"""Google Gemini API client for getting Gemini responses."""
import os
import google.generativeai as genai
from models import ContextEntry
class GeminiClient:
"""Client for interacting with Google's Gemini API."""
def __init__(self, api_key: str | None = None, model: str | None = None) -> None:
"""Initialize the Gemini client."""
self.api_key = api_key or os.getenv("GOOGLE_API_KEY")
if not self.api_key:
msg = "Google API key must be provided or set in GOOGLE_API_KEY environment variable"
raise ValueError(msg)
self.model_name: str = model or os.getenv("MCP_TOOLZ_GEMINI_MODEL") or "gemini-2.0-flash-thinking-exp-01-21"
genai.configure(api_key=self.api_key)
self.model = genai.GenerativeModel(self.model_name)
def get_second_opinion(self, context: ContextEntry, question: str | None = None) -> str:
"""Get Gemini's second opinion on a context, or answer a specific question.
Args:
context: The context entry to analyze
question: Optional specific question to ask. If None, provides general second opinion.
"""
if question:
# Custom question mode
system_instruction = """You are a senior software engineering consultant answering questions about code, \
architecture decisions, and implementation plans.
Provide clear, actionable answers based on the context provided."""
user_content = self._format_context_for_gemini(context, question)
else:
# Generic second opinion mode
system_instruction = """You are a senior software engineering consultant providing second opinions on code, \
architecture decisions, and implementation plans.
Your role is to:
- Provide constructive, balanced feedback
- Highlight both strengths and potential issues
- Suggest alternatives when appropriate
- Point out edge cases or security concerns
- Be concise but thorough
Format your response clearly with sections as needed."""
user_content = self._format_context_for_gemini(context)
# Configure model with system instruction
model_with_instruction = genai.GenerativeModel(self.model_name, system_instruction=system_instruction)
response = model_with_instruction.generate_content(user_content)
return str(response.text)
def _format_context_for_gemini(self, context: ContextEntry, question: str | None = None) -> str:
"""Format a context entry for Gemini consumption.
Args:
context: The context entry to format
question: Optional specific question to append
"""
parts = [
f"# Context: {context.title}",
f"\n**Type:** {context.type}",
f"**Timestamp:** {context.timestamp.isoformat()}",
]
if context.tags:
parts.append(f"**Tags:** {', '.join(context.tags)}")
parts.append("\n## Content\n")
# Add specific content based on type
if context.content.messages:
parts.append("### Conversation\n")
for msg in context.content.messages:
parts.append(msg)
if context.content.code:
parts.append("### Code\n")
for file_path, code in context.content.code.items():
parts.append(f"**File:** `{file_path}`\n```\n{code}\n```\n")
if context.content.suggestions:
parts.append(f"### Suggestion\n{context.content.suggestions}\n")
if context.content.errors:
parts.append(f"### Error/Debug Info\n```\n{context.content.errors}\n```\n")
# Add question or default request
if question:
parts.append(f"\n---\n**Question:** {question}")
else:
parts.append("\n---\nPlease provide a second opinion on the above context.")
return "\n".join(parts)