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Introduction

This example shows how to use Vocode as a tool augmenting the abilities of a Langchain agent. By providing it with access to Vocode, a Langchain Agent can now make autonomous phone calls and take action based on the outcome of the calls.

Our demo will walk through how to instruct the agent to lookup a phone number and make the appropriate call.

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How to run it

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Requirements

1. Install Ngrok
2. Install Redis
3. Install Poetry

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Run the example

Note: gpt-4 is required for this to work. gpt-3.5-turbo or older models are not smart enough to parse JSON responses in Langchain agents reliably out-of-the-box.

To get started, clone the Vocode repo or copy the Langchain agent app directory.

git clone https://github.com/vocodedev/vocode-python.git

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Environment

1. Copy the .env.template and fill in your API keys. You’ll need:

• Deepgram (for speech transcription)
• OpenAI (for the underlying agent)
• Azure (for speech synthesis)
• Twilio (for telephony)

2. Tunnel port 3000 to ngrok by running:

ngrok http 3000

Fill in the TELEPHONY_SERVER_BASE_URL environment variable with your ngrok base URL: don’t include https:// so should be something like:

TELEPHONY_SERVER_BASE_URL=asdf1234.ngrok.app

3. Buy a phone number on Twilio or verify your caller ID to use as the outbound phone number. Set this phone number as the OUTBOUND_CALLER_NUMBER environment variable. Include + and the area code, so for a US phone number, it would look something like.

OUTBOUND_CALLER_NUMBER=+15555555555

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Set up self-hosted telephony server

Run the following setups from the langchain_agent directory.

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Running with Docker

1. Build the telephony server Docker image

docker build -t vocode-langchain-agent-telephony-app .

2. Run the service using docker-compose

docker-compose up

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Running with Python

1. (optional) Set up a Python environment: we recommend virtualenv

python3 -m venv venv
source venv/bin/activate

2. Install requirements

poetry install

3. Run an instance of Redis at http://localhost:6379. With Docker, this can be done with:

docker run -dp 6379:6379 -it redis/redis-stack:latest

4. Run the TelephonyServer:

uvicorn telephony_app:app --reload --port 3000

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Set up the Langchain agent

With the self-hosted telephony server running:

1. Update the phone numbers in the contact book in tools/contacts.py

CONTACTS = [{"name": "Kian", "phone": "+123456789"}]

2. Run main.py

poetry install
poetry run python main.py

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Code explanation

🚧 Under construction