diff --git a/README.md b/README.md
index 3626c2dd..d41d78c3 100644
--- a/README.md
+++ b/README.md
@@ -38,6 +38,14 @@ Book a [1-on-1 Session with Kye](https://calendly.com/swarm-corp/30min), the Cre
 ## Usage
 We have a small gallery of examples to run here, [for more check out the docs to build your own agent and or swarms!](https://docs.apac.ai)
 
+All of the examples assume you have set your API keys in the environment:
+
+```bash
+export OPENAI_API_KEY='yourapikey'
+export ANTHROPIC_API_KEY='yourotherapikey'
+```
+
+
 ### Example in Colab:
 
 <a target="_blank" href="https://colab.research.google.com/github/kyegomez/swarms/blob/master/swarms_example.ipynb">
diff --git a/example.py b/example.py
index 46e8b33c..aca8c61f 100644
--- a/example.py
+++ b/example.py
@@ -1,5 +1,9 @@
 from swarms.models import OpenAIChat
 from swarms.structs import Flow
+import os
+
+openai_api_key = os.environ.get("OPENAI_API_KEY")
+anthropic_api_key = os.environ.get("ANTHROPIC_API_KEY")
 
 # Initialize the language model, this model can be swapped out with Anthropic, ETC, Huggingface Models like Mistral, ETC
 llm = OpenAIChat(
diff --git a/sequential_workflow_example.py b/sequential_workflow_example.py
index 9c17a072..5f2fe5db 100644
--- a/sequential_workflow_example.py
+++ b/sequential_workflow_example.py
@@ -1,16 +1,15 @@
 from swarms.models import OpenAIChat, BioGPT, Anthropic
 from swarms.structs import Flow
 from swarms.structs.sequential_workflow import SequentialWorkflow
-
+import os
 
 # Example usage
-api_key = (
-    ""  # Your actual API key here
-)
+openai_api_key = os.environ.get("OPENAI_API_KEY")
+anthropic_api_key = os.environ.get("ANTHROPIC_API_KEY")
 
 # Initialize the language flow
 llm = OpenAIChat(
-    openai_api_key=api_key,
+    openai_api_key=openai_api_key,
     temperature=0.5,
     max_tokens=3000,
 )
@@ -18,7 +17,7 @@ llm = OpenAIChat(
 biochat = BioGPT()
 
 # Use Anthropic
-anthropic = Anthropic()
+anthropic = Anthropic(anthropic_api_key=anthropic_api_key)
 
 # Initialize the agent with the language flow
 agent1 = Flow(llm=llm, max_loops=1, dashboard=False)