match docs with kotlin version (#2)

CODE_OF_CONDUCT.md

@@ -1,4 +1,3 @@
-# Contributor Covenant Code of Conduct
 
 ## Our Pledge
 

CONTRIBUTING.md

@@ -1,4 +1,3 @@
-# Contributing Guide
 
 Welcome and thank you for your interest in contributing to our project! This endeavor thrives on collaboration and the unique inputs from our diverse community. Whether you're fixing bugs, suggesting enhancements, improving our documentation, or sharing ideas, your contribution is valuable to us.
 

README.md

@@ -3,7 +3,7 @@
 
 <div align="center">
 
-[📚 Documentation site](https://python.ellmental.com) | [💬 Discord](https://discord.gg/34cBbvjjAx) | [🤝 Contributing](website/CONTRIBUTING.md)
+[📚 Documentation site](https://python.ellmental.com) | [💬 Discord](https://discord.gg/34cBbvjjAx) | [🤝 Contributing](./CONTRIBUTING.md)
 
 </div>
 
@@ -105,7 +105,7 @@ We believe that community contributions are essential to the development and ref
 3. Look at the [Open Issues](https://github.com/theam/ellmental.py/issues), choose one that interests you, and start contributing.
 4. Spread the word about eLLMental!
 
-Detailed instructions for community contributions can be found in our [Contributing Guide](website/CONTRIBUTING.md).
+Detailed instructions for community contributions can be found in our [Contributing Guide](./CONTRIBUTING.md).
 
 ## License
 

website/docs/03_semantic_search/03_semantic_search.md

@@ -28,9 +28,26 @@ You can use a semantic search for a huge variety of use cases. These are some of
 
 ## How does it work?
 
-To perform a semantic search, we need a way to get how similar a piece of text to a query. In other words, we need to compare the meaning of some text and how related it is to a question. We cant perform calculations on words, just numbers. However, there is a way to generate a vector that represents the meaning of a piece of text. This vector representation is called an embedding. This transformation is usually done by a neural network trained for this kind of task. This vector is then compared to other vectors to find similar documents.
-
-To have a semantic search system, you would need to have the following components:
+A semantic search service allows us to generate embeddings based on natural language text. An embedding is a 
+semantic representation of a text in the "semantics space", an imaginary high-dimensional mathematical representation of 
+all the possible semantics. In this space, each concept is associated with a specific point in a way that words or 
+phrases that are similar from a meaning point of view are placed closer than those with different meanings. In short, an embedding is an array of numbers representing the text's meaning in the semantics space.
+
+For example, If we were to represent the embeddings of the words swimming, swam, walking, walked in a very simplified 
+visualization, we could see them like this:
+
+<img
+  alt="Visualization of word embeddings"
+  src={require("../../static/img/word2vec.png").default}
+  style={{
+    width: "300px",
+  }}/>
+
+Embeddings are useful because they allow you to compare pieces of text by their meaning rather than by their characters 
+or other properties. For example, the embeddings of the sentences "I like apples" and "I like oranges" will be very 
+similar, because the vector representation of the sentences is similar.
+
+Overall, you would need to have the following components to have an end-to-end semantic search system:
 
 1. A system that can ingest text and create embeddings for it.
 2. A database that can store those embeddings.

website/docs/04_community/code_of_conduct.mdx

@@ -0,0 +1,7 @@
+import CodeOfConduct from '../../../CODE_OF_CONDUCT.md';
+
+# Contributor Covenant Code of Conduct
+
+<div class="hiddenh1s">
+<CodeOfConduct/>
+</div>

website/docs/04_community/contributing.mdx

@@ -0,0 +1,7 @@
+import ContributingGuide from '../../../CONTRIBUTING.md';
+
+# Contributing Guide
+
+<div class="hiddenh1s">
+<ContributingGuide />
+</div>

website/docs/04_community/index.md

@@ -0,0 +1,10 @@
+# Community
+
+Community contributions are essential to the development and refinement of eLLMental. You can become a part of the eLLMental community in the following ways:
+
+1. Join the conversation in our [Discord server](https://discord.gg/34cBbvjjAx).
+2. Send us suggestions, questions, or feature requests by creating a [New Issue](https://github.com/theam/ellmental/issues/new).
+3. Look at the [Open Issues](https://github.com/theam/ellmental/issues), choose one that interests you, and start contributing.
+4. Spread the word about eLLMental!
+
+Find detailed instructions and guidelines in the [Contributing Guide](contributing), and make sure to read our [Code of Conduct](code_of_conduct) before you start contributing.

website/sidebars.js

@@ -26,7 +26,22 @@ const sidebars = {
       },
       items: ['semantic_search/getting_started', 'semantic_search/embedding_generators', 'semantic_search/embedding_stores'],
     },
-    'contributing',
+    {
+      type: 'category',
+      label: 'Community',
+      link: {
+        type: 'doc',
+        id: 'community/index'
+      },
+      items: [
+        'community/contributing',
+        {
+          type: 'doc',
+          id: 'community/code_of_conduct',
+          label: 'Code of Conduct'
+        }
+      ]
+    },
   ],
 };