ragflow/rag/llm/chat_model.py

#
#  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 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_english
from rag.utils import num_tokens_from_string


class Base(ABC):
    def __init__(self, key, model_name, base_url):
        self.client = OpenAI(api_key=key, base_url=base_url)
        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 "······\n由于长度的原因，回答被截断了，要继续吗？"
            return ans, response.usage.total_tokens
        except openai.APIError as e:
            return "**ERROR**: " + str(e), 0

    def chat_streamly(self, system, history, gen_conf):
        if system:
            history.insert(0, {"role": "system", "content": system})
        ans = ""
        total_tokens = 0
        try:
            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
                ans += resp.choices[0].delta.content
                total_tokens += 1
                if resp.choices[0].finish_reason == "length":
                    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 openai.APIError as e:
            yield ans + "\n**ERROR**: " + str(e)

        yield total_tokens


class GptTurbo(Base):
    def __init__(self, key, model_name="gpt-3.5-turbo", base_url="https://api.openai.com/v1"):
        if not base_url: base_url="https://api.openai.com/v1"
        super().__init__(key, model_name, base_url)


class MoonshotChat(Base):
    def __init__(self, key, model_name="moonshot-v1-8k", base_url="https://api.moonshot.cn/v1"):
        if not base_url: base_url="https://api.moonshot.cn/v1"
        super().__init__(key, model_name, base_url)


class XinferenceChat(Base):
    def __init__(self, key=None, model_name="", base_url=""):
        key = "xxx"
        super().__init__(key, model_name, base_url)


class DeepSeekChat(Base):
    def __init__(self, key, model_name="deepseek-chat", base_url="https://api.deepseek.com/v1"):
        if not base_url: base_url="https://api.deepseek.com/v1"
        super().__init__(key, model_name, base_url)


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

    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.total_tokens
            if response.output.choices[0].get("finish_reason", "") == "length":
                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, tk_count

        return "**ERROR**: " + response.message, tk_count

    def chat_streamly(self, system, history, gen_conf):
        from http import HTTPStatus
        if system:
            history.insert(0, {"role": "system", "content": system})
        ans = ""
        try:
            response = Generation.call(
                self.model_name,
                messages=history,
                result_format='message',
                stream=True,
                **gen_conf
            )
            tk_count = 0
            for resp in response:
                if resp.status_code == HTTPStatus.OK:
                    ans = resp.output.choices[0]['message']['content']
                    tk_count = resp.usage.total_tokens
                    if resp.output.choices[0].get("finish_reason", "") == "length":
                        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
                else:
                    yield ans + "\n**ERROR**: " + resp.message if str(resp.message).find("Access")<0 else "Out of credit. Please set the API key in **settings > Model providers.**"
        except Exception as e:
            yield ans + "\n**ERROR**: " + str(e)

        yield tk_count


class ZhipuChat(Base):
    def __init__(self, key, model_name="glm-3-turbo", **kwargs):
        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:
            if "presence_penalty" in gen_conf: 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
            )
            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 "······\n由于长度的原因，回答被截断了，要继续吗？"
            return ans, response.usage.total_tokens
        except Exception as e:
            return "**ERROR**: " + str(e), 0

    def chat_streamly(self, system, history, gen_conf):
        if system:
            history.insert(0, {"role": "system", "content": system})
        if "presence_penalty" in gen_conf: del gen_conf["presence_penalty"]
        if "frequency_penalty" in gen_conf: del gen_conf["frequency_penalty"]
        ans = ""
        try:
            response = self.client.chat.completions.create(
                model=self.model_name,
                messages=history,
                stream=True,
                **gen_conf
            )
            tk_count = 0
            for resp in response:
                if not resp.choices[0].delta.content:continue
                delta = resp.choices[0].delta.content
                ans += delta
                if resp.choices[0].finish_reason == "length":
                    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？"
                    tk_count = resp.usage.total_tokens
                if resp.choices[0].finish_reason == "stop": tk_count = resp.usage.total_tokens
                yield ans
        except Exception as e:
            yield ans + "\n**ERROR**: " + str(e)

        yield tk_count


class OllamaChat(Base):
    def __init__(self, key, model_name, **kwargs):
        self.client = Client(host=kwargs["base_url"])
        self.model_name = model_name

    def chat(self, system, history, gen_conf):
        if system:
            history.insert(0, {"role": "system", "content": system})
        try:
            options = {}
            if "temperature" in gen_conf: options["temperature"] = gen_conf["temperature"]
            if "max_tokens" in gen_conf: options["num_predict"] = gen_conf["max_tokens"]
            if "top_p" in gen_conf: options["top_k"] = gen_conf["top_p"]
            if "presence_penalty" in gen_conf: 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
            )
            ans = response["message"]["content"].strip()
            return ans, response["eval_count"] + response.get("prompt_eval_count", 0)
        except Exception as e:
            return "**ERROR**: " + str(e), 0

    def chat_streamly(self, system, history, gen_conf):
        if system:
            history.insert(0, {"role": "system", "content": system})
        options = {}
        if "temperature" in gen_conf: options["temperature"] = gen_conf["temperature"]
        if "max_tokens" in gen_conf: options["num_predict"] = gen_conf["max_tokens"]
        if "top_p" in gen_conf: options["top_k"] = gen_conf["top_p"]
        if "presence_penalty" in gen_conf: options["presence_penalty"] = gen_conf["presence_penalty"]
        if "frequency_penalty" in gen_conf: options["frequency_penalty"] = gen_conf["frequency_penalty"]
        ans = ""
        try:
            response = self.client.chat(
                model=self.model_name,
                messages=history,
                stream=True,
                options=options
            )
            for resp in response:
                if resp["done"]:
                    yield resp.get("prompt_eval_count", 0) + resp.get("eval_count", 0)
                ans += resp["message"]["content"]
                yield ans
        except Exception as e:
            yield ans + "\n**ERROR**: " + str(e)
        yield 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

    def chat_streamly(self, system, history, gen_conf):
        if system:
            history.insert(0, {"role": "system", "content": system})
        token_count = 0
        answer = ""
        try:
            for ans in self.client.chat_streamly(history, gen_conf):
                answer += ans
                token_count += 1
                yield answer
        except Exception as e:
            yield answer + "\n**ERROR**: " + str(e)

        yield token_count