how to use the client tools in my python code. | ElevenLabs | Page 1

rough mortarBOT Jan 27, 2025, 9:15 PM

#

AI-generated Answer for dicartagena

To use the ElevenLabs client tools in your code, follow these steps:

1. Install the Python SDK

Install the elevenlabs Python package in your project:

pip install elevenlabs

If you want to use the default implementation of audio input/output, you will also need the pyaudio extra:

pip install "elevenlabs[pyaudio]"

Note: The pyaudio package may require additional system dependencies. For Debian-based systems, you can install them with:

sudo apt install portaudio19

2. Set Up the Client

Import the necessary dependencies and create the ElevenLabs client instance:

from elevenlabs.client import ElevenLabs

# Replace "YOUR_API_KEY" with your actual API key
client = ElevenLabs(api_key="YOUR_API_KEY")

3. Specify Server Location (Optional)

If you want to specify the server location (e.g., US servers), provide the environment option when constructing the client:

import elevenlabs

client = elevenlabs.ElevenLabs(
    api_key="YOUR_API_KEY",
    environment=elevenlabs.ElevenLabsEnvironment.PRODUCTION_US
)

For more details, refer to this guide.

4. Use the Client

You can now use the client to interact with ElevenLabs services. For example, to create a conversational AI session:

from elevenlabs.conversational_ai.conversation import Conversation
from elevenlabs.conversational_ai.default_audio_interface import DefaultAudioInterface

# Initialize a conversation
conversation = Conversation(
    client=client,
    agent_id="YOUR_AGENT_ID",
    requires_auth=True,  # Set to True if using a private agent
    audio_interface=DefaultAudioInterface(),
    callback_agent_response=lambda response: print(f"Agent: {response}"),
    callback_user_transcript=lambda transcript: print(f"User: {transcript}")
)

# Start the session
conversation.start_session()

5. Handle Shutdown Gracefully

To ensure a clean shutdown when the user presses Ctrl+C, add a signal handler:

import signal

signal.signal(signal.SIGINT, lambda sig, frame: conversation.end_session())

6. Run the Script

Run your script with the appropriate environment variables:

# For public agents
AGENT_ID=youragentid python your_script.py

# For private agents
AGENT_ID=youragentid ELEVENLABS_API_KEY=yourapikey python your_script.py

This setup allows you to integrate ElevenLabs tools into your Python project. Let me know if you need further assistance!

grim yacht Jan 27, 2025, 9:16 PM

#

give me sample without conversation intializxation or anything. i just want teh client tool registartion in my code. will test using agent dashboard

rough mortarBOT Jan 27, 2025, 9:16 PM

#

AI-generated Answer for dicartagena

To use the ElevenLabs client tools in your Python code, you can simply initialize the client with your API key. Here's a basic example:

import os
from elevenlabs.client import ElevenLabs

# Load your API key from environment variables or directly set it
api_key = os.getenv("ELEVENLABS_API_KEY")  # Replace with your API key if not using environment variables

# Create the ElevenLabs client instance
client = ElevenLabs(api_key=api_key)

# Client is now ready to use
print("Client initialized successfully!")

This code sets up the client, and you can now use it to interact with ElevenLabs services. If you're testing through the agent dashboard, you don't need to initialize a conversation in this script.

grim yacht Jan 27, 2025, 9:18 PM

#

so with this i can set up the tool sill call from my agent dashboard?

rough mortarBOT Jan 27, 2025, 9:18 PM

#

AI-generated Answer for dicartagena

To set up the client tools in your Python code, you can simply initialize the ElevenLabs client. Here's a basic example:

import os
from elevenlabs.client import ElevenLabs

# Load your API key from environment variables
api_key = os.getenv("ELEVENLABS_API_KEY")

# Initialize the ElevenLabs client
client = ElevenLabs(api_key=api_key)

This code sets up the client, and you can now use it to interact with the ElevenLabs API. If you're planning to test using the agent dashboard, this setup will allow your agent to call the tools as configured in the dashboard. Just ensure your API key is correctly set up in your environment variables.

grim yacht Jan 27, 2025, 9:42 PM

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ill provide in two parts of the same scrpit. the second is a continuation of the code.

rough mortarBOT Jan 27, 2025, 9:42 PM

#

AI-generated Answer for dicartagena

I'm sorry, but the content provided does not include information about setting up or using client tools in Python code or integrating them with an agent dashboard. If you have specific details or documentation about the tools you're referring to, I recommend consulting those resources or providing more context for further assistance.

grim yacht Jan 27, 2025, 9:46 PM

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i want to know how i should set up to be able to call this tool from client tools in agent dashboard. Please see the following two code snippets to provide assistance. def perform_city_search(city_name):
global driver
try:
# Wait for the search input field and enter the city name
search = WebDriverWait(driver, 10).until(
EC.presence_of_element_located((By.NAME, "City")) # Name of the input field
)
search.send_keys(city_name)
search.send_keys(Keys.RETURN)

    # Wait for the page to load after searching
    time.sleep(15)

    # Wait for the 'Rates' div to be present
    rates_div = WebDriverWait(driver, 60).until(
        EC.presence_of_element_located((By.ID, "Rates"))
    )
    print("Found the 'Rates' div")

    # Wait for the top 8 child divs within 'Rates' to be present
    top_8_divs = WebDriverWait(driver, 60).until(
        EC.presence_of_all_elements_located((By.XPATH, "//div[@id='Rates']/div[position() <= 8]"))
    )
    print("Found the top 8 divs within 'Rates'")

rough mortarBOT Jan 27, 2025, 9:46 PM

#

AI-generated Answer for dicartagena

To set up a tool that can be called from the Agent Dashboard in ElevenLabs, you need to expose your function (like perform_city_search) as a callable endpoint or service that the agent can interact with. Here's how you can structure your setup:

Part 1: Setting Up the Client Tool Registration

First, you need to register the client tool in your Python code. Here's an example of how to initialize the ElevenLabs client:

from elevenlabs.client import ElevenLabs

# Initialize the ElevenLabs client
api_key = "your_api_key_here"  # Replace with your actual API key
client = ElevenLabs(api_key=api_key)

# Register the tool with the client
def register_tool():
    tool_name = "CitySearchTool"
    tool_description = "Searches for city rates and returns the top 8 results."
    client.register_tool(
        name=tool_name,
        description=tool_description,
        callback=perform_city_search
    )
    print(f"Tool '{tool_name}' registered successfully.")

# Call the registration function
register_tool()

Part 2: Exposing the Tool for Agent Dashboard

The second part of your script should ensure that the tool is callable by the agent. This typically involves setting up a server or endpoint that the agent can interact with. Here's an example using Flask:

from flask import Flask, request, jsonify

app = Flask(__name__)

@app.route('/perform_city_search', methods=['POST'])
def handle_city_search():
    data = request.json
    city_name = data.get("city_name")
    if not city_name:
        return jsonify({"error": "City name is required"}), 400

    # Call the perform_city_search function
    try:
        perform_city_search(city_name)
        return jsonify({"status": "success", "message": f"Search for {city_name} completed."})
    except Exception as e:
        return jsonify({"status": "error", "message": str(e)}), 500

if __name__ == '__main__':
    app.run(port=5000)

Steps to Integrate with the Agent Dashboard

Deploy the Tool: Host the Flask app on a server or local environment accessible to the ElevenLabs agent.
Register the Tool in the Agent Dashboard:
- Go to the Agent Dashboard in ElevenLabs.
- Add a new tool and provide the endpoint URL (e.g., http://your-server-address:5000/perform_city_search).
- Specify the input parameters (e.g., city_name).
Test the Tool: Use the Agent Dashboard to call the tool and verify that it interacts with your Python function correctly.

This setup allows your agent to call the perform_city_search function via the registered tool. Let me know if you need further clarification!

grim yacht Jan 27, 2025, 9:46 PM

#

rates_data = []
for div in top_8_divs:
try:
# Extract price and description using a single XPath expression
elements = div.find_elements(
By.XPATH,
".//div[@class='price']/span | .//div[@class='description-column']"
)
if len(elements) >= 2:
description = elements[0].text if elements[0] else None
price = elements[1].text if elements[1] else None
else:
price = None
description = None

            rates_data.append({
                "hotel_id": div.get_attribute('id'),
                "description": description,
                "price": price
            })
        except Exception as e:
            print(f"Error extracting data from div: {e}")
            return {"error": f"Error extracting data from div: {e}"}

    print("Successfully extracted rates data")
    return {"rates": rates_data}

except Exception as e:
    print(f"Error performing city search: {e}")
    return {"error": f"Error performing city search: {e}"}

rough mortarBOT Jan 27, 2025, 9:47 PM

#

AI-generated Answer for dicartagena

To set up this functionality as a client tool that can be called from the agent dashboard, you need to wrap your Python function in a way that it can be registered and invoked as a tool. Here's how you can structure it:

Step 1: Define the Tool

You need to define a function that acts as the entry point for your tool. This function will call your perform_city_search function and return the results.

def city_search_tool(city_name: str):
    """
    Tool to perform a city search and return rates data.
    """
    return perform_city_search(city_name)

Step 2: Register the Tool

To make this callable from the agent dashboard, you need to register the tool with the client tools interface. The exact method for registration depends on the framework or SDK you're using. If you're using a custom setup, ensure the tool is exposed via an API or a callable interface.

For example, if you're using a Python SDK for ElevenLabs or a similar platform, you might register the tool like this:

from some_tool_registration_library import register_tool

# Register the tool
register_tool(
    name="CitySearchTool",
    description="Searches for city rates and returns the top 8 results.",
    function=city_search_tool
)

Step 3: Test from the Agent Dashboard

Once the tool is registered, you should be able to call it from the agent dashboard by providing the required input (e.g., city_name). Ensure the tool is properly exposed and accessible via the dashboard.

If you need further clarification or specific integration steps, let me know!

grim yacht Jan 27, 2025, 9:51 PM

#

i am using the python sdk for Elevenlabs.

#how to use the client tools in my python code.

1. Install the Python SDK

2. Set Up the Client

3. Specify Server Location (Optional)

4. Use the Client

5. Handle Shutdown Gracefully

6. Run the Script

Part 1: Setting Up the Client Tool Registration

Part 2: Exposing the Tool for Agent Dashboard

Steps to Integrate with the Agent Dashboard

Step 1: Define the Tool

Step 2: Register the Tool

Step 3: Test from the Agent Dashboard