fun.freechat.client.model.OpenAiParamDTO Maven / Gradle / Ivy
/*
* FreeChat OpenAPI Definition
* # FreeChat: Create Friends for Yourself with AI English | [中文版](https://github.com/freechat-fun/freechat/blob/main/README.zh-CN.md) ## Introduction Welcome! FreeChat aims to build a cloud-native, robust, and quickly commercializable enterprise-level AI virtual character platform. It also serves as a prompt engineering platform. ## Features - Primarily uses Java and emphasizes **security, robustness, scalability, traceability, and maintainability**. - Boasts **account systems and permission management**, supporting OAuth2 authentication. Introduces the \"organization\" concept and related permission constraint functions. - Extensively employs distributed technologies and caching to support **high concurrency** access. - Provides flexible character customization options, supports direct intervention in prompts, and supports **configuring multiple backends for each character**. - **Offers a comprehensive range of Open APIs**, with more than 180 interfaces and provides java/python/typescript SDKs. These interfaces enable easy construction of systems for end-users. - Supports setting **RAG** (Retrieval Augmented Generation) for characters. - Supports **long-term memory, preset memory** for characters. - Supports characters evoking **proactive chat**. - Supports setting **quota limits** for characters. - Supports characters **importing and exporting**. - Supports individual **debugging and sharing prompts**. ## Snapshots ### On PC #### Home Page  #### Development View  #### Chat View  ### On Mobile  
  ## Character Design ```mermaid flowchart TD A(Character) --> B(Profile) A --> C(Knowledge/RAG) A --> D(Album) A --> E(Backend-1) A --> F(Backend-n...) E --> G(Message Window) E --> H(Long Term Memory Settings) E --> I(Quota Limit) E --> J(Chat Prompt Task) E --> K(Greeting Prompt Task) E --> L(Moderation Settings) J --> M(Model & Parameters) J --> N(API Keys) J --> O(Prompt Refence) J --> P(Tool Specifications) O --> Q(Template) O --> R(Variables) O --> S(Version) O --> T(...) style K stroke-dasharray: 5, 5 style L stroke-dasharray: 5, 5 style P stroke-dasharray: 5, 5 ``` After setting up an unified persona and knowledge for a character, different backends can be configured. For example, different model may be adopted for different users based on cost considerations. ## How to Play ### Online Website You can visit [freechat.fun](https://freechat.fun) to experience FreeChat. Share your designed AI character! ### Running in a Kubernetes Cluster FreeChat is dedicated to the principles of cloud-native design. If you have a Kubernetes cluster, you can deploy FreeChat to your environment by following these steps: 1. Put the Kubernetes configuration file in the `configs/helm/` directory, named `kube-private.conf`. 2. Place the Helm configuration file in the same directory, named `values-private.yaml`. Make sure to reference the default `values.yaml` and customize the variables as needed. 3. Switch to the `scripts/` directory. 4. If needed, run `install-in.sh` to deploy `ingress-nginx` on the Kubernetes cluster. 5. If needed, run `install-cm.sh` to deploy `cert-manager` on the Kubernetes cluster, which automatically issues certificates for domains specified in `ingress.hosts`. 6. Run `install-pvc.sh` to install PersistentVolumeClaim resources. > By default, FreeChat operates files by accessing the \"local file system.\" You may want to use high-availability distributed storage in the cloud. As a cloud-native-designed system, we recommend interfacing through Kubernetes CSI to avoid individually adapting storage products for each cloud platform. Most cloud service providers offer cloud storage drivers for Kubernetes, with a series of predefined StorageClass resources. Please choose the appropriate configuration according to your actual needs and set it in Helm's `global.storageClass` option. > > *In the future, FreeChat may be refactored to use MinIO's APIs directly, as it is now installed in the Kubernetes cluster as a dependency (serving Milvus).* 7. Run `install.sh` script to install FreeChat and its dependencies. 8. FreeChat aims to provide Open API services. If you like the interactive experience of [freechat.fun](https://freechat.fun), run `install-web.sh` to deploy the front-end application. 9. Run `restart.sh` to restart the service. 10. If you modified any Helm configuration files, use `upgrade.sh` to update the corresponding Kubernetes resources. 11. To remove specific resources, run the `uninstall*.sh` script corresponding to the resource you want to uninstall. As a cloud-native application, the services FreeChat relies on are obtained and deployed to your cluster through the helm repository. If you prefer cloud services with SLA (Service Level Agreement) guarantees, simply make the relevant settings in `configs/helm/values-private.yaml`: ```yaml mysql: deployment: enabled: false url: auth: rootPassword: username: password: redis: deployment: enabled: false url: auth: password: milvus: deployment: enabled: false url: milvus: auth: token: ``` With this, FreeChat will not automatically install these services, but rather use the configuration information to connect directly. If your Kubernetes cluster does not have a standalone monitoring system, you can enable the following switch. This will install Prometheus and Grafana services in the same namespace, dedicated to monitoring the status of the services under the FreeChat application: ```yaml prometheus: deployment: enabled: true grafana: deployment: enabled: true ``` ### Running Locally You can also run FreeChat locally. Currently supported on MacOS and Linux (although only tested on MacOS). You need to install the Docker toolset and have a network that can access [Docker Hub](https://hub.docker.com/). Once ready, enter the `scripts/` directory and run `local-run.sh`, which will download and run the necessary docker containers. After a successful startup, you can access `http://localhost` via a browser to see the locally running freechat.fun. The built-in administrator username and password are \"admin:freechat\". Use `local-run.sh --help` to view the supported options of the script. Good luck! ### Running in an IDE To run FreeChat in an IDE, you need to start all dependent services first but do not need to run the container for the FreeChat application itself. You can execute the `scripts/local-deps.sh` script to start services like `MySQL`, `Redis`, `Milvus`, etc., locally. Once done, open and debug `freechat-start/src/main/java/fun/freechat/Application.java`。Make sure you have set the following startup VM options: ```shell -Dspring.config.location=classpath:/application.yml,classpath:/application-local.yml \\ -DAPP_HOME=local-data/freechat \\ -Dspring.profiles.active=local ``` ### Use SDK #### Java - **Dependency** ```xml fun.freechat freechat-sdk ${freechat-sdk.version} ``` - **Example** ```java import fun.freechat.client.ApiClient; import fun.freechat.client.ApiException; import fun.freechat.client.Configuration; import fun.freechat.client.api.AccountApi; import fun.freechat.client.auth.ApiKeyAuth; import fun.freechat.client.model.UserDetailsDTO; public class AccountClientExample { public static void main(String[] args) { ApiClient defaultClient = Configuration.getDefaultApiClient(); defaultClient.setBasePath(\"https://freechat.fun\"); // Configure HTTP bearer authorization: bearerAuth HttpBearerAuth bearerAuth = (HttpBearerAuth) defaultClient.getAuthentication(\"bearerAuth\"); bearerAuth.setBearerToken(\"FREECHAT_TOKEN\"); AccountApi apiInstance = new AccountApi(defaultClient); try { UserDetailsDTO result = apiInstance.getUserDetails(); System.out.println(result); } catch (ApiException e) { e.printStackTrace(); } } } ``` #### Python - **Installation** ```shell pip install freechat-sdk ``` - **Example** ```python import freechat_sdk from freechat_sdk.rest import ApiException from pprint import pprint # Defining the host is optional and defaults to https://freechat.fun # See configuration.py for a list of all supported configuration parameters. configuration = freechat_sdk.Configuration( host = \"https://freechat.fun\" ) # Configure Bearer authorization: bearerAuth configuration = freechat_sdk.Configuration( access_token = os.environ[\"FREECHAT_TOKEN\"] ) # Enter a context with an instance of the API client with freechat_sdk.ApiClient(configuration) as api_client: # Create an instance of the API class api_instance = freechat_sdk.AccountApi(api_client) try: details = api_instance.get_user_details() pprint(details) except ApiException as e: print(\"Exception when calling AccountClient->get_user_details: %s\\n\" % e) ``` #### TypeScript - **Installation** ```shell npm install freechat-sdk --save ``` - **Example** Refer to [FreeChatApiContext.tsx](https://github.com/freechat-fun/freechat/blob/main/freechat-web/src/contexts/FreeChatApiProvider.tsx) ## System Dependencies | | Projects | ---- | ---- | Application Framework | [Spring Boot](https://spring.io/projects/spring-boot/) | LLM Framework | [LangChain4j](https://docs.langchain4j.dev/) | Model Providers | [OpenAI](https://platform.openai.com/), [Azure OpenAI](https://oai.azure.com/), [DashScope(Alibaba)](https://dashscope.aliyun.com/) | Database Systems | [MySQL](https://www.mysql.com/), [Redis](https://redis.io/), [Milvus](https://milvus.io/) | Monitoring & Alerting | [Kube State Metrics](https://kubernetes.io/docs/concepts/cluster-administration/kube-state-metrics/), [Prometheus](https://prometheus.io/), [Promtail](https://grafana.com/docs/loki/latest/send-data/promtail/), [Loki](https://grafana.com/oss/loki/), [Grafana](https://grafana.com/) | OpenAPI Tools | [Springdoc-openapi](https://springdoc.org/), [OpenAPI Generator](https://github.com/OpenAPITools/openapi-generator), [OpenAPI Explorer](https://github.com/Authress-Engineering/openapi-explorer) ## Collaboration ### Application Integration The FreeChat system is entirely oriented towards Open APIs. The site [freechat.fun](https://freechat.fun) is developed using its TypeScript SDK and hardly depends on private interfaces. You can use these online interfaces to develop your own applications or sites, making them fit your preferences. Currently, FreeChat is completely free with no paid plans (after all, users use their own API Key to call LLM services). ### Model Integration FreeChat aims to explore AI virtual character technology with anthropomorphic characteristics. So far, it supports model services from OpenAI GPT and Alibaba Qwen series models. However, we are more interested in supporting models that are under research and can endow AI with more personality traits. If you are researching this area and hope FreeChat supports your model, please contact us. We look forward to AI technology helping people create their own \"soul mates\" in the future.
*
* The version of the OpenAPI document: 2.0.0
*
*
* NOTE: This class is auto generated by OpenAPI Generator (https://openapi-generator.tech).
* https://openapi-generator.tech
* Do not edit the class manually.
*/
package fun.freechat.client.model;
import java.util.Objects;
import com.google.gson.TypeAdapter;
import com.google.gson.annotations.JsonAdapter;
import com.google.gson.annotations.SerializedName;
import com.google.gson.stream.JsonReader;
import com.google.gson.stream.JsonWriter;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import com.google.gson.Gson;
import com.google.gson.GsonBuilder;
import com.google.gson.JsonArray;
import com.google.gson.JsonDeserializationContext;
import com.google.gson.JsonDeserializer;
import com.google.gson.JsonElement;
import com.google.gson.JsonObject;
import com.google.gson.JsonParseException;
import com.google.gson.TypeAdapterFactory;
import com.google.gson.reflect.TypeToken;
import com.google.gson.TypeAdapter;
import com.google.gson.stream.JsonReader;
import com.google.gson.stream.JsonWriter;
import java.io.IOException;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;
import fun.freechat.client.JSON;
/**
* OpenAI series model parameters
*/
@javax.annotation.Generated(value = "org.openapitools.codegen.languages.JavaClientCodegen", comments = "Generator version: 7.9.0")
public class OpenAiParamDTO {
public static final String SERIALIZED_NAME_API_KEY = "apiKey";
@SerializedName(SERIALIZED_NAME_API_KEY)
private String apiKey;
public static final String SERIALIZED_NAME_API_KEY_NAME = "apiKeyName";
@SerializedName(SERIALIZED_NAME_API_KEY_NAME)
private String apiKeyName;
public static final String SERIALIZED_NAME_MODEL_ID = "modelId";
@SerializedName(SERIALIZED_NAME_MODEL_ID)
private String modelId;
public static final String SERIALIZED_NAME_BASE_URL = "baseUrl";
@SerializedName(SERIALIZED_NAME_BASE_URL)
private String baseUrl;
public static final String SERIALIZED_NAME_TEMPERATURE = "temperature";
@SerializedName(SERIALIZED_NAME_TEMPERATURE)
private Double temperature;
public static final String SERIALIZED_NAME_TOP_P = "topP";
@SerializedName(SERIALIZED_NAME_TOP_P)
private Double topP;
public static final String SERIALIZED_NAME_MAX_TOKENS = "maxTokens";
@SerializedName(SERIALIZED_NAME_MAX_TOKENS)
private Integer maxTokens;
public static final String SERIALIZED_NAME_PRESENCE_PENALTY = "presencePenalty";
@SerializedName(SERIALIZED_NAME_PRESENCE_PENALTY)
private Double presencePenalty;
public static final String SERIALIZED_NAME_FREQUENCY_PENALTY = "frequencyPenalty";
@SerializedName(SERIALIZED_NAME_FREQUENCY_PENALTY)
private Double frequencyPenalty;
public static final String SERIALIZED_NAME_SEED = "seed";
@SerializedName(SERIALIZED_NAME_SEED)
private Integer seed;
public static final String SERIALIZED_NAME_STOP = "stop";
@SerializedName(SERIALIZED_NAME_STOP)
private List stop = new ArrayList<>();
public OpenAiParamDTO() {
}
public OpenAiParamDTO apiKey(String apiKey) {
this.apiKey = apiKey;
return this;
}
/**
* API-KEY, higher priority than apiKeyName. Either apiKey or apiKeyName must be specified.
* @return apiKey
*/
@javax.annotation.Nullable
public String getApiKey() {
return apiKey;
}
public void setApiKey(String apiKey) {
this.apiKey = apiKey;
}
public OpenAiParamDTO apiKeyName(String apiKeyName) {
this.apiKeyName = apiKeyName;
return this;
}
/**
* API-KEY name
* @return apiKeyName
*/
@javax.annotation.Nullable
public String getApiKeyName() {
return apiKeyName;
}
public void setApiKeyName(String apiKeyName) {
this.apiKeyName = apiKeyName;
}
public OpenAiParamDTO modelId(String modelId) {
this.modelId = modelId;
return this;
}
/**
* Model identifier
* @return modelId
*/
@javax.annotation.Nonnull
public String getModelId() {
return modelId;
}
public void setModelId(String modelId) {
this.modelId = modelId;
}
public OpenAiParamDTO baseUrl(String baseUrl) {
this.baseUrl = baseUrl;
return this;
}
/**
* OpenAI service provider address, default: https://api.openai.com/v1
* @return baseUrl
*/
@javax.annotation.Nullable
public String getBaseUrl() {
return baseUrl;
}
public void setBaseUrl(String baseUrl) {
this.baseUrl = baseUrl;
}
public OpenAiParamDTO temperature(Double temperature) {
this.temperature = temperature;
return this;
}
/**
* Used to adjust the degree of randomness from sampling in the generated model, the value range is (0, 1.0), a temperature of 0 will always produce the same output. The higher the temperature, the greater the randomness.
* @return temperature
*/
@javax.annotation.Nullable
public Double getTemperature() {
return temperature;
}
public void setTemperature(Double temperature) {
this.temperature = temperature;
}
public OpenAiParamDTO topP(Double topP) {
this.topP = topP;
return this;
}
/**
* Probability threshold of the nucleus sampling method in the generation process, for example, when the value is 0.8, only the smallest set of most likely tokens whose probabilities add up to 0.8 or more is retained as the candidate set. The value range is (0, 1.0), the larger the value, the higher the randomness of the generation; the smaller the value, the higher the certainty of the generation.
* @return topP
*/
@javax.annotation.Nullable
public Double getTopP() {
return topP;
}
public void setTopP(Double topP) {
this.topP = topP;
}
public OpenAiParamDTO maxTokens(Integer maxTokens) {
this.maxTokens = maxTokens;
return this;
}
/**
* The maximum number of tokens to generate in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length.
* @return maxTokens
*/
@javax.annotation.Nullable
public Integer getMaxTokens() {
return maxTokens;
}
public void setMaxTokens(Integer maxTokens) {
this.maxTokens = maxTokens;
}
public OpenAiParamDTO presencePenalty(Double presencePenalty) {
this.presencePenalty = presencePenalty;
return this;
}
/**
* Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
* @return presencePenalty
*/
@javax.annotation.Nullable
public Double getPresencePenalty() {
return presencePenalty;
}
public void setPresencePenalty(Double presencePenalty) {
this.presencePenalty = presencePenalty;
}
public OpenAiParamDTO frequencyPenalty(Double frequencyPenalty) {
this.frequencyPenalty = frequencyPenalty;
return this;
}
/**
* Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
* @return frequencyPenalty
*/
@javax.annotation.Nullable
public Double getFrequencyPenalty() {
return frequencyPenalty;
}
public void setFrequencyPenalty(Double frequencyPenalty) {
this.frequencyPenalty = frequencyPenalty;
}
public OpenAiParamDTO seed(Integer seed) {
this.seed = seed;
return this;
}
/**
* If specified, OpenAI will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result.
* @return seed
*/
@javax.annotation.Nullable
public Integer getSeed() {
return seed;
}
public void setSeed(Integer seed) {
this.seed = seed;
}
public OpenAiParamDTO stop(List stop) {
this.stop = stop;
return this;
}
public OpenAiParamDTO addStopItem(String stopItem) {
if (this.stop == null) {
this.stop = new ArrayList<>();
}
this.stop.add(stopItem);
return this;
}
/**
* A collection of stop words that controls the API from generating more tokens.
* @return stop
*/
@javax.annotation.Nullable
public List getStop() {
return stop;
}
public void setStop(List stop) {
this.stop = stop;
}
/**
* A container for additional, undeclared properties.
* This is a holder for any undeclared properties as specified with
* the 'additionalProperties' keyword in the OAS document.
*/
private Map additionalProperties;
/**
* Set the additional (undeclared) property with the specified name and value.
* If the property does not already exist, create it otherwise replace it.
*
* @param key name of the property
* @param value value of the property
* @return the OpenAiParamDTO instance itself
*/
public OpenAiParamDTO putAdditionalProperty(String key, Object value) {
if (this.additionalProperties == null) {
this.additionalProperties = new HashMap();
}
this.additionalProperties.put(key, value);
return this;
}
/**
* Return the additional (undeclared) property.
*
* @return a map of objects
*/
public Map getAdditionalProperties() {
return additionalProperties;
}
/**
* Return the additional (undeclared) property with the specified name.
*
* @param key name of the property
* @return an object
*/
public Object getAdditionalProperty(String key) {
if (this.additionalProperties == null) {
return null;
}
return this.additionalProperties.get(key);
}
@Override
public boolean equals(Object o) {
if (this == o) {
return true;
}
if (o == null || getClass() != o.getClass()) {
return false;
}
OpenAiParamDTO openAiParamDTO = (OpenAiParamDTO) o;
return Objects.equals(this.apiKey, openAiParamDTO.apiKey) &&
Objects.equals(this.apiKeyName, openAiParamDTO.apiKeyName) &&
Objects.equals(this.modelId, openAiParamDTO.modelId) &&
Objects.equals(this.baseUrl, openAiParamDTO.baseUrl) &&
Objects.equals(this.temperature, openAiParamDTO.temperature) &&
Objects.equals(this.topP, openAiParamDTO.topP) &&
Objects.equals(this.maxTokens, openAiParamDTO.maxTokens) &&
Objects.equals(this.presencePenalty, openAiParamDTO.presencePenalty) &&
Objects.equals(this.frequencyPenalty, openAiParamDTO.frequencyPenalty) &&
Objects.equals(this.seed, openAiParamDTO.seed) &&
Objects.equals(this.stop, openAiParamDTO.stop)&&
Objects.equals(this.additionalProperties, openAiParamDTO.additionalProperties);
}
@Override
public int hashCode() {
return Objects.hash(apiKey, apiKeyName, modelId, baseUrl, temperature, topP, maxTokens, presencePenalty, frequencyPenalty, seed, stop, additionalProperties);
}
@Override
public String toString() {
StringBuilder sb = new StringBuilder();
sb.append("class OpenAiParamDTO {\n");
sb.append(" apiKey: ").append(toIndentedString(apiKey)).append("\n");
sb.append(" apiKeyName: ").append(toIndentedString(apiKeyName)).append("\n");
sb.append(" modelId: ").append(toIndentedString(modelId)).append("\n");
sb.append(" baseUrl: ").append(toIndentedString(baseUrl)).append("\n");
sb.append(" temperature: ").append(toIndentedString(temperature)).append("\n");
sb.append(" topP: ").append(toIndentedString(topP)).append("\n");
sb.append(" maxTokens: ").append(toIndentedString(maxTokens)).append("\n");
sb.append(" presencePenalty: ").append(toIndentedString(presencePenalty)).append("\n");
sb.append(" frequencyPenalty: ").append(toIndentedString(frequencyPenalty)).append("\n");
sb.append(" seed: ").append(toIndentedString(seed)).append("\n");
sb.append(" stop: ").append(toIndentedString(stop)).append("\n");
sb.append(" additionalProperties: ").append(toIndentedString(additionalProperties)).append("\n");
sb.append("}");
return sb.toString();
}
/**
* Convert the given object to string with each line indented by 4 spaces
* (except the first line).
*/
private String toIndentedString(Object o) {
if (o == null) {
return "null";
}
return o.toString().replace("\n", "\n ");
}
public static HashSet openapiFields;
public static HashSet openapiRequiredFields;
static {
// a set of all properties/fields (JSON key names)
openapiFields = new HashSet();
openapiFields.add("apiKey");
openapiFields.add("apiKeyName");
openapiFields.add("modelId");
openapiFields.add("baseUrl");
openapiFields.add("temperature");
openapiFields.add("topP");
openapiFields.add("maxTokens");
openapiFields.add("presencePenalty");
openapiFields.add("frequencyPenalty");
openapiFields.add("seed");
openapiFields.add("stop");
// a set of required properties/fields (JSON key names)
openapiRequiredFields = new HashSet();
openapiRequiredFields.add("modelId");
}
/**
* Validates the JSON Element and throws an exception if issues found
*
* @param jsonElement JSON Element
* @throws IOException if the JSON Element is invalid with respect to OpenAiParamDTO
*/
public static void validateJsonElement(JsonElement jsonElement) throws IOException {
if (jsonElement == null) {
if (!OpenAiParamDTO.openapiRequiredFields.isEmpty()) { // has required fields but JSON element is null
throw new IllegalArgumentException(String.format("The required field(s) %s in OpenAiParamDTO is not found in the empty JSON string", OpenAiParamDTO.openapiRequiredFields.toString()));
}
}
// check to make sure all required properties/fields are present in the JSON string
for (String requiredField : OpenAiParamDTO.openapiRequiredFields) {
if (jsonElement.getAsJsonObject().get(requiredField) == null) {
throw new IllegalArgumentException(String.format("The required field `%s` is not found in the JSON string: %s", requiredField, jsonElement.toString()));
}
}
JsonObject jsonObj = jsonElement.getAsJsonObject();
if ((jsonObj.get("apiKey") != null && !jsonObj.get("apiKey").isJsonNull()) && !jsonObj.get("apiKey").isJsonPrimitive()) {
throw new IllegalArgumentException(String.format("Expected the field `apiKey` to be a primitive type in the JSON string but got `%s`", jsonObj.get("apiKey").toString()));
}
if ((jsonObj.get("apiKeyName") != null && !jsonObj.get("apiKeyName").isJsonNull()) && !jsonObj.get("apiKeyName").isJsonPrimitive()) {
throw new IllegalArgumentException(String.format("Expected the field `apiKeyName` to be a primitive type in the JSON string but got `%s`", jsonObj.get("apiKeyName").toString()));
}
if (!jsonObj.get("modelId").isJsonPrimitive()) {
throw new IllegalArgumentException(String.format("Expected the field `modelId` to be a primitive type in the JSON string but got `%s`", jsonObj.get("modelId").toString()));
}
if ((jsonObj.get("baseUrl") != null && !jsonObj.get("baseUrl").isJsonNull()) && !jsonObj.get("baseUrl").isJsonPrimitive()) {
throw new IllegalArgumentException(String.format("Expected the field `baseUrl` to be a primitive type in the JSON string but got `%s`", jsonObj.get("baseUrl").toString()));
}
// ensure the optional json data is an array if present
if (jsonObj.get("stop") != null && !jsonObj.get("stop").isJsonNull() && !jsonObj.get("stop").isJsonArray()) {
throw new IllegalArgumentException(String.format("Expected the field `stop` to be an array in the JSON string but got `%s`", jsonObj.get("stop").toString()));
}
}
public static class CustomTypeAdapterFactory implements TypeAdapterFactory {
@SuppressWarnings("unchecked")
@Override
public TypeAdapter create(Gson gson, TypeToken type) {
if (!OpenAiParamDTO.class.isAssignableFrom(type.getRawType())) {
return null; // this class only serializes 'OpenAiParamDTO' and its subtypes
}
final TypeAdapter elementAdapter = gson.getAdapter(JsonElement.class);
final TypeAdapter thisAdapter
= gson.getDelegateAdapter(this, TypeToken.get(OpenAiParamDTO.class));
return (TypeAdapter) new TypeAdapter() {
@Override
public void write(JsonWriter out, OpenAiParamDTO value) throws IOException {
JsonObject obj = thisAdapter.toJsonTree(value).getAsJsonObject();
obj.remove("additionalProperties");
// serialize additional properties
if (value.getAdditionalProperties() != null) {
for (Map.Entry entry : value.getAdditionalProperties().entrySet()) {
if (entry.getValue() instanceof String)
obj.addProperty(entry.getKey(), (String) entry.getValue());
else if (entry.getValue() instanceof Number)
obj.addProperty(entry.getKey(), (Number) entry.getValue());
else if (entry.getValue() instanceof Boolean)
obj.addProperty(entry.getKey(), (Boolean) entry.getValue());
else if (entry.getValue() instanceof Character)
obj.addProperty(entry.getKey(), (Character) entry.getValue());
else {
JsonElement jsonElement = gson.toJsonTree(entry.getValue());
if (jsonElement.isJsonArray()) {
obj.add(entry.getKey(), jsonElement.getAsJsonArray());
} else {
obj.add(entry.getKey(), jsonElement.getAsJsonObject());
}
}
}
}
elementAdapter.write(out, obj);
}
@Override
public OpenAiParamDTO read(JsonReader in) throws IOException {
JsonElement jsonElement = elementAdapter.read(in);
validateJsonElement(jsonElement);
JsonObject jsonObj = jsonElement.getAsJsonObject();
// store additional fields in the deserialized instance
OpenAiParamDTO instance = thisAdapter.fromJsonTree(jsonObj);
for (Map.Entry entry : jsonObj.entrySet()) {
if (!openapiFields.contains(entry.getKey())) {
if (entry.getValue().isJsonPrimitive()) { // primitive type
if (entry.getValue().getAsJsonPrimitive().isString())
instance.putAdditionalProperty(entry.getKey(), entry.getValue().getAsString());
else if (entry.getValue().getAsJsonPrimitive().isNumber())
instance.putAdditionalProperty(entry.getKey(), entry.getValue().getAsNumber());
else if (entry.getValue().getAsJsonPrimitive().isBoolean())
instance.putAdditionalProperty(entry.getKey(), entry.getValue().getAsBoolean());
else
throw new IllegalArgumentException(String.format("The field `%s` has unknown primitive type. Value: %s", entry.getKey(), entry.getValue().toString()));
} else if (entry.getValue().isJsonArray()) {
instance.putAdditionalProperty(entry.getKey(), gson.fromJson(entry.getValue(), List.class));
} else { // JSON object
instance.putAdditionalProperty(entry.getKey(), gson.fromJson(entry.getValue(), HashMap.class));
}
}
}
return instance;
}
}.nullSafe();
}
}
/**
* Create an instance of OpenAiParamDTO given an JSON string
*
* @param jsonString JSON string
* @return An instance of OpenAiParamDTO
* @throws IOException if the JSON string is invalid with respect to OpenAiParamDTO
*/
public static OpenAiParamDTO fromJson(String jsonString) throws IOException {
return JSON.getGson().fromJson(jsonString, OpenAiParamDTO.class);
}
/**
* Convert an instance of OpenAiParamDTO to an JSON string
*
* @return JSON string
*/
public String toJson() {
return JSON.getGson().toJson(this);
}
}
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