增加 多线程

document_ai/run.py

@@ -0,0 +1,20 @@
+from threading import Thread
+
+import worker
+import server
+
+if __name__ == '__main__':
+    # Start the worker thread
+    worker_thread = Thread(target=worker.sync_documents, args=())
+    worker_thread.start()
+
+    # Start the server thread
+    server_thread = Thread(target=server.serve, args=())
+    server_thread.start()
+
+    # Wait for the threads to finish
+    worker_thread.join()
+    server_thread.join()
+
+
+

document_ai/server.py

@@ -52,10 +52,10 @@ class AIServer(document_query_pb2_grpc.DocumentQuery):
 
         print(real_document)
 
-        print("正在调用 LLM...")
+        print("正在调用 LLM: " + question + "...")
         chain = load_qa_with_sources_chain(OpenAI(temperature=0), chain_type="map_reduce",
-                                           return_intermediate_steps=True,
+                                           return_intermediate_steps=False,
-                                           verbose=True)
+                                           verbose=False)
         output = chain({"input_documents": real_document, "question": question}, return_only_outputs=False)
         print("回复：" + output["output_text"])
 
@@ -77,4 +77,3 @@ def serve():
     server.wait_for_termination()
 
 
-serve()

document_ai/worker.py

@@ -1,13 +1,19 @@
+import time
+
 import documents_pb2_grpc
 import documents_pb2
 import init
 import doc_client
+import sys
+import signal
 
-print("获取需要更新的数据...")
-documents_response = doc_client.stub.GetNoVectorDocuments(documents_pb2.GetNoVectorDocumentsRequest()).documents
 
-# # get all documents with no vector
+def sync_documents():
-for document in documents_response:
+    while True:
+        documents_response = doc_client.stub.GetNoVectorDocuments(documents_pb2.GetNoVectorDocumentsRequest()).documents
+
+        # # get all documents with no vector
+        for document in documents_response:
             docContent = document.title + "\n" + document.content
 
             print("正在更新向量...")
@@ -25,3 +31,5 @@ for document in documents_response:
 
             print(update_vector_id_response)
             print("更新向量完成")
+
+            time.sleep(1 * 60)