Add more tools to agent

agent.py

@@ -1,20 +1,20 @@
 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
+from llama_index.tools.wikipedia import WikipediaToolSpec
+from llama_index.tools.code_interpreter import CodeInterpreterToolSpec
+from llama_index.llms.gemini import Gemini
 
-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)
+async def main(query: str, api_key: str) -> str: 
+    #hugging_face_llm = HuggingFaceInferenceAPI(model_name="Qwen/Qwen2.5-Coder-32B-Instruct", token=api_key)
+    gemini_llm = Gemini(model="models/gemini-2.0-flash-lite", token=api_key)
+
+    tools = DuckDuckGoSearchToolSpec().to_tool_list()
+    tools += WikipediaToolSpec().to_tool_list()
+    tools += CodeInterpreterToolSpec().to_tool_list()
 
     agent = AgentWorkflow.from_tools_or_functions(
-        [search_tool],
-        llm=hugging_face_llm,
+        tools_or_functions=tools,
+        llm=gemini_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]. 
@@ -25,6 +25,6 @@ async def main(query: str, hf_token: str) -> str:
 """
     )
 
-    ctx = Context(agent)
-    response = await agent.run(query, ctx=ctx)
+    response = await agent.run(query)
+
     return response

app.py

@@ -19,11 +19,10 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     Fetches all questions, runs the BasicAgent on them, submits all answers,
     and displays the results.
     """
-    for name, value in os.environ.items():
-        print("{0}: {1}".format(name, name))
 
     load_dotenv()
-    HF_TOKEN = os.getenv("HF_TOKEN")
+    #HF_TOKEN = os.getenv("HF_TOKEN")
+    API_KEY = os.getenv("GEMINI_API_KEY")
 
     # --- Determine HF Space Runtime URL and Repo URL ---
     space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
@@ -81,7 +80,8 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             print(f"Skipping item with missing task_id or question: {item}")
             continue
         try:
-            submitted_answer = asyncio.run(agent.main(question_text, HF_TOKEN))
+            agent_output = asyncio.run(agent.main(question_text, API_KEY))
+            submitted_answer = str(agent_output)
             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:
@@ -92,12 +92,13 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         print("Agent did not produce any answers to submit.")
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
-    return
     # 4. Prepare Submission 
     submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
     status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
     print(status_update)
 
+    return "Agent finished. Submitting answers...", pd.DataFrame(results_log)
+
     # 5. Submit
     print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
     try:

requirements.txt

@@ -6,4 +6,7 @@ dotenv
 llama-index
 llama_index.llms.huggingface_api
 llama_index.tools.duckduckgo
+llama_index.tools.wikipedia
+llama_index.tools.code_interpreter
+llama-index-llms-gemini
 asyncio