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upgraded core

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This commit is contained in:
Saifeddine ALOUI 2024-03-15 01:28:58 +01:00
parent 89102b9c01
commit e25e84ae31
5 changed files with 104 additions and 17 deletions
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4
configs/config.yaml
View File

@ -1,5 +1,5 @@
# =================== Lord Of Large Language Multimodal Systems Configuration file ===========================
version: 74
version: 75
binding_name: null
model_name: null
model_variant: null
@ -26,8 +26,8 @@ port: 9600
# Genreration parameters
discussion_prompt_separator: "!@>"
seed: -1
n_predict: 1024
ctx_size: 4084
max_n_predict: 4096
min_n_predict: 512
temperature: 0.9
top_k: 50

35
lollms/app.py
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@ -493,7 +493,7 @@ class LollmsApplication(LoLLMsCom):
ASCIIColors.info(f"Deleted file: {file_path}")
# -------------------------------------- Prompt preparing
def prepare_query(self, client_id: str, message_id: int = -1, is_continue: bool = False, n_tokens: int = 0, generation_type = None) -> Tuple[str, str, List[str]]:
def prepare_query(self, client_id: str, message_id: int = -1, is_continue: bool = False, n_tokens: int = 0, generation_type = None, force_using_internet=False) -> Tuple[str, str, List[str]]:
"""
Prepares the query for the model.
@ -563,19 +563,19 @@ class LollmsApplication(LoLLMsCom):
discussion = None
if generation_type != "simple_question":
if self.config.activate_internet_search:
if self.config.activate_internet_search or force_using_internet or generation_type == "full_context_with_internet":
if discussion is None:
discussion = self.recover_discussion(client_id)
if self.config.internet_activate_search_decision:
self.personality.step_start(f"Requesting if {self.personality.name} needs to search internet to answer the user")
need = not self.personality.yes_no(f"Do you have enough information to give a satisfactory answer to {self.config.user_name}'s request without internet search? (If you do not know or you can't answer 0 (no)", discussion)
need = not self.personality.yes_no(f"!@>system: Answer the question with yes or no. Don't add any extra explanation.\n!@>user: Do you have enough information to give a satisfactory answer to {self.config.user_name}'s request without internet search? (If you do not know or you can't answer 0 (no)", discussion)
self.personality.step_end(f"Requesting if {self.personality.name} needs to search internet to answer the user")
self.personality.step("Yes" if need else "No")
else:
need=True
if need:
self.personality.step_start("Crafting internet search query")
query = self.personality.fast_gen(f"!@>discussion:\n{discussion[-2048:]}\n!@>system: Read the discussion and craft a web search query suited to recover needed information to reply to last {self.config.user_name} message.\nDo not answer the prompt. Do not add explanations.\n!@>websearch query: ", max_generation_size=256, show_progress=True, callback=self.personality.sink)
query = self.personality.fast_gen(f"!@>discussion:\n{discussion[-2048:]}\n!@>system: Read the discussion and craft a web search query suited to recover needed information to reply to last {self.config.user_name} message.\nDo not answer the prompt. Do not add explanations.\n!@>current date: {datetime.now()}!@>websearch query: ", max_generation_size=256, show_progress=True, callback=self.personality.sink)
self.personality.step_end("Crafting internet search query")
self.personality.step(f"web search query: {query}")
@ -628,16 +628,25 @@ class LollmsApplication(LoLLMsCom):
except:
self.warning("Couldn't add documentation to the context. Please verify the vector database")
# Check if there is discussion knowledge to add to the prompt
if self.config.activate_skills_lib and self.long_term_memory is not None:
if knowledge=="":
knowledge="!@>knowledge:\n"
if self.config.activate_skills_lib:
try:
docs, sorted_similarities, document_ids = self.long_term_memory.recover_text(current_message.content, top_k=self.config.data_vectorization_nb_chunks)
for i,(doc, infos) in enumerate(zip(docs, sorted_similarities)):
knowledge += f"!@>knowledge {i}:\n!@>title:\n{infos[0]}\ncontent:\n{doc}"
except:
self.personality.step_start("Building skills library")
if discussion is None:
discussion = self.recover_discussion(client_id)
query = self.personality.fast_gen(f"!@>discussion:\n{discussion[-2048:]}\n!@>system: Read the discussion and craft a short skills database search query suited to recover needed information to reply to last {self.config.user_name} message.\nDo not answer the prompt. Do not add explanations.\n!@>search query: ", max_generation_size=256, show_progress=True, callback=self.personality.sink)
# skills = self.skills_library.query_entry(query)
skills = self.skills_library.query_entry_fts(query)
if len(query)>0:
if knowledge=="":
knowledge=f"!@>knowledge:\n!@>instructions: Use the knowledge to answer {self.config.user_name}'s message. If you don't have enough information or you don't know how to answer, just say you do not know.\n"
for i,(category, title, content) in enumerate(skills):
knowledge += f"!@>knowledge {i}:\n!@>category:\n{category}\n!@>title:\n{title}\ncontent:\n{content}"
self.personality.step_end("Building skills library")
except Exception as ex:
ASCIIColors.error(ex)
self.warning("Couldn't add long term memory information to the context. Please verify the vector database") # Add information about the user
self.personality.step_end("Building skills library",False)
user_description=""
if self.config.use_user_informations_in_discussion:
user_description="!@>User description:\n"+self.config.user_description+"\n"
@ -687,7 +696,7 @@ class LollmsApplication(LoLLMsCom):
total_tokens = n_cond_tk + n_isearch_tk + n_doc_tk + n_history_tk + n_user_description_tk + n_positive_boost + n_negative_boost + n_force_language + n_fun_mode
# Calculate the available space for the messages
available_space = self.config.ctx_size - n_tokens - total_tokens
available_space = min(self.config.ctx_size - n_tokens - total_tokens, self.config.max_n_predict)
# if self.config.debug:
# self.info(f"Tokens summary:\nConditionning:{n_cond_tk}\nn_isearch_tk:{n_isearch_tk}\ndoc:{n_doc_tk}\nhistory:{n_history_tk}\nuser description:{n_user_description_tk}\nAvailable space:{available_space}",10)

4
lollms/configs/config.yaml
View File

@ -1,5 +1,5 @@
# =================== Lord Of Large Language Multimodal Systems Configuration file ===========================
version: 74
version: 75
binding_name: null
model_name: null
model_variant: null
@ -26,8 +26,8 @@ port: 9600
# Genreration parameters
discussion_prompt_separator: "!@>"
seed: -1
n_predict: 1024
ctx_size: 4084
max_n_predict: 4096
min_n_predict: 512
temperature: 0.9
top_k: 50

24
lollms/databases/skills_database.py
View File

@ -25,6 +25,7 @@ class SkillsLibrary:
""")
cursor.execute("SELECT version FROM db_info")
version = cursor.fetchone()
self._create_fts_table() # Create FTS table after initializing the database
if version is None:
cursor.execute("INSERT INTO db_info (version) VALUES (1)")
conn.commit()
@ -35,6 +36,16 @@ class SkillsLibrary:
conn.close()
self._migrate_db(version[0])
def _create_fts_table(self):
conn = sqlite3.connect(self.db_path)
cursor = conn.cursor()
cursor.execute("""
CREATE VIRTUAL TABLE IF NOT EXISTS skills_library_fts USING fts5(category, title, content)
""")
conn.commit()
cursor.close()
conn.close()
def _migrate_db(self, version):
conn = sqlite3.connect(self.db_path)
cursor = conn.cursor()
@ -95,6 +106,19 @@ class SkillsLibrary:
conn.close()
return res
def query_entry_fts(self, text):
conn = sqlite3.connect(self.db_path)
cursor = conn.cursor()
# Use direct string concatenation for the MATCH expression.
# Ensure text is safely escaped to avoid SQL injection.
query = "SELECT * FROM skills_library_fts WHERE skills_library_fts MATCH ?"
cursor.execute(query, (text,))
res = cursor.fetchall()
cursor.close()
conn.close()
return res
def remove_entry(self, id):
conn = sqlite3.connect(self.db_path)
cursor = conn.cursor()

54
lollms/utilities.py
View File

@ -39,6 +39,8 @@ import git
import mimetypes
import subprocess
from functools import partial
def create_conda_env(env_name, python_version):
from conda.cli.python_api import run_command, Commands
# Create a new Conda environment with the specified Python version
@ -148,6 +150,58 @@ def yes_or_no_input(prompt):
else:
print("Please enter 'yes' or 'no'.")
def show_console_custom_dialog(title, text, options):
print(title)
print(text)
for i, option in enumerate(options, 1):
print(f"{i}. {option}")
while True:
try:
choice = int(input("Enter the number of your choice: "))
if 1 <= choice <= len(options):
return options[choice - 1]
else:
print("Invalid choice. Please try again.")
except ValueError:
print("Invalid input. Please enter a number.")
def show_custom_dialog(title, text, options):
try:
import tkinter as tk
from tkinter import simpledialog
class CustomDialog(simpledialog.Dialog):
def __init__(self, parent, title, options, root):
self.options = options
self.root = root
self.buttons = []
self.result_value = ""
super().__init__(parent, title)
def do_ok(self, option):
self.result_value = option
self.ok(option)
self.root.destroy()
def body(self, master):
for option in self.options:
button = tk.Button(master, text=option, command=partial(self.do_ok, option))
button.pack(side="left", fill="x")
self.buttons.append(button)
def apply(self):
self.result = self.options[0] # Default value
root = tk.Tk()
root.withdraw()
root.attributes('-topmost', True)
d = CustomDialog(root, title=title, options=options, root=root)
try:
d.mainloop()
except Exception as ex:
pass
result = d.result_value
return result
except Exception as ex:
ASCIIColors.error(ex)
return show_console_custom_dialog(title, text, options)
def show_yes_no_dialog(title, text):
try:
import tkinter as tk