2 new options added for the ai assistant. First, describe images, which *should* describe any images on the screen. The second is browse for image, which will provide a description for the selected image specifically.
This commit is contained in:
Storm Dragon
@@ -23,5 +23,5 @@
|
||||
# Fork of Orca Screen Reader (GNOME)
|
||||
# Original source: https://gitlab.gnome.org/GNOME/orca
|
||||
|
||||
version = "2025.08.11"
|
||||
version = "2025.08.12"
|
||||
codeName = "testing"
|
||||
|
||||
@@ -1868,14 +1868,10 @@ class CthulhuSetupGUI(cthulhu_gtkbuilder.GtkBuilderWrapper):
|
||||
# Set provider combo
|
||||
provider = prefs.get("aiProvider", settings.aiProvider)
|
||||
providerIndex = 0 # Default to Claude Code
|
||||
if provider == settings.AI_PROVIDER_CLAUDE:
|
||||
if provider == settings.AI_PROVIDER_GEMINI:
|
||||
providerIndex = 1
|
||||
elif provider == settings.AI_PROVIDER_CHATGPT:
|
||||
providerIndex = 2
|
||||
elif provider == settings.AI_PROVIDER_GEMINI:
|
||||
providerIndex = 3
|
||||
elif provider == settings.AI_PROVIDER_OLLAMA:
|
||||
providerIndex = 4
|
||||
providerIndex = 2
|
||||
self.aiProviderCombo.set_active(providerIndex)
|
||||
|
||||
# Set API key file
|
||||
@@ -1926,8 +1922,8 @@ class CthulhuSetupGUI(cthulhu_gtkbuilder.GtkBuilderWrapper):
|
||||
|
||||
def _updateProviderControls(self, provider):
|
||||
"""Update visibility/sensitivity of provider-specific controls."""
|
||||
# API key controls (needed for Claude, ChatGPT, Gemini - not for Claude Code or Ollama)
|
||||
api_key_needed = provider in [settings.AI_PROVIDER_CLAUDE, settings.AI_PROVIDER_CHATGPT, settings.AI_PROVIDER_GEMINI]
|
||||
# API key controls (only needed for Gemini - not for Claude Code or Ollama)
|
||||
api_key_needed = provider in [settings.AI_PROVIDER_GEMINI]
|
||||
self.aiApiKeyEntry.set_sensitive(api_key_needed)
|
||||
|
||||
# Get Claude API Key button (only for Claude Code)
|
||||
@@ -3695,8 +3691,7 @@ class CthulhuSetupGUI(cthulhu_gtkbuilder.GtkBuilderWrapper):
|
||||
|
||||
def aiProviderChanged(self, widget):
|
||||
"""AI Provider combo box changed handler"""
|
||||
providers = [settings.AI_PROVIDER_CLAUDE_CODE, settings.AI_PROVIDER_CLAUDE,
|
||||
settings.AI_PROVIDER_CHATGPT, settings.AI_PROVIDER_GEMINI, settings.AI_PROVIDER_OLLAMA]
|
||||
providers = [settings.AI_PROVIDER_CLAUDE_CODE, settings.AI_PROVIDER_GEMINI, settings.AI_PROVIDER_OLLAMA]
|
||||
activeIndex = widget.get_active()
|
||||
if 0 <= activeIndex < len(providers):
|
||||
provider = providers[activeIndex]
|
||||
|
||||
@@ -39,9 +39,21 @@ class AIProvider(ABC):
|
||||
"""Suggest actions to accomplish a user's request."""
|
||||
pass
|
||||
|
||||
@abstractmethod
|
||||
def analyze_images(self, user_question, screenshot_data, accessibility_data):
|
||||
"""Analyze images visible on screen, focusing on visual content rather than UI elements."""
|
||||
pass
|
||||
|
||||
def _prepare_system_prompt(self, task_type):
|
||||
"""Prepare system prompt based on task type."""
|
||||
base_prompt = """You are an AI assistant helping a screen reader user navigate and interact with computer applications. You have access to:
|
||||
if task_type == "image":
|
||||
base_prompt = """You are an AI assistant helping a screen reader user analyze image files. You have access to a single image file that the user has selected for analysis.
|
||||
|
||||
The user is using the Cthulhu screen reader, so they cannot see images visually. Your task is to provide detailed visual descriptions of the image content to make it accessible.
|
||||
|
||||
"""
|
||||
else:
|
||||
base_prompt = """You are an AI assistant helping a screen reader user navigate and interact with computer applications. You have access to:
|
||||
|
||||
1. A screenshot of the current screen
|
||||
2. Detailed accessibility tree information about UI elements
|
||||
@@ -101,119 +113,26 @@ Example for "find edit box and enter text":
|
||||
|
||||
🚨 NEVER GIVE PROGRAMMING CODE OR TECHNICAL INSTRUCTIONS"""
|
||||
|
||||
elif task_type == "image":
|
||||
return base_prompt + """Your task: Analyze and describe any images visible on the screen, focusing on visual content rather than UI elements.
|
||||
|
||||
IMPORTANT IMAGE ANALYSIS GUIDELINES:
|
||||
- Focus ONLY on the visual content of images (photos, diagrams, graphics, artwork)
|
||||
- IGNORE UI elements like buttons, menus, toolbars, window frames
|
||||
- Describe what you see IN the images: objects, people, scenes, colors, text within images
|
||||
- If multiple images are visible, describe each one separately
|
||||
- For photographs: describe the scene, subjects, lighting, composition
|
||||
- For diagrams/charts: describe the data, relationships, labels shown
|
||||
- For screenshots within images: describe the content being shown
|
||||
- Be detailed about visual elements that a screen reader user cannot access
|
||||
|
||||
If no images are clearly visible on screen, say so clearly.
|
||||
|
||||
Keep descriptions informative and well-structured."""
|
||||
|
||||
return base_prompt
|
||||
|
||||
|
||||
class ClaudeProvider(AIProvider):
|
||||
"""Claude AI provider using Anthropic's API."""
|
||||
|
||||
def __init__(self, api_key, model="claude-3-5-sonnet-20241022", **kwargs):
|
||||
super().__init__(api_key, model, **kwargs)
|
||||
self.base_url = "https://api.anthropic.com/v1/messages"
|
||||
self.headers = {
|
||||
"Content-Type": "application/json",
|
||||
"X-API-Key": self.api_key,
|
||||
"anthropic-version": "2023-06-01"
|
||||
}
|
||||
|
||||
def describe_screen(self, screenshot_data, accessibility_data):
|
||||
"""Generate a description using Claude."""
|
||||
try:
|
||||
prompt = self._build_prompt("describe", None, accessibility_data)
|
||||
return self._make_request(prompt, screenshot_data)
|
||||
except Exception as e:
|
||||
logger.error(f"Claude describe error: {e}")
|
||||
return f"Error getting screen description: {e}"
|
||||
|
||||
def answer_question(self, question, screenshot_data, accessibility_data):
|
||||
"""Answer a question using Claude."""
|
||||
try:
|
||||
prompt = self._build_prompt("question", question, accessibility_data)
|
||||
return self._make_request(prompt, screenshot_data)
|
||||
except Exception as e:
|
||||
logger.error(f"Claude question error: {e}")
|
||||
return f"Error answering question: {e}"
|
||||
|
||||
def suggest_actions(self, request, screenshot_data, accessibility_data):
|
||||
"""Suggest actions using Claude."""
|
||||
try:
|
||||
prompt = self._build_prompt("action", request, accessibility_data)
|
||||
return self._make_request(prompt, screenshot_data)
|
||||
except Exception as e:
|
||||
logger.error(f"Claude action error: {e}")
|
||||
return f"Error suggesting actions: {e}"
|
||||
|
||||
def _build_prompt(self, task_type, user_input, accessibility_data):
|
||||
"""Build the complete prompt for Claude."""
|
||||
prompt = f"Current accessibility information:\n```json\n{json.dumps(accessibility_data, indent=2)}\n```\n\n"
|
||||
|
||||
if task_type == "describe":
|
||||
prompt += "Please describe what's on this screen."
|
||||
elif task_type == "question":
|
||||
prompt += f"User question: {user_input}"
|
||||
elif task_type == "action":
|
||||
prompt += f"User wants to: {user_input}\n\nPlease suggest specific steps to accomplish this."
|
||||
|
||||
return prompt
|
||||
|
||||
def _make_request(self, prompt, screenshot_data):
|
||||
"""Make request to Claude API."""
|
||||
try:
|
||||
# Prepare the message content
|
||||
content = [
|
||||
{
|
||||
"type": "text",
|
||||
"text": prompt
|
||||
}
|
||||
]
|
||||
|
||||
# Add screenshot if available
|
||||
if screenshot_data:
|
||||
content.append({
|
||||
"type": "image",
|
||||
"source": {
|
||||
"type": "base64",
|
||||
"media_type": f"image/{screenshot_data['format']}",
|
||||
"data": screenshot_data['data']
|
||||
}
|
||||
})
|
||||
|
||||
payload = {
|
||||
"model": self.model,
|
||||
"max_tokens": 1000,
|
||||
"messages": [
|
||||
{
|
||||
"role": "user",
|
||||
"content": content
|
||||
}
|
||||
],
|
||||
"system": self._prepare_system_prompt("describe") # Will be made dynamic later
|
||||
}
|
||||
|
||||
response = requests.post(
|
||||
self.base_url,
|
||||
headers=self.headers,
|
||||
json=payload,
|
||||
timeout=30
|
||||
)
|
||||
|
||||
if response.status_code == 200:
|
||||
result = response.json()
|
||||
return result['content'][0]['text']
|
||||
else:
|
||||
error_msg = f"Claude API error {response.status_code}: {response.text}"
|
||||
logger.error(error_msg)
|
||||
return error_msg
|
||||
|
||||
except requests.RequestException as e:
|
||||
error_msg = f"Network error contacting Claude: {e}"
|
||||
logger.error(error_msg)
|
||||
return error_msg
|
||||
except Exception as e:
|
||||
error_msg = f"Unexpected error with Claude API: {e}"
|
||||
logger.error(error_msg)
|
||||
return error_msg
|
||||
|
||||
|
||||
class ClaudeCodeProvider(AIProvider):
|
||||
"""Claude Code CLI provider - uses installed Claude Code application."""
|
||||
@@ -249,34 +168,98 @@ class ClaudeCodeProvider(AIProvider):
|
||||
logger.error(f"Claude Code action error: {e}")
|
||||
return f"Error suggesting actions: {e}"
|
||||
|
||||
def analyze_images(self, user_question, screenshot_data, accessibility_data):
|
||||
"""Analyze images visible on screen using Claude Code CLI."""
|
||||
try:
|
||||
prompt = self._build_prompt("image", user_question, accessibility_data)
|
||||
|
||||
# If we have image data, save it to a temporary file for Claude Code
|
||||
temp_image_path = None
|
||||
if screenshot_data:
|
||||
import tempfile
|
||||
import base64
|
||||
import os
|
||||
|
||||
# Create temporary file with appropriate extension
|
||||
image_format = screenshot_data.get('format', 'png')
|
||||
suffix = f".{image_format}"
|
||||
|
||||
with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as temp_file:
|
||||
# Decode base64 image data and write to temp file
|
||||
image_data = base64.b64decode(screenshot_data['data'])
|
||||
temp_file.write(image_data)
|
||||
temp_image_path = temp_file.name
|
||||
|
||||
try:
|
||||
# Call Claude Code with the image file path
|
||||
result = self._call_claude_code(prompt, temp_image_path)
|
||||
return result
|
||||
finally:
|
||||
# Clean up temporary file
|
||||
if os.path.exists(temp_image_path):
|
||||
os.unlink(temp_image_path)
|
||||
else:
|
||||
# No image data, just call with text prompt
|
||||
return self._call_claude_code(prompt)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Claude Code image analysis error: {e}")
|
||||
return f"Error analyzing images: {e}"
|
||||
|
||||
def _build_prompt(self, task_type, user_input, accessibility_data):
|
||||
"""Build the complete prompt for Claude Code."""
|
||||
import json
|
||||
|
||||
system_prompt = self._get_system_prompt(task_type)
|
||||
|
||||
prompt = f"{system_prompt}\n\nCurrent accessibility information:\n```json\n{json.dumps(accessibility_data, indent=2)}\n```\n\n"
|
||||
|
||||
if task_type == "describe":
|
||||
prompt += "Please describe what's on this screen."
|
||||
elif task_type == "question":
|
||||
prompt += f"User question: {user_input}"
|
||||
elif task_type == "action":
|
||||
prompt += f"User wants to: {user_input}\n\nProvide the action analysis in the required format."
|
||||
if task_type == "image":
|
||||
# For image analysis, minimize accessibility data weight
|
||||
if user_input == "ANALYZE_SINGLE_IMAGE_FILE":
|
||||
prompt = f"{system_prompt}\n\nAnalyze and describe the single image file provided. Focus on visual content only - describe what you see in the image: objects, people, scenery, colors, text, composition, and any other visual details."
|
||||
else:
|
||||
prompt = f"{system_prompt}\n\nCurrent screen context (focus on images):\n"
|
||||
if user_input:
|
||||
prompt += f"User question about images: {user_input}\n\n"
|
||||
prompt += "Analyze and describe any images visible on this screen. Focus on visual content, not UI elements."
|
||||
else:
|
||||
# Standard prompt with full accessibility data
|
||||
prompt = f"{system_prompt}\n\nCurrent accessibility information:\n```json\n{json.dumps(accessibility_data, indent=2)}\n```\n\n"
|
||||
|
||||
if task_type == "describe":
|
||||
prompt += "Please describe what's on this screen."
|
||||
elif task_type == "question":
|
||||
prompt += f"User question: {user_input}"
|
||||
elif task_type == "action":
|
||||
prompt += f"User wants to: {user_input}\n\nProvide the action analysis in the required format."
|
||||
|
||||
return prompt
|
||||
|
||||
def _call_claude_code(self, prompt):
|
||||
"""Call Claude Code CLI with the prompt."""
|
||||
def _call_claude_code(self, prompt, image_path=None):
|
||||
"""Call Claude Code CLI with the prompt and optional image."""
|
||||
import subprocess
|
||||
import tempfile
|
||||
import os
|
||||
|
||||
try:
|
||||
# Call Claude Code CLI with the prompt directly
|
||||
# Build the command
|
||||
cmd = ['claude', '--print', '--output-format', 'text']
|
||||
|
||||
# For accessibility analysis, skip permission checks to allow automatic access
|
||||
cmd.append('--dangerously-skip-permissions')
|
||||
|
||||
# If we have an image path, include it in the prompt
|
||||
if image_path:
|
||||
prompt = f"Please analyze and describe the image at {image_path}. {prompt}"
|
||||
|
||||
# Add the prompt
|
||||
cmd.append(prompt)
|
||||
|
||||
# Call Claude Code CLI
|
||||
result = subprocess.run(
|
||||
['claude', '--print', '--output-format', 'text', prompt],
|
||||
cmd,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=60
|
||||
timeout=120 # Longer timeout for image analysis
|
||||
)
|
||||
|
||||
if result.returncode == 0:
|
||||
@@ -297,7 +280,14 @@ class ClaudeCodeProvider(AIProvider):
|
||||
|
||||
def _get_system_prompt(self, task_type):
|
||||
"""Get system prompt for Claude Code."""
|
||||
base_prompt = """You are Claude Code helping a screen reader user navigate and interact with computer applications. You have expert understanding of terminal commands, programming, and accessibility.
|
||||
if task_type == "image":
|
||||
base_prompt = """You are Claude Code helping a screen reader user analyze image files. You have access to a single image file that the user has selected for analysis.
|
||||
|
||||
The user is using the Cthulhu screen reader and cannot see images visually. Provide detailed visual descriptions of the image content to make it accessible.
|
||||
|
||||
"""
|
||||
else:
|
||||
base_prompt = """You are Claude Code helping a screen reader user navigate and interact with computer applications. You have expert understanding of terminal commands, programming, and accessibility.
|
||||
|
||||
The user is using the Cthulhu screen reader and cannot see the screen visually. Provide expert technical assistance.
|
||||
|
||||
@@ -323,6 +313,23 @@ MANDATORY FORMAT:
|
||||
|
||||
elif task_type == "question":
|
||||
return base_prompt + "Answer with expert technical knowledge about programming, terminals, and system operations."
|
||||
|
||||
elif task_type == "image":
|
||||
return base_prompt + """Your task: Analyze and describe any images visible on the screen, focusing on visual content rather than UI elements.
|
||||
|
||||
IMPORTANT IMAGE ANALYSIS GUIDELINES:
|
||||
- Focus ONLY on the visual content of images (photos, diagrams, graphics, artwork)
|
||||
- IGNORE UI elements like buttons, menus, toolbars, window frames
|
||||
- Describe what you see IN the images: objects, people, scenes, colors, text within images
|
||||
- If multiple images are visible, describe each one separately
|
||||
- For photographs: describe the scene, subjects, lighting, composition
|
||||
- For diagrams/charts: describe the data, relationships, labels shown
|
||||
- For screenshots within images: describe the content being shown
|
||||
- Be detailed about visual elements that a screen reader user cannot access
|
||||
|
||||
If no images are clearly visible on screen, say so clearly.
|
||||
|
||||
Keep descriptions informative and well-structured."""
|
||||
|
||||
return base_prompt
|
||||
|
||||
@@ -361,18 +368,38 @@ class OllamaProvider(AIProvider):
|
||||
logger.error(f"Ollama action error: {e}")
|
||||
return f"Error suggesting actions: {e}"
|
||||
|
||||
def analyze_images(self, user_question, screenshot_data, accessibility_data):
|
||||
"""Analyze images visible on screen using Ollama."""
|
||||
try:
|
||||
prompt = self._build_prompt("image", user_question, accessibility_data)
|
||||
return self._make_request(prompt, screenshot_data)
|
||||
except Exception as e:
|
||||
logger.error(f"Ollama image analysis error: {e}")
|
||||
return f"Error analyzing images: {e}"
|
||||
|
||||
def _build_prompt(self, task_type, user_input, accessibility_data):
|
||||
"""Build the complete prompt for Ollama."""
|
||||
system_prompt = self._prepare_system_prompt(task_type)
|
||||
|
||||
prompt = f"{system_prompt}\n\nCurrent accessibility information:\n```json\n{json.dumps(accessibility_data, indent=2)}\n```\n\n"
|
||||
|
||||
if task_type == "describe":
|
||||
prompt += "Please describe what's on this screen."
|
||||
elif task_type == "question":
|
||||
prompt += f"User question: {user_input}"
|
||||
elif task_type == "action":
|
||||
prompt += f"User wants to: {user_input}\n\nPlease suggest specific steps to accomplish this."
|
||||
if task_type == "image":
|
||||
# For image analysis, minimize accessibility data weight
|
||||
if user_input == "ANALYZE_SINGLE_IMAGE_FILE":
|
||||
prompt = f"{system_prompt}\n\nAnalyze and describe the single image file provided. Focus on visual content only - describe what you see in the image: objects, people, scenery, colors, text, composition, and any other visual details."
|
||||
else:
|
||||
prompt = f"{system_prompt}\n\nCurrent screen context (focus on images):\n"
|
||||
if user_input:
|
||||
prompt += f"User question about images: {user_input}\n\n"
|
||||
prompt += "Analyze and describe any images visible on this screen. Focus on visual content, not UI elements."
|
||||
else:
|
||||
# Standard prompt with full accessibility data
|
||||
prompt = f"{system_prompt}\n\nCurrent accessibility information:\n```json\n{json.dumps(accessibility_data, indent=2)}\n```\n\n"
|
||||
|
||||
if task_type == "describe":
|
||||
prompt += "Please describe what's on this screen."
|
||||
elif task_type == "question":
|
||||
prompt += f"User question: {user_input}"
|
||||
elif task_type == "action":
|
||||
prompt += f"User wants to: {user_input}\n\nPlease suggest specific steps to accomplish this."
|
||||
|
||||
return prompt
|
||||
|
||||
@@ -386,14 +413,17 @@ class OllamaProvider(AIProvider):
|
||||
"stream": False
|
||||
}
|
||||
|
||||
# Note: Ollama vision support varies by model
|
||||
# For now, we'll send text-only requests
|
||||
# TODO: Add image support when Ollama vision models are more stable
|
||||
# Add image data if available and model supports vision
|
||||
if screenshot_data and "vision" in self.model.lower():
|
||||
payload["images"] = [screenshot_data['data']]
|
||||
|
||||
# Use longer timeout for vision models as they're much slower
|
||||
timeout = 180 if screenshot_data and "vision" in self.model.lower() else 60
|
||||
|
||||
response = requests.post(
|
||||
f"{self.base_url}/api/generate",
|
||||
json=payload,
|
||||
timeout=60 # Ollama can be slower
|
||||
timeout=timeout
|
||||
)
|
||||
|
||||
if response.status_code == 200:
|
||||
@@ -414,13 +444,128 @@ class OllamaProvider(AIProvider):
|
||||
return error_msg
|
||||
|
||||
|
||||
class GeminiProvider(AIProvider):
|
||||
"""Google Gemini AI provider using Google's Gemini API."""
|
||||
|
||||
def __init__(self, api_key, model="gemini-1.5-flash", **kwargs):
|
||||
super().__init__(api_key, model, **kwargs)
|
||||
self.base_url = f"https://generativelanguage.googleapis.com/v1beta/models/{self.model}:generateContent"
|
||||
|
||||
def describe_screen(self, screenshot_data, accessibility_data):
|
||||
"""Generate a description using Gemini."""
|
||||
try:
|
||||
prompt = self._build_prompt("describe", None, accessibility_data)
|
||||
return self._make_request(prompt, screenshot_data)
|
||||
except Exception as e:
|
||||
logger.error(f"Gemini describe error: {e}")
|
||||
return f"Error getting screen description: {e}"
|
||||
|
||||
def answer_question(self, question, screenshot_data, accessibility_data):
|
||||
"""Answer a question using Gemini."""
|
||||
try:
|
||||
prompt = self._build_prompt("question", question, accessibility_data)
|
||||
return self._make_request(prompt, screenshot_data)
|
||||
except Exception as e:
|
||||
logger.error(f"Gemini question error: {e}")
|
||||
return f"Error answering question: {e}"
|
||||
|
||||
def suggest_actions(self, request, screenshot_data, accessibility_data):
|
||||
"""Suggest actions using Gemini."""
|
||||
try:
|
||||
prompt = self._build_prompt("action", request, accessibility_data)
|
||||
return self._make_request(prompt, screenshot_data)
|
||||
except Exception as e:
|
||||
logger.error(f"Gemini action error: {e}")
|
||||
return f"Error suggesting actions: {e}"
|
||||
|
||||
def analyze_images(self, user_question, screenshot_data, accessibility_data):
|
||||
"""Analyze images visible on screen using Gemini."""
|
||||
try:
|
||||
prompt = self._build_prompt("image", user_question, accessibility_data)
|
||||
return self._make_request(prompt, screenshot_data)
|
||||
except Exception as e:
|
||||
logger.error(f"Gemini image analysis error: {e}")
|
||||
return f"Error analyzing images: {e}"
|
||||
|
||||
def _build_prompt(self, task_type, user_input, accessibility_data):
|
||||
"""Build the complete prompt for Gemini."""
|
||||
system_prompt = self._prepare_system_prompt(task_type)
|
||||
|
||||
if task_type == "image":
|
||||
if user_input == "ANALYZE_SINGLE_IMAGE_FILE":
|
||||
prompt = f"{system_prompt}\n\nAnalyze and describe the single image file provided. Focus on visual content only - describe what you see in the image: objects, people, scenery, colors, text, composition, and any other visual details."
|
||||
else:
|
||||
prompt = f"{system_prompt}\n\nCurrent screen context (focus on images):\n"
|
||||
if user_input:
|
||||
prompt += f"User question about images: {user_input}\n\n"
|
||||
prompt += "Analyze and describe any images visible on this screen. Focus on visual content, not UI elements."
|
||||
else:
|
||||
prompt = f"{system_prompt}\n\nCurrent accessibility information:\n```json\n{json.dumps(accessibility_data, indent=2)}\n```\n\n"
|
||||
|
||||
if task_type == "describe":
|
||||
prompt += "Please describe what's on this screen."
|
||||
elif task_type == "question":
|
||||
prompt += f"User question: {user_input}"
|
||||
elif task_type == "action":
|
||||
prompt += f"User wants to: {user_input}\n\nPlease suggest specific steps to accomplish this."
|
||||
|
||||
return prompt
|
||||
|
||||
def _make_request(self, prompt, screenshot_data):
|
||||
"""Make request to Gemini API."""
|
||||
try:
|
||||
parts = [{"text": prompt}]
|
||||
|
||||
# Add image if available
|
||||
if screenshot_data:
|
||||
parts.append({
|
||||
"inline_data": {
|
||||
"mime_type": f"image/{screenshot_data['format']}",
|
||||
"data": screenshot_data['data']
|
||||
}
|
||||
})
|
||||
|
||||
payload = {
|
||||
"contents": [{
|
||||
"parts": parts
|
||||
}]
|
||||
}
|
||||
|
||||
response = requests.post(
|
||||
f"{self.base_url}?key={self.api_key}",
|
||||
headers={"Content-Type": "application/json"},
|
||||
json=payload,
|
||||
timeout=30
|
||||
)
|
||||
|
||||
if response.status_code == 200:
|
||||
result = response.json()
|
||||
if 'candidates' in result and len(result['candidates']) > 0:
|
||||
return result['candidates'][0]['content']['parts'][0]['text']
|
||||
else:
|
||||
return "No response from Gemini"
|
||||
else:
|
||||
error_msg = f"Gemini API error {response.status_code}: {response.text}"
|
||||
logger.error(error_msg)
|
||||
return error_msg
|
||||
|
||||
except requests.RequestException as e:
|
||||
error_msg = f"Network error contacting Gemini: {e}"
|
||||
logger.error(error_msg)
|
||||
return error_msg
|
||||
except Exception as e:
|
||||
error_msg = f"Unexpected error with Gemini API: {e}"
|
||||
logger.error(error_msg)
|
||||
return error_msg
|
||||
|
||||
|
||||
def create_provider(provider_type, **kwargs):
|
||||
"""Factory function to create AI providers."""
|
||||
if provider_type == "claude":
|
||||
return ClaudeProvider(**kwargs)
|
||||
elif provider_type == "claude_code":
|
||||
if provider_type == "claude_code":
|
||||
return ClaudeCodeProvider(**kwargs)
|
||||
elif provider_type == "ollama":
|
||||
return OllamaProvider(**kwargs)
|
||||
elif provider_type == "gemini":
|
||||
return GeminiProvider(**kwargs)
|
||||
else:
|
||||
raise ValueError(f"Unknown provider type: {provider_type}")
|
||||
@@ -103,16 +103,17 @@ class AIAssistant(Plugin):
|
||||
config_valid = self._validate_configuration()
|
||||
logger.info(f"AI Assistant configuration valid: {config_valid}")
|
||||
print(f"DEBUG: AI Assistant configuration valid: {config_valid}")
|
||||
if not config_valid:
|
||||
logger.warning("AI Assistant configuration invalid, skipping activation")
|
||||
print("DEBUG: AI Assistant configuration invalid, skipping activation")
|
||||
return
|
||||
|
||||
# Initialize AI provider (may fail but we still want menu access)
|
||||
if config_valid:
|
||||
provider_init = self._initialize_ai_provider()
|
||||
print(f"DEBUG: AI provider initialization: {provider_init}")
|
||||
else:
|
||||
logger.warning("AI Assistant configuration invalid, menu will show error messages")
|
||||
print("DEBUG: AI Assistant configuration invalid, menu will show error messages")
|
||||
provider_init = False
|
||||
|
||||
# Initialize AI provider
|
||||
self._initialize_ai_provider()
|
||||
print("DEBUG: AI provider initialized")
|
||||
|
||||
# Register keybindings only if configuration is valid
|
||||
# Always register keybindings so menu is accessible even with config issues
|
||||
self._register_keybindings()
|
||||
print("DEBUG: AI keybindings registered")
|
||||
|
||||
@@ -139,12 +140,48 @@ class AIAssistant(Plugin):
|
||||
|
||||
self._enabled = False
|
||||
|
||||
def refresh_settings(self):
|
||||
"""Refresh plugin settings and reinitialize provider. Called when settings change."""
|
||||
try:
|
||||
logger.info("AI Assistant: Refreshing settings")
|
||||
print("DEBUG: AI Assistant refreshing settings")
|
||||
|
||||
# Reload settings
|
||||
self._load_ai_settings()
|
||||
|
||||
# Validate new configuration
|
||||
config_valid = self._validate_configuration()
|
||||
print(f"DEBUG: New configuration valid: {config_valid}")
|
||||
|
||||
# Reinitialize provider if configuration is valid
|
||||
if config_valid:
|
||||
old_provider = self._ai_provider
|
||||
provider_init = self._initialize_ai_provider()
|
||||
print(f"DEBUG: Provider reinitialization: {provider_init}")
|
||||
if provider_init:
|
||||
logger.info(f"AI Assistant provider changed to: {self._provider_type}")
|
||||
print(f"DEBUG: Provider successfully changed to: {self._provider_type}")
|
||||
else:
|
||||
logger.warning("Failed to initialize new provider")
|
||||
print("DEBUG: Failed to initialize new provider")
|
||||
self._ai_provider = None
|
||||
else:
|
||||
logger.warning("New configuration invalid, clearing provider")
|
||||
print("DEBUG: New configuration invalid, clearing provider")
|
||||
self._ai_provider = None
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error refreshing AI Assistant settings: {e}")
|
||||
print(f"DEBUG: Error refreshing settings: {e}")
|
||||
|
||||
def _load_ai_settings(self):
|
||||
"""Load AI Assistant settings from Cthulhu configuration."""
|
||||
try:
|
||||
# Get provider
|
||||
provider = self._settings_manager.getSetting('aiProvider')
|
||||
self._provider_type = provider or settings.AI_PROVIDER_CLAUDE
|
||||
print(f"DEBUG: Raw provider setting: '{provider}'")
|
||||
self._provider_type = provider or settings.AI_PROVIDER_CLAUDE_CODE
|
||||
print(f"DEBUG: Final provider type: '{self._provider_type}'")
|
||||
|
||||
# Load API key from file
|
||||
api_key_file = self._settings_manager.getSetting('aiApiKeyFile')
|
||||
@@ -178,7 +215,7 @@ class AIAssistant(Plugin):
|
||||
logger.warning("No AI provider configured")
|
||||
return False
|
||||
|
||||
# Providers that don't need API keys
|
||||
# Check provider-specific requirements
|
||||
if self._provider_type == settings.AI_PROVIDER_OLLAMA:
|
||||
logger.info("Checking Ollama availability")
|
||||
return self._check_ollama_availability()
|
||||
@@ -187,15 +224,16 @@ class AIAssistant(Plugin):
|
||||
result = self._check_claude_code_availability()
|
||||
logger.info(f"Claude Code availability check result: {result}")
|
||||
return result
|
||||
|
||||
# Other providers need API keys
|
||||
logger.info(f"Checking API key for provider {self._provider_type}")
|
||||
if not self._api_key:
|
||||
logger.warning(f"No API key configured for provider {self._provider_type}")
|
||||
elif self._provider_type == settings.AI_PROVIDER_GEMINI:
|
||||
logger.info("Checking Gemini API key")
|
||||
if not self._api_key:
|
||||
logger.warning("No API key configured for Gemini")
|
||||
return False
|
||||
logger.info("Gemini configuration validated")
|
||||
return True
|
||||
else:
|
||||
logger.warning(f"Unknown provider type: {self._provider_type}")
|
||||
return False
|
||||
|
||||
logger.info("Configuration validation passed")
|
||||
return True
|
||||
|
||||
def _check_ollama_availability(self):
|
||||
"""Check if Ollama is available and has vision models."""
|
||||
@@ -244,12 +282,12 @@ class AIAssistant(Plugin):
|
||||
def _initialize_ai_provider(self):
|
||||
"""Initialize the AI provider based on settings."""
|
||||
try:
|
||||
if self._provider_type == settings.AI_PROVIDER_CLAUDE:
|
||||
self._ai_provider = create_provider("claude", api_key=self._api_key)
|
||||
elif self._provider_type == settings.AI_PROVIDER_CLAUDE_CODE:
|
||||
if self._provider_type == settings.AI_PROVIDER_CLAUDE_CODE:
|
||||
self._ai_provider = create_provider("claude_code")
|
||||
elif self._provider_type == settings.AI_PROVIDER_OLLAMA:
|
||||
self._ai_provider = create_provider("ollama", model=self._ollama_model, base_url=self._ollama_endpoint)
|
||||
elif self._provider_type == settings.AI_PROVIDER_GEMINI:
|
||||
self._ai_provider = create_provider("gemini", api_key=self._api_key)
|
||||
else:
|
||||
logger.error(f"Unsupported provider type: {self._provider_type}")
|
||||
return False
|
||||
@@ -318,12 +356,100 @@ class AIAssistant(Plugin):
|
||||
self._handle_ai_describe_with_data(self._pre_menu_screen_data)
|
||||
elif action_id == "request_action":
|
||||
self._handle_ai_activate_with_data(self._pre_menu_screen_data)
|
||||
elif action_id == "analyze_images":
|
||||
self._handle_ai_image_analysis_with_data(self._pre_menu_screen_data)
|
||||
elif action_id == "browse_image_file":
|
||||
self._handle_browse_image_file()
|
||||
else:
|
||||
logger.warning(f"Unknown AI menu action: {action_id}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error handling menu selection {action_id}: {e}")
|
||||
|
||||
def _handle_ai_image_analysis_with_data(self, data):
|
||||
"""Handle AI image analysis request with pre-captured data."""
|
||||
try:
|
||||
logger.info("AI image analysis requested with pre-captured data")
|
||||
|
||||
if not self._enabled:
|
||||
self._present_message("AI Assistant is not enabled")
|
||||
return True
|
||||
|
||||
if not self._ai_provider:
|
||||
self._present_message("AI provider not available. Check configuration.")
|
||||
return True
|
||||
|
||||
if not data:
|
||||
self._present_message("No screen data available for image analysis")
|
||||
return True
|
||||
|
||||
provider_name = self._provider_type.replace('_', ' ').title()
|
||||
self._present_message(f"AI Assistant ({provider_name}) analyzing images...")
|
||||
|
||||
# Use AI to analyze images on screen
|
||||
try:
|
||||
response = self._ai_provider.analyze_images(None,
|
||||
data.get("screenshot"),
|
||||
data.get("accessibility"))
|
||||
self._show_description_dialog(response)
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting AI image analysis: {e}")
|
||||
self._present_message(f"Error getting AI image analysis: {e}")
|
||||
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in image analysis with data: {e}")
|
||||
self._present_message(f"Error analyzing images: {e}")
|
||||
return False
|
||||
|
||||
def _handle_browse_image_file(self):
|
||||
"""Handle browsing for an image file to analyze."""
|
||||
try:
|
||||
logger.info("AI image file browsing requested")
|
||||
print("DEBUG: _handle_browse_image_file called")
|
||||
|
||||
if not self._enabled:
|
||||
print("DEBUG: AI Assistant not enabled")
|
||||
self._present_message("AI Assistant is not enabled")
|
||||
return True
|
||||
|
||||
if not self._ai_provider:
|
||||
print("DEBUG: AI provider not available")
|
||||
self._present_message("AI provider not available. Check configuration.")
|
||||
return True
|
||||
|
||||
# Show file chooser dialog
|
||||
print("DEBUG: About to show file chooser")
|
||||
image_file = self._show_image_file_chooser()
|
||||
print(f"DEBUG: File chooser returned: {image_file}")
|
||||
|
||||
if image_file:
|
||||
provider_name = self._provider_type.replace('_', ' ').title()
|
||||
self._present_message(f"AI Assistant ({provider_name}) analyzing selected image...")
|
||||
|
||||
# Load and analyze the image file
|
||||
try:
|
||||
image_data = self._load_image_file(image_file)
|
||||
if image_data:
|
||||
# For file browsing, use a special prompt to avoid confusion
|
||||
response = self._ai_provider.analyze_images("ANALYZE_SINGLE_IMAGE_FILE", image_data, {})
|
||||
self._show_description_dialog(response)
|
||||
else:
|
||||
self._present_message("Could not load the selected image file")
|
||||
except Exception as e:
|
||||
logger.error(f"Error analyzing image file: {e}")
|
||||
self._present_message(f"Error analyzing image file: {e}")
|
||||
else:
|
||||
self._present_message("No image file selected")
|
||||
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in browse image file: {e}")
|
||||
self._present_message(f"Error browsing for image file: {e}")
|
||||
return False
|
||||
|
||||
def _handle_ai_describe_with_data(self, data):
|
||||
"""Handle AI screen description request with pre-captured data."""
|
||||
try:
|
||||
@@ -1126,7 +1252,7 @@ class AIAssistant(Plugin):
|
||||
# ============================================================================
|
||||
|
||||
def _show_action_dialog(self):
|
||||
"""Show dialog for entering action requests."""
|
||||
"""Show dialog for entering action requests or analyzing images."""
|
||||
try:
|
||||
# Create dialog without parent first
|
||||
dialog = Gtk.Dialog(
|
||||
@@ -1143,18 +1269,33 @@ class AIAssistant(Plugin):
|
||||
dialog.set_modal(True)
|
||||
dialog.set_type_hint(Gdk.WindowTypeHint.DIALOG)
|
||||
|
||||
dialog.set_default_size(600, 300)
|
||||
dialog.set_default_size(600, 350)
|
||||
|
||||
content_area = dialog.get_content_area()
|
||||
|
||||
# Mode selection radio buttons
|
||||
mode_label = Gtk.Label()
|
||||
mode_label.set_markup("<b>Choose analysis mode:</b>")
|
||||
mode_label.set_halign(Gtk.Align.START)
|
||||
content_area.pack_start(mode_label, False, False, 10)
|
||||
|
||||
# Action mode radio button (default)
|
||||
action_radio = Gtk.RadioButton(label="Request an action")
|
||||
action_radio.set_active(True)
|
||||
content_area.pack_start(action_radio, False, False, 5)
|
||||
|
||||
# Image analysis mode radio button
|
||||
image_radio = Gtk.RadioButton.new_with_label_from_widget(action_radio, "Analyze image content")
|
||||
content_area.pack_start(image_radio, False, False, 5)
|
||||
|
||||
# Instruction label
|
||||
label = Gtk.Label()
|
||||
label.set_markup("<b>Tell the AI what you want to do:</b>\n" +
|
||||
instruction_label = Gtk.Label()
|
||||
instruction_label.set_markup("<b>Tell the AI what you want to do:</b>\n" +
|
||||
"Examples: 'Click the Continue button', 'Enter storm into username field', " +
|
||||
"'Copy this text to clipboard'")
|
||||
label.set_line_wrap(True)
|
||||
label.set_halign(Gtk.Align.START)
|
||||
content_area.pack_start(label, False, False, 10)
|
||||
instruction_label.set_line_wrap(True)
|
||||
instruction_label.set_halign(Gtk.Align.START)
|
||||
content_area.pack_start(instruction_label, False, False, 10)
|
||||
|
||||
# Action entry
|
||||
entry = Gtk.Entry()
|
||||
@@ -1162,6 +1303,24 @@ class AIAssistant(Plugin):
|
||||
entry.set_activates_default(True)
|
||||
content_area.pack_start(entry, False, False, 10)
|
||||
|
||||
# Update UI based on radio button selection
|
||||
def on_radio_toggled(radio_button):
|
||||
if action_radio.get_active():
|
||||
instruction_label.set_markup("<b>Tell the AI what you want to do:</b>\n" +
|
||||
"Examples: 'Click the Continue button', 'Enter storm into username field', " +
|
||||
"'Copy this text to clipboard'")
|
||||
entry.set_placeholder_text("What would you like me to do?")
|
||||
entry.set_sensitive(True)
|
||||
else: # image mode
|
||||
instruction_label.set_markup("<b>Image Analysis Mode:</b>\n" +
|
||||
"The AI will focus on describing visual content in images on the screen, " +
|
||||
"ignoring UI elements. Leave text field empty or add specific questions.")
|
||||
entry.set_placeholder_text("Optional: Ask specific questions about images (leave empty for general description)")
|
||||
entry.set_sensitive(True)
|
||||
|
||||
action_radio.connect("toggled", on_radio_toggled)
|
||||
image_radio.connect("toggled", on_radio_toggled)
|
||||
|
||||
dialog.set_default_response(Gtk.ResponseType.OK)
|
||||
dialog.show_all()
|
||||
|
||||
@@ -1170,14 +1329,20 @@ class AIAssistant(Plugin):
|
||||
response = dialog.run()
|
||||
|
||||
if response == Gtk.ResponseType.OK:
|
||||
action_request = entry.get_text().strip()
|
||||
if action_request:
|
||||
# Close this dialog and create a new confirmation dialog
|
||||
if image_radio.get_active():
|
||||
# Image analysis mode
|
||||
user_question = entry.get_text().strip()
|
||||
dialog.destroy()
|
||||
self._show_action_confirmation_dialog(action_request)
|
||||
self._handle_image_analysis(user_question)
|
||||
else:
|
||||
dialog.destroy()
|
||||
self._present_message("No action request entered")
|
||||
# Action request mode
|
||||
action_request = entry.get_text().strip()
|
||||
if action_request:
|
||||
dialog.destroy()
|
||||
self._show_action_confirmation_dialog(action_request)
|
||||
else:
|
||||
dialog.destroy()
|
||||
self._present_message("No action request entered")
|
||||
else:
|
||||
dialog.destroy()
|
||||
self._present_message("Action request cancelled")
|
||||
@@ -1186,6 +1351,41 @@ class AIAssistant(Plugin):
|
||||
logger.error(f"Error showing action dialog: {e}")
|
||||
self._present_message(f"Error showing action dialog: {e}")
|
||||
|
||||
def _handle_image_analysis(self, user_question=None):
|
||||
"""Handle image analysis request."""
|
||||
try:
|
||||
logger.info(f"Image analysis requested with question: '{user_question}'")
|
||||
|
||||
self._present_message("AI Assistant analyzing images on screen...")
|
||||
|
||||
# Use existing screen data or collect fresh data
|
||||
screen_data = self._current_screen_data
|
||||
if not screen_data:
|
||||
screen_data = self._collect_ai_data()
|
||||
|
||||
if not screen_data:
|
||||
self._present_message("Could not collect screen data for image analysis")
|
||||
return
|
||||
|
||||
# Get image analysis from AI provider
|
||||
if user_question:
|
||||
# User has a specific question about images
|
||||
result = self._ai_provider.analyze_images(user_question,
|
||||
screen_data.get("screenshot"),
|
||||
screen_data.get("accessibility"))
|
||||
else:
|
||||
# General image description
|
||||
result = self._ai_provider.analyze_images(None,
|
||||
screen_data.get("screenshot"),
|
||||
screen_data.get("accessibility"))
|
||||
|
||||
# Present the result
|
||||
self._present_message(f"Image analysis complete: {result}")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error in image analysis: {e}")
|
||||
self._present_message(f"Error analyzing images: {e}")
|
||||
|
||||
def _show_action_confirmation_dialog(self, action_request):
|
||||
"""Show a fresh confirmation dialog for the action."""
|
||||
try:
|
||||
@@ -1740,6 +1940,96 @@ class AIAssistant(Plugin):
|
||||
except Exception as e:
|
||||
logger.error(f"Error extracting text from action: {e}")
|
||||
return None
|
||||
|
||||
def _show_image_file_chooser(self):
|
||||
"""Show a file chooser dialog for selecting an image file."""
|
||||
try:
|
||||
dialog = Gtk.FileChooserDialog(
|
||||
title="Select Image File",
|
||||
parent=None,
|
||||
action=Gtk.FileChooserAction.OPEN
|
||||
)
|
||||
|
||||
# Add buttons
|
||||
dialog.add_button("Cancel", Gtk.ResponseType.CANCEL)
|
||||
dialog.add_button("Open", Gtk.ResponseType.OK)
|
||||
|
||||
# Set up image file filters
|
||||
filter_images = Gtk.FileFilter()
|
||||
filter_images.set_name("Image files")
|
||||
filter_images.add_mime_type("image/png")
|
||||
filter_images.add_mime_type("image/jpeg")
|
||||
filter_images.add_mime_type("image/jpg")
|
||||
filter_images.add_mime_type("image/gif")
|
||||
filter_images.add_mime_type("image/bmp")
|
||||
filter_images.add_mime_type("image/webp")
|
||||
filter_images.add_pattern("*.png")
|
||||
filter_images.add_pattern("*.jpg")
|
||||
filter_images.add_pattern("*.jpeg")
|
||||
filter_images.add_pattern("*.gif")
|
||||
filter_images.add_pattern("*.bmp")
|
||||
filter_images.add_pattern("*.webp")
|
||||
dialog.add_filter(filter_images)
|
||||
|
||||
# Add "All files" filter as backup
|
||||
filter_all = Gtk.FileFilter()
|
||||
filter_all.set_name("All files")
|
||||
filter_all.add_pattern("*")
|
||||
dialog.add_filter(filter_all)
|
||||
|
||||
# Run the dialog
|
||||
response = dialog.run()
|
||||
|
||||
filename = None
|
||||
if response == Gtk.ResponseType.OK:
|
||||
filename = dialog.get_filename()
|
||||
logger.info(f"Selected image file: {filename}")
|
||||
|
||||
dialog.destroy()
|
||||
return filename
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error showing image file chooser: {e}")
|
||||
return None
|
||||
|
||||
def _load_image_file(self, image_path):
|
||||
"""Load an image file and convert it to base64 for AI analysis."""
|
||||
try:
|
||||
import base64
|
||||
import os
|
||||
|
||||
# Read the image file
|
||||
with open(image_path, 'rb') as image_file:
|
||||
image_data = image_file.read()
|
||||
|
||||
# Convert to base64
|
||||
base64_data = base64.b64encode(image_data).decode('utf-8')
|
||||
|
||||
# Determine format from file extension
|
||||
_, ext = os.path.splitext(image_path.lower())
|
||||
format_map = {
|
||||
'.png': 'png',
|
||||
'.jpg': 'jpeg',
|
||||
'.jpeg': 'jpeg',
|
||||
'.gif': 'gif',
|
||||
'.bmp': 'bmp',
|
||||
'.webp': 'webp'
|
||||
}
|
||||
image_format = format_map.get(ext, 'png') # Default to png
|
||||
|
||||
logger.info(f"Loaded image file: {image_path} ({len(image_data)} bytes, format: {image_format})")
|
||||
|
||||
# Return same structure as _capture_screenshot
|
||||
return {
|
||||
'format': image_format,
|
||||
'width': 0, # We don't know dimensions, but AI doesn't need them
|
||||
'height': 0,
|
||||
'data': base64_data
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error loading image file {image_path}: {e}")
|
||||
return None
|
||||
|
||||
|
||||
class AIAssistantMenu(Gtk.Dialog):
|
||||
@@ -1772,11 +2062,15 @@ class AIAssistantMenu(Gtk.Dialog):
|
||||
self.radio_ask = Gtk.RadioButton.new_with_label(None, "Ask Question")
|
||||
self.radio_describe = Gtk.RadioButton.new_with_label_from_widget(self.radio_ask, "Describe Screen")
|
||||
self.radio_action = Gtk.RadioButton.new_with_label_from_widget(self.radio_ask, "Request Action")
|
||||
self.radio_image = Gtk.RadioButton.new_with_label_from_widget(self.radio_ask, "Analyze Images")
|
||||
self.radio_browse = Gtk.RadioButton.new_with_label_from_widget(self.radio_ask, "Browse for Image File")
|
||||
|
||||
# Pack radio buttons
|
||||
content_area.pack_start(self.radio_ask, False, False, 5)
|
||||
content_area.pack_start(self.radio_describe, False, False, 5)
|
||||
content_area.pack_start(self.radio_action, False, False, 5)
|
||||
content_area.pack_start(self.radio_image, False, False, 5)
|
||||
content_area.pack_start(self.radio_browse, False, False, 5)
|
||||
|
||||
# Set first option as selected by default
|
||||
self.radio_ask.set_active(True)
|
||||
@@ -1798,6 +2092,10 @@ class AIAssistantMenu(Gtk.Dialog):
|
||||
action_id = "describe_screen"
|
||||
elif self.radio_action.get_active():
|
||||
action_id = "request_action"
|
||||
elif self.radio_image.get_active():
|
||||
action_id = "analyze_images"
|
||||
elif self.radio_browse.get_active():
|
||||
action_id = "browse_image_file"
|
||||
else:
|
||||
action_id = None
|
||||
|
||||
|
||||
@@ -197,10 +197,8 @@ CHAT_SPEAK_ALL = 0
|
||||
CHAT_SPEAK_ALL_IF_FOCUSED = 1
|
||||
CHAT_SPEAK_FOCUSED_CHANNEL = 2
|
||||
|
||||
# AI Assistant constants
|
||||
AI_PROVIDER_CLAUDE = "claude"
|
||||
# AI Assistant constants - simplified to providers that don't need complex API key management
|
||||
AI_PROVIDER_CLAUDE_CODE = "claude_code"
|
||||
AI_PROVIDER_CHATGPT = "chatgpt"
|
||||
AI_PROVIDER_GEMINI = "gemini"
|
||||
AI_PROVIDER_OLLAMA = "ollama"
|
||||
|
||||
|
||||
Reference in New Issue
Block a user