deploy: c9b95c7c9f15441738c938bb27cca66eb86990e3

.buildinfo

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+# Sphinx build info version 1
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: 416c1b7f738dbd8ff231cf7246bbbb27
+tags: 645f666f9bcd5a90fca523b33c5a78b7

CNAME

@@ -1 +0,0 @@
-docs.archgw.com

_downloads/594e1d60c04207f4d07a934ce337cbce/prompt-config-full-reference.yml

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+version: "0.1-beta"
+
+listener:
+  address: 0.0.0.0 # or 127.0.0.1
+  port: 10000
+  # Defines how Arch should parse the content from application/json or text/pain Content-type in the http request
+  message_format: huggingface
+  common_tls_context: # If you configure port 443, you'll need to update the listener with your TLS certificates
+    tls_certificates:
+      - certificate_chain:
+          filename: "/etc/certs/cert.pem"
+        private_key:
+          filename: "/etc/certs/key.pem"
+
+# Arch creates a round-robin load balancing between different endpoints, managed via the cluster subsystem.
+endpoints:
+  app_server:
+    # value could be ip address or a hostname with port
+    # this could also be a list of endpoints for load balancing
+    # for example endpoint: [ ip1:port, ip2:port ]
+    endpoint: "127.0.0.1:80"
+    # max time to wait for a connection to be established
+    connect_timeout: 0.005s
+
+  mistral_local:
+    endpoint: "127.0.0.1:8001"
+
+  error_target:
+    endpoint: "error_target_1"
+
+# Centralized way to manage LLMs, manage keys, retry logic, failover and limits in a central way
+llm_providers:
+  - name: "OpenAI"
+    provider: "openai"
+    access_key: $OPENAI_API_KEY
+    model: gpt-4o
+    default: true
+    stream: true
+    rate_limits:
+      selector: #optional headers, to add rate limiting based on http headers like JWT tokens or API keys
+        http_header:
+          name: "Authorization"
+          value: "" # Empty value means each separate value has a separate limit
+      limit:
+        tokens: 100000 # Tokens per unit
+        unit: "minute"
+
+  - name: "Mistral8x7b"
+    provider: "mistral"
+    access_key: $MISTRAL_API_KEY
+    model: "mistral-8x7b"
+
+  - name: "MistralLocal7b"
+    provider: "local"
+    model: "mistral-7b-instruct"
+    endpoint: "mistral_local"
+
+# provides a way to override default settings for the arch system
+overrides:
+  # By default Arch uses an NLI + embedding approach to match an incomming prompt to a prompt target.
+  # The intent matching threshold is kept at 0.80, you can overide this behavior if you would like
+  prompt_target_intent_matching_threshold: 0.60
+
+# default system prompt used by all prompt targets
+system_prompt: |
+  You are a network assistant that just offers facts; not advice on manufacturers or purchasing decisions.
+
+prompt_guards:
+  input_guards:
+    jailbreak:
+      on_exception:
+        message: "Looks like you're curious about my abilities, but I can only provide assistance within my programmed parameters."
+
+prompt_targets:
+  - name: "reboot_network_device"
+    description: "Helps network operators perform device operations like rebooting a device."
+    endpoint:
+      name: app_server
+      path: "/agent/action"
+    parameters:
+      - name: "device_id"
+        # additional type options include: int | float | bool | string | list | dict
+        type: "string"
+        description: "Identifier of the network device to reboot."
+        required: true
+      - name: "confirmation"
+        type: "string"
+        description: "Confirmation flag to proceed with reboot."
+        default: "no"
+        enum: [yes, no]
+
+  - name: "information_extraction"
+    default: true
+    description: "This prompt handles all scenarios that are question and answer in nature. Like summarization, information extraction, etc."
+    endpoint:
+      name: app_server
+      path: "/agent/summary"
+    # Arch uses the default LLM and treats the response from the endpoint as the prompt to send to the LLM
+    auto_llm_dispatch_on_response: true
+    # override system prompt for this prompt target
+    system_prompt: |
+      You are a helpful information extraction assistant. Use the information that is provided to you.
+
+error_target:
+  endpoint:
+    name: error_target_1
+    path: /error
+
+tracing: 100 #sampling rate. Note by default Arch works on OpenTelemetry compatible tracing.

_downloads/76c29fa020a722e6be4b991f849978ce/intent_detection.py

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+from flask import Flask, request, jsonify
+from datetime import datetime
+import uuid
+from langchain.memory import ConversationBufferMemory
+from langchain.schema import AIMessage, HumanMessage
+from langchain import OpenAI
+
+app = Flask(__name__)
+
+# Global dictionary to keep track of user memories
+user_memories = {}
+
+def get_user_conversation(user_id):
+    """
+    Retrieve the user's conversation memory using LangChain.
+    If the user does not exist, initialize their conversation memory.
+    """
+    if user_id not in user_memories:
+        user_memories[user_id] = ConversationBufferMemory(return_messages=True)
+    return user_memories[user_id]
+
+def update_user_conversation(user_id, client_messages, intent_changed):
+    """
+    Update the user's conversation memory with new messages using LangChain.
+    Each message is augmented with a UUID, timestamp, and intent change marker.
+    Only new messages are added to avoid duplication.
+    """
+    memory = get_user_conversation(user_id)
+    stored_messages = memory.chat_memory.messages
+
+    # Determine the number of stored messages
+    num_stored_messages = len(stored_messages)
+    new_messages = client_messages[num_stored_messages:]
+
+    # Process each new message
+    for index, message in enumerate(new_messages):
+        role = message.get('role')
+        content = message.get('content')
+        metadata = {
+            'uuid': str(uuid.uuid4()),
+            'timestamp': datetime.utcnow().isoformat(),
+            'intent_changed': False  # Default value
+        }
+
+        # Mark the intent change on the last message if detected
+        if intent_changed and index == len(new_messages) - 1:
+            metadata['intent_changed'] = True
+
+        # Create a new message with metadata
+        if role == 'user':
+            memory.chat_memory.add_message(
+                HumanMessage(content=content, additional_kwargs={'metadata': metadata})
+            )
+        elif role == 'assistant':
+            memory.chat_memory.add_message(
+                AIMessage(content=content, additional_kwargs={'metadata': metadata})
+            )
+        else:
+            # Handle other roles if necessary
+            pass
+
+    return memory
+
+def get_messages_since_last_intent(messages):
+    """
+    Retrieve messages from the last intent change onwards using LangChain.
+    """
+    messages_since_intent = []
+    for message in reversed(messages):
+        # Insert message at the beginning to maintain correct order
+        messages_since_intent.insert(0, message)
+        metadata = message.additional_kwargs.get('metadata', {})
+        # Break if intent_changed is True
+        if metadata.get('intent_changed', False) == True:
+            break
+    return messages_since_intent
+
+def forward_to_llm(messages):
+    """
+    Forward messages to an upstream LLM using LangChain.
+    """
+    # Convert messages to a conversation string
+    conversation = ""
+    for message in messages:
+        role = 'User' if isinstance(message, HumanMessage) else 'Assistant'
+        content = message.content
+        conversation += f"{role}: {content}\n"
+    # Use LangChain's LLM to get a response. This call is proxied through Arch for end-to-end observability and traffic management
+    llm = OpenAI()
+    # Create a prompt that includes the conversation
+    prompt = f"{conversation}Assistant:"
+    response = llm(prompt)
+    return response
+
+@app.route('/process_rag', methods=['POST'])
+def process_rag():
+    # Extract JSON data from the request
+    data = request.get_json()
+
+    user_id = data.get('user_id')
+    if not user_id:
+        return jsonify({'error': 'User ID is required'}), 400
+
+    client_messages = data.get('messages')
+    if not client_messages or not isinstance(client_messages, list):
+        return jsonify({'error': 'Messages array is required'}), 400
+
+    # Extract the intent change marker from Arch's headers if present for the current prompt
+    intent_changed_header = request.headers.get('x-arch-intent-marker', '').lower()
+    if intent_changed_header in ['', 'false']:
+        intent_changed = False
+    elif intent_changed_header == 'true':
+        intent_changed = True
+    else:
+        # Invalid value provided
+        return jsonify({'error': 'Invalid value for x-arch-prompt-intent-change header'}), 400
+
+    # Update user conversation based on intent change
+    memory = update_user_conversation(user_id, client_messages, intent_changed)
+
+    # Retrieve messages since last intent change for LLM
+    messages_for_llm = get_messages_since_last_intent(memory.chat_memory.messages)
+
+    # Forward messages to upstream LLM
+    llm_response = forward_to_llm(messages_for_llm)
+
+    # Prepare the messages to return
+    messages_to_return = []
+    for message in memory.chat_memory.messages:
+        role = 'user' if isinstance(message, HumanMessage) else 'assistant'
+        content = message.content
+        metadata = message.additional_kwargs.get('metadata', {})
+        message_entry = {
+            'uuid': metadata.get('uuid'),
+            'timestamp': metadata.get('timestamp'),
+            'role': role,
+            'content': content,
+            'intent_changed': metadata.get('intent_changed', False)
+        }
+        messages_to_return.append(message_entry)
+
+    # Prepare the response
+    response = {
+        'user_id': user_id,
+        'messages': messages_to_return,
+        'llm_response': llm_response
+    }
+
+    return jsonify(response), 200
+
+if __name__ == '__main__':
+    app.run(debug=True)

_downloads/a0b0970c8fa22d4fe861e8362965b77c/getting-started.yml

@@ -0,0 +1,41 @@
+version: "0.1-beta"
+listener:
+  address: 127.0.0.1 | 0.0.0.0
+  port_value: 8080 #If you configure port 443, you'll need to update the listener with tls_certificates
+  messages: tuple | hugging-face-messages-api
+
+system_prompts:
+  - name: network_assistant
+    content: You are a network assistant that just offers facts about the operational health of the network
+
+llm_providers:
+    - name: "OpenAI"
+      access_key: $OPEN_AI_KEY
+      model: gpt-4o
+      default: true
+    - name: "Mistral"
+      access_key: $MISTRAL_KEY
+      model: mixtral8-7B
+
+prompt_endpoints:
+  - "http://127.0.0.2"
+  - "http://127.0.0.1"
+
+prompt_guards:
+   input-guard:
+     - name: #jailbreak
+       on-exception-message: Looks like you are curious about my abilities. But I can only
+
+prompt_targets:
+   - name: information_extraction
+     type: RAG
+     description: this prompt handles all information extractions scenarios
+     path: /agent/summary
+
+   - name: reboot_network_device
+     path: /agent/action
+     description: used to help network operators with perform device operations like rebooting a device.
+     parameters:
+error_target: #handle errors from Bolt or upstream LLMs
+    name: “error_handler”
+    path: /errors

_sources/configuration_reference.rst

@@ -0,0 +1,13 @@
+Configuration Reference
+============================
+
+The following is a complete reference of the ``prompt-conifg.yml`` that controls the behavior of a single instance of
+the Arch gateway. We've kept things simple (less than 80 lines) and held off on exposing additional functionality (for
+e.g. suppporting push observability stats, managing prompt-endpoints as virtual cluster, exposing more load balancing
+options, etc). Our belief that the simple things, should be simple. So we offert good defaults for developers, so
+that they can spend more of their time in building features unique to their AI experience.
+
+.. literalinclude:: /_config/prompt-config-full-reference.yml
+    :language: yaml
+    :linenos:
+    :caption: :download:`prompt-config-full-reference-beta-1-0.yml </_config/prompt-config-full-reference.yml>`

_sources/getting_started/getting_started.rst

@@ -0,0 +1,48 @@
+.. _getting_started:
+
+Getting Started
+================
+
+.. sidebar:: Pre-requisites
+
+    In order for you to get started, please make sure that `Docker <https://www.docker.com/get-started>`_
+    and `Python <https://www.python.org/downloads/>`_ are installed locally.
+
+    As the examples use the pre-built `Arch Docker images <https://hub.docker.com/r/katanemo/arch>`_,
+    they should work on the following architectures:
+
+        - x86_64
+        - ARM 64
+
+
+This section gets you started with a very simple configuration and provides some example configurations.
+
+
+The fastest way to get started using Arch is installing `pre-built binaries <https://hub.docker.com/r/katanemo/arch>`_.
+You can also build it from source.
+
+Step 1: Install the Arch CLI
+----------------------------
+Arch's CLI allows you to manage and interact with the Arch gateway efficiently. To install the CLI, simply
+run the following command:
+
+.. code-block:: bash
+
+    pip install archgw
+
+This will install the archgw command-line tool globally on your system.
+
+Step 2: Start Arch Gateway
+--------------------------
+
+.. code-block:: bash
+
+    archgw up --quick-start
+
+Configuration
+-------------
+
+Today, only support a static bootstrap configuration file for simplicity today:
+
+.. literalinclude:: /_config/getting-started.yml
+    :language: yaml

_sources/getting_started/use_cases.rst

@@ -0,0 +1,6 @@
+.. toctree::
+  :maxdepth: 2
+  :caption: Use Cases
+
+  use_cases/rag
+  use_cases/function_calling

_sources/getting_started/use_cases/function_calling.rst

@@ -0,0 +1,71 @@
+.. _arch_function_calling_agentic_guide:
+
+Agentic (Text-to-Action) Apps
+==============================
+
+Arch helps you easily personalize your applications by calling application-specific (API) functions
+via user prompts. This involves any predefined functions or APIs you want to expose to users to perform tasks,
+gather information, or manipulate data. This capability is generally referred to as **function calling**, where
+you have the flexibility to support “agentic” apps tailored to specific use cases - from updating insurance
+claims to creating ad campaigns - via prompts.
+
+Arch analyzes prompts, extracts critical information from prompts, engages in lightweight conversation with
+the user to gather any missing parameters and makes API calls so that you can focus on writing business logic.
+Arch does this via its purpose-built :ref:`Arch-FC LLM <llms_in_arch>` - the fastest (200ms p90 - 10x faser than GPT-4o)
+and cheapest (100x than GPT-40) function-calling LLM that matches performance with frontier models.
+______________________________________________________________________________________________
+
+.. image:: /_static/img/function-calling-network-flow.jpg
+   :width: 100%
+   :align: center
+
+
+Single Function Call
+--------------------
+In the most common scenario, users will request a single action via prompts, and Arch efficiently processes the
+request by extracting relevant parameters, validating the input, and calling the designated function or API. Here
+is how you would go about enabling this scenario with Arch:
+
+Step 1: Define prompt targets with functions
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. literalinclude:: /_config/function-calling-network-agent.yml
+    :language: yaml
+    :linenos:
+    :emphasize-lines: 16-37
+    :caption: Define prompt targets that can enable users to engage with API and backened functions of an app
+
+Step 2: Process request parameters in Flask
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Once the prompt targets are configured as above, handling those parameters is
+
+.. literalinclude:: /_include/parameter_handling_flask.py
+    :language: python
+    :linenos:
+    :caption: Flask API example for parameter extraction via HTTP request parameters
+
+Parallel/ Multiple Function Calling
+-----------------------------------
+In more complex use cases, users may request multiple actions or need multiple APIs/functions to be called
+simultaneously or sequentially. With Arch, you can handle these scenarios efficiently using parallel or multiple
+function calling. This allows your application to engage in a broader range of interactions, such as updating
+different datasets, triggering events across systems, or collecting results from multiple services in one prompt.
+
+Arch-FC1B is built to manage these parallel tasks efficiently, ensuring low latency and high throughput, even
+when multiple functions are invoked. It provides two mechanisms to handle these cases:
+
+Step 1: Define Multiple Function Targets
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+When enabling multiple function calling, define the prompt targets in a way that supports multiple functions or
+API calls based on the user's prompt. These targets can be triggered in parallel or sequentially, depending on
+the user's intent.
+
+Example of Multiple Prompt Targets in YAML:
+
+.. literalinclude:: /_config/function-calling-network-agent.yml
+    :language: yaml
+    :linenos:
+    :emphasize-lines: 16-37
+    :caption: Define prompt targets that can enable users to engage with API and backened functions of an app

_sources/getting_started/use_cases/rag.rst

@@ -0,0 +1,96 @@
+.. _arch_rag_guide:
+
+Retrieval-Augmented (RAG)
+=========================
+
+The following section describes how Arch can help you build faster, smarter and more accurate
+Retrieval-Augmented Generation (RAG) applications.
+
+Intent-drift Detection
+----------------------
+
+Developers struggle to handle `follow-up <https://www.reddit.com/r/ChatGPTPromptGenius/comments/17dzmpy/how_to_use_rag_with_conversation_history_for/?>`_
+or `clarifying <https://www.reddit.com/r/LocalLLaMA/comments/18mqwg6/best_practice_for_rag_with_followup_chat/>`_
+questions. Specifically, when users ask for changes or additions to previous responses their AI applications often
+generate entirely new responses instead of adjusting previous ones. Arch offers *intent-drift* tracking as a feature so
+that developers can know when the user has shifted away from a previous intent so that they can dramatically improve
+retrieval accuracy, lower overall token cost and  improve the speed of their responses back to users.
+
+Arch uses its built-in lightweight NLI and embedding models to know if the user has steered away from an active intent.
+Arch's intent-drift detection mechanism is based on its' *prompt_targets* primtive. Arch tries to match an incoming
+prompt to one of the *prompt_targets* configured in the gateway. Once it detects that the user has moved away from an active
+active intent, Arch adds the ``x-arch-intent-drift`` headers to the request before sending it your application servers.
+
+.. literalinclude:: /_include/intent_detection.py
+    :language: python
+    :linenos:
+    :lines: 95-125
+    :emphasize-lines: 14-22
+    :caption: :download:`Intent drift detection in python </_include/intent_detection.py>`
+
+_____________________________________________________________________________________________________________________
+
+.. Note::
+
+   Arch is (mostly) stateless so that it can scale in an embarrassingly parrallel fashion. So, while Arch offers
+   intent-drift detetction, you still have to maintain converational state with intent drift as meta-data. The
+   following code snippets show how easily you can build and enrich conversational history with Langchain (in python),
+   so that you can use the most relevant prompts for your retrieval and for prompting upstream LLMs.
+
+
+Step 1: define ConversationBufferMemory
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. literalinclude:: /_include/intent_detection.py
+    :language: python
+    :linenos:
+    :lines: 1-21
+
+Step 2: update ConversationBufferMemory w/ intent
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. literalinclude:: /_include/intent_detection.py
+    :language: python
+    :linenos:
+    :lines: 22-62
+
+Step 3: get Messages based on latest drift
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. literalinclude:: /_include/intent_detection.py
+    :language: python
+    :linenos:
+    :lines: 64-76
+
+
+You can used the last set of messages that match to an intent to prompt an LLM, use it with an vector-DB for
+improved retrieval, etc. With Arch and a few lines of code, you can improve the retrieval accuracy, lower overall
+token cost and dramatically improve the speed of their responses back to users.
+
+Parameter Extraction for RAG
+----------------------------
+
+To build RAG (Retrieval-Augmented Generation) applications, you can configure prompt targets with parameters,
+enabling Arch to retrieve critical information in a structured way for processing. This approach improves the
+retrieval quality and speed of your application. By extracting parameters from the conversation, you can pull
+the appropriate chunks from a vector database or SQL-like data store to enhance accuracy. With Arch, you can
+streamline data retrieval and processing to build more efficient and precise RAG applications.
+
+Step 1: Define prompt targets with parameter definitions
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. literalinclude:: /_config/rag-prompt-targets.yml
+    :language: yaml
+    :linenos:
+    :emphasize-lines: 16-36
+    :caption: prompt-config.yaml for parameter extraction for RAG scenarios
+
+Step 2: Process request parameters in Flask
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Once the prompt targets are configured as above, handling those parameters is
+
+.. literalinclude:: /_include/parameter_handling_flask.py
+    :language: python
+    :linenos:
+    :caption: Flask API example for parameter extraction via HTTP request parameters

_sources/intro/architecture/architecture.rst

@@ -0,0 +1,12 @@
+Technical Architecture
+======================
+
+.. toctree::
+  :maxdepth: 2
+
+  intro/terminology
+  intro/threading_model
+  listeners/listeners
+  prompt_processing/prompt_processing
+  listeners/llm_provider
+  model_serving/model_serving

_sources/intro/architecture/intro/terminology.rst

@@ -0,0 +1,46 @@
+.. _arch_terminology:
+
+Terminology
+============
+
+A few definitions before we dive into the main architecture documentation. Arch borrows from Envoy's terminology
+to keep things consistent in logs, traces and in code.
+
+**Downstream(Ingress)**: An downstream client (web application, etc.) connects to Arch, sends prompts, and receives responses.
+
+**Upstream(Egress)**: An upstream host that receives connections and prompts from Arch, and returns context or responses for a prompt
+
+.. image:: /_static/img/network-topology-ingress-egress.jpg
+   :width: 100%
+   :align: center
+
+**Listener**: A listener is a named network location (e.g., port, address, path etc.) that Arch listens on to process prompts
+before forwarding them to your application server endpoints. rch enables you to configure one listener for downstream connections
+(like port 80, 443) and creates a separate internal listener for calls that initiate from your application code to LLMs.
+
+.. Note::
+
+   When you start Arch, you specify a listener address/port that you want to bind downstream. But, Arch uses are predefined port
+   that you can use (``127.0.0.1:10000``) to proxy egress calls originating from your application to LLMs (API-based or hosted).
+   For more details, check out :ref:`LLM providers <llm_providers>`
+
+**Instance**: An instance of the Arch gateway. When you start Arch it creates at most two processes. One to handle Layer 7
+networking operations (auth, tls, observability, etc) and the second process to serve models that enable it to make smart
+decisions on how to accept, handle and forward prompts. The second process is optional, as the model serving sevice could be
+hosted on a different network (an API call). But these two processes are considered a single instance of Arch.
+
+**Prompt Targets**: Arch offers a primitive called ``prompt_targets`` to help separate business logic from undifferentiated
+work in building generative AI apps. Prompt targets are endpoints that receive prompts that are processed by Arch.
+For example, Arch enriches incoming prompts with metadata like knowing when a request is a follow-up or clarifying prompt
+so that you can build faster, more accurate retrieval (RAG) apps. To support agentic apps, like scheduling travel plans or
+sharing comments on a document - via prompts, Bolt uses its function calling abilities to extract critical information from
+the incoming prompt (or a set of prompts) needed by a downstream backend API or function call before calling it directly.
+
+**Error Targets**: Error targets are those endpoints that receive forwarded errors from Arch when issues arise,
+such as failing to properly call a function/API, detecting violations of guardrails, or encountering other processing errors.
+These errors are communicated to the application via headers (X-Arch-[ERROR-TYPE]), allowing it to handle the errors gracefully
+and take appropriate actions.
+
+**Model Serving**: Arch is a set of **two** self-contained processes that are designed to run alongside your application servers
+(or on a separate hostconnected via a network).The  **model serving** process helps Arch make intelligent decisions about the
+incoming prompts. The model server is designed to call the (fast) purpose-built :ref:`LLMs <llms_in_arch>` in Arch.

_sources/intro/architecture/intro/threading_model.rst

@@ -0,0 +1,21 @@
+.. _arch_overview_threading:
+
+Threading model
+===============
+
+Arch builds on top of Envoy's single process with multiple threads architecture.
+
+A single *primary* thread controls various sporadic coordination tasks while some number of *worker*
+threads perform filtering, and forwarding.
+
+Once a connection is accepted, the connection spends the rest of its lifetime bound to a single worker
+thread. All the functionality around prompt handling from a downstream client is handled in a separate worker thread.
+This allows the majority of Arch to be largely single threaded (embarrassingly parallel) with a small amount
+of more complex code handling coordination between the worker threads.
+
+Generally Arch is written to be 100% non-blocking.
+
+.. tip::
+
+   For most workloads we recommend configuring the number of worker threads to be equal to the number of
+   hardware threads on the machine.

_sources/intro/architecture/listeners/listeners.rst

@@ -0,0 +1,37 @@
+.. _arch_overview_listeners:
+
+Listener
+---------
+Listener is a top level primitive in Arch, which simplifies the configuration required to bind incoming
+connections from downstream clients, and for egress connections to LLMs (hosted or API)
+
+Arch builds on Envoy's Listener subsystem to streamline connection managemet for developers. Arch minimizes
+the complexity of Envoy's listener setup by using best-practices and exposing only essential settings,
+making it easier for developers to bind connections without deep knowledge of Envoy’s configuration model. This
+simplification ensures that connections are secure, reliable, and optimized for performance.
+
+Downstream (Ingress)
+^^^^^^^^^^^^^^^^^^^^^^
+Developers can configure Arch to accept connections from downstream clients. A downstream listener acts as the
+primary entry point for incoming traffic, handling initial connection setup, including network filtering, gurdrails,
+and additional network security checks. For more details on prompt security and safety,
+see :ref:`here <arch_overview_prompt_handling>`
+
+Upstream (Egress)
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Arch automatically configures a listener to route requests from your application to upstream LLM API providers (or hosts).
+When you start Arch, it creates a listener for egress traffic based on the presence of the ``llm_providers`` configuration
+section in the ``prompt_config.yml`` file. Arch binds itself to a local address such as ``127.0.0.1:9000/v1`` or a DNS-based
+address like ``arch.local:9000/v1`` for outgoing traffic. For more details on LLM providers, read :ref:`here <llm_providers>`
+
+Configure Listener
+^^^^^^^^^^^^^^^^^^
+
+To configure a Downstream (Ingress) Listner, simply add the ``listener`` directive to your ``prompt_config.yml`` file:
+
+.. literalinclude:: /_config/getting-started.yml
+    :language: yaml
+    :linenos:
+    :lines: 1-18
+    :emphasize-lines: 2-5
+    :caption: :download:`arch-getting-started.yml </_config/getting-started.yml>`

_sources/intro/architecture/listeners/llm_provider.rst

@@ -0,0 +1,52 @@
+.. _llm_providers:
+
+LLM Provider
+------------
+
+``llm_provider`` is a top-level primitive in Arch, helping developers centrally define, secure, observe,
+and manage the usage of of their LLMs. Arch builds on Envoy's reliable `cluster subsystem <https://www.envoyproxy.io/docs/envoy/v1.31.2/intro/arch_overview/upstream/cluster_manager>`_
+to manage egress traffic to LLMs, which includes intelligent routing, retry and fail-over mechanisms,
+ensuring high availability and fault tolerance. This abstraction also enables developers to seamlessly switching between LLM providers or upgrade LLM versions, simplifying the integration and scaling of LLMs across
+applications.
+
+
+Below is an example of how you can configure ``llm_providers`` with an instance of an Arch gateway.
+
+.. literalinclude:: /_config/getting-started.yml
+    :language: yaml
+    :linenos:
+    :lines: 1-20
+    :emphasize-lines: 11-18
+    :caption: :download:`arch-getting-started.yml </_config/getting-started.yml>`
+
+.. Note::
+    When you start Arch, it creates a listener port for egress traffic based on the presence of ``llm_providers``
+    configuration section in the ``prompt_config.yml`` file. Arch binds itself to a local address such as
+    ``127.0.0.1:9000/v1`` or a DNS-based address like ``arch.local:9000/v1`` for egress traffic.
+
+Arch also offers vendor-agnostic SDKs and libraries to make LLM calls to API-based LLM providers (like OpenAI,
+Anthropic, Mistral, Cohere, etc.) and supports calls to OSS LLMs that are hosted on your infrastructure. Arch
+abstracts the complexities of integrating with different LLM providers, providing a unified interface for making
+calls, handling retries, managing rate limits, and ensuring seamless integration with cloud-based and on-premise
+LLMs. Simply configure the details of the LLMs your application will use, and Arch offers a unified interface to
+make outbound LLM calls.
+
+Example: Using the Arch Python SDK
+----------------------------------
+
+.. code-block:: python
+
+   from arch_client import ArchClient
+
+   # Initialize the Arch client
+   client = ArchClient(base_url="http://127.0.0.1:9000/v1")
+
+   # Define your LLM provider and prompt
+   model_id = "openai"
+   prompt = "What is the capital of France?"
+
+   # Send the prompt to the LLM through Arch
+   response = client.completions.create(llm_provider=llm_provider, prompt=prompt)
+
+   # Print the response
+   print("LLM Response:", response)

_sources/intro/architecture/model_serving/model_serving.rst

@@ -0,0 +1,56 @@
+.. _arch_model_serving:
+
+Model Serving
+-------------
+
+Arch is a set of **two** self-contained processes that are designed to run alongside your application
+servers (or on a separate host connected via a network). The first process is designated to manage low-level
+networking and HTTP related comcerns, and the other process is for **model serving**, which helps Arch make
+intelligent decisions about the incoming prompts. The model server is designed to call the purpose-built
+:ref:`LLMs <llms_in_arch>` in Arch.
+
+.. image:: /_static/img/arch-system-architecture.jpg
+   :align: center
+   :width: 50%
+
+_____________________________________________________________________________________________________________
+
+Arch' is designed to be deployed in your cloud VPC, on a on-premises host, and can work on devices that don't
+have a GPU. Note, GPU devices are need for fast and cost-efficient use, so that Arch (model server, specifically)
+can process prompts quickly and forward control back to the applicaton host. There are three modes in which Arch
+can be configured to run its **model server** subsystem:
+
+Local Serving (CPU - Moderate)
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+The following bash commands enable you to configure the model server subsystem in Arch to run local on device
+and only use CPU devices. This will be the slowest option but can be useful in dev/test scenarios where GPUs
+might not be available.
+
+.. code-block:: bash
+
+    archgw up --local -cpu
+
+Local Serving (GPU- Fast)
+^^^^^^^^^^^^^^^^^^^^^^^^^
+The following bash commands enable you to configure the model server subsystem in Arch to run locally on the
+machine and utilize the GPU available for fast inference across all model use cases, including function calling
+guardails, etc.
+
+.. code-block:: bash
+
+    archgw up --local
+
+Cloud Serving (GPU - Blazing Fast)
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+The command below instructs Arch to intelligently use GPUs locally for fast intent detection, but default to
+cloud serving for function calling and guardails scenarios to dramatically improve the speed and overall performance
+of your applications.
+
+.. code-block:: bash
+
+    archgw up
+
+.. Note::
+    Arch's model serving in the cloud is priced at $0.05M/token (156x cheaper than GPT-4o) with averlage latency
+    of 200ms (10x faster than GPT-4o). Please refer to our :ref:`getting started guide <getting_started>` to know
+    how to generate API keys for model serving

_sources/intro/architecture/prompt_processing/prompt_processing.rst

@@ -0,0 +1,155 @@
+.. _arch_overview_prompt_handling:
+
+Prompts
+-------
+
+Arch's primary design point is to securely accept, process and handle prompts. To do that effectively,
+Arch relies on Envoy's HTTP `connection management <https://www.envoyproxy.io/docs/envoy/v1.31.2/intro/arch_overview/http/http_connection_management>`_,
+subsystem and its **prompt handler** subsystem engineered with purpose-built :ref:`LLMs <llms_in_arch>` to
+implement critical functionality on behalf of developers so that you can stay focused on business logic.
+
+.. Note::
+   Arch's **prompt handler** subsystem interacts with the **model** subsytem through Envoy's cluster manager
+   system to ensure robust, resilient and fault-tolerant experience in managing incoming prompts. Read more
+   about the :ref:`model subsystem <arch_model_serving>` and how the LLMs are hosted in Arch.
+
+Messages
+--------
+
+Arch accepts messages directly from the body of the HTTP request in a format that follows the `Hugging Face Messages API <https://huggingface.co/docs/text-generation-inference/en/messages_api>`_.
+This design allows developers to pass a list of messages, where each message is represented as a dictionary
+containing two key-value pairs:
+
+    - **Role**: Defines the role of the message sender, such as "user" or "assistant".
+    - **Content**: Contains the actual text of the message.
+
+
+Prompt Guardrails
+-----------------
+
+Arch is engineered with :ref:`Arch-Guard <llms_in_arch>`, an industry leading safety layer, powered by a
+compact and high-performimg LLM that monitors incoming prompts to detect and reject jailbreak attempts -
+ensuring that unauthorized or harmful behaviors are intercepted early in the process.
+
+To add jailbreak guardrails, see example below:
+
+.. literalinclude:: /_config/getting-started.yml
+    :language: yaml
+    :linenos:
+    :emphasize-lines: 24-27
+    :caption: :download:`arch-getting-started.yml </_config/getting-started.yml>`
+
+.. Note::
+   As a roadmap item, Arch will expose the ability for developers to define custom guardrails via Arch-Guard-v2,
+   and add support for additional safety checks defined by developers and hazardous categories like, violent crimes, privacy, hate,
+   etc. To offer feedback on our roadmap, please visit our `github page <https://github.com/orgs/katanemo/projects/1>`_
+
+
+Prompt Targets
+--------------
+
+Once a prompt passes any configured guardrail checks, Arch processes the contents of the incoming conversation
+and identifies where to forwad the conversation to via its essential ``prompt_targets`` primitve. Prompt targets
+are endpoints that receive prompts that are processed by Arch. For example, Arch enriches incoming prompts with
+metadata like knowing when a user's intent has changed so that you can build faster, more accurate RAG apps.
+
+Configuring ``prompt_targets`` is simple. See example below:
+
+.. literalinclude:: /_config/getting-started.yml
+    :language: yaml
+    :linenos:
+    :emphasize-lines: 29-38
+    :caption: :download:`arch-getting-started.yml </_config/getting-started.yml>`
+
+
+Intent Detection and Prompt Matching:
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Arch uses fast Natural Language Inference (NLI) and embedding approaches to first detect the intent of each
+incoming prompt. This intent detection phase analyzes the prompt's content and matches it against predefined
+prompt targets, ensuring that each prompt is forwarded to the most appropriate endpoint. Arch’s intent
+detection framework considers both the name and description of each prompt target, and uses a composite matching
+score between an NLI and cosine similarity to enchance accuracy in forwarding decisions.
+
+- **Embeddings**: By embedding the prompt and comparing it to known target vectors, Arch effectively identifies
+  the closest match, ensuring that the prompt is handled by the correct downstream service.
+
+- **NLI**: NLI techniques further refine the matching process by evaluating the semantic alignment between the
+  prompt and potential targets.
+
+Agentic Apps via Prompt Targets
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+To support agentic apps, like scheduling travel plans or sharing comments on a document - via prompts, Arch uses
+its function calling abilities to extract critical information from the incoming prompt (or a set of prompts)
+needed by a downstream backend API or function call before calling it directly. For more details on how you can
+build agentic applications using Arch, see our full guide :ref:`here <arch_function_calling_agentic_guide>`:
+
+.. Note::
+   Arch :ref:`Arch-FC <llms_in_arch>` is the dedicated agentic model engineered in Arch to extract information from
+   a (set of) prompts and executes necessary backend API calls. This allows for efficient handling of agentic tasks,
+   such as scheduling data retrieval, by dynamically interacting with backend services. Arch-FC is a flagship 1.3
+   billion parameter model that matches performance  with frontier models like Claude Sonnet 3.5 ang GPT-4, while
+   being 100x cheaper ($0.05M/token hosted) and 10x faster (p50 latencies of 200ms).
+
+Prompting LLMs
+--------------
+Arch is a single piece of software that is designed to manage both ingress and egress prompt traffic, drawing its
+distributed proxy nature from the robust `Envoy <https://envoyproxy.io>`_. This makes it extremely efficient and capable
+of handling upstream connections to LLMs. If your application is originating code to an API-based LLM, simply use
+Arch's Python or JavaScript client SDK to send traffic to the desired LLM of choice. By sending traffic through Arch,
+you can propagate traces, manage and monitor traffic, apply rate limits, and utilize a large set of traffic management
+capabilities in a central place.
+
+.. Attention::
+   When you start Arch, it automatically creates a listener port for egress calls to upstream LLMs. This is based on the
+   ``llm_providers`` configuration section in the ``prompt_config.yml`` file. Arch binds itself to a local address such as
+   127.0.0.1:9000/v1  or a DNS-based address like arch.local:9000/v1 for outgoing traffic.
+
+Example: Using the Arch Python SDK
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. code-block:: python
+
+   from arch_client import ArchClient
+
+   # Initialize the Arch client
+   client = ArchClient(base_url="http://127.0.0.1:9000/v1")
+
+   # Define your LLM provider and prompt
+   model_id = "openai"
+   prompt = "What is the capital of France?"
+
+   # Send the prompt to the LLM through Arch
+   response = client.completions.create(llm_provider=llm_provider, prompt=prompt)
+
+   # Print the response
+   print("LLM Response:", response)
+
+Example: Using OpenAI Client with Arch as an Egress Gateway
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. code-block:: python
+
+   import openai
+
+   # Set the OpenAI API base URL to the Arch gateway endpoint
+   openai.api_base = "http://127.0.0.1:9000/v1"
+
+   # No need to set openai.api_key since it's configured in Arch's gateway
+
+   # Use the OpenAI client as usual
+   response = openai.Completion.create(
+      model="text-davinci-003",
+      prompt="What is the capital of France?"
+   )
+
+   print("OpenAI Response:", response.choices[0].text.strip())
+
+In these examples:
+
+    The ArchClient is used to send traffic directly through the Arch egress proxy to the LLM of your choice, such as OpenAI.
+    The OpenAI client is configured to route traffic via Arch by setting the proxy to 127.0.0.1:9000, assuming Arch is
+    running locally and bound to that address and port.
+
+This setup allows you to take advantage of Arch's advanced traffic management features while interacting with LLM APIs like OpenAI.

_sources/intro/getting_help.rst

@@ -0,0 +1,15 @@
+.. _getting_help:
+
+Getting help
+============
+
+We are very interested in building a community around Arch. Please reach out to us if you are
+interested in using it and need help or want to contribute.
+
+Please see `contact info <https://github.com/katanemo/arch#contact>`_.
+
+Reporting security vulnerabilities
+----------------------------------
+
+Please see `security contact info
+<https://github.com/katanemo/arch#reporting-security-vulnerabilities>`_.

_sources/intro/intro.rst

@@ -0,0 +1,12 @@
+.. _intro:
+
+Introduction
+============
+
+.. toctree::
+  :maxdepth: 2
+
+  what_is_arch
+  architecture/architecture
+  life_of_a_request
+  getting_help

_sources/intro/life_of_a_request.rst

@@ -0,0 +1,176 @@
+.. _life_of_a_request:
+
+Life of a Request
+=================
+
+Below we describe the events in the life of a request passing through an Arch gateway instance. We first
+describe how Arch fits into the request path and then the internal events that take place following
+the arrival of a request at Arch from downtream clients. We follow the request until the corresponding
+dispatch upstream and the response path.
+
+.. image:: /_static/img/network-topology-ingress-egress.jpg
+   :width: 100%
+   :align: center
+
+Terminology
+-----------
+
+We recommend that you get familiar with some of the :ref:`terminology <arch_terminology>` used in Arch
+before reading this section.
+
+Network topology
+----------------
+
+How a request flows through the components in a network (including Arch) depends on the network’s topology.
+Arch can be used in a wide variety of networking topologies. We focus on the inner operation of Arch below,
+but briefly we address how Arch relates to the rest of the network in this section.
+
+- **Downstream(Ingress)** listeners take requests from upstream clients like a web UI or clients that forward
+  prompts to you local application responses from the application flow back through Arch to the downstream.
+
+- **Upstream(Egress)** listeners take requests from the application and forward them to LLMs.
+
+.. image:: /_static/img/network-topology-ingress-egress.jpg
+   :width: 100%
+   :align: center
+
+In practice, Arch can be deployed on the edge and as an internal load balancer between AI agents. A request path may
+traverse multiple Arch gateways:
+
+.. image:: /_static/img/network-topology-agent.jpg
+   :width: 100%
+   :align: center
+
+
+High level architecture
+-----------------------
+Arch is a set of **two** self-contained processes that are designed to run alongside your application servers
+(or on a separate server connected to your application servers via a network). The first process is designated
+to manage HTTP-level networking and connection management concerns (protocol management, request id generation,
+header sanitization, etc.), and the other process is for **model serving**, which helps Arch make intelligent
+decisions about the incoming prompts. The model server hosts the purpose-built :ref:`LLMs <llms_in_arch>` to
+manage several critical, but undifferentiated, prompt related tasks on behalf of developers.
+
+
+The request processing path in Arch has three main parts:
+
+* :ref:`Listener subsystem <arch_overview_listeners>` which handles **downstream** and **upstream** request
+  processing. It is responsible for managing the downstream (ingress) and the upstream (egress) request
+  lifecycle. The downstream and upstream HTTP/2 codec lives here.
+* :ref:`Prompt handler subsystem <arch_overview_prompt_handling>` which is responsible for selecting and
+  forwarding prompts ``prompt_targets`` and establishes the lifecycle of any **upstream** connection to a
+  hosted endpoint that implements domain-specific business logic for incoming promots. This is where knowledge
+  of targets and endpoint health, load balancing and connection pooling exists.
+* :ref:`Model serving subsystem <arch_model_serving>` which helps Arch make intelligent decisions about the
+  incoming prompts. The model server is designed to call the purpose-built :ref:`LLMs <llms_in_arch>` in Arch.
+
+The three subsystems are bridged with either the HTTP router filter, and the cluster manager subsystems of Envoy.
+
+Also, Arch utilizes `Envoy event-based thread model <https://blog.envoyproxy.io/envoy-threading-model-a8d44b922310>`_.
+A main thread is responsible forthe server lifecycle, configuration processing, stats, etc. and some number of
+:ref:`worker threads <arch_overview_threading>` process requests. All threads operate around an event loop (`libevent <https://libevent.org/>`_)
+and any given downstream TCP connection will be handled by exactly one worker thread for its lifetime. Each worker
+thread maintains its own pool of TCP connections to upstream endpoints.
+
+Worker threads rarely share state and operate in a trivially parallel fashion. This threading model
+enables scaling to very high core count CPUs.
+
+Configuration
+-------------
+
+Today, only support a static bootstrap configuration file for simplicity today:
+
+.. literalinclude:: /_config/getting-started.yml
+    :language: yaml
+
+
+Request Flow (Ingress)
+----------------------
+
+Overview
+^^^^^^^^
+A brief outline of the life cycle of a request and response using the example configuration above:
+
+1. **TCP Connection Establishment**:
+   A TCP connection from downstream is accepted by an Arch listener running on a worker thread.
+   The listener filter chain provides SNI and other pre-TLS information. The transport socket, typically TLS,
+   decrypts incoming data for processing.
+
+2. **Prompt Guardrails Check**:
+   Arch first checks the incoming prompts for guardrails such as jailbreak attempts. This ensures
+   that harmful or unwanted behaviors are detected early in the request processing pipeline.
+
+3. **Intent Matching**:
+   The decrypted data stream is deframed by the HTTP/2 codec in Arch's HTTP connection manager. Arch performs
+   intent matching via is **prompt-handler** subsystem using the name and description of the defined prompt targets,
+   determining which endpoint should handle the prompt.
+
+4. **Parameter Gathering with Arch-FC**:
+   If a prompt target requires specific parameters, Arch engages Arch-FC to extract the necessary details
+   from the incoming prompt(s). This process gathers the critical information needed for downstream API calls.
+
+5. **API Call Execution**:
+   Arch routes the prompt to the appropriate backend API or function call. If an endpoint cluster is identified,
+   load balancing is performed, circuit breakers are checked, and the request is proxied to the upstream endpoint.
+
+6. **Default Summarization by Upstream LLM**:
+   By default, if no specific endpoint processing is needed, the prompt is sent to an upstream LLM for summarization.
+   This ensures that responses are concise and relevant, enhancing user experience in RAG (Retrieval-Augmented Generation)
+   and agentic applications.
+
+7. **Error Handling and Forwarding**:
+   Errors encountered during processing, such as failed function calls or guardrail detections, are forwarded to
+   designated error targets. Error details are communicated through specific headers to the application:
+
+   - ``X-Function-Error-Code``: Code indicating the type of function call error.
+   - ``X-Prompt-Guard-Error-Code``: Code specifying violations detected by prompt guardrails.
+   - Additional headers carry messages and timestamps to aid in debugging and logging.
+
+8. **Response Handling**:
+   The upstream endpoint’s TLS transport socket encrypts the response, which is then proxied back downstream.
+   Responses pass through HTTP filters in reverse order, ensuring any necessary processing or modification before final delivery.
+
+
+Request Flow (Egress)
+---------------------
+
+Overview
+--------
+
+A brief outline of the life cycle of a request and response in the context of egress traffic from an application
+to Large Language Models (LLMs) via Arch:
+
+1. **HTTP Connection Establishment to LLM**:
+   Arch initiates an HTTP connection to the upstream LLM service. This connection is handled by Arch’s egress listener
+   running on a worker thread. The connection typically uses a secure transport protocol such as HTTPS, ensuring the
+   prompt data is encrypted before being sent to the LLM service.
+
+2. **Rate Limiting**:
+   Before sending the request to the LLM, Arch applies rate-limiting policies to ensure that the upstream LLM service
+   is not overwhelmed by excessive traffic. Rate limits are enforced per client or service, ensuring fair usage and
+   preventing accidental or malicious overload. If the rate limit is exceeded, Arch may return an appropriate HTTP
+   error (e.g., 429 Too Many Requests) without sending the prompt to the LLM.
+
+3. **Load Balancing to (hosted) LLM Endpoints**:
+   After passing the rate-limiting checks, Arch routes the prompt to the appropriate LLM endpoint.
+   If multiple LLM providers instances are available, load balancing is performed to distribute traffic evenly
+   across the instances. Arch checks the health of the LLM endpoints using circuit breakers and health checks,
+   ensuring that the prompt is only routed to a healthy, responsive instance.
+
+4. **Response Reception and Forwarding**:
+   Once the LLM processes the prompt, Arch receives the response from the LLM service. The response is typically a
+   generated text, completion, or summarization. Upon reception, Arch decrypts (if necessary) and handles the response,
+   passing it through any egress processing pipeline defined by the application, such as logging or additional response filtering.
+
+
+Post-request processing
+^^^^^^^^^^^^^^^^^^^^^^^^
+Once a request completes, the stream is destroyed. The following also takes places:
+
+* The post-request :ref:`monitoring <monitoring>` are updated (e.g. timing, active requests, upgrades, health checks).
+  Some statistics are updated earlier however, during request processing. Stats are batchedand written by the main
+  thread periodically.
+* :ref:`Access logs <arch_access_logging>` are written to the access log
+* :ref:`Trace <arch_overview_tracing>` spans are finalized. If our example request was traced, a
+  trace span, describing the duration and details of the request would be created by the HCM when
+  processing request headers and then finalized by the HCM during post-request processing.

_sources/intro/what_is_arch.rst

@@ -0,0 +1,90 @@
+What is Arch
+============
+
+Arch is an intelligent `(Layer 7) <https://www.cloudflare.com/learning/ddos/what-is-layer-7/>`_ gateway
+designed for generative AI apps, AI agents, and Co-pilots that work with prompts. Engineered with purpose-built
+:ref:`LLMs <llms_in_arch>`, Arch handles all the critical but undifferentiated tasks related to the handling and
+processing of prompts, including detecting and rejecting `jailbreak <https://github.com/verazuo/jailbreak_llms>`_
+attempts, intelligently calling “backend” APIs to fulfill the user's request represented in a prompt, routing to
+and offering disaster recovery between upstream LLMs, and managing the observability of prompts and LLM interactions
+in a centralized way.
+
+.. image:: /_static/img/arch-logo.png
+   :width: 100%
+   :align: center
+
+**The project was born out of the belief that:**
+
+  *Prompts are nuanced and opaque user requests, which require the same capabilities as traditional HTTP requests
+  including secure handling, intelligent routing, robust observability, and integration with backend (API)
+  systems for personalization - all outside business logic.*
+
+
+In practice, achieving the above goal is incredibly difficult. Arch attempts to do so by providing the
+following high level features:
+
+_____________________________________________________________________________________________________________
+
+**Out-of-process architecture, built on** `Envoy <http://envoyproxy.io/>`_: Arch is takes a dependency on
+Envoy and is a self-contained process that is designed to run alongside your application servers. Arch uses
+Envoy's HTTP connection management subsystem, HTTP L7 filtering and telemetry capabilities to extend the
+functionality exclusively for prompts and LLMs. This gives Arch several advantages:
+
+* Arch builds on Envoy's proven success. Envoy is used at masssive sacle by the leading technology companies of
+  our time including `AirBnB <https://www.airbnb.com>`_, `Dropbox <https://www.dropbox.com>`_,
+  `Google <https://www.google.com>`_, `Reddit <https://www.reddit.com>`_, `Stripe <https://www.stripe.com>`_,
+  etc. Its battle tested and scales linearly with usage and enables developers to focus on what really matters:
+  application features and business logic.
+
+* Arch works with any application language. A single Arch deployment can act as gateway for AI applications
+  written in Python, Java, C++, Go, Php, etc.
+
+* Arch can be deployed and upgraded quickly across your infrastructure transparently without the horrid pain
+  of deploying library upgrades in your applications.
+
+**Engineered with Fast LLMs:** Arch is engineered with specialized (sub-billion) LLMs that are desgined for
+fast, cost-effective and acurrate handling of prompts. These :ref:`LLMs <llms_in_arch>` are designed to be
+best-in-class for critcal prompt-related tasks like:
+
+* **Function/API Calling:** Arch helps you easily personalize your applications by enabling calls to
+  application-specific (API) operations via user prompts. This involves any predefined functions or APIs
+  you want to expose to users to perform tasks, gather information, or manipulate data. With function calling,
+  you have flexibility to support "agentic" experiences tailored to specific use cases - from updating insurance
+  claims to creating ad campaigns - via prompts. Arch analyzes prompts, extracts critical information from
+  prompts, engages in lightweight conversation to gather any missing parameters and makes API calls so that you can
+  focus on writing business logic. For more details, read :ref:`prompt processing <arch_overview_prompt_handling>`.
+
+* **Prompt Guardrails:** Arch helps you improve the safety of your application by applying prompt guardrails in
+  a centralized way for better governance hygiene. With prompt guardrails you can prevent `jailbreak <https://github.com/verazuo/jailbreak_llms>`_
+  attempts or toxicity present in user's prompts without having to write a single line of code. To learn more
+  about how to configure guardrails available in Arch, read :ref:`prompt processing <arch_overview_prompt_handling>`.
+
+* **Intent-Drift Detection:** Developers struggle to handle `follow-up <https://www.reddit.com/r/ChatGPTPromptGenius/comments/17dzmpy/how_to_use_rag_with_conversation_history_for/?>`_,
+  or `clarifying <https://www.reddit.com/r/LocalLLaMA/comments/18mqwg6/best_practice_for_rag_with_followup_chat/>`_
+  questions. Specifically, when users ask for modifications or additions to previous responses their AI applications
+  often generate entirely new responses instead of adjusting the previous ones. Arch offers intent-drift detection as a
+  feature so that developers know when the user has shifted away from the previous intent so that they can improve
+  their retrieval, lower overall token cost and dramatically improve the speed and accuracy of their responses back
+  to users.
+
+**Traffic Management:** Arch offers several capabilities for LLM calls originating from your applications, including a
+vendor-agnostic SDK to make LLM calls, smart retries on errors from upstream LLMs, and automatic cutover to other LLMs
+configured in Arch for continuous availability and disaster recovery scenarios. Arch extends Envoy's `cluster subsystem
+<https://www.envoyproxy.io/docs/envoy/latest/intro/arch_overview/upstream/cluster_manager>`_ to manage upstream connections
+to LLMs so that you can build resilient AI applications.
+
+**Front/edge Gateway:** There is substantial benefit in using the same software at the edge (observability,
+traffic shaping alogirithms, applying guardrails, etc.) as for outbound LLM inference use cases. Arch has the feature set
+that makes it exceptionally well suited as an edge gateway for AI applications. This includes TLS termination, rate limiting,
+and prompt-based routing.
+
+**Best-In Class Monitoring:** Arch offers several monitoring metrics that help you understand three
+critical aspects of your application: latency, token usage, and error rates by an upstream LLM provider. Latency
+measures the speed at which your application is responding to users, which includes metrics like time to first
+token (TFT), time per output token (TOT) metrics, and the total latency as perceived by users.
+
+**End-to-End Tracing:** Arch propagates trace context using the W3C Trace Context standard, specifically through
+the ``traceparent`` header. This allows each component in the system to record its part of the request flow,
+enabling **end-to-end tracing** across the entire application. By using OpenTelemetry, Arch ensures that
+developers can capture this trace data consistently and in a format compatible with various observability tools.
+For more details, read :ref:`tracing <arch_overview_tracing>`.

_sources/llms/llms.rst

@@ -0,0 +1,159 @@
+.. _llms_in_arch:
+
+LLMs
+====
+
+Arch utilizes purpose-built, industry leading, LLMs to handle the crufty and undifferentiated work around
+accepting, handling and processing prompts. The following sections talk about some of the core models that
+are built-in Arch.
+
+Arch-Guard-v1
+-------------
+LLM-powered applications are susceptible to prompt attacks, which are prompts intentionally designed to
+subvert the developer’s intended behavior of the LLM. Arch-Guard-v1 is a classifier model trained on a large
+corpus of attacks, capable of detecting explicitly malicious prompts (and toxicity).
+
+The model is useful as a starting point for identifying and guardrailing against the most risky realistic
+inputs to LLM-powered applications. Our goal in embedding Arch-Guard in the Arch gateway is to enable developers
+to focus on their business logic and factor out security and safety outside application logic. Wth Arch-Guard-v1
+developers can take to significantly reduce prompt attack risk while maintaining control over the user experience.
+
+Below is our test results of the strength of our model as compared to Prompt-Guard from `Meta LLama <https://huggingface.co/meta-llama/Prompt-Guard-86M>`_.
+
+.. list-table::
+   :header-rows: 1
+   :widths: 15 15 10 15 15
+
+   * - Dataset
+     - Jailbreak (Yes/No)
+     - Samples
+     - Prompt-Guard Accuracy
+     - Arch-Guard Accuracy
+   * - casual_conversation
+     - 0
+     - 3725
+     - 1.00
+     - 1.00
+   * - commonqa
+     - 0
+     - 9741
+     - 1.00
+     - 1.00
+   * - financeqa
+     - 0
+     - 1585
+     - 1.00
+     - 1.00
+   * - instruction
+     - 0
+     - 5000
+     - 1.00
+     - 1.00
+   * - jailbreak_behavior_benign
+     - 0
+     - 100
+     - 0.10
+     - 0.20
+   * - jailbreak_behavior_harmful
+     - 1
+     - 100
+     - 0.30
+     - 0.52
+   * - jailbreak_judge
+     - 1
+     - 300
+     - 0.33
+     - 0.49
+   * - jailbreak_prompts
+     - 1
+     - 79
+     - 0.99
+     - 1.00
+   * - jailbreak_tweet
+     - 1
+     - 1282
+     - 0.16
+     - 0.35
+   * - jailbreak_v
+     - 1
+     - 20000
+     - 0.90
+     - 0.93
+   * - jailbreak_vigil
+     - 1
+     - 104
+     - 1.00
+     - 1.00
+   * - mental_health
+     - 0
+     - 3512
+     - 1.00
+     - 1.00
+   * - telecom
+     - 0
+     - 4000
+     - 1.00
+     - 1.00
+   * - truthqa
+     - 0
+     - 817
+     - 1.00
+     - 0.98
+   * - weather
+     - 0
+     - 3121
+     - 1.00
+     - 1.00
+
+.. list-table::
+   :header-rows: 1
+   :widths: 15 20
+
+   * - Statistics
+     - Overall performance
+   * - Overall Accuracy
+     - 0.93568 (Prompt-Guard), 0.95267 (Arch-Guard)
+   * - True positives rate (TPR)
+     - 0.8468 (Prompt-Guard), 0.8887 (Arch-Guard)
+   * - True negative rate (TNR)
+     - 0.9972 (Prompt-Guard), 0.9970 (Arch-Guard)
+   * - False positive rate (FPR)
+     - 0.0028 (Prompt-Guard), 0.0030 (Arch-Guard)
+   * - False negative rate (FNR)
+     - 0.1532 (Prompt-Guard), 0.1113 (Arch-Guard)
+
+.. list-table::
+   :header-rows: 1
+   :widths: 15 20
+
+   * - Metrics
+     - Values
+   * - AUC
+     - 0.857 (Prompt-Guard), 0.880 (Arch-Guard)
+   * - Precision
+     - 0.715 (Prompt-Guard), 0.761 (Arch-Guard)
+   * - Recall
+     - 0.999 (Prompt-Guard), 0.999 (Arch-Guard)
+
+
+
+Arch-FC
+-------
+Arch-FC is a lean, powerful and cost-effective agentic model designed for function calling scenarios.
+You can run Arch-FC locally, or use the cloud-hosted version for as little as $0.05/M token (100x cheaper
+than GPT-4o), with a p50 latency of 200ms (5x faster than GPT-4o), while meeting frontier model performance.
+
+.. Note::
+  Function calling helps you personalize the GenAI experience by calling application-specific operations via
+  prompts. This involves any predefined functions or APIs you want to expose to perform tasks, gather
+  information, or manipulate data - via prompts.
+
+  You can get started with function calling simply by configuring a prompt target with a name, description
+  and set of parameters needed by a specific backend function or a hosted API. The name, and description helps
+  Arch-FC match a user prompt to a function or API that can process it.
+
+By using Arch-FC, Arch enables you to easily build agentic workflows tailored to domain-specific use cases -
+from updating insurance claims to creating ad campaigns. Arch-FC analyzes prompts, extracts critical information
+from prompts, engages in lightweight conversations with the user to gather any missing parameters need before
+handling control back to Arch to make the API call to your hosted backend. Arch-FC handles the muck of information
+extraction so that you can focus on the business logic of your application.

_sources/observability/access_logs.rst

@@ -0,0 +1,23 @@
+.. _arch_access_logging:
+
+Access Logging
+==============
+
+Access logging in Arch refers to the logging of detailed information about each request and response that flows through Arch.
+It provides visibility into the traffic passing through Arch, which is crucial for monitoring, debugging, and analyzing the
+behavior of AI applications and their interactions.
+
+Key Features of Access Logging in Arch:
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+* **Per-Request Logging**:
+  Each request that passes through Arch is logged. This includes important metadata such as HTTP method,
+  path, response status code, request duration, upstream host, and more.
+* **Integration with Monitoring Tools**:
+  Access logs can be exported to centralized logging systems (e.g., ELK stack or Fluentd) or used to feed monitoring and alerting systems.
+* **Structured Logging**: where each request is logged as a object, making it easier to parse and analyze using tools like Elasticsearch and Kibana.
+
+.. code-block:: yaml
+
+    [2024-09-27T14:52:01.123Z] "ARCH REQUEST" GET /path/to/resource HTTP/1.1 200 512 1024 56 upstream_service.com D
+    X-Arch-Upstream-Service-Time: 25
+    X-Arch-Attempt-Count: 1

_sources/observability/observability.rst

@@ -0,0 +1,11 @@
+.. _observability:
+
+Observability
+=============
+
+.. toctree::
+  :maxdepth: 2
+
+  tracing
+  stats
+  access_logs

_sources/observability/stats.rst

@@ -0,0 +1,9 @@
+.. _monitoring:
+
+Monitoring
+==========
+
+Arch offers several monitoring metrics that help you understand three critical aspects of your application:
+latency, token usage, and error rates by an upstream LLM provider. Latency measures the speed at which your
+application is responding to users, which includes metrics like time to first token (TFT), time per output
+token (TOT) metrics, and the total latency as perceived by users.

_sources/observability/tracing.rst

@@ -0,0 +1,313 @@
+.. _arch_overview_tracing:
+
+Tracing
+=======
+
+Overview
+--------
+
+`OpenTelemetry <https://opentelemetry.io/>`_ is an open-source observability framework providing APIs
+and instrumentation for generating, collecting, processing, and exporting telemetry data, such as traces,
+metrics, and logs. Its flexible design supports a wide range of backends and seamlessly integrates with
+modern application tools. A key feature of OpenTelemetry is its commitment to standards like the
+`W3C Trace Context <https://www.w3.org/TR/trace-context/>`_
+
+**Tracing** is a critical tool that allows developers to visualize and understand the flow of
+requests in an AI application. With tracing, you can capture a detailed view of how requests propagate
+through various services and components, which is crucial for **debugging**, **performance optimization**,
+and understanding complex AI agent architectures like Co-pilots.
+
+**Arch** propagates trace context using the W3C Trace Context standard, specifically through the
+``traceparent`` header. This allows each component in the system to record its part of the request
+flow, enabling **end-to-end tracing** across the entire application. By using OpenTelemetry, Arch ensures
+that developers can capture this trace data consistently and in a format compatible with various observability
+tools.
+______________________________________________________________________________________________
+
+Benefits of using ``traceparent`` headers
+-----------------------------------------
+
+- **Standardization**: The W3C Trace Context standard ensures compatibility across ecosystem tools, allowing
+  traces to be propagated uniformly through different layers of the system.
+- **Ease of Integration**: OpenTelemetry's design allows developers to easily integrate tracing with minimal
+  changes to their codebase, enabling quick adoption of end-to-end observability.
+- **Interoperability**: Works seamlessly with popular tracing tools like AWS X-Ray, Datadog, Jaeger, and many others,
+  making it easy to visualize traces in the tools you're already usi
+
+How to initiate a trace
+-----------------------
+
+1. **Enable Tracing Configuration**: Simply add the ``tracing: 100`` flag to in the :ref:`listener <arch_overview_listeners>` config
+
+2. **Trace Context Propagation**: Arch automatically propagates the ``traceparent`` header. When a request is received, Arch will:
+
+   - Generate a new ``traceparent`` header if one is not present.
+   - Extract the trace context from the ``traceparent`` header if it exists.
+   - Start a new span representing its processing of the request.
+   - Forward the ``traceparent`` header to downstream services.
+
+3. **Sampling Policy**: The 100 in ``tracing: 100`` means that all the requests as sampled for tracing.
+   You can adjust this value from 0-100.
+
+
+Trace Propagation
+-----------------
+
+Arch uses the W3C Trace Context standard for trace propagation, which relies on the ``traceparent`` header.
+This header carries tracing information in a standardized format, enabling interoperability between different
+tracing systems.
+
+Header Format
+~~~~~~~~~~~~~
+
+The ``traceparent`` header has the following format::
+
+   traceparent: {version}-{trace-id}-{parent-id}-{trace-flags}
+
+- {version}: The version of the Trace Context specification (e.g., ``00``).
+- {trace-id}: A 16-byte (32-character hexadecimal) unique identifier for the trace.
+- {parent-id}: An 8-byte (16-character hexadecimal) identifier for the parent span.
+- {trace-flags}: Flags indicating trace options (e.g., sampling).
+
+Instrumentation
+~~~~~~~~~~~~~~~
+
+To integrate AI tracing, your application needs to follow a few simple steps. The steps
+below are very common practice, and not unique to Arch, when you reading tracing headers and export
+`spans <https://docs.lightstep.com/docs/understand-distributed-tracing>`_ for distributed tracing.
+
+- Read the ``traceparent`` header from incoming requests.
+- Start new spans as children of the extracted context.
+- Include the ``traceparent`` header in outbound requests to propagate trace context.
+- Send tracing data to a collector or tracing backend to export spans
+
+Example with OpenTelemetry in Python
+************************************
+
+Install OpenTelemetry packages:
+
+.. code-block:: bash
+
+   pip install opentelemetry-api opentelemetry-sdk opentelemetry-exporter-otlp
+   pip install opentelemetry-instrumentation-requests
+
+Set up the tracer and exporter:
+
+.. code-block:: python
+
+   from opentelemetry import trace
+   from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
+   from opentelemetry.instrumentation.requests import RequestsInstrumentor
+   from opentelemetry.sdk.resources import Resource
+   from opentelemetry.sdk.trace import TracerProvider
+   from opentelemetry.sdk.trace.export import BatchSpanProcessor
+
+   # Define the service name
+   resource = Resource(attributes={
+       "service.name": "customer-support-agent"
+   })
+
+   # Set up the tracer provider and exporter
+   tracer_provider = TracerProvider(resource=resource)
+   otlp_exporter = OTLPSpanExporter(endpoint="otel-collector:4317", insecure=True)
+   span_processor = BatchSpanProcessor(otlp_exporter)
+   tracer_provider.add_span_processor(span_processor)
+   trace.set_tracer_provider(tracer_provider)
+
+   # Instrument HTTP requests
+   RequestsInstrumentor().instrument()
+
+Handle incoming requests:
+
+.. code-block:: python
+
+   from opentelemetry import trace
+   from opentelemetry.propagate import extract, inject
+   import requests
+
+   def handle_request(request):
+       # Extract the trace context
+       context = extract(request.headers)
+       tracer = trace.get_tracer(__name__)
+
+       with tracer.start_as_current_span("process_customer_request", context=context):
+           # Example of processing a customer request
+           print("Processing customer request...")
+
+           # Prepare headers for outgoing request to payment service
+           headers = {}
+           inject(headers)
+
+           # Make outgoing request to external service (e.g., payment gateway)
+           response = requests.get("http://payment-service/api", headers=headers)
+
+           print(f"Payment service response: {response.content}")
+
+
+AI Agent Tracing Visualization Example
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+The following is an example of tracing for an AI-powered customer support system.
+A customer interacts with AI agents, which forward their requests through different
+specialized services and external systems.
+
+::
+
+    +--------------------------+
+    |   Customer Interaction   |
+    +--------------------------+
+               |
+               v
+    +--------------------------+        +--------------------------+
+    |  Agent 1 (Main - Arch)   | ---->  | External Payment Service |
+    +--------------------------+        +--------------------------+
+               |                                  |
+               v                                  v
+    +--------------------------+        +--------------------------+
+    |  Agent 2 (Support - Arch)| ---->  |   Internal Tech Support  |
+    +--------------------------+        +--------------------------+
+               |                                  |
+               v                                  v
+    +--------------------------+        +--------------------------+
+    | Agent 3 (Orders- Arch)   | ---->  |   Inventory Management   |
+    +--------------------------+        +--------------------------+
+
+Trace Breakdown:
+****************
+
+- Customer Interaction:
+    - Span 1: Customer initiates a request via the AI-powered chatbot for billing support (e.g., asking for payment details).
+
+- AI Agent 1 (Main - Arch):
+    - Span 2: AI Agent 1 (Main) processes the request and identifies it as related to billing, forwarding the request
+      to an external payment service.
+    - Span 3: AI Agent 1 determines that additional technical support is needed for processing and forwards the request
+      to AI Agent 2.
+
+- External Payment Service:
+    - Span 4: The external payment service processes the payment-related request (e.g., verifying payment status) and sends
+      the response back to AI Agent 1.
+
+- AI Agent 2 (Tech - Arch):
+    - Span 5: AI Agent 2, responsible for technical queries, processes a request forwarded from AI Agent 1 (e.g., checking for
+      any account issues).
+    - Span 6: AI Agent 2 forwards the query to Internal Tech Support for further investigation.
+
+- Internal Tech Support:
+    - Span 7: Internal Tech Support processes the request (e.g., resolving account access issues) and responds to AI Agent 2.
+
+- AI Agent 3 (Orders - Arch):
+    - Span 8: AI Agent 3 handles order-related queries. AI Agent 1 forwards the request to AI Agent 3 after payment verification
+      is completed.
+    - Span 9: AI Agent 3 forwards a request to the Inventory Management system to confirm product availability for a pending order.
+
+- Inventory Management:
+    - Span 10: The Inventory Management system checks stock and availability and returns the information to AI Agent 3.
+
+Integrating with Tracing Tools
+------------------------------
+
+AWS X-Ray
+~~~~~~~~~
+
+To send tracing data to `AWS X-Ray <https://aws.amazon.com/xray/>`_ :
+
+1. **Configure OpenTelemetry Collector**: Set up the collector to export traces to AWS X-Ray.
+
+   Collector configuration (``otel-collector-config.yaml``):
+
+   .. code-block:: yaml
+
+      receivers:
+        otlp:
+          protocols:
+            grpc:
+
+      processors:
+        batch:
+
+      exporters:
+        awsxray:
+          region: your-aws-region
+
+      service:
+        pipelines:
+          traces:
+            receivers: [otlp]
+            processors: [batch]
+            exporters: [awsxray]
+
+2. **Deploy the Collector**: Run the collector as a Docker container, Kubernetes pod, or standalone service.
+3. **Ensure AWS Credentials**: Provide AWS credentials to the collector, preferably via IAM roles.
+4. **Verify Traces**: Access the AWS X-Ray console to view your traces.
+
+Datadog
+~~~~~~~
+
+Datadog
+
+To send tracing data to `Datadog <https://docs.datadoghq.com/getting_started/tracing/>`_:
+
+1. **Configure OpenTelemetry Collector**: Set up the collector to export traces to Datadog.
+
+   Collector configuration (``otel-collector-config.yaml``):
+
+   .. code-block:: yaml
+
+      receivers:
+        otlp:
+          protocols:
+            grpc:
+
+      processors:
+        batch:
+
+      exporters:
+        datadog:
+          api:
+            key: "${DD_API_KEY}"
+          site: "${DD_SITE}"
+
+      service:
+        pipelines:
+          traces:
+            receivers: [otlp]
+            processors: [batch]
+            exporters: [datadog]
+
+2. **Set Environment Variables**: Provide your Datadog API key and site.
+
+   .. code-block:: bash
+
+      export DD_API_KEY=your_datadog_api_key
+      export DD_SITE=datadoghq.com  # Or datadoghq.eu
+
+3. **Deploy the Collector**: Run the collector in your environment.
+4. **Verify Traces**: Access the Datadog APM dashboard to view your traces.
+
+
+Best Practices
+--------------
+
+- **Consistent Instrumentation**: Ensure all services propagate the ``traceparent`` header.
+- **Secure Configuration**: Protect sensitive data and secure communication between services.
+- **Performance Monitoring**: Be mindful of the performance impact and adjust sampling rates accordingly.
+- **Error Handling**: Implement proper error handling to prevent tracing issues from affecting your application.
+
+Conclusion
+----------
+
+By leveraging the ``traceparent`` header for trace context propagation, Arch enables developers to implement
+tracing efficiently. This approach simplifies the process of collecting and analyzing tracing data in common
+tools like AWS X-Ray and Datadog, enhancing observability and facilitating faster debugging and optimization.
+
+Additional Resources
+--------------------
+
+- **OpenTelemetry Documentation**: https://opentelemetry.io/docs/
+- **W3C Trace Context Specification**: https://www.w3.org/TR/trace-context/
+- **AWS X-Ray Exporter**: https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/exporter/awsxrayexporter
+- **Datadog Exporter**: https://github.com/open-telemetry/opentelemetry-collector-contrib/tree/main/exporter/datadogexporter
+
+.. Note::
+   Replace placeholders like ``your-aws-region``, and ``DD_API_KEY`` with your actual configurations.

_sources/root.rst

@@ -0,0 +1,22 @@
+Documentation
+=============
+
+.. image:: /_static/img/arch-logo.png
+   :width: 100%
+   :align: center
+
+**Arch is built on (and by the core contributors of) Envoy proxy with the belief that:**
+
+  *Prompts are nuanced and opaque user requests, which require the same capabilities as traditional HTTP requests
+  including secure handling, intelligent routing, robust observability, and integration with backend (API)
+  systems for personalization - all outside business logic.*
+
+.. toctree::
+  :maxdepth: 1
+
+  intro/intro
+  getting_started/getting_started
+  getting_started/use_cases
+  observability/observability
+  llms/llms
+  configuration_reference

_static/basic.css

@@ -0,0 +1,925 @@
+/*
+ * basic.css
+ * ~~~~~~~~~
+ *
+ * Sphinx stylesheet -- basic theme.
+ *
+ * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+
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+
+div.clearer {
+    clear: both;
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+
+div.section::after {
+    display: block;
+    content: '';
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+
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+
+div.related li {
+    display: inline;
+}
+
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+    float: right;
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+/* -- sidebar --------------------------------------------------------------- */
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+div.sphinxsidebarwrapper {
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+    font-size: 1.3em;
+}
+
+span.linkdescr {
+    font-style: italic;
+    padding-top: 5px;
+    font-size: 90%;
+}
+
+/* -- general index --------------------------------------------------------- */
+
+table.indextable {
+    width: 100%;
+}
+
+table.indextable td {
+    text-align: left;
+    vertical-align: top;
+}
+
+table.indextable ul {
+    margin-top: 0;
+    margin-bottom: 0;
+    list-style-type: none;
+}
+
+table.indextable > tbody > tr > td > ul {
+    padding-left: 0em;
+}
+
+table.indextable tr.pcap {
+    height: 10px;
+}
+
+table.indextable tr.cap {
+    margin-top: 10px;
+    background-color: #f2f2f2;
+}
+
+img.toggler {
+    margin-right: 3px;
+    margin-top: 3px;
+    cursor: pointer;
+}
+
+div.modindex-jumpbox {
+    border-top: 1px solid #ddd;
+    border-bottom: 1px solid #ddd;
+    margin: 1em 0 1em 0;
+    padding: 0.4em;
+}
+
+div.genindex-jumpbox {
+    border-top: 1px solid #ddd;
+    border-bottom: 1px solid #ddd;
+    margin: 1em 0 1em 0;
+    padding: 0.4em;
+}
+
+/* -- domain module index --------------------------------------------------- */
+
+table.modindextable td {
+    padding: 2px;
+    border-collapse: collapse;
+}
+
+/* -- general body styles --------------------------------------------------- */
+
+div.body {
+    min-width: 360px;
+    max-width: 800px;
+}
+
+div.body p, div.body dd, div.body li, div.body blockquote {
+    -moz-hyphens: auto;
+    -ms-hyphens: auto;
+    -webkit-hyphens: auto;
+    hyphens: auto;
+}
+
+a.headerlink {
+    visibility: hidden;
+}
+
+a:visited {
+    color: #551A8B;
+}
+
+h1:hover > a.headerlink,
+h2:hover > a.headerlink,
+h3:hover > a.headerlink,
+h4:hover > a.headerlink,
+h5:hover > a.headerlink,
+h6:hover > a.headerlink,
+dt:hover > a.headerlink,
+caption:hover > a.headerlink,
+p.caption:hover > a.headerlink,
+div.code-block-caption:hover > a.headerlink {
+    visibility: visible;
+}
+
+div.body p.caption {
+    text-align: inherit;
+}
+
+div.body td {
+    text-align: left;
+}
+
+.first {
+    margin-top: 0 !important;
+}
+
+p.rubric {
+    margin-top: 30px;
+    font-weight: bold;
+}
+
+img.align-left, figure.align-left, .figure.align-left, object.align-left {
+    clear: left;
+    float: left;
+    margin-right: 1em;
+}
+
+img.align-right, figure.align-right, .figure.align-right, object.align-right {
+    clear: right;
+    float: right;
+    margin-left: 1em;
+}
+
+img.align-center, figure.align-center, .figure.align-center, object.align-center {
+  display: block;
+  margin-left: auto;
+  margin-right: auto;
+}
+
+img.align-default, figure.align-default, .figure.align-default {
+  display: block;
+  margin-left: auto;
+  margin-right: auto;
+}
+
+.align-left {
+    text-align: left;
+}
+
+.align-center {
+    text-align: center;
+}
+
+.align-default {
+    text-align: center;
+}
+
+.align-right {
+    text-align: right;
+}
+
+/* -- sidebars -------------------------------------------------------------- */
+
+div.sidebar,
+aside.sidebar {
+    margin: 0 0 0.5em 1em;
+    border: 1px solid #ddb;
+    padding: 7px;
+    background-color: #ffe;
+    width: 40%;
+    float: right;
+    clear: right;
+    overflow-x: auto;
+}
+
+p.sidebar-title {
+    font-weight: bold;
+}
+
+nav.contents,
+aside.topic,
+div.admonition, div.topic, blockquote {
+    clear: left;
+}
+
+/* -- topics ---------------------------------------------------------------- */
+
+nav.contents,
+aside.topic,
+div.topic {
+    border: 1px solid #ccc;
+    padding: 7px;
+    margin: 10px 0 10px 0;
+}
+
+p.topic-title {
+    font-size: 1.1em;
+    font-weight: bold;
+    margin-top: 10px;
+}
+
+/* -- admonitions ----------------------------------------------------------- */
+
+div.admonition {
+    margin-top: 10px;
+    margin-bottom: 10px;
+    padding: 7px;
+}
+
+div.admonition dt {
+    font-weight: bold;
+}
+
+p.admonition-title {
+    margin: 0px 10px 5px 0px;
+    font-weight: bold;
+}
+
+div.body p.centered {
+    text-align: center;
+    margin-top: 25px;
+}
+
+/* -- content of sidebars/topics/admonitions -------------------------------- */
+
+div.sidebar > :last-child,
+aside.sidebar > :last-child,
+nav.contents > :last-child,
+aside.topic > :last-child,
+div.topic > :last-child,
+div.admonition > :last-child {
+    margin-bottom: 0;
+}
+
+div.sidebar::after,
+aside.sidebar::after,
+nav.contents::after,
+aside.topic::after,
+div.topic::after,
+div.admonition::after,
+blockquote::after {
+    display: block;
+    content: '';
+    clear: both;
+}
+
+/* -- tables ---------------------------------------------------------------- */
+
+table.docutils {
+    margin-top: 10px;
+    margin-bottom: 10px;
+    border: 0;
+    border-collapse: collapse;
+}
+
+table.align-center {
+    margin-left: auto;
+    margin-right: auto;
+}
+
+table.align-default {
+    margin-left: auto;
+    margin-right: auto;
+}
+
+table caption span.caption-number {
+    font-style: italic;
+}
+
+table caption span.caption-text {
+}
+
+table.docutils td, table.docutils th {
+    padding: 1px 8px 1px 5px;
+    border-top: 0;
+    border-left: 0;
+    border-right: 0;
+    border-bottom: 1px solid #aaa;
+}
+
+th {
+    text-align: left;
+    padding-right: 5px;
+}
+
+table.citation {
+    border-left: solid 1px gray;
+    margin-left: 1px;
+}
+
+table.citation td {
+    border-bottom: none;
+}
+
+th > :first-child,
+td > :first-child {
+    margin-top: 0px;
+}
+
+th > :last-child,
+td > :last-child {
+    margin-bottom: 0px;
+}
+
+/* -- figures --------------------------------------------------------------- */
+
+div.figure, figure {
+    margin: 0.5em;
+    padding: 0.5em;
+}
+
+div.figure p.caption, figcaption {
+    padding: 0.3em;
+}
+
+div.figure p.caption span.caption-number,
+figcaption span.caption-number {
+    font-style: italic;
+}
+
+div.figure p.caption span.caption-text,
+figcaption span.caption-text {
+}
+
+/* -- field list styles ----------------------------------------------------- */
+
+table.field-list td, table.field-list th {
+    border: 0 !important;
+}
+
+.field-list ul {
+    margin: 0;
+    padding-left: 1em;
+}
+
+.field-list p {
+    margin: 0;
+}
+
+.field-name {
+    -moz-hyphens: manual;
+    -ms-hyphens: manual;
+    -webkit-hyphens: manual;
+    hyphens: manual;
+}
+
+/* -- hlist styles ---------------------------------------------------------- */
+
+table.hlist {
+    margin: 1em 0;
+}
+
+table.hlist td {
+    vertical-align: top;
+}
+
+/* -- object description styles --------------------------------------------- */
+
+.sig {
+	font-family: 'Consolas', 'Menlo', 'DejaVu Sans Mono', 'Bitstream Vera Sans Mono', monospace;
+}
+
+.sig-name, code.descname {
+    background-color: transparent;
+    font-weight: bold;
+}
+
+.sig-name {
+	font-size: 1.1em;
+}
+
+code.descname {
+    font-size: 1.2em;
+}
+
+.sig-prename, code.descclassname {
+    background-color: transparent;
+}
+
+.optional {
+    font-size: 1.3em;
+}
+
+.sig-paren {
+    font-size: larger;
+}
+
+.sig-param.n {
+	font-style: italic;
+}
+
+/* C++ specific styling */
+
+.sig-inline.c-texpr,
+.sig-inline.cpp-texpr {
+	font-family: unset;
+}
+
+.sig.c   .k, .sig.c   .kt,
+.sig.cpp .k, .sig.cpp .kt {
+	color: #0033B3;
+}
+
+.sig.c   .m,
+.sig.cpp .m {
+	color: #1750EB;
+}
+
+.sig.c   .s, .sig.c   .sc,
+.sig.cpp .s, .sig.cpp .sc {
+	color: #067D17;
+}
+
+
+/* -- other body styles ----------------------------------------------------- */
+
+ol.arabic {
+    list-style: decimal;
+}
+
+ol.loweralpha {
+    list-style: lower-alpha;
+}
+
+ol.upperalpha {
+    list-style: upper-alpha;
+}
+
+ol.lowerroman {
+    list-style: lower-roman;
+}
+
+ol.upperroman {
+    list-style: upper-roman;
+}
+
+:not(li) > ol > li:first-child > :first-child,
+:not(li) > ul > li:first-child > :first-child {
+    margin-top: 0px;
+}
+
+:not(li) > ol > li:last-child > :last-child,
+:not(li) > ul > li:last-child > :last-child {
+    margin-bottom: 0px;
+}
+
+ol.simple ol p,
+ol.simple ul p,
+ul.simple ol p,
+ul.simple ul p {
+    margin-top: 0;
+}
+
+ol.simple > li:not(:first-child) > p,
+ul.simple > li:not(:first-child) > p {
+    margin-top: 0;
+}
+
+ol.simple p,
+ul.simple p {
+    margin-bottom: 0;
+}
+
+aside.footnote > span,
+div.citation > span {
+    float: left;
+}
+aside.footnote > span:last-of-type,
+div.citation > span:last-of-type {
+  padding-right: 0.5em;
+}
+aside.footnote > p {
+  margin-left: 2em;
+}
+div.citation > p {
+  margin-left: 4em;
+}
+aside.footnote > p:last-of-type,
+div.citation > p:last-of-type {
+    margin-bottom: 0em;
+}
+aside.footnote > p:last-of-type:after,
+div.citation > p:last-of-type:after {
+    content: "";
+    clear: both;
+}
+
+dl.field-list {
+    display: grid;
+    grid-template-columns: fit-content(30%) auto;
+}
+
+dl.field-list > dt {
+    font-weight: bold;
+    word-break: break-word;
+    padding-left: 0.5em;
+    padding-right: 5px;
+}
+
+dl.field-list > dd {
+    padding-left: 0.5em;
+    margin-top: 0em;
+    margin-left: 0em;
+    margin-bottom: 0em;
+}
+
+dl {
+    margin-bottom: 15px;
+}
+
+dd > :first-child {
+    margin-top: 0px;
+}
+
+dd ul, dd table {
+    margin-bottom: 10px;
+}
+
+dd {
+    margin-top: 3px;
+    margin-bottom: 10px;
+    margin-left: 30px;
+}
+
+.sig dd {
+    margin-top: 0px;
+    margin-bottom: 0px;
+}
+
+.sig dl {
+    margin-top: 0px;
+    margin-bottom: 0px;
+}
+
+dl > dd:last-child,
+dl > dd:last-child > :last-child {
+    margin-bottom: 0;
+}
+
+dt:target, span.highlighted {
+    background-color: #fbe54e;
+}
+
+rect.highlighted {
+    fill: #fbe54e;
+}
+
+dl.glossary dt {
+    font-weight: bold;
+    font-size: 1.1em;
+}
+
+.versionmodified {
+    font-style: italic;
+}
+
+.system-message {
+    background-color: #fda;
+    padding: 5px;
+    border: 3px solid red;
+}
+
+.footnote:target  {
+    background-color: #ffa;
+}
+
+.line-block {
+    display: block;
+    margin-top: 1em;
+    margin-bottom: 1em;
+}
+
+.line-block .line-block {
+    margin-top: 0;
+    margin-bottom: 0;
+    margin-left: 1.5em;
+}
+
+.guilabel, .menuselection {
+    font-family: sans-serif;
+}
+
+.accelerator {
+    text-decoration: underline;
+}
+
+.classifier {
+    font-style: oblique;
+}
+
+.classifier:before {
+    font-style: normal;
+    margin: 0 0.5em;
+    content: ":";
+    display: inline-block;
+}
+
+abbr, acronym {
+    border-bottom: dotted 1px;
+    cursor: help;
+}
+
+.translated {
+    background-color: rgba(207, 255, 207, 0.2)
+}
+
+.untranslated {
+    background-color: rgba(255, 207, 207, 0.2)
+}
+
+/* -- code displays --------------------------------------------------------- */
+
+pre {
+    overflow: auto;
+    overflow-y: hidden;  /* fixes display issues on Chrome browsers */
+}
+
+pre, div[class*="highlight-"] {
+    clear: both;
+}
+
+span.pre {
+    -moz-hyphens: none;
+    -ms-hyphens: none;
+    -webkit-hyphens: none;
+    hyphens: none;
+    white-space: nowrap;
+}
+
+div[class*="highlight-"] {
+    margin: 1em 0;
+}
+
+td.linenos pre {
+    border: 0;
+    background-color: transparent;
+    color: #aaa;
+}
+
+table.highlighttable {
+    display: block;
+}
+
+table.highlighttable tbody {
+    display: block;
+}
+
+table.highlighttable tr {
+    display: flex;
+}
+
+table.highlighttable td {
+    margin: 0;
+    padding: 0;
+}
+
+table.highlighttable td.linenos {
+    padding-right: 0.5em;
+}
+
+table.highlighttable td.code {
+    flex: 1;
+    overflow: hidden;
+}
+
+.highlight .hll {
+    display: block;
+}
+
+div.highlight pre,
+table.highlighttable pre {
+    margin: 0;
+}
+
+div.code-block-caption + div {
+    margin-top: 0;
+}
+
+div.code-block-caption {
+    margin-top: 1em;
+    padding: 2px 5px;
+    font-size: small;
+}
+
+div.code-block-caption code {
+    background-color: transparent;
+}
+
+table.highlighttable td.linenos,
+span.linenos,
+div.highlight span.gp {  /* gp: Generic.Prompt */
+  user-select: none;
+  -webkit-user-select: text; /* Safari fallback only */
+  -webkit-user-select: none; /* Chrome/Safari */
+  -moz-user-select: none; /* Firefox */
+  -ms-user-select: none; /* IE10+ */
+}
+
+div.code-block-caption span.caption-number {
+    padding: 0.1em 0.3em;
+    font-style: italic;
+}
+
+div.code-block-caption span.caption-text {
+}
+
+div.literal-block-wrapper {
+    margin: 1em 0;
+}
+
+code.xref, a code {
+    background-color: transparent;
+    font-weight: bold;
+}
+
+h1 code, h2 code, h3 code, h4 code, h5 code, h6 code {
+    background-color: transparent;
+}
+
+.viewcode-link {
+    float: right;
+}
+
+.viewcode-back {
+    float: right;
+    font-family: sans-serif;
+}
+
+div.viewcode-block:target {
+    margin: -1px -10px;
+    padding: 0 10px;
+}
+
+/* -- math display ---------------------------------------------------------- */
+
+img.math {
+    vertical-align: middle;
+}
+
+div.body div.math p {
+    text-align: center;
+}
+
+span.eqno {
+    float: right;
+}
+
+span.eqno a.headerlink {
+    position: absolute;
+    z-index: 1;
+}
+
+div.math:hover a.headerlink {
+    visibility: visible;
+}
+
+/* -- printout stylesheet --------------------------------------------------- */
+
+@media print {
+    div.document,
+    div.documentwrapper,
+    div.bodywrapper {
+        margin: 0 !important;
+        width: 100%;
+    }
+
+    div.sphinxsidebar,
+    div.related,
+    div.footer,
+    #top-link {
+        display: none;
+    }
+}

_static/check-solid.svg

@@ -0,0 +1,4 @@
+<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-check" width="44" height="44" viewBox="0 0 24 24" stroke-width="2" stroke="#22863a" fill="none" stroke-linecap="round" stroke-linejoin="round">
+  <path stroke="none" d="M0 0h24v24H0z" fill="none"/>
+  <path d="M5 12l5 5l10 -10" />
+</svg>

_static/copy-button.svg

@@ -0,0 +1,5 @@
+<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-copy" width="44" height="44" viewBox="0 0 24 24" stroke-width="1.5" stroke="#000000" fill="none" stroke-linecap="round" stroke-linejoin="round">
+  <path stroke="none" d="M0 0h24v24H0z" fill="none"/>
+  <rect x="8" y="8" width="12" height="12" rx="2" />
+  <path d="M16 8v-2a2 2 0 0 0 -2 -2h-8a2 2 0 0 0 -2 2v8a2 2 0 0 0 2 2h2" />
+</svg>

_static/copybutton.css

@@ -0,0 +1,94 @@
+/* Copy buttons */
+button.copybtn {
+    position: absolute;
+    display: flex;
+    top: .3em;
+    right: .3em;
+    width: 1.7em;
+    height: 1.7em;
+	opacity: 0;
+    transition: opacity 0.3s, border .3s, background-color .3s;
+    user-select: none;
+    padding: 0;
+    border: none;
+    outline: none;
+    border-radius: 0.4em;
+    /* The colors that GitHub uses */
+    border: #1b1f2426 1px solid;
+    background-color: #f6f8fa;
+    color: #57606a;
+}
+
+button.copybtn.success {
+    border-color: #22863a;
+    color: #22863a;
+}
+
+button.copybtn svg {
+    stroke: currentColor;
+    width: 1.5em;
+    height: 1.5em;
+    padding: 0.1em;
+}
+
+div.highlight  {
+    position: relative;
+}
+
+/* Show the copybutton */
+.highlight:hover button.copybtn, button.copybtn.success {
+	opacity: 1;
+}
+
+.highlight button.copybtn:hover {
+    background-color: rgb(235, 235, 235);
+}
+
+.highlight button.copybtn:active {
+    background-color: rgb(187, 187, 187);
+}
+
+/**
+ * A minimal CSS-only tooltip copied from:
+ *   https://codepen.io/mildrenben/pen/rVBrpK
+ *
+ * To use, write HTML like the following:
+ *
+ * <p class="o-tooltip--left" data-tooltip="Hey">Short</p>
+ */
+ .o-tooltip--left {
+  position: relative;
+ }
+
+ .o-tooltip--left:after {
+    opacity: 0;
+    visibility: hidden;
+    position: absolute;
+    content: attr(data-tooltip);
+    padding: .2em;
+    font-size: .8em;
+    left: -.2em;
+    background: grey;
+    color: white;
+    white-space: nowrap;
+    z-index: 2;
+    border-radius: 2px;
+    transform: translateX(-102%) translateY(0);
+    transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1);
+}
+
+.o-tooltip--left:hover:after {
+    display: block;
+    opacity: 1;
+    visibility: visible;
+    transform: translateX(-100%) translateY(0);
+    transition: opacity 0.2s cubic-bezier(0.64, 0.09, 0.08, 1), transform 0.2s cubic-bezier(0.64, 0.09, 0.08, 1);
+    transition-delay: .5s;
+}
+
+/* By default the copy button shouldn't show up when printing a page */
+@media print {
+    button.copybtn {
+        display: none;
+    }
+}

_static/copybutton.js

@@ -0,0 +1,248 @@
+// Localization support
+const messages = {
+  'en': {
+    'copy': 'Copy',
+    'copy_to_clipboard': 'Copy to clipboard',
+    'copy_success': 'Copied!',
+    'copy_failure': 'Failed to copy',
+  },
+  'es' : {
+    'copy': 'Copiar',
+    'copy_to_clipboard': 'Copiar al portapapeles',
+    'copy_success': '¡Copiado!',
+    'copy_failure': 'Error al copiar',
+  },
+  'de' : {
+    'copy': 'Kopieren',
+    'copy_to_clipboard': 'In die Zwischenablage kopieren',
+    'copy_success': 'Kopiert!',
+    'copy_failure': 'Fehler beim Kopieren',
+  },
+  'fr' : {
+    'copy': 'Copier',
+    'copy_to_clipboard': 'Copier dans le presse-papier',
+    'copy_success': 'Copié !',
+    'copy_failure': 'Échec de la copie',
+  },
+  'ru': {
+    'copy': 'Скопировать',
+    'copy_to_clipboard': 'Скопировать в буфер',
+    'copy_success': 'Скопировано!',
+    'copy_failure': 'Не удалось скопировать',
+  },
+  'zh-CN': {
+    'copy': '复制',
+    'copy_to_clipboard': '复制到剪贴板',
+    'copy_success': '复制成功!',
+    'copy_failure': '复制失败',
+  },
+  'it' : {
+    'copy': 'Copiare',
+    'copy_to_clipboard': 'Copiato negli appunti',
+    'copy_success': 'Copiato!',
+    'copy_failure': 'Errore durante la copia',
+  }
+}
+
+let locale = 'en'
+if( document.documentElement.lang !== undefined
+    && messages[document.documentElement.lang] !== undefined ) {
+  locale = document.documentElement.lang
+}
+
+let doc_url_root = DOCUMENTATION_OPTIONS.URL_ROOT;
+if (doc_url_root == '#') {
+    doc_url_root = '';
+}
+
+/**
+ * SVG files for our copy buttons
+ */
+let iconCheck = `<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-check" width="44" height="44" viewBox="0 0 24 24" stroke-width="2" stroke="#22863a" fill="none" stroke-linecap="round" stroke-linejoin="round">
+  <title>${messages[locale]['copy_success']}</title>
+  <path stroke="none" d="M0 0h24v24H0z" fill="none"/>
+  <path d="M5 12l5 5l10 -10" />
+</svg>`
+
+// If the user specified their own SVG use that, otherwise use the default
+let iconCopy = ``;
+if (!iconCopy) {
+  iconCopy = `<svg xmlns="http://www.w3.org/2000/svg" class="icon icon-tabler icon-tabler-copy" width="44" height="44" viewBox="0 0 24 24" stroke-width="1.5" stroke="#000000" fill="none" stroke-linecap="round" stroke-linejoin="round">
+  <title>${messages[locale]['copy_to_clipboard']}</title>
+  <path stroke="none" d="M0 0h24v24H0z" fill="none"/>
+  <rect x="8" y="8" width="12" height="12" rx="2" />
+  <path d="M16 8v-2a2 2 0 0 0 -2 -2h-8a2 2 0 0 0 -2 2v8a2 2 0 0 0 2 2h2" />
+</svg>`
+}
+
+/**
+ * Set up copy/paste for code blocks
+ */
+
+const runWhenDOMLoaded = cb => {
+  if (document.readyState != 'loading') {
+    cb()
+  } else if (document.addEventListener) {
+    document.addEventListener('DOMContentLoaded', cb)
+  } else {
+    document.attachEvent('onreadystatechange', function() {
+      if (document.readyState == 'complete') cb()
+    })
+  }
+}
+
+const codeCellId = index => `codecell${index}`
+
+// Clears selected text since ClipboardJS will select the text when copying
+const clearSelection = () => {
+  if (window.getSelection) {
+    window.getSelection().removeAllRanges()
+  } else if (document.selection) {
+    document.selection.empty()
+  }
+}
+
+// Changes tooltip text for a moment, then changes it back
+// We want the timeout of our `success` class to be a bit shorter than the
+// tooltip and icon change, so that we can hide the icon before changing back.
+var timeoutIcon = 2000;
+var timeoutSuccessClass = 1500;
+
+const temporarilyChangeTooltip = (el, oldText, newText) => {
+  el.setAttribute('data-tooltip', newText)
+  el.classList.add('success')
+  // Remove success a little bit sooner than we change the tooltip
+  // So that we can use CSS to hide the copybutton first
+  setTimeout(() => el.classList.remove('success'), timeoutSuccessClass)
+  setTimeout(() => el.setAttribute('data-tooltip', oldText), timeoutIcon)
+}
+
+// Changes the copy button icon for two seconds, then changes it back
+const temporarilyChangeIcon = (el) => {
+  el.innerHTML = iconCheck;
+  setTimeout(() => {el.innerHTML = iconCopy}, timeoutIcon)
+}
+
+const addCopyButtonToCodeCells = () => {
+  // If ClipboardJS hasn't loaded, wait a bit and try again. This
+  // happens because we load ClipboardJS asynchronously.
+  if (window.ClipboardJS === undefined) {
+    setTimeout(addCopyButtonToCodeCells, 250)
+    return
+  }
+
+  // Add copybuttons to all of our code cells
+  const COPYBUTTON_SELECTOR = 'div.highlight pre';
+  const codeCells = document.querySelectorAll(COPYBUTTON_SELECTOR)
+  codeCells.forEach((codeCell, index) => {
+    const id = codeCellId(index)
+    codeCell.setAttribute('id', id)
+
+    const clipboardButton = id =>
+    `<button class="copybtn o-tooltip--left" data-tooltip="${messages[locale]['copy']}" data-clipboard-target="#${id}">
+      ${iconCopy}
+    </button>`
+    codeCell.insertAdjacentHTML('afterend', clipboardButton(id))
+  })
+
+function escapeRegExp(string) {
+    return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string
+}
+
+/**
+ * Removes excluded text from a Node.
+ *
+ * @param {Node} target Node to filter.
+ * @param {string} exclude CSS selector of nodes to exclude.
+ * @returns {DOMString} Text from `target` with text removed.
+ */
+function filterText(target, exclude) {
+    const clone = target.cloneNode(true);  // clone as to not modify the live DOM
+    if (exclude) {
+        // remove excluded nodes
+        clone.querySelectorAll(exclude).forEach(node => node.remove());
+    }
+    return clone.innerText;
+}
+
+// Callback when a copy button is clicked. Will be passed the node that was clicked
+// should then grab the text and replace pieces of text that shouldn't be used in output
+function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") {
+    var regexp;
+    var match;
+
+    // Do we check for line continuation characters and "HERE-documents"?
+    var useLineCont = !!lineContinuationChar
+    var useHereDoc = !!hereDocDelim
+
+    // create regexp to capture prompt and remaining line
+    if (isRegexp) {
+        regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)')
+    } else {
+        regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)')
+    }
+
+    const outputLines = [];
+    var promptFound = false;
+    var gotLineCont = false;
+    var gotHereDoc = false;
+    const lineGotPrompt = [];
+    for (const line of textContent.split('\n')) {
+        match = line.match(regexp)
+        if (match || gotLineCont || gotHereDoc) {
+            promptFound = regexp.test(line)
+            lineGotPrompt.push(promptFound)
+            if (removePrompts && promptFound) {
+                outputLines.push(match[2])
+            } else {
+                outputLines.push(line)
+            }
+            gotLineCont = line.endsWith(lineContinuationChar) & useLineCont
+            if (line.includes(hereDocDelim) & useHereDoc)
+                gotHereDoc = !gotHereDoc
+        } else if (!onlyCopyPromptLines) {
+            outputLines.push(line)
+        } else if (copyEmptyLines && line.trim() === '') {
+            outputLines.push(line)
+        }
+    }
+
+    // If no lines with the prompt were found then just use original lines
+    if (lineGotPrompt.some(v => v === true)) {
+        textContent = outputLines.join('\n');
+    }
+
+    // Remove a trailing newline to avoid auto-running when pasting
+    if (textContent.endsWith("\n")) {
+        textContent = textContent.slice(0, -1)
+    }
+    return textContent
+}
+
+
+var copyTargetText = (trigger) => {
+  var target = document.querySelector(trigger.attributes['data-clipboard-target'].value);
+
+  // get filtered text
+  let exclude = '.linenos';
+
+  let text = filterText(target, exclude);
+  return formatCopyText(text, '', false, true, true, true, '', '')
+}
+
+  // Initialize with a callback so we can modify the text before copy
+  const clipboard = new ClipboardJS('.copybtn', {text: copyTargetText})
+
+  // Update UI with error/success messages
+  clipboard.on('success', event => {
+    clearSelection()
+    temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_success'])
+    temporarilyChangeIcon(event.trigger)
+  })
+
+  clipboard.on('error', event => {
+    temporarilyChangeTooltip(event.trigger, messages[locale]['copy'], messages[locale]['copy_failure'])
+  })
+}
+
+runWhenDOMLoaded(addCopyButtonToCodeCells)

_static/copybutton_funcs.js

@@ -0,0 +1,73 @@
+function escapeRegExp(string) {
+    return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string
+}
+
+/**
+ * Removes excluded text from a Node.
+ *
+ * @param {Node} target Node to filter.
+ * @param {string} exclude CSS selector of nodes to exclude.
+ * @returns {DOMString} Text from `target` with text removed.
+ */
+export function filterText(target, exclude) {
+    const clone = target.cloneNode(true);  // clone as to not modify the live DOM
+    if (exclude) {
+        // remove excluded nodes
+        clone.querySelectorAll(exclude).forEach(node => node.remove());
+    }
+    return clone.innerText;
+}
+
+// Callback when a copy button is clicked. Will be passed the node that was clicked
+// should then grab the text and replace pieces of text that shouldn't be used in output
+export function formatCopyText(textContent, copybuttonPromptText, isRegexp = false, onlyCopyPromptLines = true, removePrompts = true, copyEmptyLines = true, lineContinuationChar = "", hereDocDelim = "") {
+    var regexp;
+    var match;
+
+    // Do we check for line continuation characters and "HERE-documents"?
+    var useLineCont = !!lineContinuationChar
+    var useHereDoc = !!hereDocDelim
+
+    // create regexp to capture prompt and remaining line
+    if (isRegexp) {
+        regexp = new RegExp('^(' + copybuttonPromptText + ')(.*)')
+    } else {
+        regexp = new RegExp('^(' + escapeRegExp(copybuttonPromptText) + ')(.*)')
+    }
+
+    const outputLines = [];
+    var promptFound = false;
+    var gotLineCont = false;
+    var gotHereDoc = false;
+    const lineGotPrompt = [];
+    for (const line of textContent.split('\n')) {
+        match = line.match(regexp)
+        if (match || gotLineCont || gotHereDoc) {
+            promptFound = regexp.test(line)
+            lineGotPrompt.push(promptFound)
+            if (removePrompts && promptFound) {
+                outputLines.push(match[2])
+            } else {
+                outputLines.push(line)
+            }
+            gotLineCont = line.endsWith(lineContinuationChar) & useLineCont
+            if (line.includes(hereDocDelim) & useHereDoc)
+                gotHereDoc = !gotHereDoc
+        } else if (!onlyCopyPromptLines) {
+            outputLines.push(line)
+        } else if (copyEmptyLines && line.trim() === '') {
+            outputLines.push(line)
+        }
+    }
+
+    // If no lines with the prompt were found then just use original lines
+    if (lineGotPrompt.some(v => v === true)) {
+        textContent = outputLines.join('\n');
+    }
+
+    // Remove a trailing newline to avoid auto-running when pasting
+    if (textContent.endsWith("\n")) {
+        textContent = textContent.slice(0, -1)
+    }
+    return textContent
+}

_static/css/arch.css

@@ -0,0 +1,5 @@
+@import url("theme.css");
+
+body {
+  font-size: 1em;
+}

_static/doctools.js

@@ -0,0 +1,156 @@
+/*
+ * doctools.js
+ * ~~~~~~~~~~~
+ *
+ * Base JavaScript utilities for all Sphinx HTML documentation.
+ *
+ * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+"use strict";
+
+const BLACKLISTED_KEY_CONTROL_ELEMENTS = new Set([
+  "TEXTAREA",
+  "INPUT",
+  "SELECT",
+  "BUTTON",
+]);
+
+const _ready = (callback) => {
+  if (document.readyState !== "loading") {
+    callback();
+  } else {
+    document.addEventListener("DOMContentLoaded", callback);
+  }
+};
+
+/**
+ * Small JavaScript module for the documentation.
+ */
+const Documentation = {
+  init: () => {
+    Documentation.initDomainIndexTable();
+    Documentation.initOnKeyListeners();
+  },
+
+  /**
+   * i18n support
+   */
+  TRANSLATIONS: {},
+  PLURAL_EXPR: (n) => (n === 1 ? 0 : 1),
+  LOCALE: "unknown",
+
+  // gettext and ngettext don't access this so that the functions
+  // can safely bound to a different name (_ = Documentation.gettext)
+  gettext: (string) => {
+    const translated = Documentation.TRANSLATIONS[string];
+    switch (typeof translated) {
+      case "undefined":
+        return string; // no translation
+      case "string":
+        return translated; // translation exists
+      default:
+        return translated[0]; // (singular, plural) translation tuple exists
+    }
+  },
+
+  ngettext: (singular, plural, n) => {
+    const translated = Documentation.TRANSLATIONS[singular];
+    if (typeof translated !== "undefined")
+      return translated[Documentation.PLURAL_EXPR(n)];
+    return n === 1 ? singular : plural;
+  },
+
+  addTranslations: (catalog) => {
+    Object.assign(Documentation.TRANSLATIONS, catalog.messages);
+    Documentation.PLURAL_EXPR = new Function(
+      "n",
+      `return (${catalog.plural_expr})`
+    );
+    Documentation.LOCALE = catalog.locale;
+  },
+
+  /**
+   * helper function to focus on search bar
+   */
+  focusSearchBar: () => {
+    document.querySelectorAll("input[name=q]")[0]?.focus();
+  },
+
+  /**
+   * Initialise the domain index toggle buttons
+   */
+  initDomainIndexTable: () => {
+    const toggler = (el) => {
+      const idNumber = el.id.substr(7);
+      const toggledRows = document.querySelectorAll(`tr.cg-${idNumber}`);
+      if (el.src.substr(-9) === "minus.png") {
+        el.src = `${el.src.substr(0, el.src.length - 9)}plus.png`;
+        toggledRows.forEach((el) => (el.style.display = "none"));
+      } else {
+        el.src = `${el.src.substr(0, el.src.length - 8)}minus.png`;
+        toggledRows.forEach((el) => (el.style.display = ""));
+      }
+    };
+
+    const togglerElements = document.querySelectorAll("img.toggler");
+    togglerElements.forEach((el) =>
+      el.addEventListener("click", (event) => toggler(event.currentTarget))
+    );
+    togglerElements.forEach((el) => (el.style.display = ""));
+    if (DOCUMENTATION_OPTIONS.COLLAPSE_INDEX) togglerElements.forEach(toggler);
+  },
+
+  initOnKeyListeners: () => {
+    // only install a listener if it is really needed
+    if (
+      !DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS &&
+      !DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS
+    )
+      return;
+
+    document.addEventListener("keydown", (event) => {
+      // bail for input elements
+      if (BLACKLISTED_KEY_CONTROL_ELEMENTS.has(document.activeElement.tagName)) return;
+      // bail with special keys
+      if (event.altKey || event.ctrlKey || event.metaKey) return;
+
+      if (!event.shiftKey) {
+        switch (event.key) {
+          case "ArrowLeft":
+            if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break;
+
+            const prevLink = document.querySelector('link[rel="prev"]');
+            if (prevLink && prevLink.href) {
+              window.location.href = prevLink.href;
+              event.preventDefault();
+            }
+            break;
+          case "ArrowRight":
+            if (!DOCUMENTATION_OPTIONS.NAVIGATION_WITH_KEYS) break;
+
+            const nextLink = document.querySelector('link[rel="next"]');
+            if (nextLink && nextLink.href) {
+              window.location.href = nextLink.href;
+              event.preventDefault();
+            }
+            break;
+        }
+      }
+
+      // some keyboard layouts may need Shift to get /
+      switch (event.key) {
+        case "/":
+          if (!DOCUMENTATION_OPTIONS.ENABLE_SEARCH_SHORTCUTS) break;
+          Documentation.focusSearchBar();
+          event.preventDefault();
+      }
+    });
+  },
+};
+
+// quick alias for translations
+const _ = Documentation.gettext;
+
+_ready(Documentation.init);

_static/documentation_options.js

@@ -0,0 +1,13 @@
+const DOCUMENTATION_OPTIONS = {
+    VERSION: '0.1-beta',
+    LANGUAGE: 'en',
+    COLLAPSE_INDEX: false,
+    BUILDER: 'html',
+    FILE_SUFFIX: '.html',
+    LINK_SUFFIX: '.html',
+    HAS_SOURCE: true,
+    SOURCELINK_SUFFIX: '',
+    NAVIGATION_WITH_KEYS: false,
+    SHOW_SEARCH_SUMMARY: true,
+    ENABLE_SEARCH_SHORTCUTS: true,
+};

_static/images/logo_binder.svg

@@ -0,0 +1,19 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 23.0.1, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 44.4 44.4" style="enable-background:new 0 0 44.4 44.4;" xml:space="preserve">
+<style type="text/css">
+	.st0{fill:none;stroke:#F5A252;stroke-width:5;stroke-miterlimit:10;}
+	.st1{fill:none;stroke:#579ACA;stroke-width:5;stroke-miterlimit:10;}
+	.st2{fill:none;stroke:#E66581;stroke-width:5;stroke-miterlimit:10;}
+</style>
+<title>logo</title>
+<g>
+	<path class="st0" d="M33.9,6.4c3.6,3.9,3.4,9.9-0.5,13.5s-9.9,3.4-13.5-0.5s-3.4-9.9,0.5-13.5l0,0C24.2,2.4,30.2,2.6,33.9,6.4z"/>
+	<path class="st1" d="M35.1,27.3c2.6,4.6,1.1,10.4-3.5,13c-4.6,2.6-10.4,1.1-13-3.5s-1.1-10.4,3.5-13l0,0
+		C26.6,21.2,32.4,22.7,35.1,27.3z"/>
+	<path class="st2" d="M25.9,17.8c2.6,4.6,1.1,10.4-3.5,13s-10.4,1.1-13-3.5s-1.1-10.4,3.5-13l0,0C17.5,11.7,23.3,13.2,25.9,17.8z"/>
+	<path class="st1" d="M19.2,26.4c3.1-4.3,9.1-5.2,13.3-2.1c1.1,0.8,2,1.8,2.7,3"/>
+	<path class="st0" d="M19.9,19.4c-3.6-3.9-3.4-9.9,0.5-13.5s9.9-3.4,13.5,0.5"/>
+</g>
+</svg>

_static/images/logo_deepnote.svg

@@ -0,0 +1 @@
+<svg viewBox="0 0 128 128" fill="none" xmlns="http://www.w3.org/2000/svg"><path fill-rule="evenodd" clip-rule="evenodd" d="M0 128h52.512l29.539-11.077-11.077-43.487-34.051 3.693L0 128Z" fill="#0076D4"/><path fill-rule="evenodd" clip-rule="evenodd" d="M52.513 128s16.6-8.759 19.673-24.277c3.072-15.517-12.091-26.594-35.263-26.594 0-.41 20.343-28.718 20.343-28.718l49.4 1.435L95.71 107.7l-20.452 15.978L52.513 128Z" fill="#002868"/><path fill-rule="evenodd" clip-rule="evenodd" d="M0 60.718 41.025.001s1.006.01 3.282 0c16.082-.068 81.23 3.12 81.23 60.368 0 65.352-73.025 67.631-73.025 67.631s30.495-5.839 30.495-34.816c0-28.978-27.541-32.466-45.264-32.466H0Z" fill="#00A9FF"/></svg>

_static/images/logo_jupyterhub.svg

@@ -0,0 +1 @@
+<svg id="Layer_1" data-name="Layer 1" xmlns="http://www.w3.org/2000/svg" width="38.73" height="50" viewBox="0 0 38.73 50"><defs><style>.cls-1{fill:#767677;}.cls-2{fill:#f37726;}.cls-3{fill:#9e9e9e;}.cls-4{fill:#616262;}.cls-5{font-size:17.07px;fill:#fff;font-family:Roboto-Regular, Roboto;}</style></defs><title>logo_jupyterhub</title><g id="Canvas"><path id="path7_fill" data-name="path7 fill" class="cls-1" d="M39.51,3.53a3,3,0,0,1-1.7,2.9A3,3,0,0,1,34.48,6a3,3,0,0,1-.82-3.26,3,3,0,0,1,1.05-1.41A3,3,0,0,1,37.52.86a2.88,2.88,0,0,1,1,.6,3,3,0,0,1,.7.93,3.18,3.18,0,0,1,.28,1.14Z" transform="translate(-1.87 -0.69)"/><path id="path8_fill" data-name="path8 fill" class="cls-2" d="M21.91,38.39c-8,0-15.06-2.87-18.7-7.12a19.93,19.93,0,0,0,37.39,0C37,35.52,30,38.39,21.91,38.39Z" transform="translate(-1.87 -0.69)"/><path id="path9_fill" data-name="path9 fill" class="cls-2" d="M21.91,10.78c8,0,15.05,2.87,18.69,7.12a19.93,19.93,0,0,0-37.39,0C6.85,13.64,13.86,10.78,21.91,10.78Z" transform="translate(-1.87 -0.69)"/><path id="path10_fill" data-name="path10 fill" class="cls-3" d="M10.88,46.66a3.86,3.86,0,0,1-.52,2.15,3.81,3.81,0,0,1-1.62,1.51,3.93,3.93,0,0,1-2.19.34,3.79,3.79,0,0,1-2-.94,3.73,3.73,0,0,1-1.14-1.9,3.79,3.79,0,0,1,.1-2.21,3.86,3.86,0,0,1,1.33-1.78,3.92,3.92,0,0,1,3.54-.53,3.85,3.85,0,0,1,2.14,1.93,3.74,3.74,0,0,1,.37,1.43Z" transform="translate(-1.87 -0.69)"/><path id="path11_fill" data-name="path11 fill" class="cls-4" d="M4.12,9.81A2.18,2.18,0,0,1,2.9,9.48a2.23,2.23,0,0,1-.84-1A2.26,2.26,0,0,1,1.9,7.26a2.13,2.13,0,0,1,.56-1.13,2.18,2.18,0,0,1,2.36-.56,2.13,2.13,0,0,1,1,.76,2.18,2.18,0,0,1,.42,1.2A2.22,2.22,0,0,1,4.12,9.81Z" transform="translate(-1.87 -0.69)"/></g><text class="cls-5" transform="translate(5.24 30.01)">Hub</text></svg>

_static/language_data.js

@@ -0,0 +1,199 @@
+/*
+ * language_data.js
+ * ~~~~~~~~~~~~~~~~
+ *
+ * This script contains the language-specific data used by searchtools.js,
+ * namely the list of stopwords, stemmer, scorer and splitter.
+ *
+ * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS.
+ * :license: BSD, see LICENSE for details.
+ *
+ */
+
+var stopwords = ["a", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "near", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"];
+
+
+/* Non-minified version is copied as a separate JS file, if available */
+
+/**
+ * Porter Stemmer
+ */
+var Stemmer = function() {
+
+  var step2list = {
+    ational: 'ate',
+    tional: 'tion',
+    enci: 'ence',
+    anci: 'ance',
+    izer: 'ize',
+    bli: 'ble',
+    alli: 'al',
+    entli: 'ent',
+    eli: 'e',
+    ousli: 'ous',
+    ization: 'ize',
+    ation: 'ate',
+    ator: 'ate',
+    alism: 'al',
+    iveness: 'ive',
+    fulness: 'ful',
+    ousness: 'ous',
+    aliti: 'al',
+    iviti: 'ive',
+    biliti: 'ble',
+    logi: 'log'
+  };
+
+  var step3list = {
+    icate: 'ic',
+    ative: '',
+    alize: 'al',
+    iciti: 'ic',
+    ical: 'ic',
+    ful: '',
+    ness: ''
+  };
+
+  var c = "[^aeiou]";          // consonant
+  var v = "[aeiouy]";          // vowel
+  var C = c + "[^aeiouy]*";    // consonant sequence
+  var V = v + "[aeiou]*";      // vowel sequence
+
+  var mgr0 = "^(" + C + ")?" + V + C;                      // [C]VC... is m>0
+  var meq1 = "^(" + C + ")?" + V + C + "(" + V + ")?$";    // [C]VC[V] is m=1
+  var mgr1 = "^(" + C + ")?" + V + C + V + C;              // [C]VCVC... is m>1
+  var s_v   = "^(" + C + ")?" + v;                         // vowel in stem
+
+  this.stemWord = function (w) {
+    var stem;
+    var suffix;
+    var firstch;
+    var origword = w;
+
+    if (w.length < 3)
+      return w;
+
+    var re;
+    var re2;
+    var re3;
+    var re4;
+
+    firstch = w.substr(0,1);
+    if (firstch == "y")
+      w = firstch.toUpperCase() + w.substr(1);
+
+    // Step 1a
+    re = /^(.+?)(ss|i)es$/;
+    re2 = /^(.+?)([^s])s$/;
+
+    if (re.test(w))
+      w = w.replace(re,"$1$2");
+    else if (re2.test(w))
+      w = w.replace(re2,"$1$2");
+
+    // Step 1b
+    re = /^(.+?)eed$/;
+    re2 = /^(.+?)(ed|ing)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      re = new RegExp(mgr0);
+      if (re.test(fp[1])) {
+        re = /.$/;
+        w = w.replace(re,"");
+      }
+    }
+    else if (re2.test(w)) {
+      var fp = re2.exec(w);
+      stem = fp[1];
+      re2 = new RegExp(s_v);
+      if (re2.test(stem)) {
+        w = stem;
+        re2 = /(at|bl|iz)$/;
+        re3 = new RegExp("([^aeiouylsz])\\1$");
+        re4 = new RegExp("^" + C + v + "[^aeiouwxy]$");
+        if (re2.test(w))
+          w = w + "e";
+        else if (re3.test(w)) {
+          re = /.$/;
+          w = w.replace(re,"");
+        }
+        else if (re4.test(w))
+          w = w + "e";
+      }
+    }
+
+    // Step 1c
+    re = /^(.+?)y$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      re = new RegExp(s_v);
+      if (re.test(stem))
+        w = stem + "i";
+    }
+
+    // Step 2
+    re = /^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      suffix = fp[2];
+      re = new RegExp(mgr0);
+      if (re.test(stem))
+        w = stem + step2list[suffix];
+    }
+
+    // Step 3
+    re = /^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      suffix = fp[2];
+      re = new RegExp(mgr0);
+      if (re.test(stem))
+        w = stem + step3list[suffix];
+    }
+
+    // Step 4
+    re = /^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/;
+    re2 = /^(.+?)(s|t)(ion)$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      re = new RegExp(mgr1);
+      if (re.test(stem))
+        w = stem;
+    }
+    else if (re2.test(w)) {
+      var fp = re2.exec(w);
+      stem = fp[1] + fp[2];
+      re2 = new RegExp(mgr1);
+      if (re2.test(stem))
+        w = stem;
+    }
+
+    // Step 5
+    re = /^(.+?)e$/;
+    if (re.test(w)) {
+      var fp = re.exec(w);
+      stem = fp[1];
+      re = new RegExp(mgr1);
+      re2 = new RegExp(meq1);
+      re3 = new RegExp("^" + C + v + "[^aeiouwxy]$");
+      if (re.test(stem) || (re2.test(stem) && !(re3.test(stem))))
+        w = stem;
+    }
+    re = /ll$/;
+    re2 = new RegExp(mgr1);
+    if (re.test(w) && re2.test(w)) {
+      re = /.$/;
+      w = w.replace(re,"");
+    }
+
+    // and turn initial Y back to y
+    if (firstch == "y")
+      w = firstch.toLowerCase() + w.substr(1);
+    return w;
+  }
+}
+

_static/locales/ar/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ar\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "طباعة إلى PDF"
+
+msgid "Theme by the"
+msgstr "موضوع بواسطة"
+
+msgid "Download source file"
+msgstr "تنزيل ملف المصدر"
+
+msgid "open issue"
+msgstr "قضية مفتوحة"
+
+msgid "Contents"
+msgstr "محتويات"
+
+msgid "previous page"
+msgstr "الصفحة السابقة"
+
+msgid "Download notebook file"
+msgstr "تنزيل ملف دفتر الملاحظات"
+
+msgid "Copyright"
+msgstr "حقوق النشر"
+
+msgid "Download this page"
+msgstr "قم بتنزيل هذه الصفحة"
+
+msgid "Source repository"
+msgstr "مستودع المصدر"
+
+msgid "By"
+msgstr "بواسطة"
+
+msgid "repository"
+msgstr "مخزن"
+
+msgid "Last updated on"
+msgstr "آخر تحديث في"
+
+msgid "Toggle navigation"
+msgstr "تبديل التنقل"
+
+msgid "Sphinx Book Theme"
+msgstr "موضوع كتاب أبو الهول"
+
+msgid "suggest edit"
+msgstr "أقترح تحرير"
+
+msgid "Open an issue"
+msgstr "افتح قضية"
+
+msgid "Launch"
+msgstr "إطلاق"
+
+msgid "Fullscreen mode"
+msgstr "وضع ملء الشاشة"
+
+msgid "Edit this page"
+msgstr "قم بتحرير هذه الصفحة"
+
+msgid "By the"
+msgstr "بواسطة"
+
+msgid "next page"
+msgstr "الصفحة التالية"

_static/locales/bg/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: bg\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Печат в PDF"
+
+msgid "Theme by the"
+msgstr "Тема от"
+
+msgid "Download source file"
+msgstr "Изтеглете изходния файл"
+
+msgid "open issue"
+msgstr "отворен брой"
+
+msgid "Contents"
+msgstr "Съдържание"
+
+msgid "previous page"
+msgstr "предишна страница"
+
+msgid "Download notebook file"
+msgstr "Изтеглете файла на бележника"
+
+msgid "Copyright"
+msgstr "Авторско право"
+
+msgid "Download this page"
+msgstr "Изтеглете тази страница"
+
+msgid "Source repository"
+msgstr "Хранилище на източника"
+
+msgid "By"
+msgstr "От"
+
+msgid "repository"
+msgstr "хранилище"
+
+msgid "Last updated on"
+msgstr "Последна актуализация на"
+
+msgid "Toggle navigation"
+msgstr "Превключване на навигацията"
+
+msgid "Sphinx Book Theme"
+msgstr "Тема на книгата Sphinx"
+
+msgid "suggest edit"
+msgstr "предложи редактиране"
+
+msgid "Open an issue"
+msgstr "Отворете проблем"
+
+msgid "Launch"
+msgstr "Стартиране"
+
+msgid "Fullscreen mode"
+msgstr "Режим на цял екран"
+
+msgid "Edit this page"
+msgstr "Редактирайте тази страница"
+
+msgid "By the"
+msgstr "По"
+
+msgid "next page"
+msgstr "Следваща страница"

_static/locales/bn/LC_MESSAGES/booktheme.po

@@ -0,0 +1,63 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: bn\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "পিডিএফ প্রিন্ট করুন"
+
+msgid "Theme by the"
+msgstr "থিম দ্বারা"
+
+msgid "Download source file"
+msgstr "উত্স ফাইল ডাউনলোড করুন"
+
+msgid "open issue"
+msgstr "খোলা সমস্যা"
+
+msgid "previous page"
+msgstr "আগের পৃষ্ঠা"
+
+msgid "Download notebook file"
+msgstr "নোটবুক ফাইল ডাউনলোড করুন"
+
+msgid "Copyright"
+msgstr "কপিরাইট"
+
+msgid "Download this page"
+msgstr "এই পৃষ্ঠাটি ডাউনলোড করুন"
+
+msgid "Source repository"
+msgstr "উত্স সংগ্রহস্থল"
+
+msgid "By"
+msgstr "দ্বারা"
+
+msgid "Last updated on"
+msgstr "সর্বশেষ আপডেট"
+
+msgid "Toggle navigation"
+msgstr "নেভিগেশন টগল করুন"
+
+msgid "Sphinx Book Theme"
+msgstr "স্পিনিক্স বুক থিম"
+
+msgid "Open an issue"
+msgstr "একটি সমস্যা খুলুন"
+
+msgid "Launch"
+msgstr "শুরু করা"
+
+msgid "Edit this page"
+msgstr "এই পৃষ্ঠাটি সম্পাদনা করুন"
+
+msgid "By the"
+msgstr "দ্বারা"
+
+msgid "next page"
+msgstr "পরবর্তী পৃষ্ঠা"

_static/locales/ca/LC_MESSAGES/booktheme.po

@@ -0,0 +1,66 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ca\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Imprimeix a PDF"
+
+msgid "Theme by the"
+msgstr "Tema del"
+
+msgid "Download source file"
+msgstr "Baixeu el fitxer font"
+
+msgid "open issue"
+msgstr "número obert"
+
+msgid "previous page"
+msgstr "Pàgina anterior"
+
+msgid "Download notebook file"
+msgstr "Descarregar fitxer de quadern"
+
+msgid "Copyright"
+msgstr "Copyright"
+
+msgid "Download this page"
+msgstr "Descarregueu aquesta pàgina"
+
+msgid "Source repository"
+msgstr "Dipòsit de fonts"
+
+msgid "By"
+msgstr "Per"
+
+msgid "Last updated on"
+msgstr "Darrera actualització el"
+
+msgid "Toggle navigation"
+msgstr "Commuta la navegació"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema del llibre Esfinx"
+
+msgid "suggest edit"
+msgstr "suggerir edició"
+
+msgid "Open an issue"
+msgstr "Obriu un número"
+
+msgid "Launch"
+msgstr "Llançament"
+
+msgid "Edit this page"
+msgstr "Editeu aquesta pàgina"
+
+msgid "By the"
+msgstr "Per la"
+
+msgid "next page"
+msgstr "pàgina següent"

_static/locales/cs/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: cs\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Tisk do PDF"
+
+msgid "Theme by the"
+msgstr "Téma od"
+
+msgid "Download source file"
+msgstr "Stáhněte si zdrojový soubor"
+
+msgid "open issue"
+msgstr "otevřené číslo"
+
+msgid "Contents"
+msgstr "Obsah"
+
+msgid "previous page"
+msgstr "předchozí stránka"
+
+msgid "Download notebook file"
+msgstr "Stáhnout soubor poznámkového bloku"
+
+msgid "Copyright"
+msgstr "autorská práva"
+
+msgid "Download this page"
+msgstr "Stáhněte si tuto stránku"
+
+msgid "Source repository"
+msgstr "Zdrojové úložiště"
+
+msgid "By"
+msgstr "Podle"
+
+msgid "repository"
+msgstr "úložiště"
+
+msgid "Last updated on"
+msgstr "Naposledy aktualizováno"
+
+msgid "Toggle navigation"
+msgstr "Přepnout navigaci"
+
+msgid "Sphinx Book Theme"
+msgstr "Téma knihy Sfinga"
+
+msgid "suggest edit"
+msgstr "navrhnout úpravy"
+
+msgid "Open an issue"
+msgstr "Otevřete problém"
+
+msgid "Launch"
+msgstr "Zahájení"
+
+msgid "Fullscreen mode"
+msgstr "Režim celé obrazovky"
+
+msgid "Edit this page"
+msgstr "Upravit tuto stránku"
+
+msgid "By the"
+msgstr "Podle"
+
+msgid "next page"
+msgstr "další strana"

_static/locales/da/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: da\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Udskriv til PDF"
+
+msgid "Theme by the"
+msgstr "Tema af"
+
+msgid "Download source file"
+msgstr "Download kildefil"
+
+msgid "open issue"
+msgstr "åbent nummer"
+
+msgid "Contents"
+msgstr "Indhold"
+
+msgid "previous page"
+msgstr "forrige side"
+
+msgid "Download notebook file"
+msgstr "Download notesbog-fil"
+
+msgid "Copyright"
+msgstr "ophavsret"
+
+msgid "Download this page"
+msgstr "Download denne side"
+
+msgid "Source repository"
+msgstr "Kildelager"
+
+msgid "By"
+msgstr "Ved"
+
+msgid "repository"
+msgstr "lager"
+
+msgid "Last updated on"
+msgstr "Sidst opdateret den"
+
+msgid "Toggle navigation"
+msgstr "Skift navigation"
+
+msgid "Sphinx Book Theme"
+msgstr "Sphinx bogtema"
+
+msgid "suggest edit"
+msgstr "foreslå redigering"
+
+msgid "Open an issue"
+msgstr "Åbn et problem"
+
+msgid "Launch"
+msgstr "Start"
+
+msgid "Fullscreen mode"
+msgstr "Fuldskærmstilstand"
+
+msgid "Edit this page"
+msgstr "Rediger denne side"
+
+msgid "By the"
+msgstr "Ved"
+
+msgid "next page"
+msgstr "Næste side"

_static/locales/de/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: de\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "In PDF drucken"
+
+msgid "Theme by the"
+msgstr "Thema von der"
+
+msgid "Download source file"
+msgstr "Quelldatei herunterladen"
+
+msgid "open issue"
+msgstr "offenes Thema"
+
+msgid "Contents"
+msgstr "Inhalt"
+
+msgid "previous page"
+msgstr "vorherige Seite"
+
+msgid "Download notebook file"
+msgstr "Notebook-Datei herunterladen"
+
+msgid "Copyright"
+msgstr "Urheberrechte ©"
+
+msgid "Download this page"
+msgstr "Laden Sie diese Seite herunter"
+
+msgid "Source repository"
+msgstr "Quell-Repository"
+
+msgid "By"
+msgstr "Durch"
+
+msgid "repository"
+msgstr "Repository"
+
+msgid "Last updated on"
+msgstr "Zuletzt aktualisiert am"
+
+msgid "Toggle navigation"
+msgstr "Navigation umschalten"
+
+msgid "Sphinx Book Theme"
+msgstr "Sphinx-Buch-Thema"
+
+msgid "suggest edit"
+msgstr "vorschlagen zu bearbeiten"
+
+msgid "Open an issue"
+msgstr "Öffnen Sie ein Problem"
+
+msgid "Launch"
+msgstr "Starten"
+
+msgid "Fullscreen mode"
+msgstr "Vollbildmodus"
+
+msgid "Edit this page"
+msgstr "Bearbeite diese Seite"
+
+msgid "By the"
+msgstr "Bis zum"
+
+msgid "next page"
+msgstr "Nächste Seite"

_static/locales/el/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: el\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Εκτύπωση σε PDF"
+
+msgid "Theme by the"
+msgstr "Θέμα από το"
+
+msgid "Download source file"
+msgstr "Λήψη αρχείου προέλευσης"
+
+msgid "open issue"
+msgstr "ανοιχτό ζήτημα"
+
+msgid "Contents"
+msgstr "Περιεχόμενα"
+
+msgid "previous page"
+msgstr "προηγούμενη σελίδα"
+
+msgid "Download notebook file"
+msgstr "Λήψη αρχείου σημειωματάριου"
+
+msgid "Copyright"
+msgstr "Πνευματική ιδιοκτησία"
+
+msgid "Download this page"
+msgstr "Λήψη αυτής της σελίδας"
+
+msgid "Source repository"
+msgstr "Αποθήκη πηγής"
+
+msgid "By"
+msgstr "Με"
+
+msgid "repository"
+msgstr "αποθήκη"
+
+msgid "Last updated on"
+msgstr "Τελευταία ενημέρωση στις"
+
+msgid "Toggle navigation"
+msgstr "Εναλλαγή πλοήγησης"
+
+msgid "Sphinx Book Theme"
+msgstr "Θέμα βιβλίου Sphinx"
+
+msgid "suggest edit"
+msgstr "προτείνω επεξεργασία"
+
+msgid "Open an issue"
+msgstr "Ανοίξτε ένα ζήτημα"
+
+msgid "Launch"
+msgstr "Εκτόξευση"
+
+msgid "Fullscreen mode"
+msgstr "ΛΕΙΤΟΥΡΓΙΑ ΠΛΗΡΟΥΣ ΟΘΟΝΗΣ"
+
+msgid "Edit this page"
+msgstr "Επεξεργαστείτε αυτήν τη σελίδα"
+
+msgid "By the"
+msgstr "Από το"
+
+msgid "next page"
+msgstr "επόμενη σελίδα"

_static/locales/eo/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: eo\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Presi al PDF"
+
+msgid "Theme by the"
+msgstr "Temo de la"
+
+msgid "Download source file"
+msgstr "Elŝutu fontodosieron"
+
+msgid "open issue"
+msgstr "malferma numero"
+
+msgid "Contents"
+msgstr "Enhavo"
+
+msgid "previous page"
+msgstr "antaŭa paĝo"
+
+msgid "Download notebook file"
+msgstr "Elŝutu kajeran dosieron"
+
+msgid "Copyright"
+msgstr "Kopirajto"
+
+msgid "Download this page"
+msgstr "Elŝutu ĉi tiun paĝon"
+
+msgid "Source repository"
+msgstr "Fonto-deponejo"
+
+msgid "By"
+msgstr "De"
+
+msgid "repository"
+msgstr "deponejo"
+
+msgid "Last updated on"
+msgstr "Laste ĝisdatigita la"
+
+msgid "Toggle navigation"
+msgstr "Ŝalti navigadon"
+
+msgid "Sphinx Book Theme"
+msgstr "Sfinksa Libro-Temo"
+
+msgid "suggest edit"
+msgstr "sugesti redaktadon"
+
+msgid "Open an issue"
+msgstr "Malfermu numeron"
+
+msgid "Launch"
+msgstr "Lanĉo"
+
+msgid "Fullscreen mode"
+msgstr "Plenekrana reĝimo"
+
+msgid "Edit this page"
+msgstr "Redaktu ĉi tiun paĝon"
+
+msgid "By the"
+msgstr "Per la"
+
+msgid "next page"
+msgstr "sekva paĝo"

_static/locales/es/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: es\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Imprimir en PDF"
+
+msgid "Theme by the"
+msgstr "Tema por el"
+
+msgid "Download source file"
+msgstr "Descargar archivo fuente"
+
+msgid "open issue"
+msgstr "Tema abierto"
+
+msgid "Contents"
+msgstr "Contenido"
+
+msgid "previous page"
+msgstr "pagina anterior"
+
+msgid "Download notebook file"
+msgstr "Descargar archivo de cuaderno"
+
+msgid "Copyright"
+msgstr "Derechos de autor"
+
+msgid "Download this page"
+msgstr "Descarga esta pagina"
+
+msgid "Source repository"
+msgstr "Repositorio de origen"
+
+msgid "By"
+msgstr "Por"
+
+msgid "repository"
+msgstr "repositorio"
+
+msgid "Last updated on"
+msgstr "Ultima actualización en"
+
+msgid "Toggle navigation"
+msgstr "Navegación de palanca"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema del libro de la esfinge"
+
+msgid "suggest edit"
+msgstr "sugerir editar"
+
+msgid "Open an issue"
+msgstr "Abrir un problema"
+
+msgid "Launch"
+msgstr "Lanzamiento"
+
+msgid "Fullscreen mode"
+msgstr "Modo de pantalla completa"
+
+msgid "Edit this page"
+msgstr "Edita esta página"
+
+msgid "By the"
+msgstr "Por el"
+
+msgid "next page"
+msgstr "siguiente página"

_static/locales/et/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: et\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Prindi PDF-i"
+
+msgid "Theme by the"
+msgstr "Teema"
+
+msgid "Download source file"
+msgstr "Laadige alla lähtefail"
+
+msgid "open issue"
+msgstr "avatud küsimus"
+
+msgid "Contents"
+msgstr "Sisu"
+
+msgid "previous page"
+msgstr "eelmine leht"
+
+msgid "Download notebook file"
+msgstr "Laadige sülearvuti fail alla"
+
+msgid "Copyright"
+msgstr "Autoriõigus"
+
+msgid "Download this page"
+msgstr "Laadige see leht alla"
+
+msgid "Source repository"
+msgstr "Allikahoidla"
+
+msgid "By"
+msgstr "Kõrval"
+
+msgid "repository"
+msgstr "hoidla"
+
+msgid "Last updated on"
+msgstr "Viimati uuendatud"
+
+msgid "Toggle navigation"
+msgstr "Lülita navigeerimine sisse"
+
+msgid "Sphinx Book Theme"
+msgstr "Sfinksiraamatu teema"
+
+msgid "suggest edit"
+msgstr "soovita muuta"
+
+msgid "Open an issue"
+msgstr "Avage probleem"
+
+msgid "Launch"
+msgstr "Käivitage"
+
+msgid "Fullscreen mode"
+msgstr "Täisekraanirežiim"
+
+msgid "Edit this page"
+msgstr "Muutke seda lehte"
+
+msgid "By the"
+msgstr "Autor"
+
+msgid "next page"
+msgstr "järgmine leht"

_static/locales/fi/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: fi\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Tulosta PDF-tiedostoon"
+
+msgid "Theme by the"
+msgstr "Teeman tekijä"
+
+msgid "Download source file"
+msgstr "Lataa lähdetiedosto"
+
+msgid "open issue"
+msgstr "avoin ongelma"
+
+msgid "Contents"
+msgstr "Sisällys"
+
+msgid "previous page"
+msgstr "Edellinen sivu"
+
+msgid "Download notebook file"
+msgstr "Lataa muistikirjatiedosto"
+
+msgid "Copyright"
+msgstr "Tekijänoikeus"
+
+msgid "Download this page"
+msgstr "Lataa tämä sivu"
+
+msgid "Source repository"
+msgstr "Lähteen arkisto"
+
+msgid "By"
+msgstr "Tekijä"
+
+msgid "repository"
+msgstr "arkisto"
+
+msgid "Last updated on"
+msgstr "Viimeksi päivitetty"
+
+msgid "Toggle navigation"
+msgstr "Vaihda navigointia"
+
+msgid "Sphinx Book Theme"
+msgstr "Sphinx-kirjan teema"
+
+msgid "suggest edit"
+msgstr "ehdottaa muokkausta"
+
+msgid "Open an issue"
+msgstr "Avaa ongelma"
+
+msgid "Launch"
+msgstr "Tuoda markkinoille"
+
+msgid "Fullscreen mode"
+msgstr "Koko näytön tila"
+
+msgid "Edit this page"
+msgstr "Muokkaa tätä sivua"
+
+msgid "By the"
+msgstr "Mukaan"
+
+msgid "next page"
+msgstr "seuraava sivu"

_static/locales/fr/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: fr\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Imprimer au format PDF"
+
+msgid "Theme by the"
+msgstr "Thème par le"
+
+msgid "Download source file"
+msgstr "Télécharger le fichier source"
+
+msgid "open issue"
+msgstr "signaler un problème"
+
+msgid "Contents"
+msgstr "Contenu"
+
+msgid "previous page"
+msgstr "page précédente"
+
+msgid "Download notebook file"
+msgstr "Télécharger le fichier notebook"
+
+msgid "Copyright"
+msgstr "droits d'auteur"
+
+msgid "Download this page"
+msgstr "Téléchargez cette page"
+
+msgid "Source repository"
+msgstr "Dépôt source"
+
+msgid "By"
+msgstr "Par"
+
+msgid "repository"
+msgstr "dépôt"
+
+msgid "Last updated on"
+msgstr "Dernière mise à jour le"
+
+msgid "Toggle navigation"
+msgstr "Basculer la navigation"
+
+msgid "Sphinx Book Theme"
+msgstr "Thème du livre Sphinx"
+
+msgid "suggest edit"
+msgstr "suggestion de modification"
+
+msgid "Open an issue"
+msgstr "Ouvrez un problème"
+
+msgid "Launch"
+msgstr "lancement"
+
+msgid "Fullscreen mode"
+msgstr "Mode plein écran"
+
+msgid "Edit this page"
+msgstr "Modifier cette page"
+
+msgid "By the"
+msgstr "Par le"
+
+msgid "next page"
+msgstr "page suivante"

_static/locales/hr/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: hr\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Ispis u PDF"
+
+msgid "Theme by the"
+msgstr "Tema autora"
+
+msgid "Download source file"
+msgstr "Preuzmi izvornu datoteku"
+
+msgid "open issue"
+msgstr "otvoreno izdanje"
+
+msgid "Contents"
+msgstr "Sadržaj"
+
+msgid "previous page"
+msgstr "Prethodna stranica"
+
+msgid "Download notebook file"
+msgstr "Preuzmi datoteku bilježnice"
+
+msgid "Copyright"
+msgstr "Autorska prava"
+
+msgid "Download this page"
+msgstr "Preuzmite ovu stranicu"
+
+msgid "Source repository"
+msgstr "Izvorno spremište"
+
+msgid "By"
+msgstr "Po"
+
+msgid "repository"
+msgstr "spremište"
+
+msgid "Last updated on"
+msgstr "Posljednje ažuriranje:"
+
+msgid "Toggle navigation"
+msgstr "Uključi / isključi navigaciju"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema knjige Sphinx"
+
+msgid "suggest edit"
+msgstr "predloži uređivanje"
+
+msgid "Open an issue"
+msgstr "Otvorite izdanje"
+
+msgid "Launch"
+msgstr "Pokrenite"
+
+msgid "Fullscreen mode"
+msgstr "Način preko cijelog zaslona"
+
+msgid "Edit this page"
+msgstr "Uredite ovu stranicu"
+
+msgid "By the"
+msgstr "Od strane"
+
+msgid "next page"
+msgstr "sljedeća stranica"

_static/locales/id/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: id\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Cetak ke PDF"
+
+msgid "Theme by the"
+msgstr "Tema oleh"
+
+msgid "Download source file"
+msgstr "Unduh file sumber"
+
+msgid "open issue"
+msgstr "masalah terbuka"
+
+msgid "Contents"
+msgstr "Isi"
+
+msgid "previous page"
+msgstr "halaman sebelumnya"
+
+msgid "Download notebook file"
+msgstr "Unduh file notebook"
+
+msgid "Copyright"
+msgstr "hak cipta"
+
+msgid "Download this page"
+msgstr "Unduh halaman ini"
+
+msgid "Source repository"
+msgstr "Repositori sumber"
+
+msgid "By"
+msgstr "Oleh"
+
+msgid "repository"
+msgstr "gudang"
+
+msgid "Last updated on"
+msgstr "Terakhir diperbarui saat"
+
+msgid "Toggle navigation"
+msgstr "Alihkan navigasi"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema Buku Sphinx"
+
+msgid "suggest edit"
+msgstr "menyarankan edit"
+
+msgid "Open an issue"
+msgstr "Buka masalah"
+
+msgid "Launch"
+msgstr "Meluncurkan"
+
+msgid "Fullscreen mode"
+msgstr "Mode layar penuh"
+
+msgid "Edit this page"
+msgstr "Edit halaman ini"
+
+msgid "By the"
+msgstr "Oleh"
+
+msgid "next page"
+msgstr "halaman selanjutnya"

_static/locales/it/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: it\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Stampa in PDF"
+
+msgid "Theme by the"
+msgstr "Tema di"
+
+msgid "Download source file"
+msgstr "Scarica il file sorgente"
+
+msgid "open issue"
+msgstr "questione aperta"
+
+msgid "Contents"
+msgstr "Contenuti"
+
+msgid "previous page"
+msgstr "pagina precedente"
+
+msgid "Download notebook file"
+msgstr "Scarica il file del taccuino"
+
+msgid "Copyright"
+msgstr "Diritto d'autore"
+
+msgid "Download this page"
+msgstr "Scarica questa pagina"
+
+msgid "Source repository"
+msgstr "Repository di origine"
+
+msgid "By"
+msgstr "Di"
+
+msgid "repository"
+msgstr "repository"
+
+msgid "Last updated on"
+msgstr "Ultimo aggiornamento il"
+
+msgid "Toggle navigation"
+msgstr "Attiva / disattiva la navigazione"
+
+msgid "Sphinx Book Theme"
+msgstr "Tema del libro della Sfinge"
+
+msgid "suggest edit"
+msgstr "suggerisci modifica"
+
+msgid "Open an issue"
+msgstr "Apri un problema"
+
+msgid "Launch"
+msgstr "Lanciare"
+
+msgid "Fullscreen mode"
+msgstr "Modalità schermo intero"
+
+msgid "Edit this page"
+msgstr "Modifica questa pagina"
+
+msgid "By the"
+msgstr "Dal"
+
+msgid "next page"
+msgstr "pagina successiva"

_static/locales/iw/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: iw\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "הדפס לקובץ PDF"
+
+msgid "Theme by the"
+msgstr "נושא מאת"
+
+msgid "Download source file"
+msgstr "הורד את קובץ המקור"
+
+msgid "open issue"
+msgstr "בעיה פתוחה"
+
+msgid "Contents"
+msgstr "תוכן"
+
+msgid "previous page"
+msgstr "עמוד קודם"
+
+msgid "Download notebook file"
+msgstr "הורד קובץ מחברת"
+
+msgid "Copyright"
+msgstr "זכויות יוצרים"
+
+msgid "Download this page"
+msgstr "הורד דף זה"
+
+msgid "Source repository"
+msgstr "מאגר המקורות"
+
+msgid "By"
+msgstr "על ידי"
+
+msgid "repository"
+msgstr "מאגר"
+
+msgid "Last updated on"
+msgstr "עודכן לאחרונה ב"
+
+msgid "Toggle navigation"
+msgstr "החלף ניווט"
+
+msgid "Sphinx Book Theme"
+msgstr "נושא ספר ספינקס"
+
+msgid "suggest edit"
+msgstr "מציע לערוך"
+
+msgid "Open an issue"
+msgstr "פתח גיליון"
+
+msgid "Launch"
+msgstr "לְהַשִׁיק"
+
+msgid "Fullscreen mode"
+msgstr "מצב מסך מלא"
+
+msgid "Edit this page"
+msgstr "ערוך דף זה"
+
+msgid "By the"
+msgstr "דרך"
+
+msgid "next page"
+msgstr "עמוד הבא"

_static/locales/ja/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ja\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "PDFに印刷"
+
+msgid "Theme by the"
+msgstr "のテーマ"
+
+msgid "Download source file"
+msgstr "ソースファイルをダウンロード"
+
+msgid "open issue"
+msgstr "未解決の問題"
+
+msgid "Contents"
+msgstr "目次"
+
+msgid "previous page"
+msgstr "前のページ"
+
+msgid "Download notebook file"
+msgstr "ノートブックファイルをダウンロード"
+
+msgid "Copyright"
+msgstr "Copyright"
+
+msgid "Download this page"
+msgstr "このページをダウンロード"
+
+msgid "Source repository"
+msgstr "ソースリポジトリ"
+
+msgid "By"
+msgstr "著者"
+
+msgid "repository"
+msgstr "リポジトリ"
+
+msgid "Last updated on"
+msgstr "最終更新日"
+
+msgid "Toggle navigation"
+msgstr "ナビゲーションを切り替え"
+
+msgid "Sphinx Book Theme"
+msgstr "スフィンクスの本のテーマ"
+
+msgid "suggest edit"
+msgstr "編集を提案する"
+
+msgid "Open an issue"
+msgstr "問題を報告"
+
+msgid "Launch"
+msgstr "起動"
+
+msgid "Fullscreen mode"
+msgstr "全画面モード"
+
+msgid "Edit this page"
+msgstr "このページを編集"
+
+msgid "By the"
+msgstr "によって"
+
+msgid "next page"
+msgstr "次のページ"

_static/locales/ko/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ko\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "PDF로 인쇄"
+
+msgid "Theme by the"
+msgstr "테마별"
+
+msgid "Download source file"
+msgstr "소스 파일 다운로드"
+
+msgid "open issue"
+msgstr "열린 문제"
+
+msgid "Contents"
+msgstr "내용"
+
+msgid "previous page"
+msgstr "이전 페이지"
+
+msgid "Download notebook file"
+msgstr "노트북 파일 다운로드"
+
+msgid "Copyright"
+msgstr "저작권"
+
+msgid "Download this page"
+msgstr "이 페이지 다운로드"
+
+msgid "Source repository"
+msgstr "소스 저장소"
+
+msgid "By"
+msgstr "으로"
+
+msgid "repository"
+msgstr "저장소"
+
+msgid "Last updated on"
+msgstr "마지막 업데이트"
+
+msgid "Toggle navigation"
+msgstr "탐색 전환"
+
+msgid "Sphinx Book Theme"
+msgstr "스핑크스 도서 테마"
+
+msgid "suggest edit"
+msgstr "편집 제안"
+
+msgid "Open an issue"
+msgstr "이슈 열기"
+
+msgid "Launch"
+msgstr "시작하다"
+
+msgid "Fullscreen mode"
+msgstr "전체 화면으로보기"
+
+msgid "Edit this page"
+msgstr "이 페이지 편집"
+
+msgid "By the"
+msgstr "에 의해"
+
+msgid "next page"
+msgstr "다음 페이지"

_static/locales/lt/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: lt\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Spausdinti į PDF"
+
+msgid "Theme by the"
+msgstr "Tema"
+
+msgid "Download source file"
+msgstr "Atsisiųsti šaltinio failą"
+
+msgid "open issue"
+msgstr "atviras klausimas"
+
+msgid "Contents"
+msgstr "Turinys"
+
+msgid "previous page"
+msgstr "Ankstesnis puslapis"
+
+msgid "Download notebook file"
+msgstr "Atsisiųsti nešiojamojo kompiuterio failą"
+
+msgid "Copyright"
+msgstr "Autorių teisės"
+
+msgid "Download this page"
+msgstr "Atsisiųskite šį puslapį"
+
+msgid "Source repository"
+msgstr "Šaltinio saugykla"
+
+msgid "By"
+msgstr "Iki"
+
+msgid "repository"
+msgstr "saugykla"
+
+msgid "Last updated on"
+msgstr "Paskutinį kartą atnaujinta"
+
+msgid "Toggle navigation"
+msgstr "Perjungti naršymą"
+
+msgid "Sphinx Book Theme"
+msgstr "Sfinkso knygos tema"
+
+msgid "suggest edit"
+msgstr "pasiūlyti redaguoti"
+
+msgid "Open an issue"
+msgstr "Atidarykite problemą"
+
+msgid "Launch"
+msgstr "Paleiskite"
+
+msgid "Fullscreen mode"
+msgstr "Pilno ekrano režimas"
+
+msgid "Edit this page"
+msgstr "Redaguoti šį puslapį"
+
+msgid "By the"
+msgstr "Prie"
+
+msgid "next page"
+msgstr "Kitas puslapis"

_static/locales/lv/LC_MESSAGES/booktheme.po

@@ -0,0 +1,75 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: lv\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "Drukāt PDF formātā"
+
+msgid "Theme by the"
+msgstr "Autora tēma"
+
+msgid "Download source file"
+msgstr "Lejupielādēt avota failu"
+
+msgid "open issue"
+msgstr "atklāts jautājums"
+
+msgid "Contents"
+msgstr "Saturs"
+
+msgid "previous page"
+msgstr "iepriekšējā lapa"
+
+msgid "Download notebook file"
+msgstr "Lejupielādēt piezīmju grāmatiņu"
+
+msgid "Copyright"
+msgstr "Autortiesības"
+
+msgid "Download this page"
+msgstr "Lejupielādējiet šo lapu"
+
+msgid "Source repository"
+msgstr "Avota krātuve"
+
+msgid "By"
+msgstr "Autors"
+
+msgid "repository"
+msgstr "krātuve"
+
+msgid "Last updated on"
+msgstr "Pēdējoreiz atjaunināts"
+
+msgid "Toggle navigation"
+msgstr "Pārslēgt navigāciju"
+
+msgid "Sphinx Book Theme"
+msgstr "Sfinksa grāmatas tēma"
+
+msgid "suggest edit"
+msgstr "ieteikt rediģēt"
+
+msgid "Open an issue"
+msgstr "Atveriet problēmu"
+
+msgid "Launch"
+msgstr "Uzsākt"
+
+msgid "Fullscreen mode"
+msgstr "Pilnekrāna režīms"
+
+msgid "Edit this page"
+msgstr "Rediģēt šo lapu"
+
+msgid "By the"
+msgstr "Ar"
+
+msgid "next page"
+msgstr "nākamā lapaspuse"

_static/locales/ml/LC_MESSAGES/booktheme.po

@@ -0,0 +1,66 @@
+
+msgid ""
+msgstr ""
+"Project-Id-Version: Sphinx-Book-Theme\n"
+"MIME-Version: 1.0\n"
+"Content-Type: text/plain; charset=UTF-8\n"
+"Content-Transfer-Encoding: 8bit\n"
+"Language: ml\n"
+"Plural-Forms: nplurals=2; plural=(n != 1);\n"
+
+msgid "Print to PDF"
+msgstr "PDF- ലേക്ക് പ്രിന്റുചെയ്യുക"
+
+msgid "Theme by the"
+msgstr "പ്രമേയം"
+
+msgid "Download source file"
+msgstr "ഉറവിട ഫയൽ ഡൗൺലോഡുചെയ്യുക"
+
+msgid "open issue"
+msgstr "തുറന്ന പ്രശ്നം"
+
+msgid "previous page"
+msgstr "മുൻപത്തെ താൾ"
+
+msgid "Download notebook file"
+msgstr "നോട്ട്ബുക്ക് ഫയൽ ഡൺലോഡ് ചെയ്യുക"
+
+msgid "Copyright"
+msgstr "പകർപ്പവകാശം"
+
+msgid "Download this page"
+msgstr "ഈ പേജ് ഡൗൺലോഡുചെയ്യുക"
+
+msgid "Source repository"
+msgstr "ഉറവിട ശേഖരം"
+
+msgid "By"
+msgstr "എഴുതിയത്"
+
+msgid "Last updated on"
+msgstr "അവസാനം അപ്‌ഡേറ്റുചെയ്‌തത്"
+
+msgid "Toggle navigation"
+msgstr "നാവിഗേഷൻ ടോഗിൾ ചെയ്യുക"
+
+msgid "Sphinx Book Theme"
+msgstr "സ്ഫിങ്ക്സ് പുസ്തക തീം"
+
+msgid "suggest edit"
+msgstr "എഡിറ്റുചെയ്യാൻ നിർദ്ദേശിക്കുക"
+
+msgid "Open an issue"
+msgstr "ഒരു പ്രശ്നം തുറക്കുക"
+
+msgid "Launch"
+msgstr "സമാരംഭിക്കുക"
+
+msgid "Edit this page"
+msgstr "ഈ പേജ് എഡിറ്റുചെയ്യുക"
+
+msgid "By the"
+msgstr "എഴുതിയത്"
+
+msgid "next page"
+msgstr "അടുത്ത പേജ്"