chore: Align example config keys and env vars with new naming

features/create_agent/.env.example

@@ -0,0 +1,8 @@
+# Your LaunchDarkly server-side SDK key
+LAUNCHDARKLY_SDK_KEY=
+
+# Provider API key(s) for the provider your agent config uses
+OPENAI_API_KEY=
+
+# Override to use a different AI Config
+LAUNCHDARKLY_AGENT_KEY=sample-agent

features/create_agent/README.md

@@ -13,14 +13,12 @@ This example demonstrates how to use LaunchDarkly's `create_agent` method, which
 
 1. Create the following config in your LaunchDarkly project. You can use a different key by setting the environment variable in your `.env`.
 
-   - [Create an AI Agent Config](https://launchdarkly.com/docs/home/ai-configs/agents) with a model and agent instructions. Default key: `sample-agent-config`.
+   - [Create an AI Agent Config](https://launchdarkly.com/docs/home/ai-configs/agents) with a model and agent instructions. Default key: `sample-agent`.
 
-1. Create a `.env` file in this directory with the following variables:
+1. Copy `.env.example` to `.env` and fill in your keys:
 
-   ```
-   LAUNCHDARKLY_SDK_KEY=your-launchdarkly-sdk-key
-   LAUNCHDARKLY_AGENT_CONFIG_KEY=sample-agent-config
-   OPENAI_API_KEY=your-openai-api-key
+   ```bash
+   cp .env.example .env
    ```
 
 1. Install the required dependencies:

features/create_agent/create_agent_example.py

@@ -17,7 +17,7 @@
 sdk_key = os.getenv('LAUNCHDARKLY_SDK_KEY')
 
 # Set agent_config_key to the AI Agent Config key you want to evaluate.
-agent_config_key = os.getenv('LAUNCHDARKLY_AGENT_CONFIG_KEY', 'sample-agent-config')
+agent_config_key = os.getenv('LAUNCHDARKLY_AGENT_KEY', 'sample-agent')
 
 
 def get_weather(city: str) -> str:
@@ -110,6 +110,7 @@ async def async_main():
             print("\nNo judge evaluations were performed.")
 
     except Exception as err:
+        # In production, sanitize before logging — provider errors may include credentials.
         print("Error:", err)
     finally:
         # Flush pending events and close the client.

features/create_agent_graph/.env.example

@@ -0,0 +1,8 @@
+# Your LaunchDarkly server-side SDK key
+LAUNCHDARKLY_SDK_KEY=
+
+# Provider API key(s) for the provider(s) your agent graph uses
+OPENAI_API_KEY=
+
+# Override to use a different AI Config
+LAUNCHDARKLY_AGENT_GRAPH_KEY=sample-agent-graph

features/create_agent_graph/README.md

@@ -16,12 +16,10 @@ This example demonstrates how to use LaunchDarkly's `create_agent_graph` method,
    - [Create AI Agent Configs](https://launchdarkly.com/docs/home/ai-configs/agents) for each node in your graph. Configure each with a model and agent instructions. Add tools (e.g. `search_flights`, `search_hotels`, `get_weather`) to the agents that need them.
    - [Create an Agent Graph](https://launchdarkly.com/docs/home/ai-configs/create) that connects your agent configs as nodes with edges defining the workflow. Default key: `sample-agent-graph`.
 
-1. Create a `.env` file in this directory with the following variables:
+1. Copy `.env.example` to `.env` and fill in your keys:
 
-   ```
-   LAUNCHDARKLY_SDK_KEY=your-launchdarkly-sdk-key
-   LAUNCHDARKLY_AGENT_GRAPH_KEY=sample-agent-graph
-   OPENAI_API_KEY=your-openai-api-key
+   ```bash
+   cp .env.example .env
    ```
 
 1. Install the required dependencies:

features/create_agent_graph/create_agent_graph_example.py

@@ -128,6 +128,7 @@ async def async_main():
                 print(f"  reasoning: {eval_result.reasoning}")
 
     except Exception as err:
+        # In production, sanitize before logging — provider errors may include credentials.
         print("Error:", err)
     finally:
         # Flush pending events and close the client.

features/create_judge/.env.example

@@ -0,0 +1,8 @@
+# Your LaunchDarkly server-side SDK key
+LAUNCHDARKLY_SDK_KEY=
+
+# Provider API key(s) for the provider your judge config uses
+OPENAI_API_KEY=
+
+# Override to use a different AI Config
+LAUNCHDARKLY_JUDGE_KEY=sample-judge

features/create_judge/README.md

@@ -13,14 +13,12 @@ This example demonstrates how to use LaunchDarkly's `create_judge` method to eva
 
 1. Create the following config in your LaunchDarkly project. You can use a different key by setting the environment variable in your `.env`.
 
-   - [Create a Judge Config](https://launchdarkly.com/docs/home/ai-configs/judges) for evaluation. Default key: `sample-ai-judge`.
+   - [Create a Judge Config](https://launchdarkly.com/docs/home/ai-configs/judges) for evaluation. Default key: `sample-judge`.
 
-1. Create a `.env` file in this directory with the following variables:
+1. Copy `.env.example` to `.env` and fill in your keys:
 
-   ```
-   LAUNCHDARKLY_SDK_KEY=your-launchdarkly-sdk-key
-   LAUNCHDARKLY_AI_JUDGE_KEY=sample-ai-judge
-   OPENAI_API_KEY=your-openai-api-key
+   ```bash
+   cp .env.example .env
    ```
 
 1. Install the required dependencies:

features/create_judge/create_judge_example.py

@@ -17,7 +17,7 @@
 sdk_key = os.getenv('LAUNCHDARKLY_SDK_KEY')
 
 # Set judge_key to the Judge key you want to use.
-judge_key = os.getenv('LAUNCHDARKLY_AI_JUDGE_KEY', 'sample-ai-judge')
+judge_key = os.getenv('LAUNCHDARKLY_JUDGE_KEY', 'sample-judge')
 
 
 async def async_main():
@@ -95,6 +95,7 @@ async def async_main():
 
         print("\nDone!")
     except Exception as err:
+        # In production, sanitize before logging — provider errors may include credentials.
         print("Error:", err)
     finally:
         # Flush pending events and close the client.

features/create_model/.env.example

@@ -0,0 +1,8 @@
+# Your LaunchDarkly server-side SDK key
+LAUNCHDARKLY_SDK_KEY=
+
+# Provider API key(s) for the provider your AI config uses
+OPENAI_API_KEY=
+
+# Override to use a different AI Config
+LAUNCHDARKLY_COMPLETION_KEY=sample-completion

features/create_model/README.md

@@ -13,14 +13,12 @@ This example demonstrates how to use LaunchDarkly's `create_model` method, which
 
 1. Create the following config in your LaunchDarkly project. You can use a different key by setting the environment variable in your `.env`.
 
-   - [Create an AI Config](https://launchdarkly.com/docs/home/ai-configs/create) with a model and system message. Default key: `sample-completion-config`.
+   - [Create an AI Config](https://launchdarkly.com/docs/home/ai-configs/create) with a model and system message. Default key: `sample-completion`.
 
-1. Create a `.env` file in this directory with the following variables:
+1. Copy `.env.example` to `.env` and fill in your keys:
 
-   ```
-   LAUNCHDARKLY_SDK_KEY=your-launchdarkly-sdk-key
-   LAUNCHDARKLY_AI_CONFIG_KEY=sample-completion-config
-   OPENAI_API_KEY=your-openai-api-key
+   ```bash
+   cp .env.example .env
    ```
 
 1. Install the required dependencies:

features/create_model/create_model_example.py

@@ -17,7 +17,7 @@
 sdk_key = os.getenv('LAUNCHDARKLY_SDK_KEY')
 
 # Set config_key to the AI Config key you want to evaluate.
-ai_config_key = os.getenv('LAUNCHDARKLY_AI_CONFIG_KEY', 'sample-completion-config')
+ai_config_key = os.getenv('LAUNCHDARKLY_COMPLETION_KEY', 'sample-completion')
 
 
 async def async_main():
@@ -96,6 +96,7 @@ async def async_main():
             print("\nNo judge evaluations were performed. Try adding a judge to the AI config to see results.")
 
     except Exception as err:
+        # In production, sanitize before logging — provider errors may include credentials.
         print("Error:", err)
     finally:
         # Flush pending events and close the client.

getting_started/bedrock/converse/.env.example

@@ -0,0 +1,12 @@
+# Your LaunchDarkly server-side SDK key
+LAUNCHDARKLY_SDK_KEY=
+
+# Your AWS credentials for Bedrock access
+AWS_ACCESS_KEY_ID=
+AWS_SECRET_ACCESS_KEY=
+
+# Override to use a different AWS region
+AWS_DEFAULT_REGION=us-east-1
+
+# Override to use a different AI Config
+LAUNCHDARKLY_COMPLETION_KEY=sample-completion

getting_started/bedrock/converse/README.md

@@ -13,26 +13,17 @@ This example demonstrates how to use LaunchDarkly's AI Config with the AWS Bedro
 
 1. Create the following config in your LaunchDarkly project. You can use a different key by setting the environment variable in your `.env`.
 
-   - [Create an AI Config](https://launchdarkly.com/docs/home/ai-configs/create) with a Bedrock model and a system message. Default key: `sample-completion-config`.
+   - [Create an AI Config](https://launchdarkly.com/docs/home/ai-configs/create) with a Bedrock model and a system message. Default key: `sample-completion`.
 
-1. Create a `.env` file in this directory with the following variables:
+1. Copy `.env.example` to `.env` and fill in your keys:
 
+   ```bash
+   cp .env.example .env
    ```
-   LAUNCHDARKLY_SDK_KEY=your-launchdarkly-sdk-key
-   LAUNCHDARKLY_AI_CONFIG_KEY=sample-completion-config
-   ```
-
-   > `LAUNCHDARKLY_AI_CONFIG_KEY` defaults to `sample-completion-config` if not set.
 
-1. Ensure your AWS credentials can be [auto-detected by the `boto3` library](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html). You can set them in your `.env` file:
-
-   ```
-   AWS_ACCESS_KEY_ID=your-access-key-id
-   AWS_SECRET_ACCESS_KEY=your-secret-access-key
-   AWS_DEFAULT_REGION=us-east-1
-   ```
+   `LAUNCHDARKLY_COMPLETION_KEY` defaults to `sample-completion` if not set.
 
-   Other options include role providers or shared credential files.
+   Ensure your AWS credentials can be [auto-detected by the `boto3` library](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html). Setting them in `.env` is one option; role providers or shared credential files are also supported.
 
 1. Install the required dependencies:
 

getting_started/bedrock/converse/bedrock_example.py

@@ -40,14 +40,14 @@ def get_bedrock_metrics(response):
 sdk_key = os.getenv('LAUNCHDARKLY_SDK_KEY')
 
 # Set config_key to the AI Config key you want to evaluate.
-ai_config_key = os.getenv('LAUNCHDARKLY_AI_CONFIG_KEY', 'sample-completion-config')
+ai_config_key = os.getenv('LAUNCHDARKLY_COMPLETION_KEY', 'sample-completion')
 
 def main():
     if not sdk_key:
         print("*** Please set the LAUNCHDARKLY_SDK_KEY env first")
         exit()
     if not ai_config_key:
-        print("*** Please set the LAUNCHDARKLY_AI_CONFIG_KEY env first")
+        print("*** Please set the LAUNCHDARKLY_COMPLETION_KEY env first")
         exit()
 
     ldclient.set_config(Config(sdk_key, plugins=[

getting_started/gemini/generate_content/.env.example

@@ -0,0 +1,8 @@
+# Your LaunchDarkly server-side SDK key
+LAUNCHDARKLY_SDK_KEY=
+
+# Your Google API key
+GOOGLE_API_KEY=
+
+# Override to use a different AI Config
+LAUNCHDARKLY_COMPLETION_KEY=sample-completion

getting_started/gemini/generate_content/README.md

@@ -13,14 +13,12 @@ This example demonstrates how to use LaunchDarkly's AI Config with the Google Ge
 
 1. Create the following config in your LaunchDarkly project. You can use a different key by setting the environment variable in your `.env`.
 
-   - [Create an AI Config](https://launchdarkly.com/docs/home/ai-configs/create) with a Gemini model (e.g. `gemini-2.0-flash`) and a system message. Default key: `sample-completion-config`.
+   - [Create an AI Config](https://launchdarkly.com/docs/home/ai-configs/create) with a Gemini model (e.g. `gemini-2.0-flash`) and a system message. Default key: `sample-completion`.
 
-1. Create a `.env` file in this directory with the following variables:
+1. Copy `.env.example` to `.env` and fill in your keys:
 
-   ```
-   LAUNCHDARKLY_SDK_KEY=your-launchdarkly-sdk-key
-   LAUNCHDARKLY_AI_CONFIG_KEY=sample-completion-config
-   GOOGLE_API_KEY=your-google-api-key
+   ```bash
+   cp .env.example .env
    ```
 
 1. Install the required dependencies:

getting_started/gemini/generate_content/gemini_example.py

@@ -20,7 +20,7 @@
 sdk_key = os.getenv('LAUNCHDARKLY_SDK_KEY')
 
 # Set config_key to the AI Config key you want to evaluate.
-ai_config_key = os.getenv('LAUNCHDARKLY_AI_CONFIG_KEY', 'sample-completion-config')
+ai_config_key = os.getenv('LAUNCHDARKLY_COMPLETION_KEY', 'sample-completion')
 
 # Set Google API key
 google_api_key = os.getenv('GOOGLE_API_KEY')
@@ -93,7 +93,7 @@ def main():
         print("*** Please set the LAUNCHDARKLY_SDK_KEY env first")
         exit()
     if not ai_config_key:
-        print("*** Please set the LAUNCHDARKLY_AI_CONFIG_KEY env first")
+        print("*** Please set the LAUNCHDARKLY_COMPLETION_KEY env first")
         exit()
     if not google_api_key:
         print("*** Please set the GOOGLE_API_KEY env first")

getting_started/langchain/invoke/.env.example

@@ -0,0 +1,11 @@
+# Your LaunchDarkly server-side SDK key
+LAUNCHDARKLY_SDK_KEY=
+
+# Provider API keys - fill in the ones for the provider(s) your AI config uses
+OPENAI_API_KEY=
+GOOGLE_API_KEY=
+AWS_ACCESS_KEY_ID=
+AWS_SECRET_ACCESS_KEY=
+
+# Override to use a different AI Config
+LAUNCHDARKLY_COMPLETION_KEY=sample-completion

getting_started/langchain/invoke/README.md

@@ -13,22 +13,12 @@ This example demonstrates how to use LaunchDarkly's AI Config with LangChain, su
 
 1. Create the following config in your LaunchDarkly project. You can use a different key by setting the environment variable in your `.env`.
 
-   - [Create an AI Config](https://launchdarkly.com/docs/home/ai-configs/create) with a model and a system message. Default key: `sample-completion-config`.
+   - [Create an AI Config](https://launchdarkly.com/docs/home/ai-configs/create) with a model and a system message. Default key: `sample-completion`.
 
-1. Create a `.env` file in this directory with the following variables:
+1. Copy `.env.example` to `.env` and fill in your keys (only the provider keys for providers you actually use are required):
 
-   ```
-   LAUNCHDARKLY_SDK_KEY=your-launchdarkly-sdk-key
-   LAUNCHDARKLY_AI_CONFIG_KEY=sample-completion-config
-   ```
-
-   Add the API keys for the providers you want to use:
-
-   ```
-   OPENAI_API_KEY=your-openai-api-key
-   GOOGLE_API_KEY=your-google-api-key
-   AWS_ACCESS_KEY_ID=your-access-key-id
-   AWS_SECRET_ACCESS_KEY=your-secret-access-key
+   ```bash
+   cp .env.example .env
    ```
 
 1. Install the required dependencies:

getting_started/langchain/invoke/langchain_example.py

@@ -19,7 +19,7 @@
 sdk_key = os.getenv('LAUNCHDARKLY_SDK_KEY')
 
 # Set config_key to the AI Config key you want to evaluate.
-ai_config_key = os.getenv('LAUNCHDARKLY_AI_CONFIG_KEY', 'sample-completion-config')
+ai_config_key = os.getenv('LAUNCHDARKLY_COMPLETION_KEY', 'sample-completion')
 
 def map_provider_to_langchain(provider_name):
     """Map LaunchDarkly provider names to LangChain provider names."""
@@ -35,7 +35,7 @@ async def async_main():
         print("*** Please set the LAUNCHDARKLY_SDK_KEY env first")
         exit()
     if not ai_config_key:
-        print("*** Please set the LAUNCHDARKLY_AI_CONFIG_KEY env first")
+        print("*** Please set the LAUNCHDARKLY_COMPLETION_KEY env first")
         exit()
 
     ldclient.set_config(Config(sdk_key, plugins=[
@@ -119,6 +119,7 @@ async def async_main():
             print(f"  Tool calls:    {', '.join(summary.tool_calls)}")
 
     except Exception as e:
+        # In production, sanitize before logging — provider errors may include credentials.
         print(f"Error during completion: {e}")
         print("Please ensure you have the correct API keys and credentials set up for the detected provider.")
 

getting_started/langgraph/react_agent/.env.example

@@ -0,0 +1,11 @@
+# Your LaunchDarkly server-side SDK key
+LAUNCHDARKLY_SDK_KEY=
+
+# Provider API keys - fill in the ones for the provider(s) your agent config uses
+OPENAI_API_KEY=
+GOOGLE_API_KEY=
+AWS_ACCESS_KEY_ID=
+AWS_SECRET_ACCESS_KEY=
+
+# Override to use a different AI Config
+LAUNCHDARKLY_AGENT_KEY=sample-agent

getting_started/langgraph/react_agent/README.md

@@ -13,22 +13,12 @@ This example demonstrates how to use LaunchDarkly's AI Config with LangGraph to
 
 1. Create the following config in your LaunchDarkly project. You can use a different key by setting the environment variable in your `.env`.
 
-   - [Create an AI Agent Config](https://launchdarkly.com/docs/home/ai-configs/agents) with a model and agent instructions. Default key: `sample-agent-config`.
+   - [Create an AI Agent Config](https://launchdarkly.com/docs/home/ai-configs/agents) with a model and agent instructions. Default key: `sample-agent`.
 
-1. Create a `.env` file in this directory with the following variables:
+1. Copy `.env.example` to `.env` and fill in your keys (only the provider keys for providers you actually use are required):
 
-   ```
-   LAUNCHDARKLY_SDK_KEY=your-launchdarkly-sdk-key
-   LAUNCHDARKLY_AGENT_CONFIG_KEY=sample-agent-config
-   ```
-
-   Add the API keys for the providers you want to use:
-
-   ```
-   OPENAI_API_KEY=your-openai-api-key
-   GOOGLE_API_KEY=your-google-api-key
-   AWS_ACCESS_KEY_ID=your-access-key-id
-   AWS_SECRET_ACCESS_KEY=your-secret-access-key
+   ```bash
+   cp .env.example .env
    ```
 
 1. Install the required dependencies:

getting_started/langgraph/react_agent/langgraph_agent_example.py

@@ -20,7 +20,7 @@
 sdk_key = os.getenv('LAUNCHDARKLY_SDK_KEY')
 
 # Set config key for the agent
-agent_config_key = os.getenv('LAUNCHDARKLY_AGENT_CONFIG_KEY', 'sample-agent-config')
+agent_config_key = os.getenv('LAUNCHDARKLY_AGENT_KEY', 'sample-agent')
 
 def map_provider_to_langchain(provider_name):
     """Map LaunchDarkly provider names to LangChain provider names."""
@@ -122,6 +122,7 @@ def main():
             print(f"  Tool calls:    {', '.join(summary.tool_calls)}")
 
     except Exception as e:
+        # In production, sanitize before logging — provider errors may include credentials.
         print(f"\nError: {e}")
         print("Please ensure you have the correct API keys and credentials set up for the detected providers.")