We pass the text to the current LLM and ask them to generate a StableDifussion prompt.
We'll use that to generate 4 samples, temporarily creating uploads and returning their short URLs.
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.
Single and multi-chunk summaries end using different prompts for the last summary. This change detects when the summarized content fits in a single chunk and uses a slightly different prompt, which leads to more consistent summary formats.
This PR also moves the chunk-splitting step to the `FoldContent` strategy as preparation for implementing streamed summaries.
* DEV: Better strategies for summarization
The strategy responsibility needs to be "Given a collection of texts, I know how to summarize them most efficiently, using the minimum amount of requests and maximizing token usage".
There are different token limits for each model, so it all boils down to two different strategies:
Fold all these texts into a single one, doing the summarization in chunks, and then build a summary from those.
Build it by combining texts in a single prompt, and truncate it according to your token limits.
While the latter is less than ideal, we need it for "bart-large-cnn-samsum" and "flan-t5-base-samsum", both with low limits. The rest will rely on folding.
* Expose summarized chunks to users
* DEV: Remove the summarization feature
Instead, we'll register summarization implementations for OpenAI, Anthropic, and Discourse AI using the API defined in discourse/discourse#21813.
Core and chat will implement features on top of these implementations instead of this plugin extending them.
* Register instances that contain the model, requiring less site settings
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.
We'll create one bot user for each available model. When listed in the `ai_bot_enabled_chat_bots` setting, they will reply.
This PR lets us use Claude-v1 in stream mode.
This module lets you chat with our GPT bot inside a PM. The bot only replies to members of the groups listed on the ai_bot_allowed_groups setting and only if you invite it to participate in the PM.
Also adds some tests around completions and supports additional params
such as top_p, temperature and max_tokens
This also migrates off Faraday to using Net::HTTP directly
* FEATURE: Topic summarization
Summarize topics using the TopicView's "summary" filter. The UI is similar to what we do for chat, but we don't allow the user to select a timeframe.
Co-authored-by: Rafael dos Santos Silva <xfalcox@gmail.com>
Depends on discourse/discourse#20915
Hooks to the full-page-search component using an experimental API and performs an assymetric similarity search using our embeddings database.
A prompt with multiple messages leads to better results, as the AI can learn for given examples. Alongside this change, we provide a better default proofreading prompt.
* FEATURE: Composer AI helper
This change introduces a new composer button for the group members listed in the `ai_helper_allowed_groups` site setting.
Users can use chatGPT to review, improve, or translate their posts to English.
* Add a safeguard for PMs and don't rely on parentView
Rafael dos Santos Silva
Keegan George
Roman Rizzi
Sam
Roman Rizzi