Spaces:
Sleeping
Sleeping
tool: get and read tools
Browse files- .gitignore +2 -1
- agent.py +74 -6
- app.py +5 -3
- requirements.txt +2 -1
.gitignore
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.venv
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.idea
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.env
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questions.txt
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.venv
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.idea
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.env
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questions.txt
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/agent_storage/
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agent.py
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from agno.agent import Agent
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from agno.models.openai import OpenAIChat
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from agno.tools.reasoning import ReasoningTools
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from agno.models.google import Gemini
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from agno.models.openrouter import OpenRouter
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test_question = "On June 6, 2023, an article by Carolyn Collins Petersen was published in Universe Today. This article mentions a team that produced a paper about their observations, linked at the bottom of the article. Find this paper. Under what NASA award number was the work performed by R. G. Arendt supported by?"
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model = {
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return "The current date is " + date
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agent = Agent(
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model=model["
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markdown=False,
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debug_mode=True,
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instructions=
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tools=[
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ReasoningTools(think=True, add_few_shot=True),
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DuckDuckGoTools(fixed_max_results=5),
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WikipediaTools()
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],
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context={"current_time": get_current_date},
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add_context=True,
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show_tool_calls=True
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)
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# Print the response in the terminal
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# agent.print_response("Waht is greater 9.9 or 9.11?", strem=True)
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import os
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from textwrap import dedent
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import httpx
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from agno.agent import Agent
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from agno.models.openai import OpenAIChat
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from agno.tools.reasoning import ReasoningTools
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from agno.models.google import Gemini
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from agno.models.openrouter import OpenRouter
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# configurable storage root for downloaded files
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BASE_STORAGE_ROOT = os.getenv("AGENT_STORAGE_ROOT", os.path.join(os.getcwd(), "agent_storage"))
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DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
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test_question = "On June 6, 2023, an article by Carolyn Collins Petersen was published in Universe Today. This article mentions a team that produced a paper about their observations, linked at the bottom of the article. Find this paper. Under what NASA award number was the work performed by R. G. Arendt supported by?"
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model = {
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return "The current date is " + date
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def get_file_from_task_id(task_id: str) -> str:
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"""
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Use this tool to **download** the file linked to a given `task_id`.
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Args:
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task_id (str): Identifier that points to the remote file.
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Returns:
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str: task_id to be used by other tools to read the file
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"""
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# ensure storage directory exists
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task_dir = os.path.join(BASE_STORAGE_ROOT, task_id)
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os.makedirs(task_dir, exist_ok=True)
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# filename derived from task_id
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filename = task_id
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file_path = os.path.join(task_dir, filename)
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# if file already exists, return
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if os.path.exists(file_path):
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print("[INFO] Using cached file:", file_path)
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return file_path
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# fetch content from remote
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response = httpx.get(f"{DEFAULT_API_URL}/files/{task_id}", timeout=15, follow_redirects=True)
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response.raise_for_status()
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# write content to file
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with open(file_path, "wb") as f:
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f.write(response.content)
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return file_path
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def read_file_from_task_id(task_id: str) -> str:
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"""
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Args:
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task_id (str): Identifier that points to the remote file.
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Returns:
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str: Content of the downloaded (or cached) file.
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"""
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# expected local path
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file_path = os.path.join(BASE_STORAGE_ROOT, task_id, task_id)
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with open(file_path, "r", encoding="utf-8") as f:
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print("[INFO] Reading file:", file_path)
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return f.read()
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agent = Agent(
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model=model["grok"],
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markdown=False,
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debug_mode=True,
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instructions=dedent(
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"""
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You are a general AI assistant. I will ask you a question.
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Report your thoughts, but your final answer must be only the answer itself, with nothing else.
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The answer should be a number OR as few words as possible OR a comma separated list of numbers and/or strings.
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If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise.
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If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities),
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and write the digits in plain text unless specified otherwise.
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If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string.
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The questions come in the following format: "<task_id>: <question>", you can use the task_id to retrieve attached files related to the question (only if available).
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"""),
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tools=[
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ReasoningTools(think=True, add_few_shot=True),
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DuckDuckGoTools(fixed_max_results=5),
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WikipediaTools(),
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read_file_from_task_id,
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get_file_from_task_id
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],
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context={"current_time": get_current_date},
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add_context=True,
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show_tool_calls=True
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)
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app.py
CHANGED
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def __init__(self):
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pass
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def __call__(self, question: str) -> str:
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def run_agent(profile: gr.OAuthProfile | None, task_id: str | None = None, submit: bool = True):
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api_url = DEFAULT_API_URL
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questions_url = f"{api_url}/questions"
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submit_url = f"{api_url}/submit"
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try:
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agent_instance = BasicAgent()
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if not tid or qtext is None:
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continue
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try:
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submitted_answer = agent_instance(qtext)
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answers_payload.append({"task_id": tid, "submitted_answer": submitted_answer})
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results_log.append({"Task ID": tid, "Question": qtext, "Submitted Answer": submitted_answer})
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except Exception as e:
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def __init__(self):
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pass
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def __call__(self, task_id: str, question: str) -> str:
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print("[INFO] Answering question: >>>", question)
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return asyncio.run(_async_answer(f"{task_id}: {question}"))
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def run_agent(profile: gr.OAuthProfile | None, task_id: str | None = None, submit: bool = True):
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api_url = DEFAULT_API_URL
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questions_url = f"{api_url}/questions"
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submit_url = f"{api_url}/submit"
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files_url = f"{api_url}/files/{task_id}"
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try:
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agent_instance = BasicAgent()
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if not tid or qtext is None:
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continue
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try:
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submitted_answer = agent_instance(task_id, qtext)
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answers_payload.append({"task_id": tid, "submitted_answer": submitted_answer})
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results_log.append({"Task ID": tid, "Question": qtext, "Submitted Answer": submitted_answer})
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except Exception as e:
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requirements.txt
CHANGED
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@@ -5,4 +5,5 @@ openai
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duckduckgo-search
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wikipedia
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google
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google-genai
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duckduckgo-search
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wikipedia
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google
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google-genai
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httpx
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