Note, we perform permission checks on tag list against anon
to ensure we do not disclose information about private tags
to the llm which could get extracted.
In specific scenarios (no special filters or limits) we will also
always include 5 semantic results (at least) with every query.
This effectively means that all very wide queries will always return
20 results, regardless of how complex they are.
Also:
FIX: embedding backfill rake task not working
We renamed internals, this corrects the implementation
The researcher persona has access to Google and can perform
various internet research tasks. At the moment it can not read
web pages, but that is under consideration
This refactor changes it so we only include minimal data in the
system prompt which leaves us lots of tokens for specific searches
The new search command allows us to pull in settings on demand
Descriptions are include in short search results, and names only
in longer results
Also:
* In dev it is important to tell when calls are made to open ai
this adds a console log to increase awareness around token usage
* PERF: stop counting tokens so often
This changes it so we only count tokens once per response
Previously each time we heard back from open ai we would count
tokens, leading to uneeded delays
* bug fix, commands may reach in for tokenizer
* add logging to console for anthropic calls as well
* Update lib/shared/inference/openai_completions.rb
Co-authored-by: Martin Brennan <[email protected]>
Also adds ai_bot_enabled_personas so admins can tweak which stock
personas are enabled.
The new persona has a full listing of all site settings and is
able to get context for each setting.
This means you can ask it to search through settings for something
relevant.
Security wise there is no access to actual configuration of settings
just to the names / description and implementation.
Previously this was part of the forum helper persona however it
just clashes too much with other behaviors, isolating it makes
it far more powerful.
* sneaking this one in, user_emails is a non obvious table in our
structure.
usually one would assume users has emails so the clarifies a bit
better. plus it is a very common table to hit.
This splits out a bunch of code that used to live inside bots
into a dedicated concept called a Persona.
This allows us to start playing with multiple personas for the bot
Ships with:
artist - for making images
sql helper - for helping with data explorer
general - for everything and anything
Also includes a few fixes that make the generic LLM function implementation more robust
This command can be used to extract information about a discourse
site setting directly from source.
To operate it needs the rg binary in the container.
This fixes 2 big issues:
1. No matter how hard you try, grounding anthropic title prompt
is just too hard. This works around by only looking at the last
sentence it returns and treating as title
2. Non English locales would be stuck with "generic" title, this
ensures every bot message gets a title, using a custom field to
track
Also, slightly tunes some anthropic prompts.
Open AI support function calling, this has a very specific shape
that other LLMs have not quite adopted.
This simulates a command framework using system prompts on LLMs
that are not open AI.
Features include:
- Smart system prompt to steer the LLM
- Parameter validation (we ensure all the params are specified correctly)
This is being tested on Anthropic at the moment and intial results
are promising.
Previously we were not counting functions correctly and not
accounting for minimum token count per message
This corrects both issues and improves documentation internally
Azure requires a single HTTP endpoint per type of completion.
The settings: `ai_openai_gpt35_16k_url` and `ai_openai_gpt4_32k_url` can be
used now to configure the extra endpoints
This amends token limit which was off a bit due to function calls and fixes
a minor JS issue where we were not testing for a property
* FEATURE: optional warning attached to all AI bot conversations
This commit introduces `ai_bot_enable_chat_warning` which can be used
to warn people prior to starting a chat with the bot.
In particular this is useful if moderators are regularly reading chat
transcripts as it sets expectations early.
By default this is disabled.
Also:
- Stops making ajax call prior to opening composer
- Hides PM title when starting a bot PM
Co-authored-by: Rafael dos Santos Silva <[email protected]>
previously you would have to wait quite a while to see the prompt this implements
a very basic implementation of progress so you can see the API is working.
Also:
- Fix google progress.
- Handle the incredibly rare, zero results from google.
- Simplify command so it is less error prone
- replace invoke and attache results with a invoke
- ensure invoke can only ever be run once
- pass in all the information a command needs in constructor
- use new pattern throughout
- test invocation in isolation
- Attempt to hint reading is done by sending complete:true
- Do not include post_number in result unless it was sent in
- Rush visual feedback when a command is run (ensure we always revise)
- Include hyperlink in read command description
- Stop round tripping to GPT after image generation (speeds up images by a lot)
- Add a test for image command
This command is useful for reading a topics content. It allows us to perform
critical analysis or suggest answers.
Given 8k token limit in GPT-4 I hardcoded reading to 1500 tokens, but we can
follow up and allow larger windows on models that support more tokens.
On local testing even in this limited form this can be very useful.
* FIX: Google command was including full payload
Additionally there was no truncating happening meaning you could blow token
budget easily on a single search.
This made Google search mostly useless and it would mean that after using
Google we would revert to a clean slate which is very confusing.
* no need for nil there
The command framework had some confusing dispatching where it would dispatch
JSON blobs, this meant there was lots of parsing required in every command
The refactor handles transforming the args prior to dispatch which makes
consuming far simpler
This is also general prep to supporting some basic command framework in other
llms.
Claude 1 costs the same and is less good than Claude 2. Make use of Claude
2 in all spots ...
This also fixes streaming so it uses the far more efficient streaming protocol.
Reduce maximum replies to 2500 tokens and make them even for both GPT-3.5
and 4
Account for 400+ tokens in function definitions (this was unaccounted for)
* FEATURE: add ai_bot_enabled_chat commands and tune search
This allows admins to disable/enable GPT command integrations.
Also hones search results which were looping cause the result did not denote
the failure properly (it lost context)
* include more context for google command
include more context for time command
* type
```
prompt << build_message(bot_user.username, reply)
```
Would store a "cooked" prompt which is invalid, instead just store the raw
values which are later passed to build_message
Additionally:
1. Disable summary command which needs honing
2. Stop storing decorations (searched for X) in prompt which leads to straying
3. Ship username directly to model, avoiding "user: content" in prompts. This
was causing GPT to stray
Given latest GPT 3.5 16k which is both better steered and supports functions
we can now support rich bot integration.
Clunky system message based steering is removed and instead we use the
function framework provided by Open AI
Previous to this change we were chaining stuff too late and would execute
commands serially leading to very unexpected results
This corrects this and allows us to run stuff like:
> Search google 3/4 times on various permutations of
QUERY and answer this question.
We limit at 5 commands to ensure there are not pathological user cases
where you lean on the LLM to flood us with results.
For the time being smart commands only work consistently on GPT 4.
Avoid using any smart commands on the earlier models.
Additionally adds better error handling to Claude which sometimes streams
partial json and slightly tunes the search command.
blog.start_gpt_chat -> was on my blog
This also slightly tunes the search prompt to support filtering by oldest
and try a tiny bit harder to guide GPT 3.5 which is a bit of a losing battle
Co-authored-by: Krzysztof Kotlarek <[email protected]>
Sam
