chore(agent): remove v1 wording from runner internals

src/langbot/pkg/agent/runner/context_builder.py

@@ -1,4 +1,4 @@
-"""Agent run context builder for converting Query to SDK v1 AgentRunContext."""
+"""Agent run context builder for converting Query to AgentRunContext."""
 from __future__ import annotations
 
 import uuid
@@ -15,7 +15,7 @@ from .state_store import get_state_store
 from . import events as runner_events
 
 
-# Internal models for SDK v1 context protocol matching SDK v1 resources.py
+# Internal models for the agent runner context protocol.
 
 
 class AgentTrigger(typing.TypedDict):
@@ -52,32 +52,32 @@ class AgentRunState(typing.TypedDict):
     runner: dict[str, typing.Any]
 
 
-# SDK v1 Protocol resource models - matching langbot-plugin-sdk/resources.py
+# Resource payload models matching langbot-plugin-sdk/resources.py.
 
 
 class ModelResource(typing.TypedDict):
-    """Model resource per SDK v1."""
+    """Model resource payload."""
     model_id: str
     model_type: str | None
     provider: str | None
 
 
 class ToolResource(typing.TypedDict):
-    """Tool resource per SDK v1."""
+    """Tool resource payload."""
     tool_name: str
     tool_type: str | None
     description: str | None
 
 
 class KnowledgeBaseResource(typing.TypedDict):
-    """Knowledge base resource per SDK v1."""
+    """Knowledge base resource payload."""
     kb_id: str
     kb_name: str | None
     kb_type: str | None
 
 
 class FileResource(typing.TypedDict):
-    """File resource per SDK v1."""
+    """File resource payload."""
     file_id: str
     file_name: str | None
     mime_type: str | None
@@ -85,13 +85,13 @@ class FileResource(typing.TypedDict):
 
 
 class StorageResource(typing.TypedDict):
-    """Storage resource per SDK v1."""
+    """Storage resource payload."""
     plugin_storage: bool
     workspace_storage: bool
 
 
 class AgentResources(typing.TypedDict):
-    """Agent resources per SDK v1."""
+    """Agent resources payload."""
     models: list[ModelResource]
     tools: list[ToolResource]
     knowledge_bases: list[KnowledgeBaseResource]
@@ -110,8 +110,8 @@ class AgentRuntimeContext(typing.TypedDict):
     metadata: dict[str, typing.Any]
 
 
-class AgentRunContextV1(typing.TypedDict):
+class AgentRunContextPayload(typing.TypedDict):
-    """SDK v1 AgentRunContext per PROTOCOL_V1.md.
+    """AgentRunContext payload passed to an agent runner.
 
     Note: The 'config' field contains the binding config from ai.runner_config[runner_id],
     which is Pipeline's configuration for this specific runner binding (not plugin instance config).
@@ -133,7 +133,7 @@ class AgentRunContextV1(typing.TypedDict):
 
 
 class AgentRunContextBuilder:
-    """Builder for converting Query to SDK v1 AgentRunContext.
+    """Builder for converting Query to AgentRunContext.
 
     Responsibilities:
     - Generate new run_id (UUID, not query id)
@@ -168,7 +168,7 @@ class AgentRunContextBuilder:
         query: pipeline_query.Query,
         descriptor: AgentRunnerDescriptor,
         resources: AgentResources,
-    ) -> AgentRunContextV1:
+    ) -> AgentRunContextPayload:
         """Build AgentRunContext from Query.
 
         Args:
@@ -177,7 +177,7 @@ class AgentRunContextBuilder:
             resources: Built resources from AgentResourceBuilder
 
         Returns:
-            AgentRunContextV1 dict matching PROTOCOL_V1.md
+            AgentRunContext payload for the plugin runner
         """
         # Generate new run_id
         run_id = str(uuid.uuid4())
@@ -242,7 +242,7 @@ class AgentRunContextBuilder:
         }
 
         # Build full context
-        context: AgentRunContextV1 = {
+        context: AgentRunContextPayload = {
             'run_id': run_id,
             'trigger': trigger,
             'conversation': conversation,

src/langbot/pkg/agent/runner/orchestrator.py

@@ -10,7 +10,7 @@ from langbot_plugin.api.entities.builtin.pipeline import query as pipeline_query
 from ...core import app
 from .descriptor import AgentRunnerDescriptor
 from .registry import AgentRunnerRegistry
-from .context_builder import AgentRunContextBuilder, AgentRunContextV1
+from .context_builder import AgentRunContextBuilder, AgentRunContextPayload
 from .resource_builder import AgentResourceBuilder
 from .result_normalizer import AgentResultNormalizer
 from .state_store import get_state_store, RunnerScopedStateStore
@@ -133,7 +133,7 @@ class AgentRunOrchestrator:
     async def _invoke_runner(
         self,
         descriptor: AgentRunnerDescriptor,
-        context: AgentRunContextV1,
+        context: AgentRunContextPayload,
     ) -> typing.AsyncGenerator[dict[str, typing.Any], None]:
         """Invoke runner via plugin connector.
 

src/langbot/pkg/agent/runner/resource_builder.py

@@ -31,7 +31,7 @@ class AgentResourceBuilder:
     Note: This only builds the resource declaration. The actual proxy actions
     in handler.py must still validate against ctx.resources at runtime.
 
-    Resource field names match SDK v1 Protocol:
+    Resource field names match the plugin SDK payload:
     - ModelResource: model_id, model_type, provider
     - ToolResource: tool_name, tool_type, description
     - KnowledgeBaseResource: kb_id, kb_name, kb_type
@@ -93,7 +93,7 @@ class AgentResourceBuilder:
         descriptor: AgentRunnerDescriptor,
         query: typing.Any,
     ) -> list[ModelResource]:
-        """Build models list with SDK v1 field names."""
+        """Build models list with plugin SDK field names."""
         models: list[ModelResource] = []
         seen_model_ids: set[str] = set()
 
@@ -212,7 +212,7 @@ class AgentResourceBuilder:
         bound_mcp_servers: list[str] | None,
         query: typing.Any,
     ) -> list[ToolResource]:
-        """Build tools list with SDK v1 field names."""
+        """Build tools list with plugin SDK field names."""
         tools: list[ToolResource] = []
 
         # Check manifest permission
@@ -223,7 +223,7 @@ class AgentResourceBuilder:
         # Get tools from query (preproc already resolved this for local-agent)
         use_funcs = getattr(query, 'use_funcs', [])
         for tool in use_funcs:
-            # Use SDK v1 field names: tool_name, tool_type, description
+            # Use plugin SDK field names: tool_name, tool_type, description
             tools.append({
                 'tool_name': tool.name,
                 'tool_type': None,  # Tool type not available in current LLMTool
@@ -238,7 +238,7 @@ class AgentResourceBuilder:
         runner_config: dict[str, typing.Any],
         query: typing.Any,
     ) -> list[KnowledgeBaseResource]:
-        """Build knowledge bases list with SDK v1 field names."""
+        """Build knowledge bases list with plugin SDK field names."""
         kb_resources: list[KnowledgeBaseResource] = []
 
         # Check manifest permission
@@ -263,7 +263,7 @@ class AgentResourceBuilder:
             try:
                 kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
                 if kb:
-                    # Use SDK v1 field names: kb_id, kb_name, kb_type
+                    # Use plugin SDK field names: kb_id, kb_name, kb_type
                     kb_resources.append({
                         'kb_id': kb_uuid,
                         'kb_name': kb.get_name(),
@@ -278,7 +278,7 @@ class AgentResourceBuilder:
         self,
         manifest_perms: dict[str, list[str]],
     ) -> StorageResource:
-        """Build storage permissions with SDK v1 field names."""
+        """Build storage permissions with plugin SDK field names."""
         storage_perms = manifest_perms.get('storage', [])
         return {
             'plugin_storage': 'plugin' in storage_perms,

src/langbot/pkg/agent/runner/result_normalizer.py

@@ -1,4 +1,4 @@
-"""Agent result normalizer for converting SDK v1 AgentRunResult to Pipeline messages."""
+"""Agent result normalizer for converting AgentRunResult to Pipeline messages."""
 from __future__ import annotations
 
 import typing
@@ -15,10 +15,10 @@ MAX_RESULT_SIZE_BYTES = 1024 * 1024  # 1 MB
 
 
 class AgentResultNormalizer:
-    """Normalizer for converting SDK v1 AgentRunResult to Pipeline messages.
+    """Normalizer for converting AgentRunResult to Pipeline messages.
 
     Responsibilities:
-    - Accept only SDK v1 result types (message.delta, message.completed, etc.)
+    - Accept only supported result types (message.delta, message.completed, etc.)
     - Map message.delta -> MessageChunk
     - Map message.completed -> Message
     - Map run.completed (with message) -> Message
@@ -27,7 +27,7 @@ class AgentResultNormalizer:
     - Validate result size
     - Validate message schema
 
-    Per PROTOCOL_V1.md, accepted types:
+    Accepted result types:
     - message.delta
     - message.completed
     - tool.call.started
@@ -144,10 +144,10 @@ class AgentResultNormalizer:
             return None
 
         else:
-            # Unknown type - warn and ignore (SDK v1 only)
+            # Unknown type - warn and ignore.
             self.ap.logger.warning(
                 f'Runner {descriptor.id} returned unknown result type: {result_type}. '
-                f'Expected SDK v1 types (message.delta, message.completed, run.completed, run.failed, etc.)'
+                f'Expected supported types (message.delta, message.completed, run.completed, run.failed, etc.)'
             )
             return None
 

src/langbot/pkg/agent/runner/state_store.py

@@ -9,7 +9,7 @@ from langbot_plugin.api.entities.builtin.pipeline import query as pipeline_query
 from .descriptor import AgentRunnerDescriptor
 
 
-# Valid state scopes per PROTOCOL_V1.md
+# Valid state scopes for agent runner state updates.
 VALID_STATE_SCOPES = ('conversation', 'actor', 'subject', 'runner')
 
 # Key mapping for backward compatibility
@@ -25,7 +25,7 @@ class RunnerScopedStateStore:
 
     Key Design Principles:
     1. Host-owned: State is owned and managed by LangBot host, not by the plugin.
-       The plugin can only read/write through the SDK v1 protocol state API.
+       The plugin can only read/write through agent runner state updates.
     2. Scope keys based on stable host identity: Uses host-controlled identifiers
        (runner_id, bot_uuid, pipeline_uuid, launcher_type, launcher_id) rather
        than external/unstable identifiers like external conversation id.

src/langbot/pkg/plugin/connector.py

@@ -820,10 +820,10 @@ class PluginRuntimeConnector(ManagedRuntimeConnector):
             context: AgentRunContext as dict
 
         Yields:
-            AgentRunResult dicts per Protocol v1
+            AgentRunResult dicts
         """
         if not self.is_enable_plugin:
-            # Return v1 protocol run.failed
+            # Return a protocol-level failure result.
             yield {
                 'type': 'run.failed',
                 'data': {

src/langbot/pkg/plugin/handler.py

@@ -1432,7 +1432,7 @@ class RuntimeConnectionHandler(handler.Handler):
     ) -> typing.AsyncGenerator[dict[str, Any], None]:
         """Run an AgentRunner component.
 
-        Yields AgentRunResult dicts per Protocol v1.
+        Yields AgentRunResult dicts.
         """
         gen = self.call_action_generator(
             LangBotToRuntimeAction.RUN_AGENT,

tests/unit_tests/agent/test_context_builder_params_state.py

@@ -330,7 +330,7 @@ class TestBuildState:
 
     @pytest.mark.asyncio
     async def test_context_has_state_field(self):
-        """AgentRunContextV1 should have state field."""
+        """AgentRunContext should have state field."""
         reset_state_store()
         ap = FakeApplication()
         builder = AgentRunContextBuilder(ap)
@@ -394,7 +394,7 @@ class TestBuildParamsInContext:
 
     @pytest.mark.asyncio
     async def test_context_has_params_field(self):
-        """AgentRunContextV1 should have params field."""
+        """AgentRunContext should have params field."""
         reset_state_store()
         ap = FakeApplication()
         builder = AgentRunContextBuilder(ap)