Update app.py

app.py

@@ -5,7 +5,16 @@ import inspect
 import pandas as pd
 from smolagents import CodeAgent, HfApiModel, DuckDuckGoSearchTool, FinalAnswerTool
 from tools import TextTransformerTool
-from smolagents import InferenceClientModel
+import os
+import yaml
+from tools_agent import ReverseTextTool, TableCommutativityTool, VegetableListTool, ExcelSumFoodTool
+from smolagents import (
+    CodeAgent,
+    OpenAIServerModel,
+    DuckDuckGoSearchTool,
+    FinalAnswerTool,
+    PythonInterpreterTool
+)
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -19,32 +28,48 @@ import os
 from smolagents import HfApiModel
 
 
+# --- Agent Definition ---
 class BasicAgent:
     def __init__(self):
         print("Initializing BasicAgent with tools...")
 
-        # Ensure the token is available
-        hf_token = os.environ.get("HUGGINGFACEHUB_API_TOKEN")
-        if not hf_token:
-            raise ValueError("Missing Hugging Face API token!")
-        openai_token = os.environ.get("OPENAI_API_KEY")
-        # Pass it into the model
-        # model = HfApiModel(model="mistralai/Mistral-7B-Instruct-v0.2") #token=hf_token,
-        model = InferenceClientModel(provider="openai", token=openai_token, model_id="gpt-3.5-turbo")
+        # Load OpenAI token from environment
+        openai_token = os.getenv("OPENAI_API_KEY")
+        if not openai_token:
+            raise ValueError("Missing OpenAI API token!")
+
+        # Initialize model and tools
+        model = OpenAIServerModel(
+            #api_base="openai",
+            api_key=openai_token,
+            model_id="gpt-4.1"
+        )
         search_tool = DuckDuckGoSearchTool()
-        text_tool = TextTransformerTool()
-        final_answer = FinalAnswerTool()
+        final_answer_tool = FinalAnswerTool()
+        reverse_tool = ReverseTextTool()
+        table_tool = TableCommutativityTool()
+        veg_tool = VegetableListTool()
+        python_tool = PythonInterpreterTool()
+        exfood_tool = ExcelSumFoodTool()
+
+        # Load system prompt templates
+        with open("prompts.yaml", "r") as stream:
+            prompt_templates = yaml.safe_load(stream)
+
+        # Build the agent
         self.agent = CodeAgent(
             model=model,
-            tools=[search_tool, text_tool, final_answer],
+            prompt_templates=prompt_templates,
+            tools=[search_tool, reverse_tool, table_tool, veg_tool, python_tool, exfood_tool, final_answer_tool], #final_answer_tool
             add_base_tools=True,
-            planning_interval=2,
-            max_steps=6,
+            planning_interval=None,
+            name = "GoodAgent",
+            max_steps=10,
             verbosity_level=1,
         )
 
     def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
+        print(f"Agent received question (first 50 chars): {question}...")
         answer = self.agent(question)
         print(f"Agent returning answer: {answer}")
         return answer