Delete agents.py

agents.py

@@ -1,132 +0,0 @@
-#import os
-
-#from langchain.agents import load_tools
-#from openai import OpenAI
-#from openinference.instrumentation.smolagents import SmolagentsInstrumentor
-#from phoenix.otel import register
-#from smolagents import (
-#    CodeAgent,
-#    ToolCallingAgent,
-#    OpenAIServerModel,
-#    Tool,
-#    DuckDuckGoSearchTool,
-#    WikipediaSearchTool
-#)
-#from tools import VisitWebpageTool
-
-###
-from crewai import Agent
-from langchain_openai import ChatOpenAI
-from tools import scrape_tool, search_tool, today_tool
-###
-
-#MODEL_ID_1 = "gpt-4o-mini"
-#MODEL_ID_2 = "gpt-4o"
-#MODEL_ID_3 = "o4-mini"
-
-#PHOENIX_PROJECT_NAME = "gaia"
-
-#os.environ["OTEL_EXPORTER_OTLP_HEADERS"] = "api_key = " + os.environ["PHOENIX_API_KEY"];
-#os.environ["PHOENIX_CLIENT_HEADERS"] = "api_key = " + os.environ["PHOENIX_API_KEY"];
-#os.environ["PHOENIX_COLLECTOR_ENDPOINT"] = "https://app.phoenix.arize.com";
-
-#tracer_provider = register(
-#    auto_instrument = True,
-#    endpoint = "https://app.phoenix.arize.com/v1/traces",
-#    project_name = PHOENIX_PROJECT_NAME
-#)
-
-#SmolagentsInstrumentor().instrument(tracer_provider = tracer_provider)
-
-#def run_gaia(question, file_name):
-    #search_tool = Tool.from_langchain(load_tools(["serpapi"])[0])
-    #wikipedia_tool = Tool.from_langchain(load_tools(["wikipedia"])[0])
-    
-    #web_search_agent = ToolCallingAgent(
-    #    description = "Runs web searches for you. Give it your query as an argument.",
-    #    max_steps = 2,
-    #    model = OpenAIServerModel(model_id = MODEL_ID_1),
-    #    name = "web_search_agent",
-    #    tools = [search_tool, VisitWebpageTool()],
-    #    #tools = [DuckDuckGoSearchTool(), VisitWebpageTool()],
-    #    verbosity_level = 1
-    #)
-    
-    #wikipedia_search_agent = ToolCallingAgent(
-    #    description = "Runs wikipedia searches for you. Give it your query as an argument.",
-    #    max_steps = 2,
-    #    model = OpenAIServerModel(model_id = MODEL_ID_1),
-    #    name = "wikipedia_search_agent",
-    #    tools = [wikipedia_tool],
-    #    #tools = [WikipediaSearchTool()],
-    #    verbosity_level = 1
-    #)
-
-    #manager_agent = CodeAgent(
-    #    #add_base_tools = True,
-    #    #additional_authorized_imports = ["json", "numpy", "pandas", "time"],
-    #    #final_answer_checks = [get_final_answer],
-    #    #managed_agents = [web_search_agent],
-    #    #max_steps = 5,
-    #    model = OpenAIServerModel(model_id = MODEL_ID_2),
-    #    planning_interval=3,
-    #    tools = [DuckDuckGoSearchTool(), VisitWebpageTool(), WikipediaSearchTool()],
-    #    verbosity_level = 1
-    #)
-
-    #return manager_agent.run(question)
-
-    #answer = manager_agent.run(question)
-
-    #return get_final_answer(question, answer)
-    
-#def get_final_answer(question, answer):
-#    prompt_template = """
-#        You are an expert in precise question answering. You are given a question and context. You must **precisely** answer the question based on the context and then stop.
-#        **Question:** """ + str(question) + """
-#        **Context:** """ + str(answer) + """
-#        **Example 1:** What is the capital of France? Paris
-#        **Example 2:** What is the superlative of good? Best
-#        **Example 3:** What is the opposite of left? Right
-#        **Answer:**: 
-#        """
-
-#    client = OpenAI()
-#    completion = client.chat.completions.create(
-#        messages = [{"role": "user", "content": [{"type": "text", "text": prompt_template}]}],
-#        model = MODEL_ID_1
-#    )
-
-#    final_answer = completion.choices[0].message.content
-    
-#    print(f"Question: {question}")
-#    print(f"Answer: {answer}")
-#    print(f"Final answer: {final_answer}")
-    
-#    return final_answer
-
-###
-def get_researcher_agent(model, verbose):
-    return Agent(
-        role="Researcher",
-        goal="Research content on topic: {topic}.",
-        backstory="You're working on researching content on topic: {topic}. "
-                  "Your work is the basis for the Writer to write on this topic.",
-        llm=ChatOpenAI(model=model),
-        tools = [search_tool(), scrape_tool()],
-        allow_delegation=False,
-    	verbose=verbose
-    )
-
-def get_writer_agent(model, verbose):
-    return Agent(
-        role="Writer",
-        goal="Write an article on topic: {topic}.",
-        backstory="You're working on writing an article on topic: {topic}. "
-                  "You base your writing on the work of the Researcher, who provides context on this topic.",
-        llm=ChatOpenAI(model=model),
-        tools = [today_tool()],
-        allow_delegation=False,
-        verbose=verbose
-    )
-###