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(improvement)(chat) Remove langchain4j configuration file and perform all configuration for the large model through the UI interface. (#1442)

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This commit is contained in:
lexluo09
2024-07-20 21:30:46 +08:00
committed by GitHub
parent 3797cc2ce8
commit d64ed02df9
12 changed files with 35 additions and 170 deletions
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8
common/src/main/java/com/tencent/supersonic/common/config/ChatModelParameterConfig.java
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@@ -14,6 +14,8 @@ import java.util.List;
@Slf4j
public class ChatModelParameterConfig extends ParameterConfig {
public static final Parameter CHAT_MODEL_PROVIDER =
new Parameter("s2.chat.model.provider", OpenAiModelFactory.PROVIDER,
"接口协议", "",
@@ -21,17 +23,17 @@ public class ChatModelParameterConfig extends ParameterConfig {
Lists.newArrayList(OpenAiModelFactory.PROVIDER, OllamaModelFactory.PROVIDER));
public static final Parameter CHAT_MODEL_BASE_URL =
new Parameter("s2.chat.model.base.url", "",
new Parameter("s2.chat.model.base.url", "https://api.openai.com/v1",
"BaseUrl", "",
"string", "对话模型配置");
public static final Parameter CHAT_MODEL_API_KEY =
new Parameter("s2.chat.model.api.key", "",
new Parameter("s2.chat.model.api.key", "demo",
"ApiKey", "",
"string", "对话模型配置");
public static final Parameter CHAT_MODEL_NAME =
new Parameter("s2.chat.model.name", "",
new Parameter("s2.chat.model.name", "gpt-3.5-turbo",
"ModelName", "",
"string", "对话模型配置");

8
common/src/main/java/com/tencent/supersonic/common/config/EmbeddingModelParameterConfig.java
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@@ -3,6 +3,7 @@ package com.tencent.supersonic.common.config;
import com.google.common.collect.Lists;
import com.tencent.supersonic.common.pojo.EmbeddingModelConfig;
import com.tencent.supersonic.common.pojo.Parameter;
import dev.langchain4j.inmemory.spring.InMemoryAutoConfig;
import dev.langchain4j.provider.AzureModelFactory;
import dev.langchain4j.provider.DashscopeModelFactory;
import dev.langchain4j.provider.InMemoryModelFactory;
@@ -20,7 +21,7 @@ import java.util.List;
public class EmbeddingModelParameterConfig extends ParameterConfig {
public static final Parameter EMBEDDING_MODEL_PROVIDER =
new Parameter("s2.embedding.model.provider", "",
new Parameter("s2.embedding.model.provider", InMemoryModelFactory.PROVIDER,
"接口协议", "",
"string", "向量模型配置",
Lists.newArrayList(InMemoryModelFactory.PROVIDER,
@@ -43,9 +44,10 @@ public class EmbeddingModelParameterConfig extends ParameterConfig {
public static final Parameter EMBEDDING_MODEL_NAME =
new Parameter("s2.embedding.model.name", "",
new Parameter("s2.embedding.model.name", InMemoryAutoConfig.BGE_SMALL_ZH,
"ModelName", "",
"string", "向量模型配置");
"string", "向量模型配置",
Lists.newArrayList(InMemoryAutoConfig.BGE_SMALL_ZH, InMemoryAutoConfig.ALL_MINILM_L6_V2));
public static final Parameter EMBEDDING_MODEL_PATH =
new Parameter("s2.embedding.model.path", "",

8
common/src/main/java/com/tencent/supersonic/common/config/EmbeddingStoreParameterConfig.java
View File

@@ -3,6 +3,7 @@ package com.tencent.supersonic.common.config;
import com.google.common.collect.Lists;
import com.tencent.supersonic.common.pojo.EmbeddingStoreConfig;
import com.tencent.supersonic.common.pojo.Parameter;
import dev.langchain4j.store.embedding.EmbeddingStoreType;
import lombok.extern.slf4j.Slf4j;
import org.springframework.stereotype.Service;
@@ -12,9 +13,12 @@ import java.util.List;
@Slf4j
public class EmbeddingStoreParameterConfig extends ParameterConfig {
public static final Parameter EMBEDDING_STORE_PROVIDER =
new Parameter("s2.embedding.store.provider", "",
new Parameter("s2.embedding.store.provider", EmbeddingStoreType.IN_MEMORY.name(),
"向量库类型", "",
"string", "向量库配置");
"string", "向量库配置",
Lists.newArrayList(EmbeddingStoreType.IN_MEMORY.name(),
EmbeddingStoreType.MILVUS.name(),
EmbeddingStoreType.CHROMA.name()));
public static final Parameter EMBEDDING_STORE_BASE_URL =
new Parameter("s2.embedding.store.base.url", "",

21
common/src/main/java/dev/langchain4j/provider/ModelProvider.java
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@@ -1,5 +1,6 @@
package dev.langchain4j.provider;
import com.tencent.supersonic.common.config.ChatModelParameterConfig;
import com.tencent.supersonic.common.config.EmbeddingModelParameterConfig;
import com.tencent.supersonic.common.pojo.ChatModelConfig;
import com.tencent.supersonic.common.pojo.EmbeddingModelConfig;
@@ -18,11 +19,16 @@ public class ModelProvider {
factories.put(provider, modelFactory);
}
public static ChatLanguageModel getChatModel() {
return getChatModel(null);
}
public static ChatLanguageModel getChatModel(ChatModelConfig modelConfig) {
if (modelConfig == null
|| StringUtils.isBlank(modelConfig.getProvider())
if (modelConfig == null || StringUtils.isBlank(modelConfig.getProvider())
|| StringUtils.isBlank(modelConfig.getBaseUrl())) {
return ContextUtils.getBean(ChatLanguageModel.class);
ChatModelParameterConfig parameterConfig = ContextUtils.getBean(
ChatModelParameterConfig.class);
modelConfig = parameterConfig.convert();
}
ModelFactory modelFactory = factories.get(modelConfig.getProvider().toUpperCase());
if (modelFactory != null) {
@@ -33,15 +39,14 @@ public class ModelProvider {
}
public static EmbeddingModel getEmbeddingModel() {
EmbeddingModelParameterConfig parameterConfig = ContextUtils.getBean(
EmbeddingModelParameterConfig.class);
EmbeddingModelConfig embeddingModelConfig = parameterConfig.convert();
return getEmbeddingModel(embeddingModelConfig);
return getEmbeddingModel(null);
}
public static EmbeddingModel getEmbeddingModel(EmbeddingModelConfig embeddingModel) {
if (embeddingModel == null || StringUtils.isBlank(embeddingModel.getProvider())) {
return ContextUtils.getBean(EmbeddingModel.class);
EmbeddingModelParameterConfig parameterConfig = ContextUtils.getBean(
EmbeddingModelParameterConfig.class);
embeddingModel = parameterConfig.convert();
}
ModelFactory modelFactory = factories.get(embeddingModel.getProvider().toUpperCase());
if (modelFactory != null) {

6
headless/server/src/main/java/com/tencent/supersonic/headless/server/utils/AliasGenerateHelper.java
View File

@@ -5,8 +5,8 @@ import dev.langchain4j.data.message.AiMessage;
import dev.langchain4j.data.message.SystemMessage;
import dev.langchain4j.model.chat.ChatLanguageModel;
import dev.langchain4j.model.output.Response;
import dev.langchain4j.provider.ModelProvider;
import lombok.extern.slf4j.Slf4j;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Component;
@@ -14,11 +14,9 @@ import org.springframework.stereotype.Component;
@Slf4j
public class AliasGenerateHelper {
@Autowired
private ChatLanguageModel chatLanguageModel;
public String getChatCompletion(String message) {
SystemMessage from = SystemMessage.from(message);
ChatLanguageModel chatLanguageModel = ModelProvider.getChatModel();
Response<AiMessage> response = chatLanguageModel.generate(from);
log.info("message:{}\n response:{}", message, response);
return response.content().text();

13
launchers/standalone/src/main/resources/META-INF/spring.factories
View File

@@ -80,15 +80,4 @@ com.tencent.supersonic.auth.authentication.interceptor.AuthenticationInterceptor
com.tencent.supersonic.auth.authentication.interceptor.DefaultAuthenticationInterceptor
com.tencent.supersonic.auth.api.authentication.adaptor.UserAdaptor=\
com.tencent.supersonic.auth.authentication.adaptor.DefaultUserAdaptor
### common SPIs
org.springframework.boot.autoconfigure.EnableAutoConfiguration=\
dev.langchain4j.spring.LangChain4jAutoConfig,\
dev.langchain4j.openai.spring.AutoConfig,\
dev.langchain4j.ollama.spring.AutoConfig,\
dev.langchain4j.azure.openai.spring.AutoConfig,\
dev.langchain4j.azure.aisearch.spring.AutoConfig,\
dev.langchain4j.anthropic.spring.AutoConfig
com.tencent.supersonic.auth.authentication.adaptor.DefaultUserAdaptor

5
launchers/standalone/src/main/resources/application-local.yaml
View File

@@ -11,7 +11,4 @@ spring:
h2:
console:
path: /h2-console/semantic
enabled: true
config:
import:
- classpath:langchain4j-local.yaml
enabled: true

5
launchers/standalone/src/main/resources/application-prd.yaml
View File

@@ -3,7 +3,4 @@ spring:
url: jdbc:mysql://${DB_HOST}:${DB_PORT:3306}/${DB_NAME}?useUnicode=true&characterEncoding=UTF-8&useSSL=false&allowMultiQueries=true&allowPublicKeyRetrieval=true
username: ${DB_USERNAME}
password: ${DB_PASSWORD}
driver-class-name: com.mysql.jdbc.Driver
config:
import:
- classpath:langchain4j-prd.yaml
driver-class-name: com.mysql.jdbc.Driver

42
launchers/standalone/src/main/resources/langchain4j-local.yaml
View File

@@ -1,42 +0,0 @@
langchain4j:
# Replace `open_ai` with ollama/zhipu/azure/dashscope as needed.
# Note:
# 1. `open_ai` is commonly used to connect to cloud-based models;
# 2. `ollama` is commonly used to connect to local models.
open-ai:
chat-model:
# It is recommended to replace with your API key in production.
# Note: The default API key `demo` is provided by langchain4j community
# which limits 1000 tokens per request.
base-url: ${OPENAI_API_BASE:https://api.openai.com/v1}
api-key: ${OPENAI_API_KEY:demo}
model-name: ${OPENAI_MODEL_NAME:gpt-3.5-turbo}
temperature: ${OPENAI_TEMPERATURE:0.0}
timeout: ${OPENAI_TIMEOUT:PT60S}
# embedding-model:
# base-url: https://api.openai.com/v1
# api-key: demo
# model-name: text-embedding-3-small
# timeout: PT60S
in-memory:
embedding-model:
model-name: bge-small-zh
embedding-store:
persist-path: /tmp
# chroma:
# embedding-store:
# baseUrl: http://0.0.0.0:8000
# timeout: 120s
# milvus:
# embedding-store:
# host: localhost
# port: 2379
# uri: http://0.0.0.0:19530
# token: demo
# dimension: 512
# timeout: 120s

42
launchers/standalone/src/main/resources/langchain4j-prd.yaml
View File

@@ -1,42 +0,0 @@
langchain4j:
# Replace `open_ai` with ollama/zhipu/azure/dashscope as needed.
# Note:
# 1. `open_ai` is commonly used to connect to cloud-based models;
# 2. `ollama` is commonly used to connect to local models.
open-ai:
chat-model:
# It is recommended to replace with your API key in production.
# Note: The default API key `demo` is provided by langchain4j community
# which limits 1000 tokens per request.
base-url: ${OPENAI_API_BASE:https://api.openai.com/v1}
api-key: ${OPENAI_API_KEY:demo}
model-name: ${OPENAI_MODEL_NAME:gpt-3.5-turbo}
temperature: ${OPENAI_TEMPERATURE:0.0}
timeout: ${OPENAI_TIMEOUT:PT60S}
# embedding-model:
# base-url: https://api.openai.com/v1
# api-key: demo
# model-name: text-embedding-3-small
# timeout: PT60S
in-memory:
embedding-model:
model-name: bge-small-zh
# embedding-store:
# persist-path: /tmp
chroma:
embedding-store:
baseUrl: http://${CHROMA_HOST}:8000
timeout: 120s
# milvus:
# embedding-store:
# host: localhost
# port: 2379
# uri: http://0.0.0.0:19530
# token: demo
# dimension: 512
# timeout: 120s

5
launchers/standalone/src/test/resources/application-local.yaml
View File

@@ -11,7 +11,4 @@ spring:
h2:
console:
path: /h2-console/semantic
enabled: true
config:
import:
- classpath:langchain4j-local.yaml
enabled: true

42
launchers/standalone/src/test/resources/langchain4j-local.yaml
View File

@@ -1,42 +0,0 @@
langchain4j:
# Replace `open_ai` with ollama/zhipu/azure/dashscope as needed.
# Note:
# 1. `open_ai` is commonly used to connect to cloud-based models;
# 2. `ollama` is commonly used to connect to local models.
open-ai:
chat-model:
# It is recommended to replace with your API key in production.
# Note: The default API key `demo` is provided by langchain4j community
# which limits 1000 tokens per request.
base-url: ${OPENAI_API_BASE:https://api.openai.com/v1}
api-key: ${OPENAI_API_KEY:demo}
model-name: ${OPENAI_MODEL_NAME:gpt-3.5-turbo}
temperature: ${OPENAI_TEMPERATURE:0.0}
timeout: ${OPENAI_TIMEOUT:PT60S}
# embedding-model:
# base-url: https://api.openai.com/v1
# api-key: demo
# model-name: text-embedding-3-small
# timeout: PT60S
in-memory:
embedding-model:
model-name: bge-small-zh
embedding-store:
persist-path: /tmp
# chroma:
# embedding-store:
# baseUrl: http://0.0.0.0:8000
# timeout: 120s
# milvus:
# embedding-store:
# host: localhost
# port: 2379
# uri: http://0.0.0.0:19530
# token: demo
# dimension: 512
# timeout: 120s