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Merge pull request #63 from vamplabAI/feature/frontend-integration
Feature/frontend integration
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‎.gitignore‎

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eggs/
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.eggs/
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lib/
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!sgr-deep-research-frontend/src/shared/lib/
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lib64/
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parts/
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sdist/

‎README.md‎

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# SGR Agent Core — the first SGR open-source agentic framework for Schema-Guided Reasoning
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# UI For Testing
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https://github.com/user-attachments/assets/aa85b4d9-b2cb-454c-97d0-ad1443ac9a59
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[How run UI](https://github.com/vamplabAI/sgr-agent-core/blob/feature/frontend-integration/sgr-deep-research-frontend/README.md)
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## Description
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![SGR Concept Architecture](docs/sgr_concept.png)

‎agents.yaml‎

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# Example Custom Agents Configuration
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# =====================================
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# This file demonstrates how to define custom agents for SGR Deep Research
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# Notes:
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# ------
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# 1. Agent names must be unique or will be overridden
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# 2. All tools must be registered in the tool registry
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# 3. LLM, Search, Prompts, Execution, MCP settings are optional and inherit from global config
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# 4. Agents override global settings by providing their own values
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agents:
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# Example 1: Simple custom research agent with overrides
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custom_research_agent:
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base_class: "sgr_deep_research.core.SGRAgent"
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# Optional: Override LLM settings for this agent
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openai:
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model: "gpt-4o"
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temperature: 0.3
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max_tokens: 16000
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# api_key: "your-custom-api-key" # Optional: use different API key
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# base_url: "https://api.openai.com/v1" # Optional: use different endpoint
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# proxy: "http://127.0.0.1:8080" # Optional: use proxy
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# Optional: Override search settings
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search:
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max_results: 15
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max_pages: 8
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content_limit: 2000
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# Optional: Execution configuration
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execution:
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max_steps: 8
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max_iterations: 15
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max_clarifications: 5
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max_searches: 6
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mcp_context_limit: 20000
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logs_dir: "logs/custom_agent"
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reports_dir: "reports/custom_agent"
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# Optional: MCP configuration
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mcp:
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mcpServers:
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deepwiki:
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url: "https://mcp.deepwiki.com/mcp"
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# Tools this agent can use (must be registered in tool registry)
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tools:
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- "WebSearchTool"
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- "ExtractPageContentTool"
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- "CreateReportTool"
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- "ClarificationTool"
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- "GeneratePlanTool"
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- "AdaptPlanTool"
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- "FinalAnswerTool"
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# Example 2: Minimal agent with defaults
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simple_agent:
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base_class: "SGRToolCallingResearchAgent"
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# Only override what's needed
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llm:
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model: "gpt-4o-mini"
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tools:
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- "WebSearchTool"
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- "FinalAnswerTool"
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# Example 3: Fast research agent optimized for speed
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fast_research_agent:
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base_class: "SGRToolCallingAgent"
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llm:
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model: "gpt-4o-mini"
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temperature: 0.1
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max_tokens: 4000
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execution:
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max_steps: 4
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max_iterations: 8
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max_clarifications: 2
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max_searches: 3
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tools:
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- "WebSearchTool"
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- "CreateReportTool"
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- "FinalAnswerTool"
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- "ReasoningTool"
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# Example 4: Specialized technical analyst with custom prompts
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technical_analyst:
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base_class: "SGRAgent"
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llm:
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model: "gpt-4o"
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temperature: 0.2
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prompts:
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system_prompt: "You are a highly specialized technical analyst."
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execution:
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max_steps: 10
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max_iterations: 20
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max_clarifications: 3
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max_searches: 8
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tools:
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- "WebSearchTool"
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- "ExtractPageContentTool"
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- "CreateReportTool"
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- "ClarificationTool"
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- "FinalAnswerTool"
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# Example 5: Agent using inline prompts instead of files
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inline_prompt_agent:
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base_class: "SGRResearchAgent"
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prompts:
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system_prompt_str: |
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You are a helpful research assistant.
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Your goal is to provide accurate and concise information.
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initial_user_request_str: |
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User request: {user_request}
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Please analyze and respond.
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clarification_response_str: |
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I need clarification on: {clarification_needed}
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tools:
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- "WebSearchTool"
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- "FinalAnswerTool"

‎services/README.md‎

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# SGR Deep Research - Docker Deployment
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Запуск полного стека (backend + frontend) через Docker Compose.
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## Быстрый старт
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1. **Скопируйте `.env.example` в `.env`:**
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```bash
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cp .env.example .env
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```
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2. **Отредактируйте `.env` при необходимости** (опционально)
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3. **Запустите все сервисы:**
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```bash
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docker-compose up -d --build
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```
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4. **Откройте в браузере:**
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- Frontend: http://localhost:5174
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- Backend API: http://localhost:8010
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- API Docs: http://localhost:8010/docs
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## Управление
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### Запуск
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```bash
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# Запуск всех сервисов
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docker-compose up -d
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# Запуск с пересборкой
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docker-compose up -d --build
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# Запуск только backend
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docker-compose up -d sgr-backend
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# Запуск только frontend
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docker-compose up -d sgr-frontend
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```
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### Остановка
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```bash
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# Остановить все сервисы
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docker-compose down
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# Остановить и удалить volumes
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docker-compose down -v
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```
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### Логи
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```bash
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# Все логи
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docker-compose logs -f
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# Логи backend
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docker-compose logs -f sgr-backend
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# Логи frontend
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docker-compose logs -f sgr-frontend
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```
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### Перезапуск
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```bash
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# Перезапустить все
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docker-compose restart
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# Перезапустить только backend
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docker-compose restart sgr-backend
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```
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## Конфигурация
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### Переменные окружения (.env)
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```bash
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# Backend
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BACKEND_PORT=8010 # Порт для backend API
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# Frontend
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FRONTEND_PORT=5174 # Порт для frontend
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VITE_API_BASE_URL=http://localhost:8010 # URL backend API
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VITE_APP_ENV=production # Окружение (production/development)
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# Transcription API (опционально)
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VITE_TRANSCRIPTION_API_URL=https://speechcoreai.com/api
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VITE_TRANSCRIPTION_API_TOKEN=your_token_here
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```
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### Структура сервисов
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- **sgr-backend**: FastAPI backend на порту 8010
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- Healthcheck: проверяет `/health` каждые 30 секунд
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- Volumes: код, конфиги, логи, отчеты
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- **sgr-frontend**: Nginx + Vue.js frontend на порту 5174
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- Зависит от backend (запускается после healthcheck)
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- Статические файлы собираются при сборке образа
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### Сеть
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Оба сервиса находятся в одной Docker сети `sgr-network`, что позволяет им взаимодействовать по именам контейнеров.
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## Troubleshooting
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### Frontend не может подключиться к backend
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Проверьте, что `VITE_API_BASE_URL` в `.env` указывает на правильный URL backend.
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### Backend не стартует
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Проверьте логи:
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```bash
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docker-compose logs sgr-backend
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```
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Убедитесь, что `config.yaml` и `logging_config.yaml` существуют в корне проекта.
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### Порты заняты
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Измените порты в `.env`:
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```bash
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BACKEND_PORT=8011
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FRONTEND_PORT=5175
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```
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Затем перезапустите:
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```bash
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docker-compose down
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docker-compose up -d
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```

‎services/docker-compose.yml‎

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services:
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sgr:
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sgr-backend:
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build:
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context: ./api_service
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dockerfile: Dockerfile
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container_name: sgr-deep-research
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container_name: sgr-deep-research-backend
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restart: unless-stopped
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ports:
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- "8010:8010"
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- "${BACKEND_PORT:-8010}:8010"
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volumes:
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- ../sgr_deep_research:/app/sgr_deep_research:ro
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- ../config.yaml:/app/config.yaml:ro
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- ../agents.yaml:/app/agents.yaml:ro
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- ../logging_config.yaml:/app/logging_config.yaml:ro
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- ./logs:/app/logs
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- ./reports:/app/reports
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- ./logs:/app/logs
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- ./reports:/app/reports
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:8010/health"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 40s
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networks:
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- sgr-network
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sgr-frontend:
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build:
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context: ../sgr-deep-research-frontend
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dockerfile: Dockerfile
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args:
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- VITE_API_BASE_URL=${VITE_API_BASE_URL:-http://localhost:8010}
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- VITE_APP_ENV=${VITE_APP_ENV:-production}
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- VITE_TRANSCRIPTION_API_URL=${VITE_TRANSCRIPTION_API_URL:-https://speechcoreai.com/api}
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- VITE_TRANSCRIPTION_API_TOKEN=${VITE_TRANSCRIPTION_API_TOKEN:-}
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container_name: sgr-deep-research-frontend
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restart: unless-stopped
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ports:
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- "${FRONTEND_PORT:-5173}:80"
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depends_on:
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sgr-backend:
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condition: service_healthy
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networks:
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- sgr-network
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networks:
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sgr-network:
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driver: bridge

‎sgr-deep-research-frontend/.dockerignore‎

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# dependencies
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/node_modules
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.idea*
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# production
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/dist
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*.tar
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# misc
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.DS_Store
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*.pem
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.vscode
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# debug
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npm-debug.log*
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yarn-debug.log*
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yarn-error.log*
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# typescript
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*.tsbuildinfo

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