chore: import upstream snapshot with attribution

examples/rag/summary_extractor_example.py

@@ -0,0 +1,49 @@
+"""Summary extractor example.
+pre-requirements:
+    1. install openai python sdk
+    ```
+        pip install openai
+    ```
+    2. set openai key and base
+    ```
+        export OPENAI_API_KEY={your_openai_key}
+        export OPENAI_API_BASE={your_openai_base}
+    ```
+    or
+    ```
+        import os
+        os.environ["OPENAI_API_KEY"] = {your_openai_key}
+        os.environ["OPENAI_API_BASE"] = {your_openai_base}
+    ```
+Examples:
+    ..code-block:: shell
+        python examples/rag/summary_extractor_example.py
+"""
+
+import asyncio
+import os
+
+from dbgpt.configs.model_config import ROOT_PATH
+from dbgpt.model.proxy import OpenAILLMClient
+from dbgpt_ext.rag import ChunkParameters
+from dbgpt_ext.rag.assembler import SummaryAssembler
+from dbgpt_ext.rag.knowledge import KnowledgeFactory
+
+
+async def main():
+    file_path = os.path.join(ROOT_PATH, "docs/docs/awel/awel.md")
+    llm_client = OpenAILLMClient()
+    knowledge = KnowledgeFactory.from_file_path(file_path)
+    chunk_parameters = ChunkParameters(chunk_strategy="CHUNK_BY_SIZE")
+    assembler = SummaryAssembler.load_from_knowledge(
+        knowledge=knowledge,
+        chunk_parameters=chunk_parameters,
+        llm_client=llm_client,
+        model_name="gpt-3.5-turbo",
+    )
+    return await assembler.generate_summary()
+
+
+if __name__ == "__main__":
+    output = asyncio.run(main())
+    print(f"output: \n\n{output}")