Harness the collective intelligence of multiple large language models (LLMs) to enhance decision-making and problem-solving capabilities in complex scenarios.
graph TD;
B[Python]
B --> D[AI Models]
D --> E[Claude Opus ]
D --> F[Google Gemini]
D --> K[Replicate API]
K --> G[Meta LLaMA]
K --> H[Mistral AI]
D --> J[GPT 4o]
B --> L[Environment Management]
L --> M[Python-dotenv]
| Technology | Description |
|---|---|
| Python | Programming language used for backend and AI integration. |
| Anthropic Claude | One of the LLMs used for generating insights. |
| Google Gemini | Another LLM used for generating insights. |
| Meta LLaMA | An LLM used for generating insights. |
| Mistral AI | An LLM used for generating insights. |
| OpenAI API | API for accessing OpenAI's GPT models. |
| Replicate API | API for accessing various AI models and tools. |
| Python-dotenv | Read key-value pairs from a .env file and set them as environment variables. |
graph LR;
A[User Input] --> B[Backend API]
B --> C[Task Distribution]
C --> D[Peasant AIs]
D --> E[Meta LLaMA]
D --> F[Google Gemini]
D --> G[Mistral AI]
D --> H[Anthropic Claude]
E --> I[Responses]
F --> I
G --> I
H --> I
I --> J[King AI Evaluation]
J --> K[Final Answer]
K --> L[User Output]
graph LR
B(User Input) --> C[GPT 4o]
B --> D[Claude Opus]
C --> E[Advisor Models Provide Insights]
D --> E
E --> F[Primary Models Discuss Findings]
F --> G[Resolve Conflicts]
G --> H[Reach Consensus]
H --> I[Provide Final Answer]
I --> J[End]