diff --git a/.github/workflows/core-integration-tests.yml b/.github/workflows/core-integration-tests.yml
index 7be6a452..a0d806b2 100644
--- a/.github/workflows/core-integration-tests.yml
+++ b/.github/workflows/core-integration-tests.yml
@@ -41,7 +41,6 @@ jobs:
"integration_test_chat_completions.py",
"integration_test_multi_agent.py",
"integration_test_batch_api_cron_jobs.py",
- "integration_test_batch_sdk.py",
"integration_test_builtin_tools.py",
"integration_test_turbopuffer.py",
"integration_test_human_in_the_loop.py"
diff --git a/letta/server/rest_api/routers/v1/messages.py b/letta/server/rest_api/routers/v1/messages.py
index f5c52cae..e610df28 100644
--- a/letta/server/rest_api/routers/v1/messages.py
+++ b/letta/server/rest_api/routers/v1/messages.py
@@ -122,7 +122,7 @@ async def list_batches(
"""
actor = await server.user_manager.get_actor_or_default_async(actor_id=headers.actor_id)
- jobs = server.job_manager.list_jobs(
+ jobs = await server.job_manager.list_jobs_async(
actor=actor,
statuses=[JobStatus.created, JobStatus.running],
job_type=JobType.BATCH,
diff --git a/tests/integration_test_batch_sdk.py b/tests/integration_test_batch_sdk.py
deleted file mode 100644
index e70435de..00000000
--- a/tests/integration_test_batch_sdk.py
+++ /dev/null
@@ -1,139 +0,0 @@
-import os
-import threading
-import time
-
-import pytest
-from dotenv import load_dotenv
-from letta_client import Letta, LettaBatchRequest, MessageCreate, TextContent
-
-from letta.config import LettaConfig
-from letta.jobs.llm_batch_job_polling import poll_running_llm_batches
-from letta.orm import Base
-from letta.schemas.enums import JobStatus
-from letta.server.db import db_context
-from letta.server.server import SyncServer
-
-
-@pytest.fixture(autouse=True)
-def clear_batch_tables():
- """Clear batch-related tables before each test."""
- with db_context() as session:
- for table in reversed(Base.metadata.sorted_tables):
- if table.name in {"jobs", "llm_batch_job", "llm_batch_items"}:
- session.execute(table.delete()) # Truncate table
- session.commit()
-
-
-def run_server():
- """Starts the Letta server in a background thread."""
- load_dotenv()
- from letta.server.rest_api.app import start_server
-
- start_server(debug=True)
-
-
-@pytest.fixture(scope="session")
-def server_url():
- """
- Ensures a server is running and returns its base URL.
-
- Uses environment variable if available, otherwise starts a server
- in a background thread.
- """
- url = os.getenv("LETTA_SERVER_URL", "http://localhost:8283")
-
- if not os.getenv("LETTA_SERVER_URL"):
- thread = threading.Thread(target=run_server, daemon=True)
- thread.start()
- time.sleep(5) # Give server time to start
-
- return url
-
-
-@pytest.fixture(scope="module")
-def server():
- """
- Creates a SyncServer instance for testing.
-
- Loads and saves config to ensure proper initialization.
- """
- config = LettaConfig.load()
- config.save()
- return SyncServer()
-
-
-@pytest.fixture(scope="session")
-def client(server_url):
- """Creates a REST client connected to the test server."""
- return Letta(base_url=server_url)
-
-
-@pytest.mark.asyncio
-async def test_create_batch(client: Letta, server: SyncServer):
- # create agents
- agent1 = client.agents.create(
- name="agent1_batch",
- memory_blocks=[{"label": "persona", "value": "you are agent 1"}],
- model="anthropic/claude-3-7-sonnet-20250219",
- embedding="letta/letta-free",
- )
- agent2 = client.agents.create(
- name="agent2_batch",
- memory_blocks=[{"label": "persona", "value": "you are agent 2"}],
- model="anthropic/claude-3-7-sonnet-20250219",
- embedding="letta/letta-free",
- )
-
- # create a run
- run = client.batches.create(
- requests=[
- LettaBatchRequest(
- messages=[
- MessageCreate(
- role="user",
- content=[
- TextContent(
- text="hi",
- )
- ],
- )
- ],
- agent_id=agent1.id,
- ),
- LettaBatchRequest(
- messages=[
- MessageCreate(
- role="user",
- content=[
- TextContent(
- text="hi",
- )
- ],
- )
- ],
- agent_id=agent2.id,
- ),
- ]
- )
- assert run is not None
-
- # list batches
- batches = client.batches.list()
- assert len(batches) == 1, f"Expected 1 batch, got {len(batches)}"
- assert batches[0].status == JobStatus.running
-
- # Poll it once
- await poll_running_llm_batches(server)
-
- # get the batch results
- results = client.batches.retrieve(
- batch_id=run.id,
- )
- assert results is not None
-
- # cancel
- client.batches.cancel(batch_id=run.id)
- batch_job = client.batches.retrieve(
- batch_id=run.id,
- )
- assert batch_job.status == JobStatus.cancelled
diff --git a/tests/test_agent_files/test_basic_agent_with_blocks_tools_messages_v2.af b/tests/test_agent_files/test_basic_agent_with_blocks_tools_messages_v2.af
index 6db6511b..5d1142e5 100644
--- a/tests/test_agent_files/test_basic_agent_with_blocks_tools_messages_v2.af
+++ b/tests/test_agent_files/test_basic_agent_with_blocks_tools_messages_v2.af
@@ -1,7 +1,7 @@
{
"agents": [
{
- "name": "test_export_import_f72735f5-a08b-4ff0-8f8e-761af82dee33",
+ "name": "test_export_import_431ac32f-ffd1-40a7-8152-9733470c951d",
"memory_blocks": [],
"tools": [],
"tool_ids": [
@@ -20,25 +20,25 @@
"block-2"
],
"tool_rules": [
- {
- "tool_name": "conversation_search",
- "type": "continue_loop",
- "prompt_template": "\n{{ tool_name }} requires continuing your response when called\n"
- },
{
"tool_name": "memory_replace",
"type": "continue_loop",
- "prompt_template": "\n{{ tool_name }} requires continuing your response when called\n"
- },
- {
- "tool_name": "memory_insert",
- "type": "continue_loop",
- "prompt_template": "\n{{ tool_name }} requires continuing your response when called\n"
+ "prompt_template": null
},
{
"tool_name": "send_message",
"type": "exit_loop",
- "prompt_template": "\n{{ tool_name }} ends your response (yields control) when called\n"
+ "prompt_template": null
+ },
+ {
+ "tool_name": "memory_insert",
+ "type": "continue_loop",
+ "prompt_template": null
+ },
+ {
+ "tool_name": "conversation_search",
+ "type": "continue_loop",
+ "prompt_template": null
}
],
"tags": [
@@ -99,6 +99,7 @@
"template": false,
"project": null,
"tool_exec_environment_variables": {},
+ "secrets": null,
"memory_variables": null,
"project_id": null,
"template_id": null,
@@ -128,7 +129,7 @@
"content": [
{
"type": "text",
- "text": "You are a helpful assistant specializing in data analysis and mathematical computations.\n\n\nThe following memory blocks are currently engaged in your core memory unit:\n\n\n\nNone\n\n\n- chars_current=210\n- chars_limit=6000\n\n\n# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\nLine 1: Current project: Building predictive models for financial markets. Sarah is working on sequence analysis and pattern recognition. Recently interested in mathematical sequences like Fibonacci for trend analysis.\n\n\n\n\n\nThe human block: Stores key details about the person you are conversing with, allowing for more personalized and friend-like conversation.\n\n\n- chars_current=175\n- chars_limit=4000\n\n\n# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\nLine 1: username: sarah_researcher\nLine 2: occupation: data scientist\nLine 3: interests: machine learning, statistics, fibonacci sequences\nLine 4: preferred_communication: detailed explanations with examples\n\n\n\n\n\nThe persona block: Stores details about your current persona, guiding how you behave and respond. This helps you to maintain consistency and personality in your interactions.\n\n\n- chars_current=195\n- chars_limit=8000\n\n\n# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\nLine 1: You are Alex, a data analyst and mathematician who helps users with calculations and insights. You have extensive experience in statistical analysis and prefer to provide clear, accurate results.\n\n\n\n\n\n\nThe following constraints define rules for tool usage and guide desired behavior. These rules must be followed to ensure proper tool execution and workflow. A single response may contain multiple tool calls.\n\n\nconversation_search requires continuing your response when called\n\n\nmemory_replace requires continuing your response when called\n\n\nmemory_insert requires continuing your response when called\n\n\nsend_message ends your response (yields control) when called\n\n\n\n\n\n\n- The current system date is: September 08, 2025\n- Memory blocks were last modified: 2025-09-08 05:53:05 PM UTC+0000\n- -1 previous messages between you and the user are stored in recall memory (use tools to access them)\n- 2 total memories you created are stored in archival memory (use tools to access them)\n"
+ "text": "You are a helpful assistant specializing in data analysis and mathematical computations.\n\n\nThe following memory blocks are currently engaged in your core memory unit:\n\n\n\nThe persona block: Stores details about your current persona, guiding how you behave and respond. This helps you to maintain consistency and personality in your interactions.\n\n\n- chars_current=195\n- chars_limit=8000\n\n\n# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\nLine 1: You are Alex, a data analyst and mathematician who helps users with calculations and insights. You have extensive experience in statistical analysis and prefer to provide clear, accurate results.\n\n\n\n\n\nThe human block: Stores key details about the person you are conversing with, allowing for more personalized and friend-like conversation.\n\n\n- chars_current=175\n- chars_limit=4000\n\n\n# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\nLine 1: username: sarah_researcher\nLine 2: occupation: data scientist\nLine 3: interests: machine learning, statistics, fibonacci sequences\nLine 4: preferred_communication: detailed explanations with examples\n\n\n\n\n\n\n\n\n- chars_current=210\n- chars_limit=6000\n\n\n# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\nLine 1: Current project: Building predictive models for financial markets. Sarah is working on sequence analysis and pattern recognition. Recently interested in mathematical sequences like Fibonacci for trend analysis.\n\n\n\n\n\n\nThe following constraints define rules for tool usage and guide desired behavior. These rules must be followed to ensure proper tool execution and workflow. A single response may contain multiple tool calls.\n\n\nmemory_replace requires continuing your response when called\n\n\nmemory_insert requires continuing your response when called\n\n\nconversation_search requires continuing your response when called\n\n\nsend_message ends your response (yields control) when called\n\n\n\n\n- The current system date is: September 24, 2025\n- Memory blocks were last modified: 2025-09-24 10:57:40 PM UTC+0000\n- -1 previous messages between you and the user are stored in recall memory (use tools to access them)\n- 2 total memories you created are stored in archival memory (use tools to access them)\n"
}
],
"name": null,
@@ -142,7 +143,7 @@
"tool_calls": null,
"tool_call_id": null,
"tool_returns": [],
- "created_at": "2025-09-08T17:53:02.499443+00:00"
+ "created_at": "2025-09-24T22:57:39.493431+00:00"
},
{
"type": "message",
@@ -163,7 +164,7 @@
"agent_id": "agent-0",
"tool_calls": [
{
- "id": "c1ec5c60-7dbc-4b53-bfbb-c2af5d5a222f",
+ "id": "f1c5f8b4-c57c-4641-8d58-903248a31f7b",
"function": {
"arguments": "{\n \"message\": \"More human than human is our motto.\"\n}",
"name": "send_message"
@@ -173,7 +174,7 @@
],
"tool_call_id": null,
"tool_returns": [],
- "created_at": "2025-09-08T17:53:02.499491+00:00"
+ "created_at": "2025-09-24T22:57:39.493461+00:00"
},
{
"type": "message",
@@ -181,7 +182,7 @@
"content": [
{
"type": "text",
- "text": "{\n \"status\": \"OK\",\n \"message\": null,\n \"time\": \"2025-09-08 05:53:02 PM UTC+0000\"\n}"
+ "text": "{\n \"status\": \"OK\",\n \"message\": null,\n \"time\": \"2025-09-24 10:57:39 PM UTC+0000\"\n}"
}
],
"name": "send_message",
@@ -193,9 +194,9 @@
"model": "gpt-4.1-mini",
"agent_id": "agent-0",
"tool_calls": null,
- "tool_call_id": "c1ec5c60-7dbc-4b53-bfbb-c2af5d5a222f",
+ "tool_call_id": "f1c5f8b4-c57c-4641-8d58-903248a31f7b",
"tool_returns": [],
- "created_at": "2025-09-08T17:53:02.499526+00:00"
+ "created_at": "2025-09-24T22:57:39.493485+00:00"
},
{
"type": "message",
@@ -203,7 +204,7 @@
"content": [
{
"type": "text",
- "text": "{\n \"type\": \"login\",\n \"last_login\": \"Never (first login)\",\n \"time\": \"2025-09-08 05:53:02 PM UTC+0000\"\n}"
+ "text": "{\n \"type\": \"login\",\n \"last_login\": \"Never (first login)\",\n \"time\": \"2025-09-24 10:57:39 PM UTC+0000\"\n}"
}
],
"name": null,
@@ -217,7 +218,7 @@
"tool_calls": null,
"tool_call_id": null,
"tool_returns": [],
- "created_at": "2025-09-08T17:53:02.499541+00:00"
+ "created_at": "2025-09-24T22:57:39.493496+00:00"
},
{
"type": "message",
@@ -239,7 +240,7 @@
"tool_calls": null,
"tool_call_id": null,
"tool_returns": [],
- "created_at": "2025-09-08T17:53:05.017966+00:00"
+ "created_at": "2025-09-24T22:57:40.764277+00:00"
},
{
"type": "message",
@@ -247,7 +248,7 @@
"content": [
{
"type": "text",
- "text": "Responding to test message for export."
+ "text": "User sent a test message for export functionality verification."
}
],
"name": null,
@@ -260,17 +261,17 @@
"agent_id": "agent-0",
"tool_calls": [
{
- "id": "call_sMVo2qIYhILKKNT0YiOdsU24",
+ "id": "call_pvBdfaX7NpaFcjrhqNCSyg7S",
"function": {
- "arguments": "{\"message\": \"Test message received successfully. Ready to assist you with any questions or tasks.\", \"request_heartbeat\": false}",
+ "arguments": "{\"message\": \"I received your test message successfully. If you need any assistance or want to continue with our project discussions, just let me know!\", \"request_heartbeat\": false}",
"name": "send_message"
},
"type": "function"
}
],
- "tool_call_id": "call_sMVo2qIYhILKKNT0YiOdsU24",
+ "tool_call_id": "call_pvBdfaX7NpaFcjrhqNCSyg7S",
"tool_returns": [],
- "created_at": "2025-09-08T17:53:06.600989+00:00"
+ "created_at": "2025-09-24T22:57:41.948407+00:00"
},
{
"type": "message",
@@ -278,7 +279,7 @@
"content": [
{
"type": "text",
- "text": "{\n \"status\": \"OK\",\n \"message\": \"Sent message successfully.\",\n \"time\": \"2025-09-08 05:53:06 PM UTC+0000\"\n}"
+ "text": "{\n \"status\": \"OK\",\n \"message\": \"Sent message successfully.\",\n \"time\": \"2025-09-24 10:57:41 PM UTC+0000\"\n}"
}
],
"name": "send_message",
@@ -290,7 +291,7 @@
"model": "gpt-4.1-mini",
"agent_id": "agent-0",
"tool_calls": null,
- "tool_call_id": "call_sMVo2qIYhILKKNT0YiOdsU24",
+ "tool_call_id": "call_pvBdfaX7NpaFcjrhqNCSyg7S",
"tool_returns": [
{
"status": "success",
@@ -298,7 +299,7 @@
"stderr": null
}
],
- "created_at": "2025-09-08T17:53:06.601180+00:00"
+ "created_at": "2025-09-24T22:57:41.948586+00:00"
}
],
"files_agents": [],
@@ -366,7 +367,7 @@
"sources": [],
"tools": [
{
- "id": "tool-6",
+ "id": "tool-5",
"tool_type": "custom",
"description": "Analyze data and provide insights.",
"source_type": "json",
@@ -410,7 +411,7 @@
"metadata_": {}
},
{
- "id": "tool-2",
+ "id": "tool-1",
"tool_type": "custom",
"description": "Calculate the nth Fibonacci number.",
"source_type": "json",
@@ -446,7 +447,7 @@
"metadata_": {}
},
{
- "id": "tool-3",
+ "id": "tool-0",
"tool_type": "letta_core",
"description": "Search prior conversation history using hybrid search (text + semantic similarity).\n\nExamples:\n # Search all messages\n conversation_search(query=\"project updates\")\n\n # Search only assistant messages\n conversation_search(query=\"error handling\", roles=[\"assistant\"])\n\n # Search with date range (inclusive of both dates)\n conversation_search(query=\"meetings\", start_date=\"2024-01-15\", end_date=\"2024-01-20\")\n # This includes all messages from Jan 15 00:00:00 through Jan 20 23:59:59\n\n # Search messages from a specific day (inclusive)\n conversation_search(query=\"bug reports\", start_date=\"2024-09-04\", end_date=\"2024-09-04\")\n # This includes ALL messages from September 4, 2024\n\n # Search with specific time boundaries\n conversation_search(query=\"deployment\", start_date=\"2024-01-15T09:00\", end_date=\"2024-01-15T17:30\")\n # This includes messages from 9 AM to 5:30 PM on Jan 15\n\n # Search with limit\n conversation_search(query=\"debugging\", limit=10)\n\n Returns:\n str: Query result string containing matching messages with timestamps and content.",
"source_type": "python",
@@ -505,7 +506,7 @@
"metadata_": {}
},
{
- "id": "tool-1",
+ "id": "tool-2",
"tool_type": "custom",
"description": "Get user preferences for a specific category.",
"source_type": "json",
@@ -541,7 +542,7 @@
"metadata_": {}
},
{
- "id": "tool-0",
+ "id": "tool-3",
"tool_type": "letta_sleeptime_core",
"description": "The memory_insert command allows you to insert text at a specific location in a memory block.\n\nExamples:\n # Update a block containing information about the user (append to the end of the block)\n memory_insert(label=\"customer\", new_str=\"The customer's ticket number is 12345\")\n\n # Update a block containing information about the user (insert at the beginning of the block)\n memory_insert(label=\"customer\", new_str=\"The customer's ticket number is 12345\", insert_line=0)\n\n Returns:\n Optional[str]: None is always returned as this function does not produce a response.",
"source_type": "python",
@@ -630,7 +631,7 @@
"metadata_": {}
},
{
- "id": "tool-5",
+ "id": "tool-6",
"tool_type": "letta_core",
"description": "Sends a message to the human user.",
"source_type": "python",
@@ -667,7 +668,7 @@
],
"mcp_servers": [],
"metadata": {
- "revision_id": "5b804970e6a0"
+ "revision_id": "3d2e9fb40a3c"
},
- "created_at": "2025-09-08T17:53:06.749694+00:00"
+ "created_at": "2025-09-24T22:57:42.392726+00:00"
}
diff --git a/tests/test_sdk_client.py b/tests/test_sdk_client.py
index a1136e2e..a8629670 100644
--- a/tests/test_sdk_client.py
+++ b/tests/test_sdk_client.py
@@ -13,6 +13,7 @@ from letta_client import (
ContinueToolRule,
CreateBlock,
Letta as LettaSDKClient,
+ LettaBatchRequest,
LettaRequest,
MaxCountPerStepToolRule,
MessageCreate,
@@ -24,6 +25,10 @@ from letta_client.core import ApiError
from letta_client.types import AgentState, ToolReturnMessage
from pydantic import BaseModel, Field
+from letta.config import LettaConfig
+from letta.jobs.llm_batch_job_polling import poll_running_llm_batches
+from letta.schemas.enums import JobStatus
+from letta.server.server import SyncServer
from tests.helpers.utils import upload_file_and_wait
# Constants
@@ -60,6 +65,18 @@ def client() -> LettaSDKClient:
yield client
+@pytest.fixture(scope="module")
+def server():
+ """
+ Creates a SyncServer instance for testing.
+
+ Loads and saves config to ensure proper initialization.
+ """
+ config = LettaConfig.load()
+ config.save()
+ return SyncServer()
+
+
@pytest.fixture(scope="function")
def agent(client: LettaSDKClient):
agent_state = client.agents.create(
@@ -2190,3 +2207,74 @@ def test_upsert_tools(client: LettaSDKClient):
# Clean up
client.tools.delete(tool.id)
+
+
+@pytest.mark.asyncio
+async def test_create_batch(client: LettaSDKClient, server: SyncServer):
+ # create agents
+ agent1 = client.agents.create(
+ name="agent1_batch",
+ memory_blocks=[{"label": "persona", "value": "you are agent 1"}],
+ model="anthropic/claude-3-7-sonnet-20250219",
+ embedding="letta/letta-free",
+ )
+ agent2 = client.agents.create(
+ name="agent2_batch",
+ memory_blocks=[{"label": "persona", "value": "you are agent 2"}],
+ model="anthropic/claude-3-7-sonnet-20250219",
+ embedding="letta/letta-free",
+ )
+
+ # create a run
+ run = client.batches.create(
+ requests=[
+ LettaBatchRequest(
+ messages=[
+ MessageCreate(
+ role="user",
+ content=[
+ TextContent(
+ text="hi",
+ )
+ ],
+ )
+ ],
+ agent_id=agent1.id,
+ ),
+ LettaBatchRequest(
+ messages=[
+ MessageCreate(
+ role="user",
+ content=[
+ TextContent(
+ text="hi",
+ )
+ ],
+ )
+ ],
+ agent_id=agent2.id,
+ ),
+ ]
+ )
+ assert run is not None
+
+ # list batches
+ batches = client.batches.list()
+ assert len(batches) >= 1, f"Expected 1 or more batches, got {len(batches)}"
+ assert batches[0].status == JobStatus.running
+
+ # Poll it once
+ await poll_running_llm_batches(server)
+
+ # get the batch results
+ results = client.batches.retrieve(
+ batch_id=run.id,
+ )
+ assert results is not None
+
+ # cancel
+ client.batches.cancel(batch_id=run.id)
+ batch_job = client.batches.retrieve(
+ batch_id=run.id,
+ )
+ assert batch_job.status == JobStatus.cancelled