter for repetition penalty. 1.0 means no penalty.\nSee [this paper](https://arxiv.org/pdf/1909.05858.pdf) for more details.",
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"default": "null",
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"example": 1.03,
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"nullable": true,
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@ -1328,6 +1310,7 @@
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},
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"return_full_text": {
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"type": "boolean",
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"description": "Whether to prepend the prompt to the generated text",
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"default": "null",
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"example": false,
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"nullable": true
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@ -1335,6 +1318,7 @@
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"seed": {
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"type": "integer",
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"format": "int64",
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"description": "Random sampling seed.",
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"default": "null",
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"example": "null",
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"nullable": true,
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@ -1346,6 +1330,7 @@
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"items": {
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"type": "string"
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},
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"description": "Stop generating tokens if a member of `stop` is generated.",
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"example": [
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"photographer"
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],
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@ -1354,6 +1339,7 @@
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"temperature": {
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"type": "number",
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"format": "float",
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"description": "The value used to module the logits distribution.",
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"default": "null",
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"example": 0.5,
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"nullable": true,
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@ -1362,6 +1348,7 @@
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"top_k": {
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"type": "integer",
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"format": "int32",
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"description": "The number of highest probability vocabulary tokens to keep for top-k-filtering.",
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"default": "null",
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"example": 10,
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"nullable": true,
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@ -1370,6 +1357,7 @@
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"top_n_tokens": {
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"type": "integer",
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"format": "int32",
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"description": "The number of highest probability vocabulary tokens to keep for top-n-filtering.",
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"default": "null",
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"example": 5,
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"nullable": true,
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@ -1379,6 +1367,7 @@
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"top_p": {
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"type": "number",
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"format": "float",
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"description": "Top-p value for nucleus sampling.",
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"default": "null",
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"example": 0.95,
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"nullable": true,
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@ -1387,6 +1376,7 @@
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},
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"truncate": {
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"type": "integer",
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"description": "Truncate inputs tokens to the given size.",
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"default": "null",
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"example": "null",
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"nullable": true,
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@ -1395,6 +1385,7 @@
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"typical_p": {
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"type": "number",
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"format": "float",
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"description": "Typical Decoding mass\nSee [Typical Decoding for Natural Language Generation](https://arxiv.org/abs/2202.00666) for more information.",
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"default": "null",
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"example": 0.95,
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"nullable": true,
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@ -1403,6 +1394,7 @@
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},
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"watermark": {
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"type": "boolean",
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"description": "Watermarking with [A Watermark for Large Language Models](https://arxiv.org/abs/2301.10226).",
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"default": "false",
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"example": true
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}
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@ -1495,13 +1487,14 @@
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"max_concurrent_requests",
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"max_best_of",
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"max_stop_sequences",
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"max_input_length",
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"max_input_tokens",
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"max_total_tokens",
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"waiting_served_ratio",
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"max_batch_total_tokens",
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"max_waiting_tokens",
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"validation_workers",
|
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"max_client_batch_size",
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"router",
|
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"version"
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],
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"properties": {
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@ -1538,7 +1531,7 @@
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"example": "128",
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"minimum": 0
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},
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"max_input_length": {
|
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"max_input_tokens": {
|
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"type": "integer",
|
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"example": "1024",
|
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"minimum": 0
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|
|
@ -1581,6 +1574,11 @@
|
|||
"example": "e985a63cdc139290c5f700ff1929f0b5942cced2",
|
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"nullable": true
|
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},
|
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"router": {
|
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"type": "string",
|
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"description": "Router Info",
|
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"example": "text-generation-router"
|
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},
|
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"sha": {
|
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"type": "string",
|
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"example": "null",
|
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|
|
@ -1593,7 +1591,6 @@
|
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},
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"version": {
|
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"type": "string",
|
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"description": "Router Info",
|
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"example": "0.5.0"
|
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},
|
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"waiting_served_ratio": {
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|
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@ -1606,13 +1603,12 @@
|
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"Message": {
|
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"type": "object",
|
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"required": [
|
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"role"
|
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"role",
|
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"content"
|
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],
|
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"properties": {
|
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"content": {
|
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"type": "string",
|
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"example": "My name is David and I",
|
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"nullable": true
|
||||
"$ref": "#/components/schemas/MessageContent"
|
||||
},
|
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"name": {
|
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"type": "string",
|
||||
|
|
@ -1622,13 +1618,6 @@
|
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"role": {
|
||||
"type": "string",
|
||||
"example": "user"
|
||||
},
|
||||
"tool_calls": {
|
||||
"type": "array",
|
||||
"items": {
|
||||
"$ref": "#/components/schemas/ToolCall"
|
||||
},
|
||||
"nullable": true
|
||||
}
|
||||
}
|
||||
},
|
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|
|
@ -1817,9 +1806,7 @@
|
|||
"$ref": "#/components/schemas/FunctionDefinition"
|
||||
},
|
||||
"id": {
|
||||
"type": "integer",
|
||||
"format": "int32",
|
||||
"minimum": 0
|
||||
"type": "string"
|
||||
},
|
||||
"type": {
|
||||
"type": "string"
|
||||
|
|
@ -1830,20 +1817,22 @@
|
|||
"oneOf": [
|
||||
{
|
||||
"type": "object",
|
||||
"required": [
|
||||
"FunctionName"
|
||||
],
|
||||
"properties": {
|
||||
"FunctionName": {
|
||||
"type": "string"
|
||||
}
|
||||
}
|
||||
"default": null,
|
||||
"nullable": true
|
||||
},
|
||||
{
|
||||
"type": "string",
|
||||
"enum": [
|
||||
"OneOf"
|
||||
]
|
||||
"type": "string"
|
||||
},
|
||||
{
|
||||
"type": "object",
|
||||
"required": [
|
||||
"function"
|
||||
],
|
||||
"properties": {
|
||||
"function": {
|
||||
"$ref": "#/components/schemas/FunctionName"
|
||||
}
|
||||
}
|
||||
}
|
||||
]
|
||||
},
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
use axum::http::HeaderValue;
|
||||
use clap::Parser;
|
||||
use clap::Subcommand;
|
||||
use hf_hub::api::tokio::{Api, ApiBuilder, ApiRepo};
|
||||
use hf_hub::{Cache, Repo, RepoType};
|
||||
use opentelemetry::sdk::propagation::TraceContextPropagator;
|
||||
|
|
@ -27,6 +28,9 @@ use tracing_subscriber::{filter::LevelFilter, EnvFilter, Layer};
|
|||
#[derive(Parser, Debug)]
|
||||
#[clap(author, version, about, long_about = None)]
|
||||
struct Args {
|
||||
#[command(subcommand)]
|
||||
command: Option<Commands>,
|
||||
|
||||
#[clap(default_value = "128", long, env)]
|
||||
max_concurrent_requests: usize,
|
||||
#[clap(default_value = "2", long, env)]
|
||||
|
|
@ -85,10 +89,15 @@ struct Args {
|
|||
max_client_batch_size: usize,
|
||||
}
|
||||
|
||||
#[derive(Debug, Subcommand)]
|
||||
enum Commands {
|
||||
PrintSchema,
|
||||
}
|
||||
|
||||
#[tokio::main]
|
||||
async fn main() -> Result<(), RouterError> {
|
||||
// Get args
|
||||
let args = Args::parse();
|
||||
|
||||
// Pattern match configuration
|
||||
let Args {
|
||||
max_concurrent_requests,
|
||||
|
|
@ -119,10 +128,17 @@ async fn main() -> Result<(), RouterError> {
|
|||
messages_api_enabled,
|
||||
disable_grammar_support,
|
||||
max_client_batch_size,
|
||||
command,
|
||||
} = args;
|
||||
|
||||
// Launch Tokio runtime
|
||||
init_logging(otlp_endpoint, otlp_service_name, json_output);
|
||||
let print_schema_command = match command {
|
||||
Some(Commands::PrintSchema) => true,
|
||||
None => {
|
||||
// only init logging if we are not running the print schema command
|
||||
init_logging(otlp_endpoint, otlp_service_name, json_output);
|
||||
false
|
||||
}
|
||||
};
|
||||
|
||||
// Validate args
|
||||
if max_input_tokens >= max_total_tokens {
|
||||
|
|
@ -388,6 +404,7 @@ async fn main() -> Result<(), RouterError> {
|
|||
messages_api_enabled,
|
||||
disable_grammar_support,
|
||||
max_client_batch_size,
|
||||
print_schema_command,
|
||||
)
|
||||
.await?;
|
||||
Ok(())
|
||||
|
|
|
|||
|
|
@ -1387,10 +1387,10 @@ async fn tokenize(
|
|||
|
||||
/// Prometheus metrics scrape endpoint
|
||||
#[utoipa::path(
|
||||
get,
|
||||
tag = "Text Generation Inference",
|
||||
path = "/metrics",
|
||||
responses((status = 200, description = "Prometheus Metrics", body = String))
|
||||
get,
|
||||
tag = "Text Generation Inference",
|
||||
path = "/metrics",
|
||||
responses((status = 200, description = "Prometheus Metrics", body = String))
|
||||
)]
|
||||
async fn metrics(prom_handle: Extension<PrometheusHandle>) -> String {
|
||||
prom_handle.render()
|
||||
|
|
@ -1430,6 +1430,7 @@ pub async fn run(
|
|||
messages_api_enabled: bool,
|
||||
grammar_support: bool,
|
||||
max_client_batch_size: usize,
|
||||
print_schema_command: bool,
|
||||
) -> Result<(), WebServerError> {
|
||||
// OpenAPI documentation
|
||||
#[derive(OpenApi)]
|
||||
|
|
@ -1500,6 +1501,12 @@ pub async fn run(
|
|||
struct ApiDoc;
|
||||
|
||||
// Create state
|
||||
if print_schema_command {
|
||||
let api_doc = ApiDoc::openapi();
|
||||
let api_doc = serde_json::to_string_pretty(&api_doc).unwrap();
|
||||
println!("{}", api_doc);
|
||||
std::process::exit(0);
|
||||
}
|
||||
|
||||
// Open connection, get model info and warmup
|
||||
let (scheduler, health_ext, shard_info, max_batch_total_tokens): (
|
||||
|
|
|
|||
|
|
@ -1,6 +1,8 @@
|
|||
import subprocess
|
||||
import argparse
|
||||
import ast
|
||||
import json
|
||||
import os
|
||||
|
||||
TEMPLATE = """
|
||||
# Supported Models and Hardware
|
||||
|
|
@ -122,6 +124,53 @@ def check_supported_models(check: bool):
|
|||
f.write(final_doc)
|
||||
|
||||
|
||||
def get_openapi_schema():
|
||||
try:
|
||||
output = subprocess.check_output(["text-generation-router", "print-schema"])
|
||||
return json.loads(output)
|
||||
except subprocess.CalledProcessError as e:
|
||||
print(f"Error running text-generation-router print-schema: {e}")
|
||||
raise SystemExit(1)
|
||||
except json.JSONDecodeError:
|
||||
print("Error: Invalid JSON received from text-generation-router print-schema")
|
||||
raise SystemExit(1)
|
||||
|
||||
|
||||
def check_openapi(check: bool):
|
||||
new_openapi_data = get_openapi_schema()
|
||||
filename = "docs/openapi.json"
|
||||
tmp_filename = "openapi_tmp.json"
|
||||
|
||||
with open(tmp_filename, "w") as f:
|
||||
json.dump(new_openapi_data, f, indent=2)
|
||||
|
||||
if check:
|
||||
diff = subprocess.run(
|
||||
[
|
||||
"diff",
|
||||
# allow for trailing whitespace since it's not significant
|
||||
# and the precommit hook will remove it
|
||||
"--ignore-trailing-space",
|
||||
tmp_filename,
|
||||
filename,
|
||||
],
|
||||
capture_output=True,
|
||||
).stdout.decode()
|
||||
os.remove(tmp_filename)
|
||||
|
||||
if diff:
|
||||
print(diff)
|
||||
raise Exception(
|
||||
"OpenAPI documentation is not up-to-date, run `python update_doc.py` in order to update it"
|
||||
)
|
||||
|
||||
return True
|
||||
else:
|
||||
os.rename(tmp_filename, filename)
|
||||
print("OpenAPI documentation updated.")
|
||||
return True
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("--check", action="store_true")
|
||||
|
|
@ -130,6 +179,7 @@ def main():
|
|||
|
||||
check_cli(args.check)
|
||||
check_supported_models(args.check)
|
||||
check_openapi(args.check)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
|
|
|||
Loading…
Reference in New Issue