diff --git a/.github/copilot-instructions.md b/.github/copilot-instructions.md new file mode 100644 index 00000000..f71218be --- /dev/null +++ b/.github/copilot-instructions.md @@ -0,0 +1,304 @@ +# BYK-RAG Module - Copilot Instructions + +## Project Overview + +BYK-RAG is a Retrieval-Augmented Generation module for Estonian government digital services (Bürokratt ecosystem). It provides secure, multilingual AI-powered responses by integrating multiple LLM providers, contextual retrieval, and guardrails. + +## Build, Test, and Lint Commands + +### Environment Setup +```bash +# Install Python 3.12.10 and create virtual environment +uv python install 3.12.10 +uv sync --frozen + +# Install pre-commit hooks +uv run pre-commit install +``` + +### Running Services +```bash +# Always use uv run for Python scripts (whether venv is activated or not) +uv run python + +# Start all services with Docker Compose +docker compose up + +# Run FastAPI orchestration service locally +uv run uvicorn src.llm_orchestration_service_api:app --reload +``` + +### Testing +```bash +# Run all tests +uv run pytest + +# Run specific test file +uv run pytest tests/test_query_validator.py -v + +# Run integration tests (requires Docker and secrets) +uv run pytest tests/integration_tests/ -v --tb=short --log-cli-level=INFO + +# Run deepeval tests +uv run pytest tests/deepeval_tests/standard_tests.py -v --tb=short +``` + +### Linting and Formatting +```bash +# Check code formatting (does NOT modify files) +uv run ruff format --check + +# Apply code formatting (SAFE - layout only, no logic changes) +uv run ruff format + +# Check linting issues (manual fixes required) +uv run ruff check . + +# Get explanation for specific lint rule +uv run ruff rule # e.g., ANN204 + +# NEVER use ruff check --fix (can alter logic/control flow) +``` + +### Type Checking +```bash +# Run Pyright type checker (runs on src/ only, not tests/) +uv run pyright +``` + +### Pre-commit Hooks +```bash +# Run all pre-commit hooks manually +uv run pre-commit run --all-files +``` + +## Architecture + +### Core Components + +1. **LLM Orchestration Service** (`src/llm_orchestration_service.py`) + - Central business logic for RAG orchestration + - Coordinates prompt refinement, retrieval, generation, and guardrails + - Integrates with Langfuse for observability + +2. **FastAPI Application** (`src/llm_orchestration_service_api.py`) + - HTTP API layer exposing `/orchestrate` endpoint + - Handles streaming responses and rate limiting + - Request/response validation via Pydantic models + +3. **Contextual Retrieval** (`src/contextual_retrieval/`) + - Implements Anthropic's Contextual Retrieval methodology + - Hybrid search: Vector (semantic) + BM25 (lexical) with RRF fusion + - Multi-query expansion (6 refined queries per user query) + - Qdrant vector database integration + +4. **Prompt Refinement** (`src/prompt_refine_manager/`) + - DSPy-based query expansion + - Generates 5 refined variations + original query + +5. **Response Generation** (`src/response_generator/`) + - DSPy-based response synthesis + - Supports streaming via SSE (Server-Sent Events) + - Uses top-K retrieved chunks (default: 10) + +6. **Guardrails** (`src/guardrails/`) + - NeMo Guardrails integration with DSPy + - Input guardrails (pre-refinement) and output guardrails (post-generation) + - Blocks out-of-scope queries and harmful content + +7. **LLM Manager** (`src/llm_orchestrator_config/llm_manager.py`) + - Multi-provider support: AWS Bedrock, Azure OpenAI, Google Cloud, OpenAI, Anthropic + - HashiCorp Vault integration for secret management + - RSA-2048 encrypted credentials storage + +8. **Vector Indexer** (`src/vector_indexer/`) + - Qdrant collection management + - Embedding generation and indexing + - BM25 index creation + +### Supporting Services (Docker Compose) + +- **Ruuter** (Public/Private): API gateway and routing +- **DataMapper**: Data transformation layer +- **Resql**: PostgreSQL query builder +- **CronManager**: Scheduled jobs (knowledge base sync) +- **Qdrant**: Vector database +- **MinIO**: S3-compatible object storage +- **HashiCorp Vault**: Secret management +- **Grafana Loki**: Log aggregation +- **Langfuse**: LLM observability dashboard + +### Key Data Flow + +``` +User Query + ↓ +Input Guardrails (NeMo Rails) + ↓ +Prompt Refinement (DSPy) → 6 queries + ↓ +Parallel Hybrid Search (each query) + ├─→ Semantic Search (Qdrant, top-40 per query, threshold ≥0.4) + └─→ BM25 Search (top-40 per query) + ↓ +RRF Fusion → Top-K chunks (10 default) + ↓ +Response Generation (DSPy) + ↓ +Output Guardrails (NeMo Rails) + ↓ +Response to User (JSON or SSE stream) +``` + +## Key Conventions + +### Dependency Management + +- **ALWAYS use `uv add `** to add dependencies (never `pip install`) +- **ALWAYS commit both `pyproject.toml` AND `uv.lock`** together +- Use bounded version ranges: `uv add "package>=x.y,` for explanations +- Autofixes can alter control flow/logic unintentionally + +### Formatting (Ruff Formatter) + +- Double quotes for strings +- Spaces for indentation (4 spaces) +- Respects magic trailing commas +- Auto-detects line endings (LF/CRLF) +- Does NOT reformat docstring code blocks +- `uv run ruff format` is SAFE (layout only, no logic changes) + +### DSPy Usage + +- Used for prompt refinement (multi-query expansion) and response generation +- Custom LLM adapters integrate DSPy with NeMo Guardrails +- Optimization modules under `src/optimization/` for tuning prompts/metrics +- Models loaded via `optimized_module_loader.py` for compiled DSPy modules + +### HashiCorp Vault Integration + +- Secrets stored at `secret/users///` +- Each connection has `provider`, `environment`, and provider-specific keys +- RSA-2048 encryption layer BEFORE Vault storage +- GUI encrypts with public key; CronManager decrypts with private key +- Vault unavailable = graceful degradation (fail securely) + +### Logging + +- **loguru** for application logging +- Grafana Loki integration for centralized logs +- Use `logger.info()`, `logger.warning()`, `logger.error()` (NOT `print()`) +- Loki logger available at `grafana-configs/loki_logger.py` + +### Streaming Responses + +- Implemented via Server-Sent Events (SSE) in FastAPI +- `StreamConfig` and `stream_manager` coordinate streaming state +- `stream_response_native()` in response_generator yields tokens +- Timeout handling via `stream_timeout` utility +- Environment-gated: check `STREAMING_ALLOWED_ENVS` + +### Configuration Loading + +- `PromptConfigurationLoader` fetches prompt configs from Ruuter endpoint +- Cache TTL: `PROMPT_CONFIG_CACHE_TTL` +- Custom prompts per user/organization (stored in Vault/database) +- Fallback to defaults if Ruuter unavailable + +### Error Handling + +- `generate_error_id()` creates unique error IDs for tracking +- `log_error_with_context()` for structured error logging +- Localized error messages via `get_localized_message()` (multilingual support) +- Predefined message constants in `llm_orchestrator_constants.py` + +### Testing Conventions + +- Test files under `tests/` (unit, integration, deepeval) +- Integration tests use `testcontainers` for Docker orchestration +- Secrets required for integration tests (Azure OpenAI keys, etc.) +- Mock data in `tests/mocks/` and `tests/data/` + +### CI/CD Checks + +1. **uv-env-check**: Lockfile vs. pyproject.toml consistency +2. **pyright-type-check**: Type checking on src/ (strict mode) +3. **ruff-format-check**: Code formatting compliance +4. **ruff-lint-check**: Linting standards +5. **pytest-integration-check**: Full integration tests (requires secrets) +6. **deepeval-tests**: LLM evaluation metrics +7. **gitleaks-check**: Secret detection (pre-commit + CI) + +### Pre-commit Hooks + +Configured in `.pre-commit-config.yaml`: +- **gitleaks**: Secret scanning +- **uv-lock**: Ensures lockfile consistency + +### Constants and Thresholds + +Key retrieval constants (`src/vector_indexer/constants.py` and contextual retrieval): +- **Semantic search top-K**: 40 per query +- **Semantic threshold**: 0.4 (cosine similarity ≥0.4 = 50-60% alignment) +- **BM25 top-K**: 40 per query +- **Response generation top-K**: 10 chunks (after RRF fusion) +- **Query refinement count**: 5 variations + original = 6 total +- **Search timeout**: 2 seconds per query + +### Docker and Services + +- Use `docker compose` (not `docker-compose`) +- Services communicate via `bykstack` network +- Shared volumes: `shared-volume`, `cron_data` +- Vault agent containers per service (llm, gui, cron) +- Resource limits: CPU and memory constraints defined in docker-compose.yml + +## Important Notes + +- **Python version pinned to 3.12.10** (see `pyproject.toml` and `.python-version`) +- **Line length: 88** (Black-compatible, enforced by Ruff) +- **No print() statements** in production code (use loguru logger) +- **Pydantic for runtime validation** at API boundaries (FastAPI endpoints) +- **Langfuse tracing** for observability (public/secret keys from Vault) +- **Rate limiting** via `RateLimiter` utility (token and request budgets) +- **Cost tracking** via `calculate_total_costs()` and budget tracker +- **Language detection** for multilingual support (Estonian primary) diff --git a/.github/skills/code-review/SKILL.md b/.github/skills/code-review/SKILL.md new file mode 100644 index 00000000..b4e54798 --- /dev/null +++ b/.github/skills/code-review/SKILL.md @@ -0,0 +1,4 @@ +--- +name: code-review +description: Make sure all Python coding standards in the pyproject.toml file are followed, and that the code is clean, well-structured, maintainable, and efficient. Provide constructive feedback and suggestions for improvement. +--- diff --git a/.gitignore b/.gitignore index d0dc8cb8..77ec7863 100644 --- a/.gitignore +++ b/.gitignore @@ -9,6 +9,7 @@ datasets logs/ data_sets vault/agent-out +.vscode/ # RSA Private Keys - DO NOT COMMIT vault/keys/rsa_private_key.pem diff --git a/GUI/.env.development b/GUI/.env.development index 39f5e47a..ae5b1356 100644 --- a/GUI/.env.development +++ b/GUI/.env.development @@ -2,6 +2,6 @@ REACT_APP_RUUTER_API_URL=http://localhost:8086 REACT_APP_RUUTER_PRIVATE_API_URL=http://localhost:8088 REACT_APP_CUSTOMER_SERVICE_LOGIN=http://localhost:3004/et/dev-auth REACT_APP_SERVICE_ID=conversations,settings,monitoring -REACT_APP_NOTIFICATION_NODE_URL=http://localhost:3005 -REACT_APP_CSP=upgrade-insecure-requests; default-src 'self'; font-src 'self' data:; img-src 'self' data:; script-src 'self' 'unsafe-eval' 'unsafe-inline'; style-src 'self' 'unsafe-inline'; object-src 'none'; connect-src 'self' http://localhost:8086 http://localhost:8088 http://localhost:3004 http://localhost:3005 ws://localhost; +REACT_APP_NOTIFICATION_NODE_URL=http://localhost:4040 +REACT_APP_CSP=upgrade-insecure-requests; default-src 'self'; font-src 'self' data:; img-src 'self' data:; script-src 'self' 'unsafe-eval' 'unsafe-inline'; style-src 'self' 'unsafe-inline'; object-src 'none'; connect-src 'self' http://localhost:8086 http://localhost:8088 http://localhost:3004 http://localhost:4040 ws://localhost; REACT_APP_ENABLE_HIDDEN_FEATURES=TRUE \ No newline at end of file diff --git a/GUI/package-lock.json b/GUI/package-lock.json index 436ec9c4..c0f45b17 100644 --- a/GUI/package-lock.json +++ b/GUI/package-lock.json @@ -50,6 +50,7 @@ "react-i18next": "^12.1.1", "react-icons": "^4.10.1", "react-idle-timer": "^5.5.2", + "react-markdown": "^10.1.0", "react-modal": "^3.16.1", "react-redux": "^8.1.1", "react-router-dom": "^6.5.0", @@ -58,6 +59,7 @@ "react-textarea-autosize": "^8.4.0", "reactflow": "^11.4.0", "regexify-string": "^1.0.19", + "remark-gfm": "^4.0.1", "rxjs": "^7.8.1", "timeago.js": "^4.0.2", "usehooks-ts": "^2.9.1", @@ -6847,7 +6849,6 @@ "version": "4.1.12", "resolved": "https://registry.npmjs.org/@types/debug/-/debug-4.1.12.tgz", "integrity": "sha512-vIChWdVG3LG1SMxEvI/AK+FWJthlrqlTu7fbrlywTkkaONwk/UAGaULXRlf8vkzFBLVm0zkMdCquhL5aOjhXPQ==", - "dev": true, "dependencies": { "@types/ms": "*" } @@ -6855,14 +6856,31 @@ "node_modules/@types/estree": { "version": "1.0.5", "resolved": "https://registry.npmjs.org/@types/estree/-/estree-1.0.5.tgz", - "integrity": "sha512-/kYRxGDLWzHOB7q+wtSUQlFrtcdUccpfy+X+9iMBpHK8QLLhx2wIPYuS5DYtR9Wa/YlZAbIovy7qVdB1Aq6Lyw==", - "dev": true + "integrity": "sha512-/kYRxGDLWzHOB7q+wtSUQlFrtcdUccpfy+X+9iMBpHK8QLLhx2wIPYuS5DYtR9Wa/YlZAbIovy7qVdB1Aq6Lyw==" + }, + "node_modules/@types/estree-jsx": { + "version": "1.0.5", + "resolved": "https://registry.npmjs.org/@types/estree-jsx/-/estree-jsx-1.0.5.tgz", + "integrity": 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"https://registry.npmjs.org/stringify-entities/-/stringify-entities-4.0.4.tgz", + "integrity": "sha512-IwfBptatlO+QCJUo19AqvrPNqlVMpW9YEL2LIVY+Rpv2qsjCGxaDLNRgeGsQWJhfItebuJhsGSLjaBbNSQ+ieg==", + "license": "MIT", + "dependencies": { + "character-entities-html4": "^2.0.0", + "character-entities-legacy": "^3.0.0" + }, + "funding": { + "type": "github", + "url": "https://github.com/sponsors/wooorm" + } + }, "node_modules/strip-ansi": { "version": "6.0.1", "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.1.tgz", @@ -14429,6 +15710,24 @@ "url": "https://github.com/sponsors/sindresorhus" } }, + "node_modules/style-to-js": { + "version": "1.1.21", + "resolved": "https://registry.npmjs.org/style-to-js/-/style-to-js-1.1.21.tgz", + "integrity": "sha512-RjQetxJrrUJLQPHbLku6U/ocGtzyjbJMP9lCNK7Ag0CNh690nSH8woqWH9u16nMjYBAok+i7JO1NP2pOy8IsPQ==", + "license": "MIT", + "dependencies": { + "style-to-object": "1.0.14" + } + }, + "node_modules/style-to-object": { + "version": "1.0.14", + "resolved": "https://registry.npmjs.org/style-to-object/-/style-to-object-1.0.14.tgz", + "integrity": "sha512-LIN7rULI0jBscWQYaSswptyderlarFkjQ+t79nzty8tcIAceVomEVlLzH5VP4Cmsv6MtKhs7qaAiwlcp+Mgaxw==", + "license": "MIT", + "dependencies": { + "inline-style-parser": "0.2.7" + } + }, "node_modules/stylis": { "version": "4.2.0", "resolved": "https://registry.npmjs.org/stylis/-/stylis-4.2.0.tgz", @@ -14572,6 +15871,26 @@ "integrity": "sha512-N3WMsuqV66lT30CrXNbEjx4GEwlow3v6rr4mCcv6prnfwhS01rkgyFdjPNBYd9br7LpXV1+Emh01fHnq2Gdgrw==", "dev": true }, + "node_modules/trim-lines": { + "version": "3.0.1", + "resolved": "https://registry.npmjs.org/trim-lines/-/trim-lines-3.0.1.tgz", + "integrity": "sha512-kRj8B+YHZCc9kQYdWfJB2/oUl9rA99qbowYYBtr4ui4mZyAQ2JpvVBd/6U2YloATfqBhBTSMhTpgBHtU0Mf3Rg==", + "license": "MIT", + "funding": { + "type": "github", + "url": "https://github.com/sponsors/wooorm" + } + }, + "node_modules/trough": { + "version": "2.2.0", + "resolved": "https://registry.npmjs.org/trough/-/trough-2.2.0.tgz", + "integrity": "sha512-tmMpK00BjZiUyVyvrBK7knerNgmgvcV/KLVyuma/SC+TQN167GrMRciANTz09+k3zW8L8t60jWO1GpfkZdjTaw==", + "license": "MIT", + "funding": { + "type": "github", + "url": "https://github.com/sponsors/wooorm" + } + }, "node_modules/ts-api-utils": { "version": "2.1.0", "resolved": "https://registry.npmjs.org/ts-api-utils/-/ts-api-utils-2.1.0.tgz", @@ -14834,6 +16153,93 @@ "node": ">=4" } }, + "node_modules/unified": { + "version": "11.0.5", + "resolved": "https://registry.npmjs.org/unified/-/unified-11.0.5.tgz", + "integrity": "sha512-xKvGhPWw3k84Qjh8bI3ZeJjqnyadK+GEFtazSfZv/rKeTkTjOJho6mFqh2SM96iIcZokxiOpg78GazTSg8+KHA==", + "license": "MIT", + "dependencies": { + "@types/unist": "^3.0.0", + "bail": "^2.0.0", + "devlop": "^1.0.0", + "extend": "^3.0.0", + "is-plain-obj": "^4.0.0", + "trough": "^2.0.0", + "vfile": "^6.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/unist-util-is": { + "version": "6.0.1", + "resolved": "https://registry.npmjs.org/unist-util-is/-/unist-util-is-6.0.1.tgz", + "integrity": "sha512-LsiILbtBETkDz8I9p1dQ0uyRUWuaQzd/cuEeS1hoRSyW5E5XGmTzlwY1OrNzzakGowI9Dr/I8HVaw4hTtnxy8g==", + "license": "MIT", + "dependencies": { + "@types/unist": "^3.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/unist-util-position": { + "version": "5.0.0", + "resolved": "https://registry.npmjs.org/unist-util-position/-/unist-util-position-5.0.0.tgz", + "integrity": "sha512-fucsC7HjXvkB5R3kTCO7kUjRdrS0BJt3M/FPxmHMBOm8JQi2BsHAHFsy27E0EolP8rp0NzXsJ+jNPyDWvOJZPA==", + "license": "MIT", + "dependencies": { + "@types/unist": "^3.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/unist-util-stringify-position": { + "version": "4.0.0", + "resolved": "https://registry.npmjs.org/unist-util-stringify-position/-/unist-util-stringify-position-4.0.0.tgz", + "integrity": "sha512-0ASV06AAoKCDkS2+xw5RXJywruurpbC4JZSm7nr7MOt1ojAzvyyaO+UxZf18j8FCF6kmzCZKcAgN/yu2gm2XgQ==", + "license": "MIT", + "dependencies": { + "@types/unist": "^3.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/unist-util-visit": { + "version": "5.1.0", + "resolved": "https://registry.npmjs.org/unist-util-visit/-/unist-util-visit-5.1.0.tgz", + "integrity": "sha512-m+vIdyeCOpdr/QeQCu2EzxX/ohgS8KbnPDgFni4dQsfSCtpz8UqDyY5GjRru8PDKuYn7Fq19j1CQ+nJSsGKOzg==", + "license": "MIT", + "dependencies": { + "@types/unist": "^3.0.0", + "unist-util-is": "^6.0.0", + "unist-util-visit-parents": "^6.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/unist-util-visit-parents": { + "version": "6.0.2", + "resolved": "https://registry.npmjs.org/unist-util-visit-parents/-/unist-util-visit-parents-6.0.2.tgz", + "integrity": "sha512-goh1s1TBrqSqukSc8wrjwWhL0hiJxgA8m4kFxGlQ+8FYQ3C/m11FcTs4YYem7V664AhHVvgoQLk890Ssdsr2IQ==", + "license": "MIT", + "dependencies": { + "@types/unist": "^3.0.0", + "unist-util-is": "^6.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, "node_modules/universal-cookie": { "version": "4.0.4", "resolved": "https://registry.npmjs.org/universal-cookie/-/universal-cookie-4.0.4.tgz", @@ -15036,6 +16442,34 @@ "uuid": "dist/bin/uuid" } }, + "node_modules/vfile": { + "version": "6.0.3", + "resolved": "https://registry.npmjs.org/vfile/-/vfile-6.0.3.tgz", + "integrity": "sha512-KzIbH/9tXat2u30jf+smMwFCsno4wHVdNmzFyL+T/L3UGqqk6JKfVqOFOZEpZSHADH1k40ab6NUIXZq422ov3Q==", + "license": "MIT", + "dependencies": { + "@types/unist": "^3.0.0", + "vfile-message": "^4.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/vfile-message": { + "version": "4.0.3", + "resolved": "https://registry.npmjs.org/vfile-message/-/vfile-message-4.0.3.tgz", + "integrity": "sha512-QTHzsGd1EhbZs4AsQ20JX1rC3cOlt/IWJruk893DfLRr57lcnOeMaWG4K0JrRta4mIJZKth2Au3mM3u03/JWKw==", + "license": "MIT", + "dependencies": { + "@types/unist": "^3.0.0", + "unist-util-stringify-position": "^4.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, "node_modules/vite": { "version": "4.5.3", "resolved": "https://registry.npmjs.org/vite/-/vite-4.5.3.tgz", @@ -15855,6 +17289,16 @@ "peerDependencies": { "react": "^16.8.0 || ^17.0.0 || ^18.0.0" } + }, + "node_modules/zwitch": { + "version": "2.0.4", + "resolved": "https://registry.npmjs.org/zwitch/-/zwitch-2.0.4.tgz", + "integrity": "sha512-bXE4cR/kVZhKZX/RjPEflHaKVhUVl85noU3v6b8apfQEc1x4A+zBxjZ4lN8LqGd6WZ3dl98pY4o717VFmoPp+A==", + "license": "MIT", + "funding": { + "type": "github", + "url": "https://github.com/sponsors/wooorm" + } } } } diff --git a/GUI/package.json b/GUI/package.json index 09ab4a81..ec9c4e78 100644 --- a/GUI/package.json +++ b/GUI/package.json @@ -53,6 +53,7 @@ "react-i18next": "^12.1.1", "react-icons": "^4.10.1", "react-idle-timer": "^5.5.2", + "react-markdown": "^10.1.0", "react-modal": "^3.16.1", "react-redux": "^8.1.1", "react-router-dom": "^6.5.0", @@ -61,6 +62,7 @@ "react-textarea-autosize": "^8.4.0", "reactflow": "^11.4.0", "regexify-string": "^1.0.19", + "remark-gfm": "^4.0.1", "rxjs": "^7.8.1", "timeago.js": "^4.0.2", "usehooks-ts": "^2.9.1", diff --git a/GUI/src/components/MessageContent/MessageContent.scss b/GUI/src/components/MessageContent/MessageContent.scss index 7b4eea5c..aec56409 100644 --- a/GUI/src/components/MessageContent/MessageContent.scss +++ b/GUI/src/components/MessageContent/MessageContent.scss @@ -1,61 +1,112 @@ .message-content-wrapper { width: 100%; + line-height: 1.6; - .message-text { - margin-bottom: 12px; - line-height: 1.6; + // Markdown text styling + p { + margin: 0 0 12px 0; white-space: pre-wrap; word-wrap: break-word; + + &:last-child { + margin-bottom: 0; + } + } + + // Bold text + .markdown-bold, + strong { + font-weight: 600; + } + + // Ordered lists (for references) + .markdown-list, + ol { + margin: 16px 0 0 0; + padding-left: 20px; + list-style-type: decimal; } - .message-references { - margin-top: 16px; - padding-top: 12px; - border-top: 1px solid rgba(0, 0, 0, 0.1); + // List items + .markdown-list-item, + li { + margin-bottom: 6px; + line-height: 1.5; - .references-title { - display: block; - font-weight: 600; - margin-bottom: 8px; - font-size: 14px; + &:last-child { + margin-bottom: 0; } + } - .references-list { - margin: 0; - padding-left: 20px; - list-style-type: decimal; + // Links + a { + color: #0066cc; + text-decoration: none; + word-break: break-all; + transition: color 0.2s ease; - li { - margin-bottom: 6px; - line-height: 1.5; + &:hover { + color: #0052a3; + text-decoration: underline; + } - &:last-child { - margin-bottom: 0; - } - } + &:visited { + color: #551a8b; + } + } - .reference-link { - color: #0066cc; - text-decoration: none; - word-break: break-all; - transition: color 0.2s ease; + // Inline code + code { + background-color: rgba(0, 0, 0, 0.05); + padding: 2px 6px; + border-radius: 3px; + font-family: monospace; + font-size: 0.9em; + } - &:hover { - color: #0052a3; - text-decoration: underline; - } + // Code blocks + pre { + background-color: rgba(0, 0, 0, 0.05); + padding: 12px; + border-radius: 6px; + overflow-x: auto; + margin: 12px 0; - &:visited { - color: #551a8b; - } - } + code { + background-color: transparent; + padding: 0; } } + + // Headings + h1, h2, h3, h4, h5, h6 { + margin: 16px 0 8px 0; + font-weight: 600; + } + + // Blockquotes + blockquote { + border-left: 4px solid rgba(0, 0, 0, 0.2); + padding-left: 12px; + margin: 12px 0; + color: rgba(0, 0, 0, 0.7); + } } // Dark mode support .test-production-llm__message--bot { - .message-references { - border-top-color: rgba(255, 255, 255, 0.1); + .message-content-wrapper { + code { + background-color: rgba(255, 255, 255, 0.1); + } + + pre { + background-color: rgba(255, 255, 255, 0.1); + } + + blockquote { + border-left-color: rgba(255, 255, 255, 0.2); + color: rgba(255, 255, 255, 0.7); + } } } diff --git a/GUI/src/components/MessageContent/index.tsx b/GUI/src/components/MessageContent/index.tsx index 63ff7f2a..69b7ffe3 100644 --- a/GUI/src/components/MessageContent/index.tsx +++ b/GUI/src/components/MessageContent/index.tsx @@ -1,4 +1,6 @@ import { FC } from 'react'; +import ReactMarkdown from 'react-markdown'; +import remarkGfm from 'remark-gfm'; import './MessageContent.scss'; interface MessageContentProps { @@ -6,85 +8,33 @@ interface MessageContentProps { } const MessageContent: FC = ({ content }) => { - // Function to parse and render message content with proper formatting - const renderContent = () => { - // Split by **References:** pattern - const referencesMatch = content.match(/\*\*References:\*\*([\s\S]*)/); - - if (!referencesMatch) { - // No references, return plain content with line breaks - return ( -
- {content.split('\n').map((line, index) => ( - - {line} - {index < content.split('\n').length - 1 &&
} - - ))} -
- ); - } - - // Split content into main text and references - const mainText = content.substring(0, referencesMatch.index); - const referencesText = referencesMatch[1].trim(); - - // Parse numbered references with URLs - const referenceLines = referencesText - .split('\n') - .filter(line => line.trim()) - .map(line => { - // Match pattern: "1. https://url" or "1. url" - const match = line.match(/^(\d+)\.\s+(https?:\/\/[^\s]+)/); - if (match) { - return { - number: match[1], - url: match[2], - }; - } - return null; - }) - .filter(Boolean); - - return ( -
- {/* Main text */} - {mainText && ( -
- {mainText.split('\n').map((line, index) => ( - - {line} - {index < mainText.split('\n').length - 1 &&
} - - ))} -
- )} - - {/* References section */} - {referenceLines.length > 0 && ( -
- References: -
    - {referenceLines.map((ref, index) => ( -
  1. - - {ref!.url} - -
    2. - ))} -
-
- )} -
- ); - }; - - return <>{renderContent()}; + return ( + + ); }; export default MessageContent; diff --git a/GUI/src/hooks/useStreamingResponse.tsx b/GUI/src/hooks/useStreamingResponse.tsx index 211d44f5..8a9d7792 100644 --- a/GUI/src/hooks/useStreamingResponse.tsx +++ b/GUI/src/hooks/useStreamingResponse.tsx @@ -1,6 +1,19 @@ import { useState, useRef, useCallback, useEffect } from 'react'; import axios from 'axios'; +const getNotificationNodeUrl = (): string => { + const value = import.meta.env.REACT_APP_NOTIFICATION_NODE_URL; + if (!value) { + throw new Error( + 'Environment variable REACT_APP_NOTIFICATION_NODE_URL is not defined. ' + + 'Please set it to the base URL of the notification service to enable streaming responses.' + ); + } + return value; +}; +const notificationNodeUrl = getNotificationNodeUrl(); +console.log(notificationNodeUrl); + interface StreamingOptions { authorId: string; conversationHistory: Array<{ authorRole: string; message: string; timestamp: string }>; @@ -50,7 +63,7 @@ export const useStreamingResponse = (channelId: string): UseStreamingResponseRet try { // Step 1: Open SSE connection FIRST - const sseUrl = `https://est-rag-rtc.rootcode.software/notifications-server/sse/stream/${channelId}`; + const sseUrl = `${notificationNodeUrl}/sse/stream/${channelId}`; console.log('[SSE] Connecting to:', sseUrl); const eventSource = new EventSource(sseUrl); @@ -102,7 +115,7 @@ export const useStreamingResponse = (channelId: string): UseStreamingResponseRet await new Promise(resolve => setTimeout(resolve, 500)); // Step 3: POST to trigger streaming - const postUrl = `https://est-rag-rtc.rootcode.software/notifications-server/channels/${channelId}/orchestrate/stream`; + const postUrl = `${notificationNodeUrl}/channels/${channelId}/orchestrate/stream`; console.log('[API] Triggering stream:', postUrl); await axios.post(postUrl, { diff --git a/GUI/src/pages/TestModel/index.tsx b/GUI/src/pages/TestModel/index.tsx index c00c3ae1..4829d12b 100644 --- a/GUI/src/pages/TestModel/index.tsx +++ b/GUI/src/pages/TestModel/index.tsx @@ -3,6 +3,8 @@ import { Button, FormSelect, FormTextarea, Collapsible } from 'components'; import CircularSpinner from 'components/molecules/CircularSpinner/CircularSpinner'; import { FC, useState } from 'react'; import { useTranslation } from 'react-i18next'; +import ReactMarkdown from 'react-markdown'; +import remarkGfm from 'remark-gfm'; import './TestLLM.scss'; import { useDialog } from 'hooks/useDialog'; import { fetchLLMConnectionsPaginated, LegacyLLMConnectionFilters } from 'services/llmConnections'; @@ -139,7 +141,9 @@ const TestLLM: FC = () => {
Response:
- {inferenceResult.content} + + {inferenceResult.content} +
@@ -155,7 +159,9 @@ const TestLLM: FC = () => { Rank {contextItem.rank}
- {contextItem.chunkRetrieved} + + {contextItem.chunkRetrieved} +
))} diff --git a/GUI/src/pages/TestProductionLLM/TestProductionLLM.scss b/GUI/src/pages/TestProductionLLM/TestProductionLLM.scss index 1bd8e0f1..df51e327 100644 --- a/GUI/src/pages/TestProductionLLM/TestProductionLLM.scss +++ b/GUI/src/pages/TestProductionLLM/TestProductionLLM.scss @@ -77,6 +77,34 @@ border-radius: 18px 18px 18px 4px; } } + + &--error { + .test-production-llm__message-content { + border-color: #f44336; + background-color: #ffebee; + } + } + } + + &__message-error { + display: flex; + align-items: flex-start; + gap: 0.5rem; + margin-top: 0.5rem; + padding-top: 0.5rem; + border-top: 1px solid #ffcdd2; + font-size: 0.85rem; + color: #c62828; + } + + &__message-error-icon { + flex-shrink: 0; + font-size: 1rem; + } + + &__message-error-text { + flex: 1; + line-height: 1.3; } &__message-content { diff --git a/GUI/src/pages/TestProductionLLM/index.tsx b/GUI/src/pages/TestProductionLLM/index.tsx index a9c14935..d978ba16 100644 --- a/GUI/src/pages/TestProductionLLM/index.tsx +++ b/GUI/src/pages/TestProductionLLM/index.tsx @@ -1,153 +1,169 @@ -import { FC, useState, useRef, useEffect } from 'react'; +import { FC, useState, useRef, useEffect, useMemo } from 'react'; import { useTranslation } from 'react-i18next'; -import { Button, FormTextarea, Section } from 'components'; -import { productionInference, ProductionInferenceRequest } from 'services/inference'; +import { Button, FormTextarea } from 'components'; import { useToast } from 'hooks/useToast'; +import { useStreamingResponse } from 'hooks/useStreamingResponse'; import './TestProductionLLM.scss'; - +import MessageContent from 'components/MessageContent'; interface Message { id: string; content: string; isUser: boolean; timestamp: string; + hasError?: boolean; + errorMessage?: string; } const TestProductionLLM: FC = () => { const { t } = useTranslation(); const toast = useToast(); - const [message, setMessage] = useState(''); + const [inputMessage, setInputMessage] = useState(''); const [messages, setMessages] = useState([]); const [isLoading, setIsLoading] = useState(false); const messagesEndRef = useRef(null); - const scrollToBottom = () => { - messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' }); - }; + // Generate a unique channel ID for this session + const channelId = useMemo(() => `channel-${Math.random().toString(36).substring(2, 15)}`, []); + const { startStreaming, stopStreaming, isStreaming } = useStreamingResponse(channelId); + // Auto-scroll to bottom useEffect(() => { - scrollToBottom(); + messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' }); }, [messages]); + // Cleanup incomplete messages on unmount if streaming is active + useEffect(() => { + return () => { + if (isStreaming) { + stopStreaming(); + // Remove incomplete bot messages on unmount + setMessages(prev => prev.filter(msg => msg.isUser || !msg.content.trim() === false)); + } + }; + }, [isStreaming, stopStreaming]); + const handleSendMessage = async () => { - if (!message.trim()) { + if (!inputMessage.trim()) { toast.open({ type: 'warning', - title: t('warningTitle'), - message: t('emptyMessageWarning'), + title: t('testProductionLLM.warningTitle'), + message: t('testProductionLLM.emptyMessageWarning'), }); return; } + const userMessageText = inputMessage.trim(); + + // Add user message const userMessage: Message = { id: `user-${Date.now()}`, - content: message.trim(), + content: userMessageText, isUser: true, timestamp: new Date().toISOString(), }; - // Add user message to chat setMessages(prev => [...prev, userMessage]); - setMessage(''); + setInputMessage(''); setIsLoading(true); - try { - // Hardcoded values as requested - const request: ProductionInferenceRequest = { - chatId: 'test-chat-001', - message: userMessage.content, - authorId: 'test-author-001', - conversationHistory: messages.map(msg => ({ - authorRole: msg.isUser ? 'user' : 'bot', - message: msg.content, - timestamp: msg.timestamp, - })), - url: 'https://test-url.example.com', - }; - - let response; - let attemptCount = 0; - const maxAttempts = 2; - - // Retry logic - while (attemptCount < maxAttempts) { - try { - attemptCount++; - console.log(`Production Inference Attempt ${attemptCount}/${maxAttempts}`); - response = await productionInference(request); - - // If we get a successful response, break out of retry loop - if (!response.status || response.status < 400) { - break; - } - - // If first attempt failed with error status, retry once more - if (attemptCount < maxAttempts && response.status >= 400) { - console.log('Retrying due to error status...'); - continue; - } - } catch (err) { - // If first attempt threw an error, retry once more - if (attemptCount < maxAttempts) { - console.log('Retrying due to exception...'); - continue; - } - throw err; // Re-throw on final attempt - } - } + // Create bot message ID + const botMessageId = `bot-${Date.now()}`; - console.log('Production Inference Response:', response); + // Prepare conversation history (exclude the current user message) + const conversationHistory = messages.map(msg => ({ + authorRole: msg.isUser ? 'user' : 'bot', + message: msg.content, + timestamp: msg.timestamp, + })); - // Create bot response message - let botContent = ''; - let botMessageType: 'success' | 'error' = 'success'; + const streamingOptions = { + authorId: 'test-user-456', + conversationHistory, + url: 'opensearch-dashboard-test', + }; - if (response.status && response.status >= 400) { - // Error response - botContent = response.content || 'An error occurred while processing your request.'; - botMessageType = 'error'; - } else { - // Success response - botContent = response?.response?.content || 'Response received successfully.'; + // Callbacks for streaming + const onToken = (token: string) => { + console.log('[Component] Received token:', token); + + setMessages(prev => { + // Find the bot message + const botMsgIndex = prev.findIndex(msg => msg.id === botMessageId); - if (response.questionOutOfLlmScope) { - botContent += ' (Note: This question appears to be outside the LLM scope)'; + if (botMsgIndex === -1) { + // First token - add the bot message + console.log('[Component] Adding bot message with first token'); + return [ + ...prev, + { + id: botMessageId, + content: token, + isUser: false, + timestamp: new Date().toISOString(), + } + ]; + } else { + // Append token to existing message + console.log('[Component] Appending token to existing message'); + const updated = [...prev]; + updated[botMsgIndex] = { + ...updated[botMsgIndex], + content: updated[botMsgIndex].content + token, + }; + return updated; } - } - - const botMessage: Message = { - id: `bot-${Date.now()}`, - content: botContent, - isUser: false, - timestamp: new Date().toISOString(), - }; - - setMessages(prev => [...prev, botMessage]); + }); + }; - // Show toast notification - // toast.open({ - // type: botMessageType, - // title: t('errorOccurred'), - // message: t('errorMessage'), - // }); + const onComplete = () => { + console.log('[Component] Stream completed'); + // Always reset loading state on completion + setIsLoading(false); + }; - } catch (error) { - console.error('Error sending message:', error); + const onError = (error: string) => { + console.error('[Component] Stream error:', error); + // Always reset loading state on error + setIsLoading(false); + + // Handle incomplete bot message + setMessages(prev => { + const botMsgIndex = prev.findIndex(msg => msg.id === botMessageId); + + if (botMsgIndex !== -1) { + const botMessage = prev[botMsgIndex]; + + // If the bot message has content, mark it as errored + if (botMessage.content.trim()) { + const updated = [...prev]; + updated[botMsgIndex] = { + ...botMessage, + hasError: true, + errorMessage: error, + }; + return updated; + } else { + // If no content, remove the empty bot message + return prev.filter(msg => msg.id !== botMessageId); + } + } + + return prev; + }); - const errorMessage: Message = { - id: `error-${Date.now()}`, - content: 'Failed to send message. Please check your connection and try again.', - isUser: false, - timestamp: new Date().toISOString(), - }; - - setMessages(prev => [...prev, errorMessage]); - toast.open({ type: 'error', - title: 'Connection Error', - message: 'Unable to connect to the production LLM service.', + title: t('testProductionLLM.streamingErrorTitle'), + message: error, }); - } finally { + }; + + // Start streaming + try { + await startStreaming(userMessageText, streamingOptions, onToken, onComplete, onError); + } catch (error) { + console.error('[Component] Failed to start streaming:', error); + // Reset loading state if streaming fails to start setIsLoading(false); } }; @@ -161,10 +177,11 @@ const TestProductionLLM: FC = () => { const clearChat = () => { setMessages([]); + stopStreaming(); toast.open({ type: 'info', - title: 'Chat Cleared', - message: 'All messages have been cleared.', + title: t('testProductionLLM.chatClearedTitle'), + message: t('testProductionLLM.chatClearedMessage'), }); }; @@ -172,9 +189,9 @@ const TestProductionLLM: FC = () => {
-

{t('Test Production LLM')}

+

{t('testProductionLLM.title')}

@@ -182,8 +199,8 @@ const TestProductionLLM: FC = () => {
{messages.length === 0 && (
-

Welcome to Production LLM Testing

-

Start a conversation by typing a message below.

+

{t('testProductionLLM.welcomeTitle')}

+

{t('testProductionLLM.welcomeSubtitle')}

)} @@ -192,10 +209,21 @@ const TestProductionLLM: FC = () => { key={msg.id} className={`test-production-llm__message ${ msg.isUser ? 'test-production-llm__message--user' : 'test-production-llm__message--bot' + } ${ + msg.hasError ? 'test-production-llm__message--error' : '' }`} >
- {msg.content} + + {msg.hasError && ( +
+ ⚠️ + + {t('testProductionLLM.incompleteMessageError', { defaultValue: 'This message is incomplete due to an error' })} + {msg.errorMessage && `: ${msg.errorMessage}`} + +
+ )}
{new Date(msg.timestamp).toLocaleTimeString()} @@ -220,22 +248,22 @@ const TestProductionLLM: FC = () => {
setMessage(e.target.value)} + value={inputMessage} + onChange={(e) => setInputMessage(e.target.value)} onKeyDown={handleKeyPress} - placeholder="Type your message here... (Press Enter to send, Shift+Enter for new line)" + placeholder={t('testProductionLLM.messagePlaceholder')??""} hideLabel maxRows={4} - disabled={isLoading} + disabled={isLoading || isStreaming} />
diff --git a/GUI/translations/en/common.json b/GUI/translations/en/common.json index 8c2cac8a..a71a2f3e 100644 --- a/GUI/translations/en/common.json +++ b/GUI/translations/en/common.json @@ -414,6 +414,21 @@ "azure": "Azure OpenAI" } }, + "testProductionLLM": { + "title": "Test Production LLM", + "clearChat": "Clear Chat", + "welcomeTitle": "Welcome to Production LLM Testing", + "welcomeSubtitle": "Start a conversation by typing a message below.", + "messageLabel": "Message", + "messagePlaceholder": "Type your message here... (Press Enter to send, Shift+Enter for new line)", + "sendButton": "Send", + "sendingButton": "Sending...", + "warningTitle": "Warning", + "emptyMessageWarning": "Please enter a message", + "streamingErrorTitle": "Streaming Error", + "chatClearedTitle": "Chat Cleared", + "chatClearedMessage": "All messages have been cleared." + }, "promptConfigurations": { "title": "Prompt Configurations", "subtitle": "Configure and manage your prompt templates", diff --git a/GUI/translations/et/common.json b/GUI/translations/et/common.json index 1c093b6f..b1030db5 100644 --- a/GUI/translations/et/common.json +++ b/GUI/translations/et/common.json @@ -415,6 +415,21 @@ "azure": "Azure OpenAI" } }, + "testProductionLLM": { + "title": "Testi Tootmise LLM", + "clearChat": "Tühjenda Vestlus", + "welcomeTitle": "Tere tulemast Tootmise LLM Testimisse", + "welcomeSubtitle": "Alusta vestlust, kirjutades allpool sõnumi.", + "messageLabel": "Sõnum", + "messagePlaceholder": "Kirjuta oma sõnum siia... (Vajuta Enter saatmiseks, Shift+Enter uue rea jaoks)", + "sendButton": "Saada", + "sendingButton": "Saatmine...", + "warningTitle": "Hoiatus", + "emptyMessageWarning": "Palun sisesta sõnum", + "streamingErrorTitle": "Voogedastuse Viga", + "chatClearedTitle": "Vestlus Tühjendatud", + "chatClearedMessage": "Kõik sõnumid on tühjendatud." + }, "promptConfigurations": { "title": "Viiba Seaded", "subtitle": "Seadista ja halda oma viiba malle", diff --git a/docs/TOOL_CLASSIFIER_EXTENSION_SPEC.md b/docs/TOOL_CLASSIFIER_EXTENSION_SPEC.md index e198114a..469f8092 100644 --- a/docs/TOOL_CLASSIFIER_EXTENSION_SPEC.md +++ b/docs/TOOL_CLASSIFIER_EXTENSION_SPEC.md @@ -1937,4 +1937,4 @@ def process_orchestration_request(self, request: OrchestrationRequest): | False Positive Rate (Service) | < 5% | Incorrect service routing | | User Satisfaction | > 4.0/5.0 | User feedback surveys | ---- \ No newline at end of file +--- diff --git a/pyproject.toml b/pyproject.toml index dd8f876c..56e14264 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -123,4 +123,4 @@ exclude = [ ] # --- Global strictness --- -typeCheckingMode = "standard" # Standard typechecking mode \ No newline at end of file +typeCheckingMode = "standard" # Standard typechecking mode diff --git a/src/tool_classifier/workflows/context_workflow.py b/src/tool_classifier/workflows/context_workflow.py index 78d71c19..88212efa 100644 --- a/src/tool_classifier/workflows/context_workflow.py +++ b/src/tool_classifier/workflows/context_workflow.py @@ -9,35 +9,16 @@ class ContextWorkflowExecutor(BaseWorkflow): """ - Handles queries answerable from conversation history or greetings (Layer 2). - - This workflow handles two types of queries: - 1. Greetings and conversational pleasantries - - "Hello", "Good morning", "Thanks", "Goodbye" - 2. Queries referencing conversation history - - "What did you say earlier?" - - "Can you repeat that?" - - "What was the rate you mentioned?" - - Uses LLM-based detection (no regex patterns) for: - - Semantic greeting detection (multilingual) - - Context reference detection - - Answer extraction from conversation history - - Examples: - - "Tere!" → Friendly greeting response - - "Hello" → "Hello! How can I help you?" - - "What was the rate?" (history: "Rate is 1.08") → "The rate was 1.08" - - Implementation Status: SKELETON - Returns None (triggers fallback to RAG workflow) - - TODO - Full Implementation (Separate Task): - - Greeting detection using LLM - - Context availability check using LLM - - Answer extraction from conversation history - - Output guardrails for context-based responses - - Multilingual support (Estonian, English) + Handles greetings and conversation history queries (Layer 2). + + Detects: + - Greetings: "Hello", "Thanks", "Goodbye" + - History references: "What did you say earlier?", "Can you repeat that?" + + Uses LLM for semantic detection (multilingual), no regex patterns. + + Status: SKELETON - Returns None (fallback to RAG) + TODO: Implement greeting/context detection, answer extraction, guardrails """ def __init__(self, llm_manager: Any): @@ -58,32 +39,8 @@ async def execute_async( """ Execute context workflow in non-streaming mode. - TODO: Implement context workflow logic: - 1. Check if query is a greeting using LLM - - If yes: Generate appropriate greeting response - 2. If not greeting, check conversation history: - - Get recent history (last 10 turns) - - Call LLM to check if query can be answered from history - - If yes: Extract answer from history - 3. Validate answer with output guardrails - 4. Return OrchestrationResponse with context-based answer - - LLM Prompt for Context Check: - ``` - Conversation History: - 1. User: What's the exchange rate? - 2. Bot: EUR/USD rate is 1.08 - 3. User: Thanks - - Current Query: "What was the rate?" - - Can this be answered from history? If yes, provide answer. - ``` - - Failure scenarios: - - Not a greeting and no conversation history → return None - - Cannot answer from history → return None (fallback to RAG) - - Output guardrails blocked → return None or violation message + TODO: Check greeting (LLM) → generate response, OR check history (last 10 turns) + → extract answer → validate with guardrails. Return None if cannot answer. Args: request: Orchestration request with user query and history @@ -109,35 +66,8 @@ async def execute_streaming( """ Execute context workflow in streaming mode. - TODO: Implement context workflow streaming: - 1. Detect greeting or check conversation history (same as non-streaming) - 2. Get complete answer from history or generate greeting response - 3. Validate with output guardrails (validation-first) - 4. If blocked: yield violation message + END - 5. If allowed: chunk answer and stream token-by-token - 6. Simulate streaming for consistent UX with RAG - - Streaming approach (validation-first): - ```python - # Get complete context-based answer - context_result = await analyze_context(query, history) - - if not context_result.can_answer: - return None # Fallback to RAG - - # Validate BEFORE streaming - is_safe = await guardrails.check_output_async(context_result.answer) - if not is_safe: - yield format_sse(chatId, VIOLATION_MESSAGE) - yield format_sse(chatId, "END") - return - - # Stream validated answer - for chunk in split_into_tokens(context_result.answer, chunk_size=5): - yield format_sse(chatId, chunk) - await asyncio.sleep(0.01) - yield format_sse(chatId, "END") - ``` + TODO: Get answer (greeting/history) → validate BEFORE streaming → chunk and + yield as SSE. Return None if cannot answer. Args: request: Orchestration request with user query and history