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gradio_logsview
Visualize logs in your Gradio app
Installation
pip install gradio_logsview
Usage
import logging
import random
import time
import gradio as gr
from gradio_logsview import LogsView
def random_values(failing: bool = False):
for i in range(10):
logging.log(
random.choice(
[ # Random levels
logging.INFO,
logging.DEBUG,
logging.WARNING,
logging.ERROR,
logging.CRITICAL,
]
),
f"Value {i+1}", # Random values
)
time.sleep(random.uniform(0, 1))
if failing and i == 5:
raise ValueError("Failing!!")
def fn_process_success():
yield from LogsView.run_process(["python", "-u", "demo/script.py"])
def fn_process_failing():
yield from LogsView.run_process(["python", "-u", "demo/script.py", "--failing"])
def fn_thread_success():
yield from LogsView.run_thread(random_values, log_level=logging.INFO, failing=False)
def fn_thread_failing():
yield from LogsView.run_thread(random_values, log_level=logging.INFO, failing=True)
markdown_top = """
# LogsView Demo
This demo shows how to use the `LogsView` component to display logs from a process or a thread in real-time.
Click on any button to launch a process or a thread and see the logs displayed in real-time.
In the thread example, logs are generated randomly with different log levels.
In the process example, logs are generated by a Python script but any command can be executed.
"""
markdown_bottom = """
## How to run in a thread?
With `LogsView.run_thread`, you can run a function in a separate thread and capture logs in real-time.
You can configure which logs to capture (log level and logger name).
```py
from gradio_logsview import LogsView
def fn_thread():
# Run `my_function` in a separate thread
# All logs above `INFO` level will be captured and displayed in real-time.
yield from LogsView.run_thread(my_function, log_level=logging.INFO, arg1="value1")
with gr.Blocks() as demo:
logs = LogsView()
btn = gr.Button("Run thread")
btn.click(fn_thread, outputs=logs)
How to run in a process?
With LogsView.run_process, you can run a command in a separate process and capture logs from the process in real-time.
from gradio_logsview import LogsView
def fn_process():
# Run a process and capture all logs from the process
yield from LogsView.run_process(
cmd=["mergekit-yaml", "config.yaml", "merge", "--copy-", "--cuda", "--low-cpu-memory"]
)
with gr.Blocks() as demo:
logs = LogsView()
btn = gr.Button("Run process")
btn.click(fn_process, outputs=logs)
"""
with gr.Blocks() as demo: gr.Markdown(markdown_top)
with gr.Row():
btn_thread_success = gr.Button("Run thread (success)")
btn_thread_failing = gr.Button("Run thread (failing)")
with gr.Row():
btn_process_success = gr.Button("Run process (success)")
btn_process_failing = gr.Button("Run process (failing)")
logs = LogsView()
gr.Markdown(markdown_bottom)
btn_thread_failing.click(fn_thread_failing, outputs=logs)
btn_thread_success.click(fn_thread_success, outputs=logs)
btn_process_failing.click(fn_process_failing, outputs=logs)
btn_process_success.click(fn_process_success, outputs=logs)
if name == "main": demo.launch()
## `LogsView`
### Initialization
<table>
<thead>
<tr>
<th align="left">name</th>
<th align="left" style="width: 25%;">type</th>
<th align="left">default</th>
<th align="left">description</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left"><code>value</code></td>
<td align="left" style="width: 25%;">
```python
str | Callable | tuple[str] | None
None
Default value to show in the code editor. If callable, the function will be called whenever the app loads to set the initial value of the component.
every
float | None
None
If `value` is a callable, run the function 'every' number of seconds while the client connection is open. Has no effect otherwise. The event can be accessed (e.g. to cancel it) via this component's .load_event attribute.
lines
int
5
None
label
str | None
None
The label for this component. Appears above the component and is also used as the header if there are a table of examples for this component. If None and used in a `gr.Interface`, the label will be the name of the parameter this component is assigned to.
show_label
bool | None
None
if True, will display label.
container
bool
True
If True, will place the component in a container - providing some extra padding around the border.
scale
int | None
None
relative size compared to adjacent Components. For example if Components A and B are in a Row, and A has scale=2, and B has scale=1, A will be twice as wide as B. Should be an integer. scale applies in Rows, and to top-level Components in Blocks where fill_height=True.
min_width
int
160
minimum pixel width, will wrap if not sufficient screen space to satisfy this value. If a certain scale value results in this Component being narrower than min_width, the min_width parameter will be respected first.
visible
bool
True
If False, component will be hidden.
elem_id
str | None
None
An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.
elem_classes
list[str] | str | None
None
An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.
render
bool
True
If False, component will not render be rendered in the Blocks context. Should be used if the intention is to assign event listeners now but render the component later.
Events
| name | description |
|---|---|
change |
Triggered when the value of the LogsView changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See .input() for a listener that is only triggered by user input. |
input |
This listener is triggered when the user changes the value of the LogsView. |
focus |
This listener is triggered when the LogsView is focused. |
blur |
This listener is triggered when the LogsView is unfocused/blurred. |
User function
The impact on the users predict function varies depending on whether the component is used as an input or output for an event (or both).
- When used as an Input, the component only impacts the input signature of the user function.
- When used as an output, the component only impacts the return signature of the user function.
The code snippet below is accurate in cases where the component is used as both an input and an output.
- As output: Is passed, passes the code entered as a
str. - As input: Should return, expects a list of
Loglogs.
def predict(
value: LogsView
) -> list[Log]:
return value
Log
@dataclass
class Log:
level: Literal[
"INFO", "DEBUG", "WARNING", "ERROR", "CRITICAL"
]
message: str
timestamp: str
LogsView
class LogsView(Component):
EVENTS = [
Events.change,
Events.input,
Events.focus,
Events.blur,
]
def __init__(
self,
value: str | Callable | tuple[str] | None = None,
*,
every: float | None = None,
lines: int = 5,
label: str | None = None,
show_label: bool | None = None,
container: bool = True,
scale: int | None = None,
min_width: int = 160,
visible: bool = True,
elem_id: str | None = None,
elem_classes: list[str] | str | None = None,
render: bool = True,
):
self.language = "shell"
self.lines = lines
self.interactive = False
super().__init__(
label=label,
every=every,
show_label=show_label,
container=container,
scale=scale,
min_width=min_width,
visible=visible,
elem_id=elem_id,
elem_classes=elem_classes,
render=render,
value=value,
)
def preprocess(self, payload: str | None) -> "LogsView":
raise NotImplementedError(
"LogsView cannot be used as an input component."
)
def postprocess(self, value: List[Log]) -> List[Log]:
return value
def api_info(self) -> dict[str, Any]:
return {
"items": {
"level": "string",
"message": "string",
"timestamp": "number",
},
"title": "Logs",
"type": "array",
}
def example_payload(self) -> Any:
return [
Log(
"INFO",
"Hello World",
datetime.now().isoformat(),
)
]
def example_value(self) -> Any:
return [
Log(
"INFO",
"Hello World",
datetime.now().isoformat(),
)
]
@classmethod
def run_process(
cls,
command: List[str],
date_format: str = "%Y-%m-%d %H:%M:%S",
) -> Generator[List[Log], None, None]:
process = subprocess.Popen(
command,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
text=True,
)
if process.stdout is None:
raise ValueError("stdout is None")
logs = []
def _log(level: str, message: str):
log = Log(
level=level,
message=message,
timestamp=datetime.now().strftime(
date_format
),
)
logs.append(log)
return logs
_log("INFO", f"Running {' '.join(command)}")
for line in process.stdout:
yield _log("INFO", line.strip())
# TODO: what if task is cancelled but process is still running?
process.stdout.close()
return_code = process.wait()
if return_code:
yield _log(
"ERROR",
f"Process exited with code {return_code}",
)
else:
yield _log(
"INFO", "Process exited successfully"
)
@classmethod
def run_thread(
cls,
fn: Callable,
log_level: int = logging.INFO,
logger_name: str | None = None,
date_format: str = "%Y-%m-%d %H:%M:%S",
**kwargs,
) -> Generator[List[Log], None, None]:
logs = [
Log(
level="INFO",
message=f"Running {fn.__name__}({', '.join(f'{k}={v}' for k, v in kwargs.items())})",
timestamp=datetime.now().strftime(
date_format
),
)
]
yield logs
thread = Thread(
target=non_failing_fn(fn), kwargs=kwargs
)
def _log(record: logging.LogRecord) -> bool:
if record.thread != thread.ident:
return False # Skip if not from the thread
if logger_name and not record.name.startswith(
logger_name
):
return False # Skip if not from the logger
if record.levelno < log_level:
return False # Skip if too verbose
log = Log(
level=record.levelname,
message=record.getMessage(),
timestamp=datetime.fromtimestamp(
record.created
).strftime(date_format),
)
logs.append(log)
return True
with capture_logging(log_level) as log_queue:
thread.start()
# Loop to capture and yield logs from the thread
while thread.is_alive():
while True:
try:
if _log(log_queue.get_nowait()):
yield logs
except queue.Empty:
break
thread.join(
timeout=0.1
) # adjust the timeout as needed
# After the thread completes, yield any remaining logs
while True:
try:
if _log(log_queue.get_nowait()):
yield logs
except queue.Empty:
break
logs.append(
Log(
level="INFO",
message="Thread completed successfully",
timestamp=datetime.now().strftime(
date_format
),
)
)