Commit Graph

13 Commits

Author SHA1 Message Date
Sam 1320eed9b2
FEATURE: move summary to use llm_model (#699)
This allows summary to use the new LLM models and migrates of API key based model selection

Claude 3.5 etc... all work now. 

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Co-authored-by: Roman Rizzi <rizziromanalejandro@gmail.com>
2024-07-04 10:48:18 +10:00
Roman Rizzi fc081d9da6
FIX: Restore ability to fold summaries, which was accidentally removed (#700) 2024-07-03 18:10:31 -03:00
Keegan George 1b0ba9197c
DEV: Add summarization logic from core (#658) 2024-07-02 08:51:59 -07:00
Roman Rizzi 0c4069ab3f
DEV: Remove non-LLM-based summarization strategies. (#589)
We removed these services from our hosting two weeks ago. It's safe to assume everyone has moved to other LLM-based options.
2024-04-23 12:11:04 -03:00
Roman Rizzi 0634b85a81
UX: Validations to LLM-backed features (except AI Bot) (#436)
* UX: Validations to Llm-backed features (except AI Bot)

This change is part of an ongoing effort to prevent enabling a broken feature due to lack of configuration. We also want to explicit which provider we are going to use. For example, Claude models are available through AWS Bedrock and Anthropic, but the configuration differs.

Validations are:

* You must choose a model before enabling the feature.
* You must turn off the feature before setting the model to blank.
* You must configure each model settings before being able to select it.

* Add provider name to summarization options

* vLLM can technically support same models as HF

* Check we can talk to the selected model

* Check for Bedrock instead of anthropic as a site could have both creds setup
2024-01-29 16:04:25 -03:00
Roman Rizzi 450ec915d8
FIX: Make FoldContent strategy more resilient when using models with low token count. (#341)
We'll recursively summarize  the content into smaller chunks until we are sure we can concatenate
them without going over the token limit.
2023-12-06 19:00:24 -03:00
Roman Rizzi 3bc010b686
FIX: call the right method to summarize with truncation (#328) 2023-12-01 10:17:24 -03:00
Sam 6ddc17fd61
DEV: port directory structure to Zeitwerk (#319)
Previous to this change we relied on explicit loading for a files in Discourse AI.

This had a few downsides:

- Busywork whenever you add a file (an extra require relative)
- We were not keeping to conventions internally ... some places were OpenAI others are OpenAi
- Autoloader did not work which lead to lots of full application broken reloads when developing.

This moves all of DiscourseAI into a Zeitwerk compatible structure.

It also leaves some minimal amount of manual loading (automation - which is loading into an existing namespace that may or may not be there)

To avoid needing /lib/discourse_ai/... we mount a namespace thus we are able to keep /lib pointed at ::DiscourseAi

Various files were renamed to get around zeitwerk rules and minimize usage of custom inflections

Though we can get custom inflections to work it is not worth it, will require a Discourse core patch which means we create a hard dependency.
2023-11-29 15:17:46 +11:00
Roman Rizzi 3064d4c288
REFACTOR: Summarization and HyDE now use an LLM abstraction. (#297)
* DEV: One LLM abstraction to rule them all

* REFACTOR: HyDE search uses new LLM abstraction

* REFACTOR: Summarization uses the LLM abstraction

* Updated documentation and made small fixes. Remove Bedrock claude-2 restriction
2023-11-23 12:58:54 -03:00
Roman Rizzi e0691e70e8
DEV: Updates to the summarization strategy API (#301)
Introduced by discourse/discourse#24489

In the future, this change will let us log who requested the summary in the `AiApiAuditLog`.:
2023-11-21 13:27:35 -03:00
Roman Rizzi 1b568f2391
FIX: Claude's max_tookens_to_sample is a required field (#97) 2023-06-27 14:42:33 -03:00
Roman Rizzi 9a79afcdbf
DEV: Better strategies for summarization (#88)
* 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
2023-06-27 12:26:33 -03:00
Roman Rizzi 3364fec425
DEV: Remove the summarization feature (#83)
* 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
2023-06-13 14:32:26 -03:00