1) FixBug

2) Add Documents abount TASK/TODO Refactor

src/component/common_environment/local_document.py

@@ -132,7 +132,7 @@ class MetaDatabase:
 
         create_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
         summary = metadata.get("summary", "")
-        catalogs = json.dumps(metadata.get("catalogs", {}))
+        catalogs = json.dumps(metadata.get("catalogs", {}),ensure_ascii=False)
         title = metadata.get("title","")
         tags = ','.join(metadata.get("tags", []))
 
@@ -151,7 +151,7 @@ class MetaDatabase:
 
         title = meta.get("title", "")
         summary = meta.get("summary", "")
-        catalogs = json.dumps(meta.get("catalogs", {}))
+        catalogs = json.dumps(meta.get("catalogs", {}),ensure_ascii=False)
         tags = ','.join(meta.get("tags", []))
 
         cursor.execute('''
@@ -224,7 +224,7 @@ class MetaDatabase:
     def query_docs_by_tag(self, tag: str) -> List[str]:
         conn = self._get_conn()
         cursor = conn.cursor()
-        tag_json = json.dumps(tag)  # 将标签转换为 JSON 字符串
+        tag_json = json.dumps(tag,ensure_ascii=False)  # 将标签转换为 JSON 字符串
         cursor.execute('''
             SELECT documents.doc_path
             FROM documents
@@ -450,7 +450,7 @@ class ParseLocalDocument:
 
         org_path = meta.get("original_path")
         known_obj["original_path"] = org_path
-        return f"# Known information:\n## Current directory structure:\n{kb_tree}\n## Knowlege Metadata:\n{json.dumps(known_obj)}\n"
+        return f"# Known information:\n## Current directory structure:\n{kb_tree}\n## Knowlege Metadata:\n{json.dumps(known_obj,ensure_ascii=False)}\n"
 
     def _token_len(self, text: str) -> int:
         return CustomAIAgent("", "gpt-4-1106-preview", self.token_limit).token_len(text=text)
@@ -563,7 +563,7 @@ class ParseLocalDocument:
                 if bookmarks:
                     catalogs = []
                     self._parse_pdf_bookmarks(bookmarks,catalogs)
-                    metadata["catalogs"] = json.dumps(catalogs)
+                    metadata["catalogs"] = json.dumps(catalogs,ensure_ascii=False)
             except Exception as e:
                 logger.warn("parse pdf bookmarks failed:%s",e)
 

src/component/common_environment/local_file_system.py

@@ -55,7 +55,7 @@ class FilesystemEnvironment(SimpleEnvironment):
                 item_type = "directory" if is_dir else "file"
                 items.append({"name": entry.name, "type": item_type})
 
-        return json.dumps(items)
+        return json.dumps(items,ensure_ascii=False)
     
     # inner_function
     async def read(self,path:str) -> str:
@@ -120,7 +120,7 @@ class FilesystemEnvironment(SimpleEnvironment):
         try:
             file_path = self.root_path + path
             stat = os.stat(file_path)
-            return json.dumps(stat)
+            return json.dumps(stat,ensure_ascii=False)
         except Exception as e:
             return str(e)
 

src/component/mail_environment/issue.py

@@ -106,7 +106,7 @@ class Issue:
             child = desc_list.pop()
             root["child"] = child
             root = child
-        return json.dumps(root)
+        return json.dumps(root,ensure_ascii=False)
 
 
     @classmethod

src/component/mail_environment/mail.py

@@ -32,7 +32,7 @@ class Mail:
             "date": self.date, 
             "content": self.content 
         }
-        return json.dumps(prompt)
+        return json.dumps(prompt,ensure_ascii=False)
     
     @classmethod
     def prompt_desc(cls) -> dict:

src/component/openai_node/open_ai_node.py

@@ -223,7 +223,7 @@ class OpenAI_ComputeNode(ComputeNode):
                                                         max_tokens=result_token,
                                                         )
                     else:
-                        logger.info(f"call openai {mode_name} prompts: \n\t {prompts} \nfunctions: \n\t{json.dumps(llm_inner_functions)}")
+                        logger.info(f"call openai {mode_name} prompts: \n\t {prompts} \nfunctions: \n\t{json.dumps(llm_inner_functions,ensure_ascii=False)}")
                         resp = await client.chat.completions.create(model=mode_name,
                                                             messages=prompts,
                                                             response_format = response_format,

src/component/openai_node/whisper_node.py

@@ -156,11 +156,11 @@ class WhisperComputeNode(ComputeNode):
                 result.result_str = text
                 result.result = text
             elif response_format == "json":
-                result.result_str = json.dumps({"text": text})
+                result.result_str = json.dumps({"text": text},ensure_ascii=False)
                 resp.text = text
                 result.result = resp
             elif response_format == "verbose_json":
-                result.result_str = json.dumps({"text": text, "segments": results})
+                result.result_str = json.dumps({"text": text, "segments": results},ensure_ascii=False)
                 latest_resp.text = text
                 latest_resp.segments = results
                 result.result = latest_resp
@@ -190,9 +190,9 @@ class WhisperComputeNode(ComputeNode):
             result.set_from_task(task)
             result.worker_id = self.node_id
             if response_format == "json":
-                result.result_str = json.dumps({"text": resp.text})
+                result.result_str = json.dumps({"text": resp.text},ensure_ascii=False)
             elif response_format == "verbose_json":
-                result.result_str = json.dumps({"text": resp.text, "segments": resp.segments})
+                result.result_str = json.dumps({"text": resp.text, "segments": resp.segments},ensure_ascii=False)
             elif response_format == "srt" or response_format == "vtt" or response_format == "text":
                 result.result_str = resp
             else: