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Dockerfile

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+FROM python:3.10
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+# Set up a new user named "user" with user ID 1000
+RUN useradd -m -u 1000 user
+# Switch to the "user" user
+USER user
+# Set home to the user's home directory
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH
+
+# Set the working directory to the user's home directory
+WORKDIR $HOME/app
+
+# Copy the current directory contents into the container at $HOME/app setting the owner to the user
+COPY --chown=user . $HOME/app
+
+CMD ["lite", "demo.yaml", "launch", "--server_name", "0.0.0.0", "--server_port", "7860"]

demo.yaml

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+lite_metadata:
+  gradio_version: 3.32.0
+class_string: gradio.interface.Interface
+kwargs:
+  title: Gradio Webapp
+  description: Given an array of distinct integers candidates and a target integer
+    target, return a list of all unique combinations of candidates where the chosen
+    numbers sum to target
+  article: null
+  thumbnail: null
+  theme: gradio/seafoam
+  css: null
+  allow_flagging: never
+  inputs:
+    class_string: liteobj.listify
+    args:
+    - class_string: gradio.components.Dataframe
+      kwargs:
+        label: candidates
+        type: array
+    - class_string: gradio.components.Number
+      kwargs:
+        label: target
+        precision: 0
+  outputs:
+    class_string: liteobj.listify
+    args:
+    - class_string: gradio.components.Dataframe
+      kwargs:
+        label: output
+        type: array
+  fn:
+    class_string: gradify.gradify_closure
+    kwargs:
+      argmaps:
+        class_string: liteobj.listify
+        args:
+        - label: candidates
+          postprocessing: 'lambda array: list(map(int, array[0]))'
+        - label: target
+          postprocessing: null
+      func_kwargs: {}
+      ldict:
+        class_string: gradify.exec_to_dict
+        kwargs:
+          source: "def combinationSum(candidates, target):\n    res = []\n\n    def\
+            \ backtrack(start, path, target):\n        if target == 0:\n         \
+            \   res.append(path)\n            return\n        for i in range(start,\
+            \ len(candidates)):\n            if candidates[i] > target:\n        \
+            \        break\n            backtrack(i, path + [candidates[i]], target\
+            \ - candidates[i])\n    backtrack(0, [], target)\n    return res\n"

gradify.py

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+
+
+def gradify_closure(ldict, argmaps, func_kwargs={}):
+    
+    from types import FunctionType
+    for k, v in ldict.items():
+        if isinstance(v, FunctionType):
+            func = ldict.pop(k)
+            break
+
+    globals().update(ldict)
+    func_kwargs = dict(func_kwargs)
+
+    def gradify_func(*args):
+        
+        try:
+            for (arg, argmap) in zip(args, argmaps):
+
+                postprocessing = argmap.get("postprocessing", None)
+                if postprocessing:
+                    arg = eval(postprocessing)(arg)
+                    
+                kw_label = argmap["label"]
+                func_kwargs[kw_label] = arg
+
+            return func(**func_kwargs)
+        except Exception as e:
+            import gradio as gr
+            raise gr.Error(f"Error: {e}")
+
+    return gradify_func
+
+def exec_to_dict(source, target=None):
+
+    ldict = {}
+    exec(source, globals(), ldict)
+
+    return ldict.get(target, None) if target else ldict

requirements.txt

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+gradio==3.32
+liteobj==0.0.4