agent: ditch openai dependency, use cache_prompt and expose seed

examples/agent/requirements.txt

@@ -1,7 +1,6 @@
 aiohttp
 fastapi
 ipython
-openai
 pydantic
 typer
 uvicorn

examples/agent/run.py

@@ -3,7 +3,6 @@
 # dependencies = [
 #     "aiohttp",
 #     "fastapi",
-#     "openai",
 #     "pydantic",
 #     "typer",
 #     "uvicorn",
@@ -13,8 +12,6 @@ import json
 import asyncio
 import aiohttp
 from functools import wraps
-from openai import AsyncOpenAI
-from openai.types.chat import ChatCompletionMessageParam, ChatCompletionToolMessageParam, ChatCompletionUserMessageParam
 from pydantic import BaseModel
 import sys
 import typer
@@ -141,51 +138,60 @@ async def main(
     tools: Optional[list[str]] = None,
     max_iterations: Optional[int] = 10,
     verbose: bool = False,
+    cache_prompt: bool = True,
+    seed: Optional[int] = None,
     endpoint: str = "http://localhost:8080/v1/",
 ):
-    client = AsyncOpenAI(api_key=api_key, base_url=endpoint)
-
     tool_map, tools = await discover_tools(tools or [], verbose)
 
     sys.stdout.write(f'🛠️  {", ".join(tool_map.keys())}\n')
 
-    messages: list[ChatCompletionMessageParam] = [
-        ChatCompletionUserMessageParam(
+    messages = [
+        dict(
             role="user",
             content=goal,
         )
     ]
 
-    async with aiohttp.ClientSession() as session:
+    headers = {
+        'Authorization': f'Bearer {api_key}'
+    }
+    async with aiohttp.ClientSession(headers=headers) as session:
         for i in range(max_iterations or sys.maxsize):
-            response = await client.chat.completions.create(
-                model="gpt-4o",
+            url = f'{endpoint}chat/completions'
+            payload = dict(
                 messages=messages,
+                model="gpt-4o",
                 tools=tools,
+                seed=seed,
+                cache_prompt=cache_prompt,
             )
+            async with session.post(url, json=payload) as response:
+                if verbose:
+                    sys.stderr.write(f'# RESPONSE: {response}\n')
+                response.raise_for_status()
+                response = await response.json()
 
-            if verbose:
-                sys.stderr.write(f'# RESPONSE: {response}\n')
+            assert len(response["choices"]) == 1
+            choice = response["choices"][0]
 
-            assert len(response.choices) == 1
-            choice = response.choices[0]
-
-            content = choice.message.content
-            if choice.finish_reason == "tool_calls":
-                messages.append(choice.message) # type: ignore
-                assert choice.message.tool_calls
-                for tool_call in choice.message.tool_calls:
+            content = choice['message']['content']
+            if choice['finish_reason'] == "tool_calls":
+                messages.append(choice['message'])
+                assert choice['message']['tool_calls']
+                for tool_call in choice['message']['tool_calls']:
                     if content:
                         print(f'💭 {content}')
 
-                    args = json.loads(tool_call.function.arguments)
-                    pretty_call = f'{tool_call.function.name}({", ".join(f"{k}={v.model_dump_json() if isinstance(v, BaseModel) else json.dumps(v)}" for k, v in args.items())})'
+                    name = tool_call['function']['name']
+                    args = json.loads(tool_call['function']['arguments'])
+                    pretty_call = f'{name}({", ".join(f"{k}={v.model_dump_json() if isinstance(v, BaseModel) else json.dumps(v)}" for k, v in args.items())})'
                     sys.stdout.write(f'⚙️  {pretty_call}')
                     sys.stdout.flush()
-                    tool_result = await tool_map[tool_call.function.name](session, **args)
+                    tool_result = await tool_map[name](session, **args)
                     sys.stdout.write(f" → {tool_result}\n")
-                    messages.append(ChatCompletionToolMessageParam(
-                        tool_call_id=tool_call.id,
+                    messages.append(dict(
+                        tool_call_id=tool_call.get('id'),
                         role="tool",
                         content=json.dumps(tool_result),
                     ))