fix

README.md

@@ -1,2 +1,11 @@
 # agi
 langchain based agi
+
+## RAG
+- history_chain = RunnableLambda(self._enter_history, self._aenter_history).with_config(run_name="load_history")
+- history_chain = RunnablePassthrough.assign(**{"chat_history": history_chain}).with_config(run_name="insert_history")
+- retrieval_docs = (lambda x: x["input"]) | retriever
+- retriever = (lambda x: x["input"]) | retriever  or  prompt | llm | StrOutputParser() | retriever, run_name="chat_retriever_chain"
+- context=retrieval_docs.with_config(run_name="retrieve_documents")
+- "context": format_docs run_name="format_inputs"
+- answer =  "context" | prompt | llm | _output_parser     run_name="stuff_documents_chain"

agi/tasks/llm_app.py

@@ -105,7 +105,15 @@ def create_history_aware_retriever(
     ).with_config(run_name="chat_retriever_chain")
 
     return retrieve_documents
-
+
+# chain:RunnableWithMessageHistory
+# chain:insert_history
+# chain:RunnableParallel<chat_history>
+# chain:load_history
+# chain:check_sync_or_async 
+# chain:retrieval_chain 
+# chain:RunnableAssign<answer> 
+# chain:RunnableParallel<answer>
 def create_chat_with_rag(km: KnowledgeManager,llm,**kwargs):
     retrievers = create_retriever(km,**kwargs)
 

tests/tasks/task_factory_rag.py

@@ -45,7 +45,10 @@ def setUp(self):
     def test_rag(self):
         config={"configurable": {"user_id": "test", "conversation_id": "1"}}
         ret = self.rag.invoke({"text":"上海未来一周天气如何？","language":"chinese"},config=config)
-        print(ret)
+        self.assertIsNotNone(ret)
+        self.assertIsInstance(ret['chat_history'],list)
+        self.assertIsInstance(ret['context'],list)
+        self.assertIsNotNone(ret['answer'])
 
 if __name__ == '__main__':
     unittest.main()