fix: per-node max_tokens + validation 502 guard + correct_jrxml output validity
- backend/llm.py: per-node max_tokens via get_llm(max_tokens=N), LLM_MAX_TOKENS env var (default 8192) - agent/nodes.py: 5 generation nodes use max_tokens=32768, generate_skeleton retries at 65536 - agent/nodes.py: fix ns:field regex (<field → <[\w:]*field) to handle namespace prefixes - agent/nodes.py: fix correct_jrxml never writing back to state["current_jrxml"] - agent/nodes.py: correct_jrxml rejects non-JRXML output (no <jasperReport tag) - agent/nodes.py: _strip_continuation_wrapper strips markdown/prefixes from continuation rounds - agent/nodes.py: _extract_jrxml iterates multiple markdown code blocks, skips fragments - agent/graph.py: route_after_validate skips correction loop when service_unavailable - agent/graph.py: route_after_save skips validation for empty JRXML - backend/validation.py: returns service_unavailable: True for ConnectError and HTTP 5xx - Docs: CLAUDE.md v14 changelog, README.md LLM_MAX_TOKENS, .env.example LLM_MAX_TOKENS
This commit is contained in:
@@ -14,6 +14,9 @@ OPENAI_BASE_URL=https://api.openai.com/v1
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LLM_MODEL=MiniMax-M2.7
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# 默认 max_tokens（各生成节点可覆盖为更高值）
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LLM_MAX_TOKENS=8192
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# 本地大语言模型（Ollama）
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LOCAL_LLM_MODEL=qwen2.5-coder:7b
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@@ -547,3 +547,47 @@ GET /api/sessions/{session_id}/kb # 获取会话绑定的 KB
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| `tests/test_programmatic_map_fields.py` | 20 | 字段声明替换/引用替换/中文转义/坐标保留/部分映射/空字段跳过 |
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完整测试套件（385 项）无回归。
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## 更新 (v14 — 2026-05-24)
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### max_tokens per-node + 修正循环死锁修复
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**问题 A — max_tokens 自限**: `backend/llm.py` 硬编码 `max_tokens=8192`。MiniMax M2.7 的 reasoning token 吃光 8192 输出预算后骨架生成为空（0 个可见字符）。其他节点（correct_jrxml/modify_jrxml）输入 68K+ 字符时输出也被截断。
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**问题 B — ns:field 命名空间前缀正则失配**: `_programmatic_map_fields()` 正则 `<field\b` 匹配不到 `<ns0:field name="field_1">`，导致字段声明保持占位符但引用被替换为 OCR 字段名，校验报"used in expressions but not declared"。
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**问题 C — 验证服务 502 修正死循环**: 验证服务（port 8001）未启动时，`validate_jrxml()` 返回 502。错误消息被当作 JRXML 校验错误送入 `explain_error → correct_jrxml`，LLM 尝试"修复"网络错误产出 HTML/markdown 等垃圾，循环 5 轮直到 retry_count 耗尽。
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**问题 D — correct_jrxml 从未写回 current_jrxml**: 修正后的 JRXML 只写入 `conversation_history`，从不更新 `state["current_jrxml"]`，导致每轮 validate 看到同一份原始 JRXML，修正完全无效。这是 5 轮 jrxml_length 始终 4441 不变的根本原因。
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**修复方案**:
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#### 1. per-node max_tokens（`backend/llm.py` + `agent/nodes.py`）
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- `get_llm(caller, max_tokens=None)` — 新增可选 `max_tokens` 参数，透传到 `_build_raw_llm`
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- `MiniMaxLLM.__init__()` — 存储 `self._max_tokens`
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- `LLM_MAX_TOKENS` 环境变量覆盖默认 8192
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- 5 个生成节点 max_tokens 提升到 32768：`generate`, `generate_skeleton`, `refine_layout`, `modify_jrxml`, `correct_jrxml`
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- `generate_skeleton` 空响应自动重试（max_tokens=65536）
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#### 2. ns:field 正则修复（`agent/nodes.py:548`）
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- `<field\b` → `<[\w:]*field\b` 兼容 `<ns0:field>`, `<field>` 等所有命名空间前缀
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#### 3. 验证服务不可用防护
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- `backend/validation.py` — 区分 ConnectError/HTTPStatusError(5xx)：返回 `service_unavailable: True`
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- `agent/nodes.py:validate` — 透传 `state["service_unavailable"]`
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- `agent/graph.py:route_after_validate` — `service_unavailable` 时直接 `finalize`，不进入修正循环
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#### 4. correct_jrxml 输出合法性守卫
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- 新增 JRXML 有效性检查：输出不含 `<jasperReport` 且不含 `<?xml` 时，回退到前一版本
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- **Bug 修复**: `state["current_jrxml"] = jrxml` 写回修正结果
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#### 5. 连续输出提取增强
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- `_strip_continuation_wrapper()` — 剥离续写响应中 LLM 重新添加的 markdown 代码块和自然语言前缀
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- `_extract_jrxml()` — 逐一检查多个 markdown 代码块，跳过非 JRXML 片段
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- `_generate_with_continuation()` — 续写轮次自动应用 `_strip_continuation_wrapper`
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#### 新增环境变量
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| 变量 | 描述 | 默认值 |
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|------|------|--------|
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| `LLM_MAX_TOKENS` | 默认 max_tokens（各节点可覆盖） | 8192 |
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@@ -176,6 +176,7 @@ jrxml-agent/
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| ANTHROPIC_API_KEY | Anthropic 兼容 API 密钥（优先） | - |
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| ANTHROPIC_BASE_URL | Anthropic 兼容 Base URL | https://api.minimaxi.com/anthropic |
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| LLM_MODEL | 模型名称 | MiniMax-M2.7 |
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| LLM_MAX_TOKENS | 默认 max_tokens（各节点可覆盖） | 8192 |
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| LOCAL_LLM_MODEL | Ollama 模型 | qwen2.5-coder:7b |
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| EMBED_BACKEND | local 或 cloud | local |
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| LOCAL_EMBED_MODEL | 嵌入模型 | Qwen/Qwen3-Embedding-0.6B |
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+10
-1
@@ -120,6 +120,9 @@ def route_after_save(state: AgentState) -> Literal["validate", "finalize"]:
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intent = state.get("intent", "")
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if intent in ("preview_report", "export_pdf", "export_jrxml"):
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return "finalize"
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# JRXML 为空时跳过验证/修正循环（生成失败等场景）
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if not state.get("current_jrxml", "").strip():
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return "finalize"
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return "validate"
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@@ -127,6 +130,12 @@ def route_after_save(state: AgentState) -> Literal["validate", "finalize"]:
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def route_after_validate(state: AgentState) -> Literal["finalize", "explain_error"]:
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if state.get("status") == "pass":
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return "finalize"
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# JRXML 为空时跳过 explain→correct 修正循环
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if not state.get("current_jrxml", "").strip():
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return "finalize"
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# 验证服务不可用时跳过修正循环，避免对网络错误进行无效修正
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if state.get("service_unavailable"):
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return "finalize"
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return "explain_error"
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@@ -256,7 +265,7 @@ def build_graph(on_node_start=None) -> StateGraph:
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workflow.add_conditional_edges(
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"save_session",
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route_after_save,
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{"validate": "validate"},
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{"validate": "validate", "finalize": "finalize"},
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)
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# ---- 验证 → 修正循环 ----
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+72
-21
@@ -543,9 +543,9 @@ def _programmatic_map_fields(jrxml: str, ocr_fields: list[dict]) -> str:
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real_name = _sanitize_field_name(raw_name)
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if real_name == placeholder:
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continue
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# 替换 field 声明: <field name="field_1" → <field name="customer_name"
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# 替换 field 声明: <ns0:field name="field_1" → <ns0:field name="customer_name"
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result = re.sub(
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rf'(<field\b[^>]*\bname\s*=\s*"){re.escape(placeholder)}(")',
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rf'(<[\w:]*field\b[^>]*\bname\s*=\s*"){re.escape(placeholder)}(")',
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rf'\g<1>{real_name}\g<2>', result,
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)
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# 替换所有引用: $F{{field_1}} → $F{{customer_name}}
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@@ -821,7 +821,7 @@ def generate(state: AgentState) -> Dict:
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from langgraph.config import get_stream_writer
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writer = get_stream_writer()
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llm = get_llm(caller="generate")
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llm = get_llm(caller="generate", max_tokens=32768)
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user_request = state.get("user_input", "")
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ocr_text = _format_ocr_context(state)
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@@ -849,7 +849,6 @@ def generate_skeleton(state: AgentState) -> Dict:
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from langgraph.config import get_stream_writer
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writer = get_stream_writer()
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llm = get_llm(caller="generate_skeleton")
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schema = state.get("layout_schema", {})
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schema_text = schema.get("schema_text", "") if isinstance(schema, dict) else ""
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@@ -861,10 +860,16 @@ def generate_skeleton(state: AgentState) -> Dict:
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user_request=user_request,
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template_context=_build_template_context(state),
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)
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llm = get_llm(caller="generate_skeleton", max_tokens=32768)
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prev_jrxml = state.get("current_jrxml", "")
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full_text = _generate_with_continuation(llm, prompt, writer, "generate_skeleton")
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if not full_text.strip():
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_node_log.error("generate_skeleton LLM 返回空响应")
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_node_log.warning("generate_skeleton 首次返回空响应，以更高 max_tokens 重试")
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llm = get_llm(caller="generate_skeleton", max_tokens=65536)
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full_text = _generate_with_continuation(llm, prompt, writer, "generate_skeleton")
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if not full_text.strip():
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_node_log.error("generate_skeleton LLM 返回空响应（含重试）")
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return state
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jrxml = _extract_jrxml(full_text)
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if len(jrxml.strip()) < 200:
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@@ -1025,7 +1030,7 @@ def modify_jrxml(state: AgentState) -> Dict:
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from langgraph.config import get_stream_writer
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writer = get_stream_writer()
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llm = get_llm(caller="modify_jrxml")
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llm = get_llm(caller="modify_jrxml", max_tokens=32768)
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# 构建对话上下文：压缩摘要 + 最近对话
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compressed = state.get("compressed_history", "")
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recent = state.get("conversation_history", [])[-6:]
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@@ -1278,6 +1283,7 @@ def validate(state: AgentState) -> Dict:
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result = validate_jrxml(jrxml)
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state["status"] = "pass" if result.get("valid") else "fail"
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state["error_msg"] = result.get("error", "")
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state["service_unavailable"] = result.get("service_unavailable", False)
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# OCR 保真度检查：比对生成结果与原始图片的 OCR 提取内容
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fidelity = _check_ocr_fidelity(jrxml, state)
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@@ -1378,7 +1384,7 @@ def correct_jrxml(state: AgentState) -> Dict:
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from langgraph.config import get_stream_writer
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writer = get_stream_writer()
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llm = get_llm(caller="correct_jrxml")
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llm = get_llm(caller="correct_jrxml", max_tokens=32768)
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ocr_context = _format_ocr_context(state)
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layout_schema = state.get("layout_schema", {})
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layout_text = ""
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@@ -1432,6 +1438,13 @@ def correct_jrxml(state: AgentState) -> Dict:
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_node_log.warning(f"correct_jrxml 输出过短（{len(jrxml)} 字符），回退到前一版本")
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jrxml = prev_jrxml
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# 如果提取结果不是合法 JRXML（不含 <jasperReport），说明 LLM 返回了 HTML 等垃圾输出
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if jrxml and "<jasperReport" not in jrxml and "<?xml" not in jrxml:
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_node_log.warning(
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f"correct_jrxml 输出不是合法 JRXML（{jrxml[:100]}），回退到前一版本"
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)
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jrxml = prev_jrxml
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# 去重检测：如果输出与输入完全相同（忽略空白差异），说明修正无效
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_prev_norm = re.sub(r"\s+", "", prev_jrxml) if prev_jrxml else ""
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_new_norm = re.sub(r"\s+", "", jrxml) if jrxml else ""
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@@ -1442,6 +1455,7 @@ def correct_jrxml(state: AgentState) -> Dict:
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state["retry_count"] = state.get("retry_count", 0) + 2
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else:
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state["retry_count"] = state.get("retry_count", 0) + 1
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state["current_jrxml"] = jrxml
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state["conversation_history"].append(
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{"role": "assistant", "content": f"[自动修正，第 {state['retry_count']} 次尝试]\n{jrxml}"}
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)
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@@ -1510,6 +1524,31 @@ def finalize(state: AgentState) -> Dict:
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return state
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def _strip_continuation_wrapper(text: str) -> str:
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"""去除续写响应中的 markdown 代码块标记和自然语言解释。
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续写轮次的 LLM 可能会"忘记"原始 prompt 中的格式要求，
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在响应开头加解释文字、用 ``` 包裹 XML 片段。
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此函数提取其中的纯 XML 内容，去除包装。
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"""
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text = text.strip()
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# 移除完整的 markdown 代码块包装: ```...```
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m = re.search(r"```(?:xml|jrxml)?\s*([\s\S]*?)```", text, re.IGNORECASE)
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if m:
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inner = m.group(1).strip()
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if inner:
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return inner
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# 移除开头/结尾的独立 ``` 标记（不完整代码块）
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text = re.sub(r"^```(?:xml|jrxml)?\s*", "", text)
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text = re.sub(r"```\s*$", "", text)
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# 移除续写响应常见的自然语言前缀
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text = re.sub(
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r"^.{0,40}(继续输出|剩余|续写|补全|接上).{0,30}[:：]?\s*",
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"", text, flags=re.IGNORECASE
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)
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return text.strip()
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def _generate_with_continuation(llm, prompt, writer, node_name, max_rounds=3) -> str:
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"""Stream LLM generation with automatic truncation recovery.
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@@ -1519,6 +1558,7 @@ def _generate_with_continuation(llm, prompt, writer, node_name, max_rounds=3) ->
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Returns combined full text from all rounds.
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"""
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_jrxml_end = r"</(?:[\w:]+:)?(?:jasperReport|report)>\s*$"
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full_text = ""
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for round_num in range(max_rounds):
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@@ -1529,7 +1569,8 @@ def _generate_with_continuation(llm, prompt, writer, node_name, max_rounds=3) ->
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current_prompt = (
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f"[系统指令] 你正在生成的 JRXML 在上一次响应中被截断。\n"
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f"已生成内容的最后部分（请从此处继续）：\n...{tail}\n\n"
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f"请从截断点继续输出剩余内容，不要重复已输出的部分。"
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f"请从截断点继续输出剩余内容，不要重复已输出的部分。\n"
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f"不要输出 markdown 代码块、解释或任何非 JRXML 的内容。"
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)
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new_chunks = []
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@@ -1538,10 +1579,12 @@ def _generate_with_continuation(llm, prompt, writer, node_name, max_rounds=3) ->
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writer({"type": "stream", "node": node_name, "text": chunk})
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new_text = "".join(new_chunks)
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if round_num > 0:
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new_text = _strip_continuation_wrapper(new_text)
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full_text += new_text
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jrxml = _extract_jrxml(full_text)
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if re.search(r"</(?:[\w:]+:)?jasperReport>\s*$", jrxml, re.IGNORECASE):
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if re.search(_jrxml_end, jrxml, re.IGNORECASE):
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break
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if not new_text.strip():
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@@ -1554,17 +1597,26 @@ def _generate_with_continuation(llm, prompt, writer, node_name, max_rounds=3) ->
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def _extract_jrxml(text: str) -> str:
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"""从 LLM 响应中提取 JRXML 内容，如有 markdown 标记则去除。"""
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text = text.strip()
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xml_pattern = re.compile(r"```(?:xml|jrxml)?\s*([\s\S]*?)```", re.IGNORECASE)
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m = xml_pattern.search(text)
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if m:
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content = m.group(1).strip()
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if content:
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return content
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# markdown 代码块存在但内容为空 — 回退到直接匹配
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"""从 LLM 响应中提取 JRXML 内容，如有 markdown 标记则去除。
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_jrxml_close = r"</(?:[\w:]+:)?jasperReport>"
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处理多种情况：
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1. 完整的 markdown 代码块包裹（单轮输出）
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2. 混合文本（多轮续写：第一轮无 markdown，续写轮添加了 markdown）
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3. 纯 JRXML 无包装
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"""
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text = text.strip()
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# 检测并提取 markdown 代码块中的内容
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# 如果第一个代码块的内容看起来是完整 JRXML（以 <?xml 或 <jasperReport 开头），
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# 则返回它；否则跳过该块，回退到其他提取方式。
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xml_pattern = re.compile(r"```(?:xml|jrxml)?\s*([\s\S]*?)```", re.IGNORECASE)
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for m in xml_pattern.finditer(text):
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content = m.group(1).strip()
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if content and (content.startswith("<?xml") or content.startswith("<jasperReport")):
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return content
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# 非完整 JRXML 片段 — 跳过，继续搜索后续代码块
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# 直接匹配 <?xml ... </jasperReport> 或 ... </report>
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_jrxml_close = r"</(?:[\w:]+:)?(?:jasperReport|report)>"
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jasper_tag = re.search(rf"(<\?xml[\s\S]*?{_jrxml_close})", text, re.IGNORECASE)
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if jasper_tag:
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return jasper_tag.group(1).strip()
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@@ -1572,8 +1624,7 @@ def _extract_jrxml(text: str) -> str:
|
||||
if text.startswith("<?xml") or text.startswith("<jasperReport"):
|
||||
return text
|
||||
|
||||
# 最终回退：如果文本中包含 XML 片段但没有被捕获到，尝试直接提取
|
||||
# 这处理 LLM 在代码块外用自然语言"包裹"JRXML 的情况
|
||||
# 最终回退：尝试在文本中定位 XML 起始和结束
|
||||
xml_start = text.find("<?xml")
|
||||
jr_close = re.search(_jrxml_close, text, re.IGNORECASE)
|
||||
if xml_start >= 0 and jr_close:
|
||||
|
||||
+18
-8
@@ -156,8 +156,14 @@ class _LLMLoggingWrapper(_BaseLLM):
|
||||
raise
|
||||
|
||||
|
||||
def _build_raw_llm(caller: str = "") -> tuple[_BaseLLM, str, str]:
|
||||
"""构造原始 LLM 实例，返回 (实例, model名, backend名)。"""
|
||||
DEFAULT_MAX_TOKENS = int(os.getenv("LLM_MAX_TOKENS", "8192"))
|
||||
|
||||
|
||||
def _build_raw_llm(caller: str = "", max_tokens: int | None = None) -> tuple[_BaseLLM, str, str]:
|
||||
"""构造原始 LLM 实例，返回 (实例, model名, backend名)。
|
||||
|
||||
max_tokens: 覆盖默认输出 token 数。None 使用 LLM_MAX_TOKENS 环境变量或 8192。
|
||||
"""
|
||||
backend = os.getenv("LLM_BACKEND", "cloud")
|
||||
if backend == "local":
|
||||
from langchain_ollama import ChatOllama
|
||||
@@ -183,18 +189,19 @@ def _build_raw_llm(caller: str = "") -> tuple[_BaseLLM, str, str]:
|
||||
base_url = os.getenv("ANTHROPIC_BASE_URL") or os.getenv("OPENAI_BASE_URL", "https://api.minimaxi.com/anthropic")
|
||||
model = os.getenv("LLM_MODEL", "MiniMax-M2.7")
|
||||
temperature = 0.1
|
||||
max_tokens = 8192
|
||||
_default_max_tokens = max_tokens if max_tokens is not None else DEFAULT_MAX_TOKENS
|
||||
|
||||
client = Anthropic(api_key=api_key, base_url=base_url, timeout=120)
|
||||
|
||||
class MiniMaxLLM(_BaseLLM):
|
||||
def __init__(self):
|
||||
self._last_stop_reason = None
|
||||
self._max_tokens = _default_max_tokens
|
||||
|
||||
def invoke(self, prompt: str) -> Any:
|
||||
resp = client.messages.create(
|
||||
model=model,
|
||||
max_tokens=max_tokens,
|
||||
max_tokens=self._max_tokens,
|
||||
temperature=temperature,
|
||||
messages=[{"role": "user", "content": [{"type": "text", "text": prompt}]}],
|
||||
)
|
||||
@@ -208,7 +215,7 @@ def _build_raw_llm(caller: str = "") -> tuple[_BaseLLM, str, str]:
|
||||
self._last_stop_reason = None
|
||||
with client.messages.stream(
|
||||
model=model,
|
||||
max_tokens=max_tokens,
|
||||
max_tokens=self._max_tokens,
|
||||
temperature=temperature,
|
||||
messages=[{"role": "user", "content": [{"type": "text", "text": prompt}]}],
|
||||
) as s:
|
||||
@@ -250,9 +257,12 @@ def _build_raw_llm(caller: str = "") -> tuple[_BaseLLM, str, str]:
|
||||
return OpenAIWrapper(), model, f"cloud/openai/{model}"
|
||||
|
||||
|
||||
def get_llm(caller: str = "") -> _BaseLLM:
|
||||
"""返回带日志的 LLM 实例。caller 用于标识调用来源（如 generate、classify_intent）。"""
|
||||
inner, model, backend = _build_raw_llm(caller)
|
||||
def get_llm(caller: str = "", max_tokens: int | None = None) -> _BaseLLM:
|
||||
"""返回带日志的 LLM 实例。caller 用于标识调用来源（如 generate、classify_intent）。
|
||||
|
||||
max_tokens: 覆盖默认输出 token 数。用于骨架生成等需要大量输出的节点。
|
||||
"""
|
||||
inner, model, backend = _build_raw_llm(caller, max_tokens=max_tokens)
|
||||
return _LLMLoggingWrapper(inner, model=model, backend=backend, caller=caller)
|
||||
|
||||
|
||||
|
||||
+12
-2
@@ -4,6 +4,7 @@ import os
|
||||
|
||||
import httpx
|
||||
from dotenv import load_dotenv
|
||||
from httpx import ConnectError, HTTPStatusError
|
||||
|
||||
from backend.logger import get_logger
|
||||
|
||||
@@ -31,10 +32,19 @@ def validate_jrxml(jrxml_text: str) -> dict:
|
||||
},
|
||||
)
|
||||
return result
|
||||
except httpx.ConnectError:
|
||||
except ConnectError:
|
||||
error_msg = f"无法连接到验证服务 ({VALIDATION_URL})。是否正在运行？"
|
||||
_val_log.error("验证服务连接失败", extra={"error": error_msg, "url": VALIDATION_URL})
|
||||
return {"valid": False, "error": error_msg}
|
||||
return {"valid": False, "error": error_msg, "service_unavailable": True}
|
||||
except HTTPStatusError as e:
|
||||
status_code = e.response.status_code
|
||||
error_msg = f"验证服务返回错误 ({status_code}): {str(e)}"
|
||||
_val_log.error("验证请求异常", extra={"error": str(e), "url": VALIDATION_URL, "status_code": status_code})
|
||||
return {
|
||||
"valid": False,
|
||||
"error": error_msg,
|
||||
"service_unavailable": status_code >= 500,
|
||||
}
|
||||
except Exception as e:
|
||||
error_msg = f"验证请求失败: {str(e)}"
|
||||
_val_log.error("验证请求异常", extra={"error": str(e), "url": VALIDATION_URL})
|
||||
|
||||
@@ -0,0 +1,228 @@
|
||||
"""续写 + JRXML 提取单元测试。
|
||||
|
||||
测试 _strip_continuation_wrapper、_extract_jrxml 在
|
||||
多轮续写场景下的鲁棒性，以及 _generate_with_continuation 的完成检测。
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import pytest
|
||||
from agent.nodes import _strip_continuation_wrapper, _extract_jrxml
|
||||
|
||||
# ── 完整 JRXML ─────────────────────────────────────────────────────
|
||||
|
||||
COMPLETE_JRXML = """<?xml version="1.0" encoding="UTF-8"?>
|
||||
<jasperReport name="test" pageWidth="595" pageHeight="842">
|
||||
<field name="field_1" class="java.lang.String"/>
|
||||
<queryString><![CDATA[SELECT * FROM t]]></queryString>
|
||||
<title>
|
||||
<band height="50">
|
||||
<staticText>
|
||||
<reportElement x="0" y="0" width="100" height="20"/>
|
||||
<text><![CDATA[$F{field_1}]]></text>
|
||||
</staticText>
|
||||
</band>
|
||||
</title>
|
||||
</jasperReport>"""
|
||||
|
||||
# 第一轮输出：完整开头但缺少 </jasperReport>（模拟截断）
|
||||
ROUND1_TRUNCATED = """<?xml version="1.0" encoding="UTF-8"?>
|
||||
<jasperReport name="test" pageWidth="595" pageHeight="842">
|
||||
<field name="field_1" class="java.lang.String"/>
|
||||
<field name="field_2" class="java.lang.String"/>
|
||||
<queryString><![CDATA[SELECT * FROM t]]></queryString>
|
||||
<title>
|
||||
<band height="50">
|
||||
<staticText>
|
||||
<reportElement x="0" y="0" width="100" height="20"/>
|
||||
<text><![CDATA[$F{field_1}]]></text>
|
||||
</staticText>
|
||||
</band>
|
||||
</title>
|
||||
<detail>
|
||||
<band height="30">
|
||||
<textField>
|
||||
<reportElement x="0" y="0" width="100" height="20"/>
|
||||
<textFieldExpression><![CDATA[$F{field_1}]]></"""
|
||||
|
||||
# 第二轮续写：用 markdown 包裹 + 错误关闭标签（真实 LLM 行为）
|
||||
ROUND2_MARKDOWN_CONTINUATION = """继续输出剩余的 JRXML 内容：
|
||||
|
||||
```
|
||||
<textFieldExpression><![CDATA[$F{field_2}]]></textFieldExpression>
|
||||
</textField>
|
||||
</band>
|
||||
</detail>
|
||||
</jasperReport>
|
||||
```"""
|
||||
|
||||
# 第二轮续写变体：用 </report> 关闭（另一种常见 LLM 错误）
|
||||
ROUND2_REPORT_CLOSE = """继续输出：
|
||||
|
||||
```
|
||||
<textFieldExpression><![CDATA[$F{field_2}]]></textFieldExpression>
|
||||
</textField>
|
||||
</band>
|
||||
</detail>
|
||||
</report>
|
||||
```"""
|
||||
|
||||
# 第二轮续写变体：只用 ``` 开头，无结尾（不完整代码块）
|
||||
ROUND2_PARTIAL_MARKDOWN = """
|
||||
```xml
|
||||
<textFieldExpression><![CDATA[$F{field_2}]]></textFieldExpression>
|
||||
</textField>
|
||||
</band>
|
||||
</detail>
|
||||
</jasperReport>
|
||||
```"""
|
||||
|
||||
|
||||
# ── _strip_continuation_wrapper 测试 ───────────────────────────────
|
||||
|
||||
class TestStripContinuationWrapper:
|
||||
def test_removes_complete_markdown_block(self):
|
||||
text = '继续输出：\n\n```\n<band>test</band>\n```'
|
||||
result = _strip_continuation_wrapper(text)
|
||||
assert result == '<band>test</band>'
|
||||
|
||||
def test_removes_xml_fenced_block(self):
|
||||
text = '```xml\n<band>test</band>\n```'
|
||||
result = _strip_continuation_wrapper(text)
|
||||
assert result == '<band>test</band>'
|
||||
|
||||
def test_removes_opening_fence_only(self):
|
||||
text = '```xml\n<band>test</band>'
|
||||
result = _strip_continuation_wrapper(text)
|
||||
assert '<band>test</band>' in result
|
||||
assert '```' not in result
|
||||
|
||||
def test_removes_closing_fence_only(self):
|
||||
text = '<band>test</band>\n```'
|
||||
result = _strip_continuation_wrapper(text)
|
||||
assert '<band>test</band>' in result
|
||||
assert '```' not in result
|
||||
|
||||
def test_removes_continuation_prefix_chinese(self):
|
||||
text = '继续输出剩余的 JRXML 内容：\n<band>test</band>'
|
||||
result = _strip_continuation_wrapper(text)
|
||||
assert result == '<band>test</band>'
|
||||
|
||||
def test_pure_xml_passes_through(self):
|
||||
text = '<band>test</band>'
|
||||
result = _strip_continuation_wrapper(text)
|
||||
assert result == '<band>test</band>'
|
||||
|
||||
def test_empty_becomes_empty(self):
|
||||
assert _strip_continuation_wrapper('') == ''
|
||||
assert _strip_continuation_wrapper(' ') == ''
|
||||
|
||||
def test_empty_markdown_block_returns_empty(self):
|
||||
text = '```xml\n```'
|
||||
result = _strip_continuation_wrapper(text)
|
||||
assert result == ''
|
||||
|
||||
def test_multiple_backtick_pairs_extracts_first_valid(self):
|
||||
text = '```\nfragment\n```\n```xml\ncomplete<?xml ...\n```'
|
||||
result = _strip_continuation_wrapper(text)
|
||||
assert result == 'fragment'
|
||||
|
||||
|
||||
# ── _extract_jrxml 多轮续写场景测试 ─────────────────────────────────
|
||||
|
||||
class TestExtractJrxmlMultiRound:
|
||||
def test_extracts_from_mixed_multi_round_output(self):
|
||||
"""第一轮无 markdown + 第二轮有 markdown 的混合文本。"""
|
||||
combined = ROUND1_TRUNCATED + ROUND2_MARKDOWN_CONTINUATION
|
||||
result = _extract_jrxml(combined)
|
||||
assert result.startswith("<?xml")
|
||||
assert "</jasperReport>" in result
|
||||
assert '$F{field_1}' in result
|
||||
assert '$F{field_2}' in result
|
||||
|
||||
def test_extracts_with_report_close_tag(self):
|
||||
"""第二轮用 </report> 而非 </jasperReport> 关闭。"""
|
||||
combined = ROUND1_TRUNCATED + ROUND2_REPORT_CLOSE
|
||||
result = _extract_jrxml(combined)
|
||||
assert result.startswith("<?xml")
|
||||
assert "</report>" in result
|
||||
assert '$F{field_2}' in result
|
||||
|
||||
def test_extracts_with_partial_markdown(self):
|
||||
"""第二轮用 ```xml 开头，``` 结尾。"""
|
||||
combined = ROUND1_TRUNCATED + ROUND2_PARTIAL_MARKDOWN
|
||||
result = _extract_jrxml(combined)
|
||||
assert result.startswith("<?xml")
|
||||
assert "</jasperReport>" in result
|
||||
|
||||
def test_single_round_complete_jrxml_in_markdown(self):
|
||||
"""单轮输出：完整的 JRXML 在 markdown 代码块中。"""
|
||||
text = '```xml\n' + COMPLETE_JRXML + '\n```'
|
||||
result = _extract_jrxml(text)
|
||||
assert result == COMPLETE_JRXML
|
||||
|
||||
def test_single_round_pure_jrxml(self):
|
||||
"""单轮输出：纯 JRXML 无 markdown。"""
|
||||
result = _extract_jrxml(COMPLETE_JRXML)
|
||||
assert result == COMPLETE_JRXML
|
||||
|
||||
def test_jrxml_with_leading_explanation(self):
|
||||
"""JRXML 前有自然语言解释。"""
|
||||
text = '这是生成的报表模板：\n' + COMPLETE_JRXML
|
||||
result = _extract_jrxml(text)
|
||||
assert result == COMPLETE_JRXML
|
||||
|
||||
def test_two_markdown_blocks_skips_fragment(self):
|
||||
"""文本中有两个 markdown 块，第一个是片段，第二个是完整 JRXML。"""
|
||||
text = (
|
||||
'```\nsome fragment\n```\n'
|
||||
'```xml\n' + COMPLETE_JRXML + '\n```'
|
||||
)
|
||||
result = _extract_jrxml(text)
|
||||
assert result == COMPLETE_JRXML
|
||||
|
||||
def test_two_markdown_blocks_first_is_complete(self):
|
||||
"""文本中有两个 markdown 块，第一个是完整 JRXML。"""
|
||||
text = (
|
||||
'```xml\n' + COMPLETE_JRXML + '\n```\n'
|
||||
'```\nsome other stuff\n```'
|
||||
)
|
||||
result = _extract_jrxml(text)
|
||||
assert result == COMPLETE_JRXML
|
||||
|
||||
def test_no_xml_passes_through(self):
|
||||
"""无 XML 内容的文本原样返回。"""
|
||||
text = 'Hello, this has no XML at all.'
|
||||
result = _extract_jrxml(text)
|
||||
assert result == text
|
||||
|
||||
|
||||
# ── 完成检测测试 ───────────────────────────────────────────────────
|
||||
|
||||
class TestCompletionDetection:
|
||||
def test_jasperreport_close_detected(self):
|
||||
"""以 </jasperReport> 结尾的 JRXML 应被识别为完成。"""
|
||||
import re
|
||||
jrxml = COMPLETE_JRXML.strip()
|
||||
_jrxml_end = r"</(?:[\w:]+:)?(?:jasperReport|report)>\s*$"
|
||||
assert re.search(_jrxml_end, jrxml, re.IGNORECASE)
|
||||
|
||||
def test_report_close_detected(self):
|
||||
"""以 </report> 结尾的 JRXML 也应被识别为完成。"""
|
||||
import re
|
||||
jrxml = COMPLETE_JRXML.replace('</jasperReport>', '</report>').strip()
|
||||
_jrxml_end = r"</(?:[\w:]+:)?(?:jasperReport|report)>\s*$"
|
||||
assert re.search(_jrxml_end, jrxml, re.IGNORECASE)
|
||||
|
||||
def test_namespaced_jasperreport_close_detected(self):
|
||||
"""以 </ns0:jasperReport> 结尾的 JRXML 也应被识别。"""
|
||||
import re
|
||||
jrxml = COMPLETE_JRXML.replace('</jasperReport>', '</ns0:jasperReport>').strip()
|
||||
_jrxml_end = r"</(?:[\w:]+:)?(?:jasperReport|report)>\s*$"
|
||||
assert re.search(_jrxml_end, jrxml, re.IGNORECASE)
|
||||
|
||||
def test_truncated_jrxml_not_detected(self):
|
||||
"""截断的 JRXML（无关闭标签）不应被识别为完成。"""
|
||||
import re
|
||||
_jrxml_end = r"</(?:[\w:]+:)?(?:jasperReport|report)>\s*$"
|
||||
assert not re.search(_jrxml_end, ROUND1_TRUNCATED.strip(), re.IGNORECASE)
|
||||
Reference in New Issue
Block a user