LangGraph-Swift

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LangGraph-Swift is a Swift framework for building AI agent pipelines using composable graph nodes. It supports connecting to LLM models, retrieval, memory, and external tools to orchestrate workflows. Developers define type-safe graphs, visualize execution, and run on iOS, macOS, and Linux.
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May 04 2025
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LangGraph-Swift

LangGraph-Swift

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LangGraph-Swift
LangGraph-Swift is a Swift framework for building AI agent pipelines using composable graph nodes. It supports connecting to LLM models, retrieval, memory, and external tools to orchestrate workflows. Developers define type-safe graphs, visualize execution, and run on iOS, macOS, and Linux.
Added on:
Social & Email:
Platform:
Pricing:
May 04 2025
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What is LangGraph-Swift?

LangGraph-Swift provides a graph-based DSL for constructing AI workflows by chaining nodes representing actions such as LLM queries, retrieval operations, tool calls, and memory management. Each node is type-safe and can be connected to define execution order. The framework supports adapters for popular LLM services like OpenAI, Azure, and Anthropic, as well as custom tool integrations for calling APIs or functions. It includes built-in memory modules to retain context across sessions, debugging and visualization tools, and cross-platform support for iOS, macOS, and Linux. Developers can extend nodes with custom logic, enabling rapid prototyping of chatbots, document processors, and autonomous agents within native Swift.

Who will use LangGraph-Swift?

  • Swift Developers
  • iOS/macOS App Developers
  • AI Researchers
  • Software Engineers building AI agents

How to use the LangGraph-Swift?

  • Step1: Add LangGraph-Swift via Swift Package Manager to your Xcode project.
  • Step2: Import the LangGraph module in your Swift files.
  • Step3: Define a Graph and add nodes like LLMNode, ToolNode, and MemoryNode.
  • Step4: Configure LLM and tool providers with API keys and adapters.
  • Step5: Connect nodes to form a pipeline and run your graph asynchronously.
  • Step6: Use provided debugging and visualization utilities to inspect execution.

Platform

  • mac
  • linux
  • ios

LangGraph-Swift's Core Features & Benefits

The Core Features

  • Graph-based composable pipelines
  • LLM integration via adapters
  • Memory modules for context
  • Tool and API integrations
  • Type-safe Swift DSL
  • Debugging and visualization utilities

The Benefits

  • Modular and reusable AI workflows
  • Seamless native Swift integration
  • Cross-platform support
  • Type safety and compile-time checks
  • Easier debugging of complex flows

LangGraph-Swift's Main Use Cases & Applications

  • Building chatbots and conversational agents
  • Document summarization and Q&A systems
  • Automated customer support workflows
  • Retrieval-augmented generation applications
  • Custom tool and API orchestration

LangGraph-Swift's Pros & Cons

The Pros

Enables advanced visualization of language model constructs.
Facilitates complex language data representations.
Designed specifically for Swift developers, integrating well in Apple ecosystem.
Supports natural language processing tasks through graph-based representation.

The Cons

Limited to Swift language environment.
Documentation and community support appear minimal.
No explicit information about open-source status or active maintenance.

LangGraph-Swift's Pricing

Has free planNo
Free trial details
Pricing model
Is credit card requiredNo
Paid from
Has lifetime planNo
Billing frequency
For the latest prices, please visit: https://bsorrentino.github.io/LangGraph-Swift/documentation/langgraph/

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LangGraph-Swift Reviews

5/5
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LangGraph-Swift's Main Competitors and alternatives?

  • LangChain
  • Ollama Swift
  • AIKit
  • Haystack (Python)