add openai

README.md

@@ -20,6 +20,12 @@ pip install git+https://github.com/aniketmaurya/agents.git@main
   pip install -e .
 ```
 
+## Supported LLMs
+
+✅ OpenAI
+✅ Cohere Command R and Command R+
+✅ LlamaCPP
+
 ## Usage/Examples
 
 ### Simple tool use with a local or cloud LLM

src/agents/llms/__init__.py

@@ -1,3 +1,5 @@
 from .llm import create_tool_use_llm
+from ._openai import OpenAIChatCompletion
+from ._cohere import CohereChatCompletion
 
-__all__ = ["create_tool_use_llm"]
+__all__ = ["create_tool_use_llm", "CohereChatCompletion", "OpenAIChatCompletion"]

src/agents/llms/_cohere.py

@@ -51,32 +51,6 @@ def _format_cohere_to_openai(self, output: AIMessage):
         }
         return ChatCompletion(**response)
 
-    # def _format_cohere_to_openai(self, output: NonStreamedChatResponse):
-    #     _tool_calls = output.tool_calls
-    #     tool_calls = []
-    #     for tool in _tool_calls:
-    #         tool = ToolCall(id=tool["id"], type=tool["type"], function=tool["function"])
-    #         tool_calls.append(tool)
-    #
-    #     message = Message(
-    #         role="assistant", content=output.text, tool_calls=tool_calls
-    #     )
-    #     choices = Choice(index=0, logprobs=None, message=message, finish_reason=output.finish_reason)
-    #     usage = Usage(
-    #         prompt_tokens=output.meta.tokens.input_tokens,
-    #         completion_tokens=output.meta.tokens.output_tokens,
-    #         total_tokens=(output.meta.tokens.input_tokens + output.meta.tokens.output_tokens),
-    #     )
-    #     response = {
-    #         "id": output.generation_id,
-    #         "object": "",
-    #         "created": int(time.time()),
-    #         "model": "Cohere",
-    #         "choices": [choices],
-    #         "usage": usage,
-    #     }
-    #     return ChatCompletion(**response)
-
     def chat_completion(
         self, messages: List[ChatCompletionRequestMessage], **kwargs
     ) -> ChatCompletion:

src/agents/llms/_openai.py

@@ -0,0 +1,34 @@
+from typing import List, Optional, Any, Dict
+
+import logging
+from agents.specs import ChatCompletion
+from agents.tool_executor import ToolRegistry
+from langchain_core.tools import StructuredTool
+from llama_cpp import ChatCompletionRequestMessage
+from openai import OpenAI
+
+logger = logging.getLogger(__name__)
+
+
+class OpenAIChatCompletion:
+    def __init__(self, model: str = "gpt-4o"):
+        self.model = model
+        self.client = OpenAI()
+        self.tool_registry = ToolRegistry()
+
+    def bind_tools(self, tools: Optional[List[StructuredTool]] = None):
+        for tool in tools:
+            self.tool_registry.register_tool(tool)
+
+    def chat_completion(
+        self, messages: List[ChatCompletionRequestMessage], **kwargs
+    ) -> ChatCompletion:
+        tools = self.tool_registry.openai_tools
+        output = self.client.chat.completions.create(
+            model=self.model, messages=messages, tools=tools
+        )
+        logger.debug(output)
+        return output
+
+    def run_tools(self, chat_completion: ChatCompletion) -> List[Dict[str, Any]]:
+        return self.tool_registry.call_tools(chat_completion)