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README.md CHANGED
@@ -5,7 +5,7 @@ emoji: 💩
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  colorFrom: indigo
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  colorTo: indigo
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  sdk: gradio
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- sdk_version: 4.16.0
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  app_file: app.py
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  pinned: false
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  ---
 
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  colorFrom: indigo
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  colorTo: indigo
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  sdk: gradio
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+ sdk_version: 4.19.0
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  app_file: app.py
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  pinned: false
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  ---
demos/chatinterface_streaming_echo/run.ipynb CHANGED
@@ -1 +1 @@
1
- {"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: chatinterface_streaming_echo"]}, {"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": ["import time\n", "import gradio as gr\n", "\n", "def slow_echo(message, history):\n", " for i in range(len(message)):\n", " time.sleep(0.05)\n", " yield \"You typed: \" + message[: i+1]\n", "\n", "demo = gr.ChatInterface(slow_echo).queue()\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
 
1
+ {"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: chatinterface_streaming_echo"]}, {"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": ["import time\n", "import gradio as gr\n", "\n", "\n", "def slow_echo(message, history):\n", " for i in range(len(message)):\n", " time.sleep(0.05)\n", " yield \"You typed: \" + message[: i + 1]\n", "\n", "\n", "demo = gr.ChatInterface(slow_echo).queue()\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
demos/chatinterface_streaming_echo/run.py CHANGED
@@ -1,10 +1,12 @@
1
  import time
2
  import gradio as gr
3
 
 
4
  def slow_echo(message, history):
5
  for i in range(len(message)):
6
  time.sleep(0.05)
7
- yield "You typed: " + message[: i+1]
 
8
 
9
  demo = gr.ChatInterface(slow_echo).queue()
10
 
 
1
  import time
2
  import gradio as gr
3
 
4
+
5
  def slow_echo(message, history):
6
  for i in range(len(message)):
7
  time.sleep(0.05)
8
+ yield "You typed: " + message[: i + 1]
9
+
10
 
11
  demo = gr.ChatInterface(slow_echo).queue()
12
 
demos/fake_diffusion_with_gif/run.ipynb CHANGED
@@ -1 +1 @@
1
- {"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: fake_diffusion_with_gif"]}, {"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", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/fake_diffusion_with_gif/image.gif"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import numpy as np\n", "import time\n", "import os\n", "from PIL import Image\n", "import requests\n", "from io import BytesIO\n", "\n", "\n", "def create_gif(images):\n", " pil_images = []\n", " for image in images:\n", " if isinstance(image, str):\n", " response = requests.get(image)\n", " image = Image.open(BytesIO(response.content))\n", " else:\n", " image = Image.fromarray((image * 255).astype(np.uint8))\n", " pil_images.append(image)\n", " fp_out = os.path.join(os.path.abspath(''), \"image.gif\")\n", " img = pil_images.pop(0)\n", " img.save(fp=fp_out, format='GIF', append_images=pil_images,\n", " save_all=True, duration=400, loop=0)\n", " return fp_out\n", "\n", "\n", "def fake_diffusion(steps):\n", " images = []\n", " for _ in range(steps):\n", " time.sleep(1)\n", " image = np.random.random((600, 600, 3))\n", " images.append(image)\n", " yield image, gr.Image(visible=False)\n", "\n", " time.sleep(1)\n", " image = \"https://gradio-builds.s3.amazonaws.com/diffusion_image/cute_dog.jpg\"\n", " images.append(image)\n", " gif_path = create_gif(images)\n", "\n", " yield image, gr.Image(value=gif_path, visible=True)\n", "\n", "\n", "demo = gr.Interface(fake_diffusion,\n", " inputs=gr.Slider(1, 10, 3, step=1),\n", " outputs=[\"image\", gr.Image(label=\"All Images\", visible=False)])\n", "demo.queue()\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
 
1
+ {"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: fake_diffusion_with_gif"]}, {"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", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/fake_diffusion_with_gif/image.gif"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import numpy as np\n", "import time\n", "import os\n", "from PIL import Image\n", "import requests\n", "from io import BytesIO\n", "\n", "\n", "def create_gif(images):\n", " pil_images = []\n", " for image in images:\n", " if isinstance(image, str):\n", " response = requests.get(image)\n", " image = Image.open(BytesIO(response.content))\n", " else:\n", " image = Image.fromarray((image * 255).astype(np.uint8))\n", " pil_images.append(image)\n", " fp_out = os.path.join(os.path.abspath(''), \"image.gif\")\n", " img = pil_images.pop(0)\n", " img.save(fp=fp_out, format='GIF', append_images=pil_images,\n", " save_all=True, duration=400, loop=0)\n", " return fp_out\n", "\n", "\n", "def fake_diffusion(steps):\n", " rng = np.random.default_rng()\n", " images = []\n", " for _ in range(steps):\n", " time.sleep(1)\n", " image = rng.random((600, 600, 3))\n", " images.append(image)\n", " yield image, gr.Image(visible=False)\n", "\n", " time.sleep(1)\n", " image = \"https://gradio-builds.s3.amazonaws.com/diffusion_image/cute_dog.jpg\"\n", " images.append(image)\n", " gif_path = create_gif(images)\n", "\n", " yield image, gr.Image(value=gif_path, visible=True)\n", "\n", "\n", "demo = gr.Interface(fake_diffusion,\n", " inputs=gr.Slider(1, 10, 3, step=1),\n", " outputs=[\"image\", gr.Image(label=\"All Images\", visible=False)])\n", "demo.queue()\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
demos/fake_diffusion_with_gif/run.py CHANGED
@@ -24,10 +24,11 @@ def create_gif(images):
24
 
25
 
26
  def fake_diffusion(steps):
 
27
  images = []
28
  for _ in range(steps):
29
  time.sleep(1)
30
- image = np.random.random((600, 600, 3))
31
  images.append(image)
32
  yield image, gr.Image(visible=False)
33
 
 
24
 
25
 
26
  def fake_diffusion(steps):
27
+ rng = np.random.default_rng()
28
  images = []
29
  for _ in range(steps):
30
  time.sleep(1)
31
+ image = rng.random((600, 600, 3))
32
  images.append(image)
33
  yield image, gr.Image(visible=False)
34
 
demos/file_explorer_component_events/dir1/bar.txt ADDED
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demos/file_explorer_component_events/dir1/foo.txt ADDED
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demos/file_explorer_component_events/dir2/baz.png ADDED
demos/file_explorer_component_events/dir2/foo.png ADDED
demos/file_explorer_component_events/dir3/dir3_bar.log ADDED
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demos/file_explorer_component_events/dir3/dir3_foo.txt ADDED
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demos/file_explorer_component_events/dir3/dir4/dir5/dir5_foo.txt ADDED
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demos/file_explorer_component_events/dir3/dir4/dir7/dir7_foo.txt ADDED
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demos/file_explorer_component_events/dir3/dir4/dir_4_bar.log ADDED
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demos/file_explorer_component_events/dir3/dir4/dir_4_foo.txt ADDED
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demos/file_explorer_component_events/run.ipynb ADDED
@@ -0,0 +1 @@
 
 
1
+ {"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: file_explorer_component_events"]}, {"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('dir1')\n", "!wget -q -O dir1/bar.txt https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir1/bar.txt\n", "!wget -q -O dir1/foo.txt https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir1/foo.txt\n", "os.mkdir('dir2')\n", "!wget -q -O dir2/baz.png https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir2/baz.png\n", "!wget -q -O dir2/foo.png https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir2/foo.png\n", "os.mkdir('dir3')\n", "!wget -q -O dir3/dir3_bar.log https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir3/dir3_bar.log\n", "!wget -q -O dir3/dir3_foo.txt https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir3/dir3_foo.txt\n", "!wget -q -O dir3/dir4 https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir3/dir4"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from pathlib import Path\n", "\n", "base_root = Path(__file__).parent.resolve()\n", "\n", "with gr.Blocks() as demo:\n", " with gr.Row():\n", " dd = gr.Dropdown(label=\"Select File Explorer Root\",\n", " value=str(base_root / \"dir1\"),\n", " choices=[str(base_root / \"dir1\"), str(base_root / \"dir2\"),\n", " str(base_root / \"dir3\")])\n", " with gr.Group():\n", " txt_only_glob = gr.Checkbox(label=\"Show only text files\", value=False)\n", " ignore_txt_in_glob = gr.Checkbox(label=\"Ignore text files in glob\", value=False)\n", "\n", " fe = gr.FileExplorer(root_dir=str(base_root / \"dir1\"),\n", " glob=\"**/*\", interactive=True)\n", " textbox = gr.Textbox(label=\"Selected Directory\")\n", " run = gr.Button(\"Run\")\n", " \n", " txt_only_glob.select(lambda s: gr.FileExplorer(glob=\"*.txt\" if s else \"*\") ,\n", " inputs=[txt_only_glob], outputs=[fe])\n", " ignore_txt_in_glob.select(lambda s: gr.FileExplorer(ignore_glob=\"*.txt\" if s else None),\n", " inputs=[ignore_txt_in_glob], outputs=[fe]) \n", "\n", " dd.select(lambda s: gr.FileExplorer(root=s), inputs=[dd], outputs=[fe])\n", " run.click(lambda s: \",\".join(s) if isinstance(s, list) else s, inputs=[fe], outputs=[textbox])\n", "\n", " with gr.Row():\n", " a = gr.Textbox(elem_id=\"input-box\")\n", " a.change(lambda x: x, inputs=[a])\n", "\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
demos/file_explorer_component_events/run.py ADDED
@@ -0,0 +1,35 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import gradio as gr
2
+ from pathlib import Path
3
+
4
+ base_root = Path(__file__).parent.resolve()
5
+
6
+ with gr.Blocks() as demo:
7
+ with gr.Row():
8
+ dd = gr.Dropdown(label="Select File Explorer Root",
9
+ value=str(base_root / "dir1"),
10
+ choices=[str(base_root / "dir1"), str(base_root / "dir2"),
11
+ str(base_root / "dir3")])
12
+ with gr.Group():
13
+ txt_only_glob = gr.Checkbox(label="Show only text files", value=False)
14
+ ignore_txt_in_glob = gr.Checkbox(label="Ignore text files in glob", value=False)
15
+
16
+ fe = gr.FileExplorer(root_dir=str(base_root / "dir1"),
17
+ glob="**/*", interactive=True)
18
+ textbox = gr.Textbox(label="Selected Directory")
19
+ run = gr.Button("Run")
20
+
21
+ txt_only_glob.select(lambda s: gr.FileExplorer(glob="*.txt" if s else "*") ,
22
+ inputs=[txt_only_glob], outputs=[fe])
23
+ ignore_txt_in_glob.select(lambda s: gr.FileExplorer(ignore_glob="*.txt" if s else None),
24
+ inputs=[ignore_txt_in_glob], outputs=[fe])
25
+
26
+ dd.select(lambda s: gr.FileExplorer(root=s), inputs=[dd], outputs=[fe])
27
+ run.click(lambda s: ",".join(s) if isinstance(s, list) else s, inputs=[fe], outputs=[textbox])
28
+
29
+ with gr.Row():
30
+ a = gr.Textbox(elem_id="input-box")
31
+ a.change(lambda x: x, inputs=[a])
32
+
33
+
34
+ if __name__ == "__main__":
35
+ demo.launch()
demos/model3D/run.ipynb CHANGED
@@ -1 +1 @@
1
- {"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: model3D"]}, {"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/Bunny.obj https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/Bunny.obj\n", "!wget -q -O files/Duck.glb https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/Duck.glb\n", "!wget -q -O files/Fox.gltf https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/Fox.gltf\n", "!wget -q -O files/face.obj https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/face.obj\n", "!wget -q -O files/sofia.stl https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/sofia.stl\n", "!wget -q -O files/source.txt https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/source.txt"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "\n", "\n", "def load_mesh(mesh_file_name):\n", " return mesh_file_name\n", "\n", "\n", "demo = gr.Interface(\n", " fn=load_mesh,\n", " inputs=gr.Model3D(),\n", " outputs=gr.Model3D(\n", " clear_color=[0.0, 0.0, 0.0, 0.0], label=\"3D Model\"),\n", " examples=[\n", " [os.path.join(os.path.abspath(''), \"files/Bunny.obj\")],\n", " [os.path.join(os.path.abspath(''), \"files/Duck.glb\")],\n", " [os.path.join(os.path.abspath(''), \"files/Fox.gltf\")],\n", " [os.path.join(os.path.abspath(''), \"files/face.obj\")],\n", " [os.path.join(os.path.abspath(''), \"files/sofia.stl\")],\n", " ],\n", " cache_examples=True\n", ")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
 
1
+ {"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: model3D"]}, {"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/Bunny.obj https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/Bunny.obj\n", "!wget -q -O files/Duck.glb https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/Duck.glb\n", "!wget -q -O files/Fox.gltf https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/Fox.gltf\n", "!wget -q -O files/face.obj https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/face.obj\n", "!wget -q -O files/sofia.stl https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/sofia.stl\n", "!wget -q -O files/source.txt https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/source.txt"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "\n", "\n", "def load_mesh(mesh_file_name):\n", " return mesh_file_name\n", "\n", "\n", "demo = gr.Interface(\n", " fn=load_mesh,\n", " inputs=gr.Model3D(),\n", " outputs=gr.Model3D(\n", " clear_color=[0.0, 0.0, 0.0, 0.0], label=\"3D Model\"),\n", " examples=[\n", " [os.path.join(os.path.abspath(''), \"files/Bunny.obj\")],\n", " [os.path.join(os.path.abspath(''), \"files/Duck.glb\")],\n", " [os.path.join(os.path.abspath(''), \"files/Fox.gltf\")],\n", " [os.path.join(os.path.abspath(''), \"files/face.obj\")],\n", " [os.path.join(os.path.abspath(''), \"files/sofia.stl\")],\n", " [\"https://huggingface.co/datasets/dylanebert/3dgs/resolve/main/bonsai/bonsai-7k-mini.splat\"],\n", " [\"https://huggingface.co/datasets/dylanebert/3dgs/resolve/main/luigi/luigi.ply\"],\n", " ],\n", " cache_examples=True\n", ")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
demos/model3D/run.py CHANGED
@@ -17,6 +17,8 @@ demo = gr.Interface(
17
  [os.path.join(os.path.dirname(__file__), "files/Fox.gltf")],
18
  [os.path.join(os.path.dirname(__file__), "files/face.obj")],
19
  [os.path.join(os.path.dirname(__file__), "files/sofia.stl")],
 
 
20
  ],
21
  cache_examples=True
22
  )
 
17
  [os.path.join(os.path.dirname(__file__), "files/Fox.gltf")],
18
  [os.path.join(os.path.dirname(__file__), "files/face.obj")],
19
  [os.path.join(os.path.dirname(__file__), "files/sofia.stl")],
20
+ ["https://huggingface.co/datasets/dylanebert/3dgs/resolve/main/bonsai/bonsai-7k-mini.splat"],
21
+ ["https://huggingface.co/datasets/dylanebert/3dgs/resolve/main/luigi/luigi.ply"],
22
  ],
23
  cache_examples=True
24
  )
demos/stt_or_tts/run.ipynb CHANGED
@@ -1 +1 @@
1
- {"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: stt_or_tts"]}, {"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": ["import gradio as gr\n", "\n", "tts_examples = [\n", " \"I love learning machine learning\",\n", " \"How do you do?\",\n", "]\n", "\n", "tts_demo = gr.load(\n", " \"huggingface/facebook/fastspeech2-en-ljspeech\",\n", " title=None,\n", " examples=tts_examples,\n", " description=\"Give me something to say!\",\n", " cache_examples=False\n", ")\n", "\n", "stt_demo = gr.load(\n", " \"huggingface/facebook/wav2vec2-base-960h\",\n", " title=None,\n", " inputs=\"mic\",\n", " description=\"Let me try to guess what you're saying!\",\n", ")\n", "\n", "demo = gr.TabbedInterface([tts_demo, stt_demo], [\"Text-to-speech\", \"Speech-to-text\"])\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
 
1
+ {"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: stt_or_tts"]}, {"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": ["import gradio as gr\n", "\n", "tts_examples = [\n", " \"I love learning machine learning\",\n", " \"How do you do?\",\n", "]\n", "\n", "tts_demo = gr.load(\n", " \"huggingface/facebook/fastspeech2-en-ljspeech\",\n", " title=None,\n", " examples=tts_examples,\n", " description=\"Give me something to say!\",\n", ")\n", "\n", "stt_demo = gr.load(\n", " \"huggingface/facebook/wav2vec2-base-960h\",\n", " title=None,\n", " inputs=gr.Microphone(type=\"filepath\"),\n", " description=\"Let me try to guess what you're saying!\",\n", ")\n", "\n", "demo = gr.TabbedInterface([tts_demo, stt_demo], [\"Text-to-speech\", \"Speech-to-text\"])\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
demos/stt_or_tts/run.py CHANGED
@@ -10,13 +10,12 @@ tts_demo = gr.load(
10
  title=None,
11
  examples=tts_examples,
12
  description="Give me something to say!",
13
- cache_examples=False
14
  )
15
 
16
  stt_demo = gr.load(
17
  "huggingface/facebook/wav2vec2-base-960h",
18
  title=None,
19
- inputs="mic",
20
  description="Let me try to guess what you're saying!",
21
  )
22
 
 
10
  title=None,
11
  examples=tts_examples,
12
  description="Give me something to say!",
 
13
  )
14
 
15
  stt_demo = gr.load(
16
  "huggingface/facebook/wav2vec2-base-960h",
17
  title=None,
18
+ inputs=gr.Microphone(type="filepath"),
19
  description="Let me try to guess what you're saying!",
20
  )
21
 
requirements.txt CHANGED
@@ -1,6 +1,6 @@
1
 
2
- gradio-client @ git+https://github.com/gradio-app/gradio@8ff3a228bca9e09a634d9c880031b3f0592a280c#subdirectory=client/python
3
- https://gradio-builds.s3.amazonaws.com/8ff3a228bca9e09a634d9c880031b3f0592a280c/gradio-4.16.0-py3-none-any.whl
4
  pypistats==1.1.0
5
  plotly==5.10.0
6
  opencv-python==4.6.0.66
 
1
 
2
+ gradio-client @ git+https://github.com/gradio-app/gradio@766f25ab18c1fa401296b17e779a3036ccc7729e#subdirectory=client/python
3
+ https://gradio-builds.s3.amazonaws.com/766f25ab18c1fa401296b17e779a3036ccc7729e/gradio-4.19.0-py3-none-any.whl
4
  pypistats==1.1.0
5
  plotly==5.10.0
6
  opencv-python==4.6.0.66