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docs: update agent_execution_loop example code (#1350)

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# What does this PR do?
[Provide a short summary of what this PR does and why. Link to relevant
issues if applicable.]

- add missing `import`
- add client define
- update `attachments` to `documents`,
40da0d0e76

[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan
[Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.*]

[//]: # (## Documentation)

Signed-off-by: reidliu <reid201711@gmail.com>
Co-authored-by: reidliu <reid201711@gmail.com>
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Reid 2025-03-03 10:27:43 +08:00 • committed by GitHub
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1 changed files with 10 additions and 3 deletions
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13
docs/source/building_applications/agent_execution_loop.md
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@ -67,10 +67,17 @@ sequenceDiagram
Each step in this process can be monitored and controlled through configurations. Here's an example that demonstrates monitoring the agent's execution: Each step in this process can be monitored and controlled through configurations. Here's an example that demonstrates monitoring the agent's execution:
```python ```python
from llama_stack_client import LlamaStackClient
from llama_stack_client.lib.agents.agent import Agent
from llama_stack_client.lib.agents.event_logger import EventLogger from llama_stack_client.lib.agents.event_logger import EventLogger
from llama_stack_client.types.agent_create_params import AgentConfig
from rich.pretty import pprint from rich.pretty import pprint
# Replace host and port
client = LlamaStackClient(base_url=f"http://{HOST}:{PORT}")
agent_config = AgentConfig( agent_config = AgentConfig(
# Check with `llama-stack-client models list`
model="Llama3.2-3B-Instruct", model="Llama3.2-3B-Instruct",
instructions="You are a helpful assistant", instructions="You are a helpful assistant",
# Enable both RAG and tool usage # Enable both RAG and tool usage
@ -81,7 +88,7 @@ agent_config = AgentConfig(
}, },
"builtin::code_interpreter", "builtin::code_interpreter",
], ],
# Configure safety # Configure safety (optional)
input_shields=["llama_guard"], input_shields=["llama_guard"],
output_shields=["llama_guard"], output_shields=["llama_guard"],
# Control the inference loop # Control the inference loop
@ -98,7 +105,7 @@ session_id = agent.create_session("monitored_session")
# Stream the agent's execution steps # Stream the agent's execution steps
response = agent.create_turn( response = agent.create_turn(
messages=[{"role": "user", "content": "Analyze this code and run it"}], messages=[{"role": "user", "content": "Analyze this code and run it"}],
attachments=[ documents=[
{ {
"content": "https://raw.githubusercontent.com/example/code.py", "content": "https://raw.githubusercontent.com/example/code.py",
"mime_type": "text/plain", "mime_type": "text/plain",
@ -114,7 +121,7 @@ for log in EventLogger().log(response):
# Using non-streaming API, the response contains input, steps, and output. # Using non-streaming API, the response contains input, steps, and output.
response = agent.create_turn( response = agent.create_turn(
messages=[{"role": "user", "content": "Analyze this code and run it"}], messages=[{"role": "user", "content": "Analyze this code and run it"}],
attachments=[ documents=[
{ {
"content": "https://raw.githubusercontent.com/example/code.py", "content": "https://raw.githubusercontent.com/example/code.py",
"mime_type": "text/plain", "mime_type": "text/plain",