init

.gitignore

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+__pycache__
+datasets

app/main.py

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+import os
+import csv
+import time
+import gradio as gr
+from fastapi import FastAPI
+from fastapi_utils.tasks import repeat_every
+
+
+class Timer(object):
+    def __enter__(self):
+        self.start = time.perf_counter()
+        return self
+    def __exit__(self, typ, value, traceback):
+        self.elapsed = time.perf_counter() - self.start
+
+
+file_changed = False
+HF_TOKEN = os.getenv('HF_TOKEN')
+root_dataset_path = "datasets"
+huggingface_dataset_path = "Vsevolod/text2rec-users-feedback"
+feedback_dataset = gr.HuggingFaceDatasetSaver(HF_TOKEN, huggingface_dataset_path)
+local_dataset_path = f"{root_dataset_path}/{huggingface_dataset_path}"
+data_path = f"{local_dataset_path}/data.csv"
+print(os.getcwd())
+print(local_dataset_path)
+
+
+def foo(x):
+    global file_changed
+    now = time.time()
+    with open(data_path, mode="a", newline="", encoding="utf-8") as file:
+        writer = csv.writer(file)
+        writer.writerow(("Фильмы про путешествия во времени","Грань будущего","Релевантно", "mNpuTAujx-j1E6mm4PVOMQ", now, 228))
+    file_changed = True
+    return x
+
+
+def create_interface():
+    with gr.Blocks() as demo:
+        query = gr.Textbox(label="Запрос")
+        search_btn = gr.Button(label="Поиск")
+        output = gr.Textbox(label="Ответ")
+        search_btn.click(foo, inputs=query, outputs=output)
+        feedback_dataset.setup([], root_dataset_path)
+    return demo
+
+
+def get_line_count(data_path):
+    with open(data_path, "r", encoding="utf-8") as csvfile:
+        line_count = len([None for row in csv.reader(csvfile)]) - 1
+    return line_count
+
+
+demo = create_interface()
+app = FastAPI(docs_url=None, redoc_url=None)
+
+
+@app.on_event("startup")
+@repeat_every(seconds=20)
+def repeat():
+    global file_changed
+    if not file_changed:
+        return
+    print("Updating remote repo")
+    with Timer() as timer:
+        feedback_dataset.repo.git_pull(lfs=True)
+        line_count = get_line_count(data_path)
+        feedback_dataset.repo.push_to_hub(commit_message="Flagged sample #{}".format(line_count))
+    print(f"Elapsed: {timer.elapsed:.3f}")
+    file_changed = False
+
+app.mount("/", demo.app)
+
+
+# from fastapi import FastAPI import gradio as gr app = FastAPI() 
+# @app.get("/") 
+# def read_main():
+#     return {"message": "This is your main app"}
+# io = gr.Interface(lambda x: "Hello, " + x + "!", "textbox", "textbox") 
+# app = gr.mount_gradio_app(app, io, path="/gradio")

run.py

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+import subprocess
+
+subprocess.run("uvicorn app.main:app --host localhost --port 7860", shell=True)