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Update dependencies in pyproject.toml and requirements.txt, and add test_single_q.py for running single and all question tests. Introduce tools.py for Perplexity API integration with enhanced error handling and logging.
Browse files- pyproject.toml +8 -0
- requirements.txt +4 -1
- test_single_q.py +149 -0
- tools.py +68 -0
pyproject.toml
CHANGED
@@ -5,5 +5,13 @@ description = "Add your description here"
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readme = "README.md"
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requires-python = ">=3.12"
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dependencies = [
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"duckduckgo-search>=8.0.2",
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]
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readme = "README.md"
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requires-python = ">=3.12"
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dependencies = [
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"bs4>=0.0.2",
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"dotenv>=0.9.9",
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"duckduckgo-search>=8.0.2",
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"gradio>=5.29.1",
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"markdownify>=1.1.0",
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"openai>=1.75.0",
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"openpyxl>=3.1.5",
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"requests>=2.32.3",
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"smolagents[litellm]>=1.16.1",
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]
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requirements.txt
CHANGED
@@ -1,2 +1,5 @@
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gradio
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-
requests
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gradio
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requests
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openai
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smolagents
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openpyxl
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test_single_q.py
ADDED
@@ -0,0 +1,149 @@
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import json
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import os
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import requests
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import sys # Added for command-line arguments
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from agent import BasicAgent
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# --- Constants ---
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DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
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DOWNLOAD_DIR = "downloaded_task_files" # Directory to save downloaded files
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QUESTIONS_FILE = "data/questions.json"
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# QUESTION_INDEX = 3 # Removed global constant
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def run_single_question_test(question_index: int): # Added question_index parameter
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"""
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Fetches a single question by index, downloads its associated file (if any),
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runs the BasicAgent on it, and prints the answer.
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"""
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# Create download directory if it doesn't exist
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try:
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os.makedirs(DOWNLOAD_DIR, exist_ok=True)
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print(f"Ensured download directory exists: {DOWNLOAD_DIR}")
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except OSError as e:
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print(f"Error creating download directory {DOWNLOAD_DIR}: {e}")
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return
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# 1. Load Questions
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try:
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with open(QUESTIONS_FILE, 'r') as f:
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questions_data = json.load(f)
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if not questions_data or not isinstance(questions_data, list) or len(questions_data) <= question_index:
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print(f"Error: Could not load question at index {question_index} (0-indexed) from {QUESTIONS_FILE}. Total questions: {len(questions_data) if isinstance(questions_data, list) else 'N/A'}")
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return
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item = questions_data[question_index]
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print(f"Loaded question {question_index + 1} (from 1-indexed input): {item.get('question')}")
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except FileNotFoundError:
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print(f"Error: Questions file not found at {QUESTIONS_FILE}")
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return
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except json.JSONDecodeError:
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print(f"Error: Could not decode JSON from {QUESTIONS_FILE}")
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return
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except Exception as e:
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print(f"Error loading or parsing {QUESTIONS_FILE}: {e}")
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return
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# 2. Instantiate Agent
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try:
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agent = BasicAgent()
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print("Agent instantiated successfully.")
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except Exception as e:
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print(f"Error instantiating agent: {e}")
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return
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task_id = item.get("task_id")
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question_text = item.get("question")
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file_name = item.get("file_name")
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local_file_path = None
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if not task_id or question_text is None:
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print(f"Skipping item with missing task_id or question: {item}")
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return
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if file_name:
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download_url = f"{DEFAULT_API_URL}/files/{task_id}"
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local_file_path = os.path.join(DOWNLOAD_DIR, file_name)
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print(f"Attempting to download file for task {task_id} (using task_id in URL): {file_name} from {download_url}")
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try:
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file_response = requests.get(download_url, stream=True, timeout=30)
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file_response.raise_for_status()
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with open(local_file_path, 'wb') as f:
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for chunk in file_response.iter_content(chunk_size=8192):
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f.write(chunk)
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print(f"Successfully downloaded to {local_file_path}")
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except requests.exceptions.RequestException as e:
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print(f"Failed to download {file_name}: {e}")
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local_file_path = None # Ensure agent doesn't get a path to a non-existent/failed file
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except Exception as e:
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print(f"An unexpected error occurred downloading {file_name}: {e}")
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local_file_path = None
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else:
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print("No file associated with this question.")
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# 3. Run Agent on the single question
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try:
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print(f"Running agent on question: {question_text}")
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if local_file_path:
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print(f"Providing file: {local_file_path}")
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submitted_answer = agent(question_text, file_path=local_file_path)
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print(f"\n--- Agent's Answer for Task ID: {task_id} ---")
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print(submitted_answer)
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print("--- End of Answer ---")
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except Exception as e:
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print(f"Error running agent on task {task_id}: {e}")
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def run_all_questions_test():
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"""
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Runs the test for all questions in the QUESTIONS_FILE.
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"""
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print("Attempting to run tests for all questions...")
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try:
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with open(QUESTIONS_FILE, 'r') as f:
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questions_data = json.load(f)
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if not questions_data or not isinstance(questions_data, list):
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print(f"Error: Could not load questions from {QUESTIONS_FILE} or it's not a list.")
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return
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num_questions = len(questions_data)
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if num_questions == 0:
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print(f"No questions found in {QUESTIONS_FILE}.")
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return
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print(f"Found {num_questions} questions to test.")
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for i in range(num_questions):
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print(f"\n--- Running Test for Question {i+1}/{num_questions} ---")
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run_single_question_test(i)
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print(f"--- Finished Test for Question {i+1}/{num_questions} ---\n")
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print("All question tests completed.")
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except FileNotFoundError:
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print(f"Error: Questions file not found at {QUESTIONS_FILE}")
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except json.JSONDecodeError:
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print(f"Error: Could not decode JSON from {QUESTIONS_FILE}")
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except Exception as e:
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print(f"An unexpected error occurred while running all questions: {e}")
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if __name__ == "__main__":
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if len(sys.argv) < 2:
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print("Usage: python test_single_q.py <question_number | 'all'>")
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print("Example (single question): python test_single_q.py 4")
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print("Example (all questions): python test_single_q.py all")
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run_all_questions_test() # Default to running all if no argument is provided
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sys.exit(0)
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argument = sys.argv[1]
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if argument.lower() == "all":
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run_all_questions_test()
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else:
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try:
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question_number_arg = int(argument)
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if question_number_arg <= 0:
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print("Error: Question number must be a positive integer.")
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sys.exit(1)
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# Convert 1-indexed input to 0-indexed for list access
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question_idx_0_based = question_number_arg - 1
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run_single_question_test(question_idx_0_based)
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except ValueError:
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print("Error: Invalid argument. Please enter an integer for a specific question or 'all'.")
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sys.exit(1)
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tools.py
CHANGED
@@ -0,0 +1,68 @@
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from openai import OpenAI
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from smolagents import tool
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import os
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from dotenv import load_dotenv
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load_dotenv()
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PERPLEXITY_API_KEY = os.getenv("PERPLEXITY_API_KEY")
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@tool
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def perplexity_search_tool(query: str) -> str:
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"""
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Performs a web search using the Perplexity API and returns the result.
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Args:
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query: The search query.
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Returns:
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The search result from Perplexity API or an error message.
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"""
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if not PERPLEXITY_API_KEY:
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return "Error: Perplexity API key not set. Please set the PERPLEXITY_API_KEY environment variable."
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messages = [
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{
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"role": "system",
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"content": (
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"You are a helpful assistant"
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),
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},
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{
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"role": "user",
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"content": query,
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},
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]
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try:
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client = OpenAI(api_key=PERPLEXITY_API_KEY, base_url="https://api.perplexity.ai")
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response = client.chat.completions.create(
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model="sonar-pro", # Using sonar-pro as per documentation
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messages=messages,
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)
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# Assuming the main content is in the first choice's message
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if response.choices and len(response.choices) > 0:
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return response.choices[0].message.content
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else:
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return "Error: No response choices received from Perplexity API."
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except Exception as e:
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return f"Error calling Perplexity API: {str(e)}"
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if __name__ == "__main__":
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# Example usage:
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# Make sure to set the PERPLEXITY_API_KEY environment variable before running directly
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if PERPLEXITY_API_KEY:
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search_query = "What are the latest advancements in AI?"
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result = perplexity_search_tool(search_query)
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print(f"Search query: {search_query}")
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print(f"Result:\\n{result}")
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search_query_stars = "How many stars are there in our galaxy?"
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result_stars = perplexity_search_tool(search_query_stars)
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print(f"Search query: {search_query_stars}")
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print(f"Result:\\n{result_stars}")
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else:
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print("Please set the PERPLEXITY_API_KEY environment variable to test the tool.")
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