Add Azure OpenAI (#42)

* added api_key in init arg

* added azure openai

* added azure openai to modules

* fix for passing tests

* added azure openai to readme

* fixed typo

README.md

@@ -30,7 +30,8 @@ To get started, you can install the library using pip:
 pip install vision-agent
 ```
 
-Ensure you have an OpenAI API key and set it as an environment variable:
+Ensure you have an OpenAI API key and set it as an environment variable (if you are
+using Azure OpenAI please see the additional setup section):
 
 ```bash
 export OPENAI_API_KEY="your-api-key"
@@ -109,3 +110,23 @@ you. For example:
 
 
 It also has a basic set of calculate tools such as add, subtract, multiply and divide.
+
+### Additional Setup
+If you want to use Azure OpenAI models, you can set the environment variable:
+
+```bash
+export AZURE_OPENAI_API_KEY="your-api-key"
+export AZURE_OPENAI_ENDPOINT="your-endpoint"
+```
+
+You can then run Vision Agent using the Azure OpenAI models:
+
+```python
+>>> import vision_agent as va
+>>> agent = va.agent.VisionAgent(
+>>> task_model=va.llm.AzureOpenAILLM(),
+>>> answer_model=va.lmm.AzureOpenAILMM(),
+>>> reflection_model=va.lmm.AzureOpenAILMM(),
+>>> )
+```
+

vision_agent/llm/__init__.py

@@ -1 +1 @@
-from .llm import LLM, OpenAILLM
+from .llm import LLM, AzureOpenAILLM, OpenAILLM

vision_agent/llm/llm.py

@@ -1,8 +1,9 @@
 import json
+import os
 from abc import ABC, abstractmethod
-from typing import Any, Callable, Dict, List, Mapping, Union, cast
+from typing import Any, Callable, Dict, List, Mapping, Optional, Union, cast
 
-from openai import OpenAI
+from openai import AzureOpenAI, OpenAI
 
 from vision_agent.tools import (
  CHOOSE_PARAMS,
@@ -33,11 +34,16 @@ class OpenAILLM(LLM):
  def __init__(
  self,
  model_name: str = "gpt-4-turbo-preview",
+ api_key: Optional[str] = None,
  json_mode: bool = False,
  **kwargs: Any
  ):
+ if not api_key:
+ self.client = OpenAI()
+ else:
+ self.client = OpenAI(api_key=api_key)
+
  self.model_name = model_name
- self.client = OpenAI()
  self.kwargs = kwargs
  if json_mode:
  self.kwargs["response_format"] = {"type": "json_object"}
@@ -120,3 +126,32 @@ def generate_segmentor(self, question: str) -> Callable:
  ]
 
  return lambda x: GroundingSAM()(**{"prompt": params["prompt"], "image": x})
+
+
+class AzureOpenAILLM(OpenAILLM):
+ def __init__(
+ self,
+ model_name: str = "gpt-4-turbo-preview",
+ api_key: Optional[str] = None,
+ api_version: str = "2024-02-01",
+ azure_endpoint: Optional[str] = None,
+ json_mode: bool = False,
+ **kwargs: Any
+ ):
+ if not api_key:
+ api_key = os.getenv("AZURE_OPENAI_API_KEY")
+ if not azure_endpoint:
+ azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
+
+ if not api_key:
+ raise ValueError("Azure OpenAI API key is required.")
+ if not azure_endpoint:
+ raise ValueError("Azure OpenAI endpoint is required.")
+
+ self.client = AzureOpenAI(
+ api_key=api_key, api_version=api_version, azure_endpoint=azure_endpoint
+ )
+ self.model_name = model_name
+ self.kwargs = kwargs
+ if json_mode:
+ self.kwargs["response_format"] = {"type": "json_object"}

vision_agent/lmm/__init__.py

@@ -1 +1 @@
-from .lmm import LMM, LLaVALMM, OpenAILMM, get_lmm
+from .lmm import LMM, AzureOpenAILMM, LLaVALMM, OpenAILMM, get_lmm

vision_agent/lmm/lmm.py

@@ -1,12 +1,13 @@
 import base64
 import json
 import logging
+import os
 from abc import ABC, abstractmethod
 from pathlib import Path
 from typing import Any, Callable, Dict, List, Optional, Union, cast
 
 import requests
-from openai import OpenAI
+from openai import AzureOpenAI, OpenAI
 
 from vision_agent.tools import (
  CHOOSE_PARAMS,
@@ -99,12 +100,18 @@ class OpenAILMM(LMM):
  def __init__(
  self,
  model_name: str = "gpt-4-vision-preview",
+ api_key: Optional[str] = None,
  max_tokens: int = 1024,
  **kwargs: Any,
  ):
+ if not api_key:
+ self.client = OpenAI()
+ else:
+ self.client = OpenAI(api_key=api_key)
+
+ self.client = OpenAI(api_key=api_key)
  self.model_name = model_name
  self.max_tokens = max_tokens
- self.client = OpenAI()
  self.kwargs = kwargs
 
  def __call__(
@@ -248,6 +255,34 @@ def generate_segmentor(self, question: str) -> Callable:
  return lambda x: GroundingSAM()(**{"prompt": params["prompt"], "image": x})
 
 
+class AzureOpenAILMM(OpenAILMM):
+ def __init__(
+ self,
+ model_name: str = "gpt-4-vision-preview",
+ api_key: Optional[str] = None,
+ api_version: str = "2024-02-01",
+ azure_endpoint: Optional[str] = None,
+ max_tokens: int = 1024,
+ **kwargs: Any,
+ ):
+ if not api_key:
+ api_key = os.getenv("AZURE_OPENAI_API_KEY")
+ if not azure_endpoint:
+ azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
+
+ if not api_key:
+ raise ValueError("OpenAI API key is required.")
+ if not azure_endpoint:
+ raise ValueError("Azure OpenAI endpoint is required.")
+
+ self.client = AzureOpenAI(
+ api_key=api_key, api_version=api_version, azure_endpoint=azure_endpoint
+ )
+ self.model_name = model_name
+ self.max_tokens = max_tokens
+ self.kwargs = kwargs
+
+
 def get_lmm(name: str) -> LMM:
  if name == "openai":
  return OpenAILMM(name)