feat(cerebras): add chat language model provider#15420
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## Background #15349 this is a follow up to #15416. cerebras models could return a valid structured JSON answer, like {"result":"2026"}, while also marking the response as `tool_calls` and repeating a tool call in the same response. The AI SDK interpreted that as “keep calling tools,” so the loop continued until stopWhen was hit. Because the final step still had finish reason `tool-calls`, `result.output` was never parsed and threw `NoOutputGeneratedError` ## Summary - Added a CerebrasChatLanguageModel wrapper around the OpenAI-compatible chat model - For structured JSON output calls only, when cerebras returns non-empty text with raw finish reason `tool_calls`, we treat it as the final structured answer - In that narrow case, we normalize the finish reason to `stop` and drop the stray repeated tool-call part - Real tool-call turns without text are still preserved and executed normally what would have been a bug fix was treated as an opportunity to handle cerebras quirks specifically ## Manual Verification verified by running the repro: ```ts import { NoOutputGeneratedError, Output, isStepCount, tool, ToolLoopAgent } from "ai"; import z from "zod"; import { cerebras } from "@ai-sdk/cerebras"; import { run } from '../../lib/run'; run(async () => { const agent = new ToolLoopAgent({ instructions: "Use the required structured output. For simple arithmetic you may answer directly.", model: cerebras("zai-glm-4.7"), tools: { nonUsefulTool: tool({ description: "A non-useful tool that returns a magic number", inputSchema: z.object({}), execute: () => { return 2026; }, }), }, output: Output.object({ schema: z.object({ result: z.string() }), }), stopWhen: isStepCount(5), }); const result = await agent.generate({ prompt: "what is the magic number?", }); console.log( 'steps:', JSON.stringify( result.steps.map(step => ({ finishReason: step.finishReason, text: step.text, toolCalls: step.toolCalls.map(toolCall => ({ toolName: toolCall.toolName, input: toolCall.input, })), })), null, 2, ), ); try { console.log(result.output); } catch (cause) { if (NoOutputGeneratedError.isInstance(cause)) { console.error( "Structured output missing (last step did not yield valid JSON).", "finishReason:", result.finishReason, "lastText:", JSON.stringify(result.text), ); throw cause; } throw cause; } }); ``` ## Checklist - [x] All commits are signed (PRs with unsigned commits cannot be merged) - [x] Tests have been added / updated (for bug fixes / features) - [ ] Documentation has been added / updated (for bug fixes / features) - [x] A _patch_ changeset for relevant packages has been added (for bug fixes / features - run `pnpm changeset` in the project root) - [x] I have reviewed this pull request (self-review) ## Related Issues fixes #15349 --------- Co-authored-by: Gregor Martynus <39992+gr2m@users.noreply.github.com>
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## Background #15349 this is a follow up to #15416. cerebras models could return a valid structured JSON answer, like {"result":"2026"}, while also marking the response as `tool_calls` and repeating a tool call in the same response. The AI SDK interpreted that as “keep calling tools,” so the loop continued until stopWhen was hit. Because the final step still had finish reason `tool-calls`, `result.output` was never parsed and threw `NoOutputGeneratedError` ## Summary - Added a CerebrasChatLanguageModel wrapper around the OpenAI-compatible chat model - For structured JSON output calls only, when cerebras returns non-empty text with raw finish reason `tool_calls`, we treat it as the final structured answer - In that narrow case, we normalize the finish reason to `stop` and drop the stray repeated tool-call part - Real tool-call turns without text are still preserved and executed normally what would have been a bug fix was treated as an opportunity to handle cerebras quirks specifically ## Manual Verification verified by running the repro: ```ts import { NoOutputGeneratedError, Output, isStepCount, tool, ToolLoopAgent } from "ai"; import z from "zod"; import { cerebras } from "@ai-sdk/cerebras"; import { run } from '../../lib/run'; run(async () => { const agent = new ToolLoopAgent({ instructions: "Use the required structured output. For simple arithmetic you may answer directly.", model: cerebras("zai-glm-4.7"), tools: { nonUsefulTool: tool({ description: "A non-useful tool that returns a magic number", inputSchema: z.object({}), execute: () => { return 2026; }, }), }, output: Output.object({ schema: z.object({ result: z.string() }), }), stopWhen: isStepCount(5), }); const result = await agent.generate({ prompt: "what is the magic number?", }); console.log( 'steps:', JSON.stringify( result.steps.map(step => ({ finishReason: step.finishReason, text: step.text, toolCalls: step.toolCalls.map(toolCall => ({ toolName: toolCall.toolName, input: toolCall.input, })), })), null, 2, ), ); try { console.log(result.output); } catch (cause) { if (NoOutputGeneratedError.isInstance(cause)) { console.error( "Structured output missing (last step did not yield valid JSON).", "finishReason:", result.finishReason, "lastText:", JSON.stringify(result.text), ); throw cause; } throw cause; } }); ``` ## Checklist - [x] All commits are signed (PRs with unsigned commits cannot be merged) - [x] Tests have been added / updated (for bug fixes / features) - [ ] Documentation has been added / updated (for bug fixes / features) - [x] A _patch_ changeset for relevant packages has been added (for bug fixes / features - run `pnpm changeset` in the project root) - [x] I have reviewed this pull request (self-review) ## Related Issues fixes #15349 --------- Co-authored-by: Gregor Martynus <39992+gr2m@users.noreply.github.com>
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This is an automated backport of #15420 to the release-v6.0 branch. FYI @aayush-kapoor --------- Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: Gregor Martynus <39992+gr2m@users.noreply.github.com> Co-authored-by: Aayush Kapoor <aayushkapoor34@gmail.com>
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…15427) ## Background observed in #15420; when creating a new language model file, it is now important to account for workflow serialization and deserialization (serde). this was highlighted by the vercel agent in #15420 (comment) so it makes sense to include it as rule ## Summary added a new rule that which ensures provider language model files must import the helpers/symbols needed to serialize and deserialize model instances across workflow step boundaries ## Manual Verification na ## Checklist - [x] All commits are signed (PRs with unsigned commits cannot be merged) - [x] Tests have been added / updated (for bug fixes / features) - [ ] Documentation has been added / updated (for bug fixes / features) - [x] A _patch_ changeset for relevant packages has been added (for bug fixes / features - run `pnpm changeset` in the project root) - [x] I have reviewed this pull request (self-review) --------- Co-authored-by: Felix Arntz <felix.arntz@vercel.com>
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Background
#15349
this is a follow up to #15416.
cerebras models could return a valid structured JSON answer, like {"result":"2026"}, while also marking the response as
tool_callsand repeating a tool call in the same response. The AI SDK interpreted that as “keep calling tools,” so the loop continued until stopWhen was hit. Because the final step still had finish reasontool-calls,result.outputwas never parsed and threwNoOutputGeneratedErrorSummary
tool_calls, we treat it as the final structured answerstopand drop the stray repeated tool-call partwhat would have been a bug fix was treated as an opportunity to handle cerebras quirks specifically
Manual Verification
verified by running the repro:
Checklist
pnpm changesetin the project root)Related Issues
fixes #15349