mirror of
https://github.com/infiniflow/ragflow.git
synced 2025-12-08 20:42:30 +08:00
Refa: change LLM chat output from full to delta (incremental) (#6534)
### What problem does this PR solve? Change LLM chat output from full to delta (incremental) ### Type of change - [x] Refactoring
This commit is contained in:
Yongteng Lei
@ -1,5 +1,5 @@
|
||||
#
|
||||
# Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
|
||||
# Copyright 2025 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.
|
||||
@ -13,25 +13,25 @@
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
#
|
||||
import re
|
||||
import asyncio
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import random
|
||||
import re
|
||||
import time
|
||||
from abc import ABC
|
||||
|
||||
import openai
|
||||
import requests
|
||||
from dashscope import Generation
|
||||
from ollama import Client
|
||||
from openai import OpenAI
|
||||
from openai.lib.azure import AzureOpenAI
|
||||
from zhipuai import ZhipuAI
|
||||
from dashscope import Generation
|
||||
from abc import ABC
|
||||
from openai import OpenAI
|
||||
import openai
|
||||
from ollama import Client
|
||||
|
||||
from rag.nlp import is_chinese, is_english
|
||||
from rag.utils import num_tokens_from_string
|
||||
import os
|
||||
import json
|
||||
import requests
|
||||
import asyncio
|
||||
import logging
|
||||
import time
|
||||
|
||||
|
||||
# Error message constants
|
||||
ERROR_PREFIX = "**ERROR**"
|
||||
@ -53,21 +53,21 @@ LENGTH_NOTIFICATION_EN = "...\nThe answer is truncated by your chosen LLM due to
|
||||
|
||||
class Base(ABC):
|
||||
def __init__(self, key, model_name, base_url):
|
||||
timeout = int(os.environ.get('LM_TIMEOUT_SECONDS', 600))
|
||||
timeout = int(os.environ.get("LM_TIMEOUT_SECONDS", 600))
|
||||
self.client = OpenAI(api_key=key, base_url=base_url, timeout=timeout)
|
||||
self.model_name = model_name
|
||||
# Configure retry parameters
|
||||
self.max_retries = int(os.environ.get('LLM_MAX_RETRIES', 5))
|
||||
self.base_delay = float(os.environ.get('LLM_BASE_DELAY', 2.0))
|
||||
self.max_retries = int(os.environ.get("LLM_MAX_RETRIES", 5))
|
||||
self.base_delay = float(os.environ.get("LLM_BASE_DELAY", 2.0))
|
||||
|
||||
def _get_delay(self, attempt):
|
||||
"""Calculate retry delay time"""
|
||||
return self.base_delay * (2 ** attempt) + random.uniform(0, 0.5)
|
||||
|
||||
return self.base_delay * (2**attempt) + random.uniform(0, 0.5)
|
||||
|
||||
def _classify_error(self, error):
|
||||
"""Classify error based on error message content"""
|
||||
error_str = str(error).lower()
|
||||
|
||||
|
||||
if "rate limit" in error_str or "429" in error_str or "tpm limit" in error_str or "too many requests" in error_str or "requests per minute" in error_str:
|
||||
return ERROR_RATE_LIMIT
|
||||
elif "auth" in error_str or "key" in error_str or "apikey" in error_str or "401" in error_str or "forbidden" in error_str or "permission" in error_str:
|
||||
@ -98,11 +98,8 @@ class Base(ABC):
|
||||
# Implement exponential backoff retry strategy
|
||||
for attempt in range(self.max_retries):
|
||||
try:
|
||||
response = self.client.chat.completions.create(
|
||||
model=self.model_name,
|
||||
messages=history,
|
||||
**gen_conf)
|
||||
|
||||
response = self.client.chat.completions.create(model=self.model_name, messages=history, **gen_conf)
|
||||
|
||||
if any([not response.choices, not response.choices[0].message, not response.choices[0].message.content]):
|
||||
return "", 0
|
||||
ans = response.choices[0].message.content.strip()
|
||||
@ -111,17 +108,17 @@ class Base(ABC):
|
||||
ans += LENGTH_NOTIFICATION_CN
|
||||
else:
|
||||
ans += LENGTH_NOTIFICATION_EN
|
||||
return ans, self.total_token_count(response)
|
||||
return ans, self.total_token_count(response)
|
||||
except Exception as e:
|
||||
# Classify the error
|
||||
error_code = self._classify_error(e)
|
||||
|
||||
|
||||
# Check if it's a rate limit error or server error and not the last attempt
|
||||
should_retry = (error_code == ERROR_RATE_LIMIT or error_code == ERROR_SERVER) and attempt < self.max_retries - 1
|
||||
|
||||
|
||||
if should_retry:
|
||||
delay = self._get_delay(attempt)
|
||||
logging.warning(f"Error: {error_code}. Retrying in {delay:.2f} seconds... (Attempt {attempt+1}/{self.max_retries})")
|
||||
logging.warning(f"Error: {error_code}. Retrying in {delay:.2f} seconds... (Attempt {attempt + 1}/{self.max_retries})")
|
||||
time.sleep(delay)
|
||||
else:
|
||||
# For non-rate limit errors or the last attempt, return an error message
|
||||
@ -136,24 +133,23 @@ class Base(ABC):
|
||||
del gen_conf["max_tokens"]
|
||||
ans = ""
|
||||
total_tokens = 0
|
||||
reasoning_start = False
|
||||
try:
|
||||
response = self.client.chat.completions.create(
|
||||
model=self.model_name,
|
||||
messages=history,
|
||||
stream=True,
|
||||
**gen_conf)
|
||||
response = self.client.chat.completions.create(model=self.model_name, messages=history, stream=True, **gen_conf)
|
||||
for resp in response:
|
||||
if not resp.choices:
|
||||
continue
|
||||
if not resp.choices[0].delta.content:
|
||||
resp.choices[0].delta.content = ""
|
||||
if hasattr(resp.choices[0].delta, "reasoning_content") and resp.choices[0].delta.reasoning_content:
|
||||
if ans.find("<think>") < 0:
|
||||
ans += "<think>"
|
||||
ans = ans.replace("</think>", "")
|
||||
ans = ""
|
||||
if not reasoning_start:
|
||||
reasoning_start = True
|
||||
ans = "<think>"
|
||||
ans += resp.choices[0].delta.reasoning_content + "</think>"
|
||||
else:
|
||||
ans += resp.choices[0].delta.content
|
||||
reasoning_start = False
|
||||
ans = resp.choices[0].delta.content
|
||||
|
||||
tol = self.total_token_count(resp)
|
||||
if not tol:
|
||||
@ -221,7 +217,7 @@ class ModelScopeChat(Base):
|
||||
def __init__(self, key=None, model_name="", base_url=""):
|
||||
if not base_url:
|
||||
raise ValueError("Local llm url cannot be None")
|
||||
base_url = base_url.rstrip('/')
|
||||
base_url = base_url.rstrip("/")
|
||||
if base_url.split("/")[-1] != "v1":
|
||||
base_url = os.path.join(base_url, "v1")
|
||||
super().__init__(key, model_name.split("___")[0], base_url)
|
||||
@ -236,8 +232,8 @@ class DeepSeekChat(Base):
|
||||
|
||||
class AzureChat(Base):
|
||||
def __init__(self, key, model_name, **kwargs):
|
||||
api_key = json.loads(key).get('api_key', '')
|
||||
api_version = json.loads(key).get('api_version', '2024-02-01')
|
||||
api_key = json.loads(key).get("api_key", "")
|
||||
api_version = json.loads(key).get("api_version", "2024-02-01")
|
||||
self.client = AzureOpenAI(api_key=api_key, azure_endpoint=kwargs["base_url"], api_version=api_version)
|
||||
self.model_name = model_name
|
||||
|
||||
@ -264,16 +260,9 @@ class BaiChuanChat(Base):
|
||||
response = self.client.chat.completions.create(
|
||||
model=self.model_name,
|
||||
messages=history,
|
||||
extra_body={
|
||||
"tools": [{
|
||||
"type": "web_search",
|
||||
"web_search": {
|
||||
"enable": True,
|
||||
"search_mode": "performance_first"
|
||||
}
|
||||
}]
|
||||
},
|
||||
**self._format_params(gen_conf))
|
||||
extra_body={"tools": [{"type": "web_search", "web_search": {"enable": True, "search_mode": "performance_first"}}]},
|
||||
**self._format_params(gen_conf),
|
||||
)
|
||||
ans = response.choices[0].message.content.strip()
|
||||
if response.choices[0].finish_reason == "length":
|
||||
if is_chinese([ans]):
|
||||
@ -295,23 +284,16 @@ class BaiChuanChat(Base):
|
||||
response = self.client.chat.completions.create(
|
||||
model=self.model_name,
|
||||
messages=history,
|
||||
extra_body={
|
||||
"tools": [{
|
||||
"type": "web_search",
|
||||
"web_search": {
|
||||
"enable": True,
|
||||
"search_mode": "performance_first"
|
||||
}
|
||||
}]
|
||||
},
|
||||
extra_body={"tools": [{"type": "web_search", "web_search": {"enable": True, "search_mode": "performance_first"}}]},
|
||||
stream=True,
|
||||
**self._format_params(gen_conf))
|
||||
**self._format_params(gen_conf),
|
||||
)
|
||||
for resp in response:
|
||||
if not resp.choices:
|
||||
continue
|
||||
if not resp.choices[0].delta.content:
|
||||
resp.choices[0].delta.content = ""
|
||||
ans += resp.choices[0].delta.content
|
||||
ans = resp.choices[0].delta.content
|
||||
tol = self.total_token_count(resp)
|
||||
if not tol:
|
||||
total_tokens += num_tokens_from_string(resp.choices[0].delta.content)
|
||||
@ -333,6 +315,7 @@ class BaiChuanChat(Base):
|
||||
class QWenChat(Base):
|
||||
def __init__(self, key, model_name=Generation.Models.qwen_turbo, **kwargs):
|
||||
import dashscope
|
||||
|
||||
dashscope.api_key = key
|
||||
self.model_name = model_name
|
||||
if self.is_reasoning_model(self.model_name):
|
||||
@ -344,22 +327,18 @@ class QWenChat(Base):
|
||||
if self.is_reasoning_model(self.model_name):
|
||||
return super().chat(system, history, gen_conf)
|
||||
|
||||
stream_flag = str(os.environ.get('QWEN_CHAT_BY_STREAM', 'true')).lower() == 'true'
|
||||
stream_flag = str(os.environ.get("QWEN_CHAT_BY_STREAM", "true")).lower() == "true"
|
||||
if not stream_flag:
|
||||
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
|
||||
)
|
||||
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']
|
||||
ans += response.output.choices[0]["message"]["content"]
|
||||
tk_count += self.total_token_count(response)
|
||||
if response.output.choices[0].get("finish_reason", "") == "length":
|
||||
if is_chinese([ans]):
|
||||
@ -378,8 +357,9 @@ class QWenChat(Base):
|
||||
else:
|
||||
return "".join(result_list[:-1]), result_list[-1]
|
||||
|
||||
def _chat_streamly(self, system, history, gen_conf, incremental_output=False):
|
||||
def _chat_streamly(self, system, history, gen_conf, incremental_output=True):
|
||||
from http import HTTPStatus
|
||||
|
||||
if system:
|
||||
history.insert(0, {"role": "system", "content": system})
|
||||
if "max_tokens" in gen_conf:
|
||||
@ -387,17 +367,10 @@ class QWenChat(Base):
|
||||
ans = ""
|
||||
tk_count = 0
|
||||
try:
|
||||
response = Generation.call(
|
||||
self.model_name,
|
||||
messages=history,
|
||||
result_format='message',
|
||||
stream=True,
|
||||
incremental_output=incremental_output,
|
||||
**gen_conf
|
||||
)
|
||||
response = Generation.call(self.model_name, messages=history, result_format="message", stream=True, incremental_output=incremental_output, **gen_conf)
|
||||
for resp in response:
|
||||
if resp.status_code == HTTPStatus.OK:
|
||||
ans = resp.output.choices[0]['message']['content']
|
||||
ans = resp.output.choices[0]["message"]["content"]
|
||||
tk_count = self.total_token_count(resp)
|
||||
if resp.output.choices[0].get("finish_reason", "") == "length":
|
||||
if is_chinese(ans):
|
||||
@ -406,8 +379,11 @@ class QWenChat(Base):
|
||||
ans += LENGTH_NOTIFICATION_EN
|
||||
yield ans
|
||||
else:
|
||||
yield ans + "\n**ERROR**: " + resp.message if not re.search(r" (key|quota)",
|
||||
str(resp.message).lower()) else "Out of credit. Please set the API key in **settings > Model providers.**"
|
||||
yield (
|
||||
ans + "\n**ERROR**: " + resp.message
|
||||
if not re.search(r" (key|quota)", str(resp.message).lower())
|
||||
else "Out of credit. Please set the API key in **settings > Model providers.**"
|
||||
)
|
||||
except Exception as e:
|
||||
yield ans + "\n**ERROR**: " + str(e)
|
||||
|
||||
@ -423,10 +399,12 @@ class QWenChat(Base):
|
||||
|
||||
@staticmethod
|
||||
def is_reasoning_model(model_name: str) -> bool:
|
||||
return any([
|
||||
model_name.lower().find("deepseek") >= 0,
|
||||
model_name.lower().find("qwq") >= 0 and model_name.lower() != 'qwq-32b-preview',
|
||||
])
|
||||
return any(
|
||||
[
|
||||
model_name.lower().find("deepseek") >= 0,
|
||||
model_name.lower().find("qwq") >= 0 and model_name.lower() != "qwq-32b-preview",
|
||||
]
|
||||
)
|
||||
|
||||
|
||||
class ZhipuChat(Base):
|
||||
@ -444,11 +422,7 @@ class ZhipuChat(Base):
|
||||
del gen_conf["presence_penalty"]
|
||||
if "frequency_penalty" in gen_conf:
|
||||
del gen_conf["frequency_penalty"]
|
||||
response = self.client.chat.completions.create(
|
||||
model=self.model_name,
|
||||
messages=history,
|
||||
**gen_conf
|
||||
)
|
||||
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":
|
||||
if is_chinese(ans):
|
||||
@ -471,17 +445,12 @@ class ZhipuChat(Base):
|
||||
ans = ""
|
||||
tk_count = 0
|
||||
try:
|
||||
response = self.client.chat.completions.create(
|
||||
model=self.model_name,
|
||||
messages=history,
|
||||
stream=True,
|
||||
**gen_conf
|
||||
)
|
||||
response = self.client.chat.completions.create(model=self.model_name, messages=history, stream=True, **gen_conf)
|
||||
for resp in response:
|
||||
if not resp.choices[0].delta.content:
|
||||
continue
|
||||
delta = resp.choices[0].delta.content
|
||||
ans += delta
|
||||
ans = delta
|
||||
if resp.choices[0].finish_reason == "length":
|
||||
if is_chinese(ans):
|
||||
ans += LENGTH_NOTIFICATION_CN
|
||||
@ -499,8 +468,7 @@ class ZhipuChat(Base):
|
||||
|
||||
class OllamaChat(Base):
|
||||
def __init__(self, key, model_name, **kwargs):
|
||||
self.client = Client(host=kwargs["base_url"]) if not key or key == "x" else \
|
||||
Client(host=kwargs["base_url"], headers={"Authorization": f"Bear {key}"})
|
||||
self.client = Client(host=kwargs["base_url"]) if not key or key == "x" else Client(host=kwargs["base_url"], headers={"Authorization": f"Bear {key}"})
|
||||
self.model_name = model_name
|
||||
|
||||
def chat(self, system, history, gen_conf):
|
||||
@ -509,9 +477,7 @@ class OllamaChat(Base):
|
||||
if "max_tokens" in gen_conf:
|
||||
del gen_conf["max_tokens"]
|
||||
try:
|
||||
options = {
|
||||
"num_ctx": 32768
|
||||
}
|
||||
options = {"num_ctx": 32768}
|
||||
if "temperature" in gen_conf:
|
||||
options["temperature"] = gen_conf["temperature"]
|
||||
if "max_tokens" in gen_conf:
|
||||
@ -522,12 +488,7 @@ class OllamaChat(Base):
|
||||
options["presence_penalty"] = gen_conf["presence_penalty"]
|
||||
if "frequency_penalty" in gen_conf:
|
||||
options["frequency_penalty"] = gen_conf["frequency_penalty"]
|
||||
response = self.client.chat(
|
||||
model=self.model_name,
|
||||
messages=history,
|
||||
options=options,
|
||||
keep_alive=-1
|
||||
)
|
||||
response = self.client.chat(model=self.model_name, messages=history, options=options, keep_alive=-1)
|
||||
ans = response["message"]["content"].strip()
|
||||
return ans, response.get("eval_count", 0) + response.get("prompt_eval_count", 0)
|
||||
except Exception as e:
|
||||
@ -551,17 +512,11 @@ class OllamaChat(Base):
|
||||
options["frequency_penalty"] = gen_conf["frequency_penalty"]
|
||||
ans = ""
|
||||
try:
|
||||
response = self.client.chat(
|
||||
model=self.model_name,
|
||||
messages=history,
|
||||
stream=True,
|
||||
options=options,
|
||||
keep_alive=-1
|
||||
)
|
||||
response = self.client.chat(model=self.model_name, messages=history, stream=True, options=options, keep_alive=-1)
|
||||
for resp in response:
|
||||
if resp["done"]:
|
||||
yield resp.get("prompt_eval_count", 0) + resp.get("eval_count", 0)
|
||||
ans += resp["message"]["content"]
|
||||
ans = resp["message"]["content"]
|
||||
yield ans
|
||||
except Exception as e:
|
||||
yield ans + "\n**ERROR**: " + str(e)
|
||||
@ -588,9 +543,7 @@ class LocalLLM(Base):
|
||||
def __conn(self):
|
||||
from multiprocessing.connection import Client
|
||||
|
||||
self._connection = Client(
|
||||
(self.host, self.port), authkey=b"infiniflow-token4kevinhu"
|
||||
)
|
||||
self._connection = Client((self.host, self.port), authkey=b"infiniflow-token4kevinhu")
|
||||
|
||||
def __getattr__(self, name):
|
||||
import pickle
|
||||
@ -613,17 +566,17 @@ class LocalLLM(Base):
|
||||
|
||||
def _prepare_prompt(self, system, history, gen_conf):
|
||||
from rag.svr.jina_server import Prompt
|
||||
|
||||
if system:
|
||||
history.insert(0, {"role": "system", "content": system})
|
||||
return Prompt(message=history, gen_conf=gen_conf)
|
||||
|
||||
def _stream_response(self, endpoint, prompt):
|
||||
from rag.svr.jina_server import Generation
|
||||
|
||||
answer = ""
|
||||
try:
|
||||
res = self.client.stream_doc(
|
||||
on=endpoint, inputs=prompt, return_type=Generation
|
||||
)
|
||||
res = self.client.stream_doc(on=endpoint, inputs=prompt, return_type=Generation)
|
||||
loop = asyncio.get_event_loop()
|
||||
try:
|
||||
while True:
|
||||
@ -652,24 +605,24 @@ class LocalLLM(Base):
|
||||
|
||||
|
||||
class VolcEngineChat(Base):
|
||||
def __init__(self, key, model_name, base_url='https://ark.cn-beijing.volces.com/api/v3'):
|
||||
def __init__(self, key, model_name, base_url="https://ark.cn-beijing.volces.com/api/v3"):
|
||||
"""
|
||||
Since do not want to modify the original database fields, and the VolcEngine authentication method is quite special,
|
||||
Assemble ark_api_key, ep_id into api_key, store it as a dictionary type, and parse it for use
|
||||
model_name is for display only
|
||||
"""
|
||||
base_url = base_url if base_url else 'https://ark.cn-beijing.volces.com/api/v3'
|
||||
ark_api_key = json.loads(key).get('ark_api_key', '')
|
||||
model_name = json.loads(key).get('ep_id', '') + json.loads(key).get('endpoint_id', '')
|
||||
base_url = base_url if base_url else "https://ark.cn-beijing.volces.com/api/v3"
|
||||
ark_api_key = json.loads(key).get("ark_api_key", "")
|
||||
model_name = json.loads(key).get("ep_id", "") + json.loads(key).get("endpoint_id", "")
|
||||
super().__init__(ark_api_key, model_name, base_url)
|
||||
|
||||
|
||||
class MiniMaxChat(Base):
|
||||
def __init__(
|
||||
self,
|
||||
key,
|
||||
model_name,
|
||||
base_url="https://api.minimax.chat/v1/text/chatcompletion_v2",
|
||||
self,
|
||||
key,
|
||||
model_name,
|
||||
base_url="https://api.minimax.chat/v1/text/chatcompletion_v2",
|
||||
):
|
||||
if not base_url:
|
||||
base_url = "https://api.minimax.chat/v1/text/chatcompletion_v2"
|
||||
@ -687,13 +640,9 @@ class MiniMaxChat(Base):
|
||||
"Authorization": f"Bearer {self.api_key}",
|
||||
"Content-Type": "application/json",
|
||||
}
|
||||
payload = json.dumps(
|
||||
{"model": self.model_name, "messages": history, **gen_conf}
|
||||
)
|
||||
payload = json.dumps({"model": self.model_name, "messages": history, **gen_conf})
|
||||
try:
|
||||
response = requests.request(
|
||||
"POST", url=self.base_url, headers=headers, data=payload
|
||||
)
|
||||
response = requests.request("POST", url=self.base_url, headers=headers, data=payload)
|
||||
response = response.json()
|
||||
ans = response["choices"][0]["message"]["content"].strip()
|
||||
if response["choices"][0]["finish_reason"] == "length":
|
||||
@ -737,7 +686,7 @@ class MiniMaxChat(Base):
|
||||
text = ""
|
||||
if "choices" in resp and "delta" in resp["choices"][0]:
|
||||
text = resp["choices"][0]["delta"]["content"]
|
||||
ans += text
|
||||
ans = text
|
||||
tol = self.total_token_count(resp)
|
||||
if not tol:
|
||||
total_tokens += num_tokens_from_string(text)
|
||||
@ -752,9 +701,9 @@ class MiniMaxChat(Base):
|
||||
|
||||
|
||||
class MistralChat(Base):
|
||||
|
||||
def __init__(self, key, model_name, base_url=None):
|
||||
from mistralai.client import MistralClient
|
||||
|
||||
self.client = MistralClient(api_key=key)
|
||||
self.model_name = model_name
|
||||
|
||||
@ -765,10 +714,7 @@ class MistralChat(Base):
|
||||
if k not in ["temperature", "top_p", "max_tokens"]:
|
||||
del gen_conf[k]
|
||||
try:
|
||||
response = self.client.chat(
|
||||
model=self.model_name,
|
||||
messages=history,
|
||||
**gen_conf)
|
||||
response = self.client.chat(model=self.model_name, messages=history, **gen_conf)
|
||||
ans = response.choices[0].message.content
|
||||
if response.choices[0].finish_reason == "length":
|
||||
if is_chinese(ans):
|
||||
@ -788,14 +734,11 @@ class MistralChat(Base):
|
||||
ans = ""
|
||||
total_tokens = 0
|
||||
try:
|
||||
response = self.client.chat_stream(
|
||||
model=self.model_name,
|
||||
messages=history,
|
||||
**gen_conf)
|
||||
response = self.client.chat_stream(model=self.model_name, messages=history, **gen_conf)
|
||||
for resp in response:
|
||||
if not resp.choices or not resp.choices[0].delta.content:
|
||||
continue
|
||||
ans += resp.choices[0].delta.content
|
||||
ans = resp.choices[0].delta.content
|
||||
total_tokens += 1
|
||||
if resp.choices[0].finish_reason == "length":
|
||||
if is_chinese(ans):
|
||||
@ -811,23 +754,23 @@ class MistralChat(Base):
|
||||
|
||||
|
||||
class BedrockChat(Base):
|
||||
|
||||
def __init__(self, key, model_name, **kwargs):
|
||||
import boto3
|
||||
self.bedrock_ak = json.loads(key).get('bedrock_ak', '')
|
||||
self.bedrock_sk = json.loads(key).get('bedrock_sk', '')
|
||||
self.bedrock_region = json.loads(key).get('bedrock_region', '')
|
||||
|
||||
self.bedrock_ak = json.loads(key).get("bedrock_ak", "")
|
||||
self.bedrock_sk = json.loads(key).get("bedrock_sk", "")
|
||||
self.bedrock_region = json.loads(key).get("bedrock_region", "")
|
||||
self.model_name = model_name
|
||||
|
||||
if self.bedrock_ak == '' or self.bedrock_sk == '' or self.bedrock_region == '':
|
||||
if self.bedrock_ak == "" or self.bedrock_sk == "" or self.bedrock_region == "":
|
||||
# Try to create a client using the default credentials (AWS_PROFILE, AWS_DEFAULT_REGION, etc.)
|
||||
self.client = boto3.client('bedrock-runtime')
|
||||
self.client = boto3.client("bedrock-runtime")
|
||||
else:
|
||||
self.client = boto3.client(service_name='bedrock-runtime', region_name=self.bedrock_region,
|
||||
aws_access_key_id=self.bedrock_ak, aws_secret_access_key=self.bedrock_sk)
|
||||
self.client = boto3.client(service_name="bedrock-runtime", region_name=self.bedrock_region, aws_access_key_id=self.bedrock_ak, aws_secret_access_key=self.bedrock_sk)
|
||||
|
||||
def chat(self, system, history, gen_conf):
|
||||
from botocore.exceptions import ClientError
|
||||
|
||||
for k in list(gen_conf.keys()):
|
||||
if k not in ["temperature"]:
|
||||
del gen_conf[k]
|
||||
@ -853,6 +796,7 @@ class BedrockChat(Base):
|
||||
|
||||
def chat_streamly(self, system, history, gen_conf):
|
||||
from botocore.exceptions import ClientError
|
||||
|
||||
for k in list(gen_conf.keys()):
|
||||
if k not in ["temperature"]:
|
||||
del gen_conf[k]
|
||||
@ -860,14 +804,9 @@ class BedrockChat(Base):
|
||||
if not isinstance(item["content"], list) and not isinstance(item["content"], tuple):
|
||||
item["content"] = [{"text": item["content"]}]
|
||||
|
||||
if self.model_name.split('.')[0] == 'ai21':
|
||||
if self.model_name.split(".")[0] == "ai21":
|
||||
try:
|
||||
response = self.client.converse(
|
||||
modelId=self.model_name,
|
||||
messages=history,
|
||||
inferenceConfig=gen_conf,
|
||||
system=[{"text": (system if system else "Answer the user's message.")}]
|
||||
)
|
||||
response = self.client.converse(modelId=self.model_name, messages=history, inferenceConfig=gen_conf, system=[{"text": (system if system else "Answer the user's message.")}])
|
||||
ans = response["output"]["message"]["content"][0]["text"]
|
||||
return ans, num_tokens_from_string(ans)
|
||||
|
||||
@ -878,16 +817,13 @@ class BedrockChat(Base):
|
||||
try:
|
||||
# Send the message to the model, using a basic inference configuration.
|
||||
streaming_response = self.client.converse_stream(
|
||||
modelId=self.model_name,
|
||||
messages=history,
|
||||
inferenceConfig=gen_conf,
|
||||
system=[{"text": (system if system else "Answer the user's message.")}]
|
||||
modelId=self.model_name, messages=history, inferenceConfig=gen_conf, system=[{"text": (system if system else "Answer the user's message.")}]
|
||||
)
|
||||
|
||||
# Extract and print the streamed response text in real-time.
|
||||
for resp in streaming_response["stream"]:
|
||||
if "contentBlockDelta" in resp:
|
||||
ans += resp["contentBlockDelta"]["delta"]["text"]
|
||||
ans = resp["contentBlockDelta"]["delta"]["text"]
|
||||
yield ans
|
||||
|
||||
except (ClientError, Exception) as e:
|
||||
@ -897,13 +833,12 @@ class BedrockChat(Base):
|
||||
|
||||
|
||||
class GeminiChat(Base):
|
||||
|
||||
def __init__(self, key, model_name, base_url=None):
|
||||
from google.generativeai import client, GenerativeModel
|
||||
from google.generativeai import GenerativeModel, client
|
||||
|
||||
client.configure(api_key=key)
|
||||
_client = client.get_default_generative_client()
|
||||
self.model_name = 'models/' + model_name
|
||||
self.model_name = "models/" + model_name
|
||||
self.model = GenerativeModel(model_name=self.model_name)
|
||||
self.model._client = _client
|
||||
|
||||
@ -916,17 +851,15 @@ class GeminiChat(Base):
|
||||
if k not in ["temperature", "top_p", "max_tokens"]:
|
||||
del gen_conf[k]
|
||||
for item in history:
|
||||
if 'role' in item and item['role'] == 'assistant':
|
||||
item['role'] = 'model'
|
||||
if 'role' in item and item['role'] == 'system':
|
||||
item['role'] = 'user'
|
||||
if 'content' in item:
|
||||
item['parts'] = item.pop('content')
|
||||
if "role" in item and item["role"] == "assistant":
|
||||
item["role"] = "model"
|
||||
if "role" in item and item["role"] == "system":
|
||||
item["role"] = "user"
|
||||
if "content" in item:
|
||||
item["parts"] = item.pop("content")
|
||||
|
||||
try:
|
||||
response = self.model.generate_content(
|
||||
history,
|
||||
generation_config=gen_conf)
|
||||
response = self.model.generate_content(history, generation_config=gen_conf)
|
||||
ans = response.text
|
||||
return ans, response.usage_metadata.total_token_count
|
||||
except Exception as e:
|
||||
@ -941,17 +874,15 @@ class GeminiChat(Base):
|
||||
if k not in ["temperature", "top_p", "max_tokens"]:
|
||||
del gen_conf[k]
|
||||
for item in history:
|
||||
if 'role' in item and item['role'] == 'assistant':
|
||||
item['role'] = 'model'
|
||||
if 'content' in item:
|
||||
item['parts'] = item.pop('content')
|
||||
if "role" in item and item["role"] == "assistant":
|
||||
item["role"] = "model"
|
||||
if "content" in item:
|
||||
item["parts"] = item.pop("content")
|
||||
ans = ""
|
||||
try:
|
||||
response = self.model.generate_content(
|
||||
history,
|
||||
generation_config=gen_conf, stream=True)
|
||||
response = self.model.generate_content(history, generation_config=gen_conf, stream=True)
|
||||
for resp in response:
|
||||
ans += resp.text
|
||||
ans = resp.text
|
||||
yield ans
|
||||
|
||||
yield response._chunks[-1].usage_metadata.total_token_count
|
||||
@ -962,8 +893,9 @@ class GeminiChat(Base):
|
||||
|
||||
|
||||
class GroqChat(Base):
|
||||
def __init__(self, key, model_name, base_url=''):
|
||||
def __init__(self, key, model_name, base_url=""):
|
||||
from groq import Groq
|
||||
|
||||
self.client = Groq(api_key=key)
|
||||
self.model_name = model_name
|
||||
|
||||
@ -975,11 +907,7 @@ class GroqChat(Base):
|
||||
del gen_conf[k]
|
||||
ans = ""
|
||||
try:
|
||||
response = self.client.chat.completions.create(
|
||||
model=self.model_name,
|
||||
messages=history,
|
||||
**gen_conf
|
||||
)
|
||||
response = self.client.chat.completions.create(model=self.model_name, messages=history, **gen_conf)
|
||||
ans = response.choices[0].message.content
|
||||
if response.choices[0].finish_reason == "length":
|
||||
if is_chinese(ans):
|
||||
@ -999,16 +927,11 @@ class GroqChat(Base):
|
||||
ans = ""
|
||||
total_tokens = 0
|
||||
try:
|
||||
response = self.client.chat.completions.create(
|
||||
model=self.model_name,
|
||||
messages=history,
|
||||
stream=True,
|
||||
**gen_conf
|
||||
)
|
||||
response = self.client.chat.completions.create(model=self.model_name, messages=history, stream=True, **gen_conf)
|
||||
for resp in response:
|
||||
if not resp.choices or not resp.choices[0].delta.content:
|
||||
continue
|
||||
ans += resp.choices[0].delta.content
|
||||
ans = resp.choices[0].delta.content
|
||||
total_tokens += 1
|
||||
if resp.choices[0].finish_reason == "length":
|
||||
if is_chinese(ans):
|
||||
@ -1096,16 +1019,10 @@ class CoHereChat(Base):
|
||||
mes = history.pop()["message"]
|
||||
ans = ""
|
||||
try:
|
||||
response = self.client.chat(
|
||||
model=self.model_name, chat_history=history, message=mes, **gen_conf
|
||||
)
|
||||
response = self.client.chat(model=self.model_name, chat_history=history, message=mes, **gen_conf)
|
||||
ans = response.text
|
||||
if response.finish_reason == "MAX_TOKENS":
|
||||
ans += (
|
||||
"...\nFor the content length reason, it stopped, continue?"
|
||||
if is_english([ans])
|
||||
else "······\n由于长度的原因，回答被截断了，要继续吗？"
|
||||
)
|
||||
ans += "...\nFor the content length reason, it stopped, continue?" if is_english([ans]) else "······\n由于长度的原因，回答被截断了，要继续吗？"
|
||||
return (
|
||||
ans,
|
||||
response.meta.tokens.input_tokens + response.meta.tokens.output_tokens,
|
||||
@ -1133,20 +1050,14 @@ class CoHereChat(Base):
|
||||
ans = ""
|
||||
total_tokens = 0
|
||||
try:
|
||||
response = self.client.chat_stream(
|
||||
model=self.model_name, chat_history=history, message=mes, **gen_conf
|
||||
)
|
||||
response = self.client.chat_stream(model=self.model_name, chat_history=history, message=mes, **gen_conf)
|
||||
for resp in response:
|
||||
if resp.event_type == "text-generation":
|
||||
ans += resp.text
|
||||
ans = resp.text
|
||||
total_tokens += num_tokens_from_string(resp.text)
|
||||
elif resp.event_type == "stream-end":
|
||||
if resp.finish_reason == "MAX_TOKENS":
|
||||
ans += (
|
||||
"...\nFor the content length reason, it stopped, continue?"
|
||||
if is_english([ans])
|
||||
else "······\n由于长度的原因，回答被截断了，要继续吗？"
|
||||
)
|
||||
ans += "...\nFor the content length reason, it stopped, continue?" if is_english([ans]) else "······\n由于长度的原因，回答被截断了，要继续吗？"
|
||||
yield ans
|
||||
|
||||
except Exception as e:
|
||||
@ -1217,9 +1128,7 @@ class ReplicateChat(Base):
|
||||
del gen_conf["max_tokens"]
|
||||
if system:
|
||||
self.system = system
|
||||
prompt = "\n".join(
|
||||
[item["role"] + ":" + item["content"] for item in history[-5:]]
|
||||
)
|
||||
prompt = "\n".join([item["role"] + ":" + item["content"] for item in history[-5:]])
|
||||
ans = ""
|
||||
try:
|
||||
response = self.client.run(
|
||||
@ -1236,9 +1145,7 @@ class ReplicateChat(Base):
|
||||
del gen_conf["max_tokens"]
|
||||
if system:
|
||||
self.system = system
|
||||
prompt = "\n".join(
|
||||
[item["role"] + ":" + item["content"] for item in history[-5:]]
|
||||
)
|
||||
prompt = "\n".join([item["role"] + ":" + item["content"] for item in history[-5:]])
|
||||
ans = ""
|
||||
try:
|
||||
response = self.client.run(
|
||||
@ -1246,7 +1153,7 @@ class ReplicateChat(Base):
|
||||
input={"system_prompt": self.system, "prompt": prompt, **gen_conf},
|
||||
)
|
||||
for resp in response:
|
||||
ans += resp
|
||||
ans = resp
|
||||
yield ans
|
||||
|
||||
except Exception as e:
|
||||
@ -1268,10 +1175,10 @@ class HunyuanChat(Base):
|
||||
self.client = hunyuan_client.HunyuanClient(cred, "")
|
||||
|
||||
def chat(self, system, history, gen_conf):
|
||||
from tencentcloud.hunyuan.v20230901 import models
|
||||
from tencentcloud.common.exception.tencent_cloud_sdk_exception import (
|
||||
TencentCloudSDKException,
|
||||
)
|
||||
from tencentcloud.hunyuan.v20230901 import models
|
||||
|
||||
_gen_conf = {}
|
||||
_history = [{k.capitalize(): v for k, v in item.items()} for item in history]
|
||||
@ -1296,10 +1203,10 @@ class HunyuanChat(Base):
|
||||
return ans + "\n**ERROR**: " + str(e), 0
|
||||
|
||||
def chat_streamly(self, system, history, gen_conf):
|
||||
from tencentcloud.hunyuan.v20230901 import models
|
||||
from tencentcloud.common.exception.tencent_cloud_sdk_exception import (
|
||||
TencentCloudSDKException,
|
||||
)
|
||||
from tencentcloud.hunyuan.v20230901 import models
|
||||
|
||||
_gen_conf = {}
|
||||
_history = [{k.capitalize(): v for k, v in item.items()} for item in history]
|
||||
@ -1327,7 +1234,7 @@ class HunyuanChat(Base):
|
||||
resp = json.loads(resp["data"])
|
||||
if not resp["Choices"] or not resp["Choices"][0]["Delta"]["Content"]:
|
||||
continue
|
||||
ans += resp["Choices"][0]["Delta"]["Content"]
|
||||
ans = resp["Choices"][0]["Delta"]["Content"]
|
||||
total_tokens += 1
|
||||
|
||||
yield ans
|
||||
@ -1339,9 +1246,7 @@ class HunyuanChat(Base):
|
||||
|
||||
|
||||
class SparkChat(Base):
|
||||
def __init__(
|
||||
self, key, model_name, base_url="https://spark-api-open.xf-yun.com/v1"
|
||||
):
|
||||
def __init__(self, key, model_name, base_url="https://spark-api-open.xf-yun.com/v1"):
|
||||
if not base_url:
|
||||
base_url = "https://spark-api-open.xf-yun.com/v1"
|
||||
model2version = {
|
||||
@ -1374,22 +1279,14 @@ class BaiduYiyanChat(Base):
|
||||
def chat(self, system, history, gen_conf):
|
||||
if system:
|
||||
self.system = system
|
||||
gen_conf["penalty_score"] = (
|
||||
(gen_conf.get("presence_penalty", 0) + gen_conf.get("frequency_penalty",
|
||||
0)) / 2
|
||||
) + 1
|
||||
gen_conf["penalty_score"] = ((gen_conf.get("presence_penalty", 0) + gen_conf.get("frequency_penalty", 0)) / 2) + 1
|
||||
if "max_tokens" in gen_conf:
|
||||
del gen_conf["max_tokens"]
|
||||
ans = ""
|
||||
|
||||
try:
|
||||
response = self.client.do(
|
||||
model=self.model_name,
|
||||
messages=history,
|
||||
system=self.system,
|
||||
**gen_conf
|
||||
).body
|
||||
ans = response['result']
|
||||
response = self.client.do(model=self.model_name, messages=history, system=self.system, **gen_conf).body
|
||||
ans = response["result"]
|
||||
return ans, self.total_token_count(response)
|
||||
|
||||
except Exception as e:
|
||||
@ -1398,26 +1295,17 @@ class BaiduYiyanChat(Base):
|
||||
def chat_streamly(self, system, history, gen_conf):
|
||||
if system:
|
||||
self.system = system
|
||||
gen_conf["penalty_score"] = (
|
||||
(gen_conf.get("presence_penalty", 0) + gen_conf.get("frequency_penalty",
|
||||
0)) / 2
|
||||
) + 1
|
||||
gen_conf["penalty_score"] = ((gen_conf.get("presence_penalty", 0) + gen_conf.get("frequency_penalty", 0)) / 2) + 1
|
||||
if "max_tokens" in gen_conf:
|
||||
del gen_conf["max_tokens"]
|
||||
ans = ""
|
||||
total_tokens = 0
|
||||
|
||||
try:
|
||||
response = self.client.do(
|
||||
model=self.model_name,
|
||||
messages=history,
|
||||
system=self.system,
|
||||
stream=True,
|
||||
**gen_conf
|
||||
)
|
||||
response = self.client.do(model=self.model_name, messages=history, system=self.system, stream=True, **gen_conf)
|
||||
for resp in response:
|
||||
resp = resp.body
|
||||
ans += resp['result']
|
||||
ans = resp["result"]
|
||||
total_tokens = self.total_token_count(resp)
|
||||
|
||||
yield ans
|
||||
@ -1458,11 +1346,7 @@ class AnthropicChat(Base):
|
||||
).to_dict()
|
||||
ans = response["content"][0]["text"]
|
||||
if response["stop_reason"] == "max_tokens":
|
||||
ans += (
|
||||
"...\nFor the content length reason, it stopped, continue?"
|
||||
if is_english([ans])
|
||||
else "······\n由于长度的原因，回答被截断了，要继续吗？"
|
||||
)
|
||||
ans += "...\nFor the content length reason, it stopped, continue?" if is_english([ans]) else "······\n由于长度的原因，回答被截断了，要继续吗？"
|
||||
return (
|
||||
ans,
|
||||
response["usage"]["input_tokens"] + response["usage"]["output_tokens"],
|
||||
@ -1483,6 +1367,7 @@ class AnthropicChat(Base):
|
||||
|
||||
ans = ""
|
||||
total_tokens = 0
|
||||
reasoning_start = False
|
||||
try:
|
||||
response = self.client.messages.create(
|
||||
model=self.model_name,
|
||||
@ -1492,15 +1377,17 @@ class AnthropicChat(Base):
|
||||
**gen_conf,
|
||||
)
|
||||
for res in response:
|
||||
if res.type == 'content_block_delta':
|
||||
if res.type == "content_block_delta":
|
||||
if res.delta.type == "thinking_delta" and res.delta.thinking:
|
||||
if ans.find("<think>") < 0:
|
||||
ans += "<think>"
|
||||
ans = ans.replace("</think>", "")
|
||||
ans = ""
|
||||
if not reasoning_start:
|
||||
reasoning_start = True
|
||||
ans = "<think>"
|
||||
ans += res.delta.thinking + "</think>"
|
||||
else:
|
||||
reasoning_start = False
|
||||
text = res.delta.text
|
||||
ans += text
|
||||
ans = text
|
||||
total_tokens += num_tokens_from_string(text)
|
||||
yield ans
|
||||
except Exception as e:
|
||||
@ -1511,13 +1398,12 @@ class AnthropicChat(Base):
|
||||
|
||||
class GoogleChat(Base):
|
||||
def __init__(self, key, model_name, base_url=None):
|
||||
from google.oauth2 import service_account
|
||||
import base64
|
||||
|
||||
from google.oauth2 import service_account
|
||||
|
||||
key = json.loads(key)
|
||||
access_token = json.loads(
|
||||
base64.b64decode(key.get("google_service_account_key", ""))
|
||||
)
|
||||
access_token = json.loads(base64.b64decode(key.get("google_service_account_key", "")))
|
||||
project_id = key.get("google_project_id", "")
|
||||
region = key.get("google_region", "")
|
||||
|
||||
@ -1530,28 +1416,20 @@ class GoogleChat(Base):
|
||||
from google.auth.transport.requests import Request
|
||||
|
||||
if access_token:
|
||||
credits = service_account.Credentials.from_service_account_info(
|
||||
access_token, scopes=scopes
|
||||
)
|
||||
credits = service_account.Credentials.from_service_account_info(access_token, scopes=scopes)
|
||||
request = Request()
|
||||
credits.refresh(request)
|
||||
token = credits.token
|
||||
self.client = AnthropicVertex(
|
||||
region=region, project_id=project_id, access_token=token
|
||||
)
|
||||
self.client = AnthropicVertex(region=region, project_id=project_id, access_token=token)
|
||||
else:
|
||||
self.client = AnthropicVertex(region=region, project_id=project_id)
|
||||
else:
|
||||
from google.cloud import aiplatform
|
||||
import vertexai.generative_models as glm
|
||||
from google.cloud import aiplatform
|
||||
|
||||
if access_token:
|
||||
credits = service_account.Credentials.from_service_account_info(
|
||||
access_token
|
||||
)
|
||||
aiplatform.init(
|
||||
credentials=credits, project=project_id, location=region
|
||||
)
|
||||
credits = service_account.Credentials.from_service_account_info(access_token)
|
||||
aiplatform.init(credentials=credits, project=project_id, location=region)
|
||||
else:
|
||||
aiplatform.init(project=project_id, location=region)
|
||||
self.client = glm.GenerativeModel(model_name=self.model_name)
|
||||
@ -1573,15 +1451,10 @@ class GoogleChat(Base):
|
||||
).json()
|
||||
ans = response["content"][0]["text"]
|
||||
if response["stop_reason"] == "max_tokens":
|
||||
ans += (
|
||||
"...\nFor the content length reason, it stopped, continue?"
|
||||
if is_english([ans])
|
||||
else "······\n由于长度的原因，回答被截断了，要继续吗？"
|
||||
)
|
||||
ans += "...\nFor the content length reason, it stopped, continue?" if is_english([ans]) else "······\n由于长度的原因，回答被截断了，要继续吗？"
|
||||
return (
|
||||
ans,
|
||||
response["usage"]["input_tokens"]
|
||||
+ response["usage"]["output_tokens"],
|
||||
response["usage"]["input_tokens"] + response["usage"]["output_tokens"],
|
||||
)
|
||||
except Exception as e:
|
||||
return "\n**ERROR**: " + str(e), 0
|
||||
@ -1598,9 +1471,7 @@ class GoogleChat(Base):
|
||||
if "content" in item:
|
||||
item["parts"] = item.pop("content")
|
||||
try:
|
||||
response = self.client.generate_content(
|
||||
history, generation_config=gen_conf
|
||||
)
|
||||
response = self.client.generate_content(history, generation_config=gen_conf)
|
||||
ans = response.text
|
||||
return ans, response.usage_metadata.total_token_count
|
||||
except Exception as e:
|
||||
@ -1627,7 +1498,7 @@ class GoogleChat(Base):
|
||||
res = res.decode("utf-8")
|
||||
if "content_block_delta" in res and "data" in res:
|
||||
text = json.loads(res[6:])["delta"]["text"]
|
||||
ans += text
|
||||
ans = text
|
||||
total_tokens += num_tokens_from_string(text)
|
||||
except Exception as e:
|
||||
yield ans + "\n**ERROR**: " + str(e)
|
||||
@ -1647,11 +1518,9 @@ class GoogleChat(Base):
|
||||
item["parts"] = item.pop("content")
|
||||
ans = ""
|
||||
try:
|
||||
response = self.model.generate_content(
|
||||
history, generation_config=gen_conf, stream=True
|
||||
)
|
||||
response = self.model.generate_content(history, generation_config=gen_conf, stream=True)
|
||||
for resp in response:
|
||||
ans += resp.text
|
||||
ans = resp.text
|
||||
yield ans
|
||||
|
||||
except Exception as e:
|
||||
|
||||
Reference in New Issue
Block a user