Dev-Docs Update

docs/awesome-ollama-functions.md

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+
+
+  # Awesome Ollama Functions
+
+Ollama is a powerful library for interacting with language models. Here are some of its most impressive functions:
+
+## Core Functions
+
+### `generate()`
+- Generates text responses from prompts
+- Supports streaming for real-time output
+- Handles image inputs for multimodal models
+
+### `chat()`
+- Facilitates conversational interactions
+- Manages message history and context
+- Supports image inputs in messages
+
+### `embed()`
+- Creates vector embeddings from text input
+- Useful for semantic search and text analysis
+
+## Model Management
+
+### `create()`
+- Builds custom models from Modelfiles
+- Supports quantization for optimized performance
+
+### `pull()`
+- Downloads models from the Ollama registry
+- Supports progress tracking with streaming
+
+### `push()`
+- Uploads models to the Ollama registry
+- Enables sharing and distribution of custom models
+
+### `list()`
+- Retrieves information about available models
+- Provides details like model size and modification date
+
+### `copy()`
+- Duplicates existing models for customization
+- Facilitates model versioning and experimentation
+
+### `delete()`
+- Removes models from the local system
+- Helps manage storage and model versions
+
+## Advanced Features
+
+### `show()`
+- Displays detailed metadata about a model
+- Includes license, parameters, and system prompts
+
+### `embeddings()`
+- Creates vector representations of text
+- Useful for semantic similarity and clustering tasks
+
+### `parseModelfile()`
+- Processes Modelfiles for custom model creation
+- Handles file paths and blob hashing
+
+These functions showcase Ollama's versatility in model interaction, management, and customization, making it a powerful tool for AI development and deployment.
+
+

docs/best-practices/documentation-style-guide.md

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+# Documentation Style Guide
+
+## Overview
+
+This style guide provides standards for creating clear, consistent, and high-quality documentation. Following these guidelines will help ensure our docs are professional, readable, and useful for our audience.
+
+## General Principles
+
+- Use clear, concise language
+- Be consistent in terminology, formatting, and style 
+- Structure content logically with headings and lists
+- Include relevant code samples and examples
+- Link to related docs and resources
+
+## Writing Style
+
+- Use active voice and present tense
+- Write in second person ("you") when addressing the reader
+- Avoid jargon and overly technical language
+- Use gender-neutral language
+
+## Formatting
+
+- Use Markdown formatting
+- Use sentence case for headings 
+- Use code blocks for code samples
+- Use italics for emphasis sparingly
+- Use numbered lists for sequential steps
+- Use bullet lists for non-sequential items
+
+## Code Examples
+
+- Use syntax highlighting 
+- Include comments to explain complex code
+- Use consistent naming conventions
+- Provide context for code samples
+
+## Images
+
+- Use descriptive alt text
+- Compress images for faster loading
+- Use screenshots sparingly and keep them up-to-date
+
+## Links
+
+- Use descriptive link text (not "click here")
+- Check that all links are valid
+- Use relative links for internal docs
+
+By following these guidelines, we can create documentation that is clear, consistent, and valuable to our users.

docs/show.md

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+# show Documentation
+
+## Brief Description
+The `show` method retrieves and displays metadata for a specified model.
+
+## Usage
+To use the `show` method, you need to create an instance of the Ollama class and call the `show` method with the required parameters.
+
+```javascript
+import Ollama from 'ollama'
+
+const ollama = new Ollama()
+```
+
+## Parameters
+- `request` (ShowRequest object): An object containing the following properties:
+  - `model` (string, required): The name of the model to show metadata for.
+  - `system` (string, optional): A system message to include.
+  - `template` (string, optional): A template to use for the model.
+  - `options` (Partial<Options>, optional): Additional options for the model.
+
+## Return Value
+The `show` method returns a Promise that resolves to a `ShowResponse` object containing the model's metadata.
+
+## Examples
+
+```javascript
+// Basic usage to show metadata for a model
+const response = await ollama.show({ model: 'llama2' })
+console.log(response)
+
+// Show metadata with additional options
+const response = await ollama.show({
+  model: 'llama2',
+  system: 'You are a helpful assistant',
+  template: '{{.System}}\n\nHuman: {{.Prompt}}\n\nAssistant: ',
+  options: { num_gpu: 1 }
+})
+console.log(response)
+```
+
+## Notes or Considerations
+- Ensure that the specified model is available on your Ollama instance before calling the `show` method.
+- The `ShowResponse` object includes detailed information about the model, such as its license, modelfile content, parameters, template, system message, and other metadata.
+- This method is useful for inspecting model configurations and understanding the capabilities of different models in your Ollama setup.

somereadme.md

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+# Dev-Docs: AI-Powered Documentation Generator
+
+## Overview
+
+Dev-Docs is an AI-powered documentation generator designed to streamline the process of creating and maintaining internal documentation for software projects. It integrates seamlessly with Visual Studio Code and offers features like AI-generated context,
+
+![](/img/add_an_image_to_google_slides/step_10.png)
+
+API documentation, and cloud synchronization.
+
+## Key Features
+
+1. AI-powered documentation generation
+
+2. VS Code integration
+
+3. Context generation for multiple files
+
+4. API documentation generation
+
+5. Cloud synchronization
+
+6. Customizable AI prompts
+
+## How It Works
+
+```mermaid
+graph TD
+    A[Install Dev-Docs Extension] --> B[Initialize Dev-Docs]
+    B --> C[Configure dev-docs.json]
+    C --> D[Generate Documentation]
+    D --> E[AI Context Generation]
+    D --> F[API Documentation]
+    D --> G[Manual Editing]
+    E --> H[Sync to Dev-Docs Cloud]
+    F --> H
+    G --> H
+    H --> I[Access on dev-docs.io]
+```
+
+## Getting Started
+
+1. Install the Dev-Docs extension in VS Code
+
+2. Initialize Dev-Docs in your project
+
+3. Configure the `dev-docs.json` file
+
+4. Generate documentation using AI or manually
+
+5. Sync your documentation to Dev-Docs Cloud
+
+## Documentation Structure
+
+* Customize Your AI Generation
+
+* Generate Context on Multiple Files
+
+* Generate Context on a Code File
+
+* Generate Context on a Folder
+
+* Generate Documentation with AI
+
+* Intro to Dev-Docs Internal Documentation
+
+* Use VS Code Extension with Continue
+
+* Use AI to Generate API Documentation
+
+* Install the Extension and Create Your First Internal Docs
+
+* Internal Docs Configuration Options
+
+* Sync Your Dev-Docs to Dev-Docs Cloud
+
+## Key Concepts
+
+* **AI Context Generation**: Automatically create context-aware documentation for your codebase
+
+* **API Documentation**: Generate OpenAPI and Postman collections for your APIs
+
+* **Cloud Sync**: Keep your documentation up-to-date across your team by syncing to Dev-Docs Cloud
+
+* **Customizable Prompts**: Tailor AI-generated content to your specific needs
+
+## Configuration
+
+Customize your Dev-Docs experience by editing the `dev-docs.json` file. Example configuration:
+
+```json
+{
+  "quickDoc": {
+    "acceptedExtensions": [".js", ".py"],
+    "variablesAndFunctions": {
+      "prompts": [
+        {
+          "question": "Is this a function, class, or variable",
+          "title": "Code Type",
+          "documentation": ""
+        },
+        {
+          "question": "Is this code written well? If so why?",
+          "title": "Quality of Code",
+          "documentation": ""
+        }
+      ]
+    }
+  },
+  "ai": {
+    "onSave": true
+  }
+}
+```
+
+## Conclusion
+
+Dev-Docs empowers development teams to create and maintain high-quality internal documentation with minimal effort. By leveraging AI and integrating with popular development tools, Dev-Docs streamlines the documentation process, enabling teams to focus on building great software.