chore(conductor): Add new track 'DeepSeek API Support'

conductor/tracks.md

@@ -35,4 +35,14 @@ This file tracks all major tracks for the project. Each track has its own detail
 
 ---
 
+- [ ] **Track: Make sure gemini cli behavior and feature set have full parity with regular direct gemini api usage in ai_client.py and elsewhere**
+*Link: [./tracks/gemini_cli_parity_20260225/](./tracks/gemini_cli_parity_20260225/)*
+
+---
+
+- [ ] **Track: Add support for the deepseek api as a provider.**
+*Link: [./tracks/deepseek_support_20260225/](./tracks/deepseek_support_20260225/)*
+
+---
+
 

conductor/tracks/deepseek_support_20260225/index.md

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+# Track deepseek_support_20260225 Context
+
+- [Specification](./spec.md)
+- [Implementation Plan](./plan.md)
+- [Metadata](./metadata.json)

conductor/tracks/deepseek_support_20260225/metadata.json

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+{
+  "track_id": "deepseek_support_20260225",
+  "type": "feature",
+  "status": "new",
+  "created_at": "2026-02-25T00:00:00Z",
+  "updated_at": "2026-02-25T00:00:00Z",
+  "description": "Add support for the deepseek api as a provider."
+}

conductor/tracks/deepseek_support_20260225/plan.md

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+# Implementation Plan: DeepSeek API Provider Support
+
+## Phase 1: Infrastructure & Common Logic
+- [ ] Task: Initialize MMA Environment `activate_skill mma-orchestrator`
+- [ ] Task: Update `credentials.toml` schema and configuration logic in `project_manager.py` to support `deepseek`
+- [ ] Task: Define the `DeepSeekProvider` interface in `ai_client.py` and align with existing provider patterns
+- [ ] Task: Conductor - User Manual Verification 'Infrastructure & Common Logic' (Protocol in workflow.md)
+
+## Phase 2: DeepSeek API Client Implementation
+- [ ] Task: Write failing tests for `DeepSeekProvider` model selection and basic completion
+- [ ] Task: Implement `DeepSeekProvider` using the dedicated SDK
+- [ ] Task: Write failing tests for streaming and tool calling parity in `DeepSeekProvider`
+- [ ] Task: Implement streaming and tool calling logic for DeepSeek models
+- [ ] Task: Conductor - User Manual Verification 'DeepSeek API Client Implementation' (Protocol in workflow.md)
+
+## Phase 3: Reasoning Traces & Advanced Capabilities
+- [ ] Task: Write failing tests for reasoning trace capture in `DeepSeekProvider` (DeepSeek-R1)
+- [ ] Task: Implement reasoning trace processing and integration with discussion history
+- [ ] Task: Write failing tests for token estimation and cost tracking for DeepSeek models
+- [ ] Task: Implement token usage tracking according to DeepSeek pricing
+- [ ] Task: Conductor - User Manual Verification 'Reasoning Traces & Advanced Capabilities' (Protocol in workflow.md)
+
+## Phase 4: GUI Integration & Final Verification
+- [ ] Task: Update `gui_2.py` and `theme_2.py` (if necessary) to include DeepSeek in the provider selection UI
+- [ ] Task: Implement automated regression tests for the full DeepSeek lifecycle (prompt, streaming, tool call, reasoning)
+- [ ] Task: Verify overall performance and UI responsiveness with the new provider
+- [ ] Task: Conductor - User Manual Verification 'GUI Integration & Final Verification' (Protocol in workflow.md)

conductor/tracks/deepseek_support_20260225/spec.md

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+# Specification: DeepSeek API Provider Support
+
+## Overview
+Implement a new AI provider module to support the DeepSeek API within the Manual Slop application. This integration will leverage a dedicated SDK to provide access to high-performance models (DeepSeek-V3 and DeepSeek-R1) with support for streaming, tool calling, and detailed reasoning traces.
+
+## Functional Requirements
+- **Dedicated SDK Integration:** Utilize a DeepSeek-specific Python client for API interactions.
+- **Model Support:** Initial support for `deepseek-v3` (general performance) and `deepseek-r1` (reasoning).
+- **Core Features:**
+    - **Streaming:** Support real-time response generation for a better user experience.
+    - **Tool Calling:** Integrate with Manual Slop's existing tool/function execution framework.
+    - **Reasoning Traces:** Capture and display reasoning paths if provided by the model (e.g., DeepSeek-R1).
+- **Configuration Management:**
+    - Add `[deepseek]` section to `credentials.toml` for `api_key`.
+    - Update `config.toml` to allow selecting DeepSeek as the active provider.
+
+## Non-Functional Requirements
+- **Parity:** Maintain consistency with existing Gemini and Anthropic provider implementations in `ai_client.py`.
+- **Error Handling:** Robust handling of API rate limits and connection issues specific to DeepSeek.
+- **Observability:** Track token usage and costs according to DeepSeek's pricing model.
+
+## Acceptance Criteria
+- [ ] User can select "DeepSeek" as a provider in the GUI.
+- [ ] Successful completion of prompts using both DeepSeek-V3 and DeepSeek-R1 models.
+- [ ] Tool calling works correctly for standard operations (e.g., `read_file`).
+- [ ] Reasoning traces from R1 are captured and visible in the discussion history.
+- [ ] Streaming responses function correctly without blocking the GUI.
+
+## Out of Scope
+- Support for OpenAI-compatible proxies for DeepSeek in this initial track.
+- Automated fine-tuning or custom model endpoints.

conductor/tracks/gemini_cli_parity_20260225/index.md

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+# Track gemini_cli_parity_20260225 Context
+
+- [Specification](./spec.md)
+- [Implementation Plan](./plan.md)
+- [Metadata](./metadata.json)

conductor/tracks/gemini_cli_parity_20260225/metadata.json

@@ -0,0 +1,8 @@
+{
+  "track_id": "gemini_cli_parity_20260225",
+  "type": "feature",
+  "status": "new",
+  "created_at": "2026-02-25T00:00:00Z",
+  "updated_at": "2026-02-25T00:00:00Z",
+  "description": "Make sure gemini cli behavior and feature set have full parity with regular direct gemini api usage in ai_client.py and elsewhere"
+}

conductor/tracks/gemini_cli_parity_20260225/plan.md

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+# Implementation Plan: Gemini CLI Parity
+
+## Phase 1: Infrastructure & Common Logic
+- [ ] Task: Initialize MMA Environment `activate_skill mma-orchestrator`
+- [ ] Task: Audit `gemini_cli_adapter.py` and `ai_client.py` for parity gaps
+- [ ] Task: Implement common logging utilities for CLI bridge observability
+- [ ] Task: Conductor - User Manual Verification 'Infrastructure & Common Logic' (Protocol in workflow.md)
+
+## Phase 2: Token Counting & Safety Settings
+- [ ] Task: Write failing tests for token estimation in `GeminiCLIAdapter`
+- [ ] Task: Implement token counting parity in `GeminiCLIAdapter`
+- [ ] Task: Write failing tests for safety setting application in `GeminiCLIAdapter`
+- [ ] Task: Implement safety filter application in `GeminiCLIAdapter`
+- [ ] Task: Conductor - User Manual Verification 'Token Counting & Safety Settings' (Protocol in workflow.md)
+
+## Phase 3: Tool Calling Parity & System Instructions
+- [ ] Task: Write failing tests for system instruction usage in `GeminiCLIAdapter`
+- [ ] Task: Implement system instruction propagation in `GeminiCLIAdapter`
+- [ ] Task: Write failing tests for tool call/response mapping in `cli_tool_bridge.py`
+- [ ] Task: Synchronize tool call handling between bridge and `ai_client.py`
+- [ ] Task: Conductor - User Manual Verification 'Tool Calling Parity & System Instructions' (Protocol in workflow.md)
+
+## Phase 4: Final Verification & Performance Diagnostics
+- [ ] Task: Implement automated parity regression tests comparing CLI vs Direct API outputs
+- [ ] Task: Verify bridge latency and error handling robustness
+- [ ] Task: Conductor - User Manual Verification 'Final Verification & Performance Diagnostics' (Protocol in workflow.md)

conductor/tracks/gemini_cli_parity_20260225/spec.md

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+# Specification: Gemini CLI Parity
+
+## Overview
+Achieve full functional and behavioral parity between the Gemini CLI integration (`gemini_cli_adapter.py`, `cli_tool_bridge.py`) and the direct Gemini API implementation (`ai_client.py`). This ensures that users leveraging the Gemini CLI as a headless backend provider experience the same level of capability, reliability, and observability as direct API users.
+
+## Functional Requirements
+- **Token Estimation Parity:** Implement accurate token counting for both input and output in the Gemini CLI adapter to match the precision of the direct API.
+- **Safety Settings Parity:** Enable full configuration and enforcement of Gemini safety filters when using the CLI provider.
+- **Tool Calling Parity:** Synchronize tool definition mapping, call handling, and response processing between the CLI bridge and the direct SDK.
+- **System Instructions Parity:** Ensure system prompts and instructions are consistently passed and handled across both providers.
+- **Bridge Robustness:** Enhance the `cli_tool_bridge.py` and adapter to improve latency, error handling (retries), and detailed subprocess observability.
+
+## Non-Functional Requirements
+- **Observability:** Detailed logging of CLI subprocess interactions for debugging.
+- **Performance:** Minimize the overhead introduced by the bridge mechanism.
+- **Maintainability:** Ensure that future changes to `ai_client.py` can be easily mirrored in the CLI adapter.
+
+## Acceptance Criteria
+- [ ] Token counts for identical prompts match within a 5% margin between CLI and Direct API.
+- [ ] Safety settings configured in the GUI are correctly applied to CLI sessions.
+- [ ] Tool calls from the CLI are successfully executed and returned via the bridge without loss of context.
+- [ ] System instructions are correctly utilized by the model when using the CLI.
+- [ ] Automated tests verify that responses and tool execution flows are identical for both providers.
+
+## Out of Scope
+- Performance optimizations for the `gemini` CLI binary itself.
+- Support for non-Gemini CLI providers in this track.