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feat: update Azure AI handler and model picker for improved configuration and error handling

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pacnpal
2025-02-02 20:29:31 -05:00
parent 703cda7678
commit 53e307c8f3
3 changed files with 143 additions and 43 deletions
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65
src/api/providers/azure-ai.ts
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@@ -2,13 +2,12 @@ import { Anthropic } from "@anthropic-ai/sdk"
import ModelClient from "@azure-rest/ai-inference"
import { isUnexpected } from "@azure-rest/ai-inference"
import { AzureKeyCredential } from "@azure/core-auth"
import { ApiHandlerOptions, ModelInfo, AzureDeploymentConfig } from "../../shared/api"
import { ApiHandlerOptions, ModelInfo, AzureDeploymentConfig, azureAiModelInfoSaneDefaults } from "../../shared/api"
import { ApiHandler, SingleCompletionHandler } from "../index"
import { convertToOpenAiMessages } from "../transform/openai-format"
import { ApiStream } from "../transform/stream"
const DEFAULT_API_VERSION = "2024-02-15-preview"
const DEFAULT_MAX_TOKENS = 4096
const DEFAULT_API_VERSION = "2024-05-01-preview"
export class AzureAiHandler implements ApiHandler, SingleCompletionHandler {
private options: ApiHandlerOptions
@@ -32,7 +31,7 @@ export class AzureAiHandler implements ApiHandler, SingleCompletionHandler {
const modelId = this.options.apiModelId
if (!modelId) {
return {
name: "gpt-35-turbo", // Default deployment name if none specified
name: "default",
apiVersion: DEFAULT_API_VERSION,
}
}
@@ -46,7 +45,6 @@ export class AzureAiHandler implements ApiHandler, SingleCompletionHandler {
}
}
// If no custom config, use model ID as deployment name
return {
name: modelId,
apiVersion: DEFAULT_API_VERSION,
@@ -65,14 +63,17 @@ export class AzureAiHandler implements ApiHandler, SingleCompletionHandler {
messages: chatMessages,
temperature: 0,
stream: true,
max_tokens: DEFAULT_MAX_TOKENS,
max_tokens: azureAiModelInfoSaneDefaults.maxTokens,
response_format: { type: "text" },
},
headers: deployment.modelMeshName
? {
"x-ms-model-mesh-model-name": deployment.modelMeshName,
}
: undefined,
headers: {
"extra-parameters": "drop",
...(deployment.modelMeshName
? {
"azureml-model-deployment": deployment.modelMeshName,
}
: {}),
},
})
.asNodeStream()
@@ -118,13 +119,14 @@ export class AzureAiHandler implements ApiHandler, SingleCompletionHandler {
} catch (error) {
if (error instanceof Error) {
// Handle Azure-specific error cases
if ("status" in error && error.status === 429) {
if (isUnexpected(error) && error.status === 429) {
throw new Error("Azure AI rate limit exceeded. Please try again later.")
}
if ("status" in error && error.status === 400) {
const azureError = error as any
if (azureError.body?.error?.code === "ContentFilterError") {
throw new Error("Content was flagged by Azure AI content safety filters")
if (isUnexpected(error)) {
// Use proper Model Inference error handling
const message = error.body?.error?.message || error.message
if (error.status === 422) {
throw new Error(`Request validation failed: ${message}`)
}
}
throw new Error(`Azure AI error: ${error.message}`)
@@ -135,12 +137,8 @@ export class AzureAiHandler implements ApiHandler, SingleCompletionHandler {
getModel(): { id: string; info: ModelInfo } {
return {
id: this.options.apiModelId || "gpt-35-turbo",
info: {
maxTokens: DEFAULT_MAX_TOKENS,
contextWindow: 16385, // Conservative default
supportsPromptCache: true,
},
id: this.options.apiModelId || "default",
info: azureAiModelInfoSaneDefaults,
}
}
@@ -153,11 +151,14 @@ export class AzureAiHandler implements ApiHandler, SingleCompletionHandler {
temperature: 0,
response_format: { type: "text" },
},
headers: deployment.modelMeshName
? {
"x-ms-model-mesh-model-name": deployment.modelMeshName,
}
: undefined,
headers: {
"extra-parameters": "drop",
...(deployment.modelMeshName
? {
"azureml-model-deployment": deployment.modelMeshName,
}
: {}),
},
})
if (isUnexpected(response)) {
@@ -168,13 +169,13 @@ export class AzureAiHandler implements ApiHandler, SingleCompletionHandler {
} catch (error) {
if (error instanceof Error) {
// Handle Azure-specific error cases
if ("status" in error && error.status === 429) {
if (isUnexpected(error) && error.status === 429) {
throw new Error("Azure AI rate limit exceeded. Please try again later.")
}
if ("status" in error && error.status === 400) {
const azureError = error as any
if (azureError.body?.error?.code === "ContentFilterError") {
throw new Error("Content was flagged by Azure AI content safety filters")
if (isUnexpected(error)) {
const message = error.body?.error?.message || error.message
if (error.status === 422) {
throw new Error(`Request validation failed: ${message}`)
}
}
throw new Error(`Azure AI completion error: ${error.message}`)