Update claude endpoint

mm_agents/agent.py

@@ -15,7 +15,6 @@ import dashscope
 import google.generativeai as genai
 import openai
 import requests
-import wandb
 from PIL import Image
 from google.api_core.exceptions import InvalidArgument
 
@@ -523,20 +522,30 @@ class PromptAgent:
                 claude_messages[1]['content'].insert(0, claude_system_message_item)
                 claude_messages.pop(0)
 
+            # headers = {
+            #     "x-api-key": os.environ["ANTHROPIC_API_KEY"],
+            #     "anthropic-version": "2023-06-01",
+            #     "content-type": "application/json"
+            # }
+
             headers = {
-                "x-api-key": os.environ["ANTHROPIC_API_KEY"],
-                "anthropic-version": "2023-06-01",
-                "content-type": "application/json"
+                "Accept": "application / json",
+                "Authorization": "Bearer " + os.environ["ANTHROPIC_API_KEY"],
+                "User-Agent": "Apifox/1.0.0 (https://apifox.com)",
+                "Content-Type": "application/json"
             }
 
             payload = {
                 "model": self.model,
                 "max_tokens": max_tokens,
-                "messages": claude_messages
+                "messages": claude_messages,
+                "temperature": temperature,
+                "top_p": top_p
             }
 
             response = requests.post(
-                "https://api.anthropic.com/v1/messages",
+                # "https://chat.claude.com/v1/chat/completions",
+                "https://api.aigcbest.top/v1/chat/completions",
                 headers=headers,
                 json=payload
             )
@@ -546,8 +555,10 @@ class PromptAgent:
                 logger.error("Failed to call LLM: " + response.text)
                 time.sleep(5)
                 return ""
+            # else:
+            #     return response.json()['content'][0]['text']
             else:
-                return response.json()['content'][0]['text']
+                return response.json()['choices'][0]['message']['content']
 
 
         elif self.model.startswith("mistral"):
@@ -556,7 +567,7 @@ class PromptAgent:
             max_tokens = payload["max_tokens"]
             top_p = payload["top_p"]
             temperature = payload["temperature"]
-        
+
             misrtal_messages = []
 
             for i, message in enumerate(messages):
@@ -567,36 +578,34 @@ class PromptAgent:
 
                 for part in message["content"]:
                     mistral_message['content'] = part['text'] if part['type'] == "text" else ""
-                
-                
+
                 misrtal_messages.append(mistral_message)
-    
-        
+
             # openai.api_base = "http://localhost:8000/v1"
             # response = openai.ChatCompletion.create(
             #     messages=misrtal_messages,
             #     model="Mixtral-8x7B-Instruct-v0.1"
             # )
-        
+
             from openai import OpenAI
 
             client = OpenAI(api_key=os.environ["TOGETHER_API_KEY"],
                             base_url='https://api.together.xyz',
                             )
             logger.info("Generating content with Mistral model: %s", self.model)
-            
+
             response = client.chat.completions.create(
                 messages=misrtal_messages,
                 model=self.model,
                 max_tokens=max_tokens
             )
-        
+
             try:
                 return response.choices[0].message.content
             except Exception as e:
                 print("Failed to call LLM: " + str(e))
                 return ""
-            
+
         elif self.model.startswith("THUDM"):
             # THUDM/cogagent-chat-hf
             print("Call CogAgent")
@@ -604,9 +613,9 @@ class PromptAgent:
             max_tokens = payload["max_tokens"]
             top_p = payload["top_p"]
             temperature = payload["temperature"]
-            
+
             cog_messages = []
-            
+
             for i, message in enumerate(messages):
                 cog_message = {
                     "role": message["role"],
@@ -615,11 +624,12 @@ class PromptAgent:
 
                 for part in message["content"]:
                     if part['type'] == "image_url":
-                        cog_message['content'].append({"type": "image_url", "image_url": {"url": part['image_url']['url'] }  })
-                        
+                        cog_message['content'].append(
+                            {"type": "image_url", "image_url": {"url": part['image_url']['url']}})
+
                     if part['type'] == "text":
                         cog_message['content'].append({"type": "text", "text": part['text']})
-            
+
                 cog_messages.append(cog_message)
 
             # the cogagent not support system message in our endpoint, so we concatenate it at the first user message
@@ -627,7 +637,7 @@ class PromptAgent:
                 cog_system_message_item = cog_messages[0]['content'][0]
                 cog_messages[1]['content'].insert(0, cog_system_message_item)
                 cog_messages.pop(0)
-            
+
             payload = {
                 "model": self.model,
                 "max_tokens": max_tokens,
@@ -635,7 +645,7 @@ class PromptAgent:
             }
 
             base_url = "http://127.0.0.1:8000"
-            
+
             response = requests.post(f"{base_url}/v1/chat/completions", json=payload, stream=False)
             if response.status_code == 200:
                 decoded_line = response.json()