## Change
Bump dashscope-sdk-java version from 2.16.4 to 2.16.8
## General checklist
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[X] -->
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- [ ] I have added unit and integration tests for my change
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
## Issue
Closes#896Fixes#1480Fixes#1881Fixes#1858Fixes#1865
## Context
Schema for tool parameters in the low-level API (`ChatLanguageModel` +
`ToolSpecification`) is currently specified using `ToolParameters` and
`JsonSchemaProperty` classes. This API works fine for simple cases, but
it does not work well for more complicated cases (e.g., when nested
objects or collections or recursion is required).
Moreover, [Structured
Outputs](https://github.com/langchain4j/langchain4j/pull/1590) feature
is using another API and a lot of logic between tools and structured
outputs is duplicated and out of sync.
## Change
`ToolParameters` and `JsonSchemaProperty` classes are now deprecated in
favour of new `JsonSchemaElement` API (which is used for Structured
Outputs as well). Most of the logic between this 2 features is now
unified.
`JsonSchemaElement` represents a schema for a JSON element. It can be of
such types:
- `JsonArraySchema`
- `JsonBooleanSchema`
- `JsonEnumSchema`
- `JsonIntegerSchema`
- `JsonNumberSchema`
- `JsonObjectSchema`
- `JsonReferenceSchema`
- `JsonStringSchema`
All model providers that support tools (see the list below) were updated
to support the new API. Old API is still supported for backward
compatibility, but will be removed in the future.
`ToolSpecifications` helper class now generates `ToolSpecification`s
using the new API only.
Example of the new API:
```java
ToolSpecification.builder()
.name("weather")
.description("Returns the current weather in the specified city")
.parameters(JsonObjectSchema.builder()
.addStringProperty("city", s -> s.description("The name of the city, e.g., Munich"))
.addEnumProperty("units", TemperatureUnit.class)
.required("city") // the required properties should be specified explicitly
.build())
.build();
```
`JsonObjectSchema` builder has some helper methods to make it easier to
add properties (e.g., `addProperty`, `addStringProperty`,
`addIntegerProperty`, etc.), but properties can also be specified using
a map:
```java
ToolSpecification.builder()
.name("weather")
.description("Returns the current weather in the specified city")
.parameters(JsonObjectSchema.builder()
.properties(Map.of(
"city", JsonStringSchema.builder().description("The name of the city, e.g., Munich").build(),
"units", JsonEnumSchema.builder().enumValues("CELSIUS", "FAHRENHEIT").build()
))
.required("city") // the required properties should be specified explicitly
.build())
.build();
```
### Providers that support new `JsonSchemaElement` for tools
- [x] Amazon Bedrock
- [X] Anthropic
- [X] Azure OpenAI
- [X] DashScope
- [x] GitHub Models
- [X] Google AI Gemini
- [X] Google Vertex AI Gemini
- [x] Jlama
- [x] LocalAI
- [X] Mistral AI
- [X] Ollama
- [X] OpenAI
- [x] Qianfan
- [x] Zhipu AI
### Tested Providers
- [x] Amazon Bedrock
- [x] Anthropic
- [x] Azure OpenAI
- [x] DashScope
- [x] GitHub Models
- [x] Google AI Gemini
- [x] Google Vertex AI Gemini
- [x] Jlama
- [ ] LocalAI
- [x] Mistral AI
- [x] Ollama
- [x] OpenAI
- [x] Qianfan
- [x] Zhipu AI
### Additional Changes
Several bugs have been fixed along the way (see the list of Github
issues on the top).
### Breaking changes
- `ToolSpecification.parameters()` method has been renamed into
`toolParameters()`
### Potentially breaking changes
- `ToolSpecifications` helper class now generates `ToolSpecification`s
with parameters defined using the new API (`JsonObjectSchema`) instead
of the old API (`ToolParameters`).
- If `@Tool` does not have a description (`value` annotation attribute),
`ToolSpecifications` will return `ToolSpecification` with `description()
== null`
## General checklist
- [ ] There are no breaking changes (Most of the use cases should not
break)
- [x] I have added unit and integration tests for my change
- [x] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [x] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
<!-- Before adding documentation and example(s) (below), please wait
until the PR is reviewed and approved. -->
- [x] I have added/updated the
[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
- [ ] I have added an example in the [examples
repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
- [ ] I have added/updated [Spring Boot
starter(s)](https://github.com/langchain4j/langchain4j-spring) (if
applicable)
## Change
Added Qwen2.5 open-source series models, which show amazing results.
See: https://qwenlm.github.io/blog/qwen2.5/
## General checklist
<!-- Please double-check the following points and mark them like this:
[X] -->
- [X] There are no breaking changes
- [X] I have added unit and integration tests for my change
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
- [ ] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
## Change
Bump dashscope-sdk-java from 2.15.1 to 2.16.3, which exposes more model
features.
And solve related testing problems
## General checklist
<!-- Please double-check the following points and mark them like this:
[X] -->
- [X] There are no breaking changes
- [X] I have added unit and integration tests for my change
- [X] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
## Issue
Closes#1326
## Change
Construct the message list according to the constraints of Qwen models.
(Otherwise, the model provider will return an exception.)
1. If there is a system message, it should be the first message.
Otherwise, the user message is the first message.
2. User/Tool-execution-result messages and AI messages should alternate.
Use the newest one when duplicated.
3. The last message in the message list should be a
user/tool-execution-result message. This serves as the model query/input
for the current round.
## General checklist
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- [x] I have added unit and integration tests for my change
- [x] I have manually run all the unit and integration tests in the
module I have added/changed, and they are all green
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## Issue
<!-- Please paste the link to the issue this PR is addressing. For
example: https://github.com/langchain4j/langchain4j/issues/1012 -->
## Change
<!-- Please describe the changes you made. -->
## General checklist
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- [x] I have added unit and integration tests for my change
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- [x] I have manually run all the unit and integration tests in the
[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
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repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
## Checklist for adding new model integration
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- [ ] I have added my new module in the
[BOM](https://github.com/langchain4j/langchain4j/blob/main/langchain4j-bom/pom.xml)
## Checklist for adding new embedding store integration
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from either `EmbeddingStoreIT` or `EmbeddingStoreWithFilteringIT`
- [ ] I have added my new module in the
[BOM](https://github.com/langchain4j/langchain4j/blob/main/langchain4j-bom/pom.xml)
## Checklist for changing existing embedding store integration
<!-- Please double-check the following points and mark them like this:
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`{NameOfIntegration}EmbeddingStore` works correctly with the data
persisted using the latest released version of LangChain4j
## Issue
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example: https://github.com/langchain4j/langchain4j/issues/1012 -->
## Change
<!-- Please describe the changes you made. -->
## General checklist
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[core](https://github.com/langchain4j/langchain4j/tree/main/langchain4j-core)
and
[main](https://github.com/langchain4j/langchain4j/tree/main/langchain4j)
modules, and they are all green
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[documentation](https://github.com/langchain4j/langchain4j/tree/main/docs/docs)
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repo](https://github.com/langchain4j/langchain4j-examples) (only for
"big" features)
## Checklist for adding new model integration
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[BOM](https://github.com/langchain4j/langchain4j/blob/main/langchain4j-bom/pom.xml)
## Checklist for adding new embedding store integration
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- [ ] I have added my new module in the
[BOM](https://github.com/langchain4j/langchain4j/blob/main/langchain4j-bom/pom.xml)
## Checklist for changing existing embedding store integration
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1. Add Qwen multi-modal models implementation, support for image and
text information.
Example of key input fragment:
```json
"messages": [
{
"role": "user",
"content": [
{"image": "https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg"},
{"text": "What animal is in the picture?"}
]
}
]
```
Example of key output fragment:
```json
"output": {
"choices": [
{
"finish_reason": null,
"message": {
"role": "assistant",
"content": [
{
"text": "The picture shows a dog sitting on the beach with its owner."
}
]
}
}
]
}
```
Note: The dashscope sdk supports local file URL starting with file://...
2. Add new optional parameters: baseUrl, maxTokens
1. Added support for new QWen model features: repetitionPenalty,
temperature, stops, and incrementalOutput.
2. Implemented a new QwenTokenizer class.
3. Refactored code to utilize Lombok builder instead of manual builder
implementation.
The design of the Dashscope SDK is evolving towards OpenAI, offering new
fields and specifications. Utilize these latest features to refactor the
implementation of the Qwen models.
Wrap a method to return the original LLM result, allowing subclasses to
have a chance to obtain more information such as usage (input/output
tokens, finish reason...).
Qwen series models are provided by Alibaba Cloud. They are much better
in Asia languages then other LLMs.
DashScope is a model service platform. Qwen models are its primary
supported models. But it also supports other series like LLaMA2, Dolly,
ChatGLM, BiLLa(based on LLaMA)...These may be integrated sometime in the
future.
jiangsier-xyz
