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Nancy HF Space β Executable Tools Core.
Provides standard server-side tools that can be exposed to AI agents (like Ultron)
and executed locally on the FastAPI backend.
"""
from __future__ import annotations
import logging
import json
from typing import Any, Callable
from core.sessions import session_store
logger = logging.getLogger("nancy.tools")
# βββ Built-in Tools Implementation ββββββββββββββββββββββββββββββββββββββββββ
async def web_search(query: str) -> str:
"""
Search the web for the given query using DuckDuckGo Search.
Args:
query: The search query string.
Returns:
A text summary of top search results.
"""
logger.info("Executing web search: '%s'", query)
try:
from duckduckgo_search import DDGS
with DDGS() as ddgs:
results = list(ddgs.text(query, max_results=5))
if not results:
return "No search results found."
output = []
for i, r in enumerate(results, 1):
title = r.get("title", "No Title")
href = r.get("href", "#")
body = r.get("body", "")
output.append(f"[{i}] {title}\nURL: {href}\nSnippet: {body}\n")
return "\n".join(output)
except Exception as e:
logger.error("Web search failed for query '%s': %s", query, e)
return f"Error executing web search: {str(e)}"
async def nancy_new_chat(provider: str, system_prompt: str | None = None, title: str | None = None) -> str:
"""
Start a brand new conversation session with the specified provider.
Args:
provider: Target chatbot provider (e.g. 'chatgpt', 'gemini', 'deepseek').
system_prompt: Optional initial prompt or instructions to prep in the new chat.
title: Optional custom session title.
Returns:
JSON string indicating new session details.
"""
logger.info("Creating new session for provider '%s'", provider)
try:
session = await session_store.create_session(
provider=provider,
title=title,
system_prompt=system_prompt
)
return json.dumps({
"status": "success",
"message": "New chat session created successfully. To use it, pass the session_id in the 'user' field in future completions.",
"session_id": session.session_id,
"provider": session.provider,
"title": session.title
})
except Exception as e:
logger.error("Failed to create new session: %s", e)
return json.dumps({"status": "error", "message": str(e)})
async def nancy_resume_chat(session_id: str) -> str:
"""
Retrieve details of a saved chat session to resume it.
Args:
session_id: The UUID of the session.
Returns:
JSON string with session details.
"""
logger.info("Resuming session: '%s'", session_id)
try:
session = await session_store.get_session(session_id)
if not session:
return json.dumps({"status": "error", "message": f"Session {session_id} not found."})
return json.dumps({
"status": "success",
"session_id": session.session_id,
"provider": session.provider,
"title": session.title,
"conversation_url": session.conversation_url,
"system_prompt": session.system_prompt,
"message_count": session.message_count,
"status_state": session.status
})
except Exception as e:
logger.error("Failed to resume session '%s': %s", session_id, e)
return json.dumps({"status": "error", "message": str(e)})
async def nancy_list_sessions(provider: str | None = None) -> str:
"""
List all tracked conversation sessions, optionally filtered by provider.
Args:
provider: Optional filter (e.g. 'chatgpt', 'gemini').
Returns:
JSON string with session list.
"""
logger.info("Listing sessions. Filter: %s", provider)
try:
sessions = await session_store.list_sessions(provider=provider)
serialized = [s.to_dict() for s in sessions]
return json.dumps({
"status": "success",
"sessions": serialized
})
except Exception as e:
logger.error("Failed to list sessions: %s", e)
return json.dumps({"status": "error", "message": str(e)})
# βββ Tool Registry & Dispatcher ββββββββββββββββββββββββββββββββββββββββββββββ
class ToolRegistry:
"""Registry mapping tool names to their async handlers and schemas."""
def __init__(self) -> None:
self._handlers: dict[str, Callable[..., Any]] = {}
self._schemas: list[dict[str, Any]] = []
# Register our built-in tools
self.register("web_search", web_search, {
"type": "function",
"function": {
"name": "web_search",
"description": "Search the web for real-time information or questions requiring search.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Search query text."
}
},
"required": ["query"]
}
}
})
self.register("nancy_new_chat", nancy_new_chat, {
"type": "function",
"function": {
"name": "nancy_new_chat",
"description": "Start a brand new conversation session with a chatbot provider.",
"parameters": {
"type": "object",
"properties": {
"provider": {
"type": "string",
"description": "Target provider key, e.g. 'chatgpt', 'gemini', 'deepseek'."
},
"system_prompt": {
"type": "string",
"description": "Optional instructions/rules to prepend to this conversation."
},
"title": {
"type": "string",
"description": "Optional human-readable title."
}
},
"required": ["provider"]
}
}
})
self.register("nancy_resume_chat", nancy_resume_chat, {
"type": "function",
"function": {
"name": "nancy_resume_chat",
"description": "Retrieve information on an existing saved chat session by ID.",
"parameters": {
"type": "object",
"properties": {
"session_id": {
"type": "string",
"description": "The session ID UUID."
}
},
"required": ["session_id"]
}
}
})
self.register("nancy_list_sessions", nancy_list_sessions, {
"type": "function",
"function": {
"name": "nancy_list_sessions",
"description": "List all active saved conversation sessions in Nancy.",
"parameters": {
"type": "object",
"properties": {
"provider": {
"type": "string",
"description": "Optional chatbot provider to filter by."
}
}
}
}
})
def register(self, name: str, handler: Callable[..., Any], schema: dict[str, Any]) -> None:
"""Register a new tool."""
self._handlers[name] = handler
self._schemas.append(schema)
def get_schemas(self) -> list[dict[str, Any]]:
"""Get the schemas of all registered tools."""
return self._schemas
async def execute(self, name: str, arguments: dict[str, Any]) -> str:
"""Execute a tool by name with arguments."""
handler = self._handlers.get(name)
if not handler:
raise ValueError(f"Tool '{name}' is not registered.")
try:
return await handler(**arguments)
except Exception as e:
logger.error("Error executing tool '%s': %s", name, e)
return f"Execution error: {str(e)}"
# Module-level singleton registry
tool_registry = ToolRegistry()
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