BrowserStack AI Evals
Integrations

Supported Integrations

LLM providers, frameworks, and vector stores auto-instrumented by the SDK, by language.

Supported Integrations

The SDK auto-instruments the libraries below — calls are captured as traces with no manual trace() / generation() code. Support varies by language and reflects what each SDK hooks at runtime.

To enable any of these, install the library and initialize the SDK first — see Auto-Instrumentation. Provider-specific guides live under Integrations.

Legend: ✅ Supported · — Not available for this language. Newer integrations require a recent SDK version. Regardless of this table, you can record any provider's calls with the manual tracing API.

LLM Providers

ProviderTypeScriptPythonJava
OpenAI
Anthropic
Azure OpenAI 1
Google Gemini (AI Studio) 2
Vertex AI
Amazon Bedrock
LiteLLM

1 Traced via the OpenAI client configured against an Azure endpoint. 2 Package differs by language: @google/genai (Node), google-generativeai (Python), google-genai (Java).

Frameworks & Agent Frameworks

FrameworkTypeScriptPythonJava
LangChain (incl. LangGraph) 3
LangChain4j
Spring AI
LlamaIndex
Vercel AI SDK
Google ADK
OpenAI Agents
Strands Agents
Claude Agent SDK
Mastra
Amazon Bedrock AgentCore
CrewAI
AutoGen
DSPy
Pydantic AI
AgentScope
ModelScope Agent
Microsoft Agent Framework

3 On Java, use LangChain4j (listed separately).

Vector Stores

StoreTypeScriptPythonJava
Pinecone
pgvector 4

4 On Node, both the pg and postgres (postgres.js) drivers are instrumented.

Other

IntegrationTypeScriptPythonJava
Hugging Face
HTTP web frameworks 5

5 Python instruments Flask, FastAPI, Django, and Starlette so LLM calls nest under the incoming request. See HTTP Instrumentation.

Provider guides

See also