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"""This module contains the EndpointV3Compatibility class, which is used to connect to Gradio apps running 3.x.x versions of Gradio."""
from __future__ import annotations
import json
from pathlib import Path
from typing import TYPE_CHECKING, Any, Literal
import httpx
import huggingface_hub
import websockets
from packaging import version
from gradio_client import serializing, utils
from gradio_client.exceptions import SerializationSetupError
from gradio_client.utils import (
Communicator,
)
if TYPE_CHECKING:
from gradio_client import Client
class EndpointV3Compatibility:
"""Endpoint class for connecting to v3 endpoints. Backwards compatibility."""
def __init__(self, client: Client, fn_index: int, dependency: dict, *_args):
self.client: Client = client
self.fn_index = fn_index
self.dependency = dependency
api_name = dependency.get("api_name")
self.api_name: str | Literal[False] | None = (
"/" + api_name if isinstance(api_name, str) else api_name
)
self.use_ws = self._use_websocket(self.dependency)
self.protocol = "ws" if self.use_ws else "http"
self.input_component_types = []
self.output_component_types = []
self.root_url = client.src + "/" if not client.src.endswith("/") else client.src
self.is_continuous = dependency.get("types", {}).get("continuous", False)
try:
# Only a real API endpoint if backend_fn is True (so not just a frontend function), serializers are valid,
# and api_name is not False (meaning that the developer has explicitly disabled the API endpoint)
self.serializers, self.deserializers = self._setup_serializers()
self.is_valid = self.dependency["backend_fn"] and self.api_name is not False
except SerializationSetupError:
self.is_valid = False
self.backend_fn = dependency.get("backend_fn")
self.show_api = True
def __repr__(self):
return f"Endpoint src: {self.client.src}, api_name: {self.api_name}, fn_index: {self.fn_index}"
def __str__(self):
return self.__repr__()
def make_end_to_end_fn(self, helper: Communicator | None = None):
_predict = self.make_predict(helper)
def _inner(*data):
if not self.is_valid:
raise utils.InvalidAPIEndpointError()
data = self.insert_state(*data)
if self.client.upload_files:
data = self.serialize(*data)
predictions = _predict(*data)
predictions = self.process_predictions(*predictions)
# Append final output only if not already present
# for consistency between generators and not generators
if helper:
with helper.lock:
if not helper.job.outputs:
helper.job.outputs.append(predictions)
return predictions
return _inner
def make_cancel(self, helper: Communicator | None = None): # noqa: ARG002 (needed so that both endpoints classes have the same api)
return None
def make_predict(self, helper: Communicator | None = None):
def _predict(*data) -> tuple:
data = json.dumps(
{
"data": data,
"fn_index": self.fn_index,
"session_hash": self.client.session_hash,
}
)
hash_data = json.dumps(
{
"fn_index": self.fn_index,
"session_hash": self.client.session_hash,
}
)
if self.use_ws:
result = utils.synchronize_async(self._ws_fn, data, hash_data, helper)
if "error" in result:
raise ValueError(result["error"])
else:
response = httpx.post(
self.client.api_url,
headers=self.client.headers,
json=data,
verify=self.client.ssl_verify,
)
result = json.loads(response.content.decode("utf-8"))
try:
output = result["data"]
except KeyError as ke:
is_public_space = (
self.client.space_id
and not huggingface_hub.space_info(self.client.space_id).private
)
if "error" in result and "429" in result["error"] and is_public_space:
raise utils.TooManyRequestsError(
f"Too many requests to the API, please try again later. To avoid being rate-limited, "
f"please duplicate the Space using Client.duplicate({self.client.space_id}) "
f"and pass in your Hugging Face token."
) from None
elif "error" in result:
raise ValueError(result["error"]) from None
raise KeyError(
f"Could not find 'data' key in response. Response received: {result}"
) from ke
return tuple(output)
return _predict
def _predict_resolve(self, *data) -> Any:
"""Needed for gradio.load(), which has a slightly different signature for serializing/deserializing"""
outputs = self.make_predict()(*data)
if len(self.dependency["outputs"]) == 1:
return outputs[0]
return outputs
def _upload(
self, file_paths: list[str | list[str]]
) -> list[str | list[str]] | list[dict[str, Any] | list[dict[str, Any]]]:
if not file_paths:
return []
# Put all the filepaths in one file
# but then keep track of which index in the
# original list they came from so we can recreate
# the original structure
files = []
indices = []
for i, fs in enumerate(file_paths):
if not isinstance(fs, list):
fs = [fs]
for f in fs:
files.append(("files", (Path(f).name, open(f, "rb")))) # noqa: SIM115
indices.append(i)
r = httpx.post(
self.client.upload_url,
headers=self.client.headers,
files=files,
verify=self.client.ssl_verify,
)
if r.status_code != 200:
uploaded = file_paths
else:
uploaded = []
result = r.json()
for i, fs in enumerate(file_paths):
if isinstance(fs, list):
output = [o for ix, o in enumerate(result) if indices[ix] == i]
res = [
{
"is_file": True,
"name": o,
"orig_name": Path(f).name,
"data": None,
}
for f, o in zip(fs, output)
]
else:
o = next(o for ix, o in enumerate(result) if indices[ix] == i)
res = {
"is_file": True,
"name": o,
"orig_name": Path(fs).name,
"data": None,
}
uploaded.append(res)
return uploaded
def _add_uploaded_files_to_data(
self,
files: list[str | list[str]] | list[dict[str, Any] | list[dict[str, Any]]],
data: list[Any],
) -> None:
"""Helper function to modify the input data with the uploaded files."""
file_counter = 0
for i, t in enumerate(self.input_component_types):
if t in ["file", "uploadbutton"]:
data[i] = files[file_counter]
file_counter += 1
def insert_state(self, *data) -> tuple:
data = list(data)
for i, input_component_type in enumerate(self.input_component_types):
if input_component_type == utils.STATE_COMPONENT:
data.insert(i, None)
return tuple(data)
def remove_skipped_components(self, *data) -> tuple:
data = [
d
for d, oct in zip(data, self.output_component_types)
if oct not in utils.SKIP_COMPONENTS
]
return tuple(data)
def reduce_singleton_output(self, *data) -> Any:
if (
len(
[
oct
for oct in self.output_component_types
if oct not in utils.SKIP_COMPONENTS
]
)
== 1
):
return data[0]
else:
return data
def serialize(self, *data) -> tuple:
if len(data) != len(self.serializers):
raise ValueError(
f"Expected {len(self.serializers)} arguments, got {len(data)}"
)
files = [
f
for f, t in zip(data, self.input_component_types)
if t in ["file", "uploadbutton"]
]
uploaded_files = self._upload(files)
data = list(data)
self._add_uploaded_files_to_data(uploaded_files, data)
o = tuple([s.serialize(d) for s, d in zip(self.serializers, data)])
return o
def deserialize(self, *data) -> tuple:
if len(data) != len(self.deserializers):
raise ValueError(
f"Expected {len(self.deserializers)} outputs, got {len(data)}"
)
outputs = tuple(
[
s.deserialize(
d,
save_dir=self.client.output_dir,
hf_token=self.client.hf_token,
root_url=self.root_url,
)
for s, d in zip(self.deserializers, data)
]
)
return outputs
def process_predictions(self, *predictions):
if self.client.download_files:
predictions = self.deserialize(*predictions)
predictions = self.remove_skipped_components(*predictions)
predictions = self.reduce_singleton_output(*predictions)
return predictions
def _setup_serializers(
self,
) -> tuple[list[serializing.Serializable], list[serializing.Serializable]]:
inputs = self.dependency["inputs"]
serializers = []
for i in inputs:
for component in self.client.config["components"]:
if component["id"] == i:
component_name = component["type"]
self.input_component_types.append(component_name)
if component.get("serializer"):
serializer_name = component["serializer"]
if serializer_name not in serializing.SERIALIZER_MAPPING:
raise SerializationSetupError(
f"Unknown serializer: {serializer_name}, you may need to update your gradio_client version."
)
serializer = serializing.SERIALIZER_MAPPING[serializer_name]
elif component_name in serializing.COMPONENT_MAPPING:
serializer = serializing.COMPONENT_MAPPING[component_name]
else:
raise SerializationSetupError(
f"Unknown component: {component_name}, you may need to update your gradio_client version."
)
serializers.append(serializer()) # type: ignore
outputs = self.dependency["outputs"]
deserializers = []
for i in outputs:
for component in self.client.config["components"]:
if component["id"] == i:
component_name = component["type"]
self.output_component_types.append(component_name)
if component.get("serializer"):
serializer_name = component["serializer"]
if serializer_name not in serializing.SERIALIZER_MAPPING:
raise SerializationSetupError(
f"Unknown serializer: {serializer_name}, you may need to update your gradio_client version."
)
deserializer = serializing.SERIALIZER_MAPPING[serializer_name]
elif component_name in utils.SKIP_COMPONENTS:
deserializer = serializing.SimpleSerializable
elif component_name in serializing.COMPONENT_MAPPING:
deserializer = serializing.COMPONENT_MAPPING[component_name]
else:
raise SerializationSetupError(
f"Unknown component: {component_name}, you may need to update your gradio_client version."
)
deserializers.append(deserializer()) # type: ignore
return serializers, deserializers
def _use_websocket(self, dependency: dict) -> bool:
queue_enabled = self.client.config.get("enable_queue", False)
queue_uses_websocket = version.parse(
self.client.config.get("version", "2.0")
) >= version.Version("3.2")
dependency_uses_queue = dependency.get("queue", False) is not False
return queue_enabled and queue_uses_websocket and dependency_uses_queue
async def _ws_fn(self, data, hash_data, helper: Communicator):
async with websockets.connect( # type: ignore
self.client.ws_url,
open_timeout=10,
extra_headers=self.client.headers,
max_size=1024 * 1024 * 1024,
) as websocket:
return await utils.get_pred_from_ws(websocket, data, hash_data, helper)
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