lint

Author: eyurtsev

examples/migrate_pgvector_to_pgvectorstore.ipynb

@@ -280,6 +280,7 @@
    "outputs": [],
    "source": [
     "from langchain_core.embeddings import FakeEmbeddings\n",
+    "\n",
     "from langchain_postgres import PGVectorStore\n",
     "from langchain_postgres.utils.pgvector_migrator import amigrate_pgvector_collection\n",
     "\n",

examples/pg_vectorstore.ipynb

@@ -136,9 +136,10 @@
    },
    "outputs": [],
    "source": [
-    "from langchain_postgres import Column\n",
     "from sqlalchemy.exc import ProgrammingError\n",
     "\n",
+    "from langchain_postgres import Column\n",
+    "\n",
     "try:\n",
     "    await pg_engine.ainit_vectorstore_table(\n",
     "        table_name=TABLE_NAME,\n",
@@ -149,7 +150,7 @@
     "            Column(\"topic\", \"TEXT\"),\n",
     "        ],\n",
     "    )\n",
-    "except ProgrammingError as e:\n",
+    "except ProgrammingError:\n",
     "    # Catching the exception here\n",
     "    print(\"Table already exists. Skipping creation.\")"
    ]
@@ -191,7 +192,7 @@
    "source": [
     "from langchain_openai import OpenAIEmbeddings\n",
     "\n",
-    "embedding =  OpenAIEmbeddings(model=\"text-embedding-3-small\")"
+    "embedding = OpenAIEmbeddings(model=\"text-embedding-3-small\")"
    ]
   },
   {
@@ -226,7 +227,7 @@
     "    engine=pg_engine,\n",
     "    table_name=TABLE_NAME,\n",
     "    embedding_service=embedding,\n",
-    "    metadata_columns=[\"location\", \"topic\"]\n",
+    "    metadata_columns=[\"location\", \"topic\"],\n",
     ")"
    ]
   },
@@ -252,8 +253,8 @@
    "outputs": [],
    "source": [
     "import uuid\n",
-    "from langchain_core.documents import Document\n",
     "\n",
+    "from langchain_core.documents import Document\n",
     "\n",
     "docs = [\n",
     "    Document(\n",
@@ -388,7 +389,9 @@
    },
    "outputs": [],
    "source": [
-    "await vectorstore.asimilarity_search(\"birds\", filter={\"$or\": [{\"topic\": \"animals\"}, {\"location\": \"market\"}]})"
+    "await vectorstore.asimilarity_search(\n",
+    "    \"birds\", filter={\"$or\": [{\"topic\": \"animals\"}, {\"location\": \"market\"}]}\n",
+    ")"
    ]
   },
   {
@@ -410,7 +413,9 @@
    },
    "outputs": [],
    "source": [
-    "await vectorstore.asimilarity_search(\"apple\", filter={\"topic\": {\"$in\": [\"food\", \"animals\"]}})"
+    "await vectorstore.asimilarity_search(\n",
+    "    \"apple\", filter={\"topic\": {\"$in\": [\"food\", \"animals\"]}}\n",
+    ")"
    ]
   },
   {
@@ -421,7 +426,9 @@
    },
    "outputs": [],
    "source": [
-    "await vectorstore.asimilarity_search(\"sales of fruit\", filter={\"topic\": {\"$ne\": \"animals\"}})"
+    "await vectorstore.asimilarity_search(\n",
+    "    \"sales of fruit\", filter={\"topic\": {\"$ne\": \"animals\"}}\n",
+    ")"
    ]
   },
   {
@@ -450,7 +457,7 @@
    "source": [
     "from langchain_postgres.v2.indexes import IVFFlatIndex\n",
     "\n",
-    "index = IVFFlatIndex() # Add an index using a default index name\n",
+    "index = IVFFlatIndex()  # Add an index using a default index name\n",
     "await vectorstore.aapply_vector_index(index)"
    ]
   },

examples/pg_vectorstore_how_to.ipynb

@@ -278,9 +278,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_core.documents import Document\n",
     "import uuid\n",
     "\n",
+    "from langchain_core.documents import Document\n",
+    "\n",
     "docs = [\n",
     "    Document(\n",
     "        id=str(uuid.uuid4()),\n",
@@ -400,7 +401,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_postgres.v2.indexes import IVFFlatIndex, HNSWIndex\n",
+    "from langchain_postgres.v2.indexes import HNSWIndex, IVFFlatIndex\n",
     "\n",
     "index = IVFFlatIndex()\n",
     "await store.aapply_vector_index(index)\n",
@@ -461,7 +462,7 @@
    "outputs": [],
    "source": [
     "await store.adrop_vector_index()  # Delete index using the default name\n",
-    "await store.adrop_vector_index(\"my-hnsw-index\") # Delete index using the index name"
+    "await store.adrop_vector_index(\"my-hnsw-index\")  # Delete index using the index name"
    ]
   },
   {

examples/vectorstore.ipynb

@@ -68,9 +68,10 @@
    "outputs": [],
    "source": [
     "from langchain_cohere import CohereEmbeddings\n",
-    "from langchain_postgres.vectorstores import PGVector\n",
     "from langchain_core.documents import Document\n",
     "\n",
+    "from langchain_postgres.vectorstores import PGVector\n",
+    "\n",
     "# See docker command above to launch a postgres instance with pgvector enabled.\n",
     "connection = \"postgresql+psycopg://langchain:langchain@localhost:6024/langchain\"\n",
     "collection_name = \"my_docs\"\n",

langchain_postgres/chat_message_histories.py

@@ -2,6 +2,7 @@
 
 This client provides support for both sync and async via psycopg 3.
 """
+
 from __future__ import annotations
 
 import json