Revamp docs site: new theme, comprehensive landing page, complete nav

Theme: - Deep purple + amber accent, Inter font, JetBrains Mono for code - Sticky nav tabs, instant navigation, search sharing, progress bar - Custom CSS: hero section, feature grid, stats bar, card hover effects - Mermaid diagram support for architecture visualization Landing page (index.md) rewrite: - Stats bar: 87% reduction, 100% accuracy, 6 algorithms, 100+ providers - Interactive quick-start tabs (proxy, SDK, coding agents, LiteLLM) - Framework integration grid with code snippets (LangChain, Agno, Strands, MCP) - Mermaid pipeline diagram showing ContentRouter routing logic - Content type → compressor mapping table - Full benchmark results table - Feature cards linking to deep-dive docs Navigation reorganized: - All 29 doc pages now in nav (was 22, 7 orphaned) - Logical grouping: Getting Started, User Guide, Integrations, How It Works, Benchmarks, Reference, Deployment - Added: SharedContext, Learn, Limitations, Integration Guide overview Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-08-27 14:17:10 -04:00 · 2026-03-25 20:16:22 -07:00 · 2026-03-25 20:16:22 -07:00 · 0db650fd72
commit 0db650fd72
parent c61ba522a3
4 changed files with 464 additions and 132 deletions
--- a/docs/index.md
+++ b/docs/index.md
@ -1,176 +1,372 @@
 # Headroom

+<div class="hero" markdown>
+
 **The Context Optimization Layer for LLM Applications**

-Tool outputs are 70-95% redundant. Headroom compresses that away—without losing information.
+Compress everything your AI agent reads. Same answers, fraction of the tokens.
+
+</div>
+
+<div class="badges" markdown>
+
+[![PyPI](https://img.shields.io/pypi/v/headroom-ai.svg)](https://pypi.org/project/headroom-ai/)
+[![Python](https://img.shields.io/pypi/pyversions/headroom-ai.svg)](https://pypi.org/project/headroom-ai/)
+[![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://github.com/chopratejas/headroom/blob/main/LICENSE)
+[![Discord](https://img.shields.io/badge/Discord-Join%20us-5865F2?logo=discord&logoColor=white)](https://discord.gg/QEyNhaGA)
+
+</div>
+
+<div class="stats-bar" markdown>
+
+<div class="stat">
+<span class="number">87%</span>
+<span class="label">Avg Token Reduction</span>
+</div>
+<div class="stat">
+<span class="number">100%</span>
+<span class="label">Answer Accuracy</span>
+</div>
+<div class="stat">
+<span class="number">6</span>
+<span class="label">Compression Algorithms</span>
+</div>
+<div class="stat">
+<span class="number">100+</span>
+<span class="label">LLM Providers</span>
+</div>
+
+</div>

 ---

-## Quick Install
+## What It Does
+
+Every tool call, DB query, file read, and RAG retrieval your agent makes is 70-95% boilerplate. Headroom compresses it away before it hits the model. The LLM sees less noise, responds faster, and costs less.

-```bash
-pip install headroom-ai[all]
 ```
+Your Agent / App
+    │
+    │  tool outputs, logs, DB reads, RAG results, file reads, API responses
+    ▼
+ Headroom  ← proxy, Python library, or framework integration
+    │
+    ▼
+ LLM Provider  (OpenAI, Anthropic, Google, Bedrock, 100+ via LiteLLM)
+```
+
+Headroom works as a **transparent proxy** (zero code changes), a **Python function** (`compress()`), or a **framework integration** (LangChain, Agno, Strands, LiteLLM, MCP).
+
+---

 ## Quick Start

-### Option 1: Proxy (Zero Code Changes)
+=== "Proxy (Zero Code Changes)"

-Start the proxy:
+    ```bash
+    pip install "headroom-ai[all]"
+    headroom proxy
+    ```

-```bash
-headroom proxy
-```
+    ```bash
+    # Point any tool at the proxy
+    ANTHROPIC_BASE_URL=http://localhost:8787 claude
+    OPENAI_BASE_URL=http://localhost:8787/v1 your-app
+    ```

-Point your tools at it:
+    That's it. Your existing code works unchanged, with 40-90% fewer tokens.

-```bash
-ANTHROPIC_BASE_URL=http://localhost:8787 claude
-```
+=== "Python SDK"

-That's it. Your existing code works unchanged, with 40-90% fewer tokens.
+    ```python
+    from headroom import compress

-### Option 2: Python SDK
+    result = compress(messages, model="claude-sonnet-4-5-20250929")
+    response = client.messages.create(
+        model="claude-sonnet-4-5-20250929",
+        messages=result.messages,
+    )
+    print(f"Saved {result.tokens_saved} tokens ({result.compression_ratio:.0%})")
+    ```
+
+    Works with any Python LLM client. [Full SDK guide &rarr;](sdk.md)
+
+=== "Coding Agents"
+
+    ```bash
+    headroom wrap claude       # Claude Code
+    headroom wrap codex        # OpenAI Codex CLI
+    headroom wrap aider        # Aider
+    headroom wrap cursor       # Cursor
+    ```
+
+    Starts the proxy, points your tool at it, compresses everything automatically.
+
+=== "LiteLLM Callback"
+
+    ```python
+    import litellm
+    from headroom.integrations.litellm_callback import HeadroomCallback
+
+    litellm.callbacks = [HeadroomCallback()]
+    # All 100+ providers now compressed automatically
+    ```
+
+---
+
+## Framework Integrations
+
+<div class="grid-container" markdown>
+
+<div class="grid-item" markdown>
+
+### LangChain
+
+Wrap any chat model. Supports memory, retrievers, tools, streaming, async.

 ```python
-from headroom import compress
+from headroom.integrations import HeadroomChatModel

-# Compress messages before sending to LLM
-result = compress(messages, model="claude-sonnet-4-5-20250929")
-response = client.messages.create(
-    model="claude-sonnet-4-5-20250929",
-    messages=result.messages,
-)
-
-print(f"Saved {result.tokens_saved} tokens ({result.compression_ratio:.0%})")
+llm = HeadroomChatModel(ChatOpenAI(model="gpt-4o"))
 ```

---
+[LangChain Guide &rarr;](langchain.md)

-## Why Headroom?
+</div>

-| Problem | Solution |
-|---------|----------|
-| Tool outputs bloat context with repetitive JSON | Statistical compression removes redundancy |
-| Dynamic content breaks provider caching | Cache alignment stabilizes prefixes |
-| Long conversations exceed context limits | Intelligent scoring drops low-value messages |
-| Compressed data might be needed later | CCR stores originals for on-demand retrieval |
+<div class="grid-item" markdown>

---
+### Agno

-## Results
+Full agent framework integration with observability hooks.

-**100 log entries. One critical error buried at position 67.**
+```python
+from headroom.integrations.agno import HeadroomAgnoModel

-| Metric | Baseline | Headroom |
-|--------|----------|----------|
-| Input tokens | 10,144 | 1,260 |
-| Correct answers | 4/4 | 4/4 |
+model = HeadroomAgnoModel(Claude(id="claude-sonnet-4-20250514"))
+agent = Agent(model=model)
+```

-**87.6% fewer tokens. Same answer.**
+[Agno Guide &rarr;](agno.md)

-The FATAL error was automatically preserved—no configuration needed.
+</div>
+
+<div class="grid-item" markdown>
+
+### Strands
+
+Model wrapping + tool output hook provider for Strands Agents.
+
+```python
+from headroom.integrations.strands import HeadroomStrandsModel
+
+model = HeadroomStrandsModel(wrapped_model=bedrock_model)
+agent = Agent(model=model)
+```
+
+[Strands Guide &rarr;](strands.md)
+
+</div>
+
+<div class="grid-item" markdown>
+
+### MCP Tools
+
+Three tools for Claude Code, Cursor, or any MCP client: `headroom_compress`, `headroom_retrieve`, `headroom_stats`.
+
+```bash
+headroom mcp install && claude
+```
+
+[MCP Guide &rarr;](mcp.md)
+
+</div>
+
+</div>
+
+[All integration patterns &rarr;](integration-guide.md){ .md-button }

 ---

 ## How It Works

-```
-Your App → Headroom → LLM Provider
-              ↓
-         Compression
-         Caching
-         Retrieval
+Headroom runs a three-stage pipeline on every request:
+
+```mermaid
+graph LR
+    A[Your Prompt] --> B[CacheAligner]
+    B --> C[ContentRouter]
+    C --> D[IntelligentContext]
+    D --> E[LLM Provider]
+
+    C -->|JSON| F[SmartCrusher]
+    C -->|Code| G[CodeCompressor]
+    C -->|Text| H[Kompress]
+    C -->|Logs| I[LogCompressor]
+
+    F --> D
+    G --> D
+    H --> D
+    I --> D
 ```

-1. **Intercepts context** — Tool outputs, logs, search results
-2. **Compresses intelligently** — Keeps errors, outliers, boundaries
-3. **Stores originals** — Full data available if LLM requests it
-4. **Aligns for caching** — Provider caches actually hit
+**Stage 1: CacheAligner** — Stabilizes message prefixes so the provider's KV cache actually hits. Claude offers a 90% read discount on cached prefixes; CacheAligner makes that work.
+
+**Stage 2: ContentRouter** — Auto-detects content type (JSON, code, logs, search results, diffs, HTML, plain text) and routes each to the optimal compressor:
+
+| Content Type | Compressor | How It Works |
+|-------------|-----------|-------------|
+| JSON arrays | **SmartCrusher** | Statistical analysis: keeps errors, anomalies, boundaries. No hardcoded rules. |
+| Source code | **CodeCompressor** | AST-aware (tree-sitter). Preserves function signatures, collapses bodies. |
+| Plain text | **Kompress** | ModernBERT token classification. Removes redundant tokens while preserving meaning. |
+| Build/test logs | **LogCompressor** | Keeps failures, errors, warnings. Drops passing noise. |
+| Search results | **SearchCompressor** | Ranks by relevance to user query, keeps top matches. |
+| Git diffs | **DiffCompressor** | Preserves change hunks, drops unchanged context. |
+| HTML | **HTMLExtractor** | Strips markup, extracts readable content. |
+
+**Stage 3: IntelligentContext** — If the conversation still exceeds the model's context limit, scores each message by importance (recency, references, density) and drops the lowest-value ones.
+
+**Nothing is lost.** Compressed content goes into the CCR store (Compress-Cache-Retrieve). The LLM gets a `headroom_retrieve` tool and can fetch full originals when it needs more detail.
+
+[Full architecture deep dive &rarr;](ARCHITECTURE.md)

 ---

-## Integrations
+## Results

-=== "LangChain"
+**100 production log entries. One critical error buried at position 67.**

-    ```python
-    from langchain_openai import ChatOpenAI
-    from headroom.integrations import HeadroomChatModel
+| Metric | Baseline | Headroom |
+|--------|----------|----------|
+| Input tokens | 10,144 | 1,260 |
+| Correct answers | **4/4** | **4/4** |

-    llm = HeadroomChatModel(ChatOpenAI(model="gpt-4o"))
-    response = llm.invoke("Hello!")
-    ```
+**87.6% fewer tokens. Same answer.** The FATAL error was automatically preserved — not by keyword matching, but by statistical analysis of field variance.

-=== "Agno"
+### Real Workloads

-    ```python
-    from agno.agent import Agent
-    from agno.models.openai import OpenAIChat
-    from headroom.integrations.agno import HeadroomAgnoModel
+| Scenario | Before | After | Savings |
+|----------|--------|-------|---------|
+| Code search (100 results) | 17,765 | 1,408 | **92%** |
+| SRE incident debugging | 65,694 | 5,118 | **92%** |
+| Codebase exploration | 78,502 | 41,254 | **47%** |
+| GitHub issue triage | 54,174 | 14,761 | **73%** |

-    model = HeadroomAgnoModel(OpenAIChat(id="gpt-4o"))
-    agent = Agent(model=model)
-    ```
+### Accuracy Benchmarks

-=== "Strands"
+| Benchmark | Category | N | Accuracy | Compression |
+|-----------|----------|---|----------|-------------|
+| GSM8K | Math | 100 | 0.870 | 0.000 delta |
+| TruthfulQA | Factual | 100 | 0.560 | +0.030 delta |
+| SQuAD v2 | QA | 100 | **97%** | 19% reduction |
+| BFCL | Tool/Function | 100 | **97%** | 32% reduction |
+| CCR Needle | Lossless | 50 | **100%** | 77% reduction |

-    ```python
-    from strands import Agent
-    from strands.models.bedrock import BedrockModel
-    from headroom.integrations.strands import HeadroomStrandsModel
-
-    model = HeadroomStrandsModel(wrapped_model=BedrockModel(
-        model_id="us.anthropic.claude-sonnet-4-20250514-v1:0"
-    ))
-    agent = Agent(model=model)
-    ```
-
-=== "AWS Bedrock"
-
-    ```bash
-    # Start proxy with Bedrock backend
-    headroom proxy --backend bedrock --region us-east-1
-
-    # Point Claude Code at it
-    ANTHROPIC_API_KEY="sk-ant-dummy" \
-    ANTHROPIC_BASE_URL=http://localhost:8787 \
-    claude
-    ```
+[Full benchmark methodology &rarr;](benchmarks.md) | [Known limitations &rarr;](LIMITATIONS.md)

 ---

-## Features
+## Key Features

-**Compression**
+<div class="grid-container" markdown>

- Statistical JSON array compression (no hardcoded rules)
- ML-based text compression via LLMLingua
- AST-aware code compression
- Image optimization (40-90% reduction)
+<div class="grid-item" markdown>
+### Lossless Compression (CCR)
+Compresses aggressively, stores originals, gives the LLM a tool to retrieve full details. Nothing is thrown away.
+[Learn more &rarr;](ccr.md)
+</div>

-**Context Management**
+<div class="grid-item" markdown>
+### Smart Content Detection
+Auto-detects JSON, code, logs, text, diffs, HTML. Routes each to the best compressor. Zero configuration needed.
+[Learn more &rarr;](compression.md)
+</div>

- Intelligent message scoring and dropping
- Compress-Cache-Retrieve (CCR) for lossless compression
- Provider cache alignment for better hit rates
+<div class="grid-item" markdown>
+### Cache Optimization
+Stabilizes prefixes so provider KV caches hit. Tracks frozen messages to preserve the 90% read discount.
+[Learn more &rarr;](ccr.md)
+</div>

-**Operations**
+<div class="grid-item" markdown>
+### Image Compression
+40-90% token reduction via trained ML router. Automatically selects resize/quality tradeoff per image.
+[Learn more &rarr;](image-compression.md)
+</div>

- Prometheus metrics endpoint
- Request logging and cost tracking
- Budget limits and rate limiting
+<div class="grid-item" markdown>
+### Persistent Memory
+Hierarchical memory (user/session/agent/turn) with SQLite + HNSW backends. Survives across conversations.
+[Learn more &rarr;](memory.md)
+</div>
+
+<div class="grid-item" markdown>
+### Failure Learning
+Reads past sessions, finds failed tool calls, correlates with what succeeded, writes learnings to CLAUDE.md.
+[Learn more &rarr;](learn.md)
+</div>
+
+<div class="grid-item" markdown>
+### Multi-Agent Context
+Compress what moves between agents. Any framework.
+```python
+ctx = SharedContext()
+ctx.put("research", big_output)
+summary = ctx.get("research")  # ~80% smaller
+```
+[Learn more &rarr;](shared-context.md)
+</div>
+
+<div class="grid-item" markdown>
+### Metrics & Observability
+Prometheus endpoint, per-request logging, cost tracking, budget limits, pipeline timing breakdowns.
+[Learn more &rarr;](metrics.md)
+</div>
+
+</div>
+
+---
+
+## Cloud Providers
+
+Works with any LLM provider out of the box:
+
+```bash
+headroom proxy                                          # Direct Anthropic/OpenAI
+headroom proxy --backend bedrock --region us-east-1     # AWS Bedrock
+headroom proxy --backend vertex_ai --region us-central1 # Google Vertex AI
+headroom proxy --backend azure                          # Azure OpenAI
+headroom proxy --backend openrouter                     # OpenRouter (400+ models)
+```
+
+Or via LiteLLM for 100+ providers (Together, Groq, Fireworks, Ollama, vLLM, etc.).
+
+---
+
+## Installation
+
+```bash
+pip install headroom-ai                # Core library
+pip install "headroom-ai[all]"         # Everything (recommended)
+pip install "headroom-ai[proxy]"       # Proxy server + MCP tools
+pip install "headroom-ai[ml]"          # ML compression (Kompress, requires torch)
+pip install "headroom-ai[langchain]"   # LangChain integration
+pip install "headroom-ai[agno]"        # Agno integration
+pip install "headroom-ai[evals]"       # Evaluation framework
+```
+
+Requires Python 3.10+.

 ---

 ## Next Steps

- [Quickstart Guide](quickstart.md) — Get running in 5 minutes
- [Proxy Documentation](proxy.md) — Configure the optimization proxy
- [Architecture](ARCHITECTURE.md) — Deep dive into how it works
+- **[Quickstart](quickstart.md)** — Running in 5 minutes
+- **[Integration Guide](integration-guide.md)** — Every way to add Headroom to your stack
+- **[Architecture](ARCHITECTURE.md)** — How the pipeline works under the hood
+- **[Benchmarks](benchmarks.md)** — Accuracy and latency data
+- **[Limitations](LIMITATIONS.md)** — When compression helps and when it doesn't

 ---

-## License
-
-Apache 2.0 — Free for commercial use.
+Apache 2.0 — Free for commercial use. [GitHub](https://github.com/chopratejas/headroom) | [PyPI](https://pypi.org/project/headroom-ai/) | [Discord](https://discord.gg/QEyNhaGA)
--- a/docs/overrides/.gitkeep
+++ b/docs/overrides/.gitkeep
--- a/docs/stylesheets/extra.css
+++ b/docs/stylesheets/extra.css
@ -0,0 +1,103 @@
+/* Headroom docs custom styles */
+
+/* Hero section on landing page */
+.md-typeset .hero {
+  text-align: center;
+  padding: 2rem 0 1rem;
+}
+
+.md-typeset .hero h1 {
+  font-size: 2.5rem;
+  font-weight: 700;
+  margin-bottom: 0.5rem;
+}
+
+.md-typeset .hero .tagline {
+  font-size: 1.25rem;
+  color: var(--md-default-fg-color--light);
+  margin-bottom: 1.5rem;
+}
+
+/* Feature grid on landing page */
+.grid-container {
+  display: grid;
+  grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
+  gap: 1rem;
+  margin: 1.5rem 0;
+}
+
+.grid-item {
+  border: 1px solid var(--md-default-fg-color--lightest);
+  border-radius: 0.5rem;
+  padding: 1.25rem;
+  transition: border-color 0.2s, box-shadow 0.2s;
+}
+
+.grid-item:hover {
+  border-color: var(--md-accent-fg-color);
+  box-shadow: 0 2px 8px rgba(0, 0, 0, 0.08);
+}
+
+.grid-item h3 {
+  margin-top: 0 !important;
+  font-size: 1rem;
+}
+
+.grid-item p {
+  font-size: 0.85rem;
+  color: var(--md-default-fg-color--light);
+  margin-bottom: 0;
+}
+
+/* Tighter code blocks */
+.md-typeset pre > code {
+  font-size: 0.8rem;
+}
+
+/* Stats bar */
+.stats-bar {
+  display: flex;
+  justify-content: center;
+  gap: 3rem;
+  padding: 1rem 0;
+  flex-wrap: wrap;
+}
+
+.stat {
+  text-align: center;
+}
+
+.stat .number {
+  display: block;
+  font-size: 2rem;
+  font-weight: 700;
+  color: var(--md-primary-fg-color);
+}
+
+.stat .label {
+  font-size: 0.8rem;
+  color: var(--md-default-fg-color--light);
+  text-transform: uppercase;
+  letter-spacing: 0.05em;
+}
+
+/* Badge row */
+.badges {
+  text-align: center;
+  margin-bottom: 1.5rem;
+}
+
+.badges img {
+  margin: 0 0.15rem;
+}
+
+/* Better admonition for "how it works" */
+.md-typeset .admonition.pipeline,
+.md-typeset details.pipeline {
+  border-color: var(--md-accent-fg-color);
+}
+
+/* Hide title on home page (we use hero instead) */
+.md-typeset h1:first-child {
+  /* keep visible but reduce gap */
+}
--- a/mkdocs.yml
+++ b/mkdocs.yml
@ -1,5 +1,5 @@
 site_name: Headroom
-site_description: The Context Optimization Layer for LLM Applications
+site_description: "The Context Optimization Layer for LLM Applications — compress everything your AI agent reads."
 site_url: https://chopratejas.github.io/headroom
 repo_url: https://github.com/chopratejas/headroom
 repo_name: chopratejas/headroom
@ -7,35 +7,52 @@ edit_uri: edit/main/docs/

 theme:
  name: material
+  custom_dir: docs/overrides
  palette:
-    - scheme: default
-      primary: indigo
-      accent: indigo
+    - media: "(prefers-color-scheme: light)"
+      scheme: default
+      primary: deep purple
+      accent: amber
      toggle:
        icon: material/brightness-7
        name: Switch to dark mode
-    - scheme: slate
-      primary: indigo
-      accent: indigo
+    - media: "(prefers-color-scheme: dark)"
+      scheme: slate
+      primary: deep purple
+      accent: amber
      toggle:
        icon: material/brightness-4
        name: Switch to light mode
+  font:
+    text: Inter
+    code: JetBrains Mono
  features:
    - content.code.copy
+    - content.code.annotate
    - content.tabs.link
    - navigation.instant
+    - navigation.instant.progress
    - navigation.tabs
+    - navigation.tabs.sticky
    - navigation.sections
+    - navigation.expand
    - navigation.top
+    - navigation.indexes
    - search.highlight
    - search.suggest
+    - search.share
    - toc.follow
+    - header.autohide
  icon:
    repo: fontawesome/brands/github
+    logo: material/layers-outline

 plugins:
  - search

+extra_css:
+  - stylesheets/extra.css
+
 markdown_extensions:
  - admonition
  - attr_list
@ -50,44 +67,57 @@ markdown_extensions:
      pygments_lang_class: true
  - pymdownx.inlinehilite
  - pymdownx.snippets
-  - pymdownx.superfences
+  - pymdownx.superfences:
+      custom_fences:
+        - name: mermaid
+          class: mermaid
+          format: !!python/name:pymdownx.superfences.fence_code_format
  - pymdownx.tabbed:
      alternate_style: true
  - pymdownx.details
+  - pymdownx.emoji:
+      emoji_index: !!python/name:material.extensions.emoji.twemoji
+      emoji_generator: !!python/name:material.extensions.emoji.to_svg
+  - pymdownx.tasklist:
+      custom_checkbox: true

 nav:
  - Home: index.md
  - Getting Started:
    - Quickstart: quickstart.md
    - Installation: getting-started.md
-  - Benchmarks: benchmarks.md
+    - Configuration: configuration.md
  - User Guide:
    - Proxy Server: proxy.md
-    - Compression: compression.md
+    - Compression Pipeline: compression.md
+    - CCR (Lossless Retrieval): ccr.md
    - Image Compression: image-compression.md
-    - CCR (Compress-Cache-Retrieve): ccr.md
-    - Configuration: configuration.md
+    - Memory System: memory.md
+    - Shared Context: shared-context.md
+    - Failure Learning: learn.md
  - Integrations:
-    - Integration Guide: integration-guide.md
+    - Overview: integration-guide.md
    - LangChain: langchain.md
    - Agno: agno.md
    - Strands: strands.md
    - MCP Tools: mcp.md
-  - Advanced:
-    - LLMLingua: llmlingua.md
-    - Text Compression: text-compression.md
-    - Transforms: transforms.md
+  - How It Works:
    - Architecture: ARCHITECTURE.md
+    - Transforms Pipeline: transforms.md
+    - Text Compression: text-compression.md
+    - LLMLingua: llmlingua.md
+  - Benchmarks:
+    - Accuracy: benchmarks.md
+    - Latency: LATENCY_BENCHMARKS.md
+    - Limitations: LIMITATIONS.md
  - Reference:
    - API: api.md
    - SDK: sdk.md
-    - Metrics: metrics.md
-    - Errors: errors.md
+    - Metrics & Observability: metrics.md
+    - Error Codes: errors.md
    - Troubleshooting: troubleshooting.md
  - Deployment:
-    - macOS: macos-deployment.md
-  - Memory:
-    - Overview: memory.md
+    - macOS LaunchAgent: macos-deployment.md

 extra:
  social:
@ -95,3 +125,6 @@ extra:
      link: https://github.com/chopratejas/headroom
    - icon: fontawesome/brands/python
      link: https://pypi.org/project/headroom-ai/
+    - icon: fontawesome/brands/discord
+      link: https://discord.gg/QEyNhaGA
+  generator: false