add azure_gpt_4o (#197)

mm_agents/agent.py

@@ -9,6 +9,7 @@ import xml.etree.ElementTree as ET
 from http import HTTPStatus
 from io import BytesIO
 from typing import Dict, List
+from dotenv import load_dotenv
 
 import backoff
 import dashscope
@@ -565,7 +566,55 @@ class PromptAgent:
     )
     def call_llm(self, payload):
 
-        if self.model.startswith("gpt"):
+        if payload['model'].startswith("azure-gpt-4o"):
+
+
+            #.env config example :
+            # AZURE_OPENAI_API_BASE=YOUR_API_BASE
+            # AZURE_OPENAI_DEPLOYMENT=YOUR_DEPLOYMENT
+            # AZURE_OPENAI_API_VERSION=YOUR_API_VERSION
+            # AZURE_OPENAI_MODEL=gpt-4o-mini
+            # AZURE_OPENAI_API_KEY={{YOUR_API_KEY}}
+            # AZURE_OPENAI_ENDPOINT=${AZURE_OPENAI_API_BASE}/openai/deployments/${AZURE_OPENAI_DEPLOYMENT}/chat/completions?api-version=${AZURE_OPENAI_API_VERSION}
+
+
+            # Load environment variables
+            load_dotenv()
+            api_key = os.getenv('AZURE_OPENAI_API_KEY')
+            openai_endpoint = os.getenv('AZURE_OPENAI_ENDPOINT')
+            #logger.info("Openai endpoint: %s", openai_endpoint)
+
+            headers = {
+                "Content-Type": "application/json",
+                "api-key": api_key
+            }
+            logger.info("Generating content with GPT model: %s", payload['model'])
+            response = requests.post(
+                openai_endpoint,
+                headers=headers,
+                json=payload
+            )
+
+            if response.status_code != 200:
+                if response.json()['error']['code'] == "context_length_exceeded":
+                    logger.error("Context length exceeded. Retrying with a smaller context.")
+                    payload["messages"] = [payload["messages"][0]] + payload["messages"][-1:]
+                    retry_response = requests.post(
+                        openai_endpoint,
+                        headers=headers,
+                        json=payload
+                    )
+                    if retry_response.status_code != 200:
+                         logger.error(
+                            "Failed to call LLM even after attempt on shortening the history: " + retry_response.text)
+                         return ""
+
+                logger.error("Failed to call LLM: " + response.text)
+                time.sleep(5)
+                return ""
+            else:
+                return response.json()['choices'][0]['message']['content']
+        elif self.model.startswith("gpt"):
             headers = {
                 "Content-Type": "application/json",
                 "Authorization": f"Bearer {os.environ['OPENAI_API_KEY']}"
@@ -1046,7 +1095,7 @@ class PromptAgent:
             except Exception as e:
                 print("Failed to call LLM: " + str(e))
                 return ""
-
+        
         else:
             raise ValueError("Invalid model: " + self.model)
 

requirements.txt

@@ -60,3 +60,4 @@ azure-mgmt-compute
 azure-mgmt-network
 docker
 loguru
+dotenv