unstructured
ollama
unstructured | ollama | |
---|---|---|
12 | 209 | |
6,682 | 66,540 | |
17.7% | 23.9% | |
9.8 | 9.9 | |
5 days ago | about 23 hours ago | |
HTML | Go | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
unstructured
-
LlamaCloud and LlamaParse
Be careful with unstructured:
https://github.com/Unstructured-IO/unstructured/blob/d11c70c...
from: https://github.com/open-webui/open-webui/issues/687
- FLaNK 15 Jan 2024
-
Bash One-Liners for LLMs
I’ve been looking at this
https://freeling-user-manual.readthedocs.io/en/v4.2/modules/...
at the freeling library in general, also spaCy and NLTK. The chunking algorithms being used in the likes of LangChain are remarkably bad surprisingly.
There is also
https://github.com/Unstructured-IO/unstructured
But I don’t like it, can’t explain why yet.
My intuition is that 1st step is clean sentences and paragraphs and titles/labels/headers. Then probably an LLM can handle outlining and table of contents generation using a stripped down list of objects in the text.
BRIO/BERT summarization could also have a role of some type.
Those are my ideas so far.
- Unstructured – OSS libraries and APIs to build custom preprocessing pipelines
-
More intelligent Pdf parsers
Unstructured is the best one I’ve used so far: https://www.unstructured.io
- Help extracting data from multiple PDF's
- Pre-processing text documents such as PDFs, HTML and Word Documents for LLMs
-
Using ChatGPT to read multiple PDFs and create writing using them as sources
https://www.unstructured.io/ can parse PDFs, then you can feed all of them to Claude, which has a 100k context window.
-
How can I convert restaurant’s traditional menu in pdf file to well structured list of menu items with prices in Excel file? Thank you
If the copy & pase method does not work: One approach is to use the functionality of Unstructured to parse the PDF. If need be, it can do OCR on the PDF too if you have Detectron2 installed. After conversion you would still have to save it as an excel file though.
-
PDF GPT allows you to chat with the contents of your PDF file
I would check out https://github.com/Unstructured-IO/unstructured (what lang chain uses) or https://github.com/axa-group/Parsr (probably what unstructured copied to get their startup off the ground lol)
ollama
- Ollama v0.1.34 Is Out
-
Ask HN: What do you use local LLMs for?
- Basic internet search (I start ollama CLI faster than I can start a browser - https://ollama.com)
- Formatting/changing text
- Troubleshooting code, esp. new frameworks/libs
- Recipes
- Data entry
- Organizing thoughts: High-level lists, comparison, classification, synonyms, jargon & nomenclature
- Learning esp. by analogy and example
RAG for:
- Website assistants (https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...)
- Game NPCs (https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...)
- Discord/Slack/forum bots (https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...)
- Character-driven storytelling and creating art in a specific style for video game loading screens, background images, avatars, website art, etc. (https://github.com/bennyschmidt/ragdoll-studio/tree/master/r...)
- FLaNK-AIM Weekly 06 May 2024
-
Introducing Jan
Jan goes a step further by integrating with other local engines like LM Studio and ollama.
- Ollama v0.1.33
-
Hindi-Language AI Chatbot for Enterprises Using Qdrant, MLFlow, and LangChain
# install the Ollama curl -fsSL https://ollama.com/install.sh | sh # get the llama3 model ollama pull llama2 # install the MLFlow pip install mlflow
-
Create an AI prototyping environment using Jupyter Lab IDE with Typescript, LangChain.js and Ollama for rapid AI prototyping
Ollama for running LLMs locally
-
Setup Llama 3 using Ollama and Open-WebUI
curl -fsSL https://ollama.com/install.sh | sh
-
Ollama v0.1.33 with Llama 3, Phi 3, and Qwen 110B
Streaming is not a problem (it's just a simple flag: https://github.com/wiktor-k/llama-chat/blob/main/index.ts#L2...) but I've never used voice input.
The examples show image input though: https://github.com/ollama/ollama/blob/main/docs/api.md#reque...
Maybe you can file an issue here: https://github.com/ollama/ollama/issues
-
I Said Goodbye to ChatGPT and Hello to Llama 3 on Open WebUI - You Should Too
I’m a huge fan of open source models, especially the newly release Llama 3. Because of the performance of both the large 70B Llama 3 model as well as the smaller and self-host-able 8B Llama 3, I’ve actually cancelled my ChatGPT subscription in favor of Open WebUI, a self-hostable ChatGPT-like UI that allows you to use Ollama and other AI providers while keeping your chat history, prompts, and other data locally on any computer you control.
What are some alternatives?
llmsherpa - Developer APIs to Accelerate LLM Projects
llama.cpp - LLM inference in C/C++
Parsr - Transforms PDF, Documents and Images into Enriched Structured Data
gpt4all - gpt4all: run open-source LLMs anywhere
ragflow - RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
pdfGPT - PDF GPT allows you to chat with the contents of your PDF file by using GPT capabilities. The most effective open source solution to turn your pdf files in a chatbot!
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
awesome-document-understanding - A curated list of resources for Document Understanding (DU) topic
llama - Inference code for Llama models
llama_parse - Parse files for optimal RAG
LocalAI - :robot: The free, Open Source OpenAI alternative. Self-hosted, community-driven and local-first. Drop-in replacement for OpenAI running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. It allows to generate Text, Audio, Video, Images. Also with voice cloning capabilities.