- Upgrade @ai-sdk/azure from ^2.0.6 to ^3.0.26
- v3 defaults provider(id) to Responses API (works for all models)
- v2 defaulted to Chat Completions, breaking codex models
- Add useDeploymentBasedUrls: true to createAzure()
- Produces /deployments/{id}/{path} URLs (universally compatible)
- Without it, SDK uses /v1/{path} which only works on AI Foundry resources
* refactor: migrate baseten provider to AI SDK
* refactor(baseten): migrate to native @ai-sdk/baseten package
Replace OpenAICompatibleHandler with dedicated @ai-sdk/baseten package,
following the same pattern used by other native AI SDK providers (groq,
deepseek, etc.). This uses createBaseten() for provider initialization
and extends BaseProvider directly instead of the generic OpenAI-compatible
handler.
* feat: migrate Bedrock provider to AI SDK
Replace the raw AWS SDK (@aws-sdk/client-bedrock-runtime) Bedrock handler
with the Vercel AI SDK (@ai-sdk/amazon-bedrock). Reduces provider from
1,633 lines to 575 lines (65% reduction).
Key changes:
- Use streamText()/generateText() instead of ConverseStreamCommand/ConverseCommand
- Use createAmazonBedrock() with native auth (access key, secret, session,
profile via credentialProvider, API key, VPC endpoint as baseURL)
- Reasoning config via providerOptions.bedrock.reasoningConfig
- Anthropic beta headers via providerOptions.bedrock.anthropicBeta
- Thinking signature captured from providerMetadata.bedrock.signature
on reasoning-delta stream events
- Thinking signature round-tripped via providerOptions.bedrock.signature
on reasoning parts in convertToAiSdkMessages()
- Redacted thinking captured from providerMetadata.bedrock.redactedData
- isAiSdkProvider() returns true for reasoning block preservation
- Keep: getModel, ARN parsing, cross-region inference, cost calculation,
service tier pricing, 1M context beta
Tests: 83 tests skipped (mock old AWS SDK internals, need rewrite for
AI SDK mocking). 106 tests pass. 0 tests fail.
* fix: address review feedback for Bedrock AI SDK migration
- Wire usePromptCache into AI SDK via providerOptions.bedrock.cachePoint
on system prompt and last two user messages
- Remove debug logger.info that fires on every stream event with
providerMetadata
- Tighten isThrottlingError to match 'rate limit' instead of broad
'rate'/'limit' substrings that false-positive on context length errors
- Use shared handleAiSdkError utility for consistent error handling
with status code preservation for retry logic
* fix: bedrock AI SDK migration - fix usage metrics, rewrite tests, remove dead code
- Fix reasoningTokens always 0 (usage.details?.reasoningTokens → usage.reasoningTokens)
- Fix cacheReadInputTokens always 0 (read from usage.inputTokenDetails instead of providerMetadata)
- Fix invokedModelId not extracted for prompt router cost calculation
- Rewrite all 6 skipped bedrock test suites for AI SDK mocking pattern (140 tests pass)
- Remove dead code: bedrock-converse-format.ts, cache-strategy/ (6 files, ~2700 lines)
* chore: remove dead @anthropic-ai/bedrock-sdk dep and stale AWS SDK mocks
* chore: update pnpm-lock.yaml after removing @anthropic-ai/bedrock-sdk
* fix: compute cache point indices from original Anthropic messages before AI SDK conversion
The previous approach naively targeted the last 2 user messages in the
post-conversion AI SDK array, but convertToAiSdkMessages() splits user
messages containing tool_results into separate tool + user messages,
causing cache points to land on the wrong messages (tiny text fragments
instead of the intended meaty user turns).
Now we identify the last 2 user messages in the original Anthropic
message array (matching the Anthropic provider's caching strategy) and
build a parallel-walk mapping to apply cachePoint to the correct
corresponding AI SDK message.
* perf: optimize prompt caching with 3-point message strategy + anchor for 20-block window
Previous approach only cached the last 2 user messages (using 2 of 4
available cache checkpoints for messages). This left significant cache
savings on the table for longer conversations.
New strategy uses up to 3 message cache points (+ 1 system = 4 total):
- Last user message: write to cache for next request
- Second-to-last user message: read from cache for current request
- Anchor message at ~1/3 position: ensures the 20-block lookback window
from the second-to-last breakpoint hits a stable cache entry, covering
all assistant/tool messages in the middle of the conversation
Also extracted the parallel-walk mapping logic into a reusable
applyCachePointsToAiSdkMessages() helper method.
Industry benchmarks show 70-95% token cache rates are achievable;
this change should significantly improve our 39% baseline for longer
multi-turn conversations.
* chore: remove stale bedrock-sdk external, fix arnInfo property name, remove unused exports
---------
Co-authored-by: daniel-lxs <ricciodaniel98@gmail.com>
* changeset version bump
* Update CHANGELOG for version 3.47.3
Updated version number and removed redundant patch changes for 3.47.3.
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Matt Rubens <mrubens@users.noreply.github.com>
* changeset version bump
* Update CHANGELOG for version 3.47.2
Updated version number and added patch changes for 3.47.2.
* Update CHANGELOG for version 3.47.1
Updated changelog for version 3.47.1 with fixes and cleanup.
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Matt Rubens <mrubens@users.noreply.github.com>
* changeset version bump
* Update CHANGELOG for version 3.47.1
Updated changelog for version 3.47.1 with patch changes.
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: John Richmond <5629+jr@users.noreply.github.com>
* changeset version bump
* Update CHANGELOG for version 3.47.0 release
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Matt Rubens <mrubens@users.noreply.github.com>
* feat: migrate Gemini and Vertex providers to AI SDK
- Migrate GeminiHandler from @google/genai to @ai-sdk/google
- Create standalone VertexHandler using @ai-sdk/google-vertex
- Use shared AI SDK utilities (streamText, generateText, convertToAiSdkMessages)
- Support thinkingConfig via providerOptions.google.thinkingConfig
- Support Google Search and URL Context grounding tools
- Preserve cost calculation with tiered pricing
- Remove gemini-format.ts (AI SDK handles message conversion)
EXT-643
* fix: remove unused import and implement allowedFunctionNames tool filtering
- Remove unused handleAiSdkError import from gemini.ts
- Implement tool filtering based on allowedFunctionNames in both
GeminiHandler and VertexHandler createMessage methods
- Filter tools before converting to AI SDK format to restrict
model access to only allowed functions
