AstroResearch/CLAUDE.md

# CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

## Build, Lint & Test Commands

```bash
# Build (debug)
cargo build

# Build (release with optimizations)
cargo build --release

# Build (release-min profile: size-optimized LTO)
cargo build --profile release-min

# Run (debug, starts server on http://localhost:8000)
cargo run

# Run with Obscura in-process browser (no external binaries needed)
cargo run --features obscura-inprocess

# Run CLI binary
cargo run --bin astroresearch_cli

# Run health check tool
cargo run --bin health_check          # read-only scan
cargo run --bin health_check -- --fix # auto-repair

# Lint
cargo clippy

# Format
cargo fmt

# All tests
cargo test

# Unit tests only
cargo test --lib

# Run a specific test
cargo test test_name

# Coverage (requires cargo-llvm-cov)
cargo llvm-cov --fail-under-lines 80

# Frontend (cd dashboard first)
npm run dev       # HMR dev server on :5173, proxies /api to :8000
npm run build     # TypeScript check + Vite production build → dashboard/dist/
npm run lint      # ESLint
npm run lint:fix  # ESLint with auto-fix
npm run format    # Prettier format all source files
npm run format:check  # Check formatting without modifying files
```

## Architecture Overview

**Stack**: Rust Axum backend (port 8000) + React/Vite/TypeScript frontend (port 5173 in dev). In production, the Rust binary serves the pre-built `dashboard/dist/` via `ServeDir` and `ServeFile` fallback, so there is a single process.

### Source Layer Map

```
src/
├── main.rs          # Axum server entry: logging, DB pool, migrations, vec0 table,
│                    # client/service construction, route registration, AppState assembly
├── lib.rs           # Config struct + from_env() loading from .env
├── api/             # HTTP handlers, AppState, re-exports via handlers namespace
│   ├── mod.rs       # AppState (shared state), handler re-exports, permission/event types
│   ├── agent.rs     # SSE chat_agent endpoint, session CRUD, metrics, audit log
│   ├── papers.rs    # Search, download, parse, translate, embed, citations, library, export
│   ├── catalog.rs   # VizieR TAP catalog queries + cone search endpoints
│   ├── observation.rs # Observation data search/download (LAMOST/Gaia/SDSS/DESI)
│   ├── notes.rs     # Highlight/note CRUD
│   ├── sync.rs      # Meta-sync and asset-batch endpoints
│   ├── targets.rs   # Target query/associate/extract, RAG chat, figure chat
│   ├── auth.rs      # Login/logout/auth-check (token-based, session memory)
│   ├── permissions.rs # Agent tool permission rule management
│   ├── search.rs    # Search history endpoint
│   ├── error.rs     # Unified API error type (status code + user-safe message)
│   └── helpers.rs   # Shared DB helpers, format conversion, path validation (private)
├── agent/           # ReAct-based research agent (LLM-driven tool-use loop)
│   ├── tools/       # AgentTool trait, ToolRegistry, tool implementations per domain
│   │   ├── mod.rs       # AgentTool trait, ToolContext (session_id, sse_tx, silent, etc.)
│   │   ├── filesystem/  # read_file, grep_files, write, edit
│   │   ├── astro/       # search_papers, download_paper, parse_paper, rag_search,
│   │   │                #   query_target, save_note, analyze_image, research/*
│   │   ├── ask_user.rs  # Permission-gated interactive user question
│   │   ├── background.rs# bg_task_run, bg_task_check (async slow tasks)
│   │   ├── compress.rs  # Context compression trigger
│   │   ├── memory.rs    # save_memory, load_memory
│   │   ├── persist.rs   # Data persistence (used by memory/compaction)
│   │   ├── skill.rs     # load_skill
│   │   ├── subagent.rs  # Context-isolated sub-agent spawner
│   │   ├── team.rs      # spawn_teammate, send_teammate_message, etc.
│   │   └── todo.rs      # todo_write (task tracking)
│   ├── runtime/     # ReAct loop core
│   │   ├── mod.rs            # AgentRuntime: session create/resume → context → ReAct → finalize
│   │   ├── executor/         # Step executor + helpers (tool dispatch, parallel tool calls)
│   │   ├── streaming.rs      # SSE AgentStreamEvent types
│   │   ├── streaming_executor.rs # SSE-emitting executor wrapper
│   │   ├── session.rs        # Session CRUD, DB persist, agent_config
│   │   ├── token_budget.rs   # Soft/hard token limits, tiktoken counting
│   │   ├── permission.rs     # Deny > Allow > Ask rule chain, pattern matching
│   │   ├── permission_profile.rs # Named profiles (research, readonly)
│   │   ├── checkpoint.rs     # Rewind/retry state snapshots
│   │   ├── circuit_breaker.rs# CompactionCircuitBreaker (cooldown rate limiting)
│   │   ├── error_recovery.rs # Error classification + retry strategies
│   │   ├── hardline.rs       # Terminal conditions (too many denials, loops, etc.)
│   │   ├── partitioner.rs    # Message window partitioning for compaction
│   │   ├── file_cache.rs     # ReadFileState — file content dedup cache
│   │   ├── system_prompt.rs  # System prompt assembly (mode, skills, memory, tools)
│   │   ├── finalize.rs       # Post-loop cleanup: memory extraction, audit log
│   │   └── denial_tracker.rs # Consecutive denial detection
│   ├── compact/     # Context compression (micro/auto/manual layers + collapse)
│   ├── memory/      # Persistent memory manager: extraction, dedup, decay, age, guardrails
│   ├── hooks/       # Lifecycle hooks: registry, dispatch, builtins, matcher, traits
│   ├── modes/       # Agent session modes (see Agent Session Modes section below)
│   ├── skills.rs    # SkillRegistry: hot-loads SKILL.md files from skills/ directory
│   ├── subagent.rs  # Context-isolated sub-agent runner
│   ├── team/        # Multi-agent team: file-based inbox, lead/teammate coordination
│   ├── background.rs# BgNotificationQueue for async slow-task notifications
│   ├── task_board.rs# Persistent task board (agent_tasks table)
│   ├── trajectory.rs# Session trajectory recording for audit/debug
│   └── terminal.rs  # Escape sequence filter for ANSI-heavy tool outputs
├── clients/         # External API wrappers (pure communication, no business logic)
│   ├── llm/         # LlmClient (OpenAI-compatible chat + streaming), EmbeddingClient
│   ├── ads.rs       # NASA ADS API
│   ├── arxiv.rs     # arXiv Atom XML API
│   ├── cds/         # CDS services (sesame.rs — Sesame name resolver; vizier.rs — TAP queries)
│   ├── gaia/        # Gaia archive (TAP + DataLink)
│   ├── lamost/      # LAMOST archive (ConeSearch + FITS.gz download)
│   ├── sdss/        # SDSS archive (Data Lab TAP + SAS bulk download)
│   ├── desi/        # DESI archive (Data Lab TAP + HEALPix coadd SAS)
│   ├── vo/          # Virtual Observatory generic client
│   └── qiniu.rs     # Qiniu cloud storage
├── services/        # Business logic
│   ├── search.rs         # Unified cross-source search (ADS + arXiv dedup)
│   ├── download.rs       # PDF/HTML download with anti-bot measures and fallback chain
│   ├── parser/           # HTML/PDF → Markdown parsers (A&A, IOP, ar5iv, generic, PDF via MinerU)
│   ├── paper/            # Paper lifecycle: model, db (CRUD), ingest (ADS/arXiv→DB), reader (markdown)
│   ├── translation.rs    # LLM bilingual translation with Trie-based astronomy glossary
│   ├── rag.rs            # Embedding ingest + vector similarity retrieval + LLM answer generation
│   ├── cds/              # CDS business layer: target.rs (Sesame name resolver), vizier.rs (TAP + cache)
│   ├── observation/      # Cross-source observation data (spectra, light curves, photometry, images)
│   │   ├── mod.rs        #   双轴正交架构: Source × ProductType → ObservationFetcher → Registry
│   │   ├── types.rs      #   Source/ProductType/ProductSpec/Artifact/ObservationProduct/Candidate
│   │   ├── fetcher.rs    #   ObservationFetcher trait + cone search cache template methods
│   │   ├── registry.rs   #   ObservationRegistry (fetcher registration, capability discovery)
│   │   ├── dispatch.rs   #   search_observation + download_observation (unified entry points)
│   │   ├── cache.rs      #   observation_cache table read/write + file staging
│   │   ├── lamost.rs     #   LamostSpectrumFetcher
│   │   ├── gaia.rs       #   GaiaSpectrumFetcher + GaiaLightCurveFetcher
│   │   ├── sdss.rs       #   SdssSpectrumFetcher + SdssApogeeFetcher
│   │   └── desi.rs       #   DesiSpectrumFetcher
│   ├── batch/            # Meta-sync (ADS bulk harvest) and asset-batch processing engines
│   ├── citation.rs       # Citation network graph data (references + citations)
│   ├── session.rs        # Agent session listing, metrics, audit log (for API consumption)
│   ├── vision.rs         # Image analysis via dedicated vision model
│   ├── note.rs           # Highlight/note storage and retrieval
│   ├── pipeline.rs       # Synchronous paper processing pipeline (download→parse→translate→embed)
│   ├── chunker.rs        # Markdown text chunking for embedding
│   ├── query_parser.rs   # Advanced search query syntax parser
│   └── logging.rs        # Pretty console + rolling file logger
└── bin/
    ├── health_check.rs # Library consistency checker and auto-repair
    ├── cli.rs          # CLI interface
    └── reparse.rs      # Re-parse existing library items
```

### AppState — Central Shared State

All handlers access state via `Arc<AppState>`. Key fields:

- `db: SqlitePool` — SQLite connection pool (5 max connections, foreign keys enforced)
- `llm: LlmClient` / `medium_llm` / `fast_llm` — OpenAI-compatible LLM clients (multi-tier)
- `vision_llm: Option<LlmClient>` — dedicated vision model client
- `embedding: EmbeddingClient` — embedding model client
- `ads: AdsClient` / `arxiv: ArxivClient` — academic search clients
- `vizier: VizierClient` — CDS VizieR TAP catalog query client
- `lamost` / `gaia` / `sdss` / `desi` — observation data source clients
- `observation_registry: Arc<ObservationRegistry>` — cross-source observation fetcher registry
- `skill_registry: Arc<RwLock<SkillRegistry>>` — hot-reloaded agent skills
- `memory_manager: Arc<MemoryManager>` — persistent agent memory (MEMORY.md + decay)
- `cancelled_runs: Arc<DashMap<String, ()>>` — agent cancellation tokens
- `session_permission_checkers: Arc<DashMap<String, PermissionChecker>>` — per-session permission rules
- `pending_questions` / `pending_permissions` — interactive agent-user handshake channels
- `harvest_status` / `batch_status` — async batch operation status tracking

### Agent System Design

The agent (`src/agent/`) implements a **ReAct** (Thought → Action → Observation) loop:

1. **`AgentRuntime`** (`runtime/mod.rs`) orchestrates the loop: session create/resume → context build → ReAct loop → finalize
2. **Streaming**: LLM response is streamed via SSE (`AgentStreamEvent`) — thought, tool_call (with `id`), tool_result (with `tool_call_id`), text_delta, usage, error, done. Tool calls execute in parallel.
3. **Tools**: Each tool implements `AgentTool` trait (name, description, JSON Schema parameters, execute). Core tools: read_file, grep_files, glob_files, run_bash, file_write, file_edit, search_papers, download_paper, parse_paper, get_paper_content, rag_search, query_target, save_note, todo_write, compress_context, load_skill, subagent, ask_user, save_memory, analyze_image (vision model, only when `LLM_VISION_MODEL` set). Plus background tools (bg_task_run, bg_task_check) and team tools (spawn_teammate, send_teammate_message, team_broadcast, check_team_inbox).
4. **Thinking mode**: `enable_thinking` flag propagates from `AgentChatRequest` → `AgentConfig` → `ToolContext` → `LlmClient::chat_stream`. Only enabled for Qwen/DashScope backends; frontend-controlled via the `thinking` request field.
5. **Tool call ID tracking**: LLM may not return tool_call IDs — `LlmClient` generates UUID fallbacks. `ToolCall` and `ToolResult` SSE events carry matching IDs for precise frontend pairing.
6. **ToolContext** (`tools/mod.rs`): Injected into every tool execution — holds `app_state`, `session_id`, `sse_tx` (for intermediate events), `enable_thinking`, `read_file_state` (file cache for dedup), `silent` (sub-agents skip permission prompts).
7. **Context compression**: Four layers — micro (placeholder replacement), snip (old-message truncation), auto (LLM summarization), aggro_micro (aggressive placeholder). Protected by `CompactionCircuitBreaker`. Transcripts persisted in `agent_messages` table, not filesystem snapshots.
8. **Skills** (`skills.rs`): Two-layer loading — system-reminder lists names (~20 tokens each), LLM calls `load_skill` to inject full SKILL.md content. Skills are organized into subdirectories: `methodology/`, `plotting/`, `presentation/`.
9. **Sub-agents** (`subagent.rs`): `subagent` tool spawns a context-isolated sub-agent with its own ReAct loop. Sub-agent messages (system/user/assistant/tool) are persisted to `agent_messages` with `agent_name` identifier. Returns final summary + activity log. SSE progress forwarded to parent via ToolContext.
10. **Memory** (`memory/`): File-based persistent memory (MEMORY.md). `MemoryManager` handles extraction from conversation, dedup, recency decay, age-based pruning, and guardrails. Tools: `save_memory`, `load_memory` (auto-injected in system prompt).
11. **Teams** (`team/`): File-based inbox directory per session for lead/teammate message passing
12. **Background tasks** (`background.rs`): Slow ops (download, parse) can run async; results inject via `BgNotificationQueue` before next LLM call

Environment variables for agent tuning: `AGENT_TOKEN_SOFT_LIMIT` (default 80000) / `AGENT_TOKEN_HARD_LIMIT` (default 100000).

### Database

SQLite via `sqlx::sqlite`. Migrations in `migrations/` are auto-run on startup (`sqlx::migrate!("./migrations")`). Key tables: `papers`, `citations_references`, `notes`, `agent_sessions`, `agent_messages`, `agent_tasks`, `agent_audit_log`, `paper_chunks_content`, `vizier_cache`, `observation_cache`. Vector embeddings use `sqlite-vec` (`vec_paper_chunks` virtual table, auto-registered before any DB connection).

The embedding dimension is controlled by `EMBEDDING_DIM` env var (default 1536). On dimension mismatch, the vec table and chunk content are dropped and recreated.

### Observation Data System (`src/services/observation/`)

A cross-source astronomical observation data subsystem with a **dual-axis orthogonal** architecture: **Source** (LAMOST/Gaia/SDSS/DESI) × **ProductType** (Spectrum/LightCurve/Photometry/Image). Each valid combination implements an `ObservationFetcher`, registered in `ObservationRegistry`.

New fetchers follow OCP (pure addition, no modification to existing code):

1. Create `{source}.rs`, implement `ObservationFetcher` trait
2. Add `register!(YourFetcher)` in `registry.rs::default()`
3. Add new variants to `Source`/`ProductType` enums in `types.rs` if needed

External callers use `dispatch::search_observation()` (metadata only) and `dispatch::download_observation()` (metadata + file download) via `ObservationRequest`. Results are cached in `observation_cache` table with file staging to `library/`.

### Frontend (dashboard/)

React 19 + TypeScript + Vite + Tailwind CSS 4. Organized by technical layer (Type-Based):

- `pages/` — Page-level panel view components (SearchPanel, LibraryPanel, ReaderPanel, CitationPanel, SyncPanel, ResearchAgentPanel, ObservationPanel, SettingsPanel)
- `components/` — Reusable and layout components (sub-folders: agent, reader, sync, layout, dialogs)
- `hooks/` — Global and feature-specific custom stateful React Hooks (e.g., useLibrary, useSearch, useNotes, useObservation)
- `types/` — Global TypeScript type definitions (types/index.ts)
- `utils/` — Common utility helper functions
- `assets/` — Static assets and global stylesheet styles

Dependencies: `react-markdown` + `rehype-katex` + `remark-math` for Markdown/LaTeX rendering, `framer-motion` for animations, `lucide-react` for icons.

### Obscura In-Process Browser

The `obscura-inprocess` feature compiles `obscura-browser` and `obscura-net` from `libs/obscura/` directly into the binary, eliminating the need for external browser binaries. This is used for bypassing Cloudflare/WAF on PDF download. Enabled via `--features obscura-inprocess`.

### Astronomy Glossary (dictionary.txt)

A 1MB+ bilingual astronomy terminology file loaded at startup into a Trie tree for longest-match glossary construction, used by the translation service to guide LLM translations with domain-accurate term mappings.

### Agent Session Modes (`src/agent/modes/`)

Session-level modes configure the agent's identity, tool access, step limits, thinking, and permissions at creation time. Modes are pure-data constants defined at compile time — adding a new mode requires no logic changes.

Three built-in modes (registered in `ModeRegistry::builtins()`):

| Mode         | ID                    | Tools                              | Max Steps   | Thinking        | Permission Profile |
| ------------ | --------------------- | ---------------------------------- | ----------- | --------------- | ------------------ |
| 通用科研助手 | `default`           | All (unrestricted)                 | 8 (default) | user-controlled | none               |
| 深度研究     | `deep-research`     | All                                | 16          | forced on       | `research`       |
| 文献阅读助手 | `literature-reader` | Allowlist (read-only + literature) | 6           | forced off      | `readonly`       |

Key types in `modes/mod.rs`:

- **`AgentMode`** — static definition struct: id, name, description, icon, identity/principles overrides, extra sections, `ToolSet`, `ModeConfig`
- **`ToolSet`** — `All`, `Allowlist(&[&str])`, or `Except(&[&str])` — constrains which tools are available
- **`ModeConfig`** — optional overrides for `max_steps`, `enable_thinking`, `tool_timeout_secs`, `permission_profile`
- **`ModeRegistry`** — holds `&'static AgentMode` references; `get(id)` for lookup

The mode is stored in the `agent_sessions.mode` column (migration `20260624000000_add_session_mode.sql`, defaults to `'default'`). The frontend `ResearchAgentPanel` exposes mode selection.

**Mode vs Skill**: Modes are session-level ("who am I"), Skills are task-level ("how do I do X"). Modes affect initialization; the ReAct loop itself is mode-agnostic.

### Permission System (`src/agent/runtime/permission.rs`)

Tool execution is gated by a priority-ordered rule chain: **Deny > Allow > Ask** (first match wins). Rules support content-level pattern matching (e.g., `run_bash(rm *)`).

**Permission modes** (set via `AGENT_PERMISSION_MODE` env or mode's `permission_profile`):

- `default` — full rule chain evaluation
- `accept_edits` — auto-allow `file_write`/`file_edit` within the working directory
- `bypass` — skip all Ask checks (Deny rules still enforced)
- `dont_ask` — convert all Ask to Deny

**Permission profiles** (`src/agent/runtime/permission_profile.rs`) are named presets loaded by `AGENT_PERMISSION_MODE` or a mode's `permission_profile` field. Profiles `research` and `readonly` are used by deep-research and literature-reader modes respectively.

**Configuration** (in `.env`):

- `AGENT_PERMISSIONS_DENY` — comma-separated deny rules (e.g., `run_bash(rm *),run_bash(sudo *)`)
- `AGENT_PERMISSIONS_ALLOW` — comma-separated allow rules
- `AGENT_PERMISSIONS_ASK` — comma-separated ask rules
- `AGENT_PERMISSION_MODE` — default/accept_edits/bypass/dont_ask

### Multi-Tier LLM Configuration

The system supports three LLM tiers with cascade fallback:

| Tier    | Env Prefix      | Purpose                             | Fallback           |
| ------- | --------------- | ----------------------------------- | ------------------ |
| Primary | `LLM_`        | Main agent reasoning                | —                 |
| Medium  | `LLM_MEDIUM_` | Translation, RAG                    | Primary LLM config |
| Fast    | `LLM_FAST_`   | Memory extraction, background tasks | Medium LLM config  |

Each tier has `_API_KEY`, `_API_BASE`, `_MODEL` variants. Unset tiers cascade to the next tier down.

**Fallback chain**: `LLM_FALLBACK_CHAIN` (comma-separated model names) provides automatic model rotation on repeated 529 errors. `LLM_FALLBACK_MODEL` is a single backup model tried before the chain.

### Vision Model (`analyze_image` tool)

When `LLM_VISION_MODEL` env is set, the `analyze_image` tool (`src/agent/tools/astro/analyze_image.rs`) is registered. It delegates image analysis to a dedicated vision model, enabling the main agent to use a text-only model while still processing images. Supports local paths (relative to library dir) and HTTP(S) URLs. Results stream via SSE `TextDelta` events. Also supports `LLM_VISION_API_KEY` and `LLM_VISION_API_BASE` (fall back to primary LLM config).

### Auto Memory Extraction

Controlled by env vars:

- `EXTRACT_MEMORY_ENABLED` (default `false`) — enables automatic memory extraction at session end and during compaction
- `EXTRACT_MEMORY_THROTTLE_TURNS` (default `3`) — extract every N turns
- `EXTRACT_MEMORY_MAX_STEPS` (default `3`) — sub-agent max steps for extraction

### Deployment (`deploy.sh`)

The `deploy.sh` script builds the project locally (release-min profile, Composer-based) and deploys to a remote server via rsync + SSH. It handles: source compilation, frontend build, remote directory sync, service restart via docker compose, and health check verification.

## Code Conventions

- Use `anyhow` for application errors, `thiserror` for library-style typed errors
- Environment variables via `dotenvy` + `std::env::var`, with defaults in `Config::from_env()`
- SQL queries use parameterized bindings (`sqlx::query("...").bind(...)`) — never string interpolation
- API handlers take `State(Arc<AppState>)` and return Axum-compatible responses
- Agent tools implement `AgentTool` trait; new tools register in `ToolRegistry::new()`
- Front-end build is triggered by `build.rs` (auto npm install + build when `dashboard/src/` changes)
- New observation fetchers follow OCP: add module + register — don't modify existing fetchers or dispatch
- External API clients (`src/clients/`) are pure communication; business logic lives in `src/services/`
- Route registration happens in `src/main.rs`; handler re-exports are maintained in `src/api/mod.rs` → `handlers` namespace
- Agent hooks (`src/agent/hooks/`) implement lifecycles: PreToolUse, PostToolUse, Stop, etc. — register in `builtins.rs`