Commit Graph

20 Commits

Author SHA1 Message Date
Rafael dos Santos Silva a08d168740
FEATURE: Initial support for seeded LLMs (#756) 2024-08-28 15:57:58 -03:00
Keegan George f72ab12761
DEV: Clearly separate post/composer helper settings (#747) 2024-08-12 15:40:23 -07:00
Roman Rizzi bed044448c
DEV: Remove old code now that features rely on LlmModels. (#729)
* DEV: Remove old code now that features rely on LlmModels.

* Hide old settings and migrate persona llm overrides

* Remove shadowing special URL + seeding code. Use srv:// prefix instead.
2024-07-30 13:44:57 -03:00
Roman Rizzi 5c196bca89
FEATURE: Track if a model can do vision in the llm_models table (#725)
* FEATURE: Track if a model can do vision in the llm_models table

* Data migration
2024-07-24 16:29:47 -03:00
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
Keegan George 1b0ba9197c
DEV: Add summarization logic from core (#658) 2024-07-02 08:51:59 -07:00
Roman Rizzi 091dc626e8
FIX: Make sure LlmEnumerator always return value hashes using symbols (#684) 2024-06-21 16:35:31 -03:00
Roman Rizzi 8849caf136
DEV: Transition "Select model" settings to only use LlmModels (#675)
We no longer support the "provider:model" format in the "ai_helper_model" and
"ai_embeddings_semantic_search_hyde_model" settings. We'll migrate existing
values and work with our new data-driven LLM configs from now on.
2024-06-19 18:01:35 -03:00
Roman Rizzi 8d5f901a67
DEV: Rewire AI bot internals to use LlmModel (#638)
* DRAFT: Create AI Bot users dynamically and support custom LlmModels

* Get user associated to llm_model

* Track enabled bots with attribute

* Don't store bot username. Minor touches to migrate default values in settings

* Handle scenario where vLLM uses a SRV record

* Made 3.5-turbo-16k the default version so we can remove hack
2024-06-18 14:32:14 -03:00
Sam b487de933d
FEATURE: add support for all vision models (#646)
Previoulsy on GPT-4-vision was supported, change introduces support
for Google/Anthropic and new OpenAI models

Additionally this makes vision work properly in dev environments
cause we sent the encoded payload via prompt vs sending urls
2024-05-28 10:31:15 -03:00
Roman Rizzi 333b331eb9
FEATURE: Allow deleting custom LLMs. (#643)
This change allows us to delete custom models. It checks if there is no module using them.

It also fixes a bug where the after-create transition wasn't working. While this prevents a model from being saved multiple times, endpoint validations are still needed (will be added in a separate PR).:
2024-05-27 16:44:08 -03:00
Roman Rizzi 1d786fbaaf
FEATURE: Set endpoint credentials directly from LlmModel. (#625)
* FEATURE: Set endpoint credentials directly from LlmModel.

Drop Llama2Tokenizer since we no longer use it.

* Allow http for custom LLMs

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Co-authored-by: Rafael Silva <xfalcox@gmail.com>
2024-05-16 09:50:22 -03:00
Sam 8eee6893d6
FEATURE: GPT4o support and better auditing (#618)
- Introduce new support for GPT4o (automation / bot / summary / helper)
- Properly account for token counts on OpenAI models
- Track feature that was used when generating AI completions
- Remove custom llm support for summarization as we need better interfaces to control registration and de-registration
2024-05-14 13:28:46 +10:00
Roman Rizzi e22194f321
HACK: Llama3 support for summarization/AI helper. (#616)
There are still some limitations to which models we can support with the `LlmModel` class. This will enable support for Llama3 while we sort those out.
2024-05-13 15:54:42 -03:00
Roman Rizzi 62fc7d6ed0
FEATURE: Configurable LLMs. (#606)
This PR introduces the concept of "LlmModel" as a new way to quickly add new LLM models without making any code changes. We are releasing this first version and will add incremental improvements, so expect changes.

The AI Bot can't fully take advantage of this feature as users are hard-coded. We'll fix this in a separate PR.s
2024-05-13 12:46:42 -03:00
Sam 514823daca
FIX: streaming broken in bedrock when chunks are not aligned (#609)
Also

- Stop caching llm list - this cause llm list in persona to be incorrect
- Add more UI to debug screen so you can properly see raw response
2024-05-09 12:11:50 +10:00
Roman Rizzi fba9c1bf2c
UX: Re-introduce embedding settings validations (#457)
* Revert "Revert "UX: Validate embeddings settings (#455)" (#456)"

This reverts commit 392e2e8aef.

* Resstore previous default
2024-02-01 16:54:09 -03:00
Roman Rizzi 392e2e8aef
Revert "UX: Validate embeddings settings (#455)" (#456)
This reverts commit 85fca89e01.
2024-02-01 14:06:51 -03:00
Roman Rizzi 85fca89e01
UX: Validate embeddings settings (#455) 2024-02-01 13:05:38 -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