Merge pull request #47 from topoteretes/update_blog
added main docs and blog page
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docs/blog/.authors.yml
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docs/blog/.authors.yml
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authors:
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tricalt:
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name: Vasilije Markovic
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description: Creator
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avatar: https://avatars.githubusercontent.com/u/8619304?v=4
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url: https://twitter.com/intent/follow?screen_name=tricalt
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docs/blog/index.md
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docs/blog/index.md
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# Welcome to the cognee Blog
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The goal of the blog is to discuss broader topics around the cognee project, including the motivation behind the project, the technical details, and the future of the project.
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## Towards production pipelines step by step
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1. [From demo to production 1](posts/from-demo-to-production-1.md)
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2. [From demo to production 2](posts/from-demo-to-production-2.md)
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3. [From demo to production 3](posts/from-demo-to-production-3.md)
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4. [From demo to production 4](posts/from-demo-to-production-4.md)
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docs/blog/posts/from-demo-to-production-1.md
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docs/blog/posts/from-demo-to-production-1.md
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---
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draft: False
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date: 2023-10-05
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tags:
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- pydantic
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- langchain
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- llm
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- openai
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- functions
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- pdfs
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authors:
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- tricalt
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---
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# First post
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## Conclusion
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If you enjoy the content or want to try out `cognee` please check out the [github](https://github.com/topoteretes/cognee) and give us a star!
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docs/blog/posts/from-demo-to-production-2.md
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docs/blog/posts/from-demo-to-production-2.md
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## Conclusion
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If you enjoy the content or want to try out `cognee` please check out the [github](https://github.com/topoteretes/cognee) and give us a star!
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docs/blog/posts/from-demo-to-production-3.md
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docs/blog/posts/from-demo-to-production-3.md
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## Conclusion
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If you enjoy the content or want to try out `cognee` please check out the [github](https://github.com/topoteretes/cognee) and give us a star!
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docs/blog/posts/from-demo-to-production-4.md
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docs/blog/posts/from-demo-to-production-4.md
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## Conclusion
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If you enjoy the content or want to try out `cognee` please check out the [github](https://github.com/topoteretes/cognee) and give us a star!
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### HELLO WORLD
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# cognee, Make data processing for LLMs easy
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_Open-source framework for creating knowledge graphs and data models for LLMs._
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---
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[](https://twitter.com/tricalt)
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[](https://pypi.python.org/pypi/instructor)
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cognee makes it easy to reliably enrich data for Large Language Models (LLMs) like GPT-3.5, GPT-4, GPT-4-Vision, including in the future the open source models like Mistral/Mixtral from Together, Anyscale, Ollama, and llama-cpp-python.
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By leveraging various tools like graph databases, function calling, tool calling and Pydantic; cognee stands out for its aim to emulate human memory for LLM apps and frameworks.
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We leverage Neo4j to do the heavy lifting and dlt to load the data, and we've built a simple, easy-to-use API on top of it by helping you manage your context
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## Getting Started
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```
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pip install -U cognee
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```
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You can also check out our [cookbook](./examples/index.md) to learn more about how to use cognee.
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## Why use cognee?
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The question of using cognee is fundamentally a question of why to structure data inputs and outputs for your llm workflows.
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1. **Cost effective** — With our upcoming opensource release, cognee will extend the capabilities of your LLMs without the need for expensive data processing tools.
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2. **Self contained** — cognee runs as a library and is simple to use
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3. **Interpretable** — Navigate graphs instead of embeddings to understand your data.
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4. **User Guided** cognee lets you control your input and provide your own Pydantic data models
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## hello hello
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{% extends "base.html" %} {% block announce %} For updates follow
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<strong>@tricalt</strong> on
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<a href="https://twitter.com/jxnlco">
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<a href="https://twitter.com/tricalt">
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<span class="twemoji twitter">
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{% include ".icons/fontawesome/brands/twitter.svg" %}
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</span>
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