Detailed Module Descriptions
Agent Creator & Management Module
Purpose: Empowers creators to design and manage AI agents, regardless of whether they are natively built in partnr Chat or imported from an external framework.
Key Features:
Profile Editor: Customize identity, personality, behavioral parameters, and lore.
Import/Export Capability: Tools to import external agents via a memory sharing protocol.
Version Control: Track changes and history of agent configurations.
Conversational Chat Interface
Purpose: Provides an engaging and responsive user interface for real-time interaction with AI agents.
Key Features:
Real-Time Messaging: Uses WebSockets and real-time event streams.
Session Context Management: Maintains conversation history and dynamic context for accurate agent responses.
Rich Media Support: Enables emojis, images, and multimedia in chats.
Hybrid Inference Engine
Purpose: Centralizes natural language processing by dynamically routing inference requests to one or more of the following:
OpenAI, Gemini, Anthropic API,
Local LLM,
RAG system,
External framework connectors.
Features:
Dynamic Routing: Based on performance metrics, cost considerations, and user configuration.
Aggregation & Merging: Combines responses from multiple sources when necessary.
Fallback Handling: Automatically falls back to alternate inference modalities if one fails.
Quality Verification & Scoring System
Purpose: Evaluates user inputs to determine their quality and relevance.
Mechanism:
Dual-Pass Evaluation: The primary LLM response is accompanied by a quality scoring pass.
Structured Output: Uses JSON schemas to return quality scores.
Thresholding: Messages above a set threshold (e.g., ≥7/10) trigger reward workflows and are queued for fine-tuning.
Fine-Tuning & Model Update Pipeline
Purpose: Ensures continuous improvement of the underlying LLM through user-driven feedback.
Process:
Data Aggregation: Verified high-quality messages are aggregated in a data lake.
Scheduled Fine-Tuning: Periodic retraining cycles using distributed processing.
Versioning and Canary Releases: New models are deployed using a canary release strategy to minimize service disruption.
Monitoring: Performance metrics (accuracy, latency, user satisfaction) are tracked post-deployment.
Wallet Integration & Token Economy
Purpose: Provides each agent with a robust, multi-chain wallet that serves as the agent’s identity and session manager. The wallet enables decentralized management of tokens and digital assets.
Key Features:
Multi-Chain Support:
Supports multiple blockchain networks (e.g., Ethereum, Binance Smart Chain, Polygon) to optimize cost and performance.
Agents can accept gifts or purchases from users on multiple chains, maximizing accessibility.
Token Transactions:
Users may send tokens, in-app currency, or digital assets directly to an Agent’s wallet.
This can include “gifts” or “tips” sent by users who enjoy interacting with a particular Agent’s personality or services.
Agent Marketplace:
Agents can list and sell digital items—such as AI-generated art, personalized images, or other creative assets—directly through their wallet interface.
Revenue flows into the Agent’s wallet, which may then be used to fund further Agent development or be distributed to the Agent’s creator.
Decentralized Agent Session:
The wallet is integral to an Agent’s identity, keeping a record of ownership, transaction history, and any purchased digital goods.
An immutable blockchain ledger ensures transparency and trust in every transaction.
Security & Key Management:
Private keys are stored securely using HSMs or cloud-based KMS, with multi-factor authentication.
This safeguards both the Agent’s and user’s interests, ensuring that monetary exchanges cannot be hijacked or tampered with.
User-Friendly Wallet API:
A small percentage of transactions may fund platform sustainability, fueling continued R&D and community incentives.
The token economy aligns user, creator, and platform interests, reinforcing the growth and sophistication of Agents over time.
By seamlessly integrating monetization flows into the AI Agent lifecycle, partnr Chat demonstrates the potential for Agents not just to interact but to grow economically alongside their users, fostering a vibrant marketplace of ideas, digital goods, and shared value creation.
Reward Distribution Module
Purpose: Automates the reward process for high-quality interactions via blockchain transactions.
Workflow:
Trigger Event: A message passes the quality threshold.
Reward Calculation: Compute token rewards based on pre-defined parameters.
Smart Contract Invocation: The wallet API calls a smart contract function to execute the token transfer.
Audit Logging: All reward transactions are logged for compliance and traceability.
External Agent Integration & Memory Sharing Protocol
Purpose: Ensures interoperability between agents built on external frameworks (e.g., Eliza, Virtuals) and partnr Chat.
Key Features:
Memory Sharing Protocol:
Uses a standardized data format (e.g., JSON) to represent memory snapshots, context cues, and learned associations.
Provides import/export endpoints to synchronize memory between external agents and partnr Chat.
Supports versioning to maintain backward compatibility.
Adapter Modules: Custom adapters convert external memory formats into the partnr Chat schema and vice versa.
Public API:
Integration Capabilities: Enables third-party applications to leverage the platform’s advanced AI and wallet functionalities.
Customisation Endpoints: Offers endpoints for agent customisation, data retrieval, and wallet management.
Security Measures: Robust authentication and role-based access control safeguard data.