Update app.py

app.py

@@ -2,32 +2,27 @@ import os
 import json
 import gradio as gr
 from transformers import Tool
-#from transformers.tools.base import push_to_hub
-from transformers.utils import TransformersHub
-
+from huggingface_hub import upload_folder
 
 def generate_files(title="Text Generation Tool", emoji="🌖", colorFrom="blue", colorTo="blue",
                    sdk="gradio", sdk_version="4.3.0", app_file="app.py", pinned=False,
                    tags=["tool"], tool_name="text_generator", tool_description="This is a tool that chats with a user. "
                    "It takes an input named `prompt` which contains a system_role, user_message, context and history. "
                    "It returns a text message."):
-    # Convert tags to a list if it's not already
-    #if not isinstance(tags, list):
-    #    tags = [tags]
     
     # Generate readme content
     readme_content = '''## readme
-    title: {}
-    emoji: {}
-    colorFrom: {}
-    colorTo: {}
-    sdk: {}
-    sdk_version: {}
-    app_file: {}
-    pinned: false
-    tags:
-      - tool
-    '''.format(title, emoji, colorFrom, colorTo, sdk, sdk_version, app_file)
+title: {}
+emoji: {}
+colorFrom: {}
+colorTo: {}
+sdk: {}
+sdk_version: {}
+app_file: {}
+pinned: false
+tags:
+  - tool
+'''.format(title, emoji, colorFrom, colorTo, sdk, sdk_version, app_file)
 
     # Generate tool config JSON content
     tool_config = {
@@ -39,64 +34,63 @@ def generate_files(title="Text Generation Tool", emoji="🌖", colorFrom="blue",
 
     # Generate app.py content
     app_py_content = '''from transformers.tools.base import launch_gradio_demo
-        from {} import {}Tool
-        launch_gradio_demo({}Tool)
-        '''.format(tool_name, tool_name.capitalize(), tool_name.capitalize())
+from {} import {}Tool
+launch_gradio_demo({}Tool)
+'''.format(tool_name, tool_name.capitalize(), tool_name.capitalize())
 
     # Generate requirements.txt content
     requirements_content = '''transformers>=4.29.0
-        # diffusers
-        accelerate
-        torch
-        '''
+# diffusers
+accelerate
+torch
+'''
 
     # Generate text_generator.py content
     text_generator_py_content = '''import os
-    from transformers import pipeline
-    class {}Tool(Tool):
-        name = "{}"
-        description = (
-            "{}"
-        )
-        inputs = ["text"]
-        outputs = ["text"]
-        def __call__(self, prompt: str):
-            token = os.environ['hf']
-            text_generator = pipeline(model="microsoft/Orca-2-13b", token=token)
-            generated_text = text_generator(prompt, max_length=500, num_return_sequences=1, temperature=0.7)
-            print(generated_text)
-            return generated_text
-    '''.format(tool_name.capitalize(), tool_name, tool_description)
-
-    os.makedirs("new", exist_ok=True)
+from transformers import pipeline
+class {}Tool(Tool):
+    name = "{}"
+    description = (
+        "{}"
+    )
+    inputs = ["text"]
+    outputs = ["text"]
+    def __call__(self, prompt: str):
+        token = os.environ['hf']
+        text_generator = pipeline(model="microsoft/Orca-2-13b", token=token)
+        generated_text = text_generator(prompt, max_length=500, num_return_sequences=1, temperature=0.7)
+        print(generated_text)
+        return generated_text
+'''.format(tool_name.capitalize(), tool_name, tool_description)
+
+    # Create a new folder for the tool
+    os.makedirs(tool_name, exist_ok=True)
 
     # Write content to files
-    with open("new/README.md", "w") as readme_file:
+    with open(f"{tool_name}/README.md", "w") as readme_file:
         readme_file.write(readme_content)
 
-    with open("new/tool_config.json", "w") as tool_config_file:
+    with open(f"{tool_name}/tool_config.json", "w") as tool_config_file:
         tool_config_file.write(tool_config_json)
 
-    with open("new/app.py", "w") as app_py_file:
+    with open(f"{tool_name}/app.py", "w") as app_py_file:
         app_py_file.write(app_py_content)
 
-    with open("new/requirements.txt", "w") as requirements_file:
+    with open(f"{tool_name}/requirements.txt", "w") as requirements_file:
         requirements_file.write(requirements_content)
 
-    with open("new/{}.py".format(tool_name), "w") as text_generator_py_file:
+    with open(f"{tool_name}/{tool_name}.py", "w") as text_generator_py_file:
         text_generator_py_file.write(text_generator_py_content)
 
-    # Upload the files to the Hugging Face Hub
-    hub = TransformersHub(organization="Chris4K")
-    hub.create(
-        model_id=tool_name,
-        repo_path="./new/",
-        commit_message="Upload {} tool".format(tool_name),
-        private=False
+    # Upload the folder to the Hugging Face Hub
+    upload_folder(
+        folder_path=tool_name,
+        repo_id="your_username/your_repo_name",
+        repo_type="space"
     )
 
     # Return the generated files for download
-    return "README.md", "tool_config.json", "app.py", "requirements.txt", "{}.py".format(tool_name)
+    return "README.md", "tool_config.json", "app.py", "requirements.txt", f"{tool_name}.py"
 
 
 # Define the inputs for the Gradio interface