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| from serpapi.google_search import GoogleSearch | |
| from dotenv import load_dotenv | |
| import os | |
| from openai import OpenAI | |
| import asyncio | |
| import requests | |
| from agents import enable_verbose_stdout_logging | |
| enable_verbose_stdout_logging() | |
| from agents import ( | |
| Agent, | |
| function_tool, | |
| Runner, | |
| WebSearchTool, | |
| ) | |
| load_dotenv() | |
| SERP_API_KEY = os.getenv("SERP_API_KEY") | |
| openai_client = OpenAI() | |
| def describe_all_images(images_results): | |
| descriptions = [] | |
| for image in images_results: | |
| description = describe_thumbnail(image["thumbnail"]) | |
| descriptions.append({ | |
| "title": image["title"], | |
| "link": image["link"], | |
| "description": description | |
| }) | |
| break | |
| return descriptions | |
| def describe_thumbnail(image_url): | |
| response = openai_client.responses.create( | |
| model="gpt-4.1", | |
| input=[{ | |
| "role": "user", | |
| "content": [ | |
| {"type": "input_text", "text": "what's in this image? To what era/year does it belong?"}, | |
| { | |
| "type": "input_image", | |
| "image_url": image_url, | |
| }, | |
| ], | |
| }], | |
| ) | |
| return response.output_text + "\n" | |
| def search_google(item_to_find: str): | |
| params = { | |
| "engine": "google_images_light", | |
| "q": item_to_find, | |
| "api_key": SERP_API_KEY | |
| } | |
| search = GoogleSearch(params) | |
| raw_results = search.get_dict()["images_results"] | |
| images_results = [ | |
| { | |
| "thumbnail": result["thumbnail"], | |
| "link": result["link"], | |
| "title": result["title"] | |
| } | |
| for result in raw_results | |
| ] | |
| return raw_results | |
| def seach_google_for_images(item_to_find: str) -> list: | |
| """ | |
| Search Google Images for a given item and return a list of image results, with links and descriptions. | |
| Args: | |
| item_to_find (str): The item or query to search for in Google Images. | |
| Returns: | |
| list: A list of dictionaries, each containing the image title, link, and a description generated by the image analysis. | |
| """ | |
| raw_results = search_google(item_to_find) | |
| results_w_description = describe_all_images(raw_results) | |
| return results_w_description | |
| def wikipedia_lookup(query): | |
| """ | |
| Look up a query on Wikipedia and return the summary extract of the most relevant page. | |
| Args: | |
| query (str): The search term to look up on Wikipedia. | |
| Returns: | |
| str: The summary extract of the most relevant Wikipedia page, or a message if no page is found. | |
| """ | |
| # Step 1: Search | |
| search_url = "https://en.wikipedia.org/w/rest.php/v1/search/title" | |
| params = {"q": query, "limit": 1} | |
| search_resp = requests.get(search_url, params=params) | |
| search_resp.raise_for_status() | |
| search_data = search_resp.json() | |
| if not search_data.get("pages"): | |
| return f"No Wikipedia page found for '{query}'" | |
| page_key = search_data["pages"][0]["key"] | |
| # Step 2: Fetch summary | |
| summary_url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{page_key}" | |
| summary_resp = requests.get(summary_url) | |
| summary_resp.raise_for_status() | |
| return summary_resp.json().get("extract") | |
| # if __name__ == "__main__": | |
| # item_to_find = "mediterranean houses in the 16h century" | |
| # results = search_google(item_to_find) | |
| # desc = describe_all_images(results) | |
| # print(desc[0]) | |
| # # print(wikipedia_lookup("United States Constitution")) | |