# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from typing import AsyncGenerator, AsyncIterator, Callable, Dict, List, Optional

def log_message(level: str, message: str, module: str, file: str, line: int) -> None:
    """
    Log a message from Python with file and line info
    """
    ...

class JsonLike:
    """
    Any PyObject which can be serialized to JSON
    """

    ...

RequestHandler = Callable[[JsonLike], AsyncGenerator[JsonLike, None]]

class DistributedRuntime:
    """
    The runtime object for dynamo applications
    """

    ...

    def namespace(self, name: str, path: str) -> Namespace:
        """
        Create a `Namespace` object
        """
        ...

    def etcd_client(self) -> Optional[EtcdClient]:
        """
        Get the `EtcdClient` object. Not available for static workers.
        """
        ...

class EtcdClient:
    """
    Etcd is used for discovery in the DistributedRuntime
    """

    async def kv_create_or_validate(
        self, key: str, value: bytes, lease_id: Optional[int] = None
    ) -> None:
        """
        Atomically create a key if it does not exist, or validate the values are identical if the key exists.
        """
        ...

    async def kv_put(
        self, key: str, value: bytes, lease_id: Optional[int] = None
    ) -> None:
        """
        Put a key-value pair into etcd
        """
        ...

    async def kv_get_prefix(self, prefix: str) -> List[Dict[str, JsonLike]]:
        """
        Get all keys with a given prefix
        """
        ...

class Namespace:
    """
    A namespace is a collection of components
    """

    ...

    def component(self, name: str) -> Component:
        """
        Create a `Component` object
        """
        ...

class Component:
    """
    A component is a collection of endpoints
    """

    ...

    def create_service(self) -> None:
        """
        Create a service
        """
        ...

    def endpoint(self, name: str) -> Endpoint:
        """
        Create an endpoint
        """
        ...

class Endpoint:
    """
    An Endpoint is a single API endpoint
    """

    ...

    async def serve_endpoint(self, handler: RequestHandler) -> None:
        """
        Serve an endpoint discoverable by all connected clients at
        `{{ namespace }}/components/{{ component_name }}/endpoints/{{ endpoint_name }}`
        """
        ...

    async def client(self) -> Client:
        """
        Create a `Client` capable of calling served instances of this endpoint
        """
        ...

    async def lease_id(self) -> int:
        """
        Return primary lease id. Currently, cannot set a different lease id.
        """
        ...

class Client:
    """
    A client capable of calling served instances of an endpoint
    """

    ...

    async def random(self, request: JsonLike) -> AsyncIterator[JsonLike]:
        """
        Pick a random instance of the endpoint and issue the request
        """
        ...

    async def round_robin(self, request: JsonLike) -> AsyncIterator[JsonLike]:
        """
        Pick the next instance of the endpoint in a round-robin fashion
        """
        ...

    async def direct(self, request: JsonLike, instance: str) -> AsyncIterator[JsonLike]:
        """
        Pick a specific instance of the endpoint
        """
        ...

class KvRouter:
    """
    A router will determine which worker should handle a given request.
    """

    ...

    def __init__(self, drt: DistributedRuntime, component: Component) -> None:
        """
        Create a `KvRouter` object that is associated with the `component`
        """

    def schedule(self, token_ids: List[int], lora_id: int) -> int:
        """
        Return the worker id that should handle the given token ids,
        exception will be raised if there is no worker available.
        """
        ...

class DisaggregatedRouter:
    """
    A router that determines whether to perform prefill locally or remotely based on
    sequence length thresholds.
    """

    def __init__(
        self,
        drt: DistributedRuntime,
        model_name: str,
        default_max_local_prefill_length: int,
    ) -> None:
        """
        Create a `DisaggregatedRouter` object.

        Args:
            drt: The distributed runtime instance
            model_name: Name of the model
            default_max_local_prefill_length: Default maximum sequence length that can be processed locally
        """
        ...

    def prefill_remote(self, prefill_length: int, prefix_hit_length: int) -> bool:
        """
        Determine if prefill should be performed remotely based on sequence lengths.

        Args:
            prefill_length: Total length of the sequence to prefill
            prefix_hit_length: Length of the prefix that was already processed

        Returns:
            True if prefill should be performed remotely, False otherwise
        """
        ...

    def update_value(self, max_local_prefill_length: int) -> None:
        """
        Update the maximum local prefill length threshold.

        Args:
            max_local_prefill_length: New maximum sequence length that can be processed locally
        """
        ...

    def get_model_name(self) -> str:
        """
        Get the name of the model associated with this router.

        Returns:
            The model name as a string
        """
        ...

class KvMetricsPublisher:
    """
    A metrics publisher will provide KV metrics to the router.
    """

    ...

    def __init__(self) -> None:
        """
        Create a `KvMetricsPublisher` object
        """

    def create_service(self, component: Component) -> None:
        """
        Similar to Component.create_service, but only service created through
        this method will interact with KV router of the same component.
        """

    def publish(
        self,
        request_active_slots: int,
        request_total_slots: int,
        kv_active_blocks: int,
        kv_total_blocks: int,
    ) -> None:
        """
        Update the KV metrics being reported.
        """
        ...

class ModelDeploymentCard:
    """
    A model deployment card is a collection of model information
    """

    ...

class OAIChatPreprocessor:
    """
    A preprocessor for OpenAI chat completions
    """

    ...

    async def start(self) -> None:
        """
        Start the preprocessor
        """
        ...

class Backend:
    """
    LLM Backend engine manages resources and concurrency for executing inference
    requests in LLM engines (trtllm, vllm, sglang etc)
    """

    ...

    async def start(self, handler: RequestHandler) -> None:
        """
        Start the backend engine and requests to the downstream LLM engine
        """
        ...

class OverlapScores:
    """
    A collection of prefix matching scores of workers for a given token ids.
    'scores' is a map of worker id to the score which is the number of matching blocks.
    """

    ...

class KvIndexer:
    """
    A KV Indexer that tracks KV Events emitted by workers. Events include add_block and remove_block.
    """

    ...

    def __init__(self, component: Component, block_size: int) -> None:
        """
        Create a `KvIndexer` object
        """

    def find_matches_for_request(
        self, token_ids: List[int], lora_id: int
    ) -> OverlapScores:
        """
        Return the overlapping scores of workers for the given token ids.
        """
        ...

    def block_size(self) -> int:
        """
        Return the block size of the KV Indexer.
        """
        ...

class KvRecorder:
    """
    A recorder for KV Router events.
    """

    ...

    def __init__(
        self,
        component: Component,
        output_path: Optional[str] = None,
        max_lines_per_file: Optional[int] = None,
        max_count: Optional[int] = None,
        max_time: Optional[float] = None,
    ) -> None:
        """
        Create a new KvRecorder instance.

        Args:
            component: The component to associate with this recorder
            output_path: Path to the JSONL file to write events to
            max_lines_per_file: Maximum number of lines per file before rotating to a new file
            max_count: Maximum number of events to record before shutting down
            max_time: Maximum duration in seconds to record before shutting down
        """
        ...

    def event_count(self) -> int:
        """
        Get the count of recorded events.

        Returns:
            The number of events recorded
        """
        ...

    def elapsed_time(self) -> float:
        """
        Get the elapsed time since the recorder was started.

        Returns:
            The elapsed time in seconds as a float
        """
        ...

    def replay_events(
        self,
        indexer: KvIndexer,
        timed: bool = False,
        max_count: Optional[int] = None,
        max_time: Optional[float] = None,
    ) -> int:
        """
        Populate an indexer with the recorded events.

        Args:
            indexer: The KvIndexer to populate with events
            timed: If true, events will be sent according to their recorded timestamps.
                If false, events will be sent without any delay in between.
            max_count: Maximum number of events to send before stopping
            max_time: Maximum duration in seconds to send events before stopping

        Returns:
            The number of events sent to the indexer
        """
        ...

    def shutdown(self) -> None:
        """
        Shutdown the recorder.
        """
        ...

class AggregatedMetrics:
    """
    A collection of metrics of the endpoints
    """

    ...

class KvMetricsAggregator:
    """
    A metrics aggregator will collect KV metrics of the endpoints.
    """

    ...

    def __init__(self, component: Component) -> None:
        """
        Create a `KvMetricsAggregator` object
        """

    def get_metrics(self) -> AggregatedMetrics:
        """
        Return the aggregated metrics of the endpoints.
        """
        ...

class KvEventPublisher:
    """
    A KV event publisher will publish KV events corresponding to the component.
    """

    ...

    def __init__(
        self, component: Component, worker_id: int, kv_block_size: int
    ) -> None:
        """
        Create a `KvEventPublisher` object
        """

    def publish_stored(
        self,
        event_id,
        int,
        token_ids: List[int],
        num_block_tokens: List[int],
        block_hashes: List[int],
        lora_id: int,
        parent_hash: Optional[int] = None,
    ) -> None:
        """
        Publish a KV stored event.
        """
        ...

    def publish_removed(self, event_id, int, block_hashes: List[int]) -> None:
        """
        Publish a KV removed event.
        """
        ...

class HttpService:
    """
    A HTTP service for dynamo applications.
    It is a OpenAI compatible http ingress into the Dynamo Distributed Runtime.
    """

    ...

class HttpError:
    """
    An error that occurred in the HTTP service
    """

    ...

class HttpAsyncEngine:
    """
    An async engine for a distributed Dynamo http service. This is an extension of the
    python based AsyncEngine that handles HttpError exceptions from Python and
    converts them to the Rust version of HttpError
    """

    ...
