From cd454dd780f19a232649458697b5fc1894699c89 Mon Sep 17 00:00:00 2001
From: pablodanswer <pablo@danswer.ai>
Date: Mon, 16 Sep 2024 11:37:24 -0700
Subject: [PATCH] update clarity

---
 backend/danswer/chat/process_message.py    |  6 ---
 backend/danswer/llm/utils.py               | 53 ++--------------------
 web/src/app/chat/AIMessageSequenceUtils.ts | 10 +++-
 3 files changed, 12 insertions(+), 57 deletions(-)

diff --git a/backend/danswer/chat/process_message.py b/backend/danswer/chat/process_message.py
index 0474f84c4..0032a770b 100644
--- a/backend/danswer/chat/process_message.py
+++ b/backend/danswer/chat/process_message.py
@@ -634,12 +634,6 @@ def stream_chat_message_objects(
         )
 
         # LLM prompt building, response capturing, etc.
-        logger.info(f"Is connected function: {is_connected}")
-        if is_connected:
-            logger.debug(f"Is connected function type: {type(is_connected)}")
-            logger.debug(f"Is connected function callable: {callable(is_connected)}")
-        else:
-            logger.warning("Is connected function is None or falsy")
         answer = Answer(
             is_connected=is_connected,
             question=final_msg.message,
diff --git a/backend/danswer/llm/utils.py b/backend/danswer/llm/utils.py
index 7383e5d72..05ac7f76c 100644
--- a/backend/danswer/llm/utils.py
+++ b/backend/danswer/llm/utils.py
@@ -99,29 +99,6 @@ def litellm_exception_to_error_msg(e: Exception, llm: LLM) -> str:
     return error_msg
 
 
-# def translate_danswer_msg_to_langchain(
-#     msg: Union[ChatMessage, "PreviousMessage"],
-# ) -> BaseMessage:
-#     files: list[InMemoryChatFile] = []
-
-#     # If the message is a `ChatMessage`, it doesn't have the downloaded files
-#     # attached. Just ignore them for now. Also, OpenAI doesn't allow files to
-#     # be attached to AI messages, so we must remove them
-#     if not isinstance(msg, ChatMessage) and msg.message_type != MessageType.ASSISTANT:
-#         files = msg.files
-#     content = build_content_with_imgs(msg.message, files)
-
-#     if msg.message_type == MessageType.SYSTEM:
-#         raise ValueError("System messages are not currently part of history")
-#     if msg.message_type == MessageType.ASSISTANT:
-#         return AIMessage(content=content)
-#     if msg.message_type == MessageType.USER:
-#         return HumanMessage(content=content)
-
-#     raise ValueError(f"New message type {msg.message_type} not handled")
-
-
-# TODO This is quite janky
 def translate_danswer_msg_to_langchain(
     msg: Union[ChatMessage, "PreviousMessage"],
 ) -> BaseMessage:
@@ -136,37 +113,13 @@ def translate_danswer_msg_to_langchain(
 
     if msg.message_type == MessageType.SYSTEM:
         return SystemMessage(content=content)
-    wrapped_content = ""
     if msg.message_type == MessageType.ASSISTANT:
-        try:
-            parsed_content = (
-                json.loads(content) if isinstance(content, str) else content
-            )
-            if (
-                "name" in parsed_content
-                and parsed_content["name"] == "run_image_generation"
-            ):
-                wrapped_content += f"I, the AI, am now generating an \
-                image based on the prompt: '{parsed_content['args']['prompt']}'\n"
-                wrapped_content += "[/AI IMAGE GENERATION REQUEST]"
-            elif (
-                "id" in parsed_content
-                and parsed_content["id"] == "image_generation_response"
-            ):
-                wrapped_content += "I, the AI, have generated the following image(s) based on the previous request:\n"
-                for img in parsed_content["response"]:
-                    wrapped_content += f"- Description: {img['revised_prompt']}\n"
-                    wrapped_content += f"  Image URL: {img['url']}\n\n"
-                wrapped_content += "[/AI IMAGE GENERATION RESPONSE]"
-            else:
-                wrapped_content = str(content)
-        except json.JSONDecodeError:
-            wrapped_content = str(content)
-        return AIMessage(content=wrapped_content)
-
+        return AIMessage(content=content)
     if msg.message_type == MessageType.USER:
         return HumanMessage(content=content)
 
+    raise ValueError(f"New message type {msg.message_type} not handled")
+
 
 def translate_history_to_basemessages(
     history: list[ChatMessage] | list["PreviousMessage"],
diff --git a/web/src/app/chat/AIMessageSequenceUtils.ts b/web/src/app/chat/AIMessageSequenceUtils.ts
index 6e7544616..021891573 100644
--- a/web/src/app/chat/AIMessageSequenceUtils.ts
+++ b/web/src/app/chat/AIMessageSequenceUtils.ts
@@ -1,8 +1,12 @@
-// For handling AI message `sequences` (ie. ai messages which are streamed in sequence as separate messags but are in reality one message)
+// This module handles AI message sequences - consecutive AI messages that are streamed
+// separately but represent a single logical message. These utilities are used for
+// processing and displaying such sequences in the chat interface.
 
 import { Message } from "@/app/chat/interfaces";
 import { DanswerDocument } from "@/lib/search/interfaces";
 
+// Retrieves the consecutive AI messages at the end of the message history.
+// This is useful for combining or processing the latest AI response sequence.
 export function getConsecutiveAIMessagesAtEnd(
   messageHistory: Message[]
 ): Message[] {
@@ -16,6 +20,10 @@ export function getConsecutiveAIMessagesAtEnd(
   }
   return aiMessages;
 }
+
+// Extracts unique documents from a sequence of AI messages.
+// This is used to compile a comprehensive list of referenced documents
+// across multiple parts of an AI response.
 export function getUniqueDocumentsFromAIMessages(
   messages: Message[]
 ): DanswerDocument[] {