archiving tracks

conductor/archive/minimax_provider_20260306/spec.md

@@ -0,0 +1,56 @@
+# 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.
+
+## Documentation
+See all ./doc_*.md files
+
+## 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)