diff --git a/ai_providers.py b/ai_providers.py
new file mode 100644
index 0000000..957e0e2
--- /dev/null
+++ b/ai_providers.py
@@ -0,0 +1,100 @@
+import os
+import json
+import anthropic
+from openai import OpenAI
+from abc import ABC, abstractmethod
+
+class AIProvider(ABC):
+    @abstractmethod
+    def get_chat_response(self, messages):
+        pass
+
+    @abstractmethod
+    def format_messages(self, messages):
+        pass
+
+    @abstractmethod
+    def format_tool_calls(self, response):
+        pass
+
+class AnthropicProvider(AIProvider):
+    def __init__(self):
+        self.client = anthropic.Anthropic(
+            api_key=os.environ.get("ANTHROPIC_API_KEY"),
+            default_headers={"anthropic-beta": "max-tokens-3-5-sonnet-2024-07-15"}
+        )
+        self.model = "claude-3-5-sonnet-20240620"
+
+    def get_chat_response(self, messages):
+        try:
+            response = self.client.messages.create(
+                model=self.model,
+                system=messages[0]['content'],
+                messages=self.format_messages(messages[1:]),
+                max_tokens=8192,
+                tools=self.format_tools()
+            )
+            return response
+        except Exception as e:
+            logging.error(f"An error occurred: {str(e)}")
+            return None
+
+    def format_messages(self, messages):
+        return messages
+
+    def format_tool_calls(self, response):
+        tool_calls = []
+        for message in response.content:
+            if message.type == "tool_use":
+                tool_calls.append(message)
+        return tool_calls
+
+    def format_tools(self):
+        return [
+            {
+                "name": function['name'],
+                "description": function['description'],
+                "input_schema": function['parameters'] if function['parameters'] not in [None, {}] else {"type": "object", "properties": {"param1": {"type": "string", "description": "Unnecessary"}}, "required": []}
+            }
+            for function in functions  # This assumes 'functions' is globally accessible
+        ]
+
+class OpenAIProvider(AIProvider):
+    def __init__(self, use_smart_model=True):
+        self.client = OpenAI()
+        self.use_smart_model = use_smart_model
+        self.model = self.get_model()
+
+    def get_model(self):
+        return "gpt-4o" if self.use_smart_model else "gpt-4o-mini"
+
+    def get_chat_response(self, messages):
+        response = self.client.chat.completions.create(
+            model=self.model,
+            messages=self.format_messages(messages),
+            functions=functions,  # This assumes 'functions' is globally accessible
+            function_call="auto",
+            max_tokens=self.get_max_tokens()
+        )
+        return response
+
+    def format_messages(self, messages):
+        return messages
+
+    def format_tool_calls(self, response):
+        tool_calls = []
+        assistant_message = response.choices[0].message
+        if hasattr(assistant_message, 'function_call') and assistant_message.function_call is not None:
+            tool_calls.append(assistant_message.function_call)
+        return tool_calls
+
+    def get_max_tokens(self):
+        return 4096 if self.model == "gpt-4o" else 16384
+
+def create_ai_provider(provider_name="anthropic", use_smart_model=True):
+    if provider_name.lower() == "anthropic":
+        return AnthropicProvider()
+    elif provider_name.lower() == "openai":
+        return OpenAIProvider(use_smart_model)
+    else:
+        raise ValueError(f"Unknown provider: {provider_name}")
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