upgraded

lollms/functions/generate_image.py

@@ -12,7 +12,7 @@ from PyQt5 import QtWidgets, QtGui, QtCore
 import sys
 from functools import partial
 
-def build_image(prompt, width, height, processor:APScript, client:Client):
+def build_image(prompt, antiprompt, width, height, processor:APScript, client:Client):
     try:
         if processor.personality.config.active_tti_service=="autosd":
             if not processor.personality.app.tti:
@@ -23,7 +23,7 @@ def build_image(prompt, width, height, processor:APScript, client:Client):
                 processor.step_end("Loading ParisNeo's fork of AUTOMATIC1111's stable diffusion service")
             file, infos = processor.personality.app.tti.paint(
                             prompt, 
-                            "",
+                            antiprompt,
                             processor.personality.image_files,
                             width = width,
                             height = height,
@@ -58,5 +58,5 @@ def build_image_function(processor, client):
                 "function_name": "build_image",
                 "function": partial(build_image, processor=processor, client=client),
                 "function_description": "Builds and shows an image from a prompt and width and height parameters. A square 1024x1024, a portrait woudl be 1024x1820 or landscape 1820x1024.",
-                "function_parameters": [{"name": "prompt", "type": "str"}, {"name": "width", "type": "int"}, {"name": "height", "type": "int"}]                
+                "function_parameters": [{"name": "prompt", "type": "str"}, {"name": "antiprompt", "type": "str"}, {"name": "width", "type": "int"}, {"name": "height", "type": "int"}]                
             }

lollms/functions/list_personalities.py

@@ -0,0 +1,33 @@
+from lollms.utilities import PackageManager, find_first_available_file_index, discussion_path_to_url
+from lollms.client_session import Client
+from lollms.personality import APScript
+if not PackageManager.check_package_installed("pyautogui"):
+    PackageManager.install_package("pyautogui")
+if not PackageManager.check_package_installed("PyQt5"):
+    PackageManager.install_package("PyQt5")
+from ascii_colors import trace_exception
+import cv2
+import time
+from PyQt5 import QtWidgets, QtGui, QtCore
+import sys
+from functools import partial
+from lollms.personality import AIPersonality
+from typing import List
+def list_personalities(processor:APScript, client:Client):
+    members:List[AIPersonality] = processor.personality.app.mounted_personalities
+    collective_infos = "Members information:\n"
+    for i,drone in enumerate(members):
+        if drone.name!=processor.personality.name:
+            collective_infos +=  f"member id: {i}\n"
+            collective_infos +=  f"member name: {drone.name}\n"
+            collective_infos +=  f"member description: {drone.personality_description[:126]}...\n"
+    return collective_infos
+
+
+def list_personalities_function(processor, client):
+        return {
+                "function_name": "list_personalities",
+                "function": partial(list_personalities, processor=processor, client=client),
+                "function_description": "Lists the mounted ersonalities in the current sessions.",
+                "function_parameters": [] 
+            }

lollms/functions/summon_personality.py

@@ -0,0 +1,33 @@
+from lollms.utilities import PackageManager, find_first_available_file_index, discussion_path_to_url
+from lollms.client_session import Client
+from lollms.personality import APScript
+if not PackageManager.check_package_installed("pyautogui"):
+    PackageManager.install_package("pyautogui")
+if not PackageManager.check_package_installed("PyQt5"):
+    PackageManager.install_package("PyQt5")
+from ascii_colors import trace_exception
+import cv2
+import time
+from PyQt5 import QtWidgets, QtGui, QtCore
+import sys
+from functools import partial
+from lollms.personality import AIPersonality
+from typing import List
+
+def summon_personality(member_id:int, prompt: str, previous_discussion_text:str, context_details, callback, processor:APScript, client:Client):
+    members:List[AIPersonality] = processor.personality.app.mounted_personalities
+    processor.personality.app.personality = members[member_id]
+    members[member_id].callback=callback
+    members[member_id].new_message("")
+    processor.personality.app.handle_generate_msg(client.client_id, {"prompt":prompt})
+    processor.personality.app.personality = processor.personality
+    return "Execution done"
+
+
+def summon_personality_function(processor, callback, previous_discussion_text, context_details, client):
+        return {
+                "function_name": "summon_personality",
+                "function": partial(summon_personality, previous_discussion_text=previous_discussion_text, callback=callback, processor=processor, context_details=context_details, client=client),
+                "function_description": "Summon a personality by id and prompting it to do something.",
+                "function_parameters": [{"name": "member_id", "type": "int"},{"name": "prompt", "type": "str"}] 
+            }

lollms/personality.py

@@ -3284,7 +3284,7 @@ The AI should respond in this format using data from actions_list:
 
 
 
-    def generate_with_function_calls(self, prompt: str, functions: List[Dict[str, Any]], max_answer_length: Optional[int] = None) -> List[Dict[str, Any]]:
+    def generate_with_function_calls(self, prompt: str, functions: List[Dict[str, Any]], max_answer_length: Optional[int] = None, callback = None) -> List[Dict[str, Any]]:
         """
         Performs text generation with function calls.
 
@@ -3300,7 +3300,7 @@ The AI should respond in this format using data from actions_list:
         upgraded_prompt = self._upgrade_prompt_with_function_info(prompt, functions)
 
         # Generate the initial text based on the upgraded prompt.
-        generated_text = self.fast_gen(upgraded_prompt, max_answer_length)
+        generated_text = self.fast_gen(upgraded_prompt, max_answer_length, callback=callback)
 
         # Extract the function calls from the generated text.
         function_calls = self.extract_function_calls_as_json(generated_text)
@@ -3308,7 +3308,7 @@ The AI should respond in this format using data from actions_list:
         return generated_text, function_calls
 
 
-    def generate_with_function_calls_and_images(self, prompt: str, images:list, functions: List[Dict[str, Any]], max_answer_length: Optional[int] = None) -> List[Dict[str, Any]]:
+    def generate_with_function_calls_and_images(self, prompt: str, images:list, functions: List[Dict[str, Any]], max_answer_length: Optional[int] = None, callback = None) -> List[Dict[str, Any]]:
         """
         Performs text generation with function calls.
 
@@ -3324,7 +3324,7 @@ The AI should respond in this format using data from actions_list:
         upgraded_prompt = self._upgrade_prompt_with_function_info(prompt, functions)
 
         # Generate the initial text based on the upgraded prompt.
-        generated_text = self.fast_gen_with_images(upgraded_prompt, images, max_answer_length)
+        generated_text = self.fast_gen_with_images(upgraded_prompt, images, max_answer_length, callback=callback)
 
         # Extract the function calls from the generated text.
         function_calls = self.extract_function_calls_as_json(generated_text)
@@ -3435,19 +3435,24 @@ The AI should respond in this format using data from actions_list:
         return function_calls
 
 
-    def interact_with_function_call(self, prompt, function_definitions, prompt_after_execution=True):
+    def interact_with_function_call(self, prompt, function_definitions, prompt_after_execution=True, callback = None):
         if len(self.personality.image_files)>0:
-            out, function_calls = self.generate_with_function_calls_and_images(prompt, self.personality.image_files, function_definitions)
+            out, function_calls = self.generate_with_function_calls_and_images(prompt, self.personality.image_files, function_definitions, callback=callback)
         else:
-            out, function_calls = self.generate_with_function_calls(prompt, function_definitions)
+            out, function_calls = self.generate_with_function_calls(prompt, function_definitions, callback=callback)
+        if len(function_calls)>0:
+            outputs = self.execute_function_calls(function_calls,function_definitions)
+            out += "\n!@>function calls results:\n" + "\n".join([str(o) for o in outputs])
+            if prompt_after_execution:
+                prompt += out +"\n"+ "!@>"+self.personality.name+":"
+                if len(self.personality.image_files)>0:
+                    out, function_calls = self.generate_with_function_calls_and_images(prompt, self.personality.image_files, function_definitions, callback=callback)
+                else:
+                    out, function_calls = self.generate_with_function_calls(prompt, function_definitions, callback=callback)
                 if len(function_calls)>0:
                     outputs = self.execute_function_calls(function_calls,function_definitions)
                     out += "\n!@>function calls results:\n" + "\n".join([str(o) for o in outputs])
                     prompt += out +"\n"+ "!@>"+self.personality.name+":"
-            if len(self.personality.image_files)>0:
-                out, function_calls = self.generate_with_function_calls_and_images(prompt, self.personality.image_files, function_definitions)
-            else:
-                out, function_calls = self.generate_with_function_calls(prompt, function_definitions)
         return out
 
     #Helper method to convert outputs path to url

lollms/services/xtts/lollms_xtts.py

@@ -321,6 +321,7 @@ class LollmsXTTS(LollmsTTS):
         text = re.sub(r'`.*?`', '', text)
         # Remove any remaining code-like patterns (this can be adjusted as needed)
         text = re.sub(r'[\{\}\[\]\(\)<>]', '', text)  
+        text = text.replace("\\","")      
         def tts2_audio_th(thread_uid=None):
             url = f"{self.xtts_base_url}/tts_to_audio"