chore: update auto gen SDK #1300
Merged
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
hassiebp
reviewed
Aug 15, 2025
hassiebp
reviewed
Aug 15, 2025
fa5346c
into
nimar/lfe-6153-generalized-graphs-python
1 check passed
nimarb
added a commit
that referenced
this pull request
Aug 22, 2025
* init commit * Use as_type * clean * cleanup * cleanup * todo clarifty case sensitivity * format * revert * add test * lower case * fix lint * format * types * cleanup * fix test * update * update * fix cases * fix some more types * update SDK * fix types * add type checing isntructions * restore * restore 2 * restore * restore 3 * simplify * simplift * simplify * fix case * rearrange spans * restrucure a bit * cleanup * make mypy happy * py3.9 compat * happy mypy * cleanup * a bit more clean * cleanup * overload all the things * overload * rename spanwrapper to observation wrapper * don't update events * fix test * fix span * fix test * langchain * formatting * add langchain test * add core test * cleanup * add deprecation warning * fix types * change generation like and span like * fix * test format * from review * format * add generation-like test * chore: update auto gen SDK (#1300) * unrelated changes to generated sdk * also readme * reset * revert * revert * fix lint * fix tests * embedding correct attrs * fix typing * fix bug * fix mypy
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Important
This PR updates the Langfuse Python client with new LLM connections management and enhanced annotation queues, adding new modules, models, and client methods for both sync and async operations.
llm_connectionsfor managing LLM provider connections (OpenAI, Anthropic, Azure, etc.).LlmAdapter,LlmConnection,PaginatedLlmConnections,UpsertLlmConnectionRequestinllm_connections/types.list()andupsert()methods inllm_connections/client.pyfor sync and async clients.CreateAnnotationQueueRequest,AnnotationQueueAssignmentRequest,CreateAnnotationQueueAssignmentResponse,DeleteAnnotationQueueAssignmentResponseinannotation_queues/types.create_queue(),create_queue_assignment(),delete_queue_assignment()inannotation_queues/client.pyfor sync and async clients.MapValueincommons/types/map_value.pyto removefloattype.This description was created by
for 3469dcd. You can customize this summary. It will automatically update as commits are pushed.
Disclaimer: Experimental PR review
Greptile Summary
This PR represents a comprehensive auto-generated SDK update that adds significant new functionality to the Langfuse Python client. The changes introduce two major feature areas:
1. LLM Connections Management: A complete new module (
langfuse/api/resources/llm_connections/) has been added to enable users to manage connections to various LLM providers (OpenAI, Anthropic, Azure, Bedrock, Google Vertex AI, and Google AI Studio). This includes models for connection configuration, pagination, and upsert operations, along with both sync and async client implementations.2. Enhanced Annotation Queues: The existing annotation queues functionality has been expanded with new capabilities for queue creation and user assignment management. This includes new request/response models for creating annotation queues directly and managing user assignments within queues.
3. Observation Type Expansion: The
observedecorator has been enhanced to support specialized observation types (Agent, Tool, Chain, Retriever, Evaluator, Embedding, Guardrail) beyond the existing Span and Generation types, enabling more granular categorization of AI operations.The changes follow the established auto-generated patterns throughout the codebase, maintaining consistency in error handling, serialization, and API client structure. All new functionality is exposed through both synchronous and asynchronous client interfaces, and comprehensive API reference documentation has been updated to reflect the new capabilities.
Confidence score: 2/5
langfuse/api/tests/utils/test_http_client.py,langfuse/api/tests/utils/test_query_encoding.py, andlangfuse/api/resources/llm_connections/types/llm_adapter.py