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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Red Hat Ansible Lightspeed, powered by IBM Watsonx Code Assistant, is a generative AI tool that enhances the efficiency of automation teams in creating, implementing, and managing Ansible content. By utilizing natural language prompts, it generates code suggestions tailored for automation tasks while adhering to Ansible best practices. This innovative service enables the transformation of specialized knowledge into trusted and scalable Ansible code that can be utilized across various teams and sectors. With the recent addition of comprehensive Ansible Playbook generation, Ansible Lightspeed significantly speeds up the integration of automation by empowering a broader range of content creators. Designed to minimize the learning curve for new Ansible developers, it allows those with merely a foundational grasp of YAML syntax to articulate their automation objectives using everyday English. Subsequently, Ansible Lightspeed provides relevant code recommendations that facilitate the achievement of these automation goals with greater efficiency and effectiveness. Moreover, this tool not only enhances productivity but also fosters collaboration among team members by streamlining the coding process.

Description

Code Llama is an advanced language model designed to generate code through text prompts, distinguishing itself as a leading tool among publicly accessible models for coding tasks. This innovative model not only streamlines workflows for existing developers but also aids beginners in overcoming challenges associated with learning to code. Its versatility positions Code Llama as both a valuable productivity enhancer and an educational resource, assisting programmers in creating more robust and well-documented software solutions. Additionally, users can generate both code and natural language explanations by providing either type of prompt, making it an adaptable tool for various programming needs. Available for free for both research and commercial applications, Code Llama is built upon Llama 2 architecture and comes in three distinct versions: the foundational Code Llama model, Code Llama - Python which is tailored specifically for Python programming, and Code Llama - Instruct, optimized for comprehending and executing natural language directives effectively.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

1min.AI No 
BLACKBOX AI No 
CodeQwen No 
Deep Infra No 
IBM watsonx Code Assistant Yes 
IONOS Cloud AI Model Hub No 
Llama No 
Llama 2 No 
Llama 3 No 
Llama 3.1 No 
Llama 3.2 No 
Llama 3.3 No 
Meta AI No 
Ollama No 
Pipeshift No 
Prefactor No 
Supy Yes 
Tabby No 

Integrations

1min.AI Yes 
BLACKBOX AI Yes 
CodeQwen Yes 
Deep Infra Yes 
IBM watsonx Code Assistant No 
IONOS Cloud AI Model Hub Yes 
Llama Yes 
Llama 2 Yes 
Llama 3 Yes 
Llama 3.1 Yes 
Llama 3.2 Yes 
Llama 3.3 Yes 
Meta AI Yes 
Ollama Yes 
Pipeshift Yes 
Prefactor Yes 
Supy No 
Tabby Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Red Hat

Founded

1993

Country

United States

Website

www.redhat.com/en/technologies/management/ansible/ansible-lightspeed

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

ai.meta.com/blog/code-llama-large-language-model-coding/

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