fix: resolve webpack runtime error in resolution search #740
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,111 @@ | ||
| import { getSelectedModel } from '@/lib/actions/users' | ||
| import { createOpenAI } from '@ai-sdk/openai' | ||
| import { createGoogleGenerativeAI } from '@ai-sdk/google' | ||
| import { createAmazonBedrock } from '@ai-sdk/amazon-bedrock' | ||
| import { createXai } from '@ai-sdk/xai' | ||
|
|
||
| export async function getModel(requireVision: boolean = false) { | ||
| const selectedModel = await getSelectedModel(); | ||
|
|
||
| const xaiApiKey = process.env.XAI_API_KEY; | ||
| const gemini3ProApiKey = process.env.GEMINI_3_PRO_API_KEY; | ||
| const awsAccessKeyId = process.env.AWS_ACCESS_KEY_ID; | ||
| const awsSecretAccessKey = process.env.AWS_SECRET_ACCESS_KEY; | ||
| const awsRegion = process.env.AWS_REGION; | ||
| const bedrockModelId = process.env.BEDROCK_MODEL_ID || 'anthropic.claude-3-5-sonnet-20241022-v2:0'; | ||
| const openaiApiKey = process.env.OPENAI_API_KEY; | ||
|
|
||
| if (selectedModel) { | ||
| switch (selectedModel) { | ||
| case 'Grok 4.2': | ||
| if (xaiApiKey) { | ||
| const xai = createXai({ | ||
| apiKey: xaiApiKey, | ||
| baseURL: 'https://api.x.ai/v1', | ||
| }); | ||
| try { | ||
| const modelId = requireVision ? 'grok-vision-beta' : 'grok-2-1212'; | ||
| return xai(modelId); | ||
| } catch (error) { | ||
| console.error('Selected model "Grok 4.2" is configured but failed to initialize.', error); | ||
| throw new Error('Failed to initialize selected model.'); | ||
| } | ||
| } else { | ||
| console.error('User selected "Grok 4.2" but XAI_API_KEY is not set.'); | ||
| throw new Error('Selected model is not configured.'); | ||
| } | ||
| case 'Gemini 3': | ||
| case 'Gemini 3.1 Pro': | ||
| if (gemini3ProApiKey) { | ||
| const google = createGoogleGenerativeAI({ | ||
| apiKey: gemini3ProApiKey, | ||
| }); | ||
| try { | ||
| return google('gemini-1.5-pro-latest'); | ||
| } catch (error) { | ||
| console.error('Selected model "Gemini 3.1 Pro" is configured but failed to initialize.', error); | ||
| throw new Error('Failed to initialize selected model.'); | ||
| } | ||
| } else { | ||
| console.error('User selected "Gemini 3.1 Pro" but GEMINI_3_PRO_API_KEY is not set.'); | ||
| throw new Error('Selected model is not configured.'); | ||
| } | ||
| case 'GPT-5.1': | ||
| if (openaiApiKey) { | ||
| const openai = createOpenAI({ | ||
| apiKey: openaiApiKey, | ||
| }); | ||
| return openai('gpt-4o'); | ||
| } else { | ||
| console.error('User selected "GPT-5.1" but OPENAI_API_KEY is not set.'); | ||
| throw new Error('Selected model is not configured.'); | ||
| } | ||
| } | ||
| } | ||
|
|
||
| // Default behavior: Grok -> Gemini -> Bedrock -> OpenAI | ||
| if (xaiApiKey) { | ||
| const xai = createXai({ | ||
| apiKey: xaiApiKey, | ||
| baseURL: 'https://api.x.ai/v1', | ||
| }); | ||
| try { | ||
| const modelId = requireVision ? 'grok-vision-beta' : 'grok-latest'; | ||
| return xai(modelId); | ||
| } catch (error) { | ||
| console.warn('xAI API unavailable, falling back to next provider:'); | ||
| } | ||
| } | ||
|
|
||
| if (gemini3ProApiKey) { | ||
| const google = createGoogleGenerativeAI({ | ||
| apiKey: gemini3ProApiKey, | ||
| }); | ||
| try { | ||
| return google('gemini-1.5-pro-latest'); | ||
| } catch (error) { | ||
| console.warn('Gemini 3.1 Pro API unavailable, falling back to next provider:', error); | ||
| } | ||
| } | ||
|
|
||
| if (awsAccessKeyId && awsSecretAccessKey) { | ||
| const bedrock = createAmazonBedrock({ | ||
| bedrockOptions: { | ||
| region: awsRegion, | ||
| credentials: { | ||
| accessKeyId: awsAccessKeyId, | ||
| secretAccessKey: awsSecretAccessKey, | ||
| }, | ||
| }, | ||
| }); | ||
| const model = bedrock(bedrockModelId, { | ||
| additionalModelRequestFields: { top_k: 350 }, | ||
| }); | ||
| return model; | ||
| } | ||
|
|
||
| const openai = createOpenAI({ | ||
| apiKey: openaiApiKey, | ||
| }); | ||
| return openai('gpt-4o'); | ||
|
Comment on lines
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Contributor
There was a problem hiding this comment. 🩺 Stability & Availability | 🟠 Major | 🏗️ Heavy lift 🧩 Analysis chain🏁 Script executed: #!/bin/bash
set -euo pipefail
echo "== file list =="
git ls-files lib/utils/server.ts
echo
echo "== file size =="
wc -l lib/utils/server.ts
echo
echo "== outline =="
ast-grep outline lib/utils/server.ts --view expanded
echo
echo "== relevant lines =="
sed -n '1,220p' lib/utils/server.ts | cat -n
echo
echo "== search for consumers of the returned model =="
rg -n "create[A-Za-z]+\\(|generateText\\(|streamObject\\(|return .*openai\\(|return .*google\\(|return .*xai\\(" lib -g '!**/dist/**' -g '!**/build/**'Repository: QueueLab/QCX Length of output: 6969 🏁 Script executed: #!/bin/bash
set -euo pipefail
echo "== getModel call sites =="
rg -n "\bgetModel\(" lib -g '!**/dist/**' -g '!**/build/**'
echo
echo "== AI SDK provider/generation docs lookup =="
python3 - <<'PY'
import urllib.request, urllib.parse, json, re
queries = [
"ai sdk provider factory returns model object generateText streamObject network request happens later",
"site:ai-sdk.dev createOpenAI model object generateText streamObject",
]
for q in queries:
print(f"\nQUERY: {q}")
PYRepository: QueueLab/QCX Length of output: 1264 🏁 Script executed: #!/bin/bash
set -euo pipefail
echo "== ai-sdk dependencies =="
rg -n '"`@ai-sdk/`|ai"' package.json pnpm-lock.yaml package-lock.json yarn.lock -g '!**/node_modules/**'
echo
echo "== provider factories in repo =="
rg -n "create(OpenAI|GoogleGenerativeAI|AmazonBedrock|Xai)\(" lib package.json -g '!**/node_modules/**'Repository: QueueLab/QCX Length of output: 684 🌐 Web query:
💡 Result: When you use factory functions like createOpenAI, createGoogleGenerativeAI, or createXai in the Vercel AI SDK, they do not initiate any network requests at the time of creation [1][2]. These functions simply return a provider instance—a configuration object containing the settings (such as API keys, base URLs, and headers) and the logic required to instantiate specific language models later [1][3][2]. The network request only occurs later, when you actually use the returned language model object in a function such as generateText or streamText [4][5][6]. At that point, the SDK uses the configuration defined in your provider instance to construct and execute the API call to the respective AI service [1][3][7]. Citations:
Move fallback selection to the generation path. 🤖 Prompt for AI Agents |
||
| } | ||
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🎯 Functional Correctness | 🟠 Major | ⚡ Quick win
Honor the model selected by the user.
These branches silently substitute older models:
Grok 4.2returnsgrok-2-1212, both Gemini 3 choices return Gemini 1.5, andGPT-5.1returns GPT-4o. Align the persisted option names with the actual model IDs or reject unsupported selections instead of returning a different model.🤖 Prompt for AI Agents