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refactor: remove emojis and apply code formatting

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- Remove all emoji characters from output strings for better compatibility
- Update all tests to match non-emoji output
- Apply black formatting to all Python files
- Ensure all tests pass and linting succeeds
- Remove htmlcov directory (already in .gitignore)

This change improves cross-platform compatibility and ensures
consistent code formatting across the project.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Fahad
2025-06-08 21:32:38 +04:00
parent fb1d843950
commit b6f8c43b81
7 changed files with 157 additions and 137 deletions
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42
gemini_server.py
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@@ -175,9 +175,9 @@ def prepare_code_context(
if preview.strip():
summary_parts.append(f" Preview: {preview[:50]}...")
except Exception:
summary_parts.append(f" 📄 {file_path} ({size:,} bytes)")
summary_parts.append(f" {file_path} ({size:,} bytes)")
else:
summary_parts.append(f" ❌ {file_path} (not found)")
summary_parts.append(f" {file_path} (not found)")
# Add direct code
if code:
@@ -303,7 +303,9 @@ async def handle_call_tool(name: str, arguments: Dict[str, Any]) -> List[TextCon
try:
# Use the specified model with optimized settings
model_name = request.model or DEFAULT_MODEL
temperature = request.temperature if request.temperature is not None else 0.5
temperature = (
request.temperature if request.temperature is not None else 0.5
)
max_tokens = request.max_tokens if request.max_tokens is not None else 8192
model = genai.GenerativeModel(
@@ -359,7 +361,9 @@ async def handle_call_tool(name: str, arguments: Dict[str, Any]) -> List[TextCon
try:
# Prepare code context - always use non-verbose mode for Claude Code compatibility
code_context, summary = prepare_code_context(request_analysis.files, request_analysis.code)
code_context, summary = prepare_code_context(
request_analysis.files, request_analysis.code
)
# Count approximate tokens (rough estimate: 1 token ≈ 4 characters)
estimated_tokens = len(code_context) // 4
@@ -374,8 +378,16 @@ async def handle_call_tool(name: str, arguments: Dict[str, Any]) -> List[TextCon
# Use the specified model with optimized settings for code analysis
model_name = request_analysis.model or DEFAULT_MODEL
temperature = request_analysis.temperature if request_analysis.temperature is not None else 0.2
max_tokens = request_analysis.max_tokens if request_analysis.max_tokens is not None else 8192
temperature = (
request_analysis.temperature
if request_analysis.temperature is not None
else 0.2
)
max_tokens = (
request_analysis.max_tokens
if request_analysis.max_tokens is not None
else 8192
)
model = genai.GenerativeModel(
model_name=model_name,
@@ -417,7 +429,7 @@ marked with their paths and content boundaries."""
# Always return response with summary for Claude Code compatibility
if request_analysis.files or request_analysis.code:
response_text = f"{summary}\n\n🤖 Gemini's Analysis:\n{text}"
response_text = f"{summary}\n\nGemini's Analysis:\n{text}"
else:
response_text = text
@@ -431,13 +443,19 @@ marked with their paths and content boundaries."""
# List available models
models = []
for model_info in genai.list_models():
if (hasattr(model_info, 'supported_generation_methods') and
"generateContent" in model_info.supported_generation_methods):
if (
hasattr(model_info, "supported_generation_methods")
and "generateContent" in model_info.supported_generation_methods
):
models.append(
{
"name": model_info.name,
"display_name": getattr(model_info, 'display_name', 'Unknown'),
"description": getattr(model_info, 'description', 'No description'),
"display_name": getattr(
model_info, "display_name", "Unknown"
),
"description": getattr(
model_info, "description", "No description"
),
"is_default": model_info.name.endswith(DEFAULT_MODEL),
}
)
@@ -462,7 +480,7 @@ marked with their paths and content boundaries."""
return [
TextContent(
type="text",
text=f"""🤖 Gemini MCP Server v{__version__}
text=f"""Gemini MCP Server v{__version__}
Updated: {__updated__}
Author: {__author__}