Initial commit

.gitignore

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+
+.venv/
+__pycache__/
+
+.DS_Store

.vscode/launch.json

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+{
+  // Use IntelliSense to learn about possible attributes.
+  // Hover to view descriptions of existing attributes.
+  // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+  "version": "0.2.0",
+  "configurations": [
+    {
+      "name": "Run Shiny app",
+      "type": "python",
+      "request": "launch",
+      "module": "shiny",
+      "args": ["run", "${file}"],
+      "jinja": true,
+      "justMyCode": true
+    },
+    {
+      "name": "Test",
+      "type": "python",
+      "request": "launch",
+      "module": "pytest",
+      "args": [],
+      "justMyCode": true
+    }
+  ]
+}

.vscode/settings.json

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+{
+    "files.trimTrailingWhitespace": true,
+    "files.insertFinalNewline": true,
+    "python.formatting.provider": "black",
+    "python.linting.flake8Enabled": true,
+    "editor.tabSize": 2,
+    "files.encoding": "utf8",
+    "files.eol": "\n",
+    "[python]": {
+        "editor.formatOnSave": true,
+        "editor.tabSize": 4,
+        "editor.codeActionsOnSave": {
+            "source.organizeImports": true
+        },
+    },
+    "isort.args":["--profile", "black"],
+    "editor.rulers": [
+        88
+    ],
+    "files.exclude": {
+        "**/__pycache__": true,
+        "build/**": true
+    },
+    "autoDocstring.guessTypes": false,
+    "search.exclude": {
+        "build/**": true
+    },
+}

app.py

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+from shiny import App, reactive, ui
+from query import query_output_server, query_output_ui
+from htmltools import tags
+import shinyswatch
+
+app_ui = ui.page_fluid(
+    shinyswatch.theme("zephyr"),
+    ui.row(
+        ui.column(
+            2,
+            ui.br(),
+            ui.br(),
+            ui.input_action_button("add_query", "Add Query"),
+        ),
+        ui.column(
+            10,
+            ui.tags.div(query_output_ui("initial_query"), id="module_container"),
+        ),
+    ),
+)
+
+
+def server(input, output, session):
+    mod_counter = reactive.Value(0)
+
+    query_output_server("initial_query")
+
+    @reactive.Effect
+    @reactive.event(input.add_query)
+    def _():
+        counter = mod_counter.get() + 1
+        mod_counter.set(counter)
+        id = "query_" + str(counter)
+        ui.insert_ui(
+            selector="#module_container", where="afterBegin", ui=query_output_ui(id)
+        )
+        query_output_server(id)
+
+
+app = App(app_ui, server)

query.py

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+from plotnine import aes, geom_point, ggplot, labs, theme_light
+from shiny import module, ui, reactive, render
+import pandas as pd
+import requests
+from htmltools import tags
+
+
+@module.ui
+def query_output_ui():
+    out = ui.row(
+        ui.column(
+            4,
+            ui.input_text("prompt", "Prompt", placeholder="Enter query"),
+        ),
+        ui.column(4, ui.output_table("score_table")),
+        ui.column(4, ui.output_plot("score_plot")),
+    )
+
+    return out
+
+
+@module.server
+def query_output_server(input, output, session):
+    @reactive.Calc
+    def response_table():
+        # This is included to both show the expected API response, and populate
+        # the downstream item with zeros before a prompt is entered.
+        if input.prompt() == "":
+            resp = [
+                [
+                    {"label": "neutral", "score": 0},
+                    {"label": "surprise", "score": 0},
+                    {"label": "fear", "score": 0},
+                    {"label": "anger", "score": 0},
+                    {"label": "disgust", "score": 0},
+                    {"label": "sadness", "score": 0},
+                    {"label": "joy", "score": 0},
+                ]
+            ]
+        else:
+            resp = query(input.prompt())
+
+        df = pd.DataFrame(
+            {
+                "sentiment": [x["label"] for x in resp[0]],
+                "score": [x["score"] for x in resp[0]],
+            }
+        )
+        return df
+
+    @output
+    @render.plot
+    def score_plot():
+        return plot_response(response_table(), input.prompt())
+
+    @output
+    @render.table()
+    def score_table():
+        return response_table()
+
+
+def plot_response(df, plot_title):
+    out = (
+        ggplot(df, aes(y="reorder(sentiment, score)", x="score"))
+        + geom_point()
+        + theme_light()
+        + labs(title=f'Prompt: "{plot_title}"', y="Sentiment", x="Score")
+    )
+    return out
+
+
+def query(text):
+    API_URL = "https://api-inference.huggingface.co/models/j-hartmann/emotion-english-distilroberta-base"
+    headers = {"Authorization": "Bearer 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"}
+    payload = {"inputs": text}
+    response = requests.post(API_URL, headers=headers, json=payload)
+    return response.json()

requirements.txt

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+anyio==3.6.2
+appdirs==1.4.4
+asgiref==3.6.0
+black==23.3.0
+certifi==2022.12.7
+charset-normalizer==3.1.0
+click==8.1.3
+contextvars==2.4
+contourpy==1.0.7
+cycler==0.11.0
+fonttools==4.39.3
+h11==0.14.0
+htmltools==0.2.1
+idna==3.4
+immutables==0.19
+Jinja2==3.1.2
+kiwisolver==1.4.4
+linkify-it-py==2.0.0
+markdown-it-py==2.2.0
+MarkupSafe==2.1.2
+matplotlib==3.7.1
+mdit-py-plugins==0.3.5
+mdurl==0.1.2
+mizani==0.8.1
+mypy-extensions==1.0.0
+numpy==1.24.2
+packaging==23.0
+palettable==3.3.1
+pandas==2.0.0
+pathspec==0.11.1
+patsy==0.5.3
+Pillow==9.5.0
+platformdirs==3.2.0
+plotnine==0.10.1
+pyparsing==3.0.9
+python-dateutil==2.8.2
+python-multipart==0.0.6
+pytz==2023.3
+requests==2.28.2
+scipy==1.10.1
+shiny==0.3.0
+shinyswatch==0.1.1
+six==1.16.0
+sniffio==1.3.0
+starlette==0.26.1
+statsmodels==0.13.5
+tomli==2.0.1
+typing_extensions==4.5.0
+tzdata==2023.3
+uc-micro-py==1.0.1
+urllib3==1.26.15
+uvicorn==0.21.1
+websockets==11.0.1
+XStatic-bootswatch==3.3.7.0

sentence-sentiment.code-workspace

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+{
+	"folders": [
+		{
+			"path": "."
+		}
+	]
+}