mirror of
https://github.com/RYDE-WORK/Langchain-Chatchat.git
synced 2026-01-26 16:53:36 +08:00
d0846f88cc
- 重构 api.py：
- 按模块划分为不同的 router
- 添加 openai 兼容的转发接口，项目默认使用该接口以实现模型负载均衡
- 添加 /tools 接口，可以获取/调用编写的 agent tools
- 移除所有 EmbeddingFuncAdapter，统一改用 get_Embeddings
- 待办：
- /chat/chat 接口改为 openai 兼容
- 添加 /chat/kb_chat 接口，openai 兼容
- 改变 ntlk/knowledge_base/logs 等数据目录位置
154 lines
4.1 KiB
Plaintext
154 lines
4.1 KiB
Plaintext
import os
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# 默认选用的 LLM 名称
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DEFAULT_LLM_MODEL = "chatglm3-6b"
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# 默认选用的 Embedding 名称
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DEFAULT_EMBEDDING_MODEL = "bge-large-zh-v1.5"
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# AgentLM模型的名称 (可以不指定，指定之后就锁定进入Agent之后的Chain的模型，不指定就是LLM_MODELS[0])
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Agent_MODEL = None
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# 历史对话轮数
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HISTORY_LEN = 3
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# 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
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MAX_TOKENS = None
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# LLM通用对话参数
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TEMPERATURE = 0.7
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# TOP_P = 0.95 # ChatOpenAI暂不支持该参数
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SUPPORT_AGENT_MODELS = [
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"chatglm3-6b",
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"openai-api",
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"Qwen-14B-Chat",
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"Qwen-7B-Chat",
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"qwen-turbo",
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]
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LLM_MODEL_CONFIG = {
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# 意图识别不需要输出，模型后台知道就行
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"preprocess_model": {
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DEFAULT_LLM_MODEL: {
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"temperature": 0.05,
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"max_tokens": 4096,
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"history_len": 100,
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"prompt_name": "default",
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"callbacks": False
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},
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},
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"llm_model": {
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DEFAULT_LLM_MODEL: {
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"temperature": 0.9,
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"max_tokens": 4096,
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"history_len": 10,
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"prompt_name": "default",
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"callbacks": True
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},
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},
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"action_model": {
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DEFAULT_LLM_MODEL: {
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"temperature": 0.01,
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"max_tokens": 4096,
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"prompt_name": "ChatGLM3",
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"callbacks": True
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},
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},
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"postprocess_model": {
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DEFAULT_LLM_MODEL: {
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"temperature": 0.01,
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"max_tokens": 4096,
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"prompt_name": "default",
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"callbacks": True
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}
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},
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"image_model": {
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"sd-turbo": {
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"size": "256*256",
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}
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},
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"multimodal_model": {
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"qwen-vl": {}
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},
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}
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# 可以通过 loom/xinference/oneapi/fastchat 启动模型服务，然后将其 URL 和 KEY 配置过来即可。
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# - platform_name 可以任意填写，不要重复即可
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# - platform_type 可选：openai, xinference, oneapi, fastchat。以后可能根据平台类型做一些功能区分
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# - 将框架部署的模型填写到对应列表即可。不同框架可以加载同名模型，项目会自动做负载均衡。
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MODEL_PLATFORMS = [
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# {
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# "platform_name": "openai-api",
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# "platform_type": "openai",
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# "api_base_url": "https://api.openai.com/v1",
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# "api_key": "sk-",
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# "api_proxy": "",
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# "api_concurrencies": 5,
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# "llm_models": [
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# "gpt-3.5-turbo",
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# ],
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# "embed_models": [],
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# "image_models": [],
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# "multimodal_models": [],
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# },
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{
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"platform_name": "xinference",
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"platform_type": "xinference",
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"api_base_url": "http://127.0.0.1:9997/v1",
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"api_key": "EMPTY",
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"api_concurrencies": 5,
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# 注意：这里填写的是 xinference 部署的模型 UID，而非模型名称
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"llm_models": [
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"chatglm3-6b",
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],
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"embed_models": [
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"bge-large-zh-v1.5",
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],
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"image_models": [
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"sd-turbo",
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],
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"multimodal_models": [
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"qwen-vl",
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],
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},
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# {
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# "platform_name": "oneapi",
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# "platform_type": "oneapi",
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# "api_base_url": "http://127.0.0.1:3000/v1",
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# "api_key": "",
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# "api_concurrencies": 5,
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# "llm_models": [
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# "qwen-turbo",
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# "qwen-plus",
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# "chatglm_turbo",
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# "chatglm_std",
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# ],
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# "embed_models": [],
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# "image_models": [],
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# "multimodal_models": [],
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# },
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# {
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# "platform_name": "loom",
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# "platform_type": "loom",
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# "api_base_url": "http://127.0.0.1:7860/v1",
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# "api_key": "",
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# "api_concurrencies": 5,
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# "llm_models": [
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# "chatglm3-6b",
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# ],
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# "embed_models": [],
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# "image_models": [],
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# "multimodal_models": [],
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# },
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]
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LOOM_CONFIG = os.path.join(os.path.dirname(os.path.abspath(__file__)), "loom.yaml")
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