llama 3.1 docs (#1812)

* llama 3.1 docs

* update links

Author: sestinj

core/autocomplete/completionProvider.ts

@@ -446,7 +446,7 @@ export class CompletionProvider {
     ) {
       shownGptClaudeWarning = true;
       throw new Error(
-        `Warning: ${llm.model} is not trained for tab-autocomplete, and will result in low-quality suggestions. See the docs to learn more about why: https://docs.continue.dev/walkthroughs/tab-autocomplete#i-want-better-completions-should-i-use-gpt-4`,
+        `Warning: ${llm.model} is not trained for tab-autocomplete, and will result in low-quality suggestions. See the docs to learn more about why: https://docs.continue.dev/features/tab-autocomplete#i-want-better-completions-should-i-use-gpt-4`,
       );
     }
 

core/config/promptFile.ts

@@ -34,7 +34,7 @@ export async function getPromptFiles(
 const DEFAULT_PROMPT_FILE = `# This is an example ".prompt" file
 # It is used to define and reuse prompts within Continue
 # Continue will automatically create a slash command for each prompt in the .prompts folder
-# To learn more, see the full .prompt file reference: https://docs.continue.dev/walkthroughs/prompt-files
+# To learn more, see the full .prompt file reference: https://docs.continue.dev/features/prompt-files
 temperature: 0.0
 ---
 {{{ diff }}}

core/context/retrieval/retrieval.ts

@@ -25,7 +25,7 @@ export async function retrieveContextItemsFromEmbeddings(
     (await extras.ide.getIdeInfo()).ideType === "jetbrains"
   ) {
     throw new Error(
-      "The transformers.js context provider is not currently supported in JetBrains. For now, you can use Ollama to set up local embeddings, or use our 'free-trial' embeddings provider. See here to learn more: https://docs.continue.dev/walkthroughs/codebase-embeddings#embeddings-providers",
+      "The transformers.js context provider is not currently supported in JetBrains. For now, you can use Ollama to set up local embeddings, or use our 'free-trial' embeddings provider. See here to learn more: https://docs.continue.dev/features/codebase-embeddings#embeddings-providers",
     );
   }
 

docs/docs/customization/context-providers.md

@@ -60,7 +60,7 @@ Type '@open' to reference the contents of all of your open files. Set `onlyPinne
 
 ### Codebase Retrieval
 
-Type '@codebase' to automatically retrieve the most relevant snippets from your codebase. Read more about indexing and retrieval [here](../walkthroughs/codebase-embeddings.md).
+Type '@codebase' to automatically retrieve the most relevant snippets from your codebase. Read more about indexing and retrieval [here](../features/codebase-embeddings.md).
 
 ```json
 { "name": "codebase" }
@@ -498,9 +498,7 @@ Continue exposes an API for registering context providers from a 3rd party VSCod
 
 ```json
 {
-  "extensionDependencies": [
-    "continue.continue"
-  ],
+  "extensionDependencies": ["continue.continue"]
 }
 ```
 
@@ -513,7 +511,6 @@ Here is an example:
 import * as vscode from "vscode";
 
 class MyCustomProvider implements IContextProvider {
-
   get description(): ContextProviderDescription {
     return {
       title: "custom",
@@ -525,7 +522,7 @@ class MyCustomProvider implements IContextProvider {
 
   async getContextItems(
     query: string,
-    extras: ContextProviderExtras
+    extras: ContextProviderExtras,
   ): Promise<ContextItem[]> {
     return [
       {
@@ -537,7 +534,7 @@ class MyCustomProvider implements IContextProvider {
   }
 
   async loadSubmenuItems(
-    args: LoadSubmenuItemsArgs
+    args: LoadSubmenuItemsArgs,
   ): Promise<ContextSubmenuItem[]> {
     return [];
   }
@@ -554,5 +551,4 @@ const continueApi = continueExt?.exports;
 
 // register your custom provider
 continueApi?.registerCustomContextProvider(customProvider);
-
-```
+```

docs/docs/walkthroughs/codebase-embeddings.md renamed to docs/docs/features/codebase-embeddings.md

@@ -75,7 +75,7 @@ _You can also use other autocomplete models by adding them to your `config.json`
 
 ## Embeddings
 
-We recommend the following embeddings models, which are used for codebase retrieval as described [here](../walkthroughs/codebase-embeddings.md#embeddings-providers)
+We recommend the following embeddings models, which are used for codebase retrieval as described [here](../features/codebase-embeddings.md#embeddings-providers)
 
 ### Open-source models
 

docs/docs/walkthroughs/prompt-files.md renamed to docs/docs/features/prompt-files.md

@@ -66,7 +66,7 @@ You can use commercial LLMs via APIs using:
 - [Azure OpenAI Service](../reference/Model%20Providers/openai.md)
 - [Google Gemini API](../reference/Model%20Providers/geminiapi.md)
 - [Mistral API](../reference/Model%20Providers/mistral.md)
-- [Voyage AI API](../walkthroughs/codebase-embeddings.md#openai)
+- [Voyage AI API](../features/codebase-embeddings.md#openai)
 - [Cohere API](../reference/Model%20Providers/cohere.md)
 
 **In addition to selecting providers, you will need to figure out [what models to use](./select-model.md).**