Comments (2)
@snexus
https://haystack.deepset.ai/ is the haystack
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Hi @MyraBaba
Would you mind to give more example for hugginaface llamacpp models ? ie what would be the best accurate result for multilingual or language different from the english ?
Unfortunately, it is hard to answer this question since it depends on the model and the task. The goal of the package is to enable users to choose the model they like without forcing any specific model, since "best" or "accurate" are subjective. A good place to look for new models or ask for the best model for the specific task would be https://www.reddit.com/r/LocalLLaMA/
What would be the choice for summarization document ?
Summarization is not in the scope of this project - it was built for question-answering.
3 - sometimes result adding many ##### and stopping
This is not coming from the package, but from the model itself - some models might require different prompt templates for asking the question. You can consult the model card e.g. Huggingface and update the prompt template in the config like specified here -
4 - Example config for mistral , mixtral and dolphin2
As long as it is supported by llamacpp, it should be similar - download the model (e.g. in gguf format), and specify the path in the config. Some models work better with different default parameters - you can configure it in the config.yaml, similar to here -
Do you know haystack looks commercialized version.
Can you clarify the question, please?
what will be the future for enterprise AI search for internal documents ? Is it worth to invest ? Can we talk ?
Quite hard to answer - some big players are entering the space, e.g. Microsoft already offers services for enterprise-grade document question answering, where models can be deployed to an organization's private network and data doesn't leave the perimeter. I think there will be a space for open-source projects like this for small organisations and privacy-conscious users, but hard to tell if it can be monetized.
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Related Issues (20)
- Device map passed multiple times into the llm HOT 2
- Passing history in context to remember conversation HOT 3
- CSV data parsing HOT 3
- add support for using unstructured SaaS API for handling unstructured data pre-processing HOT 7
- Generate embeddings with CPU only HOT 1
- Any examples or videos? HOT 9
- Plans for RRF? HOT 3
- Support several CUDA devices HOT 2
- Support openai for Embedding HOT 1
- Reduce logging HOT 2
- update requirements.txt legacy langchain, chroma, openai HOT 1
- Model params for GPU setup HOT 1
- CMake failed HOT 1
- support for cpp and hpp source code search? Generic text search? HOT 4
- Can't change embedding model HOT 2
- Can we return source document with LLM response? HOT 8
- Can we share web app publicly with Streamlit? HOT 1
- Re-ranking model too slow HOT 10
- License HOT 1
- Feature request: Adding Llamaparse support for unstructured PDFs HOT 2
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