SoulSearcher

# SoulSearcher 默认文档：中文 SoulSearcher 是一个基于 LangGraph 的深度研究 Agent 平台。它把开放式问题转成可审批、可追踪、可复盘的研究流程：澄清问题、生成研究简报、人工审批计划、执行 Plan DAG、并行调度研究员、沉淀证据、生成报告、质量校验，并把全过程通过 SSE、Evidence Panel 和 Run Events 展示出来。      ## 一句话介绍 SoulSearcher 不是普通聊天机器人，也不是单纯 RAG。它是面向复杂研究任务的 **Workflow + Agent** 系统：确定性环节由代码控制，开放性探索交给模型和工具，所有关键状态都被结构化记录。 ```mermaid flowchart LR Q["用户问题"] --> C["澄清与研究简报"] C --> P["人工审批研究计划"] P --> D["Plan DAG"] D --> S["Supervisor 调度"] S --> R1["Researcher A"] S --> R2["Researcher B"] S --> R3["Researcher C"] R1 --> E["证据池"] R2 --> E R3 --> E E --> W["报告生成"] W --> G["质量门检查"] G --> O["报告 / 证据 / 事件回放"] ``` ## 核心能力 | 能力 | 当前实现 | | --- | --- | | 显式研究工作流 | `clarify -> brief -> classify -> plan -> supervisor -> researcher -> report -> evaluate` | | 人工计划门控 | 研究计划生成后通过 LangGraph interrupt 暂停，用户可批准、修订或取消 | | Plan DAG | 计划任务有依赖、frontier、状态、证据链接、结果预览和 replan events | | 并行研究员 | Supervisor 用结构化工具调度多个 Researcher 子图，子图独立上下文执行 | | 统一检索策略 | `RetrievalPolicy` 控制公开网页、私有资料库、用户提供来源、连接器、检索方法和预算 | | 证据系统 | evidence items、passages、source registry、citation annotations、claim support | | 质量控制 | citation gate、claim verifier、rubric evaluation、自动修订和质量补研 | | Run Events | 运行事件持久化，支持 REST 查询和 SSE 回放 | | 长期记忆 | 可选 memory service，支持实体、关系、研究发现和 procedural learning | | Skills | public/custom skills，支持 allowlist、安装、编辑、历史和回滚 | | 前端工作台 | Next.js 展示研究流、计划审批、证据、Plan DAG、Events、产物、会话和 traces | ## 整体架构 ```mermaid flowchart TB subgraph Frontend["web / Next.js"] UI["Research Workspace"] EvidencePanel["EvidencePanel\nSources / Claims / Plan / Events / Gaps"] LibraryUI["Document Library"] end subgraph API["FastAPI / main.py"] ResearchAPI["/api/research/sse"] InterruptAPI["/api/interrupt/*"] SessionAPI["/api/sessions/*"] RunAPI["/api/runs/*"] LibraryAPI["/api/library/*"] ExportTrace["export / traces / health"] end subgraph Core["agent/core"] Graph["LangGraph"] State["Typed State"] Routing["Model Routing"] Events["SSE Events"] Middleware["error / loop / token"] end subgraph Workflow["agent/workflows"] Gateway["Input Gateway"] Plan["Research Plan"] DAG["Plan Graph"] Supervisor["Supervisor"] Researcher["Researcher"] Report["Report"] Quality["Quality Check"] end subgraph Retrieval["agent/retrieval"] Policy["RetrievalPolicy"] Retrieve["retrieve_sources"] Read["read_source"] Documents["Document Library"] end subgraph Runtime["agent/runtime"] Runs["RunManager"] Background["Background Runs"] RequestBuilder["Request Builder"] end UI --> API EvidencePanel --> API API --> Core API --> Runtime Core --> Workflow Workflow --> Retrieval Workflow --> Runtime Retrieval --> Tools["tools/"] ``` ## 真实代码结构 ```text agent/core/ graph.py 主 LangGraph 构建入口 state.py AgentState / SupervisorState / ResearcherState 与结构化工具 schema configuration.py 研究运行配置 model_routing.py fast / smart / strategic 三层模型与任务级覆盖 events.py SSE 事件归一化与发送 middleware.py tool error / loop / token middleware agent/workflows/ input_gateway.py 澄清、research brief、复杂度分类 research_plan.py 研究计划、interrupt/resume、Plan DAG 初始化 plan_graph.py DAG 创建、frontier 计算、任务状态、replan actions supervisor.py supervisor loop 与并行 researcher 调度 researcher.py researcher ReAct loop 与检索策略注入 report.py 最终报告、artifacts、质量补研与 Plan DAG replan interactive_continue.py 继续研究请求转成 replan actions quality_check.py 快速质量检查与自动修订 evaluation.py rubric / degradation evaluation agent/retrieval/ policy.py RetrievalPolicy：origin / channel / method / profile / budget gateway.py 统一检索网关：retrieve_sources / read_source documents.py 用户资料库解析、chunk、hybrid ranking agent/runtime/ runs.py Run records、run-events 持久化、内存 fallback background_runs.py 后台研究任务 request_builder.py request -> graph state/config common/ config.py Settings 单一来源 evidence_store.py Evidence/session response patch session_manager.py session、artifacts、Plan DAG、run-events 读写 web/ Next.js 研究工作台、EvidencePanel、文档库、stream protocol、OpenAPI TS types ``` ## 研究执行流程 ```mermaid sequenceDiagram participant U as 用户 participant API as FastAPI participant G as LangGraph participant S as Supervisor participant R as Researchers participant E as Evidence Store participant UI as Web UI U->>API: POST /api/research/sse API->>G: 构建初始 state/config G->>G: 澄清 / brief / complexity G-->>UI: interrupt: 计划待审批 U->>API: approve / revise / cancel G->>G: 生成 Plan DAG G->>S: 进入 supervisor loop S->>R: 并行 ConductResearch R->>E: 写入来源、证据、passages S->>G: ThinkTool / ResearchComplete G->>E: 报告、质量结果、Plan DAG API-->>UI: SSE + Run Events + Artifacts ``` ## Plan DAG：唯一计划状态 Plan DAG 是当前版本唯一的计划状态。`research_todos` 只作为兼容投影存在，由 DAG 派生，不再是第二套计划系统。 ```mermaid flowchart LR A["approved/revised plan"] --> B["create_plan_graph"] B --> C["ready frontier"] C --> D["mark running"] D --> E{"research result"} E -->|证据充分| F["completed"] E -->|失败或不足| G["blocked"] F --> H["recompute frontier"] G --> I["ThinkTool / quality follow-up"] I --> J["apply replan actions"] J --> H H --> K{"全部完成?"} K -->|否| C K -->|是| L["report"] ``` 任务字段包括 `id`、`title`、`question`、`deps`、`status`、`priority`、`retrieval_policy_hint`、`evidence_ids`、`claim_ids`、`blocked_reason`、`result_preview` 等。状态更新会触发 `plan_graph_update`，并写入 session/evidence artifacts。 ## RetrievalPolicy：唯一检索策略 SoulSearcher 只保留一套检索策略：`RetrievalPolicy`。旧式来源路由输入会在 API/runtime 边界被拒绝，避免多套路由方案并存。 ```mermaid flowchart TB Request["Research Request"] --> Policy["RetrievalPolicy"] Policy --> Origins["allowed_origins\npublic_web / private_corpus / user_provided / external_system"] Policy --> Channels["channels\nsearch_api / browser / crawler / file_upload / mcp / connector"] Policy --> Methods["methods\nweb_search / academic_search / vector_search / keyword_search / crawl / deep_read"] Policy --> Budget["budget\nmax results / read chars / per-origin limits"] Origins --> Gateway["Retrieval Gateway"] Channels --> Gateway Methods --> Gateway Budget --> Gateway Gateway --> Evidence["RetrievedSource + EvidenceItem"] ``` ## Run Events：可回放的运行过程 | 接口 | 作用 | | --- | --- | | `GET /api/runs` | 运行列表 | | `GET /api/runs/{thread_id}` | 单个 run 的指标与状态 | | `GET /api/runs/{thread_id}/events?after_seq=0` | 查询指定序号后的持久化事件 | | `GET /api/runs/{thread_id}/events/sse?after_seq=0` | 用 SSE 回放持久化事件 | | `POST /api/runs/background` | 提交后台研究 | | `GET /api/runs/{thread_id}/background` | 查询后台运行状态 | Postgres 后端会自动创建 `soulsearcher_run_events` 表；开发和测试环境可回退到内存实现。 ## API 一览 | 分组 | 路由 | | --- | --- | | Research | `POST /api/research/sse`, cancel, cancel-all, fork | | Interrupt | interrupt status 与 canonical resume | | Sessions | session list/detail/state/evidence/resume/continue/delete | | Runs | run list、metrics、background、events、event replay、source injection | | Library/Retrieval | document library、document search、retrieval search | | Collaboration | share links、comments、versions、restore | | Skills | public/custom skills 的 list、read、update、install、history、rollback | | Memory | records、retrieve、graph、status、skill evolution | | Tools/Search | active tasks、tool registry、providers、cache stats/reset/clear | | Export/Traces | report export、templates、trace detail、trace summary | | Health/Ops | `/`, `/health`, `/api/health/agent`, `/api/config/public`, `/metrics` | ## 前端工作台 ```mermaid flowchart TB Workspace["Research Workspace"] --> Stream["SSE 流式研究"] Workspace --> Approval["计划审批 / 修订"] Workspace --> Thinking["Thinking Process"] Workspace --> Evidence["EvidencePanel"] Evidence --> Sources["Sources"] Evidence --> Claims["Claims"] Evidence --> Plan["Plan DAG"] Evidence --> Events["Run Events"] Evidence --> Gaps["Gaps"] Workspace --> Artifacts["Markdown / HTML / Export"] Workspace --> Sessions["Sessions / Share / Comments / Versions"] Workspace --> Trace["Trace Viewer"] ``` ## 配置 配置集中在 `common/config.py`，通过环境变量覆盖： ```bash # LLM providers OPENAI_API_KEY=... OPENAI_BASE_URL=... AZURE_OPENAI_API_KEY=... DASHSCOPE_API_KEY=... # Model routing PRIMARY_MODEL=qwen-plus REASONING_MODEL=qwen-plus FAST_LLM_MODEL=qwen-turbo SMART_LLM_MODEL=qwen-plus STRATEGIC_LLM_MODEL=qwen-plus PLANNER_MODEL=... RESEARCHER_MODEL=... WRITER_MODEL=... EVALUATOR_MODEL=... # Search providers TAVILY_API_KEY=... BOCHA_API_KEY=... SERPER_API_KEY=... SERPAPI_API_KEY=... BING_API_KEY=... BRAVE_API_KEY=... EXA_API_KEY=... FIRECRAWL_API_KEY=... # Runtime MEMORY_ENABLED=true MEMORY_BACKEND=postgres MEMORY_DATABASE_URL= ENABLE_MCP=false HUMAN_REVIEW=true TOOL_APPROVAL=false DEEPSEARCH_MODE=auto # API / Ops SOULSEARCHER_INTERNAL_API_KEY=... DATABASE_URL=sqlite:///./data/soulsearcher.db ENABLE_PROMETHEUS=false ``` ## 开发与验证 ```bash # 启动完整本地应用 ./start_soulsearcher.sh # 后端 python main.py # 后端热重载 DEBUG=true SOULSEARCHER_RELOAD=1 python main.py ``` ```bash # Python 测试 PYTHONPATH=. python -m pytest tests/ -v # 前端检查 npx --yes -p node@24 bash -lc 'cd web && node_modules/.bin/next lint' npx --yes -p node@24 bash -lc 'cd web && node_modules/.bin/tsc --noEmit' # OpenAPI 类型同步 DEBUG=false APP_ENV=prod ENABLE_FILE_LOGGING=false \ python scripts/export_openapi.py --output /tmp/soulsearcher-openapi.json npx --yes -p node@24 -p openapi-typescript openapi-typescript /tmp/soulsearcher-openapi.json -o web/lib/api-types.ts npx --yes -p node@24 -p openapi-typescript openapi-typescript /tmp/soulsearcher-openapi.json -o sdk/typescript/src/openapi-types.ts ``` ## SDK 仓库内置私有 SDK，位于 `sdk/`： - TypeScript：`SoulSearcherClient` - Python：`soulsearcher_sdk.SoulSearcherClient` 详见 [sdk/README.md](sdk/README.md)。 ## License MIT License. See [LICENSE](LICENSE).