gemini-code-flow
Version:
AI-powered development orchestration for Gemini CLI - adapted from Claude Code Flow by ruvnet
152 lines • 5.25 kB
JavaScript
;
/**
* Gemini Client Integration
* Adapted from Claude Code Flow by ruvnet
*/
Object.defineProperty(exports, "__esModule", { value: true });
exports.GeminiClient = void 0;
const generative_ai_1 = require("@google/generative-ai");
class GeminiClient {
genAI;
model;
config;
constructor(config) {
this.config = config;
// Handle authentication method
const authMethod = config.authMethod || 'google-account';
if (authMethod === 'api-key') {
if (!config.apiKey) {
throw new Error('API key is required when using api-key authentication method');
}
this.genAI = new generative_ai_1.GoogleGenerativeAI(config.apiKey);
}
else {
// For google-account method, let Gemini CLI handle authentication
// This assumes the user has already authenticated via `gemini` command
const apiKey = config.apiKey || process.env.GEMINI_API_KEY || '';
if (!apiKey) {
console.warn('No API key provided. Ensure you are authenticated via Google account or set GEMINI_API_KEY');
}
this.genAI = new generative_ai_1.GoogleGenerativeAI(apiKey);
}
this.model = this.genAI.getGenerativeModel({
model: config.model || 'gemini-1.5-pro',
});
}
/**
* Execute a prompt with the Gemini model
*/
async execute(prompt, mode) {
try {
const generationConfig = {
temperature: this.getModeTemperature(mode),
maxOutputTokens: this.config.maxOutputTokens || 8192,
};
const result = await this.model.generateContent({
contents: [{ role: 'user', parts: [{ text: prompt }] }],
generationConfig,
});
const response = await result.response;
return response.text();
}
catch (error) {
throw new Error(`Gemini execution failed: ${error instanceof Error ? error.message : 'Unknown error'}`);
}
}
/**
* Execute with multimodal input (images, PDFs, etc.)
*/
async executeMultimodal(prompt, files, mode) {
try {
const parts = [{ text: prompt }];
// Add file parts
for (const file of files) {
parts.push({
inlineData: {
mimeType: file.mimeType,
data: file.data.toString('base64'),
},
});
}
const generationConfig = {
temperature: this.getModeTemperature(mode),
maxOutputTokens: this.config.maxOutputTokens || 8192,
};
const result = await this.model.generateContent({
contents: [{ role: 'user', parts }],
generationConfig,
});
const response = await result.response;
return response.text();
}
catch (error) {
throw new Error(`Gemini multimodal execution failed: ${error instanceof Error ? error.message : 'Unknown error'}`);
}
}
/**
* Stream response for real-time output
*/
async *streamExecute(prompt, mode) {
try {
const generationConfig = {
temperature: this.getModeTemperature(mode),
maxOutputTokens: this.config.maxOutputTokens || 8192,
};
const result = await this.model.generateContentStream({
contents: [{ role: 'user', parts: [{ text: prompt }] }],
generationConfig,
});
for await (const chunk of result.stream) {
const chunkText = chunk.text();
if (chunkText) {
yield chunkText;
}
}
}
catch (error) {
throw new Error(`Gemini stream execution failed: ${error instanceof Error ? error.message : 'Unknown error'}`);
}
}
/**
* Get temperature setting for specific mode
*/
getModeTemperature(mode) {
const modeTemperatures = {
architect: 0.7,
coder: 0.3,
tester: 0.2,
debugger: 0.1,
security: 0.2,
documentation: 0.5,
integrator: 0.4,
monitor: 0.2,
optimizer: 0.3,
ask: 0.8,
devops: 0.3,
tutorial: 0.6,
database: 0.2,
specification: 0.4,
mcp: 0.3,
orchestrator: 0.5,
designer: 0.8,
};
return modeTemperatures[mode] ?? this.config.temperature ?? 0.5;
}
/**
* Check model availability and quota
*/
async checkHealth() {
try {
const result = await this.model.generateContent({
contents: [{ role: 'user', parts: [{ text: 'Hello' }] }],
generationConfig: { maxOutputTokens: 10 },
});
return !!result.response;
}
catch (error) {
return false;
}
}
}
exports.GeminiClient = GeminiClient;
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