update tool test

tests/test_toolcall.py

@@ -1,46 +1,55 @@
+import json
 import os
+from typing import Sequence
 
 from openai import OpenAI
 
 
-os.environ["OPENAI_BASE_URL"] = "http://192.168.5.193:8000/v1"
+os.environ["OPENAI_BASE_URL"] = "http://192.168.0.1:8000/v1"
 os.environ["OPENAI_API_KEY"] = "0"
 
 
+def calculate_gpa(grades: Sequence[str], hours: Sequence[int]) -> float:
+    grade_to_score = {"A": 4, "B": 3, "C": 2}
+    total_score, total_hour = 0, 0
+    for grade, hour in zip(grades, hours):
+        total_score += grade_to_score[grade] * hour
+        total_hour += hour
+    return total_score / total_hour
+
+
+tool_map = {"calculate_gpa": calculate_gpa}
+
+
 if __name__ == "__main__":
     client = OpenAI()
     tools = [
         {
             "type": "function",
             "function": {
-                "name": "get_current_weather",
+                "name": "calculate_gpa",
-                "description": "Get the current weather in a given location",
+                "description": "Calculate the Grade Point Average (GPA) based on grades and credit hours",
                 "parameters": {
                     "type": "object",
                     "properties": {
-                        "location": {"type": "string", "description": "The city and state, e.g. San Francisco, CA"}
+                        "grades": {"type": "array", "items": {"type": "string"}, "description": "The grades"},
+                        "hours": {"type": "array", "items": {"type": "integer"}, "description": "The credit hours"},
                     },
-                    "required": ["location"],
+                    "required": ["grades", "hours"],
                 },
             },
         }
     ]
-    result = client.chat.completions.create(
+    messages = []
-        messages=[{"role": "user", "content": "What is the weather like in Boston?"}],
+    messages.append({"role": "user", "content": "My grades are A, A, B, and C. The credit hours are 3, 4, 3, and 2."})
-        model="gpt-3.5-turbo",
+    result = client.chat.completions.create(messages=messages, model="test", tools=tools)
-        tools=tools,
+    tool_call = result.choices[0].message.tool_calls[0].function
+    name, arguments = tool_call.name, json.loads(tool_call.arguments)
+    messages.append(
+        {"role": "function", "content": json.dumps({"name": name, "argument": arguments}, ensure_ascii=False)}
     )
-    print(result.choices[0].message)
+    tool_result = tool_map[name](**arguments)
-    result = client.chat.completions.create(
+    messages.append({"role": "tool", "content": json.dumps({"gpa": tool_result}, ensure_ascii=False)})
-        messages=[
+    result = client.chat.completions.create(messages=messages, model="test", tools=tools)
-            {"role": "user", "content": "What is the weather like in Boston?"},
+    print(result.choices[0].message.content)
-            {
+    # Based on your grades and credit hours, your calculated Grade Point Average (GPA) is 3.4166666666666665.
-                "role": "function",
-                "content": """{"name": "get_current_weather", "arguments": {"location": "Boston, MA"}}""",
-            },
-            {"role": "tool", "content": '{"temperature": 22, "unit": "celsius", "description": "Sunny"}'},
-        ],
-        model="gpt-3.5-turbo",
-        tools=tools,
-    )
-    print(result.choices[0].message)