Modularizing everything; attacking ui_utils behemoth; fundamental rew…

…rite starting with skills/tools; see Discord...

AutoGroq/agent_management.py

@@ -42,7 +42,7 @@ def construct_request(agent_name, description, user_request, user_input, rephras
 
 
 def display_agents():
-    if "agents" in st.session_state and st.session_state.agents:
+    if "agents" in st.session_state and st.session_state.agents and len(st.session_state.agents) > 0:
         st.sidebar.title("Your Agents")
         st.sidebar.subheader("Click to interact")
         display_agent_buttons(st.session_state.agents)
@@ -201,7 +201,7 @@ def process_agent_interaction(agent_index):
     llm_provider = get_llm_provider(api_key=api_key)
     llm_request_data = {
         "model": st.session_state.model,
-        "temperature": st.session_state.get('temperature', 0.1),
+        "temperature": st.session_state.temperature,
         "max_tokens": st.session_state.max_tokens,
         "top_p": 1,
         "stop": "TERMINATE",
@@ -245,7 +245,7 @@ def regenerate_agent_description(agent):
     llm_provider = get_llm_provider(api_key=api_key)
     llm_request_data = {
         "model": st.session_state.model,
-        "temperature": st.session_state.get('temperature', 0.1),
+        "temperature": st.session_state.temperature,
         "max_tokens": st.session_state.max_tokens,
         "top_p": 1,
         "stop": "TERMINATE",

AutoGroq/cli/create_agent.py

@@ -3,6 +3,7 @@
 import datetime
 import json
 import os
+import streamlit as st
 import sys
 
 # Add the root directory to the Python module search path
@@ -11,8 +12,9 @@
 from config import MODEL_TOKEN_LIMITS
 from prompts import get_agent_prompt
 from utils.api_utils import get_llm_provider
+from utils.agent_utils import create_agent_data
 from utils.auth_utils import get_api_key
-from utils.file_utils import create_agent_data, sanitize_text
+from utils.file_utils import sanitize_text
 
 def create_agent(request, provider, model, temperature, max_tokens, output_file):
     # Get the API key and provider
@@ -28,7 +30,7 @@ def create_agent(request, provider, model, temperature, max_tokens, output_file)
     # Make the request to the LLM API
     llm_request_data = {
         "model": model,
-        "temperature": temperature,
+        "temperature": st.session_state.temperature,
         "max_tokens": max_tokens,
         "messages": [{"role": "user", "content": prompt}],
     }

AutoGroq/config.py

@@ -74,8 +74,8 @@
 
 
 # Database path
-# AUTOGEN_DB_PATH="/path/to/custom/database.sqlite"
-AUTOGEN_DB_PATH = os.environ.get('AUTOGEN_DB_PATH', default_db_path)
+# FRAMEWORK_DB_PATH="/path/to/custom/database.sqlite"
+FRAMEWORK_DB_PATH = os.environ.get('FRAMEWORK_DB_PATH', default_db_path)
 
 MODEL_CHOICES = {
     'default': None,

AutoGroq/config_local.py.example

@@ -81,8 +81,8 @@ else:
 
 
 # Database path
-# AUTOGEN_DB_PATH="/path/to/custom/database.sqlite"
-AUTOGEN_DB_PATH = os.environ.get('AUTOGEN_DB_PATH', default_db_path)
+# FRAMEWORK_DB_PATH="/path/to/custom/database.sqlite"
+FRAMEWORK_DB_PATH = os.environ.get('FRAMEWORK_DB_PATH', default_db_path)
 
 MODEL_CHOICES = {
     'default': None,

AutoGroq/llm_providers/lmstudio_provider.py

@@ -36,7 +36,7 @@ def send_request(self, data):
         lm_studio_request_data = {
             "model": data["model"],
             "messages": data["messages"],
-            "temperature": data.get("temperature", 0.1),
+            "temperature": st.session_state.temperature,
             "max_tokens": data.get("max_tokens", 2048),
             "stop": data.get("stop", "TERMINATE"),
         }

AutoGroq/llm_providers/ollama_provider.py

@@ -37,7 +37,7 @@ def send_request(self, data):
         ollama_request_data = {
             "model": data["model"],
             "prompt": data["messages"][0]["content"],
-            "temperature": data.get("temperature", 0.1),
+            "temperature": st.session_state.temperature,
             "max_tokens": data.get("max_tokens", 2048),
             "stop": data.get("stop", "TERMINATE"),
             "stream": False,