Add SQLite database support for conversation history

- Introduce SQLite database to store conversation history
- Implement functions to save and load conversations from the database
- Replace previous file-based history storage with database-backed solution
- Add new command to list and resume previous conversations
- Update chat logic to generate topics for saved conversations
- Add database initialization and management functions
- Modify command line interface to support resuming conversations

assistant.py

@@ -3,8 +3,8 @@
 import argparse
 import os
 import sys
-import datetime
 import sqlite3
+import warnings
 
 import json
 from ollama import Client
@@ -19,6 +19,10 @@ from prompt_toolkit.key_binding import KeyBindings
 from prompt_toolkit import PromptSession
 
 
+default_assistant = "qwen3:14b"
+default_topic_llm = "qwen3:1.7b"
+
+warnings.filterwarnings("ignore")
 
 class AIAssistant:
     def __init__(self, server="http://localhost:11434", model="qwen3:14b"):
@@ -76,14 +80,32 @@ class AIAssistant:
         else:
             self.history = [self.system_prompt()]
 
+    def _stringify_history(self):
+        s = ""
+        for item in self.history:
+            s += item["role"] + ":\n" + item["content"]
+        return s
+    
+    def _strip_thinking_tags(self, text: str):
+        start_idx = text.find("<think>")
+        if (start_idx < 0):
+            return text
+
+        end_idx = text.find("</think>") + len("</think>")
+        stripped_text = text[end_idx:]
+        stripped_text = stripped_text.strip()
+        return stripped_text
+
     def save_history(self):
         """Save the current conversation to the database with a generated topic."""
         # Only save if this is the first user message
         if len(self.history) == 3:
             # Generate a topic using the AI
             system_prompt = self.system_prompt()
-            user_prompt = "Generate a concise, descriptive topic for this conversation based on the following content:\n"
+            user_prompt = "/no_think Generate a concise, 5 word descriptive topic for this conversation based on the following content. Do not use markdown, just plaintext. KEEP IT TO 5 WORDS OR LESS.:\n\n"
-            topic = self.client.chat(model=self.model, messages=[system_prompt, {"role": "user", "content": user_prompt}], stream=False)['message']['content'].strip()
+            user_prompt += self._stringify_history()
+            topic = self.client.chat(model=default_topic_llm, messages=[system_prompt, {"role": "user", "content": user_prompt}], stream=False)['message']['content'].strip()
+            topic = self._strip_thinking_tags(topic)
             self._save_to_db(topic)
         else:
             # For subsequent messages, we can update the topic in the future
@@ -93,6 +115,7 @@ class AIAssistant:
         """Load a conversation from the database by ID. If no ID, start a new one."""
         if conversation_id:
             self._load_from_db(conversation_id)
+            print(self._stringify_history())
         else:
             self.history = [self.system_prompt()]
 
@@ -223,15 +246,25 @@ class InputHandler:
         except:
             return
 
+    def follow_up(self, args, query):
+        if type(args.follow_up) is str:
+            second_input = args.follow_up
+        else:
+            second_input = self.improved_input()
+        query += f'\n\nUser Question:\n{second_input}'
+        return query
+
+
     def handle_piped_input(self, args):
         all_input = sys.stdin.read()
         query = f'Use the following context to answer the question. There will be no follow up questions from the user so make sure your answer is complete:\n{all_input}\n'
         if args.copy:
             query += 'Answer the question using a codeblock for any code or shell scripts\n'
         if args.follow_up:
-            second_input = self.improved_input()
+            query = self.follow_up(args, query)
-            query += f'\n{second_input}'
         result = self.assistant.chat(query, stream=False)
+        result = self.assistant._strip_thinking_tags(result)
+        print(result)
         blocks = self.extract_code_block(result)
         if args.copy and len(blocks):
             self.copy_string_to_clipboard(blocks[0])
@@ -256,6 +289,14 @@ Description:\n
             self.assistant.history = [self.assistant.system_prompt()]
             self.arg_shell(args)
             exit()
+        if args.follow_up:
+            query = "Provide a complete answer to the user's question, there will be no follow up questions from the user.\n\n"
+            query = self.follow_up(args, query)
+            result = self.assistant.chat(query, stream=False)
+            result = self.assistant._strip_thinking_tags(result)
+            print(result)
+            exit()
+
 
         print("\033[91massistant\033[0m: Type your message (press Ctrl+D to send):")
         while True:
@@ -313,7 +354,8 @@ class CommandParser:
             '/clear': self.handle_clear,
             '/clipboard': None,
             '/exit': self.handle_exit,
-            '/copy': self.handle_copy
+            '/copy': self.handle_copy,
+            '/list': self.handle_list
         }
 
     def parse_commands(self, text):
@@ -368,6 +410,36 @@ class CommandParser:
             self.input_handler.copy_string_to_clipboard(block)
         return True
 
+    def handle_list(self):
+        assistant = self.assistant
+        db_path = assistant.db_path
+        # Connect to the database and fetch saved conversations
+        conn = sqlite3.connect(db_path)
+        cursor = conn.cursor()
+        cursor.execute("SELECT id, topic FROM conversations")
+        rows = cursor.fetchall()
+        conn.close()
+        if not rows:
+            print("No saved conversations.")
+            return
+        # Display saved conversations
+        print("\nSaved conversations:")
+        for row in rows:
+            print(f"ID: {row[0]}, Topic: {row[1]}")
+        # Prompt user to select an ID
+        choice = input("\nEnter conversation ID to load (or 'q' to quit): ").strip()
+        if choice.lower() == 'q':
+            return
+        try:
+            conv_id = int(choice)
+            assistant.load_history(conversation_id=conv_id)
+            print(f"\nLoaded conversation with ID {conv_id}.")
+        except ValueError:
+            print("Invalid ID. Please enter a number.")
+        except Exception as e:
+            print(f"Error loading conversation: {e}")
+
+
     def handle_exit(self):
         sys.exit(0)