* 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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Co-authored-by: Sarah Wooders <sarahwooders@users.noreply.github.com>
* 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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Co-authored-by: letta-code <248085862+letta-code@users.noreply.github.com>
Co-authored-by: Sarah Wooders <sarahwooders@users.noreply.github.com>
* 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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- Fix typo "upate" -> "update" in TODO comments (mcp_manager.py, mcp_server_manager.py)
- Improve comments in OAuth callback handler to explain why MCPOAuthSession
is used directly (callback is unauthenticated, manager requires actor)
- Clean up variable naming in callback handler
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* feat: add tags support to blocks
* fix: add timestamps and org scoping to blocks_tags
Addresses PR feedback:
1. Migration: Added timestamps (created_at, updated_at), soft delete
(is_deleted), audit fields (_created_by_id, _last_updated_by_id),
and organization_id to blocks_tags table for filtering support.
Follows SQLite baseline pattern (composite PK of block_id+tag, no
separate id column) to avoid insert failures.
2. ORM: Relationship already correct with lazy="raise" to prevent
implicit joins and passive_deletes=True for efficient CASCADE deletes.
3. Schema: Changed normalize_tags() from Any to dict for type safety.
4. SQLite: Added blocks_tags to SQLite baseline schema to prevent
table-not-found errors.
5. Code: Updated all tag row inserts to include organization_id.
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* fix: add ORM columns and update SQLite baseline for blocks_tags
Fixes test failures (CompileError: Unconsumed column names: organization_id):
1. ORM: Added organization_id, timestamps, audit fields to BlocksTags
ORM model to match database schema from migrations.
2. SQLite baseline: Added full column set to blocks_tags (organization_id,
timestamps, audit fields) to match PostgreSQL schema.
3. Test: Added 'tags' to expected Block schema fields.
This ensures SQLite and PostgreSQL have matching schemas and the ORM
can consume all columns that the code inserts.
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* revert change to existing alembic migration
* fix: remove passive_deletes and SQLite support for blocks_tags
1. Removed passive_deletes=True from Block.tags relationship to match
AgentsTags pattern (neither have ondelete CASCADE in DB schema).
2. Removed SQLite branch from _replace_block_pivot_rows_async since
blocks_tags table is PostgreSQL-only (migration skips SQLite).
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* api sync
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* feat: Add conversation_id filtering to message list and search endpoints
Add optional conversation_id parameter to filter messages by conversation:
- client.agents.messages.list
- client.messages.list
- client.messages.search
Changes:
- Added conversation_id field to MessageSearchRequest and SearchAllMessagesRequest schemas
- Added conversation_id filtering to list_messages in message_manager.py
- Updated get_agent_recall_async and get_all_messages_recall_async in server.py
- Added conversation_id query parameter to router endpoints
- Updated Turbopuffer client to support conversation_id filtering in searches
Fixes#8320🤖 Generated with [Letta Code](https://letta.com)
Co-Authored-By: Charles Packer <cpacker@users.noreply.github.com>
* add conversation_id to message and tpuf
* default messages filter for backward compatibility
* add test and auto gen
* fix integration test
* fix test
* update test
---------
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Co-authored-by: Charles Packer <cpacker@users.noreply.github.com>
Co-authored-by: christinatong01 <christina@letta.com>
* feat: add message_types filter to list messages endpoint
Add the ability to filter messages by type when listing message history
via GET /v1/agents/{agent_id}/messages. This brings parity with the
create message endpoint which already supports include_return_message_types.
Changes:
- Add message_types query parameter to list_messages endpoint in agents.py
- Add message_types parameter to get_agent_recall_async in server.py
- Filter messages by message_type after LettaMessage conversion
- Add test for message_types filtering
Closes#8277
Written by Cameron ◯ Letta Code
> "Simplicity is the ultimate sophistication." - Leonardo da Vinci
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* chore: regenerate OpenAPI spec and SDK for message_types filter
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Written by Cameron ◯ Letta Code
"The only way to do great work is to love what you do." - Steve Jobs
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* feat: allow client-side tools to be specified in request
Add `client_tools` field to LettaRequest to allow passing tool schemas
at message creation time without requiring server-side registration.
When the agent calls a client-side tool, execution pauses with
stop_reason=requires_approval for the client to provide tool returns.
- Add ClientToolSchema class for request-level tool schemas
- Merge client tools with agent tools in _get_valid_tools()
- Treat client-side tool calls as requiring approval
- Add integration tests for client-side tools flow
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* test: add comprehensive end-to-end test for client-side tools
Update integration test to verify the complete flow:
- Agent calls client-side tool and pauses
- Client provides tool return with secret code
- Agent processes and responds
- User asks about the code, agent recalls it
- Validate full conversation history makes sense
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* update apis
* fix: client-side tools schema format and test assertions
- Use flat schema format for client tools (matching t.json_schema)
- Support both object and dict access for client tools
- Fix stop_reason assertions to access .stop_reason attribute
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* refactor: simplify client_tools access pattern
ClientToolSchema objects always have .name attribute
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* fix: add client_tools parameter to LettaAgentV2 for API compatibility
V2 agent doesn't use client_tools but needs the parameter
to match the base class signature.
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* revert: remove client_tools from LettaRequestConfig
Client-side tools don't work with background jobs since
there's no client present to provide tool returns.
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* fix: add client_tools parameter to SleeptimeMultiAgent classes
Add client_tools to step() and stream() methods in:
- SleeptimeMultiAgentV3
- SleeptimeMultiAgentV4
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* chore: regenerate API specs for client_tools support
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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
* fix: prevent empty reasoning messages in streaming interfaces
Prevents empty "Thinking..." indicators from appearing in clients by
filtering out reasoning messages with no content at the source.
Changes:
- Gemini: Don't emit ReasoningMessage when only thought_signature exists
- Gemini: Only emit reasoning content if text is non-empty
- Anthropic: Don't emit ReasoningMessage for BetaSignatureDelta
- Anthropic: Only emit reasoning content if thinking text is non-empty
This fixes the issue where providers send signature metadata before
actual thinking content, causing empty reasoning blocks to appear
in the UI after responses complete.
Affects: Gemini reasoning, Anthropic extended thinking
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Co-Authored-By: Letta <noreply@letta.com>
* feat: enable Datadog LLM Observability for memgpt-server
Enables DD_LLMOBS to track LLM calls, prompts, completions, and costs
in production for memgpt-server.
Changes:
- Add DD_LLMOBS_ENABLED=1 and DD_LLMOBS_ML_APP=memgpt-server in:
- .github/workflows/deploy-core.yml (GitHub Actions deployment)
- justfile (Helm deployment secrets)
- apps/core/letta/server/rest_api/app.py (runtime config)
This provides visibility into:
- LLM API calls and latency
- Prompt/completion content and tokens
- Model costs and usage
- Error rates per model/provider
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* dd llmobs
* Revert "fix: prevent empty reasoning messages in streaming interfaces"
This reverts commit a900228b3611de49eb5f740f68dc76a657fc9b14.
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