Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

...

  • Give your chatbot (experiment) a name and description. 

  • Select your LLM type

    • Base Language Model

      • Select an LLM provider

      • Select a model (e.g. GPT-4)*

      • Select a temperature (can keep to 0.7 for now, we will provide more context soon)

      • Specify the prompt for the bot

    • Assistant

    • Pipeline (this is only available when you have the pipelines feature flag enabled)

  • Add a seed message (e.g. "hi"): every time a new chatbot session is initiated (e.g. by a user on WhatsApp/Telegram/web), this message will be sent to the chatbot behind the scenes so that the bot knows to kick off the conversation. It's important to add the seed message because this enables the first message of any interaction to be sent by the chatbot. 

  • Select any pre- and post-surveys and consent forms. 

  • Click the create button at the end. 

LLM Types

...

Base Language Model

Assistant

...

To understand assistants better, please refer to this and this. Instead of directly sending a query to the Language Model (LLM), you have the option to have an assistant address the user's inquiry, following a similar approach to the Base Language Model. Before utilizing this functionality, it is essential to set up an assistant in OpenChatStudio. To create an assistant, navigate to the “Assistants” section found in the sidebar. Assistants are equipped with the ability to access and search through files. Therefore, any source material that needs to be linked to the bot should be uploaded during the assistant creation process.

...

Pipeline

Info

This option is only available if you have the Pipelines feature flag enabled.

This allows you to run a pipeline on the user input. In this case, the pipeline will define your bot.

Note: Please contact ocs-info@dimagi.com for information about LLM providers and models.