feat: ✨ Working tool calls

o
	new file:   llm_interface.py

main.py

@@ -1,91 +1,51 @@
 from rich import print
 from rich.console import Console
-from rich.table import Table
 from rich.panel import Panel
-from rich.progress import Progress, SpinnerColumn, BarColumn, track
 from rich.markdown import Markdown
-from rich.syntax import Syntax
-from rich.live import Live
-from rich.prompt import Prompt
-import requests
-import sys
-from tools import ToolExecutor
-import random
-import time
 
-LM_STUDIO_URL = "http://127.0.0.1:1234/v1/chat/completions"
-EXIT_STRINGS = ['exit','goodbye','go away','fuck off']
+import sys
+
+import time
+import config
+from llm_interface import llm
+
+import logging
+
+#TODO: add context for llm calls so we have history and can chain messages
 
 console = Console()
 
-PRE_PROMPT = '''You have the following tools available, only use the tools if you need to.
-please reply with only the tool call if you need to
-{
-  "name": "get_weather",
-  "description": "Get current weather for a location",
-  "examples": [
-    {
-      "input": {"tool": "get_weather", "parameters":{"city":"New York"}},
-      "output": {"temperature": 22, "condition": "partly cloudy", "humidity": 65}
-    },
-    {
-      "input": {"tool": "get_weather", "parameters":{"city":"London"}},
-      "output": {"temperature": 18, "condition": "rainy", "humidity": 80}
-    }
-  ]
-}'''
+class RichConsoleHandler(logging.StreamHandler):
+    def emit(self, record):
+        if record.levelno >= logging.CRITICAL:
+            console.print(f"[bold magenta]CRITICAL:[/bold magenta] {record.getMessage()}")
+        elif record.levelno >= logging.ERROR:
+            console.print(f"[bold red]ERROR:[/bold red] {record.getMessage()}")
+        elif record.levelno >= logging.WARNING:
+            console.print(f"[bold yellow]WARNING:[/bold yellow] {record.getMessage()}")
+        # elif record.levelno >= logging.INFO:
+        #     console.print(f"[bold blue]INFO:[/bold blue] {record.getMessage()}")
+        # elif record.levelno >= logging.DEBUG:
+        #     console.print(f"[bold green]DEBUG:[/bold green] {record.getMessage()}")
 
-def ask_model(prompt: str, url=LM_STUDIO_URL) -> str:
-    payload = {
-        "model": 'qwen/qwen3-coder-30b',
-        "messages": [{"role": "user", "content": PRE_PROMPT+prompt}],
-        "temperature": 0.7,
-        "max_tokens": 2048,
-    }
-    resp = requests.post(url, json=payload)
-    resp.raise_for_status()
-    return resp.json()["choices"][0]["message"]["content"].strip()
-
-def ask_model_no_pre(prompt: str, url=LM_STUDIO_URL) -> str:
-    payload = {
-        #"model": 'qwen/qwen3-coder-30b',
-        "model": 'openai/gpt-oss-20b',
-        "messages": [{"role": "user", "content": prompt}],
-        "temperature": 0.7,
-        "max_tokens": 2048,
-    }
-    resp = requests.post(url, json=payload)
-    resp.raise_for_status()
-    return resp.json()["choices"][0]["message"]["content"].strip()
-
-def get_llm_prompt():
+            
+def main(logger):
+    logger.info('Application Started')
+    language_model = llm(logger)
     while True:
-        llm_prompt = Prompt.ask("[bold cyan]Ask your local llm[/]")
-        if llm_prompt.strip():
-            return llm_prompt.strip()
-        console.print("[red]Cannot be empty![/]", style="bold")
-        return llm_prompt
-
-def handle_llm_reply(llm_reply:str):
-    architect = ToolExecutor()
-    return architect.process_llm_response(llm_output=llm_reply)
-
-def main():
-    while True:
-        llm_prompt = get_llm_prompt()
-        if llm_prompt.lower() in EXIT_STRINGS:
+        llm_prompt = language_model.get_llm_prompt()
+        if llm_prompt.lower() in config.EXIT_STRINGS:
             sys.exit()
         start = time.time()
           
-        llm_reply = ask_model(llm_prompt)
-        print(llm_reply)
-        handled_response = handle_llm_reply(llm_reply)
-        print(handled_response)
-        print(handled_response == llm_reply)
+        llm_reply = language_model.ask_model(llm_prompt)
+        logger.info(f"LLM Reply: {llm_reply}")
+        handled_response = language_model.handle_llm_reply(llm_reply)
+        logger.info(f"Handled Response: {handled_response}")
+        logger.info(f"Response equals original: {handled_response == llm_reply}")
 
         if handled_response != llm_reply:
-            output = ask_model_no_pre(prompt=f'Make this lovely markdown, use fun emojis {handled_response}')
-
+            output = language_model.tool_response(prompt=f'Make this lovely markdown, use fun emojis {handled_response}')
         elif handled_response == llm_reply:
             output = handled_response
 
@@ -99,5 +59,21 @@ def main():
         console.print(panel_narrow)
 
 if __name__ == "__main__":
-    main()
+    # Setup logging with custom handler for warnings and errors
+    logging.basicConfig(
+        level=logging.DEBUG,
+        format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+        handlers=[
+            logging.FileHandler('app.log')
+        ]
+    )
+    
+    logger = logging.getLogger(__name__)
+    logger.addHandler(RichConsoleHandler())
+    logger.info("Logging Instantiated")
+    
+    main(logger)
+    
+
+