Update tools.py

tools.py

@@ -1,55 +1,55 @@
-# tools.py
-
-from smolagents import tool
-from retriever import retrieve_context
-
-def clean_answer_with_prompt(agent_output: str) -> str:
-    """
-    Extracts and cleans the final answer from the agent output.
-    For GAIA, ensure no 'FINAL ANSWER:' prefix is returned — just the answer.
-    """
-    if "FINAL ANSWER:" in agent_output:
-        return agent_output.split("FINAL ANSWER:")[-1].strip()
-    return agent_output.strip()
-
-@tool
-def guest_info_tool(name: str) -> str:
-    """
-    Retrieves background info about a guest using the document store.
-
-    Args:
-        name (str): The name of the guest to retrieve context for.
-
-    Returns:
-        str: Relevant background information from the document store.
-    """
-    return retrieve_context(name)
-
-@tool
-def greeting_tool(name: str) -> str:
-    """
-    Generates a custom greeting for the guest.
-
-    Args:
-        name (str): The name of the guest to greet.
-
-    Returns:
-        str: A friendly greeting message.
-    """
-    return f"Welcome to the gala, {name}! We're honored to have you with us."
-
-def build_prompt(question: str, context: str = "") -> str:
-    """
-    Constructs a prompt for the agent using a question and optional context.
-
-    Args:
-        question (str): The user query to be answered.
-        context (str): Optional supporting context or retrieved documents.
-
-    Returns:
-        str: A formatted prompt for the LLM.
-    """
-    if context:
-        return f"Here is some context: {context}\n\nQuestion: {question}\n\nAnswer:"
-    else:
-        return f"Question: {question}\n\nAnswer:"
+# tools.py
+
+from smolagents import tool
+from retriever import retrieve_relevant_context
+
+def clean_answer_with_prompt(agent_output: str) -> str:
+    """
+    Extracts and cleans the final answer from the agent output.
+    For GAIA, ensure no 'FINAL ANSWER:' prefix is returned — just the answer.
+    """
+    if "FINAL ANSWER:" in agent_output:
+        return agent_output.split("FINAL ANSWER:")[-1].strip()
+    return agent_output.strip()
+
+@tool
+def guest_info_tool(name: str) -> str:
+    """
+    Retrieves background info about a guest using the document store.
+
+    Args:
+        name (str): The name of the guest to retrieve context for.
+
+    Returns:
+        str: Relevant background information from the document store.
+    """
+    return retrieve_relevant_context(name)
+
+@tool
+def greeting_tool(name: str) -> str:
+    """
+    Generates a custom greeting for the guest.
+
+    Args:
+        name (str): The name of the guest to greet.
+
+    Returns:
+        str: A friendly greeting message.
+    """
+    return f"Welcome to the gala, {name}! We're honored to have you with us."
+
+def build_prompt(question: str, context: str = "") -> str:
+    """
+    Constructs a prompt for the agent using a question and optional context.
+
+    Args:
+        question (str): The user query to be answered.
+        context (str): Optional supporting context or retrieved documents.
+
+    Returns:
+        str: A formatted prompt for the LLM.
+    """
+    if context:
+        return f"Here is some context: {context}\n\nQuestion: {question}\n\nAnswer:"
+    else:
+        return f"Question: {question}\n\nAnswer:"