Use llama_index as agent framework

.gitignore

@@ -172,3 +172,5 @@ cython_debug/
 
 # PyPI configuration file
 .pypirc
+
+*.old

agent.py

@@ -1,27 +1,30 @@
-from smolagents import DuckDuckGoSearchTool, CodeAgent, HfApiModel
+from llama_index.core.agent.workflow import AgentWorkflow
+from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
+from llama_index.tools.duckduckgo import DuckDuckGoSearchToolSpec
+from llama_index.core.tools import FunctionTool
+from llama_index.core.workflow import Context
 import os
 import yaml
 
-class BasicAgent:
-    def __init__(self):
-        print("BasicAgent initialized.")
+async def main(query: str, hf_token: str) -> str: 
+    hugging_face_llm = HuggingFaceInferenceAPI(model_name="Qwen/Qwen2.5-Coder-32B-Instruct", token=hf_token)
+    
+    ddg = DuckDuckGoSearchToolSpec()
+    search_tool = FunctionTool.from_defaults(ddg.duckduckgo_full_search)
 
-    def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
-        
-        with open("prompts.yaml", 'r') as stream:
-            prompt_templates = yaml.safe_load(stream)
+    agent = AgentWorkflow.from_tools_or_functions(
+        [search_tool],
+        llm=hugging_face_llm,
+        system_prompt="""
+    You are a general AI assistant. I will ask you a question. 
+    Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. 
+    YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. 
+    If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. 
+    If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. 
+    If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string.
+"""
+    )
 
-        model = HfApiModel(model_id="Qwen/Qwen3-235B-A22B")
-        search_tool = DuckDuckGoSearchTool()
-
-        agent = CodeAgent(
-            tools=[search_tool],
-            model=model,
-            add_base_tools = True,
-            prompt_templates=prompt_templates
-        )
-
-        fixed_answer = agent.run(question)
-        print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
+    ctx = Context(agent)
+    response = await agent.run(query, ctx=ctx)
+    return response

app.py

@@ -3,12 +3,9 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
-from agent import BasicAgent
 from dotenv.main import load_dotenv
-
-load_dotenv()
-
-HF_TOKEN = os.getenv("HF_TOKEN")
+import agent
+import asyncio
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -22,6 +19,11 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     Fetches all questions, runs the BasicAgent on them, submits all answers,
     and displays the results.
     """
+
+    load_dotenv()
+
+    HF_TOKEN = os.getenv("HF_TOKEN")
+
     # --- Determine HF Space Runtime URL and Repo URL ---
     space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
 
@@ -35,13 +37,13 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     api_url = DEFAULT_API_URL
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
-
+    
     # 1. Instantiate Agent ( modify this part to create your agent)
-    try:
-        agent = BasicAgent()
-    except Exception as e:
-        print(f"Error instantiating agent: {e}")
-        return f"Error initializing agent: {e}", None
+    #try:
+    #    agent = BasicAgent()
+    #except Exception as e:
+    #    print(f"Error instantiating agent: {e}")
+    #    return f"Error initializing agent: {e}", None
     # In the case of an app running as a hugging Face space, this link points toward your codebase ( usefull for others so please keep it public)
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
     print(agent_code)
@@ -78,7 +80,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             print(f"Skipping item with missing task_id or question: {item}")
             continue
         try:
-            submitted_answer = agent(question_text)
+            submitted_answer = asyncio.run(agent.main(question_text, HF_TOKEN))
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
         except Exception as e:

requirements.txt

@@ -2,4 +2,8 @@ gradio
 requests
 smolagents
 pyyaml
-dotenv
+dotenv
+llama-index
+llama_index.llms.huggingface_api
+llama_index.tools.duckduckgo
+asyncio