Merge pull request #51 from ParisNeo/flask_sse

Multimodel is working

app.py

@@ -1,12 +1,11 @@
 import argparse
 import json
 import re
-import sqlite3
 import traceback
 from datetime import datetime
 from concurrent.futures import ThreadPoolExecutor
 import sys
-
+from db import Discussion, export_to_json, check_discussion_db, last_discussion_has_messages
 from flask import (
     Flask,
     Response,
@@ -14,155 +13,11 @@ from flask import (
     render_template,
     request,
     stream_with_context,
+    send_from_directory
 )
 from pyllamacpp.model import Model
 from queue import Queue
-
-# =================================== Database ==================================================================
-class Discussion:
-    def __init__(self, discussion_id, db_path="database.db"):
-        self.discussion_id = discussion_id
-        self.db_path = db_path
-
-    @staticmethod
-    def create_discussion(db_path="database.db", title="untitled"):
-        with sqlite3.connect(db_path) as conn:
-            cur = conn.cursor()
-            cur.execute("INSERT INTO discussion (title) VALUES (?)", (title,))
-            discussion_id = cur.lastrowid
-            conn.commit()
-        return Discussion(discussion_id, db_path)
-
-    @staticmethod
-    def get_discussion(db_path="database.db", discussion_id=0):
-        return Discussion(discussion_id, db_path)
-
-    def add_message(self, sender, content):
-        with sqlite3.connect(self.db_path) as conn:
-            cur = conn.cursor()
-            cur.execute(
-                "INSERT INTO message (sender, content, discussion_id) VALUES (?, ?, ?)",
-                (sender, content, self.discussion_id),
-            )
-            message_id = cur.lastrowid
-            conn.commit()
-        return message_id
-
-    @staticmethod
-    def get_discussions(db_path):
-        with sqlite3.connect(db_path) as conn:
-            cursor = conn.cursor()
-            cursor.execute("SELECT * FROM discussion")
-            rows = cursor.fetchall()
-        return [{"id": row[0], "title": row[1]} for row in rows]
-
-    @staticmethod
-    def rename(db_path, discussion_id, title):
-        with sqlite3.connect(db_path) as conn:
-            cursor = conn.cursor()
-            cursor.execute(
-                "UPDATE discussion SET title=? WHERE id=?", (title, discussion_id)
-            )
-            conn.commit()
-
-    def delete_discussion(self):
-        with sqlite3.connect(self.db_path) as conn:
-            cur = conn.cursor()
-            cur.execute(
-                "DELETE FROM message WHERE discussion_id=?", (self.discussion_id,)
-            )
-            cur.execute("DELETE FROM discussion WHERE id=?", (self.discussion_id,))
-            conn.commit()
-
-    def get_messages(self):
-        with sqlite3.connect(self.db_path) as conn:
-            cur = conn.cursor()
-            cur.execute(
-                "SELECT * FROM message WHERE discussion_id=?", (self.discussion_id,)
-            )
-            rows = cur.fetchall()
-        return [{"sender": row[1], "content": row[2], "id": row[0]} for row in rows]
-
-    def update_message(self, message_id, new_content):
-        with sqlite3.connect(self.db_path) as conn:
-            cur = conn.cursor()
-            cur.execute(
-                "UPDATE message SET content = ? WHERE id = ?", (new_content, message_id)
-            )
-            conn.commit()
-
-    def remove_discussion(self):
-        with sqlite3.connect(self.db_path) as conn:
-            conn.cursor().execute(
-                "DELETE FROM discussion WHERE id=?", (self.discussion_id,)
-            )
-            conn.commit()
-
-
-def last_discussion_has_messages(db_path="database.db"):
-    with sqlite3.connect(db_path) as conn:
-        cursor = conn.cursor()
-        cursor.execute("SELECT * FROM message ORDER BY id DESC LIMIT 1")
-        last_message = cursor.fetchone()
-    return last_message is not None
-
-
-def export_to_json(db_path="database.db"):
-    with sqlite3.connect(db_path) as conn:
-        cur = conn.cursor()
-        cur.execute("SELECT * FROM discussion")
-        discussions = []
-        for row in cur.fetchall():
-            discussion_id = row[0]
-            discussion = {"id": discussion_id, "messages": []}
-            cur.execute("SELECT * FROM message WHERE discussion_id=?", (discussion_id,))
-            for message_row in cur.fetchall():
-                discussion["messages"].append(
-                    {"sender": message_row[1], "content": message_row[2]}
-                )
-            discussions.append(discussion)
-        return discussions
-
-
-def remove_discussions(db_path="database.db"):
-    with sqlite3.connect(db_path) as conn:
-        cur = conn.cursor()
-        cur.execute("DELETE FROM message")
-        cur.execute("DELETE FROM discussion")
-        conn.commit()
-
-
-# create database schema
-def check_discussion_db(db_path):
-    print("Checking discussions database...")
-    with sqlite3.connect(db_path) as conn:
-        cur = conn.cursor()
-        cur.execute(
-            """
-            CREATE TABLE IF NOT EXISTS discussion (
-                id INTEGER PRIMARY KEY AUTOINCREMENT,
-                title TEXT
-            )
-        """
-        )
-        cur.execute(
-            """
-            CREATE TABLE IF NOT EXISTS message (
-                id INTEGER PRIMARY KEY AUTOINCREMENT,
-                sender TEXT NOT NULL,
-                content TEXT NOT NULL,
-                discussion_id INTEGER NOT NULL,
-                FOREIGN KEY (discussion_id) REFERENCES discussion(id)
-            )
-        """
-        )
-        conn.commit()
-
-    print("Ok")
-
-
-# ========================================================================================================================
-
+from pathlib import Path
 
 app = Flask("GPT4All-WebUI", static_url_path="/static", static_folder="static")
 
@@ -174,8 +29,11 @@ class Gpt4AllWebUI:
         self.app = _app
         self.db_path = args.db_path
 
+        # This is the queue used to stream text to the ui as the bot spits out its response
         self.text_queue = Queue(0)
 
+        
+        
         self.add_endpoint("/", "", self.index, methods=["GET"])
         self.add_endpoint("/export", "export", self.export, methods=["GET"])
         self.add_endpoint(
@@ -203,9 +61,21 @@ class Gpt4AllWebUI:
             "/update_model_params", "update_model_params", self.update_model_params, methods=["POST"]
         )
 
+        self.add_endpoint(
+            "/list_models", "list_models", self.list_models, methods=["GET"]
+        )
+
+
+        self.add_endpoint(
+            "/get_args", "get_args", self.get_args, methods=["GET"]
+        )
         
         self.prepare_a_new_chatbot()
 
+    def list_models(self):
+        models_dir = Path('./models')  # replace with the actual path to the models folder
+        models = [f.name for f in models_dir.glob('*.bin')]
+        return jsonify(models)
 
     def prepare_a_new_chatbot(self):
         # Create chatbot
@@ -463,7 +333,12 @@ GPT4All:Welcome! I'm here to assist you with anything you need. What can I do fo
 
     def update_model_params(self):
         data = request.get_json()
-        self.args.model = str(data["model"])
+        model =  str(data["model"])
+        if self.args.model != model:
+            print("New model selected")
+            self.args.model = model
+            self.prepare_a_new_chatbot()
+
         self.args.n_predict = int(data["nPredict"])
         self.args.seed = int(data["seed"])
         
@@ -484,6 +359,10 @@ GPT4All:Welcome! I'm here to assist you with anything you need. What can I do fo
         return jsonify({"status":"ok"})
     
     
+    def get_args(self):
+        return jsonify(self.args)
+
+
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description="Start the chatbot Flask app.")
     parser.add_argument(

db.py

@@ -0,0 +1,146 @@
+
+import sqlite3
+# =================================== Database ==================================================================
+class Discussion:
+    def __init__(self, discussion_id, db_path="database.db"):
+        self.discussion_id = discussion_id
+        self.db_path = db_path
+
+    @staticmethod
+    def create_discussion(db_path="database.db", title="untitled"):
+        with sqlite3.connect(db_path) as conn:
+            cur = conn.cursor()
+            cur.execute("INSERT INTO discussion (title) VALUES (?)", (title,))
+            discussion_id = cur.lastrowid
+            conn.commit()
+        return Discussion(discussion_id, db_path)
+
+    @staticmethod
+    def get_discussion(db_path="database.db", discussion_id=0):
+        return Discussion(discussion_id, db_path)
+
+    def add_message(self, sender, content):
+        with sqlite3.connect(self.db_path) as conn:
+            cur = conn.cursor()
+            cur.execute(
+                "INSERT INTO message (sender, content, discussion_id) VALUES (?, ?, ?)",
+                (sender, content, self.discussion_id),
+            )
+            message_id = cur.lastrowid
+            conn.commit()
+        return message_id
+
+    @staticmethod
+    def get_discussions(db_path):
+        with sqlite3.connect(db_path) as conn:
+            cursor = conn.cursor()
+            cursor.execute("SELECT * FROM discussion")
+            rows = cursor.fetchall()
+        return [{"id": row[0], "title": row[1]} for row in rows]
+
+    @staticmethod
+    def rename(db_path, discussion_id, title):
+        with sqlite3.connect(db_path) as conn:
+            cursor = conn.cursor()
+            cursor.execute(
+                "UPDATE discussion SET title=? WHERE id=?", (title, discussion_id)
+            )
+            conn.commit()
+
+    def delete_discussion(self):
+        with sqlite3.connect(self.db_path) as conn:
+            cur = conn.cursor()
+            cur.execute(
+                "DELETE FROM message WHERE discussion_id=?", (self.discussion_id,)
+            )
+            cur.execute("DELETE FROM discussion WHERE id=?", (self.discussion_id,))
+            conn.commit()
+
+    def get_messages(self):
+        with sqlite3.connect(self.db_path) as conn:
+            cur = conn.cursor()
+            cur.execute(
+                "SELECT * FROM message WHERE discussion_id=?", (self.discussion_id,)
+            )
+            rows = cur.fetchall()
+        return [{"sender": row[1], "content": row[2], "id": row[0]} for row in rows]
+
+    def update_message(self, message_id, new_content):
+        with sqlite3.connect(self.db_path) as conn:
+            cur = conn.cursor()
+            cur.execute(
+                "UPDATE message SET content = ? WHERE id = ?", (new_content, message_id)
+            )
+            conn.commit()
+
+    def remove_discussion(self):
+        with sqlite3.connect(self.db_path) as conn:
+            conn.cursor().execute(
+                "DELETE FROM discussion WHERE id=?", (self.discussion_id,)
+            )
+            conn.commit()
+
+
+def last_discussion_has_messages(db_path="database.db"):
+    with sqlite3.connect(db_path) as conn:
+        cursor = conn.cursor()
+        cursor.execute("SELECT * FROM message ORDER BY id DESC LIMIT 1")
+        last_message = cursor.fetchone()
+    return last_message is not None
+
+
+def export_to_json(db_path="database.db"):
+    with sqlite3.connect(db_path) as conn:
+        cur = conn.cursor()
+        cur.execute("SELECT * FROM discussion")
+        discussions = []
+        for row in cur.fetchall():
+            discussion_id = row[0]
+            discussion = {"id": discussion_id, "messages": []}
+            cur.execute("SELECT * FROM message WHERE discussion_id=?", (discussion_id,))
+            for message_row in cur.fetchall():
+                discussion["messages"].append(
+                    {"sender": message_row[1], "content": message_row[2]}
+                )
+            discussions.append(discussion)
+        return discussions
+
+
+def remove_discussions(db_path="database.db"):
+    with sqlite3.connect(db_path) as conn:
+        cur = conn.cursor()
+        cur.execute("DELETE FROM message")
+        cur.execute("DELETE FROM discussion")
+        conn.commit()
+
+
+# create database schema
+def check_discussion_db(db_path):
+    print("Checking discussions database...")
+    with sqlite3.connect(db_path) as conn:
+        cur = conn.cursor()
+        cur.execute(
+            """
+            CREATE TABLE IF NOT EXISTS discussion (
+                id INTEGER PRIMARY KEY AUTOINCREMENT,
+                title TEXT
+            )
+        """
+        )
+        cur.execute(
+            """
+            CREATE TABLE IF NOT EXISTS message (
+                id INTEGER PRIMARY KEY AUTOINCREMENT,
+                sender TEXT NOT NULL,
+                content TEXT NOT NULL,
+                discussion_id INTEGER NOT NULL,
+                FOREIGN KEY (discussion_id) REFERENCES discussion(id)
+            )
+        """
+        )
+        conn.commit()
+
+    print("Ok")
+
+
+# ========================================================================================================================

install.bat

@@ -171,11 +171,29 @@ goto :CONTINUE
 :CONTINUE
 echo.
 
+set /p choice=Do you want to download and install the GPT4All model? [Y/N]
+if /i ".choice." equ "Y" (
+echo -n "Checking for git..."
+if command -v git > /dev/null 2>&1; then
+  echo "OK"
+else
+  read -p "Git is not installed. Would you like to install Git? [Y/N] " choice
+  if [ "$choice" = "Y" ] || [ "$choice" = "y" ]; then
+    echo "Installing Git..."
+    sudo apt update
+    sudo apt install -y git
+  else
+    echo "Please install Git and try again."
+    exit 1
+  fi
+fi
+
 echo Converting the model to the new format
 if not exist tmp/llama.cpp git clone https://github.com/ggerganov/llama.cpp.git tmp\llama.cpp
 move models\gpt4all-lora-quantized-ggml.bin models\gpt4all-lora-quantized-ggml.bin.original
 python tmp\llama.cpp\migrate-ggml-2023-03-30-pr613.py models\gpt4all-lora-quantized-ggml.bin.original models\gpt4all-lora-quantized-ggml.bin
 echo The model file (gpt4all-lora-quantized-ggml.bin) has been fixed.
+)
 
 
 echo Cleaning tmp folder

static/js/settings.js

@@ -1,3 +1,36 @@
+function populate_models(){
+  // Get a reference to the <select> element
+  const selectElement = document.getElementById('model');
+
+  // Fetch the list of .bin files from the models subfolder
+  fetch('/list_models')
+    .then(response => response.json())
+    .then(data => {
+      if (Array.isArray(data)) {
+        // data is an array
+        const selectElement = document.getElementById('model');
+        data.forEach(filename => {
+          const optionElement = document.createElement('option');
+          optionElement.value = filename;
+          optionElement.textContent = filename;
+          selectElement.appendChild(optionElement);
+        });
+
+        // fetch('/get_args')
+        // .then(response=> response.json())
+        // .then(data=>{
+          
+        // })
+      } else {
+        console.error('Expected an array, but received:', data);
+      }
+    });
+
+}
+
+populate_models()
+
+
 
 const submitButton = document.getElementById('submit-model-params');
 submitButton.addEventListener('click', (event) => {

templates/chat.html

@@ -28,7 +28,8 @@
                     <form id="model-params-form" class="bg-white shadow-md rounded px-8 pt-6 pb-8 mb-4">
                     <div class="mb-4">
                         <label class="block text-gray-700 font-bold mb-2" for="model">Model</label>
-                        <input class="bg-gray-700 shadow appearance-none border rounded w-full py-2 px-3 text-gray-700 leading-tight focus:outline-none focus:shadow-outline" id="model" type="text" name="model" value="gpt4all-lora-quantized.bin">
+                        <select class="bg-gray-700 shadow appearance-none border rounded w-full py-2 px-3 text-gray-700 leading-tight focus:outline-none focus:shadow-outline" id="model" name="model"  value="gpt4all-lora-quantized.bin">
+                        </select>
                     </div>
                     <div class="mb-4">
                         <label class="block text-gray-700 font-bold mb-2" for="seed">Seed</label>