feat: ✨ Weather is in

main.py

@@ -7,41 +7,103 @@ 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"  # default LM Studio endpoint
+EXIT_STRINGS = ['exit','goodbye','go away','fuck off']
+
 console = Console()
 
-def ask_name() -> str:
-    """Ask for a name and keep asking until it's not empty."""
+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}
+    }
+  ]
+}'''
+#   "parameters": {
+#     "type": "object",
+#     "properties": {
+#       "city": {"type": "string", "description": "City name"},
+#     },
+#     "required": ["city"]
+#   },
+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():
     while True:
-        name = Prompt.ask("[bold cyan]What is your name?[/]")
-        if name.strip():
-            return name.strip()
-        console.print("[red]Name cannot be empty![/]", style="bold")
+        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 ask_age() -> int:
-    """Ask for age and validate it's a positive integer."""
+def handle_llm_reply(llm_reply:str):
+    architect = ToolExecutor()
+    return architect.process_llm_response(llm_output=llm_reply)
+
+def main():
     while True:
-        age_str = Prompt.ask("[bold cyan]How old are you?[/]")
-        try:
-            age = int(age_str)
-            if age <= 0:
-                raise ValueError
-            return age
-        except ValueError:
-            console.print("[red]Please enter a valid positive integer.[/]", style="bold")
+        llm_prompt = get_llm_prompt()
+        if llm_prompt.lower() in 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)
 
-name = ask_name()
-age = ask_age()
+        if handled_response != llm_reply:
+            output = ask_model_no_pre(prompt=f'Make this lovely markdown, use fun emojis {handled_response}')
 
-panel_narrow = Panel(
-    f"[bold green]Your Name is: {name}[/bold green]\n"
-    f"[blue]And you are {age} Years Old.[/blue]",
-    title="About You",
-    subtitle="The info you gave",
-    expand=False,
-)
+        elif handled_response == llm_reply:
+            output = handled_response
+
+        elapsed = time.time() - start
+        panel_narrow = Panel(Markdown(output),
+            title="LLM Reply",
+            subtitle=f"Response time: {elapsed:.2f}s",
+            expand=False,
+        )
+
+        console.print(panel_narrow)
+
+if __name__ == "__main__":
+    main()
 
-console.print(panel_narrow)