oracle · YouNeedCryDear · Jul 30, 2025 · Jul 9, 2025 · Jul 10, 2025 · Jul 10, 2025
diff --git a/.gitignore b/.gitignore
@@ -6,3 +6,4 @@ __pycache__
 .env
 .venv*
 .idea
+.coverage
diff --git a/README.md b/README.md
@@ -1,154 +1,47 @@
 # 🦜️🔗 LangChain 🤝 Oracle
 
-Welcome to the official repository for LangChain integration with [Oracle Cloud Infrastructure (OCI)](https://cloud.oracle.com/). This library provides native LangChain components for interacting with Oracle's AI services—combining support for **OCI Generative AI** and **OCI Data Science**.
+Welcome to the official repository for LangChain integration with [Oracle Cloud Infrastructure (OCI)](https://cloud.oracle.com/) and [Oracle AI Vector Search](https://www.oracle.com/database/ai-vector-search/). This project provides native LangChain components for interacting with Oracle's AI services—providing support for **OCI Generative AI**, **OCI Data Science** and **Oracle AI Vector Search**.
 
 ## Features
 
 - **LLMs**: Includes LLM classes for OCI services like [Generative AI](https://cloud.oracle.com/ai-services/generative-ai) and [ModelDeployment Endpoints](https://cloud.oracle.com/ai-services/model-deployment), allowing you to leverage their language models within LangChain.
 - **Agents**: Includes Runnables to support [Oracle Generative AI Agents](https://www.oracle.com/artificial-intelligence/generative-ai/agents/), allowing you to leverage Generative AI Agents within LangChain and LangGraph.
-- **More to come**: This repository will continue to expand and offer additional components for various OCI services as development progresses.
+- **Vector Search**: Offers native integration with [Oracle AI Vector Search](https://www.oracle.com/database/ai-vector-search/) through a LangChain-compatible components. This enables pipelines that can:
+    - Load the documents from various sources using `OracleDocLoader`
+    - Summarize content within/outside the database using `OracleSummary`
+    - Generate embeddings within/outside the database using `OracleEmbeddings`
+    - Chunk according to different requirements using Advanced Oracle Capabilities from `OracleTextSplitter`
+    - Store, index, and query vectors using `OracleVS`
+- **More to come**: This repository will continue to expand and offer additional components for various OCI and Oracle AI services as development progresses.
 
-> This project merges and replaces earlier OCI integrations from the `langchain-community` repository and unifies contributions from Oracle's GenAI and Data Science teams.
-> All integrations in this package assume that you have the credentials setup to connect with oci services.
+> This project merges and replaces earlier OCI and Oracle AI Vector Search integrations from the `langchain-community` repository and unifies contributions from Oracle teams.
+> All integrations in this package assume that you have the credentials setup to connect with oci and database services.
 
 ---
 
 ## Installation
 
+For OCI services:
 
 ```bash
-pip install -U langchain-oci
+python -m pip install -U langchain-oci
 ```
 
----
-
-## Quick Start
-
-This repository includes two main integration categories:
-
-- [OCI Generative AI](#oci-generative-ai-examples)
-- [OCI Data Science (Model Deployment)](#oci-data-science-model-deployment-examples)
-
-
----
-
-## OCI Generative AI Examples
-
-### 1. Use a Chat Model
-
-`ChatOCIGenAI` class exposes chat models from OCI Generative AI.
-
-```python
-from langchain_oci import ChatOCIGenAI
-
-llm = ChatOCIGenAI()
-llm.invoke("Sing a ballad of LangChain.")
-```
-
-### 2. Use a Completion Model
-`OCIGenAI` class exposes LLMs from OCI Generative AI.
-
-```python
-from langchain_oci import OCIGenAI
-
-llm = OCIGenAI()
-llm.invoke("The meaning of life is")
-```
+For Oracle AI Vector Search services:
 
-### 3. Use an Embedding Model
-`OCIGenAIEmbeddings` class exposes embeddings from OCI Generative AI.
-
-```python
-from langchain_oci import OCIGenAIEmbeddings
-
-embeddings = OCIGenAIEmbeddings()
-embeddings.embed_query("What is the meaning of life?")
-```
-
-
-## OCI Data Science Model Deployment Examples
-
-### 1. Use a Chat Model
-
-You may instantiate the OCI Data Science model with the generic `ChatOCIModelDeployment` or framework specific class like `ChatOCIModelDeploymentVLLM`.
-
-```python
-from langchain_oci.chat_models import ChatOCIModelDeployment, ChatOCIModelDeploymentVLLM
-
-# Create an instance of OCI Model Deployment Endpoint
-# Replace the endpoint uri with your own
-endpoint = "https://modeldeployment.<region>.oci.customer-oci.com/<ocid>/predict"
-
-messages = [
-    (
-        "system",
-        "You are a helpful assistant that translates English to French. Translate the user sentence.",
-    ),
-    ("human", "I love programming."),
-]
-
-chat = ChatOCIModelDeployment(
-    endpoint=endpoint,
-    streaming=True,
-    max_retries=1,
-    model_kwargs={
-        "temperature": 0.2,
-        "max_tokens": 512,
-    },  # other model params...
-    default_headers={
-        "route": "/v1/chat/completions",
-        # other request headers ...
-    },
-)
-chat.invoke(messages)
-
-chat_vllm = ChatOCIModelDeploymentVLLM(endpoint=endpoint)
-chat_vllm.invoke(messages)
-```
-
-### 2. Use a Completion Model
-You may instantiate the OCI Data Science model with `OCIModelDeploymentLLM` or `OCIModelDeploymentVLLM`.
-
-```python
-from langchain_oci.llms import OCIModelDeploymentLLM, OCIModelDeploymentVLLM
-
-# Create an instance of OCI Model Deployment Endpoint
-# Replace the endpoint uri and model name with your own
-endpoint = "https://modeldeployment.<region>.oci.customer-oci.com/<ocid>/predict"
-
-llm = OCIModelDeploymentLLM(
-    endpoint=endpoint,
-    model="odsc-llm",
-)
-llm.invoke("Who is the first president of United States?")
-
-vllm = OCIModelDeploymentVLLM(
-    endpoint=endpoint,
-)
-vllm.invoke("Who is the first president of United States?")
+```bash
+python -m pip install -U langchain-oracledb
 ```
 
-### 3. Use an Embedding Model
-You may instantiate the OCI Data Science model with the `OCIModelDeploymentEndpointEmbeddings`.
-
-```python
-from langchain_oci.embeddings import OCIModelDeploymentEndpointEmbeddings
-
-# Create an instance of OCI Model Deployment Endpoint
-# Replace the endpoint uri with your own
-endpoint = "https://modeldeployment.<region>.oci.customer-oci.com/<ocid>/predict"
-
-embeddings = OCIModelDeploymentEndpointEmbeddings(
-    endpoint=endpoint,
-)
+---
 
-query = "Hello World!"
-embeddings.embed_query(query)
+## Quick Start
 
-documents = ["This is a sample document", "and here is another one"]
-embeddings.embed_documents(documents)
-```
+This repository includes three main integration categories. For detailed information, please refer to the respective libraries:
 
+- [OCI Generative AI](https://github.com/oracle/langchain-oracle/tree/main/libs/oci)
+- [OCI Data Science (Model Deployment)](https://github.com/oracle/langchain-oracle/tree/main/libs/oci)
+- [Oracle AI Vector Search](https://github.com/oracle/langchain-oracle/tree/main/libs/oracledb)
 
 ## Contributing
 

diff --git a/libs/oracledb/LICENSE.txt b/libs/oracledb/LICENSE.txt
@@ -0,0 +1,35 @@
+Copyright (c) 2025 Oracle and/or its affiliates. All rights reserved.
+
+The Universal Permissive License (UPL), Version 1.0
+
+Subject to the condition set forth below, permission is hereby granted to any
+person obtaining a copy of this software, associated documentation and/or data
+(collectively the "Software"), free of charge and under any and all copyright
+rights in the Software, and any and all patent rights owned or freely
+licensable by each licensor hereunder covering either (i) the unmodified
+Software as contributed to or provided by such licensor, or (ii) the Larger
+Works (as defined below), to deal in both
+
+(a) the Software, and
+(b) any piece of software and/or hardware listed in the lrgrwrks.txt file if
+one is included with the Software (each a "Larger Work" to which the Software
+is contributed by such licensors),
+
+without restriction, including without limitation the rights to copy, create
+derivative works of, display, perform, and distribute the Software and make,
+use, sell, offer for sale, import, export, have made, and have sold the
+Software and the Larger Work(s), and to sublicense the foregoing rights on
+either these or other terms.
+
+This license is subject to the following condition:
+The above copyright notice and either this complete permission notice or at
+a minimum a reference to the UPL must be included in all copies or
+substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/libs/oracledb/Makefile b/libs/oracledb/Makefile
@@ -0,0 +1,59 @@
+.PHONY: all format lint test tests integration_tests help
+
+# Default target executed when no arguments are given to make.
+all: help
+
+# Define a variable for the test file path.
+TEST_FILE ?= tests/unit_tests/
+integration_test integration_tests: TEST_FILE = tests/integration_tests/
+
+test tests integration_test integration_tests:
+	poetry run pytest $(TEST_FILE)
+
+test_watch:
+	poetry run ptw --snapshot-update --now . -- -vv $(TEST_FILE)
+
+######################
+# LINTING AND FORMATTING
+######################
+
+# Define a variable for Python and notebook files.
+PYTHON_FILES=.
+MYPY_CACHE=.mypy_cache
+lint format: PYTHON_FILES=.
+lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/oracledb --name-only --diff-filter=d main | grep -E '\.py$$|\.ipynb$$')
+lint_package: PYTHON_FILES=langchain_oracledb
+lint_tests: PYTHON_FILES=tests
+lint_tests: MYPY_CACHE=.mypy_cache_test
+
+lint lint_diff lint_package lint_tests:
+	poetry run ruff .
+	poetry run ruff format $(PYTHON_FILES) --diff
+	poetry run ruff --select I $(PYTHON_FILES)
+	mkdir -p $(MYPY_CACHE); poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
+
+format format_diff:
+	poetry run ruff format $(PYTHON_FILES)
+	poetry run ruff --select I --fix $(PYTHON_FILES)
+
+spell_check:
+	poetry run codespell --toml pyproject.toml
+
+spell_fix:
+	poetry run codespell --toml pyproject.toml -w
+
+check_imports: $(shell find langchain_oracledb -name '*.py')
+	poetry run python ./scripts/check_imports.py $^
+
+######################
+# HELP
+######################
+
+help:
+	@echo '----'
+	@echo 'check_imports				- check imports'
+	@echo 'format                       - run code formatters'
+	@echo 'lint                         - run linters'
+	@echo 'test                         - run unit tests'
+	@echo 'tests                        - run unit tests'
+	@echo 'test TEST_FILE=<test_file>   - run all tests in file'
-Original file line number
+Diff line change
@@ Expand Up / @@ -6,3 +6,4 @@ __pycache__ @@
     .env
     .venv*
     .idea
+    .coverage