updated readme

README.md

@@ -1,3 +1,55 @@
 # Langchain with InterSystems IRIS
 
-[Langchain](https://github.com/langchain-ai/langchain) with support for InterSystems IRIS
+[Langchain](https://github.com/langchain-ai/langchain) with support for InterSystems IRIS
+
+
+## Install
+
+```shell
+pip install langchain-iris
+```
+
+## Example
+
+```python
+import os
+from dotenv import load_dotenv
+
+from langchain.docstore.document import Document
+from langchain.document_loaders import TextLoader
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.embeddings.fastembed import FastEmbedEmbeddings
+
+from langchain_iris import IRISVector
+
+loader = TextLoader("state_of_the_union.txt")
+documents = loader.load()
+text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
+docs = text_splitter.split_documents(documents)
+
+CONNECTION_STRING = 'iris://_SYSTEM:SYS@localhost:1972/USER'
+
+load_dotenv(override=True)
+
+embeddings = OpenAIEmbeddings()
+
+COLLECTION_NAME = "state_of_the_union_test"
+
+db = IRISVector.from_documents(
+    embedding=embeddings,
+    documents=docs,
+    collection_name=COLLECTION_NAME,
+    connection_string=CONNECTION_STRING,
+)
+
+query = "What did the president say about Ketanji Brown Jackson"
+docs_with_score = db.similarity_search_with_score(query)
+
+for doc, score in docs_with_score:
+    print("-" * 80)
+    print("Score: ", score)
+    print(doc.page_content)
+    print("-" * 80)
+```

setup.py

@@ -6,8 +6,8 @@
         include=["langchain_iris", "langchain_iris.*"]
     ),
     install_requires=[
-        "langchain==0.0.348",
+        "langchain>=0.0.348",
         "sqlalchemy-iris>=0.13.0",
     ],
-    python_requires=">3.7,<3.12",
+    python_requires=">3.7",
 )