File size: 6,297 Bytes
3079197 484e5ab 3079197 3245107 d0db329 4c52eb9 cfd888e 1550520 cfd888e d0db329 3245107 34b2ab3 3245107 34b2ab3 3245107 a8294f2 4c52eb9 cfd888e 4c52eb9 cfd888e 4c52eb9 cfd888e 3245107 9fe9fc4 c1bdfb8 9fe9fc4 34b2ab3 d0db329 34b2ab3 3245107 a8294f2 3245107 34b2ab3 d0db329 a8294f2 3245107 cfd888e 3245107 cfd888e 5e0a689 a8294f2 cfd888e 1550520 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 |
#
# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from abc import ABC
from openai import OpenAI
import openai
from rag.nlp import is_english
from rag.utils import num_tokens_from_string
class Base(ABC):
def __init__(self, key, model_name):
pass
def chat(self, system, history, gen_conf):
raise NotImplementedError("Please implement encode method!")
class GptTurbo(Base):
def __init__(self, key, model_name="gpt-3.5-turbo"):
self.client = OpenAI(api_key=key)
self.model_name = model_name
def chat(self, system, history, gen_conf):
if system: history.insert(0, {"role": "system", "content": system})
try:
response = self.client.chat.completions.create(
model=self.model_name,
messages=history,
**gen_conf)
ans = response.output.choices[0]['message']['content'].strip()
if response.output.choices[0].get("finish_reason", "") == "length":
ans += "...\nFor the content length reason, it stopped, continue?" if is_english(
[ans]) else "路路路路路路\n鐢变簬闀垮害鐨勫師鍥狅紝鍥炵瓟琚埅鏂簡锛岃缁х画鍚楋紵"
return ans, response.usage.completion_tokens
except openai.APIError as e:
return "**ERROR**: "+str(e), 0
class MoonshotChat(GptTurbo):
def __init__(self, key, model_name="moonshot-v1-8k"):
self.client = OpenAI(api_key=key, base_url="https://api.moonshot.cn/v1",)
self.model_name = model_name
def chat(self, system, history, gen_conf):
if system: history.insert(0, {"role": "system", "content": system})
try:
response = self.client.chat.completions.create(
model=self.model_name,
messages=history,
**gen_conf)
ans = response.choices[0].message.content.strip()
if response.choices[0].finish_reason == "length":
ans += "...\nFor the content length reason, it stopped, continue?" if is_english(
[ans]) else "路路路路路路\n鐢变簬闀垮害鐨勫師鍥狅紝鍥炵瓟琚埅鏂簡锛岃缁х画鍚楋紵"
return ans, response.usage.completion_tokens
except openai.APIError as e:
return "**ERROR**: "+str(e), 0
from dashscope import Generation
class QWenChat(Base):
def __init__(self, key, model_name=Generation.Models.qwen_turbo):
import dashscope
dashscope.api_key = key
self.model_name = model_name
def chat(self, system, history, gen_conf):
from http import HTTPStatus
if system: history.insert(0, {"role": "system", "content": system})
response = Generation.call(
self.model_name,
messages=history,
result_format='message',
**gen_conf
)
ans = ""
tk_count = 0
if response.status_code == HTTPStatus.OK:
ans += response.output.choices[0]['message']['content']
tk_count += response.usage.output_tokens
if response.output.choices[0].get("finish_reason", "") == "length":
ans += "...\nFor the content length reason, it stopped, continue?" if is_english([ans]) else "路路路路路路\n鐢变簬闀垮害鐨勫師鍥狅紝鍥炵瓟琚埅鏂簡锛岃缁х画鍚楋紵"
return ans, tk_count
return "**ERROR**: " + response.message, tk_count
from zhipuai import ZhipuAI
class ZhipuChat(Base):
def __init__(self, key, model_name="glm-3-turbo"):
self.client = ZhipuAI(api_key=key)
self.model_name = model_name
def chat(self, system, history, gen_conf):
if system: history.insert(0, {"role": "system", "content": system})
try:
response = self.client.chat.completions.create(
self.model_name,
messages=history,
**gen_conf
)
ans = response.output.choices[0]['message']['content'].strip()
if response.output.choices[0].get("finish_reason", "") == "length":
ans += "...\nFor the content length reason, it stopped, continue?" if is_english(
[ans]) else "路路路路路路\n鐢变簬闀垮害鐨勫師鍥狅紝鍥炵瓟琚埅鏂簡锛岃缁х画鍚楋紵"
return ans, response.usage.completion_tokens
except Exception as e:
return "**ERROR**: " + str(e), 0
class LocalLLM(Base):
class RPCProxy:
def __init__(self, host, port):
self.host = host
self.port = int(port)
self.__conn()
def __conn(self):
from multiprocessing.connection import Client
self._connection = Client((self.host, self.port), authkey=b'infiniflow-token4kevinhu')
def __getattr__(self, name):
import pickle
def do_rpc(*args, **kwargs):
for _ in range(3):
try:
self._connection.send(pickle.dumps((name, args, kwargs)))
return pickle.loads(self._connection.recv())
except Exception as e:
self.__conn()
raise Exception("RPC connection lost!")
return do_rpc
def __init__(self, key, model_name="glm-3-turbo"):
self.client = LocalLLM.RPCProxy("127.0.0.1", 7860)
def chat(self, system, history, gen_conf):
if system: history.insert(0, {"role": "system", "content": system})
try:
ans = self.client.chat(
history,
gen_conf
)
return ans, num_tokens_from_string(ans)
except Exception as e:
return "**ERROR**: " + str(e), 0
|