Commit Graph

5 Commits

Author SHA1 Message Date
Rafael dos Santos Silva 49f2453c2d
FEATURE: Tweaks to Anthropic Summarization (#138)
* FEATURE: Tweaks to Anthropic Summarization

* fix specs
2023-08-16 15:09:52 -03:00
Sam 4b0c077ce5
FEATURE: port to use claude-2 for chat bot (#114)
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.
2023-07-27 11:24:44 +10:00
Roman Rizzi 5f0c617880
REFACTOR: Cohesive narrative for single-chunk summaries. (#103)
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.
2023-07-13 17:05:41 -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