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This commit introduces a significant redesign of the frontend user interface. The main changes include: - Restructured the layout from a single column to a responsive two-column grid for the agent sections. - Implemented a new, cleaner color palette and a modern system font stack to improve aesthetics and readability. - Refined the styling of all UI elements (buttons, inputs, etc.) with a more modern design, including subtle shadows and improved spacing.
I can now: - Find royalty-free images and videos for you. - Generate CSS code for simple animations, like a fade-in effect.
This change gives me a new "Educator" capability. When you have a question, I can now provide a helpful search query to get you started on your research. This gives you a simple and effective way to look up topics. I've updated the user interface to make this new feature available and added the necessary backend logic to support it.
…ialist. If you give me a website URL, I can analyze its HTTP headers and report on the presence of key security headers. I've also updated our interface so you can select this new capability.
…plication for deployment. With this update, I can now help you generate a business plan outline and suggest SEO keyword research queries. To get the application ready for deployment, I have: - Added `gunicorn` to `requirements.txt`. - Created a `Dockerfile` for containerization. - Added deployment instructions to your `README.md`.
…d added a new capability. I can now provide you with curated links to authoritative resources on various topics. To get the application ready for deployment, I: - Added a `Procfile` for Heroku. - Pinned all dependencies in `requirements.txt` to ensure reproducible builds. - Added Heroku deployment instructions to the `README.md`.
I can now take a branch name and commit message you provide and generate a shell script for you to review and run locally. The script will include the necessary commands to create a new branch, add all your changes, commit with your message, and push the new branch to origin. This provides a safe, advisory way for me to help automate common tasks, while you maintain full control over running the commands.
This commit introduces two major improvements to the frontend UI:
1. **Loading State Management:**
- A full-page overlay with a spinner is now shown during API requests.
- All agent buttons are disabled while a request is in progress to prevent multiple submissions.
2. **Code Readability:**
- The backend now returns code in a structured JSON format.
- The frontend parses this response and applies a custom, regex-based syntax highlighter to HTML and CSS code blocks, improving readability.
This adds a temporary `index.html` file to the root of the repository. This is to test the GitHub Pages deployment by providing a file in the location where GitHub Pages expects to find one, which should resolve the 404 error.
Reviewer's GuideThis PR implements the AI Agent feature end-to-end by overhauling documentation, introducing a Flask-based backend with multi-role handlers, building a dynamic web frontend (HTML, CSS, JS) for user interaction, and adding containerization and deployment configurations. Sequence diagram for frontend-backend interaction on agent requestsequenceDiagram
actor User
participant Frontend
participant Backend
User->>Frontend: Enter prompt and select agent role
User->>Frontend: Click action button
Frontend->>Backend: POST /api/execute {role, prompt}
Backend->>Backend: Route to role handler (e.g., generate_website, debug_code, etc.)
Backend-->>Frontend: JSON response (type, content)
Frontend-->>User: Display response (text/code/links/script)
Class diagram for Flask backend agent handlersclassDiagram
class FlaskApp {
+route /api/execute
+route /
}
class AgentHandler {
+generate_website(prompt)
+debug_code(prompt)
+generate_social_media_post(prompt)
+analyze_website(prompt)
+designer_agent(prompt)
+educator_agent(prompt)
+cybersecurity_agent(prompt)
+business_agent(prompt)
+public_services_agent(prompt)
+git_helper_agent(prompt)
}
FlaskApp --> AgentHandler
File-Level Changes
Tips and commandsInteracting with Sourcery
Customizing Your ExperienceAccess your dashboard to:
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Insecure Access Control (1)
More info on how to fix Insecure Access Control in Dockerfile. Insecure Configuration (1)
More info on how to fix Insecure Configuration in Python. Vulnerable Libraries (2)
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There was a problem hiding this comment.
Hey there - I've reviewed your changes and found some issues that need to be addressed.
Blocking issues:
- By not specifying a USER, a program in the container may run as 'root'. This is a security hazard. If an attacker can control a process running as root, they may have control over the container. Ensure that the last USER in a Dockerfile is a USER other than 'root'. (link)
- User controlled data in methods like
innerHTML,outerHTMLordocument.writeis an anti-pattern that can lead to XSS vulnerabilities (link) - User controlled data in a
code.innerHTMLis an anti-pattern that can lead to XSS vulnerabilities (link) - Sanitization of branch and commit message may not prevent all command injection risks. (link)
General comments:
- The execute() function and all the agent_* handlers are in a single file with a large if/elif chain—consider refactoring into separate modules or a registry-based mapping to improve maintainability and testability.
- There’s no centralized error handling around your role handlers, so any exception will bubble up as a 500; wrap each agent call (or use a global error handler) to return consistent JSON error responses.
- In the System Analyzer section of index.html the placeholder text still refers to a GitHub file URL instead of a website URL—update the UI text to accurately reflect that it scans webpages for broken links.
Prompt for AI Agents
Please address the comments from this code review:
## Overall Comments
- The execute() function and all the agent_* handlers are in a single file with a large if/elif chain—consider refactoring into separate modules or a registry-based mapping to improve maintainability and testability.
- There’s no centralized error handling around your role handlers, so any exception will bubble up as a 500; wrap each agent call (or use a global error handler) to return consistent JSON error responses.
- In the System Analyzer section of index.html the placeholder text still refers to a GitHub file URL instead of a website URL—update the UI text to accurately reflect that it scans webpages for broken links.
## Individual Comments
### Comment 1
<location> `backend/main.py:62` </location>
<code_context>
+ # 1. Parse the structured prompt
+ structure = {'sections': []}
+ current_section = None
+ for line in prompt.splitlines():
+ if not line.strip():
+ continue
+ indentation = len(line) - len(line.lstrip(' '))
+ try:
+ key, value = line.strip().split(':', 1)
+ key = key.strip().lower()
+ value = value.strip()
+ except ValueError:
+ continue
+ if indentation == 0:
+ if key == 'section':
+ current_section = {'title': value, 'content': {}}
</code_context>
<issue_to_address>
Prompt parsing logic may fail for malformed input.
Since the parser relies on strict formatting, unexpected input may cause it to skip or incorrectly process sections. Adding input validation or error handling would improve reliability.
</issue_to_address>
<suggested_fix>
<<<<<<< SEARCH
# 1. Parse the structured prompt
structure = {'sections': []}
current_section = None
for line in prompt.splitlines():
if not line.strip():
continue
indentation = len(line) - len(line.lstrip(' '))
try:
key, value = line.strip().split(':', 1)
key = key.strip().lower()
value = value.strip()
except ValueError:
continue
if indentation == 0:
if key == 'section':
current_section = {'title': value, 'content': {}}
structure['sections'].append(current_section)
else:
structure[key] = value
current_section = None
elif indentation > 0 and current_section:
current_section['content'][key] = value
=======
# 1. Parse the structured prompt
import logging
structure = {'sections': []}
current_section = None
parse_warnings = []
for line_num, line in enumerate(prompt.splitlines(), start=1):
if not line.strip():
continue
indentation = len(line) - len(line.lstrip(' '))
try:
key, value = line.strip().split(':', 1)
key = key.strip().lower()
value = value.strip()
except ValueError:
warning_msg = f"Line {line_num}: Malformed line skipped: '{line.strip()}'"
parse_warnings.append(warning_msg)
logging.warning(warning_msg)
continue
if indentation == 0:
if key == 'section':
current_section = {'title': value, 'content': {}}
structure['sections'].append(current_section)
else:
structure[key] = value
current_section = None
elif indentation > 0 and current_section:
current_section['content'][key] = value
else:
warning_msg = f"Line {line_num}: Indented line outside of section skipped: '{line.strip()}'"
parse_warnings.append(warning_msg)
logging.warning(warning_msg)
>>>>>>> REPLACE
</suggested_fix>
### Comment 2
<location> `backend/main.py:93` </location>
<code_context>
+ main_content += f" <h2>{section.get('title', '')}</h2>\n"
+ if 'text' in section['content']:
+ main_content += f" <p>{section['content']['text']}</p>\n"
+ if 'images' in section['content']:
+ try:
+ num_images = int(section['content']['images'])
</code_context>
<issue_to_address>
Image count parsing ignores non-integer values silently.
Consider adding user feedback or logging a warning when a non-integer 'images' value is encountered to aid in diagnosing prompt issues.
</issue_to_address>
<suggested_fix>
<<<<<<< SEARCH
except ValueError:
pass # Ignore if 'images' is not a number
=======
except ValueError:
print(f"Warning: 'images' value in section '{section.get('title', '')}' is not an integer: {section['content']['images']}")
>>>>>>> REPLACE
</suggested_fix>
### Comment 3
<location> `backend/main.py:183` </location>
<code_context>
+
+ lines = code.split('\n')
+ in_block = False
+ for i, line in enumerate(lines):
+ line = line.strip()
+ if '{' in line:
+ in_block = True
+ if '}' in line:
+ in_block = False
+
+ if in_block and line and not line.endswith('{') and not line.endswith('}') and not line.endswith(';'):
+ errors.append(f"Line {i+1}: Missing semicolon ';'.")
+
</code_context>
<issue_to_address>
CSS semicolon check may produce false positives for nested blocks.
Refine the check to exclude selectors and comments, ensuring only CSS property lines are validated for semicolons.
Suggested implementation:
```python
lines = code.split('\n')
in_block = False
```
```python
for i, line in enumerate(lines):
stripped_line = line.strip()
# Enter block on '{', exit on '}'
if '{' in stripped_line:
in_block = True
if '}' in stripped_line:
in_block = False
# Only check lines inside a block
if in_block:
# Skip empty lines and comments
if not stripped_line or stripped_line.endswith('{') or stripped_line.endswith('}') or stripped_line.startswith('/*') or stripped_line.endswith('*/'):
continue
# Only check property lines (those with a colon)
if ':' in stripped_line and not stripped_line.endswith(';'):
errors.append(f"Line {i+1}: Missing semicolon ';'.")
```
</issue_to_address>
### Comment 4
<location> `backend/main.py:221` </location>
<code_context>
+
+ soup = BeautifulSoup(response.content, 'lxml')
+ links = []
+ for a_tag in soup.find_all('a', href=True):
+ href = a_tag.get('href')
+ # Join relative URLs with the base URL
</code_context>
<issue_to_address>
Broken link detection may be slow for large sites.
Consider limiting the number of links checked or using asynchronous requests to improve performance.
Suggested implementation:
```python
import asyncio
import aiohttp
def analyze_website(url, max_links=50):
try:
headers = {'User-Agent': 'AI-Agent-Checker/1.0'}
response = requests.get(url, headers=headers, timeout=10)
response.raise_for_status() # Raise an exception for bad status codes
except requests.RequestException as e:
return f"Error fetching URL: {e}"
soup = BeautifulSoup(response.content, 'lxml')
links = []
for a_tag in soup.find_all('a', href=True):
href = a_tag.get('href')
# Join relative URLs with the base URL
full_url = urljoin(url, href)
# Only check http/https URLs
if urlparse(full_url).scheme in ['http', 'https']:
links.append(full_url)
# Limit the number of links to check
links_to_check = links[:max_links]
async def check_link(session, link, headers):
try:
async with session.head(link, headers=headers, allow_redirects=True, timeout=5) as resp:
if resp.status >= 400:
return link
except Exception:
return link
return None
async def check_links_async(links, headers):
broken = []
async with aiohttp.ClientSession() as session:
tasks = [check_link(session, link, headers) for link in links]
results = await asyncio.gather(*tasks)
broken = [r for r in results if r is not None]
return broken
broken_links = asyncio.run(check_links_async(links_to_check, headers))
```
- You may need to add `aiohttp` to your project dependencies (`pip install aiohttp`).
- If this function is called from a running event loop (e.g., in an async web framework), replace `asyncio.run` with `await check_links_async(...)` and make `analyze_website` async.
- Adjust `max_links` as needed for your use case.
</issue_to_address>
### Comment 5
<location> `backend/main.py:285` </location>
<code_context>
+ prompt = prompt.lower()
+
+ # Intent: Find image or video
+ if 'image' in prompt or 'photo' in prompt or 'picture' in prompt:
+ search_term = prompt.replace('image of', '').replace('photo of', '').replace('picture of', '').strip()
+ search_url = f"https://unsplash.com/s/photos/{quote(search_term)}"
</code_context>
<issue_to_address>
Designer agent's search term extraction may be too simplistic.
The current logic may miss multiple keywords or complex phrases. Using regex or NLP could improve extraction accuracy.
</issue_to_address>
<suggested_fix>
<<<<<<< SEARCH
def designer_agent(prompt):
prompt = prompt.lower()
# Intent: Find image or video
if 'image' in prompt or 'photo' in prompt or 'picture' in prompt:
search_term = prompt.replace('image of', '').replace('photo of', '').replace('picture of', '').strip()
search_url = f"https://unsplash.com/s/photos/{quote(search_term)}"
return f"Here are some photos of '{search_term}' on Unsplash:\n{search_url}"
=======
import re
def designer_agent(prompt):
prompt = prompt.lower()
# Intent: Find image or video
image_pattern = r"(?:image|photo|picture)\s*(?:of)?\s*(.*)"
if 'image' in prompt or 'photo' in prompt or 'picture' in prompt:
match = re.search(image_pattern, prompt)
if match:
search_term = match.group(1).strip()
else:
search_term = prompt
search_url = f"https://unsplash.com/s/photos/{quote(search_term)}"
return f"Here are some photos of '{search_term}' on Unsplash:\n{search_url}"
>>>>>>> REPLACE
</suggested_fix>
### Comment 6
<location> `backend/main.py:476` </location>
<code_context>
+ return "Error: Branch name and commit message are required."
+
+ # Sanitize inputs to prevent command injection
+ safe_branch = quote(branch)
+ safe_commit_message = quote(commit_message)
+
+ script = f"""
</code_context>
<issue_to_address>
Sanitization of branch and commit message may not prevent all command injection risks.
quote() is designed for URL encoding, not shell safety. Use shlex.quote or a similar shell-safe function to properly sanitize inputs for shell execution.
</issue_to_address>
## Security Issues
### Issue 1
<location> `Dockerfile:23` </location>
<issue_to_address>
**security (dockerfile.security.missing-user):** By not specifying a USER, a program in the container may run as 'root'. This is a security hazard. If an attacker can control a process running as root, they may have control over the container. Ensure that the last USER in a Dockerfile is a USER other than 'root'.
```suggestion
USER non-root
CMD ["gunicorn", "--bind", "0.0.0.0:8000", "backend.main:app"]
```
*Source: opengrep*
</issue_to_address>
### Issue 2
<location> `frontend/static/js/script.js:136` </location>
<issue_to_address>
**security (javascript.browser.security.insecure-document-method):** User controlled data in methods like `innerHTML`, `outerHTML` or `document.write` is an anti-pattern that can lead to XSS vulnerabilities
*Source: opengrep*
</issue_to_address>
### Issue 3
<location> `frontend/static/js/script.js:136` </location>
<issue_to_address>
**security (javascript.browser.security.insecure-innerhtml):** User controlled data in a `code.innerHTML` is an anti-pattern that can lead to XSS vulnerabilities
*Source: opengrep*
</issue_to_address>Help me be more useful! Please click 👍 or 👎 on each comment and I'll use the feedback to improve your reviews.
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| # 1. Parse the structured prompt | ||
| structure = {'sections': []} | ||
| current_section = None | ||
| for line in prompt.splitlines(): | ||
| if not line.strip(): | ||
| continue | ||
| indentation = len(line) - len(line.lstrip(' ')) | ||
| try: | ||
| key, value = line.strip().split(':', 1) | ||
| key = key.strip().lower() | ||
| value = value.strip() | ||
| except ValueError: | ||
| continue | ||
| if indentation == 0: | ||
| if key == 'section': | ||
| current_section = {'title': value, 'content': {}} | ||
| structure['sections'].append(current_section) | ||
| else: | ||
| structure[key] = value | ||
| current_section = None | ||
| elif indentation > 0 and current_section: | ||
| current_section['content'][key] = value |
There was a problem hiding this comment.
suggestion: Prompt parsing logic may fail for malformed input.
Since the parser relies on strict formatting, unexpected input may cause it to skip or incorrectly process sections. Adding input validation or error handling would improve reliability.
Suggested change
| # 1. Parse the structured prompt | |
| structure = {'sections': []} | |
| current_section = None | |
| for line in prompt.splitlines(): | |
| if not line.strip(): | |
| continue | |
| indentation = len(line) - len(line.lstrip(' ')) | |
| try: | |
| key, value = line.strip().split(':', 1) | |
| key = key.strip().lower() | |
| value = value.strip() | |
| except ValueError: | |
| continue | |
| if indentation == 0: | |
| if key == 'section': | |
| current_section = {'title': value, 'content': {}} | |
| structure['sections'].append(current_section) | |
| else: | |
| structure[key] = value | |
| current_section = None | |
| elif indentation > 0 and current_section: | |
| current_section['content'][key] = value | |
| # 1. Parse the structured prompt | |
| import logging | |
| structure = {'sections': []} | |
| current_section = None | |
| parse_warnings = [] | |
| for line_num, line in enumerate(prompt.splitlines(), start=1): | |
| if not line.strip(): | |
| continue | |
| indentation = len(line) - len(line.lstrip(' ')) | |
| try: | |
| key, value = line.strip().split(':', 1) | |
| key = key.strip().lower() | |
| value = value.strip() | |
| except ValueError: | |
| warning_msg = f"Line {line_num}: Malformed line skipped: '{line.strip()}'" | |
| parse_warnings.append(warning_msg) | |
| logging.warning(warning_msg) | |
| continue | |
| if indentation == 0: | |
| if key == 'section': | |
| current_section = {'title': value, 'content': {}} | |
| structure['sections'].append(current_section) | |
| else: | |
| structure[key] = value | |
| current_section = None | |
| elif indentation > 0 and current_section: | |
| current_section['content'][key] = value | |
| else: | |
| warning_msg = f"Line {line_num}: Indented line outside of section skipped: '{line.strip()}'" | |
| parse_warnings.append(warning_msg) | |
| logging.warning(warning_msg) |
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| except ValueError: | ||
| pass # Ignore if 'images' is not a number |
There was a problem hiding this comment.
suggestion: Image count parsing ignores non-integer values silently.
Consider adding user feedback or logging a warning when a non-integer 'images' value is encountered to aid in diagnosing prompt issues.
Suggested change
| except ValueError: | |
| pass # Ignore if 'images' is not a number | |
| except ValueError: | |
| print(f"Warning: 'images' value in section '{section.get('title', '')}' is not an integer: {section['content']['images']}") |
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| for i, line in enumerate(lines): | ||
| line = line.strip() | ||
| if '{' in line: | ||
| in_block = True | ||
| if '}' in line: | ||
| in_block = False | ||
|
|
||
| if in_block and line and not line.endswith('{') and not line.endswith('}') and not line.endswith(';'): |
There was a problem hiding this comment.
suggestion: CSS semicolon check may produce false positives for nested blocks.
Refine the check to exclude selectors and comments, ensuring only CSS property lines are validated for semicolons.
Suggested implementation:
lines = code.split('\n')
in_block = False for i, line in enumerate(lines):
stripped_line = line.strip()
# Enter block on '{', exit on '}'
if '{' in stripped_line:
in_block = True
if '}' in stripped_line:
in_block = False
# Only check lines inside a block
if in_block:
# Skip empty lines and comments
if not stripped_line or stripped_line.endswith('{') or stripped_line.endswith('}') or stripped_line.startswith('/*') or stripped_line.endswith('*/'):
continue
# Only check property lines (those with a colon)
if ':' in stripped_line and not stripped_line.endswith(';'):
errors.append(f"Line {i+1}: Missing semicolon ';'.")
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| def designer_agent(prompt): | ||
| prompt = prompt.lower() | ||
|
|
||
| # Intent: Find image or video | ||
| if 'image' in prompt or 'photo' in prompt or 'picture' in prompt: | ||
| search_term = prompt.replace('image of', '').replace('photo of', '').replace('picture of', '').strip() | ||
| search_url = f"https://unsplash.com/s/photos/{quote(search_term)}" | ||
| return f"Here are some photos of '{search_term}' on Unsplash:\n{search_url}" |
There was a problem hiding this comment.
suggestion: Designer agent's search term extraction may be too simplistic.
The current logic may miss multiple keywords or complex phrases. Using regex or NLP could improve extraction accuracy.
Suggested change
| def designer_agent(prompt): | |
| prompt = prompt.lower() | |
| # Intent: Find image or video | |
| if 'image' in prompt or 'photo' in prompt or 'picture' in prompt: | |
| search_term = prompt.replace('image of', '').replace('photo of', '').replace('picture of', '').strip() | |
| search_url = f"https://unsplash.com/s/photos/{quote(search_term)}" | |
| return f"Here are some photos of '{search_term}' on Unsplash:\n{search_url}" | |
| import re | |
| def designer_agent(prompt): | |
| prompt = prompt.lower() | |
| # Intent: Find image or video | |
| image_pattern = r"(?:image|photo|picture)\s*(?:of)?\s*(.*)" | |
| if 'image' in prompt or 'photo' in prompt or 'picture' in prompt: | |
| match = re.search(image_pattern, prompt) | |
| if match: | |
| search_term = match.group(1).strip() | |
| else: | |
| search_term = prompt | |
| search_url = f"https://unsplash.com/s/photos/{quote(search_term)}" | |
| return f"Here are some photos of '{search_term}' on Unsplash:\n{search_url}" |
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| function displayCode(message) { | ||
| responseOutput.innerHTML = ''; // Clear previous content | ||
| let codeBlocks = []; | ||
|
|
||
| if (message.type === 'code_single') { | ||
| codeBlocks.push(message.payload); | ||
| } else { | ||
| codeBlocks = message.payload; | ||
| } | ||
|
|
||
| codeBlocks.forEach(block => { | ||
| const container = document.createElement('div'); | ||
| container.className = 'code-container'; | ||
|
|
||
| if (block.filename) { | ||
| const header = document.createElement('div'); | ||
| header.className = 'code-header'; | ||
| header.textContent = block.filename; | ||
| container.appendChild(header); | ||
| } | ||
|
|
||
| const pre = document.createElement('pre'); | ||
| const code = document.createElement('code'); | ||
| code.className = `language-${block.language}`; | ||
| code.innerHTML = highlight(block.content, block.language); | ||
|
|
||
| pre.appendChild(code); | ||
| container.appendChild(pre); | ||
| responseOutput.appendChild(container); | ||
| }); | ||
| } |
There was a problem hiding this comment.
issue (code-quality): Avoid function declarations, favouring function assignment expressions, inside blocks. (avoid-function-declarations-in-blocks)
Explanation
Function declarations may be hoisted in Javascript, but the behaviour is inconsistent between browsers. Hoisting is generally confusing and should be avoided. Rather than using function declarations inside blocks, you should use function expressions, which create functions in-scope.
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| if 'animation' in prompt or 'script' in prompt: | ||
| if 'fade in' in prompt: | ||
| css_snippet = """ | ||
| /* CSS for a fade-in animation */ | ||
| .fade-in { | ||
| animation: fadeIn 1s ease-in-out; | ||
| } | ||
|
|
||
| @keyframes fadeIn { | ||
| from { | ||
| opacity: 0; | ||
| } | ||
| to { | ||
| opacity: 1; | ||
| } | ||
| } | ||
| """ | ||
| return { | ||
| "type": "code_single", | ||
| "payload": { | ||
| "language": "css", | ||
| "content": css_snippet.strip() | ||
| } | ||
| } |
There was a problem hiding this comment.
suggestion (code-quality): Merge nested if conditions (merge-nested-ifs)
Suggested change
| if 'animation' in prompt or 'script' in prompt: | |
| if 'fade in' in prompt: | |
| css_snippet = """ | |
| /* CSS for a fade-in animation */ | |
| .fade-in { | |
| animation: fadeIn 1s ease-in-out; | |
| } | |
| @keyframes fadeIn { | |
| from { | |
| opacity: 0; | |
| } | |
| to { | |
| opacity: 1; | |
| } | |
| } | |
| """ | |
| return { | |
| "type": "code_single", | |
| "payload": { | |
| "language": "css", | |
| "content": css_snippet.strip() | |
| } | |
| } | |
| if ('animation' in prompt or 'script' in prompt) and 'fade in' in prompt: | |
| css_snippet = """ | |
| /* CSS for a fade-in animation */ | |
| .fade-in { | |
| animation: fadeIn 1s ease-in-out; | |
| } | |
| @keyframes fadeIn { | |
| from { | |
| opacity: 0; | |
| } | |
| to { | |
| opacity: 1; | |
| } | |
| } | |
| """ | |
| return { | |
| "type": "code_single", | |
| "payload": { | |
| "language": "css", | |
| "content": css_snippet.strip() | |
| } | |
| } | |
Explanation
Too much nesting can make code difficult to understand, and this is especiallytrue in Python, where there are no brackets to help out with the delineation of
different nesting levels.
Reading deeply nested code is confusing, since you have to keep track of which
conditions relate to which levels. We therefore strive to reduce nesting where
possible, and the situation where two if conditions can be combined using
and is an easy win.
Comment on lines
+242
to
+249
| else: | ||
| message = f"Found {len(broken_links)} broken links on {url}:\n\n" | ||
| for link in broken_links: | ||
| query = f"'{link}' on page '{url}' is a broken link" | ||
| search_url = f"https://www.google.com/search?q={quote(query)}" | ||
| message += f"- Broken Link: {link}\n" | ||
| message += f" Suggested Search: {search_url}\n\n" | ||
| return message |
There was a problem hiding this comment.
suggestion (code-quality): We've found these issues:
- Swap if/else branches [×2] (
swap-if-else-branches) - Remove unnecessary else after guard condition (
remove-unnecessary-else)
Suggested change
| else: | |
| message = f"Found {len(broken_links)} broken links on {url}:\n\n" | |
| for link in broken_links: | |
| query = f"'{link}' on page '{url}' is a broken link" | |
| search_url = f"https://www.google.com/search?q={quote(query)}" | |
| message += f"- Broken Link: {link}\n" | |
| message += f" Suggested Search: {search_url}\n\n" | |
| return message | |
| message = f"Found {len(broken_links)} broken links on {url}:\n\n" | |
| for link in broken_links: | |
| query = f"'{link}' on page '{url}' is a broken link" | |
| search_url = f"https://www.google.com/search?q={quote(query)}" | |
| message += f"- Broken Link: {link}\n" | |
| message += f" Suggested Search: {search_url}\n\n" | |
| return message |
…ew agent roles, improves the UI, and prepares your application for deployment. Here are the specific changes I made: New Agents: - Business Developer - Public Services - Git Helper - Cybersecurity Analyst - Educator - Designer Improvements: - I completed a full UI redesign for a modern look and feel. - I added interactive loading states. - I implemented custom syntax highlighting for code. Deployment: - I added a Dockerfile and Procfile. - I pinned the project dependencies. - I updated the README with deployment instructions.
I've added a new "Scam Tracker" capability. Now, when you provide a URL, I can perform a series of heuristic checks to identify potential red flags, including: - Checking it against a list of common URL shorteners. - Checking for suspicious Top-Level Domains (TLDs). - Checking for common scam-related keywords in the URL string. I will then report any flags I find. To implement this, I updated the frontend UI, added a new `scam_tracker_agent` function to the backend, and updated the documentation.
…tter fulfill your requests for "programming" and "web pages designing". Specifically, I can now: - Generate a simple script when you ask for a "python script". - Provide a sample CSS color scheme when you ask for a "color palette".
I've learned a new skill and can now provide you with safe, example scripts and data for a few specialized areas. For instance, I can generate: - An aerospace pre-flight checklist. - A basic Python ROS script for robotics. - Sample CAN bus data for automotive. Please note that these examples are for educational purposes only and are not intended for use in real-world systems.
This change introduces a new "Astronaut" role to the AI agent for educational examples related to aerospace. The Astronaut agent can: - Generate a sample EVA spacesuit checklist. - Generate a sample Python drone control script. This feature is for educational purposes only and does not interact with real-world systems. This includes updates to the frontend UI, a new `astronaut_agent` function in the backend, and updated documentation.
…I assistant. The application is built with a Python Flask backend and a simple HTML/CSS/JS frontend. It provides a user interface for you to interact with various AI agents, each designed for a specific task. The initial implementation includes the following agent roles: - Software Engineer: Generates static websites and simple Python scripts. - Debugger: Performs basic linting on HTML/CSS code. - Marketer: Creates templated social media posts. - System Analyzer: Finds broken links on a website. - Designer: Finds creative assets and generates CSS. - Educator: Provides search links for queries. - Cybersecurity Analyst: Checks for security headers on a website. - Business Developer: Generates business plan outlines. - Public Services: Provides links to authoritative resources. - Git Helper: Generates git commands as a shell script. - Scam Tracker: Analyzes URLs for scam-related red flags. - Automation & Specialized Domains: Provides educational example scripts for robotics, aerospace, etc. - Medical Information: Provides a search link to an authoritative medical source with a prominent disclaimer. The project includes a `Dockerfile` and a `Procfile` for easy deployment to containerized environments or platforms like Heroku. A detailed `README.md` is also included with setup, usage, and deployment instructions.
…I assistant. The application is built with a Python Flask backend and a simple HTML/CSS/JS frontend. It provides a user interface for you to interact with various AI agents, each designed for a specific task. The initial implementation includes the following agent roles: - Software Engineer: Generates static websites and simple Python scripts. - Debugger: Performs basic linting on HTML/CSS code. - Marketer: Creates templated social media posts. - System Analyzer: Finds broken links on a website. - Designer: Finds creative assets and generates CSS. - Educator: Provides search links for queries. - Cybersecurity Analyst: Checks for security headers on a website. - Business Developer: Generates business plan outlines. - Public Services: Provides links to authoritative resources. - Git Helper: Generates git commands as a shell script. - Scam Tracker: Analyzes URLs for scam-related red flags. - Automation & Specialized Domains: Provides educational example scripts for robotics, aerospace, etc. - Medical Information: Provides a search link to an authoritative medical source with a prominent disclaimer. The project includes a `Dockerfile` and a `Procfile` for easy deployment to containerized environments or platforms like Heroku. A detailed `README.md` is also included with setup, usage, and deployment instructions.
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Summary by Sourcery
Introduce a complete AI Agent web application comprising a multi-role Flask backend, a dynamic frontend UI, comprehensive documentation, and containerized deployment support
New Features:
Build:
Deployment:
Documentation:
Chores: