From 30117f7139941de9228d0815e697b1ebfbf49cdd Mon Sep 17 00:00:00 2001 From: Casper Nielsen Date: Mon, 5 Oct 2026 09:09:55 +0200 Subject: [PATCH] fix(deps): bump ruff to 0.16.2 and reformat with new rules Ruff 0.16.2 introduces new markdown formatting rules, particularly for list alignment and spacing. This commit updates the ruff dependency and reformats affected markdown files (mainly AGENTS.md and README.md) to comply with the new formatting standards. All linting and type checks pass with the updated rules. Signed-off-by: Casper Nielsen --- dapr/ext/databricks/AGENTS.md | 16 +- dapr/ext/databricks/README.md | 36 +- dapr/ext/fastapi/AGENTS.md | 6 +- dapr/ext/flask/AGENTS.md | 6 +- dapr/ext/flask/README.md | 1 + dapr/ext/grpc/AGENTS.md | 49 +- dapr/ext/rag/AGENTS.md | 13 +- dapr/ext/rag/README.md | 9 +- dapr/ext/strands/AGENTS.md | 6 +- dapr/ext/workflow/AGENTS.md | 18 +- dapr/ext/workflow/docs/concurrency.md | 1 + docs/rag/README.md | 59 +- docs/rag/foundry-iq.md | 13 +- docs/rag/observability.md | 14 +- examples/conversation/README.md | 96 ++- examples/conversation/TOOL-CALL-QUICKSTART.md | 24 +- examples/jobs/README.md | 22 +- examples/mcp/README.md | 14 +- examples/w3c-tracing/README.md | 18 +- pyproject.toml | 2 +- uv.lock | 710 +++++++++--------- 21 files changed, 591 insertions(+), 542 deletions(-) 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 != 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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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(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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