wehub-resource-sync
116 lines
4.8 KiB
Markdown
116 lines
4.8 KiB
Markdown
---
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layout: default
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title: Query
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parent: Components
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nav_order: 8
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description: overview of the major modules and classes of LLMWare
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permalink: /components/query
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---
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# Retrieval & Query
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---
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Query libraries with mix of text, semantic, hybrid, metadata, and custom filters. The retrieval.py module implements the
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`Query` class, which is the primary way that search and retrieval is performed. Each `Query` object, when constructed,
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requires that a Library is passed as a mandatory parameter in the constructor. The Query object will operate against that
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Library, and have access to all of Library's specific attributes, metadata and methods.
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Retrievals in llmware leverage the Library abstraction as the primary unit against which a particular query or retrieval is
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executed. This provides the ability to have multiple distinct knowledge-bases, potentially aligned to different use cases, and/or
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users, accounts and permissions.
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# Executing Queries
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```python
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from llmware.retrieval import Query
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from llmware.library import Library
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# step 1 - load a previously created library
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lib = Library().load_library("my_library")
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# step 2 - create a query object
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q = Query(lib)
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# step 3 - run lots of different queries (many other options in the examples)
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# basic text query
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results1 = q.text_query("text query", result_count=20, exact_mode=False)
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# semantic query
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results2 = q.semantic_query("semantic query", result_count=10)
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# combining a text query restricted to only certain documents in the library and "exact" match to the query
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results3 = q.text_query_with_document_filter("new query", {"file_name": "selected file name"}, exact_mode=True)
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# to apply a specific embedding (if multiple on library), pass the names when creating the query object
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q2 = Query(lib, embedding_model_name="mini_lm_sbert", vector_db="milvus")
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results4 = q2.semantic_query("new semantic query")
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```
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Need help or have questions?
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============================
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Check out the [llmware videos](https://www.youtube.com/@llmware) and [GitHub repository](https://github.com/llmware-ai/llmware).
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Reach out to us on [GitHub Discussions](https://github.com/llmware-ai/llmware/discussions).
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# About the project
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`llmware` is © 2023-{{ "now" | date: "%Y" }} by [AI Bloks](https://www.aibloks.com/home).
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## Contributing
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Please first discuss any change you want to make publicly, for example on GitHub via raising an [issue](https://github.com/llmware-ai/llmware/issues) or starting a [new discussion](https://github.com/llmware-ai/llmware/discussions).
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You can also write an email or start a discussion on our Discrod channel.
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Read more about becoming a contributor in the [GitHub repo](https://github.com/llmware-ai/llmware/blob/main/CONTRIBUTING.md).
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## Code of conduct
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We welcome everyone into the ``llmware`` community.
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[View our Code of Conduct](https://github.com/llmware-ai/llmware/blob/main/CODE_OF_CONDUCT.md) in our GitHub repository.
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## ``llmware`` and [AI Bloks](https://www.aibloks.com/home)
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``llmware`` is an open source project from [AI Bloks](https://www.aibloks.com/home) - the company behind ``llmware``.
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The company offers a Software as a Service (SaaS) Retrieval Augmented Generation (RAG) service.
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[AI Bloks](https://www.aibloks.com/home) was founded by [Namee Oberst](https://www.linkedin.com/in/nameeoberst/) and [Darren Oberst](https://www.linkedin.com/in/darren-oberst-34a4b54/) in Oktober 2022.
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## License
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`llmware` is distributed by an [Apache-2.0 license](https://github.com/llmware-ai/llmware/blob/main/LICENSE).
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## Thank you to the contributors of ``llmware``!
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<ul class="list-style-none">
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{% for contributor in site.github.contributors %}
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<li class="d-inline-block mr-1">
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<a href="{{ contributor.html_url }}">
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<img src="{{ contributor.avatar_url }}" width="32" height="32" alt="{{ contributor.login }}">
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</a>
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</li>
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{% endfor %}
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</ul>
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---
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<ul class="list-style-none">
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<li class="d-inline-block mr-1">
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<a href="https://discord.gg/MhZn5Nc39h"><span><i class="fa-brands fa-discord"></i></span></a>
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</li>
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<li class="d-inline-block mr-1">
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<a href="https://www.youtube.com/@llmware"><span><i class="fa-brands fa-youtube"></i></span></a>
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</li>
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<li class="d-inline-block mr-1">
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<a href="https://huggingface.co/llmware"><span> <img src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg" alt="Hugging Face" class="hugging-face-logo"/> </span></a>
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</li>
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<li class="d-inline-block mr-1">
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<a href="https://www.linkedin.com/company/aibloks/"><span><i class="fa-brands fa-linkedin"></i></span></a>
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</li>
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<li class="d-inline-block mr-1">
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<a href="https://twitter.com/AiBloks"><span><i class="fa-brands fa-square-x-twitter"></i></span></a>
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</li>
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<li class="d-inline-block mr-1">
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<a href="https://www.instagram.com/aibloks/"><span><i class="fa-brands fa-instagram"></i></span></a>
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</li>
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</ul>
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---
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