New Model providers, Execute a Flow within a Flow

Connect with More Providers, Build complex Agentic Systems and Refined Access Controls

· 2 min read
New Model providers, Execute a Flow within a Flow

Adding 10 model providers → Expanding Model Capabilities

We have upgraded our model proxy system to support several new models, including:

  • Cloudflare
  • Cohere
  • xAI
  • AWS Bedrock
  • Azure
  • Cohere
  • Perplexity
  • FireworksAI
  • DeepInfra
  • Together AI

In addition, we now provide recommendations for the optimal model from each provider, categorized as follows:

  • Preferred: The default model we recommend, offering the best balance of speed and quality.
  • Best Quality: The model with the highest overall response quality.
  • Fastest: The model with the quickest response time.
  • Cheapest: The model with the lowest token cost (including both input and output).
Models in Generative AI Projects - Lamatic.ai Docs
Models in Lamatic Studio

Execute Flow within a Flow

Agentic Systems now support complex workflows where you can invoke other Agentic Flows to achieve your desired outcomes. This new capability allows for the creation of intricate, multi-step processes. Simply select the Execute Flow node from the node selector and choose the Flow you want to run.

Currently, you can select flows that use Lamatic-built interfaces as trigger nodes, such as GraphQL, Chat, and Search.

Execute Flow Documentation - Lamatic.ai Docs

Other Improvements

Improved Support for Role based Access Controls

We have significantly improved support for Role-Based Access Control (RBAC) to ensure a more secure, scalable, and flexible management of permissions within the system.

Function

Owner

Admin

Editor

Developer

Viewer

Manage Org

Billing

Manage Project

Manage Flow

Test & Preview Flows

Log Access

Integration Access

Easier Integration of third party applications

We have simplified the process of integrating third-party applications into your flows, making it more efficient and user-friendly.

Passing context history in JSON Generator

The JSON Generator now supports passing context history, enabling more dynamic and context-aware responses. This feature allows you to include historical data or previous interactions as part of the JSON structure to improve the flow and relevance of your output.


What Feature would you like to see next? let us know below

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