Quorabot uses multiple LLMs coordinated by an AI Agent, where each model handles a specific task such as reasoning, generation, validation, or refinement to produce accurate, high-quality, and human-like content.
The step wise working of these multiple LLMs are as follows:-
1. User Request Analysis: - User submits a query in the form of chat, report, blog, research, etc. AI Agent analyzes domain , intent and tone.
2. Task Decomposition: - The request is split into smaller tasks such as: Reasoning & planning , Content generation , Fact validation ,etc.
3. Model Selection: - Different LLMs are assigned based on their strengths like : Reasoning Models , Core generation models , search enabled models,etc.
4. Parallel & Sequential Execution: - Some tasks are run parallely while others are in a proper sequence.Some tasks are run parallely while others are in a proper sequence.
5. Context Optimization: - Only relevant outputs from each model are retained. Redundant or conflicting information is removed.
6. Validation & Refinement: - Smart Editor fine-tunes the result. Secondary models checks consistency , originality and human likeness.
7. Human-in-the-Loop: - Final output is delivered. User can edit, regenerate, or approve.
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