diff --git a/.github/workflows/claude-code-review.yml b/.github/workflows/claude-code-review.yml
new file mode 100644
index 000000000..4caf96a2f
--- /dev/null
+++ b/.github/workflows/claude-code-review.yml
@@ -0,0 +1,54 @@
+name: Claude Code Review
+
+on:
+ pull_request:
+ types: [opened, synchronize]
+ # Optional: Only run on specific file changes
+ # paths:
+ # - "src/**/*.ts"
+ # - "src/**/*.tsx"
+ # - "src/**/*.js"
+ # - "src/**/*.jsx"
+
+jobs:
+ claude-review:
+ # Optional: Filter by PR author
+ # if: |
+ # github.event.pull_request.user.login == 'external-contributor' ||
+ # github.event.pull_request.user.login == 'new-developer' ||
+ # github.event.pull_request.author_association == 'FIRST_TIME_CONTRIBUTOR'
+
+ runs-on: ubuntu-latest
+ permissions:
+ contents: read
+ pull-requests: read
+ issues: read
+ id-token: write
+
+ steps:
+ - name: Checkout repository
+ uses: actions/checkout@v4
+ with:
+ fetch-depth: 1
+
+ - name: Run Claude Code Review
+ id: claude-review
+ uses: anthropics/claude-code-action@v1
+ with:
+ claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
+ prompt: |
+ Please review this pull request and provide feedback on:
+ - Code quality and best practices
+ - Potential bugs or issues
+ - Performance considerations
+ - Security concerns
+ - Test coverage
+
+ Use the repository's CLAUDE.md for guidance on style and conventions. Be constructive and helpful in your feedback.
+
+ Use `gh pr comment` with your Bash tool to leave your review as a comment on the PR.
+
+ # See https://github.com/anthropics/claude-code-action/blob/main/docs/usage.md
+ # or https://docs.anthropic.com/en/docs/claude-code/sdk#command-line for available options
+ claude_args: '--allowed-tools "Bash(gh issue view:*),Bash(gh search:*),Bash(gh issue list:*),Bash(gh pr comment:*),Bash(gh pr diff:*),Bash(gh pr view:*),Bash(gh pr list:*)"'
+
diff --git a/.github/workflows/claude.yml b/.github/workflows/claude.yml
new file mode 100644
index 000000000..ae36c007f
--- /dev/null
+++ b/.github/workflows/claude.yml
@@ -0,0 +1,50 @@
+name: Claude Code
+
+on:
+ issue_comment:
+ types: [created]
+ pull_request_review_comment:
+ types: [created]
+ issues:
+ types: [opened, assigned]
+ pull_request_review:
+ types: [submitted]
+
+jobs:
+ claude:
+ if: |
+ (github.event_name == 'issue_comment' && contains(github.event.comment.body, '@claude')) ||
+ (github.event_name == 'pull_request_review_comment' && contains(github.event.comment.body, '@claude')) ||
+ (github.event_name == 'pull_request_review' && contains(github.event.review.body, '@claude')) ||
+ (github.event_name == 'issues' && (contains(github.event.issue.body, '@claude') || contains(github.event.issue.title, '@claude')))
+ runs-on: ubuntu-latest
+ permissions:
+ contents: read
+ pull-requests: read
+ issues: read
+ id-token: write
+ actions: read # Required for Claude to read CI results on PRs
+ steps:
+ - name: Checkout repository
+ uses: actions/checkout@v4
+ with:
+ fetch-depth: 1
+
+ - name: Run Claude Code
+ id: claude
+ uses: anthropics/claude-code-action@v1
+ with:
+ claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
+
+ # This is an optional setting that allows Claude to read CI results on PRs
+ additional_permissions: |
+ actions: read
+
+ # Optional: Give a custom prompt to Claude. If this is not specified, Claude will perform the instructions specified in the comment that tagged it.
+ # prompt: 'Update the pull request description to include a summary of changes.'
+
+ # Optional: Add claude_args to customize behavior and configuration
+ # See https://github.com/anthropics/claude-code-action/blob/main/docs/usage.md
+ # or https://docs.anthropic.com/en/docs/claude-code/sdk#command-line for available options
+ # claude_args: '--model claude-opus-4-1-20250805 --allowed-tools Bash(gh pr:*)'
+
diff --git a/.gitignore b/.gitignore
index fe7f553d9..a55667e96 100644
--- a/.gitignore
+++ b/.gitignore
@@ -16,8 +16,13 @@ pages/research/local_research/
.vscode
agent.toml
content_suggestions/
+.claude/
+.qodo/
# app
.next
node_modules
-prompts
\ No newline at end of file
+prompts
+
+#mcp
+.mcp.json
diff --git a/README.md b/README.md
index cac60a8c7..9da0484bf 100644
--- a/README.md
+++ b/README.md
@@ -1,12 +1,18 @@
# Prompt Engineering Guide
+
+ Sponsored by
+
+
Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently use language models (LMs) for a wide variety of applications and research topics. Prompt engineering skills help to better understand the capabilities and limitations of large language models (LLMs). Researchers use prompt engineering to improve the capacity of LLMs on a wide range of common and complex tasks such as question answering and arithmetic reasoning. Developers use prompt engineering to design robust and effective prompting techniques that interface with LLMs and other tools.
Motivated by the high interest in developing with LLMs, we have created this new prompt engineering guide that contains all the latest papers, learning guides, lectures, references, and tools related to prompt engineering for LLMs.
🌐 [Prompt Engineering Guide (Web Version)](https://www.promptingguide.ai/)
-🎉 We are excited to launch our brand new prompt engineering courses under the DAIR.AI Academy. [Join Now](https://dair-ai.thinkific.com/bundles/pro)!
+🎉 We are excited to launch our new prompt engineering, RAG, and AI Agents courses under the DAIR.AI Academy. [Join Now](https://dair-ai.thinkific.com/bundles/pro)!
+
+The courses are meant to compliment this guide and provide a more hands-on approach to learning about prompt engineering, context engineering, and AI Agents.
Use code PROMPTING20 to get an extra 20% off.
diff --git a/components/ContentFileNames.tsx b/components/ContentFileNames.tsx
index 837ad452d..a0a64cbfb 100644
--- a/components/ContentFileNames.tsx
+++ b/components/ContentFileNames.tsx
@@ -15,15 +15,14 @@ const ContentFileNames = ({ section = 'research', lang = 'en' }) => {
return (
{fileNames.map(({ slug, title }, index) => (
- }
- title={title}
- href={`/${section}/${slug}`}
- >
- {/* Add your desired content here, or an empty fragment if no content is needed */}
- <>>
-
+
+ }
+ title={title}
+ href={`/${section}/${slug}`}
+ children={<>>}
+ />
+
))}
);
diff --git a/components/TabsComponent.tsx b/components/TabsComponent.tsx
index 8d52df68d..30b02556e 100644
--- a/components/TabsComponent.tsx
+++ b/components/TabsComponent.tsx
@@ -31,13 +31,13 @@ response = client.chat.completions.create(
};
return (
- tab.model)}>
- {tabsData.map((tab, index) => (
+ tab.model)} children={
+ tabsData.map((tab, index) => (
{renderCodeBlock(tab)}
- ))}
-
+ ))
+ } />
);
};
diff --git a/img/agents/Screenshot 2025-10-15 at 11.23.08.png b/img/agents/Screenshot 2025-10-15 at 11.23.08.png
new file mode 100644
index 000000000..8b0b6e5c8
Binary files /dev/null and b/img/agents/Screenshot 2025-10-15 at 11.23.08.png differ
diff --git a/img/agents/cs-persistent-storage.png b/img/agents/cs-persistent-storage.png
new file mode 100644
index 000000000..3bb59976c
Binary files /dev/null and b/img/agents/cs-persistent-storage.png differ
diff --git a/img/agents/cs-planning.png b/img/agents/cs-planning.png
new file mode 100644
index 000000000..9cf4f0d11
Binary files /dev/null and b/img/agents/cs-planning.png differ
diff --git a/img/agents/cs-subagents.png b/img/agents/cs-subagents.png
new file mode 100644
index 000000000..5f9a304fb
Binary files /dev/null and b/img/agents/cs-subagents.png differ
diff --git a/img/agents/cs-verification-agent.png b/img/agents/cs-verification-agent.png
new file mode 100644
index 000000000..e83248445
Binary files /dev/null and b/img/agents/cs-verification-agent.png differ
diff --git a/img/agents/customer-support-deep-agent.png b/img/agents/customer-support-deep-agent.png
new file mode 100644
index 000000000..585537455
Binary files /dev/null and b/img/agents/customer-support-deep-agent.png differ
diff --git a/img/agents/parallelization.png b/img/agents/parallelization.png
new file mode 100644
index 000000000..757a3a90b
Binary files /dev/null and b/img/agents/parallelization.png differ
diff --git a/img/agents/prompt-chaining.png b/img/agents/prompt-chaining.png
new file mode 100644
index 000000000..a8d09ec97
Binary files /dev/null and b/img/agents/prompt-chaining.png differ
diff --git a/img/agents/routing.png b/img/agents/routing.png
new file mode 100644
index 000000000..9f7162104
Binary files /dev/null and b/img/agents/routing.png differ
diff --git a/img/agents/simple-dr-agent.png b/img/agents/simple-dr-agent.png
new file mode 100644
index 000000000..76fe0daa0
Binary files /dev/null and b/img/agents/simple-dr-agent.png differ
diff --git a/img/agents/task-planner-agent.png b/img/agents/task-planner-agent.png
new file mode 100644
index 000000000..e96c7ff3d
Binary files /dev/null and b/img/agents/task-planner-agent.png differ
diff --git a/pages/_meta.en.json b/pages/_meta.en.json
index 6635eb59b..a1a9463e4 100644
--- a/pages/_meta.en.json
+++ b/pages/_meta.en.json
@@ -2,7 +2,7 @@
"index": "Prompt Engineering",
"introduction": "Introduction",
"techniques": "Prompting Techniques",
- "agents": "Agents",
+ "agents": "AI Agents",
"guides": "Guides",
"applications": "Applications",
"prompts": "Prompt Hub",
@@ -28,7 +28,11 @@
},
"intro-ai-agents": {
"title": "Intro to AI Agents",
- "href": "https://dair-ai.thinkific.com/courses/introduction-building-ai-agents"
+ "href": "https://dair-ai.thinkific.com/courses/introduction-ai-agents"
+ },
+ "agents-with-n8n": {
+ "title": "Building Effective AI Agents with n8n",
+ "href": "https://dair-ai.thinkific.com/courses/agents-with-n8n"
},
"rag-systems": {
"title": "Build RAG Systems",
diff --git a/pages/about.en.mdx b/pages/about.en.mdx
index f601c169f..612cef410 100644
--- a/pages/about.en.mdx
+++ b/pages/about.en.mdx
@@ -1,9 +1,15 @@
# About
-The Prompt Engineering Guide is a project by [DAIR.AI](https://github.com/dair-ai). It aims to educate researchers and practitioners about prompt engineering.
+The Prompt Engineering Guide is a project by [DAIR.AI](https://github.com/dair-ai). It aims to educate researchers and practitioners about prompt engineering, context engineering, RAG, and AI Agents.
DAIR.AI aims to democratize AI research, education, and technologies. Our mission is to enable the next-generation of AI innovators and creators.
+## Sponsorship
+
+We are open to sponsorship opportunities to help us continue building and maintaining this guide. If you're interested in sponsoring this project, please reach out to us at [hello@dair.ai](mailto:hello@dair.ai).
+
+## Contributions
+
We welcome contributions from the community. Lookout for the Edit buttons.
License information [here](https://github.com/dair-ai/Prompt-Engineering-Guide#license).
diff --git a/pages/agents.en.mdx b/pages/agents.en.mdx
index 16da39706..95283e4e1 100644
--- a/pages/agents.en.mdx
+++ b/pages/agents.en.mdx
@@ -1,10 +1,12 @@
# Agents
import { Callout } from 'nextra/components'
+import ContentFileNames from 'components/ContentFileNames'
-In this section, we provide an overview of language agents, including definitions, common design patterns, tips, and applications.
+In this section, we provide an overview of LLM-based agents, including definitions, common design patterns, tips, use cases, and applications.
-
-Learn to build Agents in our new structured courses with examples and code. [Join now!](https://dair-ai.thinkific.com/)
-Use code PROMPTING20 to get an extra 20% off.
+
+This content is based on our new course ["Building Effective AI Agents with n8n"](https://dair-ai.thinkific.com/courses/agents-with-n8n), which provides comprehensive insights, downloadable templates, prompts, and advanced tips into designing and implementing agentic systems.
+
+
diff --git a/pages/agents/_meta.en.json b/pages/agents/_meta.en.json
index 4b0165bd5..c09c9ca61 100644
--- a/pages/agents/_meta.en.json
+++ b/pages/agents/_meta.en.json
@@ -1,4 +1,8 @@
{
"introduction": "Introduction to Agents",
- "components": "Agent Components"
+ "components": "Agent Components",
+ "ai-workflows-vs-ai-agents": "AI Workflows vs AI Agents",
+ "context-engineering": "Context Engineering for AI Agents",
+ "context-engineering-deep-dive": "Context Engineering Deep Dive",
+ "deep-agents": "Deep Agents"
}
\ No newline at end of file
diff --git a/pages/agents/ai-workflows-vs-ai-agents.en.mdx b/pages/agents/ai-workflows-vs-ai-agents.en.mdx
new file mode 100644
index 000000000..df6fa7cad
--- /dev/null
+++ b/pages/agents/ai-workflows-vs-ai-agents.en.mdx
@@ -0,0 +1,229 @@
+# AI Workflows vs. AI Agents
+
+import { Callout } from 'nextra/components'
+
+
+
+Agentic systems represent a paradigm shift in how we orchestrate Large Language Models (LLMs) and tools to accomplish complex tasks. This guide explores the fundamental distinction between **AI workflows** and **AI Agents**, helping you understand when to use each approach in your AI applications.
+
+
+This content is based on our new course ["Building Effective AI Agents with n8n"](https://dair-ai.thinkific.com/courses/agents-with-n8n), which provides comprehensive insights, downloadable templates, prompts, and advanced tips into designing and implementing agentic systems.
+
+
+## What Are Agentic Systems?
+
+Agentic systems can be categorized into two main types:
+
+### 1. AI Workflows
+
+**AI workflows** are systems where LLMs and tools are orchestrated through **predefined code paths**. These systems follow a structured sequence of operations with explicit control flow.
+
+**Key Characteristics:**
+
+Key characteristics of AI workflows include:
+
+- Predefined steps and execution paths
+- High predictability and control
+- Well-defined task boundaries
+- Explicit orchestration logic
+
+**When to Use Workflows:**
+
+Use AI workflows in the following scenarios:
+
+- Well-defined tasks with clear requirements
+- Scenarios requiring predictability and consistency
+- Tasks where you need explicit control over execution flow
+- Production systems where reliability is critical
+
+### 2. AI Agents
+
+**AI agents** are systems where LLMs **dynamically direct their own processes** and tool usage, maintaining autonomous control over how they accomplish tasks.
+
+**Key Characteristics:**
+
+Key characteristics of AI agents include:
+
+- Dynamic decision-making
+- Autonomous tool selection and usage
+- Reasoning and reflection capabilities
+- Self-directed task execution
+
+**When to Use Agents:**
+
+Use AI agents in the following scenarios:
+
+- Open-ended tasks with variable execution paths
+- Complex scenarios where the number of steps is difficult to define upfront
+- Tasks requiring adaptive reasoning
+- Situations where flexibility outweighs predictability
+
+## Common AI Workflow Patterns
+
+### Pattern 1: Prompt Chaining
+
+
+
+Prompt chaining involves breaking down a complex task into sequential LLM calls, where each step's output feeds into the next.
+
+**Example: Document Generation Workflow**
+
+
+
+This workflow demonstrates a prompt chaining pattern for document generation that begins when a chat message is received. The system first uses GPT-4.1-mini to generate an initial outline, then checks the outline against predefined criteria. A manual "Set Grade" step evaluates the quality, followed by a conditional "If" node that determines the next action based on the grade. If the outline passes validation, it proceeds to expand the outline sections using GPT-4o and then refines and polishes the final document. If the outline fails validation, the workflow branches to an "Edit Fields" step for manual adjustments before continuing, ensuring quality control throughout the multi-stage document creation process.
+
+**Prompt Chaining Use Cases:**
+- Content generation pipelines
+- Multi-stage document processing
+- Sequential validation workflows
+
+### Pattern 2: Routing
+
+Routing directs different requests to specialized LLM chains or agents based on query classification.
+
+**Example: Customer Support Router**
+
+
+
+This workflow illustrates a routing pattern for intelligent query distribution in a customer support system. When a chat message is received, it's first processed by a Query Classifier using GPT-4.1-mini along with a Structured Output Parser to categorize the request type. Based on the classification, a "Route by Type" switch directs the query to one of three specialized LLM chains: a General LLM Chain for basic inquiries, a Refund LLM Chain for payment-related issues, or a Support LLM Chain for technical assistance. Each query type receives specialized handling while maintaining a unified response system, optimizing both accuracy and efficiency in customer service operations.
+
+**Routing Use Cases:**
+- Customer support systems
+- Multi-domain question answering
+- Request prioritization and delegation
+- Resource optimization by routing to appropriate models
+
+**Benefits:**
+- Efficient resource utilization
+- Specialized handling for different query types
+- Cost optimization through selective model usage
+
+### Pattern 3: Parallelization
+
+Parallelization executes multiple independent LLM operations simultaneously to improve efficiency.
+
+**Example: Content Safety Pipeline**
+
+
+
+**Parallelization Use Cases:**
+- Content moderation systems
+- Multi-criteria evaluation
+- Concurrent data processing
+- Independent verification tasks
+
+**Advantages:**
+- Reduced latency
+- Better resource utilization
+- Improved throughput
+
+## AI Agents: Autonomous Task Execution
+
+AI agents combine LLMs with autonomous decision-making capabilities, enabling them to perform complex tasks through reasoning, reflection, and dynamic tool usage.
+
+**Example: Task Planning Agent**
+
+**Scenario**: User asks "Add a meeting with John tomorrow at 2 PM"
+
+
+
+
+This workflow demonstrates an autonomous Task Planner agent that showcases agent behavior with dynamic decision-making capabilities. When a chat message is received, it's routed to a Task Planner agent that has access to three key components: a Chat Model (Reasoning LLM) for understanding and planning, a Memory system for maintaining context across interactions, and a Tool collection. The agent can autonomously select from multiple tools including add_update_tasks (to append or update tasks in a Google Sheet) and search_task (to read and search existing tasks from the sheet). Unlike predefined workflows, the agent independently determines which tools to use, when to use them, and in what sequence based on the user's request, exemplifying the flexibility and autonomy that distinguishes AI agents from traditional AI workflows.
+
+
+**Key Insight**: The agent determines which tools to use and in what order, based on the request context—not on predefined rules.
+
+
+**AI Agent Use Cases:**
+
+- Deep research systems
+- Agentic RAG systems
+- Coding agents
+- Data analysis and processing
+- Content generation and editing
+- Customer support and assistance
+- Interactive chatbots and virtual assistants
+
+
+**Core Components:**
+
+Here is a list of key components for building AI Agents:
+
+1. **Tool Access**: Integration with external systems (Google Sheets, search APIs, databases)
+2. **Memory**: Context retention across interactions for continuity
+3. **Reasoning Engine**: Decision-making logic for tool selection and task planning
+4. **Autonomy**: Self-directed execution without predefined control flow
+
+### How Agents Differ from Workflows
+
+| Aspect | AI Workflows | AI Agents |
+|--------|-------------|-----------|
+| **Control Flow** | Predefined, explicit | Dynamic, autonomous |
+| **Decision Making** | Hard-coded logic | LLM-driven reasoning |
+| **Tool Usage** | Orchestrated by code | Self-selected by agent |
+| **Adaptability** | Fixed paths | Flexible execution |
+| **Complexity** | Lower, more predictable | Higher, more capable |
+| **Use Cases** | Well-defined tasks | Open-ended problems |
+
+
+## Design Considerations
+
+### Choosing Between Workflows and Agents
+
+**Use AI Workflows when:**
+- Task requirements are clear and stable
+- Predictability is essential
+- You need explicit control over execution
+- Debugging and monitoring are priorities
+- Cost management is critical
+
+**Use AI Agents when:**
+- Tasks are open-ended or exploratory
+- Flexibility is more important than predictability
+- The problem space is complex with many variables
+- Human-like reasoning is beneficial
+- Adaptability to changing conditions is required
+
+### Hybrid Approaches
+
+Many production systems combine both approaches:
+- **Workflows for structure**: Use workflows for reliable, well-defined components
+- **Agents for flexibility**: Deploy agents for adaptive, complex decision-making
+- **Example**: A workflow routes requests to specialized agents, each handling open-ended subtasks
+
+We will introduce an example of this in an upcoming article.
+
+## Best Practices
+
+### For AI Workflows
+
+1. **Clear Step Definition**: Document each stage in the workflow
+2. **Error Handling**: Implement fallback paths for failures
+3. **Validation Gates**: Add checks between critical steps
+4. **Performance Monitoring**: Track latency and success rates per step
+
+### For AI Agents
+
+1. **Tool Design**: Provide clear, well-documented tools with explicit purposes
+2. **Memory Management**: Implement effective context retention strategies
+3. **Guardrails**: Set boundaries on agent behavior and tool usage
+4. **Observability**: Log agent reasoning and decision-making processes
+5. **Iterative Testing**: Continuously evaluate agent performance on diverse scenarios
+
+We will discuss these more extensively in future articles.
+
+## Conclusion
+
+Understanding the distinction between AI workflows and AI agents is crucial for building effective agentic systems. Workflows provide control and predictability for well-defined tasks, while agents offer flexibility and autonomy for complex, open-ended problems.
+
+The choice between workflows and agents—or a combination of both—depends on your specific use case, performance requirements, and tolerance for autonomous decision-making. By aligning your system design with task characteristics, you can build more effective, efficient, and reliable AI applications.
+
+
+This content is based on our new course ["Building Effective AI Agents with n8n"](https://dair-ai.thinkific.com/courses/agents-with-n8n), which provides comprehensive insights, downloadable templates, prompts, and advanced tips into designing and implementing agentic systems.
+
+
+## Additional Resources
+
+- [Anthropic: Building Effective Agents](https://www.anthropic.com/research/building-effective-agents)
+- [Prompt Engineering Guide](https://www.promptingguide.ai/)
+- [Building Effective AI Agents with n8n](https://dair-ai.thinkific.com/courses/agents-with-n8n)
diff --git a/pages/agents/context-engineering-deep-dive.en.mdx b/pages/agents/context-engineering-deep-dive.en.mdx
new file mode 100644
index 000000000..46e0029c3
--- /dev/null
+++ b/pages/agents/context-engineering-deep-dive.en.mdx
@@ -0,0 +1,284 @@
+# Context Engineering Deep Dive: Building a Deep Research Agent
+
+import { Callout } from 'nextra/components'
+
+[Context engineering](https://www.promptingguide.ai/guides/context-engineering-guide) requires significant iteration and careful design decisions to build reliable AI agents. This guide takes a deep dive into the practical aspects of context engineering through the development of a basic deep research agent, exploring some of the techniques and design patterns that improve agent reliability and performance.
+
+
+This content is based on our new course ["Building Effective AI Agents with n8n"](https://dair-ai.thinkific.com/courses/agents-with-n8n), which provides comprehensive insights, downloadable templates, prompts, and advanced tips into designing and implementing agentic systems.
+
+
+## The Reality of Context Engineering
+
+Building effective AI agents requires substantial tuning of system prompts and tool definitions. The process involves spending hours iterating on:
+
+- System prompt design and refinement
+- Tool definitions and usage instructions
+- Agent architecture and communication patterns
+- Input/output specifications between agents
+
+
+Don't underestimate the effort required for context engineering. It's not a one-time task but an iterative process that significantly impacts agent reliability and performance.
+
+## Agent Architecture Design
+
+### The Original Design Problem
+
+
+
+Let's look at a basic deep research agent architecture. The initial architecture connects the web search tool directly to the deep research agent. This design places too much burden on a single agent responsible for:
+
+- Managing tasks (creating, updating, deleting)
+- Saving information to memory
+- Executing web searches
+- Generating final reports
+
+**Consequences of this design:**
+- Context grew too long
+- Agent forgot to execute web searches
+- Task completion updates were missed
+- Unreliable behavior across different queries
+
+### The Improved Multi-Agent Architecture
+
+The solution involved separating concerns by introducing a dedicated search worker agent:
+
+**Benefits of the multi-agent design:**
+
+1. **Separation of Concerns**: The parent agent (Deep Research Agent) handles planning and orchestration, while the search worker agent focuses exclusively on executing web searches
+2. **Improved Reliability**: Each agent has a clear, focused responsibility, reducing the likelihood of missed tasks or forgotten operations
+3. **Model Selection Flexibility**: Different agents can use different language models optimized for their specific tasks
+ - Deep Research Agent: Uses Gemini 2.5 Pro for complex planning and reasoning
+ - Search Worker Agent: Uses Gemini 2.5 Flash for faster, more cost-effective search execution
+
+If you are using models from other providers like OpenAI, you can leverage GPT-5 (for planning and reasoning) and GPT-5-mini (for search execution) for similar performance.
+
+
+**Design Principle**: Separating agent responsibilities improves reliability and enables cost-effective model selection for different subtasks.
+
+
+## System Prompt Engineering
+
+Here is the full system prompt for the deep research agent we built in n8n:
+
+```md
+You are a deep research agent who will help with planning and executing search tasks to generate a deep research report.
+
+## GENERAL INSTRUCTIONS
+
+The user will provide a query, and you will convert that query into a search plan with multiple search tasks (3 web searches). You will execute each search task and maintain the status of those searches in a spreadsheet.
+
+You will then generate a final deep research report for the user.
+
+For context, today's date is: {{ $now.format('yyyy-MM-dd') }}
+
+## TOOL DESCRIPTIONS
+
+Below are some useful instructions for how to use the available tools.
+
+Deleting tasks: Use the delete_task tool to clear up all the tasks before starting the search plan.
+
+Planning tasks: You will create a plan with the search tasks (3 web searches) and add them to the Google Sheet using the append_update_task tool. Make sure to keep the status of each task updated after completing each search. Each task begins with a todo status and will be updated to a "done" status once the search worker returns information regarding the search task.
+
+Executing tasks: Use the Search Worker Agent tool to execute the search plan. The input to the agent are the actual search queries, word for word.
+
+Use the tools in the order that makes the most sense to you but be efficient.
+```
+
+Let's break it down into parts and discuss why each section is important:
+
+
+### High-Level Agent Definition
+
+The system prompt begins with a clear definition of the agent's role:
+
+```md
+You are a deep research agent who will help with planning and executing search tasks to generate a deep research report.
+```
+
+### General Instructions
+
+Provide explicit instructions about the agent's workflow:
+
+```md
+## GENERAL INSTRUCTIONS
+
+The user will provide a query, and you will convert that query into a search plan with multiple search tasks (3 web searches). You will execute each search task and maintain the status of those searches in a spreadsheet.
+
+You will then generate a final deep research report for the user.
+```
+
+### Providing Essential Context
+
+**Current Date Information:**
+
+Including the current date is crucial for research agents to get up-to-date information:
+
+```md
+For context, today's date is: {{ $now.format('yyyy-MM-dd') }}
+```
+
+**Why this matters:**
+- LLMs typically have knowledge cutoffs months or years behind the current date
+- Without current date context, agents often search for outdated information
+- This ensures agents understand temporal context for queries like "latest news" or "recent developments"
+
+In n8n, you can dynamically inject the current date using built-in functions with customizable formats (date only, date with time, specific timezones, etc.).
+
+## Tool Definitions and Usage Instructions
+
+### The Importance of Detailed Tool Descriptions
+
+Tool definitions typically appear in two places:
+
+1. **In the system prompt**: Detailed explanations of what tools do and when to use them
+2. **In the actual tool implementation**: Technical specifications and parameters
+
+
+**Key Insight**: The biggest performance improvements often come from clearly explaining tool usage in the system prompt, not just defining tool parameters.
+
+
+### Example Tool Instructions
+
+The system prompt also includes detailed instructions for using the available tools:
+
+```md
+## TOOL DESCRIPTIONS
+
+Below are some useful instructions for how to use the available tools.
+
+Deleting tasks: Use the delete_task tool to clear up all the tasks before starting the search plan.
+
+Planning tasks: You will create a plan with the search tasks (3 web searches) and add them to the Google Sheet using the append_update_task tool. Make sure to keep the status of each task updated after completing each search. Each task begins with a todo status and will be updated to a "done" status once the search worker returns information regarding the search task.
+
+Executing tasks: Use the Search Worker Agent tool to execute the search plan. The input to the agent are the actual search queries, word for word.
+
+Use the tools in the order that makes the most sense to you but be efficient.
+```
+
+
+Initially, without explicit status definitions, the agent would use different status values across runs:
+- Sometimes "pending", sometimes "to-do"
+- Sometimes "completed", sometimes "done", sometimes "finished"
+
+Be explicit about allowed values. This eliminates ambiguity and ensures consistent behavior.
+
+Note that the system prompt also includes this instruction:
+
+```md
+Use the tools in the order that makes most sense to you, but be efficient.
+```
+
+What's the reasoning behind this decision?
+
+This provides flexibility for the agent to optimize its execution strategy. During testing, the agent might:
+- Execute only 2 searches instead of 3 if it determines that's sufficient
+- Combine redundant search queries
+- Skip searches that overlap significantly
+
+Here is a specific instruction you can use, if you require all search tasks to be executed:
+
+```md
+You MUST execute a web search for each and every search task you create.
+Do NOT skip any tasks, even if they seem redundant.
+```
+
+**When to use flexible vs. rigid approaches:**
+- **Flexible**: During development and testing to observe agent decision-making patterns
+- **Rigid**: In production when consistency and completeness are critical
+
+## Context Engineering Iteration Process
+
+### The Iterative Nature of Improving Context
+
+Context engineering is not a one-time effort. The development process involves:
+
+1. **Initial implementation** with basic system prompts
+2. **Testing** with diverse queries
+3. **Identifying issues** (missed tasks, wrong status values, incomplete searches)
+4. **Adding specific instructions** to address each issue
+5. **Re-testing** to validate improvements
+6. **Repeating** the cycle
+
+### What's Still Missing
+
+Even after multiple iterations, there are opportunities for further improvement:
+
+**Search Task Metadata:**
+- Augmenting search queries
+- Search type (web search, news search, academic search, PDF search)
+- Time period filters (today, last week, past month, past year, all time)
+- Domain focus (technology, science, health, etc.)
+- Priority levels for task execution order
+
+**Enhanced Search Planning:**
+- More detailed instructions on how to generate search tasks
+- Preferred formats for search queries
+- Guidelines for breaking down complex queries
+- Examples of good vs. bad search task decomposition
+
+**Date Range Specification:**
+- Start date and end date for time-bounded searches
+- Format specifications for date parameters
+- Logic for inferring date ranges from time period keywords
+
+Based on the recommended improvements, it's easy to appreciate that web search for AI agents is a challenging effort that requires a lot of context engineering.
+
+
+## Advanced Considerations
+
+### Sub-Agent Communication
+
+When designing multi-agent systems, carefully consider:
+
+**What information does the sub-agent need?**
+- For the search worker: Just the search query text
+- Not the full context or task metadata
+- Keep sub-agent inputs minimal and focused
+
+**What information should the sub-agent return?**
+- Search results and relevant findings
+- Error states or failure conditions
+- Metadata about the search execution
+
+### Context Length Management
+
+As agents execute multiple tasks, context grows:
+- Task history accumulates
+- Search results add tokens
+- Conversation history expands
+
+**Strategies to manage context length:**
+- Use separate agents to isolate context
+- Implement memory management tools
+- Summarize long outputs before adding to context
+- Clear task lists between research queries
+
+### Error Handling in System Prompts
+
+Include instructions for failure scenarios:
+
+```text
+ERROR HANDLING:
+- If search_worker fails, retry once with rephrased query
+- If task cannot be completed, mark status as "failed" with reason
+- If critical errors occur, notify user and request guidance
+- Never proceed silently when operations fail
+```
+
+## Conclusion
+
+Context engineering is a critical practice for building reliable AI agents that requires:
+
+- **Significant iteration time** spent tuning prompts and tool definitions
+- **Careful architectural decisions** about agent separation and communication
+- **Explicit instructions** that eliminate assumptions
+- **Continuous refinement** based on observed behavior
+- **Balance between flexibility and control**
+
+The deep research agent example demonstrates how thoughtful context engineering transforms an unreliable prototype into a robust, production-ready system. By applying these principles—clear role definitions, explicit tool instructions, essential context provision, and iterative improvement—you can build AI agents that consistently deliver high-quality results.
+
+
+Learn how to build production-ready AI agents with hands-on examples and templates. [Join our comprehensive course!](https://dair-ai.thinkific.com/courses/agents-with-n8n)
+Use code PROMPTING20 to get an extra 20% off.
+
diff --git a/pages/agents/context-engineering.en.mdx b/pages/agents/context-engineering.en.mdx
new file mode 100644
index 000000000..c50a03a85
--- /dev/null
+++ b/pages/agents/context-engineering.en.mdx
@@ -0,0 +1,242 @@
+# Why Context Engineering?
+
+import { Callout } from 'nextra/components'
+
+[Context engineering](https://www.promptingguide.ai/guides/context-engineering-guide) is a critical practice for building reliable and effective AI agents. This guide explores the importance of context engineering through a practical example of building a deep research agent.
+
+Context engineering involves carefully crafting and refining the prompts, instructions, and constraints that guide an AI agent's behavior to achieve desired outcomes.
+
+
+This content is based on our new course ["Building Effective AI Agents with n8n"](https://dair-ai.thinkific.com/courses/agents-with-n8n), which provides comprehensive insights, downloadable templates, prompts, and advanced tips into designing and implementing agentic systems.
+
+
+## What is Context Engineering?
+
+[Context engineering](https://www.promptingguide.ai/guides/context-engineering-guide) is the process of designing, testing, and iterating on the contextual information provided to AI agents to shape their behavior and improve task performance. Unlike simple prompt engineering for single LLM calls, context engineering for agents involves (but not limited to):
+
+- **System prompts** that define agent behavior and capabilities
+- **Task constraints** that guide decision-making
+- **Tool descriptions** that clarify when and how to use available functions/tools
+- **Memory management** for tracking state across multiple steps
+- **Error handling** patterns for robust execution
+
+## Building a Deep Research Agent: A Case Study
+
+Let's explore context engineering principles through an example: a minimal deep research agent that performs web searches and generates reports.
+
+
+
+### The Context Engineering Challenge
+
+When building the first version of this agent system, the initial implementation revealed several behavioral issues that required careful context engineering:
+
+#### Issue 1: Incomplete Task Execution
+
+**Problem**: When running the agentic workflow, the orchestrator agent often creates three search tasks but only executes searches for two of them, skipping the third task without explicit justification.
+
+**Root Cause**: The agent's system prompt lacked explicit constraints about task completion requirements. The agent made assumptions about which searches were necessary, leading to inconsistent behavior.
+
+**Solution**: Two approaches are possible:
+
+1. **Flexible Approach** (current): Allow the agent to decide which searches are necessary, but require explicit reasoning for skipped tasks
+2. **Strict Approach**: Add explicit constraints requiring search execution for all planned tasks
+
+Example system prompt enhancement:
+
+```text
+You are a deep research agent responsible for executing comprehensive research tasks.
+
+TASK EXECUTION RULES:
+- For each search task you create, you MUST either:
+ 1. Execute a web search and document findings, OR
+ 2. Explicitly state why the search is unnecessary and mark it as completed with justification
+
+- Do NOT skip tasks silently or make assumptions about task redundancy
+- If you determine tasks overlap, consolidate them BEFORE execution
+- Update task status in the spreadsheet after each action
+```
+
+#### Issue 2: Lack of Debugging Visibility
+
+**Problem**: Without proper logging and state tracking, it was difficult to understand why the agent made certain decisions.
+
+**Solution**: For this example, it helps to implement a task management system using a spreadsheet or text file (for simplicity) with the following fields:
+
+- Task ID
+- Search query
+- Status (todo, in_progress, completed)
+- Results summary
+- Timestamp
+
+This visibility enables:
+- Real-time debugging of agent decisions
+- Understanding of task execution flow
+- Identification of behavioral patterns
+- Data for iterative improvements
+
+### Context Engineering Best Practices
+
+Based on this case study, here are key principles for effective context engineering:
+
+#### 1. Eliminate Prompt Ambiguity
+
+**Bad Example:**
+```text
+Perform research on the given topic.
+```
+
+**Good Example:**
+```text
+Perform research on the given topic by:
+1. Breaking down the query into 3-5 specific search subtasks
+2. Executing a web search for EACH subtask using the search_tool
+3. Documenting findings for each search in the task tracker
+4. Synthesizing all findings into a comprehensive report
+```
+
+#### 2. Make Expectations Explicit
+
+Don't assume the agent knows what you want. Be explicit about:
+- Required vs. optional actions
+- Quality standards
+- Output formats
+- Decision-making criteria
+
+#### 3. Implement Observability
+
+Build debugging mechanisms into your agentic system:
+- Log all agent decisions and reasoning
+- Track state changes in external storage
+- Record tool calls and their outcomes
+- Capture errors and edge cases
+
+
+Pay close attention to every run of your agentic system. Strange behaviors and edge cases are opportunities to improve your context engineering efforts.
+
+
+#### 4. Iterate Based on Behavior
+
+Context engineering is an iterative process:
+
+1. **Deploy** the agent with initial context
+2. **Observe** actual behavior in production
+3. **Identify** deviations from expected behavior
+4. **Refine** system prompts and constraints
+5. **Test** and validate improvements
+6. **Repeat**
+
+#### 5. Balance Flexibility and Constraints
+
+Consider the tradeoff between:
+- **Strict constraints**: More predictable but less adaptable
+- **Flexible guidelines**: More adaptable but potentially inconsistent
+
+Choose based on your use case requirements.
+
+## Advanced Context Engineering Techniques
+
+### Layered Context Architecture
+
+Context engineering applies to all stages of the AI agent build process. Depending on the AI Agent, it's sometimes helpful to think of context as a hierarchical structure. For our basic agentic system, we can organize context into hierarchical layers:
+
+1. **System Layer**: Core agent identity and capabilities
+2. **Task Layer**: Specific instructions for the current task
+3. **Tool Layer**: Descriptions and usage guidelines for each tool
+4. **Memory Layer**: Relevant historical context and learnings
+
+### Dynamic Context Adjustment
+
+Another approach is to dynamically adjust context based on the task complexity, available resources, previous execution history, and error patterns. Based on our example, we can adjust context based on:
+
+- Task complexity
+- Available resources
+- Previous execution history
+- Error patterns
+
+### Context Validation
+
+Evaluation is key to ensuring context engineering techniques are working as they should for your AI agents. Before deployment, validate your context design:
+
+- **Completeness**: Does it cover all important scenarios?
+- **Clarity**: Is it unambiguous?
+- **Consistency**: Do different parts align?
+- **Testability**: Can you verify the behavior?
+
+## Common Context Engineering Pitfalls
+
+Below are a few common context engineering pitfalls to avoid when building AI agents:
+
+### 1. Over-Constraint
+
+**Problem**: Too many rules make the agent inflexible and unable to handle edge cases.
+
+**Example**:
+```text
+NEVER skip a search task.
+ALWAYS perform exactly 3 searches.
+NEVER combine similar queries.
+```
+
+**Better Approach**:
+```text
+Aim to perform searches for all planned tasks. If you determine that tasks are redundant, consolidate them before execution and document your reasoning.
+```
+
+### 2. Under-Specification
+
+**Problem**: Vague instructions lead to unpredictable behavior.
+
+**Example**:
+```text
+Do some research and create a report.
+```
+
+**Better Approach**:
+```text
+Execute research by:
+1. Analyzing the user query to identify key information needs
+2. Creating 3-5 specific search tasks covering different aspects
+3. Executing searches using the search_tool for each task
+4. Synthesizing findings into a structured report with sections for:
+ - Executive summary
+ - Key findings per search task
+ - Conclusions and insights
+```
+
+### 3. Ignoring Error Cases
+
+**Problem**: Context doesn't specify behavior when things go wrong.
+
+**Solution**: In some cases, it helps to add error handling instructions to your AI Agents:
+```text
+ERROR HANDLING:
+- If a search fails, retry once with a rephrased query
+- If retry fails, document the failure and continue with remaining tasks
+- If more than 50% of searches fail, alert the user and request guidance
+- Never stop execution completely without user notification
+```
+
+## Measuring Context Engineering Success
+
+Track these metrics to evaluate context engineering effectiveness:
+
+1. **Task Completion Rate**: Percentage of tasks completed successfully
+2. **Behavioral Consistency**: Similarity of agent behavior across similar inputs
+3. **Error Rate**: Frequency of failures and unexpected behaviors
+4. **User Satisfaction**: Quality and usefulness of outputs
+5. **Debugging Time**: Time required to identify and fix issues
+
+It's important to not treat context engineering as a one-time activity but an ongoing practice that requires:
+
+- **Systematic observation** of agent behavior
+- **Careful analysis** of failures and edge cases
+- **Iterative refinement** of instructions and constraints
+- **Rigorous testing** of changes
+
+We will be covering these principles in more detail in upcoming guides. By applying these principles, you can build AI agent systems that are reliable, predictable, and effective at solving complex tasks.
+
+
+
+Learn how to build production-ready AI agents in our comprehensive course. [Join now!](https://dair-ai.thinkific.com/courses/agents-with-n8n)
+Use code PROMPTING20 to get an extra 20% off.
+
diff --git a/pages/agents/deep-agents.en.mdx b/pages/agents/deep-agents.en.mdx
new file mode 100644
index 000000000..b86e0844e
--- /dev/null
+++ b/pages/agents/deep-agents.en.mdx
@@ -0,0 +1,78 @@
+# Deep Agents
+
+import { Callout } from 'nextra/components'
+
+Most agents today are shallow.
+
+They easily break down on long, multi-step problems (e.g., deep research or agentic coding).
+
+That’s changing fast!
+
+We’re entering the era of "Deep Agents", systems that strategically plan, remember, and delegate intelligently for solving very complex problems.
+
+We at the [DAIR.AI Academy](https://dair-ai.thinkific.com/) and other folks from [LangChain](https://docs.langchain.com/labs/deep-agents/overview), [Claude Code](https://www.anthropic.com/engineering/building-agents-with-the-claude-agent-sdk), as well as more recently, individuals like [Philipp Schmid](https://www.philschmid.de/agents-2.0-deep-agents), have been documenting this idea.
+
+Here is an example of a deep agent built to power the [DAIR.AI Academy's](https://dair-ai.thinkific.com/) customer support system intended for students to ask questions regarding our trainings and courses:
+
+
+
+
+This post is based on our new course ["Building Effective AI Agents with n8n"](https://dair-ai.thinkific.com/courses/agents-with-n8n), which provides comprehensive insights, downloadable templates, prompts, and advanced tips into designing and implementing deep agents.
+
+
+Here’s roughly the core idea behind Deep Agents (based on my own thoughts and notes that I've gathered from others):
+
+## Planning
+
+
+
+Instead of reasoning ad-hoc inside a single context window, Deep Agents maintain structured task plans they can update, retry, and recover from. Think of it as a living to-do list that guides the agent toward its long-term goal. To experience this, just try out Claude Code or Codex for planning; the results are significantly better once you enable it before executing any task.
+
+We have also written recently on the power of brainstorming for longer with Claude Code, and this shows the power of planning, expert context, and human-in-the-loop (your expertise gives you an important edge when working with deep agents). Planning will also be critical for long-horizon problems (think agents for scientific discovery, which comes next).
+
+## Orchestrator & Sub-agent Architecture
+
+
+
+One big agent (typically with a very long context) is no longer enough. I've seen [arguments](https://cognition.ai/blog/dont-build-multi-agents) against multi-agent systems and in favor of monolithic systems, but I'm skeptical about this.
+
+The orchestrator-sub-agent architecture is one of the most powerful LLM-based agentic architectures you can leverage today for any domain you can imagine. An orchestrator manages specialized sub-agents such as search agents, coders, KB retrievers, analysts, verifiers, and writers, each with its own clean context and domain focus.
+
+The orchestrator delegates intelligently, and subagents execute efficiently. The orchestrator integrates their outputs into a coherent result. Claude Code popularized the use of this approach for coding and sub-agents, which, it turns out, are particularly useful for efficiently managing context (through separation of concerns).
+
+I wrote a few notes on the power of using orchestrator and subagents [here](https://x.com/omarsar0/status/1960877597191245974) and [here](https://x.com/omarsar0/status/1971975884077965783).
+
+## Context Retrieval and Agentic Search
+
+
+
+Deep Agents don’t rely on conversation history alone. They store intermediate work in external memory like files, notes, vectors, or databases, letting them reference what matters without overloading the model’s context. High-quality structured memory is a thing of beauty.
+
+Take a look at recent works like [ReasoningBank](https://arxiv.org/abs/2509.25140) and [Agentic Context Engineering](https://arxiv.org/abs/2510.04618) for some really cool ideas on how to better optimize memory building and retrieval. Building with the orchestrator-subagents architecture means that you can also leverage hybrid memory techniques (e.g., agentic search + semantic search), and you can let the agent decide what strategy to use.
+
+## Context Engineering
+
+One of the worst things you can do when interacting with these types of agents is underspecified instructions/prompts. Prompt engineering was and is important, but we will use the new term [context engineering](https://www.promptingguide.ai/guides/context-engineering-guide) to emphasize the importance of building context for agents. The instructions need to be more explicit, detailed, and intentional to define when to plan, when to use a sub-agent, how to name files, and how to collaborate with humans. Part of context engineering also involves efforts around structured outputs, system prompt optimization, compacting context, evaluating context effectiveness, and [optimizing tool definitions](https://www.anthropic.com/engineering/writing-tools-for-agents).
+
+Read our previous guide on context engineering to learn more: [Context Engineering Deep Dive](https://www.promptingguide.ai/guides/context-engineering-guide)
+
+## Verification
+
+
+
+Next to context engineering, verification is one of the most important components of an agentic system (though less often discussed). Verification boils down to verifying outputs, which can be automated (LLM-as-a-Judge) or done by a human. Because of the effectiveness of modern LLMs at generating text (in domains like math and coding), it's easy to forget that they still suffer from hallucination, sycophancy, prompt injection, and a number of other issues. Verification helps with making your agents more reliable and more production-ready. You can build good verifiers by leveraging systematic evaluation pipelines.
+
+## Final Words
+
+This is a huge shift in how we build with AI agents. Deep agents also feel like an important building block for what comes next: personalized proactive agents that can act on our behalf. I will write more on proactive agents in a future post.
+
+I've been teaching these ideas to agent builders over the past couple of months. If you are interested in more hands-on experience for how to build deep agents check out the new course in our academy: https://dair-ai.thinkific.com/courses/agents-with-n8n
+
+
+The figures you see in the post describe an agentic RAG system that students need to build for the course final project.
+
+
+This post is based on our new course ["Building Effective AI Agents with n8n"](https://dair-ai.thinkific.com/courses/agents-with-n8n), which provides comprehensive insights, downloadable templates, prompts, and advanced tips into designing and implementing deep agents.
+
+
+*Written by Elvis Saravia (creator of the Prompting Engineering Guide and co-founder of the DAIR.AI Academy)*
\ No newline at end of file
diff --git a/pages/guides/context-engineering-guide.en.mdx b/pages/guides/context-engineering-guide.en.mdx
index 56ff881d9..964464da7 100644
--- a/pages/guides/context-engineering-guide.en.mdx
+++ b/pages/guides/context-engineering-guide.en.mdx
@@ -269,13 +269,7 @@ Context can dilute or become inefficient (i.e., be filled with stale and irrelev
I expect that context engineering continues to evolve as an important set of skills for AI developers/engineers. Beyond manual context engineering, there are also opportunities to build methods that automate the processing of effective context engineering. I’ve seen a few tools that have attempted this, but there needs to be more progress in this area.
- This guide is a Work in Progress.
-
- Learn how to apply context engineering in your own projects.
-
- Join our hands-on courses in [DAIR.AI Academy](https://dair-ai.thinkific.com/) for practical workflows, agent design, and more.
-
- We are also hosting a workshop on context engineering for our Pro members on July 31, 2025. Hope to meet some of you there.
+ This content is based on our new course ["Building Effective AI Agents with n8n"](https://dair-ai.thinkific.com/courses/agents-with-n8n), which provides comprehensive insights, downloadable templates, prompts, and advanced tips into designing and implementing agentic systems.
Use code PROMPTING20
for 20% off Pro membership.
@@ -292,7 +286,4 @@ Below are some recommended readings from other folks who have recently written a
* [https://blog.langchain.com/the-rise-of-context-engineering/](https://blog.langchain.com/the-rise-of-context-engineering/)
-
-*Please reach out if you see any mistakes in this article.*
-
import { Callout } from 'nextra/components'
diff --git a/pnpm-lock.yaml b/pnpm-lock.yaml
index fe1001740..cffd8a3d7 100644
--- a/pnpm-lock.yaml
+++ b/pnpm-lock.yaml
@@ -1,2531 +1,3747 @@
-lockfileVersion: '6.0'
-
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- specifier: ^6.5.1
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- version: 0.2.0(@fortawesome/fontawesome-svg-core@6.5.1)(react@18.2.0)
- '@napi-rs/simple-git':
- specifier: ^0.1.19
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- '@svgr/webpack':
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- '@vercel/analytics':
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- next:
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- version: 2.13.2(next@13.5.6)(react-dom@18.2.0)(react@18.2.0)
- nextra-theme-docs:
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- react:
- specifier: ^18.2.0
- version: 18.2.0
- react-dom:
- specifier: ^18.2.0
- version: 18.2.0(react@18.2.0)
-
-devDependencies:
- '@types/node':
- specifier: 18.11.10
- version: 18.11.10
- typescript:
- specifier: ^4.9.5
- version: 4.9.5
+lockfileVersion: '9.0'
-packages:
+settings:
+ autoInstallPeers: true
+ excludeLinksFromLockfile: false
- /@ampproject/remapping@2.2.1:
- resolution: {integrity: sha512-lFMjJTrFL3j7L9yBxwYfCq2k6qqwHyzuUl/XBnif78PWTJYyL/dfowQHWE3sp6U6ZzqWiiIZnpTMO96zhkjwtg==}
- engines: {node: '>=6.0.0'}
- dependencies:
- '@jridgewell/gen-mapping': 0.3.3
- '@jridgewell/trace-mapping': 0.3.20
- dev: false
+importers:
+
+ .:
+ dependencies:
+ '@fortawesome/fontawesome-svg-core':
+ specifier: ^6.5.1
+ version: 6.7.2
+ '@fortawesome/free-solid-svg-icons':
+ specifier: ^6.5.1
+ version: 6.7.2
+ '@fortawesome/react-fontawesome':
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- engines: {node: '>=12'}
+ d3-time@3.1.0:
dependencies:
d3-array: 3.2.4
- dev: false
- /d3-timer@3.0.1:
- resolution: {integrity: sha512-ndfJ/JxxMd3nw31uyKoY2naivF+r29V+Lc0svZxe1JvvIRmi8hUsrMvdOwgS1o6uBHmiz91geQ0ylPP0aj1VUA==}
- engines: {node: '>=12'}
- dev: false
+ d3-timer@3.0.1: {}
- /d3-transition@3.0.1(d3-selection@3.0.0):
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- engines: {node: '>=12'}
- peerDependencies:
- d3-selection: 2 - 3
+ d3-transition@3.0.1(d3-selection@3.0.0):
dependencies:
d3-color: 3.1.0
d3-dispatch: 3.0.1
@@ -2533,22 +3749,16 @@ packages:
d3-interpolate: 3.0.1
d3-selection: 3.0.0
d3-timer: 3.0.1
- dev: false
- /d3-zoom@3.0.0:
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- engines: {node: '>=12'}
+ d3-zoom@3.0.0:
dependencies:
d3-dispatch: 3.0.1
d3-drag: 3.0.0
d3-interpolate: 3.0.1
d3-selection: 3.0.0
d3-transition: 3.0.1(d3-selection@3.0.0)
- dev: false
- /d3@7.8.5:
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- engines: {node: '>=12'}
+ d3@7.9.0:
dependencies:
d3-array: 3.2.4
d3-axis: 3.0.0
@@ -2564,7 +3774,7 @@ packages:
d3-fetch: 3.0.1
d3-force: 3.0.0
d3-format: 3.1.0
- d3-geo: 3.1.0
+ d3-geo: 3.1.1
d3-hierarchy: 3.1.2
d3-interpolate: 3.0.1
d3-path: 3.1.0
@@ -2572,7 +3782,7 @@ packages:
d3-quadtree: 3.0.1
d3-random: 3.0.1
d3-scale: 4.0.2
- d3-scale-chromatic: 3.0.0
+ d3-scale-chromatic: 3.1.0
d3-selection: 3.0.0
d3-shape: 3.2.0
d3-time: 3.1.0
@@ -2580,196 +3790,115 @@ packages:
d3-timer: 3.0.1
d3-transition: 3.0.1(d3-selection@3.0.0)
d3-zoom: 3.0.0
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+ dagre-d3-es@7.0.10:
dependencies:
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+ d3: 7.9.0
lodash-es: 4.17.21
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- /dayjs@1.11.10:
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- dev: false
+ dayjs@1.11.18: {}
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- engines: {node: '>=6.0'}
- peerDependencies:
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- peerDependenciesMeta:
- supports-color:
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+ debug@4.4.3:
dependencies:
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- dev: false
+ ms: 2.1.3
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+ decode-named-character-reference@1.2.0:
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character-entities: 2.0.2
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- /deepmerge@4.3.1:
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- engines: {node: '>=0.10.0'}
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+ deepmerge@4.3.1: {}
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+ delaunator@5.0.1:
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domhandler: 5.0.3
entities: 4.5.0
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domelementtype: 2.3.0
domhandler: 5.0.3
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- /dot-case@3.0.4:
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+ dot-case@3.0.4:
dependencies:
no-case: 3.0.4
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+ tslib: 2.8.1
- /electron-to-chromium@1.4.616:
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+ elkjs@0.9.3: {}
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+ entities@4.5.0: {}
+
+ entities@6.0.1: {}
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+ escalade@3.2.0: {}
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+ escape-string-regexp@1.0.5: {}
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- engines: {node: '>=12'}
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+ escape-string-regexp@5.0.0: {}
- /esprima@4.0.1:
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- engines: {node: '>=4'}
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+ esprima@4.0.1: {}
- /estree-util-attach-comments@2.1.1:
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+ estree-util-attach-comments@2.1.1:
dependencies:
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- dev: false
+ '@types/estree': 1.0.8
- /estree-util-build-jsx@2.2.2:
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+ estree-util-build-jsx@2.2.2:
dependencies:
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+ '@types/estree-jsx': 1.0.5
estree-util-is-identifier-name: 2.1.0
estree-walker: 3.0.3
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- /estree-util-is-identifier-name@2.1.0:
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- dev: false
+ estree-util-is-identifier-name@2.1.0: {}
- /estree-util-to-js@1.2.0:
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+ estree-util-to-js@1.2.0:
dependencies:
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- astring: 1.8.6
- source-map: 0.7.4
- dev: false
+ '@types/estree-jsx': 1.0.5
+ astring: 1.9.0
+ source-map: 0.7.6
- /estree-util-value-to-estree@1.3.0:
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- engines: {node: '>=12.0.0'}
+ estree-util-value-to-estree@3.4.0:
dependencies:
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- dev: false
+ '@types/estree': 1.0.8
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+ estree-util-visit@1.2.1:
dependencies:
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- '@types/unist': 2.0.10
- dev: false
+ '@types/estree-jsx': 1.0.5
+ '@types/unist': 2.0.11
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+ estree-walker@3.0.3:
dependencies:
- '@types/estree': 1.0.5
- dev: false
+ '@types/estree': 1.0.8
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- engines: {node: '>=0.10.0'}
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+ esutils@2.0.3: {}
- /execa@0.8.0:
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- engines: {node: '>=4'}
+ execa@0.8.0:
dependencies:
cross-spawn: 5.1.0
get-stream: 3.0.0
@@ -2778,512 +3907,302 @@ packages:
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signal-exit: 3.0.7
strip-eof: 1.0.0
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- /extend-shallow@2.0.1:
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- engines: {node: '>=0.10.0'}
+ extend-shallow@2.0.1:
dependencies:
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- /extend@3.0.2:
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+ extend@3.0.2: {}
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+ flexsearch@0.7.43: {}
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- dev: false
+ focus-visible@5.2.1: {}
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+ function-bind@1.1.2: {}
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+ gensync@1.0.0-beta.2: {}
- /get-stream@3.0.0:
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+ get-stream@3.0.0: {}
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+ git-up@7.0.0:
dependencies:
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+ is-ssh: 1.4.1
parse-url: 8.1.0
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- /git-url-parse@13.1.1:
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+ git-url-parse@13.1.1:
dependencies:
git-up: 7.0.0
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+ github-slugger@2.0.0: {}
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+ glob-to-regexp@0.4.1: {}
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+ graceful-fs@4.2.11: {}
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dependencies:
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kind-of: 6.0.3
section-matter: 1.0.0
strip-bom-string: 1.0.0
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dependencies:
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type-fest: 1.4.0
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- engines: {node: '>= 0.4'}
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dependencies:
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dependencies:
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- resolution: {integrity: sha512-7fm3l3NAF9WfN6W3JOmf5drwpVqX78JtoGJ3A6W0a6ZnldM41w2fV5D490psKFTpMds8TJse/eHLFFsNHHjHgg==}
+ lower-case@2.0.2:
dependencies:
- tslib: 2.6.2
- dev: false
+ tslib: 2.8.1
- /lru-cache@4.1.5:
- resolution: {integrity: sha512-sWZlbEP2OsHNkXrMl5GYk/jKk70MBng6UU4YI/qGDYbgf6YbP4EvmqISbXCoJiRKs+1bSpFHVgQxvJ17F2li5g==}
+ lru-cache@4.1.5:
dependencies:
pseudomap: 1.0.2
yallist: 2.1.2
- dev: false
- /lru-cache@5.1.1:
- resolution: {integrity: sha512-KpNARQA3Iwv+jTA0utUVVbrh+Jlrr1Fv0e56GGzAFOXN7dk/FviaDW8LHmK52DlcH4WP2n6gI8vN1aesBFgo9w==}
+ lru-cache@5.1.1:
dependencies:
yallist: 3.1.1
- dev: false
- /markdown-extensions@1.1.1:
- resolution: {integrity: sha512-WWC0ZuMzCyDHYCasEGs4IPvLyTGftYwh6wIEOULOF0HXcqZlhwRzrK0w2VUlxWA98xnvb/jszw4ZSkJ6ADpM6Q==}
- engines: {node: '>=0.10.0'}
- dev: false
+ markdown-extensions@1.1.1: {}
- /markdown-table@3.0.3:
- resolution: {integrity: sha512-Z1NL3Tb1M9wH4XESsCDEksWoKTdlUafKc4pt0GRwjUyXaCFZ+dc3g2erqB6zm3szA2IUSi7VnPI+o/9jnxh9hw==}
- dev: false
+ markdown-table@3.0.4: {}
- /match-sorter@6.3.1:
- resolution: {integrity: sha512-mxybbo3pPNuA+ZuCUhm5bwNkXrJTbsk5VWbR5wiwz/GC6LIiegBGn2w3O08UG/jdbYLinw51fSQ5xNU1U3MgBw==}
+ match-sorter@6.3.4:
dependencies:
- '@babel/runtime': 7.23.7
- remove-accents: 0.4.2
- dev: false
+ '@babel/runtime': 7.28.4
+ remove-accents: 0.5.0
- /mdast-util-definitions@5.1.2:
- resolution: {integrity: sha512-8SVPMuHqlPME/z3gqVwWY4zVXn8lqKv/pAhC57FuJ40ImXyBpmO5ukh98zB2v7Blql2FiHjHv9LVztSIqjY+MA==}
+ mdast-util-definitions@5.1.2:
dependencies:
'@types/mdast': 3.0.15
- '@types/unist': 2.0.10
+ '@types/unist': 2.0.11
unist-util-visit: 4.1.2
- dev: false
- /mdast-util-find-and-replace@2.2.2:
- resolution: {integrity: sha512-MTtdFRz/eMDHXzeK6W3dO7mXUlF82Gom4y0oOgvHhh/HXZAGvIQDUvQ0SuUx+j2tv44b8xTHOm8K/9OoRFnXKw==}
+ mdast-util-find-and-replace@2.2.2:
dependencies:
'@types/mdast': 3.0.15
escape-string-regexp: 5.0.0
unist-util-is: 5.2.1
unist-util-visit-parents: 5.1.3
- dev: false
- /mdast-util-from-markdown@1.3.1:
- resolution: {integrity: sha512-4xTO/M8c82qBcnQc1tgpNtubGUW/Y1tBQ1B0i5CtSoelOLKFYlElIr3bvgREYYO5iRqbMY1YuqZng0GVOI8Qww==}
+ mdast-util-from-markdown@1.3.1:
dependencies:
'@types/mdast': 3.0.15
- '@types/unist': 2.0.10
- decode-named-character-reference: 1.0.2
+ '@types/unist': 2.0.11
+ decode-named-character-reference: 1.2.0
mdast-util-to-string: 3.2.0
micromark: 3.2.0
micromark-util-decode-numeric-character-reference: 1.1.0
@@ -3295,52 +4214,40 @@ packages:
uvu: 0.5.6
transitivePeerDependencies:
- supports-color
- dev: false
- /mdast-util-gfm-autolink-literal@1.0.3:
- resolution: {integrity: sha512-My8KJ57FYEy2W2LyNom4n3E7hKTuQk/0SES0u16tjA9Z3oFkF4RrC/hPAPgjlSpezsOvI8ObcXcElo92wn5IGA==}
+ mdast-util-gfm-autolink-literal@1.0.3:
dependencies:
'@types/mdast': 3.0.15
ccount: 2.0.1
mdast-util-find-and-replace: 2.2.2
micromark-util-character: 1.2.0
- dev: false
- /mdast-util-gfm-footnote@1.0.2:
- resolution: {integrity: sha512-56D19KOGbE00uKVj3sgIykpwKL179QsVFwx/DCW0u/0+URsryacI4MAdNJl0dh+u2PSsD9FtxPFbHCzJ78qJFQ==}
+ mdast-util-gfm-footnote@1.0.2:
dependencies:
'@types/mdast': 3.0.15
mdast-util-to-markdown: 1.5.0
micromark-util-normalize-identifier: 1.1.0
- dev: false
- /mdast-util-gfm-strikethrough@1.0.3:
- resolution: {integrity: sha512-DAPhYzTYrRcXdMjUtUjKvW9z/FNAMTdU0ORyMcbmkwYNbKocDpdk+PX1L1dQgOID/+vVs1uBQ7ElrBQfZ0cuiQ==}
+ mdast-util-gfm-strikethrough@1.0.3:
dependencies:
'@types/mdast': 3.0.15
mdast-util-to-markdown: 1.5.0
- dev: false
- /mdast-util-gfm-table@1.0.7:
- resolution: {integrity: sha512-jjcpmNnQvrmN5Vx7y7lEc2iIOEytYv7rTvu+MeyAsSHTASGCCRA79Igg2uKssgOs1i1po8s3plW0sTu1wkkLGg==}
+ mdast-util-gfm-table@1.0.7:
dependencies:
'@types/mdast': 3.0.15
- markdown-table: 3.0.3
+ markdown-table: 3.0.4
mdast-util-from-markdown: 1.3.1
mdast-util-to-markdown: 1.5.0
transitivePeerDependencies:
- supports-color
- dev: false
- /mdast-util-gfm-task-list-item@1.0.2:
- resolution: {integrity: sha512-PFTA1gzfp1B1UaiJVyhJZA1rm0+Tzn690frc/L8vNX1Jop4STZgOE6bxUhnzdVSB+vm2GU1tIsuQcA9bxTQpMQ==}
+ mdast-util-gfm-task-list-item@1.0.2:
dependencies:
'@types/mdast': 3.0.15
mdast-util-to-markdown: 1.5.0
- dev: false
- /mdast-util-gfm@2.0.2:
- resolution: {integrity: sha512-qvZ608nBppZ4icQlhQQIAdc6S3Ffj9RGmzwUKUWuEICFnd1LVkN3EktF7ZHAgfcEdvZB5owU9tQgt99e2TlLjg==}
+ mdast-util-gfm@2.0.2:
dependencies:
mdast-util-from-markdown: 1.3.1
mdast-util-gfm-autolink-literal: 1.0.3
@@ -3351,49 +4258,41 @@ packages:
mdast-util-to-markdown: 1.5.0
transitivePeerDependencies:
- supports-color
- dev: false
- /mdast-util-math@2.0.2:
- resolution: {integrity: sha512-8gmkKVp9v6+Tgjtq6SYx9kGPpTf6FVYRa53/DLh479aldR9AyP48qeVOgNZ5X7QUK7nOy4yw7vg6mbiGcs9jWQ==}
+ mdast-util-math@2.0.2:
dependencies:
'@types/mdast': 3.0.15
longest-streak: 3.1.0
mdast-util-to-markdown: 1.5.0
- dev: false
- /mdast-util-mdx-expression@1.3.2:
- resolution: {integrity: sha512-xIPmR5ReJDu/DHH1OoIT1HkuybIfRGYRywC+gJtI7qHjCJp/M9jrmBEJW22O8lskDWm562BX2W8TiAwRTb0rKA==}
+ mdast-util-mdx-expression@1.3.2:
dependencies:
- '@types/estree-jsx': 1.0.3
- '@types/hast': 2.3.9
+ '@types/estree-jsx': 1.0.5
+ '@types/hast': 2.3.10
'@types/mdast': 3.0.15
mdast-util-from-markdown: 1.3.1
mdast-util-to-markdown: 1.5.0
transitivePeerDependencies:
- supports-color
- dev: false
- /mdast-util-mdx-jsx@2.1.4:
- resolution: {integrity: sha512-DtMn9CmVhVzZx3f+optVDF8yFgQVt7FghCRNdlIaS3X5Bnym3hZwPbg/XW86vdpKjlc1PVj26SpnLGeJBXD3JA==}
+ mdast-util-mdx-jsx@2.1.4:
dependencies:
- '@types/estree-jsx': 1.0.3
- '@types/hast': 2.3.9
+ '@types/estree-jsx': 1.0.5
+ '@types/hast': 2.3.10
'@types/mdast': 3.0.15
- '@types/unist': 2.0.10
+ '@types/unist': 2.0.11
ccount: 2.0.1
mdast-util-from-markdown: 1.3.1
mdast-util-to-markdown: 1.5.0
- parse-entities: 4.0.1
- stringify-entities: 4.0.3
+ parse-entities: 4.0.2
+ stringify-entities: 4.0.4
unist-util-remove-position: 4.0.2
unist-util-stringify-position: 3.0.3
vfile-message: 3.1.4
transitivePeerDependencies:
- supports-color
- dev: false
- /mdast-util-mdx@2.0.1:
- resolution: {integrity: sha512-38w5y+r8nyKlGvNjSEqWrhG0w5PmnRA+wnBvm+ulYCct7nsGYhFVb0lljS9bQav4psDAS1eGkP2LMVcZBi/aqw==}
+ mdast-util-mdx@2.0.1:
dependencies:
mdast-util-from-markdown: 1.3.1
mdast-util-mdx-expression: 1.3.2
@@ -3402,31 +4301,25 @@ packages:
mdast-util-to-markdown: 1.5.0
transitivePeerDependencies:
- supports-color
- dev: false
- /mdast-util-mdxjs-esm@1.3.1:
- resolution: {integrity: sha512-SXqglS0HrEvSdUEfoXFtcg7DRl7S2cwOXc7jkuusG472Mmjag34DUDeOJUZtl+BVnyeO1frIgVpHlNRWc2gk/w==}
+ mdast-util-mdxjs-esm@1.3.1:
dependencies:
- '@types/estree-jsx': 1.0.3
- '@types/hast': 2.3.9
+ '@types/estree-jsx': 1.0.5
+ '@types/hast': 2.3.10
'@types/mdast': 3.0.15
mdast-util-from-markdown: 1.3.1
mdast-util-to-markdown: 1.5.0
transitivePeerDependencies:
- supports-color
- dev: false
- /mdast-util-phrasing@3.0.1:
- resolution: {integrity: sha512-WmI1gTXUBJo4/ZmSk79Wcb2HcjPJBzM1nlI/OUWA8yk2X9ik3ffNbBGsU+09BFmXaL1IBb9fiuvq6/KMiNycSg==}
+ mdast-util-phrasing@3.0.1:
dependencies:
'@types/mdast': 3.0.15
unist-util-is: 5.2.1
- dev: false
- /mdast-util-to-hast@12.3.0:
- resolution: {integrity: sha512-pits93r8PhnIoU4Vy9bjW39M2jJ6/tdHyja9rrot9uujkN7UTU9SDnE6WNJz/IGyQk3XHX6yNNtrBH6cQzm8Hw==}
+ mdast-util-to-hast@12.3.0:
dependencies:
- '@types/hast': 2.3.9
+ '@types/hast': 2.3.10
'@types/mdast': 3.0.15
mdast-util-definitions: 5.1.2
micromark-util-sanitize-uri: 1.2.0
@@ -3434,79 +4327,66 @@ packages:
unist-util-generated: 2.0.1
unist-util-position: 4.0.4
unist-util-visit: 4.1.2
- dev: false
- /mdast-util-to-hast@13.0.2:
- resolution: {integrity: sha512-U5I+500EOOw9e3ZrclN3Is3fRpw8c19SMyNZlZ2IS+7vLsNzb2Om11VpIVOR+/0137GhZsFEF6YiKD5+0Hr2Og==}
+ mdast-util-to-hast@13.2.0:
dependencies:
- '@types/hast': 3.0.3
- '@types/mdast': 4.0.3
- '@ungap/structured-clone': 1.2.0
+ '@types/hast': 3.0.4
+ '@types/mdast': 4.0.4
+ '@ungap/structured-clone': 1.3.0
devlop: 1.1.0
- micromark-util-sanitize-uri: 2.0.0
+ micromark-util-sanitize-uri: 2.0.1
trim-lines: 3.0.1
unist-util-position: 5.0.0
unist-util-visit: 5.0.0
- dev: false
+ vfile: 6.0.3
- /mdast-util-to-markdown@1.5.0:
- resolution: {integrity: sha512-bbv7TPv/WC49thZPg3jXuqzuvI45IL2EVAr/KxF0BSdHsU0ceFHOmwQn6evxAh1GaoK/6GQ1wp4R4oW2+LFL/A==}
+ mdast-util-to-markdown@1.5.0:
dependencies:
'@types/mdast': 3.0.15
- '@types/unist': 2.0.10
+ '@types/unist': 2.0.11
longest-streak: 3.1.0
mdast-util-phrasing: 3.0.1
mdast-util-to-string: 3.2.0
micromark-util-decode-string: 1.1.0
unist-util-visit: 4.1.2
zwitch: 2.0.4
- dev: false
- /mdast-util-to-string@3.2.0:
- resolution: {integrity: sha512-V4Zn/ncyN1QNSqSBxTrMOLpjr+IKdHl2v3KVLoWmDPscP4r9GcCi71gjgvUV1SFSKh92AjAG4peFuBl2/YgCJg==}
+ mdast-util-to-string@3.2.0:
dependencies:
'@types/mdast': 3.0.15
- dev: false
- /mdn-data@2.0.28:
- resolution: {integrity: sha512-aylIc7Z9y4yzHYAJNuESG3hfhC+0Ibp/MAMiaOZgNv4pmEdFyfZhhhny4MNiAfWdBQ1RQ2mfDWmM1x8SvGyp8g==}
- dev: false
+ mdn-data@2.0.28: {}
- /mdn-data@2.0.30:
- resolution: {integrity: sha512-GaqWWShW4kv/G9IEucWScBx9G1/vsFZZJUO+tD26M8J8z3Kw5RDQjaoZe03YAClgeS/SWPOcb4nkFBTEi5DUEA==}
- dev: false
+ mdn-data@2.0.30: {}
- /mermaid@10.6.1:
- resolution: {integrity: sha512-Hky0/RpOw/1il9X8AvzOEChfJtVvmXm+y7JML5C//ePYMy0/9jCEmW1E1g86x9oDfW9+iVEdTV/i+M6KWRNs4A==}
+ mermaid@10.9.4:
dependencies:
'@braintree/sanitize-url': 6.0.4
- '@types/d3-scale': 4.0.8
- '@types/d3-scale-chromatic': 3.0.3
- cytoscape: 3.28.1
- cytoscape-cose-bilkent: 4.1.0(cytoscape@3.28.1)
- cytoscape-fcose: 2.2.0(cytoscape@3.28.1)
- d3: 7.8.5
+ '@types/d3-scale': 4.0.9
+ '@types/d3-scale-chromatic': 3.1.0
+ cytoscape: 3.33.1
+ cytoscape-cose-bilkent: 4.1.0(cytoscape@3.33.1)
+ d3: 7.9.0
d3-sankey: 0.12.3
dagre-d3-es: 7.0.10
- dayjs: 1.11.10
- dompurify: 3.0.6
- elkjs: 0.8.2
+ dayjs: 1.11.18
+ dompurify: 3.1.6
+ elkjs: 0.9.3
+ katex: 0.16.24
khroma: 2.1.0
lodash-es: 4.17.21
mdast-util-from-markdown: 1.3.1
non-layered-tidy-tree-layout: 2.0.2
- stylis: 4.3.1
+ stylis: 4.3.6
ts-dedent: 2.2.0
uuid: 9.0.1
- web-worker: 1.2.0
+ web-worker: 1.5.0
transitivePeerDependencies:
- supports-color
- dev: false
- /micromark-core-commonmark@1.1.0:
- resolution: {integrity: sha512-BgHO1aRbolh2hcrzL2d1La37V0Aoz73ymF8rAcKnohLy93titmv62E0gP8Hrx9PKcKrqCZ1BbLGbP3bEhoXYlw==}
+ micromark-core-commonmark@1.1.0:
dependencies:
- decode-named-character-reference: 1.0.2
+ decode-named-character-reference: 1.2.0
micromark-factory-destination: 1.1.0
micromark-factory-label: 1.1.0
micromark-factory-space: 1.1.0
@@ -3522,19 +4402,15 @@ packages:
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
uvu: 0.5.6
- dev: false
- /micromark-extension-gfm-autolink-literal@1.0.5:
- resolution: {integrity: sha512-z3wJSLrDf8kRDOh2qBtoTRD53vJ+CWIyo7uyZuxf/JAbNJjiHsOpG1y5wxk8drtv3ETAHutCu6N3thkOOgueWg==}
+ micromark-extension-gfm-autolink-literal@1.0.5:
dependencies:
micromark-util-character: 1.2.0
micromark-util-sanitize-uri: 1.2.0
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
- dev: false
- /micromark-extension-gfm-footnote@1.1.2:
- resolution: {integrity: sha512-Yxn7z7SxgyGWRNa4wzf8AhYYWNrwl5q1Z8ii+CSTTIqVkmGZF1CElX2JI8g5yGoM3GAman9/PVCUFUSJ0kB/8Q==}
+ micromark-extension-gfm-footnote@1.1.2:
dependencies:
micromark-core-commonmark: 1.1.0
micromark-factory-space: 1.1.0
@@ -3544,10 +4420,8 @@ packages:
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
uvu: 0.5.6
- dev: false
- /micromark-extension-gfm-strikethrough@1.0.7:
- resolution: {integrity: sha512-sX0FawVE1o3abGk3vRjOH50L5TTLr3b5XMqnP9YDRb34M0v5OoZhG+OHFz1OffZ9dlwgpTBKaT4XW/AsUVnSDw==}
+ micromark-extension-gfm-strikethrough@1.0.7:
dependencies:
micromark-util-chunked: 1.1.0
micromark-util-classify-character: 1.1.0
@@ -3555,36 +4429,28 @@ packages:
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
uvu: 0.5.6
- dev: false
- /micromark-extension-gfm-table@1.0.7:
- resolution: {integrity: sha512-3ZORTHtcSnMQEKtAOsBQ9/oHp9096pI/UvdPtN7ehKvrmZZ2+bbWhi0ln+I9drmwXMt5boocn6OlwQzNXeVeqw==}
+ micromark-extension-gfm-table@1.0.7:
dependencies:
micromark-factory-space: 1.1.0
micromark-util-character: 1.2.0
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
uvu: 0.5.6
- dev: false
- /micromark-extension-gfm-tagfilter@1.0.2:
- resolution: {integrity: sha512-5XWB9GbAUSHTn8VPU8/1DBXMuKYT5uOgEjJb8gN3mW0PNW5OPHpSdojoqf+iq1xo7vWzw/P8bAHY0n6ijpXF7g==}
+ micromark-extension-gfm-tagfilter@1.0.2:
dependencies:
micromark-util-types: 1.1.0
- dev: false
- /micromark-extension-gfm-task-list-item@1.0.5:
- resolution: {integrity: sha512-RMFXl2uQ0pNQy6Lun2YBYT9g9INXtWJULgbt01D/x8/6yJ2qpKyzdZD3pi6UIkzF++Da49xAelVKUeUMqd5eIQ==}
+ micromark-extension-gfm-task-list-item@1.0.5:
dependencies:
micromark-factory-space: 1.1.0
micromark-util-character: 1.2.0
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
uvu: 0.5.6
- dev: false
- /micromark-extension-gfm@2.0.3:
- resolution: {integrity: sha512-vb9OoHqrhCmbRidQv/2+Bc6pkP0FrtlhurxZofvOEy5o8RtuuvTq+RQ1Vw5ZDNrVraQZu3HixESqbG+0iKk/MQ==}
+ micromark-extension-gfm@2.0.3:
dependencies:
micromark-extension-gfm-autolink-literal: 1.0.5
micromark-extension-gfm-footnote: 1.1.2
@@ -3594,24 +4460,20 @@ packages:
micromark-extension-gfm-task-list-item: 1.0.5
micromark-util-combine-extensions: 1.1.0
micromark-util-types: 1.1.0
- dev: false
- /micromark-extension-math@2.1.2:
- resolution: {integrity: sha512-es0CcOV89VNS9wFmyn+wyFTKweXGW4CEvdaAca6SWRWPyYCbBisnjaHLjWO4Nszuiud84jCpkHsqAJoa768Pvg==}
+ micromark-extension-math@2.1.2:
dependencies:
'@types/katex': 0.16.7
- katex: 0.16.9
+ katex: 0.16.24
micromark-factory-space: 1.1.0
micromark-util-character: 1.2.0
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
uvu: 0.5.6
- dev: false
- /micromark-extension-mdx-expression@1.0.8:
- resolution: {integrity: sha512-zZpeQtc5wfWKdzDsHRBY003H2Smg+PUi2REhqgIhdzAa5xonhP03FcXxqFSerFiNUr5AWmHpaNPQTBVOS4lrXw==}
+ micromark-extension-mdx-expression@1.0.8:
dependencies:
- '@types/estree': 1.0.5
+ '@types/estree': 1.0.8
micromark-factory-mdx-expression: 1.0.9
micromark-factory-space: 1.1.0
micromark-util-character: 1.2.0
@@ -3619,13 +4481,11 @@ packages:
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
uvu: 0.5.6
- dev: false
- /micromark-extension-mdx-jsx@1.0.5:
- resolution: {integrity: sha512-gPH+9ZdmDflbu19Xkb8+gheqEDqkSpdCEubQyxuz/Hn8DOXiXvrXeikOoBA71+e8Pfi0/UYmU3wW3H58kr7akA==}
+ micromark-extension-mdx-jsx@1.0.5:
dependencies:
'@types/acorn': 4.0.6
- '@types/estree': 1.0.5
+ '@types/estree': 1.0.8
estree-util-is-identifier-name: 2.1.0
micromark-factory-mdx-expression: 1.0.9
micromark-factory-space: 1.1.0
@@ -3634,18 +4494,14 @@ packages:
micromark-util-types: 1.1.0
uvu: 0.5.6
vfile-message: 3.1.4
- dev: false
- /micromark-extension-mdx-md@1.0.1:
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+ micromark-extension-mdx-md@1.0.1:
dependencies:
micromark-util-types: 1.1.0
- dev: false
- /micromark-extension-mdxjs-esm@1.0.5:
- resolution: {integrity: sha512-xNRBw4aoURcyz/S69B19WnZAkWJMxHMT5hE36GtDAyhoyn/8TuAeqjFJQlwk+MKQsUD7b3l7kFX+vlfVWgcX1w==}
+ micromark-extension-mdxjs-esm@1.0.5:
dependencies:
- '@types/estree': 1.0.5
+ '@types/estree': 1.0.8
micromark-core-commonmark: 1.1.0
micromark-util-character: 1.2.0
micromark-util-events-to-acorn: 1.2.3
@@ -3654,42 +4510,34 @@ packages:
unist-util-position-from-estree: 1.1.2
uvu: 0.5.6
vfile-message: 3.1.4
- dev: false
- /micromark-extension-mdxjs@1.0.1:
- resolution: {integrity: sha512-7YA7hF6i5eKOfFUzZ+0z6avRG52GpWR8DL+kN47y3f2KhxbBZMhmxe7auOeaTBrW2DenbbZTf1ea9tA2hDpC2Q==}
+ micromark-extension-mdxjs@1.0.1:
dependencies:
- acorn: 8.11.3
- acorn-jsx: 5.3.2(acorn@8.11.3)
+ acorn: 8.15.0
+ acorn-jsx: 5.3.2(acorn@8.15.0)
micromark-extension-mdx-expression: 1.0.8
micromark-extension-mdx-jsx: 1.0.5
micromark-extension-mdx-md: 1.0.1
micromark-extension-mdxjs-esm: 1.0.5
micromark-util-combine-extensions: 1.1.0
micromark-util-types: 1.1.0
- dev: false
- /micromark-factory-destination@1.1.0:
- resolution: {integrity: sha512-XaNDROBgx9SgSChd69pjiGKbV+nfHGDPVYFs5dOoDd7ZnMAE+Cuu91BCpsY8RT2NP9vo/B8pds2VQNCLiu0zhg==}
+ micromark-factory-destination@1.1.0:
dependencies:
micromark-util-character: 1.2.0
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
- dev: false
- /micromark-factory-label@1.1.0:
- resolution: {integrity: sha512-OLtyez4vZo/1NjxGhcpDSbHQ+m0IIGnT8BoPamh+7jVlzLJBH98zzuCoUeMxvM6WsNeh8wx8cKvqLiPHEACn0w==}
+ micromark-factory-label@1.1.0:
dependencies:
micromark-util-character: 1.2.0
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
uvu: 0.5.6
- dev: false
- /micromark-factory-mdx-expression@1.0.9:
- resolution: {integrity: sha512-jGIWzSmNfdnkJq05c7b0+Wv0Kfz3NJ3N4cBjnbO4zjXIlxJr+f8lk+5ZmwFvqdAbUy2q6B5rCY//g0QAAaXDWA==}
+ micromark-factory-mdx-expression@1.0.9:
dependencies:
- '@types/estree': 1.0.5
+ '@types/estree': 1.0.8
micromark-util-character: 1.2.0
micromark-util-events-to-acorn: 1.2.3
micromark-util-symbol: 1.1.0
@@ -3697,167 +4545,119 @@ packages:
unist-util-position-from-estree: 1.1.2
uvu: 0.5.6
vfile-message: 3.1.4
- dev: false
- /micromark-factory-space@1.1.0:
- resolution: {integrity: sha512-cRzEj7c0OL4Mw2v6nwzttyOZe8XY/Z8G0rzmWQZTBi/jjwyw/U4uqKtUORXQrR5bAZZnbTI/feRV/R7hc4jQYQ==}
+ micromark-factory-space@1.1.0:
dependencies:
micromark-util-character: 1.2.0
micromark-util-types: 1.1.0
- dev: false
- /micromark-factory-title@1.1.0:
- resolution: {integrity: sha512-J7n9R3vMmgjDOCY8NPw55jiyaQnH5kBdV2/UXCtZIpnHH3P6nHUKaH7XXEYuWwx/xUJcawa8plLBEjMPU24HzQ==}
+ micromark-factory-title@1.1.0:
dependencies:
micromark-factory-space: 1.1.0
micromark-util-character: 1.2.0
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
- dev: false
- /micromark-factory-whitespace@1.1.0:
- resolution: {integrity: sha512-v2WlmiymVSp5oMg+1Q0N1Lxmt6pMhIHD457whWM7/GUlEks1hI9xj5w3zbc4uuMKXGisksZk8DzP2UyGbGqNsQ==}
+ micromark-factory-whitespace@1.1.0:
dependencies:
micromark-factory-space: 1.1.0
micromark-util-character: 1.2.0
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
- dev: false
- /micromark-util-character@1.2.0:
- resolution: {integrity: sha512-lXraTwcX3yH/vMDaFWCQJP1uIszLVebzUa3ZHdrgxr7KEU/9mL4mVgCpGbyhvNLNlauROiNUq7WN5u7ndbY6xg==}
+ micromark-util-character@1.2.0:
dependencies:
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
- dev: false
- /micromark-util-character@2.0.1:
- resolution: {integrity: sha512-3wgnrmEAJ4T+mGXAUfMvMAbxU9RDG43XmGce4j6CwPtVxB3vfwXSZ6KhFwDzZ3mZHhmPimMAXg71veiBGzeAZw==}
+ micromark-util-character@2.1.1:
dependencies:
- micromark-util-symbol: 2.0.0
- micromark-util-types: 2.0.0
- dev: false
+ micromark-util-symbol: 2.0.1
+ micromark-util-types: 2.0.2
- /micromark-util-chunked@1.1.0:
- resolution: {integrity: sha512-Ye01HXpkZPNcV6FiyoW2fGZDUw4Yc7vT0E9Sad83+bEDiCJ1uXu0S3mr8WLpsz3HaG3x2q0HM6CTuPdcZcluFQ==}
+ micromark-util-chunked@1.1.0:
dependencies:
micromark-util-symbol: 1.1.0
- dev: false
- /micromark-util-classify-character@1.1.0:
- resolution: {integrity: sha512-SL0wLxtKSnklKSUplok1WQFoGhUdWYKggKUiqhX+Swala+BtptGCu5iPRc+xvzJ4PXE/hwM3FNXsfEVgoZsWbw==}
+ micromark-util-classify-character@1.1.0:
dependencies:
micromark-util-character: 1.2.0
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
- dev: false
- /micromark-util-combine-extensions@1.1.0:
- resolution: {integrity: sha512-Q20sp4mfNf9yEqDL50WwuWZHUrCO4fEyeDCnMGmG5Pr0Cz15Uo7KBs6jq+dq0EgX4DPwwrh9m0X+zPV1ypFvUA==}
+ micromark-util-combine-extensions@1.1.0:
dependencies:
micromark-util-chunked: 1.1.0
micromark-util-types: 1.1.0
- dev: false
- /micromark-util-decode-numeric-character-reference@1.1.0:
- resolution: {integrity: sha512-m9V0ExGv0jB1OT21mrWcuf4QhP46pH1KkfWy9ZEezqHKAxkj4mPCy3nIH1rkbdMlChLHX531eOrymlwyZIf2iw==}
+ micromark-util-decode-numeric-character-reference@1.1.0:
dependencies:
micromark-util-symbol: 1.1.0
- dev: false
- /micromark-util-decode-string@1.1.0:
- resolution: {integrity: sha512-YphLGCK8gM1tG1bd54azwyrQRjCFcmgj2S2GoJDNnh4vYtnL38JS8M4gpxzOPNyHdNEpheyWXCTnnTDY3N+NVQ==}
+ micromark-util-decode-string@1.1.0:
dependencies:
- decode-named-character-reference: 1.0.2
+ decode-named-character-reference: 1.2.0
micromark-util-character: 1.2.0
micromark-util-decode-numeric-character-reference: 1.1.0
micromark-util-symbol: 1.1.0
- dev: false
- /micromark-util-encode@1.1.0:
- resolution: {integrity: sha512-EuEzTWSTAj9PA5GOAs992GzNh2dGQO52UvAbtSOMvXTxv3Criqb6IOzJUBCmEqrrXSblJIJBbFFv6zPxpreiJw==}
- dev: false
+ micromark-util-encode@1.1.0: {}
- /micromark-util-encode@2.0.0:
- resolution: {integrity: sha512-pS+ROfCXAGLWCOc8egcBvT0kf27GoWMqtdarNfDcjb6YLuV5cM3ioG45Ys2qOVqeqSbjaKg72vU+Wby3eddPsA==}
- dev: false
+ micromark-util-encode@2.0.1: {}
- /micromark-util-events-to-acorn@1.2.3:
- resolution: {integrity: sha512-ij4X7Wuc4fED6UoLWkmo0xJQhsktfNh1J0m8g4PbIMPlx+ek/4YdW5mvbye8z/aZvAPUoxgXHrwVlXAPKMRp1w==}
+ micromark-util-events-to-acorn@1.2.3:
dependencies:
'@types/acorn': 4.0.6
- '@types/estree': 1.0.5
- '@types/unist': 2.0.10
+ '@types/estree': 1.0.8
+ '@types/unist': 2.0.11
estree-util-visit: 1.2.1
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
uvu: 0.5.6
vfile-message: 3.1.4
- dev: false
- /micromark-util-html-tag-name@1.2.0:
- resolution: {integrity: sha512-VTQzcuQgFUD7yYztuQFKXT49KghjtETQ+Wv/zUjGSGBioZnkA4P1XXZPT1FHeJA6RwRXSF47yvJ1tsJdoxwO+Q==}
- dev: false
+ micromark-util-html-tag-name@1.2.0: {}
- /micromark-util-normalize-identifier@1.1.0:
- resolution: {integrity: sha512-N+w5vhqrBihhjdpM8+5Xsxy71QWqGn7HYNUvch71iV2PM7+E3uWGox1Qp90loa1ephtCxG2ftRV/Conitc6P2Q==}
+ micromark-util-normalize-identifier@1.1.0:
dependencies:
micromark-util-symbol: 1.1.0
- dev: false
- /micromark-util-resolve-all@1.1.0:
- resolution: {integrity: sha512-b/G6BTMSg+bX+xVCshPTPyAu2tmA0E4X98NSR7eIbeC6ycCqCeE7wjfDIgzEbkzdEVJXRtOG4FbEm/uGbCRouA==}
+ micromark-util-resolve-all@1.1.0:
dependencies:
micromark-util-types: 1.1.0
- dev: false
- /micromark-util-sanitize-uri@1.2.0:
- resolution: {integrity: sha512-QO4GXv0XZfWey4pYFndLUKEAktKkG5kZTdUNaTAkzbuJxn2tNBOr+QtxR2XpWaMhbImT2dPzyLrPXLlPhph34A==}
+ micromark-util-sanitize-uri@1.2.0:
dependencies:
micromark-util-character: 1.2.0
micromark-util-encode: 1.1.0
micromark-util-symbol: 1.1.0
- dev: false
- /micromark-util-sanitize-uri@2.0.0:
- resolution: {integrity: sha512-WhYv5UEcZrbAtlsnPuChHUAsu/iBPOVaEVsntLBIdpibO0ddy8OzavZz3iL2xVvBZOpolujSliP65Kq0/7KIYw==}
+ micromark-util-sanitize-uri@2.0.1:
dependencies:
- micromark-util-character: 2.0.1
- micromark-util-encode: 2.0.0
- micromark-util-symbol: 2.0.0
- dev: false
+ micromark-util-character: 2.1.1
+ micromark-util-encode: 2.0.1
+ micromark-util-symbol: 2.0.1
- /micromark-util-subtokenize@1.1.0:
- resolution: {integrity: sha512-kUQHyzRoxvZO2PuLzMt2P/dwVsTiivCK8icYTeR+3WgbuPqfHgPPy7nFKbeqRivBvn/3N3GBiNC+JRTMSxEC7A==}
+ micromark-util-subtokenize@1.1.0:
dependencies:
micromark-util-chunked: 1.1.0
micromark-util-symbol: 1.1.0
micromark-util-types: 1.1.0
uvu: 0.5.6
- dev: false
- /micromark-util-symbol@1.1.0:
- resolution: {integrity: sha512-uEjpEYY6KMs1g7QfJ2eX1SQEV+ZT4rUD3UcF6l57acZvLNK7PBZL+ty82Z1qhK1/yXIY4bdx04FKMgR0g4IAag==}
- dev: false
+ micromark-util-symbol@1.1.0: {}
- /micromark-util-symbol@2.0.0:
- resolution: {integrity: sha512-8JZt9ElZ5kyTnO94muPxIGS8oyElRJaiJO8EzV6ZSyGQ1Is8xwl4Q45qU5UOg+bGH4AikWziz0iN4sFLWs8PGw==}
- dev: false
+ micromark-util-symbol@2.0.1: {}
- /micromark-util-types@1.1.0:
- resolution: {integrity: sha512-ukRBgie8TIAcacscVHSiddHjO4k/q3pnedmzMQ4iwDcK0FtFCohKOlFbaOL/mPgfnPsL3C1ZyxJa4sbWrBl3jg==}
- dev: false
+ micromark-util-types@1.1.0: {}
- /micromark-util-types@2.0.0:
- resolution: {integrity: sha512-oNh6S2WMHWRZrmutsRmDDfkzKtxF+bc2VxLC9dvtrDIRFln627VsFP6fLMgTryGDljgLPjkrzQSDcPrjPyDJ5w==}
- dev: false
+ micromark-util-types@2.0.2: {}
- /micromark@3.2.0:
- resolution: {integrity: sha512-uD66tJj54JLYq0De10AhWycZWGQNUvDI55xPgk2sQM5kn1JYlhbCMTtEeT27+vAhW2FBQxLlOmS3pmA7/2z4aA==}
+ micromark@3.2.0:
dependencies:
'@types/debug': 4.1.12
- debug: 4.3.4
- decode-named-character-reference: 1.0.2
+ debug: 4.4.3
+ decode-named-character-reference: 1.2.0
micromark-core-commonmark: 1.1.0
micromark-factory-space: 1.1.0
micromark-util-character: 1.2.0
@@ -3874,427 +4674,270 @@ packages:
uvu: 0.5.6
transitivePeerDependencies:
- supports-color
- dev: false
- /mri@1.2.0:
- resolution: {integrity: sha512-tzzskb3bG8LvYGFF/mDTpq3jpI6Q9wc3LEmBaghu+DdCssd1FakN7Bc0hVNmEyGq1bq3RgfkCb3cmQLpNPOroA==}
- engines: {node: '>=4'}
- dev: false
+ mri@1.2.0: {}
- /ms@2.1.2:
- resolution: {integrity: sha512-sGkPx+VjMtmA6MX27oA4FBFELFCZZ4S4XqeGOXCv68tT+jb3vk/RyaKWP0PTKyWtmLSM0b+adUTEvbs1PEaH2w==}
- dev: false
+ ms@2.1.3: {}
- /nanoid@3.3.7:
- resolution: {integrity: sha512-eSRppjcPIatRIMC1U6UngP8XFcz8MQWGQdt1MTBQ7NaAmvXDfvNxbvWV3x2y6CdEUciCSsDHDQZbhYaB8QEo2g==}
- engines: {node: ^10 || ^12 || ^13.7 || ^14 || >=15.0.1}
- hasBin: true
- dev: false
+ nanoid@3.3.11: {}
- /next-mdx-remote@4.4.1(react-dom@18.2.0)(react@18.2.0):
- resolution: {integrity: sha512-1BvyXaIou6xy3XoNF4yaMZUCb6vD2GTAa5ciOa6WoO+gAUTYsb1K4rI/HSC2ogAWLrb/7VSV52skz07vOzmqIQ==}
- engines: {node: '>=14', npm: '>=7'}
- peerDependencies:
- react: '>=16.x <=18.x'
- react-dom: '>=16.x <=18.x'
+ next-mdx-remote@4.4.1(react-dom@18.3.1(react@18.3.1))(react@18.3.1):
dependencies:
'@mdx-js/mdx': 2.3.0
- '@mdx-js/react': 2.3.0(react@18.2.0)
- react: 18.2.0
- react-dom: 18.2.0(react@18.2.0)
+ '@mdx-js/react': 2.3.0(react@18.3.1)
+ react: 18.3.1
+ react-dom: 18.3.1(react@18.3.1)
vfile: 5.3.7
vfile-matter: 3.0.1
transitivePeerDependencies:
- supports-color
- dev: false
- /next-seo@6.4.0(next@13.5.6)(react-dom@18.2.0)(react@18.2.0):
- resolution: {integrity: sha512-XQFxkOL2hw0YE+P100HbI3EAvcludlHPxuzMgaIjKb7kPK0CvjGvLFjd9hszZFEDc5oiQkGFA8+cuWcnip7eYA==}
- peerDependencies:
- next: ^8.1.1-canary.54 || >=9.0.0
- react: '>=16.0.0'
- react-dom: '>=16.0.0'
+ next-seo@6.8.0(next@13.5.11(@babel/core@7.28.4)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react-dom@18.3.1(react@18.3.1))(react@18.3.1):
dependencies:
- next: 13.5.6(react-dom@18.2.0)(react@18.2.0)
- react: 18.2.0
- react-dom: 18.2.0(react@18.2.0)
- dev: false
+ next: 13.5.11(@babel/core@7.28.4)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
+ react: 18.3.1
+ react-dom: 18.3.1(react@18.3.1)
- /next-themes@0.2.1(next@13.5.6)(react-dom@18.2.0)(react@18.2.0):
- resolution: {integrity: sha512-B+AKNfYNIzh0vqQQKqQItTS8evEouKD7H5Hj3kmuPERwddR2TxvDSFZuTj6T7Jfn1oyeUyJMydPl1Bkxkh0W7A==}
- peerDependencies:
- next: '*'
- react: '*'
- react-dom: '*'
+ next-themes@0.2.1(next@13.5.11(@babel/core@7.28.4)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react-dom@18.3.1(react@18.3.1))(react@18.3.1):
dependencies:
- next: 13.5.6(react-dom@18.2.0)(react@18.2.0)
- react: 18.2.0
- react-dom: 18.2.0(react@18.2.0)
- dev: false
+ next: 13.5.11(@babel/core@7.28.4)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
+ react: 18.3.1
+ react-dom: 18.3.1(react@18.3.1)
- /next@13.5.6(react-dom@18.2.0)(react@18.2.0):
- resolution: {integrity: sha512-Y2wTcTbO4WwEsVb4A8VSnOsG1I9ok+h74q0ZdxkwM3EODqrs4pasq7O0iUxbcS9VtWMicG7f3+HAj0r1+NtKSw==}
- engines: {node: '>=16.14.0'}
- hasBin: true
- peerDependencies:
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- react: ^18.2.0
- react-dom: ^18.2.0
- sass: ^1.3.0
- peerDependenciesMeta:
- '@opentelemetry/api':
- optional: true
- sass:
- optional: true
+ next@13.5.11(@babel/core@7.28.4)(react-dom@18.3.1(react@18.3.1))(react@18.3.1):
dependencies:
- '@next/env': 13.5.6
+ '@next/env': 13.5.11
'@swc/helpers': 0.5.2
busboy: 1.6.0
- caniuse-lite: 1.0.30001636
+ caniuse-lite: 1.0.30001750
postcss: 8.4.31
- react: 18.2.0
- react-dom: 18.2.0(react@18.2.0)
- styled-jsx: 5.1.1(react@18.2.0)
+ react: 18.3.1
+ react-dom: 18.3.1(react@18.3.1)
+ styled-jsx: 5.1.1(@babel/core@7.28.4)(react@18.3.1)
watchpack: 2.4.0
optionalDependencies:
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- '@next/swc-darwin-x64': 13.5.6
- '@next/swc-linux-arm64-gnu': 13.5.6
- '@next/swc-linux-arm64-musl': 13.5.6
- '@next/swc-linux-x64-gnu': 13.5.6
- '@next/swc-linux-x64-musl': 13.5.6
- '@next/swc-win32-arm64-msvc': 13.5.6
- '@next/swc-win32-ia32-msvc': 13.5.6
- '@next/swc-win32-x64-msvc': 13.5.6
+ '@next/swc-darwin-arm64': 13.5.9
+ '@next/swc-darwin-x64': 13.5.9
+ '@next/swc-linux-arm64-gnu': 13.5.9
+ '@next/swc-linux-arm64-musl': 13.5.9
+ '@next/swc-linux-x64-gnu': 13.5.9
+ '@next/swc-linux-x64-musl': 13.5.9
+ '@next/swc-win32-arm64-msvc': 13.5.9
+ '@next/swc-win32-ia32-msvc': 13.5.9
+ '@next/swc-win32-x64-msvc': 13.5.9
transitivePeerDependencies:
- '@babel/core'
- babel-plugin-macros
- dev: false
- /nextra-theme-docs@2.13.2(next@13.5.6)(nextra@2.13.2)(react-dom@18.2.0)(react@18.2.0):
- resolution: {integrity: sha512-yE4umXaImp1/kf/sFciPj2+EFrNSwd9Db26hi98sIIiujzGf3+9eUgAz45vF9CwBw50FSXxm1QGRcY+slQ4xQQ==}
- peerDependencies:
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- nextra: 2.13.2
- react: '>=16.13.1'
- react-dom: '>=16.13.1'
+ nextra-theme-docs@2.13.4(next@13.5.11(@babel/core@7.28.4)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(nextra@2.13.4(next@13.5.11(@babel/core@7.28.4)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react-dom@18.3.1(react@18.3.1))(react@18.3.1):
dependencies:
- '@headlessui/react': 1.7.17(react-dom@18.2.0)(react@18.2.0)
+ '@headlessui/react': 1.7.19(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
'@popperjs/core': 2.11.8
- clsx: 2.1.0
+ clsx: 2.1.1
escape-string-regexp: 5.0.0
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unicode-match-property-ecmascript: 2.0.0
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unist-util-visit-parents: 6.0.1
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- engines: {node: '>=16'}
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+ rehype-pretty-code@0.9.11(shiki@0.14.7):
dependencies:
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+ '@types/hast': 2.3.10
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+ rehype-raw@7.0.0:
dependencies:
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@@ -4302,591 +4945,351 @@ packages:
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micromark-extension-mdxjs: 1.0.1
transitivePeerDependencies:
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+ '@types/unist': 2.0.11
- /unist-util-position@5.0.0:
- resolution: {integrity: sha512-fucsC7HjXvkB5R3kTCO7kUjRdrS0BJt3M/FPxmHMBOm8JQi2BsHAHFsy27E0EolP8rp0NzXsJ+jNPyDWvOJZPA==}
+ unist-util-position@5.0.0:
dependencies:
- '@types/unist': 3.0.2
- dev: false
+ '@types/unist': 3.0.3
- /unist-util-remove-position@4.0.2:
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+ unist-util-remove-position@4.0.2:
dependencies:
- '@types/unist': 2.0.10
+ '@types/unist': 2.0.11
unist-util-visit: 4.1.2
- dev: false
- /unist-util-remove-position@5.0.0:
- resolution: {integrity: sha512-Hp5Kh3wLxv0PHj9m2yZhhLt58KzPtEYKQQ4yxfYFEO7EvHwzyDYnduhHnY1mDxoqr7VUwVuHXk9RXKIiYS1N8Q==}
+ unist-util-remove-position@5.0.0:
dependencies:
- '@types/unist': 3.0.2
+ '@types/unist': 3.0.3
unist-util-visit: 5.0.0
- dev: false
- /unist-util-remove@4.0.0:
- resolution: {integrity: sha512-b4gokeGId57UVRX/eVKej5gXqGlc9+trkORhFJpu9raqZkZhU0zm8Doi05+HaiBsMEIJowL+2WtQ5ItjsngPXg==}
+ unist-util-remove@4.0.0:
dependencies:
- '@types/unist': 3.0.2
+ '@types/unist': 3.0.3
unist-util-is: 6.0.0
unist-util-visit-parents: 6.0.1
- dev: false
- /unist-util-stringify-position@3.0.3:
- resolution: {integrity: sha512-k5GzIBZ/QatR8N5X2y+drfpWG8IDBzdnVj6OInRNWm1oXrzydiaAT2OQiA8DPRRZyAKb9b6I2a6PxYklZD0gKg==}
+ unist-util-stringify-position@3.0.3:
dependencies:
- '@types/unist': 2.0.10
- dev: false
+ '@types/unist': 2.0.11
- /unist-util-stringify-position@4.0.0:
- resolution: {integrity: sha512-0ASV06AAoKCDkS2+xw5RXJywruurpbC4JZSm7nr7MOt1ojAzvyyaO+UxZf18j8FCF6kmzCZKcAgN/yu2gm2XgQ==}
+ unist-util-stringify-position@4.0.0:
dependencies:
- '@types/unist': 3.0.2
- dev: false
+ '@types/unist': 3.0.3
- /unist-util-visit-parents@4.1.1:
- resolution: {integrity: sha512-1xAFJXAKpnnJl8G7K5KgU7FY55y3GcLIXqkzUj5QF/QVP7biUm0K0O2oqVkYsdjzJKifYeWn9+o6piAK2hGSHw==}
+ unist-util-visit-parents@4.1.1:
dependencies:
- '@types/unist': 2.0.10
+ '@types/unist': 2.0.11
unist-util-is: 5.2.1
- dev: false
- /unist-util-visit-parents@5.1.3:
- resolution: {integrity: sha512-x6+y8g7wWMyQhL1iZfhIPhDAs7Xwbn9nRosDXl7qoPTSCy0yNxnKc+hWokFifWQIDGi154rdUqKvbCa4+1kLhg==}
+ unist-util-visit-parents@5.1.3:
dependencies:
- '@types/unist': 2.0.10
+ '@types/unist': 2.0.11
unist-util-is: 5.2.1
- dev: false
- /unist-util-visit-parents@6.0.1:
- resolution: {integrity: sha512-L/PqWzfTP9lzzEa6CKs0k2nARxTdZduw3zyh8d2NVBnsyvHjSX4TWse388YrrQKbvI8w20fGjGlhgT96WwKykw==}
+ unist-util-visit-parents@6.0.1:
dependencies:
- '@types/unist': 3.0.2
+ '@types/unist': 3.0.3
unist-util-is: 6.0.0
- dev: false
- /unist-util-visit@3.1.0:
- resolution: {integrity: sha512-Szoh+R/Ll68QWAyQyZZpQzZQm2UPbxibDvaY8Xc9SUtYgPsDzx5AWSk++UUt2hJuow8mvwR+rG+LQLw+KsuAKA==}
+ unist-util-visit@3.1.0:
dependencies:
- '@types/unist': 2.0.10
+ '@types/unist': 2.0.11
unist-util-is: 5.2.1
unist-util-visit-parents: 4.1.1
- dev: false
- /unist-util-visit@4.1.2:
- resolution: {integrity: sha512-MSd8OUGISqHdVvfY9TPhyK2VdUrPgxkUtWSuMHF6XAAFuL4LokseigBnZtPnJMu+FbynTkFNnFlyjxpVKujMRg==}
+ unist-util-visit@4.1.2:
dependencies:
- '@types/unist': 2.0.10
+ '@types/unist': 2.0.11
unist-util-is: 5.2.1
unist-util-visit-parents: 5.1.3
- dev: false
- /unist-util-visit@5.0.0:
- resolution: {integrity: sha512-MR04uvD+07cwl/yhVuVWAtw+3GOR/knlL55Nd/wAdblk27GCVt3lqpTivy/tkJcZoNPzTwS1Y+KMojlLDhoTzg==}
+ unist-util-visit@5.0.0:
dependencies:
- '@types/unist': 3.0.2
+ '@types/unist': 3.0.3
unist-util-is: 6.0.0
unist-util-visit-parents: 6.0.1
- dev: false
- /update-browserslist-db@1.0.13(browserslist@4.22.2):
- resolution: {integrity: sha512-xebP81SNcPuNpPP3uzeW1NYXxI3rxyJzF3pD6sH4jE7o/IX+WtSpwnVU+qIsDPyk0d3hmFQ7mjqc6AtV604hbg==}
- hasBin: true
- peerDependencies:
- browserslist: '>= 4.21.0'
+ update-browserslist-db@1.1.3(browserslist@4.26.3):
dependencies:
- browserslist: 4.22.2
- escalade: 3.1.1
- picocolors: 1.0.0
- dev: false
+ browserslist: 4.26.3
+ escalade: 3.2.0
+ picocolors: 1.1.1
- /uuid@9.0.1:
- resolution: {integrity: sha512-b+1eJOlsR9K8HJpow9Ok3fiWOWSIcIzXodvv0rQjVoOVNpWMpxf1wZNpt4y9h10odCNrqnYp1OBzRktckBe3sA==}
- hasBin: true
- dev: false
+ uuid@9.0.1: {}
- /uvu@0.5.6:
- resolution: {integrity: sha512-+g8ENReyr8YsOc6fv/NVJs2vFdHBnBNdfE49rshrTzDWOlUx4Gq7KOS2GD8eqhy2j+Ejq29+SbKH8yjkAqXqoA==}
- engines: {node: '>=8'}
- hasBin: true
+ uvu@0.5.6:
dependencies:
dequal: 2.0.3
- diff: 5.1.0
+ diff: 5.2.0
kleur: 4.1.5
sade: 1.8.1
- dev: false
- /vfile-location@5.0.2:
- resolution: {integrity: sha512-NXPYyxyBSH7zB5U6+3uDdd6Nybz6o6/od9rk8bp9H8GR3L+cm/fC0uUTbqBmUTnMCUDslAGBOIKNfvvb+gGlDg==}
+ vfile-location@5.0.3:
dependencies:
- '@types/unist': 3.0.2
- vfile: 6.0.1
- dev: false
+ '@types/unist': 3.0.3
+ vfile: 6.0.3
- /vfile-matter@3.0.1:
- resolution: {integrity: sha512-CAAIDwnh6ZdtrqAuxdElUqQRQDQgbbIrYtDYI8gCjXS1qQ+1XdLoK8FIZWxJwn0/I+BkSSZpar3SOgjemQz4fg==}
+ vfile-matter@3.0.1:
dependencies:
'@types/js-yaml': 4.0.9
is-buffer: 2.0.5
js-yaml: 4.1.0
- dev: false
- /vfile-message@3.1.4:
- resolution: {integrity: sha512-fa0Z6P8HUrQN4BZaX05SIVXic+7kE3b05PWAtPuYP9QLHsLKYR7/AlLW3NtOrpXRLeawpDLMsVkmk5DG0NXgWw==}
+ vfile-message@3.1.4:
dependencies:
- '@types/unist': 2.0.10
+ '@types/unist': 2.0.11
unist-util-stringify-position: 3.0.3
- dev: false
- /vfile-message@4.0.2:
- resolution: {integrity: sha512-jRDZ1IMLttGj41KcZvlrYAaI3CfqpLpfpf+Mfig13viT6NKvRzWZ+lXz0Y5D60w6uJIBAOGq9mSHf0gktF0duw==}
+ vfile-message@4.0.3:
dependencies:
- '@types/unist': 3.0.2
+ '@types/unist': 3.0.3
unist-util-stringify-position: 4.0.0
- dev: false
- /vfile@5.3.7:
- resolution: {integrity: sha512-r7qlzkgErKjobAmyNIkkSpizsFPYiUPuJb5pNW1RB4JcYVZhs4lIbVqk8XPk033CV/1z8ss5pkax8SuhGpcG8g==}
+ vfile@5.3.7:
dependencies:
- '@types/unist': 2.0.10
+ '@types/unist': 2.0.11
is-buffer: 2.0.5
unist-util-stringify-position: 3.0.3
vfile-message: 3.1.4
- dev: false
- /vfile@6.0.1:
- resolution: {integrity: sha512-1bYqc7pt6NIADBJ98UiG0Bn/CHIVOoZ/IyEkqIruLg0mE1BKzkOXY2D6CSqQIcKqgadppE5lrxgWXJmXd7zZJw==}
+ vfile@6.0.3:
dependencies:
- '@types/unist': 3.0.2
- unist-util-stringify-position: 4.0.0
- vfile-message: 4.0.2
- dev: false
+ '@types/unist': 3.0.3
+ vfile-message: 4.0.3
- /vscode-oniguruma@1.7.0:
- resolution: {integrity: sha512-L9WMGRfrjOhgHSdOYgCt/yRMsXzLDJSL7BPrOZt73gU0iWO4mpqzqQzOz5srxqTvMBaR0XZTSrVWo4j55Rc6cA==}
- dev: false
+ vscode-oniguruma@1.7.0: {}
- /vscode-textmate@8.0.0:
- resolution: {integrity: sha512-AFbieoL7a5LMqcnOF04ji+rpXadgOXnZsxQr//r83kLPr7biP7am3g9zbaZIaBGwBRWeSvoMD4mgPdX3e4NWBg==}
- dev: false
+ vscode-textmate@8.0.0: {}
- /watchpack@2.4.0:
- resolution: {integrity: sha512-Lcvm7MGST/4fup+ifyKi2hjyIAwcdI4HRgtvTpIUxBRhB+RFtUh8XtDOxUfctVCnhVi+QQj49i91OyvzkJl6cg==}
- engines: {node: '>=10.13.0'}
+ watchpack@2.4.0:
dependencies:
glob-to-regexp: 0.4.1
graceful-fs: 4.2.11
- dev: false
- /web-namespaces@2.0.1:
- resolution: {integrity: sha512-bKr1DkiNa2krS7qxNtdrtHAmzuYGFQLiQ13TsorsdT6ULTkPLKuu5+GsFpDlg6JFjUTwX2DyhMPG2be8uPrqsQ==}
- dev: false
+ web-namespaces@2.0.1: {}
- /web-worker@1.2.0:
- resolution: {integrity: sha512-PgF341avzqyx60neE9DD+XS26MMNMoUQRz9NOZwW32nPQrF6p77f1htcnjBSEV8BGMKZ16choqUG4hyI0Hx7mA==}
- dev: false
+ web-worker@1.5.0: {}
- /which@1.3.1:
- resolution: {integrity: sha512-HxJdYWq1MTIQbJ3nw0cqssHoTNU267KlrDuGZ1WYlxDStUtKUhOaJmh112/TZmHxxUfuJqPXSOm7tDyas0OSIQ==}
- hasBin: true
+ which@1.3.1:
dependencies:
isexe: 2.0.0
- dev: false
-
- /yallist@2.1.2:
- resolution: {integrity: sha512-ncTzHV7NvsQZkYe1DW7cbDLm0YpzHmZF5r/iyP3ZnQtMiJ+pjzisCiMNI+Sj+xQF5pXhSHxSB3uDbsBTzY/c2A==}
- dev: false
- /yallist@3.1.1:
- resolution: {integrity: sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g==}
- dev: false
+ yallist@2.1.2: {}
- /yocto-queue@0.1.0:
- resolution: {integrity: sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q==}
- engines: {node: '>=10'}
- dev: false
+ yallist@3.1.1: {}
- /zod@3.22.4:
- resolution: {integrity: sha512-iC+8Io04lddc+mVqQ9AZ7OQ2MrUKGN+oIQyq1vemgt46jwCwLfhq7/pwnBnNXXXZb8VTVLKwp9EDkx+ryxIWmg==}
- dev: false
+ yocto-queue@0.1.0: {}
- /zwitch@2.0.4:
- resolution: {integrity: sha512-bXE4cR/kVZhKZX/RjPEflHaKVhUVl85noU3v6b8apfQEc1x4A+zBxjZ4lN8LqGd6WZ3dl98pY4o717VFmoPp+A==}
- dev: false
+ zod@3.25.76: {}
-settings:
- autoInstallPeers: true
- excludeLinksFromLockfile: false
+ zwitch@2.0.4: {}
diff --git a/theme.config.tsx b/theme.config.tsx
index de025629e..582dd5965 100644
--- a/theme.config.tsx
+++ b/theme.config.tsx
@@ -62,11 +62,28 @@ const config: DocsThemeConfig = {
},
docsRepositoryBase: 'https://github.com/dair-ai/Prompt-Engineering-Guide/tree/main/',
footer: {
- text: 'Copyright © 2024 DAIR.AI',
+ text: (
+ Copyright © 2024 DAIR.AI
+ ),
},
search: {
placeholder: 'Search...',
},
+ gitTimestamp: ({ timestamp }) => (
+
+
Last updated on {timestamp.toDateString()}
+
+
Sponsored by
+
+
+
+
+
+ ),
components: {
pre: Pre,
},