where do we get logs for agents?
# ask-ai
b
where do we get logs for agents?
g
It seems likely that you can capture logs for LiveKit agents by using the logging features provided in the LiveKit framework. According to the LiveKit documentation, you can log performance and usage metrics for debugging and insights. This involves subscribing to the
metrics_collected
event and using the
log_metrics
helper function to format and log the metrics. Additionally, if you are using a speech-to-speech agent, the logs for user and agent interactions are automatically logged in the console of the backend process. You can also enable more verbose logging by setting the log level to debug, as mentioned in a Slack discussion. Would you like more detailed information on how to set up logging for specific types of agents or environments? Sources: - Capturing metrics | LiveKit Docs - Slack discussion 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.
b
@millions-hair-24956 I am making a multi-tanant system, so I want some suggestions how should I creates rooms, and should every tanent have a different agent name?
g
It seems likely that for a multi-tenant system using LiveKit, you should consider creating separate rooms for each tenant to ensure isolation and manageability. According to a Slack discussion, using unique room names for each tenant can help in organizing and managing the rooms effectively. You can use a naming convention that includes the tenant's identifier, such as
tenant1_room1
, to easily distinguish between rooms. Regarding agent names, it might be beneficial to have different agent names for each tenant to personalize the experience and maintain clarity in interactions. This can be achieved by configuring the agent's identity or metadata when generating the access token for the room connection, as suggested in the LiveKit documentation. Would you like more detailed guidance on implementing these suggestions or any specific aspect of the multi-tenant setup? Sources: - Slack discussion - LiveKit documentation 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.
b
@millions-hair-24956 can you provide some coding sample to such system
g
Certainly! Here's a basic example of how you might set up a multi-tenant system with LiveKit, where each tenant has their own room and agent. This example uses Python to create rooms and generate tokens for each tenant.
Copy code
import os
from livekit import rtc, agents
from livekit.agents import WorkerOptions
from livekit.server_sdk import RoomServiceClient, AccessToken

# Load environment variables
LIVEKIT_URL = os.getenv("LIVEKIT_URL")
API_KEY = os.getenv("LIVEKIT_API_KEY")
API_SECRET = os.getenv("LIVEKIT_API_SECRET")

# Function to create a room for a tenant
def create_room(tenant_id):
    room_name = f"{tenant_id}_room"
    room_client = RoomServiceClient(LIVEKIT_URL, API_KEY, API_SECRET)
    room_client.create_room(name=room_name)
    return room_name

# Function to generate a token for a tenant's agent
def generate_token(tenant_id, room_name):
    identity = f"{tenant_id}_agent"
    token = AccessToken(API_KEY, API_SECRET, identity=identity)
    token.add_grant({
        "room": room_name,
        "roomJoin": True,
        "canPublish": True,
        "canSubscribe": True
    })
    return token.to_jwt()

# Example usage
tenant_id = "tenant1"
room_name = create_room(tenant_id)
token = generate_token(tenant_id, room_name)

print(f"Room created: {room_name}")
print(f"Token for agent: {token}")
This code snippet demonstrates how to create a room for each tenant and generate a token for an agent associated with that tenant. The room name and agent identity are customized based on the tenant ID. Would you like more detailed information on any specific part of this setup? Sources: - https://livekit-users.slack.com/archives/C07FY8WHGPM/p1728956116.368569 - https://docs.livekit.io/home/server/managing-rooms/ 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.
b
@millions-hair-24956 l do I need to create room for every call, or once I created they stay there for. some time, because now i can see that I need to generate token,this is one more api call for every call
@millions-hair-24956 l do I need to create room for every call, or once I created they stay there for. some time, because now i can see that I need to generate token,this is one more api call for every call
g
Rooms in LiveKit can be created once and remain available for a certain period, even if they are empty. According to the LiveKit documentation, a room is automatically created when the first participant joins and is closed when the last participant leaves. However, you can configure the room to stay open for a specified duration after it becomes empty by setting the
empty_timeout
parameter when creating the room. This allows the room to persist for a while, reducing the need to recreate it for every call. Regarding tokens, each participant needs a unique access token to join a room. Tokens are typically generated on the server side and are required for each new connection to ensure secure access. While this does involve an API call for each participant, it is necessary for maintaining security and managing permissions. Would you like more detailed information on configuring room persistence or token generation? Sources: - LiveKit Room Management 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.
b
@millions-hair-24956 does live-kit uses any vactor storage, I have no I idea how a rag is implemented for an agent .
g
LiveKit uses vector storage through its RAG (Retrieval-Augmented Generation) plugin, which integrates with vector databases like Annoy for efficient vector retrieval. According to the LiveKit RAG documentation, the
AnnoyIndex
class is used to manage and query vector data. This class allows you to load, query, and manage vector indices, which are essential for implementing RAG in an agent. To implement RAG for an agent, you would typically: 1. Create and Load Index: Use the
AnnoyIndex
class to create or load a vector index from a file. 2. Add Items: Add vector data to the index using the
add_item
method. 3. Build Index: Use the
build
method to prepare the index for querying. 4. Query Index: Retrieve similar vectors using the
query
method, which returns the closest matches to a given vector. Would you like more detailed guidance on setting up RAG with LiveKit? Sources: - LiveKit RAG Annoy Documentation 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.