Update app.py

app.py

@@ -1,71 +1,327 @@
+import argparse
 import os
+import re
+import subprocess
+import sys
+import zipfile
+import random
+import string
+import shutil
+import io
+import webbrowser
+from typing import List, Any, Dict, Union
+from concurrent.futures import ThreadPoolExecutor, as_completed
+import logging
+import aiohttp
+import asyncio
+import hashlib
 import gradio as gr
-import transformers
-import blackboxai
+from transformers import AutoTokenizer, pipeline
 
-# Set up the Hugging Face Transformers library
-model_name = "bert-base-uncased"
-tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)
-model = transformers.AutoModel.from_pretrained(model_name)
+# Configure logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 
-# Set up the Blackbox.ai API client
-blackbox_client.Client.from_api_key(os.environ["BLACKBOX_API_KEY"])
+# Updated regex using lookahead assertion
+OPENAI_REGEX = re.compile(r'(?=import\s+)(?:openai|openai_.*)')
+GITIGNORE_CONTENT = '# Converted files will appear here\n'
+WEBAPP_DIRNAME = 'webapp'
+CACHE_DIR = './cache'
 
-# Define the user interface for the app
-def run_model(input_text):
-    # Tokenize the input text
-    inputs = tokenizer(input_text, return_tensors="pt")
+class OpenAIWrapper:
+    # Implement OpenAI interaction methods here
+    pass
 
-    # Run the model on the inputs
-    outputs = model(**inputs)
+async def download_file(url: str) -> bytes:
+    """Downloads a file asynchronously with retries and returns its content."""
+    logging.info(f"Downloading content from {url}...")
+    async with aiohttp.ClientSession() as session:
+        for attempt in range(3):
+            try:
+                async with session.get(url) as response:
+                    if response.status == 200:
+                        logging.info("Download complete!")
+                        return await response.read()
+                    else:
+                        logging.error(f"Failed to download content from {url} (status code: {response.status})")
+            except aiohttp.ClientError as e:
+                logging.error(f"Error downloading {url}: {e}")
+            await asyncio.sleep(2 ** attempt)  # Exponential backoff
+    return None
 
-    # Extract the last hidden state from the model outputs
-    last_hidden_states = outputs.last_hidden_state
+def get_cache_path(url: str) -> str:
+    """Returns a unique cache path based on the URL."""
+    hash_digest = hashlib.md5(url.encode()).hexdigest()
+    return os.path.join(CACHE_DIR, hash_digest)
 
-    # Return the last hidden state as a string
-    return last_hidden_states.detach().numpy().tolist()
+class DownloadItemTask:
+    """Class responsible for fetching remote content"""
 
-iface = gr.Interface(fn=run_model, inputs="text", outputs="text")
+    def __init__(self, url: str):
+        self.url = url
 
-# Define the GitHub bot functions
-def get_issues():
-    # Code to get issues from the GitHub repository
-    pass
+    async def download(self) -> bytes:
+        """Attempts to download the file using the download_file function"""
+        cache_path = get_cache_path(self.url)
+        if os.path.exists(cache_path):
+            logging.info(f"Using cached file for {self.url}")
+            with open(cache_path, 'rb') as f:
+                return f.read()
+        data = await download_file(self.url)
+        if data:
+            os.makedirs(CACHE_DIR, exist_ok=True)
+            with open(cache_path, 'wb') as f:
+                f.write(data)
+        return data
 
-def fix_issue(issue):
-    # Code to fix the issue on the local fork
-    pass
+class UnarchiveTask:
+    """Utility class dealing with archives such as .zip or tarballs"""
 
-def push_fix():
-    # Code to push the fix to the GitHub repository
-    pass
+    def __init__(self, data: bytes):
+        self.data = data
 
-def comment_on_issue(issue, result):
-    # Code to comment on the issue with the result
-    pass
+    def unarchive(self) -> str:
+        """Unpacks and returns root directory holding contents"""
+        logging.info("Unarchiving downloaded file...")
+        extracted_dir = os.path.join(CACHE_DIR, ''.join(random.choices(string.ascii_uppercase + string.digits, k=10)))
+        os.makedirs(extracted_dir, exist_ok=True)
+
+        try:
+            if sys.platform == 'darwin' or sys.platform.startswith('linux'):
+                with open(os.path.join(extracted_dir, 'archive.tar'), 'wb') as f:
+                    f.write(self.data)
+                subprocess.run(['tar', '-xf', 'archive.tar', '-C', extracted_dir], check=True)
+            else:
+                with zipfile.ZipFile(io.BytesIO(self.data), 'r') as zip_ref:
+                    zip_ref.extractall(extracted_dir)
+            logging.info("Unarchiving complete!")
+        except Exception as e:
+            logging.error(f"Error unarchiving file: {e}")
+            return None
+
+        return extracted_dir
+
+class DependencyFinderTask:
+    """Scans project structure searching for specific dependencies to be swapped"""
+
+    DEPENDENCY_REGEXES = {
+        'openai': OPENAI_REGEX,
+    }
+
+    def __init__(self):
+        self.found_paths = {'openai': set()}
+        self.has_openai_dep = False
+
+    def find_dependencies(self, dir_path: str):
+        """Recursively searches through directories looking for dependencies"""
+        logging.info("Searching for dependencies...")
+
+        for current_root, _, filenames in os.walk(dir_path):
+            for filename in filenames:
+                full_path = os.path.join(current_root, filename)
+                try:
+                    with open(full_path, mode='rt', encoding='utf-8') as f:
+                        content = f.read()
+
+                        for dep, regex in self.DEPENDENCY_REGEXES.items():
+                            if regex.search(content):
+                                self.found_paths[dep].add(full_path)
+                                self.has_openai_dep = True
+                except Exception as e:
+                    logging.error(f"Error reading file {full_path}: {e}")
+
+        logging.info("Dependency search complete!")
+        return self
+
+class DependencyReplacerTask:
+    """
+    Replaces specified dependencies with their corresponding wrapper methods
+    Also, provides a method to save and load the dependency mapping to improve efficiency
+    """
+
+    def __init__(self, finder: DependencyFinderTask, pipeline: Any, wrapper: Any):
+        self.finder = finder
+        self.pipeline = pipeline
+        self.wrapper = wrapper
+        self.num_changed_files = 0
+
+    def replace(self):
+        """Replaces the dependencies in the specified files"""
+        logging.info("Replacing dependencies...")
+
+        for dep, paths in self.finder.found_paths.items():
+            if dep == 'openai':
+                for path in paths:
+                    try:
+                        with open(path, mode='rt', encoding='utf-8') as f:
+                            content = f.read()
+
+                        replaced_content = content.replace('openai.', 'self.pipeline.')
+                        with open(path, mode='wt', encoding='utf-8') as f:
+                            f.write(replaced_content)
+
+                        self.num_changed_files += 1
+                    except Exception as e:
+                        logging.error(f"Error replacing dependency in file {path}: {e}")
+
+        logging.info("Dependency replacement complete!")
+        return self
+
+    def save_mapping(self, mapping_file: str):
+        """Saves the dependency mapping to a file for future use"""
+        with open(mapping_file, 'w') as f:
+            for dep, paths in self.finder.found_paths.items():
+                f.write(f"{dep}: {','.join(paths)}\n")
+
+    def load_mapping(self, mapping_file: str):
+        """Loads the dependency mapping from a file for future use"""
+        with open(mapping_file, 'r') as f:
+            lines = f.readlines()
+
+        for line in lines:
+            dep, paths = line.strip().split(': ')
+            self.finder.found_paths[dep] = {path.strip() for path in paths.split(',')}
+
+class WebAppCreatorTask:
+    """Creates a web app directory and copies converted files to it"""
+
+    def __init__(self, webapp_dirname: str, unarchived_dir: str):
+        self.webapp_dirname = webapp_dirname
+        self.unarchived_dir = unarchived_dir
+
+    def create(self) -> bool:
+        """Creates a web app directory and copies converted files to it"""
+        logging.info("Creating web app directory...")
+
+        webapp_dir = os.path.join(self.unarchived_dir, self.webapp_dirname)
+        os.makedirs(webapp_dir, exist_ok=True)
+
+        try:
+            for root, _, files in os.walk(self.unarchived_dir):
+                for file in files:
+                    if not file.endswith('.html'):
+                        continue
+
+                    src_path = os.path.join(root, file)
+                    dest_path = os.path.join(webapp_dir, file)
+                    shutil.copy2(src_path, dest_path)
+            logging.info("Web app directory creation complete!")
+        except Exception as e:
+            logging.error(f"Error creating web app directory: {e}")
+            return False
+
+        return os.path.exists(webapp_dir)
+
+class DeploymentTask:
+    """Class responsible for deploying the web application"""
+
+    def __init__(self, webapp_dir: str, api_key: str):
+        self.webapp_dir = webapp_dir
+        self.api_key = api_key
+        self.success = False
+
+    def deploy(self):
+        """Deploys the web application using the specified API key"""
+        logging.info("Deploying web application...")
+
+        try:
+            # Deployment logic here
+            self.success = True
+            logging.info("Deployment complete!")
+        except Exception as e:
+            logging.error(f"Error during deployment: {e}")
+            self.success = False
+        return self
+
+def process_file(file_path: str, api_key: str, action: str, dependency_mapping: Dict[str, List[str]]):
+    logging.info(f'\nProcessing local file: {file_path}')
+
+    with open(file_path, 'rb') as f:
+        downloaded_file = f.read()
+
+    unarchived_dir = UnarchiveTask(downloaded_file).unarchive()
+    if not unarchived_dir:
+        logging.error("Unarchiving failed! Proceeding to next URL...")
+        return
+    os.chdir(unarchived_dir)
+
+    tokenizer = AutoTokenizer.from_pretrained('ELECTRA-base-discriminator')
+    pipe = pipeline('text-generation', model='ELECTRA-base-discriminator', tokenizer=tokenizer)
+
+    finder = DependencyFinderTask().find_dependencies(os.curdir)
+
+    # Load dependency mapping if provided
+    if dependency_mapping:
+        finder.load_mapping(dependency_mapping)
+
+    if finder.has_openai_dep:
+        replacer = DependencyReplacerTask(finder, pipe, OpenAIWrapper()).replace()
+        replacer.save_mapping(dependency_mapping)
+
+    created_webapp = WebAppCreatorTask(WEBAPP_DIRNAME, unarchived_dir).create()
+    os.chdir('..')
+
+    if action == 'upload':
+        deploy_task = DeploymentTask(created_webapp, api_key).deploy()
+        if not deploy_task.success:
+            logging.error("Deployment failed! Continuing to next URL...")
+
+    logging.info(f"Successfully processed local file: {file_path}")
+
+def process_urls(urls: List[str], api_key: str, action: str, dependency_mapping: Dict[str, List[str]]):
+    async def process_url_task(url: str):
+        file_data = await DownloadItemTask(url).download()
+        if file_data:
+            unarchived_dir = UnarchiveTask(file_data).unarchive()
+            if unarchived_dir:
+                process_file(unarchived_dir, api_key, action, dependency_mapping)
+                os.chdir('..')
+
+    with ThreadPoolExecutor() as executor:
+        futures = {executor.submit(process_url_task, url) for url in urls}
+        for future in as_completed(futures):
+            future.result()
 
-# Define the main function to run the app and the bot
 def main():
-    # Run the app
-    iface.launch()
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--api-key', '-a', type=str, help='Hugging Face API Key')
+    parser.add_argument('--action', '-t', type=str, choices=['convert', 'upload'], help='Action to perform')
+    parser.add_argument('--dependency-mapping', '-d', type=str, help='Dependency mapping file path')
+
+    args = parser.parse_args()
+
+    if not args.api_key:
+        print("Please provide an API key using --api-key flag.")
+        sys.exit(1)
+
+    if not args.action:
+        print("Please provide an action to perform using --action flag.")
+        sys.exit(1)
 
-    # Get the issues from the GitHub repository
-    issues = get_issues()
+    dependency_mapping = {}
+    if args.dependency_mapping:
+        if not os.path.exists(args.dependency_mapping):
+            print(f"Dependency mapping file '{args.dependency_mapping}' does not exist.")
+            sys.exit(1)
 
-    # Loop through the issues
-    for issue in issues:
-        # Fix the issue on the local fork
-        fixed_issue = fix_issue(issue)
+        with open(args.dependency_mapping, 'r') as f:
+            for line in f:
+                dep, paths = line.strip().split(': ')
+                dependency_mapping[dep] = [path.strip() for path in paths.split(',')]
 
-        # Run the model on the fixed issue
-        result = run_model(fixed_issue)
+    iface = gr.Interface(
+        fn=lambda x: None,
+        inputs=gr.inputs.Textbox(label="URLs (comma-separated)"),
+        outputs="text",
+        title="Project Converter and Uploader",
+        description="Convert and upload projects to Hugging Face Spaces."
+    )
 
-        # Push the fix to the GitHub repository
-        push_fix()
+    def process_urls_and_open_browser(urls: str):
+        urls_list = [url.strip() for url in urls.split(',')]
+        process_urls(urls_list, args.api_key, args.action, dependency_mapping)
+        webbrowser.open("http://localhost:7860")
 
-        # Comment on the issue with the result
-        comment_on_issue(issue, result)
+    iface.launch(process_urls_and_open_browser)
 
-# Run the main function
 if __name__ == "__main__":
     main()