Feat: Use data pipeline to visualize the parsing configuration of the knowledge base (#10423)

### What problem does this PR solve?

#9869

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

---------

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rag/flow/extractor/extractor.py

@@ -0,0 +1,63 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+import random
+from copy import deepcopy
+from agent.component.llm import LLMParam, LLM
+from rag.flow.base import ProcessBase, ProcessParamBase
+
+
+class ExtractorParam(ProcessParamBase, LLMParam):
+    def __init__(self):
+        super().__init__()
+        self.field_name = ""
+
+    def check(self):
+        super().check()
+        self.check_empty(self.field_name, "Result Destination")
+
+
+class Extractor(ProcessBase, LLM):
+    component_name = "Extractor"
+
+    async def _invoke(self, **kwargs):
+        self.set_output("output_format", "chunks")
+        self.callback(random.randint(1, 5) / 100.0, "Start to generate.")
+        inputs = self.get_input_elements()
+        chunks = []
+        chunks_key = ""
+        args = {}
+        for k, v in inputs.items():
+            args[k] = v["value"]
+            if isinstance(args[k], list):
+                chunks = deepcopy(args[k])
+                chunks_key = k
+
+        if chunks:
+            prog = 0
+            for i, ck in enumerate(chunks):
+                args[chunks_key] = ck["text"]
+                msg, sys_prompt = self._sys_prompt_and_msg([], args)
+                msg.insert(0, {"role": "system", "content": sys_prompt})
+                ck[self._param.field_name] = self._generate(msg)
+                prog += 1./len(chunks)
+                if i % (len(chunks)//100+1) == 1:
+                    self.callback(prog, f"{i+1} / {len(chunks)}")
+            self.set_output("chunks", chunks)
+        else:
+            msg, sys_prompt = self._sys_prompt_and_msg([], args)
+            msg.insert(0, {"role": "system", "content": sys_prompt})
+            self.set_output("chunks", [{self._param.field_name: self._generate(msg)}])
+
+