* feat: centralize telemetry logging at LLM client level
Moves telemetry logging from individual adapters to LLMClientBase:
- Add TelemetryStreamWrapper for streaming telemetry on stream close
- Add request_async_with_telemetry() for non-streaming requests
- Add stream_async_with_telemetry() for streaming requests
- Add set_telemetry_context() to configure agent_id, run_id, step_id
Updates adapters and agents to use new pattern:
- LettaLLMAdapter now accepts agent_id/run_id in constructor
- Adapters call set_telemetry_context() before LLM requests
- Removes duplicate telemetry logging from adapters
- Enriches traces with agent_id, run_id, call_type metadata
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* fix: accumulate streaming response content for telemetry
TelemetryStreamWrapper now extracts actual response data from chunks:
- Content text (concatenated from deltas)
- Tool calls (id, name, arguments)
- Model name, finish reason, usage stats
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* refactor: move streaming telemetry to caller (option 3)
- Remove TelemetryStreamWrapper class
- Add log_provider_trace_async() helper to LLMClientBase
- stream_async_with_telemetry() now just returns raw stream
- Callers log telemetry after processing with rich interface data
Updated callers:
- summarizer.py: logs content + usage after stream processing
- letta_agent.py: logs tool_call, reasoning, model, usage
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* fix: pass agent_id and run_id to parent adapter class
LettaLLMStreamAdapter was not passing agent_id/run_id to parent,
causing "unexpected keyword argument" errors.
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Co-authored-by: Letta <noreply@letta.com>
* feat: add provider trace backend abstraction for multi-backend telemetry
Introduces a pluggable backend system for provider traces:
- Base class with async/sync create and read interfaces
- PostgreSQL backend (existing behavior)
- ClickHouse backend (via OTEL instrumentation)
- Socket backend (writes to Unix socket for crouton sidecar)
- Factory for instantiating backends from config
Refactors TelemetryManager to use backends with support for:
- Multi-backend writes (concurrent via asyncio.gather)
- Primary backend for reads (first in config list)
- Graceful error handling per backend
Config: LETTA_TELEMETRY_PROVIDER_TRACE_BACKEND (comma-separated)
Example: "postgres,socket" for dual-write to Postgres and crouton
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* feat: add protocol version to socket backend records
Adds PROTOCOL_VERSION constant to socket backend:
- Included in every telemetry record sent to crouton
- Must match ProtocolVersion in apps/crouton/main.go
- Enables crouton to detect and reject incompatible messages
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* fix: remove organization_id from ProviderTraceCreate calls
The organization_id is now handled via the actor parameter in the
telemetry manager, not through ProviderTraceCreate schema. This fixes
validation errors after changing ProviderTraceCreate to inherit from
BaseProviderTrace which forbids extra fields.
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* consolidate provider trace
* add clickhouse-connect to fix bug on main lmao
* auto generated sdk changes, and deployment details, and clikchouse prefix bug and added fields to runs trace return api
* auto generated sdk changes, and deployment details, and clikchouse prefix bug and added fields to runs trace return api
* consolidate provider trace
* consolidate provider trace bug fix
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Co-authored-by: Letta <noreply@letta.com>
This commit addresses the httpx.ReadTimeout error detected in production
by adding explicit timeout configurations to several httpx client usages:
1. MCP SSE client: Pass mcp_connect_to_server_timeout (30s) to sse_client()
2. MCP StreamableHTTP client: Pass mcp_connect_to_server_timeout (30s) to streamablehttp_client()
3. OpenAI model list API: Add 30s timeout with 10s connect timeout
4. Google AI model list/details API: Add 30s timeout with 10s connect timeout
Previously, these httpx clients were created without explicit timeouts,
which could cause ReadTimeout errors when remote servers are slow to respond.
Fixes#8073🤖 Generated with [Letta Code](https://letta.com)
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Co-authored-by: Kian Jones <11655409+kianjones9@users.noreply.github.com>
When the Anthropic SDK detects a request may exceed 10 minutes, it
raises a ValueError requiring streaming mode. This fix catches that
specific error in request_async and automatically falls back to
streaming mode, accumulating the response into the same format as
non-streaming.
This resolves the production error:
"ValueError: Streaming is required for operations that may take
longer than 10 minutes"
Fixes#8516🤖 Generated with [Letta Code](https://letta.com)
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Critical fixes:
- llm_client_base.send_llm_request() now calls await self.request_async() instead of self.request()
- Remove unused sync get_openai_embedding() that used sync OpenAI client
- Remove deprecated compile_in_thread_async() from Memory
These were blocking the event loop during LLM requests and embeddings.
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Adds explicit handling for httpx network errors (ReadError, WriteError,
ConnectError) in AnthropicClient, OpenAIClient, and GoogleVertexClient.
These errors can occur during streaming when the connection is unexpectedly
closed while reading/writing data.
Maps these errors to LLMConnectionError for consistent error handling.
Fixes#8221 (and duplicate #8156)
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The Anthropic API returns a 413 status code with error type `request_too_large`
when the request payload exceeds the maximum allowed size. This error should
be converted to `ContextWindowExceededError` so the system can handle it
appropriately (e.g., by summarizing the conversation to reduce context size).
Changes:
- Added `request_too_large` and `request exceeds the maximum size` to the
early string-based error detection in `handle_llm_error`
- Added specific handling for HTTP 413 status code in the `APIStatusError`
handler
- Added tests to verify the new error handling behavior
Fixes: #8422🤖 Generated with [Letta Code](https://letta.com)
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* feat: add zai provider support
* add zai_api_key secret to deploy-core
* add to justfile
* add testing, provider integration skill
* enable zai key
* fix zai test
* clean up skill a little
* small changes
* Revert "fix test"
This reverts commit 5126815f23cefb4edad3e3bf9e7083209dcc7bf1.
* fix server and better test
* test fix, get api key for base and byok?
* set letta default endpoint
* try to fix timeout for test
* fix for letta api key
* Delete apps/core/tests/sdk_v1/conftest.py
* Update utils.py
* clean up a few issues
* fix filterning on list_llm_models
* soft delete models with provider
* add one more test
* fix ci
* add timeout
* band aid for letta embedding provider
* info instead of error logs when creating models
* first hack with test
* remove changes integration test
* Delete apps/core/tests/sdk_v1/integration/integration_test_send_message_v2.py
* add test
* remove comment
* stage and publish api
* deprecate base level response_schema
* add param to llm_config test
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Co-authored-by: Ari Webb <ari@letta.com>
* feat: add support for new model
* fix: just stage-api && just publish-api (anthropic model settings changed)
* fix: just stage-api && just publish-api (anthropic model settings changed)
* fix: make kevlar have default reasoning on
* fix: bump anthropic sdk version
* fix: patch name
* pin newer version anthropic
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Co-authored-by: Ari Webb <ari@letta.com>