diff --git a/dapr/ext/databricks/AGENTS.md b/dapr/ext/databricks/AGENTS.md index 0dc507f9c..4eec4204e 100644 --- a/dapr/ext/databricks/AGENTS.md +++ b/dapr/ext/databricks/AGENTS.md @@ -78,14 +78,14 @@ identity layer on top of the existing `dapr.ext.workflow.DaprWorkflowClient`. ```python from dapr.ext.databricks import ( - register_workflow_sink, # high-level: registers a foreach_batch_sink - DaprWorkflowBatchHandler, # low-level: reusable batch-processing handler - WorkflowSinkConfig, # typed config, if constructing a handler directly - default_row_mapper, # the default Row -> dict mapper - DaprDatabricksError, # base exception - SinkConfigurationError, # bad register_workflow_sink() config - MissingBusinessKeyError, # configured id_field/id_fields absent or null on a row - DaprDatabricksSinkError, # a micro-batch could not be durably handed off + register_workflow_sink, # high-level: registers a foreach_batch_sink + DaprWorkflowBatchHandler, # low-level: reusable batch-processing handler + WorkflowSinkConfig, # typed config, if constructing a handler directly + default_row_mapper, # the default Row -> dict mapper + DaprDatabricksError, # base exception + SinkConfigurationError, # bad register_workflow_sink() config + MissingBusinessKeyError, # configured id_field/id_fields absent or null on a row + DaprDatabricksSinkError, # a micro-batch could not be durably handed off ) ``` diff --git a/dapr/ext/databricks/README.md b/dapr/ext/databricks/README.md index a2a187c2b..cb1597ba4 100644 --- a/dapr/ext/databricks/README.md +++ b/dapr/ext/databricks/README.md @@ -44,6 +44,7 @@ register_workflow_sink( namespace='orders', ) + @dp.append_flow(target='order_actions', name='order_actions_flow') def order_actions_flow(): return spark.readStream.table('validated_orders') @@ -81,7 +82,7 @@ register_workflow_sink( register_workflow_sink( name='transfers', workflow='process_transfer', - instance_id_factory=lambda row, batch_id: f"{row['account_id']}:{row['transaction_id']}", + instance_id_factory=lambda row, batch_id: f'{row["account_id"]}:{row["transaction_id"]}', ) ``` @@ -108,6 +109,7 @@ handler = DaprWorkflowBatchHandler( WorkflowSinkConfig(name='orders', workflow='process_order', id_field='order_id') ) + @dp.foreach_batch_sink(name='orders') def orders_handler(df, batch_id): handler.process(df, batch_id) @@ -171,24 +173,20 @@ scheduling latency. Business record contents are never logged. ```python register_workflow_sink( - name='orders', # sink name (foreach_batch_sink name) - workflow='process_order', # registered Dapr Workflow name - - id_field='order_id', # business key column (mutually exclusive with the two below) - id_fields=None, # composite business key columns - instance_id_factory=None, # (row, batch_id) -> business-key component - - namespace='orders', # identity partition; part of the instance ID - generation='v1', # identity epoch; bump to replay after a full refresh - - input_mapper=None, # Row -> dict; defaults to a JSON-safe asDict() - metadata=True, # wrap input as {'data': ..., 'metadata': {...}} - - max_in_flight=8, # bounded concurrent schedule_new_workflow calls - max_records_per_batch=None, # optional hard cap; fails the batch, never truncates silently - - host=None, port=None, # Dapr endpoint; defaults to the standard SDK env/settings - allow_batch_position_identity=False, # required opt-in to run without any id_field/id_fields/instance_id_factory + name='orders', # sink name (foreach_batch_sink name) + workflow='process_order', # registered Dapr Workflow name + id_field='order_id', # business key column (mutually exclusive with the two below) + id_fields=None, # composite business key columns + instance_id_factory=None, # (row, batch_id) -> business-key component + namespace='orders', # identity partition; part of the instance ID + generation='v1', # identity epoch; bump to replay after a full refresh + input_mapper=None, # Row -> dict; defaults to a JSON-safe asDict() + metadata=True, # wrap input as {'data': ..., 'metadata': {...}} + max_in_flight=8, # bounded concurrent schedule_new_workflow calls + max_records_per_batch=None, # optional hard cap; fails the batch, never truncates silently + host=None, + port=None, # Dapr endpoint; defaults to the standard SDK env/settings + allow_batch_position_identity=False, # required opt-in to run without any id_field/id_fields/instance_id_factory ) ``` diff --git a/dapr/ext/fastapi/AGENTS.md b/dapr/ext/fastapi/AGENTS.md index 2996230f8..2a518311b 100644 --- a/dapr/ext/fastapi/AGENTS.md +++ b/dapr/ext/fastapi/AGENTS.md @@ -32,8 +32,10 @@ Wraps a FastAPI instance to add Dapr pub/sub event handling. app = FastAPI() dapr_app = DaprApp(app, router_tags=['PubSub']) # router_tags optional, default ['PubSub'] -@dapr_app.subscribe(pubsub='pubsub', topic='orders', route='/handle-order', - metadata={}, dead_letter_topic=None) + +@dapr_app.subscribe( + pubsub='pubsub', topic='orders', route='/handle-order', metadata={}, dead_letter_topic=None +) def handle_order(event_data): return {'status': 'ok'} ``` diff --git a/dapr/ext/flask/AGENTS.md b/dapr/ext/flask/AGENTS.md index 90d9d2603..211275c51 100644 --- a/dapr/ext/flask/AGENTS.md +++ b/dapr/ext/flask/AGENTS.md @@ -34,8 +34,10 @@ Wraps a Flask instance to add Dapr pub/sub event handling. app = Flask('myapp') dapr_app = DaprApp(app) -@dapr_app.subscribe(pubsub='pubsub', topic='orders', route='/handle-order', - metadata={}, dead_letter_topic=None) + +@dapr_app.subscribe( + pubsub='pubsub', topic='orders', route='/handle-order', metadata={}, dead_letter_topic=None +) def handle_order(): event_data = request.json return 'ok' diff --git a/dapr/ext/flask/README.md b/dapr/ext/flask/README.md index 62990ad7c..269f136cf 100644 --- a/dapr/ext/flask/README.md +++ b/dapr/ext/flask/README.md @@ -14,6 +14,7 @@ from dapr.ext.flask import DaprApp app = Flask('myapp') dapr_app = DaprApp(app) + @dapr_app.subscribe(pubsub='pubsub', topic='some_topic', route='/some_endpoint') def my_event_handler(): # request.data contains the pubsub event diff --git a/dapr/ext/grpc/AGENTS.md b/dapr/ext/grpc/AGENTS.md index 6f29f0a29..64980314f 100644 --- a/dapr/ext/grpc/AGENTS.md +++ b/dapr/ext/grpc/AGENTS.md @@ -25,17 +25,17 @@ Installed via the `grpc` extra on core dapr: `pip install "dapr[grpc]"`. ```python from dapr.ext.grpc import ( - App, # Main entry point — decorator-based gRPC server - Rule, # CEL-based topic rule with priority - SubscriptionMessage, # Event type received by pub/sub topic handlers (preferred) - InvokeMethodRequest, # Request object for service invocation handlers - InvokeMethodResponse, # Response object for service invocation handlers - BindingRequest, # Request object for input binding handlers - TopicEventResponse, # Response object for pub/sub handlers - Job, # Job definition for scheduler - JobEvent, # Job event received by handler - FailurePolicy, # ABC for job failure policies - DropFailurePolicy, # Drop on failure (no retry) + App, # Main entry point — decorator-based gRPC server + Rule, # CEL-based topic rule with priority + SubscriptionMessage, # Event type received by pub/sub topic handlers (preferred) + InvokeMethodRequest, # Request object for service invocation handlers + InvokeMethodResponse, # Response object for service invocation handlers + BindingRequest, # Request object for input binding handlers + TopicEventResponse, # Response object for pub/sub handlers + Job, # Job definition for scheduler + JobEvent, # Job event received by handler + FailurePolicy, # ABC for job failure policies + DropFailurePolicy, # Drop on failure (no retry) ConstantFailurePolicy, # Retry with constant interval ) ``` @@ -51,22 +51,29 @@ The central entry point. Creates a gRPC server and provides decorators for handl ```python app = App() + @app.method('method_name') -def handle_method(request: InvokeMethodRequest) -> InvokeMethodResponse: - ... +def handle_method(request: InvokeMethodRequest) -> InvokeMethodResponse: ... + + +@app.subscribe( + pubsub_name='pubsub', + topic='orders', + metadata={}, + dead_letter_topic=None, + rule=Rule('event.type == "order"', priority=1), + disable_topic_validation=False, +) +def handle_event(event: SubscriptionMessage) -> Optional[TopicEventResponse]: ... -@app.subscribe(pubsub_name='pubsub', topic='orders', metadata={}, dead_letter_topic=None, - rule=Rule('event.type == "order"', priority=1), disable_topic_validation=False) -def handle_event(event: SubscriptionMessage) -> Optional[TopicEventResponse]: - ... @app.binding('binding_name') -def handle_binding(request: BindingRequest) -> None: - ... +def handle_binding(request: BindingRequest) -> None: ... + @app.job_event('job_name') -def handle_job(event: JobEvent) -> None: - ... +def handle_job(event: JobEvent) -> None: ... + app.register_health_check(lambda: None) # Not a decorator — direct registration ``` diff --git a/dapr/ext/rag/AGENTS.md b/dapr/ext/rag/AGENTS.md index df3bff570..6c977ef3b 100644 --- a/dapr/ext/rag/AGENTS.md +++ b/dapr/ext/rag/AGENTS.md @@ -118,10 +118,15 @@ per-adapter optional-import guards). ```python from dapr.ext.rag import ( - DurableRAGPipeline, PipelineConfig, - S3Source, AzureBlobSource, - UnstructuredParser, TextSplitter, OpenAIEmbedder, - PgVectorStore, PineconeVectorStore, + DurableRAGPipeline, + PipelineConfig, + S3Source, + AzureBlobSource, + UnstructuredParser, + TextSplitter, + OpenAIEmbedder, + PgVectorStore, + PineconeVectorStore, ActiveVersionResolver, ) diff --git a/dapr/ext/rag/README.md b/dapr/ext/rag/README.md index 66bf44416..79c37fe0a 100644 --- a/dapr/ext/rag/README.md +++ b/dapr/ext/rag/README.md @@ -11,7 +11,14 @@ pip install "dapr[rag,rag-azure,rag-pinecone]" # Azure Blob + Pinecone ``` ```python -from dapr.ext.rag import DurableRAGPipeline, S3Source, UnstructuredParser, TextSplitter, OpenAIEmbedder, PgVectorStore +from dapr.ext.rag import ( + DurableRAGPipeline, + S3Source, + UnstructuredParser, + TextSplitter, + OpenAIEmbedder, + PgVectorStore, +) pipeline = DurableRAGPipeline( source=S3Source(bucket='company-docs', prefix='policies/'), diff --git a/dapr/ext/strands/AGENTS.md b/dapr/ext/strands/AGENTS.md index 7955becef..6144776bf 100644 --- a/dapr/ext/strands/AGENTS.md +++ b/dapr/ext/strands/AGENTS.md @@ -31,9 +31,9 @@ Extends both `RepositorySessionManager` and `SessionRepository` from the Strands manager = DaprSessionManager( session_id='my-session', state_store_name='statestore', - dapr_client=client, # DaprClient instance - ttl=3600, # Optional: TTL in seconds - consistency='eventual', # 'eventual' (default) or 'strong' + dapr_client=client, # DaprClient instance + ttl=3600, # Optional: TTL in seconds + consistency='eventual', # 'eventual' (default) or 'strong' ) ``` diff --git a/dapr/ext/workflow/AGENTS.md b/dapr/ext/workflow/AGENTS.md index 4874a576c..b52bc20e0 100644 --- a/dapr/ext/workflow/AGENTS.md +++ b/dapr/ext/workflow/AGENTS.md @@ -76,16 +76,16 @@ All public symbols are exported from `dapr.ext.workflow`: ```python from dapr.ext.workflow import ( - WorkflowRuntime, # Registration & lifecycle (start/shutdown) - DaprWorkflowClient, # Sync client for scheduling/managing workflows - DaprWorkflowContext, # Passed to workflow functions as first arg + WorkflowRuntime, # Registration & lifecycle (start/shutdown) + DaprWorkflowClient, # Sync client for scheduling/managing workflows + DaprWorkflowContext, # Passed to workflow functions as first arg WorkflowActivityContext, # Passed to activity functions as first arg - WorkflowState, # Snapshot of a workflow instance's state - WorkflowStatus, # Enum: UNKNOWN, RUNNING, COMPLETED, FAILED, TERMINATED, PENDING, SUSPENDED, STALLED - when_all, # Parallel combinator — wait for all tasks - when_any, # Race combinator — wait for first task - alternate_name, # Decorator to set a custom registration name - RetryPolicy, # Retry config for activities/child workflows + WorkflowState, # Snapshot of a workflow instance's state + WorkflowStatus, # Enum: UNKNOWN, RUNNING, COMPLETED, FAILED, TERMINATED, PENDING, SUSPENDED, STALLED + when_all, # Parallel combinator — wait for all tasks + when_any, # Race combinator — wait for first task + alternate_name, # Decorator to set a custom registration name + RetryPolicy, # Retry config for activities/child workflows ) # Async client: diff --git a/dapr/ext/workflow/docs/concurrency.md b/dapr/ext/workflow/docs/concurrency.md index 50353dc64..2b926cdcc 100644 --- a/dapr/ext/workflow/docs/concurrency.md +++ b/dapr/ext/workflow/docs/concurrency.md @@ -75,6 +75,7 @@ cap: ```python _shared_client: httpx.AsyncClient | None = None + def _get_client() -> httpx.AsyncClient: global _shared_client if _shared_client is None: diff --git a/docs/rag/README.md b/docs/rag/README.md index 542c57fb0..0463f2b18 100644 --- a/docs/rag/README.md +++ b/docs/rag/README.md @@ -79,7 +79,7 @@ single set of scripts that switches between all of them via environment variable ```python from dapr.ext.rag import S3Source -source = S3Source(bucket="company-docs", prefix="policies/") +source = S3Source(bucket='company-docs', prefix='policies/') ``` Credentials come from **boto3's standard credential-provider chain** (environment variables, @@ -95,7 +95,11 @@ LocalStack for local development (see below), and `region_name`/explicit ```python from dapr.ext.rag import AzureBlobSource -source = AzureBlobSource(account_url="https://example.blob.core.windows.net", container="company-docs", prefix="policies/") +source = AzureBlobSource( + account_url='https://example.blob.core.windows.net', + container='company-docs', + prefix='policies/', +) ``` Authenticates with **`DefaultAzureCredential`** by default (managed identity, workload identity, @@ -109,7 +113,7 @@ Pass `connection_string=...` instead for Azurite or another local/dev connection ```python from dapr.ext.rag import OpenAIEmbedder -embedder = OpenAIEmbedder(model="text-embedding-3-small") +embedder = OpenAIEmbedder(model='text-embedding-3-small') ``` Resolves `OPENAI_API_KEY` from the environment by default. Requires the `rag` extra @@ -122,8 +126,8 @@ from azure.identity import DefaultAzureCredential from dapr.ext.rag import AzureOpenAIEmbedder embedder = AzureOpenAIEmbedder( - endpoint="https://my-resource.openai.azure.com", - deployment="text-embedding-3-small", + endpoint='https://my-resource.openai.azure.com', + deployment='text-embedding-3-small', credential=DefaultAzureCredential(), # this is also the default when omitted ) ``` @@ -142,7 +146,9 @@ one. Requires the `rag` and `rag-azure` extras. ```python from dapr.ext.rag import PgVectorStore -vector_store = PgVectorStore(connection_string="postgresql://user:password@host/db", collection="company_knowledge") +vector_store = PgVectorStore( + connection_string='postgresql://user:password@host/db', collection='company_knowledge' +) ``` All versions of one `collection` share a single physical table (`rag_chunks_{collection}`), scoped @@ -156,7 +162,7 @@ underscores). Requires the `rag-pgvector` extra (`psycopg[binary]`). ```python from dapr.ext.rag import PineconeVectorStore -vector_store = PineconeVectorStore(index_name="company-knowledge") +vector_store = PineconeVectorStore(index_name='company-knowledge') ``` Uses one **namespace per version** within a single Pinecone index (create the index itself, with a @@ -169,9 +175,9 @@ matching vector dimension/metric, ahead of time -- this class does not create in from dapr.ext.rag import AzureAISearchVectorStore vector_store = AzureAISearchVectorStore( - endpoint="https://my-search.search.windows.net", - index_base_name="company-knowledge", # creates company-knowledge-{version} indexes - semantic_configuration_name="company-knowledge-semantic", # optional + endpoint='https://my-search.search.windows.net', + index_base_name='company-knowledge', # creates company-knowledge-{version} indexes + semantic_configuration_name='company-knowledge-semantic', # optional ) ``` @@ -202,13 +208,19 @@ write documents, create indexes, or switch the alias. ```python pipeline = DurableRAGPipeline( - source=..., parser=UnstructuredParser(), splitter=TextSplitter(chunk_size=1000, chunk_overlap=150), - embedder=..., vector_store=..., state_store_name="rag-pipeline-state", + source=..., + parser=UnstructuredParser(), + splitter=TextSplitter(chunk_size=1000, chunk_overlap=150), + embedder=..., + vector_store=..., + state_store_name='rag-pipeline-state', ) pipeline.run_worker() # only in the process that should execute the workflow -- see examples/rag/worker.py -instance_id = pipeline.start(version="2026-09", activate_when_complete=True) -status = pipeline.get_status("2026-09") # PipelineStatus: counts, chunks, retries, bytes, stage, ... +instance_id = pipeline.start(version='2026-09', activate_when_complete=True) +status = pipeline.get_status( + '2026-09' +) # PipelineStatus: counts, chunks, retries, bytes, stage, ... active = pipeline.resolve_active_version() # None until activation succeeds ``` @@ -224,9 +236,13 @@ pipeline (it needs only the vector store, embedder, and state store -- not sourc ```python from dapr.ext.rag import ActiveVersionResolver -resolver = ActiveVersionResolver(pipeline_id="company-knowledge", state_store_name="rag-pipeline-state", - vector_store=..., embedder=...) -matches = resolver.query("What is the remote work policy?", top_k=5) +resolver = ActiveVersionResolver( + pipeline_id='company-knowledge', + state_store_name='rag-pipeline-state', + vector_store=..., + embedder=..., +) +matches = resolver.query('What is the remote work policy?', top_k=5) ``` `resolver.query(...)` always resolves the active version fresh (with strong read consistency) and @@ -295,10 +311,15 @@ behavior-affecting settings. ```python # S3 against LocalStack -S3Source(bucket="company-docs", endpoint_url="http://localhost:4566", aws_access_key_id="test", aws_secret_access_key="test") +S3Source( + bucket='company-docs', + endpoint_url='http://localhost:4566', + aws_access_key_id='test', + aws_secret_access_key='test', +) # Azure Blob against Azurite -AzureBlobSource(container="company-docs", connection_string="UseDevelopmentStorage=true") +AzureBlobSource(container='company-docs', connection_string='UseDevelopmentStorage=true') ``` Both accept an injected `client=`, so the default unit test run exercises the same adapter code diff --git a/docs/rag/foundry-iq.md b/docs/rag/foundry-iq.md index 75d536c35..7da6dc334 100644 --- a/docs/rag/foundry-iq.md +++ b/docs/rag/foundry-iq.md @@ -36,13 +36,16 @@ experience for all of this remains preview regardless of REST API version. Sourc from dapr.ext.rag import DurableRAGPipeline, FoundryIQKnowledgeSourceConfig pipeline = DurableRAGPipeline( - source=..., parser=..., splitter=..., embedder=..., + source=..., + parser=..., + splitter=..., + embedder=..., vector_store=..., # must be AzureAISearchVectorStore - state_store_name="rag-pipeline-state", + state_store_name='rag-pipeline-state', foundry_iq_knowledge_source=FoundryIQKnowledgeSourceConfig( - name="company-knowledge-ks", - source_data_fields=("title", "source_uri"), - search_fields=("content",), + name='company-knowledge-ks', + source_data_fields=('title', 'source_uri'), + search_fields=('content',), ), ) ``` diff --git a/docs/rag/observability.md b/docs/rag/observability.md index 7654925d8..919d7b8f8 100644 --- a/docs/rag/observability.md +++ b/docs/rag/observability.md @@ -160,7 +160,7 @@ from azure.monitor.opentelemetry import configure_azure_monitor configure_azure_monitor( # Falls back to the APPLICATIONINSIGHTS_CONNECTION_STRING environment # variable automatically if this kwarg is omitted. - connection_string=os.environ["APPLICATIONINSIGHTS_CONNECTION_STRING"], + connection_string=os.environ['APPLICATIONINSIGHTS_CONNECTION_STRING'], ) ``` @@ -173,13 +173,13 @@ reference above: ```python from opentelemetry import trace -tracer = trace.get_tracer("dapr.ext.rag") +tracer = trace.get_tracer('dapr.ext.rag') -with tracer.start_as_current_span("rag.process_document") as span: - span.set_attribute("dapr.workflow.instance_id", instance_id) - span.set_attribute("rag.pipeline_id", pipeline_id) - span.set_attribute("rag.version", version) - span.set_attribute("rag.document.id", document_id) +with tracer.start_as_current_span('rag.process_document') as span: + span.set_attribute('dapr.workflow.instance_id', instance_id) + span.set_attribute('rag.pipeline_id', pipeline_id) + span.set_attribute('rag.version', version) + span.set_attribute('rag.document.id', document_id) ... ``` diff --git a/examples/conversation/README.md b/examples/conversation/README.md index 4f630d46d..27d62d3e8 100644 --- a/examples/conversation/README.md +++ b/examples/conversation/README.md @@ -168,11 +168,13 @@ When using the Decorator or Function-to-Schema approach, you get the following b ```python from dapr.clients.grpc import conversation + @conversation.tool def get_weather(location: str, unit: str = 'fahrenheit') -> str: """Get current weather for a location.""" # Implementation or placeholder - return f"Weather in {location} (unit={unit})" + return f'Weather in {location} (unit={unit})' + # Tools registered via @conversation.tool can be retrieved with: tools = conversation.get_registered_tools() @@ -194,7 +196,7 @@ class Units(Enum): def get_weather(location: str, unit: Units = Units.FAHRENHEIT) -> str: """Get current weather for a location.""" - return f"Weather in {location}" + return f'Weather in {location}' # Use the from_function class method for automatic schema generation @@ -211,15 +213,13 @@ Use when you can't decorate or need to build tools dynamically. from dapr.clients.grpc import conversation function = conversation.ConversationToolsFunction( - name="calculate", - description="Perform calculations", + name='calculate', + description='Perform calculations', parameters={ - "type": "object", - "properties": { - "expression": {"type": "string", "description": "Math expression"} - }, - "required": ["expression"] - } + 'type': 'object', + 'properties': {'expression': {'type': 'string', 'description': 'Math expression'}}, + 'required': ['expression'], + }, ) calc_tool = conversation.ConversationTools(function=function) ``` @@ -229,9 +229,9 @@ calc_tool = conversation.ConversationTools(function=function) from dapr.clients.grpc import conversation function = conversation.ConversationToolsFunction( - name="get_time", - description="Get current time", - parameters={"type": "object", "properties": {}, "required": []} + name='get_time', + description='Get current time', + parameters={'type': 'object', 'properties': {}, 'required': []}, ) time_tool = conversation.ConversationTools(function=function) ``` @@ -241,19 +241,16 @@ time_tool = conversation.ConversationTools(function=function) from dapr.clients.grpc import conversation function = conversation.ConversationToolsFunction( - name="search", - description="Search the web", + name='search', + description='Search the web', parameters={ - "type": "object", - "properties": { - "query": {"type": "string"}, - "domains": { - "type": "array", - "items": {"type": "string"} - } + 'type': 'object', + 'properties': { + 'query': {'type': 'string'}, + 'domains': {'type': 'array', 'items': {'type': 'string'}}, }, - "required": ["query"] - } + 'required': ['query'], + }, ) search_tool = conversation.ConversationTools(function=function) ``` @@ -285,7 +282,7 @@ user_message = ConversationMessage( ```python system_message = ConversationMessage( of_system=ConversationMessageOfSystem( - content=[ConversationMessageContent(text="You are a helpful AI assistant.")] + content=[ConversationMessageContent(text='You are a helpful AI assistant.')] ) ) ``` @@ -294,8 +291,7 @@ system_message = ConversationMessage( ```python developer_message = ConversationMessage( of_developer=ConversationMessageOfDeveloper( - name="developer", - content=[ConversationMessageContent(text="System configuration update.")] + name='developer', content=[ConversationMessageContent(text='System configuration update.')] ) ) ``` @@ -304,8 +300,8 @@ developer_message = ConversationMessage( ```python assistant_message = ConversationMessage( of_assistant=ConversationMessageOfAssistant( - content=[ConversationMessageContent(text="I can help you with that!")], - tool_calls=[...] # Optional tool calls + content=[ConversationMessageContent(text='I can help you with that!')], + tool_calls=[...], # Optional tool calls ) ) ``` @@ -314,9 +310,9 @@ assistant_message = ConversationMessage( ```python tool_message = ConversationMessage( of_tool=ConversationMessageOfTool( - tool_id="call_123", - name="get_weather", - content=[ConversationMessageContent(text="Weather: 72°F, sunny")] + tool_id='call_123', + name='get_weather', + content=[ConversationMessageContent(text='Weather: 72°F, sunny')], ) ) ``` @@ -329,10 +325,10 @@ You can create the same messages more concisely using helpers from `conversation from dapr.clients.grpc import conversation user = conversation.create_user_message("What's the weather in Paris?") -system = conversation.create_system_message("You are a helpful AI assistant.") -assistant = conversation.create_assistant_message("I can help you with that!") +system = conversation.create_system_message('You are a helpful AI assistant.') +assistant = conversation.create_assistant_message('I can help you with that!') tool_result = conversation.create_tool_message( - tool_id="call_123", name="get_weather", content="Weather: 72°F, sunny" + tool_id='call_123', name='get_weather', content='Weather: 72°F, sunny' ) ``` @@ -344,12 +340,13 @@ Alpha2 excels at multi-turn conversations with proper context accumulation: from dapr.clients.grpc import conversation conversation_history: list[conversation.ConversationMessage] = [ - conversation.create_user_message("What's the weather in SF?")] + conversation.create_user_message("What's the weather in SF?") +] # Turn 1: User asks a question response1: conversation.ConversationResponseAlpha2 = client.converse_alpha2( - name="openai", + name='openai', inputs=[conversation.ConversationInputAlpha2(messages=conversation_history)], tools=conversation.get_registered_tools(), tool_choice='auto', @@ -362,13 +359,15 @@ for msg in response1.to_assistant_messages(): for tc in msg.of_assistant.tool_calls: tool_output = conversation.execute_registered_tool(tc.function.name, tc.function.arguments) conversation_history.append( - conversation.create_tool_message(tool_id=tc.id, name=tc.function.name, content=str(tool_output)) + conversation.create_tool_message( + tool_id=tc.id, name=tc.function.name, content=str(tool_output) + ) ) # Turn 2 with accumulated context -conversation_history.append(conversation.create_user_message("Should I bring an umbrella?")) +conversation_history.append(conversation.create_user_message('Should I bring an umbrella?')) response2 = client.converse_alpha2( - name="openai", + name='openai', inputs=[conversation.ConversationInputAlpha2(messages=conversation_history)], tools=conversation.get_registered_tools(), ) @@ -381,9 +380,8 @@ We have added a trace print method to the ConversationMessage class that will pr For example in the real_llm_providers_example.py file, we have the following code in a multi-turn conversation: ```python - - for msg in conversation_history: - msg.trace_print(2) +for msg in conversation_history: + msg.trace_print(2) ``` That will print the conversation history with the following output (might vary depending on the LLM provider): @@ -451,19 +449,19 @@ Full async/await support for non-blocking operations: ```python from dapr.aio.clients import DaprClient as AsyncDaprClient + async def async_conversation(): async with AsyncDaprClient() as client: - user_message = create_user_message("Tell me a joke about async programming.") + user_message = create_user_message('Tell me a joke about async programming.') input_alpha2 = ConversationInputAlpha2(messages=[user_message]) - + response = await client.converse_alpha2( - name="openai", - inputs=[input_alpha2], - parameters={'temperature': 0.7} + name='openai', inputs=[input_alpha2], parameters={'temperature': 0.7} ) - + return response.outputs[0].choices[0].message.content + # Run async function result = asyncio.run(async_conversation()) ``` diff --git a/examples/conversation/TOOL-CALL-QUICKSTART.md b/examples/conversation/TOOL-CALL-QUICKSTART.md index 4d0ab88ee..e7d061fe1 100644 --- a/examples/conversation/TOOL-CALL-QUICKSTART.md +++ b/examples/conversation/TOOL-CALL-QUICKSTART.md @@ -12,7 +12,7 @@ from dapr.clients.grpc import conversation @conversation.tool def get_weather(location: str, unit: str = 'fahrenheit') -> str: """Get current weather for a location.""" - return f"Weather in {location} (unit={unit})" + return f'Weather in {location} (unit={unit})' user_msg = conversation.create_user_message("What's the weather in Paris?") @@ -20,7 +20,7 @@ input_alpha2 = conversation.ConversationInputAlpha2(messages=[user_msg]) with DaprClient() as client: response = client.converse_alpha2( - name="openai", + name='openai', inputs=[input_alpha2], tools=conversation.get_registered_tools(), # tools registered by @conversation.tool tool_choice='auto', @@ -30,7 +30,7 @@ with DaprClient() as client: for msg in response.to_assistant_messages(): if msg.of_assistant.tool_calls: for tc in msg.of_assistant.tool_calls: - print(f"Tool call: {tc.function.name} args={tc.function.arguments}") + print(f'Tool call: {tc.function.name} args={tc.function.arguments}') else: print(msg.of_assistant.content[0].text) ``` @@ -44,7 +44,7 @@ from dapr.clients.grpc import conversation @conversation.tool def get_weather(location: str, unit: str = 'fahrenheit') -> str: - return f"Weather in {location} (unit={unit})" + return f'Weather in {location} (unit={unit})' history: list[conversation.ConversationMessage] = [] @@ -53,7 +53,7 @@ history.append(conversation.create_user_message("What's the weather in San Franc with DaprClient() as client: # Turn 1 resp1 = client.converse_alpha2( - name="openai", + name='openai', inputs=[conversation.ConversationInputAlpha2(messages=history)], tools=conversation.get_registered_tools(), tool_choice='auto', @@ -65,15 +65,19 @@ with DaprClient() as client: history.append(msg) for tc in msg.of_assistant.tool_calls: # Execute (we suggest validating inputs before execution in production) - tool_output = conversation.execute_registered_tool(tc.function.name, tc.function.arguments) + tool_output = conversation.execute_registered_tool( + tc.function.name, tc.function.arguments + ) history.append( - conversation.create_tool_message(tool_id=tc.id, name=tc.function.name, content=str(tool_output)) + conversation.create_tool_message( + tool_id=tc.id, name=tc.function.name, content=str(tool_output) + ) ) # Turn 2 (LLM sees tool result) - history.append(conversation.create_user_message("Should I bring an umbrella?")) + history.append(conversation.create_user_message('Should I bring an umbrella?')) resp2 = client.converse_alpha2( - name="openai", + name='openai', inputs=[conversation.ConversationInputAlpha2(messages=history)], tools=conversation.get_registered_tools(), parameters={'temperature': 0.2}, @@ -100,7 +104,7 @@ class Units(Enum): def get_weather(location: str, unit: Units = Units.FAHRENHEIT) -> str: - return f"Weather in {location}" + return f'Weather in {location}' fn = conversation.ConversationToolsFunction.from_function(get_weather) diff --git a/examples/jobs/README.md b/examples/jobs/README.md index 2125050c6..0a97df550 100644 --- a/examples/jobs/README.md +++ b/examples/jobs/README.md @@ -195,11 +195,7 @@ Drops the job when it fails to trigger (no retries): ```python from dapr.clients import Job, DropFailurePolicy -job = Job( - name="my-job", - schedule="@every 30s", - failure_policy=DropFailurePolicy() -) +job = Job(name='my-job', schedule='@every 30s', failure_policy=DropFailurePolicy()) ``` ### ConstantFailurePolicy @@ -210,12 +206,12 @@ Retries the job at constant intervals when it fails to trigger: from dapr.clients import Job, ConstantFailurePolicy job = Job( - name="my-job", - schedule="@every 30s", + name='my-job', + schedule='@every 30s', failure_policy=ConstantFailurePolicy( - max_retries=3, # Maximum number of retries (optional) - interval_seconds=10 # Interval between retries in seconds - ) + max_retries=3, # Maximum number of retries (optional) + interval_seconds=10, # Interval between retries in seconds + ), ) ``` @@ -232,13 +228,15 @@ from dapr.ext.grpc import App, JobEvent app = App() + @app.job_event('my-job') def handle_my_job(job_event: JobEvent) -> None: - print(f"Job {job_event.name} triggered!") + print(f'Job {job_event.name} triggered!') data_str = job_event.get_data_as_string() - print(f"Job data: {data_str}") + print(f'Job data: {data_str}') # Process the job... + app.run(13551) ``` diff --git a/examples/mcp/README.md b/examples/mcp/README.md index aac2981d7..ae0916059 100644 --- a/examples/mcp/README.md +++ b/examples/mcp/README.md @@ -76,11 +76,11 @@ spec: ```python from dapr.ext.workflow import DaprMCPClient -client = DaprMCPClient(timeout_in_seconds=30, allowed_tools={"get_weather"}) -client.connect("weather") +client = DaprMCPClient(timeout_in_seconds=30, allowed_tools={'get_weather'}) +client.connect('weather') for tool in client.get_all_tools(): - print(tool.name, "→", tool.call_tool_workflow) + print(tool.name, '→', tool.call_tool_workflow) ``` `MCPToolDef` carries: @@ -110,20 +110,21 @@ from dapr.ext.workflow.mcp_schema import create_pydantic_model_from_schema # ---- 1. Discover --------------------------------------------------------- client = DaprMCPClient() -client.connect("weather") +client.connect('weather') + # ---- 2. Translate each MCPToolDef into your framework's tool ------------ def to_my_framework_tool(tool_def): # Build an args model from the JSON Schema args_model: Optional[Type[BaseModel]] = create_pydantic_model_from_schema( - tool_def.input_schema, f"{tool_def.name}Args" + tool_def.input_schema, f'{tool_def.name}Args' ) # Build the executor that schedules the child workflow def _executor(ctx: Any, **kwargs: Any) -> Any: return ctx.call_child_workflow( workflow=tool_def.call_tool_workflow, - input={"arguments": kwargs}, + input={'arguments': kwargs}, ) return MyFrameworkTool( @@ -133,6 +134,7 @@ def to_my_framework_tool(tool_def): args_model=args_model, ) + tools = [to_my_framework_tool(t) for t in client.get_all_tools()] # ... pass `tools` to your framework's agent constructor. ``` diff --git a/examples/w3c-tracing/README.md b/examples/w3c-tracing/README.md index d63c3b544..55cbf0aec 100644 --- a/examples/w3c-tracing/README.md +++ b/examples/w3c-tracing/README.md @@ -80,10 +80,7 @@ def saytrace(request: InvokeMethodRequest) -> InvokeMethodResponse: print(request.metadata, flush=True) print(request.text(), flush=True) - resp = { - 'receivedtraceid': span.get_span_context().trace_id, - 'method': 'SAY' - } + resp = {'receivedtraceid': span.get_span_context().trace_id, 'method': 'SAY'} return InvokeMethodResponse(json.dumps(resp), 'application/json; charset=UTF-8') ``` @@ -121,7 +118,7 @@ def forward(request: InvokeMethodRequest) -> InvokeMethodResponse: resp = d.invoke_method( 'invoke-receiver', 'saytrace', - data=request.text().encode("utf-8"), + data=request.text().encode('utf-8'), ) return InvokeMethodResponse(json.dumps(resp.json()), 'application/json; charset=UTF-8') @@ -169,7 +166,7 @@ from dapr.clients import DaprClient tracer_provider = TracerProvider(sampler=ALWAYS_ON) # Create a span processor -span_processor = BatchSpanProcessor(ZipkinExporter(endpoint="http://localhost:9411/api/v2/spans")) +span_processor = BatchSpanProcessor(ZipkinExporter(endpoint='http://localhost:9411/api/v2/spans')) # Add the span processor to the tracer provider tracer_provider.add_span_processor(span_processor) @@ -213,9 +210,12 @@ with tracer.start_as_current_span(name='main') as span: print(resp.text(), flush=True) forwarded_resp = d.invoke_method('invoke-receiver', 'forward', data='') - match_string = 'matches' if ( - forwarded_resp.json()["receivedtraceid"] == traceid) else 'does not match' - print(f"Trace ID {match_string} after forwarding", flush=True) + match_string = ( + 'matches' + if (forwarded_resp.json()['receivedtraceid'] == traceid) + else 'does not match' + ) + print(f'Trace ID {match_string} after forwarding', flush=True) ``` The class knows the `app-id` for the remote application. It uses `invoke_method` to invoke API calls on the service endpoint. Instrumentation happens automatically in `Dapr` client via the `tracer` argument. diff --git a/pyproject.toml b/pyproject.toml index d2cd7de45..fb08b3985 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -188,7 +188,7 @@ dev = [ "Flask~=3.1.3", "pytest>=9.0.2,<9.2.0", "pytest-asyncio>=0.23", - "ruff==0.15.19", + "ruff==0.16.2", "python-dotenv~=1.2.2", "pydantic~=2.13.3", "PyYAML~=6.0.3", diff --git a/uv.lock b/uv.lock index 717b54331..07f68fcfe 100644 --- a/uv.lock +++ b/uv.lock @@ -8,12 +8,12 @@ resolution-markers = [ "python_full_version == '3.14.*' and sys_platform == 'win32'", "python_full_version == '3.14.*' and sys_platform != 'win32'", "python_full_version == '3.13.*' and sys_platform == 'win32'", - "python_full_version == '3.12.*' and sys_platform == 'win32'", - "python_full_version == '3.11.*' and sys_platform == 'win32'", - "python_full_version < '3.11' and sys_platform == 'win32'", "python_full_version == '3.13.*' and sys_platform != 'win32'", + "python_full_version == '3.12.*' and sys_platform == 'win32'", "python_full_version == '3.12.*' and sys_platform != 'win32'", + "python_full_version == '3.11.*' and sys_platform == 'win32'", "python_full_version == '3.11.*' and sys_platform != 'win32'", + "python_full_version < '3.11' and sys_platform == 'win32'", "python_full_version < '3.11' and sys_platform != 'win32'", ] @@ -26,15 +26,15 @@ version = "1.15.0" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "huggingface-hub", version = "1.16.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11' and sys_platform != 'win32'" }, - { name = "huggingface-hub", version = "1.31.0", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version >= '3.11' and sys_platform != 'win32') or (python_full_version < '3.11' and sys_platform == 'win32') or (python_full_version == '3.12.*' and sys_platform == 'win32')" }, + { name = "huggingface-hub", version = "1.31.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11' or sys_platform == 'win32'" }, { name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.11'" }, { name = "numpy", version = "2.4.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version == '3.11.*' and sys_platform != 'win32'" }, { name = "numpy", version = "2.5.3", source = { registry = "https://pypi.org/simple" }, marker = "(python_full_version >= '3.12' and sys_platform != 'win32') or (python_full_version == '3.12.*' and sys_platform == 'win32')" }, - { name = "packaging", marker = "python_full_version < '3.11' or python_full_version == '3.12.*' or sys_platform != 'win32'" }, - { name = "psutil", marker = "python_full_version < '3.11' or python_full_version == '3.12.*' or sys_platform != 'win32'" }, - { name = "pyyaml", marker = "python_full_version < '3.11' or python_full_version == '3.12.*' or sys_platform != 'win32'" }, - { name = "safetensors", marker = "python_full_version < '3.11' or python_full_version == '3.12.*' or sys_platform != 'win32'" }, - { name = "torch", marker = "python_full_version < '3.11' or python_full_version == '3.12.*' or sys_platform != 'win32'" }, + { name = "packaging" }, + { name = "psutil" }, + { name = "pyyaml" }, + { name = "safetensors" }, + { name = "torch" }, ] sdist = { url = "https://files.pythonhosted.org/packages/f5/b5/1d3ed029ac71d3f2961346829a268da923698e9fd63f218f78841f216bfd/accelerate-1.15.0.tar.gz", hash = "sha256:5654f8c5eaa0d4fa68b33e287a97765da6849bf6d51dcac874e73fbbddfb6134", size = 422615, upload-time = "2026-09-09T13:04:49.078Z" } wheels = [ @@ -419,7 +419,7 @@ name = "blis" version = "1.3.3" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "numpy", version = "2.4.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version == '3.11.*'" }, + { name = "numpy", version = "2.4.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, { name = "numpy", version = "2.5.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, ] sdist = { url = "https://files.pythonhosted.org/packages/d0/d0/d8cc8c9a4488a787e7fa430f6055e5bd1ddb22c340a751d9e901b82e2efe/blis-1.3.3.tar.gz", hash = "sha256:034d4560ff3cc43e8aa37e188451b0440e3261d989bb8a42ceee865607715ecd", size = 2644873, upload-time = "2025-11-17T12:28:30.511Z" } @@ -688,7 +688,7 @@ resolution-markers = [ "python_full_version < '3.11' and sys_platform != 'win32'", ] dependencies = [ - { name = "colorama", marker = "(python_full_version == '3.11.*' and sys_platform == 'win32') or (python_full_version == '3.14.*' and sys_platform == 'win32')" }, + { name = "colorama", marker = "sys_platform == 'win32'" }, ] sdist = { url = "https://files.pythonhosted.org/packages/3d/fa/656b739db8587d7b5dfa22e22ed02566950fbfbcdc20311993483657a5c0/click-8.3.1.tar.gz", hash 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+ { name = "nvidia-cublas", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" }, + { name = "nvidia-cuda-nvrtc", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" }, ] cudart = [ - { name = "nvidia-cuda-runtime", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, + { name = "nvidia-cuda-runtime", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" }, ] cufft = [ - { name = "nvidia-cufft", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, - { name = "nvidia-nvjitlink", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, + { name = "nvidia-cufft", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" }, + { name = "nvidia-nvjitlink", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" }, ] cufile = [ - { name = "nvidia-cufile", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, + { name = "nvidia-cufile", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" }, ] cupti = [ - { name = "nvidia-cuda-cupti", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, + { name = "nvidia-cuda-cupti", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" }, ] curand = [ - { name = "nvidia-curand", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, + { name = "nvidia-curand", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" }, ] cusolver = [ - { name = "nvidia-cublas", marker = "(platform_machine == 'aarch64' 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== 'x86_64'" }, ] cusparse = [ - { name = "nvidia-cusparse", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, - { name = "nvidia-nvjitlink", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, + { name = "nvidia-cusparse", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" }, + { name = "nvidia-nvjitlink", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" }, ] nvjitlink = [ - { name = "nvidia-nvjitlink", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, + { name = "nvidia-nvjitlink", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" }, ] nvrtc = [ - { name = "nvidia-cuda-nvrtc", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, + { name = "nvidia-cuda-nvrtc", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" }, ] nvtx = [ - { name = "nvidia-nvtx", marker = "(platform_machine == 'aarch64' and sys_platform == 'linux') or (platform_machine == 'x86_64' and sys_platform == 'linux')" }, + { name = "nvidia-nvtx", marker = "platform_machine == 'aarch64' or platform_machine == 'x86_64'" }, ] [[package]] @@ -1450,7 +1450,7 @@ dev = [ { name = "python-dotenv", specifier = "~=1.2.2" }, { name = "pyyaml", specifier = "~=6.0.3" }, { name = "redis", specifier = ">=7.4.0" }, - { name = "ruff", specifier = "==0.15.19" }, + { name = "ruff", specifier = "==0.16.2" }, { name = "types-grpcio-status", specifier = "~=1.0.0" }, { name = "types-python-dateutil", specifier = "~=2.9.0" }, { name = "wheel", specifier = "~=0.46.3" }, @@ -1476,7 +1476,7 @@ tests = [ { name = "python-dotenv", specifier = "~=1.2.2" }, { name = "pyyaml", specifier = 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dependencies = [ - { name = "cloudpickle", marker = "python_full_version < '3.11'" }, + { name = "cloudpickle" }, ] sdist = { url = "https://files.pythonhosted.org/packages/d5/1d/537ab090f302b838943a1b56497dd53059b9a9b46a074936470173a2e207/joblib-1.6.0.tar.gz", hash = "sha256:2ccc96785b12046c08fd6d55839c12857831b54a3c1673ffadd2f04bfc4eda03", size = 327903, upload-time = "2026-08-31T09:39:04.122Z" } wheels = [ @@ -3090,7 +3090,7 @@ name = "marshmallow" version = "3.26.2" source = { registry = "https://pypi.org/simple" } dependencies = [ - { name = "packaging", marker = "python_full_version < '3.11'" }, + { name = "packaging" }, ] sdist = { url = "https://files.pythonhosted.org/packages/55/79/de6c16cc902f4fc372236926b0ce2ab7845268dcc30fb2fbb7f71b418631/marshmallow-3.26.2.tar.gz", hash = "sha256:bbe2adb5a03e6e3571b573f42527c6fe926e17467833660bebd11593ab8dfd57", size = 222095, upload-time = "2025-12-22T06:53:53.309Z" } wheels = [ @@ -3106,15 +3106,15 @@ resolution-markers = [ 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