multi-llm-agent

Multi-LLM orchestration coordinates OpenAI, Gemini, Anthropic, and Ollama APIs to execute collaborative patterns—role-based division, discussion, chain pipelines, and parallel execution—solving tasks like code review, design, and security assessment by applying diverse model perspectives simultaneously.

Multi-LLM agent supports role-based task distribution where agents assume specialized roles, discussion patterns enabling consensus, chain pipelines sequencing LLM outputs, and parallel execution with synthesis, enabling complex workflows across heterogeneous providers.

Yes. The agent integrates OpenAI, Gemini, Anthropic, and Ollama through unified APIs, enabling dynamic runtime composition of scenarios with multiple providers, token accounting, detailed logging, and environment configuration for team workflows.

The agent provides detailed logging and token accounting across all provider calls, supporting environment configuration and reusable presets so teams can track API consumption, monitor collaboration patterns, and audit multi-LLM interactions programmatically.

Role-based patterns assign specialized tasks to specific LLMs, while discussion patterns enable multiple LLMs to iterate and reach consensus. Chain patterns sequence outputs linearly; parallel patterns execute simultaneously and synthesize results for comprehensive solutions.

Yes. The agent uses YAML configuration with reusable presets enabling dynamic scenario composition at runtime, allowing teams to define collaboration patterns, provider selection, role assignments, and workflow parameters without code changes.