Merge pull request #605 from seehi/feature-upgrade-langchain

Upgrade langchain to support new openai

examples/search_kb.py

@@ -5,12 +5,13 @@
 """
 import asyncio
 
-from metagpt.actions import Action
+from langchain.embeddings import OpenAIEmbeddings
+
+from metagpt.config import CONFIG
 from metagpt.const import DATA_PATH
 from metagpt.document_store import FaissStore
 from metagpt.logs import logger
 from metagpt.roles import Sales
-from metagpt.schema import Message
 
 """ example.json, e.g.
 [
@@ -26,14 +27,15 @@ from metagpt.schema import Message
 """
 
 
+def get_store():
+    embedding = OpenAIEmbeddings(openai_api_key=CONFIG.openai_api_key, openai_api_base=CONFIG.openai_base_url)
+    return FaissStore(DATA_PATH / "example.json", embedding=embedding)
+
+
 async def search():
-    store = FaissStore(DATA_PATH / "example.json")
-    role = Sales(profile="Sales", store=store)
-    role._watch({Action})
-    queries = [
-        Message(content="Which facial cleanser is good for oily skin?", cause_by=Action),
-        Message(content="Is L'Oreal good to use?", cause_by=Action),
-    ]
+    role = Sales(profile="Sales", store=get_store())
+    queries = ["Which facial cleanser is good for oily skin?", "Is L'Oreal good to use?"]
+
     for query in queries:
         logger.info(f"User: {query}")
         result = await role.run(query)

metagpt/actions/search_and_summarize.py

@@ -5,7 +5,7 @@
 @Author  : alexanderwu
 @File    : search_google.py
 """
-from typing import Optional
+from typing import Any, Optional
 
 import pydantic
 from pydantic import Field, root_validator
@@ -111,7 +111,7 @@ class SearchAndSummarize(Action):
     llm: BaseGPTAPI = Field(default_factory=LLM)
     config: None = Field(default_factory=Config)
     engine: Optional[SearchEngineType] = CONFIG.search_engine
-    search_func: Optional[str] = None
+    search_func: Optional[Any] = None
     search_engine: SearchEngine = None
 
     result = ""

metagpt/document_store/base_store.py

@@ -33,6 +33,7 @@ class LocalStore(BaseStore, ABC):
             raise FileNotFoundError
         self.config = Config()
         self.raw_data_path = raw_data_path
+        self.fname = self.raw_data_path.stem
         if not cache_dir:
             cache_dir = raw_data_path.parent
         self.cache_dir = cache_dir
@@ -40,10 +41,9 @@ class LocalStore(BaseStore, ABC):
         if not self.store:
             self.store = self.write()
 
-    def _get_index_and_store_fname(self):
-        fname = self.raw_data_path.name.split(".")[0]
-        index_file = self.cache_dir / f"{fname}.index"
-        store_file = self.cache_dir / f"{fname}.pkl"
+    def _get_index_and_store_fname(self, index_ext=".index", pkl_ext=".pkl"):
+        index_file = self.cache_dir / f"{self.fname}{index_ext}"
+        store_file = self.cache_dir / f"{self.fname}{pkl_ext}"
         return index_file, store_file
 
     @abstractmethod

metagpt/document_store/faiss_store.py

@@ -6,13 +6,12 @@
 @File    : faiss_store.py
 """
 import asyncio
-import pickle
 from pathlib import Path
 from typing import Optional
 
-import faiss
 from langchain.embeddings import OpenAIEmbeddings
 from langchain.vectorstores import FAISS
+from langchain_core.embeddings import Embeddings
 
 from metagpt.const import DATA_PATH
 from metagpt.document import IndexableDocument
@@ -21,35 +20,29 @@ from metagpt.logs import logger
 
 
 class FaissStore(LocalStore):
-    def __init__(self, raw_data_path: Path, cache_dir=None, meta_col="source", content_col="output"):
+    def __init__(
+        self, raw_data: Path, cache_dir=None, meta_col="source", content_col="output", embedding: Embeddings = None
+    ):
         self.meta_col = meta_col
         self.content_col = content_col
-        super().__init__(raw_data_path, cache_dir)
+        self.embedding = embedding or OpenAIEmbeddings()
+        super().__init__(raw_data, cache_dir)
 
     def _load(self) -> Optional["FaissStore"]:
-        index_file, store_file = self._get_index_and_store_fname()
+        index_file, store_file = self._get_index_and_store_fname(index_ext=".faiss")  # langchain FAISS using .faiss
+
         if not (index_file.exists() and store_file.exists()):
             logger.info("Missing at least one of index_file/store_file, load failed and return None")
             return None
-        index = faiss.read_index(str(index_file))
-        with open(str(store_file), "rb") as f:
-            store = pickle.load(f)
-        store.index = index
-        return store
+
+        return FAISS.load_local(self.raw_data_path.parent, self.embedding, self.fname)
 
     def _write(self, docs, metadatas):
-        store = FAISS.from_texts(docs, OpenAIEmbeddings(openai_api_version="2020-11-07"), metadatas=metadatas)
+        store = FAISS.from_texts(docs, self.embedding, metadatas=metadatas)
         return store
 
     def persist(self):
-        index_file, store_file = self._get_index_and_store_fname()
-        store = self.store
-        index = self.store.index
-        faiss.write_index(store.index, str(index_file))
-        store.index = None
-        with open(store_file, "wb") as f:
-            pickle.dump(store, f)
-        store.index = index
+        self.store.save_local(self.raw_data_path.parent, self.fname)
 
     def search(self, query, expand_cols=False, sep="\n", *args, k=5, **kwargs):
         rsp = self.store.similarity_search(query, k=k, **kwargs)

metagpt/roles/sales.py

@@ -8,7 +8,8 @@
 
 from typing import Optional
 
-from metagpt.actions import SearchAndSummarize
+from metagpt.actions import SearchAndSummarize, UserRequirement
+from metagpt.document_store.base_store import BaseStore
 from metagpt.roles import Role
 from metagpt.tools import SearchEngineType
 
@@ -23,7 +24,7 @@ class Sales(Role):
     "but pretend to be what I know. Note that each of my replies will be replied in the tone of a "
     "professional guide"
 
-    store: Optional[str] = None
+    store: Optional[BaseStore] = None
 
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
@@ -35,3 +36,4 @@ class Sales(Role):
         else:
             action = SearchAndSummarize()
         self._init_actions([action])
+        self._watch([UserRequirement])

requirements.txt

@@ -11,7 +11,7 @@ typer
 # godot==0.1.1
 # google_api_python_client==2.93.0
 lancedb==0.1.16
-langchain==0.0.231
+langchain==0.0.352
 loguru==0.6.0
 meilisearch==0.21.0
 numpy==1.24.3