refactor: The first refactored version for sdk release (#907)

Co-authored-by: chengfangyin2 <chengfangyin3@jd.com>

dbgpt/model/proxy/llms/tongyi.py

@@ -0,0 +1,73 @@
+import logging
+from typing import List
+from dbgpt.model.proxy.llms.proxy_model import ProxyModel
+from dbgpt.core.interface.message import ModelMessage, ModelMessageRoleType
+
+logger = logging.getLogger(__name__)
+
+
+def __convert_2_tongyi_messages(messages: List[ModelMessage]):
+    chat_round = 0
+    tongyi_messages = []
+
+    last_usr_message = ""
+    system_messages = []
+
+    for message in messages:
+        if message.role == ModelMessageRoleType.HUMAN:
+            last_usr_message = message.content
+        elif message.role == ModelMessageRoleType.SYSTEM:
+            system_messages.append(message.content)
+        elif message.role == ModelMessageRoleType.AI:
+            last_ai_message = message.content
+            tongyi_messages.append({"role": "user", "content": last_usr_message})
+            tongyi_messages.append({"role": "assistant", "content": last_ai_message})
+    if len(system_messages) > 0:
+        if len(system_messages) < 2:
+            tongyi_messages.insert(0, {"role": "system", "content": system_messages[0]})
+        else:
+            tongyi_messages.append({"role": "user", "content": system_messages[1]})
+    else:
+        last_message = messages[-1]
+        if last_message.role == ModelMessageRoleType.HUMAN:
+            tongyi_messages.append({"role": "user", "content": last_message.content})
+
+    return tongyi_messages
+
+
+def tongyi_generate_stream(
+    model: ProxyModel, tokenizer, params, device, context_len=2048
+):
+    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
+    dashscope.api_key = proxy_api_key
+
+    proxyllm_backend = model_params.proxyllm_backend
+    if not proxyllm_backend:
+        proxyllm_backend = Generation.Models.qwen_turbo  # By Default qwen_turbo
+
+    messages: List[ModelMessage] = params["messages"]
+
+    history = __convert_2_tongyi_messages(messages)
+    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:
+            if r["status_code"] == 200:
+                content = r["output"]["choices"][0]["message"].get("content")
+                yield content
+            else:
+                content = r["code"] + ":" + r["message"]
+                yield content