diff --git a/fern/pages/-ARCHIVE-/old-tutorials/semantic-search.mdx b/fern/pages/-ARCHIVE-/old-tutorials/semantic-search.mdx index f94fe131..32385f5f 100644 --- a/fern/pages/-ARCHIVE-/old-tutorials/semantic-search.mdx +++ b/fern/pages/-ARCHIVE-/old-tutorials/semantic-search.mdx @@ -58,7 +58,7 @@ If you're running this in a jupyter notebook, you'll need to prepend a `!` to th !pip install --upgrade cohere ``` -Get your Cohere API key by [signing up here](https://os.cohere.ai/register). Paste it in `api_key` below. +Get your Cohere API key by [signing up here](https://dashboard.cohere.ai/register). Paste it in `api_key` below. #### 1a. Import the Necessary Dependencies to Run this Example diff --git a/fern/pages/-ARCHIVE-/text-classification-guide.mdx b/fern/pages/-ARCHIVE-/text-classification-guide.mdx index 21ddae87..bc273cf3 100644 --- a/fern/pages/-ARCHIVE-/text-classification-guide.mdx +++ b/fern/pages/-ARCHIVE-/text-classification-guide.mdx @@ -14,7 +14,7 @@ Human collaboration runs on language. The firehose of documents, emails, and mes - Analysis of financial filings and reports ![](../../assets/images/698b185-Text_Classification_Visual_1.svg) -The Cohere platform aims to help you build classifiers for these and other use cases. You can [start trying Cohere for free when you sign up](https://os.cohere.ai/) and automatically receive $75 in free credits. +The Cohere platform aims to help you build classifiers for these and other use cases. You can [start trying Cohere for free when you sign up](https://dashboard.cohere.ai/) and automatically receive $75 in free credits. ## Training classifiers with Cohere’s language models diff --git a/fern/pages/cohere-api/create-an-api-key.mdx b/fern/pages/cohere-api/create-an-api-key.mdx index 12dccc65..da0bbb67 100644 --- a/fern/pages/cohere-api/create-an-api-key.mdx +++ b/fern/pages/cohere-api/create-an-api-key.mdx @@ -28,7 +28,7 @@ updatedAt: "Wed Sep 14 2022 15:18:32 GMT+0000 (Coordinated Universal Time)" Use the command `co key create [key_name]`. -You must be [signed in](auth) to use this command. +You must be [signed in](/docs/auth) to use this command. # Retrieving an API Key diff --git a/fern/pages/command-line-interface/command-reference.mdx b/fern/pages/command-line-interface/command-reference.mdx index 88cab325..d9cbc81e 100644 --- a/fern/pages/command-line-interface/command-reference.mdx +++ b/fern/pages/command-line-interface/command-reference.mdx @@ -23,7 +23,7 @@ This page shows some common CLI Commands. For more info about a specific command co auth login --email string="example@youremail.com" ``` -You will be prompted to put in your password. For more commands related to your Cohere account, see the [Auth](auth) and [User](user) commands. +You will be prompted to put in your password. For more commands related to your Cohere account, see the [Auth](/docs/auth) and [User](/docs/user) commands. Currently, SSO accounts cannot log in via the CLI. @@ -55,7 +55,7 @@ co model generate --max-tokens n '[Your Prompt Here]' ``` - If you want to use a finetuned model, you can do so by using the model's full ID with the `model` flag. See the [Model reference page](model) for more details. + If you want to use a finetuned model, you can do so by using the model's full ID with the `model` flag. See the [Model reference page](/docs/model) for more details. ## Finetune a Model diff --git a/fern/pages/cookbooks/hello-world-meet-ai.mdx b/fern/pages/cookbooks/hello-world-meet-ai.mdx index a9d7314c..1e75c432 100644 --- a/fern/pages/cookbooks/hello-world-meet-ai.mdx +++ b/fern/pages/cookbooks/hello-world-meet-ai.mdx @@ -27,7 +27,7 @@ We’ll cover three groups of tasks that you will typically work on when dealing - Classifying text - Analyzing text -The first step is to install the Cohere Python SDK. Next, create an API key, which you can generate from the Cohere [dashboard](https://dashboard.cohere.com/register) or [CLI tool](https://docs.cohere.ai/cli-key). +The first step is to install the Cohere Python SDK. Next, create an API key, which you can generate from the Cohere [dashboard](https://dashboard.cohere.com/register) or [CLI tool](/docs/key). ```python PYTHON ! pip install cohere altair umap-learn -q diff --git a/fern/pages/llm-university/intro-building-apps/app-examples.mdx b/fern/pages/llm-university/intro-building-apps/app-examples.mdx index 28aefebb..80c7355a 100644 --- a/fern/pages/llm-university/intro-building-apps/app-examples.mdx +++ b/fern/pages/llm-university/intro-building-apps/app-examples.mdx @@ -10,27 +10,27 @@ updatedAt: "Thu Apr 18 2024 10:45:10 GMT+0000 (Coordinated Universal Time)" Use the embed endpoint with Langchain to efficiently build semantic search applications on top of Cohere’s multilingual model. -### Multilingual Movie Search +### Multilingual Movie Search Build a movie search and recommendation app using the embed endpoint, similarity, and nearest neighbors. -### Topic Modeler +### Topic Modeler Using the embed endpoint and clustering, build an app that extracts the main topics from a large collection of text documents. -### Invoice Extractor +### Invoice Extractor Using the generate endpoint, build an app that extracts important information from invoices. -### News Article Recommender +### News Article Recommender Build an article recommender app using the embed endpoint and similarity to find the closest articles to a given article. Then classify each article by category and extract tags from the articles. -### Multilingual Sentiment Analysis +### Multilingual Sentiment Analysis Using embeddings, build a sentiment analysis classifier that works in many languages. -### Document Question Answering +### Document Question Answering Build an app that takes a user's question about a given document and generates an answer by searching the most semantically similar sections of the document. diff --git a/fern/pages/llm-university/intro-text-representation/embed-endpoint.mdx b/fern/pages/llm-university/intro-text-representation/embed-endpoint.mdx index af4d3f51..cc87e3fc 100644 --- a/fern/pages/llm-university/intro-text-representation/embed-endpoint.mdx +++ b/fern/pages/llm-university/intro-text-representation/embed-endpoint.mdx @@ -9,7 +9,7 @@ createdAt: "Mon May 01 2023 14:37:21 GMT+0000 (Coordinated Universal Time)" updatedAt: "Wed Apr 03 2024 19:03:21 GMT+0000 (Coordinated Universal Time)" --- ![](../../../assets/images/0d1dd7c-image.png) -In Module 1 you learned about text embeddings, and how they are a very useful way to turn text into numbers that capture its meaning and context. In this chapter you'll learn how to put them in practice using the Embed endpoint. You'll use it to explore a dataset of sentences, and be able to plot them in the plane and observe graphically that indeed similar sentences are mapped to close points in the embedding. +In Module 1 you learned about text embeddings, and how they are a very useful way to turn text into numbers that capture its meaning and context. In this chapter you'll learn how to put them in practice using the Embed endpoint. You'll use it to explore a dataset of sentences, and be able to plot them in the plane and observe graphically that indeed similar sentences are mapped to close points in the embedding. ### Colab Notebook diff --git a/fern/pages/llm-university/intro-the-cohere-platform/endpoints.mdx b/fern/pages/llm-university/intro-the-cohere-platform/endpoints.mdx index 9f0422f0..700a63b3 100644 --- a/fern/pages/llm-university/intro-the-cohere-platform/endpoints.mdx +++ b/fern/pages/llm-university/intro-the-cohere-platform/endpoints.mdx @@ -29,7 +29,7 @@ Example use cases: Foundational model: Command -[API Reference](/reference/chat-1) +[API Reference](/reference/chat) ### Embed diff --git a/scripts/cookbooks-mdx/analyzing-hacker-news.mdx b/scripts/cookbooks-mdx/analyzing-hacker-news.mdx index 3f2ff378..ab2a46d6 100644 --- a/scripts/cookbooks-mdx/analyzing-hacker-news.mdx +++ b/scripts/cookbooks-mdx/analyzing-hacker-news.mdx @@ -229,7 +229,7 @@ warnings.filterwarnings('ignore') pd.set_option('display.max_colwidth', None) ``` -Fill in your Cohere API key in the next cell. To do this, begin by [signing up to Cohere](https://os.cohere.ai/) (for free!) if you haven't yet. Then get your API key [here](https://dashboard.cohere.com/api-keys). +Fill in your Cohere API key in the next cell. To do this, begin by [signing up to Cohere](https://dashboard.cohere.ai/) (for free!) if you haven't yet. Then get your API key [here](https://dashboard.cohere.com/api-keys). ```python PYTHON co = cohere.Client("COHERE_API_KEY") # Insert your Cohere API key diff --git a/scripts/cookbooks-mdx/basic-semantic-search.mdx b/scripts/cookbooks-mdx/basic-semantic-search.mdx index e1fb8646..fcc1ef9e 100644 --- a/scripts/cookbooks-mdx/basic-semantic-search.mdx +++ b/scripts/cookbooks-mdx/basic-semantic-search.mdx @@ -151,7 +151,7 @@ And if you're running an older version of the SDK, you might need to upgrade it #!pip install --upgrade cohere ``` -Get your Cohere API key by [signing up here](https://os.cohere.ai/register). Paste it in the cell below. +Get your Cohere API key by [signing up here](https://dashboard.cohere.ai/register). Paste it in the cell below. ## 1. Getting Set Up @@ -173,7 +173,7 @@ warnings.filterwarnings('ignore') pd.set_option('display.max_colwidth', None) ``` -You'll need your API key for this next cell. [Sign up to Cohere](https://os.cohere.ai/) and get one if you haven't yet. +You'll need your API key for this next cell. [Sign up to Cohere](https://dashboard.cohere.ai/) and get one if you haven't yet. ```python PYTHON model_name = "embed-english-v3.0" diff --git a/scripts/cookbooks-mdx/hello-world-meet-ai.mdx b/scripts/cookbooks-mdx/hello-world-meet-ai.mdx index de119e06..d98018ed 100644 --- a/scripts/cookbooks-mdx/hello-world-meet-ai.mdx +++ b/scripts/cookbooks-mdx/hello-world-meet-ai.mdx @@ -146,7 +146,7 @@ We’ll cover three groups of tasks that you will typically work on when dealing - Classifying text - Analyzing text -The first step is to install the Cohere Python SDK. Next, create an API key, which you can generate from the Cohere [dashboard](https://os.cohere.ai/register) or [CLI tool](https://docs.cohere.ai/cli-key). +The first step is to install the Cohere Python SDK. Next, create an API key, which you can generate from the Cohere [dashboard](https://dashboard.cohere.ai/register) or [CLI tool](https://docs.cohere.ai/cli-key). ```python PYTHON ! pip install cohere altair umap-learn -q diff --git a/scripts/cookbooks-mdx/text-classification-using-embeddings.mdx b/scripts/cookbooks-mdx/text-classification-using-embeddings.mdx index f03a02b1..566d0dcb 100644 --- a/scripts/cookbooks-mdx/text-classification-using-embeddings.mdx +++ b/scripts/cookbooks-mdx/text-classification-using-embeddings.mdx @@ -245,7 +245,7 @@ labels_test = labels_test[:95] ## 2. Set up the Cohere client and get the embeddings of the reviews -We're now ready to retrieve the embeddings from the API. You'll need your API key for this next cell. [Sign up to Cohere](https://os.cohere.ai/) and get one if you haven't yet. +We're now ready to retrieve the embeddings from the API. You'll need your API key for this next cell. [Sign up to Cohere](https://dashboard.cohere.ai/) and get one if you haven't yet. ```python PYTHON model_name = "embed-english-v3.0"