incorporated optional parameters to the model + overall enhancement

README.md

@@ -93,7 +93,8 @@ On Linux/MacOS more details are [here](docs/Linux_Osx_Usage.md)
 
 
 ## Options
-
+*   `--model`: the name of the model to be used. The model should be placed in models folder (default: gpt4all-lora-quantized.bin)
+*   `--seed`: the random seed for reproductibility. If fixed, it is possible to reproduce the outputs exactly (default: random)
 *   `--port`: the port on which to run the server (default: 9600)
 *   `--host`: the host address on which to run the server (default: localhost)
 *   `--temp`: the sampling temperature for the model (default: 0.1)

app.py

@@ -1,6 +1,7 @@
 import argparse
 import json
 import re
+import random
 import sqlite3
 import traceback
 from datetime import datetime
@@ -166,11 +167,12 @@ app = Flask("GPT4All-WebUI", static_url_path="/static", static_folder="static")
 
 
 class Gpt4AllWebUI:
-    def __init__(self, chatbot_bindings, _app, db_path="database.db") -> None:
+    def __init__(self, _app, args) -> None:
+        self.args = args
         self.current_discussion = None
-        self.chatbot_bindings = chatbot_bindings
         self.app = _app
-        self.db_path = db_path
+        self.db_path = args.db_path
+        
         self.add_endpoint("/", "", self.index, methods=["GET"])
         self.add_endpoint("/export", "export", self.export, methods=["GET"])
         self.add_endpoint(
@@ -195,21 +197,41 @@ class Gpt4AllWebUI:
             "/update_message", "update_message", self.update_message, methods=["GET"]
         )
 
-        conditionning_message = """
+
+        # Create chatbot
+        self.chatbot_bindings = self.create_chatbot()
+        # Chatbot conditionning
+        self.condition_chatbot()
+
+
+    def create_chatbot(self):
+        return Model(
+            ggml_model=f"./models/{self.args.model}", 
+            n_ctx=self.args.ctx_size, 
+            seed=self.args.seed,
+            )
+
+    def condition_chatbot(self, conditionning_message = """
 Instruction: Act as GPT4All. A kind and helpful AI bot built to help users solve problems.
 Start by welcoming the user then stop sending text.
-GPT4All:"""
+GPT4All:Welcome! I'm here to assist you with anything you need. What can I do for you today?"""
+                          ):
+        
         self.prepare_query(conditionning_message)
-        chatbot_bindings.generate(
+        self.chatbot_bindings.generate(
             conditionning_message,
-            n_predict=55,
             new_text_callback=self.new_text_callback,
+
+            n_predict=len(conditionning_message),
+            temp=self.args.temp,
+            top_k=self.args.top_k,
+            top_p=self.args.top_p,
+            repeat_penalty=self.args.repeat_penalty,
+            repeat_last_n = self.args.repeat_last_n,
+            #seed=self.args.seed,
             n_threads=8,
         )
-        print(f"Bot said:{self.bot_says}")
-        # Chatbot conditionning
-        # response = self.chatbot_bindings.prompt("This is a discussion between A user and an AI. AI responds to user questions in a helpful manner. AI is not allowed to lie or deceive. AI welcomes the user\n### Response:")
-        # print(response)
+        print(f"Bot said:{self.bot_says}")        
 
     def prepare_query(self, message):
         self.bot_says = ""
@@ -291,12 +313,19 @@ GPT4All:"""
             )
         )
 
-        self.current_message = "User: " + message + "\nGPT4All:"
+        self.current_message = "\nUser: " + message + "\nGPT4All: "
         self.prepare_query(self.current_message)
-        chatbot_model_bindings.generate(
+        self.chatbot_bindings.generate(
             self.current_message,
-            n_predict=55,
             new_text_callback=self.new_text_callback,
+
+            n_predict=len(self.current_message)+args.n_predict,
+            temp=self.args.temp,
+            top_k=self.args.top_k,
+            top_p=self.args.top_p,
+            repeat_penalty=self.args.repeat_penalty,
+            repeat_last_n = self.args.repeat_last_n,
+            #seed=self.args.seed,
             n_threads=8,
         )
 
@@ -363,6 +392,21 @@ GPT4All:"""
         discussion_id = data["id"]
         self.current_discussion = Discussion(discussion_id, self.db_path)
         messages = self.current_discussion.get_messages()
+        full_message = ""
+        for message in messages:
+            full_message += message['sender'] + ": " + message['content'] + "\n"
+            
+        self.chatbot_bindings.generate(
+            full_message,
+            new_text_callback=self.new_text_callback,
+            n_predict=len(messages),
+            temp=self.args.temp,
+            top_k=self.args.top_k,
+            top_p=self.args.top_p,
+            repeat_penalty= self.args.repeat_penalty,
+            repeat_last_n = self.args.repeat_last_n,
+            n_threads=8,
+        )
         return jsonify(messages)
 
     def delete_discussion(self):
@@ -395,24 +439,30 @@ GPT4All:"""
         # Get the current timestamp
         timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
 
-        # add a new discussion
-        # self.chatbot_bindings.close()
-        # self.chatbot_bindings.open()
-
+        # Create chatbot
+        self.chatbot_bindings = self.create_chatbot()
+        # Chatbot conditionning
+        self.condition_chatbot()
         # Return a success response
         return json.dumps({"id": self.current_discussion.discussion_id, "time": timestamp})
 
 
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description="Start the chatbot Flask app.")
+    parser.add_argument(
+        "-s", "--seed", type=int, default=0, help="Force using a specific model."
+    )
 
+    parser.add_argument(
+        "-m", "--model", type=str, default="gpt4all-lora-quantized.bin", help="Force using a specific model."
+    )
     parser.add_argument(
         "--temp", type=float, default=0.1, help="Temperature parameter for the model."
     )
     parser.add_argument(
         "--n_predict",
         type=int,
-        default=128,
+        default=256,#128,
         help="Number of tokens to predict at each step.",
     )
     parser.add_argument(
@@ -433,7 +483,7 @@ if __name__ == "__main__":
     parser.add_argument(
         "--ctx_size",
         type=int,
-        default=2048,
+        default=512,#2048,
         help="Size of the context window for the model.",
     )
     parser.add_argument(
@@ -450,26 +500,10 @@ if __name__ == "__main__":
         "--db_path", type=str, default="database.db", help="Database path"
     )
     parser.set_defaults(debug=False)
-
     args = parser.parse_args()
 
-    chatbot_model_bindings = Model(
-        ggml_model="./models/gpt4all-lora-quantized-ggml.bin", n_ctx=512
-    )
-
-    # Old Code
-    # GPT4All(decoder_config = {
-    #     'temp': args.temp,
-    #     'n_predict':args.n_predict,
-    #     'top_k':args.top_k,
-    #     'top_p':args.top_p,
-    #     #'color': True,#"## Instruction",
-    #     'repeat_penalty': args.repeat_penalty,
-    #     'repeat_last_n':args.repeat_last_n,
-    #     'ctx_size': args.ctx_size
-    # })
     check_discussion_db(args.db_path)
-    bot = Gpt4AllWebUI(chatbot_model_bindings, app, args.db_path)
+    bot = Gpt4AllWebUI(app, args)
 
     if args.debug:
         app.run(debug=True, host=args.host, port=args.port)

run.bat

@@ -37,4 +37,4 @@ echo HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH
 
 echo on
 call env/Scripts/activate.bat
-python app.py
+python app.py %*

static/js/chat.js

@@ -527,6 +527,7 @@ const welcome_message = `
 - Act as ChefAI an AI that has the ability to create recipes for any occasion. Instruction: Give me a recipe for my next anniversary.<br>
 </code>
 </div>
+<div>Welcome! I'm here to assist you with anything you need. What can I do for you today?</div>
 `;
 //welcome_message = add_collapsible_div("Note:", text, 'hints');