Update llm.py

llm.py

@@ -120,7 +120,7 @@ def construct_index(
             index = GPTVectorStoreIndex.from_documents(documents, service_context=service_context)
         else:
             index = GPTListIndex.from_documents(documents, service_context=service_context)
-        index.storage_context.persist(persist_dir=f"{index_name}")
+        index.storage_context.persist(persist_dir="./index")
     except Exception as e:
         print(e)
         return None
@@ -163,7 +163,7 @@ def chat_ai(
     print(response)
 
     if response is None:
-        response = llm._call(question)
+        response = "Please upload a document first"
     response = parse_text(response)
 
     context.append({"role": "user", "content": question})
@@ -184,17 +184,17 @@ def ask_ai(
 ):
     logging.debug("Querying index...")
     prompt_helper = PromptHelper(
-        2048,
-        512,
-        20
+        300,
+        200,
+        -20000
     )
     llm = LlamaCpp(model_path=model_path,
-        n_ctx=2048, 
+        n_ctx=300, 
         use_mlock=True,
         n_parts=-1, 
         temperature=temprature, 
         top_p=0.40,
-        last_n_tokens_size=400,
+        last_n_tokens_size=100,
         n_threads=4,
         f16_kv=True,
         max_tokens=200
@@ -212,8 +212,9 @@ def ask_ai(
         vector_store=SimpleVectorStore.from_persist_dir(persist_dir="./index"),
         index_store=SimpleIndexStore.from_persist_dir(persist_dir="./index"),
     )
-    index = load_index_from_storage(service_context=service_context, storage_context=storage_context)
-    response = query_llm(index, question, service_context)
+    if storage_context is not None:
+        index = load_index_from_storage(service_context=service_context, storage_context=storage_context)
+        response = query_llm(index, question, service_context)
 
     if response is not None:
         logging.info(f"Response: {response}")
@@ -278,3 +279,5 @@ def search_construct(question, search_mode, index_select):
     print("\n".join(links))
     search_index_name = " ".join(search_terms.split(","))
     construct_index(links, search_index_name, "GPTVectorStoreIndex")
+    print(f"Index {search_index_name} constructed.")
+    return search_index_name + "_GPTVectorStoreIndex"