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Adding definitions for the Chat API (#26038)
* Adding definitions for the Chat API * renamed dir * adding placeholder docs to make generators happy * python options * ts config * Adding auth. Marking props as optional. * more fixes * adding client.tsp * more optional stuff. * templated interface * adding route * updated generic argument type * warnings * rollback package.json * adding examples + tspconfig update * prettier * updating based on spec * Updated namespace. * rename * Updating documentation for models and operations. Removing references out-of-scope features. * typo * Adding autorest generation. * fixes * more openapi fixes * feedback * updating example * updating docs * updating js package name * using RpcOperation * rollback to using Foundations.Operation * updating example * updated template parameter names. * regenerated openapi * removing usage of azure-core + removing api-version param. * adding oauth * feedback * Update specification/machinelearning/Azure.AI.ChatProtocol/tspconfig.yaml * Update specification/machinelearning/Azure.AI.ChatProtocol/tspconfig.yaml * java config * Updating route. Wire to use camelCase. * missing field * path * path * Revert "path" This reverts commit f663ecc. * adding back route param * Adding message kind definition * renaming model * removing template parameters to work around emitter issue. * updating sample * updates * discriminator for streaming deltas. * update samples * typo * forcing ChatRole to be public. --------- Co-authored-by: Mary Gao <[email protected]> Co-authored-by: Weidong Xu <[email protected]>
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‎specification/machinelearning/Azure.AI.ChatProtocol/client.tsp

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import "@azure-tools/typespec-client-generator-core";
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import "./main.tsp";
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using Azure.ClientGenerator.Core;
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@@access(Azure.AI.ChatProtocol.Chat.createStreaming, Access.internal, "csharp");
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@@access(Azure.AI.ChatProtocol.ChatRole, Access.public, "csharp");

‎specification/machinelearning/Azure.AI.ChatProtocol/examples/2023-10-01-preview/create.json

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{
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"operationId": "Chat_Create",
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"title": "Creates a chat completion for the provided prompt using streaming.",
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"parameters": {
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"endpoint": "{endpoint}",
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"operationRoute": "chat",
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"body": {
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"messages": [
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{
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"kind": "text",
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"content": "Tell me a joke",
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"role": "user"
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}
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],
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"stream": false
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}
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},
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"responses": {
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"200": {
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"body": {
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"choices": [
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{
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"index": 0,
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"message": {
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"kind": "text",
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"content": "Why did the tomato turn red?\nBecause it saw the salad dressing!",
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"role": "assistant",
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"sessionState": {
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"active_skill": "QnA"
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}
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},
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"context": {
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"function_call": "none"
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},
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"sessionState": {
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"session_cookie": "d2d1b2c3-4a5b-6c7d-8e9f-0a1b2c3d4e5f"
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},
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"finishReason": "stop"
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}
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]
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}
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}
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}
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}

‎specification/machinelearning/Azure.AI.ChatProtocol/examples/2023-10-01-preview/create_streaming.json

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{
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"operationId": "Chat_CreateStreaming",
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"title": "Creates a chat completion for the provided prompt using streaming.",
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"parameters": {
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"endpoint": "{endpoint}",
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"operationRoute": "chat",
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"body": {
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"messages": [
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{
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"kind": "text",
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"content": "Tell me a joke",
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"role": "user"
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}
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],
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"stream": true
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}
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},
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"responses": {
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"200": {
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"body": {
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"choices": [
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{
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"index": 0,
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"delta": {
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"kind": "text",
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"content": "Why did the tomato turn red?\nBecause it saw the salad dressing!",
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"role": "assistant",
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"sessionState": {
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"active_skill": "QnA"
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}
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},
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"context": {
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"function_call": "none"
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},
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"sessionState": {
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"session_cookie": "d2d1b2c3-4a5b-6c7d-8e9f-0a1b2c3d4e5f"
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},
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"finishReason": "stop"
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}
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]
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}
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}
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}
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}

‎specification/machinelearning/Azure.AI.ChatProtocol/main.tsp

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import "@typespec/rest";
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import "@typespec/http";
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import "@typespec/versioning";
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import "./operations.tsp";
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using TypeSpec.Http;
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using TypeSpec.Versioning;
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#suppress "@azure-tools/typespec-azure-core/casing-style" "Using the AI acronym similar to what was done for OpenAI"
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@doc("Azure APIs for the Azure Chat protocol.")
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@service({
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title: "Azure ML Chat",
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})
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@useAuth(
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ApiKeyAuth<ApiKeyLocation.header, "api-key"> | OAuth2Auth<[
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{
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type: OAuth2FlowType.implicit,
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authorizationUrl: "https://login.microsoftonline.com/common/oauth2/v2.0/authorize",
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scopes: [],
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}
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]>
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)
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@server(
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"{endpoint}",
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"Azure Chat Protocol APIs",
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{
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endpoint: string,
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}
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)
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@versioned(APIVersion)
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namespace Azure.AI.ChatProtocol;
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#suppress "@azure-tools/typespec-azure-core/documentation-required" "https://github.com/Azure/typespec-azure/issues/3107"
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enum APIVersion {
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v20231001Preview: "2023-10-01-preview",
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}

‎specification/machinelearning/Azure.AI.ChatProtocol/models/blocking.tsp

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import "./common.tsp";
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namespace Azure.AI.ChatProtocol;
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@doc("The representation of a single generated completion.")
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model ChatChoice {
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@doc("The index of the of the chat choice, relative to the other choices in the same completion.")
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index: safeint;
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@doc("The chat message for a given chat completion.")
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message: ChatMessage;
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...StateProperty;
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...ContextProperty;
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@doc("The reason this chat completion completed its generation.")
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finishReason: FinishReason;
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}
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@doc("Representation of the response to a chat completion request.")
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model ChatCompletion {
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@doc("The collection of generated completions.")
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choices: ChatChoice[];
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}
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@doc("The configuration for a chat completion request.")
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model ChatCompletionOptions {
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@doc("The collection of context messages associated with this completion request.")
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messages: ChatMessage[];
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@doc("Indicates whether the completion is a streaming or non-streaming completion.")
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stream: false;
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...StateProperty;
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...ContextProperty;
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}

‎specification/machinelearning/Azure.AI.ChatProtocol/models/common.tsp

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import "@typespec/http";
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namespace Azure.AI.ChatProtocol;
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using TypeSpec.Http;
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@doc("Representation of the reason why a chat session has finished processing.")
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enum FinishReason {
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@doc("Completion ended normally.")
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stopped: "stop",
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@doc("The completion exhausted available tokens before generation could complete.")
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tokenLimitReached: "length",
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}
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@doc("A representation of the intended purpose of a message.")
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enum ChatRole {
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@doc("The role that provides input to the completion.")
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user: "user",
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@doc("The role that instructs or configures the behavior of the assistant.")
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system: "system",
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@doc("The role that provides responses to the system-instructed, user-prompted input.")
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assistant: "assistant",
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}
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@doc("A property that represents backend-specific context or arguments.")
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model ContextProperty {
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#suppress "@azure-tools/typespec-azure-core/bad-record-type" "Protocol defines the type as Record<any>"
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@doc("""
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Context allows the chat app to receive extra parameters from the client, such as temperature, functions, or
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customer_info. These parameters are specific to the chat app and not understood by the generic clients.
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""")
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context?: Record<unknown>;
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}
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@doc("A property that represents backend-specific information for the tracking of a session.")
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model StateProperty {
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#suppress "@azure-tools/typespec-azure-core/no-unknown" "The protocol defines these as any (object/scalar) for now"
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@doc("""
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Field that allows the chat app to store and retrieve data, the structure of such data is dependant on the backend
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being used. The client must send back the data in this field unchanged in subsequent requests, until the chat app
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sends a new one. The data in this field can be used to implement stateful services, such as remembering previous
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conversations or user preferences.
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""")
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sessionState?: unknown;
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}
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@doc("Identifies the type of a message.")
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enum MessageKind {
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@doc("The message context is text.")
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text: "text",
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}
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@doc("A single, role-attributed message within a chat completion interaction.")
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@discriminator("kind")
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model ChatMessage {
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@doc("The type of the message. If not specified, the message is assumed to be text.")
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kind: MessageKind;
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@doc("The role associated with the message.")
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role: ChatRole;
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...StateProperty;
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}
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@doc("A single, role-attributed text message within a chat completion interaction.")
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model TextChatMessage extends ChatMessage {
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@doc("The type of the message.")
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kind: MessageKind.text;
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@doc("The text associated with the message.")
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content: string;
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}
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@doc("Parameter that describes the route of the operation to be performed.")
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model OperationRouteParam {
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@doc("The route where the endpoint exposes the chat operations.")
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@path
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operationRoute: string = "chat";
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}

‎specification/machinelearning/Azure.AI.ChatProtocol/models/streaming.tsp

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import "./common.tsp";
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namespace Azure.AI.ChatProtocol;
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@doc("The representation of a delta message received in a streaming completion.")
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@discriminator("kind")
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model ChatMessageDelta {
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@doc("The type of the message. If not specified, the message is assumed to be text.")
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kind: MessageKind;
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@doc("The role associated with the message.")
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role?: ChatRole;
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...StateProperty;
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}
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@doc("The representation of a delta text message received in a streaming completion.")
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model TextChatMessageDelta extends ChatMessageDelta {
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@doc("The type of the message.")
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kind: MessageKind.text;
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@doc("An incremental part of the text associated with the message.")
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content?: string;
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}
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@doc("The representation of an incremental choice received in a streaming completion.")
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model ChoiceDelta {
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@doc("The index of the of the chat choice, relative to the other choices in the same completion.")
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index: safeint;
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@doc("The partial message received for this choice.")
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delta: ChatMessageDelta;
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...StateProperty;
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...ContextProperty;
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@doc("The reason this chat completion completed its generation.")
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finishReason?: FinishReason;
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}
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@doc("A single response to a streaming completion request.")
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model ChatCompletionChunk {
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@doc("The collection of choice deltas received in this chunk.")
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choices: ChoiceDelta[];
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}
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@doc("The configuration for a streaming chat completion request.")
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model StreamingChatCompletionOptions {
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@doc("The collection of context messages associated with this completion request.")
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messages: ChatMessage[];
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@doc("Indicates whether the completion is a streaming or non-streaming completion.")
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stream: true;
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...StateProperty;
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...ContextProperty;
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}

‎specification/machinelearning/Azure.AI.ChatProtocol/operations.tsp

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import "@typespec/http";
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import "./models/common.tsp";
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import "./models/blocking.tsp";
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import "./models/streaming.tsp";
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namespace Azure.AI.ChatProtocol;
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using TypeSpec.Http;
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interface Chat {
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/* This operation returns a stream of objects in jsonl format. */
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#suppress "@azure-tools/typespec-azure-core/use-standard-operations" "Defining the operation in an Azure independent fashion"
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#suppress "@azure-tools/typespec-azure-core/operation-missing-api-version" "API version is not supported by the back end"
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@doc("Creates a new streaming chat completion.")
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@sharedRoute
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createStreaming(
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...StreamingChatCompletionOptions,
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...OperationRouteParam,
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): ChatCompletionChunk;
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#suppress "@azure-tools/typespec-azure-core/use-standard-operations" "Defining the operation in an Azure independent fashion"
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#suppress "@azure-tools/typespec-azure-core/operation-missing-api-version" "API version is not supported by the back end"
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@doc("Creates a new chat completion.")
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@sharedRoute
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create(...ChatCompletionOptions, ...OperationRouteParam): ChatCompletion;
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}

‎specification/machinelearning/Azure.AI.ChatProtocol/tspconfig.yaml

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parameters:
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"service-dir":
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default: "sdk/machinelearning"
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emit:
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- "@azure-tools/typespec-autorest"
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# - "@typespec/openapi3"
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linter:
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extends:
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- "@azure-tools/typespec-azure-core/all"
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options:
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"@azure-tools/typespec-autorest":
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emitter-output-dir: "{project-root}/../"
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output-file: "{azure-resource-provider-folder}/Azure.AI.ChatProtocol/{version-status}/{version}/generated.json"
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azure-resource-provider-folder: "data-plane"
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examples-directory: examples
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omit-unreachable-types: true
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"@azure-tools/typespec-csharp":
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package-dir: "Azure.AI.ChatProtocol"
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namespace: "Azure.AI.ChatProtocol"
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clear-output-folder: true
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model-namespace: false
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"@azure-tools/typespec-python":
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package-dir: "azure-ai-chatprotocol"
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package-name: "{package-dir}"
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package-mode: dataplane
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"@azure-tools/typespec-ts":
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package-dir: "ai-chat-protocol"
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isModularLibrary: true
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packageDetails:
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name: "@azure/ai-chat-protocol"
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"@azure-tools/typespec-java":
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package-dir: "azure-ai-chatprotocol"
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namespace: "com.azure.ai.chatprotocol"

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