how to set up client tools to create function calls in my python code? | ElevenLabs | Page 1

#

AI-generated Answer for dicartagena

To set up client tools for creating function calls in your Python code using ElevenLabs, you can follow these steps:

Install the ElevenLabs Python Package: First, you need to install the elevenlabs package in your project. You can do this using pip:
```
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 that the pyaudio package might require additional system dependencies. For Debian-based systems, you can install these with:
```
sudo apt install portaudio19
```

Import Necessary Dependencies: In your Python script, import the required modules:

import os
import signal
from elevenlabs.client import ElevenLabs
from elevenlabs.conversational_ai.conversation import Conversation
from elevenlabs.conversational_ai.default_audio_interface import DefaultAudioInterface

Load Environment Variables: Load your agent ID and API key from environment variables:
```
agent_id = os.getenv("AGENT_ID")
api_key = os.getenv("ELEVENLABS_API_KEY")
```
Create the ElevenLabs Client Instance: Initialize the client with your API key:
```
client = ElevenLabs(api_key=api_key)
```

Initialize the Conversation Instance: Set up the conversation with the necessary parameters:

conversation = Conversation(
    client,
    agent_id,
    requires_auth=bool(api_key),
    audio_interface=DefaultAudioInterface(),
    callback_agent_response=lambda response: print(f"Agent: {response}"),
    callback_agent_response_correction=lambda original, corrected: print(f"Agent: {original} -> {corrected}"),
    callback_user_transcript=lambda transcript: print(f"User: {transcript}")
)

Start the Conversation: Begin the session and handle clean shutdowns:

conversation.start_session()
signal.signal(signal.SIGINT, lambda sig, frame: conversation.end_session())
conversation_id = conversation.wait_for_session_end()
print(f"Conversation ID: {conversation_id}")

By following these steps, you can set up your Python environment to create function calls using the ElevenLabs client tools.

#

AI-generated Answer for dicartagena

To set up client tools for function calls in your Python code, you need to ensure the following steps are in place:

Define the Endpoint: Create an endpoint in your Python application that will handle the tool call. For example:

from fastapi import FastAPI, Body, HTTPException
from fastapi.responses import JSONResponse
from typing import Dict

app = FastAPI()

@app.post("/tool_endpoint/", status_code=200)
def tool_function(body: Dict[str, str] = Body(...)):
    try:
        # Extract data from the request body
        transcript = body.get("transcript")
        user_id = body.get("user_id")
        unit_id = body.get("unit_id")
        unit_name = body.get("unit_name")
    except:
        raise HTTPException(status_code=400, detail="Bad Request")

    # Process the data (example function call)
    response = process_data(transcript, user_id, unit_id, unit_name)

    # Return the response
    return JSONResponse(content={"response": response, "user_id": user_id, "unit_id": unit_id})

def process_data(transcript, user_id, unit_id, unit_name):
    # Example processing logic
    return f"Processed data for {unit_name} with transcript: {transcript}"

Test the Endpoint: Use a tool like Postman or curl to test the endpoint. Send a POST request with a JSON body, for example:
```
{
    "user_id": "user1",
    "unit_id": "a0L4K000008UDoJUAW",
    "unit_name": "NEST3G07",
    "transcript": "Hello, how can I help you?"
}
```
Ensure the endpoint responds correctly with the expected output.
Secure the Endpoint: Make sure the endpoint is served over HTTPS. If your endpoint redirects to an insecure HTTP address, the tool call will fail. Use a valid HTTPS URL for your endpoint.
Integrate with the Conversational AI: Configure the tool in the Conversational AI platform to call your endpoint. Ensure the tool is set up with the correct URL and matches the expected request format.

Handle Errors Gracefully: Add error handling in your code to manage unexpected inputs or failures. For example:

try:
    # Your logic here
except Exception as e:
    return JSONResponse(content={"error": str(e)}, status_code=500)

Debugging: If the tool call fails, check the logs on both the Conversational AI platform and your server. Ensure the endpoint URL is correct, and no required headers or parameters are missing.

By following these steps, you can set up a client tool to create function calls in your Python code. Let me know if you need further clarification!

#how to set up client tools to create function calls in my python code?