Update app.py

app.py

@@ -1,35 +1,99 @@
-class WebAppTemplate:
-    def __init__(self, template: str, output_path: str):
-        self.template = template
-        self.output_path = output_path
-
-    def generate_code(self, user_input: dict) -> str:
-        # Generate the code based on the user_input and the app template
-        tokenizer, model = load_model(user_input["model_name"], user_input["model_path"])
-        # Use the tokenizer and model to generate the code
-        pass
-
-    def load_model(self, model_name: str, model_path: str) -> Any:
-        tokenizer = AutoTokenizer.from_pretrained(model_path)
-        model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
-        return tokenizer, model
-
-    def main(self, port: int = 8000, debug: bool = False) -> None:
-        # Implement the main function that creates the Gradio interface and launches the app
-        pass
+import os
+import sys
+import time
 
-if __name__ == "__main__":
-    # Initialize the app template
-    app_template = WebAppTemplate("template.txt", "output_path")
+import huggingface_hub
+
+from huggingface_hub.commands import HfFolder
+
+import transformers
+
+from transformers import pipeline
+
+import gradio as gr
+
+import tempfile
+
+from huggingface_hub import HfFolder
 
-    # Get user input
-    user_input = get_user_input()
+def main():
+    # Get the user's idea
+    idea = input("What is your idea for an application? ")
 
-    # Generate the code
-    generated_code = app_template.generate_code(user_input)
+    # Generate the code for the application
+    code = gemmacode.generate(idea)
 
-    # Save the generated code
-    save_generated_code(generated_code)
+    # Test the code
+    try:
+        transformers.pipeline("text-generation")(code)
+    except Exception as e:
+        print("The code failed to run:", e)
+        return
 
-    # Launch the app
-    app_template.main(port=8000, debug=False)
+    # Ensure the functionality of the application
+    try:
+        gr.Interface(fn=transformers.pipeline("text-generation"), inputs=gr.Textbox(), outputs=gr.Textbox()).launch()
+    except Exception as e:
+        print("The application failed to run:", e)
+        return
+
+    # Provide an embedded webapp demo of the user's idea implementation
+    try:
+        hf_folder = HfFolder(path=tempfile.mkdtemp())
+        hf_folder.save(code)
+        hf_folder.push_to_hub(repo_id="acecalisto3/gemmacode-demo", commit_message="Initial commit")
+        print(f"The demo is available at: https://huggingface.co/acecalisto3/gemmacode-demo")
+    except Exception as e:
+        print("The demo failed to launch:", e)
+        return
+
+    # Offer the option to rebuild or deploy
+    while True:
+        choice = input("Do you want to rebuild or deploy the application? (r/d/q) ")
+        if choice == "r":
+            # Rebuild the code
+            code = gemmacode.generate(idea)
+
+            # Test the code
+            try:
+                transformers.pipeline("text-generation")(code)
+            except Exception as e:
+                print("The code failed to run:", e)
+                return
+
+            # Ensure the functionality of the application
+            try:
+                gr.Interface(fn=transformers.pipeline("text-generation"), inputs=gr.Textbox(), outputs=gr.Textbox()).launch()
+            except Exception as e:
+                print("The application failed to run:", e)
+                return
+
+            # Provide an embedded webapp demo of the user's idea implementation
+            try:
+                hf_folder = HfFolder(path=tempfile.mkdtemp())
+                hf_folder.save(code)
+                hf_folder.push_to_hub(repo_id="acecalisto3/gemmacode-demo", commit_message="Initial commit")
+                print(f"The demo is available at: https://huggingface.co/acecalisto3/gemmacode-demo")
+            except Exception as e:
+                print("The demo failed to launch:", e)
+                return
+        elif choice == "d":
+            # Deploy the application
+            try:
+                api_token = os.environ["HF_TOKEN"]
+                hub = huggingface_hub.HfApi(api_token=api_token)
+                hub.create_repo(name="my-app", organization="my-org")
+                hf_folder = HfFolder(path=tempfile.mkdtemp())
+                hf_folder.save(code)
+                hf_folder.push_to_hub(repo_id="my-org/my-app", commit_message="Initial commit")
+                print("The application has been deployed to: https://huggingface.co/my-org/my-app")
+            except Exception as e:
+                print("The application failed to deploy:", e)
+                return
+        elif choice == "q":
+            break
+        else:
+            print("Invalid choice")
+
+if __name__ == "__main__":
+    main()