Solutions to Enable Collaboration of AI Intelligentsia Across Frameworks
BACKGROUND: In development environments where multiple AI frameworks coexist, it is often difficult for intelligences from different frameworks such as LangChain, LlamaIndex, etc. to collaborate directly, which can lead to reduced development efficiency and increased system complexity.AgentIQ solves this challenge by:
- Unified Interface Design: Provide standardized interface specifications that allow intelligences from different frameworks to communicate in a uniform manner
- YAML configuration integration: Define the collaboration process through the workflow.yaml configuration file, for example
_type: react_agentCollaboration modes can be specified - MCP protocol support: Compatible with Model Context Protocol to ensure compatibility with external tool calls.
Specific implementation steps:
- Define the smartbody configuration for each framework separately in workflow.yaml
- set up
tool_namesparameter specifies the list of tools to collaborate on - utilization
llm_nameParameter Unified Management Language Model Calls - pass (a bill or inspection etc)
aiq runCommand Execute Collaboration Tasks
Advantage: Developers can realize intelligent body collaboration without modifying the original technology stack, significantly reducing integration costs.
This answer comes from the articleAgentIQ: An open source tool for flexible connection and management of AI intelligencesThe
May not be reproduced without permission:AI productivity tools " How to solve the problem of different AI framework intelligences not being able to collaborate?
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