Merge pull request #23 from nalbam/main

chore: Update conversation function to handle multiple contexts and a…

bedrock/invoke_claude_3.py

@@ -14,7 +14,11 @@
 
 MODEL_ID_TEXT = "anthropic.claude-3-5-sonnet-20240620-v1:0"
 
-SYSTEM_MESSAGE = "너는 사람들에게 친절하게 도움을 주는 구루미(Gurumi)야. 답변을 할때 참고한 문서가 있다면 링크도 알려줘."
+# Set up System messages
+PERSONAL_MESSAGE = os.environ.get(
+    "PERSONAL_MESSAGE", "당신은 친절하고 전문적인 AI 비서 입니다."
+)
+SYSTEM_MESSAGE = "답변을 할때 참고한 문서가 있다면 링크도 알려줘."
 
 
 # Initialize the Amazon Bedrock runtime client
@@ -78,16 +82,14 @@ def main():
     query = args.prompt
 
     prompts = []
-    prompts.append(
-        "Human: You are a advisor AI system, and provides answers to questions by using fact based and statistical information when possible."
-    )
-    prompts.append(
-        "If you don't know the answer, just say that you don't know, don't try to make up an answer."
-    )
+    prompts.append("User: {}".format(PERSONAL_MESSAGE))
+    prompts.append("If you don't know the answer, just say that you don't know, don't try to make up an answer.")
 
     if SYSTEM_MESSAGE != "None":
         prompts.append(SYSTEM_MESSAGE)
 
+    prompts.append("<question> 태그로 감싸진 질문에 답변을 제공하세요.")
+
     try:
         # Add the question to the prompts
         prompts.append("")
@@ -96,7 +98,6 @@ def main():
         prompts.append("</question>")
         prompts.append("")
 
-        # prompts.append("The response should be specific and use statistics or numbers when possible.")
         prompts.append("Assistant:")
 
         # Combine the prompts

bedrock/invoke_claude_3_image.py

@@ -6,8 +6,6 @@
 import boto3
 import base64
 
-SYSTEM_MESSAGE = "너는 구름이(Gurumi) 야. 구름이는 한국어로 구름을 친숙하게 부르는 표현이야. AWSKRUG(AWS Korea User Group)의 마스코트지."
-
 
 def parse_args():
     p = argparse.ArgumentParser(description="invoke_claude_3")
@@ -62,9 +60,6 @@ def invoke_claude_3(prompt):
             ],
         }
 
-        if SYSTEM_MESSAGE:
-            body["system"] = SYSTEM_MESSAGE
-
         # print("request: {}".format(body))
 
         response = bedrock.invoke_model(

bedrock/invoke_knowledge_base.py

@@ -22,7 +22,11 @@
 
 MODEL_ID_TEXT = "anthropic.claude-3-sonnet-20240229-v1:0"
 
-SYSTEM_MESSAGE = "너는 사람들에게 친절하게 도움을 주는 구루미(Gurumi)야. 답변을 할때 참고한 문서가 있다면 링크도 알려줘."
+# Set up System messages
+PERSONAL_MESSAGE = os.environ.get(
+    "PERSONAL_MESSAGE", "당신은 친절하고 전문적인 AI 비서 입니다."
+)
+SYSTEM_MESSAGE = "답변을 할때 참고한 문서가 있다면 링크도 알려줘."
 
 
 # Initialize the Amazon Bedrock runtime client
@@ -133,23 +137,21 @@ def main():
     query = args.prompt
 
     prompts = []
-    prompts.append(
-        "Human: You are a advisor AI system, and provides answers to questions by using fact based and statistical information when possible."
-    )
-    prompts.append(
-        "If you don't know the answer, just say that you don't know, don't try to make up an answer."
-    )
+    prompts.append("User: {}".format(PERSONAL_MESSAGE))
+    prompts.append("If you don't know the answer, just say that you don't know, don't try to make up an answer.")
 
     if SYSTEM_MESSAGE != "None":
         prompts.append(SYSTEM_MESSAGE)
 
+    prompts.append("<question> 태그로 감싸진 질문에 답변을 제공하세요.")
+
     try:
         # Get the knowledge base contexts
         if KNOWLEDGE_BASE_ID != "None":
             contexts = invoke_knowledge_base(query)
 
             prompts.append(
-                "Use the following pieces of information to provide a concise answer to the question enclosed in <question> tags."
+                "<context> 에 정보가 제공 되면, 해당 정보를 사용하여 답변해 주세요."
             )
             prompts.append("<context>")
             prompts.append("\n\n".join(contexts))
@@ -162,7 +164,6 @@ def main():
         prompts.append("</question>")
         prompts.append("")
 
-        # prompts.append("The response should be specific and use statistics or numbers when possible.")
         prompts.append("Assistant:")
 
         # Combine the prompts

handler.py

@@ -12,8 +12,6 @@
 from slack_bolt.adapter.aws_lambda import SlackRequestHandler
 
 
-BOT_CURSOR = os.environ.get("BOT_CURSOR", ":robot_face:")
-
 AWS_REGION = os.environ.get("AWS_REGION", "us-east-1")
 
 # Set up Slack API credentials
@@ -47,6 +45,8 @@
 MAX_LEN_SLACK = int(os.environ.get("MAX_LEN_SLACK", 3000))
 MAX_LEN_BEDROCK = int(os.environ.get("MAX_LEN_BEDROCK", 4000))
 
+BOT_CURSOR = os.environ.get("BOT_CURSOR", ":robot_face:")
+
 MSG_KNOWLEDGE = "지식 기반 검색 중... " + BOT_CURSOR
 MSG_PREVIOUS = "이전 대화 내용 확인 중... " + BOT_CURSOR
 MSG_RESPONSE = "응답 기다리는 중... " + BOT_CURSOR
@@ -307,8 +307,8 @@ def conversation(say: Say, thread_ts, query, channel, client_msg_id):
     latest_ts = result["ts"]
 
     prompts = []
-    prompts.append("Human: {}".format(PERSONAL_MESSAGE))
-    prompts.append("답변을 모르면 모른다고 하세요. 답을 지어내려고 하지 마세요.")
+    prompts.append("User: {}".format(PERSONAL_MESSAGE))
+    prompts.append("If you don't know the answer, just say that you don't know, don't try to make up an answer.")
 
     if SYSTEM_MESSAGE != "None":
         prompts.append(SYSTEM_MESSAGE)