Phase 4: UI — Agent selector, conversation history, chat persistence
Add sidebar layout with agent selector (Radio), conversation history (gr.render), and BrowserState for localStorage session persistence. Conversations tagged by agent_name for per-agent history filtering. Sidebar auto-closes on mobile viewports via JS. 11 new tests (135 total). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>cora-start
parent
c311ae5909
commit
0f2274e6f1
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@ -131,7 +131,7 @@ def main():
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log.warning("Scheduler not available: %s", e)
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log.info("Launching Gradio UI on %s:%s...", config.host, config.port)
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app = create_ui(default_agent, config, default_llm, notification_bus=notification_bus)
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app = create_ui(registry, config, default_llm, notification_bus=notification_bus)
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app.launch(
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server_name=config.host,
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server_port=config.port,
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@ -95,14 +95,19 @@ class Agent:
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def ensure_conversation(self) -> str:
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if not self.conv_id:
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self.conv_id = uuid.uuid4().hex[:12]
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self.db.create_conversation(self.conv_id)
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self.db.create_conversation(self.conv_id, agent_name=self.name)
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return self.conv_id
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def new_conversation(self) -> str:
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self.conv_id = uuid.uuid4().hex[:12]
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self.db.create_conversation(self.conv_id)
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self.db.create_conversation(self.conv_id, agent_name=self.name)
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return self.conv_id
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def load_conversation(self, conv_id: str) -> list[dict]:
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"""Load an existing conversation by ID. Returns message list."""
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self.conv_id = conv_id
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return self.db.get_messages(conv_id)
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def respond(self, user_input: str, files: list | None = None) -> Generator[str, None, None]:
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"""Process user input and yield streaming response text."""
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conv_id = self.ensure_conversation()
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@ -2,6 +2,7 @@
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from __future__ import annotations
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import contextlib
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import json
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import sqlite3
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import threading
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@ -72,22 +73,40 @@ class Database:
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created_at TEXT NOT NULL
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);
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""")
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# Migration: add agent_name column to conversations (idempotent)
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with contextlib.suppress(sqlite3.OperationalError):
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self._conn.execute(
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"ALTER TABLE conversations ADD COLUMN agent_name TEXT DEFAULT 'default'"
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)
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self._conn.commit()
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# -- Conversations --
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def create_conversation(self, conv_id: str, title: str = "New Chat") -> str:
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def create_conversation(
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self, conv_id: str, title: str = "New Chat", agent_name: str = "default"
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) -> str:
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now = _now()
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self._conn.execute(
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"INSERT INTO conversations (id, title, created_at, updated_at) VALUES (?, ?, ?, ?)",
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(conv_id, title, now, now),
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"INSERT INTO conversations (id, title, created_at, updated_at, agent_name)"
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" VALUES (?, ?, ?, ?, ?)",
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(conv_id, title, now, now, agent_name),
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)
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self._conn.commit()
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return conv_id
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def list_conversations(self, limit: int = 50) -> list[dict]:
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def list_conversations(
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self, limit: int = 50, agent_name: str | None = None
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) -> list[dict]:
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if agent_name:
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rows = self._conn.execute(
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"SELECT id, title, updated_at FROM conversations ORDER BY updated_at DESC LIMIT ?",
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"SELECT id, title, updated_at, agent_name FROM conversations"
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" WHERE agent_name = ? ORDER BY updated_at DESC LIMIT ?",
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(agent_name, limit),
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).fetchall()
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else:
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rows = self._conn.execute(
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"SELECT id, title, updated_at, agent_name FROM conversations"
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" ORDER BY updated_at DESC LIMIT ?",
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(limit,),
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).fetchall()
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return [dict(r) for r in rows]
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250
cheddahbot/ui.py
250
cheddahbot/ui.py
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@ -9,14 +9,32 @@ from typing import TYPE_CHECKING
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import gradio as gr
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if TYPE_CHECKING:
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from .agent import Agent
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from .agent_registry import AgentRegistry
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from .config import Config
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from .llm import LLMAdapter
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from .notifications import NotificationBus
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log = logging.getLogger(__name__)
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_HEAD = '<meta name="viewport" content="width=device-width, initial-scale=1">'
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_HEAD = """
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<script>
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// Auto-close sidebar on mobile so users land on the chat
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(function() {
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if (window.innerWidth > 768) return;
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var attempts = 0;
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var timer = setInterval(function() {
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// Gradio sidebar toggle is the button inside the sidebar's nav/header area
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var sidebar = document.querySelector('[class*="sidebar"]');
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if (sidebar) {
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var btn = sidebar.querySelector('button');
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if (btn) { btn.click(); clearInterval(timer); return; }
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}
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if (++attempts > 40) clearInterval(timer);
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}, 150);
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})();
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</script>
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"""
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_CSS = """
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footer { display: none !important; }
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@ -29,6 +47,34 @@ footer { display: none !important; }
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font-size: 0.9em;
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}
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/* Sidebar conversation buttons */
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.conv-btn {
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text-align: left !important;
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overflow: hidden;
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text-overflow: ellipsis;
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white-space: nowrap;
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padding: 8px 12px !important;
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margin: 2px 0 !important;
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font-size: 0.85em !important;
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min-height: 44px !important;
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width: 100% !important;
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}
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.conv-btn.active {
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border-color: var(--color-accent) !important;
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background: var(--color-accent-soft) !important;
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}
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/* Agent radio: larger touch targets */
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.agent-radio .wrap {
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gap: 4px !important;
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}
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.agent-radio .wrap label {
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min-height: 44px !important;
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padding: 8px 12px !important;
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display: flex;
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align-items: center;
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}
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/* Mobile optimizations */
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@media (max-width: 768px) {
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.gradio-container { padding: 4px !important; }
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@ -40,7 +86,7 @@ footer { display: none !important; }
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.chatbot {
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overflow-y: auto !important;
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-webkit-overflow-scrolling: touch;
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height: calc(100dvh - 220px) !important;
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height: calc(100dvh - 200px) !important;
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max-height: none !important;
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}
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@ -69,12 +115,29 @@ footer { display: none !important; }
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/* Reduce model dropdown row padding */
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.contain .gr-row { gap: 4px !important; }
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/* Prevent horizontal overflow on narrow viewports */
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.gradio-container { overflow-x: hidden !important; max-width: 100vw !important; }
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}
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"""
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def _messages_to_chatbot(messages: list[dict]) -> list[dict]:
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"""Convert DB messages to Gradio chatbot format, skipping tool messages."""
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chatbot_msgs = []
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for msg in messages:
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role = msg.get("role", "")
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content = msg.get("content", "")
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if role in ("user", "assistant") and content:
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chatbot_msgs.append({"role": role, "content": content})
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return chatbot_msgs
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def create_ui(
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agent: Agent, config: Config, llm: LLMAdapter, notification_bus: NotificationBus | None = None
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registry: AgentRegistry,
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config: Config,
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llm: LLMAdapter,
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notification_bus: NotificationBus | None = None,
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) -> gr.Blocks:
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"""Build and return the Gradio app."""
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@ -85,7 +148,63 @@ def create_ui(
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exec_status = "available" if llm.is_execution_brain_available() else "unavailable"
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clickup_status = "enabled" if config.clickup.enabled else "disabled"
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# Build agent name → display_name mapping
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agent_names = registry.list_agents()
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agent_display_map = {} # display_name → internal name
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agent_choices = [] # (display_name, internal_name) for Radio
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for name in agent_names:
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agent = registry.get(name)
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display = agent.agent_config.display_name if agent else name
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agent_display_map[display] = name
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agent_choices.append((display, name))
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default_agent_name = registry.default_name
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with gr.Blocks(title="CheddahBot", fill_width=True, css=_CSS, head=_HEAD) as app:
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# -- State --
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active_agent_name = gr.State(default_agent_name)
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conv_list_state = gr.State([]) # list of {id, title, updated_at}
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browser_state = gr.BrowserState(
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{"agent_name": default_agent_name, "conv_id": None},
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storage_key="cheddahbot_session",
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)
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# -- Sidebar --
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with gr.Sidebar(label="CheddahBot", open=True, width=280):
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gr.Markdown("### Agents")
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agent_selector = gr.Radio(
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choices=agent_choices,
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value=default_agent_name,
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label="Active Agent",
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interactive=True,
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elem_classes=["agent-radio"],
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)
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gr.Markdown("---")
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new_chat_btn = gr.Button("+ New Chat", variant="secondary", size="sm")
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gr.Markdown("### History")
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@gr.render(inputs=[conv_list_state])
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def render_conv_list(convs):
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if not convs:
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gr.Markdown("*No conversations yet*")
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return
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for conv in convs:
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btn = gr.Button(
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conv["title"] or "New Chat",
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elem_classes=["conv-btn"],
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variant="secondary",
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size="sm",
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key=f"conv-{conv['id']}",
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)
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btn.click(
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on_load_conversation,
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inputs=[gr.State(conv["id"]), active_agent_name],
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outputs=[chatbot, conv_list_state, browser_state],
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)
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# -- Main area --
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gr.Markdown("# CheddahBot", elem_classes=["contain"])
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gr.Markdown(
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f"*Chat Brain:* `{current_model}` | "
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@ -111,7 +230,6 @@ def create_ui(
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scale=3,
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)
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refresh_btn = gr.Button("Refresh", scale=0, min_width=70)
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new_chat_btn = gr.Button("New Chat", scale=1, variant="secondary")
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chatbot = gr.Chatbot(
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label="Chat",
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@ -134,22 +252,61 @@ def create_ui(
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sources=["upload", "microphone"],
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)
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# -- Helper functions --
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def _get_agent(agent_name: str):
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"""Get agent by name, falling back to default."""
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return registry.get(agent_name) or registry.default
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def _refresh_conv_list(agent_name: str) -> list[dict]:
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"""Load conversation list for the given agent."""
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agent = _get_agent(agent_name)
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if not agent:
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return []
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return agent.db.list_conversations(limit=50, agent_name=agent_name)
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# -- Event handlers --
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def on_model_change(model_id):
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llm.switch_model(model_id)
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return f"Switched to {model_id}"
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def on_refresh_models():
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models = llm.list_chat_models()
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choices = [(m.name, m.id) for m in models]
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return gr.update(choices=choices, value=llm.current_model)
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def on_new_chat():
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def on_agent_switch(agent_name, browser):
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"""Switch to a different agent: clear chat, refresh history."""
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agent = _get_agent(agent_name)
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if agent:
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agent.new_conversation()
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return []
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convs = _refresh_conv_list(agent_name)
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browser = dict(browser) if browser else {}
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browser["agent_name"] = agent_name
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browser["conv_id"] = agent.conv_id if agent else None
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return agent_name, [], convs, browser
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def on_user_message(message, chat_history):
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def on_new_chat(agent_name, browser):
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"""Create a new conversation on the active agent."""
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agent = _get_agent(agent_name)
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if agent:
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agent.new_conversation()
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convs = _refresh_conv_list(agent_name)
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browser = dict(browser) if browser else {}
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browser["conv_id"] = agent.conv_id if agent else None
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return [], convs, browser
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def on_load_conversation(conv_id, agent_name):
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"""Load an existing conversation into the chatbot."""
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agent = _get_agent(agent_name)
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if not agent:
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return [], [], {"agent_name": agent_name, "conv_id": None}
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messages = agent.load_conversation(conv_id)
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chatbot_msgs = _messages_to_chatbot(messages)
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convs = _refresh_conv_list(agent_name)
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return chatbot_msgs, convs, {"agent_name": agent_name, "conv_id": conv_id}
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def on_user_message(message, chat_history, agent_name):
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chat_history = chat_history or []
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# Extract text and files from MultimodalTextbox
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@ -161,7 +318,7 @@ def create_ui(
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files = []
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if not text and not files:
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yield chat_history, gr.update(value=None)
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yield chat_history, gr.update(value=None), gr.update()
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return
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# Handle audio files - transcribe them
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@ -197,9 +354,10 @@ def create_ui(
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user_display += f"\n[Attached: {', '.join(file_names)}]"
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chat_history = [*chat_history, {"role": "user", "content": user_display}]
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yield chat_history, gr.update(value=None)
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yield chat_history, gr.update(value=None), gr.update()
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# Stream assistant response
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agent = _get_agent(agent_name)
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try:
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response_text = ""
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chat_history = [*chat_history, {"role": "assistant", "content": ""}]
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@ -207,7 +365,7 @@ def create_ui(
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for chunk in agent.respond(text, files=processed_files):
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response_text += chunk
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chat_history[-1] = {"role": "assistant", "content": response_text}
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yield chat_history, gr.update(value=None)
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yield chat_history, gr.update(value=None), gr.update()
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# If no response came through, show a fallback
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if not response_text:
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@ -215,14 +373,48 @@ def create_ui(
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"role": "assistant",
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"content": "(No response received from model)",
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}
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yield chat_history, gr.update(value=None)
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yield chat_history, gr.update(value=None), gr.update()
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except Exception as e:
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log.error("Error in agent.respond: %s", e, exc_info=True)
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chat_history = [*chat_history, {"role": "assistant", "content": f"Error: {e}"}]
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yield chat_history, gr.update(value=None)
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chat_history = [
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*chat_history,
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{"role": "assistant", "content": f"Error: {e}"},
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]
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yield chat_history, gr.update(value=None), gr.update()
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def poll_pipeline_status():
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# Refresh conversation list after message (title/updated_at may have changed)
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convs = _refresh_conv_list(agent_name)
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yield chat_history, gr.update(value=None), convs
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def on_app_load(browser):
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"""Restore session from browser localStorage on page load."""
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browser = browser or {}
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agent_name = browser.get("agent_name", default_agent_name)
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conv_id = browser.get("conv_id")
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# Validate agent exists
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agent = registry.get(agent_name)
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if not agent:
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agent_name = default_agent_name
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agent = registry.default
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chatbot_msgs = []
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if conv_id and agent:
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messages = agent.load_conversation(conv_id)
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chatbot_msgs = _messages_to_chatbot(messages)
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elif agent:
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agent.ensure_conversation()
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conv_id = agent.conv_id
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convs = _refresh_conv_list(agent_name)
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new_browser = {"agent_name": agent_name, "conv_id": conv_id}
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return agent_name, agent_name, chatbot_msgs, convs, new_browser
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def poll_pipeline_status(agent_name):
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"""Poll the DB for pipeline progress updates."""
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agent = _get_agent(agent_name)
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if not agent:
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return gr.update(value="", visible=False)
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status = agent.db.kv_get("pipeline:status")
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if status:
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return gr.update(value=f"⏳ {status}", visible=True)
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@ -248,17 +440,35 @@ def create_ui(
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model_dropdown.change(on_model_change, [model_dropdown], None)
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refresh_btn.click(on_refresh_models, None, [model_dropdown])
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new_chat_btn.click(on_new_chat, None, [chatbot])
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agent_selector.change(
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on_agent_switch,
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[agent_selector, browser_state],
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[active_agent_name, chatbot, conv_list_state, browser_state],
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)
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new_chat_btn.click(
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on_new_chat,
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[active_agent_name, browser_state],
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[chatbot, conv_list_state, browser_state],
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)
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msg_input.submit(
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on_user_message,
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[msg_input, chatbot],
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[chatbot, msg_input],
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[msg_input, chatbot, active_agent_name],
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[chatbot, msg_input, conv_list_state],
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)
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# Restore session on page load
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app.load(
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on_app_load,
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inputs=[browser_state],
|
||||
outputs=[active_agent_name, agent_selector, chatbot, conv_list_state, browser_state],
|
||||
)
|
||||
|
||||
# Pipeline status polling timer (every 3 seconds)
|
||||
status_timer = gr.Timer(3)
|
||||
status_timer.tick(poll_pipeline_status, None, [pipeline_status])
|
||||
status_timer.tick(poll_pipeline_status, [active_agent_name], [pipeline_status])
|
||||
|
||||
# Notification polling timer (every 10 seconds)
|
||||
if notification_bus:
|
||||
|
|
|
|||
|
|
@ -1,9 +1,63 @@
|
|||
"""Tests for the Database kv_scan and notifications methods."""
|
||||
"""Tests for the Database kv_scan, notifications, and conversations methods."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
|
||||
from cheddahbot.db import Database
|
||||
|
||||
|
||||
class TestConversationsAgentName:
|
||||
"""Conversations are tagged by agent_name for per-agent history filtering."""
|
||||
|
||||
def test_create_with_default_agent_name(self, tmp_db):
|
||||
tmp_db.create_conversation("conv1")
|
||||
convs = tmp_db.list_conversations()
|
||||
assert len(convs) == 1
|
||||
assert convs[0]["agent_name"] == "default"
|
||||
|
||||
def test_create_with_custom_agent_name(self, tmp_db):
|
||||
tmp_db.create_conversation("conv1", agent_name="writer")
|
||||
convs = tmp_db.list_conversations()
|
||||
assert convs[0]["agent_name"] == "writer"
|
||||
|
||||
def test_list_filters_by_agent_name(self, tmp_db):
|
||||
tmp_db.create_conversation("c1", agent_name="default")
|
||||
tmp_db.create_conversation("c2", agent_name="writer")
|
||||
tmp_db.create_conversation("c3", agent_name="default")
|
||||
|
||||
default_convs = tmp_db.list_conversations(agent_name="default")
|
||||
writer_convs = tmp_db.list_conversations(agent_name="writer")
|
||||
all_convs = tmp_db.list_conversations()
|
||||
|
||||
assert len(default_convs) == 2
|
||||
assert len(writer_convs) == 1
|
||||
assert len(all_convs) == 3
|
||||
|
||||
def test_list_without_filter_returns_all(self, tmp_db):
|
||||
tmp_db.create_conversation("c1", agent_name="a")
|
||||
tmp_db.create_conversation("c2", agent_name="b")
|
||||
|
||||
convs = tmp_db.list_conversations()
|
||||
assert len(convs) == 2
|
||||
|
||||
def test_list_returns_agent_name_in_results(self, tmp_db):
|
||||
tmp_db.create_conversation("c1", agent_name="researcher")
|
||||
convs = tmp_db.list_conversations()
|
||||
assert "agent_name" in convs[0]
|
||||
assert convs[0]["agent_name"] == "researcher"
|
||||
|
||||
def test_migration_idempotency(self, tmp_path):
|
||||
"""Running _init_schema twice doesn't error (ALTER TABLE is skipped)."""
|
||||
db_path = tmp_path / "test_migrate.db"
|
||||
db1 = Database(db_path)
|
||||
db1.create_conversation("c1", agent_name="ops")
|
||||
# Re-init on same DB file triggers migration again
|
||||
db2 = Database(db_path)
|
||||
convs = db2.list_conversations()
|
||||
assert len(convs) == 1
|
||||
assert convs[0]["agent_name"] == "ops"
|
||||
|
||||
|
||||
class TestKvScan:
|
||||
"""kv_scan is used to find all tracked ClickUp task states efficiently.
|
||||
|
|
|
|||
|
|
@ -0,0 +1,53 @@
|
|||
"""Tests for UI helper functions."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from cheddahbot.ui import _messages_to_chatbot
|
||||
|
||||
|
||||
class TestMessagesToChatbot:
|
||||
"""_messages_to_chatbot converts DB messages to Gradio chatbot format."""
|
||||
|
||||
def test_converts_user_and_assistant(self):
|
||||
messages = [
|
||||
{"role": "user", "content": "Hello"},
|
||||
{"role": "assistant", "content": "Hi there"},
|
||||
]
|
||||
result = _messages_to_chatbot(messages)
|
||||
assert result == [
|
||||
{"role": "user", "content": "Hello"},
|
||||
{"role": "assistant", "content": "Hi there"},
|
||||
]
|
||||
|
||||
def test_skips_tool_messages(self):
|
||||
messages = [
|
||||
{"role": "user", "content": "Search for X"},
|
||||
{"role": "assistant", "content": "Let me search..."},
|
||||
{"role": "tool", "content": '{"results": []}'},
|
||||
{"role": "assistant", "content": "Here are the results."},
|
||||
]
|
||||
result = _messages_to_chatbot(messages)
|
||||
assert len(result) == 3
|
||||
assert all(m["role"] in ("user", "assistant") for m in result)
|
||||
|
||||
def test_skips_empty_content(self):
|
||||
messages = [
|
||||
{"role": "user", "content": "Hi"},
|
||||
{"role": "assistant", "content": ""},
|
||||
{"role": "assistant", "content": "Real response"},
|
||||
]
|
||||
result = _messages_to_chatbot(messages)
|
||||
assert len(result) == 2
|
||||
assert result[1]["content"] == "Real response"
|
||||
|
||||
def test_empty_input(self):
|
||||
assert _messages_to_chatbot([]) == []
|
||||
|
||||
def test_skips_system_messages(self):
|
||||
messages = [
|
||||
{"role": "system", "content": "You are a bot"},
|
||||
{"role": "user", "content": "Hi"},
|
||||
]
|
||||
result = _messages_to_chatbot(messages)
|
||||
assert len(result) == 1
|
||||
assert result[0]["role"] == "user"
|
||||
Loading…
Reference in New Issue