Integrating gradio demo

extra-requirements.txt

@@ -36,6 +36,7 @@ docarray>=0.16.4: core
 jina-hubble-sdk>=0.30.4: core
 jcloud>=0.0.35: core
 opentelemetry-api>=1.12.0: core
+gradio: core
 opentelemetry-instrumentation-grpc>=0.35b0: core 
 uvloop: perf,standard,devel
 prometheus_client>=0.12.0: perf,standard,devel

jina/serve/runtimes/worker/http_fastapi_app.py

@@ -1,5 +1,7 @@
 import inspect
 from typing import TYPE_CHECKING, Callable, Dict, List, Optional, Union
+import gradio as gr
+from pydantic import BaseModel
 
 from jina import DocumentArray, Document
 from jina._docarray import docarray_v2
@@ -189,6 +191,15 @@
  output_doc_list_model=output_doc_model,
  )
 
+ def _executor_caller(*args):
+ return args
+
+ print(input_doc_model, output_doc_model)
+ inputs = generate_gradio_interface(input_doc_model)
+ outputs = generate_gradio_interface(output_doc_model)
+ interface = gr.Interface(_executor_caller, inputs, outputs)
+ app = gr.mount_gradio_app(app, interface, path="/_jina_gradio_demo")
+
  from jina.serve.runtimes.gateway.health_model import JinaHealthModel
 
  @app.get(
@@ -222,3 +233,62 @@
  return {'event': 'update', 'data': doc.to_dict()}
  else:
  return {'event': 'update', 'data': doc.dict()}
+
+def generate_gradio_interface(model: BaseModel):
+ """helper function to convert pydantic model to gradio interface"""
+ inputs = []
+
+ # Process each attribute in the model
+ for attr, field in model.__annotations__.items():
+ input_type = field.__name__
+ input_label = attr.replace("_", " ").capitalize()
+
+ # Generate appropriate input component based on the field type
+ if input_type == "str":
+ # Additional options for string type
+ field_info = model.__annotations__[attr]
+ default = field_info.default if hasattr(field_info, "default") else None
+ choices = field_info.choices if hasattr(field_info, "choices") else None
+
+ input_component = gr.Textbox(
+ label=input_label,
+ )
+ elif input_type == "int":
+ # Additional options for integer type
+ field_info = model.__annotations__[attr]
+ ge = field_info.ge if hasattr(field_info, "ge") else None
+ le = field_info.le if hasattr(field_info, "le") else None
+
+ input_component = gr.Number(
+ label=input_label,
+ minimum=ge,
+ maximum=le,
+ step=1,
+ )
+ elif input_type == "float":
+ # Additional options for float type
+ field_info = model.__annotations__[attr]
+ ge = field_info.ge if hasattr(field_info, "ge") else None
+ le = field_info.le if hasattr(field_info, "le") else None
+
+ input_component = gr.Number(
+ label=input_label,
+ minimum=ge,
+ maximum=le,
+ step=0.01,
+ )
+ elif input_type == "bool":
+ # Additional options for boolean type
+ field_info = model.__annotations__[attr]
+ input_component = gr.Checkbox(label=input_label)
+ elif input_type == "File":
+ input_component = gr.File(label=input_label)
+ elif input_type == "Path":
+ input_component = gr.Textbox(label=input_label)
+ else:
+ # For unsupported types, skip the attribute
+ continue
+
+ # Add the input component to the inputs list
+ inputs.append(input_component)
+ return inputs