> ## Documentation Index
> Fetch the complete documentation index at: https://guide.gpt-trainer.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Chat with Chatbot

In this section, we will guide you on how to start chatting with your chatbot using the GPT-trainer API.
Before you begin, please ensure you meet the following prerequisites:

## Prerequisites

* An API key for accessing the GPT-trainer API.
* A development environment or tool for making HTTP requests, such as Curl or a programming language like Python.

<Note>
  Please note that to chat on specific topics, your chatbot needs to have
  relevant data sources uploaded.
</Note>

## Start with creating a chat session

### Why Create a Chat Session?

Before sending messages to the chatbot, it's essential to create a chat session. A chat session acts as a container that holds all the messages exchanged between you and the chatbot. Here's why creating a chat session is necessary:

1. **Message Context:** A chat session allows you to maintain context throughout a conversation. It ensures that the chatbot understands the context of your questions or statements.

2. **Order of Messages:** The chat session helps in maintaining the order of messages. This is crucial for having meaningful and coherent conversations with the chatbot.

3. **State Management:** The chat session allows you to manage the state of the conversation. You can continue a conversation seamlessly by referencing the same session UUID.

### Create a chat session

To create a chat session, you need to use a POST request to the API endpoint: `https://app.gpt-trainer.com/api/v1/chatbot/{chatbot_uuid}/session/create`.

<Warning>
  Make sure to replace `{chatbot_uuid}` with the UUID of your chatbot.
</Warning>

### Example Request

Here're example command to create a chatbot using the GPT-trainer API:

<Warning>Replace **token** with your actual API key.</Warning>

<CodeGroup>
  ```bash Curl theme={null}
  curl --location --request POST 'https://app.gpt-trainer.com/api/v1/chatbot/{chatbot_uuid}/session/create' \
  --header 'Content-Type: application/json' \
  --header 'Authorization: Bearer <token>' \
  ```

  ```py Python theme={null}
  import requests

  url = 'https://app.gpt-trainer.com/api/v1/chatbot/{chatbot_uuid}/session/create'
  headers = {
      'Content-Type': 'application/json',
      'Authorization': 'Bearer <token>'
  }


  response = requests.post(url,  headers=headers, params=params)

  if response.status_code == 200:
      print("Request successful!")
      print(response.json())
  else:
      print("Request failed with status code:", response.status_code)
      print(response.text)
  ```

  ```ts JavaScript theme={null}
  const axios = require("axios");

  const url =
    "https://app.gpt-trainer.com/api/v1/chatbot/{chatbot_uuid}/session/create";
  const headers = {
    "Content-Type": "application/json",
    Authorization: "Bearer <token>",
  };

  axios
    .post(url, { headers, params })
    .then((response) => {
      console.log("Request successful!");
      console.log(response.data);
    })
    .catch((error) => {
      console.error("Request failed:", error);
    });
  ```
</CodeGroup>

This API request returns JSON data that you can reuse to send messages:

```json theme={null}
{
  "created_at": "string",
  "modified_at": "string",
  "uuid": "string"
}
```

<Note>
  The uuid from this response is essential for sending messages within the
  established chat session. It will be used in the following steps.
</Note>

## Chat Within a Session

### Send Messages

With a chat session created, you can now send messages to your chatbot.
Use the following API endpoint to send messages and get a streamed AI response:\
`https://app.gpt-trainer.com/api/v1/session/{session_uuid}/message/stream`

<Warning>
  Make sure to replace `{session_uuid}` with the `uuid` obtained from the chat
  session creation response
</Warning>

### Example Request

Here're example command to create a message using the GPT-trainer API:

<Warning>Replace **token** with your actual API key.</Warning>

<CodeGroup>
  ```bash Curl theme={null}
  curl --location --request POST 'https://app.gpt-trainer.com/api/v1/session/{session_uuid}/message/stream' \
  --header 'Content-Type: application/json' \
  --header 'Authorization: Bearer YOUR_ACCESS_TOKEN' \
  --data-raw '{"query": "Your query goes here"}'
  ```

  ```py Python theme={null}
  import requests

  url = f"https://app.gpt-trainer.com/api/v1/session/{session_uuid}/message/stream"
  headers = {
      "Authorization": "Bearer YOUR_ACCESS_TOKEN",
      "Content-Type": "application/json"
  }

  data = {
      "query": "Your query goes here"
  }

  response = requests.post(url, headers=headers, json=data, stream=True)

  if response.status_code == 200:
      for line in response.iter_lines(decode_unicode=True):
          # Process streaming response here
          print(line + '\n')
  else:
      print("Error:", response.status_code)
  ```

  ```ts JavaScript theme={null}
  const xhr = new XMLHttpRequest();
  xhr.open(
    "POST",
    `https://app.gpt-trainer.com/api/v1/session/{session_uuid}/message/stream`,
    true
  );

  xhr.setRequestHeader("Authorization", "Bearer YOUR_ACCESS_TOKEN");
  xhr.setRequestHeader("Content-Type", "application/json;charset=UTF-8");

  const data = JSON.stringify({ query: "Your query goes here" });

  xhr.send(data);

  xhr.onprogress = () => {
    const streamingResponse = xhr.responseText;
    console.log(streamingResponse);
  };

  xhr.onreadystatechange = () => {
    if (xhr.readyState === 4) {
      if (xhr.status === 200) {
        console.log("Streaming completed successfully");
      } else {
        console.error("Error:", xhr.status);
      }
    }
  };
  ```
</CodeGroup>

That's it! You've now learned how to chat with your own chatbot using the GPT-trainer API.