> ## Documentation Index
> Fetch the complete documentation index at: https://staging.docs.vocode.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Langchain agent

> Empower Langchain agents to interact with the real world via phone calls

# 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](https://python.langchain.com/en/latest/modules/agents.html)
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.

<div>
  <iframe
    style={{
  width: "100%",
  height: "300px",
  paddingLeft: "75px",
  paddingRight: "75px",
}}
    src="https://www.loom.com/embed/ba80f55524944ccc8c3b437b7a909270"
  />
</div>

<br />

# How to run it

## Requirements

1. Install [Ngrok](https://ngrok.com/)
2. Install [Redis](https://redis.com/)
3. Install [Poetry](https://python-poetry.org/)

## 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](https://github.com/vocodedev/vocode-python/tree/main/apps/langchain_agent) directory.

```bash theme={null}
git clone https://github.com/vocodedev/vocode-python.git
```

### Environment

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

* [Deepgram](https://deepgram.com) (for speech transcription)
* [OpenAI](https://platform.openai.com) (for the underlying agent)
* [Azure](https://azure.microsoft.com/en-us/products/cognitive-services/text-to-speech/) (for speech synthesis)
* [Twilio](https://console.twilio.com/) (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](https://support.twilio.com/hc/en-us/articles/223180048-Adding-a-Verified-Phone-Number-or-Caller-ID-with-Twilio) 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
```

### Set up self-hosted telephony server

Run the following setups from the `langchain_agent` directory.

#### 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
```

#### Running with Python

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

```
python3 -m venv venv
source venv/bin/activate
```

2. Install requirements

```bash theme={null}
poetry install
```

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

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

4. Run the `TelephonyServer`:

```bash theme={null}
uvicorn telephony_app:app --reload --port 3000
```

### 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`

```python theme={null}
CONTACTS = [{"name": "Kian", "phone": "+123456789"}]
```

2. Run `main.py`

```bash theme={null}
poetry install
poetry run python main.py
```

# Code explanation

🚧 Under construction