| |
|
|
| import os |
| from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI |
| from llama_index.core.agent.workflow import AgentWorkflow, ReActAgent |
| from llama_index.tools.duckduckgo import DuckDuckGoSearchToolSpec |
| from llama_index.core.tools import FunctionTool |
|
|
| class BasicAgent: |
| def __init__(self): |
| print("Initializing BasicAgent...") |
|
|
| |
| def add(a: int, b: int) -> int: |
| return a + b |
|
|
| def multiply(a: int, b: int) -> int: |
| return a * b |
|
|
| add_tool = FunctionTool.from_defaults(fn=add) |
| multiply_tool = FunctionTool.from_defaults(fn=multiply) |
|
|
| |
| tool_spec = DuckDuckGoSearchToolSpec() |
| search_tools = tool_spec.to_tool_list() |
|
|
| all_tools = [add_tool, multiply_tool] + search_tools |
|
|
| |
| hf_token = os.getenv("HF_TOKEN") |
| self.llm = HuggingFaceInferenceAPI( |
| model_name="Qwen/Qwen2.5-Coder-32B-Instruct", |
| token=hf_token, |
| ) |
|
|
| |
| self.agent = ReActAgent( |
| name="universal_agent", |
| description="An assistant that can search the web and do math.", |
| system_prompt="You are a helpful assistant with access to tools.", |
| tools=all_tools, |
| llm=self.llm, |
| ) |
|
|
| |
| self.workflow = AgentWorkflow( |
| agents=[self.agent], |
| root_agent="universal_agent", |
| ) |
|
|
| async def __call__(self, question: str) -> str: |
| print(f"[BasicAgent] Received question: {question}") |
| response = await self.workflow.run(user_msg=question) |
| return str(response) |
|
|
