test async

main.py

@@ -1,3 +1,5 @@
+import asyncio
+
 from dotenv import load_dotenv
 from langchain_classic.retrievers import ContextualCompressionRetriever
 from langchain_core.output_parsers import StrOutputParser
@@ -13,6 +15,7 @@ PROJECT = "akqa-ita-ai-poc1"
 DATA_STORE = "akern-ds_1771234036654"
 MODEL = "gemini-2.5-flash"
 LOCATION = "eu"
+PRINT_SOURCES = False
 
 # LLM CONFIG
 TOP_K = 40
@@ -30,19 +33,22 @@ prompt = ChatPromptTemplate.from_template(template)
 
 def format_docs(question: str) -> str:
     retrieved_docs = base_retriever.invoke(question)
-
-    print("========== RETRIEVER DOCUMENTS ==========")
-    for idx, doc in enumerate(retrieved_docs, start=1):
-        snippet = doc.page_content[:200].replace("\n", " ")
-        print(f"[{idx}] metadata={doc.metadata['source']} | snippet=...{snippet}...")
-
     reranked_docs = compression_retriever.invoke(question)
-    print("========== RERANKED DOCUMENTS ==========")
-    for idx, doc in enumerate(reranked_docs, start=1):
-        snippet = doc.page_content[:200].replace("\n", " ")
-        print(
-            f"[{idx}] metadata={doc.metadata['relevance_score']} | snippet=...{snippet}..."
-        )
+
+    if PRINT_SOURCES:
+        print("========== RETRIEVER DOCUMENTS ==========")
+        for idx, doc in enumerate(retrieved_docs, start=1):
+            snippet = doc.page_content[:200].replace("\n", " ")
+            print(
+                f"[{idx}] metadata={doc.metadata['source']} | snippet=...{snippet}..."
+            )
+
+        print("========== RERANKED DOCUMENTS ==========")
+        for idx, doc in enumerate(reranked_docs, start=1):
+            snippet = doc.page_content[:200].replace("\n", " ")
+            print(
+                f"[{idx}] metadata={doc.metadata['relevance_score']} | snippet=...{snippet}..."
+            )
 
     return "\n\n".join(doc.page_content for doc in reranked_docs)
 
@@ -84,40 +90,24 @@ rag_chain = (
 )
 
 
-# def parse_questions():
-#     domande_dir = "domande"
-#     risposte_dir = "risposte"
+async def async_invoke(rag_chain, prompt: str):
+    return rag_chain.invoke(prompt)
 
-#     os.makedirs(risposte_dir, exist_ok=True)
 
-#     for filename in sorted(os.listdir(domande_dir)):
-#         if not filename.lower().endswith(".txt"):
-#             continue
+async def main():
+    (
+        res1,
+        res2,
+    ) = await asyncio.gather(
+        async_invoke(rag_chain, "come si calcola l'angolo di fase?"),
+        async_invoke(rag_chain, "cos'e' la massa magra?"),
+    )
 
-#         domanda_path = os.path.join(domande_dir, filename)
-
-#         with open(domanda_path, "r", encoding="utf-8") as f:
-#             contents = f.read()
-#             print(f"========== DOMANDA ({domanda_path}) ==========")
-#             print(contents)
-
-#         response = rag_chain.invoke(contents)
-
-#         print("========== RISPOSTA ==========")
-#         print(response)
-#         print("\n\n")
-
-#         base_name = os.path.splitext(filename)[0]
-#         suffix = "".join(ch for ch in base_name if ch.isdigit()) or base_name
-#         risposta_path = os.path.join(risposte_dir, f"risposta{suffix}.txt")
-
-#         with open(risposta_path, "w", encoding="utf-8") as f:
-#             f.write(response)
+    print("RES1")
+    print(res1)
+    print("\n\nRES2")
+    print(res2)
 
 
 if __name__ == "__main__":
-    response = rag_chain.invoke(
-        """Buongiorno, non so se è la mail specifica ma volevo se possibile dei chiarimenti per l’interpretazione dei parametri BCM /SMM/ASMM. Mi capita a volte di trovare casi in cui la BCM è aumentata ma allo stesso tempo SMM/ASMM hanno subito una piccola flessione in negativo (o viceversa). Se la parte metabolicamente attiva aumenta perchè può succedere che gli altri compartimenti si riducono?? E allo stesso tempo phA e BCM possono essere inversamente proporzionali?? So che il phA correla con massa e struttura + idratazione."""
-    )
-
-    print(response)
+    asyncio.run(main())