* Initial pass at backend changes to support agents
- Add a db model for Agents, attaching them to conversations
- When an agent is added to a conversation, override the system prompt to tweak the instructions
- Agents can be configured with prompt modification, model specification, a profile picture, and other things
- Admin-configured models will not be editable by individual users
- Add unit tests to verify agent behavior. Unit tests demonstrate imperfect adherence to prompt specifications
* Customize default behaviors for conversations without agents or with default agents
* Use agent_id for getting correct agent
* Merge migrations
* Simplify some variable definitions, add additional security checks for agents
* Rename agent.tuning -> agent.personality
* Display given_name field only if it is not None
* Add default slugs in the migration script
* Ensure that updated_at is saved appropriately, make sure most recent chat is returned for default history
* Remove the bin button from the chat interface, given deletion is handled in the drop-down menus
* Refresh the side panel when a new chat is created
* Improveme tool retrieval prompt, don't let /online fail, and improve parsing of extract questions
* Fix ending chat response by offline chat on hitting a stop phrase
Previously the whole phrase wouldn't be in the same response chunk, so
chat response wouldn't stop on hitting a stop phrase
Now use a queue to keep track of last 3 chunks, and to stop responding
when hit a stop phrase
* Make chat on Obsidian backward compatible post chat session API updates
- Make chat on Obsidian get chat history from
`responseJson.response.chat' when available (i.e when using new api)
- Else fallback to loading chat history from
responseJson.response (i.e when using old api)
* Fix detecting success of indexing update in khoj.el
When khoj.el attempts to index on a Khoj server served behind an https
endpoint, the success reponse status contains plist with certs. This
doesn't mean the update failed.
Look for :errors key in status instead to determine if indexing API
call failed. This fixes detecting indexing API call success on the
Khoj Emacs client, even for Khoj servers running behind SSL/HTTPS
* Fix the mechanism for populating notes references in the conversation primer for both offline and online chat
* Return conversation.default when empty list for dynamic prompt selection, send all cmds in telemetry
* Fix making chat on Obsidian backward compatible post chat session API updates
New API always has conversation_id set, not `chat' which can be unset
when chat session is empty.
So use conversation_id to decide whether to get chat logs from
`responseJson.response.chat' or `responseJson.response' instead
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Co-authored-by: Debanjum Singh Solanky <debanjum@gmail.com>
* Have Khoj dynamically select which conversation command(s) are to be used in the chat flow
- Intercept the commands if in default mode, and have Khoj dynamically guess which tools would be the most relevant for answering the user's query
* Remove conditional for default to enter online search mode
* Add multiple-tool examples in the prompt, make prompt for tools more specific to info collection
- Can now expect date awareness chat quality test to pass
- Prevent offline chat model from printing verbatim user Notes and
special tokens
- Make it ask follow-up questions if it needs more context
* Initailize changes to incporate web scraping logic after getting SERP results
- Do some minor refactors to pass a symptom prompt to the openai model when making a query
- integrate Olostep in order to perform the webscraping
* Fix truncation error with new line, fix typing in olostep code
* Use the authorization header for the token
* Add a small hint/indicator for how to use Khojs other modalities in the welcome prompt
* Add more detailed error message if Olostep query fails
* Add unit tests which invoke Olostep in chat director
* Add test for olostep tool
- Add a data model which allows us to store Conversations with users. This does a minimal lift over the current setup, where the underlying data is stored in a JSON file. This maintains parity with that configuration.
- There does _seem_ to be some regression in chat quality, which is most likely attributable to search results.
This will help us with #275. It should become much easier to maintain multiple Conversations in a given table in the backend now. We will have to do some thinking on the UI.
* Store conversation command options in an Enum
* Move to slash commands instead of using @ to specify general commands
* Calculate conversation command once & pass it as arg to child funcs
* Add /notes command to respond using only knowledge base as context
This prevents the chat model to try respond using it's general world
knowledge only without any references pulled from the indexed
knowledge base
* Test general and notes slash commands in openai chat director tests
* Update gpt4all tests to use md configuration
* Add a /help tooltip
* Add dynamic support for describing slash commands. Remove default and treat notes as the default type
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Co-authored-by: sabaimran <narmiabas@gmail.com>
