feat(mma): Complete Visual DAG implementation, fix link creation/deletion, and sync docs

This commit is contained in:
2026-03-06 19:13:20 -05:00
parent 1c977d25d5
commit 661566573c
11 changed files with 260 additions and 36 deletions

View File

@@ -0,0 +1,10 @@
{
"id": "minimax_provider_20260306",
"title": "MiniMax Provider Integration",
"description": "Add MiniMax as a new AI provider with M2.5, M2.1, M2 models",
"type": "feature",
"status": "new",
"created_at": "2026-03-06",
"priority": "high",
"owner": "tier2-tech-lead"
}

View File

@@ -0,0 +1,93 @@
# Implementation Plan: MiniMax Provider Integration (minimax_provider_20260306)
> **Reference:** [Spec](./spec.md)
## Phase 1: Provider Registration
Focus: Add minimax to PROVIDERS lists and credentials
- [ ] Task 1.1: Add "minimax" to PROVIDERS list
- WHERE: src/gui_2.py line 28
- WHAT: Add "minimax" to PROVIDERS list
- HOW: Edit the list
- [ ] Task 1.2: Add "minimax" to app_controller.py PROVIDERS
- WHERE: src/app_controller.py line 117
- WHAT: Add "minimax" to PROVIDERS list
- [ ] Task 1.3: Add minimax credentials template
- WHERE: src/ai_client.py (credentials template section)
- WHAT: Add minimax API key section to credentials template
- HOW:
```toml
[minimax]
api_key = "your-key"
```
## Phase 2: Client Implementation
Focus: Implement MiniMax client and model listing
- [ ] Task 2.1: Add client globals
- WHERE: src/ai_client.py (around line 73)
- WHAT: Add _minimax_client, _minimax_history, _minimax_history_lock
- [ ] Task 2.2: Implement _list_minimax_models
- WHERE: src/ai_client.py
- WHAT: Return list of available models
- HOW:
```python
def _list_minimax_models(api_key: str) -> list[str]:
return ["MiniMax-M2.5", "MiniMax-M2.5-highspeed", "MiniMax-M2.1", "MiniMax-M2.1-highspeed", "MiniMax-M2"]
```
- [ ] Task 2.3: Implement _classify_minimax_error
- WHERE: src/ai_client.py
- WHAT: Map MiniMax errors to ProviderError
- [ ] Task 2.4: Implement _ensure_minimax_client
- WHERE: src/ai_client.py
- WHAT: Initialize OpenAI client with MiniMax base URL
## Phase 3: Send Implementation
Focus: Implement _send_minimax function
- [ ] Task 3.1: Implement _send_minimax
- WHERE: src/ai_client.py (after _send_deepseek)
- WHAT: Send chat completion request to MiniMax API
- HOW:
- Use OpenAI SDK with base_url="https://api.minimax.chat/v1"
- Support streaming and non-streaming
- Handle tool calls
- Manage conversation history
- [ ] Task 3.2: Add minimax to list_models routing
- WHERE: src/ai_client.py list_models function
- WHAT: Add elif provider == "minimax": return _list_minimax_models()
## Phase 4: Integration
Focus: Wire minimax into the send function
- [ ] Task 4.1: Add minimax to set_provider
- WHERE: src/ai_client.py set_provider function
- WHAT: Validate minimax model
- [ ] Task 4.2: Add minimax to send routing
- WHERE: src/ai_client.py send function (around line 1607)
- WHAT: Add elif for minimax to call _send_minimax
- [ ] Task 4.3: Add minimax to reset_session
- WHERE: src/ai_client.py reset_session function
- WHAT: Clear minimax history
- [ ] Task 4.4: Add minimax to history bleeding
- WHERE: src/ai_client.py _add_bleed_derived
- WHAT: Handle minimax history
## Phase 5: Testing
Focus: Verify integration works
- [ ] Task 5.1: Write unit tests for minimax integration
- WHERE: tests/test_minimax_provider.py
- WHAT: Test model listing, error classification
- [ ] Task 5.2: Manual verification
- WHAT: Test provider switching in GUI

View File

@@ -0,0 +1,53 @@
# Track Specification: MiniMax Provider Integration
## Overview
Add MiniMax as a new AI provider to Manual Slop. MiniMax provides high-performance text generation models (M2.5, M2.1, M2) with massive context windows (200k+ tokens) and competitive pricing.
## Current State Audit
- `src/ai_client.py`: Contains provider integration for gemini, anthropic, gemini_cli, deepseek
- `src/gui_2.py`: Line 28 - PROVIDERS list
- `src/app_controller.py`: Line 117 - PROVIDERS list
- credentials.toml: Has sections for gemini, anthropic, deepseek
## Integration Approach
Based on MiniMax documentation, the API is compatible with both **Anthropic SDK** and **OpenAI SDK**. We will use the **OpenAI SDK** approach since it is well-supported and similar to DeepSeek integration.
### API Details (from platform.minimax.io)
- **Base URL**: `https://api.minimax.chat/v1`
- **Models**:
- `MiniMax-M2.5` (204,800 context, ~60 tps)
- `MiniMax-M2.5-highspeed` (204,800 context, ~100 tps)
- `MiniMax-M2.1` (204,800 context)
- `MiniMax-M2.1-highspeed` (204,800 context)
- `MiniMax-M2` (204,800 context)
- **Authentication**: API key in header `Authorization: Bearer <key>`
## Goals
1. Add minimax provider to Manual Slop
2. Support chat completions with tool calling
3. Integrate into existing provider switching UI
## Functional Requirements
- FR1: Add "minimax" to PROVIDERS list in gui_2.py and app_controller.py
- FR2: Add minimax credentials section to credentials.toml template
- FR3: Implement _minimax_client initialization
- FR4: Implement _list_minimax_models function
- FR5: Implement _send_minimax function with streaming support
- FR6: Implement error classification for MiniMax
- FR7: Add minimax to provider switching dropdown in GUI
- FR8: Add to ai_client.py send() function routing
- FR9: Add history management (like deepseek)
## Non-Functional Requirements
- NFR1: Follow existing provider pattern (see deepseek integration)
- NFR2: Support tool calling for function execution
- NFR3: Handle rate limits and auth errors
- NFR4: Use OpenAI SDK for simplicity
## Architecture Reference
- `docs/guide_architecture.md`: AI client multi-provider architecture
- Existing deepseek integration in `src/ai_client.py` (lines 1328-1520)
## Out of Scope
- Voice/T2S, Video, Image generation (text only for this track)
- Caching support (future enhancement)