diff --git a/poetry.lock b/poetry.lock
index 197c8d5b..434a6bcc 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
 
 [[package]]
 name = "absl-py"
@@ -743,7 +743,7 @@ name = "cachetools"
 version = "5.3.0"
 description = "Extensible memoizing collections and decorators"
 category = "main"
-optional = true
+optional = false
 python-versions = "~=3.7"
 files = [
     {file = "cachetools-5.3.0-py3-none-any.whl", hash = "sha256:429e1a1e845c008ea6c85aa35d4b98b65d6a9763eeef3e37e92728a12d1de9d4"},
@@ -1338,20 +1338,20 @@ files = [
 
 [[package]]
 name = "deeplake"
-version = "3.2.21"
+version = "3.2.22"
 description = "Activeloop Deep Lake"
 category = "main"
 optional = false
 python-versions = "*"
 files = [
-    {file = "deeplake-3.2.21.tar.gz", hash = "sha256:3ad6f81f666ba9e2951aff697babb845249b54dfdd72f22e3c7ef5838ae2e9d7"},
+    {file = "deeplake-3.2.22.tar.gz", hash = "sha256:068280561366dd1bd891d3ffda8638ec59860a23b9426815a484b0591ab467a6"},
 ]
 
 [package.dependencies]
 aioboto3 = {version = "10.4.0", markers = "python_version >= \"3.7\" and sys_platform != \"win32\""}
 boto3 = "*"
 click = "*"
-humbug = ">=0.2.6"
+humbug = ">=0.3.1"
 nest_asyncio = {version = "*", markers = "python_version >= \"3.7\" and sys_platform != \"win32\""}
 numcodecs = "*"
 numpy = "*"
@@ -1955,14 +1955,14 @@ uritemplate = ">=3.0.1,<5"
 
 [[package]]
 name = "google-auth"
-version = "2.17.2"
+version = "2.17.3"
 description = "Google Authentication Library"
 category = "main"
 optional = true
 python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*"
 files = [
-    {file = "google-auth-2.17.2.tar.gz", hash = "sha256:295c80ebb95eac74003c07a696cf3ef6b414e9230ae8894f3843f8215fd2aa56"},
-    {file = "google_auth-2.17.2-py2.py3-none-any.whl", hash = "sha256:544536a43d44dff0f64222e4d027d124989fcb9c10979687e589e1694fba9c94"},
+    {file = "google-auth-2.17.3.tar.gz", hash = "sha256:ce311e2bc58b130fddf316df57c9b3943c2a7b4f6ec31de9663a9333e4064efc"},
+    {file = "google_auth-2.17.3-py2.py3-none-any.whl", hash = "sha256:f586b274d3eb7bd932ea424b1c702a30e0393a2e2bc4ca3eae8263ffd8be229f"},
 ]
 
 [package.dependencies]
@@ -2064,14 +2064,14 @@ grpc = ["grpcio (>=1.44.0,<2.0.0dev)"]
 
 [[package]]
 name = "gptcache"
-version = "0.1.8"
-description = "GPT Cache, a powerful caching library that can be used to speed up and lower the cost of chat applications that rely on the LLM service. GPT Cache works as a memcache for AIGC applications, similar to how Redis works for traditional applications."
+version = "0.1.9"
+description = "GPTCache, a powerful caching library that can be used to speed up and lower the cost of chat applications that rely on the LLM service. GPTCache works as a memcache for AIGC applications, similar to how Redis works for traditional applications."
 category = "main"
-optional = true
+optional = false
 python-versions = ">=3.8.1"
 files = [
-    {file = "gptcache-0.1.8-py3-none-any.whl", hash = "sha256:953662291819471e5461920c89367084f905237a8506f1a1605729f3e633f147"},
-    {file = "gptcache-0.1.8.tar.gz", hash = "sha256:23200cc0783776210cce85a588ae68222d522ce9456f74b7836945ebe8b15820"},
+    {file = "gptcache-0.1.9-py3-none-any.whl", hash = "sha256:c603dea4a6e835032875ccc21a9205bb4d8ef0f2696a8df3ac13ac3a060c4cf6"},
+    {file = "gptcache-0.1.9.tar.gz", hash = "sha256:b92f30e4d8bc22a017a71fb4801f469739d4c83734a874fea51ca6998ef833d4"},
 ]
 
 [package.dependencies]
@@ -2954,14 +2954,14 @@ websockets = ["websockets"]
 
 [[package]]
 name = "jina-hubble-sdk"
-version = "0.35.0"
+version = "0.36.0"
 description = "SDK for Hubble API at Jina AI."
 category = "main"
 optional = true
 python-versions = ">=3.7.0"
 files = [
-    {file = "jina-hubble-sdk-0.35.0.tar.gz", hash = "sha256:f0826dc6d22aa8da983e4f67af8fa5b78dd852274da71adea7a38d9620438b37"},
-    {file = "jina_hubble_sdk-0.35.0-py3-none-any.whl", hash = "sha256:957e4ce5e9400ee27aad7a6e728172cdcffb8bb6667e430fa3c97f000650beb3"},
+    {file = "jina-hubble-sdk-0.36.0.tar.gz", hash = "sha256:ba1a72c7a5c14963fdad9af1ff4c3bba26a03ddcced08111bd11a95b153249ec"},
+    {file = "jina_hubble_sdk-0.36.0-py3-none-any.whl", hash = "sha256:56db142147d7c72142ed1b6505020c3b4d8070b1603d07ff796e56d491dde294"},
 ]
 
 [package.dependencies]
@@ -4794,14 +4794,14 @@ tests = ["pytest", "pytest-cov", "pytest-pep8"]
 
 [[package]]
 name = "packaging"
-version = "23.0"
+version = "23.1"
 description = "Core utilities for Python packages"
 category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "packaging-23.0-py3-none-any.whl", hash = "sha256:714ac14496c3e68c99c29b00845f7a2b85f3bb6f1078fd9f72fd20f0570002b2"},
-    {file = "packaging-23.0.tar.gz", hash = "sha256:b6ad297f8907de0fa2fe1ccbd26fdaf387f5f47c7275fedf8cce89f99446cf97"},
+    {file = "packaging-23.1-py3-none-any.whl", hash = "sha256:994793af429502c4ea2ebf6bf664629d07c1a9fe974af92966e4b8d2df7edc61"},
+    {file = "packaging-23.1.tar.gz", hash = "sha256:a392980d2b6cffa644431898be54b0045151319d1e7ec34f0cfed48767dd334f"},
 ]
 
 [[package]]
@@ -5188,14 +5188,14 @@ testing = ["pytest", "pytest-benchmark"]
 
 [[package]]
 name = "posthog"
-version = "2.4.2"
+version = "2.5.0"
 description = "Integrate PostHog into any python application."
 category = "dev"
 optional = false
 python-versions = "*"
 files = [
-    {file = "posthog-2.4.2-py2.py3-none-any.whl", hash = "sha256:8c7c37de997d955aea61bf0aa0069970e71f0d9d79c9e6b3a134e6593d5aa3d6"},
-    {file = "posthog-2.4.2.tar.gz", hash = "sha256:652a628623aab26597e8421a7ddf9caaf19dd93cc1288901a6b23db9693d34e5"},
+    {file = "posthog-2.5.0-py2.py3-none-any.whl", hash = "sha256:3d3ece06c3fe4135497c239f211c82344962b93e4fd4ba5afd20bd4ad12d77be"},
+    {file = "posthog-2.5.0.tar.gz", hash = "sha256:7601ef75b483eb67a6229cafec02da9624f6d46df61066771ca9e3f986284fc3"},
 ]
 
 [package.dependencies]
@@ -5309,6 +5309,22 @@ files = [
 [package.dependencies]
 wcwidth = "*"
 
+[[package]]
+name = "promptlayer"
+version = "0.1.80"
+description = "PromptLayer is a package to keep track of your GPT models training"
+category = "dev"
+optional = false
+python-versions = "*"
+files = [
+    {file = "promptlayer-0.1.80.tar.gz", hash = "sha256:1012018ed3e4bca4f0d9c9164cb00b7ca0936cba6a40d4de53e87ef08fdff62f"},
+]
+
+[package.dependencies]
+langchain = "*"
+openai = "*"
+requests = "*"
+
 [[package]]
 name = "protobuf"
 version = "3.19.6"
@@ -6228,14 +6244,14 @@ cffi = {version = "*", markers = "implementation_name == \"pypy\""}
 
 [[package]]
 name = "qdrant-client"
-version = "1.1.3"
+version = "1.1.4"
 description = "Client library for the Qdrant vector search engine"
 category = "main"
 optional = true
 python-versions = ">=3.7,<3.12"
 files = [
-    {file = "qdrant_client-1.1.3-py3-none-any.whl", hash = "sha256:c95f59fb9e3e89d163517f8992ee4557eccb45c252147e11e45c608ef1c7dd29"},
-    {file = "qdrant_client-1.1.3.tar.gz", hash = "sha256:2b7de2b987fc456c643a06878a4150947c3d3d6c6515f6c29f6e707788daa6e7"},
+    {file = "qdrant_client-1.1.4-py3-none-any.whl", hash = "sha256:12ad9dba63228cc5493e137bf35c59af56d84ca3a2b088c4298825d4893c7100"},
+    {file = "qdrant_client-1.1.4.tar.gz", hash = "sha256:92ad225bd770fb6a7ac10f75e38f53ffebe63c7f239b02fc7d2bc993246eb74c"},
 ]
 
 [package.dependencies]
@@ -6473,14 +6489,14 @@ files = [
 
 [[package]]
 name = "rich"
-version = "13.3.3"
+version = "13.3.4"
 description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
 category = "main"
 optional = true
 python-versions = ">=3.7.0"
 files = [
-    {file = "rich-13.3.3-py3-none-any.whl", hash = "sha256:540c7d6d26a1178e8e8b37e9ba44573a3cd1464ff6348b99ee7061b95d1c6333"},
-    {file = "rich-13.3.3.tar.gz", hash = "sha256:dc84400a9d842b3a9c5ff74addd8eb798d155f36c1c91303888e0a66850d2a15"},
+    {file = "rich-13.3.4-py3-none-any.whl", hash = "sha256:22b74cae0278fd5086ff44144d3813be1cedc9115bdfabbfefd86400cb88b20a"},
+    {file = "rich-13.3.4.tar.gz", hash = "sha256:b5d573e13605423ec80bdd0cd5f8541f7844a0e71a13f74cf454ccb2f490708b"},
 ]
 
 [package.dependencies]
@@ -6675,49 +6691,57 @@ transformers = ">=4.6.0,<5.0.0"
 
 [[package]]
 name = "sentencepiece"
-version = "0.1.97"
+version = "0.1.98"
 description = "SentencePiece python wrapper"
 category = "main"
 optional = false
 python-versions = "*"
 files = [
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 [[package]]
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 ]
 
 [package.dependencies]
@@ -6869,24 +6893,24 @@ wasabi = ">=0.9.1,<1.2.0"
 
 [package.extras]
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-cuda110 = ["cupy-cuda110 (>=5.0.0b4,<12.0.0)"]
-cuda111 = ["cupy-cuda111 (>=5.0.0b4,<12.0.0)"]
-cuda112 = ["cupy-cuda112 (>=5.0.0b4,<12.0.0)"]
-cuda113 = ["cupy-cuda113 (>=5.0.0b4,<12.0.0)"]
-cuda114 = ["cupy-cuda114 (>=5.0.0b4,<12.0.0)"]
-cuda115 = ["cupy-cuda115 (>=5.0.0b4,<12.0.0)"]
-cuda116 = ["cupy-cuda116 (>=5.0.0b4,<12.0.0)"]
-cuda117 = ["cupy-cuda117 (>=5.0.0b4,<12.0.0)"]
-cuda11x = ["cupy-cuda11x (>=11.0.0,<12.0.0)"]
-cuda80 = ["cupy-cuda80 (>=5.0.0b4,<12.0.0)"]
-cuda90 = ["cupy-cuda90 (>=5.0.0b4,<12.0.0)"]
-cuda91 = ["cupy-cuda91 (>=5.0.0b4,<12.0.0)"]
-cuda92 = ["cupy-cuda92 (>=5.0.0b4,<12.0.0)"]
+cuda = ["cupy (>=5.0.0b4,<13.0.0)"]
+cuda-autodetect = ["cupy-wheel (>=11.0.0,<13.0.0)"]
+cuda100 = ["cupy-cuda100 (>=5.0.0b4,<13.0.0)"]
+cuda101 = ["cupy-cuda101 (>=5.0.0b4,<13.0.0)"]
+cuda102 = ["cupy-cuda102 (>=5.0.0b4,<13.0.0)"]
+cuda110 = ["cupy-cuda110 (>=5.0.0b4,<13.0.0)"]
+cuda111 = ["cupy-cuda111 (>=5.0.0b4,<13.0.0)"]
+cuda112 = ["cupy-cuda112 (>=5.0.0b4,<13.0.0)"]
+cuda113 = ["cupy-cuda113 (>=5.0.0b4,<13.0.0)"]
+cuda114 = ["cupy-cuda114 (>=5.0.0b4,<13.0.0)"]
+cuda115 = ["cupy-cuda115 (>=5.0.0b4,<13.0.0)"]
+cuda116 = ["cupy-cuda116 (>=5.0.0b4,<13.0.0)"]
+cuda117 = ["cupy-cuda117 (>=5.0.0b4,<13.0.0)"]
+cuda11x = ["cupy-cuda11x (>=11.0.0,<13.0.0)"]
+cuda80 = ["cupy-cuda80 (>=5.0.0b4,<13.0.0)"]
+cuda90 = ["cupy-cuda90 (>=5.0.0b4,<13.0.0)"]
+cuda91 = ["cupy-cuda91 (>=5.0.0b4,<13.0.0)"]
+cuda92 = ["cupy-cuda92 (>=5.0.0b4,<13.0.0)"]
 ja = ["sudachidict-core (>=20211220)", "sudachipy (>=0.5.2,!=0.6.1)"]
 ko = ["natto-py (>=0.9.0)"]
 lookups = ["spacy-lookups-data (>=1.0.3,<1.1.0)"]
@@ -7234,7 +7258,7 @@ files = [
 ]
 
 [package.dependencies]
-greenlet = {version = "!=0.4.17", markers = "python_version >= \"3\" and (platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\")"}
+greenlet = {version = "!=0.4.17", markers = "python_version >= \"3\" and platform_machine == \"aarch64\" or python_version >= \"3\" and platform_machine == \"ppc64le\" or python_version >= \"3\" and platform_machine == \"x86_64\" or python_version >= \"3\" and platform_machine == \"amd64\" or python_version >= \"3\" and platform_machine == \"AMD64\" or python_version >= \"3\" and platform_machine == \"win32\" or python_version >= \"3\" and platform_machine == \"WIN32\""}
 
 [package.extras]
 aiomysql = ["aiomysql", "greenlet (!=0.4.17)"]
@@ -8096,14 +8120,14 @@ test = ["black (>=22.3.0,<23.0.0)", "coverage (>=6.2,<7.0)", "isort (>=5.0.6,<6.
 
 [[package]]
 name = "types-pyopenssl"
-version = "23.1.0.1"
+version = "23.1.0.2"
 description = "Typing stubs for pyOpenSSL"
 category = "dev"
 optional = false
 python-versions = "*"
 files = [
-    {file = "types-pyOpenSSL-23.1.0.1.tar.gz", hash = "sha256:59044283c475eaa5a29b36a903c123d52bdf4a7e012f0a1ca0e41115b99216da"},
-    {file = "types_pyOpenSSL-23.1.0.1-py3-none-any.whl", hash = "sha256:ac7fbc240930c2f9a1cbd2d04f9cb14ad0f15b0ad8d6528732a83747b1b2086e"},
+    {file = "types-pyOpenSSL-23.1.0.2.tar.gz", hash = "sha256:20b80971b86240e8432a1832bd8124cea49c3088c7bfc77dfd23be27ffe4a517"},
+    {file = "types_pyOpenSSL-23.1.0.2-py3-none-any.whl", hash = "sha256:b050641aeff6dfebf231ad719bdac12d53b8ee818d4afb67b886333484629957"},
 ]
 
 [package.dependencies]
@@ -9002,13 +9026,13 @@ cffi = {version = ">=1.11", markers = "platform_python_implementation == \"PyPy\
 cffi = ["cffi (>=1.11)"]
 
 [extras]
-all = ["anthropic", "cohere", "openai", "nlpcloud", "huggingface_hub", "jina", "manifest-ml", "elasticsearch", "opensearch-py", "google-search-results", "faiss-cpu", "sentence-transformers", "transformers", "spacy", "nltk", "wikipedia", "beautifulsoup4", "tiktoken", "torch", "jinja2", "pinecone-client", "pinecone-text", "weaviate-client", "redis", "google-api-python-client", "wolframalpha", "qdrant-client", "tensorflow-text", "pypdf", "networkx", "nomic", "aleph-alpha-client", "deeplake", "pgvector", "psycopg2-binary", "pyowm"]
+all = ["aleph-alpha-client", "anthropic", "beautifulsoup4", "cohere", "deeplake", "elasticsearch", "faiss-cpu", "google-api-python-client", "google-search-results", "huggingface_hub", "jina", "jinja2", "manifest-ml", "networkx", "nlpcloud", "nltk", "nomic", "openai", "opensearch-py", "pgvector", "pinecone-client", "pinecone-text", "psycopg2-binary", "pyowm", "pypdf", "qdrant-client", "redis", "sentence-transformers", "spacy", "tensorflow-text", "tiktoken", "torch", "transformers", "weaviate-client", "wikipedia", "wolframalpha"]
 cohere = ["cohere"]
-llms = ["anthropic", "cohere", "openai", "nlpcloud", "huggingface_hub", "manifest-ml", "torch", "transformers"]
+llms = ["anthropic", "cohere", "huggingface_hub", "manifest-ml", "nlpcloud", "openai", "torch", "transformers"]
 openai = ["openai"]
 qdrant = ["qdrant-client"]
 
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "26b1bbfbc3a228b892b2466af3561b799238a6d379853d325dc3c798776df0d8"
+content-hash = "3c8488864a754852fdec3e56dd5630ed73852ec2120a94cfe22537c075901b24"
diff --git a/pyproject.toml b/pyproject.toml
index 7acd501b..d3f34c3c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -104,6 +104,9 @@ deeplake = "^3.2.21"
 torch = "^1.0.0"
 chromadb = "^0.3.21"
 tiktoken = "^0.3.3"
+python-dotenv = "^1.0.0"
+gptcache = "^0.1.9"
+promptlayer = "^0.1.80"
 
 [tool.poetry.group.lint.dependencies]
 ruff = "^0.0.249"
diff --git a/tests/README.md b/tests/README.md
index b0296faf..0ccd5374 100644
--- a/tests/README.md
+++ b/tests/README.md
@@ -39,6 +39,11 @@ cd tests/integration_tests/vectorstores/docker-compose
 docker-compose -f elasticsearch.yml up
 ```
 
+### Prepare environment variables for local testing:
+
+- copy `tests/.env.example` to `tests/.env`
+- set variables in `tests/.env` file, e.g `OPENAI_API_KEY`
+
 Additionally, it's important to note that some integration tests may require certain
 environment variables to be set, such as `OPENAI_API_KEY`. Be sure to set any required
 environment variables before running the tests to ensure they run correctly.
@@ -54,7 +59,9 @@ cassettes. You can use the --vcr-record=none command-line option to disable reco
 new cassettes. Here's an example:
 
 ```bash
+pytest --log-cli-level=10 tests/integration_tests/vectorstores/test_pinecone.py --vcr-record=none
 pytest tests/integration_tests/vectorstores/test_elasticsearch.py --vcr-record=none
+
 ```
 
 ### Run some tests with coverage:
diff --git a/tests/integration_tests/.env.example b/tests/integration_tests/.env.example
new file mode 100644
index 00000000..6b39afda
--- /dev/null
+++ b/tests/integration_tests/.env.example
@@ -0,0 +1,9 @@
+# openai
+# your api key from https://platform.openai.com/account/api-keys
+OPENAI_API_KEY=
+
+# pinecone
+# your api key from left menu "API Keys" in https://app.pinecone.io
+PINECONE_API_KEY=your_pinecone_api_key_here
+# your pinecone environment from left menu "API Keys" in https://app.pinecone.io
+PINECONE_ENVIRONMENT=us-west4-gcp
\ No newline at end of file
diff --git a/tests/integration_tests/conftest.py b/tests/integration_tests/conftest.py
index cdddb4ea..8fcd9e0c 100644
--- a/tests/integration_tests/conftest.py
+++ b/tests/integration_tests/conftest.py
@@ -1,10 +1,31 @@
 import os
+from pathlib import Path
 
 import pytest
 
 # Getting the absolute path of the current file's directory
 ABS_PATH = os.path.dirname(os.path.abspath(__file__))
 
+# Getting the absolute path of the project's root directory
+PROJECT_DIR = os.path.abspath(os.path.join(ABS_PATH, os.pardir, os.pardir))
+
+
+# Loading the .env file if it exists
+def _load_env() -> None:
+    dotenv_path = os.path.join(PROJECT_DIR, "tests", "integration_tests", ".env")
+    if os.path.exists(dotenv_path):
+        from dotenv import load_dotenv
+
+        load_dotenv(dotenv_path)
+
+
+_load_env()
+
+
+@pytest.fixture(scope="module")
+def test_dir() -> Path:
+    return Path(os.path.join(PROJECT_DIR, "tests", "integration_tests"))
+
 
 # This fixture returns a string containing the path to the cassette directory for the
 # current module
@@ -15,18 +36,3 @@ def vcr_cassette_dir(request: pytest.FixtureRequest) -> str:
         "cassettes",
         os.path.basename(request.module.__file__).replace(".py", ""),
     )
-
-
-# This fixture returns a dictionary containing filter_headers options
-# for replacing certain headers with dummy values during cassette playback
-# Specifically, it replaces the authorization header with a dummy value to
-# prevent sensitive data from being recorded in the cassette.
-@pytest.fixture(scope="module")
-def vcr_config() -> dict:
-    return {
-        "filter_headers": [
-            ("authorization", "authorization-DUMMY"),
-            ("X-OpenAI-Client-User-Agent", "X-OpenAI-Client-User-Agent-DUMMY"),
-            ("User-Agent", "User-Agent-DUMMY"),
-        ],
-    }
diff --git a/tests/integration_tests/vectorstores/cassettes/test_pinecone/TestPinecone.test_from_texts.yaml b/tests/integration_tests/vectorstores/cassettes/test_pinecone/TestPinecone.test_from_texts.yaml
new file mode 100644
index 00000000..d3af2d8a
--- /dev/null
+++ b/tests/integration_tests/vectorstores/cassettes/test_pinecone/TestPinecone.test_from_texts.yaml
@@ -0,0 +1,489 @@
+interactions:
+- request:
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+    headers:
+      Accept:
+      - '*/*'
+      Accept-Encoding:
+      - gzip, deflate
+      Connection:
+      - keep-alive
+      Content-Length:
+      - '2798'
+      Content-Type:
+      - application/json
+      User-Agent:
+      - User-Agent-DUMMY
+      X-OpenAI-Client-User-Agent:
+      - X-OpenAI-Client-User-Agent-DUMMY
+      authorization:
+      - authorization-DUMMY
+    method: POST
+    uri: https://api.openai.com/v1/engines/text-embedding-ada-002/embeddings
+  response:
+    body:
+      string: !!binary |
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diff --git a/tests/integration_tests/vectorstores/conftest.py b/tests/integration_tests/vectorstores/conftest.py
index f7171a1a..9687af92 100644
--- a/tests/integration_tests/vectorstores/conftest.py
+++ b/tests/integration_tests/vectorstores/conftest.py
@@ -1,15 +1,49 @@
 import os
-from typing import Generator, List
+from typing import Generator, List, Union
 
 import pytest
+from vcr.request import Request
 
 from langchain.document_loaders import TextLoader
+from langchain.embeddings import OpenAIEmbeddings
 from langchain.schema import Document
 from langchain.text_splitter import CharacterTextSplitter
 
 
-# Define a fixture that yields a generator object returning a list of documents
+# This fixture returns a dictionary containing filter_headers options
+# for replacing certain headers with dummy values during cassette playback
+# Specifically, it replaces the authorization header with a dummy value to
+# prevent sensitive data from being recorded in the cassette.
+# It also filters request to certain hosts (specified in the `ignored_hosts` list)
+# to prevent data from being recorded in the cassette.
 @pytest.fixture(scope="module")
+def vcr_config() -> dict:
+    skipped_host = ["pinecone.io"]
+
+    def before_record_response(response: dict) -> Union[dict, None]:
+        return response
+
+    def before_record_request(request: Request) -> Union[Request, None]:
+        for host in skipped_host:
+            if request.host.startswith(host) or request.host.endswith(host):
+                return None
+        return request
+
+    return {
+        "before_record_request": before_record_request,
+        "before_record_response": before_record_response,
+        "filter_headers": [
+            ("authorization", "authorization-DUMMY"),
+            ("X-OpenAI-Client-User-Agent", "X-OpenAI-Client-User-Agent-DUMMY"),
+            ("Api-Key", "Api-Key-DUMMY"),
+            ("User-Agent", "User-Agent-DUMMY"),
+        ],
+        "ignore_localhost": True,
+    }
+
+
+# Define a fixture that yields a generator object returning a list of documents
+@pytest.fixture(scope="function")
 def documents() -> Generator[List[Document], None, None]:
     """Return a generator that yields a list of documents."""
 
@@ -23,3 +57,18 @@ def documents() -> Generator[List[Document], None, None]:
 
     # Yield the documents split into chunks
     yield text_splitter.split_documents(documents)
+
+
+@pytest.fixture(scope="function")
+def texts() -> Generator[List[str], None, None]:
+    # Load the documents from a file located in the fixtures directory
+    documents = TextLoader(
+        os.path.join(os.path.dirname(__file__), "fixtures", "sharks.txt")
+    ).load()
+
+    yield [doc.page_content for doc in documents]
+
+
+@pytest.fixture(scope="module")
+def embedding_openai() -> OpenAIEmbeddings:
+    return OpenAIEmbeddings()
diff --git a/tests/integration_tests/vectorstores/test_elasticsearch.py b/tests/integration_tests/vectorstores/test_elasticsearch.py
index 06865a5a..b79d2b6b 100644
--- a/tests/integration_tests/vectorstores/test_elasticsearch.py
+++ b/tests/integration_tests/vectorstores/test_elasticsearch.py
@@ -21,6 +21,11 @@ docker-compose -f elasticsearch.yml up
 
 
 class TestElasticsearch:
+    @classmethod
+    def setup_class(cls) -> None:
+        if not os.getenv("OPENAI_API_KEY"):
+            raise ValueError("OPENAI_API_KEY environment variable is not set")
+
     @pytest.fixture(scope="class", autouse=True)
     def elasticsearch_url(self) -> Union[str, Generator[str, None, None]]:
         """Return the elasticsearch url."""
@@ -34,15 +39,6 @@ class TestElasticsearch:
             # print(index_name)
             es.indices.delete(index=index_name)
 
-    @pytest.fixture(scope="class", autouse=True)
-    def openai_api_key(self) -> Union[str, Generator[str, None, None]]:
-        """Return the OpenAI API key."""
-        openai_api_key = os.getenv("OPENAI_API_KEY")
-        if not openai_api_key:
-            raise ValueError("OPENAI_API_KEY environment variable is not set")
-
-        yield openai_api_key
-
     def test_similarity_search_without_metadata(self, elasticsearch_url: str) -> None:
         """Test end to end construction and search without metadata."""
         texts = ["foo", "bar", "baz"]
@@ -67,15 +63,17 @@ class TestElasticsearch:
 
     @pytest.mark.vcr(ignore_localhost=True)
     def test_default_index_from_documents(
-        self, documents: List[Document], openai_api_key: str, elasticsearch_url: str
+        self,
+        documents: List[Document],
+        embedding_openai: OpenAIEmbeddings,
+        elasticsearch_url: str,
     ) -> None:
         """This test checks the construction of a default
         ElasticSearch index using the 'from_documents'."""
-        embedding = OpenAIEmbeddings(openai_api_key=openai_api_key)
 
         elastic_vector_search = ElasticVectorSearch.from_documents(
             documents=documents,
-            embedding=embedding,
+            embedding=embedding_openai,
             elasticsearch_url=elasticsearch_url,
         )
 
@@ -86,16 +84,18 @@ class TestElasticsearch:
 
     @pytest.mark.vcr(ignore_localhost=True)
     def test_custom_index_from_documents(
-        self, documents: List[Document], openai_api_key: str, elasticsearch_url: str
+        self,
+        documents: List[Document],
+        embedding_openai: OpenAIEmbeddings,
+        elasticsearch_url: str,
     ) -> None:
         """This test checks the construction of a custom
         ElasticSearch index using the 'from_documents'."""
 
         index_name = f"custom_index_{uuid.uuid4().hex}"
-        embedding = OpenAIEmbeddings(openai_api_key=openai_api_key)
         elastic_vector_search = ElasticVectorSearch.from_documents(
             documents=documents,
-            embedding=embedding,
+            embedding=embedding_openai,
             elasticsearch_url=elasticsearch_url,
             index_name=index_name,
         )
@@ -110,15 +110,17 @@ class TestElasticsearch:
 
     @pytest.mark.vcr(ignore_localhost=True)
     def test_custom_index_add_documents(
-        self, documents: List[Document], openai_api_key: str, elasticsearch_url: str
+        self,
+        documents: List[Document],
+        embedding_openai: OpenAIEmbeddings,
+        elasticsearch_url: str,
     ) -> None:
         """This test checks the construction of a custom
         ElasticSearch index using the 'add_documents'."""
 
         index_name = f"custom_index_{uuid.uuid4().hex}"
-        embedding = OpenAIEmbeddings(openai_api_key=openai_api_key)
         elastic_vector_search = ElasticVectorSearch(
-            embedding=embedding,
+            embedding=embedding_openai,
             elasticsearch_url=elasticsearch_url,
             index_name=index_name,
         )
diff --git a/tests/integration_tests/vectorstores/test_pinecone.py b/tests/integration_tests/vectorstores/test_pinecone.py
index bcfe4104..4a6a8fb1 100644
--- a/tests/integration_tests/vectorstores/test_pinecone.py
+++ b/tests/integration_tests/vectorstores/test_pinecone.py
@@ -1,97 +1,208 @@
-"""Test Pinecone functionality."""
+import importlib
+import os
+import uuid
+from typing import List
+
 import pinecone
+import pytest
 
 from langchain.docstore.document import Document
+from langchain.embeddings import OpenAIEmbeddings
 from langchain.vectorstores.pinecone import Pinecone
-from tests.integration_tests.vectorstores.fake_embeddings import FakeEmbeddings
 
-pinecone.init(api_key="YOUR_API_KEY", environment="YOUR_ENV")
+index_name = "langchain-test-index"  # name of the index
+namespace_name = "langchain-test-namespace"  # name of the namespace
+dimension = 1536  # dimension of the embeddings
 
-# if the index already exists, delete it
-try:
-    pinecone.delete_index("langchain-demo")
-except Exception:
-    pass
-index = pinecone.Index("langchain-demo")
 
+def reset_pinecone() -> None:
+    assert os.environ.get("PINECONE_API_KEY") is not None
+    assert os.environ.get("PINECONE_ENVIRONMENT") is not None
 
-def test_pinecone() -> None:
-    """Test end to end construction and search."""
-    texts = ["foo", "bar", "baz"]
-    docsearch = Pinecone.from_texts(
-        texts, FakeEmbeddings(), index_name="langchain-demo", namespace="test"
-    )
-    output = docsearch.similarity_search("foo", k=1, namespace="test")
-    assert output == [Document(page_content="foo")]
-
-
-def test_pinecone_with_metadatas() -> None:
-    """Test end to end construction and search."""
-    texts = ["foo", "bar", "baz"]
-    metadatas = [{"page": i} for i in range(len(texts))]
-    docsearch = Pinecone.from_texts(
-        texts,
-        FakeEmbeddings(),
-        index_name="langchain-demo",
-        metadatas=metadatas,
-        namespace="test-metadata",
-    )
-    output = docsearch.similarity_search("foo", k=1, namespace="test-metadata")
-    assert output == [Document(page_content="foo", metadata={"page": 0})]
-
-
-def test_pinecone_with_scores() -> None:
-    """Test end to end construction and search with scores and IDs."""
-    texts = ["foo", "bar", "baz"]
-    metadatas = [{"page": i} for i in range(len(texts))]
-    docsearch = Pinecone.from_texts(
-        texts,
-        FakeEmbeddings(),
-        index_name="langchain-demo",
-        metadatas=metadatas,
-        namespace="test-metadata-score",
-    )
-    output = docsearch.similarity_search_with_score(
-        "foo", k=3, namespace="test-metadata-score"
-    )
-    docs = [o[0] for o in output]
-    scores = [o[1] for o in output]
-    assert docs == [
-        Document(page_content="foo", metadata={"page": 0}),
-        Document(page_content="bar", metadata={"page": 1}),
-        Document(page_content="baz", metadata={"page": 2}),
-    ]
-    assert scores[0] > scores[1] > scores[2]
-
-
-def test_pinecone_with_namespaces() -> None:
-    "Test that namespaces are properly handled." ""
-    # Create two indexes with the same name but different namespaces
-    texts = ["foo", "bar", "baz"]
-    metadatas = [{"page": i} for i in range(len(texts))]
-    Pinecone.from_texts(
-        texts,
-        FakeEmbeddings(),
-        index_name="langchain-demo",
-        metadatas=metadatas,
-        namespace="test-namespace",
-    )
+    import pinecone
 
-    texts = ["foo2", "bar2", "baz2"]
-    metadatas = [{"page": i} for i in range(len(texts))]
-    Pinecone.from_texts(
-        texts,
-        FakeEmbeddings(),
-        index_name="langchain-demo",
-        metadatas=metadatas,
-        namespace="test-namespace2",
-    )
+    importlib.reload(pinecone)
 
-    # Search with namespace
-    docsearch = Pinecone.from_existing_index(
-        "langchain-demo", embedding=FakeEmbeddings(), namespace="test-namespace"
+    pinecone.init(
+        api_key=os.environ.get("PINECONE_API_KEY"),
+        environment=os.environ.get("PINECONE_ENVIRONMENT"),
     )
-    output = docsearch.similarity_search("foo", k=6)
-    # check that we don't get results from the other namespace
-    page_contents = [o.page_content for o in output]
-    assert set(page_contents) == set(["foo", "bar", "baz"])
+
+
+class TestPinecone:
+    index: pinecone.Index
+
+    @classmethod
+    def setup_class(cls) -> None:
+        reset_pinecone()
+
+        cls.index = pinecone.Index(index_name)
+
+        if index_name in pinecone.list_indexes():
+            index_stats = cls.index.describe_index_stats()
+            if index_stats["dimension"] == dimension:
+                # delete all the vectors in the index if the dimension is the same
+                # from all namespaces
+                index_stats = cls.index.describe_index_stats()
+                for _namespace_name in index_stats["namespaces"].keys():
+                    cls.index.delete(delete_all=True, namespace=_namespace_name)
+
+            else:
+                pinecone.delete_index(index_name)
+                pinecone.create_index(name=index_name, dimension=dimension)
+        else:
+            pinecone.create_index(name=index_name, dimension=dimension)
+
+        # insure the index is empty
+        index_stats = cls.index.describe_index_stats()
+        assert index_stats["dimension"] == dimension
+        if index_stats["namespaces"].get(namespace_name) is not None:
+            assert index_stats["namespaces"][namespace_name]["vector_count"] == 0
+
+    @classmethod
+    def teardown_class(cls) -> None:
+        index_stats = cls.index.describe_index_stats()
+        for _namespace_name in index_stats["namespaces"].keys():
+            cls.index.delete(delete_all=True, namespace=_namespace_name)
+
+        reset_pinecone()
+
+    @pytest.fixture(autouse=True)
+    def setup(self) -> None:
+        # delete all the vectors in the index
+        index_stats = self.index.describe_index_stats()
+        for _namespace_name in index_stats["namespaces"].keys():
+            self.index.delete(delete_all=True, namespace=_namespace_name)
+
+        reset_pinecone()
+
+    @pytest.mark.vcr()
+    def test_from_texts(
+        self, texts: List[str], embedding_openai: OpenAIEmbeddings
+    ) -> None:
+        """Test end to end construction and search."""
+        unique_id = uuid.uuid4().hex
+        needs = f"foobuu {unique_id} booo"
+        texts.insert(0, needs)
+
+        docsearch = Pinecone.from_texts(
+            texts=texts,
+            embedding=embedding_openai,
+            index_name=index_name,
+            namespace=namespace_name,
+        )
+        output = docsearch.similarity_search(unique_id, k=1, namespace=namespace_name)
+        assert output == [Document(page_content=needs)]
+
+    @pytest.mark.vcr()
+    def test_from_texts_with_metadatas(
+        self, texts: List[str], embedding_openai: OpenAIEmbeddings
+    ) -> None:
+        """Test end to end construction and search."""
+
+        unique_id = uuid.uuid4().hex
+        needs = f"foobuu {unique_id} booo"
+        texts.insert(0, needs)
+
+        metadatas = [{"page": i} for i in range(len(texts))]
+        docsearch = Pinecone.from_texts(
+            texts,
+            embedding_openai,
+            index_name=index_name,
+            metadatas=metadatas,
+            namespace=namespace_name,
+        )
+        output = docsearch.similarity_search(needs, k=1, namespace=namespace_name)
+
+        # TODO: why metadata={"page": 0.0}) instead of {"page": 0}?
+        assert output == [Document(page_content=needs, metadata={"page": 0.0})]
+
+    @pytest.mark.vcr()
+    def test_from_texts_with_scores(self, embedding_openai: OpenAIEmbeddings) -> None:
+        """Test end to end construction and search with scores and IDs."""
+        texts = ["foo", "bar", "baz"]
+        metadatas = [{"page": i} for i in range(len(texts))]
+        docsearch = Pinecone.from_texts(
+            texts,
+            embedding_openai,
+            index_name=index_name,
+            metadatas=metadatas,
+            namespace=namespace_name,
+        )
+        output = docsearch.similarity_search_with_score(
+            "foo", k=3, namespace=namespace_name
+        )
+        docs = [o[0] for o in output]
+        scores = [o[1] for o in output]
+        sorted_documents = sorted(docs, key=lambda x: x.metadata["page"])
+
+        # TODO: why metadata={"page": 0.0}) instead of {"page": 0}, etc???
+        assert sorted_documents == [
+            Document(page_content="foo", metadata={"page": 0.0}),
+            Document(page_content="bar", metadata={"page": 1.0}),
+            Document(page_content="baz", metadata={"page": 2.0}),
+        ]
+        assert scores[0] > scores[1] > scores[2]
+
+    def test_from_existing_index_with_namespaces(
+        self, embedding_openai: OpenAIEmbeddings
+    ) -> None:
+        """Test that namespaces are properly handled."""
+        # Create two indexes with the same name but different namespaces
+        texts_1 = ["foo", "bar", "baz"]
+        metadatas = [{"page": i} for i in range(len(texts_1))]
+        Pinecone.from_texts(
+            texts_1,
+            embedding_openai,
+            index_name=index_name,
+            metadatas=metadatas,
+            namespace=f"{index_name}-1",
+        )
+
+        texts_2 = ["foo2", "bar2", "baz2"]
+        metadatas = [{"page": i} for i in range(len(texts_2))]
+
+        Pinecone.from_texts(
+            texts_2,
+            embedding_openai,
+            index_name=index_name,
+            metadatas=metadatas,
+            namespace=f"{index_name}-2",
+        )
+
+        # Search with namespace
+        docsearch = Pinecone.from_existing_index(
+            index_name=index_name,
+            embedding=embedding_openai,
+            namespace=f"{index_name}-1",
+        )
+        output = docsearch.similarity_search("foo", k=20, namespace=f"{index_name}-1")
+        # check that we don't get results from the other namespace
+        page_contents = sorted(set([o.page_content for o in output]))
+        assert all(content in ["foo", "bar", "baz"] for content in page_contents)
+        assert all(content not in ["foo2", "bar2", "baz2"] for content in page_contents)
+
+    def test_add_documents_with_ids(
+        self, texts: List[str], embedding_openai: OpenAIEmbeddings
+    ) -> None:
+        ids = [uuid.uuid4().hex for _ in range(len(texts))]
+        Pinecone.from_texts(
+            texts=texts,
+            ids=ids,
+            embedding=embedding_openai,
+            index_name=index_name,
+            namespace=index_name,
+        )
+        index_stats = self.index.describe_index_stats()
+        assert index_stats["namespaces"][index_name]["vector_count"] == len(texts)
+
+        ids_1 = [uuid.uuid4().hex for _ in range(len(texts))]
+        Pinecone.from_texts(
+            texts=texts,
+            ids=ids_1,
+            embedding=embedding_openai,
+            index_name=index_name,
+            namespace=index_name,
+        )
+        index_stats = self.index.describe_index_stats()
+        assert index_stats["namespaces"][index_name]["vector_count"] == len(texts) * 2