* 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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* 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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* feat: add TypeScript tool support for E2B sandbox execution
This change implements TypeScript tool support using the same E2B path as Python tools:
- Add TypeScript execution script generator (typescript_generator.py)
- Modify E2B sandbox to detect TypeScript tools and use language='ts'
- Add npm package installation for TypeScript tool dependencies
- Add validation requiring json_schema for TypeScript tools
- Add comprehensive integration tests for TypeScript tools
TypeScript tools:
- Require explicit json_schema (no docstring parsing)
- Use JSON serialization instead of pickle for results
- Support async functions with top-level await
- Support npm package dependencies via npm_requirements field
Closes#8793
Co-authored-by: Sarah Wooders <sarahwooders@users.noreply.github.com>
* fix: disable AgentState for TypeScript tools & add letta-client injection
Based on Sarah's feedback:
1. AgentState is a legacy Python-only feature, disabled for TS tools
2. Added @letta-ai/letta-client npm package injection for TypeScript
(similar to letta_client for Python)
Changes:
- base.py: Explicitly set inject_agent_state=False for TypeScript tools
- typescript_generator.py: Inject LettaClient initialization code
- e2b_sandbox.py: Auto-install @letta-ai/letta-client for TS tools
- Added tests verifying both behaviors
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* Update core-integration-tests.yml
* fix: convert TypeScript test fixtures to async
The OrganizationManager and UserManager no longer have sync methods,
only async variants. Updated all fixtures to use:
- create_organization_async
- create_actor_async
- create_or_update_tool_async
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* fix: skip Python AST parsing for TypeScript tools in sandbox base
The _init_async method was calling parse_function_arguments (which uses
Python's ast.parse) before checking if the tool was TypeScript, causing
SyntaxError when running TypeScript tools.
Moved the is_typescript_tool() check to happen first, skipping Python
AST parsing entirely for TypeScript tools.
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* letta_agent_id
* skip ast parsing for s
* add tool execution test
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The import was `from datetime import datetime` but the code used
`datetime.timezone.utc` which is incorrect - timezone is a sibling
class in the datetime module, not an attribute of the datetime class.
This caused the error: "type object 'datetime.datetime' has no
attribute 'timezone'"
PR #8682 added code that references settings.use_clickhouse_for_provider_traces
but never added the field to Settings, causing AttributeError in prod.
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feat(core): add run_id filter to internal runs endpoint
Adds the ability to filter runs by a specific run ID in the
internal runs list endpoint.
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* chore: deprecate identities/groups APIs and remove from SDK
- Mark all /v1/identities/* endpoints as deprecated
- Mark all /v1/groups/* endpoints as deprecated
- Remove identities, groups, and batches resources from stainless.yml
- Batch API remains active but hidden from SDK
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* chore: update autogenerated SDK files
* chore: regenerate SDK and OpenAPI spec
Run `just stage-api` and `just publish-api` to sync generated files.
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* chore: remove schedule API from stainless SDK
Remove schedule subresource from stainless.yml to hide scheduled messages
endpoints from the SDK generation.
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* feat: add /v1/runs/{run_id}/trace endpoint for OTEL traces
- Add new endpoint to retrieve filtered OTEL spans for a run
- Filter to only return UI-relevant spans (agent_step, tool executions, root span, TTFT)
- Skip Postgres writes when ClickHouse is enabled for provider traces
- Add USE_CLICKHOUSE_FOR_PROVIDER_TRACES env var to helm/justfile
- Move typecheck CI to self-hosted runners
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* fix: add missing clickhouse_provider_traces.py
The telemetry_manager.py imports ClickhouseProviderTraceReader from
this module, but the file was not included when splitting the PR.
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* autogen
* fix: add trace.retrieve to stainless.yml for SDK generation
Adds the runs.trace.retrieve method mapping so Stainless generates
the useRunsServiceRetrieveTraceForRun hook.
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* feat: add conversation_id parameter to context endpoint [LET-6989]
Add optional conversation_id query parameter to retrieve_agent_context_window.
When provided, the endpoint uses messages from the specific conversation
instead of the agent's default message_ids.
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* chore: regenerate SDK after context endpoint update [LET-6989]
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* feat: add isolated blocks support for conversations
Allows conversations to have their own copies of specific memory blocks (e.g., todo_list) that override agent defaults, enabling conversation-specific state isolation.
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* undo
* update apis
* test
* cleanup
* fix tests
* simplify
* move override logic
* patch
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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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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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The FastMCP clients were not properly wrapping exceptions from
`connect_to_server()`, causing raw RuntimeErrors (like DNS resolution
failures with "[Errno -2] Name or service not known") to propagate
up unchanged.
Changes:
- Both `AsyncFastMCPSSEClient` and `AsyncFastMCPStreamableHTTPClient`
now properly catch all exceptions and wrap them in `ConnectionError`
- Added warning-level logging for failed connections
- Provides user-friendly error messages with the server URL
Fixes#8568
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This fixes a 400 INVALID_ARGUMENT error from Google's Gemini API where
function calls were missing required thought_signature in functionCall parts.
Changes:
- Allow signatures when self.model is None (backwards compatibility for
older messages that may not have had their model field set)
- Only add thought_signature to the FIRST function call for parallel
tool calls, per Google's docs
- Take the first non-None signature found (don't keep overwriting)
Reference: https://ai.google.dev/gemini-api/docs/thought-signaturesCloses#8589🤖 Generated with [Letta Code](https://letta.com)
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