File size: 4,014 Bytes
28a5857
f2f5171
28a5857
 
 
 
 
 
 
 
957c035
 
 
 
 
 
f2f5171
 
28a5857
 
 
 
 
 
 
f2f5171
 
 
28a5857
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
957c035
f2f5171
28a5857
957c035
d95cbea
 
 
 
28a5857
957c035
f2f5171
d95cbea
 
 
 
 
957c035
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d95cbea
 
957c035
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d95cbea
957c035
d95cbea
 
 
 
 
 
 
 
 
 
 
 
957c035
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
import os
import gradio as gr
from pathlib import Path
from fastapi import FastAPI, Request
from fastapi.staticfiles import StaticFiles
from fastapi.responses import HTMLResponse
from fastapi.templating import Jinja2Templates
from dotenv import load_dotenv

from app import Summarizer, TextRequest, Result
from app import (
    EN_SENTIMENT_MODEL,
    EN_SUMMARY_MODEL,
    RU_SENTIMENT_MODEL,
    RU_SUMMARY_MODEL,
)
from app import DEFAULT_EN_TEXT, DEFAULT_RU_TEXT

load_dotenv()

SITE_KEY = os.getenv("SITE_KEY")
SECRET_KEY = os.getenv("SECRET_KEY")
VERIFY_URL = "https://www.google.com/recaptcha/api/siteverify"

# create FastAPI app
app = FastAPI()
pipe = Summarizer()

# create a static directory to store the static files
static_dir = Path("./static")
static_dir.mkdir(parents=True, exist_ok=True)

# mount FastAPI StaticFiles server
app.mount("/static", StaticFiles(directory=static_dir), name="static")
templates = Jinja2Templates(directory="templates")


@app.get("/verify_page", response_class=HTMLResponse)
async def verify_page(request: Request):
    return templates.TemplateResponse(
        request=request, name="verification.html", context={"site_key": SITE_KEY}
    )


@app.get("/bad_request", response_class=HTMLResponse)
async def bad_request(request: Request):
    return templates.TemplateResponse("bad_request.html", {"request": request})


@app.post("/verify")
async def verify(request: Request):
    # verify_response = requests.post(
    #     url=VERIFY_URL,
    #     data={
    #         "secret": SECRET_KEY,
    #         "response": request.form["g-recaptcha-response"],
    #     },
    # )
    # print(verify_response.json())
    return templates.TemplateResponse("bad_request.html", {"request": request})


@app.post("/summ_ru", response_model=Result)
async def ru_summ_api(request: TextRequest):
    results = pipe.summarize(request.text, lang="ru")
    return results


@app.post("/summ_en", response_model=Result)
async def en_summ_api(request: TextRequest):
    results = pipe.summarize(request.text, lang="en")
    return results


with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column(scale=2, min_width=600):
            en_sum_description = gr.Markdown(
                value=f"Model for Summary: {EN_SUMMARY_MODEL}"
            )
            en_sent_description = gr.Markdown(
                value=f"Model for Sentiment: {EN_SENTIMENT_MODEL}"
            )
            en_inputs = gr.Textbox(
                label="en_input",
                lines=5,
                value=DEFAULT_EN_TEXT,
                placeholder=DEFAULT_EN_TEXT,
            )
            en_lang = gr.Textbox(value="en", visible=False)
            en_outputs = gr.Textbox(
                label="en_output",
                lines=5,
                placeholder="Summary and Sentiment would be here...",
            )
            en_inbtn = gr.Button("Proceed")
        with gr.Column(scale=2, min_width=600):
            ru_sum_description = gr.Markdown(
                value=f"Model for Summary: {RU_SUMMARY_MODEL}"
            )
            ru_sent_description = gr.Markdown(
                value=f"Model for Sentiment: {RU_SENTIMENT_MODEL}"
            )
            ru_inputs = gr.Textbox(
                label="ru_input",
                lines=5,
                value=DEFAULT_RU_TEXT,
                placeholder=DEFAULT_RU_TEXT,
            )
            ru_lang = gr.Textbox(value="ru", visible=False)
            ru_outputs = gr.Textbox(
                label="ru_output",
                lines=5,
                placeholder="Здесь будет обобщение и эмоциональный окрас текста...",
            )
            ru_inbtn = gr.Button("Запустить")

    en_inbtn.click(
        pipe.summ,
        [en_inputs, en_lang],
        [en_outputs],
    )
    ru_inbtn.click(
        pipe.summ,
        [ru_inputs, ru_lang],
        [ru_outputs],
    )

# mounting at the root path
app = gr.mount_gradio_app(app, demo, path="/")