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Used model-agnostic examples in quickstart/firsts. (#2773)
Updated prereqs and setup steps to point to the now-more-model-agnostic LLM setup guide, and updated the relevant text to go with it. Co-authored-by: Tony Kipkemboi <iamtonykipkemboi@gmail.com>
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Mark McDonald
@@ -35,7 +35,8 @@ Let's get started building your first crew!
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Before starting, make sure you have:
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1. Installed CrewAI following the [installation guide](/installation)
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2. Set up your OpenAI API key in your environment variables
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2. Set up your LLM API key in your environment, following the [LLM setup
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guide](/concepts/llms#setting-up-your-llm)
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3. Basic understanding of Python
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## Step 1: Create a New CrewAI Project
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@@ -92,7 +93,8 @@ For our research crew, we'll create two agents:
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1. A **researcher** who excels at finding and organizing information
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2. An **analyst** who can interpret research findings and create insightful reports
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Let's modify the `agents.yaml` file to define these specialized agents:
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Let's modify the `agents.yaml` file to define these specialized agents. Be sure
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to set `llm` to the provider you are using.
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```yaml
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# src/research_crew/config/agents.yaml
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@@ -107,7 +109,7 @@ researcher:
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finding relevant information from various sources. You excel at
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organizing information in a clear and structured manner, making
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complex topics accessible to others.
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llm: openai/gpt-4o-mini
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llm: provider/model-id # e.g. openai/gpt-4o, google/gemini-2.0-flash, anthropic/claude...
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analyst:
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role: >
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@@ -120,7 +122,7 @@ analyst:
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and technical writing. You have a talent for identifying patterns
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and extracting meaningful insights from research data, then
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communicating those insights effectively through well-crafted reports.
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llm: openai/gpt-4o-mini
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llm: provider/model-id # e.g. openai/gpt-4o, google/gemini-2.0-flash, anthropic/claude...
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```
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Notice how each agent has a distinct role, goal, and backstory. These elements aren't just descriptive - they actively shape how the agent approaches its tasks. By crafting these carefully, you can create agents with specialized skills and perspectives that complement each other.
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@@ -282,12 +284,12 @@ This script prepares the environment, specifies our research topic, and kicks of
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Create a `.env` file in your project root with your API keys:
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```
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OPENAI_API_KEY=your_openai_api_key
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```sh
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SERPER_API_KEY=your_serper_api_key
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# Add your provider's API key here too.
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```
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You can get a Serper API key from [Serper.dev](https://serper.dev/).
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See the [LLM Setup guide](/concepts/llms#setting-up-your-llm) for details on configuring your provider of choice. You can get a Serper API key from [Serper.dev](https://serper.dev/).
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## Step 8: Install Dependencies
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@@ -45,7 +45,8 @@ Let's dive in and build your first flow!
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Before starting, make sure you have:
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1. Installed CrewAI following the [installation guide](/installation)
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2. Set up your OpenAI API key in your environment variables
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2. Set up your LLM API key in your environment, following the [LLM setup
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guide](/concepts/llms#setting-up-your-llm)
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3. Basic understanding of Python
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## Step 1: Create a New CrewAI Flow Project
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@@ -107,6 +108,8 @@ Now, let's modify the generated files for the content writer crew. We'll set up
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1. First, update the agents configuration file to define our content creation team:
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Remember to set `llm` to the provider you are using.
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```yaml
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# src/guide_creator_flow/crews/content_crew/config/agents.yaml
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content_writer:
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@@ -119,7 +122,7 @@ content_writer:
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You are a talented educational writer with expertise in creating clear, engaging
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content. You have a gift for explaining complex concepts in accessible language
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and organizing information in a way that helps readers build their understanding.
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llm: openai/gpt-4o-mini
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llm: provider/model-id # e.g. openai/gpt-4o, google/gemini-2.0-flash, anthropic/claude...
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content_reviewer:
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role: >
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@@ -132,7 +135,7 @@ content_reviewer:
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content. You have an eye for detail, clarity, and coherence. You excel at
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improving content while maintaining the original author's voice and ensuring
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consistent quality across multiple sections.
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llm: openai/gpt-4o-mini
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llm: provider/model-id # e.g. openai/gpt-4o, google/gemini-2.0-flash, anthropic/claude...
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```
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These agent definitions establish the specialized roles and perspectives that will shape how our AI agents approach content creation. Notice how each agent has a distinct purpose and expertise.
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@@ -441,10 +444,15 @@ This is the power of flows - combining different types of processing (user inter
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## Step 6: Set Up Your Environment Variables
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Create a `.env` file in your project root with your API keys:
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Create a `.env` file in your project root with your API keys. See the [LLM setup
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guide](/concepts/llms#setting-up-your-llm) for details on configuring a provider.
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```
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```sh .env
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OPENAI_API_KEY=your_openai_api_key
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# or
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GEMINI_API_KEY=your_gemini_api_key
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# or
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ANTHROPIC_API_KEY=your_anthropic_api_key
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```
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## Step 7: Install Dependencies
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@@ -547,7 +555,10 @@ Let's break down the key components of flows to help you understand how to build
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Flows allow you to make direct calls to language models when you need simple, structured responses:
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```python
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llm = LLM(model="openai/gpt-4o-mini", response_format=GuideOutline)
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llm = LLM(
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model="model-id-here", # gpt-4o, gemini-2.0-flash, anthropic/claude...
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response_format=GuideOutline
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)
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response = llm.call(messages=messages)
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```
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@@ -180,8 +180,9 @@ Follow the steps below to get Crewing! 🚣♂️
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</Step>
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<Step title="Set your environment variables">
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Before running your crew, make sure you have the following keys set as environment variables in your `.env` file:
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- An [OpenAI API key](https://platform.openai.com/account/api-keys) (or other LLM API key): `OPENAI_API_KEY=sk-...`
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- A [Serper.dev](https://serper.dev/) API key: `SERPER_API_KEY=YOUR_KEY_HERE`
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- The configuration for your choice of model, such as an API key. See the
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[LLM setup guide](/concepts/llms#setting-up-your-llm) to learn how to configure models from any provider.
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</Step>
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<Step title="Lock and install the dependencies">
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- Lock the dependencies and install them by using the CLI command:
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@@ -317,7 +318,7 @@ email_summarizer:
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Summarize emails into a concise and clear summary
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backstory: >
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You will create a 5 bullet point summary of the report
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llm: openai/gpt-4o
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llm: provider/model-id # Add your choice of model here
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```
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<Tip>
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