Spaces:
Running
Running
File size: 2,374 Bytes
2ea8556 8157183 2ea8556 8157183 637daef 8157183 637daef 8157183 2ea8556 8157183 637daef 8157183 2ea8556 8157183 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 |
from google.genai import types
from typing import List
from googlesearch import search
from CEO.CEO import GeminiManager
from CEO.tool_loader import ToolLoader
import warnings
# Define the web search tool function.
def web_search(website: str, query: str) -> List[str]:
"""
Searches the specified website for the given query.
The search query is formed by combining the website domain and the query string.
"""
search_query = f"site:{website} {query}"
results = []
for result in search(search_query, num_results=10):
# Filter out irrelevant search pages
if "/search?num=" not in result:
results.append(result)
return results
if __name__ == "__main__":
warnings.filterwarnings("ignore")
# Define the tool metadata for orchestration.
tools = [
{
'type': 'function',
'function': {
'name': 'web_search',
'description': 'Search for results on a specified website using a query string. '
'The CEO model should define which website to search from and the query to use.',
'parameters': {
'type': 'object',
'required': ['website', 'query'],
'properties': {
'website': {'type': 'string', 'description': 'The website domain to search from (e.g., huggingface.co)'},
'query': {'type': 'string', 'description': 'The search query to use on the specified website'},
},
},
},
}
]
# Load the tools using the ToolLoader class.
tool_loader = ToolLoader()
model_manager = GeminiManager(toolsLoader=tool_loader)
# Example prompt instructing the CEO model to create a strategy for Ashton Hall.
# The prompt explicitly mentions that it can use the web_search tool if needed,
# and that it is allowed to choose the website for the search.
task_prompt = (
"Create a strategy for Ashton Hall to improve its online presence."
)
# Request a CEO response with the prompt.
user_prompt_content = types.Content(
role='user',
parts=[types.Part.from_text(text=task_prompt)],
)
response = model_manager.request([user_prompt_content])
print("\nCEO Response:", response)
|