diff --git a/.github/workflows/e2e_test.yml b/.github/workflows/e2e_test.yml
new file mode 100644
index 00000000..65dea033
--- /dev/null
+++ b/.github/workflows/e2e_test.yml
@@ -0,0 +1,36 @@
+name: E2E Testing
+
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+
+env:
+  POETRY_VERSION: "1.6.1"
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      # You can use PyPy versions in python-version.
+      # For example, pypy-2.7 and pypy-3.8
+      matrix:
+        python-version: ["3.11", "3.12"]
+    steps:
+      - uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+      - name: Set up python ${{ matrix.python-version }}
+        uses: actions/setup-python@v4
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install deps
+        shell: bash
+        run: pip install -e .
+      - name: Run All E2E Tests
+        env:
+          CI: true
+        shell: bash
+        working-directory: e2e_tests
+        run: sh run_all_e2e_tests.sh
diff --git a/.github/workflows/publish_release.yml b/.github/workflows/publish_release.yml
index 66d0626c..e852c806 100644
--- a/.github/workflows/publish_release.yml
+++ b/.github/workflows/publish_release.yml
@@ -9,7 +9,7 @@ on:
 
 env:
   POETRY_VERSION: "1.8.3"
-  PYTHON_VERSION: "3.9"
+  PYTHON_VERSION: "3.11"
 
 jobs:
   build-n-publish:
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 4488f3f1..bffbfba6 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -49,7 +49,7 @@ repos:
             --ignore-missing-imports,
             --python-version=3.11,
           ]
-        exclude: examples/
+        exclude: ^(examples/|e2e_tests/)
   - repo: https://github.com/adamchainz/blacken-docs
     rev: 1.16.0
     hooks:
diff --git a/README.md b/README.md
index d1c3ca0e..0ef2a5f9 100644
--- a/README.md
+++ b/README.md
@@ -86,16 +86,33 @@ from llama_deploy import (
     ControlPlaneConfig,
     SimpleMessageQueueConfig,
 )
-from llama_index.core.workflow import Workflow, StartEvent, StopEvent, step
+from llama_index.core.workflow import (
+    Context,
+    Event,
+    Workflow,
+    StartEvent,
+    StopEvent,
+    step,
+)
+
+
+class ProgressEvent(Event):
+    progress: str
 
 
 # create a dummy workflow
 class MyWorkflow(Workflow):
     @step()
-    async def run_step(self, ev: StartEvent) -> StopEvent:
+    async def run_step(self, ctx: Context, ev: StartEvent) -> StopEvent:
         # Your workflow logic here
         arg1 = str(ev.get("arg1", ""))
         result = arg1 + "_result"
+
+        # stream events as steps run
+        ctx.write_event_to_stream(
+            ProgressEvent(progress="I am doing something!")
+        )
+
         return StopEvent(result=result)
 
 
@@ -133,6 +150,25 @@ print(result)
 # prints 'hello_world_result'
 ```
 
+If you want to see the event stream as well, you can do:
+
+```python
+# create a session
+session = client.create_session()
+
+# kick off run
+task_id = session.run_nowait("streaming_workflow", arg1="hello_world")
+
+# stream events -- the will yield a dict representing each event
+for event in session.get_task_result_stream(task_id):
+    print(event)
+
+# get final result
+result = session.get_task_result(task_id)
+print(result)
+# prints 'hello_world_result'
+```
+
 ### Deploying Nested Workflows
 
 Every `Workflow` is capable of injecting and running nested workflows. For example
diff --git a/docs/docs/module_guides/workflow/deployment.md b/docs/docs/module_guides/workflow/deployment.md
index 55f696d9..0ef2a5f9 100644
--- a/docs/docs/module_guides/workflow/deployment.md
+++ b/docs/docs/module_guides/workflow/deployment.md
@@ -1,11 +1,15 @@
 # 🦙 `llama_deploy` 🤖
 
-[`llama_deploy`](https://github.com/run-llama/llama_deploy) (formerly `llama-agents`) is an async-first framework for deploying, scaling, and productionizing agentic multi-service systems based on [workflows from `llama_index`](https://docs.llamaindex.ai/en/stable/understanding/workflows/). With `llama_deploy`, you can build any number of workflows in `llama_index` and then bring them into `llama_deploy` for deployment.
+`llama_deploy` (formerly `llama-agents`) is an async-first framework for deploying, scaling, and productionizing agentic multi-service systems based on [workflows from `llama_index`](https://docs.llamaindex.ai/en/stable/understanding/workflows/). With `llama_deploy`, you can build any number of workflows in `llama_index` and then bring them into `llama_deploy` for deployment.
 
 In `llama_deploy`, each workflow is seen as a `service`, endlessly processing incoming tasks. Each workflow pulls and publishes messages to and from a `message queue`.
 
 At the top of a `llama_deploy` system is the `control plane`. The control plane handles ongoing tasks, manages state, keeps track of which services are in the network, and also decides which service should handle the next step of a task using an `orchestrator`. The default `orchestrator` is purely programmatic, handling failures, retries, and state-passing.
 
+The overall system layout is pictured below.
+
+![A basic system in llama_deploy](./system_diagram.png)
+
 ## Why `llama_deploy`?
 
 1. **Seamless Deployment**: It bridges the gap between development and production, allowing you to deploy `llama_index` workflows with minimal changes to your code.
@@ -63,7 +67,7 @@ async def main():
     )
 
 
-if name == "main":
+if __name__ == "__main__":
     import asyncio
 
     asyncio.run(main())
@@ -76,23 +80,39 @@ This will set up the basic infrastructure for your `llama_deploy` system. You ca
 To deploy a workflow as a service, you can use the `deploy_workflow` function:
 
 ```python
-python
 from llama_deploy import (
     deploy_workflow,
     WorkflowServiceConfig,
     ControlPlaneConfig,
     SimpleMessageQueueConfig,
 )
-from llama_index.core.workflow import Workflow, StartEvent, StopEvent, step
+from llama_index.core.workflow import (
+    Context,
+    Event,
+    Workflow,
+    StartEvent,
+    StopEvent,
+    step,
+)
+
+
+class ProgressEvent(Event):
+    progress: str
 
 
 # create a dummy workflow
 class MyWorkflow(Workflow):
     @step()
-    async def run_step(self, ev: StartEvent) -> StopEvent:
+    async def run_step(self, ctx: Context, ev: StartEvent) -> StopEvent:
         # Your workflow logic here
         arg1 = str(ev.get("arg1", ""))
         result = arg1 + "_result"
+
+        # stream events as steps run
+        ctx.write_event_to_stream(
+            ProgressEvent(progress="I am doing something!")
+        )
+
         return StopEvent(result=result)
 
 
@@ -106,7 +126,7 @@ async def main():
     )
 
 
-if name == "main":
+if __name__ == "__main__":
     import asyncio
 
     asyncio.run(main())
@@ -119,7 +139,7 @@ This will deploy your workflow as a service within the `llama_deploy` system, an
 Once deployed, you can interact with your deployment using a client.
 
 ```python
-from llama_deploy import LlamaDeployClient
+from llama_deploy import LlamaDeployClient, ControlPlaneConfig
 
 # points to deployed control plane
 client = LlamaDeployClient(ControlPlaneConfig())
@@ -130,6 +150,25 @@ print(result)
 # prints 'hello_world_result'
 ```
 
+If you want to see the event stream as well, you can do:
+
+```python
+# create a session
+session = client.create_session()
+
+# kick off run
+task_id = session.run_nowait("streaming_workflow", arg1="hello_world")
+
+# stream events -- the will yield a dict representing each event
+for event in session.get_task_result_stream(task_id):
+    print(event)
+
+# get final result
+result = session.get_task_result(task_id)
+print(result)
+# prints 'hello_world_result'
+```
+
 ### Deploying Nested Workflows
 
 Every `Workflow` is capable of injecting and running nested workflows. For example
@@ -207,7 +246,7 @@ async def main():
     await asyncio.gather(inner_task, outer_task)
 
 
-if name == "main":
+if __name__ == "__main__":
     import asyncio
 
     asyncio.run(main())
@@ -460,6 +499,7 @@ async_client = AsyncLlamaDeployClient(ControlPlaneConfig())
 
 - `client.deregister_service(service_name)`: Deregisters a service from the control plane.
   Example:
+
   ```python
   client.deregister_service("my_workflow")
   ```
@@ -502,14 +542,45 @@ async_client = AsyncLlamaDeployClient(ControlPlaneConfig())
 
 - `session.get_task_result(task_id)`: Gets the result of a task in the session if it has one.
   Example:
+
   ```python
   result = session.get_task_result("task_123")
   if result:
       print(result.result)
   ```
 
-## Examples
+### Message Queue Integrations
+
+In addition to `SimpleMessageQueue`, we provide integrations for various
+message queue providers, such as RabbitMQ, Redis, etc. The general usage pattern
+for any of these message queues is the same as that for `SimpleMessageQueue`,
+however the appropriate extra would need to be installed along with `llama-deploy`.
 
-We have many examples showing how to use various message queues, and different ways to scaffold your project for deployment with docker and kubernetes.
+For example, for `RabbitMQMessageQueue`, we need to install the "rabbitmq" extra:
 
-You can find all examples in the [examples folder for the `llama-deploy` repository.](https://github.com/run-llama/llama_deploy/tree/main/examples)
+```sh
+# using pip install
+pip install llama-agents[rabbitmq]
+
+# using poetry
+poetry add llama-agents -E "rabbitmq"
+```
+
+Using the `RabbitMQMessageQueue` is then done as follows:
+
+```python
+from llama_agents.message_queue.rabbitmq import (
+    RabbitMQMessageQueueConfig,
+    RabbitMQMessageQueue,
+)
+
+message_queue_config = (
+    RabbitMQMessageQueueConfig()
+)  # loads params from environment vars
+message_queue = RabbitMQMessageQueue(**message_queue_config)
+```
+
+<!-- prettier-ignore-start -->
+> [!NOTE]
+> `RabbitMQMessageQueueConfig` can load its params from environment variables.
+<!-- prettier-ignore-end -->
diff --git a/e2e_tests/README.md b/e2e_tests/README.md
new file mode 100644
index 00000000..834086db
--- /dev/null
+++ b/e2e_tests/README.md
@@ -0,0 +1,9 @@
+# E2E Tests
+
+E2E tests are run in the `e2e-tests` workflow in `.github/workflows/e2e-tests.yml`.
+
+They are written such that a `run.sh` script can be executed to run some number of tests locally.
+
+Each folder in this directory represents a set of tests for simple scenarios.
+
+When new folders are added, they will be executed automatically in the CI/CD pipeline, assuming the `run.sh` script runs successfully.
diff --git a/e2e_tests/basic_streaming/launch_core.py b/e2e_tests/basic_streaming/launch_core.py
new file mode 100644
index 00000000..766fee4c
--- /dev/null
+++ b/e2e_tests/basic_streaming/launch_core.py
@@ -0,0 +1,14 @@
+from llama_deploy import deploy_core, ControlPlaneConfig, SimpleMessageQueueConfig
+
+
+async def main():
+    await deploy_core(
+        ControlPlaneConfig(),
+        SimpleMessageQueueConfig(),
+    )
+
+
+if __name__ == "__main__":
+    import asyncio
+
+    asyncio.run(main())
diff --git a/e2e_tests/basic_streaming/launch_workflow.py b/e2e_tests/basic_streaming/launch_workflow.py
new file mode 100644
index 00000000..a14abc42
--- /dev/null
+++ b/e2e_tests/basic_streaming/launch_workflow.py
@@ -0,0 +1,81 @@
+import asyncio
+from llama_index.core.workflow import (
+    Context,
+    Event,
+    Workflow,
+    StartEvent,
+    StopEvent,
+    step,
+)
+from llama_deploy import deploy_workflow, ControlPlaneConfig, WorkflowServiceConfig
+
+
+class ProgressEvent(Event):
+    progress: float
+
+
+class Step1(Event):
+    arg1: str
+
+
+class Step2(Event):
+    arg1: str
+
+
+class StreamingWorkflow(Workflow):
+    @step()
+    async def run_step_1(self, ctx: Context, ev: StartEvent) -> Step1:
+        arg1 = ev.get("arg1")
+        if not arg1:
+            raise ValueError("arg1 is required.")
+
+        ctx.write_event_to_stream(ProgressEvent(progress=0.3))
+
+        return Step1(arg1=str(arg1) + "_result")
+
+    @step()
+    async def run_step_2(self, ctx: Context, ev: Step1) -> Step2:
+        arg1 = ev.arg1
+        if not arg1:
+            raise ValueError("arg1 is required.")
+
+        ctx.write_event_to_stream(ProgressEvent(progress=0.6))
+
+        return Step2(arg1=str(arg1) + "_result")
+
+    @step()
+    async def run_step_3(self, ctx: Context, ev: Step2) -> StopEvent:
+        arg1 = ev.arg1
+        if not arg1:
+            raise ValueError("arg1 is required.")
+
+        ctx.write_event_to_stream(ProgressEvent(progress=0.9))
+
+        return StopEvent(result=str(arg1) + "_result")
+
+
+streaming_workflow = StreamingWorkflow(timeout=10)
+
+
+async def main():
+    # sanity check
+    result = await streaming_workflow.run(arg1="hello_world")
+    assert result == "hello_world_result_result_result", "Sanity check failed"
+
+    outer_task = asyncio.create_task(
+        deploy_workflow(
+            streaming_workflow,
+            WorkflowServiceConfig(
+                host="127.0.0.1",
+                port=8002,
+                service_name="streaming_workflow",
+            ),
+            ControlPlaneConfig(),
+        )
+    )
+
+    await asyncio.gather(outer_task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/e2e_tests/basic_streaming/run.sh b/e2e_tests/basic_streaming/run.sh
new file mode 100644
index 00000000..19f8df6d
--- /dev/null
+++ b/e2e_tests/basic_streaming/run.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+
+# Kill any previously running scripts
+echo "Killing any previously running scripts"
+pkill -f "launch_"
+
+# Wait for processes to terminate
+sleep 2
+
+set -e
+
+echo "Launching core"
+python ./launch_core.py &
+sleep 5
+
+echo "Launching workflow"
+python ./launch_workflow.py &
+sleep 5
+
+echo "Running client tests"
+python ./test_run_client.py
+
+# Kill any previously running scripts
+echo "Killing any previously running scripts"
+pkill -f "launch_"
diff --git a/e2e_tests/basic_streaming/test_run_client.py b/e2e_tests/basic_streaming/test_run_client.py
new file mode 100644
index 00000000..fda42c65
--- /dev/null
+++ b/e2e_tests/basic_streaming/test_run_client.py
@@ -0,0 +1,82 @@
+from llama_deploy import AsyncLlamaDeployClient, ControlPlaneConfig, LlamaDeployClient
+
+
+def test_run_client():
+    client = LlamaDeployClient(ControlPlaneConfig(), timeout=10)
+
+    # sanity check
+    sessions = client.list_sessions()
+    assert len(sessions) == 0, "Sessions list is not empty"
+
+    # test streaming
+    session = client.create_session()
+
+    # kick off run
+    task_id = session.run_nowait("streaming_workflow", arg1="hello_world")
+
+    num_events = 0
+    for event in session.get_task_result_stream(task_id):
+        if "progress" in event:
+            num_events += 1
+            if num_events == 1:
+                assert event["progress"] == 0.3, "First progress event is not 0.3"
+            elif num_events == 2:
+                assert event["progress"] == 0.6, "Second progress event is not 0.6"
+            elif num_events == 3:
+                assert event["progress"] == 0.9, "Third progress event is not 0.9"
+
+    # get final result
+    final_result = session.get_task_result(task_id)
+    assert (
+        final_result.result == "hello_world_result_result_result"
+    ), "Final result is not 'hello_world_result_result_result'"
+
+    # delete everything
+    client.delete_session(session.session_id)
+    sessions = client.list_sessions()
+    assert len(sessions) == 0, "Sessions list is not empty"
+
+
+async def test_run_client_async():
+    client = AsyncLlamaDeployClient(ControlPlaneConfig(), timeout=10)
+
+    # sanity check
+    sessions = await client.list_sessions()
+    assert len(sessions) == 0, "Sessions list is not empty"
+
+    # test streaming
+    session = await client.create_session()
+
+    # kick off run
+    task_id = await session.run_nowait("streaming_workflow", arg1="hello_world")
+
+    num_events = 0
+    async for event in session.get_task_result_stream(task_id):
+        if "progress" in event:
+            num_events += 1
+            if num_events == 1:
+                assert event["progress"] == 0.3, "First progress event is not 0.3"
+            elif num_events == 2:
+                assert event["progress"] == 0.6, "Second progress event is not 0.6"
+            elif num_events == 3:
+                assert event["progress"] == 0.9, "Third progress event is not 0.9"
+
+    final_result = await session.get_task_result(task_id)
+    assert (
+        final_result.result == "hello_world_result_result_result"
+    ), "Final result is not 'hello_world_result_result_result'"
+
+    # delete everything
+    await client.delete_session(session.session_id)
+    sessions = await client.list_sessions()
+    assert len(sessions) == 0, "Sessions list is not empty"
+
+
+if __name__ == "__main__":
+    import asyncio
+
+    print("Running async test")
+    asyncio.run(test_run_client_async())
+
+    print("Running sync test")
+    test_run_client()
diff --git a/e2e_tests/basic_workflow/launch_core.py b/e2e_tests/basic_workflow/launch_core.py
new file mode 100644
index 00000000..766fee4c
--- /dev/null
+++ b/e2e_tests/basic_workflow/launch_core.py
@@ -0,0 +1,14 @@
+from llama_deploy import deploy_core, ControlPlaneConfig, SimpleMessageQueueConfig
+
+
+async def main():
+    await deploy_core(
+        ControlPlaneConfig(),
+        SimpleMessageQueueConfig(),
+    )
+
+
+if __name__ == "__main__":
+    import asyncio
+
+    asyncio.run(main())
diff --git a/e2e_tests/basic_workflow/launch_workflow.py b/e2e_tests/basic_workflow/launch_workflow.py
new file mode 100644
index 00000000..279bc68d
--- /dev/null
+++ b/e2e_tests/basic_workflow/launch_workflow.py
@@ -0,0 +1,40 @@
+import asyncio
+from llama_index.core.workflow import Context, Workflow, StartEvent, StopEvent, step
+from llama_deploy import deploy_workflow, ControlPlaneConfig, WorkflowServiceConfig
+
+
+class OuterWorkflow(Workflow):
+    @step()
+    async def run_step(self, ctx: Context, ev: StartEvent) -> StopEvent:
+        arg1 = ev.get("arg1")
+        if not arg1:
+            raise ValueError("arg1 is required.")
+
+        return StopEvent(result=str(arg1) + "_result")
+
+
+outer = OuterWorkflow(timeout=10)
+
+
+async def main():
+    # sanity check
+    result = await outer.run(arg1="hello_world")
+    assert result == "hello_world_result", "Sanity check failed"
+
+    outer_task = asyncio.create_task(
+        deploy_workflow(
+            outer,
+            WorkflowServiceConfig(
+                host="127.0.0.1",
+                port=8002,
+                service_name="outer",
+            ),
+            ControlPlaneConfig(),
+        )
+    )
+
+    await asyncio.gather(outer_task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
diff --git a/e2e_tests/basic_workflow/run.sh b/e2e_tests/basic_workflow/run.sh
new file mode 100644
index 00000000..19f8df6d
--- /dev/null
+++ b/e2e_tests/basic_workflow/run.sh
@@ -0,0 +1,25 @@
+#!/bin/bash
+
+# Kill any previously running scripts
+echo "Killing any previously running scripts"
+pkill -f "launch_"
+
+# Wait for processes to terminate
+sleep 2
+
+set -e
+
+echo "Launching core"
+python ./launch_core.py &
+sleep 5
+
+echo "Launching workflow"
+python ./launch_workflow.py &
+sleep 5
+
+echo "Running client tests"
+python ./test_run_client.py
+
+# Kill any previously running scripts
+echo "Killing any previously running scripts"
+pkill -f "launch_"
diff --git a/e2e_tests/basic_workflow/test_run_client.py b/e2e_tests/basic_workflow/test_run_client.py
new file mode 100644
index 00000000..be441101
--- /dev/null
+++ b/e2e_tests/basic_workflow/test_run_client.py
@@ -0,0 +1,85 @@
+from llama_deploy import AsyncLlamaDeployClient, ControlPlaneConfig, LlamaDeployClient
+
+
+def test_run_client():
+    client = LlamaDeployClient(ControlPlaneConfig(), timeout=10)
+
+    # test connections
+    assert (
+        len(client.list_services()) == 1
+    ), f"Expected 1 service, got {client.list_services()}"
+    assert (
+        len(client.list_sessions()) == 0
+    ), f"Expected 0 sessions, got {client.list_sessions()}"
+
+    # test create session
+    session = client.get_or_create_session("fake_session_id")
+    sessions = client.list_sessions()
+    assert len(sessions) == 1, f"Expected 1 session, got {sessions}"
+    assert (
+        sessions[0].session_id == session.session_id
+    ), f"Expected session id to be {session.session_id}, got {sessions[0].session_id}"
+
+    # test run with session
+    result = session.run("outer", arg1="hello_world")
+    assert result == "hello_world_result"
+
+    # test number of tasks
+    tasks = session.get_tasks()
+    assert len(tasks) == 1, f"Expected 1 task, got {len(tasks)} tasks"
+    assert (
+        tasks[0].agent_id == "outer"
+    ), f"Expected id to be 'outer', got {tasks[0].agent_id}"
+
+    # delete everything
+    client.delete_session(session.session_id)
+    assert (
+        len(client.list_sessions()) == 0
+    ), f"Expected 0 sessions, got {client.list_sessions()}"
+
+
+async def test_run_client_async():
+    client = AsyncLlamaDeployClient(ControlPlaneConfig(), timeout=10)
+
+    # test connections
+    assert (
+        len(await client.list_services()) == 1
+    ), f"Expected 1 service, got {await client.list_services()}"
+    assert (
+        len(await client.list_sessions()) == 0
+    ), f"Expected 0 sessions, got {await client.list_sessions()}"
+
+    # test create session
+    session = await client.get_or_create_session("fake_session_id")
+    sessions = await client.list_sessions()
+    assert len(sessions) == 1, f"Expected 1 session, got {sessions}"
+    assert (
+        sessions[0].session_id == session.session_id
+    ), f"Expected session id to be {session.session_id}, got {sessions[0].session_id}"
+
+    # test run with session
+    result = await session.run("outer", arg1="hello_world")
+    assert result == "hello_world_result"
+
+    # test number of tasks
+    tasks = await session.get_tasks()
+    assert len(tasks) == 1, f"Expected 1 task, got {len(tasks)} tasks"
+    assert (
+        tasks[0].agent_id == "outer"
+    ), f"Expected id to be 'outer', got {tasks[0].agent_id}"
+
+    # delete everything
+    await client.delete_session(session.session_id)
+    assert (
+        len(await client.list_sessions()) == 0
+    ), f"Expected 0 sessions, got {await client.list_sessions()}"
+
+
+if __name__ == "__main__":
+    import asyncio
+
+    print("Running async test")
+    asyncio.run(test_run_client_async())
+
+    print("Running sync test")
+    test_run_client()
diff --git a/e2e_tests/run_all_e2e_tests.sh b/e2e_tests/run_all_e2e_tests.sh
new file mode 100644
index 00000000..6389d3f5
--- /dev/null
+++ b/e2e_tests/run_all_e2e_tests.sh
@@ -0,0 +1,11 @@
+#!/bin/bash
+
+set -e
+
+for test_dir in */; do
+    echo "Running tests in $test_dir"
+
+    cd $test_dir
+    sh ./run.sh
+    cd ..
+done
diff --git a/llama_deploy/client/async_client.py b/llama_deploy/client/async_client.py
index 1b8f30b6..17e3a6b2 100644
--- a/llama_deploy/client/async_client.py
+++ b/llama_deploy/client/async_client.py
@@ -1,7 +1,8 @@
+import asyncio
 import httpx
 import json
-import asyncio
-from typing import Any, List, Optional
+import time
+from typing import Any, AsyncGenerator, List, Optional
 
 from llama_deploy.control_plane.server import ControlPlaneConfig
 from llama_deploy.types import (
@@ -12,7 +13,7 @@
 )
 
 DEFAULT_TIMEOUT = 120.0
-DEFAULT_POLL_INTERVAL = 0.1
+DEFAULT_POLL_INTERVAL = 0.5
 
 
 class AsyncSessionClient:
@@ -45,6 +46,15 @@ async def _get_result() -> str:
 
         return await asyncio.wait_for(_get_result(), timeout=self.timeout)
 
+    async def run_nowait(self, service_name: str, **run_kwargs: Any) -> str:
+        """Implements the workflow-based run API for a session, but does not wait for the task to complete."""
+
+        task_input = json.dumps(run_kwargs)
+        task_def = TaskDefinition(input=task_input, agent_id=service_name)
+        task_id = await self.create_task(task_def)
+
+        return task_id
+
     async def create_task(self, task_def: TaskDefinition) -> str:
         """Create a new task in this session.
 
@@ -104,6 +114,39 @@ async def get_task_result(self, task_id: str) -> Optional[TaskResult]:
             data = response.json()
             return TaskResult(**data) if data else None
 
+    async def get_task_result_stream(
+        self, task_id: str
+    ) -> AsyncGenerator[dict[str, Any], None]:
+        """Get the result of a task in this session if it has one.
+
+        Args:
+            task_id (str): The ID of the task to get the result for.
+
+        Returns:
+            AsyncGenerator[str, None, None]: A generator that yields the result of the task.
+        """
+        start_time = time.time()
+        async with httpx.AsyncClient() as client:
+            while True:
+                try:
+                    response = await client.get(
+                        f"{self.control_plane_url}/sessions/{self.session_id}/tasks/{task_id}/result_stream"
+                    )
+                    response.raise_for_status()
+                    async for line in response.aiter_lines():
+                        json_line = json.loads(line)
+                        yield json_line
+                    break  # Exit the function if successful
+                except httpx.HTTPStatusError as e:
+                    if e.response.status_code != 404:
+                        raise  # Re-raise if it's not a 404 error
+                    if time.time() - start_time < self.timeout:
+                        await asyncio.sleep(self.poll_interval)
+                    else:
+                        raise TimeoutError(
+                            f"Task result not available after waiting for {self.timeout} seconds"
+                        )
+
 
 class AsyncLlamaDeployClient:
     def __init__(
@@ -140,7 +183,9 @@ async def list_sessions(self) -> List[SessionDefinition]:
         """
         async with httpx.AsyncClient(timeout=self.timeout) as client:
             response = await client.get(f"{self.control_plane_url}/sessions")
-            return [SessionDefinition(**session) for session in response.json()]
+            return [
+                SessionDefinition(**session) for session in response.json().values()
+            ]
 
     async def get_session(
         self, session_id: str, poll_interval: float = DEFAULT_POLL_INTERVAL
diff --git a/llama_deploy/client/sync_client.py b/llama_deploy/client/sync_client.py
index 9419b448..45ee41f5 100644
--- a/llama_deploy/client/sync_client.py
+++ b/llama_deploy/client/sync_client.py
@@ -1,7 +1,7 @@
 import httpx
 import json
 import time
-from typing import Any, List, Optional
+from typing import Any, Generator, List, Optional
 
 from llama_deploy.control_plane.server import ControlPlaneConfig
 from llama_deploy.types import (
@@ -12,7 +12,7 @@
 )
 
 DEFAULT_TIMEOUT = 120.0
-DEFAULT_POLL_INTERVAL = 0.1
+DEFAULT_POLL_INTERVAL = 0.5
 
 
 class SessionClient:
@@ -45,6 +45,15 @@ def run(self, service_name: str, **run_kwargs: Any) -> str:
 
         raise TimeoutError(f"Task {task_id} timed out after {self.timeout} seconds")
 
+    def run_nowait(self, service_name: str, **run_kwargs: Any) -> str:
+        """Implements the workflow-based run API for a session, but does not wait for the task to complete."""
+
+        task_input = json.dumps(run_kwargs)
+        task_def = TaskDefinition(input=task_input, agent_id=service_name)
+        task_id = self.create_task(task_def)
+
+        return task_id
+
     def create_task(self, task_def: TaskDefinition) -> str:
         """Create a new task in this session.
 
@@ -104,6 +113,44 @@ def get_task_result(self, task_id: str) -> Optional[TaskResult]:
             data = response.json()
             return TaskResult(**data) if data else None
 
+    def get_task_result_stream(
+        self, task_id: str
+    ) -> Generator[str | dict[str, Any], None, None]:
+        """Get the result of a task in this session if it has one.
+
+        Args:
+            task_id (str): The ID of the task to get the result for.
+            max_retries (int): Maximum number of retries if the result is not ready.
+            retry_delay (float): Delay in seconds between retries.
+
+        Returns:
+            Generator[str, None, None]: A generator that yields the result of the task.
+
+        Raises:
+            TimeoutError: If the result is not available after max_retries.
+        """
+        start_time = time.time()
+        with httpx.Client() as client:
+            while True:
+                try:
+                    response = client.get(
+                        f"{self.control_plane_url}/sessions/{self.session_id}/tasks/{task_id}/result_stream"
+                    )
+                    response.raise_for_status()
+                    for line in response.iter_lines():
+                        json_line = json.loads(line)
+                        yield json_line
+                    break  # Exit the function if successful
+                except httpx.HTTPStatusError as e:
+                    if e.response.status_code != 404:
+                        raise  # Re-raise if it's not a 404 error
+                    if time.time() - start_time < self.timeout:
+                        time.sleep(self.poll_interval)
+                    else:
+                        raise TimeoutError(
+                            f"Task result not available after waiting for {self.timeout} seconds"
+                        )
+
 
 class LlamaDeployClient:
     def __init__(
@@ -140,7 +187,9 @@ def list_sessions(self) -> List[SessionDefinition]:
         """
         with httpx.Client(timeout=self.timeout) as client:
             response = client.get(f"{self.control_plane_url}/sessions")
-            return [SessionDefinition(**session) for session in response.json()]
+            return [
+                SessionDefinition(**session) for session in response.json().values()
+            ]
 
     def get_session(
         self, session_id: str, poll_interval: float = DEFAULT_POLL_INTERVAL
diff --git a/llama_deploy/control_plane/server.py b/llama_deploy/control_plane/server.py
index 7cfc79a8..5029ab43 100644
--- a/llama_deploy/control_plane/server.py
+++ b/llama_deploy/control_plane/server.py
@@ -1,10 +1,12 @@
+import asyncio
 import json
 import uuid
 import uvicorn
 from fastapi import FastAPI, HTTPException
+from fastapi.responses import StreamingResponse
 from logging import getLogger
 from pydantic_settings import BaseSettings, SettingsConfigDict
-from typing import Dict, List, Optional
+from typing import AsyncGenerator, Dict, List, Optional, Any
 
 from llama_index.core.storage.kvstore.types import BaseKVStore
 from llama_index.core.storage.kvstore import SimpleKVStore
@@ -19,13 +21,14 @@
 from llama_deploy.message_queues.base import BaseMessageQueue, PublishCallback
 from llama_deploy.messages.base import QueueMessage
 from llama_deploy.orchestrators.base import BaseOrchestrator
-from llama_deploy.orchestrators.utils import get_result_key
+from llama_deploy.orchestrators.utils import get_result_key, get_stream_key
 from llama_deploy.types import (
     ActionTypes,
     SessionDefinition,
     ServiceDefinition,
     TaskDefinition,
     TaskResult,
+    TaskStream,
 )
 
 logger = getLogger(__name__)
@@ -217,6 +220,12 @@ def __init__(
             methods=["GET"],
             tags=["Sessions"],
         )
+        self.app.add_api_route(
+            "/sessions/{session_id}/tasks/{task_id}/result_stream",
+            self.get_task_result_stream,
+            methods=["GET"],
+            tags=["Sessions"],
+        )
 
     @property
     def message_queue(self) -> BaseMessageQueue:
@@ -241,6 +250,8 @@ async def process_message(self, message: QueueMessage) -> None:
             await self.add_task_to_session(task_def.session_id, task_def)
         elif action == ActionTypes.COMPLETED_TASK and message.data is not None:
             await self.handle_service_completion(TaskResult(**message.data))
+        elif action == ActionTypes.TASK_STREAM and message.data is not None:
+            await self.add_stream_to_session(TaskStream(**message.data))
         else:
             raise ValueError(f"Action {action} not supported by control plane")
 
@@ -426,7 +437,7 @@ async def handle_service_completion(
             collection=self.session_store_key,
         )
 
-        # generate and send new tasks (if any)
+        # generate and send new tasks when needed
         task_def = await self.send_task_to_service(task_def)
 
         await self.state_store.aput(
@@ -478,6 +489,95 @@ async def get_task_result(
 
         return result
 
+    async def add_stream_to_session(self, task_stream: TaskStream) -> None:
+        # get session
+        if task_stream.session_id is None:
+            raise ValueError(
+                f"Task stream with id {task_stream.stream_id} has no session"
+            )
+
+        session = await self.get_session(task_stream.session_id)
+
+        # add new stream data to session state
+        existing_stream = session.state.get(get_stream_key(task_stream.task_id), [])
+        existing_stream.append(task_stream.model_dump())
+        session.state[get_stream_key(task_stream.task_id)] = existing_stream
+
+        # update session state in store
+        await self.state_store.aput(
+            task_stream.session_id,
+            session.model_dump(),
+            collection=self.session_store_key,
+        )
+
+    async def get_task_result_stream(
+        self, session_id: str, task_id: str
+    ) -> StreamingResponse:
+        session = await self.get_session(session_id)
+
+        stream_key = get_stream_key(task_id)
+        if stream_key not in session.state:
+            raise HTTPException(status_code=404, detail="Task stream not found")
+
+        async def event_generator(
+            session: SessionDefinition, stream_key: str
+        ) -> AsyncGenerator[str | dict[str, Any], None]:
+            try:
+                stream_results = session.state[stream_key]
+                stream_results = sorted(stream_results, key=lambda x: x["index"])
+                for result in stream_results:
+                    if not isinstance(result, TaskStream):
+                        if isinstance(result, dict):
+                            result = TaskStream(**result)
+                        elif isinstance(result, str):
+                            result = TaskStream(**json.loads(result))
+                        else:
+                            raise ValueError("Unexpected result type in stream")
+
+                    yield json.dumps(result.data) + "\n"
+
+                # check if there is a final result
+                final_result = await self.get_task_result(task_id, session_id)
+                if final_result is not None:
+                    return
+
+                # Continue to check for new results
+                while True:
+                    await asyncio.sleep(
+                        self.step_interval
+                    )  # Small delay to prevent tight loop
+                    session = await self.get_session(session_id)
+                    new_results = session.state[stream_key][len(stream_results) :]
+                    new_results = sorted(new_results, key=lambda x: x["index"])
+
+                    for result in new_results:
+                        if not isinstance(result, TaskStream):
+                            if isinstance(result, dict):
+                                result = TaskStream(**result)
+                            elif isinstance(result, str):
+                                result = TaskStream(**json.loads(result))
+                            else:
+                                raise ValueError("Unexpected result type")
+
+                        yield json.dumps(result.data) + "\n"
+
+                    # check if there is a final result
+                    final_result = await self.get_task_result(task_id, session_id)
+                    if final_result is not None:
+                        return
+
+                    # update results list used for indexing
+                    stream_results.extend(new_results)
+            except Exception as e:
+                logger.error(
+                    f"Error in event stream for session {session_id}, task {task_id}: {str(e)}"
+                )
+                yield json.dumps({"error": str(e)}) + "\n"
+
+        return StreamingResponse(
+            event_generator(session, stream_key), media_type="application/x-ndjson"
+        )
+
     async def get_message_queue_config(self) -> Dict[str, dict]:
         """
         Gets the config dict for the message queue being used.
@@ -493,7 +593,6 @@ async def register_to_message_queue(self) -> StartConsumingCallable:
 
 
 if __name__ == "__main__":
-    import asyncio
     from llama_deploy import SimpleMessageQueue, SimpleOrchestrator
 
     control_plane = ControlPlaneServer(SimpleMessageQueue(), SimpleOrchestrator())
diff --git a/llama_deploy/deploy/deploy.py b/llama_deploy/deploy/deploy.py
index afef0ad3..3828c217 100644
--- a/llama_deploy/deploy/deploy.py
+++ b/llama_deploy/deploy/deploy.py
@@ -32,9 +32,14 @@
 DEFAULT_TIMEOUT = 120.0
 
 
-def _deploy_local_message_queue(config: SimpleMessageQueueConfig) -> asyncio.Task:
+async def _deploy_local_message_queue(config: SimpleMessageQueueConfig) -> asyncio.Task:
     queue = SimpleMessageQueue(**config.model_dump())
-    return asyncio.create_task(queue.launch_server())
+    task = asyncio.create_task(queue.launch_server())
+
+    # let message queue boot up
+    await asyncio.sleep(2)
+
+    return task
 
 
 def _get_message_queue_config(config_dict: dict) -> BaseSettings:
@@ -128,7 +133,7 @@ async def deploy_core(
         isinstance(message_queue_config, SimpleMessageQueueConfig)
         and not disable_message_queue
     ):
-        message_queue_task = _deploy_local_message_queue(message_queue_config)
+        message_queue_task = await _deploy_local_message_queue(message_queue_config)
     elif (
         isinstance(message_queue_config, SimpleMessageQueueConfig)
         and disable_message_queue
diff --git a/llama_deploy/orchestrators/simple.py b/llama_deploy/orchestrators/simple.py
index 01bd04a8..09d7a21d 100644
--- a/llama_deploy/orchestrators/simple.py
+++ b/llama_deploy/orchestrators/simple.py
@@ -92,6 +92,7 @@ async def add_result_to_state(
         cur_retries = state.get("retries", -1) + 1
         state["retries"] = cur_retries
 
+        # add result to state
         state[get_result_key(result.task_id)] = result
 
         return state
diff --git a/llama_deploy/orchestrators/utils.py b/llama_deploy/orchestrators/utils.py
index db9a9a9e..0e692294 100644
--- a/llama_deploy/orchestrators/utils.py
+++ b/llama_deploy/orchestrators/utils.py
@@ -1,2 +1,6 @@
 def get_result_key(task_id: str) -> str:
     return f"result_{task_id}"
+
+
+def get_stream_key(task_id: str) -> str:
+    return f"stream_{task_id}"
diff --git a/llama_deploy/services/workflow.py b/llama_deploy/services/workflow.py
index 386828bd..51863906 100644
--- a/llama_deploy/services/workflow.py
+++ b/llama_deploy/services/workflow.py
@@ -12,7 +12,7 @@
 from pydantic_settings import BaseSettings, SettingsConfigDict
 from typing import AsyncGenerator, Dict, Optional, Any
 
-from llama_index.core.workflow import Workflow
+from llama_index.core.workflow import Context, Workflow
 
 from llama_deploy.message_consumers.base import BaseMessageQueueConsumer
 from llama_deploy.message_consumers.callable import CallableMessageConsumer
@@ -25,6 +25,7 @@
     ActionTypes,
     NewTask,
     TaskResult,
+    TaskStream,
     ServiceDefinition,
     CONTROL_PLANE_NAME,
 )
@@ -67,6 +68,10 @@ class WorkflowState(BaseModel):
     run_kwargs: Dict[str, Any] = Field(
         default_factory=dict, description="Run kwargs needed to run the workflow."
     )
+    session_id: Optional[str] = Field(
+        default=None, description="Session ID for the current task."
+    )
+    task_id: str = Field(description="Task ID for the current run.")
 
 
 class WorkflowService(BaseService):
@@ -202,39 +207,33 @@ def publish_callback(self) -> Optional[PublishCallback]:
     def lock(self) -> asyncio.Lock:
         return self._lock
 
-    def load_workflow_state(self, workflow: Workflow, state: WorkflowState) -> Workflow:
-        """Fork the workflow with the given state.
+    def load_workflow_state(self, state: WorkflowState) -> Optional[Context]:
+        """Load the existing context from the workflow state.
 
-        TODO: Support managing the workflow state.
+        TODO: Support managing the workflow state?
         """
-        context_hash = state.hash
-        context_str = state.state
-        if not context_str:
-            return workflow
-
-        if hash(context_str + hash_secret) != context_hash:
-            raise ValueError("Context hash does not match. Possible data corruption.")
-
-        # only load context once it's been verified(?)
-
-        return workflow
+        return None
 
     def dump_workflow_state(
-        self, workflow: Workflow, run_kawrgs: dict
+        self, ctx: Context, current_state: WorkflowState
     ) -> WorkflowState:
         """Dump the workflow state.
 
-        TODO: Support managing the workflow state.
+        TODO: Support managing the workflow state?
         """
         context_bytes = pickle.dumps({})
         context_str = base64.b64encode(context_bytes).decode("ascii")
         context_hash = hash(context_str + hash_secret)
 
         return WorkflowState(
-            hash=context_hash, state=context_str, run_kwargs=run_kawrgs
+            hash=context_hash,
+            state=context_str,
+            run_kwargs=current_state.run_kwargs,
+            session_id=current_state.session_id,
+            task_id=current_state.task_id,
         )
 
-    async def process_call(self, task_id: str, current_call: WorkflowState) -> None:
+    async def process_call(self, current_call: WorkflowState) -> None:
         """Processes a given task, and writes a response to the message queue.
 
         Handles errors with a generic try/except, and publishes the error message
@@ -248,34 +247,54 @@ async def process_call(self, task_id: str, current_call: WorkflowState) -> None:
         """
         try:
             # load the state
-            self.load_workflow_state(self.workflow, current_call)
+            ctx = self.load_workflow_state(current_call)
 
             # run the workflow
-            result = await self.workflow.run(**current_call.run_kwargs)
+            handler = self.workflow.run(ctx=ctx, **current_call.run_kwargs)
+
+            index = 0
+            async for ev in handler.stream_events():
+                logger.debug(f"Publishing event: {ev}")
+
+                await self.message_queue.publish(
+                    QueueMessage(
+                        type=CONTROL_PLANE_NAME,
+                        action=ActionTypes.TASK_STREAM,
+                        data=TaskStream(
+                            task_id=current_call.task_id,
+                            session_id=current_call.session_id,
+                            data=ev.model_dump(),
+                            index=index,
+                        ).model_dump(),
+                    )
+                )
+                index += 1
 
-            # dump the state
-            updated_state = self.dump_workflow_state(
-                self.workflow, current_call.run_kwargs
-            )
+            final_result = await handler
+
+            # dump the state # dump the state
+            updated_state = self.dump_workflow_state(handler.ctx, current_call)
 
+            logger.debug(f"Publishing final result: {final_result}")
             await self.message_queue.publish(
                 QueueMessage(
                     type=CONTROL_PLANE_NAME,
                     action=ActionTypes.COMPLETED_TASK,
                     data=TaskResult(
-                        task_id=task_id,
+                        task_id=current_call.task_id,
                         history=[],
-                        result=str(result),
-                        data=updated_state.dict(),
+                        result=str(final_result),
+                        data=updated_state.model_dump(),
                     ).model_dump(),
                 )
             )
         except Exception as e:
-            logger.error(f"Encountered error in task {task_id}! {str(e)}")
+            if self.raise_exceptions:
+                raise e
+
+            logger.error(f"Encountered error in task {current_call.task_id}! {str(e)}")
             # dump the state
-            updated_state = self.dump_workflow_state(
-                self.workflow, current_call.run_kwargs
-            )
+            updated_state = self.dump_workflow_state(handler.ctx, current_call)
 
             # return failure
             await self.message_queue.publish(
@@ -283,18 +302,18 @@ async def process_call(self, task_id: str, current_call: WorkflowState) -> None:
                     type=CONTROL_PLANE_NAME,
                     action=ActionTypes.COMPLETED_TASK,
                     data=TaskResult(
-                        task_id=task_id,
+                        task_id=current_call.task_id,
                         history=[],
                         result=str(e),
-                        data=updated_state.dict(),
+                        data=updated_state.model_dump(),
                     ).model_dump(),
                 )
             )
         finally:
             # clean up
             async with self.lock:
-                self._outstanding_calls.pop(task_id, None)
-            self._ongoing_tasks.pop(task_id, None)
+                self._outstanding_calls.pop(current_call.task_id, None)
+            self._ongoing_tasks.pop(current_call.task_id, None)
 
     async def manage_tasks(self) -> None:
         """Acts as a manager to process outstanding tasks from a queue.
@@ -328,7 +347,7 @@ async def manage_tasks(self) -> None:
             for task_id, current_call in new_calls:
                 if len(self._ongoing_tasks) >= self.max_concurrent_tasks:
                     break
-                task = asyncio.create_task(self.process_call(task_id, current_call))
+                task = asyncio.create_task(self.process_call(current_call))
                 self._ongoing_tasks[task_id] = task
 
             await asyncio.sleep(0.1)  # Small sleep to prevent busy-waiting
@@ -357,6 +376,8 @@ async def process_message(self, message: QueueMessage) -> None:
             async with self.lock:
                 new_task.state["run_kwargs"] = json.loads(new_task.task.input)
                 workflow_state = WorkflowState(
+                    session_id=new_task.task.session_id,
+                    task_id=new_task.task.task_id,
                     **new_task.state,
                 )
                 self._outstanding_calls[new_task.task.task_id] = workflow_state
diff --git a/llama_deploy/types.py b/llama_deploy/types.py
index d4d630bd..2e57b355 100644
--- a/llama_deploy/types.py
+++ b/llama_deploy/types.py
@@ -77,6 +77,7 @@ class ActionTypes(str, Enum):
     REQUEST_FOR_HELP = "request_for_help"
     NEW_TOOL_CALL = "new_tool_call"
     COMPLETED_TOOL_CALL = "completed_tool_call"
+    TASK_STREAM = "task_stream"
 
 
 class TaskDefinition(BaseModel):
@@ -146,6 +147,10 @@ class TaskResult(BaseModel):
             The task result.
         data (dict):
             Additional data about the task or result.
+        is_last (bool):
+            If not true, there are more results to be streamed.
+        index (int):
+            The index of the task in the session.
     """
 
     task_id: str
@@ -154,6 +159,25 @@ class TaskResult(BaseModel):
     data: dict = Field(default_factory=dict)
 
 
+class TaskStream(BaseModel):
+    """
+    A stream of data generated by a task.
+
+    Attributes:
+        task_id (str):
+            The associated task ID.
+        data (List[dict]):
+            The stream data.
+        index (int):
+            The index of the stream data.
+    """
+
+    task_id: str
+    session_id: Optional[str]
+    data: dict
+    index: int
+
+
 class ToolCallBundle(BaseModel):
     """
     A bundle of information for a tool call.
diff --git a/poetry.lock b/poetry.lock
index 7b2d3247..0c9f0d2b 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
 
 [[package]]
 name = "aio-pika"
@@ -17,24 +17,24 @@ yarl = "*"
 
 [[package]]
 name = "aiobotocore"
-version = "2.15.0"
+version = "2.15.1"
 description = "Async client for aws services using botocore and aiohttp"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "aiobotocore-2.15.0-py3-none-any.whl", hash = "sha256:6d0b4a51d70bc33b1b4eba411076b0cc979aecbdad8e084bab202202423c0725"},
-    {file = "aiobotocore-2.15.0.tar.gz", hash = "sha256:988eef33fd9dd4b070959cfec922278e84166950695b2160bd581623cb6a420c"},
+    {file = "aiobotocore-2.15.1-py3-none-any.whl", hash = "sha256:0f738cde74108553b753b24655094289a3c7ea0f0f179ed1c0f8cea488999a35"},
+    {file = "aiobotocore-2.15.1.tar.gz", hash = "sha256:1f9f16eec2a3da32df162b5db12da779ec6d6c6311715c936cad511f436efa74"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.9.2,<4.0.0"
 aioitertools = ">=0.5.1,<1.0.0"
-botocore = ">=1.35.16,<1.35.17"
+botocore = ">=1.35.16,<1.35.24"
 wrapt = ">=1.10.10,<2.0.0"
 
 [package.extras]
-awscli = ["awscli (>=1.34.16,<1.34.17)"]
-boto3 = ["boto3 (>=1.35.16,<1.35.17)"]
+awscli = ["awscli (>=1.34.16,<1.34.24)"]
+boto3 = ["boto3 (>=1.35.16,<1.35.24)"]
 
 [[package]]
 name = "aiohappyeyeballs"
@@ -267,13 +267,13 @@ files = [
 
 [[package]]
 name = "anyio"
-version = "4.4.0"
+version = "4.6.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "anyio-4.4.0-py3-none-any.whl", hash = "sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7"},
-    {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"},
+    {file = "anyio-4.6.0-py3-none-any.whl", hash = "sha256:c7d2e9d63e31599eeb636c8c5c03a7e108d73b345f064f1c19fdc87b79036a9a"},
+    {file = "anyio-4.6.0.tar.gz", hash = "sha256:137b4559cbb034c477165047febb6ff83f390fc3b20bf181c1fc0a728cb8beeb"},
 ]
 
 [package.dependencies]
@@ -281,9 +281,9 @@ idna = ">=2.8"
 sniffio = ">=1.1"
 
 [package.extras]
-doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
-test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
-trio = ["trio (>=0.23)"]
+doc = ["Sphinx (>=7.4,<8.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.21.0b1)"]
+trio = ["trio (>=0.26.1)"]
 
 [[package]]
 name = "async-timeout"
@@ -317,13 +317,13 @@ tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
 
 [[package]]
 name = "botocore"
-version = "1.35.16"
+version = "1.35.23"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "botocore-1.35.16-py3-none-any.whl", hash = "sha256:3564a980d95ff2861a6ca74313173d8778aa659125c63cf49c93ad23896c63b1"},
-    {file = "botocore-1.35.16.tar.gz", hash = "sha256:1b48c94e8a4bbe23143f3d1c21a32b9ffc7476b651ef42371ab45d678f6dbfbc"},
+    {file = "botocore-1.35.23-py3-none-any.whl", hash = "sha256:cab9ec4e0367b9f33f0bc02c5a29f587b0119ecffd6d125bacee085dcbc8817d"},
+    {file = "botocore-1.35.23.tar.gz", hash = "sha256:25b17a9ccba6ad32bb5bf7ba4f52656aa03c1cb29f6b4e438050ee4ad1967a3b"},
 ]
 
 [package.dependencies]
@@ -336,13 +336,13 @@ crt = ["awscrt (==0.21.5)"]
 
 [[package]]
 name = "botocore-stubs"
-version = "1.35.21"
+version = "1.35.24"
 description = "Type annotations and code completion for botocore"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "botocore_stubs-1.35.21-py3-none-any.whl", hash = "sha256:ae3a0810110e831bf29f73772fbd137f37444e12b0945583cd18e0a12d809e6f"},
-    {file = "botocore_stubs-1.35.21.tar.gz", hash = "sha256:4859206b5766907ecfeff42c25d6596ffaa0b0528b0b41d7eaa081f59dc591fc"},
+    {file = "botocore_stubs-1.35.24-py3-none-any.whl", hash = "sha256:052eead5808ef138988089b6de6786f6271fc7f395ee0d4395e96e06ab04573c"},
+    {file = "botocore_stubs-1.35.24.tar.gz", hash = "sha256:20ca0d0c77215b599ab79e365f2bf5f909a49f4c5440bbbbb08175971a3de442"},
 ]
 
 [package.dependencies]
@@ -792,77 +792,84 @@ test = ["coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock", "mypy", "pre-commit",
 
 [[package]]
 name = "greenlet"
-version = "3.1.0"
+version = "3.1.1"
 description = "Lightweight in-process concurrent programming"
 optional = false
 python-versions = ">=3.7"
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 [package.extras]
@@ -993,13 +1000,13 @@ zstd = ["zstandard"]
 
 [[package]]
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-version = "0.11.10"
+version = "0.11.12"
 description = "Interface between LLMs and your data"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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 ]
 
 [package.dependencies]
@@ -2006,7 +2013,7 @@ files = [
 ]
 
 [package.dependencies]
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+greenlet = {version = "!=0.4.17", optional = true, markers = "python_version < \"3.13\" and (platform_machine == \"win32\" or platform_machine == \"WIN32\" or platform_machine == \"AMD64\" or platform_machine == \"amd64\" or platform_machine == \"x86_64\" or platform_machine == \"ppc64le\" or platform_machine == \"aarch64\") or extra == \"asyncio\""}
 typing-extensions = ">=4.6.0"
 
 [package.extras]
@@ -2036,13 +2043,13 @@ sqlcipher = ["sqlcipher3_binary"]
 
 [[package]]
 name = "starlette"
-version = "0.38.5"
+version = "0.38.6"
 description = "The little ASGI library that shines."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2140,13 +2147,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "types-aiobotocore"
-version = "2.15.0"
-description = "Type annotations for aiobotocore 2.15.0 generated with mypy-boto3-builder 8.0.1"
+version = "2.15.1"
+description = "Type annotations for aiobotocore 2.15.1 generated with mypy-boto3-builder 8.1.2"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
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 docdb-elastic = ["types-aiobotocore-docdb-elastic (>=2.15.0,<2.16.0)"]
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 ds = ["types-aiobotocore-ds (>=2.15.0,<2.16.0)"]
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 ebs = ["types-aiobotocore-ebs (>=2.15.0,<2.16.0)"]
@@ -2306,6 +2314,7 @@ forecastquery = ["types-aiobotocore-forecastquery (>=2.15.0,<2.16.0)"]
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 fsx = ["types-aiobotocore-fsx (>=2.15.0,<2.16.0)"]
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 globalaccelerator = ["types-aiobotocore-globalaccelerator (>=2.15.0,<2.16.0)"]
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-description = "Type annotations for aiobotocore.SNS 2.15.0 service generated with mypy-boto3-builder 8.0.1"
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 [package.dependencies]
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 [[package]]
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+version = "2.15.1"
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+    {file = "yarl-1.12.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7f68c40c010c14bd8f6e72de697d26076c8781424a5c49d304d79686601dad1a"},
+    {file = "yarl-1.12.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:86506c846feae80207dce9184ab624e54fdbb673c0d7cef19b534d3bf7b3db81"},
+    {file = "yarl-1.12.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:8f228b52b894a26d0dd9dd8ec00e1c81c7306781592cd6feb755aa1c506393ed"},
+    {file = "yarl-1.12.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:e1494cd90443dd24d4876e78a54e973b81ce3859d627b5440857a59d1acd605f"},
+    {file = "yarl-1.12.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:2b50effb9f07946245b23f1bab56640489643a69c1c78deff38f4cdc4537d29e"},
+    {file = "yarl-1.12.0-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:d78254767e9f989bf7eeb546a43499e14c81f0a2fcd47fb31c7d2b30e2234fc6"},
+    {file = "yarl-1.12.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:1b204e8d4ffcfe0fb5f2c1a2fbf674e93123418d83483a1824f65638b5a855a4"},
+    {file = "yarl-1.12.0-cp39-cp39-win32.whl", hash = "sha256:3c181855ef31dc3ddfb808e21dacce4526ee6908bbbb347fee4ad196d3f16f98"},
+    {file = "yarl-1.12.0-cp39-cp39-win_amd64.whl", hash = "sha256:d85245d8f84b3257a6fc2bc0608c84a7cf2b1bf2018c76a483268d45e739ea8e"},
+    {file = "yarl-1.12.0-py3-none-any.whl", hash = "sha256:f666914996c6f3a6253f7b4a9c9250554bdaa0eb63fe045da426b973f9eba138"},
+    {file = "yarl-1.12.0.tar.gz", hash = "sha256:4c801b9a281a7078e085efbc0e87f0938cea011928c0d48bdcb7c0a58451fb8e"},
 ]
 
 [package.dependencies]
@@ -2839,4 +2848,4 @@ redis = ["redis"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.11,<4.0"
-content-hash = "d1770facdd4ceeea02b1c86f0737e8b773028e7a659faec98c7502e3efeb5774"
+content-hash = "b8708c88a8c14a4857227b433e84f024652765bfc9c2fc813dbf7488dbaa55ac"
diff --git a/pyproject.toml b/pyproject.toml
index 2751c191..24923334 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -21,7 +21,7 @@ readme = "README.md"
 [tool.poetry.dependencies]
 python = ">=3.11,<4.0"
 fastapi = ">=0.109.1"
-llama-index-core = "^0.11.0"
+llama-index-core = "^0.11.10"
 pydantic-settings = ">=2.0,<3.0"
 PyYAML = ">6"
 uvicorn = ">=0.12.0"
diff --git a/tests/orchestrators/test_simple_orchestrator.py b/tests/orchestrators/test_simple_orchestrator.py
index 671fbecb..ada5e578 100644
--- a/tests/orchestrators/test_simple_orchestrator.py
+++ b/tests/orchestrators/test_simple_orchestrator.py
@@ -70,6 +70,7 @@ async def test_add_result_to_state() -> None:
 
     assert get_result_key(TASK_DEF.task_id) in new_state
     result = new_state[get_result_key(TASK_DEF.task_id)]
+
     assert isinstance(result, TaskResult)
     assert result.task_id == TASK_DEF.task_id
     assert result.result == "The secret fact is: A Cria is a baby llama."
diff --git a/tests/services/test_workflow_service.py b/tests/services/test_workflow_service.py
index 96439bcc..a245b4f0 100644
--- a/tests/services/test_workflow_service.py
+++ b/tests/services/test_workflow_service.py
@@ -62,7 +62,7 @@ async def test_workflow_service(
     # pass a task to the service
     task = TaskDefinition(
         input=json.dumps({"arg1": "test_arg1"}),
-        state=WorkflowState().dict(),
+        state=WorkflowState(task_id="test_task_id").model_dump(),
     )
 
     await workflow_service.process_message(
@@ -78,6 +78,6 @@ async def test_workflow_service(
     server_task.cancel()
 
     # check the result
-    result = human_output_consumer.processed_messages[0]
+    result = human_output_consumer.processed_messages[-1]
     assert result.action == ActionTypes.COMPLETED_TASK
     assert result.data["result"] == "test_arg1_result"