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Dev (#1892)

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* 支持了agentlm

* 支持了agentlm和相关提示词

* 修改了Agent的一些功能，加入了Embed方面的一个优化

* 修改了部分Agent的工具

* 增加一些Langchain的自带工具

* 修复一些兼容性的bug

* 恢复知识库

* 恢复知识库

* 1

* 修复Azure问题

* 修复zilliz的问题

* 修复Agent历史记录问题，优化知识库问答搜索的uoji

* 修复讯飞大模型token问题

* 修复讯飞大模型token问题和配置文件

---------

Co-authored-by: zR <zRzRzRzRzRzRzR>
This commit is contained in:
zR 2023-10-27 13:14:48 +08:00 committed by GitHub
parent 24d1e28a07
commit dea468ab0f
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GPG Key ID: 4AEE18F83AFDEB23
7 changed files with 46 additions and 35 deletions
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6
configs/model_config.py.example
View File

@ -108,6 +108,10 @@ LLM_DEVICE = "auto"
# 历史对话轮数
HISTORY_LEN = 3
# 大模型最长支持的长度，如果不填写，则使用模型默认的最大长度，如果填写，则为用户设定的最大长度
MAX_TOKENS = None
# LLM通用对话参数
TEMPERATURE = 0.7
# TOP_P = 0.95 # ChatOpenAI暂不支持该参数
@ -132,7 +136,7 @@ ONLINE_LLM_MODEL = {
"APPID": "",
"APISecret": "",
"api_key": "",
"is_v2": False,
"version": "v1.5", # 你使用的讯飞星火大模型版本，可选包括 "v3.0", "v1.5", "v2.0"
"provider": "XingHuoWorker",
},
# 百度千帆 API，申请方式请参考 https://cloud.baidu.com/doc/WENXINWORKSHOP/s/4lilb2lpf

4
server/agent/tools/search_all_knowledge_more.py
View File

@ -11,7 +11,7 @@ from langchain.schema.language_model import BaseLanguageModel
from typing import List, Any, Optional
from langchain.prompts import PromptTemplate
from server.chat.knowledge_base_chat import knowledge_base_chat
from configs import VECTOR_SEARCH_TOP_K, SCORE_THRESHOLD
from configs import VECTOR_SEARCH_TOP_K, SCORE_THRESHOLD, MAX_TOKENS
import asyncio
from server.agent import model_container
@ -23,7 +23,7 @@ async def search_knowledge_base_iter(database: str, query: str) -> str:
temperature=0.01,
history=[],
top_k=VECTOR_SEARCH_TOP_K,
max_tokens=None,
max_tokens=MAX_TOKENS,
prompt_name="default",
score_threshold=SCORE_THRESHOLD,
stream=False)

4
server/agent/tools/search_all_knowledge_once.py
View File

@ -19,7 +19,7 @@ import json
sys.path.append(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
from server.chat.knowledge_base_chat import knowledge_base_chat
from configs import VECTOR_SEARCH_TOP_K, SCORE_THRESHOLD
from configs import VECTOR_SEARCH_TOP_K, SCORE_THRESHOLD, MAX_TOKENS
import asyncio
from server.agent import model_container
@ -32,7 +32,7 @@ async def search_knowledge_base_iter(database: str, query: str):
temperature=0.01,
history=[],
top_k=VECTOR_SEARCH_TOP_K,
max_tokens=None,
max_tokens=MAX_TOKENS,
prompt_name="knowledge_base_chat",
score_threshold=SCORE_THRESHOLD,
stream=False)

4
server/agent/tools/search_internet.py
View File

@ -1,6 +1,6 @@
import json
from server.chat.search_engine_chat import search_engine_chat
from configs import VECTOR_SEARCH_TOP_K
from configs import VECTOR_SEARCH_TOP_K, MAX_TOKENS
import asyncio
from server.agent import model_container
@ -11,7 +11,7 @@ async def search_engine_iter(query: str):
temperature=0.01, # Agent 搜索互联网的时候，温度设置为0.01
history=[],
top_k = VECTOR_SEARCH_TOP_K,
max_tokens= None, # Agent 搜索互联网的时候，max_tokens设置为None
max_tokens= MAX_TOKENS,
prompt_name = "default",
stream=False)

3
server/agent/tools/search_knowledge_simple.py
View File

@ -1,5 +1,5 @@
from server.chat.knowledge_base_chat import knowledge_base_chat
from configs import VECTOR_SEARCH_TOP_K, SCORE_THRESHOLD
from configs import VECTOR_SEARCH_TOP_K, SCORE_THRESHOLD, MAX_TOKENS
import json
import asyncio
from server.agent import model_container
@ -11,6 +11,7 @@ async def search_knowledge_base_iter(database: str, query: str) -> str:
temperature=0.01,
history=[],
top_k=VECTOR_SEARCH_TOP_K,
max_tokens=MAX_TOKENS,
prompt_name="knowledge_base_chat",
score_threshold=SCORE_THRESHOLD,
stream=False)

4
server/model_workers/SparkApi.py
View File

@ -52,7 +52,7 @@ class Ws_Param(object):
return url
def gen_params(appid, domain,question, temperature):
def gen_params(appid, domain, question, temperature, max_token):
"""
通过appid和用户的提问来生成请参数
"""
@ -65,7 +65,7 @@ def gen_params(appid, domain,question, temperature):
"chat": {
"domain": domain,
"random_threshold": 0.5,
"max_tokens": None,
"max_tokens": max_token,
"auditing": "default",
"temperature": temperature,
}

56
server/model_workers/xinghuo.py
View File

@ -9,32 +9,31 @@ from server.utils import iter_over_async, asyncio
from typing import List, Dict
async def request(appid, api_key, api_secret, Spark_url,domain, question, temperature):
# print("星火:")
async def request(appid, api_key, api_secret, Spark_url, domain, question, temperature, max_token):
wsParam = SparkApi.Ws_Param(appid, api_key, api_secret, Spark_url)
wsUrl = wsParam.create_url()
data = SparkApi.gen_params(appid, domain, question, temperature)
data = SparkApi.gen_params(appid, domain, question, temperature, max_token)
async with websockets.connect(wsUrl) as ws:
await ws.send(json.dumps(data, ensure_ascii=False))
finish = False
while not finish:
chunk = await ws.recv()
response = json.loads(chunk)
if response.get("header", {}).get("status") == 2:
finish = True
if text := response.get("payload", {}).get("choices", {}).get("text"):
chunk = await ws.recv()
response = json.loads(chunk)
if response.get("header", {}).get("status") == 2:
finish = True
if text := response.get("payload", {}).get("choices", {}).get("text"):
yield text[0]["content"]
class XingHuoWorker(ApiModelWorker):
def __init__(
self,
*,
model_names: List[str] = ["xinghuo-api"],
controller_addr: str = None,
worker_addr: str = None,
version: str = None,
**kwargs,
self,
*,
model_names: List[str] = ["xinghuo-api"],
controller_addr: str = None,
worker_addr: str = None,
version: str = None,
**kwargs,
):
kwargs.update(model_names=model_names, controller_addr=controller_addr, worker_addr=worker_addr)
kwargs.setdefault("context_len", 8192)
@ -45,27 +44,34 @@ class XingHuoWorker(ApiModelWorker):
# TODO: 当前每次对话都要重新连接websocket，确认是否可以保持连接
params.load_config(self.model_names[0])
if params.is_v2:
domain = "generalv2" # v2.0版本
Spark_url = "ws://spark-api.xf-yun.com/v2.1/chat" # v2.0环境的地址
else:
domain = "general" # v1.5版本
Spark_url = "ws://spark-api.xf-yun.com/v1.1/chat" # v1.5环境的地址
version_mapping = {
"v1.5": {"domain": "general", "url": "ws://spark-api.xf-yun.com/v1.1/chat","max_tokens": 2048},
"v2.0": {"domain": "generalv2", "url": "ws://spark-api.xf-yun.com/v2.1/chat","max_tokens": 4096},
"v3.0": {"domain": "generalv3", "url": "ws://spark-api.xf-yun.com/v3.1/chat","max_tokens": 8192},
}
def get_version_details(version_key):
return version_mapping.get(version_key, {"domain": None, "url": None})
# 使用方法：
details = get_version_details(params.version)
domain = details["domain"]
Spark_url = details["url"]
text = ""
try:
loop = asyncio.get_event_loop()
except:
loop = asyncio.new_event_loop()
params.max_tokens = min(details["max_tokens"], params.max_tokens)
for chunk in iter_over_async(
request(params.APPID, params.api_key, params.APISecret, Spark_url, domain, params.messages, params.temperature),
loop=loop,
request(params.APPID, params.api_key, params.APISecret, Spark_url, domain, params.messages,
params.temperature, params.max_tokens),
loop=loop,
):
if chunk:
text += chunk
yield {"error_code": 0, "text": text}
def get_embeddings(self, params):
# TODO: 支持embeddings
print("embedding")