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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

The Meta Model API is an innovative developer interface designed for utilizing Muse Spark 1.1, Meta's advanced multimodal reasoning model tailored for agentic tasks such as coding, tool utilization, and comprehensive computer interactions. Currently available in public preview, this API enables developers to seamlessly integrate Muse Spark 1.1 via an OpenAI-compatible package, simplifying the transition for existing clients while maintaining the same code framework and allowing for easy configuration to the muse-spark-1.1 model. This model excels in personal agentic functions, facilitating planning and coordination across various external applications and services, while also adapting to new native tools, MCP servers, and bespoke skills. Functioning as a primary agent, it can collect contextual information, devise plans, and oversee execution across multiple subagents; conversely, as a subagent, it adheres to its designated role, comprehends available tools, and recognizes when to escalate issues. Additionally, the model is capable of managing a context window of 1 million tokens, allowing it to remember past actions, retrieve information from significantly earlier tasks, and effectively condense context for optimal performance. With these capabilities, the Meta Model API represents a significant advancement in the development of intelligent, responsive applications.

Description

Spark Streaming extends the capabilities of Apache Spark by integrating its language-based API for stream processing, allowing you to create streaming applications in the same manner as batch applications. This powerful tool is compatible with Java, Scala, and Python. One of its key features is the automatic recovery of lost work and operator state, such as sliding windows, without requiring additional code from the user. By leveraging the Spark framework, Spark Streaming enables the reuse of the same code for batch processes, facilitates the joining of streams with historical data, and supports ad-hoc queries on the stream's state. This makes it possible to develop robust interactive applications rather than merely focusing on analytics. Spark Streaming is an integral component of Apache Spark, benefiting from regular testing and updates with each new release of Spark. Users can deploy Spark Streaming in various environments, including Spark's standalone cluster mode and other compatible cluster resource managers, and it even offers a local mode for development purposes. For production environments, Spark Streaming ensures high availability by utilizing ZooKeeper and HDFS, providing a reliable framework for real-time data processing. This combination of features makes Spark Streaming an essential tool for developers looking to harness the power of real-time analytics efficiently.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Apache Spark No 
Claude Agent SDK Yes 
Codex CLI Yes 
Continue Yes 
GitHub Yes 
Hermes Agent Yes 
Hugging Face Yes 
Llama 3 Yes 
Llama 4 Behemoth Yes 
Llama 4 Maverick Yes 
Meta AI Yes 
Muse Spark Yes 
Muse Spark 1.1 Yes 
Muse Spark 1.3 Yes 
OpenAI Yes 
OpenAI Agents SDK Yes 
OpenAI Codex Yes 
PubSub+ Platform No 
Vercel AI SDK Yes 

Integrations

Apache Spark Yes 
Claude Agent SDK No 
Codex CLI No 
Continue No 
GitHub No 
Hermes Agent No 
Hugging Face No 
Llama 3 No 
Llama 4 Behemoth No 
Llama 4 Maverick No 
Meta AI No 
Muse Spark No 
Muse Spark 1.1 No 
Muse Spark 1.3 No 
OpenAI No 
OpenAI Agents SDK No 
OpenAI Codex No 
PubSub+ Platform Yes 
Vercel AI SDK No 

Pricing Details

$1.25 per 1M tokens
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

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 No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

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

Customer Support

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

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Meta

Country

United States

Website

developer.meta.com/ai/products/meta-model-api/

Vendor Details

Company Name

Apache Software Foundation

Founded

1999

Country

United States

Website

spark.apache.org/streaming/

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