rag add chromadb save&load example

examples/rag_pipeline.py

@@ -3,10 +3,12 @@ import asyncio
 
 from pydantic import BaseModel
 
-from metagpt.const import EXAMPLE_DATA_PATH
+from metagpt.const import DATA_PATH, EXAMPLE_DATA_PATH
 from metagpt.rag.engines import SimpleEngine
 from metagpt.rag.schema import (
     BM25RetrieverConfig,
+    ChromaIndexConfig,
+    ChromaRetrieverConfig,
     FAISSRetrieverConfig,
     LLMRankerConfig,
 )
@@ -118,6 +120,30 @@ class RAGExample:
         player: Player = nodes[0].metadata["obj"]
         print(player)
 
+    async def rag_chromadb(self):
+        """This example show how to use chromadb. how to save and load index. will print something like:
+
+        Query Result:
+        Bob likes traveling.
+        """
+        self._print_title("RAG ChromaDB")
+
+        # save index
+        output_dir = DATA_PATH / "rag"
+        SimpleEngine.from_docs(
+            input_files=[TRAVEL_DOC_PATH],
+            retriever_configs=[ChromaRetrieverConfig(persist_path=output_dir)],
+        )
+
+        # load index
+        engine = SimpleEngine.from_index(
+            index_config=ChromaIndexConfig(persist_path=output_dir),
+        )
+
+        # query
+        answer = engine.query(TRAVEL_QUESTION)
+        self._print_result(answer, state="Query")
+
     @staticmethod
     def _print_title(title):
         print(f"{'#'*50} {title} {'#'*50}")
@@ -147,6 +173,7 @@ async def main():
     await e.rag_pipeline()
     await e.rag_add_docs()
     await e.rag_add_objs()
+    await e.rag_chromadb()
 
 
 if __name__ == "__main__":

metagpt/rag/engines/simple.py

@@ -100,7 +100,7 @@ class SimpleEngine(RetrieverQueryEngine):
         llm: LLM = None,
         retriever_configs: list[BaseRetrieverConfig] = None,
         ranker_configs: list[BaseRankerConfig] = None,
-    ):
+    ) -> "SimpleEngine":
         """Load from previously maintained"""
         index = get_index(index_config, embed_model=embed_model or get_rag_embedding())
         return cls._from_index(index, llm=llm, retriever_configs=retriever_configs, ranker_configs=ranker_configs)
@@ -112,7 +112,7 @@ class SimpleEngine(RetrieverQueryEngine):
         llm: LLM = None,
         retriever_configs: list[BaseRetrieverConfig] = None,
         ranker_configs: list[BaseRankerConfig] = None,
-    ):
+    ) -> "SimpleEngine":
         llm = llm or get_rag_llm()
         retriever = get_retriever(configs=retriever_configs, index=index)
         rankers = get_rankers(configs=ranker_configs, llm=llm)

requirements.txt

@@ -10,7 +10,7 @@ typer==0.9.0
 # godot==0.1.1
 # google_api_python_client==2.93.0  # Used by search_engine.py
 lancedb==0.4.0
-llama-index-core==0.10.12
+llama-index-core==0.10.15
 llama-index-embeddings-azure-openai==0.1.6
 llama-index-embeddings-huggingface==0.1.3
 llama-index-embeddings-openai==0.1.5
@@ -70,7 +70,7 @@ typing-extensions==4.9.0
 socksio~=1.0.0
 gitignore-parser==0.1.9
 # connexion[uvicorn]~=3.0.5 # Used by metagpt/tools/openapi_v3_hello.py
-websockets~=12.0
+websockets~=11.0
 networkx~=3.2.1
 google-generativeai==0.3.2
 playwright>=1.26  # used at metagpt/tools/libs/web_scraping.py