docs: add some new links

mehdihadeli · Sep 20, 2024 · 1afbc15 · 1afbc15
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diff --git a/docs/ai/ai.md b/docs/ai/ai.md
@@ -12,6 +12,8 @@
 - [geffzhang/awesome-semantickernel](https://github.com/geffzhang/awesome-semantickernel) - Awesome list of tools and projects with the awesome semantic kernel framework
 - [jmatthiesen/dotnet-ai-resources](https://github.com/jmatthiesen/dotnet-ai-resources) - A collection of resources available to .NET developers working with AI
 - [dair-ai/Prompt-Engineering-Guide](https://github.com/dair-ai/Prompt-Engineering-Guide) - Guides, papers, lecture, notebooks and resources for prompt engineering
+- [LLM University](https://cohere.com/llmu)
+- [e2b-dev/awesome-ai-agents](https://github.com/e2b-dev/awesome-ai-agents) - A list of AI autonomous agents
 
 ## Articles
 - [Reviewing GitHub Copilot by Building a Deck of Cards](https://programmingpercy.tech/blog/reviewing-github-copilot-by-building-deck-of-cards/)
@@ -82,6 +84,15 @@
 - [microsoft/JARVIS](https://github.com/microsoft/JARVIS) - JARVIS, a system to connect LLMs with ML community. Paper:
 - [Kwai-Kolors/Kolors](https://github.com/Kwai-Kolors/Kolors) - Kolors: Effective Training of Diffusion Model for Photorealistic Text-to-Image Synthesis
 - [microsoft/kernel-memory](https://github.com/microsoft/kernel-memory) - RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns
+- [TabbyML/tabby](https://github.com/TabbyML/tabby) - Self-hosted AI coding assistant
+- [gpt-engineer-org/gpt-engineer](https://github.com/gpt-engineer-org/gpt-engineer) - Platform to experiment with the AI Software Engineer. Terminal based. NOTE: Very different from
+- [Pythagora-io/gpt-pilot](https://github.com/Pythagora-io/gpt-pilot) - The first real AI developer
+- [microsoft/chat-copilot](https://github.com/microsoft/chat-copilot)
+- [paul-gauthier/aider](https://github.com/paul-gauthier/aider) - aider is AI pair programming in your terminal
+- [continuedev/continue](https://github.com/continuedev/continue) - Continue is the leading open-source AI code assistant. You can connect any models and any context to build custom autocomplete and chat experiences inside VS Code and JetBrains
+- [AbanteAI/mentat](https://github.com/AbanteAI/mentat) - Mentat - The AI Coding Assistant
+- [stitionai/devika](https://github.com/stitionai/devika) - Devika is an Agentic AI Software Engineer that can understand high-level human instructions, break them down into steps, research relevant information, and write code to achieve the given objective.
+- [unslothai/unsloth](https://github.com/unslothai/unsloth) - Finetune Llama 3.1, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory
 
 ## Samples
 - [Azure-Samples/openai-dotnet-samples](https://github.com/Azure-Samples/openai-dotnet-samples)

diff --git a/docs/ai/embedding-vector.md b/docs/ai/embedding-vector.md
@@ -0,0 +1,5 @@
+# Embedding & Vector
+
+## Videos
+- [Vector Database Explained | What is Vector Database?](https://www.youtube.com/watch?v=72XgD322wZ8)
+- [OpenAI Embeddings and Vector Databases Crash Course](https://www.youtube.com/watch?v=ySus5ZS0b94)
diff --git a/docs/ai/langchain.md b/docs/ai/langchain.md
@@ -0,0 +1,11 @@
+# LangChain
+
+## Articles
+- [Build a Retrieval Augmented Generation (RAG) App](https://js.langchain.com/v0.2/docs/tutorials/rag/)
+
+## Videos
+- [LangChain Crash Course For Beginners | LangChain Tutorial](https://www.youtube.com/watch?v=nAmC7SoVLd8)
+- [LangChain Explained In 15 Minutes - A MUST Learn For Python Programmers](https://www.youtube.com/watch?v=mrjq3lFz23s)
+- [The LangChain Cookbook - Beginner Guide To 7 Essential Concepts](https://www.youtube.com/watch?v=2xxziIWmaSA)
+- [RAG + Langchain Python Project: Easy AI/Chat For Your Docs](https://www.youtube.com/watch?v=tcqEUSNCn8I)
+- [Building Production-Ready RAG Applications: Jerry Liu](https://www.youtube.com/watch?v=TRjq7t2Ms5I)
diff --git a/docs/ai/models/ollama.md b/docs/ai/models/ollama.md
@@ -0,0 +1,15 @@
+# Ollama
+
+## Articles
+- [Importing a model in Ollama](https://github.com/ollama/ollama/blob/main/docs/import.md)
+- [OpenAI compatibility](https://ollama.com/blog/openai-compatibility)
+- [Ollama OpenAI compatibility](https://github.com/ollama/ollama/blob/main/docs/openai.md)
+- [Importing a model in Ollama](https://github.com/ollama/ollama/blob/main/docs/import.md)
+
+## Videos
+- [Importing Open Source Models to Ollama](https://www.youtube.com/watch?v=fnvZJU5Fj3Q)
+- [Adding Custom Models to Ollama](https://www.youtube.com/watch?v=0ou51l-MLCo)
+- [Ollama adds OpenAI API support](https://www.youtube.com/watch?v=Zgb2TjZ5zTk)
+- [Finally Ollama has an OpenAI compatible API](https://www.youtube.com/watch?v=38jlvmBdBrU)
+- [LLAMA-3.1 🦙: EASIET WAY To FINE-TUNE ON YOUR DATA](https://www.youtube.com/watch?v=rpAtVIZB72U)
+- [Gen AI Project Using Llama3.1 | End to End Gen AI Project](https://www.youtube.com/watch?v=CO4E_9V6li0)
diff --git a/docs/ai/rag.md b/docs/ai/rag.md
@@ -1,16 +1,23 @@
 # RAG
 
 ## Articles
+- [Build a Retrieval Augmented Generation (RAG) App](https://js.langchain.com/v0.2/docs/tutorials/rag/)
 - [Building a Local RAG System for Privacy Preservation with Ollama and Weaviate](https://weaviate.io/blog/local-rag-with-ollama-and-weaviate)
 - [Typical RAG Implementation Using Semantic Kernel, Kernel Memory, and Aspire in .NET](https://nikiforovall.github.io/dotnet/ai/2024/09/04/typical-rag-dotnet.html)
 - [Using Phi-3 & C# with ONNX for text and vision samples](https://devblogs.microsoft.com/dotnet/using-phi3-csharp-with-onnx-for-text-and-vision-samples-md/)
 - [Introducing Phi-3: Redefining what’s possible with SLMs](https://azure.microsoft.com/en-us/blog/introducing-phi-3-redefining-whats-possible-with-slms/)
+- [Optimizing SLM with ONNX Runtime: Phi-3 on CPU with Sidecars for App Service](https://azure.github.io/AppService/2024/08/19/Phi-3-ONNX.html)
+- [Building Smarter Apps: Integrating Phi-3 SLM with Linux App Service](https://azure.github.io/AppService/2024/08/05/Using-SLM-with-Sidecar.html)
+- [Building an Advanced RAG System With Self-Querying Retrieval](https://www.mongodb.com/developer/products/atlas/advanced-rag-self-querying-retrieval/)
 
 ## Videos
 - [.NET AI Community Standup - Phi-3 & C#: Bringing AI to your .NET Apps](https://www.youtube.com/watch?v=fbojvzHGtkM)
 
 ## Libraries
 - [microsoft/kernel-memory](https://github.com/microsoft/kernel-memory) - RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns
 
+## Samples
+- [NikiforovAll/notebook-agent](https://github.com/NikiforovAll/notebook-agent) - Demonstrates how to use Semantic Kernel and Kernel Memory in a polyglot notebook environment.
+
 ## Books
 - [Building LLMs for Production: Enhancing LLM Abilities and Reliability with Prompting, Fine-Tuning, and RAG](https://www.amazon.com/Building-LLMs-Production-Reliability-Fine-Tuning/dp/B0D4FFPFW8)
diff --git a/docs/devops/kubernetes/kubernetes.md b/docs/devops/kubernetes/kubernetes.md
@@ -161,6 +161,7 @@
 - [metalbear-co/mirrord](https://github.com/metalbear-co/mirrord) - Connect your local process and your cloud environment, and run local code in cloud conditions
 - [gefyrahq/gefyra](https://github.com/gefyrahq/gefyra) - Blazingly-fast, rock-solid, local application development with Kubernetes.
 - [cdk8s-team/cdk8s](https://github.com/cdk8s-team/cdk8s) - Define Kubernetes native apps and abstractions using object-oriented programming
+- [kubecolor/kubecolor](https://github.com/kubecolor/kubecolor) - Colorize your kubectl output
 
 ## 🚀 Samples
 - [arashkaffamanesh/practical-kubernetes-problems](https://github.com/arashkaffamanesh/practical-kubernetes-problems) - For Kubernauts' Practical Kubernetes Trainings

diff --git a/docs/domain-driven-design/value-objects.md b/docs/domain-driven-design/value-objects.md
@@ -41,6 +41,7 @@
 - [Design Smell: Primitive Obsession by Mark Seemann](https://blog.ploeh.dk/2011/05/25/DesignSmellPrimitiveObsession/)
 - [From Primitive Obsession to Domain Modelling by Mark Seemann](https://blog.ploeh.dk/2015/01/19/from-primitive-obsession-to-domain-modelling/)
 - [eShopOnWeb Architecture (2/16) – uses Value Objects to model immutable domain concepts](https://davecallan.com/eshoponweb-uses-value-objects-to-model-immutable-domain-concepts/)
+- [A Modern Way to Create Value Objects to Solve Primitive Obsession in .NET](https://antondevtips.com/blog/a-modern-way-to-create-value-objects-to-solve-primitive-obsession-in-net)
 
 ## 📺 Videos
 - [Treating Primitive Obsession with ValueObjects | DDD in .NET](https://www.youtube.com/watch?v=h4uldNA1JUE)

diff --git a/docs/microservices/tools/wolverine.md b/docs/microservices/tools/wolverine.md
@@ -31,6 +31,7 @@
 - [Critter Stack Improvements for Event Driven Architecture](https://jeremydmiller.com/2024/05/02/critter-stack-improvements-for-event-driven-architecture/)
 - [Low Ceremony Sagas with Wolverine](https://jeremydmiller.com/2024/08/20/low-ceremony-sagas-with-wolverine/)
 - [How Wolverine allows for easier testing](https://jeremydmiller.com/2022/12/13/how-wolverine-allows-for-easier-testing/)
+- [CQRS Command Handlers with Marten](https://jeremydmiller.com/2024/09/09/cqrs-command-handlers-with-marten/)
 
 ## Videos
 - [Don't let MediatR hold you back, try this...](https://www.youtube.com/watch?v=YlG3bnJ7yCc)

diff --git a/mkdocs.yml b/mkdocs.yml
@@ -64,7 +64,11 @@ nav:
   - Protoactor: actor-model-architecture/protoactor.md
 - AI:
     AI: ai/ai.md
+    Embedding & Vector: ai/embedding-vector.md
+    LangChain: ai/langchain.md
     RAG: ai/rag.md
+    Models:
+      - Ollama: ai/models/Ollama.md
 - Algorithms: algorithm.md
 - Anti Patterns:
   - Anti Patterns: anti-patterns/anti-patterns.md