feat: add luchuan config;

a76f1b8c · ccran · 34f37d76 · a76f1b8c · a76f1b8c · a76f1b8c
Commit a76f1b8c authored Jul 25, 2026 by ccran
11 changed files
--- a/README.md
+++ b/README.md
@@ -138,7 +138,7 @@ result = requests.get(
 ## 🔐 安全说明
 - API Key 配置在 `core/config.py` 中
- 支持内外网环境切换 (`use_lufa` 参数)
+- 支持按平台切换运行环境（`platform` 参数，如 `"jp"`、`"lufa"`）
 - 临时文件自动清理
 ## 📊 数据格式

--- a/core/config.py
+++ b/core/config.py
-import platform
 from dataclasses import dataclass
-# 可配置运行参数
-use_docker = False
-# @dataclass
-# class LLMConfig:
-#     base_url: str = "https://api.deepseek.com/v1"
-#     api_key: str = "sk-3df81e63afe44ca39cbd7108d59bc91a"
-#     model: str = "deepseek-v4-pro"
-@dataclass
-class LLMConfig:
-    base_url: str = "http://172.21.107.80:9002/v1"
-    api_key: str = "none"
-    model: str = "Qwen2-72B-Instruct"
-# @dataclass
-# class LLMConfig:
-#     base_url: str = "http://192.168.252.71:9002/v1"
-#     api_key: str = "none"
-#     model: str = "Qwen2-72B-Instruct"
 # 最大分片数量
 min_single_chunk_size = 2000
 max_single_chunk_size = 100000
@@ -59,51 +35,61 @@ FILE_SUFFIX = "-审核批注"
 ## 关键参数**
 use_non_fastgpt_llm = False
-use_lufa = False
+# 运行平台。新增平台时在下方补充对应配置，并同步各平台专属提示词。
-use_jp_machine = True
+platform = "luchuan"
 debug_mode = False
 ## 关键参数**
 max_model_len = 131072
-ocr_url = 'http://192.168.252.71:8202/openapi/ocrUploadFile'
+ocr_url = ''
-if use_lufa:
+if platform == "lufa":
+    base_url = "http://192.168.252.71:9002/v1"
+    model = "Qwen2-72B-Instruct"
    outer_backend_url = "http://znkf.lgfzgroup.com:48081"
    base_fastgpt_url = "http://192.168.252.71:18089"
    base_backend_url = "http://192.168.252.71:48081"
+    ocr_url = 'http://192.168.252.71:8202/openapi/ocrUploadFile'
    segment_review_api_key = (
        "fastgpt-zMavJKKgqA9jRNHLXxzXCVZx1JXxfuNkH1p2qfLhtPfMp41UvdSQvt8"
    )
    reflect_retry_api_key = (
        "fastgpt-ao3al2vgfnArt9qi2bTpPeRHouCO7qngUZiQsIM1E2x91u22z65J"
    )
-else:
+elif platform == "jp":
-    if not use_jp_machine:
+    base_url = "http://172.21.107.80:9002/v1"
-        outer_backend_url = "http://218.77.58.8:48080"
+    model = "Qwen2-72B-Instruct"
-        base_fastgpt_url = "http://192.168.252.71:18088"
+    outer_backend_url = "https://172.21.107.45:48080"
-        base_backend_url = "http://192.168.252.71:48080"
+    base_fastgpt_url = "http://172.21.107.45:3030"
-    else:
+    base_backend_url = "http://172.21.107.45:1122"
-        outer_backend_url = "https://172.21.107.45:48080"
+    ocr_url = "http://172.21.107.45:8202/openapi/ocrUploadFile"
-        base_fastgpt_url = "http://172.21.107.45:3030"
-        base_backend_url = "http://172.21.107.45:1122"
-        ocr_url = "http://172.21.107.45:8202/openapi/ocrUploadFile"
    segment_review_api_key = (
        "fastgpt-vLu2JHAfqwEq5FUQhvATFDK0yDS6fs804v7KwWBMyU4sRrHzh4UGl89Zpa"
    )
    reflect_retry_api_key = (
        "fastgpt-abxzi4CC7SGuVdxDVFmhAFFQHqi6owK5YsIfXdvOMEAcpIhZWDPObTz2Xn"
    )
+elif platform == "luchuan":
+    base_url = "http://znkf.lgfzgroup.com:18089/qwen/v1"
+    model = "Qwen2-72B-Instruct"
+    outer_backend_url = "http://nas.hnluchuan.com:14124"
+    base_fastgpt_url = "http://nas.hnluchuan.com:14125"
+    base_backend_url = "http://192.168.0.70:1122"
+    ocr_url = "http://192.168.0.70:8202/openapi/ocrUploadFile"
+    segment_review_api_key = (
+        "fastgpt-oZs0FUIgkiCmJtNcsHqaQRPI93RHhevq0i3CNGSsJlzdw9hLzyeLeaPepiitb3Hy"
+    )
+    reflect_retry_api_key = (
+        "fastgpt-dZXQ5YF3OuVuVqWsgYB8UTXvC6NzjvfdWhvfxfxhIT1RcMv5OtlQSyq9BqhUC"
+    )
+else:
+    raise ValueError(f"Unsupported platform: {platform!r}")
+@dataclass
+class LLMConfig:
+    base_url: str = base_url
+    api_key: str = "none"
+    model: str = model
-# 项目根目录
-root_path = r"E:\PycharmProject\contract_review_agent"
-system = platform.system()
-if system == "Linux":
-    # root_path = "/data/home/ccran/contract_review_agent"
-    root_path = "/home/ccran/contract_review_agent"
-elif system == "Darwin":
-    root_path = "/Users/chenran/PycharmProjects/contract_review_agent"
-# docker设置
-if use_docker:
-    root_path = "/app"
 LLM = {
    "base_tool_llm": LLMConfig(),
    "fastgpt_segment_review": (

--- a/core/memory.py
+++ b/core/memory.py
@@ -11,7 +11,7 @@ from uuid import uuid4
 from utils.http_util import upload_file
 from utils.doc_util import DocBase
-from core.config import META_KEY, FILE_SUFFIX, use_lufa
+from core.config import META_KEY, FILE_SUFFIX, platform
 from core.finding_preprocessor import FindingPreprocessor
 from core.tools.memory_export_filter import MemoryExportFilter
@@ -468,7 +468,7 @@ class MemoryStore:
            for idx, f in enumerate(target_findings, start=1):
                segment_id = int(f.segment_id or 0)
                chunk_id = max(segment_id, 0)
-                if use_lufa:
+                if platform == "lufa":
                    suggest_parts = []
                    if f.risk_level:
                        suggest_parts.append(f"风险等级：{f.risk_level}")

--- a/core/tools/reflect_retry.py
+++ b/core/tools/reflect_retry.py
@@ -5,7 +5,7 @@ from typing import Dict, List, Optional, Any
 from core.tool import tool, tool_func
 from core.tools.segment_llm import LLMTool
-from core.config import use_lufa
+from core.config import platform
 REFLECT_SYSTEM_PROMPT_LF = """
 你是合同审查反思智能体（ReviewReflection）。
@@ -478,7 +478,7 @@ OUTPUT_FORMAT_SCHEMA = """
 @tool("reflect_retry", "反思重试质量闸")
 class ReflectRetryTool(LLMTool):
    def __init__(self) -> None:
-        if use_lufa:
+        if platform == "lufa":
            super().__init__(REFLECT_SYSTEM_PROMPT_LF, "fastgpt_reflect_retry")
        else:
            super().__init__(REFLECT_SYSTEM_PROMPT, "fastgpt_reflect_retry")
@@ -516,7 +516,7 @@ class ReflectRetryTool(LLMTool):
        #     return []
        user_content = (
-            REFLECT_USER_PROMPT_LF if use_lufa else REFLECT_USER_PROMPT
+            REFLECT_USER_PROMPT_LF if platform == "lufa" else REFLECT_USER_PROMPT
        ).format(
            rule=self._stringify_rule(rule),
            findings_json=json.dumps(base_findings, ensure_ascii=False),
@@ -525,7 +525,7 @@ class ReflectRetryTool(LLMTool):
            # TODO 不同规则可能有不同的反思思路提示，目前先不区分，后续可根据需要增加规则专属反思思路提示，如针对付款条款审查的反思思路提示、针对担保条款审查的反思思路提示等 --- IGNORE ---
            rule_reflection_prompt=None,
        ) + (
-            OUTPUT_FORMAT_SCHEMA_LF if use_lufa else OUTPUT_FORMAT_SCHEMA
+            OUTPUT_FORMAT_SCHEMA_LF if platform == "lufa" else OUTPUT_FORMAT_SCHEMA
        )
        messages = self.build_messages(user_content)

--- a/core/tools/rules_retrieve_reference.py
+++ b/core/tools/rules_retrieve_reference.py
@@ -38,20 +38,36 @@ class RulesRetrieveReferenceTool(ToolBase):
            "type": "object",
            "properties": {
                "ruleset_id": {"type": "string"},
+                "rules": {"type": "array", "items": {"type": "object"}},
                "routed_rule_titles": {"type": "array", "items": {"type": "string"}},
            },
            "required": [],
        }
    )
    def run(
-        self, ruleset_id: str = "", routed_rule_titles: List[str] | None = None
+        self,
+        ruleset_id: str = "",
+        rules: List[Dict[str, Any]] | None = None,
+        routed_rule_titles: List[str] | None = None,
    ) -> Dict[str, Any]:
-        target_ruleset_id = ruleset_id or self.default_ruleset_id
+        """Retrieve rules from a ruleset or from caller-supplied rules.
-        full_rules = (
-            self.rulesets.get(target_ruleset_id)
+        A non-empty ``ruleset_id`` keeps the historical ruleset lookup behavior.
-            or self.rulesets.get(self.default_ruleset_id, [])
+        When it is empty, a supplied ``rules`` list is used directly.  If neither
-            or []
+        is supplied, the default ruleset remains the backwards-compatible fallback.
-        )
+        """
+        target_ruleset_id = (ruleset_id or "").strip()
+        if target_ruleset_id:
+            full_rules = (
+                self.rulesets.get(target_ruleset_id)
+                or self.rulesets.get(self.default_ruleset_id, [])
+                or []
+            )
+        elif rules is not None:
+            full_rules = [rule for rule in rules if isinstance(rule, dict)]
+        else:
+            target_ruleset_id = self.default_ruleset_id
+            full_rules = self.rulesets.get(target_ruleset_id, []) or []
        if routed_rule_titles is None:
            rules = full_rules
        else:

--- a/core/tools/segment_review.py
+++ b/core/tools/segment_review.py
@@ -5,7 +5,7 @@ import json
 from typing import Dict, List, Optional
 from core.tool import tool, tool_func
-from core.config import use_lufa
+from core.config import platform
 from core.tools.segment_llm import LLMTool
 import re
 from loguru import logger
@@ -281,7 +281,7 @@ def _has_evidence(f: Dict) -> bool:
 @tool("segment_review", "合同分段审查")
 class SegmentReviewTool(LLMTool):
    def __init__(self):
-        if use_lufa:
+        if platform == "lufa":
            super().__init__(REVIEW_SYSTEM_PROMPT_LF)
        else:
            super().__init__(REVIEW_SYSTEM_PROMPT_JP)
@@ -349,7 +349,7 @@ class SegmentReviewTool(LLMTool):
        context_memories: Optional[List[Dict]],
    ) -> List[Dict[str, str]]:
        user_content = (
-            REVIEW_USER_PROMPT_JP if not use_lufa else REVIEW_USER_PROMPT_LF
+            REVIEW_USER_PROMPT_LF if platform == "lufa" else REVIEW_USER_PROMPT_JP
        ).format(
            segment_id=segment_id,
            segment_text=segment_text,
@@ -358,7 +358,7 @@ class SegmentReviewTool(LLMTool):
            # context_memories_json=json.dumps(context_memories or [], ensure_ascii=False),
            ruleset_text=self._stringify_rule(rule),
        ) + (
-            REVIEW_OUTPUT_SCHEMA_JP if not use_lufa else REVIEW_OUTPUT_SCHEMA_LF
+            REVIEW_OUTPUT_SCHEMA_LF if platform == "lufa" else REVIEW_OUTPUT_SCHEMA_JP
        )
        return self.build_messages(user_content)
@@ -373,7 +373,7 @@ class SegmentReviewTool(LLMTool):
    ) -> List[Dict[str, str]]:
        ruleset_text = "\n\n".join([self._stringify_rule(rule) for rule in rules])
        user_content = (
-            REVIEW_USER_PROMPT_JP if not use_lufa else REVIEW_USER_PROMPT_LF
+            REVIEW_USER_PROMPT_LF if platform == "lufa" else REVIEW_USER_PROMPT_JP
        ).format(
            segment_id=segment_id,
            segment_text=segment_text,
@@ -383,7 +383,7 @@ class SegmentReviewTool(LLMTool):
                context_memories or [], ensure_ascii=False
            ),
            ruleset_text=ruleset_text,
-        ) + (REVIEW_OUTPUT_SCHEMA_JP if not use_lufa else REVIEW_OUTPUT_SCHEMA_LF)
+        ) + (REVIEW_OUTPUT_SCHEMA_LF if platform == "lufa" else REVIEW_OUTPUT_SCHEMA_JP)
        return self.build_messages(user_content)
    async def _evaluate_rules_async(

--- a/data/batch/batch.py
+++ b/data/batch/batch.py
@@ -13,13 +13,13 @@ from loguru import logger
 from utils.common_util import random_str
 from utils.http_util import upload_file, fastgpt_openai_chat, download_file
-use_lufa = False
+platform = "jp"
 batch_size = 5
 def get_params():
    output_suffix = f"{time.strftime('%Y%m%d-%H%M%S')}-{time.time_ns() % 1_000_000:06d}"
-    if not use_lufa:
+    if platform == "jp":
        return {
            "suffix": "_麓发迁移",
            "batch_size": batch_size,
@@ -38,18 +38,21 @@ def get_params():
            # "token": "fastgpt-n74gGX5ZqLT6o1ysMBSGUTjIciswYOWDRfQ75krMkE5gDVDkpzsbz8u",
        }
-    return {
+    if platform == "lufa":
-        "suffix": "_麓发",
+        return {
-        "batch_size": batch_size,
+            "suffix": "_麓发",
-        "batch_input_dir_path": "4.24测财务合同审核",
+            "batch_size": batch_size,
-        "batch_output_dir_path": f"4.24测财务合同审核-batch-{output_suffix}",
+            "batch_input_dir_path": "4.24测财务合同审核",
-        # 麓发fastgpt接口
+            "batch_output_dir_path": f"4.24测财务合同审核-batch-{output_suffix}",
-        "url": "http://192.168.252.71:18089/api/v1/chat/completions",
+            # 麓发fastgpt接口
-        # 麓发合同审查生产token
+            "url": "http://192.168.252.71:18089/api/v1/chat/completions",
-        # "token": "fastgpt-ek3Z6PxI6sXgYc0jxzZ5bVGqrxwM6aVyfSmA6JVErJYBMr2KmYxrHwEUOIMSYz",
+            # 麓发合同审查生产token
-        # 麓发合同审查生产token-标准化
+            # "token": "fastgpt-ek3Z6PxI6sXgYc0jxzZ5bVGqrxwM6aVyfSmA6JVErJYBMr2KmYxrHwEUOIMSYz",
-        "token": "fastgpt-mg5tQUgreJeF7peoOr5zqP0NR4EIrfS2bEVXge6FUL94Suu1TvEMR1sGNRSiV",
+            # 麓发合同审查生产token-标准化
-    }
+            "token": "fastgpt-mg5tQUgreJeF7peoOr5zqP0NR4EIrfS2bEVXge6FUL94Suu1TvEMR1sGNRSiV",
+        }
+    raise ValueError(f"Unsupported platform: {platform!r}")
 def extract_url(text):

--- a/main.py
+++ b/main.py
@@ -19,7 +19,7 @@ from core.config import (
    pdf_support_formats,
    MERGE_RULE_PROMPT,
    FULL_TEXT_SEGMENT_ID,
-    use_lufa,
+    platform,
    max_model_len,
    debug_mode,
 )
@@ -45,7 +45,7 @@ summary_tool = SegmentSummaryTool()
 review_tool = SegmentReviewTool()
 rule_router_tool = SegmentRuleRouterTool()
 rule_filter_tool = RuleFilterTool()
-# if use_lufa:
+# if platform == "lufa":
 #     rule_filter_tool = LufaPartyRuleFilterTool()
 # else:
 #     rule_filter_tool = JpRuleFilterTool()
@@ -60,12 +60,12 @@ party_role_tool = PartyRoleTool()
 nanobot_llm_tool = LLMTool(llm_key="nanobot_llm")
-@app.post("/sleep")
+class TestModel(BaseModel):
-def sleep(t: int):
+    role: str
-    import time
+    rules: List[Dict]
+@app.post("/test")
-    time.sleep(t)
+def test(t: TestModel):
-    return {"res": f"sleep over for {t} seconds."}
+    return t
 class NanobotLLMChatRequest(BaseModel):
@@ -100,7 +100,11 @@ class DocumentParseRequest(BaseModel):
    conversation_id: str
    urls: List[str] = Field(..., description="File download url")
    file_ext: Optional[str] = None
-    ruleset_id: Optional[str] = "通用"
+    ruleset_id: Optional[str] = None
+    rules: Optional[List[Dict[str, Any]]] = Field(
+        default=None,
+        description="规则集为空时直接使用的规则列表",
+    )
 class DocumentParseResponse(BaseModel):
@@ -135,6 +139,19 @@ class PartyRoleResponse(BaseModel):
    reason: Optional[str] = ""
+def retrieve_rules(
+    ruleset_id: Optional[str] = None,
+    rules: Optional[List[Dict[str, Any]]] = None,
+    routed_rule_titles: Optional[List[str]] = None,
+) -> Dict[str, Any]:
+    """Resolve rules from a ruleset or directly from the request payload."""
+    return rules_reference_tool.run(
+        ruleset_id=ruleset_id or "",
+        rules=rules,
+        routed_rule_titles=routed_rule_titles,
+    )
 @app.post("/rulesets/route", response_model=RulesetRouteResponse)
 def route_ruleset(payload: RulesetRouteRequest) -> RulesetRouteResponse:
    question = (payload.question or "").strip()
@@ -197,8 +214,10 @@ async def parse_document(payload: DocumentParseRequest) -> DocumentParseResponse
    # TODO: FastGPT BUG segment_ids必须从1开始，0开始会缺少第一段文本，后续需要修复
    segment_ids = [idx + 1 for idx in segment_ids]
    # get ruleset items
-    ruleset_id = payload.ruleset_id or rules_reference_tool.default_ruleset_id
+    ruleset_items = retrieve_rules(
-    ruleset_items = rules_reference_tool.run(ruleset_id=ruleset_id).get("rules", [])
+        ruleset_id=payload.ruleset_id,
+        rules=payload.rules,
+    ).get("rules", [])
    ruleset_review_items = [
        t
        for t in (r.get("title") for r in ruleset_items)
@@ -207,7 +226,7 @@ async def parse_document(payload: DocumentParseRequest) -> DocumentParseResponse
    summary_names = list(
        dict.fromkeys(
            s.strip()
-            for s in (r.get("summa  y") for r in ruleset_items)
+            for s in (r.get("summary") for r in ruleset_items)
            if isinstance(s, str) and s.strip()
        )
    )
@@ -230,7 +249,8 @@ class SegmentSummaryRequest(BaseModel):
    conversation_id: str
    segment_id: int
    party_role: Optional[str] = ""
-    ruleset_id: Optional[str] = "通用"
+    ruleset_id: Optional[str] = None
+    rules: Optional[List[Dict[str, Any]]] = None
    routed_rule_titles: Optional[List[str]] = None
    routed_summary_names: Optional[List[str]] = None
    file_ext: str
@@ -262,22 +282,25 @@ def summarize_facts(payload: SegmentSummaryRequest) -> SegmentSummaryResponse:
            detail=f"Segment text not found for id {payload.segment_id}: {exc}. Please parse document first.",
        )
-    ruleset_id = payload.ruleset_id or rules_reference_tool.default_ruleset_id
    if payload.routed_summary_names is not None:
        summary_names = {
            name.strip()
            for name in payload.routed_summary_names
            if isinstance(name, str) and name.strip()
        }
-        all_rules = rules_reference_tool.run(ruleset_id=ruleset_id).get("rules", [])
+        all_rules = retrieve_rules(
+            ruleset_id=payload.ruleset_id,
+            rules=payload.rules,
+        ).get("rules", [])
        rules = [
            rule
            for rule in all_rules
            if str(rule.get("summary", "")).strip() in summary_names
        ]
    else:
-        rules = rules_reference_tool.run(
+        rules = retrieve_rules(
-            ruleset_id=ruleset_id,
+            ruleset_id=payload.ruleset_id,
+            rules=payload.rules,
            routed_rule_titles=payload.routed_rule_titles,
        ).get("rules", [])
    result = summary_tool.run(
@@ -310,7 +333,8 @@ class SegmentReviewRequest(BaseModel):
        description="segment_id 为 FULL_TEXT_SEGMENT_ID 时用于审查的全文文本",
    )
    party_role: Optional[str] = ""
-    ruleset_id: Optional[str] = "通用"
+    ruleset_id: Optional[str] = None
+    rules: Optional[List[Dict[str, Any]]] = None
    routed_rule_titles: Optional[List[str]] = None
    file_ext: Optional[str] = None
    context_memories: Optional[List[Dict]] = None
@@ -380,9 +404,9 @@ def review_segment(payload: SegmentReviewRequest) -> SegmentReviewResponse:
    store = get_cached_memory(payload.conversation_id)
    segment_idx, segment_text, _ = _resolve_review_segment(payload)
-    ruleset_id = payload.ruleset_id or rules_reference_tool.default_ruleset_id
+    rules = retrieve_rules(
-    rules = rules_reference_tool.run(
+        ruleset_id=payload.ruleset_id,
-        ruleset_id=ruleset_id,
+        rules=payload.rules,
        routed_rule_titles=payload.routed_rule_titles,
    ).get("rules", [])
    # 暂时不添加摘要看下结果
@@ -435,8 +459,11 @@ def review_segment(payload: SegmentReviewRequest) -> SegmentReviewResponse:
 def route_segment_rules(payload: SegmentReviewRequest) -> SegmentRuleRouterResponse:
    segment_idx, segment_text, doc_obj = _resolve_review_segment(payload)
-    ruleset_id = payload.ruleset_id or rules_reference_tool.default_ruleset_id
+    rules_result = retrieve_rules(
-    rules = rules_reference_tool.run(ruleset_id=ruleset_id).get("rules", [])
+        ruleset_id=payload.ruleset_id,
+        rules=payload.rules,
+    )
+    rules = rules_result.get("rules", [])
    try:
        total_segments = len(doc_obj.get_chunk_id_list() or [])
@@ -470,7 +497,7 @@ def route_segment_rules(payload: SegmentReviewRequest) -> SegmentRuleRouterRespo
    return SegmentRuleRouterResponse(
        conversation_id=payload.conversation_id,
        segment_id=payload.segment_id,
-        ruleset_id=ruleset_id,
+        ruleset_id=rules_result.get("ruleset_id", ""),
        route_by=result.get("route_by", payload.route_by),
        routed_rule_titles=routed_rule_titles,
        routed_summary_names=result.get("routed_summary_names", []),
@@ -482,12 +509,14 @@ def route_segment_rules(payload: SegmentReviewRequest) -> SegmentRuleRouterRespo
 class ReflectReviewRequest(BaseModel):
    conversation_id: str
    party_role: str
-    ruleset_id: Optional[str] = "通用"
+    ruleset_id: Optional[str] = None
+    rules: Optional[List[Dict[str, Any]]] = None
    rule_title: str
 class RuleStringifyRequest(BaseModel):
-    ruleset_id: Optional[str] = "通用"
+    ruleset_id: Optional[str] = None
+    rules: Optional[List[Dict[str, Any]]] = None
    rule_title: str
@@ -530,8 +559,11 @@ class FactsMergerResponse(BaseModel):
 @app.post("/rules/stringify", response_model=RuleStringifyResponse)
 def stringify_rule(payload: RuleStringifyRequest) -> RuleStringifyResponse:
-    ruleset_id = payload.ruleset_id or rules_reference_tool.default_ruleset_id
+    rules_result = retrieve_rules(
-    ruleset_items = rules_reference_tool.run(ruleset_id=ruleset_id).get("rules", [])
+        ruleset_id=payload.ruleset_id,
+        rules=payload.rules,
+    )
+    ruleset_items = rules_result.get("rules", [])
    rule = next(
        (r for r in ruleset_items if r.get("title") == payload.rule_title), None
    )
@@ -541,7 +573,7 @@ def stringify_rule(payload: RuleStringifyRequest) -> RuleStringifyResponse:
        )
    return RuleStringifyResponse(
-        ruleset_id=ruleset_id,
+        ruleset_id=rules_result.get("ruleset_id", ""),
        rule_title=payload.rule_title,
        rule_string=reflect_tool._stringify_rule(rule),
    )
@@ -550,8 +582,10 @@ def stringify_rule(payload: RuleStringifyRequest) -> RuleStringifyResponse:
 @app.post("/segments/review/reflect", response_model=ReflectReviewResponse)
 def reflect_review(payload: ReflectReviewRequest) -> ReflectReviewResponse:
    store = get_cached_memory(payload.conversation_id)
-    ruleset_id = payload.ruleset_id or rules_reference_tool.default_ruleset_id
+    ruleset_items = retrieve_rules(
-    ruleset_items = rules_reference_tool.run(ruleset_id=ruleset_id).get("rules", [])
+        ruleset_id=payload.ruleset_id,
+        rules=payload.rules,
+    ).get("rules", [])
    rule = next(
        (r for r in ruleset_items if r.get("title") == payload.rule_title), None
    )
@@ -799,12 +833,10 @@ def export_facts_memory(payload: FactsMemoryExportRequest) -> FactsMemoryExportR
 if __name__ == "__main__":
-    from core.config import use_lufa
+    if platform == "lufa" or platform == "luchuan":
-    if use_lufa:
        port = 18168
    else:
        port = 18169
    if debug_mode:
        port += 10
-    uvicorn.run("main:app", host="0.0.0.0", port=port, log_level="info", reload=False)
+    uvicorn.run("main:app", host="0.0.0.0", port=port, log_level="info", reload=True)
--- a/requirements.txt
+++ b/requirements.txt
@@ -76,3 +76,5 @@ urllib3==2.6.3
 uvicorn==0.40.0
 wheel==0.45.1
 yarl==1.22.0
+spire-doc==14.6.1
+spire-pdf==12.6.2
\ No newline at end of file
--- a/utils/http_util.py
+++ b/utils/http_util.py
@@ -8,7 +8,7 @@ import requests
 from loguru import logger
 from requests_toolbelt import MultipartEncoder
-from core.config import base_fastgpt_url, base_backend_url, outer_backend_url
+from core.config import base_fastgpt_url, base_backend_url, outer_backend_url,platform
 def fastgpt_openai_chat(url, token, model, chat_id, file_url, text, stream=True):
@@ -58,7 +58,10 @@ def fastgpt_openai_chat(url, token, model, chat_id, file_url, text, stream=True)
 def upload_file(path, input_url_to_inner=True, output_url_to_inner=False) -> str:
    # 登录获取token
-    login_data = {"username": "admin", "password": "admin@jpai.com"}
+    if platform == "luchuan":
+        login_data = {"username": "chenran", "password": "CR@lgfz2026"}
+    else:
+        login_data = {"username": "admin", "password": "admin@jpai.com"}
    login_url = f"{base_backend_url}/admin-api/system/auth/login"
    response = requests.post(
        url=login_url,

--- a/utils/spire_word_util.py
+++ b/utils/spire_word_util.py
@@ -4,7 +4,7 @@ import re
 from thefuzz import fuzz
 from utils.doc_util import DocBase
 from utils.common_util import adjust_single_chunk_size
-from core.config import FULL_TEXT_SEGMENT_ID, use_lufa
+from core.config import FULL_TEXT_SEGMENT_ID
 import os