hf tool calling agnt updated with langchain wikipedia tool

app.py

@@ -3,7 +3,8 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
-from agent import codeAgent, toolCallingAgent
+# from agent import codeAgent
+from hf_tool_calling_agent import toolCallingAgent
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -15,8 +16,8 @@ class BasicAgent:
     def __init__(self):
         print("BasicAgent initialized.")
     def __call__(self, question: str) -> str:
-        return codeAgent.run(question)
-        # return toolCallingAgent.run(question)
+        # return codeAgent.run(question)
+        return toolCallingAgent.run(question)
         # print(f"Agent received question (first 50 chars): {question[:50]}...")
         # fixed_answer = "This is a default answer."
         # print(f"Agent returning fixed answer: {fixed_answer}")

agent.py → code_agent.py

@@ -1,4 +1,3 @@
-import os
 from smolagents import (
     HfApiModel,
     CodeAgent,
@@ -61,18 +60,3 @@ codeAgent.logger.console.width = 66
 # )
 # answer = codeAgent.run("search wikipedia for: what the name of the main character of the fast and furious movie")
 # print(answer)
-
-
-# Tool Calling Agent
-llm = HfApiModel("Qwen/Qwen2.5-72B-Instruct", temperature=0.6)
-
-toolCallingAgent = ToolCallingAgent(
-    model=model,
-    tools=tools,
-    max_steps=20,
-)
-
-toolCallingAgent.logger.console.width = 66
-
-# answer = toolCallingAgent.run(question)
-# print(answer)

hf_tool_calling_agent.py

@@ -0,0 +1,59 @@
+from smolagents import (
+    HfApiModel,
+    CodeAgent,
+    load_tool,
+    Tool,
+    InferenceClientModel,
+    ToolCallingAgent,
+    FinalAnswerTool,
+    DuckDuckGoSearchTool,
+    VisitWebpageTool,
+    GoogleSearchTool,
+    PythonInterpreterTool,
+)
+import os
+from huggingface_hub import login
+from dotenv import load_dotenv
+from langchain.agents import load_tools
+
+load_dotenv()
+login(os.environ["HF_API_KEY"])
+from sample_questions import QUESTIONS
+
+
+# Tools
+
+wikipedia = Tool.from_langchain(load_tools(["wikipedia"])[0])
+
+tools = [
+    DuckDuckGoSearchTool(),
+    VisitWebpageTool(),
+    PythonInterpreterTool(),
+    FinalAnswerTool(),
+    wikipedia,
+]
+
+# Model
+# LLM Model
+model = HfApiModel(
+    "Qwen/Qwen2.5-72B-Instruct",
+    provider="together",
+    # max_tokens=40096,
+    temperature=0.1,
+    # token=get_huggingface_token(),
+)
+
+# Tool Calling Agent
+llm = HfApiModel("Qwen/Qwen2.5-72B-Instruct", temperature=0.6)
+
+toolCallingAgent = ToolCallingAgent(
+    model=model,
+    tools=tools,
+    max_steps=20,
+)
+
+toolCallingAgent.logger.console.width = 66
+
+question = QUESTIONS[0]
+answer = toolCallingAgent.run(question)
+print(answer)

requirements.txt

@@ -6,4 +6,5 @@ duckduckgo-search
 markdownify
 pandas
 numpy
-langchain
+langchain
+wikipedia