feat!: bump to v4.0.0

CHANGELOG.md

@@ -5,7 +5,15 @@ All notable changes to the AxonFlow Python SDK will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [3.9.0] - 2026-03-06
+## [4.0.0] - 2026-03-09
+
+### Breaking Changes
+
+- **Removed `total_steps` from `CreateWorkflowRequest`**. Requires Platform v4.5.0+ (recommended v5.0.0+).
+  Total steps are auto-computed when the workflow reaches a terminal state.
+- **`mcp_check_input()` default `operation` changed from `"query"` to `"execute"`**. Callers relying on
+  the implicit `"query"` default must now pass `operation="query"` explicitly. This better reflects the
+  default MCP tool call pattern where side effects are unknown.
 
 ### Added
 
@@ -15,13 +23,20 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
     - `operation`: Operation type forwarded to `mcp_check_input` (default: `"execute"`; use `"query"` for known read-only tool calls)
   - `MCPInterceptorOptions` and `WorkflowApprovalRequiredError` are now exported from `axonflow.adapters`
 
+### Fixed
+
+- `mcp_tool_interceptor()` now uses JSON serialization (`json.dumps`) for `statement` and output `message` fields instead of Python `repr()`, ensuring the policy engine receives valid structured data
+
 ### Changed
 
-- `mcp_check_input()` default `operation` changed from `"query"` to `"execute"` to better reflect the default MCP tool call pattern where side effects are unknown
+- Removed Scarf tracking pixel from README (GitHub's camo proxy strips viewer identity, making the pixel unattributable)
+- Disabled SDK telemetry in CI workflows with `DO_NOT_TRACK=1` to prevent test runs from polluting checkpoint data
+- Added pip dependency caching to CI and release workflows for faster builds
 
-### Fixed
+### Note
 
-- `mcp_tool_interceptor()` now uses JSON serialization (`json.dumps`) for `statement` and output `message` fields instead of Python `repr()`, ensuring the policy engine receives valid structured data
+`MediaAnalysisResult.extracted_text` was replaced by `has_extracted_text` + `extracted_text_length`
+in v3.5.0. This major version formally acknowledges that breaking change.
 
 ---
 

axonflow/_version.py

@@ -1,3 +1,3 @@
 """Single source of truth for the AxonFlow SDK version."""
 
-__version__ = "3.8.0"
+__version__ = "4.0.0"

axonflow/adapters/langgraph.py

@@ -115,7 +115,7 @@ class AxonFlowLangGraphAdapter:
 
     Example:
         >>> adapter = AxonFlowLangGraphAdapter(client, "code-review-pipeline")
-        >>> await adapter.start_workflow(total_steps=5)
+        >>> await adapter.start_workflow()
         >>>
         >>> # Before each LangGraph node execution
         >>> if await adapter.check_gate("analyze", "llm_call"):
@@ -149,7 +149,6 @@ def __init__(
 
     async def start_workflow(
         self,
-        total_steps: int | None = None,
         metadata: dict[str, Any] | None = None,
         trace_id: str | None = None,
     ) -> str:
@@ -158,7 +157,6 @@ async def start_workflow(
         Call this at the start of your LangGraph workflow execution.
 
         Args:
-            total_steps: Total number of steps (if known)
             metadata: Additional workflow metadata
             trace_id: External trace ID for correlation (Langsmith, Datadog, OTel)
 
@@ -167,15 +165,13 @@ async def start_workflow(
 
         Example:
             >>> workflow_id = await adapter.start_workflow(
-            ...     total_steps=5,
             ...     metadata={"customer_id": "cust-123"},
             ...     trace_id="langsmith-run-abc123",
             ... )
         """
         request = CreateWorkflowRequest(
             workflow_name=self.workflow_name,
             source=self.source,
-            total_steps=total_steps,
             metadata=metadata or {},
             trace_id=trace_id,
         )

axonflow/client.py

@@ -3439,7 +3439,6 @@ async def create_workflow(
             ...     CreateWorkflowRequest(
             ...         workflow_name="customer-support-agent",
             ...         source=WorkflowSource.LANGGRAPH,
-            ...         total_steps=5,
             ...         metadata={"customer_id": "cust-123"}
             ...     )
             ... )
@@ -3448,7 +3447,6 @@ async def create_workflow(
         body = {
             "workflow_name": request.workflow_name,
             "source": request.source.value if request.source else "external",
-            "total_steps": request.total_steps,
             "metadata": request.metadata,
         }
         if request.trace_id:

axonflow/workflow.py

@@ -75,9 +75,6 @@ class CreateWorkflowRequest(BaseModel):
     source: WorkflowSource | None = Field(
         default=None, description="Source orchestrator running the workflow"
     )
-    total_steps: int | None = Field(
-        default=None, ge=0, description="Total number of steps in the workflow (if known)"
-    )
     metadata: dict[str, Any] = Field(
         default_factory=dict, description="Additional metadata for the workflow"
     )

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "axonflow"
-version = "3.8.0"
+version = "4.0.0"
 description = "AxonFlow Python SDK - Enterprise AI Governance in 3 Lines of Code"
 readme = "README.md"
 license = {text = "MIT"}

tests/test_wcp_approvals.py

@@ -865,7 +865,6 @@ async def test_create_workflow(
         request = CreateWorkflowRequest(
             workflow_name="customer-support",
             source=WorkflowSource.LANGGRAPH,
-            total_steps=3,
             metadata={"customer_id": "cust-1"},
         )
         result = await client.create_workflow(request)