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

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

dbgpt/model/proxy/llms/spark.py

@@ -0,0 +1,153 @@
+import json
+import base64
+import hmac
+import hashlib
+from websockets.sync.client import connect
+from datetime import datetime
+from typing import List
+from time import mktime
+from urllib.parse import urlencode
+from urllib.parse import urlparse
+from wsgiref.handlers import format_date_time
+from dbgpt.core.interface.message import ModelMessage, ModelMessageRoleType
+from dbgpt.model.proxy.llms.proxy_model import ProxyModel
+
+SPARK_DEFAULT_API_VERSION = "v3"
+
+
+def getlength(text):
+    length = 0
+    for content in text:
+        temp = content["content"]
+        leng = len(temp)
+        length += leng
+    return length
+
+
+def checklen(text):
+    while getlength(text) > 8192:
+        del text[0]
+    return text
+
+
+def spark_generate_stream(
+    model: ProxyModel, tokenizer, params, device, context_len=2048
+):
+    model_params = model.get_params()
+    proxy_api_version = model_params.proxyllm_backend or SPARK_DEFAULT_API_VERSION
+    proxy_api_key = model_params.proxy_api_key
+    proxy_api_secret = model_params.proxy_api_secret
+    proxy_app_id = model_params.proxy_api_app_id
+
+    if proxy_api_version == SPARK_DEFAULT_API_VERSION:
+        url = "ws://spark-api.xf-yun.com/v3.1/chat"
+        domain = "generalv3"
+    else:
+        url = "ws://spark-api.xf-yun.com/v2.1/chat"
+        domain = "generalv2"
+
+    messages: List[ModelMessage] = params["messages"]
+
+    last_user_input = None
+    for index in range(len(messages) - 1, -1, -1):
+        print(f"index: {index}")
+        if messages[index].role == ModelMessageRoleType.HUMAN:
+            last_user_input = {"role": "user", "content": messages[index].content}
+            del messages[index]
+            break
+
+    history = []
+    # Add history conversation
+    for message in messages:
+        # There is no role for system in spark LLM
+        if message.role == ModelMessageRoleType.HUMAN or ModelMessageRoleType.SYSTEM:
+            history.append({"role": "user", "content": message.content})
+        elif message.role == ModelMessageRoleType.AI:
+            history.append({"role": "assistant", "content": message.content})
+        else:
+            pass
+
+    question = checklen(history + [last_user_input])
+
+    print('last_user_input.get("content")', last_user_input.get("content"))
+    data = {
+        "header": {"app_id": proxy_app_id, "uid": str(params.get("request_id", 1))},
+        "parameter": {
+            "chat": {
+                "domain": domain,
+                "random_threshold": 0.5,
+                "max_tokens": context_len,
+                "auditing": "default",
+                "temperature": params.get("temperature"),
+            }
+        },
+        "payload": {"message": {"text": question}},
+    }
+
+    spark_api = SparkAPI(proxy_app_id, proxy_api_key, proxy_api_secret, url)
+    request_url = spark_api.gen_url()
+    return get_response(request_url, data)
+
+
+def get_response(request_url, data):
+    with connect(request_url) as ws:
+        ws.send(json.dumps(data, ensure_ascii=False))
+        result = ""
+        while True:
+            try:
+                chunk = ws.recv()
+                response = json.loads(chunk)
+                print("look out the response: ", response)
+                choices = response.get("payload", {}).get("choices", {})
+                if text := choices.get("text"):
+                    result += text[0]["content"]
+                if choices.get("status") == 2:
+                    break
+            except Exception:
+                break
+    yield result
+
+
+class SparkAPI:
+    def __init__(
+        self, appid: str, api_key: str, api_secret: str, spark_url: str
+    ) -> None:
+        self.appid = appid
+        self.api_key = api_key
+        self.api_secret = api_secret
+        self.host = urlparse(spark_url).netloc
+        self.path = urlparse(spark_url).path
+
+        self.spark_url = spark_url
+
+    def gen_url(self):
+        # 生成RFC1123格式的时间戳
+        now = datetime.now()
+        date = format_date_time(mktime(now.timetuple()))
+
+        # 拼接字符串
+        signature_origin = "host: " + self.host + "\n"
+        signature_origin += "date: " + date + "\n"
+        signature_origin += "GET " + self.path + " HTTP/1.1"
+
+        # 进行hmac-sha256进行加密
+        signature_sha = hmac.new(
+            self.api_secret.encode("utf-8"),
+            signature_origin.encode("utf-8"),
+            digestmod=hashlib.sha256,
+        ).digest()
+
+        signature_sha_base64 = base64.b64encode(signature_sha).decode(encoding="utf-8")
+
+        authorization_origin = f'api_key="{self.api_key}", algorithm="hmac-sha256", headers="host date request-line", signature="{signature_sha_base64}"'
+
+        authorization = base64.b64encode(authorization_origin.encode("utf-8")).decode(
+            encoding="utf-8"
+        )
+
+        # 将请求的鉴权参数组合为字典
+        v = {"authorization": authorization, "date": date, "host": self.host}
+        # 拼接鉴权参数，生成url
+        url = self.spark_url + "?" + urlencode(v)
+        # 此处打印出建立连接时候的url,参考本demo的时候可取消上方打印的注释，比对相同参数时生成的url与自己代码生成的url是否一致
+        return url