File size: 7,473 Bytes
8766bc5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
import tempfile
from concurrent.futures import wait

import pytest

import gradio as gr
from gradio import helpers


def invalid_fn(message):
    return message


def double(message, history):
    return message + " " + message


async def async_greet(message, history):
    return "hi, " + message


def stream(message, history):
    for i in range(len(message)):
        yield message[: i + 1]


async def async_stream(message, history):
    for i in range(len(message)):
        yield message[: i + 1]


def count(message, history):
    return str(len(history))


def echo_system_prompt_plus_message(message, history, system_prompt, tokens):
    response = f"{system_prompt} {message}"
    for i in range(min(len(response), int(tokens))):
        yield response[: i + 1]


class TestInit:
    def test_no_fn(self):
        with pytest.raises(TypeError):
            gr.ChatInterface()

    def test_configuring_buttons(self):
        chatbot = gr.ChatInterface(double, submit_btn=None, retry_btn=None)
        assert chatbot.submit_btn is None
        assert chatbot.retry_btn is None

    def test_events_attached(self):
        chatbot = gr.ChatInterface(double)
        dependencies = chatbot.dependencies
        textbox = chatbot.textbox._id
        submit_btn = chatbot.submit_btn._id
        assert next(
            (
                d
                for d in dependencies
                if d["targets"] == [(textbox, "submit"), (submit_btn, "click")]
            ),
            None,
        )
        for btn_id in [
            chatbot.retry_btn._id,
            chatbot.clear_btn._id,
            chatbot.undo_btn._id,
        ]:
            assert next(
                (d for d in dependencies if d["targets"][0] == (btn_id, "click")),
                None,
            )

    @pytest.mark.asyncio
    async def test_example_caching(self, monkeypatch):
        monkeypatch.setattr(helpers, "CACHED_FOLDER", tempfile.mkdtemp())
        chatbot = gr.ChatInterface(
            double, examples=["hello", "hi"], cache_examples=True
        )
        prediction_hello = await chatbot.examples_handler.load_from_cache(0)
        prediction_hi = await chatbot.examples_handler.load_from_cache(1)
        assert prediction_hello[0][0] == ["hello", "hello hello"]
        assert prediction_hi[0][0] == ["hi", "hi hi"]

    @pytest.mark.asyncio
    async def test_example_caching_async(self, monkeypatch):
        monkeypatch.setattr(helpers, "CACHED_FOLDER", tempfile.mkdtemp())
        chatbot = gr.ChatInterface(
            async_greet, examples=["abubakar", "tom"], cache_examples=True
        )
        prediction_hello = await chatbot.examples_handler.load_from_cache(0)
        prediction_hi = await chatbot.examples_handler.load_from_cache(1)
        assert prediction_hello[0][0] == ["abubakar", "hi, abubakar"]
        assert prediction_hi[0][0] == ["tom", "hi, tom"]

    @pytest.mark.asyncio
    async def test_example_caching_with_streaming(self, monkeypatch):
        monkeypatch.setattr(helpers, "CACHED_FOLDER", tempfile.mkdtemp())
        chatbot = gr.ChatInterface(
            stream, examples=["hello", "hi"], cache_examples=True
        )
        prediction_hello = await chatbot.examples_handler.load_from_cache(0)
        prediction_hi = await chatbot.examples_handler.load_from_cache(1)
        assert prediction_hello[0][0] == ["hello", "hello"]
        assert prediction_hi[0][0] == ["hi", "hi"]

    @pytest.mark.asyncio
    async def test_example_caching_with_streaming_async(self, monkeypatch):
        monkeypatch.setattr(helpers, "CACHED_FOLDER", tempfile.mkdtemp())
        chatbot = gr.ChatInterface(
            async_stream, examples=["hello", "hi"], cache_examples=True
        )
        prediction_hello = await chatbot.examples_handler.load_from_cache(0)
        prediction_hi = await chatbot.examples_handler.load_from_cache(1)
        assert prediction_hello[0][0] == ["hello", "hello"]
        assert prediction_hi[0][0] == ["hi", "hi"]

    @pytest.mark.asyncio
    async def test_example_caching_with_additional_inputs(self, monkeypatch):
        monkeypatch.setattr(helpers, "CACHED_FOLDER", tempfile.mkdtemp())
        chatbot = gr.ChatInterface(
            echo_system_prompt_plus_message,
            additional_inputs=["textbox", "slider"],
            examples=[["hello", "robot", 100], ["hi", "robot", 2]],
            cache_examples=True,
        )
        prediction_hello = await chatbot.examples_handler.load_from_cache(0)
        prediction_hi = await chatbot.examples_handler.load_from_cache(1)
        assert prediction_hello[0][0] == ["hello", "robot hello"]
        assert prediction_hi[0][0] == ["hi", "ro"]

    @pytest.mark.asyncio
    async def test_example_caching_with_additional_inputs_already_rendered(
        self, monkeypatch
    ):
        monkeypatch.setattr(helpers, "CACHED_FOLDER", tempfile.mkdtemp())
        with gr.Blocks():
            with gr.Accordion("Inputs"):
                text = gr.Textbox()
                slider = gr.Slider()
                chatbot = gr.ChatInterface(
                    echo_system_prompt_plus_message,
                    additional_inputs=[text, slider],
                    examples=[["hello", "robot", 100], ["hi", "robot", 2]],
                    cache_examples=True,
                )
        prediction_hello = await chatbot.examples_handler.load_from_cache(0)
        prediction_hi = await chatbot.examples_handler.load_from_cache(1)
        assert prediction_hello[0][0] == ["hello", "robot hello"]
        assert prediction_hi[0][0] == ["hi", "ro"]


class TestAPI:
    def test_get_api_info(self):
        chatbot = gr.ChatInterface(double)
        api_info = gr.blocks.get_api_info(chatbot.get_config_file())
        assert len(api_info["named_endpoints"]) == 1
        assert len(api_info["unnamed_endpoints"]) == 0
        assert "/chat" in api_info["named_endpoints"]

    def test_streaming_api(self, connect):
        chatbot = gr.ChatInterface(stream).queue()
        with connect(chatbot) as client:
            job = client.submit("hello")
            wait([job])
            assert job.outputs() == ["h", "he", "hel", "hell", "hello"]

    def test_streaming_api_async(self, connect):
        chatbot = gr.ChatInterface(async_stream).queue()
        with connect(chatbot) as client:
            job = client.submit("hello")
            wait([job])
            assert job.outputs() == ["h", "he", "hel", "hell", "hello"]

    def test_non_streaming_api(self, connect):
        chatbot = gr.ChatInterface(double)
        with connect(chatbot) as client:
            result = client.predict("hello")
            assert result == "hello hello"

    def test_non_streaming_api_async(self, connect):
        chatbot = gr.ChatInterface(async_greet)
        with connect(chatbot) as client:
            result = client.predict("gradio")
            assert result == "hi, gradio"

    def test_streaming_api_with_additional_inputs(self, connect):
        chatbot = gr.ChatInterface(
            echo_system_prompt_plus_message,
            additional_inputs=["textbox", "slider"],
        ).queue()
        with connect(chatbot) as client:
            job = client.submit("hello", "robot", 7)
            wait([job])
            assert job.outputs() == [
                "r",
                "ro",
                "rob",
                "robo",
                "robot",
                "robot ",
                "robot h",
            ]