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from smolagents import CodeAgent,ToolCallingAgent, PythonInterpreterTool , VisitWebpageTool, DuckDuckGoSearchTool | |
from src.final_assignment_template.models import openrouter_qwenCoder_model, modelLiteLLm | |
from src.final_assignment_template.tools import travily_tool, bm25_query, BM25Tool,extract_filter_textual_info_from_textual_context, summarize_before_final_answer, Video_link_understanding_tool, image_understanding_tool, get_task_file | |
# (Keep Constants as is) | |
# --- Constants --- | |
# retrived_context_qa_agent = ToolCallingAgent( | |
# name="retrived_context_qa_agent", | |
# description=""" | |
# You are a simple QA agent for the retrived web contect. | |
# 1. Pass query and context and avaialbe tools. | |
# 2. If you can answer directly, respond in plain text. | |
# 3. Otherwise, return an explicit action JSON, e.g. | |
# {"action": "use_tool", "tool_name": "...", "input": "..."}. | |
# """, | |
# model=modelLiteLLm, | |
# tools=[], # no extra tools by default | |
# add_base_tools=False, # don’t add PythonInterpreterTool, etc. | |
# verbosity_level=1, | |
# planning_interval=1, | |
# ) | |
# web_agent = CodeAgent( | |
# model=openrouter_qwenCoder_model, | |
# tools=[ | |
# # GoogleSearchTool(provider="serper"), | |
# # DuckDuckGoSearchTool(max_results=10), | |
# travily_tool, | |
# VisitWebpageTool(), | |
# ], | |
# name="web_agent", | |
# description="""Browses the web to find information""", | |
# verbosity_level=1, | |
# planning_interval=1, | |
# max_steps=8, | |
# ) | |
# code_agent = CodeAgent( | |
# model=openrouter_qwenCoder_model, | |
# tools=[ | |
# # GoogleSearchTool(provider="serper"), | |
# # DuckDuckGoSearchTool(max_results=10), | |
# PythonInterpreterTool(additional_authorized_imports=[ | |
# "json", | |
# "markdown", | |
# 'numpy', | |
# 'pandas' | |
# 'math', 'statistics', 're', 'unicodedata', 'random', | |
# 'datetime', 'queue', 'time', 'collections', 'stat', 'itertools', | |
# ]) | |
# ], | |
# name="code_agent", | |
# description="""You can execute python code using this agent""", | |
# verbosity_level=1, | |
# max_steps=3, | |
# ) | |
# - When using the Video_Link_Understanding_Tool and Image_Understanding_Tool, consider their responses and generate an answer based on the textual understanding they provide. | |
# - Video_Link_Understanding_Tool: This tool can only return textual understanding. | |
# - Image_Understanding_Tool: This tool can only return textual understanding. | |
Task_agent = CodeAgent( | |
name="task_Agent", | |
description=""" | |
- You are the Task Agent. | |
- Provide the correct answer | |
- Must call 'summarize_before_final_answer' at the end | |
""", | |
model=modelLiteLLm, | |
add_base_tools=True, | |
tools=[ | |
PythonInterpreterTool(), | |
Video_link_understanding_tool, | |
image_understanding_tool, | |
get_task_file, | |
travily_tool, | |
# DuckDuckGoSearchTool(), | |
# bm25_query, | |
VisitWebpageTool(), | |
extract_filter_textual_info_from_textual_context, | |
# summarize_before_final_answer, | |
], | |
additional_authorized_imports=[ | |
'numpy', | |
'pandas' | |
'math', | |
'datetime', | |
], | |
# managed_agents=[web_agent], | |
planning_interval=1, | |
verbosity_level=1, | |
max_steps=7, | |
# final_answer_checks=[check_reasoning_and_plot], | |
) | |