fix: MAX_RETRY 5 + rolling continuation + namespace-aware JRXML extraction
- MAX_RETRY: 3→5 (graph.py:35, nodes.py:25) with env override - Rolling continuation: _generate_with_continuation() auto-detects truncated JRXML and sends anchor-based continuation, max 3 rounds - JRXML extraction: regex/end-tag now namespace-prefix aware (ns0:jasperReport, ns:jasperReport, etc.) - All 5 generation nodes refactored to use continuation helper - Tests updated: scenario1 accepts ns-prefixed root, max_retry verifies graph termination - stop_reason capture + WARNING log on max_tokens truncation - Correction prompt now injects OCR context + layout schema
This commit is contained in:
+102
-29
@@ -673,11 +673,15 @@ def generate_skeleton(state: AgentState) -> Dict:
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context=state.get("retrieved_context", ""),
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user_request=user_request,
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)
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full = []
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for chunk in llm.stream(prompt):
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full.append(chunk)
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writer({"type": "stream", "node": "generate_skeleton", "text": chunk})
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jrxml = _extract_jrxml("".join(full))
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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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return state
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jrxml = _extract_jrxml(full_text)
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if len(jrxml.strip()) < 200:
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_node_log.warning(f"generate_skeleton 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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state["current_jrxml"] = jrxml
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state["conversation_history"].append({"role": "assistant", "content": jrxml})
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return state
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@@ -705,11 +709,15 @@ def refine_layout(state: AgentState) -> Dict:
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current_jrxml=state.get("current_jrxml", ""),
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sampled_coordinates=sampled_text,
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)
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full = []
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for chunk in llm.stream(prompt):
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full.append(chunk)
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writer({"type": "stream", "node": "refine_layout", "text": chunk})
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jrxml = _extract_jrxml("".join(full))
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prev_jrxml = state.get("current_jrxml", "")
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full_text = _generate_with_continuation(llm, prompt, writer, "refine_layout")
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if not full_text.strip():
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_node_log.error("refine_layout LLM 返回空响应，保留前一版本")
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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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_node_log.warning(f"refine_layout 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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state["current_jrxml"] = jrxml
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state["conversation_history"].append({"role": "assistant", "content": jrxml})
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return state
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@@ -744,11 +752,15 @@ def map_fields(state: AgentState) -> Dict:
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current_jrxml=state.get("current_jrxml", ""),
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ocr_fields=fields_text,
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)
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full = []
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for chunk in llm.stream(prompt):
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full.append(chunk)
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writer({"type": "stream", "node": "map_fields", "text": chunk})
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jrxml = _extract_jrxml("".join(full))
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prev_jrxml = state.get("current_jrxml", "")
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full_text = _generate_with_continuation(llm, prompt, writer, "map_fields")
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if not full_text.strip():
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_node_log.error("map_fields LLM 返回空响应，保留占位字段版本")
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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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_node_log.warning(f"map_fields 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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state["current_jrxml"] = jrxml
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state["conversation_history"].append({"role": "assistant", "content": jrxml})
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return state
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@@ -776,11 +788,15 @@ def modify_jrxml(state: AgentState) -> Dict:
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modification_request=state.get("user_modification_request", ""),
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ocr_context=_format_ocr_context(state),
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)
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full = []
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for chunk in llm.stream(prompt):
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full.append(chunk)
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writer({"type": "stream", "node": "modify_jrxml", "text": chunk})
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jrxml = _extract_jrxml("".join(full))
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prev_jrxml = state.get("current_jrxml", "")
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full_text = _generate_with_continuation(llm, prompt, writer, "modify_jrxml")
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if not full_text.strip():
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_node_log.error("modify_jrxml LLM 返回空响应，保留原版本")
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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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_node_log.warning(f"modify_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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state["current_jrxml"] = jrxml
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state["conversation_history"].append(
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{
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@@ -876,10 +892,17 @@ def correct_jrxml(state: AgentState) -> Dict:
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writer = get_stream_writer()
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llm = get_llm(caller="correct_jrxml")
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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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if isinstance(layout_schema, dict):
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layout_text = layout_schema.get("schema_text", "")
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prompt = load_prompt("correction").format(
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current_jrxml=state.get("current_jrxml", ""),
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error_msg=state.get("error_msg", ""),
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explanation=state.get("natural_explanation", ""),
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ocr_context=ocr_context,
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layout_schema_text=layout_text,
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)
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# 保存修正前状态（供 validate 判断是否写入错误知识库）
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state["last_error_case"] = {
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@@ -888,11 +911,16 @@ def correct_jrxml(state: AgentState) -> Dict:
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"correction_prompt": prompt,
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}
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full = []
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for chunk in llm.stream(prompt):
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full.append(chunk)
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writer({"type": "stream", "node": "correct_jrxml", "text": chunk})
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jrxml = _extract_jrxml("".join(full))
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prev_jrxml = state.get("current_jrxml", "")
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full_text = _generate_with_continuation(llm, prompt, writer, "correct_jrxml")
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if not full_text.strip():
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_node_log.error("correct_jrxml LLM 返回空响应，保留原版本")
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state["retry_count"] = state.get("retry_count", 0) + 1
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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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_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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state["current_jrxml"] = jrxml
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state["retry_count"] = state.get("retry_count", 0) + 1
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state["conversation_history"].append(
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@@ -963,6 +991,49 @@ def finalize(state: AgentState) -> Dict:
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return state
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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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After each stream round, checks if the extracted JRXML ends with
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</jasperReport>. If truncated, sends a continuation request with
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the last 800 chars as anchor context.
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Returns combined full text from all rounds.
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"""
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full_text = ""
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for round_num in range(max_rounds):
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if round_num == 0:
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current_prompt = prompt
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else:
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tail = full_text[-800:] if len(full_text) > 800 else full_text
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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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)
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new_chunks = []
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for chunk in llm.stream(current_prompt):
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new_chunks.append(chunk)
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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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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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break
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if not new_text.strip():
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_node_log.warning(f"{node_name} 第{round_num+1}轮续写无输出，停止")
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break
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else:
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_node_log.warning(f"{node_name} 经{max_rounds}轮续写仍未完整")
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return full_text
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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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@@ -974,7 +1045,8 @@ def _extract_jrxml(text: str) -> str:
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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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jasper_tag = re.search(r"(<\?xml[\s\S]*?</jasperReport>)", text, re.IGNORECASE)
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_jrxml_close = r"</(?:[\w:]+:)?jasperReport>"
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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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@@ -984,8 +1056,9 @@ def _extract_jrxml(text: str) -> str:
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# 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
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# 这处理 LLM 在代码块外用自然语言"包裹"JRXML 的情况
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xml_start = text.find("<?xml")
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jr_end = text.lower().rfind("</jasperreport>")
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if xml_start >= 0 and jr_end > xml_start:
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return text[xml_start:jr_end + len("</jasperreport>")].strip()
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jr_close = re.search(_jrxml_close, text, re.IGNORECASE)
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if xml_start >= 0 and jr_close:
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jr_end = jr_close.end()
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return text[xml_start:jr_end].strip()
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return text
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