From 731eec3dc5dea649720341bc430791b3da7f9e66 Mon Sep 17 00:00:00 2001
From: Gabriel Luiz Freitas Almeida <gabriel@langflow.org>
Date: Tue, 7 May 2024 18:29:42 -0300
Subject: [PATCH] Fixes Pinecone implementation (#1856)
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

* ⬆️ (pyproject.toml): upgrade langchain-pinecone dependency to version 0.1.0

* 📝 (Pinecone.py): Update Pinecone component to use new DistanceStrategy enum for distance calculation and improve configuration options for Pinecone vector store creation.

* ⬆️ (pyproject.toml): upgrade package version from 0.6.18 to 0.6.19
---
 poetry.lock                                   | 1118 ++++++++---------
 pyproject.toml                                |    3 +-
 .../components/vectorstores/Pinecone.py       |  128 +-
 3 files changed, 665 insertions(+), 584 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 50ba4f3e3e4..04dfa7a1661 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -396,28 +396,28 @@ files = [
 
 [[package]]
 name = "blinker"
-version = "1.8.1"
+version = "1.8.2"
 description = "Fast, simple object-to-object and broadcast signaling"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "blinker-1.8.1-py3-none-any.whl", hash = "sha256:5f1cdeff423b77c31b89de0565cd03e5275a03028f44b2b15f912632a58cced6"},
-    {file = "blinker-1.8.1.tar.gz", hash = "sha256:da44ec748222dcd0105ef975eed946da197d5bdf8bafb6aa92f5bc89da63fa25"},
+    {file = "blinker-1.8.2-py3-none-any.whl", hash = "sha256:1779309f71bf239144b9399d06ae925637cf6634cf6bd131104184531bf67c01"},
+    {file = "blinker-1.8.2.tar.gz", hash = "sha256:8f77b09d3bf7c795e969e9486f39c2c5e9c39d4ee07424be2bc594ece9642d83"},
 ]
 
 [[package]]
 name = "boto3"
-version = "1.34.93"
+version = "1.34.100"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "boto3-1.34.93-py3-none-any.whl", hash = "sha256:b59355bf4a1408563969526f314611dbeacc151cf90ecb22af295dcc4fe18def"},
-    {file = "boto3-1.34.93.tar.gz", hash = "sha256:e39516e4ca21612932599819662759c04485d53ca457996a913163da11f052a4"},
+    {file = "boto3-1.34.100-py3-none-any.whl", hash = "sha256:bbe2bb0dfcd92380da2a2fa2c2f586ba06c118b796380b2d0f3d0ebd103ec28d"},
+    {file = "boto3-1.34.100.tar.gz", hash = "sha256:016f6d66900bb1a835dea2063f1e91fc7057dbf7fb7df8add0706f0da9492631"},
 ]
 
 [package.dependencies]
-botocore = ">=1.34.93,<1.35.0"
+botocore = ">=1.34.100,<1.35.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.10.0,<0.11.0"
 
@@ -426,13 +426,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.34.93"
+version = "1.34.100"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "botocore-1.34.93-py3-none-any.whl", hash = "sha256:6fbd5a53a2adc9b3d4ebd90ae0ede83a91a41d96231f8a5984051f75495f246d"},
-    {file = "botocore-1.34.93.tar.gz", hash = "sha256:79d39b0b87e962991c6dd55e78ce15155099f6fb741be88b1b8a456a702cc150"},
+    {file = "botocore-1.34.100-py3-none-any.whl", hash = "sha256:ee516fb9e9e906d311f2a9921afaf79c594db239a5b4b626e89e6960401aad0b"},
+    {file = "botocore-1.34.100.tar.gz", hash = "sha256:513bea60c6531af8e1ae1fdb2947e3ef99712f39c58f4656b5efef9cb6f75a13"},
 ]
 
 [package.dependencies]
@@ -1059,63 +1059,63 @@ yaml = ["PyYAML"]
 
 [[package]]
 name = "coverage"
-version = "7.5.0"
+version = "7.5.1"
 description = "Code coverage measurement for Python"
 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
@@ -1126,43 +1126,43 @@ toml = ["tomli"]
 
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 optional = false
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 ]
 
 [package.dependencies]
@@ -1474,13 +1474,13 @@ develop = ["aiohttp", "furo", "httpx", "mock", "opentelemetry-api", "opentelemet
 
 [[package]]
 name = "elasticsearch"
-version = "8.13.0"
+version = "8.13.1"
 description = "Python client for Elasticsearch"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -1490,6 +1490,7 @@ elastic-transport = ">=8.13,<9"
 async = ["aiohttp (>=3,<4)"]
 orjson = ["orjson (>=3)"]
 requests = ["requests (>=2.4.0,<3.0.0)"]
+vectorstore-mmr = ["numpy (>=1)", "simsimd (>=3)"]
 
 [[package]]
 name = "emoji"
@@ -1780,13 +1781,13 @@ dotenv = ["python-dotenv"]
 
 [[package]]
 name = "flask-cors"
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+version = "4.0.1"
 description = "A Flask extension adding a decorator for CORS support"
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 python-versions = "*"
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 [package.dependencies]
@@ -2135,13 +2136,13 @@ protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4
 
 [[package]]
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+version = "2.19.0"
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@@ -2166,13 +2167,13 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-api-python-client"
-version = "2.127.0"
+version = "2.128.0"
 description = "Google API Client Library for Python"
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 python-versions = ">=3.7"
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 [package.dependencies]
@@ -2222,13 +2223,13 @@ httplib2 = ">=0.19.0"
 
 [[package]]
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-version = "1.49.0"
+version = "1.50.0"
 description = "Vertex AI API client library"
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 python-versions = ">=3.8"
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 [package.dependencies]
@@ -2269,13 +2270,13 @@ xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
 
 [[package]]
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 python-versions = ">=3.7"
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 [[package]]
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 description = "HTTP/2-based RPC framework"
 optional = false
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 [[package]]
 name = "grpcio-health-checking"
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 [[package]]
 name = "jinja2"
-version = "3.1.3"
+version = "3.1.4"
 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
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 [package.dependencies]
@@ -3214,13 +3207,13 @@ files = [
 
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-version = "1.4.0"
+version = "1.4.2"
 description = "Lightweight pipelining with Python functions"
 optional = false
 python-versions = ">=3.8"
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 [[package]]
@@ -3445,13 +3438,13 @@ adal = ["adal (>=1.0.2)"]
 
 [[package]]
 name = "langchain"
-version = "0.1.16"
+version = "0.1.17"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
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 [package.dependencies]
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 jsonpatch = ">=1.33,<2.0"
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-langchain-core = ">=0.1.42,<0.2.0"
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 langchain-text-splitters = ">=0.0.1,<0.1"
 langsmith = ">=0.1.17,<0.2.0"
 numpy = ">=1,<2"
@@ -3502,19 +3495,19 @@ langchain-core = ">=0.1.43,<0.2.0"
 
 [[package]]
 name = "langchain-community"
-version = "0.0.34"
+version = "0.0.37"
 description = "Community contributed LangChain integrations."
 optional = false
 python-versions = "<4.0,>=3.8.1"
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 langsmith = ">=0.1.0,<0.2.0"
 numpy = ">=1,<2"
 PyYAML = ">=5.3"
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 [package.extras]
 cli = ["typer (>=0.9.0,<0.10.0)"]
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+extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.3.11,<0.4.0)", "arxiv (>=1.4,<2.0)", "assemblyai (>=0.17.0,<0.18.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "azure-ai-documentintelligence (>=1.0.0b1,<2.0.0)", "azure-identity (>=1.15.0,<2.0.0)", "azure-search-documents (==11.4.0)", "beautifulsoup4 (>=4,<5)", "bibtexparser (>=1.4.0,<2.0.0)", "cassio (>=0.1.6,<0.2.0)", "chardet (>=5.1.0,<6.0.0)", "cloudpickle (>=2.0.0)", "cohere (>=4,<5)", "databricks-vectorsearch (>=0.21,<0.22)", "datasets (>=2.15.0,<3.0.0)", "dgml-utils (>=0.3.0,<0.4.0)", "elasticsearch (>=8.12.0,<9.0.0)", "esprima (>=4.0.1,<5.0.0)", "faiss-cpu (>=1,<2)", "feedparser (>=6.0.10,<7.0.0)", "fireworks-ai (>=0.9.0,<0.10.0)", "friendli-client (>=1.2.4,<2.0.0)", "geopandas (>=0.13.1,<0.14.0)", "gitpython (>=3.1.32,<4.0.0)", "google-cloud-documentai (>=2.20.1,<3.0.0)", "gql (>=3.4.1,<4.0.0)", "gradientai (>=1.4.0,<2.0.0)", "hdbcli (>=2.19.21,<3.0.0)", "hologres-vector (>=0.0.6,<0.0.7)", "html2text (>=2020.1.16,<2021.0.0)", "httpx (>=0.24.1,<0.25.0)", "httpx-sse (>=0.4.0,<0.5.0)", "javelin-sdk (>=0.1.8,<0.2.0)", "jinja2 (>=3,<4)", "jq (>=1.4.1,<2.0.0)", "jsonschema (>1)", "lxml (>=4.9.3,<6.0)", "markdownify (>=0.11.6,<0.12.0)", "motor (>=3.3.1,<4.0.0)", "msal (>=1.25.0,<2.0.0)", "mwparserfromhell (>=0.6.4,<0.7.0)", "mwxml (>=0.3.3,<0.4.0)", "newspaper3k (>=0.2.8,<0.3.0)", "numexpr (>=2.8.6,<3.0.0)", "nvidia-riva-client (>=2.14.0,<3.0.0)", "oci (>=2.119.1,<3.0.0)", "openai (<2)", "openapi-pydantic (>=0.3.2,<0.4.0)", "oracle-ads (>=2.9.1,<3.0.0)", "oracledb (>=2.2.0,<3.0.0)", "pandas (>=2.0.1,<3.0.0)", "pdfminer-six (>=20221105,<20221106)", "pgvector (>=0.1.6,<0.2.0)", "praw (>=7.7.1,<8.0.0)", "premai (>=0.3.25,<0.4.0)", "psychicapi (>=0.8.0,<0.9.0)", "py-trello (>=0.19.0,<0.20.0)", "pyjwt (>=2.8.0,<3.0.0)", "pymupdf (>=1.22.3,<2.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pypdfium2 (>=4.10.0,<5.0.0)", "pyspark (>=3.4.0,<4.0.0)", "rank-bm25 (>=0.2.2,<0.3.0)", "rapidfuzz (>=3.1.1,<4.0.0)", "rapidocr-onnxruntime (>=1.3.2,<2.0.0)", "rdflib (==7.0.0)", "requests-toolbelt (>=1.0.0,<2.0.0)", "rspace_client (>=2.5.0,<3.0.0)", "scikit-learn (>=1.2.2,<2.0.0)", "sqlite-vss (>=0.1.2,<0.2.0)", "streamlit (>=1.18.0,<2.0.0)", "sympy (>=1.12,<2.0)", "telethon (>=1.28.5,<2.0.0)", "tidb-vector (>=0.0.3,<1.0.0)", "timescale-vector (>=0.0.1,<0.0.2)", "tqdm (>=4.48.0)", "tree-sitter (>=0.20.2,<0.21.0)", "tree-sitter-languages (>=1.8.0,<2.0.0)", "upstash-redis (>=0.15.0,<0.16.0)", "vdms (>=0.0.20,<0.0.21)", "xata (>=1.0.0a7,<2.0.0)", "xmltodict (>=0.13.0,<0.14.0)"]
 
 [[package]]
 name = "langchain-core"
-version = "0.1.46"
+version = "0.1.52"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_core-0.1.46-py3-none-any.whl", hash = "sha256:1c0befcd2665dd4aa153318aa9bf729071644b4c179e491769b8e583b4bf7441"},
-    {file = "langchain_core-0.1.46.tar.gz", hash = "sha256:17c416349f5c7a9808e70e3725749a3a2df5088f1ecca045c883871aa95f9c9e"},
+    {file = "langchain_core-0.1.52-py3-none-any.whl", hash = "sha256:62566749c92e8a1181c255c788548dc16dbc319d896cd6b9c95dc17af9b2a6db"},
+    {file = "langchain_core-0.1.52.tar.gz", hash = "sha256:084c3fc452f5a6966c28ab3ec5dbc8b8d26fc3f63378073928f4e29d90b6393f"},
 ]
 
 [package.dependencies]
@@ -3601,6 +3594,22 @@ numpy = ">=1,<2"
 openai = ">=1.10.0,<2.0.0"
 tiktoken = ">=0.5.2,<1"
 
+[[package]]
+name = "langchain-pinecone"
+version = "0.1.0"
+description = "An integration package connecting Pinecone and LangChain"
+optional = false
+python-versions = "<3.13,>=3.8.1"
+files = [
+    {file = "langchain_pinecone-0.1.0-py3-none-any.whl", hash = "sha256:d957f27b1cceab425c3e8603c7a32533d4593ce8705242e78f6dc03aa71cf417"},
+    {file = "langchain_pinecone-0.1.0.tar.gz", hash = "sha256:93f81e7c3926027cc6a87b001ee4d2e02a432a916709dbd395162b342bf84586"},
+]
+
+[package.dependencies]
+langchain-core = ">=0.1.40,<0.2.0"
+numpy = ">=1,<2"
+pinecone-client = ">=3.2.2,<4.0.0"
+
 [[package]]
 name = "langchain-text-splitters"
 version = "0.0.1"
@@ -3634,17 +3643,17 @@ six = "*"
 
 [[package]]
 name = "langfuse"
-version = "2.27.2"
+version = "2.29.1"
 description = "A client library for accessing langfuse"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langfuse-2.27.2-py3-none-any.whl", hash = "sha256:6556dcd942ed596c6cbcd688bfed2aeca37065b68b9009f5e4ed829a32a9e513"},
-    {file = "langfuse-2.27.2.tar.gz", hash = "sha256:7b77f188fd72261473fb329151a15ff676c49261b5084eb25a3ded49d1577234"},
+    {file = "langfuse-2.29.1-py3-none-any.whl", hash = "sha256:73819e8c62c9aa5de531ee9aa986b50bf6090eda300c10243fff2a0ffdb1e48e"},
+    {file = "langfuse-2.29.1.tar.gz", hash = "sha256:320a5e739863f500292ecc1eeb75648eb7337af6cf38ce21c1f50f7767796840"},
 ]
 
 [package.dependencies]
-backoff = ">=2.2.1,<3.0.0"
+backoff = ">=1.10.0"
 httpx = ">=0.15.4,<1.0"
 idna = ">=3.7,<4.0"
 packaging = ">=23.2,<24.0"
@@ -3658,13 +3667,13 @@ openai = ["openai (>=0.27.8)"]
 
 [[package]]
 name = "langsmith"
-version = "0.1.52"
+version = "0.1.54"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.1.52-py3-none-any.whl", hash = "sha256:4518e269b9a0e10197550f050b6518d1276fe68732f7b8579b3e1302b8471d29"},
-    {file = "langsmith-0.1.52.tar.gz", hash = "sha256:f767fddb13c794bea7cc827a77f050a8a1c075ab1d997eb37849b975b0eef1b0"},
+    {file = "langsmith-0.1.54-py3-none-any.whl", hash = "sha256:e8ba2758dbdff0fccb35337c28a5ab641dd980b22e178d390b72a15c9ae9caff"},
+    {file = "langsmith-0.1.54.tar.gz", hash = "sha256:86f5a90e48303de897f37a893f8bb635eabdaf23e674099e8bc0f2e9ca2f8faf"},
 ]
 
 [package.dependencies]
@@ -3691,12 +3700,12 @@ regex = ["regex"]
 
 [[package]]
 name = "llama-cpp-python"
-version = "0.2.65"
+version = "0.2.69"
 description = "Python bindings for the llama.cpp library"
 optional = true
 python-versions = ">=3.8"
 files = [
-    {file = "llama_cpp_python-0.2.65.tar.gz", hash = "sha256:5d8b8bec70576176f213b7abedda267aedafda1d165b4a30b3ebf9d3df597d55"},
+    {file = "llama_cpp_python-0.2.69.tar.gz", hash = "sha256:b37e864b4d9f7ac286a3e926d87afab2f136ae9290e11088f7a205b80d3c04a9"},
 ]
 
 [package.dependencies]
@@ -3752,13 +3761,13 @@ query-tools = ["guidance (>=0.0.64,<0.0.65)", "jsonpath-ng (>=1.6.0,<2.0.0)", "l
 
 [[package]]
 name = "locust"
-version = "2.26.0"
+version = "2.27.0"
 description = "Developer friendly load testing framework"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "locust-2.26.0-py3-none-any.whl", hash = "sha256:7957d8346e5830ba35e3a7a9c1eebe0fb73b0be117e54213c61ef3bc658a1ae6"},
-    {file = "locust-2.26.0.tar.gz", hash = "sha256:a5cb4c96b8fa1ae5c20876ab8ca9d1e980d56148ed3c187df610cc2546705bff"},
+    {file = "locust-2.27.0-py3-none-any.whl", hash = "sha256:c4db5747eb9a3851216deae8147143d335db41978a9291ac32e113fa9ec8ad39"},
+    {file = "locust-2.27.0.tar.gz", hash = "sha256:0c6d3d2523976dafe734012c41b2f7d9ad7120cbcea76d47d80cec5d6d139905"},
 ]
 
 [package.dependencies]
@@ -3773,7 +3782,6 @@ psutil = ">=5.9.1"
 pywin32 = {version = "*", markers = "platform_system == \"Windows\""}
 pyzmq = ">=25.0.0"
 requests = ">=2.26.0"
-roundrobin = ">=0.0.2"
 tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
 Werkzeug = ">=2.0.0"
 
@@ -4017,13 +4025,13 @@ files = [
 
 [[package]]
 name = "marshmallow"
-version = "3.21.1"
+version = "3.21.2"
 description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "marshmallow-3.21.1-py3-none-any.whl", hash = "sha256:f085493f79efb0644f270a9bf2892843142d80d7174bbbd2f3713f2a589dc633"},
-    {file = "marshmallow-3.21.1.tar.gz", hash = "sha256:4e65e9e0d80fc9e609574b9983cf32579f305c718afb30d7233ab818571768c3"},
+    {file = "marshmallow-3.21.2-py3-none-any.whl", hash = "sha256:70b54a6282f4704d12c0a41599682c5c5450e843b9ec406308653b47c59648a1"},
+    {file = "marshmallow-3.21.2.tar.gz", hash = "sha256:82408deadd8b33d56338d2182d455db632c6313aa2af61916672146bb32edc56"},
 ]
 
 [package.dependencies]
@@ -4031,7 +4039,7 @@ packaging = ">=17.0"
 
 [package.extras]
 dev = ["marshmallow[tests]", "pre-commit (>=3.5,<4.0)", "tox"]
-docs = ["alabaster (==0.7.16)", "autodocsumm (==0.2.12)", "sphinx (==7.2.6)", "sphinx-issues (==4.0.0)", "sphinx-version-warning (==1.1.2)"]
+docs = ["alabaster (==0.7.16)", "autodocsumm (==0.2.12)", "sphinx (==7.3.7)", "sphinx-issues (==4.1.0)", "sphinx-version-warning (==1.1.2)"]
 tests = ["pytest", "pytz", "simplejson"]
 
 [[package]]
@@ -4293,13 +4301,13 @@ files = [
 
 [[package]]
 name = "msoffcrypto-tool"
-version = "5.3.1"
-description = "Python tool and library for decrypting MS Office files with passwords or other keys"
+version = "5.4.0"
+description = "Python tool and library for decrypting and encrypting MS Office files using a password or other keys"
 optional = false
-python-versions = ">=3.8,<4.0"
+python-versions = "<4.0,>=3.8"
 files = [
-    {file = "msoffcrypto_tool-5.3.1-py3-none-any.whl", hash = "sha256:4e44c10e38ca06d0ea511a31ee8834bfdedaf304b1369a0d3919db4f495dd5e4"},
-    {file = "msoffcrypto_tool-5.3.1.tar.gz", hash = "sha256:f800ff133b9a753dfedff6a37b0f79bfeb8cc6856487b91dd486110c7d4f4099"},
+    {file = "msoffcrypto_tool-5.4.0-py3-none-any.whl", hash = "sha256:0e39319f982c22a449505e5ab7da18a8ae76376a0008e180e1528a0875525da7"},
+    {file = "msoffcrypto_tool-5.4.0.tar.gz", hash = "sha256:0f5f45d91d1eaa2ca0b3adefb5aac4932afb50c678dfa8d7da390d187f1dac39"},
 ]
 
 [package.dependencies]
@@ -4865,13 +4873,13 @@ sympy = "*"
 
 [[package]]
 name = "openai"
-version = "1.20.0"
+version = "1.26.0"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.7.1"
 files = [
-    {file = "openai-1.20.0-py3-none-any.whl", hash = "sha256:9fcc75256b2425393800e358cd520b02b5ab1a8731921e45aa7ae6aec3ee8187"},
-    {file = "openai-1.20.0.tar.gz", hash = "sha256:d7c0e824b7da3c043731943965c737595cf9631c913b7a1464c502fdf492b9a9"},
+    {file = "openai-1.26.0-py3-none-any.whl", hash = "sha256:884ced523fb0225780f8b0e0ed6f7e014049c32d049a41ad0ac962869f1055d1"},
+    {file = "openai-1.26.0.tar.gz", hash = "sha256:642e857b60855702ee6ff665e8fa80946164f77b92e58fd24e01b545685b8405"},
 ]
 
 [package.dependencies]
@@ -5928,13 +5936,13 @@ pyasn1 = ">=0.4.6,<0.7.0"
 
 [[package]]
 name = "pyautogen"
-version = "0.2.26"
+version = "0.2.27"
 description = "Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework"
 optional = false
 python-versions = "<3.13,>=3.8"
 files = [
-    {file = "pyautogen-0.2.26-py3-none-any.whl", hash = "sha256:290e606ea357edc895aefd2408a3488e60cd25285e38dae12d155738f1471a4d"},
-    {file = "pyautogen-0.2.26.tar.gz", hash = "sha256:4e3079065973977161b2651ba7cc15672540e17395b510dd861df32318faa0f0"},
+    {file = "pyautogen-0.2.27-py3-none-any.whl", hash = "sha256:9eb5c38544a0f79475c43442f9c5af2623165e32a7b9dd24ec141492f603a630"},
+    {file = "pyautogen-0.2.27.tar.gz", hash = "sha256:a8939d14fed1893109738a4c34ce490bfc6d869fd8a4ecb22932b86c81d9a5a5"},
 ]
 
 [package.dependencies]
@@ -5942,7 +5950,7 @@ diskcache = "*"
 docker = "*"
 flaml = "*"
 numpy = ">=1.17.0,<2"
-openai = ">=1.3,<1.21"
+openai = ">=1.3"
 pydantic = ">=1.10,<2.6.0 || >2.6.0,<3"
 python-dotenv = "*"
 termcolor = "*"
@@ -5959,10 +5967,10 @@ lmm = ["pillow", "replicate"]
 mathchat = ["pydantic (==1.10.9)", "sympy", "wolframalpha"]
 redis = ["redis"]
 retrievechat = ["beautifulsoup4", "chromadb", "ipython", "markdownify", "pypdf", "sentence-transformers"]
-retrievechat-pgvector = ["beautifulsoup4", "ipython", "markdownify", "pgvector (>=0.2.5)", "psycopg (>=3.1.18)", "pypdf", "sentence-transformers"]
-retrievechat-qdrant = ["beautifulsoup4", "ipython", "markdownify", "pypdf", "qdrant-client[fastembed]", "sentence-transformers"]
+retrievechat-pgvector = ["beautifulsoup4", "chromadb", "ipython", "markdownify", "pgvector (>=0.2.5)", "psycopg (>=3.1.18)", "pypdf", "sentence-transformers"]
+retrievechat-qdrant = ["beautifulsoup4", "chromadb", "ipython", "markdownify", "pypdf", "qdrant-client[fastembed]", "sentence-transformers"]
 teachable = ["chromadb"]
-test = ["coverage (>=5.3)", "ipykernel", "nbconvert", "nbformat", "pandas", "pre-commit", "pytest (>=6.1.1,<8)", "pytest-asyncio"]
+test = ["ipykernel", "nbconvert", "nbformat", "pandas", "pre-commit", "pytest (>=6.1.1,<8)", "pytest-asyncio", "pytest-cov (>=5)"]
 types = ["ipykernel (>=6.29.0)", "jupyter-client (>=8.6.0)", "jupyter-kernel-gateway", "mypy (==1.9.0)", "pytest (>=6.1.1,<8)", "requests", "websocket-client"]
 websockets = ["websockets (>=12.0,<13)"]
 websurfer = ["beautifulsoup4", "markdownify", "pathvalidate", "pdfminer.six"]
@@ -6150,86 +6158,85 @@ yaml = ["pyyaml (>=6.0.1)"]
 
 [[package]]
 name = "pygments"
-version = "2.17.2"
+version = "2.18.0"
 description = "Pygments is a syntax highlighting package written in Python."
 optional = false
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+    {file = "SQLAlchemy-2.0.30-py3-none-any.whl", hash = "sha256:7108d569d3990c71e26a42f60474b4c02c8586c4681af5fd67e51a044fdea86a"},
+    {file = "SQLAlchemy-2.0.30.tar.gz", hash = "sha256:2b1708916730f4830bc69d6f49d37f7698b5bd7530aca7f04f785f8849e95255"},
 ]
 
 [package.dependencies]
@@ -7684,13 +7681,13 @@ test = ["pylint", "pytest", "pytest-black", "pytest-cov", "pytest-pylint"]
 
 [[package]]
 name = "supabase"
-version = "2.4.3"
+version = "2.4.5"
 description = "Supabase client for Python."
 optional = false
 python-versions = "<4.0,>=3.8"
 files = [
-    {file = "supabase-2.4.3-py3-none-any.whl", hash = "sha256:31b7cf5577471f473e690e6afb1b2f8ffe881a5a81f2c33a5fa7b07ba0fb9857"},
-    {file = "supabase-2.4.3.tar.gz", hash = "sha256:ee9a5db8ecc3de20fe8351b0d3bc7667809095322915cea753f83db310494001"},
+    {file = "supabase-2.4.5-py3-none-any.whl", hash = "sha256:100441c36bf3390b040818c636c372a91645d18b6a9e0c12cea061fb00db664c"},
+    {file = "supabase-2.4.5.tar.gz", hash = "sha256:8520b5a194c6d8fdbdd71b45aefc8b5a42d1a6711a2c693b6d299aeb785e8532"},
 ]
 
 [package.dependencies]
@@ -7758,17 +7755,18 @@ files = [
 
 [[package]]
 name = "tenacity"
-version = "8.2.3"
+version = "8.3.0"
 description = "Retry code until it succeeds"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "tenacity-8.2.3-py3-none-any.whl", hash = "sha256:ce510e327a630c9e1beaf17d42e6ffacc88185044ad85cf74c0a8887c6a0f88c"},
-    {file = "tenacity-8.2.3.tar.gz", hash = "sha256:5398ef0d78e63f40007c1fb4c0bff96e1911394d2fa8d194f77619c05ff6cc8a"},
+    {file = "tenacity-8.3.0-py3-none-any.whl", hash = "sha256:3649f6443dbc0d9b01b9d8020a9c4ec7a1ff5f6f3c6c8a036ef371f573fe9185"},
+    {file = "tenacity-8.3.0.tar.gz", hash = "sha256:953d4e6ad24357bceffbc9707bc74349aca9d245f68eb65419cf0c249a1949a2"},
 ]
 
 [package.extras]
-doc = ["reno", "sphinx", "tornado (>=4.5)"]
+doc = ["reno", "sphinx"]
+test = ["pytest", "tornado (>=4.5)", "typeguard"]
 
 [[package]]
 name = "termcolor"
@@ -8051,13 +8049,13 @@ files = [
 
 [[package]]
 name = "tqdm"
-version = "4.66.2"
+version = "4.66.4"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tqdm-4.66.2-py3-none-any.whl", hash = "sha256:1ee4f8a893eb9bef51c6e35730cebf234d5d0b6bd112b0271e10ed7c24a02bd9"},
-    {file = "tqdm-4.66.2.tar.gz", hash = "sha256:6cd52cdf0fef0e0f543299cfc96fec90d7b8a7e88745f411ec33eb44d5ed3531"},
+    {file = "tqdm-4.66.4-py3-none-any.whl", hash = "sha256:b75ca56b413b030bc3f00af51fd2c1a1a5eac6a0c1cca83cbb37a5c52abce644"},
+    {file = "tqdm-4.66.4.tar.gz", hash = "sha256:e4d936c9de8727928f3be6079590e97d9abfe8d39a590be678eb5919ffc186bb"},
 ]
 
 [package.dependencies]
@@ -8086,13 +8084,13 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
 
 [[package]]
 name = "transformers"
-version = "4.40.1"
+version = "4.40.2"
 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
 optional = true
 python-versions = ">=3.8.0"
 files = [
-    {file = "transformers-4.40.1-py3-none-any.whl", hash = "sha256:9d5ee0c8142a60501faf9e49a0b42f8e9cb8611823bce4f195a9325a6816337e"},
-    {file = "transformers-4.40.1.tar.gz", hash = "sha256:55e1697e6f18b58273e7117bb469cdffc11be28995462d8d5e422fef38d2de36"},
+    {file = "transformers-4.40.2-py3-none-any.whl", hash = "sha256:71cb94301ec211a2e1d4b8c8d18dcfaa902dfa00a089dceca167a8aa265d6f2d"},
+    {file = "transformers-4.40.2.tar.gz", hash = "sha256:657b6054a2097671398d976ad46e60836e7e15f9ea9551631a96e33cb9240649"},
 ]
 
 [package.dependencies]
@@ -8654,13 +8652,13 @@ test = ["Cython (>=0.29.36,<0.30.0)", "aiohttp (==3.9.0b0)", "aiohttp (>=3.8.1)"
 
 [[package]]
 name = "validators"
-version = "0.28.0"
+version = "0.28.1"
 description = "Python Data Validation for Humans™"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "validators-0.28.0-py3-none-any.whl", hash = "sha256:e0184691dea3ba82b52c161ba81d3ec1d8be8da9609f0137d1430b395b366521"},
-    {file = "validators-0.28.0.tar.gz", hash = "sha256:85bc82511f6ccd0800f4c15d8c0dc546c15e369640c5ea1f24349ba0b3b17815"},
+    {file = "validators-0.28.1-py3-none-any.whl", hash = "sha256:890c98789ad884037f059af6ea915ec2d667129d509180c2c590b8009a4c4219"},
+    {file = "validators-0.28.1.tar.gz", hash = "sha256:5ac88e7916c3405f0ce38ac2ac82a477fcf4d90dbbeddd04c8193171fc17f7dc"},
 ]
 
 [[package]]
@@ -8774,13 +8772,13 @@ files = [
 
 [[package]]
 name = "weaviate-client"
-version = "4.5.6"
+version = "4.5.7"
 description = "A python native Weaviate client"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "weaviate_client-4.5.6-py3-none-any.whl", hash = "sha256:bdafbf94343f621ca68bc547b5c9a5272dc6ca7953ad6a228f5ad8179021de68"},
-    {file = "weaviate_client-4.5.6.tar.gz", hash = "sha256:32a2b328f0a6637228c064e04aa6004c4ba733469b81754ae4598750735a9624"},
+    {file = "weaviate_client-4.5.7-py3-none-any.whl", hash = "sha256:97958050d215ab64d702e5dd29206c4b855a3372d3ae22f784287a2d0ed085dc"},
+    {file = "weaviate_client-4.5.7.tar.gz", hash = "sha256:130f7371c4af31949e6f3537683813f0e5adb7ec94a5536e2278768c5fe057bf"},
 ]
 
 [package.dependencies]
@@ -8788,10 +8786,10 @@ authlib = ">=1.2.1,<2.0.0"
 grpcio = ">=1.57.0,<2.0.0"
 grpcio-health-checking = ">=1.57.0,<2.0.0"
 grpcio-tools = ">=1.57.0,<2.0.0"
-httpx = "0.27.0"
+httpx = ">=0.25.0,<=0.27.0"
 pydantic = ">=2.5.0,<3.0.0"
 requests = ">=2.30.0,<3.0.0"
-validators = "0.28.0"
+validators = "0.28.1"
 
 [[package]]
 name = "websocket-client"
@@ -8889,13 +8887,13 @@ files = [
 
 [[package]]
 name = "werkzeug"
-version = "3.0.2"
+version = "3.0.3"
 description = "The comprehensive WSGI web application library."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "werkzeug-3.0.2-py3-none-any.whl", hash = "sha256:3aac3f5da756f93030740bc235d3e09449efcf65f2f55e3602e1d851b8f48795"},
-    {file = "werkzeug-3.0.2.tar.gz", hash = "sha256:e39b645a6ac92822588e7b39a692e7828724ceae0b0d702ef96701f90e70128d"},
+    {file = "werkzeug-3.0.3-py3-none-any.whl", hash = "sha256:fc9645dc43e03e4d630d23143a04a7f947a9a3b5727cd535fdfe155a17cc48c8"},
+    {file = "werkzeug-3.0.3.tar.gz", hash = "sha256:097e5bfda9f0aba8da6b8545146def481d06aa7d3266e7448e2cccf67dd8bd18"},
 ]
 
 [package.dependencies]
@@ -9233,4 +9231,4 @@ local = ["ctransformers", "llama-cpp-python", "sentence-transformers"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9,<3.12"
-content-hash = "1c79f55577a8fa603c09b2b7c02a01a7a397960c6c9c134dcee7e2f6eeea3d9e"
+content-hash = "9e44217b28f8d17704c4c8a7748d94f0bd8a61ca70de62c7be6ee0f65c826f2d"
diff --git a/pyproject.toml b/pyproject.toml
index c21e18faa89..31b75de3dbb 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langflow"
-version = "0.6.18"
+version = "0.6.19"
 description = "A Python package with a built-in web application"
 authors = ["Logspace <contact@logspace.ai>"]
 maintainers = [
@@ -105,6 +105,7 @@ llama-index = "0.9.48"
 langchain-openai = "^0.0.6"
 urllib3 = "<2"
 langchain-anthropic = "^0.1.4"
+langchain-pinecone = "^0.1.0"
 
 [tool.poetry.group.dev.dependencies]
 pytest-asyncio = "^0.23.1"
diff --git a/src/backend/langflow/components/vectorstores/Pinecone.py b/src/backend/langflow/components/vectorstores/Pinecone.py
index 147af1df847..f886905f05c 100644
--- a/src/backend/langflow/components/vectorstores/Pinecone.py
+++ b/src/backend/langflow/components/vectorstores/Pinecone.py
@@ -1,63 +1,145 @@
-import os
 from typing import List, Optional, Union
 
-import pinecone  # type: ignore
 from langchain.schema import BaseRetriever
 from langchain_community.vectorstores import VectorStore
-from langchain_community.vectorstores.pinecone import Pinecone
-from langflow import CustomComponent
-from langflow.field_typing import Document, Embeddings
+from langchain_core.documents import Document
+from langchain_pinecone._utilities import DistanceStrategy
+from langchain_pinecone.vectorstores import PineconeVectorStore
+
+from langflow.field_typing import Embeddings
+from langflow.interface.custom.custom_component import CustomComponent
 
 
 class PineconeComponent(CustomComponent):
     display_name = "Pinecone"
     description = "Construct Pinecone wrapper from raw documents."
+    icon = "Pinecone"
+    field_order = ["index_name", "namespace", "distance_strategy", "pinecone_api_key", "documents", "embedding"]
 
     def build_config(self):
+        distance_options = [e.value.title().replace("_", " ") for e in DistanceStrategy]
+        distance_value = distance_options[0]
         return {
-            "documents": {"display_name": "Documents"},
+            "inputs": {"display_name": "Input", "input_types": ["Document", "Record"]},
             "embedding": {"display_name": "Embedding"},
             "index_name": {"display_name": "Index Name"},
             "namespace": {"display_name": "Namespace"},
-            "pinecone_api_key": {"display_name": "Pinecone API Key", "default": "", "password": True, "required": True},
-            "pinecone_env": {"display_name": "Pinecone Environment", "default": "", "required": True},
-            "search_kwargs": {"display_name": "Search Kwargs", "default": "{}"},
-            "pool_threads": {"display_name": "Pool Threads", "default": 1, "advanced": True},
+            "text_key": {"display_name": "Text Key"},
+            "distance_strategy": {
+                "display_name": "Distance Strategy",
+                # get values from enum
+                # and make them title case for display
+                "options": distance_options,
+                "advanced": True,
+                "value": distance_value,
+            },
+            "pinecone_api_key": {
+                "display_name": "Pinecone API Key",
+                "default": "",
+                "password": True,
+                "required": True,
+            },
+            "pool_threads": {
+                "display_name": "Pool Threads",
+                "default": 1,
+                "advanced": True,
+            },
         }
 
-    def build(
+    def from_existing_index(
         self,
+        index_name: str,
         embedding: Embeddings,
-        pinecone_env: str,
+        pinecone_api_key: str | None,
+        text_key: str = "text",
+        namespace: Optional[str] = None,
+        distance_strategy: DistanceStrategy = DistanceStrategy.COSINE,
+        pool_threads: int = 4,
+    ) -> PineconeVectorStore:
+        """Load pinecone vectorstore from index name."""
+        pinecone_index = PineconeVectorStore.get_pinecone_index(
+            index_name, pool_threads, pinecone_api_key=pinecone_api_key
+        )
+        return PineconeVectorStore(
+            index=pinecone_index,
+            embedding=embedding,
+            text_key=text_key,
+            namespace=namespace,
+            distance_strategy=distance_strategy,
+        )
+
+    def from_documents(
+        self,
         documents: List[Document],
+        embedding: Embeddings,
+        index_name: str,
+        pinecone_api_key: str | None,
+        text_key: str = "text",
+        namespace: Optional[str] = None,
+        pool_threads: int = 4,
+        distance_strategy: DistanceStrategy = DistanceStrategy.COSINE,
+        batch_size: int = 32,
+        upsert_kwargs: Optional[dict] = None,
+        embeddings_chunk_size: int = 1000,
+    ) -> PineconeVectorStore:
+        """Create a new pinecone vectorstore from documents."""
+        texts = [d.page_content for d in documents]
+        metadatas = [d.metadata for d in documents]
+        pinecone = self.from_existing_index(
+            index_name=index_name,
+            embedding=embedding,
+            pinecone_api_key=pinecone_api_key,
+            text_key=text_key,
+            namespace=namespace,
+            distance_strategy=distance_strategy,
+            pool_threads=pool_threads,
+        )
+        pinecone.add_texts(
+            texts,
+            metadatas=metadatas,
+            ids=None,
+            namespace=namespace,
+            batch_size=batch_size,
+            embedding_chunk_size=embeddings_chunk_size,
+            **(upsert_kwargs or {}),
+        )
+        return pinecone
+
+    def build(
+        self,
+        embedding: Embeddings,
+        distance_strategy: str,
+        documents: Optional[List[Document]] = None,
         text_key: str = "text",
         pool_threads: int = 4,
         index_name: Optional[str] = None,
         pinecone_api_key: Optional[str] = None,
         namespace: Optional[str] = "default",
-    ) -> Union[VectorStore, Pinecone, BaseRetriever]:
-        if pinecone_api_key is None or pinecone_env is None:
-            raise ValueError("Pinecone API Key and Environment are required.")
-        if os.getenv("PINECONE_API_KEY") is None and pinecone_api_key is None:
-            raise ValueError("Pinecone API Key is required.")
-
-        pinecone.init(api_key=pinecone_api_key, environment=pinecone_env)  # type: ignore
+    ) -> Union[VectorStore, BaseRetriever]:
+        # get distance strategy from string
+        distance_strategy = distance_strategy.replace(" ", "_").upper()
+        _distance_strategy = DistanceStrategy[distance_strategy]
         if not index_name:
             raise ValueError("Index Name is required.")
+
         if documents:
-            return Pinecone.from_documents(
+            return self.from_documents(
                 documents=documents,
                 embedding=embedding,
                 index_name=index_name,
-                pool_threads=pool_threads,
-                namespace=namespace,
+                pinecone_api_key=pinecone_api_key,
                 text_key=text_key,
+                namespace=namespace,
+                distance_strategy=_distance_strategy,
+                pool_threads=pool_threads,
             )
 
-        return Pinecone.from_existing_index(
+        return self.from_existing_index(
             index_name=index_name,
             embedding=embedding,
+            pinecone_api_key=pinecone_api_key,
             text_key=text_key,
             namespace=namespace,
+            distance_strategy=_distance_strategy,
             pool_threads=pool_threads,
         )