end of project

main.py

@@ -5,28 +5,92 @@ from dotenv import load_dotenv
 from google import genai
 from google.genai import types
 
+from config import SYSTEM_PROMPT, MAX_ITERS
+from call_function import available_functions, call_function
+
 def main():
-    print("Hello from python-ai-agent!")
-    print('argv', sys.argv)
-    if len(sys.argv) < 2 or str(sys.argv[1]) == "--verbose":
+    load_dotenv()
+
+    verbose = "--verbose" in sys.argv
+    args = []
+    for arg in sys.argv[1:]:
+        if not arg.startswith("--"):
+            args.append(arg)
+
+    if not args:
+        print("AI Code Assistant")
+        print('\nUsage: python main.py "your prompt here" [--verbose]')
+        print('Example: python main.py "How do I fix the calculator?"')
         sys.exit(1)
 
-    load_dotenv()
     api_key = os.environ.get("GEMINI_API_KEY")
-
     client = genai.Client(api_key=api_key)
-    
+
+    user_prompt = " ".join(args)
+
+    if verbose:
+        print(f"User prompt: {user_prompt}\n")
+
     messages = [
-        types.Content(role="user", parts=[types.Part(text=sys.argv[1])]),
+        types.Content(role="user", parts=[types.Part(text=user_prompt)]),
     ]
 
-    response = client.models.generate_content(model="gemini-2.0-flash-001", contents=messages)
-    print(f"Response: {response.text}")
-    
-    if "--verbose" in sys.argv:
-        print(f"User prompt: {sys.argv[1]}")
-        print(f"Prompt tokens: {response.usage_metadata.prompt_token_count}")
-        print(f"Response tokens: {response.usage_metadata.candidates_token_count}")
+    iters = 0
+    while True:
+        iters += 1
+        if iters > MAX_ITERS:
+            print(f"Maximum iterations ({MAX_ITERS}) reached.")
+            sys.exit(1)
+
+        try:
+            final_response = generate_content(client, messages, verbose)
+            if final_response:
+                print("Final response:")
+                print(final_response)
+                break
+        except Exception as e:
+            print(f"Error in generate_content: {e}")
+
+    generate_content(client, messages, verbose)
+
+
+def generate_content(client, messages, verbose):
+    response = client.models.generate_content(
+        model="gemini-2.0-flash-001",
+        contents=messages,
+        config=types.GenerateContentConfig(
+            tools=[available_functions], system_instruction=SYSTEM_PROMPT
+        ),
+    )
+    if verbose:
+        print("Prompt tokens:", response.usage_metadata.prompt_token_count)
+        print("Response tokens:", response.usage_metadata.candidates_token_count)
+
+
+    if response.candidates:
+        for candidate in response.candidates:
+            function_call_content = candidate.content
+            messages.append(function_call_content)
+
+    if not response.function_calls:
+        return response.text
+
+    function_responses = []
+    for function_call_part in response.function_calls:
+        function_call_result = call_function(function_call_part, verbose)
+        if (
+            not function_call_result.parts
+            or not function_call_result.parts[0].function_response
+        ):
+            raise Exception("empty function call result")
+        if verbose:
+            print(f"-> {function_call_result.parts[0].function_response.response}")
+        function_responses.append(function_call_result.parts[0])
+
+    if not function_responses:
+        raise Exception("no function responses generated, exiting.")
+
+    messages.append(types.Content(role="user", parts=function_responses))
 
 if __name__ == "__main__":
     main()