feat: rename retrieve reference; add nanobot llm;

core/config.py

@@ -118,6 +118,9 @@ LLM = {
             base_url=f"{base_fastgpt_url}/api/v1", api_key=reflect_retry_api_key
         )
     ),
+    "nanobot_llm": LLMConfig(
+        base_url="http://172.21.107.80:19090/v1", api_key='none', model="Qwen3.5-122B-A10B-AWQ"
+    ),
 }
 doc_support_formats = [".docx", ".doc", ".wps"]
 pdf_support_formats = [".txt", ".md", ".pdf"]

core/tools/retrieve_reference.py → core/tools/rules_retrieve_reference.py

@@ -9,8 +9,8 @@ from core.tool import ToolBase, tool, tool_func
 from utils.excel_util import ExcelUtil
 
 
-@tool("retrieve_reference", "审查参考检索")
-class RetrieveReferenceTool(ToolBase):
+@tool("rules_retrieve_reference", "审查参考检索")
+class RulesRetrieveReferenceTool(ToolBase):
     def __init__(self) -> None:
         self.default_ruleset_id = DEFAULT_RULESET_ID
         self.column_map = {
@@ -72,7 +72,7 @@ class RetrieveReferenceTool(ToolBase):
 
 
 if __name__ == "__main__":
-    tool = RetrieveReferenceTool()
+    tool = RulesRetrieveReferenceTool()
     result = tool.run(ruleset_id="金盘", routed_rule_titles=None)
     for rule in result.get("rules", []):
         print(f"Rule Title: {rule.get('title')}")

core/tools/segment_llm.py

@@ -13,17 +13,20 @@ class LLMTool(ToolBase):
     """LLM-backed processor: builds prompts, calls LLM, parses JSON."""
 
     def __init__(
-        self, system_prompt: str, llm_key: str = "fastgpt_segment_review"
+        self, system_prompt: str = None, llm_key: str = "fastgpt_segment_review"
     ) -> None:
         super().__init__()
         self.system_prompt = system_prompt
         self.llm = OpenAITool(LLM[llm_key], max_workers=MAX_WORKERS)
 
     def build_messages(self, user_content: str, system_content: str = None) -> List[Dict[str, str]]:
+        if system_content or self.system_prompt:
             return [
                 {"role": "system", "content": system_content or self.system_prompt},
                 {"role": "user", "content": user_content},
             ]
+        else:
+            return [{"role": "user", "content": user_content}]
 
     async def chat_async(self, messages: List[Dict[str, str]]):
         return await self.llm.chat(messages)
@@ -47,3 +50,8 @@ class LLMTool(ToolBase):
             return data[0] if data else {}
         except Exception:
             return {}
+
+if __name__ == "__main__":
+    tool = LLMTool(llm_key="nanobot_llm")
+    results = asyncio.run(tool.chat_async(tool.build_messages("列出工作目录")))
+    print(results)
\ No newline at end of file

main.py

@@ -26,7 +26,7 @@ from core.tools.segment_summary import SegmentSummaryTool
 from core.tools.segment_review import SegmentReviewTool
 from core.tools.segment_rule_router import SegmentRuleRouterTool
 from core.tools.rule_filter import LufaPartyRuleFilterTool
-from core.tools.retrieve_reference import RetrieveReferenceTool
+from core.tools.rules_retrieve_reference import RulesRetrieveReferenceTool
 from core.tools.reflect_retry import ReflectRetryTool
 from core.tools.segment_merger import SegmentMergerTool
 from core.tools.fact_merger import FactMergerTool
@@ -42,7 +42,7 @@ summary_tool = SegmentSummaryTool()
 review_tool = SegmentReviewTool()
 rule_router_tool = SegmentRuleRouterTool()
 lufa_party_rule_filter_tool = LufaPartyRuleFilterTool()
-reference_tool = RetrieveReferenceTool()
+rules_reference_tool = RulesRetrieveReferenceTool()
 reflect_tool = ReflectRetryTool()
 merger_tool = SegmentMergerTool()
 fact_merger_tool = FactMergerTool()
@@ -74,6 +74,7 @@ class DocumentParseResponse(BaseModel):
     ruleset_items: List[str]
     summary_names: List[str]
     text: Optional[str] = None
+    text_file_path: Optional[str] = None
     file_ext: Optional[str] = None
     file_name: Optional[str] = None
 
@@ -155,12 +156,14 @@ async def parse_document(payload: DocumentParseRequest) -> DocumentParseResponse
     # ocr
     await doc_obj.get_from_ocr()
     text = doc_obj.get_all_text()
+    text_file_path = Path(file_path).with_suffix(".txt").resolve()
+    text_file_path.write_text(text or "", encoding="utf-8")
     segment_ids = doc_obj.get_chunk_id_list()
     # 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 reference_tool.default_ruleset_id
-    ruleset_items = reference_tool.run(ruleset_id=ruleset_id).get("rules", [])
+    ruleset_id = payload.ruleset_id or rules_reference_tool.default_ruleset_id
+    ruleset_items = rules_reference_tool.run(ruleset_id=ruleset_id).get("rules", [])
     ruleset_review_items = [
         t
         for t in (r.get("title") for r in ruleset_items)
@@ -169,13 +172,14 @@ async def parse_document(payload: DocumentParseRequest) -> DocumentParseResponse
     summary_names = list(
         dict.fromkeys(
             s.strip()
-            for s in (r.get("summary") for r in ruleset_items)
+            for s in (r.get("summa  y") for r in ruleset_items)
             if isinstance(s, str) and s.strip()
         )
     )
     return DocumentParseResponse(
         conversation_id=payload.conversation_id,
         text=text,
+        text_file_path=str(text_file_path),
         segment_ids=segment_ids,
         ruleset_items=ruleset_review_items,
         summary_names=summary_names,
@@ -223,21 +227,21 @@ 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 reference_tool.default_ruleset_id
+    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 = reference_tool.run(ruleset_id=ruleset_id).get("rules", [])
+        all_rules = rules_reference_tool.run(ruleset_id=ruleset_id).get("rules", [])
         rules = [
             rule
             for rule in all_rules
             if str(rule.get("summary", "")).strip() in summary_names
         ]
     else:
-        rules = reference_tool.run(
+        rules = rules_reference_tool.run(
             ruleset_id=ruleset_id,
             routed_rule_titles=payload.routed_rule_titles,
         ).get("rules", [])
@@ -309,13 +313,13 @@ def review_segment(payload: SegmentReviewRequest) -> SegmentReviewResponse:
             detail=f"Segment text not found for id {payload.segment_id}: {exc}. Please parse document first.",
         )
 
-    ruleset_id = payload.ruleset_id or reference_tool.default_ruleset_id
-    rules = reference_tool.run(
+    ruleset_id = payload.ruleset_id or rules_reference_tool.default_ruleset_id
+    rules = rules_reference_tool.run(
         ruleset_id=ruleset_id,
         routed_rule_titles=payload.routed_rule_titles,
     ).get("rules", [])
     # 暂时不添加摘要看下结果
-    # summary_keywords = reference_tool.summary_keywords(rules)
+    # summary_keywords = rules_reference_tool.summary_keywords(rules)
     # context_summaries = store.search_facts(summary_keywords)
 
     result = review_tool.run(
@@ -378,8 +382,8 @@ def route_segment_rules(payload: SegmentReviewRequest) -> SegmentRuleRouterRespo
             detail=f"Segment text not found for id {payload.segment_id}: {exc}. Please parse document first.",
         )
 
-    ruleset_id = payload.ruleset_id or reference_tool.default_ruleset_id
-    rules = reference_tool.run(ruleset_id=ruleset_id).get("rules", [])
+    ruleset_id = payload.ruleset_id or rules_reference_tool.default_ruleset_id
+    rules = rules_reference_tool.run(ruleset_id=ruleset_id).get("rules", [])
 
     if use_lufa and rules:
         try:
@@ -458,8 +462,8 @@ class FactsMergerResponse(BaseModel):
 @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 reference_tool.default_ruleset_id
-    ruleset_items = reference_tool.run(ruleset_id=ruleset_id).get("rules", [])
+    ruleset_id = payload.ruleset_id or rules_reference_tool.default_ruleset_id
+    ruleset_items = rules_reference_tool.run(ruleset_id=ruleset_id).get("rules", [])
     rule = next(
         (r for r in ruleset_items if r.get("title") == payload.rule_title), None
     )
@@ -467,7 +471,7 @@ def reflect_review(payload: ReflectReviewRequest) -> ReflectReviewResponse:
         raise HTTPException(
             status_code=404, detail=f"Rule not found: {payload.rule_title}"
         )
-    summary_keywords = reference_tool.summary_keywords([rule])
+    summary_keywords = rules_reference_tool.summary_keywords([rule])
     context_summaries_facts = store.search_facts(summary_keywords)
     # 查找审查规则对应的 findings
     findings = [