Update agent.py

agent.py

@@ -1,6 +1,7 @@
-"""LangGraph Agent – retry 5s, 30s, 60s; senza Supabase"""
+"""LangGraph Agent – retry 5s, 30s, 60s; senza Supabase (fix ‘ll’)."""
 
-import os, time
+import os
+import time
 from dotenv import load_dotenv
 from langgraph.graph import START, StateGraph, MessagesState
 from langgraph.prebuilt import ToolNode, tools_condition
@@ -93,28 +94,28 @@ tools = [
 # --------------------------------------------------------------------------- #
 #  Retry parameters                                                           #
 # --------------------------------------------------------------------------- #
-RETRY_DELAYS = [0, 5, 30, 60]        # secondi: tentativo 0, 1, 2, 3
+RETRY_DELAYS = [0, 5, 30, 60]   # 4 tentativi complessivi
 MAX_ATTEMPTS = len(RETRY_DELAYS)
 
 # --------------------------------------------------------------------------- #
 #  Build LangGraph                                                            #
 # --------------------------------------------------------------------------- #
 def build_graph(provider: str = "groq"):
-    """Return a LangGraph graph with explicit retry logic (5s, 30s, 60s)."""
+    """Return a LangGraph graph with custom retry logic."""
 
     # ----------- LLM selection -------------------------------------------- #
     if provider == "google":
-        llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash", temperature=0)
+        llm_selected = ChatGoogleGenerativeAI(model="gemini-2.0-flash", temperature=0)
 
     elif provider == "groq":
-        llm = ChatGroq(
+        llm_selected = ChatGroq(
             model="qwen-qwq-32b",
             temperature=0,
-            max_retries=0,      # disabilitiamo i retry interni
+            max_retries=0,  # gestiamo noi i retry
         )
 
     elif provider == "huggingface":
-        llm = ChatHuggingFace(
+        llm_selected = ChatHuggingFace(
             llm=HuggingFaceEndpoint(
                 url="https://api-inference.huggingface.co/models/Meta-DeepLearning/llama-2-7b-chat-hf",
                 temperature=0,
@@ -123,13 +124,13 @@ def build_graph(provider: str = "groq"):
     else:
         raise ValueError("Invalid provider. Choose 'google', 'groq' or 'huggingface'.")
 
-    llm_with_tools = llm.bind_tools(tools)
+    llm_with_tools = llm_selected.bind_tools(tools)
 
     # ---------------- Retry wrapper -------------------------------------- #
     def invoke_with_retry(messages):
         last_err = None
         for attempt, delay in enumerate(RETRY_DELAYS):
-            if delay > 0:
+            if delay:
                 print(f"[Retry {attempt}/{MAX_ATTEMPTS-1}] waiting {delay}s")
                 time.sleep(delay)
             try:
@@ -138,9 +139,8 @@ def build_graph(provider: str = "groq"):
                 err_text = str(e)
                 if ("503" in err_text or "Service Unavailable" in err_text) and attempt < MAX_ATTEMPTS - 1:
                     last_err = e
-                    continue   # passa al prossimo tentativo
-                raise  # altro errore o ultimi tentativo esaurito
-        # se per qualche motivo esce dal loop senza raise
+                    continue  # retry
+                raise  # altro errore o tentativi finiti
         raise last_err or RuntimeError("Unknown error during LLM invocation")
 
     # ---------------- Nodes ---------------------------------------------- #
@@ -159,13 +159,17 @@ def build_graph(provider: str = "groq"):
 
     return builder.compile()
 
+
 # --------------------------------------------------------------------------- #
-#  Test rapido                                                                #
+#  Stand-alone test                                                           #
 # --------------------------------------------------------------------------- #
 if __name__ == "__main__":
-    g = build_graph(provider="groq")
-    q = "When was a picture of St. Thomas Aquinas first added to the Wikipedia page on the Principle of double effect?"
-    msgs = [HumanMessage(content=q)]
-    res = g.invoke({"messages": msgs})
-    for m in res["messages"]:
+    graph = build_graph(provider="groq")
+    question = (
+        "When was a picture of St. Thomas Aquinas first added to the Wikipedia "
+        "page on the Principle of double effect?"
+    )
+    msgs = [HumanMessage(content=question)]
+    result = graph.invoke({"messages": msgs})
+    for m in result["messages"]:
         m.pretty_print()