Fail CI if lint or typecheck fails (#7770)

* fail

* test

* revert

* run shebang

* fix

* fixes

* add changeset

* changes

* bash

* not required

* file

* textbox

* add changeset

* changes to demo

* notebook

---------

Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com>

.changeset/icy-planets-live.md

@@ -0,0 +1,5 @@
+---
+"gradio": patch
+---
+
+feat:Fail CI if lint or typecheck fails

.github/workflows/test-python.yml

@@ -68,12 +68,12 @@ jobs:
       if: runner.os == 'Linux'
       run: |
         . venv/bin/activate
-        bash scripts/lint_backend.sh
+        ./scripts/lint_backend.sh
     - name: Typecheck
       if: runner.os == 'Linux'
       run: |
         . venv/bin/activate
-        bash scripts/type_check_backend.sh
+        ./scripts/type_check_backend.sh
     - name: Run tests
       run: |
         . ${{steps.install_deps.outputs.venv_activate}}

demo/chatbot_multimodal/run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: chatbot_multimodal"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('files')\n", "!wget -q -O files/avatar.png https://github.com/gradio-app/gradio/raw/main/demo/chatbot_multimodal/files/avatar.png\n", "!wget -q -O files/lion.jpg https://github.com/gradio-app/gradio/raw/main/demo/chatbot_multimodal/files/lion.jpg"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "import time\n", "\n", "# Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text.\n", "\n", "\n", "def print_like_dislike(x: gr.LikeData):\n", "    print(x.index, x.value, x.liked)\n", "\n", "def add_message(history, message):\n", "    for x in message[\"files\"]:\n", "        history.append(((x[\"path\"],), None))  \n", "    if message[\"text\"] is not None:\n", "        history.append((message[\"text\"], None))\n", "    return history, gr.MultimodalTextbox(value=None, interactive=False, file_types=[\"image\"])\n", "\n", "def bot(history):\n", "    response = \"**That's cool!**\"\n", "    history[-1][1] = \"\"\n", "    for character in response:\n", "        history[-1][1] += character\n", "        time.sleep(0.05)\n", "        yield history\n", "\n", "\n", "with gr.Blocks() as demo:\n", "    chatbot = gr.Chatbot(\n", "        [],\n", "        elem_id=\"chatbot\",\n", "        bubble_full_width=False,\n", "        avatar_images=(None, (os.path.join(os.path.abspath(''), \"files/avatar.png\"))),\n", "    )\n", "\n", "    chat_input = gr.MultimodalTextbox(interactive=True, file_types=[\"image\"], placeholder=\"Enter message or upload file...\", show_label=False)\n", "    chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input], queue=False).then(\n", "        bot, chatbot, chatbot, api_name=\"bot_response\"\n", "    )\n", "    chat_msg.then(lambda: gr.Textbox(interactive=True), None, [chat_input], queue=False)\n", "    chatbot.like(print_like_dislike, None, None)\n", "\n", "demo.queue()\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: chatbot_multimodal"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('files')\n", "!wget -q -O files/avatar.png https://github.com/gradio-app/gradio/raw/main/demo/chatbot_multimodal/files/avatar.png\n", "!wget -q -O files/lion.jpg https://github.com/gradio-app/gradio/raw/main/demo/chatbot_multimodal/files/lion.jpg"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "import time\n", "\n", "# Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text.\n", "\n", "\n", "def print_like_dislike(x: gr.LikeData):\n", "    print(x.index, x.value, x.liked)\n", "\n", "def add_message(history, message):\n", "    for x in message[\"files\"]:\n", "        history.append(((x,), None))\n", "    if message[\"text\"] is not None:\n", "        history.append((message[\"text\"], None))\n", "    return history, gr.MultimodalTextbox(value=None, interactive=False)\n", "\n", "def bot(history):\n", "    response = \"**That's cool!**\"\n", "    history[-1][1] = \"\"\n", "    for character in response:\n", "        history[-1][1] += character\n", "        time.sleep(0.05)\n", "        yield history\n", "\n", "\n", "with gr.Blocks() as demo:\n", "    chatbot = gr.Chatbot(\n", "        [],\n", "        elem_id=\"chatbot\",\n", "        bubble_full_width=False,\n", "        avatar_images=(None, (os.path.join(os.path.abspath(''), \"files/avatar.png\"))),\n", "    )\n", "\n", "    chat_input = gr.MultimodalTextbox(interactive=True, file_types=[\"image\"], placeholder=\"Enter message or upload file...\", show_label=False)\n", "\n", "    chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input])\n", "    bot_msg = chat_msg.then(bot, chatbot, chatbot, api_name=\"bot_response\")\n", "    bot_msg.then(lambda: gr.MultimodalTextbox(interactive=True), None, [chat_input])\n", "\n", "    chatbot.like(print_like_dislike, None, None)\n", "\n", "demo.queue()\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

demo/chatbot_multimodal/run.py

@@ -10,10 +10,10 @@ def print_like_dislike(x: gr.LikeData):
 
 def add_message(history, message):
     for x in message["files"]:
-        history.append(((x["path"],), None))  
+        history.append(((x,), None))
     if message["text"] is not None:
         history.append((message["text"], None))
-    return history, gr.MultimodalTextbox(value=None, interactive=False, file_types=["image"])
+    return history, gr.MultimodalTextbox(value=None, interactive=False)
 
 def bot(history):
     response = "**That's cool!**"
@@ -33,10 +33,11 @@ with gr.Blocks() as demo:
     )
 
     chat_input = gr.MultimodalTextbox(interactive=True, file_types=["image"], placeholder="Enter message or upload file...", show_label=False)
-    chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input], queue=False).then(
-        bot, chatbot, chatbot, api_name="bot_response"
-    )
-    chat_msg.then(lambda: gr.Textbox(interactive=True), None, [chat_input], queue=False)
+
+    chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input])
+    bot_msg = chat_msg.then(bot, chatbot, chatbot, api_name="bot_response")
+    bot_msg.then(lambda: gr.MultimodalTextbox(interactive=True), None, [chat_input])
+
     chatbot.like(print_like_dislike, None, None)
 
 demo.queue()

gradio/components/multimodal_textbox.py

@@ -3,11 +3,12 @@
 from __future__ import annotations
 
 from pathlib import Path
-from typing import Any, Callable, List, Literal, Optional, TypedDict
+from typing import Any, Callable, List, Literal, TypedDict
 
 import gradio_client.utils as client_utils
 from gradio_client.documentation import document
 from pydantic import Field
+from typing_extensions import NotRequired
 
 from gradio.components.base import FormComponent
 from gradio.data_classes import FileData, GradioModel
@@ -15,8 +16,8 @@ from gradio.events import Events
 
 
 class MultimodalData(GradioModel):
-    text: Optional[str] = None
-    files: Optional[List[FileData]] = Field(default_factory=list)
+    text: str
+    files: List[FileData] = Field(default_factory=list)
 
 
 class MultimodalPostprocess(TypedDict):
@@ -24,6 +25,11 @@ class MultimodalPostprocess(TypedDict):
     files: List[FileData]
 
 
+class MultimodalValue(TypedDict):
+    text: NotRequired[str]
+    files: NotRequired[list[str]]
+
+
 @document()
 class MultimodalTextbox(FormComponent):
     """
@@ -127,18 +133,21 @@ class MultimodalTextbox(FormComponent):
         self.rtl = rtl
         self.text_align = text_align
 
-    def preprocess(
-        self, payload: MultimodalData | None
-    ) -> dict[str, str | list] | None:
+    def preprocess(self, payload: MultimodalData | None) -> MultimodalValue | None:
         """
         Parameters:
             payload: the text and list of file(s) entered in the multimodal textbox.
         Returns:
             Passes text value and list of file(s) as a {dict} into the function.
         """
-        return None if payload is None else payload.model_dump()
+        if payload is None:
+            return None
+        return {
+            "text": payload.text,
+            "files": [f.path for f in payload.files],
+        }
 
-    def postprocess(self, value: dict[str, str | list] | None) -> MultimodalData:
+    def postprocess(self, value: MultimodalValue | None) -> MultimodalData:
         """
         Parameters:
             value: Expects a {dict} with "text" and "files", both optional. The files array is a list of file paths or URLs.
@@ -151,24 +160,20 @@ class MultimodalTextbox(FormComponent):
             raise ValueError(
                 f"MultimodalTextbox expects a dictionary with optional keys 'text' and 'files'. Received {value.__class__.__name__}"
             )
+        text = value.get("text", "")
         if "files" in value and isinstance(value["files"], list):
-            value["files"] = [
+            files = [
                 file
                 if isinstance(file, FileData)
                 else FileData(
-                    path=file["path"] if "path" in file else file,
-                    mime_type=file["mime_type"]
-                    if "mime_type" in file
-                    else client_utils.get_mimetype(file),
-                    orig_name=file["orig_name"]
-                    if "orig_name" in file
-                    else Path(file).name,
-                    size=file["size"] if "size" in file else Path(file).stat().st_size,
+                    path=file,
+                    orig_name=Path(file).name,
+                    mime_type=client_utils.get_mimetype(file),
                 )
                 for file in value["files"]
             ]
-        text = value.get("text", "")
-        files = value.get("files", [])
+        else:
+            files = []
         if not isinstance(text, str):
             raise TypeError(
                 f"Expected 'text' to be a string, but got {type(text).__name__}"