From 0ac1e5f372dbe6baf16f1b0c3d4df1bf5da5efdb Mon Sep 17 00:00:00 2001
From: Debanjum Singh Solanky <debanjum@gmail.com>
Date: Sun, 28 Nov 2021 13:13:39 +0530
Subject: [PATCH] Summarize chat logs and notes returned by semantic search via
 /chat API

---
 src/main.py                       | 18 ++++++++++++++----
 src/processor/conversation/gpt.py |  4 ++--
 2 files changed, 16 insertions(+), 6 deletions(-)

diff --git a/src/main.py b/src/main.py
index 9eb3734a..ad4ccf9d 100644
--- a/src/main.py
+++ b/src/main.py
@@ -9,10 +9,10 @@ from fastapi import FastAPI
 
 # Internal Packages
 from src.search_type import asymmetric, symmetric_ledger, image_search
-from src.utils.helpers import get_absolute_path
+from src.utils.helpers import get_absolute_path, get_from_dict
 from src.utils.cli import cli
 from src.utils.config import SearchType, SearchModels, TextSearchConfig, ImageSearchConfig, SearchConfig, ProcessorConfig, ConversationProcessorConfig
-from src.processor.conversation.gpt import converse, message_to_log, message_to_prompt, understand
+from src.processor.conversation.gpt import converse, message_to_log, message_to_prompt, understand, summarize
 
 
 # Application Global State
@@ -95,8 +95,14 @@ def chat(q: str):
     meta_log = processor_config.conversation.meta_log
 
     # Converse with OpenAI GPT
-    gpt_response = converse(q, chat_log, api_key=processor_config.conversation.openai_api_key)
     metadata = understand(q, api_key=processor_config.conversation.openai_api_key)
+    if get_from_dict(metadata, "intent", "memory-type") == "notes":
+        query = get_from_dict(metadata, "intent", "query")
+        result_list = search(query, n=1, t=SearchType.Notes)
+        collated_result = "\n".join([item["Entry"] for item in result_list])
+        gpt_response = summarize(collated_result, metadata["intent"]["memory-type"], user_query=q, api_key=processor_config.conversation.openai_api_key)
+    else:
+        gpt_response = converse(q, chat_log, api_key=processor_config.conversation.openai_api_key)
 
     # Update Conversation History
     processor_config.conversation.chat_log = message_to_prompt(q, chat_log, gpt_message=gpt_response)
@@ -169,10 +175,14 @@ def shutdown_event():
     elif processor_config.conversation.verbose:
         print('INFO:\tSaving conversation logs to disk...')
 
+    # Summarize Conversation Logs for this Session
+    session_summary = summarize(processor_config.conversation.chat_log, "chat", api_key=processor_config.conversation.openai_api_key)
+
     # Save Conversation Metadata Logs to Disk
+    conversation_logs = {"session": { "summary": session_summary, "meta": processor_config.conversation.meta_log}},
     conversation_logfile = get_absolute_path(processor_config.conversation.conversation_logfile)
     with open(conversation_logfile, "w+", encoding='utf-8') as logfile:
-        json.dump(processor_config.conversation.meta_log, logfile)
+        json.dump(conversation_logs, logfile)
 
     print('INFO:\tConversation logs saved to disk.')
 
diff --git a/src/processor/conversation/gpt.py b/src/processor/conversation/gpt.py
index ae321237..e08c54bf 100644
--- a/src/processor/conversation/gpt.py
+++ b/src/processor/conversation/gpt.py
@@ -18,7 +18,7 @@ def summarize(text, summary_type, user_query=None, api_key=None, temperature=0.5
     if summary_type == "chat":
         prompt = f"You are an AI. Summarize the conversation below from your perspective:\n\n{text}\n\nSummarize the conversation from the AI's first-person perspective:"
     elif summary_type == "notes":
-        prompt = f"Summarize the below notes about {user_query}:\n\n{text}\n\nSummarize:"
+        prompt = f"Summarize the below notes about {user_query}:\n\n{text}\n\nSummarize the notes in second person perspective and use past tense:"
 
     # Get Response from GPT
     response = openai.Completion.create(
@@ -33,7 +33,7 @@ def summarize(text, summary_type, user_query=None, api_key=None, temperature=0.5
 
     # Extract, Clean Message from GPT's Response
     story = response['choices'][0]['text']
-    return str(story)
+    return str(story).replace("\n\n", "")
 
 
 def understand(text, api_key=None, temperature=0.5, max_tokens=100):