feat: + tongyi and wenxin

examples/tongyi.py

@@ -0,0 +1,49 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import dashscope
+import requests
+from http import HTTPStatus
+from dashscope import Generation
+
+def call_with_messages():
+    messages = [{'role': 'system', 'content': '你是生活助手机器人。'},
+                {'role': 'user', 'content': '如何做西红柿鸡蛋？'}]
+    gen = Generation()
+    response = gen.call(
+        Generation.Models.qwen_turbo,
+        messages=messages,
+        stream=True,
+        top_p=0.8,
+        result_format='message',  # set the result to be "message" format.
+    )
+
+    for response in response:
+        # The response status_code is HTTPStatus.OK indicate success,
+        # otherwise indicate request is failed, you can get error code
+        # and message from code and message.
+        if response.status_code == HTTPStatus.OK: 
+            print(response.output) # The output text
+            print(response.usage)  # The usage information
+        else:
+            print(response.code) # The error code.
+            print(response.message) # The error message.
+
+
+
+def build_access_token(api_key: str, secret_key: str) -> str:
+    """
+        Generate Access token according AK, SK
+    """
+    
+    url = "https://aip.baidubce.com/oauth/2.0/token"
+    params = {"grant_type": "client_credentials", "client_id": api_key, "client_secret": secret_key}
+
+    res = requests.get(url=url, params=params)
+     
+    if res.status_code == 200:
+        return res.json().get("access_token")
+
+  
+if __name__ == '__main__':
+    call_with_messages()

pilot/configs/config.py

@@ -46,10 +46,13 @@ class Config(metaclass=Singleton):
         # This is a proxy server, just for test_py.  we will remove this later.
         self.proxy_api_key = os.getenv("PROXY_API_KEY")
         self.bard_proxy_api_key = os.getenv("BARD_PROXY_API_KEY")
+
         # In order to be compatible with the new and old model parameter design
         if self.bard_proxy_api_key:
             os.environ["bard_proxyllm_proxy_api_key"] = self.bard_proxy_api_key
 
+        self.tongyi_api_key = os.getenv("TONGYI_PROXY_API_KEY")
+
         self.proxy_server_url = os.getenv("PROXY_SERVER_URL")
 
         self.elevenlabs_api_key = os.getenv("ELEVENLABS_API_KEY")

pilot/model/proxy/llms/tongyi.py

@@ -1,7 +1,66 @@
+import os
+import logging
+from typing import List
 from pilot.model.proxy.llms.proxy_model import ProxyModel
+from pilot.scene.base_message import ModelMessage, ModelMessageRoleType
 
+logger = logging.getLogger(__name__)
 
 def tongyi_generate_stream(
     model: ProxyModel, tokenizer, params, device, context_len=2048
 ):
-    yield "tongyi LLM was not supported!"
+    
+    import dashscope
+    from dashscope import Generation
+    model_params = model.get_params()
+    print(f"Model: {model}, model_params: {model_params}")
+
+    # proxy_api_key = model_params.proxy_api_key # // TODO Set this according env
+    dashscope.api_key = os.getenv("TONGYI_PROXY_API_KEY") 
+
+    
+    proxyllm_backend = model_params.proxyllm_backend
+    if not proxyllm_backend:
+        proxyllm_backend = Generation.Models.qwen_turbo  # By Default qwen_turbo
+    
+    history = []
+
+    messages: List[ModelMessage] = params["messages"]
+    # Add history conversation
+
+    for message in messages:
+        if message.role == ModelMessageRoleType.HUMAN:
+            history.append({"role": "user", "content": message.content})
+        elif message.role == ModelMessageRoleType.SYSTEM:
+            history.append({"role": "system", "content": message.content})
+        elif message.role == ModelMessageRoleType.AI:
+            history.append({"role": "assistant", "content": message.content})
+        else:
+            pass
+            
+    temp_his = history[::-1]
+    last_user_input = None
+    for m in temp_his:
+        if m["role"] == "user":
+            last_user_input = m
+            break
+            
+    if last_user_input:
+        history.remove(last_user_input)
+        history.append(last_user_input)
+    
+    print("history", history)  
+    gen = Generation()
+    res = gen.call(
+        proxyllm_backend,
+        messages=history,
+        top_p=params.get("top_p", 0.8),
+        stream=True,
+        result_format='message' 
+    )
+    
+    for r in res:
+        if r["output"]["choices"][0]["message"].get("content") is not None:
+            content = r["output"]["choices"][0]["message"].get("content") 
+            yield content 
+    

pilot/model/proxy/llms/wenxin.py

@@ -1,7 +1,90 @@
+import os
+import requests
+import json
+from typing import List
 from pilot.model.proxy.llms.proxy_model import ProxyModel
+from pilot.scene.base_message import ModelMessage, ModelMessageRoleType
+from cachetools import cached, TTLCache
 
+@cached(TTLCache(1, 1800))
+def _build_access_token(api_key: str, secret_key: str) -> str:
+    """
+        Generate Access token according AK, SK
+    """
+    
+    url = "https://aip.baidubce.com/oauth/2.0/token"
+    params = {"grant_type": "client_credentials", "client_id": api_key, "client_secret": secret_key}
+
+    res = requests.get(url=url, params=params)
+     
+    if res.status_code == 200:
+        return res.json().get("access_token")
 
 def wenxin_generate_stream(
     model: ProxyModel, tokenizer, params, device, context_len=2048
 ):
-    yield "wenxin LLM is not supported!"
+    MODEL_VERSION = {
+        "ERNIE-Bot": "completions",
+        "ERNIE-Bot-turbo": "eb-instant",
+    }
+
+    model_params = model.get_params()    
+    model_name = os.getenv("WEN_XIN_MODEL_VERSION")
+    model_version = MODEL_VERSION.get(model_name)
+    if not model_version:
+        yield f"Unsupport model version {model_name}"
+        
+    proxy_api_key = os.getenv("WEN_XIN_API_KEY")
+    proxy_api_secret = os.getenv("WEN_XIN_SECRET_KEY")
+    access_token = _build_access_token(proxy_api_key, proxy_api_secret)
+     
+    headers = {
+        "Content-Type": "application/json",
+        "Accept": "application/json"
+    }
+
+    proxy_server_url = f'https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/{model_version}?access_token={access_token}'
+    
+    if not access_token:
+        yield "Failed to get access token. please set the correct api_key and secret key." 
+    
+    messages: List[ModelMessage] = params["messages"] 
+
+    history = []
+    # Add history conversation
+    for message in messages:
+        if message.role == ModelMessageRoleType.HUMAN:
+            history.append({"role": "user", "content": message.content})
+        elif message.role == ModelMessageRoleType.SYSTEM:
+            history.append({"role": "system", "content": message.content})
+        elif message.role == ModelMessageRoleType.AI:
+            history.append({"role": "assistant", "content": message.content})
+        else:
+            pass
+    
+    payload = {
+        "messages": history,
+        "temperature": params.get("temperature"),
+        "stream": True
+    }
+
+    text = ""
+    res = requests.post(proxy_server_url, headers=headers, json=payload, stream=True)
+    print(f"Send request to {proxy_server_url} with real model {model_name}")
+    for line in res.iter_lines():
+        if line:
+            if not line.startswith(b"data: "):
+                error_message = line.decode("utf-8")
+                yield error_message
+            else:
+                json_data = line.split(b": ", 1)[1]
+                decoded_line = json_data.decode("utf-8")
+                if decoded_line.lower() != "[DONE]".lower():
+                    obj = json.loads(json_data)
+                    if obj["result"] is not None:
+                        content = obj["result"]
+                        text += content
+                yield text
+    
+
+