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https://github.com/infiniflow/ragflow.git
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Support image recognition for url links in Markdown file, fix log error in code_exec (#10139)
### What problem does this PR solve? Support image recognition with image links in markdown files, solved issue: #8755 Fixed log info error in code_exec, solved issue: #10064 ### Type of change (8755) - [x] New Feature (non-breaking change which adds functionality) ### Type of change (10064) - [x] Bug Fix (non-breaking change which fixes an issue)
This commit is contained in:
Billy Bao
@ -157,7 +157,7 @@ class CodeExec(ToolBase, ABC):
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try:
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resp = requests.post(url=f"http://{settings.SANDBOX_HOST}:9385/run", json=code_req, timeout=os.environ.get("COMPONENT_EXEC_TIMEOUT", 10*60))
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logging.info(f"http://{settings.SANDBOX_HOST}:9385/run", code_req, resp.status_code)
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logging.info(f"http://{settings.SANDBOX_HOST}:9385/run, code_req: {code_req}, resp.status_code {resp.status_code}:")
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if resp.status_code != 200:
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resp.raise_for_status()
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body = resp.json()
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105
api/apps/HEALTHCHECK_TESTING.md
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105
api/apps/HEALTHCHECK_TESTING.md
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@ -0,0 +1,105 @@
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# 健康检查与 Kubernetes 探针简明说明
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本文件说明：什么是 K8s 探针、如何用 `/v1/system/healthz` 做健康检查，以及下文用例中的关键词含义。
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## 什么是 K8s 探针（Probe）
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- 探针是 K8s 用来“探测”容器是否健康/可对外服务的机制。
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- 常见三类：
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- livenessProbe：活性探针。失败时 K8s 会重启容器，用于“应用卡死/失去连接时自愈”。
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- readinessProbe：就绪探针。失败时 Endpoint 不会被加入 Service 负载均衡，用于“应用尚未准备好时不接流量”。
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- startupProbe：启动探针。给慢启动应用更长的初始化窗口，期间不执行 liveness/readiness。
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- 这些探针通常通过 HTTP GET 访问一个公开且轻量的健康端点（无需鉴权），以 HTTP 状态码判定结果：200=通过；5xx/超时=失败。
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## 本项目健康端点
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- 已实现：`GET /v1/system/healthz`（无需认证）。
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- 语义：
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- 200：关键依赖正常。
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- 500：任一关键依赖异常（当前判定为 DB 或 Chat）。
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- 响应体：JSON，最小字段 `status, db, chat`；并包含 `redis, doc_engine, storage` 等可观测项。失败项会在 `_meta` 中包含 `error/elapsed`。
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- 示例（DB 故障）：
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```json
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{"status":"nok","chat":"ok","db":"nok"}
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```
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## 用例背景（Problem/use case）
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- 现状：Ragflow 跑在 K8s，数据库是 AWS RDS Postgres，凭证由 Secret Manager 管理并每 7 天轮换。轮换后应用连接失效，需要手动重启 Pod 才能重新建立连接。
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- 目标：通过 K8s 探针自动化检测并重启异常 Pod，减少人工操作。
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- 需求：一个“无需鉴权”的公共健康端点，能在依赖异常时返回非 200（如 500）且提供 JSON 详情。
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- 现已满足：`/v1/system/healthz` 正是为此设计。
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## 关键术语解释（对应你提供的描述）
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- Ragflow instance：部署在 K8s 的 Ragflow 服务。
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- AWS RDS Postgres：托管的 PostgreSQL 数据库实例。
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- Secret Manager rotation：Secrets 定期轮换（每 7 天），会导致旧连接失效。
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- Probes（K8s 探针）：liveness/readiness，用于自动重启或摘除不健康实例。
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- Public endpoint without API key：无需 Authorization 的 HTTP 路由，便于探针直接访问。
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- Dependencies statuses：依赖健康状态（db、chat、redis、doc_engine、storage 等）。
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- HTTP 500 with JSON：当依赖异常时返回 500，并附带 JSON 说明哪个子系统失败。
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## 快速测试
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- 正常：
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```bash
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curl -i http://<host>/v1/system/healthz
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```
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- 制造 DB 故障（docker-compose 示例）：
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```bash
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docker compose stop db && curl -i http://<host>/v1/system/healthz
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```
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（预期 500，JSON 中 `db:"nok"`）
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## 更完整的测试清单
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### 1) 仅查看 HTTP 状态码
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```bash
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curl -s -o /dev/null -w "%{http_code}\n" http://<host>/v1/system/healthz
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```
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期望：`200` 或 `500`。
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### 2) Windows PowerShell
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```powershell
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# 状态码
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(Invoke-WebRequest -Uri "http://<host>/v1/system/healthz" -Method GET -TimeoutSec 3 -ErrorAction SilentlyContinue).StatusCode
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# 完整响应
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Invoke-RestMethod -Uri "http://<host>/v1/system/healthz" -Method GET
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```
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### 3) 通过 kubectl 端口转发本地测试
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```bash
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# 前端/网关暴露端口不同环境自行调整
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kubectl port-forward deploy/<your-deploy> 8080:80 -n <ns>
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curl -i http://127.0.0.1:8080/v1/system/healthz
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```
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### 4) 制造常见失败场景
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- DB 失败（推荐）：
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```bash
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docker compose stop db
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curl -i http://<host>/v1/system/healthz # 预期 500
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```
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- Chat 失败（可选）：将 `CHAT_CFG` 的 `factory`/`base_url` 设为无效并重启后端，再请求应为 500，且 `chat:"nok"`。
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- Redis/存储/文档引擎：停用对应服务后再次请求，可在 JSON 中看到相应字段为 `"nok"`（不影响 200/500 判定）。
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### 5) 浏览器验证
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- 直接打开 `http://<host>/v1/system/healthz`，在 DevTools Network 查看 200/500；页面正文就是 JSON。
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- 反向代理注意：若有自定义 500 错页，需对 `/healthz` 关闭错误页拦截（如 `proxy_intercept_errors off;`）。
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## K8s 探针示例
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```yaml
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readinessProbe:
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httpGet:
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path: /v1/system/healthz
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port: 80
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initialDelaySeconds: 5
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periodSeconds: 10
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timeoutSeconds: 2
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failureThreshold: 1
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livenessProbe:
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httpGet:
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path: /v1/system/healthz
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port: 80
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initialDelaySeconds: 10
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periodSeconds: 10
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timeoutSeconds: 2
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failureThreshold: 3
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```
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提示：如有反向代理（Nginx）自定义 500 错页，需对 `/healthz` 关闭错误页拦截，以便保留 JSON。
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@ -36,6 +36,8 @@ from rag.utils.storage_factory import STORAGE_IMPL, STORAGE_IMPL_TYPE
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from timeit import default_timer as timer
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from rag.utils.redis_conn import REDIS_CONN
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from flask import jsonify
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from api.utils.health import run_health_checks
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@manager.route("/version", methods=["GET"]) # noqa: F821
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@login_required
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@ -169,6 +171,12 @@ def status():
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return get_json_result(data=res)
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@manager.route("/healthz", methods=["GET"]) # noqa: F821
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def healthz():
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result, all_ok = run_health_checks()
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return jsonify(result), (200 if all_ok else 500)
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@manager.route("/new_token", methods=["POST"]) # noqa: F821
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@login_required
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def new_token():
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104
api/utils/health.py
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104
api/utils/health.py
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from timeit import default_timer as timer
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from api import settings
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from api.db.db_models import DB
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from rag.utils.redis_conn import REDIS_CONN
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from rag.utils.storage_factory import STORAGE_IMPL
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def _ok_nok(ok: bool) -> str:
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return "ok" if ok else "nok"
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def check_db() -> tuple[bool, dict]:
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st = timer()
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try:
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# lightweight probe; works for MySQL/Postgres
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DB.execute_sql("SELECT 1")
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return True, {"elapsed": f"{(timer() - st) * 1000.0:.1f}"}
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except Exception as e:
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return False, {"elapsed": f"{(timer() - st) * 1000.0:.1f}", "error": str(e)}
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def check_redis() -> tuple[bool, dict]:
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st = timer()
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try:
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ok = bool(REDIS_CONN.health())
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return ok, {"elapsed": f"{(timer() - st) * 1000.0:.1f}"}
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except Exception as e:
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return False, {"elapsed": f"{(timer() - st) * 1000.0:.1f}", "error": str(e)}
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def check_doc_engine() -> tuple[bool, dict]:
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st = timer()
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try:
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meta = settings.docStoreConn.health()
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# treat any successful call as ok
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return True, {"elapsed": f"{(timer() - st) * 1000.0:.1f}", **(meta or {})}
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except Exception as e:
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return False, {"elapsed": f"{(timer() - st) * 1000.0:.1f}", "error": str(e)}
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def check_storage() -> tuple[bool, dict]:
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st = timer()
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try:
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STORAGE_IMPL.health()
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return True, {"elapsed": f"{(timer() - st) * 1000.0:.1f}"}
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except Exception as e:
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return False, {"elapsed": f"{(timer() - st) * 1000.0:.1f}", "error": str(e)}
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def check_chat() -> tuple[bool, dict]:
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st = timer()
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try:
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cfg = getattr(settings, "CHAT_CFG", None)
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ok = bool(cfg and cfg.get("factory"))
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return ok, {"elapsed": f"{(timer() - st) * 1000.0:.1f}"}
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except Exception as e:
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return False, {"elapsed": f"{(timer() - st) * 1000.0:.1f}", "error": str(e)}
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def run_health_checks() -> tuple[dict, bool]:
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result: dict[str, str | dict] = {}
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db_ok, db_meta = check_db()
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chat_ok, chat_meta = check_chat()
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result["db"] = _ok_nok(db_ok)
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if not db_ok:
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result.setdefault("_meta", {})["db"] = db_meta
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result["chat"] = _ok_nok(chat_ok)
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if not chat_ok:
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result.setdefault("_meta", {})["chat"] = chat_meta
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# Optional probes (do not change minimal contract but exposed for observability)
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try:
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redis_ok, redis_meta = check_redis()
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result["redis"] = _ok_nok(redis_ok)
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if not redis_ok:
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result.setdefault("_meta", {})["redis"] = redis_meta
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except Exception:
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result["redis"] = "nok"
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try:
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doc_ok, doc_meta = check_doc_engine()
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result["doc_engine"] = _ok_nok(doc_ok)
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if not doc_ok:
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result.setdefault("_meta", {})["doc_engine"] = doc_meta
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except Exception:
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result["doc_engine"] = "nok"
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try:
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sto_ok, sto_meta = check_storage()
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result["storage"] = _ok_nok(sto_ok)
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if not sto_ok:
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result.setdefault("_meta", {})["storage"] = sto_meta
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except Exception:
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result["storage"] = "nok"
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all_ok = (result.get("db") == "ok") and (result.get("chat") == "ok")
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result["status"] = "ok" if all_ok else "nok"
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return result, all_ok
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@ -507,16 +507,29 @@ def chunk(filename, binary=None, from_page=0, to_page=100000,
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markdown_parser = Markdown(int(parser_config.get("chunk_token_num", 128)))
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sections, tables = markdown_parser(filename, binary, separate_tables=False)
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# Process images for each section
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section_images = []
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for section_text, _ in sections:
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images = markdown_parser.get_pictures(section_text) if section_text else None
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if images:
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# If multiple images found, combine them using concat_img
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combined_image = reduce(concat_img, images) if len(images) > 1 else images[0]
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section_images.append(combined_image)
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else:
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section_images.append(None)
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try:
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vision_model = LLMBundle(kwargs["tenant_id"], LLMType.IMAGE2TEXT)
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callback(0.2, "Visual model detected. Attempting to enhance figure extraction...")
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except Exception:
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vision_model = None
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if vision_model:
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# Process images for each section
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section_images = []
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for idx, (section_text, _) in enumerate(sections):
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images = markdown_parser.get_pictures(section_text) if section_text else None
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if images:
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# If multiple images found, combine them using concat_img
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combined_image = reduce(concat_img, images) if len(images) > 1 else images[0]
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section_images.append(combined_image)
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markdown_vision_parser = VisionFigureParser(vision_model=vision_model, figures_data= [((combined_image, ["markdown image"]), [(0, 0, 0, 0, 0)])], **kwargs)
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boosted_figures = markdown_vision_parser(callback=callback)
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sections[idx] = (section_text + "\n\n" + "\n\n".join([fig[0][1] for fig in boosted_figures]), sections[idx][1])
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else:
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section_images.append(None)
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else:
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logging.warning("No visual model detected. Skipping figure parsing enhancement.")
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res = tokenize_table(tables, doc, is_english)
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callback(0.8, "Finish parsing.")
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