app.py

from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool

from Gradio_UI import GradioUI

#!pip install duckduckgo-search --upgrade

from duckduckgo_search import DDGS

# Custom search tool class
class CustomDuckDuckGoSearchTool:
    def __call__(self, query: str, max_results: int = 5):
        try:
            with DDGS() as ddgs:
                results = []
                for r in ddgs.text(query):
                    results.append(r)
                    if len(results) >= max_results:
                        break
            return results
        except Exception as e:
            return f"Search error: {str(e)}"

# Dummy placeholder for `visit_webpage` tool
class VisitWebpageTool:
    def __call__(self, url: str):
        return f"Pretending to visit: {url}"

# Final answer tool to format and return the final response
class FinalAnswerTool:
    def __call__(self, results):
        formatted_answer = "Final Answer:\n"
        for result in results:
            formatted_answer += f"- {str(result)}\n"
        return formatted_answer

# Dummy model
class DummyModel:
    def call(self, input_text):
        return f"Model processing: {input_text}"

# Modified ToolCallingAgent to use FinalAnswerTool
class ToolCallingAgent:
    def __init__(self, tools, model, final_answer_tool, max_steps=10):
        self.tools = tools
        self.model = model
        self.final_answer_tool = final_answer_tool
        self.max_steps = max_steps

    def run(self, query):
        print(f"Running agent with query: {query}")
        tool_outputs = []
        for tool in self.tools:
            output = tool(query)
            print("Tool output:", output)
            tool_outputs.append(output)
        # Use the final answer tool to format the collected outputs
        final_result = self.final_answer_tool(tool_outputs)
        print(final_result)
        return final_result

# Initialize tools and model
model = DummyModel()
search_tool = CustomDuckDuckGoSearchTool()
visit_webpage = VisitWebpageTool()
final_answer = FinalAnswerTool()

# Initialize the agent
web_agent = ToolCallingAgent(
    tools=[search_tool, visit_webpage],
    model=model,
    final_answer_tool=final_answer,
    max_steps=10
)

# Example usage
web_agent.run("Latest AI tools")


final_answer = FinalAnswerTool()

# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' 

model = HfApiModel(
max_tokens=2096,
temperature=0.5,
model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded
custom_role_conversions=None,
)


# Import tool from Hub
image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)

with open("prompts.yaml", 'r') as stream:
    prompt_templates = yaml.safe_load(stream)
    
agent = CodeAgent(
    model=model,
    tools=[final_answer], ## add your tools here (don't remove final answer)
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)


GradioUI(agent).launch()