docs: Update model reference in LLM configuration

[AMatisse]

This pull request includes a small change to the docs/concepts/llms.mdx file. The change updates the command to run a model from ollama run llama2 to ollama run llama3.

[joaomdmoura]

Disclaimer: This review was made by a crew of AI Agents.

Code Review Comment for PR #2267

Overview

The recent modifications to docs/concepts/llms.mdx aim to improve the documentation surrounding Language Learning Models (LLMs) within the CrewAI framework. This review outlines both the strengths of the documentation and critical areas for improvement.

Identified Issues and Recommendations

1. Inconsistent Model Reference

Location: Ollama configuration section
Issue: The reference to llama3 is likely incorrect, as the correct model should be llama2. Misleading model references can lead users to ineffective implementations.
Recommendation: Update the documentation as follows:

- 2. Run a model: `ollama run llama3`
+ 2. Run a model: `ollama run llama2`

2. Formatting Inconsistencies

Location: Throughout the file
Issue: There are multiple instances of trailing whitespace that detract from the document's professional appearance.
Recommendation: Standardize formatting by removing trailing whitespace from the following lines:

• Line 62 (after "# your model here")
• Line 114 (after "capabilities.")
• Remove unnecessary empty lines throughout configuration examples.

3. Non-Standard Model Name

Location: Example configurations
Issue: The gpt-4o model name is not a recognized OpenAI model.
Recommendation: Correct the example to reflect the accurate model name:

- llm = LLM(model="openai/gpt-4o")  # 128K tokens
+ llm = LLM(model="openai/gpt-4-turbo-preview")  # 128K tokens

4. Structural Improvements

Location: Provider Configuration Examples section
Issue: The authentication examples lack clarity and structure.
Recommendation: Restructure the section for better readability:

## Authentication Examples

### API Key Format
```bash
# OpenAI
OPENAI_API_KEY=sk-...            # Format: sk-... (51 characters)

# Anthropic
ANTHROPIC_API_KEY=sk-ant-...     # Format: sk-ant-... (40+ characters)

Basic Usage

from crewai import LLM

# OpenAI Configuration
llm = LLM(
    provider="openai",
    model="gpt-4-turbo-preview",
    api_key="sk-..."  # Optional if set in environment
)

## Positive Aspects
- The documentation is well-organized and easy to follow, with clear examples for each provider.
- The comprehensive coverage of configuration options enhances user understanding and usability.
- The inclusion of warnings and tips throughout the document is particularly helpful for users.

## Suggestions for Enhancement
1. Add version compatibility information for each provider to inform users of necessary changes when models are updated.
2. Incorporate specific error handling examples to guide users in understanding potential issues with configurations.
3. Develop a troubleshooting section outlining common issues and their solutions.
4. Consider creating a comparative table of popular models, highlighting their characteristics and usage scenarios.

## Documentation Style Enhancements
1. Utilize more inline code comments to clarify complex configurations.
2. Link to provider-specific documentation for detailed insights on configurations and options.
3. Include a quick reference table at the document's beginning for easy navigation.

## Security Considerations
1. Emphasize best practices for API key management to protect users.
2. Provide information regarding rate limits and cost considerations.
3. Offer examples of secure configuration practices to strengthen user security awareness.

Overall, the documentation updates are a positive step toward improving user experience; however, addressing the identified issues and incorporating the recommended enhancements will significantly elevate the clarity and utility of the documentation. Continuous updates in accordance with API changes will ensure that users can effectively utilize the LLM configurations in their projects.