Initial MKDocs (#285)

.github/workflows/deploy_docs.yml

@@ -0,0 +1,52 @@
+name: Deploy SDK Docs
+
+on:
+  push:
+    branches:
+      - master 
+  workflow_dispatch:
+
+permissions:
+  contents: read
+  pages: write
+  id-token: write
+
+concurrency:
+  group: "pages"
+  cancel-in-progress: false
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    steps:
+        - uses: actions/checkout@v4
+        - name: install deps
+          run: |
+            pip install poetry poethepoet
+        - name: Set up Python
+          uses: actions/setup-python@v4
+          with:
+            python-version: 3.12
+            cache: poetry
+            cache-dependency-path: 'poetry.lock'
+
+        - name: Poetry install
+          run: |
+            poetry install
+            poetry run pip install -r docs/docs-requirements.txt
+
+        - name: Build site
+          working-directory: ./docs
+          run: make build-docs
+        
+        - name: Configure GitHub Pages
+          uses: actions/configure-pages@v4
+        
+        - name: Upload Pages Artifact
+          uses: actions/upload-pages-artifact@v3
+          with:
+            path: ./docs/site/
+
+        - name: Deploy to GitHub Pages
+          id: deployment
+          uses: actions/deploy-pages@v4

.github/workflows/link_check.yml

@@ -22,6 +22,9 @@ jobs:
         uses: actions/checkout@v4
       - name: Check links in Markdown files
         uses: gaurav-nelson/github-action-markdown-link-check@v1
+        with:
+          folder-path: 'examples/'
+          file-path: './README.md'
 
   notebook-link-check:
     runs-on: ubuntu-latest
@@ -45,4 +48,4 @@ jobs:
         env:
           LANGCHAIN_API_KEY: test
           shell: bash
-        run: poetry run pytest -o python_files=non_python_only --check-links --ignore="*.py" -k .ipynb --check-links-ignore "https://(api|web)\.smith\.langchain\.com/.*" --check-links-ignore "https://x.com/.*" .
+        run: poetry run pytest -o python_files=non_python_only --check-links --ignore="*.py" -k .ipynb --check-links-ignore "https://(api|web)\.smith\.langchain\.com/.*" --check-links-ignore "https://x.com/.*" ./examples

Makefile

@@ -1,4 +1,4 @@
-.PHONY: all clean docs_build docs_clean docs_linkcheck api_docs_build api_docs_clean api_docs_linkcheck format lint test tests test_watch integration_tests docker_tests help extended_tests
+.PHONY: all clean docs_build docs_clean docs_linkcheck api_docs_build api_docs_clean api_docs_linkcheck format lint test tests test_watch integration_tests docker_tests help extended_tests coverage spell_check spell_fix build-docs serve-docs
 
 # Default target executed when no arguments are given to make.
 all: help
@@ -49,6 +49,13 @@ spell_check:
 spell_fix:
 	poetry run codespell --toml pyproject.toml -w
 
+build-docs:
+	poetry run python docs/_scripts/copy_notebooks.py
+	poetry run mkdocs build --clean -f docs/mkdocs.yml
+
+serve-docs: build-docs
+	poetry run mkdocs serve -f docs/mkdocs.yml
+
 ######################
 # HELP
 ######################

docs/.gitignore

@@ -0,0 +1,2 @@
+*.ipynb
+site/

docs/_scripts/copy_notebooks.py

@@ -0,0 +1,64 @@
+import os
+import shutil
+from pathlib import Path
+
+root_dir = Path(__file__).resolve().parents[2]
+
+examples_dir = root_dir / "examples"
+docs_dir = root_dir / "docs/docs"
+how_tos_dir = docs_dir / "how-tos"
+tutorials_dir = docs_dir / "tutorials"
+
+_HOW_TOS = {"agent_executor", "chat_agent_executor_with_function_calling", "docs"}
+_IGNORE = (".ipynb_checkpoints", ".venv", ".cache")
+
+
+def clean_notebooks():
+    roots = (how_tos_dir, tutorials_dir)
+    for dir_ in roots:
+        traversed = []
+        for root, dirs, files in os.walk(dir_):
+            for file in files:
+                if file.endswith(".ipynb"):
+                    os.remove(os.path.join(root, file))
+            # Now delete the dir if it is empty now
+            if root not in roots:
+                traversed.append(root)
+
+        for root in reversed(traversed):
+            if not os.listdir(root):
+                os.rmdir(root)
+
+
+def copy_notebooks():
+    # Nested ones are mostly tutorials rn
+    for root, dirs, files in os.walk(examples_dir):
+        if root == str(examples_dir):
+            continue
+        if any(path.startswith(".") or path.startswith("__") for path in root.split(os.sep)):
+            continue
+        if any(path in _HOW_TOS for path in root.split(os.sep)):
+            dst_dir = how_tos_dir
+        else:
+            dst_dir = tutorials_dir
+        for file in files:
+            if file.endswith(".ipynb"):
+                src_path = os.path.join(root, file)
+                dst_path = os.path.join(
+                    dst_dir, os.path.relpath(src_path, examples_dir)
+                )
+                os.makedirs(os.path.dirname(dst_path), exist_ok=True)
+                shutil.copy(src_path, dst_path)
+    # Top level notebooks are "how-to's"
+    for file in examples_dir.iterdir():
+        if file.suffix.endswith(".ipynb") and not os.path.isdir(
+            os.path.join(examples_dir, file)
+        ):
+            src_path = os.path.join(examples_dir, file)
+            dst_path = os.path.join(docs_dir, "how-tos", file.name)
+            shutil.copy(src_path, dst_path)
+
+
+if __name__ == "__main__":
+    clean_notebooks()
+    copy_notebooks()

docs/css/mkdocstrings.css

@@ -0,0 +1,7 @@
+/* https://mkdocstrings.github.io/crystal/styling.html#recommended-styles */
+
+/* Indent and distinguish sub-items */
+div.doc-contents:not(.first) {
+  padding-left: 15px;
+  border-left: 4px solid rgba(230, 230, 230);
+}

docs/docs-requirements.txt

@@ -0,0 +1,8 @@
+mkdocs
+mkdocstrings
+mkdocstrings-python
+mkdocs-jupyter
+mkdocs-redirects
+mkdocs-minify-plugin
+mkdocs-rss-plugin
+mkdocs-material[imaging]

docs/docs/concepts.md

@@ -0,0 +1,4 @@
+# Concepts
+
+
+## State

docs/docs/how-tos/index.md

@@ -0,0 +1,25 @@
+# How-To Guides
+
+Welcome to the LangGraph How-To Guides! These guides provide practical, step-by-step instructions for accomplishing key tasks in LangGraph.
+
+## Basics
+
+- [State Management](state-model.ipynb): How to define and manage complex state in your graphs
+- [Tool Integration](sql_example.ipynb): How to integrate external tools and data sources
+- [Human-in-the-Loop](human-in-the-loop.ipynb): How to incorporate human feedback and intervention
+
+## Performance
+
+- [Async Execution](async.ipynb): How to run nodes asynchronously for improved performance
+- [Streaming Responses](streaming-tokens.ipynb): How to stream agent responses in real-time
+
+## Graph Structure
+
+- [Subgraphs](subgraph.ipynb): How to modularize your graphs with subgraphs
+- [Branching](branching.ipynb): How to create branching logic in your graphs
+
+## Development
+
+- [Persistence](persistence.ipynb): How to save and load graph state for long-running applications
+- [Visualization](visualization.ipynb): How to visualize your graphs
+- [Time Travel](time-travel.ipynb): How to navigate and manipulate graph execution history

docs/docs/index.md

@@ -0,0 +1,122 @@
+# 🦜🕸️LangGraph
+
+[![Downloads](https://static.pepy.tech/badge/langgraph/month)](https://pepy.tech/project/langgraph)
+
+⚡ Build language agents as graphs ⚡
+
+
+## Overview
+
+Suppose you're building a customer support assistant. You want your assistant to:
+
+1. Try to answer user questions using a knowledge base
+2. Escalate to a human if it's not confident in its answer
+3. Relay the human's resolution back to the user
+4. Remember the full conversation context across multiple user messages
+
+With raw LLMs, the code to control the agentic loop, conversation state, route between the chatbot and human, and checkpoint the full application state can get complex.
+
+LangGraph makes it simple. First install:
+
+```shell
+pip install -U langgraph
+```
+
+Then define your assistant:
+
+```python
+from langgraph.graph import StateGraph
+from langgraph.checkpoint.sqlite import SqliteSaver
+
+from langchain_anthropic
+
+
+# Define the chatbot state 
+class ChatbotState(TypedDict):
+    conversation_history: Annotated[ConversationHistory, operator.add]
+    pending_human_request: Optional[HumanRequest]
+
+# Create nodes for the chatbot and human
+def chatbot(state: ChatbotState):
+    # TODO
+
+def human(state: ChatbotState):
+    # TODO
+
+# Create the graph
+graph = StateGraph(ChatbotState)
+graph.add_node("chatbot", chatbot)
+graph.add_node("human", human)
+
+# Define routing logic between chatbot and human
+def should_escalate(state):
+    if state['pending_human_request']:
+        return "human"
+    else:
+        return "chatbot"
+
+graph.add_conditional_edges("chatbot", should_escalate, {
+    "human": "human", 
+    "chatbot": "chatbot"
+})
+
+graph.add_edge("human", "chatbot")
+
+memory = SqliteSaver.from_conn_string(":memory:")
+app = graph.compile(checkpointer=memory)
+# Run the graph
+result = app.invoke(new_user_message)
+```
+
+The graph handles all the hard parts:
+
+- `conversation_history` in the state contains the assistant's "memory"
+- Conditional edges enable dynamic routing between the chatbot and human based on the chatbot's confidence
+- Persistence makes it easy to route to a human so they can respond and resume at any time
+
+With LangGraph, you can build complex, stateful agents without getting bogged down in manual state and interrupt management. Just define your nodes, edges, and state schema - and let the graph take care of the rest.
+
+## Concepts
+
+- [Graphs](concepts.md#graphs)
+- [State](concepts.md#state): The data structure passed between nodes, allowing you to persist context 
+- [Nodes](concepts.#nodes): The building blocks of your graph - LLMs, tools, or custom logic 
+- [Edges](concepts.md#edges): The connections that define the flow of data between your nodes
+- [Conditional Edges](concepts.md#conditional_edges): Special edges that let you dynamically route between nodes based on state
+- [Persistence](concepts.md#persistence): Save and resume your graph's state for long-running applications
+
+## How-To Guides
+
+Check out the [How-To Guides](how-tos/index.md) for instructions on handling common tasks with LangGraph.
+
+- Manage State
+- Tool Integration  
+- Human-in-the-Loop
+- Async Execution
+- Streaming Responses
+- Subgraphs & Branching
+- Persistence, Visualization, Time Travel 
+- Benchmarking
+
+## Tutorials
+
+Consult the [Tutorials](tutorials/index.md) to learn more about implementing advanced 
+
+- **Agent Executors**: Chat and Langchain agents
+- **Planning Agents**: Plan-and-Execute, ReWOO, LLMCompiler  
+- **Reflection & Critique**: Improving quality via reflection
+- **Multi-Agent Systems**: Collaboration, supervision, teams
+- **Research & QA**: Web research, retrieval-augmented QA  
+- **Applications**: Chatbots, code assist, web tasks
+- **Evaluation & Analysis**: Simulation, self-discovery, swarms
+
+## Why LangGraph?
+
+LangGraph extends the core strengths of LangChain Runnables (shared interface for streaming, async, and batch calls) to make it easy to:
+
+- Seamless state management across multiple turns of conversation or tool usage
+- The ability to flexibly route between nodes based on dynamic criteria 
+- Smooth switching between LLMs and human intervention  
+- Persistence for long-running, multi-session applications
+
+If you're building a straightforward DAG,, LangChain expression language is a great fit. But for more complex, stateful applications with nonlinear flows, LangGraph is the perfect tool for the job.

docs/docs/reference/checkpoints.md

@@ -0,0 +1,11 @@
+# Checkpoints
+
+
+::: langgraph.checkpoint
+    handler: python
+    options:
+      selection:
+        docstring_style: google
+      rendering:
+        heading_level: 3
+      show_root_toc_entry: false

docs/docs/reference/graphs.md

@@ -0,0 +1,11 @@
+# StateGraph
+
+
+::: langgraph.graph
+    handler: python
+    options:
+      selection:
+        docstring_style: google
+      rendering:
+        heading_level: 3
+      show_root_toc_entry: false

docs/docs/reference/prebuilt.md

@@ -0,0 +1,11 @@
+# Prebuilt 
+
+
+::: langgraph.prebuilt
+    handler: python
+    options:
+      selection:
+        docstring_style: google
+      rendering:
+        heading_level: 3
+      show_root_toc_entry: false

docs/docs/tutorials/index.md

@@ -0,0 +1,69 @@
+# Tutorials
+
+Welcome to the LangGraph Tutorials! These notebooks provide end-to-end walkthroughs for building various types of language agents and applications using LangGraph.
+
+## Agent Executors
+
+- **Chat Agent (Function Calling)**
+    - [Base](chat_agent_executor_with_function_calling/base.ipynb): Implementing a chat agent executor with function calling
+    - [High-Level](chat_agent_executor_with_function_calling/high-level.ipynb): Using the high-level chat agent executor API
+    - [High-Level Tools](chat_agent_executor_with_function_calling/high-level-tools.ipynb): Integrating tools into the high-level chat agent executor
+    - **Modifications**
+        - [Human-in-the-Loop](chat_agent_executor_with_function_calling/human-in-the-loop.ipynb)
+        - [Force Tool First](chat_agent_executor_with_function_calling/force-calling-a-tool-first.ipynb)
+        - [Respond in Format](chat_agent_executor_with_function_calling/respond-in-format.ipynb)
+        - [Dynamic Direct Return](chat_agent_executor_with_function_calling/dynamically-returning-directly.ipynb)
+        - [Manage Agent Steps](chat_agent_executor_with_function_calling/managing-agent-steps.ipynb)
+
+- **LangChain Agent**
+    - [Base](agent_executor/base.ipynb): Implementing an agent executor with Langchain agents  
+    - [High-Level](agent_executor/high-level.ipynb): Using the high-level Langchain agent executor API
+    - **Modifications** 
+        - [Human-in-the-Loop](agent_executor/human-in-the-loop.ipynb)
+        - [Force Tool First](agent_executor/force-calling-a-tool-first.ipynb)
+        - [Manage Agent Steps](agent_executor/managing-agent-steps.ipynb)
+
+## Planning Agents
+
+- [Plan-and-Execute](plan-and-execute/plan-and-execute.ipynb): Implementing a basic planning and execution agent  
+- [Reasoning without Observation](rewoo/rewoo.ipynb): Reducing re-planning by saving observations as variables 
+- [LLMCompiler](llm-compiler/LLMCompiler.ipynb): Streaming and eagerly executing a DAG of tasks from a planner
+
+## Reflection & Critique 
+
+- [Basic Reflection](reflection/reflection.ipynb): Prompting the agent to reflect on and revise its outputs
+- [Reflexion](reflexion/reflexion.ipynb): Critiquing missing and superfluous details to guide next steps
+- [Language Agent Tree Search](lats/lats.ipynb): Using reflection and rewards to drive a tree search over agents
+
+## Multi-Agent Systems
+
+- [Collaboration](multi_agent/multi-agent-collaboration.ipynb): Enabling two agents to collaborate on a task  
+- [Supervision](multi_agent/agent_supervisor.ipynb): Using an LLM to orchestrate and delegate to individual agents
+- [Hierarchical Teams](multi_agent/hierarchical_agent_teams.ipynb): Orchestrating nested teams of agents to solve problems
+
+## Research & QA
+
+- **Retrieval-Augmented Generation**
+    - [langgraph_adaptive_rag.ipynb](rag/langgraph_adaptive_rag.ipynb)
+    - [langgraph_adaptive_rag_cohere.ipynb](rag/langgraph_adaptive_rag_cohere.ipynb) 
+    - [langgraph_adaptive_rag_local.ipynb](rag/langgraph_adaptive_rag_local.ipynb)
+    - [langgraph_agentic_rag.ipynb](rag/langgraph_agentic_rag.ipynb)
+    - [langgraph_crag.ipynb](rag/langgraph_crag.ipynb)
+    - [langgraph_crag_local.ipynb](rag/langgraph_crag_local.ipynb)
+    - [langgraph_self_rag.ipynb](rag/langgraph_self_rag.ipynb)
+    - [langgraph_self_rag_local.ipynb](rag/langgraph_self_rag_local.ipynb)
+- [Web Research (STORM)](storm/storm.ipynb): Generating Wikipedia-like articles via research and multi-perspective QA
+
+## Applications
+
+- **Chatbots**
+    - [Customer Support](chatbots/customer-support.ipynb): Building a customer support chatbot
+    - [Info Gathering](chatbots/information-gather-prompting.ipynb): Building an information gathering chatbot  
+- [Code Assistant](code_assistant/langgraph_code_assistant.ipynb): Building a code analysis and generation assistant
+- [Web Navigation](web-navigation/web_voyager.ipynb): Building an agent that can navigate and interact with websites
+
+## Evaluation & Analysis
+
+- **Chatbot Evaluation via Simulation**  
+    - [Agent-based](chatbot-simulation-evaluation/agent-simulation-evaluation.ipynb): Evaluating chatbots via simulated user interactions
+    - [Dataset-based](chatbot-simulation-evaluation/langsmith-agent-simulation-evaluation.ipynb): Evaluating chatbots over a dialog dataset

docs/mkdocs.yml

@@ -0,0 +1,197 @@
+site_name: LangGraph
+site_description: Build language agents as graphs
+site_url: https://langchain-ai.github.io/langgraph/
+theme:
+  name: material
+  custom_dir: overrides
+  logo: static/img/brand/wordmark.png
+  favicon: static/img/brand/favicon.png
+  features:
+    - announce.dismiss
+    - content.action.edit
+    - content.action.view
+    - content.code.annotate
+    - content.code.copy
+    - content.code.select
+    - content.tabs.link
+    - content.tooltips
+    - header.autohide
+    - navigation.expand
+    - navigation.footer
+    - navigation.indexes
+    - navigation.instant
+    - navigation.instant.prefetch
+    - navigation.instant.progress
+    - navigation.prune
+    - navigation.sections
+    - navigation.tabs
+    - navigation.top
+    - navigation.tracking
+    - search.highlight
+    - search.share
+    - search.suggest
+    - toc.follow
+  palette:
+  - scheme: default
+    primary: white
+    accent: gray
+    toggle:
+      icon: material/brightness-7
+      name: Switch to dark mode
+  - scheme: slate
+    primary: grey
+    accent: white
+    toggle:
+      icon: material/brightness-4
+      name: Switch to light mode
+  font:
+    text: "Public Sans"
+    code: "Roboto Mono"
+plugins:
+  - search:
+      separator: '[\s\u200b\-_,:!=\[\]()"`/]+|\.(?!\d)|&[lg]t;|(?!\b)(?=[A-Z][a-z])'
+  - autorefs
+  - mkdocstrings:
+      handlers:
+        python:
+          options:
+            members_order: source 
+            allow_inspection: true
+            show_bases: true
+  - mkdocs-jupyter:
+      ignore_h1_titles: true
+      execute: false
+      include_source: True
+      include_requirejs: true
+  # TODO: Add minify plugin once it works alright with code block copying
+  # - minify:
+  #     minify_html: true
+nav:
+  - Home: 
+      - 'index.md'
+      - Quick Start: quick_start.ipynb
+  - Concepts:
+      - 'concepts.md'
+  - "How-to Guides":
+      - Basics:
+          - State Management: how-tos/state-model.ipynb
+          - Tool Integration: how-tos/sql_example.ipynb
+          - Human-in-the-Loop: how-tos/human-in-the-loop.ipynb
+      - Performance:  
+          - Async Execution: how-tos/async.ipynb
+          - Streaming Responses: how-tos/streaming-tokens.ipynb
+      - Graph Structure:
+          - Subgraphs: how-tos/subgraph.ipynb 
+          - Branching: how-tos/branching.ipynb
+      - Development:
+          - Persistence: how-tos/persistence.ipynb
+          - Visualization: how-tos/visualization.ipynb 
+          - Time Travel: how-tos/time-travel.ipynb
+          - Benchmarking: how-tos/swe-bench.ipynb
+  - Tutorials:
+      - Agent Executors:
+          - Chat Agent (Function Calling):
+              - Base: tutorials/chat_agent_executor_with_function_calling/base.ipynb
+              - High-Level: tutorials/chat_agent_executor_with_function_calling/high-level.ipynb
+              - High-Level Tools: tutorials/chat_agent_executor_with_function_calling/high-level-tools.ipynb
+              - Modifications:
+                  - Human-in-the-Loop: tutorials/chat_agent_executor_with_function_calling/human-in-the-loop.ipynb
+                  - Force Tool First: tutorials/chat_agent_executor_with_function_calling/force-calling-a-tool-first.ipynb
+                  - Respond in Format: tutorials/chat_agent_executor_with_function_calling/respond-in-format.ipynb 
+                  - Dynamic Direct Return: tutorials/chat_agent_executor_with_function_calling/dynamically-returning-directly.ipynb
+                  - Manage Agent Steps: tutorials/chat_agent_executor_with_function_calling/managing-agent-steps.ipynb
+          - Langchain Agent:
+              - Base: tutorials/agent_executor/base.ipynb
+              - High-Level: tutorials/agent_executor/high-level.ipynb  
+              - Modifications:
+                  - Human-in-the-Loop: tutorials/agent_executor/human-in-the-loop.ipynb
+                  - Force Tool First: tutorials/agent_executor/force-calling-a-tool-first.ipynb
+                  - Manage Agent Steps: tutorials/agent_executor/managing-agent-steps.ipynb
+      - Planning Agents:  
+          - Plan-and-Execute: tutorials/plan-and-execute/plan-and-execute.ipynb
+          - Reasoning w/o Observation: tutorials/rewoo/rewoo.ipynb 
+          - LLMCompiler: tutorials/llm-compiler/LLMCompiler.ipynb
+      - Reflection & Critique:
+          - Basic Reflection: tutorials/reflection/reflection.ipynb
+          - Reflexion: tutorials/reflexion/reflexion.ipynb
+          - Language Agent Tree Search: tutorials/lats/lats.ipynb
+      - Multi-Agent Systems:
+          - Collaboration: tutorials/multi_agent/multi-agent-collaboration.ipynb  
+          - Supervision: tutorials/multi_agent/agent_supervisor.ipynb
+          - Hierarchical Teams: tutorials/multi_agent/hierarchical_agent_teams.ipynb
+      - Research & QA:   
+          - Web Research (STORM): tutorials/storm/storm.ipynb
+          - Retrieval-Augmented Generation:
+              - tutorials/rag/langgraph_adaptive_rag.ipynb
+              - tutorials/rag/langgraph_adaptive_rag_cohere.ipynb
+              - tutorials/rag/langgraph_adaptive_rag_local.ipynb
+              - tutorials/rag/langgraph_agentic_rag.ipynb 
+              - tutorials/rag/langgraph_crag.ipynb
+              - tutorials/rag/langgraph_crag_local.ipynb
+              - tutorials/rag/langgraph_self_rag.ipynb  
+              - tutorials/rag/langgraph_self_rag_local.ipynb
+      - Applications:
+          - Chatbots: 
+              - Customer Support: tutorials/chatbots/customer-support.ipynb
+              - Info Gathering: tutorials/chatbots/information-gather-prompting.ipynb
+          - Code Assistant: tutorials/code_assistant/langgraph_code_assistant.ipynb  
+          - Web Navigation: tutorials/web-navigation/web_voyager.ipynb
+      - Evaluation & Analysis:  
+          - Chatbot Eval via Sim:
+              - Agent-based: tutorials/chatbot-simulation-evaluation/agent-simulation-evaluation.ipynb
+              - Dataset-based: tutorials/chatbot-simulation-evaluation/langsmith-agent-simulation-evaluation.ipynb  
+          - Self-Discovering Agent: tutorials/self-discover/self-discover.ipynb
+          - Swarm: tutorials/gptswarm/swarm.ipynb
+  - Reference:
+      - Graphs: reference/graphs.md
+      - Checkpointing: reference/checkpoints.md
+      - Prebuilt Components: reference/prebuilt_components.md
+  
+
+markdown_extensions:
+  - abbr
+  - admonition
+  - pymdownx.details
+  - attr_list
+  - def_list
+  - footnotes
+  - md_in_html
+  - toc:
+      permalink: true
+  - pymdownx.arithmatex:
+      generic: true
+  - pymdownx.betterem:
+      smart_enable: all
+  - pymdownx.caret
+  - pymdownx.details
+  - pymdownx.emoji:
+      emoji_generator: !!python/name:material.extensions.emoji.to_svg
+      emoji_index: !!python/name:material.extensions.emoji.twemoji
+  - pymdownx.highlight:
+      anchor_linenums: true
+      line_spans: __span
+      pygments_lang_class: true
+  - pymdownx.inlinehilite
+  - pymdownx.keys
+  - pymdownx.magiclink:
+      normalize_issue_symbols: true
+      repo_url_shorthand: true
+      user: langchain-ai 
+      repo: langgraph
+  - pymdownx.mark
+  - pymdownx.smartsymbols
+  - pymdownx.snippets:
+      auto_append:
+        - includes/mkdocs.md
+  - pymdownx.superfences:
+      custom_fences:
+        - name: mermaid
+          class: mermaid
+          format: !!python/name:pymdownx.superfences.fence_code_format
+  - pymdownx.tabbed:
+      alternate_style: true
+      combine_header_slug: true
+  - pymdownx.tasklist:
+      custom_checkbox: true
+extra_css:
+  - css/mkdocstrings.css

docs/overrides/main.html

@@ -0,0 +1,137 @@
+{% extends "base.html" %}
+
+{% block extrahead %}
+  <style>
+    @import url("https://fonts.googleapis.com/css2?family=Public+Sans&display=swap");
+    :root {
+      --md-primary-fg-color: #333333;
+      --md-accent-fg-color: #1E88E5;
+      --md-default-bg-color: #FFFFFF;
+      --md-default-fg-color: #333333;
+      --md-text-font-family: "Public Sans", sans-serif;
+    }
+
+    body {
+      font-family: var(--md-text-font-family);
+      background-color: var(--md-default-bg-color);
+      color: var(--md-default-fg-color);
+    }
+
+    .md-main {
+      background-color: #FFFFFF;
+    }
+
+    .navbar {
+      background-color: #FFFFFF;
+      color: #333333;
+      box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+    }
+
+    .md-footer {
+      background-color: #F5F5F5;
+      color: #666666;
+    }
+
+    .md-footer-meta {
+      background-color: #EEEEEE;
+    }
+
+    .md-typeset a {
+      color: #1E88E5;
+    }
+
+    .md-typeset a:hover {
+      color: #1565C0;
+    }
+
+    .md-nav__link--active,
+    .md-nav__link:active {
+      color: #1E88E5;
+    }
+
+    .md-search__input {
+      background-color: #F5F5F5;
+      color: #333333;
+    }
+
+    .md-search__input:hover,
+    .md-search__input:focus {
+      background-color: #EEEEEE;
+    }
+    /* Table of contents styles */
+    .md-nav--secondary .md-nav__item--active > .md-nav__link {
+      font-weight: bold;
+      color: var(--md-primary-fg-color);
+    }
+
+    .md-nav--secondary .md-nav__item--nested > .md-nav__link {
+      font-weight: normal;
+      color: var(--md-default-fg-color);
+    }
+
+    .md-nav--secondary .md-nav__item--nested > .md-nav__link::before {
+      content: "";
+      display: inline-block;
+      width: 6px;
+      height: 6px;
+      background-color: var(--md-default-fg-color);
+      border-radius: 50%;
+      margin-right: 0.5rem;
+    }
+
+    [data-md-color-scheme="slate"] {
+      --md-default-bg-color: #1E1E1E;
+      --md-default-fg-color: #FFFFFF;
+      --md-accent-fg-color: #64B5F6;
+    }
+
+    [data-md-color-scheme="slate"] .md-main {
+      background-color: #1E1E1E;
+    }
+
+    [data-md-color-scheme="slate"] .navbar {
+      background-color: #1E1E1E;
+      color: #FFFFFF;
+      box-shadow: none;
+    }
+
+    [data-md-color-scheme="slate"] .md-footer {
+      background-color: #1E1E1E;
+      color: #BDBDBD;
+    }
+
+    [data-md-color-scheme="slate"] .md-footer-meta {
+      background-color: #1E1E1E;
+    }
+
+    [data-md-color-scheme="slate"] .md-typeset a {
+      color: #64B5F6;
+    }
+
+    [data-md-color-scheme="slate"] .md-typeset a:hover {
+      color: #90CAF9;
+    }
+    .notebook-links {
+      display: flex;
+      justify-content: flex-end;
+      margin-bottom: 1rem;
+    }
+    .notebook-links .md-content__button {
+      margin-left: 0.5rem;
+    }
+    
+  </style>
+{% endblock %}
+
+
+{% block content %}
+<div class="notebook-links">
+  {% if page.nb_url %}
+    <a href="{{ page.nb_url }}" title="Download Notebook" class="md-content__button md-icon">
+      {% include ".icons/material/download.svg" %}
+    </a>
+  {% endif %}
+</div>
+
+{{ super() }}
+{% endblock content %}