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commit 72cac0448d4aa2fb0461b45c762e48e5616131c9 Author: youjin <[email protected]> AuthorDate: Mon Jan 26 11:15:07 2026 +0800 [api][python] Introduce Hierarchical ResourceClassName for Cross-Language Resource Creation --- python/flink_agents/api/resource.py | 145 ++++++++++++++------- .../chat_model_integration_agent.py | 20 +-- .../e2e_tests_mcp/mcp_test.py | 8 +- .../e2e_tests_integration/long_term_memory_test.py | 12 +- .../e2e_tests_integration/react_agent_test.py | 10 +- .../chat_model_cross_language_agent.py | 16 +-- .../embedding_model_cross_language_agent.py | 14 +- .../vector_store_cross_language_agent.py | 22 ++-- .../agents/custom_types_and_resources.py | 4 +- .../quickstart/agents/product_suggestion_agent.py | 4 +- .../quickstart/agents/review_analysis_agent.py | 4 +- .../examples/quickstart/react_agent_example.py | 10 +- .../flink_agents/examples/rag/rag_agent_example.py | 12 +- 13 files changed, 170 insertions(+), 111 deletions(-) diff --git a/python/flink_agents/api/resource.py b/python/flink_agents/api/resource.py index fa0e5b4b..f7f7aee8 100644 --- a/python/flink_agents/api/resource.py +++ b/python/flink_agents/api/resource.py @@ -211,55 +211,102 @@ def get_resource_class(module_path: str, class_name: str) -> Type[Resource]: module = importlib.import_module(module_path) return getattr(module, class_name) +class ResourceName: + """Hierarchical resource class names for pointing a resource implementation in + ResourceDescriptor. -class Constant: - """Constant strings for pointing a built-in resource implementation.""" + Structure: + - Python implementation: ResourceType.PROVIDER_RESOURCEKIND + - Java implementation: ResourceType.Java.PROVIDER_RESOURCEKIND - # Built-in ChatModel - # java wrapper - JAVA_CHAT_MODEL_CONNECTION = ( - "flink_agents.api.chat_models.java_chat_model.JavaChatModelConnection" - ) - JAVA_CHAT_MODEL_SETUP = ( - "flink_agents.api.chat_models.java_chat_model.JavaChatModelSetup" - ) - # ollama - OLLAMA_CHAT_MODEL_CONNECTION = "flink_agents.integrations.chat_models.ollama_chat_model.OllamaChatModelConnection" - OLLAMA_CHAT_MODEL_SETUP = ( - "flink_agents.integrations.chat_models.ollama_chat_model.OllamaChatModelSetup" - ) - # anthropic - ANTHROPIC_CHAT_MODEL_CONNECTION = "flink_agents.integrations.chat_models.anthropic.anthropic_chat_model.AnthropicChatModelConnection" - ANTHROPIC_CHAT_MODEL_SETUP = "flink_agents.integrations.chat_models.anthropic.anthropic_chat_model.AnthropicChatModelSetup" - # Azure - TONGYI_CHAT_MODEL_CONNECTION = "flink_agents.integrations.chat_models.tongyi_chat_model.TongyiChatModelConnection" - TONGYI_CHAT_MODEL_SETUP = ( - "flink_agents.integrations.chat_models.tongyi_chat_model.TongyiChatModelSetup" - ) - # OpenAI - OPENAI_CHAT_MODEL_CONNECTION = "flink_agents.integrations.chat_models.openai.openai_chat_model.OpenAIChatModelConnection" - OPENAI_CHAT_MODEL_SETUP = "flink_agents.integrations.chat_models.openai.openai_chat_model.OpenAIChatModelSetup" - - # Built-in EmbeddingModel - # java wrapper - JAVA_EMBEDDING_MODEL_CONNECTION = "flink_agents.api.embedding_models.java_embedding_model.JavaEmbeddingModelConnection" - JAVA_EMBEDDING_MODEL_SETUP = ( - "flink_agents.api.embedding_models.java_embedding_model.JavaEmbeddingModelSetup" - ) - # ollama - OLLAMA_EMBEDDING_MODEL_CONNECTION = "flink_agents.integrations.embedding_models.local.ollama_embedding_model.OllamaEmbeddingModelConnection" - OLLAMA_EMBEDDING_MODEL_SETUP = "flink_agents.integrations.embedding_models.local.ollama_embedding_model.OllamaEmbeddingModelSetup" - - # OpenAI - OPENAI_EMBEDDING_MODEL_CONNECTION = "flink_agents.integrations.embedding_models.openai_embedding_model.OpenAIEmbeddingModelConnection" - OPENAI_EMBEDDING_MODEL_SETUP = "flink_agents.integrations.embedding_models.openai_embedding_model.OpenAIEmbeddingModelSetup" - - # Built-in VectorStore - # java wrapper - JAVA_VECTOR_STORE = "flink_agents.api.vector_stores.java_vector_store.JavaVectorStore" - JAVA_COLLECTION_MANAGEABLE_VECTOR_STORE = "flink_agents.api.vector_stores.java_vector_store.JavaCollectionManageableVectorStore" - # chroma - CHROMA_VECTOR_STORE = "flink_agents.integrations.vector_stores.chroma.chroma_vector_store.ChromaVectorStore" - - # MCP + Example usage: + # Python implementation + ResourceName.ChatModel.OLLAMA_CONNECTION + ResourceName.ChatModel.OPENAI_SETUP + + # Java implementation + ResourceName.ChatModel.Java.OLLAMA_CONNECTION + """ + + class ChatModel: + """ChatModel resource names.""" + + # Anthropic + ANTHROPIC_CONNECTION = "flink_agents.integrations.chat_models.anthropic.anthropic_chat_model.AnthropicChatModelConnection" + ANTHROPIC_SETUP = "flink_agents.integrations.chat_models.anthropic.anthropic_chat_model.AnthropicChatModelSetup" + + # Ollama + OLLAMA_CONNECTION = "flink_agents.integrations.chat_models.ollama_chat_model.OllamaChatModelConnection" + OLLAMA_SETUP = "flink_agents.integrations.chat_models.ollama_chat_model.OllamaChatModelSetup" + + # OpenAI + OPENAI_CONNECTION = "flink_agents.integrations.chat_models.openai.openai_chat_model.OpenAIChatModelConnection" + OPENAI_SETUP = "flink_agents.integrations.chat_models.openai.openai_chat_model.OpenAIChatModelSetup" + + # Tongyi + TONGYI_CONNECTION = "flink_agents.integrations.chat_models.tongyi_chat_model.TongyiChatModelConnection" + TONGYI_SETUP = "flink_agents.integrations.chat_models.tongyi_chat_model.TongyiChatModelSetup" + + # Java Wrapper + JAVA_WRAPPER_CONNECTION = "flink_agents.api.chat_models.java_chat_model.JavaChatModelConnection" + JAVA_WRAPPER_SETUP = "flink_agents.api.chat_models.java_chat_model.JavaChatModelSetup" + + class Java: + """Java implementations of ChatModel.""" + + # Anthropic + ANTHROPIC_CONNECTION = "org.apache.flink.agents.integrations.chatmodels.anthropic.AnthropicChatModelConnection" + ANTHROPIC_SETUP = "org.apache.flink.agents.integrations.chatmodels.anthropic.AnthropicChatModelSetup" + + # Azure + AZURE_CONNECTION = "org.apache.flink.agents.integrations.chatmodels.anthropic.AzureAIChatModelConnection" + AZURE_SETUP = "org.apache.flink.agents.integrations.chatmodels.anthropic.AzureAIChatModelSetup" + + # Ollama + OLLAMA_CONNECTION = "org.apache.flink.agents.integrations.chatmodels.ollama.OllamaChatModelConnection" + OLLAMA_SETUP = "org.apache.flink.agents.integrations.chatmodels.ollama.OllamaChatModelSetup" + + # OpenAI + OPENAI_CONNECTION = "org.apache.flink.agents.integrations.chatmodels.openai.OpenAIChatModelConnection" + OPENAI_SETUP = "org.apache.flink.agents.integrations.chatmodels.openai.OpenAIChatModelSetup" + + class EmbeddingModel: + """EmbeddingModel resource names.""" + + # Ollama + OLLAMA_CONNECTION = "flink_agents.integrations.embedding_models.local.ollama_embedding_model.OllamaEmbeddingModelConnection" + OLLAMA_SETUP = "flink_agents.integrations.embedding_models.local.ollama_embedding_model.OllamaEmbeddingModelSetup" + + # OpenAI + OPENAI_CONNECTION = "flink_agents.integrations.embedding_models.openai_embedding_model.OpenAIEmbeddingModelConnection" + OPENAI_SETUP = "flink_agents.integrations.embedding_models.openai_embedding_model.OpenAIEmbeddingModelSetup" + + # Java Wrapper + JAVA_WRAPPER_CONNECTION = "flink_agents.api.embedding_models.java_embedding_model.JavaEmbeddingModelConnection" + JAVA_WRAPPER_SETUP = "flink_agents.api.embedding_models.java_embedding_model.JavaEmbeddingModelSetup" + + class Java: + """Java implementations of EmbeddingModel.""" + + # Ollama + OLLAMA_CONNECTION = "org.apache.flink.agents.integrations.embeddingmodels.ollama.OllamaEmbeddingModelConnection" + OLLAMA_SETUP = "org.apache.flink.agents.integrations.embeddingmodels.ollama.OllamaEmbeddingModelSetup" + + class VectorStore: + """VectorStore resource names.""" + + # Chroma + CHROMA_VECTOR_STORE = "flink_agents.integrations.vector_stores.chroma.chroma_vector_store.ChromaVectorStore" + + # Java Wrapper + JAVA_WRAPPER_VECTOR_STORE = "flink_agents.api.vector_stores.java_vector_store.JavaVectorStore" + JAVA_WRAPPER_COLLECTION_MANAGEABLE_VECTOR_STORE = "flink_agents.api.vector_stores.java_vector_store.JavaCollectionManageableVectorStore" + + class Java: + """Java implementations of VectorStore.""" + + # Elasticsearch + ELASTICSEARCH_VECTOR_STORE = "org.apache.flink.agents.integrations.vectorstores.elasticsearch.ElasticsearchVectorStore" + + # MCP resource names MCP_SERVER = "flink_agents.integrations.mcp.mcp.MCPServer" diff --git a/python/flink_agents/e2e_tests/e2e_tests_integration/chat_model_integration_agent.py b/python/flink_agents/e2e_tests/e2e_tests_integration/chat_model_integration_agent.py index b68a2f1a..427f642e 100644 --- a/python/flink_agents/e2e_tests/e2e_tests_integration/chat_model_integration_agent.py +++ b/python/flink_agents/e2e_tests/e2e_tests_integration/chat_model_integration_agent.py @@ -28,8 +28,8 @@ from flink_agents.api.decorators import ( from flink_agents.api.events.chat_event import ChatRequestEvent, ChatResponseEvent from flink_agents.api.events.event import InputEvent, OutputEvent from flink_agents.api.resource import ( - Constant, ResourceDescriptor, + ResourceName, ) from flink_agents.api.runner_context import RunnerContext @@ -42,21 +42,21 @@ class ChatModelTestAgent(Agent): def openai_connection() -> ResourceDescriptor: """ChatModelConnection responsible for openai model service connection.""" return ResourceDescriptor( - clazz=Constant.OPENAI_CHAT_MODEL_CONNECTION, api_key=os.environ.get("OPENAI_API_KEY") + clazz=ResourceName.ChatModel.OPENAI_CONNECTION, api_key=os.environ.get("OPENAI_API_KEY") ) @chat_model_connection @staticmethod def tongyi_connection() -> ResourceDescriptor: """ChatModelConnection responsible for tongyi model service connection.""" - return ResourceDescriptor(clazz=Constant.TONGYI_CHAT_MODEL_CONNECTION) + return ResourceDescriptor(clazz=ResourceName.ChatModel.TONGYI_CONNECTION) @chat_model_connection @staticmethod def ollama_connection() -> ResourceDescriptor: """ChatModelConnection responsible for ollama model service connection.""" return ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_CONNECTION, request_timeout=240.0 + clazz=ResourceName.ChatModel.OLLAMA_CONNECTION, request_timeout=240.0 ) @chat_model_setup @@ -66,14 +66,14 @@ class ChatModelTestAgent(Agent): model_provider = os.environ.get("MODEL_PROVIDER") if model_provider == "Tongyi": return ResourceDescriptor( - clazz=Constant.TONGYI_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.TONGYI_SETUP, connection="tongyi_connection", model=os.environ.get("TONGYI_CHAT_MODEL", "qwen-plus"), tools=["add"], ) elif model_provider == "Ollama": return ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.OLLAMA_SETUP, connection="ollama_connection", model=os.environ.get("OLLAMA_CHAT_MODEL", "qwen3:1.7b"), tools=["add"], @@ -81,7 +81,7 @@ class ChatModelTestAgent(Agent): ) elif model_provider == "OpenAI": return ResourceDescriptor( - clazz=Constant.OPENAI_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.OPENAI_SETUP, connection="openai_connection", model=os.environ.get("OPENAI_CHAT_MODEL", "gpt-3.5-turbo"), tools=["add"], @@ -97,20 +97,20 @@ class ChatModelTestAgent(Agent): model_provider = os.environ.get("MODEL_PROVIDER") if model_provider == "Tongyi": return ResourceDescriptor( - clazz=Constant.TONGYI_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.TONGYI_SETUP, connection="tongyi_connection", model=os.environ.get("TONGYI_CHAT_MODEL", "qwen-plus"), ) elif model_provider == "Ollama": return ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.OLLAMA_SETUP, connection="ollama_connection", model=os.environ.get("OLLAMA_CHAT_MODEL", "qwen3:1.7b"), extract_reasoning=True, ) elif model_provider == "OpenAI": return ResourceDescriptor( - clazz=Constant.OPENAI_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.OPENAI_SETUP, connection="openai_connection", model=os.environ.get("OPENAI_CHAT_MODEL", "gpt-3.5-turbo"), ) diff --git a/python/flink_agents/e2e_tests/e2e_tests_integration/e2e_tests_mcp/mcp_test.py b/python/flink_agents/e2e_tests/e2e_tests_integration/e2e_tests_mcp/mcp_test.py index 37da6e26..a5f5efc4 100644 --- a/python/flink_agents/e2e_tests/e2e_tests_integration/e2e_tests_mcp/mcp_test.py +++ b/python/flink_agents/e2e_tests/e2e_tests_integration/e2e_tests_mcp/mcp_test.py @@ -47,8 +47,8 @@ from flink_agents.api.events.chat_event import ChatRequestEvent, ChatResponseEve from flink_agents.api.events.event import InputEvent, OutputEvent from flink_agents.api.execution_environment import AgentsExecutionEnvironment from flink_agents.api.resource import ( - Constant, ResourceDescriptor, + ResourceName, ) from flink_agents.api.runner_context import RunnerContext from flink_agents.e2e_tests.test_utils import pull_model @@ -71,14 +71,14 @@ class MyMCPAgent(Agent): @staticmethod def my_mcp_server() -> ResourceDescriptor: """Define MCP server connection.""" - return ResourceDescriptor(clazz=Constant.MCP_SERVER, endpoint=MCP_SERVER_ENDPOINT) + return ResourceDescriptor(clazz=ResourceName.MCP_SERVER, endpoint=MCP_SERVER_ENDPOINT) @chat_model_connection @staticmethod def ollama_connection() -> ResourceDescriptor: """ChatModelConnection for Ollama.""" return ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_CONNECTION, request_timeout=240.0 + clazz=ResourceName.ChatModel.OLLAMA_CONNECTION, request_timeout=240.0 ) @chat_model_setup @@ -86,7 +86,7 @@ class MyMCPAgent(Agent): def math_chat_model() -> ResourceDescriptor: """ChatModel using MCP prompt and tool.""" return ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.OLLAMA_SETUP, connection="ollama_connection", model=OLLAMA_MODEL, prompt="ask_sum", # MCP prompt registered from my_mcp_server diff --git a/python/flink_agents/e2e_tests/e2e_tests_integration/long_term_memory_test.py b/python/flink_agents/e2e_tests/e2e_tests_integration/long_term_memory_test.py index 339bf526..46ed4427 100644 --- a/python/flink_agents/e2e_tests/e2e_tests_integration/long_term_memory_test.py +++ b/python/flink_agents/e2e_tests/e2e_tests_integration/long_term_memory_test.py @@ -55,8 +55,8 @@ from flink_agents.api.memory.long_term_memory import ( MemorySetItem, ) from flink_agents.api.resource import ( - Constant, ResourceDescriptor, + ResourceName, ) from flink_agents.api.runner_context import RunnerContext from flink_agents.e2e_tests.test_utils import pull_model @@ -124,7 +124,7 @@ class LongTermMemoryAgent(Agent): def ollama_connection() -> ResourceDescriptor: """ChatModelConnection responsible for ollama model service connection.""" return ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_CONNECTION, request_timeout=480.0 + clazz=ResourceName.ChatModel.OLLAMA_CONNECTION, request_timeout=480.0 ) @chat_model_setup @@ -132,7 +132,7 @@ class LongTermMemoryAgent(Agent): def ollama_qwen3() -> ResourceDescriptor: """ChatModel which focus on math, and reuse ChatModelConnection.""" return ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.OLLAMA_SETUP, connection="ollama_connection", model=OLLAMA_CHAT_MODEL, extract_reasoning=True, @@ -143,14 +143,14 @@ class LongTermMemoryAgent(Agent): @staticmethod def ollama_embedding_connection() -> ResourceDescriptor: # noqa D102 return ResourceDescriptor( - clazz=Constant.OLLAMA_EMBEDDING_MODEL_CONNECTION, request_timeout=240.0 + clazz=ResourceName.EmbeddingModel.OLLAMA_CONNECTION, request_timeout=240.0 ) @embedding_model_setup @staticmethod def ollama_nomic_embed_text() -> ResourceDescriptor: # noqa D102 return ResourceDescriptor( - clazz=Constant.OLLAMA_EMBEDDING_MODEL_SETUP, + clazz=ResourceName.EmbeddingModel.OLLAMA_SETUP, connection="ollama_embedding_connection", model=OLLAMA_EMBEDDING_MODEL, ) @@ -160,7 +160,7 @@ class LongTermMemoryAgent(Agent): def chroma_vector_store() -> ResourceDescriptor: """Vector store setup for knowledge base.""" return ResourceDescriptor( - clazz=Constant.CHROMA_VECTOR_STORE, + clazz=ResourceName.VectorStore.CHROMA_VECTOR_STORE, embedding_model="ollama_nomic_embed_text", persist_directory=chromadb_path, ) diff --git a/python/flink_agents/e2e_tests/e2e_tests_integration/react_agent_test.py b/python/flink_agents/e2e_tests/e2e_tests_integration/react_agent_test.py index dee3bcea..f2ca48ea 100644 --- a/python/flink_agents/e2e_tests/e2e_tests_integration/react_agent_test.py +++ b/python/flink_agents/e2e_tests/e2e_tests_integration/react_agent_test.py @@ -35,8 +35,8 @@ from flink_agents.api.core_options import AgentConfigOptions, ErrorHandlingStrat from flink_agents.api.execution_environment import AgentsExecutionEnvironment from flink_agents.api.prompts.prompt import Prompt from flink_agents.api.resource import ( - Constant, ResourceDescriptor, + ResourceName, ResourceType, ) from flink_agents.api.tools.tool import Tool @@ -87,7 +87,7 @@ def test_react_agent_on_local_runner() -> None: # noqa: D103 env.add_resource( "ollama", ResourceType.CHAT_MODEL_CONNECTION, - ResourceDescriptor(clazz=Constant.OLLAMA_CHAT_MODEL_CONNECTION, request_timeout=240.0), + ResourceDescriptor(clazz=ResourceName.ChatModel.OLLAMA_CONNECTION, request_timeout=240.0), ) .add_resource("add", ResourceType.TOOL, Tool.from_callable(add)) .add_resource("multiply", ResourceType.TOOL, Tool.from_callable(multiply)) @@ -107,7 +107,7 @@ def test_react_agent_on_local_runner() -> None: # noqa: D103 # create ReAct agent. agent = ReActAgent( chat_model=ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.OLLAMA_SETUP, connection="ollama", model=OLLAMA_MODEL, tools=["add", "multiply"], @@ -166,7 +166,7 @@ def test_react_agent_on_remote_runner(tmp_path: Path) -> None: # noqa: D103 env.add_resource( "ollama", ResourceType.CHAT_MODEL_CONNECTION, - ResourceDescriptor(clazz=Constant.OLLAMA_CHAT_MODEL_CONNECTION, request_timeout=240.0), + ResourceDescriptor(clazz=ResourceName.ChatModel.OLLAMA_CONNECTION, request_timeout=240.0), ) .add_resource("add", ResourceType.TOOL, Tool.from_callable(add)) .add_resource("multiply", ResourceType.TOOL, Tool.from_callable(multiply)) @@ -191,7 +191,7 @@ def test_react_agent_on_remote_runner(tmp_path: Path) -> None: # noqa: D103 # create ReAct agent. agent = ReActAgent( chat_model=ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.OLLAMA_SETUP, connection="ollama", model=OLLAMA_MODEL, tools=["add", "multiply"], diff --git a/python/flink_agents/e2e_tests/e2e_tests_resource_cross_language/chat_model_cross_language_agent.py b/python/flink_agents/e2e_tests/e2e_tests_resource_cross_language/chat_model_cross_language_agent.py index 44ab63ce..709bb6a4 100644 --- a/python/flink_agents/e2e_tests/e2e_tests_resource_cross_language/chat_model_cross_language_agent.py +++ b/python/flink_agents/e2e_tests/e2e_tests_resource_cross_language/chat_model_cross_language_agent.py @@ -30,8 +30,8 @@ from flink_agents.api.events.chat_event import ChatRequestEvent, ChatResponseEve from flink_agents.api.events.event import InputEvent, OutputEvent from flink_agents.api.prompts.prompt import Prompt from flink_agents.api.resource import ( - Constant, ResourceDescriptor, + ResourceName, ) from flink_agents.api.runner_context import RunnerContext @@ -69,7 +69,7 @@ class ChatModelCrossLanguageAgent(Agent): def ollama_connection_python() -> ResourceDescriptor: """ChatModelConnection responsible for ollama model service connection.""" return ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_CONNECTION, request_timeout=240.0 + clazz=ResourceName.ChatModel.OLLAMA_CONNECTION, request_timeout=240.0 ) @chat_model_connection @@ -77,8 +77,8 @@ class ChatModelCrossLanguageAgent(Agent): def ollama_connection_java() -> ResourceDescriptor: """ChatModelConnection responsible for ollama model service connection.""" return ResourceDescriptor( - clazz=Constant.JAVA_CHAT_MODEL_CONNECTION, - java_clazz="org.apache.flink.agents.integrations.chatmodels.ollama.OllamaChatModelConnection", + clazz=ResourceName.ChatModel.JAVA_WRAPPER_CONNECTION, + java_clazz=ResourceName.ChatModel.Java.OLLAMA_CONNECTION, endpoint="http://localhost:11434";, requestTimeout=120, ) @@ -88,9 +88,9 @@ class ChatModelCrossLanguageAgent(Agent): def math_chat_model() -> ResourceDescriptor: """ChatModel which focus on math, and reuse ChatModelConnection.""" return ResourceDescriptor( - clazz=Constant.JAVA_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.JAVA_WRAPPER_SETUP, + java_clazz=ResourceName.ChatModel.Java.OLLAMA_SETUP, connection="ollama_connection_python", - java_clazz="org.apache.flink.agents.integrations.chatmodels.ollama.OllamaChatModelSetup", model=os.environ.get("OLLAMA_CHAT_MODEL", "qwen3:1.7b"), prompt="from_messages_prompt", tools=["add"], @@ -102,9 +102,9 @@ class ChatModelCrossLanguageAgent(Agent): def creative_chat_model() -> ResourceDescriptor: """ChatModel which focus on text generate, and reuse ChatModelConnection.""" return ResourceDescriptor( - clazz=Constant.JAVA_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.JAVA_WRAPPER_SETUP, + java_clazz=ResourceName.ChatModel.Java.OLLAMA_SETUP, connection="ollama_connection_java", - java_clazz="org.apache.flink.agents.integrations.chatmodels.ollama.OllamaChatModelSetup", model=os.environ.get("OLLAMA_CHAT_MODEL", "qwen3:1.7b"), prompt="from_text_prompt", extract_reasoning=True, diff --git a/python/flink_agents/e2e_tests/e2e_tests_resource_cross_language/embedding_model_cross_language_agent.py b/python/flink_agents/e2e_tests/e2e_tests_resource_cross_language/embedding_model_cross_language_agent.py index ba701898..56a85ffc 100644 --- a/python/flink_agents/e2e_tests/e2e_tests_resource_cross_language/embedding_model_cross_language_agent.py +++ b/python/flink_agents/e2e_tests/e2e_tests_resource_cross_language/embedding_model_cross_language_agent.py @@ -24,7 +24,11 @@ from flink_agents.api.decorators import ( embedding_model_setup, ) from flink_agents.api.events.event import InputEvent, OutputEvent -from flink_agents.api.resource import Constant, ResourceDescriptor, ResourceType +from flink_agents.api.resource import ( + ResourceDescriptor, + ResourceName, + ResourceType, +) from flink_agents.api.runner_context import RunnerContext @@ -36,8 +40,8 @@ class EmbeddingModelCrossLanguageAgent(Agent): def embedding_model_connection() -> ResourceDescriptor: """EmbeddingModelConnection responsible for ollama model service connection.""" return ResourceDescriptor( - clazz=Constant.JAVA_EMBEDDING_MODEL_CONNECTION, - java_clazz="org.apache.flink.agents.integrations.embeddingmodels.ollama.OllamaEmbeddingModelConnection", + clazz=ResourceName.EmbeddingModel.JAVA_WRAPPER_CONNECTION, + java_clazz=ResourceName.EmbeddingModel.Java.OLLAMA_CONNECTION, host="http://localhost:11434";, ) @@ -46,8 +50,8 @@ class EmbeddingModelCrossLanguageAgent(Agent): def embedding_model() -> ResourceDescriptor: """EmbeddingModel which focus on math, and reuse ChatModelConnection.""" return ResourceDescriptor( - clazz=Constant.JAVA_EMBEDDING_MODEL_SETUP, - java_clazz="org.apache.flink.agents.integrations.embeddingmodels.ollama.OllamaEmbeddingModelSetup", + clazz=ResourceName.EmbeddingModel.JAVA_WRAPPER_SETUP, + java_clazz=ResourceName.EmbeddingModel.Java.OLLAMA_SETUP, connection="embedding_model_connection", model=os.environ.get("OLLAMA_EMBEDDING_MODEL", "nomic-embed-text:latest"), ) diff --git a/python/flink_agents/e2e_tests/e2e_tests_resource_cross_language/vector_store_cross_language_agent.py b/python/flink_agents/e2e_tests/e2e_tests_resource_cross_language/vector_store_cross_language_agent.py index 576dc244..cc41e5a1 100644 --- a/python/flink_agents/e2e_tests/e2e_tests_resource_cross_language/vector_store_cross_language_agent.py +++ b/python/flink_agents/e2e_tests/e2e_tests_resource_cross_language/vector_store_cross_language_agent.py @@ -32,7 +32,11 @@ from flink_agents.api.events.context_retrieval_event import ( ContextRetrievalResponseEvent, ) from flink_agents.api.events.event import InputEvent, OutputEvent -from flink_agents.api.resource import Constant, ResourceDescriptor, ResourceType +from flink_agents.api.resource import ( + ResourceDescriptor, + ResourceName, + ResourceType, +) from flink_agents.api.runner_context import RunnerContext from flink_agents.api.vector_stores.vector_store import ( CollectionManageableVectorStore, @@ -51,12 +55,12 @@ class VectorStoreCrossLanguageAgent(Agent): """EmbeddingModelConnection responsible for ollama model service connection.""" if os.environ.get("EMBEDDING_TYPE") == "JAVA": return ResourceDescriptor( - clazz=Constant.JAVA_EMBEDDING_MODEL_CONNECTION, - java_clazz="org.apache.flink.agents.integrations.embeddingmodels.ollama.OllamaEmbeddingModelConnection", + clazz=ResourceName.EmbeddingModel.JAVA_WRAPPER_CONNECTION, + java_clazz=ResourceName.EmbeddingModel.Java.OLLAMA_CONNECTION, host="http://localhost:11434";, ) return ResourceDescriptor( - clazz=Constant.OLLAMA_EMBEDDING_MODEL_CONNECTION, + clazz=ResourceName.EmbeddingModel.OLLAMA_CONNECTION, host="http://localhost:11434";, ) @@ -66,15 +70,15 @@ class VectorStoreCrossLanguageAgent(Agent): """EmbeddingModel which focus on math, and reuse ChatModelConnection.""" if os.environ.get("EMBEDDING_TYPE") == "JAVA": return ResourceDescriptor( - clazz=Constant.JAVA_EMBEDDING_MODEL_SETUP, - java_clazz="org.apache.flink.agents.integrations.embeddingmodels.ollama.OllamaEmbeddingModelSetup", + clazz=ResourceName.EmbeddingModel.JAVA_WRAPPER_SETUP, + java_clazz=ResourceName.EmbeddingModel.Java.OLLAMA_SETUP, connection="embedding_model_connection", model=os.environ.get( "OLLAMA_EMBEDDING_MODEL", "nomic-embed-text:latest" ), ) return ResourceDescriptor( - clazz=Constant.OLLAMA_EMBEDDING_MODEL_SETUP, + clazz=ResourceName.EmbeddingModel.OLLAMA_SETUP, connection="embedding_model_connection", model=os.environ.get("OLLAMA_EMBEDDING_MODEL", "nomic-embed-text:latest"), ) @@ -84,8 +88,8 @@ class VectorStoreCrossLanguageAgent(Agent): def vector_store() -> ResourceDescriptor: """Vector store setup for knowledge base.""" return ResourceDescriptor( - clazz=Constant.JAVA_COLLECTION_MANAGEABLE_VECTOR_STORE, - java_clazz="org.apache.flink.agents.integrations.vectorstores.elasticsearch.ElasticsearchVectorStore", + clazz=ResourceName.VectorStore.JAVA_WRAPPER_COLLECTION_MANAGEABLE_VECTOR_STORE, + java_clazz=ResourceName.VectorStore.Java.ELASTICSEARCH_VECTOR_STORE, embedding_model="embedding_model", host=os.environ.get("ES_HOST"), index="my_documents", diff --git a/python/flink_agents/examples/quickstart/agents/custom_types_and_resources.py b/python/flink_agents/examples/quickstart/agents/custom_types_and_resources.py index a150604b..3bd463f9 100644 --- a/python/flink_agents/examples/quickstart/agents/custom_types_and_resources.py +++ b/python/flink_agents/examples/quickstart/agents/custom_types_and_resources.py @@ -21,7 +21,7 @@ from pydantic import BaseModel from flink_agents.api.chat_message import ChatMessage, MessageRole from flink_agents.api.prompts.prompt import Prompt -from flink_agents.api.resource import Constant, ResourceDescriptor +from flink_agents.api.resource import ResourceDescriptor, ResourceName # Prompt for review analysis agent. review_analysis_system_prompt_str = """ @@ -198,5 +198,5 @@ class ProductReviewAnalysisRes(BaseModel): # ollama chat model connection descriptor ollama_server_descriptor = ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_CONNECTION, request_timeout=120 + clazz=ResourceName.ChatModel.OLLAMA_CONNECTION, request_timeout=120 ) diff --git a/python/flink_agents/examples/quickstart/agents/product_suggestion_agent.py b/python/flink_agents/examples/quickstart/agents/product_suggestion_agent.py index e82c8130..2bd5a116 100644 --- a/python/flink_agents/examples/quickstart/agents/product_suggestion_agent.py +++ b/python/flink_agents/examples/quickstart/agents/product_suggestion_agent.py @@ -29,7 +29,7 @@ from flink_agents.api.decorators import ( from flink_agents.api.events.chat_event import ChatRequestEvent, ChatResponseEvent from flink_agents.api.events.event import InputEvent, OutputEvent from flink_agents.api.prompts.prompt import Prompt -from flink_agents.api.resource import Constant, ResourceDescriptor +from flink_agents.api.resource import ResourceDescriptor, ResourceName from flink_agents.api.runner_context import RunnerContext from flink_agents.examples.quickstart.agents.custom_types_and_resources import ( ProductSuggestion, @@ -65,7 +65,7 @@ class ProductSuggestionAgent(Agent): def generate_suggestion_model() -> ResourceDescriptor: """ChatModel which focus on generating product suggestions.""" return ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.OLLAMA_SETUP, connection="ollama_server", model="qwen3:8b", prompt="generate_suggestion_prompt", diff --git a/python/flink_agents/examples/quickstart/agents/review_analysis_agent.py b/python/flink_agents/examples/quickstart/agents/review_analysis_agent.py index b6abc284..18f0326e 100644 --- a/python/flink_agents/examples/quickstart/agents/review_analysis_agent.py +++ b/python/flink_agents/examples/quickstart/agents/review_analysis_agent.py @@ -30,7 +30,7 @@ from flink_agents.api.decorators import ( from flink_agents.api.events.chat_event import ChatRequestEvent, ChatResponseEvent from flink_agents.api.events.event import InputEvent, OutputEvent from flink_agents.api.prompts.prompt import Prompt -from flink_agents.api.resource import Constant, ResourceDescriptor +from flink_agents.api.resource import ResourceDescriptor, ResourceName from flink_agents.api.runner_context import RunnerContext from flink_agents.examples.quickstart.agents.custom_types_and_resources import ( ProductReviewAnalysisRes, @@ -81,7 +81,7 @@ class ReviewAnalysisAgent(Agent): def review_analysis_model() -> ResourceDescriptor: """ChatModel which focus on review analysis.""" return ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.OLLAMA_SETUP, connection="ollama_server", model="qwen3:8b", prompt="review_analysis_prompt", diff --git a/python/flink_agents/examples/quickstart/react_agent_example.py b/python/flink_agents/examples/quickstart/react_agent_example.py index 9f883c15..ca309975 100644 --- a/python/flink_agents/examples/quickstart/react_agent_example.py +++ b/python/flink_agents/examples/quickstart/react_agent_example.py @@ -23,7 +23,11 @@ from pyflink.datastream.connectors.file_system import FileSource, StreamFormat from flink_agents.api.agents.react_agent import ReActAgent from flink_agents.api.execution_environment import AgentsExecutionEnvironment -from flink_agents.api.resource import Constant, ResourceDescriptor, ResourceType +from flink_agents.api.resource import ( + ResourceDescriptor, + ResourceName, + ResourceType, +) from flink_agents.api.tools.tool import Tool from flink_agents.examples.quickstart.agents.custom_types_and_resources import ( ProductReview, @@ -54,7 +58,7 @@ def main() -> None: agents_env.add_resource( "ollama_server", ResourceType.CHAT_MODEL_CONNECTION, - ResourceDescriptor(clazz=Constant.OLLAMA_CHAT_MODEL_CONNECTION, request_timeout=120), + ResourceDescriptor(clazz=ResourceName.ChatModel.OLLAMA_CONNECTION, request_timeout=120), ).add_resource( "notify_shipping_manager", ResourceType.TOOL, Tool.from_callable(notify_shipping_manager) ) @@ -79,7 +83,7 @@ def main() -> None: # Create react agent review_analysis_react_agent = ReActAgent( chat_model=ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.OLLAMA_SETUP, connection="ollama_server", model="qwen3:8b", tools=["notify_shipping_manager"], diff --git a/python/flink_agents/examples/rag/rag_agent_example.py b/python/flink_agents/examples/rag/rag_agent_example.py index 0e44f909..8d9352a2 100644 --- a/python/flink_agents/examples/rag/rag_agent_example.py +++ b/python/flink_agents/examples/rag/rag_agent_example.py @@ -35,8 +35,8 @@ from flink_agents.api.events.event import InputEvent, OutputEvent from flink_agents.api.execution_environment import AgentsExecutionEnvironment from flink_agents.api.prompts.prompt import Prompt from flink_agents.api.resource import ( - Constant, ResourceDescriptor, + ResourceName, ResourceType, ) from flink_agents.api.runner_context import RunnerContext @@ -78,7 +78,7 @@ Please provide a helpful answer based on the context provided.""" def text_embedder() -> ResourceDescriptor: """Embedding model setup for generating text embeddings.""" return ResourceDescriptor( - clazz=Constant.OLLAMA_EMBEDDING_MODEL_SETUP, + clazz=ResourceName.EmbeddingModel.OLLAMA_SETUP, connection="ollama_embedding_connection", model=OLLAMA_EMBEDDING_MODEL, ) @@ -88,7 +88,7 @@ Please provide a helpful answer based on the context provided.""" def knowledge_base() -> ResourceDescriptor: """Vector store setup for knowledge base.""" return ResourceDescriptor( - clazz=Constant.CHROMA_VECTOR_STORE, + clazz=ResourceName.VectorStore.CHROMA_VECTOR_STORE, embedding_model="text_embedder", collection="example_knowledge_base", ) @@ -98,7 +98,7 @@ Please provide a helpful answer based on the context provided.""" def chat_model() -> ResourceDescriptor: """Chat model setup for generating responses.""" return ResourceDescriptor( - clazz=Constant.OLLAMA_CHAT_MODEL_SETUP, + clazz=ResourceName.ChatModel.OLLAMA_SETUP, connection="ollama_chat_connection", model=OLLAMA_CHAT_MODEL ) @@ -174,8 +174,8 @@ if __name__ == "__main__": agents_env = AgentsExecutionEnvironment.get_execution_environment() # Setup Ollama embedding and chat model connections - agents_env.add_resource("ollama_embedding_connection", ResourceType.EMBEDDING_MODEL_CONNECTION, ResourceDescriptor(clazz=Constant.OLLAMA_EMBEDDING_MODEL_CONNECTION)) - agents_env.add_resource("ollama_chat_connection", ResourceType.EMBEDDING_MODEL, ResourceDescriptor(clazz=Constant.OLLAMA_CHAT_MODEL_CONNECTION)) + agents_env.add_resource("ollama_embedding_connection", ResourceType.EMBEDDING_MODEL_CONNECTION, ResourceDescriptor(clazz=ResourceName.EmbeddingModel.OLLAMA_CONNECTION)) + agents_env.add_resource("ollama_chat_connection", ResourceType.EMBEDDING_MODEL, ResourceDescriptor(clazz=ResourceName.ChatModel.OLLAMA_CONNECTION)) output_list = agents_env.from_list(input_list).apply(agent).to_list()
