Merge pull request chenfei-wu#378 from qfyin/azure

chenfei-wu · web-flow · commit 1001c38f5694 · 2023-04-26T10:10:00.000+08:00
Azure OpenAI service support
diff --git a/LowCodeLLM/README.md b/LowCodeLLM/README.md
@@ -13,6 +13,8 @@ https://user-images.githubusercontent.com/43716920/233937121-cd057f04-dec8-45b8-
 
 ## Quick Start
 Please note that due to time constraints, the code we provide is only the minimum viable version of the low-code LLM interactive code, i.e. only demonstrating the core concept of Low-code LLM human-LLM interaction. We welcome anyone who is interested in improving our front-end interface.
+Currently, both the `OpenAI API` and `Azure OpenAI Service` are supported. You would be required to provide the requisite information to invoke these APIs.
+
 ```
 # clone the repo
 git clone https://github.com/microsoft/TaskMatrix.git
@@ -22,10 +24,16 @@ cd LowCodeLLM
 
 # build and run docker
 docker build -t lowcode:latest .
+
+# If OpenAI API is being used, it is only necessary to provide the API key.
 docker run -p 8888:8888 --env OPENAIKEY={Your_Private_Openai_Key} lowcode:latest
 
-# Open the webpage (./src/index.html)
+# When using Azure OpenAI Service, it is advisable to store the necessary information in a configuration file for ease of access.
+# Kindly duplicate the config.template file and name the copied file as config.ini. Then, fill out the necessary information in the config.ini file.
+docker run -p 8888:8888 --env-file config.ini lowcode:latest
 ```
+You can now try it by visiting [Demo page](http://localhost:8888/)
+
 
 ## System Overview
 
diff --git a/LowCodeLLM/config.template b/LowCodeLLM/config.template
@@ -0,0 +1,5 @@
+USE_AZURE=True
+OPENAIKEY=your-azure-openai-service-key
+API_BASE=your-base-url-for-azure
+API_VERSION=2023-03-15-preview
+MODEL=your-gpt-deployment-name
diff --git a/LowCodeLLM/src/app.py b/LowCodeLLM/src/app.py
@@ -1,11 +1,11 @@
 import os
-from flask import Flask, request
+from flask import Flask, request, send_from_directory
 from flask_cors import CORS, cross_origin
 from lowCodeLLM import lowCodeLLM
 from flask.logging import default_handler
 import logging
 
-app = Flask('lowcode-llm', static_url_path='', template_folder='')
+app = Flask('lowcode-llm', static_folder='', template_folder='')
 app.debug = True
 llm = lowCodeLLM()
 gunicorn_logger = logging.getLogger('gunicorn.error')
@@ -14,6 +14,10 @@
     '%(asctime)s - %(levelname)s - %(filename)s - %(funcName)s - %(lineno)s - %(message)s')
 default_handler.setFormatter(logging_format)
 
+@app.route("/")
+def index():
+    return send_from_directory(".", "index.html")
+
 @app.route('/api/get_workflow', methods=['POST'])
 @cross_origin()
 def get_workflow():
diff --git a/LowCodeLLM/src/openAIWrapper.py b/LowCodeLLM/src/openAIWrapper.py
@@ -4,7 +4,28 @@
 class OpenAIWrapper:
     def __init__(self, temperature):
         self.key = os.environ.get("OPENAIKEY")
-        self.chat_model_id = "gpt-3.5-turbo"
+        openai.api_key = self.key
+
+        # Access the USE_AZURE environment variable
+        self.use_azure = os.environ.get('USE_AZURE')
+
+        # Check if USE_AZURE is defined
+        if self.use_azure is not None:
+            # Convert the USE_AZURE value to boolean
+            self.use_azure = self.use_azure.lower() == 'true'
+        else:
+            self.use_azure = False
+
+        if self.use_azure:
+            openai.api_type = "azure"
+            self.api_base = os.environ.get('API_BASE')
+            openai.api_base = self.api_base
+            self.api_version = os.environ.get('API_VERSION')
+            openai.api_version = self.api_version
+            self.engine = os.environ.get('MODEL')
+        else:
+            self.chat_model_id = "gpt-3.5-turbo"
+            
         self.temperature = temperature
         self.max_tokens = 2048
         self.top_p = 1
@@ -15,15 +36,24 @@ def run(self, prompt):
 
     def _post_request_chat(self, messages):
         try:
-            openai.api_key = self.key
-            response = openai.ChatCompletion.create(
-                model=self.chat_model_id,
-                messages=messages,
-                temperature=self.temperature,
-                max_tokens=self.max_tokens,
-                frequency_penalty=0,
-                presence_penalty=0
-            )
+            if self.use_azure:
+                response = openai.ChatCompletion.create(
+                    engine=self.engine,
+                    messages=messages,
+                    temperature=self.temperature,
+                    max_tokens=self.max_tokens,
+                    frequency_penalty=0,
+                    presence_penalty=0
+                )
+            else:
+                response = openai.ChatCompletion.create(
+                    model=self.chat_model_id,
+                    messages=messages,
+                    temperature=self.temperature,
+                    max_tokens=self.max_tokens,
+                    frequency_penalty=0,
+                    presence_penalty=0
+                )
             res = response['choices'][0]['message']['content']
             return res, True
         except Exception as e:
