341 lines
12 KiB
Python
341 lines
12 KiB
Python
# pyright: reportPossiblyUnboundVariable=false
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import asyncio
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import uuid
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from collections.abc import AsyncIterable
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from datetime import datetime
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from pathlib import Path
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from typing import TYPE_CHECKING, Any
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from ag_ui.core import EventType
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from pydantic_ai import (
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Agent,
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AgentStreamEvent,
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FunctionToolCallEvent,
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FunctionToolResultEvent,
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RunContext,
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)
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from pydantic_ai.messages import ModelMessage
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from haiku.rag.agents.chat.agent import create_chat_agent
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from haiku.rag.agents.chat.state import (
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AGUI_STATE_KEY,
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ChatDeps,
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ChatSessionState,
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CitationInfo,
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)
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from haiku.rag.client import HaikuRAG
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from haiku.rag.config import get_config
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if TYPE_CHECKING:
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from textual.app import ComposeResult
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try:
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import logfire
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logfire.configure(send_to_logfire="if-token-present", console=False)
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except ImportError:
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pass
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try:
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import textual_image.widget # noqa: F401 - import early for renderer detection
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from textual.app import App
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from textual.binding import Binding
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from textual.widgets import Footer, Header, Input
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from textual.worker import Worker
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from haiku.rag.chat.widgets.chat_history import ChatHistory, CitationWidget
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TEXTUAL_AVAILABLE = True
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except ImportError:
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TEXTUAL_AVAILABLE = False
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App = object # type: ignore
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class ChatApp(App):
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"""Textual TUI for conversational RAG."""
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TITLE = "haiku.rag Chat"
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CSS = """
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Screen {
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layout: grid;
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grid-size: 1 2;
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grid-rows: 1fr auto;
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background: $surface;
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}
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#chat-history {
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height: 100%;
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}
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Header {
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background: $primary;
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}
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Footer {
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background: $surface-darken-1;
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}
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"""
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BINDINGS = [
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Binding("ctrl+l", "clear_chat", "Clear", show=True),
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Binding("ctrl+g", "show_visual", "Visual", show=True),
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Binding("ctrl+i", "show_info", "Info", show=True),
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Binding("escape", "focus_input", "Focus Input", show=False),
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]
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def __init__(
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self,
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db_path: Path,
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read_only: bool = False,
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before: datetime | None = None,
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background_context: str | None = None,
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) -> None:
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super().__init__()
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self.db_path = db_path
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self.read_only = read_only
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self.before = before
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self.background_context = background_context
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self.client: HaikuRAG | None = None
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self.config = get_config()
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self.agent: Agent[ChatDeps, str] | None = None
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self.session_state: ChatSessionState | None = None
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self._is_processing = False
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self._tool_call_widgets: dict[str, Any] = {}
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self._last_citations: list[CitationInfo] = []
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self._selected_citation_idx: int | None = None
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self._current_worker: Worker[None] | None = None
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self._message_history: list[ModelMessage] = []
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def compose(self) -> "ComposeResult":
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"""Compose the UI layout."""
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yield Header()
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yield ChatHistory(id="chat-history")
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yield Input(placeholder="Ask a question...", id="chat-input")
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yield Footer()
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async def on_mount(self) -> None:
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"""Initialize the app when mounted."""
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self.client = HaikuRAG(
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db_path=self.db_path,
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config=self.config,
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read_only=self.read_only,
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before=self.before,
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)
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await self.client.__aenter__()
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# Create agent and session state
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self.agent = create_chat_agent(self.config)
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self.session_state = ChatSessionState(
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session_id=str(uuid.uuid4()),
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background_context=self.background_context,
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)
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# Focus the input field
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self.query_one(Input).focus()
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async def on_unmount(self) -> None:
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"""Clean up when unmounting."""
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if self.client:
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await self.client.__aexit__(None, None, None)
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async def _handle_stream_event(self, event: AgentStreamEvent) -> None:
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"""Handle streaming events from the agent."""
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chat_history = self.query_one(ChatHistory)
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if isinstance(event, FunctionToolCallEvent):
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tool_name = event.part.tool_name
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tool_call_id = event.part.tool_call_id or str(uuid.uuid4())
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args = event.part.args_as_dict()
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widget = await chat_history.add_tool_call(tool_name, args)
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self._tool_call_widgets[tool_call_id] = widget
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elif isinstance(event, FunctionToolResultEvent):
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tool_call_id = event.tool_call_id
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if tool_call_id and tool_call_id in self._tool_call_widgets:
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widget = self._tool_call_widgets[tool_call_id]
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chat_history.mark_tool_complete(widget)
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# Extract citations from StateSnapshotEvent in tool metadata
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result = getattr(event, "result", None)
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metadata = getattr(result, "metadata", None) if result else None
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if metadata:
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for meta_event in metadata:
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if (
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hasattr(meta_event, "type")
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and meta_event.type == EventType.STATE_SNAPSHOT
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):
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snapshot = getattr(meta_event, "snapshot", {})
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chat_state = snapshot.get(AGUI_STATE_KEY, snapshot)
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self._last_citations = [
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CitationInfo(**c) for c in chat_state["citations"]
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]
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async def _event_stream_handler(
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self,
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_ctx: RunContext[ChatDeps],
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event_stream: AsyncIterable[AgentStreamEvent],
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) -> None:
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"""Handle streaming events from the agent."""
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async for event in event_stream:
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await self._handle_stream_event(event)
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# Yield to event loop to keep UI responsive
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await asyncio.sleep(0)
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async def on_input_submitted(self, event: Input.Submitted) -> None:
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"""Handle user input submission."""
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user_message = event.value.strip()
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if not user_message or self._is_processing:
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return
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if not self.client or not self.agent:
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return
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# Clear the input
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event.input.clear()
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# Add user message to history
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chat_history = self.query_one(ChatHistory)
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await chat_history.add_message("user", user_message)
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# Clear for new query
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self._tool_call_widgets.clear()
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self._last_citations.clear()
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self._selected_citation_idx = None
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# Run agent in a worker to keep UI responsive
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self._is_processing = True
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self.query_one(Input).disabled = True
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self._current_worker = self.run_worker(
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self._run_agent(user_message), exclusive=True
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)
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async def _run_agent(self, user_message: str) -> None:
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"""Run the agent in a background worker."""
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if not self.client or not self.agent:
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return
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chat_history = self.query_one(ChatHistory)
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# Show thinking indicator
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await chat_history.show_thinking()
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try:
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deps = ChatDeps(
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client=self.client,
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config=self.config,
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session_state=self.session_state,
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state_key=AGUI_STATE_KEY,
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)
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async with self.agent.run_stream(
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user_message,
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deps=deps,
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message_history=self._message_history,
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event_stream_handler=self._event_stream_handler,
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) as stream:
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# Hide thinking when we start getting content
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chat_history.hide_thinking()
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# Create assistant message for streaming
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assistant_msg = await chat_history.add_message("assistant", "")
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# Stream text updates
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async for text in stream.stream_text():
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assistant_msg.update_content(text)
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chat_history.scroll_end(animate=False)
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# Yield to event loop to keep UI responsive
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await asyncio.sleep(0)
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# Update message history with this conversation
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self._message_history = stream.all_messages()
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# Add citations captured from tool metadata
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if self._last_citations:
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await chat_history.add_citations(self._last_citations)
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except asyncio.CancelledError:
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chat_history.hide_thinking()
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await chat_history.add_message("assistant", "*Cancelled*")
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except Exception as e:
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chat_history.hide_thinking()
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await chat_history.add_message("assistant", f"Error: {e}")
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finally:
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self._is_processing = False
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self._current_worker = None
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chat_input = self.query_one(Input)
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chat_input.disabled = False
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chat_input.focus()
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async def action_clear_chat(self) -> None:
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"""Clear the chat history and reset session."""
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chat_history = self.query_one(ChatHistory)
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await chat_history.clear_messages()
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self._last_citations.clear()
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self._selected_citation_idx = None
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self._message_history.clear()
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# Reset session state for fresh conversation (preserve background_context)
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self.session_state = ChatSessionState(
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session_id=str(uuid.uuid4()),
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background_context=self.background_context,
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)
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def action_focus_input(self) -> None:
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"""Focus the input field, or cancel if processing."""
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if self._is_processing and self._current_worker:
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self._current_worker.cancel()
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self.query_one(Input).focus()
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def _clear_citation_selection(self) -> None:
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"""Clear citation selection."""
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chat_history = self.query_one(ChatHistory)
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for widget in chat_history.query(CitationWidget):
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widget.remove_class("selected")
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self._selected_citation_idx = None
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def on_descendant_focus(self, _event: object) -> None:
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"""Clear citation selection when input is focused."""
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if isinstance(self.focused, Input):
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self._clear_citation_selection()
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async def action_show_visual(self) -> None:
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"""Show visual grounding for the selected citation."""
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if not self.client or not self._last_citations:
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return
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idx = (
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self._selected_citation_idx
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if self._selected_citation_idx is not None
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else 0
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)
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citation = self._last_citations[idx]
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chunk = await self.client.chunk_repository.get_by_id(citation.chunk_id)
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if not chunk:
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return
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from haiku.rag.inspector.widgets.visual_modal import VisualGroundingModal
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await self.push_screen(VisualGroundingModal(chunk=chunk, client=self.client))
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async def action_show_info(self) -> None:
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"""Show database info modal."""
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if not self.client:
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return
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from haiku.rag.inspector.widgets.info_modal import InfoModal
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await self.push_screen(InfoModal(self.client, self.db_path))
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def on_citation_widget_selected(self, event: CitationWidget.Selected) -> None:
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"""Handle citation selection."""
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chat_history = self.query_one(ChatHistory)
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# Remove selected class from all citations
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for widget in chat_history.query(CitationWidget):
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widget.remove_class("selected")
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# Add selected class to the newly selected citation
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citation_widgets = list(chat_history.query(CitationWidget))
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if 0 <= event.citation_index < len(citation_widgets):
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citation_widgets[event.citation_index].add_class("selected")
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self._selected_citation_idx = event.citation_index
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