oracle · garethoracle · Sep 10, 2026 · Sep 10, 2026
diff --git a/README.md b/README.md
@@ -33,25 +33,6 @@ pip install oracle-vecdb
 uv add oracle-vecdb
 ```
 
-### Connect
-### Requirements
-
-- **Python:** 3.10+
-- **Oracle AI Database:** 23.26.3+
-- **ORDS:** 26.2.2+
-
-### Installation
-
-Install with `pip` or `uv`:
-
-```bash
-# pip
-pip install oracle-vecdb
-
-# uv
-uv add oracle-vecdb
-```
-
 ### Connect
 
 ```python
@@ -60,27 +41,21 @@ from oracle_vecdb import OracleVecDB, Configuration
 config = Configuration(
     rest_url="https://<host>:<port>/ords/<schema>/_/db-api/stable/vecdb/",
     access_token="<access-token>",
-    access_token="<access-token>",
 )
 
 vecdb = OracleVecDB(config)
 ```
 
 ### Run a semantic search with metadata filtering
 
-> This example assumes a vector table named demo already exists and contains data. See the [full quickstart](https://docs.oracle.com/en/cloud/paas/autonomous-vector-database/vcapi/quickstart.html) for create_vector_table() and upsert().
-### Run a semantic search with metadata filtering
-
 > This example assumes a vector table named demo already exists and contains data. See the [full quickstart](https://docs.oracle.com/en/cloud/paas/autonomous-vector-database/vcapi/quickstart.html) for create_vector_table() and upsert().
 
 ```python
 results = vecdb.query(
     table_name="demo",
     query_by={"text": "family film"},  # uses integrated embeddings for the query text
-    query_by={"text": "family film"},  # uses integrated embeddings for the query text
     filters={"genre": {"$eq": "drama"}},
     top_k=3,
-    top_k=3,
 )
 
 for index in range(len(results)):
@@ -202,120 +177,6 @@ Learn Oracle VecDB hands-on. The Oracle AI Developer Hub includes runnable noteb
 
 [Browse all VecDB notebooks →](https://github.com/oracle-devrel/oracle-ai-developer-hub/tree/main/notebooks/vecdb)
 
----
-### ⚡ **Integrated embeddings. Automatic vector indexing. Semantic search + structured filtering. One Python SDK.**
-
-[Read the full quickstart →](https://docs.oracle.com/en/cloud/paas/autonomous-vector-database/vcapi/quickstart.html)
-
----
-
-# 🧪 See what you can build
-
-Complete applications built with `oracle-vecdb` are available in the [Oracle AI Developer Hub](https://github.com/oracle-devrel/oracle-ai-developer-hub/tree/main/apps/vecdb).
-
-## 🌲 Semantic + Geospatial Search
-
-**Combine vector similarity with spatial filtering in one application.**
-
-Semantic search plus geographic and structured constraints, powered by Oracle AI Database.
-
-![Ask the Parks — semantic, metadata, and spatial search with Oracle VecDB](https://raw.githubusercontent.com/oracle-devrel/oracle-ai-developer-hub/main/apps/vecdb/vecdb_ask_parks/static/assets/ask_the_parks_demo.gif)
-
-**Oracle Spatial · Vector Search · Oracle VecDB**
-
-[View the sample app →](https://github.com/oracle-devrel/oracle-ai-developer-hub/tree/main/apps/vecdb/vecdb_ask_parks)
-
----
-
-## 💻 Semantic Code Search
-
-**Search source code by meaning, not just keywords.**
-
-Use natural-language queries to find relevant functions, files, and surrounding code.
-
-![Semantic Code Search - natural-language query, ranked code results, repository navigation, and highlighted source code](https://raw.githubusercontent.com/oracle-devrel/oracle-ai-developer-hub/main/apps/vecdb/semantic_code_search/images/semantic_code_search.gif)
-
-**FastAPI · React · Jina Embeddings · Oracle VecDB**
-
-[View the sample app →](https://github.com/oracle-devrel/oracle-ai-developer-hub/tree/main/apps/vecdb/semantic_code_search)
-
----
-
-## 🤖 RAG Document Chatbot
-
-**Upload documents and ask grounded questions over their content.**
-
-Chunk documents, generate embeddings, retrieve relevant context, and pass it to an LLM for grounded answers.
-
-![Document Chatbot UI showing uploaded documents, a user question, retrieved context, and a grounded answer](https://raw.githubusercontent.com/oracle-devrel/oracle-ai-developer-hub/main/apps/vecdb/doc_chatbot/images/doc_chat_bot.gif)
-
-**Streamlit · OpenAI / Ollama · Oracle VecDB**
-
-[View the sample app →](https://github.com/oracle-devrel/oracle-ai-developer-hub/tree/main/apps/vecdb/doc_chatbot)
-
----
-
-**More examples:** Multi-Modal Product Search, Product Recommendations · hands-on notebooks
-
-[Explore all sample applications →](https://github.com/oracle-devrel/oracle-ai-developer-hub/tree/main/apps/vecdb)
-
----
-
-# 💡 Why Oracle VecDB?
-
-Modern AI applications often need vector search plus the structured data around each result.
-
-Oracle VecDB lets Python applications use vector search alongside relational, spatial, and all other capabilities of the Oracle AI Database.
-
-Use Oracle VecDB to:
-
-- 🔎 Run semantic and similarity search
-- 🌍 Combine vector search with spatial and structured queries
-- 🤖 Build RAG applications and AI agents
-- 🧠 Use integrated embeddings or bring your own vectors
-- ⚡ Create vector indexes automatically by default
-- 🎛️ Tune HNSW and embedding settings when needed
-
-If you're building enterprise AI apps, the data you need is probably already in an Oracle AI Database, VecDB can reduce the need to move or synchronize that data into a separate vector database.
-
----
-
-# 📓 Hands-on notebooks
-
-Learn Oracle VecDB hands-on. The Oracle AI Developer Hub includes runnable notebooks that take you from first query to production-oriented tuning.
-
-## 🧠 Embeddings & RAG
-
-- **Integrated embeddings** — generate embeddings as part of the VecDB workflow
-- **Bring Your Own Vectors** — use embeddings from your preferred model or provider
-- **Gemini RAG** — build retrieval-augmented generation with Gemini
-- **OCI Generative AI embeddings** — use OCI-hosted embedding models with VecDB
-- **Oracle Private AI Services Container** - use in an air-gapped environment with OpenAI-style inference layer
-
-[Explore embeddings & RAG notebooks →](https://github.com/oracle-devrel/oracle-ai-developer-hub/tree/main/notebooks/vecdb)
-
-## 🔎 Search & filtering
-
-- **Semantic search** — retrieve results by meaning rather than keywords
-- **Metadata filtering** — combine vector similarity with structured constraints
-- **Search diagnostics** — inspect and understand vector-search behavior
-- **Financial-data search** — apply vector retrieval to structured financial datasets
-
-[Explore search notebooks →](https://github.com/oracle-devrel/oracle-ai-developer-hub/tree/main/notebooks/vecdb)
-
-## ⚡ Performance & scale
-
-- **HNSW tuning** — understand and tune vector-index search parameters
-- **Bulk vector loading** — compare approaches for loading larger datasets
-- **Index management** — create, inspect, and manage vector indexes
-- **Maintenance workflows** — operate vector tables and indexes over time
-
-[Explore performance notebooks →](https://github.com/oracle-devrel/oracle-ai-developer-hub/tree/main/notebooks/vecdb)
-
-> **New to Oracle VecDB?** Start with integrated embeddings and semantic search, then move on to filtering and HNSW tuning.
-
-[Browse all VecDB notebooks →](https://github.com/oracle-devrel/oracle-ai-developer-hub/tree/main/notebooks/vecdb)
-
 ---
 
 ## Examples
@@ -335,18 +196,6 @@ Learn Oracle VecDB hands-on. The Oracle AI Developer Hub includes runnable noteb
 - **[GitHub Releases](https://github.com/oracle/vecdb-python-sdk/releases)**
 - **[Locally-managed REST](https://docs.oracle.com/en/database/oracle/oracle-rest-data-services/26.2/)**
 
----
----
-
-# 📚 Documentation
-
-- **[Getting Started](https://docs.oracle.com/en/cloud/paas/autonomous-vector-database/vcapi/quickstart.html)**
-- **[Python API Reference](https://docs.oracle.com/en/cloud/paas/autonomous-vector-database/vcapi/python-api-reference.html)**
-- **[Sample Applications](https://github.com/oracle-devrel/oracle-ai-developer-hub/tree/main/apps/vecdb)**
-- **[Hands-on Notebooks](https://github.com/oracle-devrel/oracle-ai-developer-hub/tree/main/notebooks/vecdb)**
-- **[GitHub Releases](https://github.com/oracle/vecdb-python-sdk/releases)**
-- **[Locally-managed REST](https://docs.oracle.com/en/database/oracle/oracle-rest-data-services/26.2/)**
-
 ---
 
 ## Help
@@ -357,8 +206,6 @@ Problem reports can be raised in [GitHub Issues](https://github.com/oracle/vecdb
 
 ---
 
----
-
 ## 🤝 Contributing
 
 This project welcomes contributions from the community. Before submitting a pull request, please [review our contribution guide](./CONTRIBUTING.md)
@@ -367,18 +214,12 @@ This project welcomes contributions from the community. Before submitting a pull
 
 ---
 
-[Open an issue →](https://github.com/oracle/vecdb-python-sdk/issues)
-
----
-
 ## 🔐 Security
 
 Please consult the [security guide](./SECURITY.md) for our responsible security vulnerability disclosure process
 
 ---
 
----
-
 ## 📄 License
 
 See [LICENSE.txt](./LICENSE.txt), [THIRD_PARTY_LICENSE.txt](./THIRD_PARTY_LICENSE.txt), and [NOTICE.txt](./NOTICE.txt).
@@ -390,11 +231,3 @@ See [LICENSE.txt](./LICENSE.txt), [THIRD_PARTY_LICENSE.txt](./THIRD_PARTY_LICENS
 **[Star `oracle/vecdb-python-sdk` →](https://github.com/oracle/vecdb-python-sdk)**
 
 It helps you follow the project and helps other Python and AI developers discover it.
-
----
-
-## ⭐ Like Oracle VecDB?
-
-**[Star `oracle/vecdb-python-sdk` →](https://github.com/oracle/vecdb-python-sdk)**
-
-It helps you follow the project and helps other Python and AI developers discover it.