When the tool applyDocumentOperations is used, we have to force the
usage of a system prompt in order to force the model to use it the right
without inventing different actions. The pydantic Agent class can use a
system prompt but this noe is ignoried when a UI adapter is used like
the VercelAiAdapter.
The frontend application is using Vercel AI SDK and it's data stream
protocol. We decided to use the pydantic AI library to use it's vercel
ai adapter. It will make the payload validation, use AsyncIterator and
deal with vercel specification.
Standard can vary depending on the AI service used.
To work with Albert API:
- a description field is required in the payload
for every tools call.
- if stream is set to false, stream_options must
be omitted from the payload.
- the response from Albert sometimes didn't respect
the format expected by Blocknote, so we added a
system prompt to enforce it.
We want to monitor AI actions. For this we choose to use langfuse. As
this usage is optional, we load langfuse sdk only if settings are
configured. Also, the openai client from langfuse is a dropin
replacement of openai client, so we only have to change how openai is
imported.
The AI answer was activating the code block feature
in the editor, which was not desired.
The prompt for AI actions has been updated to
instruct the AI to return content directly
without wrapping it in code blocks or markdown
delimiters.
The ai translation were quite lossy about formatting.
Colors, background, breaklines, table sizes were
lost in the translation.
We improve the AI translation request to keep
the formatting as close as possible by using
html instead of markdown.
Albert send us back a malformed IA json, the
sanitize function was not able to handle it correctly.
We add a try catch on it, to not use the sanitizer if
the json.loads fails.
We created 2 new action endpoints on the document
to perform AI operations:
- POST /api/v1.0/documents/{uuid}/ai-transform
- POST /api/v1.0/documents/{uuid}/ai-translate
