Added content to README

CONTRIBUTING.md

@@ -0,0 +1,69 @@
+# Contributing to the Neo4j Ecosystem
+
+At [Neo4j](https://neo4j.com/), we develop our software in the open at GitHub.
+This provides transparency for you, our users, and allows you to fork the software to make your own additions and enhancements.
+We also provide areas specifically for community contributions, in particular the [neo4j-contrib](https://github.com/neo4j-contrib) space.
+
+There's an active [Neo4j Online Community](https://community.neo4j.com/) where we work directly with the community.
+If you're not already a member, sign up!
+
+We love our community and wouldn't be where we are without you.
+
+
+## Need to raise an issue?
+
+Where you raise an issue depends largely on the nature of the problem.
+
+Firstly, if you are an Enterprise customer, you might want to head over to our [Customer Support Portal](https://support.neo4j.com/).
+
+There are plenty of public channels available too, though.
+If you simply want to get started or have a question on how to use a particular feature, ask a question in [Neo4j Online Community](https://community.neo4j.com/).
+If you think you might have hit a bug in our software (it happens occasionally!) or you have specific feature request then use the issue feature on the relevant GitHub repository.
+Check first though as someone else may have already raised something similar.
+
+[StackOverflow](https://stackoverflow.com/questions/tagged/neo4j) also hosts a ton of questions and might already have a discussion around your problem.
+Make sure you have a look there too.
+
+Include as much information as you can in any request you make:
+
+- Which versions of our products are you using?
+- Which language (and which version of that language) are you developing with?
+- What operating system are you on?
+- Are you working with a cluster or on a single machine?
+- What code are you running?
+- What errors are you seeing?
+- What solutions have you tried already?
+
+
+## Want to contribute?
+
+If you want to contribute a pull request, we have a little bit of process you'll need to follow:
+
+- Do all your work in a personal fork of the original repository
+- [Rebase](https://github.com/edx/edx-platform/wiki/How-to-Rebase-a-Pull-Request), don't merge (we prefer to keep our history clean)
+- Create a branch (with a useful name) for your contribution
+- Make sure you're familiar with the appropriate coding style (this varies by language so ask if you're in doubt)
+- Include unit tests if appropriate (obviously not necessary for documentation changes)
+- Take a moment to read and sign our [CLA](https://neo4j.com/developer/cla)
+
+We can't guarantee that we'll accept pull requests and may ask you to make some changes before they go in.
+Occasionally, we might also have logistical, commercial, or legal reasons why we can't accept your work but we'll try to find an alternative way for you to contribute in that case.
+Remember that many community members have become regular contributors and some are now even Neo employees!
+
+
+## Specifically for this project
+Setting up the development environment:
+
+1. Install Python 3.9.1+
+2. Install poetry (see https://python-poetry.org/docs/#installation)
+3. Install dependencies:
+
+```shell
+poetry install
+```
+
+4. Install the pre-commit hook, that will do some code-format-checking everytime you commit.
+
+```shell
+pre-commit install
+```

README.md

@@ -1,3 +1,69 @@
 # Neo4j GenAI package for Python
 
 This repository contains the official Neo4j GenAI features for Python.
+
+## Installation
+
+This package requires Python (>=3.8.1).
+
+To install the latest stable version, use:
+
+```shell
+pip install neo4j-genai
+```
+
+## Example
+After setting up a Neo4j database instance:
+```python
+from neo4j import GraphDatabase
+from neo4j_genai import VectorRetriever
+
+from random import random
+
+from neo4j_genai.indexes import create_vector_index
+
+URI = "neo4j://localhost:7687"
+AUTH = ("neo4j", "password")
+
+INDEX_NAME = "embedding-name"
+DIMENSION = 1536
+
+# Connect to Neo4j database
+driver = GraphDatabase.driver(URI, auth=AUTH)
+
+# Creating the index
+create_vector_index(
+    driver,
+    INDEX_NAME,
+    label="Document",
+    property="propertyKey",
+    dimensions=DIMENSION,
+    similarity_fn="euclidean",
+)
+
+# Initialize the retriever
+retriever = VectorRetriever(driver, INDEX_NAME)
+
+# Upsert the vector
+vector = [random() for _ in range(DIMENSION)]
+insert_query = (
+    "MERGE (n:Document {id: $id})"
+    "WITH n "
+    "CALL db.create.setNodeVectorProperty(n, 'propertyKey', $vector)"
+    "RETURN n"
+)
+parameters = {
+    "id": 0,
+    "vector": vector,
+}
+driver.execute_query(insert_query, parameters)
+
+# Perform the similarity search for a vector query
+query_vector = [random() for _ in range(DIMENSION)]
+print(retriever.search(query_vector=query_vector, top_k=5))
+
+```
+
+## Further information
+- [The official Neo4j Python driver](https://github.com/neo4j/neo4j-python-driver)
+- [Neo4j GenAI integrations](https://neo4j.com/docs/cypher-manual/current/genai-integrations/)

examples/openai_search.py

@@ -34,13 +34,15 @@
 
 # Upsert the query
 vector = [random() for _ in range(DIMENSION)]
+
 insert_query = (
-    "MERGE (n:Document)"
+    "MERGE (n:Document {id: $id})"
     "WITH n "
     "CALL db.create.setNodeVectorProperty(n, 'propertyKey', $vector)"
     "RETURN n"
 )
 parameters = {
+    "id": 0,
     "vector": vector,
 }
 driver.execute_query(insert_query, parameters)

examples/similarity_search_for_text.py

@@ -40,12 +40,13 @@ def embed_query(self, text: str) -> List[float]:
 # Upsert the query
 vector = [random() for _ in range(DIMENSION)]
 insert_query = (
-    "MERGE (n:Document)"
+    "MERGE (n:Document {id: $id})"
     "WITH n "
     "CALL db.create.setNodeVectorProperty(n, 'propertyKey', $vector)"
     "RETURN n"
 )
 parameters = {
+    "id": 0,
     "vector": vector,
 }
 driver.execute_query(insert_query, parameters)

examples/similarity_search_for_vector.py

@@ -30,15 +30,15 @@
 # Upsert the vector
 vector = [random() for _ in range(DIMENSION)]
 insert_query = (
-    "MERGE (n:Document)"
+    "MERGE (n:Document {id: $id})"
     "WITH n "
     "CALL db.create.setNodeVectorProperty(n, 'propertyKey', $vector)"
     "RETURN n"
 )
 parameters = {
+    "id": 0,
     "vector": vector,
 }
-
 driver.execute_query(insert_query, parameters)
 
 # Perform the similarity search for a vector query