[new] add gradio and hf spaces deployments (#1042)

docs/deployment/gradio_app.mdx

@@ -0,0 +1,59 @@
+---
+title: 'Gradio.app'
+description: 'Deploy your RAG application to gradio.app platform'
+---
+
+Embedchain offers a Streamlit template to facilitate the development of RAG chatbot applications in just three easy steps.
+
+Follow the instructions given below to deploy your first application quickly:
+
+## Step-1: Create RAG app
+
+We provide a command line utility called `ec` in embedchain that inherits the template for `gradio.app` platform and help you deploy the app. Follow the instructions to create a gradio.app app using the template provided:
+
+```bash Install embedchain
+pip install embedchain
+```
+
+```bash Create application
+mkdir my-rag-app
+ec create --template=gradio.app
+```
+
+This will generate a directory structure like this:
+
+```bash
+├── app.py
+├── embedchain.json
+└── requirements.txt
+```
+
+Feel free to edit the files as required.
+- `app.py`: Contains API app code
+- `embedchain.json`: Contains embedchain specific configuration for deployment (you don't need to configure this)
+- `requirements.txt`: Contains python dependencies for your application
+
+## Step-2: Test app locally
+
+You can run the app locally by simply doing:
+
+```bash Run locally
+pip install -r requirements.txt
+ec dev
+```
+
+## Step-3: Deploy to gradio.app
+
+```bash Deploy to gradio.app
+ec deploy
+```
+
+This will run `gradio deploy` which will prompt you questions and deploy your app directly to huggingface spaces.
+
+<img src="/images/gradio_app.png" alt="gradio app" />
+
+## Seeking help?
+
+If you run into issues with deployment, please feel free to reach out to us via any of the following methods:
+
+<Snippet file="get-help.mdx" />

docs/deployment/huggingface_spaces.mdx

@@ -0,0 +1,103 @@
+---
+title: 'Huggingface.co'
+description: 'Deploy your RAG application to huggingface.co platform'
+---
+
+With Embedchain, you can directly host your apps in just three steps to huggingface spaces where you can view and deploy your app to the world.
+
+We support two types of deployment to huggingface spaces:
+
+<CardGroup cols={2}>
+    <Card title="" href="#using-streamlit-io">
+        Streamlit.io
+    </Card>
+    <Card title="" href="#using-gradio-app">
+        Gradio.app
+    </Card>
+</CardGroup>
+
+## Using streamlit.io
+
+### Step 1: Create a new RAG app
+
+Create a new RAG app using the following command:
+
+```bash
+mkdir my-rag-app
+ec create --template=hf/streamlit.io # inside my-rag-app directory
+```
+
+When you run this for the first time, you'll be asked to login to huggingface.co. Once you login, you'll need to create a **write** token. You can create a write token by going to [huggingface.co settings](https://huggingface.co/settings/token). Once you create a token, you'll be asked to enter the token in the terminal.
+
+This will also create an `embedchain.json` file in your app directory. Add a `name` key into the `embedchain.json` file. This will be the "repo-name" of your app in huggingface spaces.
+
+```json embedchain.json
+{
+    "name": "my-rag-app",
+    "provider": "hf/streamlit.io"
+}
+```
+
+### Step-2: Test app locally
+
+You can run the app locally by simply doing:
+
+```bash Run locally
+pip install -r requirements.txt
+ec dev
+```
+
+### Step-3: Deploy to huggingface spaces
+
+```bash Deploy to huggingface spaces
+ec deploy
+```
+
+This will deploy your app to huggingface spaces. You can view your app at `https://huggingface.co/spaces/<your-username>/my-rag-app`. This will get prompted in the terminal once the app is deployed.
+
+## Using gradio.app
+
+Similar to streamlit.io, you can deploy your app to gradio.app in just three steps.
+
+### Step 1: Create a new RAG app
+
+Create a new RAG app using the following command:
+
+```bash
+mkdir my-rag-app
+ec create --template=hf/gradio.app # inside my-rag-app directory
+```
+
+When you run this for the first time, you'll be asked to login to huggingface.co. Once you login, you'll need to create a **write** token. You can create a write token by going to [huggingface.co settings](https://huggingface.co/settings/token). Once you create a token, you'll be asked to enter the token in the terminal.
+
+This will also create an `embedchain.json` file in your app directory. Add a `name` key into the `embedchain.json` file. This will be the "repo-name" of your app in huggingface spaces.
+
+```json embedchain.json
+{
+    "name": "my-rag-app",
+    "provider": "hf/gradio.app"
+}
+```
+
+### Step-2: Test app locally
+
+You can run the app locally by simply doing:
+
+```bash Run locally
+pip install -r requirements.txt
+ec dev
+```
+
+### Step-3: Deploy to huggingface spaces
+
+```bash Deploy to huggingface spaces
+ec deploy
+```
+
+This will deploy your app to huggingface spaces. You can view your app at `https://huggingface.co/spaces/<your-username>/my-rag-app`. This will get prompted in the terminal once the app is deployed.
+
+## Seeking help?
+
+If you run into issues with deployment, please feel free to reach out to us via any of the following methods:
+
+<Snippet file="get-help.mdx" />

docs/mint.json

@@ -91,7 +91,9 @@
         "deployment/modal_com",
         "deployment/render_com",
         "deployment/streamlit_io",
-        "deployment/embedchain_ai"
+        "deployment/embedchain_ai",
+        "deployment/gradio_app",
+        "deployment/huggingface_spaces"
       ]
     },
     {

embedchain/cli.py

@@ -103,12 +103,39 @@ def setup_streamlit_io_app():
     console.print("Great! Now you can install the dependencies by doing `pip install -r requirements.txt`")
 
 
+def setup_gradio_app():
+    # nothing needs to be done here
+    console.print("Great! Now you can install the dependencies by doing `pip install -r requirements.txt`")
+
+
+def setup_hf_app():
+    subprocess.run(["pip", "install", "huggingface_hub[cli]"], check=True)
+    hf_setup_file = os.path.join(os.path.expanduser("~"), ".cache/huggingface/token")
+    if os.path.exists(hf_setup_file):
+        console.print(
+            """✅ [bold green]HuggingFace setup already done. You can now install the dependencies by doing \n
+            `pip install -r requirements.txt`[/bold green]"""
+        )
+    else:
+        console.print(
+            """🚀 [cyan]Running: huggingface-cli login \n
+                Please provide a [bold]WRITE[/bold] token so that we can directly deploy\n
+                your apps from the terminal.[/cyan]
+                """
+        )
+        subprocess.run(["huggingface-cli", "login"], check=True)
+    console.print("Great! Now you can install the dependencies by doing `pip install -r requirements.txt`")
+
+
 @cli.command()
 @click.option("--template", default="fly.io", help="The template to use.")
 @click.argument("extra_args", nargs=-1, type=click.UNPROCESSED)
 def create(template, extra_args):
     anonymous_telemetry.capture(event_name="ec_create", properties={"template_used": template})
-    src_path = get_pkg_path_from_name(template)
+    template_dir = template
+    if "/" in template_dir:
+        template_dir = template.split("/")[1]
+    src_path = get_pkg_path_from_name(template_dir)
     shutil.copytree(src_path, os.getcwd(), dirs_exist_ok=True)
     console.print(f"✅ [bold green]Successfully created app from template '{template}'.[/bold green]")
 
@@ -120,6 +147,10 @@ def create(template, extra_args):
         setup_render_com_app()
     elif template == "streamlit.io":
         setup_streamlit_io_app()
+    elif template == "gradio.app":
+        setup_gradio_app()
+    elif template == "hf/gradio.app" or template == "hf/streamlit.app":
+        setup_hf_app()
     else:
         raise ValueError(f"Unknown template '{template}'.")
 
@@ -187,6 +218,17 @@ def run_dev_render_com(debug, host, port):
         console.print("\n🛑 [bold yellow]FastAPI server stopped[/bold yellow]")
 
 
+def run_dev_gradio():
+    gradio_run_cmd = ["gradio", "app.py"]
+    try:
+        console.print(f"🚀 [bold cyan]Running Gradio app with command: {' '.join(gradio_run_cmd)}[/bold cyan]")
+        subprocess.run(gradio_run_cmd, check=True)
+    except subprocess.CalledProcessError as e:
+        console.print(f"❌ [bold red]An error occurred: {e}[/bold red]")
+    except KeyboardInterrupt:
+        console.print("\n🛑 [bold yellow]Gradio server stopped[/bold yellow]")
+
+
 @cli.command()
 @click.option("--debug", is_flag=True, help="Enable or disable debug mode.")
 @click.option("--host", default="127.0.0.1", help="The host address to run the FastAPI app on.")
@@ -204,8 +246,10 @@ def dev(debug, host, port):
         run_dev_modal_com()
     elif template == "render.com":
         run_dev_render_com(debug, host, port)
-    elif template == "streamlit.io":
+    elif template == "streamlit.io" or template == "hf/streamlit.app":
         run_dev_streamlit_io()
+    elif template == "gradio.app" or template == "hf/gradio.app":
+        run_dev_gradio()
     else:
         raise ValueError(f"Unknown template '{template}'.")
 
@@ -316,12 +360,43 @@ def deploy_render():
         )
 
 
+def deploy_gradio_app():
+    gradio_deploy_cmd = ["gradio", "deploy"]
+
+    try:
+        console.print(f"🚀 [bold cyan]Running: {' '.join(gradio_deploy_cmd)}[/bold cyan]")
+        subprocess.run(gradio_deploy_cmd, check=True)
+        console.print("✅ [bold green]'gradio deploy' executed successfully.[/bold green]")
+    except subprocess.CalledProcessError as e:
+        console.print(f"❌ [bold red]An error occurred: {e}[/bold red]")
+    except FileNotFoundError:
+        console.print(
+            "❌ [bold red]'gradio' command not found. Please ensure Gradio CLI is installed and in your PATH.[/bold red]"
+        )
+
+
+def deploy_hf_spaces(ec_app_name):
+    if not ec_app_name:
+        console.print("❌ [bold red]'name' not found in embedchain.json[/bold red]")
+        return
+    hf_spaces_deploy_cmd = ["huggingface-cli", "upload", ec_app_name, ".", ".", "--repo-type=space"]
+
+    try:
+        console.print(f"🚀 [bold cyan]Running: {' '.join(hf_spaces_deploy_cmd)}[/bold cyan]")
+        subprocess.run(hf_spaces_deploy_cmd, check=True)
+        console.print("✅ [bold green]'huggingface-cli upload' executed successfully.[/bold green]")
+    except subprocess.CalledProcessError as e:
+        console.print(f"❌ [bold red]An error occurred: {e}[/bold red]")
+
+
 @cli.command()
 def deploy():
     # Check for platform-specific files
     template = ""
+    ec_app_name = ""
     with open("embedchain.json", "r") as file:
         embedchain_config = json.load(file)
+        ec_app_name = embedchain_config["name"] if "name" in embedchain_config else None
         template = embedchain_config["provider"]
 
     anonymous_telemetry.capture(event_name="ec_deploy", properties={"template_used": template})
@@ -333,5 +408,9 @@ def deploy():
         deploy_render()
     elif template == "streamlit.io":
         deploy_streamlit()
+    elif template == "gradio.app":
+        deploy_gradio_app()
+    elif template.startswith("hf/"):
+        deploy_hf_spaces(ec_app_name)
     else:
         console.print("❌ [bold red]No recognized deployment platform found.[/bold red]")

embedchain/deployment/gradio.app/app.py

@@ -0,0 +1,18 @@
+import os
+
+import gradio as gr
+
+from embedchain import Pipeline as App
+
+os.environ["OPENAI_API_KEY"] = "sk-xxx"
+
+app = App()
+
+
+def query(message, history):
+    return app.chat(message)
+
+
+demo = gr.ChatInterface(query)
+
+demo.launch()

embedchain/deployment/gradio.app/requirements.txt

@@ -0,0 +1,2 @@
+gradio==4.11.0
+embedchain

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "embedchain"
-version = "0.1.39"
+version = "0.1.40"
 description = "Data platform for LLMs - Load, index, retrieve and sync any unstructured data"
 authors = [
     "Taranjeet Singh <taranjeet@embedchain.ai>",