- The previous mechanism to trigger saving on shutdown event did not work
- Use scheduler to persist chat sessions to disk at a 5 minute interval
- This improve time granularity, fixed interval of saving chat logs
- It may lose ~5 minutes of chat history until mechanism to also
write on shutdown found/resolved
- Create conversation directory if it doesn't exist before attempting write
- Reset chat_session after writing it to disk
- Previously the backend was just throwing backend error.
The frontend calling the /update API wasn't getting notified
- Now the frontend can react appropriately and make the issue
visible to the user
Use the timer context manager in all places where code was being timed
- Benefits
- Deduplicate timing code scattered across codebase.
- Provides single place to manage perf timing code
- Use consistent timing log patterns
This is unlike the more general chat API that combines summarization
of top search result and conversing with the OpenAI model
This should give faster summary results. As no intent categorization
API call required
- Default to using `text-davinci-003' if conversation model not
explicitly configured by user. Stop using the older `davinci' and
`davinci-instruct' models
- Use `model' instead of `engine' as parameter.
Usage of `engine' parameter in OpenAI API is deprecated
This can ease configuring khoj from the different interfaces
- Don't need to know all the (default) config used by khoj.
- Just get default config by calling the above API endpoint.
- Then modify desired portions and call POST /api/config/data to
configure khoj.
- There are 3 paths to updating/setting the index (stored in state.model)
- App start
- API
- Scheduler
- Put all updates to the index behind a lock. As multiple updates path
that could (potentially) run at the same time (via API or Scheduler)
- Reason
- All clients that currently consume the API are part of Khoj
- Any breaking API changes will be fixed in clients immediately
- So decoupling client from API is not required
- This removes the burden of maintaining muliple versions of the API
- Both Text, Image Search were already giving list of entry, score
- This change just concretizes this change and exposes this in the API
documentation (i.e OpenAPI, Swagger, Redocs)
- Split router.py into v1.0, beta and frontend (no-prefix) api modules
under new router package. Version tag in main.py via prefix
- Update frontends to use the versioned api endpoints
- Update tests to work with versioned api endpoints
- Update docs to mentioned, reference only versioned api endpoints
