chore: Improve default examples

examples/bedrock_example.py

@@ -40,26 +40,20 @@ def main():
         .build()
     )
 
-    DEFAULT_SYSTEM_MESSAGE = "You are a helpful assistant that can answer questions and help with tasks."
-
-    # Set a fallback AIConfig to use if a config is not found or your application is not able to connect to LaunchDarkly.
-    default_value = AIConfig(
-        enabled=True,
-        model=ModelConfig(name='my-default-model', parameters={}),
-        provider=ProviderConfig(name='bedrock'),
-        messages=[LDMessage(role='system', content=DEFAULT_SYSTEM_MESSAGE)],
-    )
-
-    # Optionally, you can use a disabled AIConfig
-    # default_value = AIConfig(
-    #     enabled=False
-    # )
-
+    # Pass a default for improved resiliency when the AI config is unavailable
+    # or LaunchDarkly is unreachable; omit for a disabled default.
+    # Example:
+    #   default = AIConfig(
+    #       enabled=True,
+    #       model=ModelConfig(name='my-default-model'),
+    #       provider=ProviderConfig(name='bedrock'),
+    #       messages=[LDMessage(role='system', content='You are a helpful assistant.')],
+    #   )
+    #   config_value, tracker = aiclient.config(ai_config_key, context, default, {'myUserVariable': "Testing Variable"})
     config_value, tracker = aiclient.config(
         ai_config_key,
         context,
-        default_value,
-        {'myUserVariable': "Testing Variable"}
+        variables={'myUserVariable': "Testing Variable"}
     )
 
     if not config_value.enabled:

examples/chat_judge_example.py

@@ -38,12 +38,17 @@ async def async_main():
     )
 
     try:
-        # Example using the chat functionality which automates the judge evaluation
-        default_value = AICompletionConfigDefault(
-            enabled=False,
-        )
-
-        chat = await aiclient.create_chat(ai_config_key, context, default_value, {
+        # Pass a default for improved resiliency when the AI config is unavailable
+        # or LaunchDarkly is unreachable; omit for a disabled default.
+        # Example:
+        #   default = AICompletionConfigDefault(
+        #       enabled=True,
+        #       model={'name': 'gpt-4'},
+        #       provider={'name': 'openai'},
+        #       messages=[{'role': 'system', 'content': 'You are a helpful assistant.'}],
+        #   )
+        #   chat = await aiclient.create_chat(ai_config_key, context, default, {'companyName': 'LaunchDarkly'})
+        chat = await aiclient.create_chat(ai_config_key, context, variables={
             'companyName': 'LaunchDarkly',
         })
 
@@ -59,6 +64,10 @@ async def async_main():
         chat_response = await chat.invoke(user_input)
         print("Chat Response:", chat_response.message.content)
 
+        # Judge evaluations run asynchronously. Await them (e.g. with asyncio.gather) so they
+        # complete before the process or request ends—even if you don't need to log or use
+        # the results. Below we await and then log the results for demonstration.
+
         # Log judge evaluation results with full detail
         if chat_response.evaluations is not None and len(chat_response.evaluations) > 0:
             # Note: Judge evaluations run asynchronously and do not block your application.

examples/chat_observability_example.py

@@ -58,14 +58,20 @@ async def async_main():
     )
 
     try:
-        # Create a chat instance with custom variables
-        default_value = AICompletionConfigDefault(enabled=False)
-
+        # Pass a default for improved resiliency when the AI config is unavailable
+        # or LaunchDarkly is unreachable; omit for a disabled default.
+        # Example:
+        #   default = AICompletionConfigDefault(
+        #       enabled=True,
+        #       model={'name': 'gpt-4'},
+        #       provider={'name': 'openai'},
+        #       messages=[{'role': 'system', 'content': 'You are a helpful assistant.'}],
+        #   )
+        #   chat = await aiclient.create_chat(ai_config_key, context, default, {'example_type': 'observability_demo'})
         chat = await aiclient.create_chat(
-            ai_config_key, 
-            context, 
-            default_value, 
-            {
+            ai_config_key,
+            context,
+            variables={
                 'example_type': 'observability_demo',
                 'session_id': 'demo-session-123',
                 'feature': 'ai_chat'
@@ -84,10 +90,18 @@ async def async_main():
 
         user_input_2 = "Give me a specific use case example."
         print("\nUser Input:", user_input_2)
-        
+
         response_2 = await chat.invoke(user_input_2)
         print("Chat Response:", response_2.message.content)
 
+        # Judge evaluations run asynchronously. Await them (e.g. with asyncio.gather) so they
+        # complete before the process or request ends—even if you don't need to log or use
+        # the results.
+        if response_1.evaluations:
+            await asyncio.gather(*response_1.evaluations)
+        if response_2.evaluations:
+            await asyncio.gather(*response_2.evaluations)
+
         print("\nSuccess.")
 
     except Exception as err:

examples/direct_judge_example.py

@@ -4,7 +4,7 @@
 import ldclient
 from ldclient import Context
 from ldclient.config import Config
-from ldai import LDAIClient, AICompletionConfigDefault
+from ldai import LDAIClient, AIJudgeConfigDefault
 
 # Set sdk_key to your LaunchDarkly SDK key.
 sdk_key = os.getenv('LAUNCHDARKLY_SDK_KEY')
@@ -38,12 +38,21 @@ async def async_main():
     )
 
     try:
-        # Example of using the judge functionality with direct input and output
-        # Get AI judge configuration from LaunchDarkly
-        judge_default_value = AICompletionConfigDefault(
-            enabled=False,
-        )
-        judge = await aiclient.create_judge(judge_key, context, judge_default_value)
+        # Pass a default for improved resiliency when the AI config is unavailable
+        # or LaunchDarkly is unreachable; omit for a disabled default.
+        # Example (enabled default; judge default has three messages):
+        #   default = AIJudgeConfigDefault(
+        #       enabled=True,
+        #       model={'name': 'gpt-4'},
+        #       provider={'name': 'openai'},
+        #       messages=[
+        #           {'role': 'system', 'content': 'Your judge criteria here.'},
+        #           {'role': 'assistant', 'content': 'MESSAGE HISTORY: {{message_history}}'},
+        #           {'role': 'user', 'content': 'RESPONSE TO EVALUATE: {{response_to_evaluate}}'},
+        #       ],
+        #   )
+        #   judge = await aiclient.create_judge(judge_key, context, default)
+        judge = await aiclient.create_judge(judge_key, context)
 
         if not judge:
             print(f"*** AI judge configuration is not enabled for key: {judge_key}")

examples/gemini_example.py

@@ -110,26 +110,20 @@ def main():
         .build()
     )
 
-    DEFAULT_SYSTEM_MESSAGE = "You are a helpful assistant that can answer questions and help with tasks."
-
-    # Set a fallback AIConfig to use if a config is not found or your application is not able to connect to LaunchDarkly.
-    default_value = AIConfig(
-        enabled=True,
-        model=ModelConfig(name='gemini-pro', parameters={}),
-        provider=ProviderConfig(name='google'),
-        messages=[LDMessage(role='system', content=DEFAULT_SYSTEM_MESSAGE)],
-    )
-
-    # Optionally, you can use a disabled AIConfig
-    # default_value = AIConfig(
-    #     enabled=False
-    # )
-
+    # Pass a default for improved resiliency when the AI config is unavailable
+    # or LaunchDarkly is unreachable; omit for a disabled default.
+    # Example:
+    #   default = AIConfig(
+    #       enabled=True,
+    #       model=ModelConfig(name='gemini-pro'),
+    #       provider=ProviderConfig(name='google'),
+    #       messages=[LDMessage(role='system', content='You are a helpful assistant.')],
+    #   )
+    #   config_value, tracker = aiclient.config(ai_config_key, context, default, {'myUserVariable': "Testing Variable"})
     config_value, tracker = aiclient.config(
         ai_config_key,
         context,
-        default_value,
-        {'myUserVariable': "Testing Variable"}
+        variables={'myUserVariable': "Testing Variable"}
     )
 
     if not config_value.enabled:

examples/langchain_example.py

@@ -83,26 +83,20 @@ def main():
         .build()
     )
 
-    DEFAULT_SYSTEM_MESSAGE = "You are a helpful assistant that can answer questions and help with tasks."
-
-    # Set a fallback AIConfig to use if a config is not found or your application is not able to connect to LaunchDarkly.
-    default_value = AIConfig(
-        enabled=True,
-        model=ModelConfig(name='gpt-3.5-turbo', parameters={}),  # Default to OpenAI
-        provider=ProviderConfig(name='openai'),
-        messages=[LDMessage(role='system', content=DEFAULT_SYSTEM_MESSAGE)],
-    )
-
-    # Optionally, you can use a disabled AIConfig
-    # default_value = AIConfig(
-    #     enabled=False
-    # )
-
+    # Pass a default for improved resiliency when the AI config is unavailable
+    # or LaunchDarkly is unreachable; omit for a disabled default.
+    # Example:
+    #   default = AIConfig(
+    #       enabled=True,
+    #       model=ModelConfig(name='gpt-4'),
+    #       provider=ProviderConfig(name='openai'),
+    #       messages=[LDMessage(role='system', content='You are a helpful assistant.')],
+    #   )
+    #   config_value, tracker = aiclient.config(ai_config_key, context, default, {'myUserVariable': "Testing Variable"})
     config_value, tracker = aiclient.config(
         ai_config_key,
         context,
-        default_value,
-        {'myUserVariable': "Testing Variable"}
+        variables={'myUserVariable': "Testing Variable"}
     )
 
     if not config_value.enabled:

examples/langgraph_agent_example.py

@@ -85,16 +85,17 @@ def main():
     print(f"🔍 Using agent config: {agent_config_key}")
     print()
 
-    # Create a LangChain model with LaunchDarkly AI config.
-    # Default value with disabled agent
-    default_value = LDAIAgentDefaults(
-        enabled=False,  # Disabled by default
-    )
-
-    agent_config = aiclient.agent(
+    # Pass a default for improved resiliency when the agent config is unavailable
+    # or LaunchDarkly is unreachable; omit for a disabled default.
+    # Example (enabled default):
+    #   default = LDAIAgentDefaults(
+    #       enabled=True,
+    #       instructions='You are a helpful assistant.',
+    #   )
+    #   agent_config = aiclient.agent_config(agent_config_key, context, default=default)
+    agent_config = aiclient.agent_config(
         LDAIAgentConfig(
             key=agent_config_key,
-            default_value=default_value,
         ),
         context
     )

examples/langgraph_multi_agent_example.py

@@ -73,14 +73,17 @@ def track_langgraph_metrics(tracker, func, prev_message_count=0):
 
 def create_agent_with_config(aiclient, config_key, context):
     """Create a LangChain model with LaunchDarkly AI config."""
-    default_value = LDAIAgentDefaults(
-        enabled=False,  # Disabled by default
-    )
-
-    agent_config = aiclient.agent(
+    # Pass a default for improved resiliency when the agent config is unavailable
+    # or LaunchDarkly is unreachable; omit for a disabled default.
+    # Example (enabled default):
+    #   default = LDAIAgentDefaults(
+    #       enabled=True,
+    #       instructions='You are a helpful assistant.',
+    #   )
+    #   agent_config = aiclient.agent_config(LDAIAgentConfig(key=config_key, default=default), context)
+    agent_config = aiclient.agent_config(
         LDAIAgentConfig(
             key=config_key,
-            default_value=default_value,
         ),
         context
     )

examples/openai_example.py

@@ -41,26 +41,20 @@ def main():
         .build()
     )
 
-    DEFAULT_SYSTEM_MESSAGE = "You are a helpful assistant that can answer questions and help with tasks."
-
-    # Set a fallback AIConfig to use if a config is not found or your application is not able to connect to LaunchDarkly.
-    default_value = AIConfig(
-        enabled=True,
-        model=ModelConfig(name='my-default-model', parameters={}),
-        provider=ProviderConfig(name='openai'),
-        messages=[LDMessage(role='system', content=DEFAULT_SYSTEM_MESSAGE)],
-    )
-
-    # Optionally, you can use a disabled AIConfig
-    # default_value = AIConfig(
-    #     enabled=False
-    # )
-
+    # Pass a default for improved resiliency when the AI config is unavailable
+    # or LaunchDarkly is unreachable; omit for a disabled default.
+    # Example:
+    #   default = AIConfig(
+    #       enabled=True,
+    #       model=ModelConfig(name='gpt-4'),
+    #       provider=ProviderConfig(name='openai'),
+    #       messages=[LDMessage(role='system', content='You are a helpful assistant.')],
+    #   )
+    #   config_value, tracker = aiclient.config(ai_config_key, context, default, {'myUserVariable': "Testing Variable"})
     config_value, tracker = aiclient.config(
         ai_config_key,
         context,
-        default_value,
-        {'myUserVariable': "Testing Variable"}
+        variables={'myUserVariable': "Testing Variable"}
     )
 
     if not config_value.enabled:

pyproject.toml

@@ -20,7 +20,7 @@ direct-judge-example = 'examples.direct_judge_example:main'
 
 [tool.poetry.dependencies]
 python = "^3.10"
-launchdarkly-server-sdk-ai = "^0.15.0"
+launchdarkly-server-sdk-ai = "^0.16.0"
 launchdarkly-server-sdk-ai-langchain = "^0.3.0"
 launchdarkly-server-sdk-ai-openai = "^0.1.0"
 launchdarkly-observability = { version = ">=0.1.0", optional = true }