Update app.py

app.py

@@ -24,29 +24,18 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 load_dotenv()
 
 
-import os
-import io
-import contextlib
-from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
-
-class MistralToolCallingAgentTool:
-    name = "mistral_tool_agent"
-    description = "Uses Mistral-7B-Instruct to answer questions using code or reasoning"
+class ZephyrToolCallingAgentTool:
+    name = "zephyr_tool_agent"
+    description = "Uses Zephyr-7B to answer questions using code or reasoning"
 
     def __init__(self):
-        self.model_id = "mistralai/Mistral-7B-Instruct-v0.3"
-        token = os.getenv("HF_TOKEN")
+        self.model_id = "HuggingFaceH4/zephyr-7b-beta"
+        token = os.getenv("HF_TOKEN")  # Optional unless private
 
-        if token is None:
-            raise EnvironmentError("HF_TOKEN is not set in environment variables.")
-
-        try:
-            self.tokenizer = AutoTokenizer.from_pretrained(self.model_id, token=token)
-            self.model = AutoModelForCausalLM.from_pretrained(
-                self.model_id, device_map="auto", torch_dtype="auto", token=token
-            )
-        except Exception as e:
-            raise RuntimeError(f"Error loading Mistral model: {e}")
+        self.tokenizer = AutoTokenizer.from_pretrained(self.model_id, token=token)
+        self.model = AutoModelForCausalLM.from_pretrained(
+            self.model_id, device_map="auto", torch_dtype="auto", token=token
+        )
 
         self.pipeline = pipeline(
             "text-generation",
@@ -69,6 +58,7 @@ class MistralToolCallingAgentTool:
         prompt = f"""You are a helpful assistant. Use code to solve questions that involve calculations.
 If code is needed, return a block like <tool>code</tool>. End your answer with <final>answer</final>.
 
+
 Question: {question}
 Answer:"""