muhammadmaazuddin's picture
Score : 45
2b557d7
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],
)