Feat: Adds cognito and memory

assistente/agent.py

@@ -0,0 +1,70 @@
+import json
+import time
+from langchain_aws import ChatBedrock
+from langchain_aws.retrievers import AmazonKnowledgeBasesRetriever
+from langgraph.checkpoint.memory import MemorySaver
+from langgraph.prebuilt import create_react_agent
+from langfuse import Langfuse
+from langfuse.langchain import CallbackHandler
+from tools import secrets,dynamo
+langfuse = Langfuse(
+    public_key=json.loads(secrets.get_secret())['api-langfuse-public'],
+    secret_key=json.loads(secrets.get_secret())['api-langfuse-secret'],
+    host="http://44.200.69.191:3000/"
+)
+langfuse_handler = CallbackHandler()
+def agent_call(event,context):
+    llm = ChatBedrock(
+    model_id="us.anthropic.claude-sonnet-4-20250514-v1:0",
+    region_name="us-east-1",
+    #aws_access_key_id=os.environ["AWS_ACCESS_KEY_ID"],
+    #aws_secret_access_key=os.environ["AWS_SECRET_ACCESS_KEY"],
+    #aws_session_token=os.environ["AWS_SESSION_TOKEN"],
+    model_kwargs={"temperature": 0.1, 'max_tokens': 1000,},
+    provider='anthropic'
+)
+    retriever = AmazonKnowledgeBasesRetriever(
+    knowledge_base_id="PETAZDUOFZ",
+    region_name="us-east-1",
+    retrieval_config={"vectorSearchConfiguration": {"numberOfResults": 4}},
+
+)  
+    username=(event['username'])
+    if event['chat_history']==[]:
+        history=dynamo.read_memory('frente')
+    else:
+        history=event['chat_history']
+    memory = MemorySaver()
+    model = llm
+    tools = [retriever.as_tool()]
+    prompt="""<rules>
+    Act like a human in Portuguese Brasil.
+    You are a assistant for employees and store owners that wants to know about the COMM.pix product, wich makes it possible to use Pix as a payment method outside of Brasil.
+    Answer questions based on the documents that you have access using the retriever tool, do not create information.
+    The chat history will be given, without any documents.
+    If there are info or context missing ask the user before proceding with the document retrieval.
+    Also return the title of the source document.
+    If you don't know the answer or can't find it, say so.
+    <\rules>
+    <glossary>
+    <\glossary>
+    <chain_of_thought>
+    <\chain_of_thought>
+    <general_info>
+    <\general_info>
+Answer the following questions as best you can. You have access to the following tools:
+
+{tools}
+
+Chat History:"""+str(history)
+    agent_executor = create_react_agent(model, tools, checkpointer=memory, prompt=prompt)
+    config = {"configurable": {"thread_id": "abc123"},"callbacks": [langfuse_handler]}
+    input_message = event["message"]
+    dict=input_message[0]
+    #input_message=[{"role":"user","content":"aluno superior, nunca recebi auxilio, campus são paulo, Meu pai não é registrado, como faço para ganhar auxilio?"}]
+    response=""
+    for step in agent_executor.stream({"messages": input_message}, config, stream_mode="values"):
+        response={"json":(step["messages"][-1].text())}
+    response['dynamo_reponse']=dynamo.write_memory(username,int(time.time()),dict['role'],dict['content'])
+    response['chat_history']=history
+    return (response)