31 lines
1.8 KiB
Markdown
31 lines
1.8 KiB
Markdown
# Principles & Interactions
|
|
|
|
The effectiveness of the 4-Tier Multi-Model Architecture depends on well-defined interfaces and clear communication protocols between layers.
|
|
|
|
## Interaction Flow
|
|
|
|
1. **Ingress:** The User sends a query to Tier 1.
|
|
2. **Intent & Routing:** Tier 1 analyzes the query and identifies the required expertise.
|
|
3. **Specialist Call:** Tier 1 dispatches a request to one or more Tier 2 specialists.
|
|
4. **Knowledge Retrieval:** Tier 2 specialists query Tier 3 for specific facts or context needed for their task.
|
|
5. **Execution:** Tier 2 specialists process the request using the retrieved data.
|
|
6. **Synthesis:** Tier 1 receives the output from Tier 2, synthesizes it, and presents it to the User.
|
|
7. **Observation:** Tier 4 logs the entire transaction, collects feedback, and updates metrics.
|
|
|
|
## Core Architectural Principles
|
|
|
|
### 1. Separation of Concerns
|
|
Each tier should have a single, clear responsibility. Tier 1 should not perform heavy computation; Tier 2 should not handle user-facing conversation logic.
|
|
|
|
### 2. Standardized Communication
|
|
Use structured data formats (like JSON) for all inter-tier communication. This ensures that different models (potentially from different providers) can work together seamlessly.
|
|
|
|
### 3. Graceful Degradation
|
|
If a Tier 2 specialist fails or is unavailable, Tier 1 should be able to fall back to a more general model or provide a meaningful error message to the user.
|
|
|
|
### 4. Verification Over Trust
|
|
Tier 1 should validate the output of Tier 2 specialists before presenting it to the user. Tier 4 should periodically audit the entire pipeline to ensure quality and safety.
|
|
|
|
### 5. Data Privacy & Governance
|
|
Ensure that data flowing through Tier 3 and 4 is handled according to security policies, with proper sanitization and access controls.
|