Spring/spring-ai
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Remove deprecated code from 1.0 M2 and before

Browse Source 
- Remove deprecated types,methods and references
 - Remove usage of "Generation(String text)" and replace with
  "Generation(AssistantMessage)"
 - Remove MiniMaxApi,MootShotApi,OpenAiApi,ZhiPuAiApi
   ChatCompletionFinishReason's FUNCTION_CALL
 - Remove OllamaApi's deprecated types
 - Remove deprecated constructors from PostgresMlEmbeddingModel
 - Remove deprecated constructor from Media
 - Remove tokenNames usage from antlr4 FiltersLexer and FiltersParser
 - Remove deprecated methods from CassandraVectorStoreProperties
 - Remove deprecated constructor and static config class from QdrantVectorStore
 - Minor cleanups on removing deprecated models and versions
 - Remove old name for mixtral models

Resolves #1599
This commit is contained in:
Ilayaperumal Gopinathan
2024-11-14 12:28:13 +00:00
committed by Mark Pollack
parent ea1871041c
commit 72c84fe8b8
29 changed files with 73 additions and 607 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic/BedrockAnthropicChatModel.java
View File

@@ -24,6 +24,7 @@ import org.springframework.ai.bedrock.MessageToPromptConverter;
import org.springframework.ai.bedrock.anthropic.api.AnthropicChatBedrockApi;
import org.springframework.ai.bedrock.anthropic.api.AnthropicChatBedrockApi.AnthropicChatRequest;
import org.springframework.ai.bedrock.anthropic.api.AnthropicChatBedrockApi.AnthropicChatResponse;
import org.springframework.ai.chat.messages.AssistantMessage;
import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.model.ChatResponse;
@@ -68,7 +69,7 @@ public class BedrockAnthropicChatModel implements ChatModel, StreamingChatModel
AnthropicChatResponse response = this.anthropicChatApi.chatCompletion(request);
return new ChatResponse(List.of(new Generation(response.completion())));
return new ChatResponse(List.of(new Generation(new AssistantMessage(response.completion()))));
}
@Override
@@ -80,12 +81,13 @@ public class BedrockAnthropicChatModel implements ChatModel, StreamingChatModel
return fluxResponse.map(response -> {
String stopReason = response.stopReason() != null ? response.stopReason() : null;
var generation = new Generation(response.completion());
ChatGenerationMetadata chatGenerationMetadata = null;
if (response.amazonBedrockInvocationMetrics() != null) {
generation = generation.withGenerationMetadata(
ChatGenerationMetadata.from(stopReason, response.amazonBedrockInvocationMetrics()));
chatGenerationMetadata = ChatGenerationMetadata.from(stopReason,
response.amazonBedrockInvocationMetrics());
}
return new ChatResponse(List.of(generation));
return new ChatResponse(
List.of(new Generation(new AssistantMessage(response.completion()), chatGenerationMetadata)));
});
}

13
models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic3/BedrockAnthropic3ChatModel.java
View File

@@ -114,16 +114,13 @@ public class BedrockAnthropic3ChatModel implements ChatModel, StreamingChatModel
inputTokens.set(response.message().usage().inputTokens());
}
String content = response.type() == StreamingType.CONTENT_BLOCK_DELTA ? response.delta().text() : "";
var generation = new Generation(content);
ChatGenerationMetadata chatGenerationMetadata = null;
if (response.type() == StreamingType.MESSAGE_DELTA) {
generation = generation.withGenerationMetadata(ChatGenerationMetadata
.from(response.delta().stopReason(), new Anthropic3ChatBedrockApi.AnthropicUsage(inputTokens.get(),
response.usage().outputTokens())));
chatGenerationMetadata = ChatGenerationMetadata.from(response.delta().stopReason(),
new Anthropic3ChatBedrockApi.AnthropicUsage(inputTokens.get(),
response.usage().outputTokens()));
}
return new ChatResponse(List.of(generation));
return new ChatResponse(List.of(new Generation(new AssistantMessage(content), chatGenerationMetadata)));
});
}

10
models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/cohere/BedrockCohereChatModel.java
View File

@@ -25,6 +25,7 @@ import org.springframework.ai.bedrock.MessageToPromptConverter;
import org.springframework.ai.bedrock.cohere.api.CohereChatBedrockApi;
import org.springframework.ai.bedrock.cohere.api.CohereChatBedrockApi.CohereChatRequest;
import org.springframework.ai.bedrock.cohere.api.CohereChatBedrockApi.CohereChatResponse;
import org.springframework.ai.chat.messages.AssistantMessage;
import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
import org.springframework.ai.chat.metadata.Usage;
import org.springframework.ai.chat.model.ChatModel;
@@ -61,7 +62,10 @@ public class BedrockCohereChatModel implements ChatModel, StreamingChatModel {
@Override
public ChatResponse call(Prompt prompt) {
CohereChatResponse response = this.chatApi.chatCompletion(this.createRequest(prompt, false));
List<Generation> generations = response.generations().stream().map(g -> new Generation(g.text())).toList();
List<Generation> generations = response.generations()
.stream()
.map(g -> new Generation(new AssistantMessage(g.text())))
.toList();
return new ChatResponse(generations);
}
@@ -73,9 +77,9 @@ public class BedrockCohereChatModel implements ChatModel, StreamingChatModel {
String finishReason = g.finishReason().name();
Usage usage = BedrockUsage.from(g.amazonBedrockInvocationMetrics());
return new ChatResponse(List
.of(new Generation("").withGenerationMetadata(ChatGenerationMetadata.from(finishReason, usage))));
.of(new Generation(new AssistantMessage(""), ChatGenerationMetadata.from(finishReason, usage))));
}
return new ChatResponse(List.of(new Generation(g.text())));
return new ChatResponse(List.of(new Generation(new AssistantMessage(g.text()))));
});
}

5
models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/jurassic2/BedrockAi21Jurassic2ChatModel.java
View File

@@ -19,6 +19,7 @@ package org.springframework.ai.bedrock.jurassic2;
import org.springframework.ai.bedrock.MessageToPromptConverter;
import org.springframework.ai.bedrock.jurassic2.api.Ai21Jurassic2ChatBedrockApi;
import org.springframework.ai.bedrock.jurassic2.api.Ai21Jurassic2ChatBedrockApi.Ai21Jurassic2ChatRequest;
import org.springframework.ai.chat.messages.AssistantMessage;
import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.model.ChatResponse;
@@ -68,8 +69,8 @@ public class BedrockAi21Jurassic2ChatModel implements ChatModel {
return new ChatResponse(response.completions()
.stream()
.map(completion -> new Generation(completion.data().text())
.withGenerationMetadata(ChatGenerationMetadata.from(completion.finishReason().reason(), null)))
.map(completion -> new Generation(new AssistantMessage(completion.data().text()),
ChatGenerationMetadata.from(completion.finishReason().reason(), null)))
.toList());
}

7
models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/llama/BedrockLlamaChatModel.java
View File

@@ -24,6 +24,7 @@ import org.springframework.ai.bedrock.MessageToPromptConverter;
import org.springframework.ai.bedrock.llama.api.LlamaChatBedrockApi;
import org.springframework.ai.bedrock.llama.api.LlamaChatBedrockApi.LlamaChatRequest;
import org.springframework.ai.bedrock.llama.api.LlamaChatBedrockApi.LlamaChatResponse;
import org.springframework.ai.chat.messages.AssistantMessage;
import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
import org.springframework.ai.chat.metadata.Usage;
import org.springframework.ai.chat.model.ChatModel;
@@ -68,7 +69,7 @@ public class BedrockLlamaChatModel implements ChatModel, StreamingChatModel {
LlamaChatResponse response = this.chatApi.chatCompletion(request);
return new ChatResponse(List.of(new Generation(response.generation()).withGenerationMetadata(
return new ChatResponse(List.of(new Generation(new AssistantMessage(response.generation()),
ChatGenerationMetadata.from(response.stopReason().name(), extractUsage(response)))));
}
@@ -81,8 +82,8 @@ public class BedrockLlamaChatModel implements ChatModel, StreamingChatModel {
return fluxResponse.map(response -> {
String stopReason = response.stopReason() != null ? response.stopReason().name() : null;
return new ChatResponse(List.of(new Generation(response.generation())
.withGenerationMetadata(ChatGenerationMetadata.from(stopReason, extractUsage(response)))));
return new ChatResponse(List.of(new Generation(new AssistantMessage(response.generation()),
ChatGenerationMetadata.from(stopReason, extractUsage(response)))));
});
}

18
models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/titan/BedrockTitanChatModel.java
View File

@@ -25,6 +25,7 @@ import org.springframework.ai.bedrock.titan.api.TitanChatBedrockApi;
import org.springframework.ai.bedrock.titan.api.TitanChatBedrockApi.TitanChatRequest;
import org.springframework.ai.bedrock.titan.api.TitanChatBedrockApi.TitanChatResponse;
import org.springframework.ai.bedrock.titan.api.TitanChatBedrockApi.TitanChatResponseChunk;
import org.springframework.ai.chat.messages.AssistantMessage;
import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
import org.springframework.ai.chat.metadata.Usage;
import org.springframework.ai.chat.model.ChatModel;
@@ -62,7 +63,7 @@ public class BedrockTitanChatModel implements ChatModel, StreamingChatModel {
TitanChatResponse response = this.chatApi.chatCompletion(this.createRequest(prompt));
List<Generation> generations = response.results()
.stream()
.map(result -> new Generation(result.outputText()))
.map(result -> new Generation(new AssistantMessage(result.outputText())))
.toList();
return new ChatResponse(generations);
@@ -71,21 +72,18 @@ public class BedrockTitanChatModel implements ChatModel, StreamingChatModel {
@Override
public Flux<ChatResponse> stream(Prompt prompt) {
return this.chatApi.chatCompletionStream(this.createRequest(prompt)).map(chunk -> {
Generation generation = new Generation(chunk.outputText());
ChatGenerationMetadata chatGenerationMetadata = null;
if (chunk.amazonBedrockInvocationMetrics() != null) {
String completionReason = chunk.completionReason().name();
generation = generation.withGenerationMetadata(
ChatGenerationMetadata.from(completionReason, chunk.amazonBedrockInvocationMetrics()));
chatGenerationMetadata = ChatGenerationMetadata.from(completionReason,
chunk.amazonBedrockInvocationMetrics());
}
else if (chunk.inputTextTokenCount() != null && chunk.totalOutputTextTokenCount() != null) {
String completionReason = chunk.completionReason().name();
generation = generation
.withGenerationMetadata(ChatGenerationMetadata.from(completionReason, extractUsage(chunk)));
chatGenerationMetadata = ChatGenerationMetadata.from(completionReason, extractUsage(chunk));
}
return new ChatResponse(List.of(generation));
return new ChatResponse(
List.of(new Generation(new AssistantMessage(chunk.outputText()), chatGenerationMetadata)));
});
}

9
models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/llama/BedrockLlamaChatModelIT.java
View File

@@ -92,8 +92,11 @@ class BedrockLlamaChatModelIT {
@Test
void roleTest() {
UserMessage userMessage = new UserMessage(
"Tell me about 3 famous pirates from the Golden Age of Piracy and why they did.");
String message = """
Describe 3 of the most feared and legendary pirates from the Golden Age of Piracy, particularly
those known for their intimidating tactics and whose stories influenced popular culture.
""";
UserMessage userMessage = new UserMessage(message);
SystemPromptTemplate systemPromptTemplate = new SystemPromptTemplate(this.systemResource);
Message systemMessage = systemPromptTemplate.createMessage(Map.of("name", "Bob", "voice", "pirate"));
@@ -111,7 +114,7 @@ class BedrockLlamaChatModelIT {
String format = outputConverter.getFormat();
String template = """
List five {subject}
List exactly five {subject}, no more and no less.
{format}
""";
PromptTemplate promptTemplate = new PromptTemplate(template,

4
models/spring-ai-huggingface/src/main/java/org/springframework/ai/huggingface/HuggingfaceChatModel.java
View File

@@ -23,6 +23,8 @@ import java.util.Map;
import com.fasterxml.jackson.core.type.TypeReference;
import com.fasterxml.jackson.databind.ObjectMapper;
import org.springframework.ai.chat.messages.AssistantMessage;
import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.chat.model.Generation;
@@ -105,7 +107,7 @@ public class HuggingfaceChatModel implements ChatModel {
new TypeReference<Map<String, Object>>() {
});
Generation generation = new Generation(generatedText, detailsMap);
Generation generation = new Generation(new AssistantMessage(generatedText, detailsMap));
generations.add(generation);
}
return new ChatResponse(generations);

10
models/spring-ai-minimax/src/main/java/org/springframework/ai/minimax/api/MiniMaxApi.java
View File

@@ -224,10 +224,7 @@ public class MiniMaxApi {
ABAB_6_5_T_Chat("abab6.5t-chat"),
ABAB_6_5_G_Chat("abab6.5g-chat"),
ABAB_5_5_Chat("abab5.5-chat"),
ABAB_5_5_S_Chat("abab5.5s-chat"),
@Deprecated(since = "1.0.0-M2", forRemoval = true) // Replaced by ABAB_6_5_S_Chat
ABAB_6_Chat("abab6-chat");
ABAB_5_5_S_Chat("abab5.5s-chat");
public final String value;
@@ -269,11 +266,6 @@ public class MiniMaxApi {
*/
@JsonProperty("tool_calls")
TOOL_CALLS,
/**
* (deprecated) The model called a function.
*/
@JsonProperty("function_call")
FUNCTION_CALL,
/**
* Only for compatibility with Mistral AI API.
*/

6
models/spring-ai-mistral-ai/src/main/java/org/springframework/ai/mistralai/api/MistralAiApi.java
View File

@@ -264,15 +264,11 @@ public class MistralAiApi {
public enum ChatModel implements ChatModelDescription {
// @formatter:off
@Deprecated(since = "1.0.0-M1", forRemoval = true) // Replaced by OPEN_MISTRAL_7B
TINY("open-mistral-7b"),
@Deprecated(since = "1.0.0-M1", forRemoval = true) // Replaced by OPEN_MIXTRAL_7B
MIXTRAL("open-mixtral-8x7b"),
OPEN_MISTRAL_7B("open-mistral-7b"),
OPEN_MIXTRAL_7B("open-mixtral-8x7b"),
OPEN_MIXTRAL_22B("open-mixtral-8x22b"),
SMALL("mistral-small-latest"),
@Deprecated(since = "1.0.0-M1", forRemoval = true) // Mistral is removing this model
@Deprecated(since = "1.0.0-M1", forRemoval = true) // Mistral will be removing this model - see https://docs.mistral.ai/getting-started/models/models_overview/
MEDIUM("mistral-medium-latest"),
LARGE("mistral-large-latest");
// @formatter:on

5
models/spring-ai-moonshot/src/main/java/org/springframework/ai/moonshot/api/MoonshotApi.java
View File

@@ -195,11 +195,6 @@ public class MoonshotApi {
*/
@JsonProperty("tool_calls")
TOOL_CALLS,
/**
* (deprecated) The model called a function.
*/
@JsonProperty("function_call")
FUNCTION_CALL,
/**
* Only for compatibility with Mistral AI API.
*/

297
models/spring-ai-ollama/src/main/java/org/springframework/ai/ollama/api/OllamaApi.java
View File

@@ -104,54 +104,6 @@ public class OllamaApi {
this.webClient = webClientBuilder.baseUrl(baseUrl).defaultHeaders(defaultHeaders).build();
}
/**
* Generate a completion for the given prompt.
* @param completionRequest Completion request.
* @return Completion response.
* @deprecated Use {@link #chat(ChatRequest)} instead.
*/
@Deprecated(since = "1.0.0-M2", forRemoval = true)
public GenerateResponse generate(GenerateRequest completionRequest) {
Assert.notNull(completionRequest, REQUEST_BODY_NULL_ERROR);
Assert.isTrue(!completionRequest.stream(), "Stream mode must be disabled.");
return this.restClient.post()
.uri("/api/generate")
.body(completionRequest)
.retrieve()
.onStatus(this.responseErrorHandler)
.body(GenerateResponse.class);
}
// --------------------------------------------------------------------------
// Generate & Streaming Generate
// --------------------------------------------------------------------------
/**
* Generate a streaming completion for the given prompt.
* @param completionRequest Completion request. The request must set the stream
* property to true.
* @return Completion response as a {@link Flux} stream.
* @deprecated Use {@link #streamingChat(ChatRequest)} instead.
*/
@Deprecated(since = "1.0.0-M2", forRemoval = true)
public Flux<GenerateResponse> generateStreaming(GenerateRequest completionRequest) {
Assert.notNull(completionRequest, REQUEST_BODY_NULL_ERROR);
Assert.isTrue(completionRequest.stream(), "Request must set the stream property to true.");
return this.webClient.post()
.uri("/api/generate")
.body(Mono.just(completionRequest), GenerateRequest.class)
.retrieve()
.bodyToFlux(GenerateResponse.class)
.handle((data, sink) -> {
if (logger.isTraceEnabled()) {
logger.trace(data);
}
sink.next(data);
});
}
/**
* Generate the next message in a chat with a provided model.
* This is a streaming endpoint (controlled by the 'stream' request property), so
@@ -183,7 +135,7 @@ public class OllamaApi {
return this.webClient.post()
.uri("/api/chat")
.body(Mono.just(chatRequest), GenerateRequest.class)
.body(Mono.just(chatRequest), ChatRequest.class)
.retrieve()
.bodyToFlux(ChatResponse.class)
.handle((data, sink) -> {
@@ -210,28 +162,6 @@ public class OllamaApi {
.body(EmbeddingsResponse.class);
}
// --------------------------------------------------------------------------
// Chat & Streaming Chat
// --------------------------------------------------------------------------
/**
* Generate embeddings from a model.
* @param embeddingRequest Embedding request.
* @return Embedding response.
* @deprecated Use {@link #embed(EmbeddingsRequest)} instead.
*/
@Deprecated(since = "1.0.0-M2", forRemoval = true)
public EmbeddingResponse embeddings(EmbeddingRequest embeddingRequest) {
Assert.notNull(embeddingRequest, REQUEST_BODY_NULL_ERROR);
return this.restClient.post()
.uri("/api/embeddings")
.body(embeddingRequest)
.retrieve()
.onStatus(this.responseErrorHandler)
.body(EmbeddingResponse.class);
}
/**
* List models that are available locally on the machine where Ollama is running.
*/
@@ -321,192 +251,6 @@ public class OllamaApi {
}
/**
* The request object sent to the /generate endpoint.
*
* @param model (required) The model to use for completion.
* @param prompt (required) The prompt(s) to generate completions for.
* @param format (optional) The format to return the response in. Currently, the only
* accepted value is "json".
* @param options (optional) additional model parameters listed in the documentation
* for the Model file such as temperature.
* @param system (optional) system prompt to (overrides what is defined in the Model file).
* @param template (optional) the full prompt or prompt template (overrides what is
* defined in the Model file).
* @param context the context parameter returned from a previous request to /generate,
* this can be used to keep a short conversational memory.
* @param stream (optional) if false the response will be returned as a single
* response object, rather than a stream of objects.
* @param raw (optional) if true no formatting will be applied to the prompt and no
* context will be returned. You may choose to use the raw parameter if you are
* specifying a full templated prompt in your request to the API, and are managing
* history yourself.
* @param images (optional) a list of base64-encoded images (for multimodal models such as llava).
* @param keepAlive (optional) controls how long the model will stay loaded into memory following the request (default: 5m).
*/
@Deprecated(since = "1.0.0-M2", forRemoval = true)
@JsonInclude(Include.NON_NULL)
public record GenerateRequest(
@JsonProperty("model") String model,
@JsonProperty("prompt") String prompt,
@JsonProperty("format") String format,
@JsonProperty("options") Map<String, Object> options,
@JsonProperty("system") String system,
@JsonProperty("template") String template,
@JsonProperty("context") List<Integer> context,
@JsonProperty("stream") Boolean stream,
@JsonProperty("raw") Boolean raw,
@JsonProperty("images") List<String> images,
@JsonProperty("keep_alive") String keepAlive) {
/**
* Shortcut constructor to create a CompletionRequest without options.
* @param model The model used for completion.
* @param prompt The prompt(s) to generate completions for.
* @param stream Whether to stream the response.
*/
public GenerateRequest(String model, String prompt, Boolean stream) {
this(model, prompt, null, null, null, null, null, stream, null, null, null);
}
/**
* Shortcut constructor to create a CompletionRequest without options.
* @param model The model used for completion.
* @param prompt The prompt(s) to generate completions for.
* @param enableJsonFormat Whether to return the response in json format.
* @param stream Whether to stream the response.
*/
public GenerateRequest(String model, String prompt, boolean enableJsonFormat, Boolean stream) {
this(model, prompt, (enableJsonFormat) ? "json" : null, null, null, null, null, stream, null, null, null);
}
/**
* Create a CompletionRequest builder.
* @param prompt The prompt(s) to generate completions for.
*/
public static Builder builder(String prompt) {
return new Builder(prompt);
}
public static class Builder {
private final String prompt;
private String model;
private String format;
private Map<String, Object> options;
private String system;
private String template;
private List<Integer> context;
private Boolean stream;
private Boolean raw;
private List<String> images;
private String keepAlive;
public Builder(String prompt) {
this.prompt = prompt;
}
public Builder withModel(String model) {
this.model = model;
return this;
}
public Builder withFormat(String format) {
this.format = format;
return this;
}
public Builder withOptions(Map<String, Object> options) {
this.options = options;
return this;
}
public Builder withOptions(OllamaOptions options) {
this.options = options.toMap();
return this;
}
public Builder withSystem(String system) {
this.system = system;
return this;
}
public Builder withTemplate(String template) {
this.template = template;
return this;
}
public Builder withContext(List<Integer> context) {
this.context = context;
return this;
}
public Builder withStream(Boolean stream) {
this.stream = stream;
return this;
}
public Builder withRaw(Boolean raw) {
this.raw = raw;
return this;
}
public Builder withImages(List<String> images) {
this.images = images;
return this;
}
public Builder withKeepAlive(String keepAlive) {
this.keepAlive = keepAlive;
return this;
}
public GenerateRequest build() {
return new GenerateRequest(this.model, this.prompt, this.format, this.options, this.system, this.template, this.context, this.stream, this.raw, this.images, this.keepAlive);
}
}
}
/**
* The response object returned from the /generate endpoint. To calculate how fast the
* response is generated in tokens per second (token/s), divide eval_count /
* eval_duration.
*
* @param model The model used for completion.
* @param createdAt When the request was made.
* @param response The completion response. Empty if the response was streamed, if not
* streamed, this will contain the full response
* @param done Whether this is the final response. If true, this response may be
* followed by another response with the following, additional fields: context,
* prompt_eval_count, prompt_eval_duration, eval_count, eval_duration.
* @param context Encoding of the conversation used in this response, this can be sent
* in the next request to keep a conversational memory.
* @param totalDuration Time spent generating the response.
* @param loadDuration Time spent loading the model.
* @param promptEvalCount Number of times the prompt was evaluated.
* @param promptEvalDuration Time spent evaluating the prompt.
* @param evalCount Number of tokens in the response.
* @param evalDuration Time spent generating the response.
*/
@Deprecated(since = "1.0.0-M2", forRemoval = true)
@JsonInclude(Include.NON_NULL)
public record GenerateResponse(
@JsonProperty("model") String model,
@JsonProperty("created_at") Instant createdAt,
@JsonProperty("response") String response,
@JsonProperty("done") Boolean done,
@JsonProperty("context") List<Integer> context,
@JsonProperty("total_duration") Duration totalDuration,
@JsonProperty("load_duration") Duration loadDuration,
@JsonProperty("prompt_eval_count") Integer promptEvalCount,
@JsonProperty("prompt_eval_duration") Duration promptEvalDuration,
@JsonProperty("eval_count") Integer evalCount,
@JsonProperty("eval_duration") Duration evalDuration) {
}
/**
* Chat message object.
*
@@ -830,45 +574,6 @@ public class OllamaApi {
}
}
/**
* Generate embeddings from a model.
*
* @param model The name of model to generate embeddings from.
* @param prompt The text generate embeddings for
* @param keepAlive Controls how long the model will stay loaded into memory following the request (default: 5m).
* @param options Additional model parameters listed in the documentation for the
* @deprecated Use {@link EmbeddingsRequest} instead.
*/
@Deprecated(since = "1.0.0-M2", forRemoval = true)
@JsonInclude(Include.NON_NULL)
public record EmbeddingRequest(
@JsonProperty("model") String model,
@JsonProperty("prompt") String prompt,
@JsonProperty("keep_alive") Duration keepAlive,
@JsonProperty("options") Map<String, Object> options) {
/**
* Shortcut constructor to create a EmbeddingRequest without options.
* @param model The name of model to generate embeddings from.
* @param prompt The text to generate embeddings for.
*/
public EmbeddingRequest(String model, String prompt) {
this(model, prompt, null, null);
}
}
/**
* The response object returned from the /embedding endpoint.
*
* @param embedding The embedding generated from the model.
* @deprecated Use {@link EmbeddingsResponse} instead.
*/
@Deprecated(since = "1.0.0-M2", forRemoval = true)
@JsonInclude(Include.NON_NULL)
public record EmbeddingResponse(
@JsonProperty("embedding") List<Float> embedding) {
}
/**
* The response object returned from the /embedding endpoint.
* @param model The model used for generating the embeddings.

20
models/spring-ai-ollama/src/test/java/org/springframework/ai/ollama/api/OllamaApiIT.java
View File

@@ -24,13 +24,12 @@ import org.junit.jupiter.api.BeforeAll;
import org.junit.jupiter.api.Test;
import reactor.core.publisher.Flux;
import org.springframework.ai.chat.messages.UserMessage;
import org.springframework.ai.ollama.BaseOllamaIT;
import org.springframework.ai.ollama.api.OllamaApi.ChatRequest;
import org.springframework.ai.ollama.api.OllamaApi.ChatResponse;
import org.springframework.ai.ollama.api.OllamaApi.EmbeddingsRequest;
import org.springframework.ai.ollama.api.OllamaApi.EmbeddingsResponse;
import org.springframework.ai.ollama.api.OllamaApi.GenerateRequest;
import org.springframework.ai.ollama.api.OllamaApi.GenerateResponse;
import org.springframework.ai.ollama.api.OllamaApi.Message;
import org.springframework.ai.ollama.api.OllamaApi.Message.Role;
@@ -49,23 +48,6 @@ public class OllamaApiIT extends BaseOllamaIT {
initializeOllama(MODEL);
}
@Test
public void generation() {
var request = GenerateRequest
.builder("What is the capital of Bulgaria and what is the size? What it the national anthem?")
.withModel(MODEL)
.withStream(false)
.build();
GenerateResponse response = getOllamaApi().generate(request);
System.out.println(response);
assertThat(response).isNotNull();
assertThat(response.model()).contains(MODEL);
assertThat(response.response()).contains("Sofia");
}
@Test
public void chat() {
var request = ChatRequest.builder(MODEL)

20
models/spring-ai-openai/src/main/java/org/springframework/ai/openai/api/OpenAiApi.java
View File

@@ -397,27 +397,12 @@ public class OpenAiApi {
*/
GPT_4_TURBO_PREVIEW("gpt-4-turbo-preview"),
/**
* GPT-4 with the ability to understand images, in addition to all other GPT-4
* Turbo capabilities. Currently points to gpt-4-1106-vision-preview. Returns a
* maximum of 4,096 output tokens Context window: 128k tokens
*/
@Deprecated(since = "1.0.0-M2", forRemoval = true) // Replaced by GPT_4_O
GPT_4_VISION_PREVIEW("gpt-4-vision-preview"),
/**
* Currently points to gpt-4-0613. Snapshot of gpt-4 from June 13th 2023 with
* improved function calling support. Context window: 8k tokens
*/
GPT_4("gpt-4"),
/**
* Currently points to gpt-4-32k-0613. Snapshot of gpt-4-32k from June 13th 2023
* with improved function calling support. Context window: 32k tokens
*/
@Deprecated(since = "1.0.0-M2", forRemoval = true) // Replaced by GPT_4_O
GPT_4_32K("gpt-4-32k"),
/**
* Currently points to gpt-3.5-turbo-0125. model with higher accuracy at
* responding in requested formats and a fix for a bug which caused a text
@@ -483,11 +468,6 @@ public class OpenAiApi {
*/
@JsonProperty("tool_calls")
TOOL_CALLS,
/**
* (deprecated) The model called a function.
*/
@JsonProperty("function_call")
FUNCTION_CALL,
/**
* Only for compatibility with Mistral AI API.
*/

50
models/spring-ai-postgresml/src/main/java/org/springframework/ai/postgresml/PostgresMlEmbeddingModel.java
View File

@@ -88,56 +88,6 @@ public class PostgresMlEmbeddingModel extends AbstractEmbeddingModel implements
this.createExtension = createExtension;
}
/**
* a constructor
* @param jdbcTemplate JdbcTemplate
* @param transformer huggingface sentence-transformer name
*/
@Deprecated(since = "0.8.0", forRemoval = true)
public PostgresMlEmbeddingModel(JdbcTemplate jdbcTemplate, String transformer) {
this(jdbcTemplate, transformer, VectorType.PG_ARRAY);
}
/**
* a constructor
* @deprecated Use the constructor with {@link PostgresMlEmbeddingOptions} instead.
* @param jdbcTemplate JdbcTemplate
* @param transformer huggingface sentence-transformer name
* @param vectorType vector type in PostgreSQL
*/
@Deprecated(since = "0.8.0", forRemoval = true)
public PostgresMlEmbeddingModel(JdbcTemplate jdbcTemplate, String transformer, VectorType vectorType) {
this(jdbcTemplate, transformer, vectorType, Map.of(), MetadataMode.EMBED, false);
}
/**
* a constructor * @deprecated Use the constructor with
* {@link PostgresMlEmbeddingOptions} instead.
* @param jdbcTemplate JdbcTemplate
* @param transformer huggingface sentence-transformer name
* @param vectorType vector type in PostgreSQL
* @param kwargs optional arguments
*/
@Deprecated(since = "0.8.0", forRemoval = true)
public PostgresMlEmbeddingModel(JdbcTemplate jdbcTemplate, String transformer, VectorType vectorType,
Map<String, Object> kwargs, MetadataMode metadataMode, boolean createExtension) {
Assert.notNull(jdbcTemplate, "jdbc template must not be null.");
Assert.notNull(transformer, "transformer must not be null.");
Assert.notNull(vectorType, "vectorType must not be null.");
Assert.notNull(kwargs, "kwargs must not be null.");
Assert.notNull(metadataMode, "metadataMode must not be null.");
this.jdbcTemplate = jdbcTemplate;
this.defaultOptions = PostgresMlEmbeddingOptions.builder()
.withTransformer(transformer)
.withVectorType(vectorType)
.withMetadataMode(metadataMode)
.withKwargs(ModelOptionsUtils.toJsonString(kwargs))
.build();
this.createExtension = createExtension;
}
@SuppressWarnings("null")
@Override
public float[] embed(String text) {

10
models/spring-ai-vertex-ai-embedding/src/test/java/org/springframework/ai/vertexai/embedding/multimodal/VertexAiMultimodalEmbeddingModelIT.java
View File

@@ -16,6 +16,10 @@
package org.springframework.ai.vertexai.embedding.multimodal;
import java.net.MalformedURLException;
import java.net.URI;
import java.net.URL;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
@@ -104,10 +108,12 @@ class VertexAiMultimodalEmbeddingModelIT {
}
@Test
void textMediaEmbedding() {
void textMediaEmbedding() throws MalformedURLException {
assertThat(this.multiModelEmbeddingModel).isNotNull();
var document = Document.builder().withMedia(new Media(MimeTypeUtils.TEXT_PLAIN, "Hello World")).build();
var document = Document.builder()
.withMedia(new Media(MimeTypeUtils.TEXT_PLAIN, URI.create("http://example.com/image.png").toURL()))
.build();
DocumentEmbeddingRequest embeddingRequest = new DocumentEmbeddingRequest(document);

14
models/spring-ai-watsonx-ai/src/test/java/org/springframework/ai/watsonx/WatsonxAiChatModelTest.java
View File

@@ -26,6 +26,7 @@ import org.junit.Test;
import reactor.core.publisher.Flux;
import reactor.test.StepVerifier;
import org.springframework.ai.chat.messages.AssistantMessage;
import org.springframework.ai.chat.messages.SystemMessage;
import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
import org.springframework.ai.chat.model.ChatResponse;
@@ -172,9 +173,9 @@ public class WatsonxAiChatModelTest {
given(mockChatApi.generate(any(WatsonxAiChatRequest.class)))
.willReturn(ResponseEntity.of(Optional.of(fakeResponse)));
Generation expectedGenerator = new Generation("LLM response")
.withGenerationMetadata(ChatGenerationMetadata.from("max_tokens",
Map.of("warnings", List.of(Map.of("message", "the message", "id", "disclaimer_warning")))));
Generation expectedGenerator = new Generation(new AssistantMessage("LLM response"),
ChatGenerationMetadata.from("max_tokens",
Map.of("warnings", List.of(Map.of("message", "the message", "id", "disclaimer_warning")))));
ChatResponse expectedResponse = new ChatResponse(List.of(expectedGenerator));
ChatResponse response = chatModel.call(prompt);
@@ -205,10 +206,9 @@ public class WatsonxAiChatModelTest {
Flux<WatsonxAiChatResponse> fakeResponse = Flux.just(fakeResponseFirst, fakeResponseSecond);
given(mockChatApi.generateStreaming(any(WatsonxAiChatRequest.class))).willReturn(fakeResponse);
Generation firstGen = new Generation("LLM resp")
.withGenerationMetadata(ChatGenerationMetadata.from("max_tokens",
Map.of("warnings", List.of(Map.of("message", "the message", "id", "disclaimer_warning")))));
Generation secondGen = new Generation("onse");
Generation firstGen = new Generation(new AssistantMessage("LLM resp"), ChatGenerationMetadata.from("max_tokens",
Map.of("warnings", List.of(Map.of("message", "the message", "id", "disclaimer_warning")))));
Generation secondGen = new Generation(new AssistantMessage("onse"));
Flux<ChatResponse> response = chatModel.stream(prompt);

5
models/spring-ai-zhipuai/src/main/java/org/springframework/ai/zhipuai/api/ZhiPuAiApi.java
View File

@@ -279,11 +279,6 @@ public class ZhiPuAiApi {
*/
@JsonProperty("tool_calls")
TOOL_CALLS,
/**
* (deprecated) The model called a function.
*/
@JsonProperty("function_call")
FUNCTION_CALL,
/**
* Only for compatibility with Mistral AI API.
*/

30
spring-ai-core/src/main/java/org/springframework/ai/chat/model/Generation.java
View File

@@ -16,13 +16,11 @@
package org.springframework.ai.chat.model;
import java.util.Map;
import java.util.Objects;
import org.springframework.ai.chat.messages.AssistantMessage;
import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
import org.springframework.ai.model.ModelResult;
import org.springframework.lang.Nullable;
/**
* Represents a response returned by the AI.
@@ -33,22 +31,6 @@ public class Generation implements ModelResult<AssistantMessage> {
private ChatGenerationMetadata chatGenerationMetadata;
/**
* @deprecated Use {@link #Generation(AssistantMessage)} constructor instead.
*/
@Deprecated
public Generation(String text) {
this(text, Map.of());
}
/**
* @deprecated Use {@link #Generation(AssistantMessage)} constructor instead.
*/
@Deprecated
public Generation(String text, Map<String, Object> properties) {
this(new AssistantMessage(text, properties));
}
public Generation(AssistantMessage assistantMessage) {
this(assistantMessage, ChatGenerationMetadata.NULL);
}
@@ -69,18 +51,6 @@ public class Generation implements ModelResult<AssistantMessage> {
return chatGenerationMetadata != null ? chatGenerationMetadata : ChatGenerationMetadata.NULL;
}
/**
* @deprecated Use {@link #Generation(AssistantMessage, ChatGenerationMetadata)}
* constructor instead.
* @param chatGenerationMetadata
* @return
*/
@Deprecated
public Generation withGenerationMetadata(@Nullable ChatGenerationMetadata chatGenerationMetadata) {
this.chatGenerationMetadata = chatGenerationMetadata;
return this;
}
@Override
public boolean equals(Object o) {
if (this == o) {

8
spring-ai-core/src/main/java/org/springframework/ai/converter/StructuredOutputConverter.java
View File

@@ -17,7 +17,6 @@
package org.springframework.ai.converter;
import org.springframework.core.convert.converter.Converter;
import org.springframework.lang.NonNull;
/**
* Converts the (raw) LLM output into a structured responses of type. The
@@ -30,11 +29,4 @@ import org.springframework.lang.NonNull;
*/
public interface StructuredOutputConverter<T> extends Converter<String, T>, FormatProvider {
/**
* @deprecated Use the {@link #convert(Object)} instead.
*/
default T parse(@NonNull String source) {
return this.convert(source);
}
}

15
spring-ai-core/src/main/java/org/springframework/ai/model/Media.java
View File

@@ -38,21 +38,6 @@ public class Media {
private final Object data;
/**
* The Media class represents the data and metadata of a media attachment in a
* message. It consists of a MIME type and the raw data.
*
* This class is used as a parameter in the constructor of the UserMessage class.
* @deprecated This constructor is deprecated since version 1.0.0 M1 and will be
* removed in a future release.
*/
@Deprecated(since = "1.0.0 M1", forRemoval = true)
public Media(MimeType mimeType, Object data) {
Assert.notNull(mimeType, "MimeType must not be null");
this.mimeType = mimeType;
this.data = data;
}
public Media(MimeType mimeType, URL url) {
Assert.notNull(mimeType, "MimeType must not be null");
this.mimeType = mimeType;

1
spring-ai-core/src/main/java/org/springframework/ai/model/function/MethodFunctionCallback.java
View File

@@ -167,6 +167,7 @@ public class MethodFunctionCallback implements FunctionCallback {
return ModelOptionsUtils.toJsonString(response);
}
return "" + response;
}
catch (Exception e) {

13
spring-ai-core/src/test/java/org/springframework/ai/chat/client/ChatClientResponseEntityTests.java
View File

@@ -26,6 +26,7 @@ import org.mockito.Captor;
import org.mockito.Mock;
import org.mockito.junit.jupiter.MockitoExtension;
import org.springframework.ai.chat.messages.AssistantMessage;
import org.springframework.ai.chat.messages.Message;
import org.springframework.ai.chat.messages.MessageType;
import org.springframework.ai.chat.metadata.ChatResponseMetadata;
@@ -56,9 +57,9 @@ public class ChatClientResponseEntityTests {
ChatResponseMetadata metadata = ChatResponseMetadata.builder().withKeyValue("key1", "value1").build();
var chatResponse = new ChatResponse(List.of(new Generation("""
var chatResponse = new ChatResponse(List.of(new Generation(new AssistantMessage("""
{"name":"John", "age":30}
""")), metadata);
"""))), metadata);
given(this.chatModel.call(this.promptCaptor.capture())).willReturn(chatResponse);
@@ -82,12 +83,12 @@ public class ChatClientResponseEntityTests {
@Test
public void parametrizedResponseEntityTest() {
var chatResponse = new ChatResponse(List.of(new Generation("""
var chatResponse = new ChatResponse(List.of(new Generation(new AssistantMessage("""
[
{"name":"Max", "age":10},
{"name":"Adi", "age":13}
]
""")));
"""))));
given(this.chatModel.call(this.promptCaptor.capture())).willReturn(chatResponse);
@@ -112,9 +113,9 @@ public class ChatClientResponseEntityTests {
@Test
public void customSoCResponseEntityTest() {
var chatResponse = new ChatResponse(List.of(new Generation("""
var chatResponse = new ChatResponse(List.of(new Generation(new AssistantMessage("""
{"name":"Max", "age":10},
""")));
"""))));
given(this.chatModel.call(this.promptCaptor.capture())).willReturn(chatResponse);

12
spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vectorstore/cassandra/CassandraVectorStoreProperties.java
View File

@@ -89,18 +89,6 @@ public class CassandraVectorStoreProperties extends CommonVectorStoreProperties
this.embeddingColumnName = embeddingColumnName;
}
@Deprecated
public boolean getDisallowSchemaCreation() {
logger.warn("getDisallowSchemaCreation() is deprecated, use isInitializeSchema()");
return !super.isInitializeSchema();
}
@Deprecated
public void setDisallowSchemaCreation(boolean disallowSchemaCreation) {
logger.warn("setDisallowSchemaCreation(boolean) is deprecated, use setInitializeSchema(boolean)");
super.setInitializeSchema(!disallowSchemaCreation);
}
public boolean getReturnEmbeddings() {
return this.returnEmbeddings;
}

3
spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/cassandra/CassandraVectorStorePropertiesTests.java
View File

@@ -36,7 +36,6 @@ class CassandraVectorStorePropertiesTests {
assertThat(props.getContentColumnName()).isEqualTo(CassandraVectorStoreConfig.DEFAULT_CONTENT_COLUMN_NAME);
assertThat(props.getEmbeddingColumnName()).isEqualTo(CassandraVectorStoreConfig.DEFAULT_EMBEDDING_COLUMN_NAME);
assertThat(props.getIndexName()).isNull();
assertThat(props.getDisallowSchemaCreation()).isTrue();
assertThat(props.getFixedThreadPoolExecutorSize())
.isEqualTo(CassandraVectorStoreConfig.DEFAULT_ADD_CONCURRENCY);
}
@@ -49,7 +48,6 @@ class CassandraVectorStorePropertiesTests {
props.setContentColumnName("my_content");
props.setEmbeddingColumnName("my_vector");
props.setIndexName("my_sai");
props.setDisallowSchemaCreation(true);
props.setFixedThreadPoolExecutorSize(10);
assertThat(props.getKeyspace()).isEqualTo("my_keyspace");
@@ -57,7 +55,6 @@ class CassandraVectorStorePropertiesTests {
assertThat(props.getContentColumnName()).isEqualTo("my_content");
assertThat(props.getEmbeddingColumnName()).isEqualTo("my_vector");
assertThat(props.getIndexName()).isEqualTo("my_sai");
assertThat(props.getDisallowSchemaCreation()).isTrue();
assertThat(props.getFixedThreadPoolExecutorSize()).isEqualTo(10);
}

2
spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vectorstore/neo4j/Neo4jVectorStoreAutoConfigurationIT.java
View File

@@ -52,8 +52,6 @@ import static org.springframework.ai.autoconfigure.vectorstore.observation.Obser
@Testcontainers
public class Neo4jVectorStoreAutoConfigurationIT {
// Needs to be Neo4j 5.15+, because Neo4j 5.15 deprecated the used embedding storing
// function.
@Container
static Neo4jContainer<?> neo4jContainer = new Neo4jContainer<>(DockerImageName.parse("neo4j:5.18"))
.withRandomPassword();

2
vector-stores/spring-ai-neo4j-store/src/test/java/org/springframework/ai/vectorstore/Neo4jImage.java
View File

@@ -23,8 +23,6 @@ import org.testcontainers.utility.DockerImageName;
*/
public final class Neo4jImage {
// Needs to be Neo4j 5.15+ because Neo4j 5.15 deprecated the old vector index creation
// function.
public static final DockerImageName DEFAULT_IMAGE = DockerImageName.parse("neo4j:5.24");
private Neo4jImage() {

74
vector-stores/spring-ai-qdrant-store/src/main/java/org/springframework/ai/vectorstore/qdrant/QdrantVectorStore.java
View File

@@ -79,18 +79,6 @@ public class QdrantVectorStore extends AbstractObservationVectorStore implements
private final BatchingStrategy batchingStrategy;
/**
* Constructs a new QdrantVectorStore.
* @param config The configuration for the store.
* @param embeddingModel The client for embedding operations.
* @deprecated since 1.0.0 in favor of {@link QdrantVectorStore}.
*/
@Deprecated(since = "1.0.0", forRemoval = true)
public QdrantVectorStore(QdrantClient qdrantClient, QdrantVectorStoreConfig config, EmbeddingModel embeddingModel,
boolean initializeSchema) {
this(qdrantClient, config.collectionName, embeddingModel, initializeSchema);
}
/**
* Constructs a new QdrantVectorStore.
* @param qdrantClient A {@link QdrantClient} instance for interfacing with Qdrant.
@@ -283,66 +271,4 @@ public class QdrantVectorStore extends AbstractObservationVectorStore implements
}
/**
* Configuration class for the QdrantVectorStore.
*
* @deprecated since 1.0.0 in favor of {@link QdrantVectorStore}.
*/
@Deprecated(since = "1.0.0", forRemoval = true)
public static final class QdrantVectorStoreConfig {
private final String collectionName;
/*
* Constructor using the builder.
*
* @param builder The configuration builder.
*/
private QdrantVectorStoreConfig(Builder builder) {
this.collectionName = builder.collectionName;
}
/**
* Start building a new configuration.
* @return The entry point for creating a new configuration.
*/
public static Builder builder() {
return new Builder();
}
/**
* {@return the default config}
*/
public static QdrantVectorStoreConfig defaultConfig() {
return builder().build();
}
public final static class Builder {
private String collectionName;
private Builder() {
}
/**
* @param collectionName REQUIRED. The name of the collection.
*/
public Builder withCollectionName(String collectionName) {
this.collectionName = collectionName;
return this;
}
/**
* {@return the immutable configuration}
*/
public QdrantVectorStoreConfig build() {
Assert.notNull(this.collectionName, "collectionName cannot be null");
return new QdrantVectorStoreConfig(this);
}
}
}
}

5
vector-stores/spring-ai-qdrant-store/src/test/java/org/springframework/ai/vectorstore/qdrant/QdrantVectorStoreIT.java
View File

@@ -29,6 +29,7 @@ import io.qdrant.client.grpc.Collections.VectorParams;
import org.junit.jupiter.api.BeforeAll;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariables;
import org.testcontainers.junit.jupiter.Container;
import org.testcontainers.junit.jupiter.Testcontainers;
import org.testcontainers.qdrant.QdrantContainer;
@@ -53,8 +54,8 @@ import static org.assertj.core.api.Assertions.assertThat;
* @since 0.8.1
*/
@Testcontainers
@EnabledIfEnvironmentVariable(named = "MISTRAL_AI_API_KEY", matches = ".+")
@EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
@EnabledIfEnvironmentVariables({ @EnabledIfEnvironmentVariable(named = "MISTRAL_AI_API_KEY", matches = ".+"),
@EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+") })
public class QdrantVectorStoreIT {
private static final String COLLECTION_NAME = "test_collection";