array to list

Author: activesoull

README.md

@@ -264,13 +264,11 @@ retriever.get_relevant_documents("What are some movies about dinosaurs")
 ```
 
 Output:
-Output:
-
 ```
-[Document(metadata={'genre': 'science fiction', 'rating': array(7.7), 'year': array(1993)}, page_content='A bunch of scientists bring back dinosaurs and mayhem breaks loose'),
- Document(metadata={'genre': 'science fiction', 'rating': array(7.7), 'year': array(1993)}, page_content='A bunch of scientists bring back dinosaurs and mayhem breaks loose'),
- Document(metadata={'genre': 'animated', 'year': array(1995)}, page_content='Toys come alive and have a blast doing so'),
- Document(metadata={'genre': 'animated', 'year': array(1995)}, page_content='Toys come alive and have a blast doing so')]
+[Document(metadata={'genre': 'science fiction', 'rating': 7.7, 'year': 1993}, page_content='A bunch of scientists bring back dinosaurs and mayhem breaks loose'),
+ Document(metadata={'genre': 'science fiction', 'rating': 7.7, 'year': 1993}, page_content='A bunch of scientists bring back dinosaurs and mayhem breaks loose'),
+ Document(metadata={'genre': 'animated', 'year': 1995}, page_content='Toys come alive and have a blast doing so'),
+ Document(metadata={'genre': 'animated', 'year': 1995}, page_content='Toys come alive and have a blast doing so')]
 ```
 
 Now we can run a query to find movies that are above a certain ranking:
@@ -282,12 +280,11 @@ retriever.get_relevant_documents("I want to watch a movie rated higher than 8.5"
 
 Output:
 ```
-[Document(metadata={'director': 'Satoshi Kon', 'rating': array(8.6), 'year': array(2006)}, page_content='A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea'),
- Document(metadata={'director': 'Andrei Tarkovsky', 'genre': 'science fiction', 'rating': array(9.9), 'year': array(1979)}, page_content='Three men walk into the Zone, three men walk out of the Zone'),
- Document(metadata={'director': 'Satoshi Kon', 'rating': array(8.6), 'year': array(2006)}, page_content='A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea'),
- Document(metadata={'director': 'Andrei Tarkovsky', 'genre': 'science fiction', 'rating': array(9.9), 'year': array(1979)}, page_content='Three men walk into the Zone, three men walk out of the Zone'), Document(metadata={'director': 'Satoshi Kon', 'rating': array(8.6), 'year': array(2006)}, page_content='A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea'), Document(metadata={'director': 'Andrei Tarkovsky', 'genre': 'science fiction', 'rating': array(9.9), 'year': array(1979)}, page_content='Three men walk into the Zone, three men walk out of the Zone')]
+[Document(metadata={'director': 'Satoshi Kon', 'rating': 8.6, 'year': 2006}, page_content='A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea'),
+ Document(metadata={'director': 'Andrei Tarkovsky', 'genre': 'science fiction', 'rating': 9.9, 'year': 1979}, page_content='Three men walk into the Zone, three men walk out of the Zone'),
+ Document(metadata={'director': 'Satoshi Kon', 'rating': 8.6, 'year': 2006}, page_content='A psychologist / detective gets lost in a series of dreams within dreams within dreams and Inception reused the idea'),
+ Document(metadata={'director': 'Andrei Tarkovsky', 'genre': 'science fiction', 'rating': 9.9, 'year': 1979}, page_content='Three men walk into the Zone, three men walk out of the Zone')]
 ```
 
 
 Congrats! You just used the Deep Lake Vector Store in LangChain to create a Q&A App! 🎉
-

langchain_deeplake/vectorstores.py

@@ -158,7 +158,7 @@ def get_by_ids(self, ids: List[str], **kwargs: Any) -> List[Document]:
         docs = results["documents"][:]
         metadatas = results["metadata"][:]
         return [
-            Document(page_content=docs[i], metadata=metadatas[i].to_dict())
+            Document(page_content=docs[i], metadata=metadatas[i].to_dict(convert_numpy_to_list=True))
             for i in range(len(results))
         ]
 
@@ -250,7 +250,7 @@ def similarity_search_with_score(
         for i in range(len(results)):
             doc = Document(
                 page_content=docs_with_scores_columnar["documents"][i],
-                metadata=docs_with_scores_columnar["metadata"][i].to_dict(),
+                metadata=docs_with_scores_columnar["metadata"][i].to_dict(convert_numpy_to_list=True),
             )
             score = docs_with_scores_columnar["score"][i] if has_score else None
             docs_with_scores.append((doc, score))

pyproject.toml

@@ -6,21 +6,17 @@ build-backend = "poetry.core.masonry.api"
 name = "langchain-deeplake"
 version = "0.1.0"
 description = "An integration package connecting Deeplake and LangChain"
-authors = []
 readme = "README.md"
+authors = ["activeloop.ai <[email protected]>"]
 repository = "https://github.com/activeloopai/langchain-deeplake"
 license = "MIT"
 
 [tool.mypy]
 disallow_untyped_defs = "True"
 
-[tool.poetry.urls]
-"Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/deeplake"
-"Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22deeplake%3D%3D0%22&expanded=true"
-
 [tool.poetry.dependencies]
-python = ">=3.9,<4.0"
-langchain-core = "^0.3.15"
+python = ">=3.8,<4.0"
+langchain-core = ">=0.2.43"
 deeplake = ">=4.1"
 
 [tool.ruff.lint]