simplify csv args (#4182)

docs/modules/indexes/retrievers/examples/chroma_self_query_retriever.ipynb

@@ -14,7 +14,7 @@
    "id": "68e75fb9",
    "metadata": {},
    "source": [
-    "## Creating a Pinecone index\n",
+    "## Creating a Chroma vectorstore\n",
     "First we'll want to create a Chroma VectorStore and seed it with some data. We've created a small demo set of documents that contain summaries of movies.\n",
     "\n",
     "NOTE: The self-query retriever requires you to have `lark` installed (`pip install lark`)"
@@ -46,7 +46,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "id": "bcbe04d9",
    "metadata": {},
    "outputs": [
@@ -77,13 +77,13 @@
    "id": "5ecaab6d",
    "metadata": {},
    "source": [
-    "# Creating our self-querying retriever\n",
+    "## Creating our self-querying retriever\n",
     "Now we can instantiate our retriever. To do this we'll need to provide some information upfront about the metadata fields that our documents support and a short description of the document contents."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "id": "86e34dbf",
    "metadata": {},
    "outputs": [],
@@ -124,13 +124,13 @@
    "id": "ea9df8d4",
    "metadata": {},
    "source": [
-    "# Testing it out\n",
+    "## Testing it out\n",
     "And now we can try actually using our retriever!"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "id": "38a126e9",
    "metadata": {},
    "outputs": [
@@ -150,7 +150,7 @@
        " Document(page_content='Leo DiCaprio gets lost in a dream within a dream within a dream within a ...', metadata={'year': 2010, 'director': 'Christopher Nolan', 'rating': 8.2})]"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -162,7 +162,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "id": "fc3f1e6e",
    "metadata": {},
    "outputs": [
@@ -180,7 +180,7 @@
        " Document(page_content='Three men walk into the Zone, three men walk out of the Zone', metadata={'year': 1979, 'rating': 9.9, 'director': 'Andrei Tarkovsky', 'genre': 'science fiction'})]"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -192,7 +192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "id": "b19d4da0",
    "metadata": {},
    "outputs": [
@@ -209,7 +209,7 @@
        "[Document(page_content='A bunch of normal-sized women are supremely wholesome and some men pine after them', metadata={'year': 2019, 'director': 'Greta Gerwig', 'rating': 8.3})]"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -221,7 +221,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "id": "f900e40e",
    "metadata": {},
    "outputs": [
@@ -238,7 +238,7 @@
        "[Document(page_content='Three men walk into the Zone, three men walk out of the Zone', metadata={'year': 1979, 'rating': 9.9, 'director': 'Andrei Tarkovsky', 'genre': 'science fiction'})]"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -250,7 +250,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "id": "12a51522",
    "metadata": {},
    "outputs": [
@@ -267,7 +267,7 @@
        "[Document(page_content='Toys come alive and have a blast doing so', metadata={'year': 1995, 'genre': 'animated'})]"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -276,6 +276,14 @@
     "# This example specifies a query and composite filter\n",
     "retriever.get_relevant_documents(\"What's a movie after 1990 but before 2005 that's all about toys, and preferably is animated\")"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "60110338",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -294,7 +302,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.9.1"
   }
  },
  "nbformat": 4,

docs/modules/indexes/retrievers/examples/contextual-compression.ipynb

@@ -363,7 +363,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.9.1"
   }
  },
  "nbformat": 4,

docs/modules/indexes/retrievers/examples/self_query_retriever.ipynb

@@ -95,7 +95,7 @@
    "id": "5ecaab6d",
    "metadata": {},
    "source": [
-    "# Creating our self-querying retriever\n",
+    "## Creating our self-querying retriever\n",
     "Now we can instantiate our retriever. To do this we'll need to provide some information upfront about the metadata fields that our documents support and a short description of the document contents."
    ]
   },
@@ -142,7 +142,7 @@
    "id": "ea9df8d4",
    "metadata": {},
    "source": [
-    "# Testing it out\n",
+    "## Testing it out\n",
     "And now we can try actually using our retriever!"
    ]
   },
@@ -320,7 +320,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.9.1"
   }
  },
  "nbformat": 4,

langchain/document_loaders/csv_loader.py

@@ -36,13 +36,7 @@ class CSVLoader(BaseLoader):
         self.file_path = file_path
         self.source_column = source_column
         self.encoding = encoding
-        if csv_args is None:
-            self.csv_args = {
-                "delimiter": csv.Dialect.delimiter,
-                "quotechar": csv.Dialect.quotechar,
-            }
-        else:
-            self.csv_args = csv_args
+        self.csv_args = csv_args or {}
 
     def load(self) -> List[Document]:
         """Load data into document objects."""