llama_parse
SillyTavern
llama_parse | SillyTavern | |
---|---|---|
4 | 76 | |
1,195 | 6,225 | |
45.0% | 12.8% | |
9.1 | 10.0 | |
about 5 hours ago | about 20 hours ago | |
Python | JavaScript | |
MIT License | GNU Affero General Public License v3.0 |
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llama_parse
- FLaNK AI for 11 March 2024
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LlamaCloud and LlamaParse
I'm part of the team that build LlamaParse. It's net improvement compare to other PDF->Structured Text extractors (I build several in the past, includig https://github.com/axa-group/Parsr).
For character extraction, LlamaParse use a mixture of OCR / character extraction from the PDF (it's the only parser I'm aware of that address some of the buggy PDF font issues, check the 'text' mode to see raw document before reconstruction), use a mixture of heuristic and Machine learning models to reconstruct the document.
Once plug with a Recursive retrieval strategy, allow you to get Sota result on question answering over complexe text (see notebook: https://github.com/run-llama/llama_parse/blob/main/examples/...).
AMA
SillyTavern
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Claude 3 beats GPT-4 on Aider's code editing benchmark β aider
Right, but it's certainly easier for people who might not even know what "API" stands for, and that's quite nifty. As far as self-hosted frontends go, I can personally recommend SillyTavern[1] in the browser, ChatterUI[2] on mobile, and ShellGPT[3] for CLI. LobeChat looks pretty cool, though! I'll definitely check it out.
[1] https://github.com/SillyTavern/SillyTavern
[2] https://github.com/Vali-98/ChatterUI
[3] https://github.com/TheR1D/shell_gpt
- FLaNK AI for 11 March 2024
- Show HN: I made an app to use local AI as daily driver
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Group chats vs online defined characters, token efficiency question
I don't think there is any enumeration for {{char}} macros. Here is some good discussion on the subject.
- SillyTavern 1.11.0 has been released
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Is possible to run local voice chat agent? If yes what GPU do i Need with 500β¬ budget?
As for SillyTavern, you need the main SillyTavern frontend and SillyTavern-extras (for TTS, STT, etc.) They're pretty easy to install. SillyTavern connects to oobabooga and SillyTavern-extras via API.
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What do you use to run your models?
Finally, no matter what backend I use, I need it to be compatible with my power-user frontend, SillyTavern. That way I always use the same UI, with the characters I created and extensions I want, e. g. web search, XTTS text-to-speech and Whisper speech recognition for real-time voice chat - and all of that local!
- SillyTavern 1.10.10 has been released
- LM Studio β Discover, download, and run local LLMs
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πΊπ¦ββ¬ LLM Comparison/Test: Mistral 7B Updates (OpenHermes 2.5, OpenChat 3.5, Nous Capybara 1.9)
SillyTavern v1.10.5 frontend (not the latest as I don't want to upgrade mid-test)
What are some alternatives?
llmsherpa - Developer APIs to Accelerate LLM Projects
TavernAI - TavernAI for nerds [Moved to: https://github.com/Cohee1207/SillyTavern]
unstructured - Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.
character-editor - Create, edit and convert AI character files for CharacterAI, Pygmalion, Text Generation, KoboldAI and TavernAI
llama-hub - A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain
TavernAI - Atmospheric adventure chat for AI language models (KoboldAI, NovelAI, Pygmalion, OpenAI chatgpt, gpt-4)
SillyTavern-extras - Extensions API for SillyTavern [Moved to: https://github.com/SillyTavern/SillyTavern-extras]
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
SillyTavern-Extras - Extensions API for SillyTavern.
tortoise-tts - A multi-voice TTS system trained with an emphasis on quality
chroma - the AI-native open-source embedding database
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI