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# Directory Structure
```
├── .devcontainer
│ ├── .vscode
│ │ └── settings.json
│ ├── devcontainer.json
│ ├── OPTIMIZING_FOR_CODESPACES.md
│ ├── POST_SETUP_README.md
│ └── README.md
├── .dockerignore
├── .gitattributes
├── .github
│ ├── policheck.yml
│ └── workflows
│ ├── assistants-codespace-assistant.yml
│ ├── assistants-document-assistant.yml
│ ├── assistants-explorer-assistant.yml
│ ├── assistants-guided-conversation-assistant.yml
│ ├── assistants-knowledge-transfer-assistant.yml
│ ├── assistants-navigator-assistant.yml
│ ├── assistants-project-assistant.yml
│ ├── assistants-prospector-assistant.yml
│ ├── assistants-skill-assistant.yml
│ ├── libraries.yml
│ ├── mcp-server-giphy.yml
│ ├── mcp-server-memory-filesystem-edit.yml
│ ├── mcp-server-memory-user-bio.yml
│ ├── mcp-server-memory-whiteboard.yml
│ ├── mcp-server-open-deep-research-clone.yml
│ ├── mcp-server-web-research.yml
│ ├── workbench-app.yml
│ └── workbench-service.yml
├── .gitignore
├── .multi-root-tools
│ ├── Makefile
│ └── README.md
├── .vscode
│ ├── extensions.json
│ ├── launch.json
│ └── settings.json
├── ai_context
│ └── generated
│ ├── ASPIRE_ORCHESTRATOR.md
│ ├── ASSISTANT_CODESPACE.md
│ ├── ASSISTANT_DOCUMENT.md
│ ├── ASSISTANT_NAVIGATOR.md
│ ├── ASSISTANT_PROJECT.md
│ ├── ASSISTANT_PROSPECTOR.md
│ ├── ASSISTANTS_OTHER.md
│ ├── ASSISTANTS_OVERVIEW.md
│ ├── CONFIGURATION.md
│ ├── DOTNET_LIBRARIES.md
│ ├── EXAMPLES.md
│ ├── MCP_SERVERS.md
│ ├── PYTHON_LIBRARIES_AI_CLIENTS.md
│ ├── PYTHON_LIBRARIES_CORE.md
│ ├── PYTHON_LIBRARIES_EXTENSIONS.md
│ ├── PYTHON_LIBRARIES_SKILLS.md
│ ├── PYTHON_LIBRARIES_SPECIALIZED.md
│ ├── TOOLS.md
│ ├── WORKBENCH_FRONTEND.md
│ └── WORKBENCH_SERVICE.md
├── aspire-orchestrator
│ ├── .editorconfig
│ ├── Aspire.AppHost
│ │ ├── .gitignore
│ │ ├── appsettings.json
│ │ ├── Aspire.AppHost.csproj
│ │ ├── Program.cs
│ │ └── Properties
│ │ └── launchSettings.json
│ ├── Aspire.Extensions
│ │ ├── Aspire.Extensions.csproj
│ │ ├── Dashboard.cs
│ │ ├── DockerFileExtensions.cs
│ │ ├── PathNormalizer.cs
│ │ ├── UvAppHostingExtensions.cs
│ │ ├── UvAppResource.cs
│ │ ├── VirtualEnvironment.cs
│ │ └── WorkbenchServiceHostingExtensions.cs
│ ├── Aspire.ServiceDefaults
│ │ ├── Aspire.ServiceDefaults.csproj
│ │ └── Extensions.cs
│ ├── README.md
│ ├── run.sh
│ ├── SemanticWorkbench.Aspire.sln
│ └── SemanticWorkbench.Aspire.sln.DotSettings
├── assistants
│ ├── codespace-assistant
│ │ ├── .claude
│ │ │ └── settings.local.json
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── extensions.json
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── assets
│ │ │ │ ├── icon_context_transfer.svg
│ │ │ │ └── icon.svg
│ │ │ ├── chat.py
│ │ │ ├── config.py
│ │ │ ├── helpers.py
│ │ │ ├── response
│ │ │ │ ├── __init__.py
│ │ │ │ ├── completion_handler.py
│ │ │ │ ├── models.py
│ │ │ │ ├── request_builder.py
│ │ │ │ ├── response.py
│ │ │ │ ├── step_handler.py
│ │ │ │ └── utils
│ │ │ │ ├── __init__.py
│ │ │ │ ├── abbreviations.py
│ │ │ │ ├── formatting_utils.py
│ │ │ │ ├── message_utils.py
│ │ │ │ └── openai_utils.py
│ │ │ ├── text_includes
│ │ │ │ ├── card_content_context_transfer.md
│ │ │ │ ├── card_content.md
│ │ │ │ ├── codespace_assistant_info.md
│ │ │ │ ├── context_transfer_assistant_info.md
│ │ │ │ ├── guardrails_prompt.txt
│ │ │ │ ├── guidance_prompt_context_transfer.txt
│ │ │ │ ├── guidance_prompt.txt
│ │ │ │ ├── instruction_prompt_context_transfer.txt
│ │ │ │ └── instruction_prompt.txt
│ │ │ └── whiteboard
│ │ │ ├── __init__.py
│ │ │ ├── _inspector.py
│ │ │ └── _whiteboard.py
│ │ ├── assistant.code-workspace
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── document-assistant
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── assets
│ │ │ │ └── icon.svg
│ │ │ ├── chat.py
│ │ │ ├── config.py
│ │ │ ├── context_management
│ │ │ │ ├── __init__.py
│ │ │ │ └── inspector.py
│ │ │ ├── filesystem
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _convert.py
│ │ │ │ ├── _file_sources.py
│ │ │ │ ├── _filesystem.py
│ │ │ │ ├── _inspector.py
│ │ │ │ ├── _model.py
│ │ │ │ ├── _prompts.py
│ │ │ │ └── _tasks.py
│ │ │ ├── guidance
│ │ │ │ ├── __init__.py
│ │ │ │ ├── dynamic_ui_inspector.py
│ │ │ │ ├── guidance_config.py
│ │ │ │ ├── guidance_prompts.py
│ │ │ │ └── README.md
│ │ │ ├── response
│ │ │ │ ├── __init__.py
│ │ │ │ ├── completion_handler.py
│ │ │ │ ├── models.py
│ │ │ │ ├── prompts.py
│ │ │ │ ├── responder.py
│ │ │ │ └── utils
│ │ │ │ ├── __init__.py
│ │ │ │ ├── formatting_utils.py
│ │ │ │ ├── message_utils.py
│ │ │ │ ├── openai_utils.py
│ │ │ │ ├── tokens_tiktoken.py
│ │ │ │ └── workbench_messages.py
│ │ │ ├── text_includes
│ │ │ │ └── document_assistant_info.md
│ │ │ ├── types.py
│ │ │ └── whiteboard
│ │ │ ├── __init__.py
│ │ │ ├── _inspector.py
│ │ │ └── _whiteboard.py
│ │ ├── assistant.code-workspace
│ │ ├── CLAUDE.md
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ ├── __init__.py
│ │ │ ├── test_convert.py
│ │ │ └── test_data
│ │ │ ├── blank_image.png
│ │ │ ├── Formatting Test.docx
│ │ │ ├── sample_data.csv
│ │ │ ├── sample_data.xlsx
│ │ │ ├── sample_page.html
│ │ │ ├── sample_presentation.pptx
│ │ │ └── simple_pdf.pdf
│ │ └── uv.lock
│ ├── explorer-assistant
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── chat.py
│ │ │ ├── config.py
│ │ │ ├── helpers.py
│ │ │ ├── response
│ │ │ │ ├── __init__.py
│ │ │ │ ├── model.py
│ │ │ │ ├── response_anthropic.py
│ │ │ │ ├── response_openai.py
│ │ │ │ └── response.py
│ │ │ └── text_includes
│ │ │ └── guardrails_prompt.txt
│ │ ├── assistant.code-workspace
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── guided-conversation-assistant
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── agents
│ │ │ │ ├── guided_conversation
│ │ │ │ │ ├── config.py
│ │ │ │ │ ├── definition.py
│ │ │ │ │ └── definitions
│ │ │ │ │ ├── er_triage.py
│ │ │ │ │ ├── interview.py
│ │ │ │ │ ├── patient_intake.py
│ │ │ │ │ └── poem_feedback.py
│ │ │ │ └── guided_conversation_agent.py
│ │ │ ├── chat.py
│ │ │ ├── config.py
│ │ │ └── text_includes
│ │ │ └── guardrails_prompt.txt
│ │ ├── assistant.code-workspace
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── knowledge-transfer-assistant
│ │ ├── .claude
│ │ │ └── settings.local.json
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── agentic
│ │ │ │ ├── __init__.py
│ │ │ │ ├── analysis.py
│ │ │ │ ├── coordinator_support.py
│ │ │ │ └── team_welcome.py
│ │ │ ├── assets
│ │ │ │ ├── icon-knowledge-transfer.svg
│ │ │ │ └── icon.svg
│ │ │ ├── assistant.py
│ │ │ ├── common.py
│ │ │ ├── config.py
│ │ │ ├── conversation_clients.py
│ │ │ ├── conversation_share_link.py
│ │ │ ├── data.py
│ │ │ ├── domain
│ │ │ │ ├── __init__.py
│ │ │ │ ├── audience_manager.py
│ │ │ │ ├── information_request_manager.py
│ │ │ │ ├── knowledge_brief_manager.py
│ │ │ │ ├── knowledge_digest_manager.py
│ │ │ │ ├── learning_objectives_manager.py
│ │ │ │ └── share_manager.py
│ │ │ ├── files.py
│ │ │ ├── logging.py
│ │ │ ├── notifications.py
│ │ │ ├── respond.py
│ │ │ ├── storage_models.py
│ │ │ ├── storage.py
│ │ │ ├── string_utils.py
│ │ │ ├── text_includes
│ │ │ │ ├── assistant_info.md
│ │ │ │ ├── card_content.md
│ │ │ │ ├── coordinator_instructions.txt
│ │ │ │ ├── coordinator_role.txt
│ │ │ │ ├── knowledge_digest_instructions.txt
│ │ │ │ ├── knowledge_digest_prompt.txt
│ │ │ │ ├── share_information_request_detection.txt
│ │ │ │ ├── team_instructions.txt
│ │ │ │ ├── team_role.txt
│ │ │ │ └── welcome_message_generation.txt
│ │ │ ├── tools
│ │ │ │ ├── __init__.py
│ │ │ │ ├── base.py
│ │ │ │ ├── information_requests.py
│ │ │ │ ├── learning_objectives.py
│ │ │ │ ├── learning_outcomes.py
│ │ │ │ ├── progress_tracking.py
│ │ │ │ └── share_setup.py
│ │ │ ├── ui_tabs
│ │ │ │ ├── __init__.py
│ │ │ │ ├── brief.py
│ │ │ │ ├── common.py
│ │ │ │ ├── debug.py
│ │ │ │ ├── learning.py
│ │ │ │ └── sharing.py
│ │ │ └── utils.py
│ │ ├── CLAUDE.md
│ │ ├── docs
│ │ │ ├── design
│ │ │ │ ├── actions.md
│ │ │ │ └── inference.md
│ │ │ ├── DEV_GUIDE.md
│ │ │ ├── how-kta-works.md
│ │ │ ├── JTBD.md
│ │ │ ├── knowledge-transfer-goals.md
│ │ │ ├── learning_assistance.md
│ │ │ ├── notable_claude_conversations
│ │ │ │ ├── clarifying_quad_modal_design.md
│ │ │ │ ├── CLAUDE_PROMPTS.md
│ │ │ │ ├── transfer_state.md
│ │ │ │ └── trying_the_context_agent.md
│ │ │ └── opportunities-of-knowledge-transfer.md
│ │ ├── knowledge-transfer-assistant.code-workspace
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ ├── __init__.py
│ │ │ ├── test_artifact_loading.py
│ │ │ ├── test_inspector.py
│ │ │ ├── test_share_manager.py
│ │ │ ├── test_share_storage.py
│ │ │ ├── test_share_tools.py
│ │ │ └── test_team_mode.py
│ │ └── uv.lock
│ ├── Makefile
│ ├── navigator-assistant
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── assets
│ │ │ │ ├── card_content.md
│ │ │ │ └── icon.svg
│ │ │ ├── chat.py
│ │ │ ├── config.py
│ │ │ ├── helpers.py
│ │ │ ├── response
│ │ │ │ ├── __init__.py
│ │ │ │ ├── completion_handler.py
│ │ │ │ ├── completion_requestor.py
│ │ │ │ ├── local_tool
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── add_assistant_to_conversation.py
│ │ │ │ │ ├── list_assistant_services.py
│ │ │ │ │ └── model.py
│ │ │ │ ├── models.py
│ │ │ │ ├── prompt.py
│ │ │ │ ├── request_builder.py
│ │ │ │ ├── response.py
│ │ │ │ ├── step_handler.py
│ │ │ │ └── utils
│ │ │ │ ├── __init__.py
│ │ │ │ ├── formatting_utils.py
│ │ │ │ ├── message_utils.py
│ │ │ │ ├── openai_utils.py
│ │ │ │ └── tools.py
│ │ │ ├── text_includes
│ │ │ │ ├── guardrails_prompt.md
│ │ │ │ ├── guidance_prompt.md
│ │ │ │ ├── instruction_prompt.md
│ │ │ │ ├── navigator_assistant_info.md
│ │ │ │ └── semantic_workbench_features.md
│ │ │ └── whiteboard
│ │ │ ├── __init__.py
│ │ │ ├── _inspector.py
│ │ │ └── _whiteboard.py
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── project-assistant
│ │ ├── .cspell
│ │ │ └── custom-dictionary-workspace.txt
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── agentic
│ │ │ │ ├── __init__.py
│ │ │ │ ├── act.py
│ │ │ │ ├── coordinator_next_action.py
│ │ │ │ ├── create_invitation.py
│ │ │ │ ├── detect_audience_and_takeaways.py
│ │ │ │ ├── detect_coordinator_actions.py
│ │ │ │ ├── detect_information_request_needs.py
│ │ │ │ ├── detect_knowledge_package_gaps.py
│ │ │ │ ├── focus.py
│ │ │ │ ├── respond.py
│ │ │ │ ├── team_welcome.py
│ │ │ │ └── update_digest.py
│ │ │ ├── assets
│ │ │ │ ├── icon-knowledge-transfer.svg
│ │ │ │ └── icon.svg
│ │ │ ├── assistant.py
│ │ │ ├── common.py
│ │ │ ├── config.py
│ │ │ ├── conversation_clients.py
│ │ │ ├── data.py
│ │ │ ├── domain
│ │ │ │ ├── __init__.py
│ │ │ │ ├── audience_manager.py
│ │ │ │ ├── conversation_preferences_manager.py
│ │ │ │ ├── information_request_manager.py
│ │ │ │ ├── knowledge_brief_manager.py
│ │ │ │ ├── knowledge_digest_manager.py
│ │ │ │ ├── learning_objectives_manager.py
│ │ │ │ ├── share_manager.py
│ │ │ │ ├── tasks_manager.py
│ │ │ │ └── transfer_manager.py
│ │ │ ├── errors.py
│ │ │ ├── files.py
│ │ │ ├── logging.py
│ │ │ ├── notifications.py
│ │ │ ├── prompt_utils.py
│ │ │ ├── storage.py
│ │ │ ├── string_utils.py
│ │ │ ├── text_includes
│ │ │ │ ├── actor_instructions.md
│ │ │ │ ├── assistant_info.md
│ │ │ │ ├── card_content.md
│ │ │ │ ├── coordinator_instructions copy.md
│ │ │ │ ├── coordinator_instructions.md
│ │ │ │ ├── create_invitation.md
│ │ │ │ ├── detect_audience.md
│ │ │ │ ├── detect_coordinator_actions.md
│ │ │ │ ├── detect_information_request_needs.md
│ │ │ │ ├── detect_knowledge_package_gaps.md
│ │ │ │ ├── focus.md
│ │ │ │ ├── knowledge_digest_instructions.txt
│ │ │ │ ├── team_instructions.txt
│ │ │ │ ├── to_do.md
│ │ │ │ ├── update_knowledge_brief.md
│ │ │ │ ├── update_knowledge_digest.md
│ │ │ │ └── welcome_message_generation.txt
│ │ │ ├── tools
│ │ │ │ ├── __init__.py
│ │ │ │ ├── base.py
│ │ │ │ ├── conversation_preferences.py
│ │ │ │ ├── information_requests.py
│ │ │ │ ├── learning_objectives.py
│ │ │ │ ├── learning_outcomes.py
│ │ │ │ ├── progress_tracking.py
│ │ │ │ ├── share_setup.py
│ │ │ │ ├── system_reminders.py
│ │ │ │ ├── tasks.py
│ │ │ │ └── todo.py
│ │ │ ├── ui_tabs
│ │ │ │ ├── __init__.py
│ │ │ │ ├── brief.py
│ │ │ │ ├── common.py
│ │ │ │ ├── debug.py
│ │ │ │ ├── learning.py
│ │ │ │ └── sharing.py
│ │ │ └── utils.py
│ │ ├── CLAUDE.md
│ │ ├── docs
│ │ │ ├── design
│ │ │ │ ├── actions.md
│ │ │ │ ├── control_options.md
│ │ │ │ ├── design.md
│ │ │ │ ├── inference.md
│ │ │ │ └── PXL_20250814_190140267.jpg
│ │ │ ├── DEV_GUIDE.md
│ │ │ ├── how-kta-works.md
│ │ │ ├── JTBD.md
│ │ │ ├── knowledge-transfer-goals.md
│ │ │ ├── learning_assistance.md
│ │ │ ├── notable_claude_conversations
│ │ │ │ ├── clarifying_quad_modal_design.md
│ │ │ │ ├── CLAUDE_PROMPTS.md
│ │ │ │ ├── transfer_state.md
│ │ │ │ └── trying_the_context_agent.md
│ │ │ └── opportunities-of-knowledge-transfer.md
│ │ ├── knowledge-transfer-assistant.code-workspace
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ ├── __init__.py
│ │ │ ├── test_artifact_loading.py
│ │ │ ├── test_inspector.py
│ │ │ ├── test_share_manager.py
│ │ │ ├── test_share_storage.py
│ │ │ └── test_team_mode.py
│ │ └── uv.lock
│ ├── prospector-assistant
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── agents
│ │ │ │ ├── artifact_agent.py
│ │ │ │ ├── document
│ │ │ │ │ ├── config.py
│ │ │ │ │ ├── gc_draft_content_feedback_config.py
│ │ │ │ │ ├── gc_draft_outline_feedback_config.py
│ │ │ │ │ ├── guided_conversation.py
│ │ │ │ │ └── state.py
│ │ │ │ └── document_agent.py
│ │ │ ├── artifact_creation_extension
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _llm.py
│ │ │ │ ├── config.py
│ │ │ │ ├── document.py
│ │ │ │ ├── extension.py
│ │ │ │ ├── store.py
│ │ │ │ ├── test
│ │ │ │ │ ├── conftest.py
│ │ │ │ │ ├── evaluation.py
│ │ │ │ │ ├── test_completion_with_tools.py
│ │ │ │ │ └── test_extension.py
│ │ │ │ └── tools.py
│ │ │ ├── chat.py
│ │ │ ├── config.py
│ │ │ ├── form_fill_extension
│ │ │ │ ├── __init__.py
│ │ │ │ ├── config.py
│ │ │ │ ├── extension.py
│ │ │ │ ├── inspector.py
│ │ │ │ ├── state.py
│ │ │ │ └── steps
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _guided_conversation.py
│ │ │ │ ├── _llm.py
│ │ │ │ ├── acquire_form_step.py
│ │ │ │ ├── extract_form_fields_step.py
│ │ │ │ ├── fill_form_step.py
│ │ │ │ └── types.py
│ │ │ ├── helpers.py
│ │ │ ├── legacy.py
│ │ │ └── text_includes
│ │ │ ├── artifact_agent_enabled.md
│ │ │ ├── guardrails_prompt.txt
│ │ │ ├── guided_conversation_agent_enabled.md
│ │ │ └── skills_agent_enabled.md
│ │ ├── assistant.code-workspace
│ │ ├── gc_learnings
│ │ │ ├── gc_learnings.md
│ │ │ └── images
│ │ │ ├── gc_conversation_plan_fcn.png
│ │ │ ├── gc_conversation_plan_template.png
│ │ │ ├── gc_execute_plan_callstack.png
│ │ │ ├── gc_functions.png
│ │ │ ├── gc_generate_plan_callstack.png
│ │ │ ├── gc_get_resource_instructions.png
│ │ │ ├── gc_get_termination_instructions.png
│ │ │ ├── gc_kernel_arguments.png
│ │ │ ├── gc_plan_calls.png
│ │ │ ├── gc_termination_instructions.png
│ │ │ ├── sk_get_chat_message_contents.png
│ │ │ ├── sk_inner_get_chat_message_contents.png
│ │ │ ├── sk_send_request_prep.png
│ │ │ └── sk_send_request.png
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ └── skill-assistant
│ ├── .env.example
│ ├── .vscode
│ │ ├── launch.json
│ │ └── settings.json
│ ├── assistant
│ │ ├── __init__.py
│ │ ├── config.py
│ │ ├── logging.py
│ │ ├── skill_assistant.py
│ │ ├── skill_engine_registry.py
│ │ ├── skill_event_mapper.py
│ │ ├── text_includes
│ │ │ └── guardrails_prompt.txt
│ │ └── workbench_helpers.py
│ ├── assistant.code-workspace
│ ├── Makefile
│ ├── pyproject.toml
│ ├── README.md
│ ├── tests
│ │ └── test_setup.py
│ └── uv.lock
├── CLAUDE.md
├── CODE_OF_CONDUCT.md
├── CONTRIBUTING.md
├── docs
│ ├── .vscode
│ │ └── settings.json
│ ├── ASSISTANT_CONFIG.md
│ ├── ASSISTANT_DEVELOPMENT_GUIDE.md
│ ├── CUSTOM_APP_REGISTRATION.md
│ ├── HOSTED_ASSISTANT_WITH_LOCAL_MCP_SERVERS.md
│ ├── images
│ │ ├── architecture-animation.gif
│ │ ├── configure_assistant.png
│ │ ├── conversation_canvas_open.png
│ │ ├── conversation_duplicate.png
│ │ ├── conversation_export.png
│ │ ├── conversation_share_dialog.png
│ │ ├── conversation_share_link.png
│ │ ├── dashboard_configured_view.png
│ │ ├── dashboard_view.png
│ │ ├── license_agreement.png
│ │ ├── message_bar.png
│ │ ├── message_inspection.png
│ │ ├── message_link.png
│ │ ├── new_prospector_assistant_dialog.png
│ │ ├── open_conversation_canvas.png
│ │ ├── prospector_example.png
│ │ ├── readme1.png
│ │ ├── readme2.png
│ │ ├── readme3.png
│ │ ├── rewind.png
│ │ ├── signin_page.png
│ │ └── splash_screen.png
│ ├── LOCAL_ASSISTANT_WITH_REMOTE_WORKBENCH.md
│ ├── SETUP_DEV_ENVIRONMENT.md
│ └── WORKBENCH_APP.md
├── examples
│ ├── dotnet
│ │ ├── .editorconfig
│ │ ├── dotnet-01-echo-bot
│ │ │ ├── appsettings.json
│ │ │ ├── dotnet-01-echo-bot.csproj
│ │ │ ├── MyAgent.cs
│ │ │ ├── MyAgentConfig.cs
│ │ │ ├── MyWorkbenchConnector.cs
│ │ │ ├── Program.cs
│ │ │ └── README.md
│ │ ├── dotnet-02-message-types-demo
│ │ │ ├── appsettings.json
│ │ │ ├── ConnectorExtensions.cs
│ │ │ ├── docs
│ │ │ │ ├── abc.png
│ │ │ │ ├── code.png
│ │ │ │ ├── config.png
│ │ │ │ ├── echo.png
│ │ │ │ ├── markdown.png
│ │ │ │ ├── mermaid.png
│ │ │ │ ├── reverse.png
│ │ │ │ └── safety-check.png
│ │ │ ├── dotnet-02-message-types-demo.csproj
│ │ │ ├── MyAgent.cs
│ │ │ ├── MyAgentConfig.cs
│ │ │ ├── MyWorkbenchConnector.cs
│ │ │ ├── Program.cs
│ │ │ └── README.md
│ │ └── dotnet-03-simple-chatbot
│ │ ├── appsettings.json
│ │ ├── ConnectorExtensions.cs
│ │ ├── dotnet-03-simple-chatbot.csproj
│ │ ├── MyAgent.cs
│ │ ├── MyAgentConfig.cs
│ │ ├── MyWorkbenchConnector.cs
│ │ ├── Program.cs
│ │ └── README.md
│ ├── Makefile
│ └── python
│ ├── python-01-echo-bot
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── chat.py
│ │ │ └── config.py
│ │ ├── assistant.code-workspace
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── python-02-simple-chatbot
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant
│ │ │ ├── __init__.py
│ │ │ ├── chat.py
│ │ │ ├── config.py
│ │ │ └── text_includes
│ │ │ └── guardrails_prompt.txt
│ │ ├── assistant.code-workspace
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ └── python-03-multimodel-chatbot
│ ├── .env.example
│ ├── .vscode
│ │ ├── launch.json
│ │ └── settings.json
│ ├── assistant
│ │ ├── __init__.py
│ │ ├── chat.py
│ │ ├── config.py
│ │ ├── model_adapters.py
│ │ └── text_includes
│ │ └── guardrails_prompt.txt
│ ├── assistant.code-workspace
│ ├── Makefile
│ ├── pyproject.toml
│ ├── README.md
│ └── uv.lock
├── KNOWN_ISSUES.md
├── libraries
│ ├── dotnet
│ │ ├── .editorconfig
│ │ ├── pack.sh
│ │ ├── README.md
│ │ ├── SemanticWorkbench.sln
│ │ ├── SemanticWorkbench.sln.DotSettings
│ │ └── WorkbenchConnector
│ │ ├── AgentBase.cs
│ │ ├── AgentConfig
│ │ │ ├── AgentConfigBase.cs
│ │ │ ├── AgentConfigPropertyAttribute.cs
│ │ │ └── ConfigUtils.cs
│ │ ├── Constants.cs
│ │ ├── IAgentBase.cs
│ │ ├── icon.png
│ │ ├── Models
│ │ │ ├── Command.cs
│ │ │ ├── Conversation.cs
│ │ │ ├── ConversationEvent.cs
│ │ │ ├── DebugInfo.cs
│ │ │ ├── Insight.cs
│ │ │ ├── Message.cs
│ │ │ ├── MessageMetadata.cs
│ │ │ ├── Participant.cs
│ │ │ ├── Sender.cs
│ │ │ └── ServiceInfo.cs
│ │ ├── Storage
│ │ │ ├── AgentInfo.cs
│ │ │ ├── AgentServiceStorage.cs
│ │ │ └── IAgentServiceStorage.cs
│ │ ├── StringLoggingExtensions.cs
│ │ ├── Webservice.cs
│ │ ├── WorkbenchConfig.cs
│ │ ├── WorkbenchConnector.cs
│ │ └── WorkbenchConnector.csproj
│ ├── Makefile
│ └── python
│ ├── anthropic-client
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── anthropic_client
│ │ │ ├── __init__.py
│ │ │ ├── client.py
│ │ │ ├── config.py
│ │ │ └── messages.py
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── assistant-data-gen
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── assistant_data_gen
│ │ │ ├── __init__.py
│ │ │ ├── assistant_api.py
│ │ │ ├── config.py
│ │ │ ├── gce
│ │ │ │ ├── __init__.py
│ │ │ │ ├── gce_agent.py
│ │ │ │ └── prompts.py
│ │ │ └── pydantic_ai_utils.py
│ │ ├── configs
│ │ │ └── document_assistant_example_config.yaml
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── scripts
│ │ │ ├── gce_simulation.py
│ │ │ └── generate_scenario.py
│ │ └── uv.lock
│ ├── assistant-drive
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── extensions.json
│ │ │ └── settings.json
│ │ ├── assistant_drive
│ │ │ ├── __init__.py
│ │ │ ├── drive.py
│ │ │ └── tests
│ │ │ └── test_basic.py
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── pytest.ini
│ │ ├── README.md
│ │ ├── usage.ipynb
│ │ └── uv.lock
│ ├── assistant-extensions
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── assistant_extensions
│ │ │ ├── __init__.py
│ │ │ ├── ai_clients
│ │ │ │ └── config.py
│ │ │ ├── artifacts
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _artifacts.py
│ │ │ │ ├── _inspector.py
│ │ │ │ └── _model.py
│ │ │ ├── attachments
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _attachments.py
│ │ │ │ ├── _convert.py
│ │ │ │ ├── _model.py
│ │ │ │ ├── _shared.py
│ │ │ │ └── _summarizer.py
│ │ │ ├── chat_context_toolkit
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _config.py
│ │ │ │ ├── archive
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── _archive.py
│ │ │ │ │ └── _summarizer.py
│ │ │ │ ├── message_history
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── _history.py
│ │ │ │ │ └── _message.py
│ │ │ │ └── virtual_filesystem
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _archive_file_source.py
│ │ │ │ └── _attachments_file_source.py
│ │ │ ├── dashboard_card
│ │ │ │ ├── __init__.py
│ │ │ │ └── _dashboard_card.py
│ │ │ ├── document_editor
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _extension.py
│ │ │ │ ├── _inspector.py
│ │ │ │ └── _model.py
│ │ │ ├── mcp
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _assistant_file_resource_handler.py
│ │ │ │ ├── _client_utils.py
│ │ │ │ ├── _devtunnel.py
│ │ │ │ ├── _model.py
│ │ │ │ ├── _openai_utils.py
│ │ │ │ ├── _sampling_handler.py
│ │ │ │ ├── _tool_utils.py
│ │ │ │ └── _workbench_file_resource_handler.py
│ │ │ ├── navigator
│ │ │ │ ├── __init__.py
│ │ │ │ └── _navigator.py
│ │ │ └── workflows
│ │ │ ├── __init__.py
│ │ │ ├── _model.py
│ │ │ ├── _workflows.py
│ │ │ └── runners
│ │ │ └── _user_proxy.py
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── test
│ │ │ └── attachments
│ │ │ └── test_attachments.py
│ │ └── uv.lock
│ ├── chat-context-toolkit
│ │ ├── .claude
│ │ │ └── settings.local.json
│ │ ├── .env.sample
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── assets
│ │ │ ├── archive_v1.png
│ │ │ ├── history_v1.png
│ │ │ └── vfs_v1.png
│ │ ├── chat_context_toolkit
│ │ │ ├── __init__.py
│ │ │ ├── archive
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _archive_reader.py
│ │ │ │ ├── _archive_task_queue.py
│ │ │ │ ├── _state.py
│ │ │ │ ├── _types.py
│ │ │ │ └── summarization
│ │ │ │ ├── __init__.py
│ │ │ │ └── _summarizer.py
│ │ │ ├── history
│ │ │ │ ├── __init__.py
│ │ │ │ ├── _budget.py
│ │ │ │ ├── _decorators.py
│ │ │ │ ├── _history.py
│ │ │ │ ├── _prioritize.py
│ │ │ │ ├── _types.py
│ │ │ │ └── tool_abbreviations
│ │ │ │ ├── __init__.py
│ │ │ │ └── _tool_abbreviations.py
│ │ │ └── virtual_filesystem
│ │ │ ├── __init__.py
│ │ │ ├── _types.py
│ │ │ ├── _virtual_filesystem.py
│ │ │ ├── README.md
│ │ │ └── tools
│ │ │ ├── __init__.py
│ │ │ ├── _ls_tool.py
│ │ │ ├── _tools.py
│ │ │ └── _view_tool.py
│ │ ├── CLAUDE.md
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── test
│ │ │ ├── archive
│ │ │ │ └── test_archive_reader.py
│ │ │ ├── history
│ │ │ │ ├── test_abbreviate_messages.py
│ │ │ │ ├── test_history.py
│ │ │ │ ├── test_pair_and_order_tool_messages.py
│ │ │ │ ├── test_prioritize.py
│ │ │ │ └── test_truncate_messages.py
│ │ │ └── virtual_filesystem
│ │ │ ├── test_virtual_filesystem.py
│ │ │ └── tools
│ │ │ ├── test_ls_tool.py
│ │ │ ├── test_tools.py
│ │ │ └── test_view_tool.py
│ │ └── uv.lock
│ ├── content-safety
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── content_safety
│ │ │ ├── __init__.py
│ │ │ ├── evaluators
│ │ │ │ ├── __init__.py
│ │ │ │ ├── azure_content_safety
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── config.py
│ │ │ │ │ └── evaluator.py
│ │ │ │ ├── config.py
│ │ │ │ ├── evaluator.py
│ │ │ │ └── openai_moderations
│ │ │ │ ├── __init__.py
│ │ │ │ ├── config.py
│ │ │ │ └── evaluator.py
│ │ │ └── README.md
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── events
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── events
│ │ │ ├── __init__.py
│ │ │ └── events.py
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── guided-conversation
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── guided_conversation
│ │ │ ├── __init__.py
│ │ │ ├── functions
│ │ │ │ ├── __init__.py
│ │ │ │ ├── conversation_plan.py
│ │ │ │ ├── execution.py
│ │ │ │ └── final_update_plan.py
│ │ │ ├── guided_conversation_agent.py
│ │ │ ├── plugins
│ │ │ │ ├── __init__.py
│ │ │ │ ├── agenda.py
│ │ │ │ └── artifact.py
│ │ │ └── utils
│ │ │ ├── __init__.py
│ │ │ ├── base_model_llm.py
│ │ │ ├── conversation_helpers.py
│ │ │ ├── openai_tool_calling.py
│ │ │ ├── plugin_helpers.py
│ │ │ └── resources.py
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── llm-client
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── llm_client
│ │ │ ├── __init__.py
│ │ │ └── model.py
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── Makefile
│ ├── mcp-extensions
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_extensions
│ │ │ ├── __init__.py
│ │ │ ├── _client_session.py
│ │ │ ├── _model.py
│ │ │ ├── _sampling.py
│ │ │ ├── _server_extensions.py
│ │ │ ├── _tool_utils.py
│ │ │ ├── llm
│ │ │ │ ├── __init__.py
│ │ │ │ ├── chat_completion.py
│ │ │ │ ├── helpers.py
│ │ │ │ ├── llm_types.py
│ │ │ │ ├── mcp_chat_completion.py
│ │ │ │ └── openai_chat_completion.py
│ │ │ └── server
│ │ │ ├── __init__.py
│ │ │ └── storage.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ └── test_tool_utils.py
│ │ └── uv.lock
│ ├── mcp-tunnel
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_tunnel
│ │ │ ├── __init__.py
│ │ │ ├── _devtunnel.py
│ │ │ ├── _dir.py
│ │ │ └── _main.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── openai-client
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── openai_client
│ │ │ ├── __init__.py
│ │ │ ├── chat_driver
│ │ │ │ ├── __init__.py
│ │ │ │ ├── chat_driver.ipynb
│ │ │ │ ├── chat_driver.py
│ │ │ │ ├── message_history_providers
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── in_memory_message_history_provider.py
│ │ │ │ │ ├── local_message_history_provider.py
│ │ │ │ │ ├── message_history_provider.py
│ │ │ │ │ └── tests
│ │ │ │ │ └── formatted_instructions_test.py
│ │ │ │ └── README.md
│ │ │ ├── client.py
│ │ │ ├── completion.py
│ │ │ ├── config.py
│ │ │ ├── errors.py
│ │ │ ├── logging.py
│ │ │ ├── messages.py
│ │ │ ├── tokens.py
│ │ │ └── tools.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ ├── test_command_parsing.py
│ │ │ ├── test_formatted_messages.py
│ │ │ ├── test_messages.py
│ │ │ └── test_tokens.py
│ │ └── uv.lock
│ ├── semantic-workbench-api-model
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── semantic_workbench_api_model
│ │ │ ├── __init__.py
│ │ │ ├── assistant_model.py
│ │ │ ├── assistant_service_client.py
│ │ │ ├── workbench_model.py
│ │ │ └── workbench_service_client.py
│ │ └── uv.lock
│ ├── semantic-workbench-assistant
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── semantic_workbench_assistant
│ │ │ ├── __init__.py
│ │ │ ├── assistant_app
│ │ │ │ ├── __init__.py
│ │ │ │ ├── assistant.py
│ │ │ │ ├── config.py
│ │ │ │ ├── content_safety.py
│ │ │ │ ├── context.py
│ │ │ │ ├── error.py
│ │ │ │ ├── export_import.py
│ │ │ │ ├── protocol.py
│ │ │ │ └── service.py
│ │ │ ├── assistant_service.py
│ │ │ ├── auth.py
│ │ │ ├── canonical.py
│ │ │ ├── command.py
│ │ │ ├── config.py
│ │ │ ├── logging_config.py
│ │ │ ├── settings.py
│ │ │ ├── start.py
│ │ │ └── storage.py
│ │ ├── tests
│ │ │ ├── conftest.py
│ │ │ ├── test_assistant_app.py
│ │ │ ├── test_canonical.py
│ │ │ ├── test_config.py
│ │ │ └── test_storage.py
│ │ └── uv.lock
│ └── skills
│ ├── .vscode
│ │ └── settings.json
│ ├── Makefile
│ ├── README.md
│ └── skill-library
│ ├── .vscode
│ │ └── settings.json
│ ├── docs
│ │ └── vs-recipe-tool.md
│ ├── Makefile
│ ├── pyproject.toml
│ ├── README.md
│ ├── skill_library
│ │ ├── __init__.py
│ │ ├── chat_driver_helpers.py
│ │ ├── cli
│ │ │ ├── azure_openai.py
│ │ │ ├── conversation_history.py
│ │ │ ├── README.md
│ │ │ ├── run_routine.py
│ │ │ ├── settings.py
│ │ │ └── skill_logger.py
│ │ ├── engine.py
│ │ ├── llm_info.txt
│ │ ├── logging.py
│ │ ├── README.md
│ │ ├── routine_stack.py
│ │ ├── skill.py
│ │ ├── skills
│ │ │ ├── common
│ │ │ │ ├── __init__.py
│ │ │ │ ├── common_skill.py
│ │ │ │ └── routines
│ │ │ │ ├── bing_search.py
│ │ │ │ ├── consolidate.py
│ │ │ │ ├── echo.py
│ │ │ │ ├── gather_context.py
│ │ │ │ ├── get_content_from_url.py
│ │ │ │ ├── gpt_complete.py
│ │ │ │ ├── select_user_intent.py
│ │ │ │ └── summarize.py
│ │ │ ├── eval
│ │ │ │ ├── __init__.py
│ │ │ │ ├── eval_skill.py
│ │ │ │ └── routines
│ │ │ │ └── eval.py
│ │ │ ├── fabric
│ │ │ │ ├── __init__.py
│ │ │ │ ├── fabric_skill.py
│ │ │ │ ├── patterns
│ │ │ │ │ ├── agility_story
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── ai
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_answers
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_candidates
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_cfp_submission
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_claims
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_comments
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_debate
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_email_headers
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_incident
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_interviewer_techniques
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_logs
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_malware
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_military_strategy
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_mistakes
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_paper
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_patent
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_personality
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_presentation
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_product_feedback
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_proposition
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_prose
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_prose_json
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_prose_pinker
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_risk
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_sales_call
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_spiritual_text
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_tech_impact
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_threat_report
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── analyze_threat_report_cmds
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── analyze_threat_report_trends
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── answer_interview_question
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── ask_secure_by_design_questions
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── ask_uncle_duke
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── capture_thinkers_work
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── check_agreement
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── clean_text
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── coding_master
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── compare_and_contrast
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── convert_to_markdown
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_5_sentence_summary
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_academic_paper
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_ai_jobs_analysis
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_aphorisms
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_art_prompt
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_better_frame
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_coding_project
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_command
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_cyber_summary
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_design_document
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_diy
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_formal_email
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_git_diff_commit
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_graph_from_input
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_hormozi_offer
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_idea_compass
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_investigation_visualization
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_keynote
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_logo
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_markmap_visualization
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_mermaid_visualization
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_mermaid_visualization_for_github
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_micro_summary
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_network_threat_landscape
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_newsletter_entry
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_npc
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_pattern
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_prd
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_prediction_block
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_quiz
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_reading_plan
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_recursive_outline
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_report_finding
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_rpg_summary
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_security_update
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_show_intro
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_sigma_rules
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_story_explanation
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_stride_threat_model
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_summary
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_tags
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_threat_scenarios
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_ttrc_graph
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_ttrc_narrative
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_upgrade_pack
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_user_story
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── create_video_chapters
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── create_visualization
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── dialog_with_socrates
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── enrich_blog_post
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── explain_code
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── explain_docs
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── explain_math
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── explain_project
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── explain_terms
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── export_data_as_csv
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_algorithm_update_recommendations
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── extract_article_wisdom
│ │ │ │ │ │ ├── dmiessler
│ │ │ │ │ │ │ └── extract_wisdom-1.0.0
│ │ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ │ └── user.md
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── extract_book_ideas
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_book_recommendations
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_business_ideas
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_controversial_ideas
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_core_message
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_ctf_writeup
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_domains
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_extraordinary_claims
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_ideas
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_insights
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_insights_dm
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_instructions
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_jokes
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_latest_video
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_main_idea
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_most_redeeming_thing
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_patterns
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_poc
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── extract_predictions
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_primary_problem
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_primary_solution
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_product_features
│ │ │ │ │ │ ├── dmiessler
│ │ │ │ │ │ │ └── extract_wisdom-1.0.0
│ │ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ │ └── user.md
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_questions
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_recipe
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_recommendations
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── extract_references
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── extract_skills
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_song_meaning
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_sponsors
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_videoid
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── extract_wisdom
│ │ │ │ │ │ ├── dmiessler
│ │ │ │ │ │ │ └── extract_wisdom-1.0.0
│ │ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ │ └── user.md
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_wisdom_agents
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_wisdom_dm
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── extract_wisdom_nometa
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── find_hidden_message
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── find_logical_fallacies
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── get_wow_per_minute
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── get_youtube_rss
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── humanize
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── identify_dsrp_distinctions
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── identify_dsrp_perspectives
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── identify_dsrp_relationships
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── identify_dsrp_systems
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── identify_job_stories
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── improve_academic_writing
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── improve_prompt
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── improve_report_finding
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── improve_writing
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── judge_output
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── label_and_rate
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── loaded
│ │ │ │ │ ├── md_callout
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── official_pattern_template
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── pattern_explanations.md
│ │ │ │ │ ├── prepare_7s_strategy
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── provide_guidance
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── rate_ai_response
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── rate_ai_result
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── rate_content
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── rate_value
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── raw_query
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── raycast
│ │ │ │ │ │ ├── capture_thinkers_work
│ │ │ │ │ │ ├── create_story_explanation
│ │ │ │ │ │ ├── extract_primary_problem
│ │ │ │ │ │ ├── extract_wisdom
│ │ │ │ │ │ └── yt
│ │ │ │ │ ├── recommend_artists
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── recommend_pipeline_upgrades
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── recommend_talkpanel_topics
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── refine_design_document
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── review_design
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── sanitize_broken_html_to_markdown
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── show_fabric_options_markmap
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── solve_with_cot
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── stringify
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── suggest_pattern
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── summarize
│ │ │ │ │ │ ├── dmiessler
│ │ │ │ │ │ │ └── summarize
│ │ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ │ └── user.md
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── summarize_debate
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── summarize_git_changes
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── summarize_git_diff
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── summarize_lecture
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── summarize_legislation
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── summarize_meeting
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── summarize_micro
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── summarize_newsletter
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── summarize_paper
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── summarize_prompt
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── summarize_pull-requests
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── summarize_rpg_session
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_analyze_challenge_handling
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_check_metrics
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_create_h3_career
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_create_opening_sentences
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_describe_life_outlook
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_extract_intro_sentences
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_extract_panel_topics
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_find_blindspots
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_find_negative_thinking
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_find_neglected_goals
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_give_encouragement
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_red_team_thinking
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_threat_model_plans
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_visualize_mission_goals_projects
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── t_year_in_review
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── to_flashcards
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── transcribe_minutes
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── translate
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── tweet
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── write_essay
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── write_hackerone_report
│ │ │ │ │ │ ├── README.md
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── write_latex
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── write_micro_essay
│ │ │ │ │ │ └── system.md
│ │ │ │ │ ├── write_nuclei_template_rule
│ │ │ │ │ │ ├── system.md
│ │ │ │ │ │ └── user.md
│ │ │ │ │ ├── write_pull-request
│ │ │ │ │ │ └── system.md
│ │ │ │ │ └── write_semgrep_rule
│ │ │ │ │ ├── system.md
│ │ │ │ │ └── user.md
│ │ │ │ └── routines
│ │ │ │ ├── list.py
│ │ │ │ ├── run.py
│ │ │ │ └── show.py
│ │ │ ├── guided_conversation
│ │ │ │ ├── __init__.py
│ │ │ │ ├── agenda.py
│ │ │ │ ├── artifact_helpers.py
│ │ │ │ ├── chat_completions
│ │ │ │ │ ├── fix_agenda_error.py
│ │ │ │ │ ├── fix_artifact_error.py
│ │ │ │ │ ├── generate_agenda.py
│ │ │ │ │ ├── generate_artifact_updates.py
│ │ │ │ │ ├── generate_final_artifact.py
│ │ │ │ │ └── generate_message.py
│ │ │ │ ├── conversation_guides
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── acrostic_poem.py
│ │ │ │ │ ├── er_triage.py
│ │ │ │ │ ├── interview.py
│ │ │ │ │ └── patient_intake.py
│ │ │ │ ├── guide.py
│ │ │ │ ├── guided_conversation_skill.py
│ │ │ │ ├── logging.py
│ │ │ │ ├── message.py
│ │ │ │ ├── resources.py
│ │ │ │ ├── routines
│ │ │ │ │ └── guided_conversation.py
│ │ │ │ └── tests
│ │ │ │ ├── conftest.py
│ │ │ │ ├── test_artifact_helpers.py
│ │ │ │ ├── test_generate_agenda.py
│ │ │ │ ├── test_generate_artifact_updates.py
│ │ │ │ ├── test_generate_final_artifact.py
│ │ │ │ └── test_resource.py
│ │ │ ├── meta
│ │ │ │ ├── __init__.py
│ │ │ │ ├── meta_skill.py
│ │ │ │ ├── README.md
│ │ │ │ └── routines
│ │ │ │ └── generate_routine.py
│ │ │ ├── posix
│ │ │ │ ├── __init__.py
│ │ │ │ ├── posix_skill.py
│ │ │ │ ├── routines
│ │ │ │ │ ├── append_file.py
│ │ │ │ │ ├── cd.py
│ │ │ │ │ ├── ls.py
│ │ │ │ │ ├── make_home_dir.py
│ │ │ │ │ ├── mkdir.py
│ │ │ │ │ ├── mv.py
│ │ │ │ │ ├── pwd.py
│ │ │ │ │ ├── read_file.py
│ │ │ │ │ ├── rm.py
│ │ │ │ │ ├── touch.py
│ │ │ │ │ └── write_file.py
│ │ │ │ └── sandbox_shell.py
│ │ │ ├── README.md
│ │ │ ├── research
│ │ │ │ ├── __init__.py
│ │ │ │ ├── README.md
│ │ │ │ ├── research_skill.py
│ │ │ │ └── routines
│ │ │ │ ├── answer_question_about_content.py
│ │ │ │ ├── evaluate_answer.py
│ │ │ │ ├── generate_research_plan.py
│ │ │ │ ├── generate_search_query.py
│ │ │ │ ├── update_research_plan.py
│ │ │ │ ├── web_research.py
│ │ │ │ └── web_search.py
│ │ │ ├── research2
│ │ │ │ ├── __init__.py
│ │ │ │ ├── README.md
│ │ │ │ ├── research_skill.py
│ │ │ │ └── routines
│ │ │ │ ├── facts.py
│ │ │ │ ├── make_final_report.py
│ │ │ │ ├── research.py
│ │ │ │ ├── search_plan.py
│ │ │ │ ├── search.py
│ │ │ │ └── visit_pages.py
│ │ │ └── web_research
│ │ │ ├── __init__.py
│ │ │ ├── README.md
│ │ │ ├── research_skill.py
│ │ │ └── routines
│ │ │ ├── facts.py
│ │ │ ├── make_final_report.py
│ │ │ ├── research.py
│ │ │ ├── search_plan.py
│ │ │ ├── search.py
│ │ │ └── visit_pages.py
│ │ ├── tests
│ │ │ ├── test_common_skill.py
│ │ │ ├── test_integration.py
│ │ │ ├── test_routine_stack.py
│ │ │ ├── tst_skill
│ │ │ │ ├── __init__.py
│ │ │ │ └── routines
│ │ │ │ ├── __init__.py
│ │ │ │ └── a_routine.py
│ │ │ └── utilities
│ │ │ ├── test_find_template_vars.py
│ │ │ ├── test_make_arg_set.py
│ │ │ ├── test_paramspec.py
│ │ │ ├── test_parse_command_string.py
│ │ │ └── test_to_string.py
│ │ ├── types.py
│ │ ├── usage.py
│ │ └── utilities.py
│ └── uv.lock
├── LICENSE
├── Makefile
├── mcp-servers
│ ├── ai-assist-content
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── mcp-example-brave-search.md
│ │ ├── mcp-fastmcp-typescript-README.md
│ │ ├── mcp-llms-full.txt
│ │ ├── mcp-metadata-tips.md
│ │ ├── mcp-python-sdk-README.md
│ │ ├── mcp-typescript-sdk-README.md
│ │ ├── pydanticai-documentation.md
│ │ ├── pydanticai-example-question-graph.md
│ │ ├── pydanticai-example-weather.md
│ │ ├── pydanticai-tutorial.md
│ │ └── README.md
│ ├── Makefile
│ ├── mcp-server-bing-search
│ │ ├── .env.example
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server_bing_search
│ │ │ ├── __init__.py
│ │ │ ├── config.py
│ │ │ ├── prompts
│ │ │ │ ├── __init__.py
│ │ │ │ ├── clean_website.py
│ │ │ │ └── filter_links.py
│ │ │ ├── server.py
│ │ │ ├── start.py
│ │ │ ├── tools.py
│ │ │ ├── types.py
│ │ │ ├── utils.py
│ │ │ └── web
│ │ │ ├── __init__.py
│ │ │ ├── get_content.py
│ │ │ ├── llm_processing.py
│ │ │ ├── process_website.py
│ │ │ └── search_bing.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ └── test_tools.py
│ │ └── uv.lock
│ ├── mcp-server-bundle
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server_bundle
│ │ │ ├── __init__.py
│ │ │ └── main.py
│ │ ├── pyinstaller.spec
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── mcp-server-filesystem
│ │ ├── .env.example
│ │ ├── .github
│ │ │ └── workflows
│ │ │ └── ci.yml
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server_filesystem
│ │ │ ├── __init__.py
│ │ │ ├── config.py
│ │ │ ├── server.py
│ │ │ └── start.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ └── test_filesystem.py
│ │ └── uv.lock
│ ├── mcp-server-filesystem-edit
│ │ ├── .env.example
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── data
│ │ │ ├── attachments
│ │ │ │ ├── Daily Game Ideas.txt
│ │ │ │ ├── Frontend Framework Proposal.txt
│ │ │ │ ├── ReDoodle.txt
│ │ │ │ └── Research Template.tex
│ │ │ ├── test_cases.yaml
│ │ │ └── transcripts
│ │ │ ├── transcript_research_simple.md
│ │ │ ├── transcript_Startup_Idea_1_202503031513.md
│ │ │ ├── transcript_Startup_Idea_2_202503031659.md
│ │ │ └── transcript_Web_Frontends_202502281551.md
│ │ ├── Makefile
│ │ ├── mcp_server_filesystem_edit
│ │ │ ├── __init__.py
│ │ │ ├── app_handling
│ │ │ │ ├── __init__.py
│ │ │ │ ├── excel.py
│ │ │ │ ├── miktex.py
│ │ │ │ ├── office_common.py
│ │ │ │ ├── powerpoint.py
│ │ │ │ └── word.py
│ │ │ ├── config.py
│ │ │ ├── evals
│ │ │ │ ├── __init__.py
│ │ │ │ ├── common.py
│ │ │ │ ├── run_comments.py
│ │ │ │ ├── run_edit.py
│ │ │ │ └── run_ppt_edit.py
│ │ │ ├── prompts
│ │ │ │ ├── __init__.py
│ │ │ │ ├── add_comments.py
│ │ │ │ ├── analyze_comments.py
│ │ │ │ ├── latex_edit.py
│ │ │ │ ├── markdown_draft.py
│ │ │ │ ├── markdown_edit.py
│ │ │ │ └── powerpoint_edit.py
│ │ │ ├── server.py
│ │ │ ├── start.py
│ │ │ ├── tools
│ │ │ │ ├── __init__.py
│ │ │ │ ├── add_comments.py
│ │ │ │ ├── edit_adapters
│ │ │ │ │ ├── __init__.py
│ │ │ │ │ ├── common.py
│ │ │ │ │ ├── latex.py
│ │ │ │ │ └── markdown.py
│ │ │ │ ├── edit.py
│ │ │ │ └── helpers.py
│ │ │ └── types.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ ├── app_handling
│ │ │ │ ├── test_excel.py
│ │ │ │ ├── test_miktext.py
│ │ │ │ ├── test_office_common.py
│ │ │ │ ├── test_powerpoint.py
│ │ │ │ └── test_word.py
│ │ │ ├── conftest.py
│ │ │ └── tools
│ │ │ └── edit_adapters
│ │ │ ├── test_latex.py
│ │ │ └── test_markdown.py
│ │ └── uv.lock
│ ├── mcp-server-fusion
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── AddInIcon.svg
│ │ ├── config.py
│ │ ├── FusionMCPServerAddIn.manifest
│ │ ├── FusionMCPServerAddIn.py
│ │ ├── mcp_server_fusion
│ │ │ ├── __init__.py
│ │ │ ├── fusion_mcp_server.py
│ │ │ ├── fusion_utils
│ │ │ │ ├── __init__.py
│ │ │ │ ├── event_utils.py
│ │ │ │ ├── general_utils.py
│ │ │ │ └── tool_utils.py
│ │ │ ├── mcp_tools
│ │ │ │ ├── __init__.py
│ │ │ │ ├── fusion_3d_operation.py
│ │ │ │ ├── fusion_geometry.py
│ │ │ │ ├── fusion_pattern.py
│ │ │ │ └── fusion_sketch.py
│ │ │ └── vendor
│ │ │ └── README.md
│ │ ├── README.md
│ │ └── requirements.txt
│ ├── mcp-server-giphy
│ │ ├── .env.example
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server
│ │ │ ├── __init__.py
│ │ │ ├── config.py
│ │ │ ├── giphy_search.py
│ │ │ ├── sampling.py
│ │ │ ├── server.py
│ │ │ ├── start.py
│ │ │ └── utils.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── mcp-server-memory-user-bio
│ │ ├── .env.example
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server_memory_user_bio
│ │ │ ├── __init__.py
│ │ │ ├── config.py
│ │ │ ├── server.py
│ │ │ └── start.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── mcp-server-memory-whiteboard
│ │ ├── .env.example
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server_memory_whiteboard
│ │ │ ├── __init__.py
│ │ │ ├── config.py
│ │ │ ├── server.py
│ │ │ └── start.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── mcp-server-office
│ │ ├── .env.example
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── build.sh
│ │ ├── data
│ │ │ ├── attachments
│ │ │ │ ├── Daily Game Ideas.txt
│ │ │ │ ├── Frontend Framework Proposal.txt
│ │ │ │ └── ReDoodle.txt
│ │ │ └── word
│ │ │ ├── test_cases.yaml
│ │ │ └── transcripts
│ │ │ ├── transcript_Startup_Idea_1_202503031513.md
│ │ │ ├── transcript_Startup_Idea_2_202503031659.md
│ │ │ └── transcript_Web_Frontends_202502281551.md
│ │ ├── Makefile
│ │ ├── mcp_server
│ │ │ ├── __init__.py
│ │ │ ├── app_interaction
│ │ │ │ ├── __init__.py
│ │ │ │ ├── excel_editor.py
│ │ │ │ ├── powerpoint_editor.py
│ │ │ │ └── word_editor.py
│ │ │ ├── config.py
│ │ │ ├── constants.py
│ │ │ ├── evals
│ │ │ │ ├── __init__.py
│ │ │ │ ├── common.py
│ │ │ │ ├── run_comment_analysis.py
│ │ │ │ ├── run_feedback.py
│ │ │ │ └── run_markdown_edit.py
│ │ │ ├── helpers.py
│ │ │ ├── markdown_edit
│ │ │ │ ├── __init__.py
│ │ │ │ ├── comment_analysis.py
│ │ │ │ ├── feedback_step.py
│ │ │ │ ├── markdown_edit.py
│ │ │ │ └── utils.py
│ │ │ ├── prompts
│ │ │ │ ├── __init__.py
│ │ │ │ ├── comment_analysis.py
│ │ │ │ ├── feedback.py
│ │ │ │ ├── markdown_draft.py
│ │ │ │ └── markdown_edit.py
│ │ │ ├── server.py
│ │ │ ├── start.py
│ │ │ └── types.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── tests
│ │ │ └── test_word_editor.py
│ │ └── uv.lock
│ ├── mcp-server-open-deep-research
│ │ ├── .env.example
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server
│ │ │ ├── __init__.py
│ │ │ ├── config.py
│ │ │ ├── libs
│ │ │ │ └── open_deep_research
│ │ │ │ ├── cookies.py
│ │ │ │ ├── mdconvert.py
│ │ │ │ ├── run_agents.py
│ │ │ │ ├── text_inspector_tool.py
│ │ │ │ ├── text_web_browser.py
│ │ │ │ └── visual_qa.py
│ │ │ ├── open_deep_research.py
│ │ │ ├── server.py
│ │ │ └── start.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ └── uv.lock
│ ├── mcp-server-open-deep-research-clone
│ │ ├── .env.example
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json
│ │ │ └── settings.json
│ │ ├── Makefile
│ │ ├── mcp_server_open_deep_research_clone
│ │ │ ├── __init__.py
│ │ │ ├── azure_openai.py
│ │ │ ├── config.py
│ │ │ ├── logging.py
│ │ │ ├── sampling.py
│ │ │ ├── server.py
│ │ │ ├── start.py
│ │ │ ├── utils.py
│ │ │ └── web_research.py
│ │ ├── pyproject.toml
│ │ ├── README.md
│ │ ├── test
│ │ │ └── test_open_deep_research_clone.py
│ │ └── uv.lock
│ ├── mcp-server-template
│ │ ├── .taplo.toml
│ │ ├── .vscode
│ │ │ └── settings.json
│ │ ├── copier.yml
│ │ ├── README.md
│ │ └── template
│ │ └── {{ project_slug }}
│ │ ├── .env.example.jinja
│ │ ├── .gitignore
│ │ ├── .vscode
│ │ │ ├── launch.json.jinja
│ │ │ └── settings.json
│ │ ├── {{ module_name }}
│ │ │ ├── __init__.py
│ │ │ ├── config.py.jinja
│ │ │ ├── server.py.jinja
│ │ │ └── start.py.jinja
│ │ ├── Makefile.jinja
│ │ ├── pyproject.toml.jinja
│ │ └── README.md.jinja
│ ├── mcp-server-vscode
│ │ ├── .eslintrc.cjs
│ │ ├── .gitignore
│ │ ├── .npmrc
│ │ ├── .vscode
│ │ │ ├── extensions.json
│ │ │ ├── launch.json
│ │ │ ├── settings.json
│ │ │ └── tasks.json
│ │ ├── .vscode-test.mjs
│ │ ├── .vscodeignore
│ │ ├── ASSISTANT_BOOTSTRAP.md
│ │ ├── eslint.config.mjs
│ │ ├── images
│ │ │ └── icon.png
│ │ ├── LICENSE
│ │ ├── Makefile
│ │ ├── out
│ │ │ ├── extension.d.ts
│ │ │ ├── extension.js
│ │ │ ├── test
│ │ │ │ ├── extension.test.d.ts
│ │ │ │ └── extension.test.js
│ │ │ ├── tools
│ │ │ │ ├── code_checker.d.ts
│ │ │ │ ├── code_checker.js
│ │ │ │ ├── debug_tools.d.ts
│ │ │ │ ├── debug_tools.js
│ │ │ │ ├── focus_editor.d.ts
│ │ │ │ ├── focus_editor.js
│ │ │ │ ├── search_symbol.d.ts
│ │ │ │ └── search_symbol.js
│ │ │ └── utils
│ │ │ ├── port.d.ts
│ │ │ └── port.js
│ │ ├── package.json
│ │ ├── pnpm-lock.yaml
│ │ ├── prettier.config.cjs
│ │ ├── README.md
│ │ ├── src
│ │ │ ├── extension.d.ts
│ │ │ ├── extension.ts
│ │ │ ├── test
│ │ │ │ ├── extension.test.d.ts
│ │ │ │ └── extension.test.ts
│ │ │ ├── tools
│ │ │ │ ├── code_checker.d.ts
│ │ │ │ ├── code_checker.ts
│ │ │ │ ├── debug_tools.d.ts
│ │ │ │ ├── debug_tools.ts
│ │ │ │ ├── focus_editor.d.ts
│ │ │ │ ├── focus_editor.ts
│ │ │ │ ├── search_symbol.d.ts
│ │ │ │ └── search_symbol.ts
│ │ │ └── utils
│ │ │ ├── port.d.ts
│ │ │ └── port.ts
│ │ ├── tsconfig.json
│ │ ├── tsconfig.tsbuildinfo
│ │ ├── vsc-extension-quickstart.md
│ │ └── webpack.config.js
│ └── mcp-server-web-research
│ ├── .env.example
│ ├── .gitignore
│ ├── .vscode
│ │ ├── launch.json
│ │ └── settings.json
│ ├── Makefile
│ ├── mcp_server_web_research
│ │ ├── __init__.py
│ │ ├── azure_openai.py
│ │ ├── config.py
│ │ ├── logging.py
│ │ ├── sampling.py
│ │ ├── server.py
│ │ ├── start.py
│ │ ├── utils.py
│ │ └── web_research.py
│ ├── pyproject.toml
│ ├── README.md
│ ├── test
│ │ └── test_web_research.py
│ └── uv.lock
├── README.md
├── RESPONSIBLE_AI_FAQ.md
├── ruff.toml
├── SECURITY.md
├── semantic-workbench.code-workspace
├── SUPPORT.md
├── tools
│ ├── build_ai_context_files.py
│ ├── collect_files.py
│ ├── docker
│ │ ├── azure_website_sshd.conf
│ │ ├── docker-entrypoint.sh
│ │ ├── Dockerfile.assistant
│ │ └── Dockerfile.mcp-server
│ ├── makefiles
│ │ ├── docker-assistant.mk
│ │ ├── docker-mcp-server.mk
│ │ ├── docker.mk
│ │ ├── python.mk
│ │ ├── recursive.mk
│ │ └── shell.mk
│ ├── reset-service-data.ps1
│ ├── reset-service-data.sh
│ ├── run-app.ps1
│ ├── run-app.sh
│ ├── run-canonical-agent.ps1
│ ├── run-canonical-agent.sh
│ ├── run-dotnet-examples-with-aspire.sh
│ ├── run-python-example1.sh
│ ├── run-python-example2.ps1
│ ├── run-python-example2.sh
│ ├── run-service.ps1
│ ├── run-service.sh
│ ├── run-workbench-chatbot.ps1
│ └── run-workbench-chatbot.sh
├── workbench-app
│ ├── .dockerignore
│ ├── .env.example
│ ├── .eslintrc.cjs
│ ├── .gitignore
│ ├── .vscode
│ │ ├── launch.json
│ │ └── settings.json
│ ├── docker-entrypoint.sh
│ ├── Dockerfile
│ ├── docs
│ │ ├── APP_DEV_GUIDE.md
│ │ ├── MESSAGE_METADATA.md
│ │ ├── MESSAGE_TYPES.md
│ │ ├── README.md
│ │ └── STATE_INSPECTORS.md
│ ├── index.html
│ ├── Makefile
│ ├── nginx.conf
│ ├── package.json
│ ├── pnpm-lock.yaml
│ ├── prettier.config.cjs
│ ├── public
│ │ └── assets
│ │ ├── background-1-upscaled.jpg
│ │ ├── background-1-upscaled.png
│ │ ├── background-1.jpg
│ │ ├── background-1.png
│ │ ├── background-2.jpg
│ │ ├── background-2.png
│ │ ├── experimental-feature.jpg
│ │ ├── favicon.svg
│ │ ├── workflow-designer-1.jpg
│ │ ├── workflow-designer-outlets.jpg
│ │ ├── workflow-designer-states.jpg
│ │ └── workflow-designer-transitions.jpg
│ ├── README.md
│ ├── run.sh
│ ├── src
│ │ ├── components
│ │ │ ├── App
│ │ │ │ ├── AppFooter.tsx
│ │ │ │ ├── AppHeader.tsx
│ │ │ │ ├── AppMenu.tsx
│ │ │ │ ├── AppView.tsx
│ │ │ │ ├── CodeLabel.tsx
│ │ │ │ ├── CommandButton.tsx
│ │ │ │ ├── ConfirmLeave.tsx
│ │ │ │ ├── ContentExport.tsx
│ │ │ │ ├── ContentImport.tsx
│ │ │ │ ├── CopyButton.tsx
│ │ │ │ ├── DialogControl.tsx
│ │ │ │ ├── DynamicIframe.tsx
│ │ │ │ ├── ErrorListFromAppState.tsx
│ │ │ │ ├── ErrorMessageBar.tsx
│ │ │ │ ├── ExperimentalNotice.tsx
│ │ │ │ ├── FormWidgets
│ │ │ │ │ ├── BaseModelEditorWidget.tsx
│ │ │ │ │ ├── CustomizedArrayFieldTemplate.tsx
│ │ │ │ │ ├── CustomizedFieldTemplate.tsx
│ │ │ │ │ ├── CustomizedObjectFieldTemplate.tsx
│ │ │ │ │ └── InspectableWidget.tsx
│ │ │ │ ├── LabelWithDescription.tsx
│ │ │ │ ├── Loading.tsx
│ │ │ │ ├── MenuItemControl.tsx
│ │ │ │ ├── MiniControl.tsx
│ │ │ │ ├── MyAssistantServiceRegistrations.tsx
│ │ │ │ ├── MyItemsManager.tsx
│ │ │ │ ├── OverflowMenu.tsx
│ │ │ │ ├── PresenceMotionList.tsx
│ │ │ │ ├── ProfileSettings.tsx
│ │ │ │ └── TooltipWrapper.tsx
│ │ │ ├── Assistants
│ │ │ │ ├── ApplyConfigButton.tsx
│ │ │ │ ├── AssistantAdd.tsx
│ │ │ │ ├── AssistantConfigExportButton.tsx
│ │ │ │ ├── AssistantConfigImportButton.tsx
│ │ │ │ ├── AssistantConfiguration.tsx
│ │ │ │ ├── AssistantConfigure.tsx
│ │ │ │ ├── AssistantCreate.tsx
│ │ │ │ ├── AssistantDelete.tsx
│ │ │ │ ├── AssistantDuplicate.tsx
│ │ │ │ ├── AssistantExport.tsx
│ │ │ │ ├── AssistantImport.tsx
│ │ │ │ ├── AssistantRemove.tsx
│ │ │ │ ├── AssistantRename.tsx
│ │ │ │ ├── AssistantServiceInfo.tsx
│ │ │ │ ├── AssistantServiceMetadata.tsx
│ │ │ │ └── MyAssistants.tsx
│ │ │ ├── AssistantServiceRegistrations
│ │ │ │ ├── AssistantServiceRegistrationApiKey.tsx
│ │ │ │ ├── AssistantServiceRegistrationApiKeyReset.tsx
│ │ │ │ ├── AssistantServiceRegistrationCreate.tsx
│ │ │ │ └── AssistantServiceRegistrationRemove.tsx
│ │ │ ├── Conversations
│ │ │ │ ├── Canvas
│ │ │ │ │ ├── AssistantCanvas.tsx
│ │ │ │ │ ├── AssistantCanvasList.tsx
│ │ │ │ │ ├── AssistantInspector.tsx
│ │ │ │ │ ├── AssistantInspectorList.tsx
│ │ │ │ │ └── ConversationCanvas.tsx
│ │ │ │ ├── ChatInputPlugins
│ │ │ │ │ ├── ClearEditorPlugin.tsx
│ │ │ │ │ ├── LexicalMenu.ts
│ │ │ │ │ ├── ParticipantMentionsPlugin.tsx
│ │ │ │ │ ├── TypeaheadMenuPlugin.css
│ │ │ │ │ └── TypeaheadMenuPlugin.tsx
│ │ │ │ ├── ContentRenderers
│ │ │ │ │ ├── CodeContentRenderer.tsx
│ │ │ │ │ ├── ContentListRenderer.tsx
│ │ │ │ │ ├── ContentRenderer.tsx
│ │ │ │ │ ├── DiffRenderer.tsx
│ │ │ │ │ ├── HtmlContentRenderer.tsx
│ │ │ │ │ ├── JsonSchemaContentRenderer.tsx
│ │ │ │ │ ├── MarkdownContentRenderer.tsx
│ │ │ │ │ ├── MarkdownEditorRenderer.tsx
│ │ │ │ │ ├── MermaidContentRenderer.tsx
│ │ │ │ │ ├── MusicABCContentRenderer.css
│ │ │ │ │ └── MusicABCContentRenderer.tsx
│ │ │ │ ├── ContextWindow.tsx
│ │ │ │ ├── ConversationCreate.tsx
│ │ │ │ ├── ConversationDuplicate.tsx
│ │ │ │ ├── ConversationExport.tsx
│ │ │ │ ├── ConversationFileIcon.tsx
│ │ │ │ ├── ConversationRemove.tsx
│ │ │ │ ├── ConversationRename.tsx
│ │ │ │ ├── ConversationShare.tsx
│ │ │ │ ├── ConversationShareCreate.tsx
│ │ │ │ ├── ConversationShareList.tsx
│ │ │ │ ├── ConversationShareView.tsx
│ │ │ │ ├── ConversationsImport.tsx
│ │ │ │ ├── ConversationTranscript.tsx
│ │ │ │ ├── DebugInspector.tsx
│ │ │ │ ├── FileItem.tsx
│ │ │ │ ├── FileList.tsx
│ │ │ │ ├── InputAttachmentList.tsx
│ │ │ │ ├── InputOptionsControl.tsx
│ │ │ │ ├── InteractHistory.tsx
│ │ │ │ ├── InteractInput.tsx
│ │ │ │ ├── Message
│ │ │ │ │ ├── AttachmentSection.tsx
│ │ │ │ │ ├── ContentRenderer.tsx
│ │ │ │ │ ├── ContentSafetyNotice.tsx
│ │ │ │ │ ├── InteractMessage.tsx
│ │ │ │ │ ├── MessageActions.tsx
│ │ │ │ │ ├── MessageBase.tsx
│ │ │ │ │ ├── MessageBody.tsx
│ │ │ │ │ ├── MessageContent.tsx
│ │ │ │ │ ├── MessageFooter.tsx
│ │ │ │ │ ├── MessageHeader.tsx
│ │ │ │ │ ├── NotificationAccordion.tsx
│ │ │ │ │ └── ToolResultMessage.tsx
│ │ │ │ ├── MessageDelete.tsx
│ │ │ │ ├── MessageLink.tsx
│ │ │ │ ├── MyConversations.tsx
│ │ │ │ ├── MyShares.tsx
│ │ │ │ ├── ParticipantAvatar.tsx
│ │ │ │ ├── ParticipantAvatarGroup.tsx
│ │ │ │ ├── ParticipantItem.tsx
│ │ │ │ ├── ParticipantList.tsx
│ │ │ │ ├── ParticipantStatus.tsx
│ │ │ │ ├── RewindConversation.tsx
│ │ │ │ ├── ShareRemove.tsx
│ │ │ │ ├── SpeechButton.tsx
│ │ │ │ └── ToolCalls.tsx
│ │ │ └── FrontDoor
│ │ │ ├── Chat
│ │ │ │ ├── AssistantDrawer.tsx
│ │ │ │ ├── CanvasDrawer.tsx
│ │ │ │ ├── Chat.tsx
│ │ │ │ ├── ChatCanvas.tsx
│ │ │ │ ├── ChatControls.tsx
│ │ │ │ └── ConversationDrawer.tsx
│ │ │ ├── Controls
│ │ │ │ ├── AssistantCard.tsx
│ │ │ │ ├── AssistantSelector.tsx
│ │ │ │ ├── AssistantServiceSelector.tsx
│ │ │ │ ├── ConversationItem.tsx
│ │ │ │ ├── ConversationList.tsx
│ │ │ │ ├── ConversationListOptions.tsx
│ │ │ │ ├── NewConversationButton.tsx
│ │ │ │ ├── NewConversationForm.tsx
│ │ │ │ └── SiteMenuButton.tsx
│ │ │ ├── GlobalContent.tsx
│ │ │ └── MainContent.tsx
│ │ ├── Constants.ts
│ │ ├── global.d.ts
│ │ ├── index.css
│ │ ├── libs
│ │ │ ├── AppStorage.ts
│ │ │ ├── AuthHelper.ts
│ │ │ ├── EventSubscriptionManager.ts
│ │ │ ├── Theme.ts
│ │ │ ├── useAssistantCapabilities.ts
│ │ │ ├── useChatCanvasController.ts
│ │ │ ├── useConversationEvents.ts
│ │ │ ├── useConversationUtility.ts
│ │ │ ├── useCreateConversation.ts
│ │ │ ├── useDebugComponentLifecycle.ts
│ │ │ ├── useDragAndDrop.ts
│ │ │ ├── useEnvironment.ts
│ │ │ ├── useExportUtility.ts
│ │ │ ├── useHistoryUtility.ts
│ │ │ ├── useKeySequence.ts
│ │ │ ├── useMediaQuery.ts
│ │ │ ├── useMicrosoftGraph.ts
│ │ │ ├── useNotify.tsx
│ │ │ ├── useParticipantUtility.tsx
│ │ │ ├── useSiteUtility.ts
│ │ │ ├── useWorkbenchEventSource.ts
│ │ │ ├── useWorkbenchService.ts
│ │ │ └── Utility.ts
│ │ ├── main.tsx
│ │ ├── models
│ │ │ ├── Assistant.ts
│ │ │ ├── AssistantCapability.ts
│ │ │ ├── AssistantServiceInfo.ts
│ │ │ ├── AssistantServiceRegistration.ts
│ │ │ ├── Config.ts
│ │ │ ├── Conversation.ts
│ │ │ ├── ConversationFile.ts
│ │ │ ├── ConversationMessage.ts
│ │ │ ├── ConversationMessageDebug.ts
│ │ │ ├── ConversationParticipant.ts
│ │ │ ├── ConversationShare.ts
│ │ │ ├── ConversationShareRedemption.ts
│ │ │ ├── ConversationState.ts
│ │ │ ├── ConversationStateDescription.ts
│ │ │ ├── ServiceEnvironment.ts
│ │ │ └── User.ts
│ │ ├── redux
│ │ │ ├── app
│ │ │ │ ├── hooks.ts
│ │ │ │ ├── rtkQueryErrorLogger.ts
│ │ │ │ └── store.ts
│ │ │ └── features
│ │ │ ├── app
│ │ │ │ ├── appSlice.ts
│ │ │ │ └── AppState.ts
│ │ │ ├── chatCanvas
│ │ │ │ ├── chatCanvasSlice.ts
│ │ │ │ └── ChatCanvasState.ts
│ │ │ ├── localUser
│ │ │ │ ├── localUserSlice.ts
│ │ │ │ └── LocalUserState.ts
│ │ │ └── settings
│ │ │ ├── settingsSlice.ts
│ │ │ └── SettingsState.ts
│ │ ├── Root.tsx
│ │ ├── routes
│ │ │ ├── AcceptTerms.tsx
│ │ │ ├── AssistantEditor.tsx
│ │ │ ├── AssistantServiceRegistrationEditor.tsx
│ │ │ ├── Dashboard.tsx
│ │ │ ├── ErrorPage.tsx
│ │ │ ├── FrontDoor.tsx
│ │ │ ├── Login.tsx
│ │ │ ├── Settings.tsx
│ │ │ ├── ShareRedeem.tsx
│ │ │ └── Shares.tsx
│ │ ├── services
│ │ │ └── workbench
│ │ │ ├── assistant.ts
│ │ │ ├── assistantService.ts
│ │ │ ├── conversation.ts
│ │ │ ├── file.ts
│ │ │ ├── index.ts
│ │ │ ├── participant.ts
│ │ │ ├── share.ts
│ │ │ ├── state.ts
│ │ │ └── workbench.ts
│ │ └── vite-env.d.ts
│ ├── tools
│ │ └── filtered-ts-prune.cjs
│ ├── tsconfig.json
│ └── vite.config.ts
└── workbench-service
├── .env.example
├── .vscode
│ ├── extensions.json
│ ├── launch.json
│ └── settings.json
├── alembic.ini
├── devdb
│ ├── docker-compose.yaml
│ └── postgresql-init.sh
├── Dockerfile
├── Makefile
├── migrations
│ ├── env.py
│ ├── README
│ ├── script.py.mako
│ └── versions
│ ├── 2024_09_19_000000_69dcda481c14_init.py
│ ├── 2024_09_19_190029_dffb1d7e219a_file_version_filename.py
│ ├── 2024_09_20_204130_b29524775484_share.py
│ ├── 2024_10_30_231536_039bec8edc33_index_message_type.py
│ ├── 2024_11_04_204029_5149c7fb5a32_conversationmessagedebug.py
│ ├── 2024_11_05_015124_245baf258e11_double_check_debugs.py
│ ├── 2024_11_25_191056_a106de176394_drop_workflow.py
│ ├── 2025_03_19_140136_aaaf792d4d72_set_user_title_set.py
│ ├── 2025_03_21_153250_3763629295ad_add_assistant_template_id.py
│ ├── 2025_05_19_163613_b2f86e981885_delete_context_transfer_assistants.py
│ └── 2025_06_18_174328_503c739152f3_delete_knowlege_transfer_assistants.py
├── pyproject.toml
├── README.md
├── semantic_workbench_service
│ ├── __init__.py
│ ├── api.py
│ ├── assistant_api_key.py
│ ├── auth.py
│ ├── azure_speech.py
│ ├── config.py
│ ├── controller
│ │ ├── __init__.py
│ │ ├── assistant_service_client_pool.py
│ │ ├── assistant_service_registration.py
│ │ ├── assistant.py
│ │ ├── conversation_share.py
│ │ ├── conversation.py
│ │ ├── convert.py
│ │ ├── exceptions.py
│ │ ├── export_import.py
│ │ ├── file.py
│ │ ├── participant.py
│ │ └── user.py
│ ├── db.py
│ ├── event.py
│ ├── files.py
│ ├── logging_config.py
│ ├── middleware.py
│ ├── query.py
│ ├── service_user_principals.py
│ ├── service.py
│ └── start.py
├── tests
│ ├── __init__.py
│ ├── conftest.py
│ ├── docker-compose.yaml
│ ├── test_assistant_api_key.py
│ ├── test_files.py
│ ├── test_integration.py
│ ├── test_middleware.py
│ ├── test_migrations.py
│ ├── test_workbench_service.py
│ └── types.py
└── uv.lock
```
# Files
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/judge_output/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY
You are a Honeycomb query evaluator with advanced capabilities to judge if a query is good or not.
You understand the nuances of the Honeycomb query language, including what is likely to be
most useful from an analytics perspective.
# Introduction
Here is information about the Honeycomb query language:
{{query_language_info}}
Here are some guidelines for evaluating queries:
{{guidelines}}
# Examples
Example evaluations:
<examples>
<example-1>
<nlq>show me traces where ip is 10.0.2.90</nlq>
<query>
{
"breakdowns": ["trace.trace_id"],
"calculations": [{"op": "COUNT"}],
"filters": [{"column": "net.host.ip", "op": "=", "value": "10.0.2.90"}]
}
</query>
<critique>
{
"critique": "The query correctly filters for traces with an IP address of 10.0.2.90
and counts the occurrences of those traces, grouped by trace.trace_id. The response
is good as it meets the requirement of showing traces from a specific IP address
without additional complexities.",
"outcome": "good"
}
</critique>
</example-1>
<example-2>
<nlq>show me slowest trace</nlq>
<query>
{
"calculations": [{"column": "duration_ms", "op": "MAX"}],
"orders": [{"column": "duration_ms", "op": "MAX", "order": "descending"}],
"limit": 1
}
</query>
<critique>
{
"critique": "While the query attempts to find the slowest trace using MAX(duration_ms)
and ordering correctly, it fails to group by trace.trace_id. Without this grouping,
the query only shows the MAX(duration_ms) measurement over time, not the actual
slowest trace.",
"outcome": "bad"
}
</critique>
</example-2>
<example-3>
<nlq>count window-hash where window-hash exists per hour</nlq>
<query>
{
"breakdowns": ["window-hash"],
"calculations": [{"op": "COUNT"}],
"filters": [{"column": "window-hash", "op": "exists"}],
"time_range": 3600
}
</query>
<critique>
{
"critique": "While the query correctly counts window-hash occurrences, the time_range
of 3600 seconds (1 hour) is insufficient for per-hour analysis. When we say 'per hour',
we need a time_range of at least 36000 seconds to show meaningful hourly patterns.",
"outcome": "bad"
}
</critique>
</example-3>
</examples>
For the following query, first write a detailed critique explaining your reasoning,
then provide a pass/fail judgment in the same format as above.
<nlq>{{user_input}}</nlq>
<query>
{{generated_query}}
</query>
<critique>
```
--------------------------------------------------------------------------------
/workbench-app/src/components/Assistants/AssistantConfigure.tsx:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import { DialogOpenChangeData, DialogOpenChangeEvent, makeStyles, tokens } from '@fluentui/react-components';
import React from 'react';
import { Assistant } from '../../models/Assistant';
import { DialogControl } from '../App/DialogControl';
import { AssistantConfiguration } from './AssistantConfiguration';
const useClasses = makeStyles({
dialogSurface: {
maxWidth: 'calc(min(1000px, 100vw) - 32px)',
minWidth: 'min(600px, 100vw)',
width: 'fit-content',
},
dialogContent: {
height: 'calc(100vh - 150px)',
width: 'calc(min(1000px, 100vw) - 100px)',
paddingRight: '8px',
boxSizing: 'border-box',
overflowY: 'auto',
},
content: {
display: 'flex',
flexDirection: 'column',
gap: tokens.spacingVerticalM,
},
});
interface AssistantConfigureDialogProps {
assistant?: Assistant;
open: boolean;
onOpenChange: (event: DialogOpenChangeEvent, data: DialogOpenChangeData) => void;
}
export const AssistantConfigureDialog: React.FC<AssistantConfigureDialogProps> = (props) => {
const { assistant, open, onOpenChange } = props;
const classes = useClasses();
const [isDirty, setIsDirty] = React.useState(false);
const handleOpenChange = React.useCallback(
(event: DialogOpenChangeEvent, data: DialogOpenChangeData) => {
if (data.open) {
setIsDirty(false);
return;
}
if (isDirty) {
const result = window.confirm('Are you sure you want to close without saving?');
if (!result) {
return;
}
}
setIsDirty(false);
onOpenChange(event, data);
},
[isDirty, onOpenChange],
);
return (
<DialogControl
open={open}
onOpenChange={handleOpenChange}
title={assistant && `Configure "${assistant.name}"`}
content={
<div className={classes.content}>
{assistant && <AssistantConfiguration assistant={assistant} onIsDirtyChange={setIsDirty} />}
</div>
}
classNames={{
dialogSurface: classes.dialogSurface,
dialogContent: classes.dialogContent,
}}
/>
);
};
```
--------------------------------------------------------------------------------
/assistants/document-assistant/.vscode/settings.json:
--------------------------------------------------------------------------------
```json
{
"editor.bracketPairColorization.enabled": true,
"editor.codeActionsOnSave": {
"source.organizeImports": "explicit",
"source.fixAll": "explicit"
},
"editor.guides.bracketPairs": "active",
"editor.formatOnPaste": true,
"editor.formatOnType": true,
"editor.formatOnSave": true,
"files.eol": "\n",
"files.exclude": {
"**/.git": true,
"**/.svn": true,
"**/.hg": true,
"**/CVS": true,
"**/.DS_Store": true,
"**/Thumbs.db": true
},
"files.trimTrailingWhitespace": true,
"[json]": {
"editor.defaultFormatter": "esbenp.prettier-vscode",
"editor.formatOnSave": true
},
"[jsonc]": {
"editor.defaultFormatter": "esbenp.prettier-vscode",
"editor.formatOnSave": true
},
"python.analysis.autoFormatStrings": true,
"python.analysis.autoImportCompletions": true,
"python.analysis.diagnosticMode": "workspace",
"python.analysis.fixAll": ["source.unusedImports"],
"python.analysis.inlayHints.functionReturnTypes": true,
"python.analysis.typeCheckingMode": "standard",
"python.defaultInterpreterPath": "${workspaceFolder}/.venv",
"[python]": {
"editor.defaultFormatter": "charliermarsh.ruff",
"editor.formatOnSave": true,
"editor.codeActionsOnSave": {
"source.fixAll": "explicit",
"source.unusedImports": "explicit",
"source.organizeImports": "explicit",
"source.formatDocument": "explicit"
}
},
"ruff.nativeServer": "on",
"search.exclude": {
"**/.venv": true,
"**/.data": true,
"**/__pycache__": true
},
// For use with optional extension: "streetsidesoftware.code-spell-checker"
"cSpell.ignorePaths": [
".venv",
"node_modules",
"package-lock.json",
"settings.json",
"uv.lock"
],
"cSpell.words": [
"Codespaces",
"contentsafety",
"debugpy",
"deepmerge",
"devcontainer",
"dotenv",
"endregion",
"Excalidraw",
"fastapi",
"GIPHY",
"jsonschema",
"Langchain",
"modelcontextprotocol",
"moderations",
"mzxrai",
"openai",
"pdfplumber",
"pydantic",
"pyproject",
"pyright",
"pytest",
"semanticworkbench",
"semanticworkbenchteam",
"tiktoken",
"updown",
"virtualenvs",
"webresearch"
],
// Python testing configuration
"python.testing.pytestEnabled": true,
"python.testing.unittestEnabled": false,
"python.testing.pytestArgs": ["tests", "-s"]
}
```
--------------------------------------------------------------------------------
/mcp-servers/mcp-server-bing-search/mcp_server_bing_search/tools.py:
--------------------------------------------------------------------------------
```python
# Copyright (c) Microsoft. All rights reserved.
import asyncio
import logging
import time
from mcp_server_bing_search import settings
from mcp_server_bing_search.types import Link, WebResult
from mcp_server_bing_search.utils import format_web_results, lookup_url
from mcp_server_bing_search.web.process_website import process_website
from mcp_server_bing_search.web.search_bing import search_bing
logger = logging.getLogger(__name__)
def sync_process_website(
website: Link,
apply_post_processing: bool = True,
) -> WebResult:
return asyncio.run(process_website(website, apply_post_processing))
async def _process_websites_parallel(
urls: list[str],
) -> str:
tasks = []
for url in urls:
tasks.append(asyncio.to_thread(sync_process_website, Link(url=url), settings.improve_with_sampling))
start_time = time.time()
results = await asyncio.gather(*tasks)
end_time = time.time()
response_duration = round(end_time - start_time, 4)
logger.info(f"Processed {len(urls)} URLs in {response_duration} seconds.")
# Filter out any None or empty results
web_results = [result for result in results if result and result.content]
if not web_results:
return "No content could be extracted from the provided URLs."
web_results = format_web_results(web_results)
return web_results
async def search(query: str) -> str:
"""
Searches for web results using the provided query.
Returns:
A formatted string containing web search results suitable for LLM consumption.
"""
search_results = search_bing(query)
if not search_results:
return "No results found."
urls = [result.url for result in search_results]
results = await _process_websites_parallel(urls)
return results
async def click(hashes: list[str]) -> str:
"""
Looks up each of the hashes to get the associated URLs and then processes the URLs.
Returns:
A formatted string containing the processed web content for LLM consumption
"""
# Look up URLs for each hash
urls = []
for url_hash in hashes:
url = lookup_url(url_hash)
if url:
urls.append(url)
# Only use the max num_search_results amount of urls
urls = urls[: settings.num_search_results]
if not urls:
return "No results found."
results = await _process_websites_parallel(urls)
return results
```
--------------------------------------------------------------------------------
/workbench-app/src/components/App/OverflowMenu.tsx:
--------------------------------------------------------------------------------
```typescript
import {
Button,
makeStyles,
Menu,
MenuItem,
MenuList,
MenuPopover,
MenuTrigger,
Slot,
tokens,
useIsOverflowItemVisible,
useOverflowMenu,
} from '@fluentui/react-components';
import { MoreHorizontalRegular } from '@fluentui/react-icons';
import React from 'react';
const useClasses = makeStyles({
menu: {
backgroundColor: tokens.colorNeutralBackground1,
},
menuButton: {
alignSelf: 'center',
},
});
export interface OverflowMenuItemData {
id: string;
icon?: Slot<'span'>;
name?: string;
}
interface OverflowMenuItemProps {
item: OverflowMenuItemData;
onClick: (event: React.MouseEvent, id: string) => void;
}
export const OverflowMenuItem: React.FC<OverflowMenuItemProps> = (props) => {
const { item, onClick } = props;
const isVisible = useIsOverflowItemVisible(item.id);
if (isVisible) {
return null;
}
return (
<MenuItem key={item.id} icon={item.icon} onClick={(event) => onClick(event, item.id)}>
{item.name}
</MenuItem>
);
};
interface OverflowMenuProps {
items: OverflowMenuItemData[];
onItemSelect: (id: string) => void;
}
export const OverflowMenu: React.FC<OverflowMenuProps> = (props) => {
const { items, onItemSelect } = props;
const classes = useClasses();
const { ref, isOverflowing, overflowCount } = useOverflowMenu<HTMLButtonElement>();
const handleItemClick = (_event: React.MouseEvent, id: string) => {
onItemSelect(id);
};
if (!isOverflowing) {
return null;
}
return (
<Menu hasIcons={items.find((item) => item.icon !== undefined) !== undefined}>
<MenuTrigger disableButtonEnhancement>
<Button
className={classes.menuButton}
appearance="transparent"
ref={ref}
icon={<MoreHorizontalRegular />}
aria-label={`${overflowCount} more options`}
role="tab"
/>
</MenuTrigger>
<MenuPopover>
<MenuList className={classes.menu}>
{items.map((item) => (
<OverflowMenuItem key={item.id} item={item} onClick={handleItemClick}></OverflowMenuItem>
))}
</MenuList>
</MenuPopover>
</Menu>
);
};
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/common/routines/consolidate.py:
--------------------------------------------------------------------------------
```python
from typing import Any, Optional, cast
from openai_client import (
CompletionError,
create_system_message,
create_user_message,
extra_data,
make_completion_args_serializable,
message_content_from_completion,
validate_completion,
)
from skill_library import AskUserFn, EmitFn, RunContext, RunRoutineFn
from skill_library.logging import logger
from skill_library.skills.common import CommonSkill
DEFAULT_MAX_LENGTH = 10000
async def main(
context: RunContext,
routine_state: dict[str, Any],
emit: EmitFn,
run: RunRoutineFn,
ask_user: AskUserFn,
content: str,
max_length: Optional[int] = DEFAULT_MAX_LENGTH,
) -> str:
"""
Consolidate various pieces of content into a cohesive whole.
"""
common_skill = cast(CommonSkill, context.skills["common"])
language_model = common_skill.config.language_model
system_message = "Consolide the content provided by the user into a cohesive whole. Try not to lose any information, but reorder and deduplicate as necessary and give it all a singular tone. Just respond with your consolidated content."
completion_args = {
"model": "gpt-4o",
"messages": [
create_system_message(system_message),
create_user_message(content),
],
"max_tokens": max_length,
}
logger.debug("Completion call.", extra=extra_data(make_completion_args_serializable(completion_args)))
metadata = {}
metadata["completion_args"] = make_completion_args_serializable(completion_args)
try:
completion = await language_model.beta.chat.completions.parse(
**completion_args,
)
validate_completion(completion)
logger.debug("Completion response.", extra=extra_data({"completion": completion.model_dump()}))
metadata["completion"] = completion.model_dump()
except Exception as e:
completion_error = CompletionError(e)
metadata["completion_error"] = completion_error.message
logger.error(
completion_error.message,
extra=extra_data({"completion_error": completion_error.body, "metadata": context.metadata_log}),
)
raise completion_error from e
else:
consolidation = message_content_from_completion(completion)
metadata["consolidation"] = consolidation
return consolidation
finally:
context.log("consolidated", metadata)
```
--------------------------------------------------------------------------------
/libraries/python/openai-client/openai_client/client.py:
--------------------------------------------------------------------------------
```python
from azure.identity import DefaultAzureCredential, get_bearer_token_provider
from openai import AsyncAzureOpenAI, AsyncOpenAI
from openai.lib.azure import AsyncAzureADTokenProvider
from .config import (
AzureOpenAIApiKeyAuthConfig,
AzureOpenAIAzureIdentityAuthConfig,
AzureOpenAIServiceConfig,
OpenAIServiceConfig,
ServiceConfig,
)
def create_client(service_config: ServiceConfig, *, api_version: str = "2024-12-01-preview") -> AsyncOpenAI:
"""
Creates an AsyncOpenAI client based on the provided service configuration.
"""
match service_config:
case AzureOpenAIServiceConfig():
match service_config.auth_config:
case AzureOpenAIApiKeyAuthConfig():
return AsyncAzureOpenAI(
api_key=service_config.auth_config.azure_openai_api_key,
azure_deployment=service_config.azure_openai_deployment,
azure_endpoint=str(service_config.azure_openai_endpoint),
api_version=api_version,
)
case AzureOpenAIAzureIdentityAuthConfig():
return AsyncAzureOpenAI(
azure_ad_token_provider=_get_azure_bearer_token_provider(),
azure_deployment=service_config.azure_openai_deployment,
azure_endpoint=str(service_config.azure_openai_endpoint),
api_version=api_version,
)
case _:
raise ValueError(f"Invalid auth method type: {type(service_config.auth_config)}")
case OpenAIServiceConfig():
return AsyncOpenAI(
api_key=service_config.openai_api_key,
organization=service_config.openai_organization_id or None,
)
case _:
raise ValueError(f"Invalid service config type: {type(service_config)}")
_lazy_initialized_azure_bearer_token_provider = None
def _get_azure_bearer_token_provider() -> AsyncAzureADTokenProvider:
global _lazy_initialized_azure_bearer_token_provider
if _lazy_initialized_azure_bearer_token_provider is None:
_lazy_initialized_azure_bearer_token_provider = get_bearer_token_provider(
DefaultAzureCredential(),
"https://cognitiveservices.azure.com/.default",
)
return _lazy_initialized_azure_bearer_token_provider
```
--------------------------------------------------------------------------------
/docs/SETUP_DEV_ENVIRONMENT.md:
--------------------------------------------------------------------------------
```markdown
# Semantic Workbench Setup Guide
This document covers the common setup information for the Semantic Workbench.
# Codespaces
We recommend using [GitHub Codespaces for developing with the Semantic Workbench](../.devcontainer/README.md). This will provide a pre-configured environment with all development tools already installed.
# Local Development
## Prerequisites
Recommended installers:
- Linux: apt or your distribution's package manager
- macOS: [brew](https://brew.sh/)
- Windows: [winget](https://learn.microsoft.com/en-us/windows/package-manager/winget/)
## Development tools
The backend service for the Semantic Workbench is written in Python.
The frontend for the Semantic Workbench is written in Typescript.
The core dependencies you need to install are:
- `make` - for scripting installation steps of the various projects within this repo
- `uv` - for managing installed versions of `python` - for installing python dependencies
- `nvm` - for managing installed versions of `node`
- `pnpm` - for installing node dependencies
Linux:
# make is installed by default on linux
sudo apt update && sudo apt install pipx
pipx ensurepath
pipx install uv
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.40.1/install.sh | bash
nvm install 20 lts
nvm use 20
npm install -g pnpm
macOS:
brew install make
brew install uv
brew install nvm
nvm install 20 lts
nvm use 20
npm install -g pnpm
Windows:
winget install ezwinports.make -e
winget install astral-sh.uv -e
winget install CoreyButler.NVMforWindows -e
On Windows, exit and restart the VSCode and/or terminal you installed from to re-load your environment
variables and ensure the newly installed apps are available on your PATH.
Windows continued:
nvm install 20 lts
nvm use 20
npm install -g pnpm
If you haven't already, enable long file paths on Windows.
- Run `regedit`.
- Navigate to `HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\FileSystem`.
- Find the `LongPathsEnabled` key. If it doesn’t exist, right-click on the `FileSystem` key, select `New > DWORD (32-bit) Value`, and name it `LongPathsEnabled`.
- Double-click on `LongPathsEnabled`, set its value to `1`, and click OK.
# Install and run the backend
See [workbench-service/README.md](../workbench-service/README.md)
# Install and run the frontend
See [workbench-app/README.md](../workbench-app/README.md)
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/to_flashcards/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You are a professional Anki card creator, able to create Anki cards from texts.
# INSTRUCTIONS
When creating Anki cards, stick to three principles:
1. Minimum information principle. The material you learn must be formulated in as simple way as it is only possible. Simplicity does not have to imply losing information and skipping the difficult part.
2. Optimize wording: The wording of your items must be optimized to make sure that in minimum time the right bulb in your brain lights
up. This will reduce error rates, increase specificity, reduce response time, and help your concentration.
3. No external context: The wording of your items must not include words such as "according to the text". This will make the cards
usable even to those who haven't read the original text.
# EXAMPLE
The following is a model card-create template for you to study.
Text: The characteristics of the Dead Sea: Salt lake located on the border between Israel and Jordan. Its shoreline is the lowest point on the Earth's surface, averaging 396 m below sea level. It is 74 km long. It is seven times as salty (30% by volume) as the ocean. Its density keeps swimmers afloat. Only simple organisms can live in its saline waters
Create cards based on the above text as follows:
Q: Where is the Dead Sea located? A: on the border between Israel and Jordan
Q: What is the lowest point on the Earth's surface? A: The Dead Sea shoreline
Q: What is the average level on which the Dead Sea is located? A: 400 meters (below sea level)
Q: How long is the Dead Sea? A: 70 km
Q: How much saltier is the Dead Sea as compared with the oceans? A: 7 times
Q: What is the volume content of salt in the Dead Sea? A: 30%
Q: Why can the Dead Sea keep swimmers afloat? A: due to high salt content
Q: Why is the Dead Sea called Dead? A: because only simple organisms can live in it
Q: Why only simple organisms can live in the Dead Sea? A: because of high salt content
# STEPS
- Extract main points from the text
- Formulate questions according to the above rules and examples
- Present questions and answers in the form of a Markdown table
# OUTPUT INSTRUCTIONS
- Output the cards you create as a CSV table. Put the question in the first column, and the answer in the second. Don't include the CSV
header.
- Do not output warnings or notes—just the requested sections.
- Do not output backticks: just raw CSV data.
# INPUT:
INPUT:
```
--------------------------------------------------------------------------------
/mcp-servers/mcp-server-fusion/mcp_server_fusion/fusion_utils/general_utils.py:
--------------------------------------------------------------------------------
```python
# Copyright 2022 by Autodesk, Inc.
# Permission to use, copy, modify, and distribute this software in object code form
# for any purpose and without fee is hereby granted, provided that the above copyright
# notice appears in all copies and that both that copyright notice and the limited
# warranty and restricted rights notice below appear in all supporting documentation.
#
# AUTODESK PROVIDES THIS PROGRAM "AS IS" AND WITH ALL FAULTS. AUTODESK SPECIFICALLY
# DISCLAIMS ANY IMPLIED WARRANTY OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR USE.
# AUTODESK, INC. DOES NOT WARRANT THAT THE OPERATION OF THE PROGRAM WILL BE
# UNINTERRUPTED OR ERROR FREE.
# import os
import traceback
import adsk.core
app = adsk.core.Application.get()
ui = app.userInterface
# Attempt to read DEBUG flag from parent config.
try:
from ... import config
DEBUG = config.DEBUG
except Exception:
DEBUG = False
def log(message: str, level: adsk.core.LogLevels = adsk.core.LogLevels.InfoLogLevel, force_console: bool = False):
"""Utility function to easily handle logging in your app.
Arguments:
message -- The message to log.
level -- The logging severity level.
force_console -- Forces the message to be written to the Text Command window.
"""
# Always print to console, only seen through IDE.
print(message)
# Log all errors to Fusion log file.
if level == adsk.core.LogLevels.ErrorLogLevel:
log_type = adsk.core.LogTypes.FileLogType
app.log(message, level, log_type)
# If config.DEBUG is True write all log messages to the console.
if DEBUG or force_console:
log_type = adsk.core.LogTypes.ConsoleLogType
app.log(message, level, log_type)
def handle_error(name: str, show_message_box: bool = False):
"""Utility function to simplify error handling.
Arguments:
name -- A name used to label the error.
show_message_box -- Indicates if the error should be shown in the message box.
If False, it will only be shown in the Text Command window
and logged to the log file.
"""
log('===== Error =====', adsk.core.LogLevels.ErrorLogLevel)
log(f'{name}\n{traceback.format_exc()}', adsk.core.LogLevels.ErrorLogLevel)
# If desired you could show an error as a message box.
if show_message_box:
ui.messageBox(f'{name}\n{traceback.format_exc()}')
```
--------------------------------------------------------------------------------
/assistants/project-assistant/assistant/domain/conversation_preferences_manager.py:
--------------------------------------------------------------------------------
```python
from semantic_workbench_assistant.assistant_app import ConversationContext
from assistant.config import assistant_config
from assistant.data import ConversationPreferences, ConversationRole, InspectorTab
from assistant.domain.share_manager import ShareManager
from assistant.notifications import Notifications
from assistant.storage import ConversationStorage
class ConversationPreferencesManager:
@staticmethod
async def update_preferred_communication_style(
context: ConversationContext,
preferred_communication_style: str,
) -> None:
"""
Update the preferences for a conversation.
"""
preferences = ConversationStorage.read_conversation_preferences(context)
# Set the default preferences based on the assistant config.
if not preferences:
config = await assistant_config.get(context.assistant)
role = await ShareManager.get_conversation_role(context)
if role == ConversationRole.COORDINATOR:
style = config.coordinator_config.preferred_communication_style
else:
style = config.team_config.preferred_communication_style
preferences = ConversationPreferences(
preferred_communication_style=style,
)
preferences.preferred_communication_style = preferred_communication_style.strip()
ConversationStorage.write_conversation_preferences(context, preferences)
await Notifications.notify(context, "Preferred communication style updated.")
await Notifications.notify_all_state_update(context, [InspectorTab.DEBUG])
@staticmethod
async def get_preferred_communication_style(context: ConversationContext) -> str:
"""
Get the preferred communication style for a conversation.
"""
preferences = ConversationStorage.read_conversation_preferences(context)
if preferences and preferences.preferred_communication_style:
return preferences.preferred_communication_style
# Return the default from the assistant config if not set.
config = await assistant_config.get(context.assistant)
role = await ShareManager.get_conversation_role(context)
if role == ConversationRole.COORDINATOR:
return config.coordinator_config.preferred_communication_style
else:
return config.team_config.preferred_communication_style
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/routines/run.py:
--------------------------------------------------------------------------------
```python
from pathlib import Path
from typing import Any, cast
from events import MessageEvent
from openai.types.chat import ChatCompletionMessageParam
from openai_client import (
CompletionError,
create_system_message,
create_user_message,
extra_data,
make_completion_args_serializable,
message_content_from_completion,
validate_completion,
)
from skill_library import AskUserFn, EmitFn, RunContext, RunRoutineFn
from skill_library.logging import logger
from skill_library.skills.common import CommonSkill
async def main(
context: RunContext,
routine_state: dict[str, Any],
emit: EmitFn,
run: RunRoutineFn,
ask_user: AskUserFn,
pattern: str,
input: str | None = None,
) -> str:
"""Run a fabric pattern."""
common_skill = cast(CommonSkill, context.skills["common"])
language_model = common_skill.config.language_model
pattern_file = Path(__file__).parent.parent / "patterns" / pattern / "system.md"
if not pattern_file.exists():
emit(MessageEvent(message=f"Pattern {pattern} not found."))
return f"Pattern {pattern} not found."
with open(pattern_file, "r") as f:
pattern = f.read()
messages: list[ChatCompletionMessageParam] = [
create_system_message(
pattern,
)
]
if input:
messages.append(create_user_message(input))
completion_args = {
"model": "gpt-4o",
"messages": messages,
}
metadata = {}
logger.debug("Completion call.", extra=extra_data(make_completion_args_serializable(completion_args)))
metadata["completion_args"] = make_completion_args_serializable(completion_args)
try:
completion = await language_model.beta.chat.completions.parse(
**completion_args,
)
validate_completion(completion)
logger.debug("Completion response.", extra=extra_data({"completion": completion.model_dump()}))
metadata["completion"] = completion.model_dump()
except Exception as e:
completion_error = CompletionError(e)
metadata["completion_error"] = completion_error.message
logger.error(
completion_error.message,
extra=extra_data({"completion_error": completion_error.body, "metadata": metadata}),
)
raise completion_error from e
else:
context.log("gpt_complete", metadata=metadata)
return message_content_from_completion(completion)
```
--------------------------------------------------------------------------------
/libraries/python/openai-client/tests/test_command_parsing.py:
--------------------------------------------------------------------------------
```python
from typing import Any, Callable
import pytest
from openai_client.tools import ToolFunctions
def no_op() -> None:
pass
def echo(value: Any) -> str:
match value:
case str():
return value
case list():
return ", ".join(map(str, value))
case dict():
return ", ".join(f"{k}: {v}" for k, v in value.items())
case int() | bool() | float():
return str(value)
case _:
return str(value)
# Create tool functions.
functions = [echo, no_op]
tf = ToolFunctions()
for func in functions:
tf.add_function(func)
@pytest.mark.parametrize(
"command_string, expected_command, expected_args, expected_kwargs, expected_error",
[
# Simplest case.
("no_op()", "no_op", [], {}, None),
# Args.
('/echo("Hello!")', "echo", ["Hello!"], {}, None),
("/echo(42)", "echo", [42], {}, None),
("/echo(42.0)", "echo", [42.0], {}, None),
("/echo(True)", "echo", [True], {}, None),
("/echo([1, 2, 3])", "echo", [[1, 2, 3]], {}, None),
('/echo({"a": 1, "b": 2})', "echo", [{"a": 1, "b": 2}], {}, None),
# Keyword args.
('/echo(value="Hello!")', "echo", [], {"value": "Hello!"}, None),
("/echo(value=42)", "echo", [], {"value": 42}, None),
("/echo(value=42.0)", "echo", [], {"value": 42.0}, None),
("/echo(value=True)", "echo", [], {"value": True}, None),
("/echo(value=[1, 2, 3])", "echo", [], {"value": [1, 2, 3]}, None),
('/echo(value={"a": 1, "b": 2})', "echo", [], {"value": {"a": 1, "b": 2}}, None),
# No cmd prefix.
('echo("Hello!")', "echo", ["Hello!"], {}, None),
# Unregistered command.
('unregistered("Hello!")', None, [], {}, None),
# Invalid args.
("/echo(Hello!)", None, [], {}, ValueError),
],
)
def test_command_parsing_pythonic(
command_string: str,
expected_command: Callable,
expected_args: list[Any],
expected_kwargs: dict[str, Any],
expected_error: Any,
):
try:
command, args, kwargs = tf.parse_function_string(command_string)
except Exception as e:
assert expected_error is not None
assert isinstance(e, expected_error)
return
if command is None:
assert expected_command is None
else:
assert command.name == expected_command
assert args == expected_args
assert kwargs == expected_kwargs
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/capture_thinkers_work/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You take a philosopher, professional, notable figure, thinker, writer, author, philosophers, or philosophy as input, and you output a template about what it/they taught.
Take a deep breath and think step-by-step how to do the following STEPS.
# STEPS
1. Look for the mention of a notable person, professional, thinker, writer, author, philosopher, philosophers, or philosophy in the input.
2. For each thinker, output the following template:
ONE-LINE ENCAPSULATION:
The philosopher's overall philosophy encapsulated in a 10-20 words.
BACKGROUND:
5 15-word word bullets on their background.
SCHOOL:
Give the one-two word formal school of philosophy or thinking they fall under, along with a 20-30 word description of that school of philosophy/thinking.
MOST IMPACTFUL IDEAS:
5 15-word bullets on their teachings, starting from most important to least important.
THEIR PRIMARY ADVICE/TEACHINGS:
5 20-30 word bullets on their teachings, starting from most important to least important.
WORKS:
5 15-word bullets on their most popular works and what they were about.
QUOTES:
5 of their most insightful quotes.
APPLICATION:
Describe in 30 words what it means to have something be $philosopher-ian, e.g., Socratic for Socrates, Hegelian for Hegel. Etc.
In other words if the name of the philosopher is Hitchens, the output would be something like,
Something is Hitchensian if it is like…(continued)
ADVICE:
5 20-30 word bullets on how to live life.
3. For each philosophy output the following template:
BACKGROUND:
5 20-30 word bullets on the philosophy's background.
ONE-LINE ENCAPSULATION:
The philosophy's overall philosophy encapsulated in a 10-20 words.
OPPOSING SCHOOLS:
Give 3 20-30 word bullets on opposing philosophies and what they believe that's different from the philosophy provided.
TEACHINGS:
5 20-30 word bullets on the philosophy's teachings, starting from most important to least important.
MOST PROMINENT REPRESENTATIVES:
5 of the philosophy's most prominent representatives.
QUOTES:
5 of the philosophy's most insightful quotes.
APPLICATION:
Describe in 30 words what it means to have something be $philosophian, e.g., Rationalist, Empiricist, etc.
In other words if the name of the philosophy is Rationalism, the output would be something like,
An idea is Rationalist if it is like…(continued)
ADVICE:
5 20-30 word bullets on how to live life according to that philosophy.
# INPUT:
INPUT:
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/rate_ai_response/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY
You are an expert at rating the quality of AI responses and determining how good they are compared to ultra-qualified humans performing the same tasks.
# STEPS
- Fully and deeply process and understand the instructions that were given to the AI. These instructions will come after the #AI INSTRUCTIONS section below.
- Fully and deeply process the response that came back from the AI. You are looking for how good that response is compared to how well the best human expert in the world would do on that task if given the same input and 3 months to work on it.
- Give a rating of the AI's output quality using the following framework:
- A+: As good as the best human expert in the world
- A: As good as a top 1% human expert
- A-: As good as a top 10% human expert
- B+: As good as an untrained human with a 115 IQ
- B: As good as an average intelligence untrained human
- B-: As good as an average human in a rush
- C: Worse than a human but pretty good
- D: Nowhere near as good as a human
- F: Not useful at all
- Give 5 15-word bullets about why they received that letter grade, comparing and contrasting what you would have expected from the best human in the world vs. what was delivered.
- Give a 1-100 score of the AI's output.
- Give an explanation of how you arrived at that score using the bullet point explanation and the grade given above.
# OUTPUT
- In a section called LETTER GRADE, give the letter grade score. E.g.:
LETTER GRADE
A: As good as a top 1% human expert
- In a section called LETTER GRADE REASONS, give your explanation of why you gave that grade in 5 bullets. E.g.:
(for a B+ grade)
- The points of analysis were good but almost anyone could create them
- A human with a couple of hours could have come up with that output
- The education and IQ requirement required for a human to make this would have been roughly 10th grade level
- A 10th grader could have done this quality of work in less than 2 hours
- There were several deeper points about the input that was not captured in the output
- In a section called OUTPUT SCORE, give the 1-100 score for the output, with 100 being at the quality of the best human expert in the world working on that output full-time for 3 months.
# OUTPUT INSTRUCTIONS
- Output in valid Markdown only.
- DO NOT complain about anything, including copyright; just do it.
# INPUT INSTRUCTIONS
(the input below will be the instructions to the AI followed by the AI's output)
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/extract_patterns/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You take a collection of ideas or data or observations and you look for the most interesting and surprising patterns. These are like where the same idea or observation kept coming up over and over again.
Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
# STEPS
- Think deeply about all the input and the core concepts contained within.
- Extract 20 to 50 of the most surprising, insightful, and/or interesting pattern observed from the input into a section called PATTERNS.
- Weight the patterns by how often they were mentioned or showed up in the data, combined with how surprising, insightful, and/or interesting they are. But most importantly how often they showed up in the data.
- Each pattern should be captured as a bullet point of no more than 16 words.
- In a new section called META, talk through the process of how you assembled each pattern, where you got the pattern from, how many components of the input lead to each pattern, and other interesting data about the patterns.
- Give the names or sources of the different people or sources that combined to form a pattern. For example: "The same idea was mentioned by both John and Jane."
- Each META point should be captured as a bullet point of no more than 16 words.
- Add a section called ANALYSIS that gives a one sentence, 30-word summary of all the patterns and your analysis thereof.
- Add a section called BEST 5 that gives the best 5 patterns in a list of 30-word bullets. Each bullet should describe the pattern itself and why it made the top 5 list, using evidence from the input as its justification.
- Add a section called ADVICE FOR BUILDERS that gives a set of 15-word bullets of advice for people in a startup space related to the input. For example if a builder was creating a company in this space, what should they do based on the PATTERNS and ANALYSIS above?
# OUTPUT INSTRUCTIONS
- Only output Markdown.
- Extract at least 20 PATTERNS from the content.
- Limit each idea bullet to a maximum of 16 words.
- Write in the style of someone giving helpful analysis finding patterns
- Do not give warnings or notes; only output the requested sections.
- You use bulleted lists for output, not numbered lists.
- Do not repeat ideas, quotes, facts, or resources.
- Do not start items with the same opening words.
- Ensure you follow ALL these instructions when creating your output.
# INPUT
INPUT:
```
--------------------------------------------------------------------------------
/workbench-app/src/components/App/AppView.tsx:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import { makeStyles, mergeClasses, shorthands, tokens } from '@fluentui/react-components';
import React from 'react';
import { useNavigate } from 'react-router-dom';
import { Constants } from '../../Constants';
import { useAppSelector } from '../../redux/app/hooks';
import { AppFooter } from './AppFooter';
import { AppHeader } from './AppHeader';
const useClasses = makeStyles({
documentBody: {
// backgroundImage: `url('/assets/background-1.jpg')`,
backgroundImage: `linear-gradient(to right, #FFFFFF, #E6EEFF)`,
},
root: {
display: 'grid',
gridTemplateRows: 'auto 1fr auto',
height: '100vh',
},
content: {
overflowY: 'auto',
height: '100%',
display: 'flex',
flexDirection: 'column',
maxWidth: `${Constants.app.maxContentWidth}px`,
boxSizing: 'border-box',
width: '100%',
gap: tokens.spacingVerticalM,
...shorthands.margin('0', 'auto'),
...shorthands.padding(tokens.spacingVerticalM),
},
fullSize: {
...shorthands.padding(0),
maxWidth: '100%',
},
});
interface AppViewProps {
title: string | React.ReactNode;
actions?: {
items: React.ReactNode[];
replaceExisting?: boolean;
hideProfileSettings?: boolean;
};
fullSizeContent?: boolean;
children?: React.ReactNode;
}
export const AppView: React.FC<AppViewProps> = (props) => {
const { title, actions, fullSizeContent, children } = props;
const classes = useClasses();
const completedFirstRun = useAppSelector((state) => state.app.completedFirstRun);
const navigate = useNavigate();
React.useLayoutEffect(() => {
document.body.className = classes.documentBody;
return () => {
document.body.className = '';
};
}, [classes.documentBody]);
React.useEffect(() => {
if (!completedFirstRun?.app && window.location.pathname !== '/terms') {
navigate('/terms', { state: { redirectTo: window.location.pathname } });
}
}, [completedFirstRun, navigate]);
return (
<div id="app" className={classes.root}>
<AppHeader title={title} actions={actions} />
<div className={fullSizeContent ? mergeClasses(classes.content, classes.fullSize) : classes.content}>
{children}
</div>
<AppFooter />
</div>
);
};
```
--------------------------------------------------------------------------------
/workbench-service/semantic_workbench_service/config.py:
--------------------------------------------------------------------------------
```python
from typing import Annotated
from pydantic import Field, HttpUrl
from pydantic_settings import BaseSettings, SettingsConfigDict
from .files import StorageSettings
from .logging_config import LoggingSettings
class DBSettings(BaseSettings):
url: str = "sqlite:///.data/workbench.db"
echosql: bool = False
postgresql_ssl_mode: str = "require"
postgresql_pool_size: int = 10
alembic_config_path: str = "./alembic.ini"
class ApiKeySettings(BaseSettings):
key_vault_url: HttpUrl | None = None
@property
def is_secured(self) -> bool:
return self.key_vault_url is not None
class AuthSettings(BaseSettings):
allowed_jwt_algorithms: set[str] = {"RS256"}
allowed_app_id: str = "d0a2fed8-abb0-4831-8a24-09f5a0b54d97"
class AssistantIdentifiers(BaseSettings):
assistant_service_id: str
template_id: str
name: str
class WebServiceSettings(BaseSettings):
protocol: str = "http"
host: str = "127.0.0.1"
port: int = 3000
assistant_api_key: ApiKeySettings = ApiKeySettings()
anonymous_paths: list[str] = ["/", "/docs", "/openapi.json"]
assistant_service_online_check_interval_seconds: float = 10.0
azure_openai_endpoint: Annotated[str, Field(validation_alias="azure_openai_endpoint")] = ""
azure_openai_deployment: Annotated[str, Field(validation_alias="azure_openai_deployment")] = "gpt-4o-mini"
azure_openai_model: Annotated[str, Field(validation_alias="azure_openai_model")] = "gpt-4o-mini"
azure_openai_api_version: Annotated[str, Field(validation_alias="azure_openai_api_version")] = "2025-02-01-preview"
default_assistants: list[AssistantIdentifiers] = []
class AzureSpeechSettings(BaseSettings):
model_config = SettingsConfigDict(
env_prefix="azure_speech__", env_nested_delimiter="_", env_file=".env", extra="allow"
)
resource_id: str = ""
region: str = ""
class Settings(BaseSettings):
model_config = SettingsConfigDict(
env_prefix="workbench__", env_nested_delimiter="__", env_file=".env", extra="allow"
)
db: DBSettings = DBSettings()
storage: StorageSettings = StorageSettings()
logging: LoggingSettings = LoggingSettings()
service: WebServiceSettings = WebServiceSettings()
azure_speech: AzureSpeechSettings = AzureSpeechSettings()
auth: AuthSettings = AuthSettings()
if __name__ == "__main__":
# for verifying environment variables are having the expected effect
settings = Settings()
print(settings.model_dump())
```
--------------------------------------------------------------------------------
/workbench-app/src/components/Assistants/AssistantServiceMetadata.tsx:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import { Label, Text, makeStyles, tokens } from '@fluentui/react-components';
import React from 'react';
import { AssistantServiceRegistration } from '../../models/AssistantServiceRegistration';
import { useGetAssistantServiceRegistrationsQuery } from '../../services/workbench';
const useClasses = makeStyles({
root: {
display: 'flex',
flexDirection: 'column',
gap: tokens.spacingVerticalM,
},
data: {
display: 'flex',
flexDirection: 'column',
gap: tokens.spacingVerticalS,
},
});
interface AssistantServiceMetadataProps {
assistantServiceId: string;
}
export const AssistantServiceMetadata: React.FC<AssistantServiceMetadataProps> = (props) => {
const { assistantServiceId } = props;
const classes = useClasses();
const {
data: assistantServices,
isLoading: isAssistantServicesLoading,
isError: getAssistantServicesError,
} = useGetAssistantServiceRegistrationsQuery({});
if (getAssistantServicesError) {
const errorMessage = JSON.stringify(getAssistantServicesError);
throw new Error(`Error loading assistant services: ${errorMessage}`);
}
const [assistantService, setAssistantService] = React.useState<AssistantServiceRegistration | undefined>(undefined);
React.useEffect(() => {
const service = assistantServices?.find((service) => service.assistantServiceId === assistantServiceId);
if (service) {
setAssistantService(service);
}
}, [assistantServiceId, assistantServices, setAssistantService]);
if (isAssistantServicesLoading) return null;
if (!assistantService) return null;
return (
<div className={classes.root}>
<Text size={400} weight="semibold">
Assistant Backend Service
</Text>
<div className={classes.data}>
<Label weight="semibold">{assistantService.name}</Label>
<Label>
<em>{assistantService.description}</em>
</Label>
<Label size="small">Assistant service ID: {assistantService.assistantServiceId}</Label>
<Label size="small">Hosted at: {assistantService.assistantServiceUrl}</Label>
<Label size="small">
Created by: {assistantService.createdByUserName} [{assistantService.createdByUserId}]
</Label>
</div>
</div>
);
};
```
--------------------------------------------------------------------------------
/workbench-app/src/libs/useMicrosoftGraph.ts:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import { InteractionRequiredAuthError } from '@azure/msal-browser';
import { useMsal } from '@azure/msal-react';
import { Client, ResponseType } from '@microsoft/microsoft-graph-client';
import React from 'react';
import { AuthHelper } from './AuthHelper';
export const useMicrosoftGraph = () => {
const msal = useMsal();
const getClientAsync = React.useCallback(async (): Promise<Client> => {
const account = msal.instance.getActiveAccount();
if (!account) {
throw new Error('No active account');
}
const response = await msal.instance
.acquireTokenSilent({
...AuthHelper.loginRequest,
account,
})
.catch(async (error) => {
if (error instanceof InteractionRequiredAuthError) {
return await AuthHelper.loginAsync(msal.instance);
}
throw error;
});
if (!response) {
throw new Error('error acquiring access token');
}
return Client.init({
authProvider: (done) => {
done(null, response.accessToken);
},
});
}, [msal]);
const getAsync = React.useCallback(
async <T>(url: string): Promise<T> => {
const client = await getClientAsync();
return (await client.api(url).get()) as T;
},
[getClientAsync],
);
const blobToBase64Async = React.useCallback(async (blob: Blob): Promise<string> => {
return await new Promise((resolve, reject) => {
const reader = new FileReader();
reader.onerror = reject;
reader.onload = () => {
resolve(reader.result as string);
};
reader.readAsDataURL(blob);
});
}, []);
const getPhotoAsync = React.useCallback(
async (url: string): Promise<string> => {
const client = await getClientAsync();
const response = (await client.api(url).responseType(ResponseType.RAW).get()) as Response;
const blob = await response.blob();
return await blobToBase64Async(blob);
},
[blobToBase64Async, getClientAsync],
);
const getMyPhotoAsync = React.useCallback(async (): Promise<string> => {
return await getPhotoAsync('/me/photo/$value');
}, [getPhotoAsync]);
return {
getAsync,
getMyPhotoAsync,
};
};
```
--------------------------------------------------------------------------------
/workbench-app/src/components/Conversations/ConversationExport.tsx:
--------------------------------------------------------------------------------
```typescript
// Copyright (c) Microsoft. All rights reserved.
import { ProgressBar } from '@fluentui/react-components';
import React from 'react';
import { useExportUtility } from '../../libs/useExportUtility';
import { useNotify } from '../../libs/useNotify';
import { Utility } from '../../libs/Utility';
import { ContentExport } from '../App/ContentExport';
import { DialogControl } from '../App/DialogControl';
interface ConversationExportWithStatusDialogProps {
conversationId?: string;
onExport: (id: string) => Promise<void>;
}
export const ConversationExportWithStatusDialog: React.FC<ConversationExportWithStatusDialogProps> = (props) => {
const { conversationId, onExport } = props;
const { exportConversation } = useExportUtility();
const { notifyWarning } = useNotify();
const [submitted, setSubmitted] = React.useState(false);
const handleError = React.useCallback(
(error: Error) => {
notifyWarning({
id: 'error',
title: 'Export conversation failed',
message: error.message,
});
},
[notifyWarning],
);
React.useEffect(() => {
if (!conversationId) {
return;
}
(async () => {
try {
await Utility.withStatus(setSubmitted, async () => {
await exportConversation(conversationId);
await onExport(conversationId);
});
} catch (error) {
handleError(error as Error);
}
})();
}, [conversationId, exportConversation, handleError, notifyWarning, onExport]);
return (
<DialogControl
open={submitted}
title="Exporting Conversation"
hideDismissButton
content={
<p>
<ProgressBar />
</p>
}
/>
);
};
interface ConversationExportProps {
conversationId: string;
iconOnly?: boolean;
asToolbarButton?: boolean;
}
export const ConversationExport: React.FC<ConversationExportProps> = (props) => {
const { conversationId, iconOnly, asToolbarButton } = props;
const { exportConversationFunction } = useExportUtility();
return (
<ContentExport
id={conversationId}
contentTypeLabel="conversation"
exportFunction={exportConversationFunction}
iconOnly={iconOnly}
asToolbarButton={asToolbarButton}
/>
);
};
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/improve_report_finding/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You are a extremely experienced 'jack-of-all-trades' cyber security consultant that is diligent, concise but informative and professional. You are highly experienced in web, API, infrastructure (on-premise and cloud), and mobile testing. Additionally, you are an expert in threat modeling and analysis.
You have been tasked with improving a security finding that has been pulled from a penetration test report, and you must output an improved report finding in markdown format.
Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
# STEPS
- Create a Title section that contains the title of the finding.
- Create a Description section that details the nature of the finding, including insightful and informative information. Do not solely use bullet point lists for this section.
- Create a Risk section that details the risk of the finding. Do not solely use bullet point lists for this section.
- Extract the 5 to 15 of the most surprising, insightful, and/or interesting recommendations that can be collected from the report into a section called Recommendations.
- Create a References section that lists 1 to 5 references that are suitibly named hyperlinks that provide instant access to knowledgeable and informative articles that talk about the issue, the tech and remediations. Do not hallucinate or act confident if you are unsure.
- Create a summary sentence that captures the spirit of the finding and its insights in less than 25 words in a section called One-Sentence-Summary:. Use plain and conversational language when creating this summary. Don't use jargon or marketing language.
- Extract 10 to 20 of the most surprising, insightful, and/or interesting quotes from the input into a section called Quotes:. Favour text from the Description, Risk, Recommendations, and Trends sections. Use the exact quote text from the input.
# OUTPUT INSTRUCTIONS
- Only output Markdown.
- Do not output the markdown code syntax, only the content.
- Do not use bold or italics formatting in the markdown output.
- Extract at least 5 TRENDS from the content.
- Extract at least 10 items for the other output sections.
- Do not give warnings or notes; only output the requested sections.
- You use bulleted lists for output, not numbered lists.
- Do not repeat ideas, quotes, facts, or resources.
- Do not start items with the same opening words.
- Ensure you follow ALL these instructions when creating your output.
# INPUT
INPUT:
```
--------------------------------------------------------------------------------
/workbench-app/src/libs/useDragAndDrop.ts:
--------------------------------------------------------------------------------
```typescript
import debug from 'debug';
import React from 'react';
const useDragAndDrop = (domElement?: HTMLElement | null, log?: debug.Debugger, ignoreFileDrop: boolean = false) => {
const [isDraggingOver, setIsDraggingOver] = React.useState(false);
React.useEffect(() => {
if (!domElement) {
// no-op if the dom element is not provided
// allowed so that the hook can be used with
// React.useRef()
return;
}
log?.('adding event listeners for drag and drop');
const handleDragEnter = (event: DragEvent) => {
event.preventDefault();
setIsDraggingOver(true);
};
const handleDragLeave = (event: DragEvent) => {
const relatedTarget = event.relatedTarget as HTMLElement;
const currentTarget = event.currentTarget as HTMLElement;
if (currentTarget.contains(relatedTarget)) {
// ignore the event if the drag is still within the target element
return;
}
setIsDraggingOver(false);
};
const handleDragOver = (event: DragEvent) => {
// needed to allow drop event to fire
event.preventDefault();
};
const handleDrop = (event: DragEvent) => {
// ignore file drop events at the document level, but only file types this
// prevents the undesirable behavior of the browser opening the file in the
// window if the drop event is not handled or the user misses the drop target
if (ignoreFileDrop && event.dataTransfer?.files.length) {
log?.('ignoring file drop event');
event.preventDefault();
}
setIsDraggingOver(false);
};
domElement.addEventListener('dragenter', handleDragEnter);
domElement.addEventListener('dragleave', handleDragLeave);
domElement.addEventListener('dragover', handleDragOver);
domElement.addEventListener('drop', handleDrop);
return () => {
log?.('removing event listeners for drag and drop');
domElement.removeEventListener('dragenter', handleDragEnter);
domElement.removeEventListener('dragleave', handleDragLeave);
domElement.removeEventListener('dragover', handleDragOver);
domElement.removeEventListener('drop', handleDrop);
};
}, [log, domElement, ignoreFileDrop]);
return isDraggingOver;
};
export default useDragAndDrop;
```
--------------------------------------------------------------------------------
/mcp-servers/mcp-server-filesystem-edit/mcp_server_filesystem_edit/evals/run_edit.py:
--------------------------------------------------------------------------------
```python
# Copyright (c) Microsoft. All rights reserved.
import asyncio
import logging
import os
from dotenv import load_dotenv
from mcp_extensions.llm.openai_chat_completion import openai_client
from rich.columns import Columns
from rich.console import Console
from rich.markdown import Markdown
from rich.panel import Panel
from mcp_server_filesystem_edit.evals.common import load_test_cases
from mcp_server_filesystem_edit.tools.edit import CommonEdit
from mcp_server_filesystem_edit.types import (
CustomContext,
EditOutput,
FileOpRequest,
)
logger = logging.getLogger(__name__)
load_dotenv(override=True)
def print_edit_output(
console: Console,
output: EditOutput,
test_index: int,
custom_context: CustomContext,
) -> None:
"""
Print the edit output to console using Rich formatting.
"""
console.rule(f"Test Case {test_index} Results. Latency: {output.llm_latency:.2f} seconds.", style="cyan")
console.print(
Panel(
custom_context.chat_history[-1].content, # type: ignore
title="User Request",
border_style="blue",
width=120,
)
)
original_doc = Panel(
Markdown(custom_context.document),
title="Original Document",
border_style="yellow",
width=90,
)
new_doc = Panel(
Markdown(output.new_content),
title="Edited Document",
border_style="green",
width=90,
)
console.print(Columns([original_doc, new_doc]))
console.print(
Panel(
output.change_summary or output.output_message,
title="Change Summary",
border_style="blue",
width=120,
)
)
console.print()
async def main() -> None:
console = Console()
custom_contexts = load_test_cases(test_case_type="writing")
client = openai_client(
api_type="azure_openai",
azure_endpoint=os.getenv("ASSISTANT__AZURE_OPENAI_ENDPOINT"),
aoai_api_version="2025-01-01-preview",
)
for i, custom_context in enumerate(custom_contexts):
edit_request = FileOpRequest(
context=custom_context,
file_type=custom_context.file_type,
request_type="dev",
chat_completion_client=client,
file_content=custom_context.document,
)
editor = CommonEdit()
output = await editor.run(edit_request)
print_edit_output(console, output, i + 1, custom_context)
if __name__ == "__main__":
asyncio.run(main())
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/analyze_sales_call/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY
You are an advanced AI specializing in rating sales call transcripts across a number of performance dimensions.
# GOALS
1. Determine how well the salesperson performed in the call across multiple dimensions.
2. Provide clear and actionable scores that can be used to assess a given call and salesperson.
3. Provide concise and actionable feedback to the salesperson based on the scores.
# BELIEFS AND APPROACH
- The approach is to understand everything about the business first so that we have proper context to evaluate the sales calls.
- It's not possible to have a good sales team, or sales associate, or sales call if the salesperson doesn't understand the business, it's vision, it's goals, it's products, and how those are relevant to the customer they're talking to.
# STEPS
1. Deeply understand the business from the SELLING COMPANY BUSINESS CONTEXT section of the input.
2. Analyze the sales call based on the provided transcript.
3. Analyze how well the sales person matched their pitch to the official pitch, mission, products, and vision of the company.
4. Rate the sales call across the following dimensions:
SALES FUNDAMENTALS (i.e., did they properly pitch the product, did they customize the pitch to the customer, did they handle objections well, did they close the sale or work towards the close, etc.)
PITCH ALIGNMENT (i.e., how closely they matched their conversation to the talking points and vision and products for the company vs. being general or nebulous or amorphous and meandering.
Give a 1-10 score for each dimension where 5 is meh, 7 is decent, 8 is good, 9 is great, and 10 is perfect. 4 and below are varying levels of bad.
# OUTPUT
- In a section called SALES CALL ANALYSIS OVERVIEW, give a 15-word summary of how good of a sales call this was, and why.
- In a section called CORE FAILURES, give a list of ways that the salesperson failed to properly align their pitch to the company's pitch and vision and/or use proper sales techniques to get the sale. E.g.:
- Didn't properly differentiate the product from competitors.
- Didn't have proper knowledge of and empathy for the customer.
- Made the product sound like everything else.
- Didn't push for the sale.
- Etc.
- (list as many as are relevant)
- In a section called SALES CALL PERFORMANCE RATINGS, give the 1-10 scores for SALES FUNDAMENTALS and PITCH ALIGNMENT.
- In a section called RECOMMENDATIONS, give a set of 10 15-word bullet points describing how this salesperson should improve their approach in the future.
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/guided_conversation/message.py:
--------------------------------------------------------------------------------
```python
from enum import StrEnum
from openai.types.chat import ChatCompletionMessageParam
from pydantic import BaseModel, Field
class ConversationMessageType(StrEnum):
DEFAULT = "default"
ARTIFACT_UPDATE = "artifact-update"
REASONING = "reasoning"
class Message(BaseModel):
param: ChatCompletionMessageParam
type: ConversationMessageType = Field(default=ConversationMessageType.DEFAULT)
turn: int | None = None
class Conversation(BaseModel):
messages: list[Message] = Field(default_factory=list)
turn: int = 0
def exclude(self, types: list[ConversationMessageType]) -> "Conversation":
return Conversation(
messages=[message for message in self.messages if message.type not in types], turn=self.turn
)
def __str__(self) -> str:
message_strs = []
current_turn = None
for message in self.messages:
# Modify the default user to be capitalized for consistency with how
# assistant is written.
name = message.param["role"]
if name == "user":
name = "User"
# Append the turn number if it has changed.
if message.turn is not None and current_turn != message.turn:
current_turn = message.turn
message_strs.append(f"[Turn {current_turn}]")
# Append the message content.
content = message.param.get("content", "")
if message.param["role"] == "assistant":
if message.type == ConversationMessageType.ARTIFACT_UPDATE:
message_strs.append(content)
else:
message_strs.append(f"Assistant: {content}")
else:
user_string = str(content).strip()
if user_string == "":
message_strs.append(f"{name}: <sent an empty message>")
else:
message_strs.append(f"{name}: {user_string}")
return "\n".join(message_strs)
def add_user_message(self, content: str) -> "Conversation":
self.messages.append(Message(param={"role": "user", "content": content}, turn=self.turn))
return self
def add_assistant_message(self, content: str) -> "Conversation":
self.turn += 1
self.messages.append(
Message(
param={
"role": "assistant",
"content": content,
},
turn=self.turn,
)
)
return self
```
--------------------------------------------------------------------------------
/libraries/python/skills/skill-library/skill_library/skills/fabric/patterns/create_pattern/system.md:
--------------------------------------------------------------------------------
```markdown
# IDENTITY and PURPOSE
You are an AI assistant whose primary responsibility is to interpret LLM/AI prompts and deliver responses based on pre-defined structures. You are a master of organization, meticulously analyzing each prompt to identify the specific instructions and any provided examples. You then utilize this knowledge to generate an output that precisely matches the requested structure. You are adept at understanding and following formatting instructions, ensuring that your responses are always accurate and perfectly aligned with the intended outcome.
Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
# STEPS
- Extract a summary of the role the AI will be taking to fulfil this pattern into a section called IDENTITY and PURPOSE.
- Extract a step by step set of instructions the AI will need to follow in order to complete this pattern into a section called STEPS.
- Analyze the prompt to determine what format the output should be in.
- Extract any specific instructions for how the output should be formatted into a section called OUTPUT INSTRUCTIONS.
- Extract any examples from the prompt into a subsection of OUTPUT INSTRUCTIONS called EXAMPLE.
# OUTPUT INSTRUCTIONS
- Only output Markdown.
- All sections should be Heading level 1
- Subsections should be one Heading level higher than it's parent section
- All bullets should have their own paragraph
- Write the IDENTITY and PURPOSE section including the summary of the role using personal pronouns such as 'You'. Be sure to be extremely detailed in explaining the role. Finalize this section with a new paragraph advising the AI to 'Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.'.
- Write the STEPS bullets from the prompt
- Write the OUTPUT INSTRUCTIONS bullets starting with the first bullet explaining the only output format. If no specific output was able to be determined from analyzing the prompt then the output should be markdown. There should be a final bullet of 'Ensure you follow ALL these instructions when creating your output.'. Outside of these two specific bullets in this section, any other bullets must have been extracted from the prompt.
- If an example was provided write the EXAMPLE subsection under the parent section of OUTPUT INSTRUCTIONS.
- Write a final INPUT section with just the value 'INPUT:' inside it.
- Ensure you follow ALL these instructions when creating your output.
# INPUT
INPUT:
```
--------------------------------------------------------------------------------
/libraries/python/openai-client/openai_client/chat_driver/message_history_providers/local_message_history_provider.py:
--------------------------------------------------------------------------------
```python
import json
from dataclasses import dataclass, field
from os import PathLike
from pathlib import Path
from typing import Any
from openai.types.chat import (
ChatCompletionMessageParam,
)
from openai_client.messages import MessageFormatter, format_with_liquid
from .message_history_provider import MessageHistoryProviderProtocol
DEFAULT_DATA_DIR = Path(".data")
@dataclass
class LocalMessageHistoryProviderConfig:
session_id: str
data_dir: PathLike | str | None = None
messages: list[ChatCompletionMessageParam] = field(default_factory=list)
formatter: MessageFormatter | None = None
class LocalMessageHistoryProvider(MessageHistoryProviderProtocol):
def __init__(self, config: LocalMessageHistoryProviderConfig) -> None:
if not config.data_dir:
self.data_dir = DEFAULT_DATA_DIR / "chat_driver" / config.session_id
else:
self.data_dir = Path(config.data_dir)
self.formatter = config.formatter or format_with_liquid
# Create the messages file if it doesn't exist.
if not self.data_dir.exists():
self.data_dir.mkdir(parents=True)
self.messages_file = self.data_dir / "messages.json"
if not self.messages_file.exists():
self.messages_file.write_text("[]")
async def get(self) -> list[ChatCompletionMessageParam]:
"""
Get all messages. This method is required for conforming to the
MessageFormatter protocol.
"""
return json.loads(self.messages_file.read_text())
async def append(self, message: ChatCompletionMessageParam) -> None:
"""
Append a message to the history. This method is required for conforming
to the MessageFormatter protocol.
"""
messages = await self.get()
messages.append(message)
self.messages_file.write_text(json.dumps(messages, indent=2))
async def extend(self, messages: list[ChatCompletionMessageParam]) -> None:
"""
Append a list of messages to the history.
"""
existing_messages = await self.get()
existing_messages.extend(messages)
self.messages_file.write_text(json.dumps(existing_messages, indent=2))
async def set(self, messages: list[ChatCompletionMessageParam], vars: dict[str, Any]) -> None:
"""
Completely replace the messages with the new messages.
"""
self.messages_file.write_text(json.dumps(messages, indent=2))
def delete_all(self) -> None:
self.messages_file.write_text("[]")
```
--------------------------------------------------------------------------------
/libraries/dotnet/WorkbenchConnector/Constants.cs:
--------------------------------------------------------------------------------
```csharp
// Copyright (c) Microsoft. All rights reserved.
using System.Net.Http;
namespace Microsoft.SemanticWorkbench.Connector;
public static class Constants
{
// Unique service ID
public const string HeaderServiceId = "X-Assistant-Service-ID";
// Agent ID
public const string HeaderAgentId = "X-Assistant-ID";
// HTTP methods
public static readonly HttpMethod[] HttpMethodsWithBody = [HttpMethod.Post, HttpMethod.Put, HttpMethod.Patch];
// Registering the multi-agent service into the workbench connector
public static class AgentServiceRegistration
{
public const string Placeholder = "{assistant_service_id}";
public const string Path = "/assistant-service-registrations/{assistant_service_id}";
}
// Sending a message into an existing conversation
public static class SendAgentMessage
{
public const string ConversationPlaceholder = "{conversation_id}";
public const string Path = "/conversations/{conversation_id}/messages";
}
// Sending a temporary status to show inline in a conversation, before sending a message
public static class SendAgentStatusMessage
{
public const string AgentPlaceholder = "{agent_id}";
public const string ConversationPlaceholder = "{conversation_id}";
public const string Path = "/conversations/{conversation_id}/participants/{agent_id}";
}
// Sending a notification about a state content change
public static class SendAgentConversationInsightsEvent
{
public const string AgentPlaceholder = "{agent_id}";
public const string ConversationPlaceholder = "{conversation_id}";
public const string Path = "/assistants/{agent_id}/states/events?conversation_id={conversation_id}";
}
// Get list of files
public static class GetConversationFiles
{
public const string ConversationPlaceholder = "{conversation_id}";
public const string Path = "/conversations/{conversation_id}/files";
}
// Download/Delete file
public static class ConversationFile
{
public const string ConversationPlaceholder = "{conversation_id}";
public const string FileNamePlaceholder = "{filename}";
public const string Path = "/conversations/{conversation_id}/files/{filename}";
}
// Upload file
public static class UploadConversationFile
{
public const string ConversationPlaceholder = "{conversation_id}";
public const string Path = "/conversations/{conversation_id}/files";
}
}
```
--------------------------------------------------------------------------------
/libraries/python/assistant-extensions/assistant_extensions/chat_context_toolkit/virtual_filesystem/_archive_file_source.py:
--------------------------------------------------------------------------------
```python
from typing import Iterable, cast
from chat_context_toolkit.virtual_filesystem import DirectoryEntry, FileEntry, MountPoint
from openai.types.chat import ChatCompletionMessageParam
from semantic_workbench_assistant.assistant_app import ConversationContext
from ..archive._archive import archive_reader_for
from ..archive._summarizer import convert_oai_messages_to_xml
class ArchiveFileSource:
def __init__(self, context: ConversationContext, archive_storage_sub_directory: str = "archives") -> None:
self._archive_reader = archive_reader_for(
context=context, archive_storage_sub_directory=archive_storage_sub_directory
)
async def list_directory(self, path: str) -> Iterable[DirectoryEntry | FileEntry]:
"""
List files and directories at the specified path.
Archive does not have a directory structure, so it only supports the root path "/".
"""
if not path == "/":
raise FileNotFoundError("Archive does not have a directory structure, only the root path '/' is supported.")
files: list[FileEntry] = []
async for manifest in self._archive_reader.list():
files.append(
FileEntry(
path=f"/{manifest.filename}",
size=manifest.content_size_bytes or 0,
timestamp=manifest.timestamp_most_recent,
permission="read",
description=manifest.summary,
)
)
return files
async def read_file(self, path: str) -> str:
"""
Read the content of a file at the specified path.
Archive does not have a directory structure, so it only supports the root path "/".
"""
archive_path = path.lstrip("/")
if not archive_path:
raise FileNotFoundError("Path must be specified, e.g. '/archive_filename.json'")
content = await self._archive_reader.read(filename=archive_path)
if content is None:
raise FileNotFoundError(f"File not found: '{path}'")
return convert_oai_messages_to_xml(cast(list[ChatCompletionMessageParam], content.messages))
def archive_file_source_mount(context: ConversationContext) -> MountPoint:
return MountPoint(
entry=DirectoryEntry(
path="/archives",
description="Archives of the conversation history that no longer fit in the context window.",
permission="read",
),
file_source=ArchiveFileSource(context=context),
)
```