chore: release api v0.3.4

webber-api/src/domains/agents/task/agent.py

@@ -0,0 +1,174 @@
+"""
+Task Agent implementation using PydanticAI.
+
+Full orchestrator agent that can:
+- Execute multi-step tasks autonomously
+- Use all tools (read + write)
+- Spawn sub-agents (Explore, Plan) for focused work
+"""
+import os
+from collections.abc import AsyncIterator
+from dataclasses import dataclass
+from typing import Any
+
+from pydantic_ai import Agent
+from pydantic_ai.models.openai import OpenAIModel
+
+from src.domains.agents.base import BaseAgent, AgentContext, register_agent
+from src.domains.agents.task.prompts import TASK_SYSTEM_PROMPT
+from src.ollama.provider import get_ollama_provider
+from src.shared.config import get_settings
+from src.shared.logging import logged, get_logger, trace_span
+
+logger = get_logger(__name__)
+
+
+@dataclass
+class TaskContext(AgentContext):
+    """
+    Context for task agent tools.
+
+    Passed to all tool functions via RunContext.
+    Uses the same fields as base AgentContext.
+    """
+    pass
+
+
+class TaskAgentImpl(BaseAgent):
+    """
+    Full orchestrator agent for autonomous task execution.
+
+    Has access to ALL tools:
+    - Read-only: read_file, glob_files, grep_content, bash_readonly
+    - Write: edit_file, write_file, bash
+    - External: web_search
+    - Orchestration: spawn_agent (launch sub-agents)
+
+    Can spawn Explore and Plan agents to offload focused tasks,
+    keeping context efficient across complex multi-step work.
+    """
+
+    name = "task"
+    description = "Autonomous multi-step task execution with sub-agent orchestration"
+
+    def __init__(self):
+        """Initialize the task agent."""
+        self._agent: Agent[TaskContext, str] | None = None
+        self._settings = get_settings()
+
+    def _create_agent(self) -> Agent[TaskContext, str]:
+        """Create the PydanticAI agent with Ollama backend."""
+        # Use sanitized Ollama provider to fix content: null issues
+        model = OpenAIModel(
+            model_name=self._settings.ollama_agent_model,
+            provider=get_ollama_provider(),
+        )
+
+        agent: Agent[TaskContext, str] = Agent(
+            model=model,
+            system_prompt=TASK_SYSTEM_PROMPT,
+            deps_type=TaskContext,
+            output_type=str,
+            # Mistral Nemo settings:
+            # - temperature 0.3 (Nemo needs slightly higher than 0.0)
+            # - tool_choice "required" forces tool use
+            model_settings={
+                "temperature": 0.3,
+                "extra_body": {"tool_choice": "required"},
+            },
+        )
+
+        # Register all tools including orchestration
+        self._register_tools(agent)
+
+        return agent
+
+    def _register_tools(self, agent: Agent[TaskContext, str]) -> None:
+        """Register all tools with the agent."""
+        from src.domains.agents.task.tools import register_task_tools
+        register_task_tools(agent)
+
+    @logged()
+    async def run(
+        self,
+        prompt: str,
+        working_dir: str | None = None,
+        allowed_paths: list[str] | None = None,
+        **kwargs: Any
+    ) -> str:
+        """
+        Run the task agent to execute a multi-step task.
+
+        Args:
+            prompt: Description of the task to execute
+            working_dir: Working directory for the agent
+            allowed_paths: Restrict tool access to these paths
+
+        Returns:
+            Consolidated task summary with results
+        """
+        ctx = TaskContext(
+            working_dir=working_dir or os.getcwd(),
+            allowed_paths=allowed_paths or self._settings.effective_allowed_paths,
+            timeout_seconds=self._settings.tool_timeout_seconds,
+        )
+
+        async with trace_span("task_agent_run"):
+            try:
+                # Use run() not run_stream() - Ollama has bugs with streaming + tools
+                result = await self.agent.run(prompt, deps=ctx)
+                return result.output
+            except Exception as e:
+                logger.exception(f"Task agent error: {e}")
+                raise
+
+    async def run_stream(
+        self,
+        prompt: str,
+        working_dir: str | None = None,
+        allowed_paths: list[str] | None = None,
+        **kwargs: Any
+    ) -> AsyncIterator[str]:
+        """
+        Run the task agent with streaming output.
+
+        Yields text chunks as they become available.
+        """
+        ctx = TaskContext(
+            working_dir=working_dir or os.getcwd(),
+            allowed_paths=allowed_paths or self._settings.effective_allowed_paths,
+            timeout_seconds=self._settings.tool_timeout_seconds,
+        )
+
+        async with trace_span("task_agent_stream"):
+            try:
+                async with self.agent.run_stream(prompt, deps=ctx) as result:
+                    async for chunk in result.stream_text():
+                        yield chunk
+            except Exception as e:
+                logger.exception(f"Task agent stream error: {e}")
+                raise
+
+
+# Create and register the singleton instance
+task_agent = TaskAgentImpl()
+register_agent(task_agent)
+
+
+async def task(
+    prompt: str,
+    working_dir: str | None = None,
+    **kwargs: Any
+) -> str:
+    """Run task execution."""
+    return await task_agent.run(prompt, working_dir=working_dir, **kwargs)
+
+
+async def task_stream(
+    prompt: str,
+    working_dir: str | None = None,
+    **kwargs: Any
+) -> AsyncIterator[str]:
+    """Run task execution with streaming."""
+    async for chunk in task_agent.run_stream(prompt, working_dir=working_dir, **kwargs):
+        yield chunk