aggiunte istruzioni generali per l'agent

agent.py

@@ -25,6 +25,13 @@ GEMINI_TEMPERATURE = float(os.environ.get("GEMINI_TEMPERATURE"))
 
 TOOLS_CALL_DELAY = 1.5
 
+GENERAL_AGENT_INSTRUCTIONS = """You are a general AI assistant. I will ask you a question.
+Your answer should be a number OR as few words as possible OR a comma separated list of numbers and/or strings.
+If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise.
+If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise.
+If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string.
+Provide only the answer, without notes, explanations or comments."""
+
 #
 # Inizializza il modello e gli associa i tool
 #
@@ -90,13 +97,23 @@ def call_model( state: AgentState, config: RunnableConfig):
     # Invoke the model with the system prompt and the messages
     #response = chat_with_tools.invoke(state["messages"], config)
 
-    # Modo 2)
+    # Modo 2) - aggiunge in fondo alcune istruzioni
     # Create a copy to avoid modifying the original state and append instruction to the end
-    messages = state["messages"][:]
-    messages.append(
-        HumanMessage(content="Provide only the answer, without explanations or comments.")
-    )  # Append instruction to the end
-    response = chat_with_tools.invoke(messages, config)
+    # messages = state["messages"][:]
+    # messages.append(
+    #     HumanMessage(content="Provide only the answer, without explanations or comments.")
+    # )  # Append instruction to the end
+    # response = chat_with_tools.invoke(messages, config)
+
+    # Modo 3)
+    # Create a new list for messages to send to the LLM
+    # Start with the general instructions
+    messages_to_send = [HumanMessage(content=GENERAL_AGENT_INSTRUCTIONS)]
+
+    # Append all existing messages from the agent state
+    messages_to_send.extend(state["messages"])
+
+    response = chat_with_tools.invoke(messages_to_send)
 
     # We return a list, because this will get added to the existing messages state using the add_messages reducer
     return {"messages": [response]}