Merge branch 'main' of https://gitea.iconsz.com/fengruixiang/hklii_samples
commit
d3cba48e12
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@ -68,6 +68,7 @@ import json
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import re
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import sys
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import time
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from concurrent.futures import ThreadPoolExecutor, as_completed
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Any
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@ -760,13 +761,19 @@ REASON_OBJECT_SYSTEM_ZH = f"""從香港判決書中抽取：
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2. case_object（標的物）：
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- 訴訟請求指向的實體權利或利益
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- 例：汽車、黃金、珠寶、不動產產權、撫養權、人身傷害賠償、合同履行、房產所有權、精神困擾賠償、居留權
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- 涉及金錢標的時必須提取，並標明幣種與具體金額（如「拖欠貨款 HK$850,000」「索償 HK$1,000,000」「拖欠租金 HK$120,000」）；金額未定或待評定者註明「金額待評定」
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- 合併本質相同的標的
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- 嚴禁：證據材料、程序性訴求（如"要求法庭裁決"）、法律條文名稱
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用語要求：一律使用規範的法律專業用語（如「申索」「損害賠償」「違約」「侵權」「衡平法濟助」），避免口語化或不準確的表述。
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只輸出 JSON。"""
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REASON_OBJECT_FEWSHOT_ZH = """範例輸出：
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{"case_reason":"申索人為商場保安員，就被告於2023年7月在商場毆打申索人造成的人身傷害向被告提出損害賠償申索。","case_object":["人身傷害賠償","醫療費用","精神困擾賠償"]}"""
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REASON_OBJECT_FEWSHOT_ZH = """範例輸出1（人身傷害）：
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{"case_reason":"申索人為商場保安員，就被告於2023年7月在商場毆打申索人造成的人身傷害向被告提出損害賠償申索。","case_object":["人身傷害賠償","醫療費用","精神困擾賠償"]}
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範例輸出2（金錢申索，標的物須含具體金額）：
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{"case_reason":"原告就被告未支付2022年買賣合約項下的貨款，向被告提出追討欠款的申索。","case_object":["拖欠貨款 HK$850,000","合約利息","訟費"]}"""
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# 英文提示詞
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REASON_OBJECT_SYSTEM_EN = f"""Extract from Hong Kong judgment:
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@ -781,16 +788,37 @@ REASON_OBJECT_SYSTEM_EN = f"""Extract from Hong Kong judgment:
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2. case_object (Subject Matter):
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- Tangible rights or interests targeted by the claim
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- Examples: vehicle, gold, jewelry, property title, custody, personal injury damages, contract performance, property ownership, distress damages, right of abode
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- When a monetary subject matter is involved, it MUST be extracted with currency and the specific amount (e.g., "outstanding goods price HK$850,000", "claim of HK$1,000,000", "arrears of rent HK$120,000"); if the amount is unascertained, note "amount to be assessed"
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- Merge essentially identical subjects
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- MUST NOT include: evidentiary materials, procedural requests (e.g., "seeking court ruling"), names of statutes
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Terminology requirement: consistently use precise, standard legal terminology (e.g., "claim", "damages", "breach of contract", "negligence", "equitable relief"); avoid colloquial or imprecise wording.
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Output only JSON."""
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REASON_OBJECT_FEWSHOT_EN = """Example Output:
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{"case_reason":"Plaintiff, a shopping mall security guard, claims damages from defendant for personal injuries caused by defendant's assault at the mall in July 2023.","case_object":["personal injury damages","medical expenses","distress damages"]}"""
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REASON_OBJECT_FEWSHOT_EN = """Example Output 1 (personal injury):
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{"case_reason":"Plaintiff, a shopping mall security guard, claims damages from defendant for personal injuries caused by defendant's assault at the mall in July 2023.","case_object":["personal injury damages","medical expenses","distress damages"]}
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Example Output 2 (monetary claim, subject matter must carry the specific amount):
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{"case_reason":"Plaintiff claims against defendant for non-payment of the price of goods supplied under a 2022 sale and purchase contract.","case_object":["outstanding goods price HK$850,000","contractual interest","costs"]}"""
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def _reason_object_validator(out: dict, lang: str = 'zh') -> tuple[bool, str]:
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# 金錢數額識別：幣種前綴 + 數字，或數字 + 中文金額單位
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MONEY_RE = re.compile(
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r"(?:HK\$|US\$|RMB|MOP|港幣|港元|人民幣|美元|美金)\s*[\d,]+(?:\.\d+)?"
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r"|[\$＄]\s*[\d,]+(?:\.\d+)?"
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r"|[\d,]+(?:\.\d+)?\s*(?:萬元|億元|元|萬|億)",
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re.I,
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)
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def _object_has_amount(objs: list[str]) -> bool:
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"""case_object 中是否已含具體金額（任一項出現數字即視為已提取金額）"""
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return any(re.search(r"\d", o or "") for o in (objs or []))
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def _reason_object_validator(out: dict, lang: str = 'zh',
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context: str = "") -> tuple[bool, str]:
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r = out.get("case_reason", "")
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max_length = 100 if lang == 'zh' else 200 # 英文允許 2 倍字符數
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target_length = 80 if lang == 'zh' else 160 # 建議壓縮目標
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@ -819,6 +847,18 @@ def _reason_object_validator(out: dict, lang: str = 'zh') -> tuple[bool, str]:
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else:
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return False, f"case_reason should not contain judgment result term '{keyword}', describe only cause and relief sought."
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# 金錢標的物強制提取：原文出現金錢數額但 case_object 未含金額時要求補充
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if context and MONEY_RE.search(context) and not _object_has_amount(out.get("case_object", [])):
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if lang == 'zh':
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return False, ("原文出現金錢數額。若該數額屬於訴訟標的（如欠款、索償、賠償金額），"
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"必須在 case_object 中提取並標明幣種與具體金額（如「拖欠貨款 HK$850,000」）；"
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"若僅為無關引用則可忽略。")
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else:
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return False, ("Monetary amounts appear in the source. If an amount forms part of the "
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"subject matter (e.g., debt, claim, damages), it MUST be extracted in "
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"case_object with currency and the specific figure (e.g., \"outstanding "
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"goods price HK$850,000\"); ignore only if it is an unrelated citation.")
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return True, ""
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@ -837,7 +877,7 @@ def extract_reason_object(client: OpenAICompatibleClient, context: str, lang: st
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return client.chat_json_with_retry(system, user,
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schema,
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validator=lambda x: _reason_object_validator(x, lang))
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validator=lambda x: _reason_object_validator(x, lang, context[:5000]))
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# --- Call 3: 判決結果 -------------------------------------------------------
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@ -875,7 +915,9 @@ JUDGMENT_RESULT_SYSTEM_ZH = """從香港判決書尾部的命令/裁定部分抽
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- result 必須包含：
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a) 明確結果（勝訴/敗訴/部分勝訴/維持/撤銷/駁回/發還等）
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b) 2-3 個關鍵法庭理由（如有）
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c) 具體金額、利率或命令內容（如有）
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c) 具體金額、利率或命令內容；凡有判給/命令支付的金錢數額，必須原文照錄幣種與金額（如 HK$28,500），不得省略或約化
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用語要求：一律使用規範的法律專業用語（如「判給」「訟費」「利息」「駁回」「發還重審」），避免口語化或不準確的表述。
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只輸出 JSON。"""
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@ -900,7 +942,9 @@ Splitting Principles:
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- result must include:
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a) Clear outcome (allowed/dismissed/partially allowed/upheld/quashed/remitted, etc.)
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b) 2-3 key court reasons (if any)
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c) Specific amounts, interest rates or order details (if any)
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c) Specific amounts, interest rates or order details; whenever a sum is awarded/ordered to be paid, the currency and figure MUST be reproduced verbatim (e.g., HK$28,500), never omitted or rounded
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Terminology requirement: consistently use precise, standard legal terminology (e.g., "awarded", "costs", "interest", "dismissed", "remitted for retrial"); avoid colloquial or imprecise wording.
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Output only JSON."""
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@ -998,6 +1042,8 @@ ENTITIES_SYSTEM_ZH = """從香港判決書中抽取所有相關實體（自然
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- 純案例名稱（如 Donoghue v Stevenson）
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- 文獻、期刊名
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用語要求：reason 一律使用規範的法律專業用語（如「主審」「闡述」「先例」「判詞」），避免口語化或不準確的表述。
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只輸出 JSON。"""
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ENTITIES_FEWSHOT_ZH = """範例輸出：
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@ -1022,6 +1068,8 @@ MUST NOT include:
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- Pure case names (e.g., Donoghue v Stevenson)
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- Literature, journal names
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Terminology requirement: write each reason in precise, standard legal terminology (e.g., "presiding", "articulated", "precedent", "judgment"); avoid colloquial or imprecise wording.
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Output only JSON."""
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ENTITIES_FEWSHOT_EN = """Example Output:
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@ -1106,6 +1154,8 @@ SUMMARY_SYSTEM_ZH = """根據已抽取的結構化字段 + 法庭分析段，撰
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**重要：judgment_summary 必須使用中文撰寫。**
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用語要求：一律使用規範的法律專業用語；涉及金錢的判給或標的，須保留具體金額（含幣種）。
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嚴格 ≤300 字。只輸出 JSON。"""
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# 英文提示詞
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@ -1122,6 +1172,8 @@ Four-element structure (must cover all, in coherent single paragraph):
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**IMPORTANT: judgment_summary MUST be written in English.**
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Terminology requirement: consistently use precise, standard legal terminology; preserve specific monetary figures (with currency) for any award or subject matter involving money.
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Strictly ≤500 characters. Output only JSON."""
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@ -1268,8 +1320,9 @@ def run_pipeline(text: str, model: str, base_url: str, api_key: str,
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entities_window: int = 400,
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entities_max: int = 6500,
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analysis_window: int = 500,
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analysis_max: int = 6500) -> tuple[dict, OpenAICompatibleClient]:
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log = lambda m: print(m, file=sys.stderr)
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analysis_max: int = 6500,
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log_prefix: str = "") -> tuple[dict, OpenAICompatibleClient]:
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log = lambda m: print(f"{log_prefix}{m}", file=sys.stderr)
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log("[0/7] 檢測語言...")
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lang = detect_language(text)
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@ -1416,6 +1469,93 @@ def to_yaml(result: dict) -> str:
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default_flow_style=False, width=100)
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# =============================================================================
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# 7. 多模型運行：解析運行規格 + 輸出路徑推導
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# =============================================================================
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@dataclass
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class RunSpec:
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"""單個模型的運行規格（標籤 + 連接參數 + 計費配置）"""
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label: str # 用於日誌前綴與輸出文件名（配置名或模型名）
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model: str
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base_url: str
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api_key: str
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profile: dict | None = None # models.json 配置（用於成本計算），無則 None
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def _safe_label(name: str) -> str:
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"""把配置/模型名轉成可安全用於文件名的標籤（如 anthropic/claude → anthropic_claude）"""
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safe = re.sub(r"[^0-9A-Za-z._-]+", "_", name).strip("_")
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return safe or "model"
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def parse_run_specs(args) -> list[RunSpec]:
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"""解析 --config / --model（均支持逗號分隔）為一組運行規格。
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優先級：
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- 有 --config：逐個從 models.json 加載配置（自帶 model/base_url/api_key/價格）
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- 否則：用 --model（可逗號分隔多個），共用 --base-url / --api-key
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"""
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specs: list[RunSpec] = []
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if args.config:
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names = [n.strip() for n in args.config.split(",") if n.strip()]
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for name in names:
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profile = load_model_profile(name, args.models_file)
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specs.append(RunSpec(
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label=name,
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model=profile.get("model") or args.model,
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base_url=profile.get("BaseApiUrl") or args.base_url,
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api_key=profile.get("ApiKey") or args.api_key,
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profile=profile,
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))
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else:
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names = [n.strip() for n in args.model.split(",") if n.strip()] or [args.model]
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for name in names:
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specs.append(RunSpec(
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label=name,
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model=name,
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base_url=args.base_url,
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api_key=args.api_key,
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profile=None,
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))
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return specs
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def build_out_path(args, input_path: Path, label: str, multi: bool) -> Path | None:
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"""推導某個模型的 YAML 輸出路徑。
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- 單模型：沿用原行為（--out 指定則用之，否則 None 表示輸出到 stdout）
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- 多模型：在文件名中插入標籤；未給 --out 時用「輸入名_標籤.yaml」
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"""
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if not multi:
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return Path(args.out) if args.out else None
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safe = _safe_label(label)
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if args.out:
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base = Path(args.out)
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return base.with_name(f"{base.stem}_{safe}{base.suffix or '.yaml'}")
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return input_path.with_name(f"{input_path.stem}_{safe}.yaml")
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def build_cost_path(out_path: Path | None, input_path: Path,
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label: str, multi: bool) -> Path:
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"""成本文件路徑：有輸出文件時用「輸出名_cost.json」，否則回退到輸入名。"""
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if out_path is not None:
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return out_path.with_name(out_path.stem + "_cost.json")
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if multi:
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return input_path.with_name(f"{input_path.stem}_{_safe_label(label)}_cost.json")
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return input_path.with_name(input_path.stem + "_cost.json")
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def build_debug_path(args, label: str, multi: bool) -> Path | None:
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"""debug-dump 路徑：多模型時在文件名中插入標籤。"""
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if not args.debug_dump:
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return None
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base = Path(args.debug_dump)
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if multi:
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return base.with_name(f"{base.stem}_{_safe_label(label)}{base.suffix or '.json'}")
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return base
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# =============================================================================
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# CLI
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# =============================================================================
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@ -1444,6 +1584,17 @@ def main() -> None:
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--model gpt-4 \\
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--api-key your-api-key
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# 同時跑多個模型（逗號分隔），並發執行，分別輸出到不同文件
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python hk_case_extractor.py case.txt \\
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--config openrouter-claude-sonnet,openrouter-gpt4o,ollama-qwen \\
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--out result.yaml --cost
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# 生成 result_openrouter-claude-sonnet.yaml / result_openrouter-gpt4o.yaml / ...
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# 及各自的 *_cost.json
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# 多個本地 Ollama 模型共用同一端點
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python hk_case_extractor.py case.txt \\
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--model qwen2.5:7b-instruct,llama3.1:8b --out result.yaml
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# 調整截取長度
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python hk_case_extractor.py case.txt \\
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--head-length 8000 \\
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@ -1455,21 +1606,24 @@ def main() -> None:
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)
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ap.add_argument("input", help="判決書文本路徑（.txt 或 .json）")
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ap.add_argument("--config", default=None,
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help="models.json 中的配置名稱（Name），"
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help="models.json 中的配置名稱（Name），可逗號分隔多個以同時運行多個模型，"
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"使用後可省略 --model/--base-url/--api-key")
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ap.add_argument("--models-file", default=DEFAULT_MODELS_FILE,
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help=f"模型配置文件路徑（默認：{DEFAULT_MODELS_FILE}）")
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ap.add_argument("--model", default=DEFAULT_MODEL,
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help=f"模型名稱（默認：{DEFAULT_MODEL}）")
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help=f"模型名稱（默認：{DEFAULT_MODEL}），可逗號分隔多個（共用 --base-url/--api-key）")
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ap.add_argument("--base-url", default=DEFAULT_BASE_URL,
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help=f"API base URL（默認：{DEFAULT_BASE_URL}）")
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ap.add_argument("--api-key", default=DEFAULT_API_KEY,
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help="API key（Ollama 可忽略）")
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ap.add_argument("--out", default=None, help="輸出 YAML 路徑（默認 stdout）")
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ap.add_argument("--out", default=None,
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help="輸出 YAML 路徑（單模型默認 stdout）；多模型時在文件名中插入標籤")
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ap.add_argument("--max-workers", type=int, default=0,
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help="多模型時的並發數（默認 0 = 模型數量；設為 1 則順序執行）")
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ap.add_argument("--cost", action="store_true",
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help="輸出成本統計到 {輸出文件名}_cost.json（默認不輸出）")
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ap.add_argument("--debug-dump", default=None,
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help="額外輸出原始 JSON 結果到該路徑（便於 diff）")
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||||
help="額外輸出原始 JSON 結果到該路徑（多模型時在文件名中插入標籤）")
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||||
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||||
# 截取長度控制參數
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||||
ap.add_argument("--head-length", type=int, default=5000,
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||||
|
|
@ -1487,24 +1641,17 @@ def main() -> None:
|
|||
|
||||
args = ap.parse_args()
|
||||
|
||||
# 解析模型配置：--config 優先，未命中的字段回退到命令行/默認值
|
||||
profile: dict | None = None
|
||||
if args.config:
|
||||
profile = load_model_profile(args.config, args.models_file)
|
||||
model = profile.get("model") or args.model
|
||||
base_url = profile.get("BaseApiUrl") or args.base_url
|
||||
api_key = profile.get("ApiKey") or args.api_key
|
||||
print(f"使用配置 '{args.config}'：model={model}, base_url={base_url}",
|
||||
file=sys.stderr)
|
||||
else:
|
||||
model = args.model
|
||||
base_url = args.base_url
|
||||
api_key = args.api_key
|
||||
# 解析運行規格（--config / --model 均支持逗號分隔多個）
|
||||
specs = parse_run_specs(args)
|
||||
multi = len(specs) > 1
|
||||
for spec in specs:
|
||||
if spec.profile is not None:
|
||||
print(f"使用配置 '{spec.label}'：model={spec.model}, base_url={spec.base_url}",
|
||||
file=sys.stderr)
|
||||
|
||||
# 支持从 .json 文件的 content 字段读取
|
||||
input_path = Path(args.input)
|
||||
if input_path.suffix.lower() == '.json':
|
||||
import json
|
||||
data = json.loads(input_path.read_text(encoding="utf-8"))
|
||||
text = data.get("content", "")
|
||||
if not text:
|
||||
|
|
@ -1513,43 +1660,76 @@ def main() -> None:
|
|||
else:
|
||||
text = input_path.read_text(encoding="utf-8")
|
||||
|
||||
start = time.perf_counter()
|
||||
result, client = run_pipeline(text, model, base_url, api_key,
|
||||
args.head_length, args.tail_length,
|
||||
args.entities_window, args.entities_max,
|
||||
args.analysis_window, args.analysis_max)
|
||||
elapsed = time.perf_counter() - start
|
||||
def run_and_emit(spec: RunSpec) -> str:
|
||||
"""跑單個模型並寫出其 YAML / cost / debug 文件，返回輸出路徑描述。"""
|
||||
log_prefix = f"[{spec.label}] " if multi else ""
|
||||
start = time.perf_counter()
|
||||
result, client = run_pipeline(
|
||||
text, spec.model, spec.base_url, spec.api_key,
|
||||
args.head_length, args.tail_length,
|
||||
args.entities_window, args.entities_max,
|
||||
args.analysis_window, args.analysis_max,
|
||||
log_prefix=log_prefix)
|
||||
elapsed = time.perf_counter() - start
|
||||
|
||||
# 成本統計：僅在 --cost 時輸出到 {summary_file_name}_cost.json
|
||||
if args.cost:
|
||||
cost = compute_cost(client, elapsed, profile)
|
||||
if args.out:
|
||||
cost_path = Path(args.out).with_name(Path(args.out).stem + "_cost.json")
|
||||
else:
|
||||
cost_path = input_path.with_name(input_path.stem + "_cost.json")
|
||||
cost_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
cost_path.write_text(json.dumps(cost, ensure_ascii=False, indent=2),
|
||||
encoding="utf-8")
|
||||
print(f"💰 成本統計已寫入 {cost_path}：耗時 {cost['elapsed_seconds']}s，"
|
||||
f"input={cost['input_tokens']} output={cost['output_tokens']} "
|
||||
f"total_cost={cost['total_cost']} {cost['price_unit'] or ''}",
|
||||
file=sys.stderr)
|
||||
out_path = build_out_path(args, input_path, spec.label, multi)
|
||||
|
||||
if args.debug_dump:
|
||||
debug_path = Path(args.debug_dump)
|
||||
debug_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
debug_path.write_text(
|
||||
json.dumps(result, ensure_ascii=False, indent=2),
|
||||
encoding="utf-8")
|
||||
# 成本統計：僅在 --cost 時輸出到 {輸出文件名}_cost.json
|
||||
if args.cost:
|
||||
cost = compute_cost(client, elapsed, spec.profile)
|
||||
cost_path = build_cost_path(out_path, input_path, spec.label, multi)
|
||||
cost_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
cost_path.write_text(json.dumps(cost, ensure_ascii=False, indent=2),
|
||||
encoding="utf-8")
|
||||
print(f"{log_prefix}💰 成本統計已寫入 {cost_path}：耗時 {cost['elapsed_seconds']}s，"
|
||||
f"input={cost['input_tokens']} output={cost['output_tokens']} "
|
||||
f"total_cost={cost['total_cost']} {cost['price_unit'] or ''}",
|
||||
file=sys.stderr)
|
||||
|
||||
yaml_str = to_yaml(result)
|
||||
if args.out:
|
||||
out_path = Path(args.out)
|
||||
out_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
out_path.write_text(yaml_str, encoding="utf-8")
|
||||
print(f"\n✅ 已寫入 {args.out}", file=sys.stderr)
|
||||
else:
|
||||
# debug dump（原始 JSON）
|
||||
debug_path = build_debug_path(args, spec.label, multi)
|
||||
if debug_path is not None:
|
||||
debug_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
debug_path.write_text(json.dumps(result, ensure_ascii=False, indent=2),
|
||||
encoding="utf-8")
|
||||
|
||||
# YAML 輸出
|
||||
yaml_str = to_yaml(result)
|
||||
if out_path is not None:
|
||||
out_path.parent.mkdir(parents=True, exist_ok=True)
|
||||
out_path.write_text(yaml_str, encoding="utf-8")
|
||||
print(f"{log_prefix}✅ 已寫入 {out_path}", file=sys.stderr)
|
||||
return str(out_path)
|
||||
print(yaml_str)
|
||||
return "(stdout)"
|
||||
|
||||
if multi and args.max_workers != 1:
|
||||
# 並發執行：每個模型一個線程，日誌以 [標籤] 前綴區分
|
||||
workers = args.max_workers if args.max_workers > 0 else len(specs)
|
||||
print(f"⏳ 同時運行 {len(specs)} 個模型（並發 {workers}）："
|
||||
f"{[s.label for s in specs]}", file=sys.stderr)
|
||||
summary: list[tuple[str, str]] = []
|
||||
with ThreadPoolExecutor(max_workers=workers) as ex:
|
||||
futures = {ex.submit(run_and_emit, spec): spec for spec in specs}
|
||||
for fut in as_completed(futures):
|
||||
spec = futures[fut]
|
||||
try:
|
||||
summary.append((spec.label, fut.result()))
|
||||
except Exception as e:
|
||||
print(f"[{spec.label}] ❌ 運行失敗：{e}", file=sys.stderr)
|
||||
summary.append((spec.label, f"FAILED: {e}"))
|
||||
print("\n=== 多模型運行結果 ===", file=sys.stderr)
|
||||
for label, out in sorted(summary):
|
||||
print(f" {label:30s} → {out}", file=sys.stderr)
|
||||
else:
|
||||
# 單模型，或多模型但顯式 --max-workers 1 順序執行
|
||||
for spec in specs:
|
||||
try:
|
||||
run_and_emit(spec)
|
||||
except Exception as e:
|
||||
if not multi:
|
||||
raise
|
||||
print(f"[{spec.label}] ❌ 運行失敗：{e}", file=sys.stderr)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
|
|
|||
Loading…
Reference in New Issue