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29
.github/workflows/close-issue.yml
vendored
29
.github/workflows/close-issue.yml
vendored
@@ -1,29 +0,0 @@
|
||||
name: Close inactive issues
|
||||
on:
|
||||
workflow_dispatch: # for manual run
|
||||
schedule:
|
||||
- cron: "0 0 * * *" # Runs daily at midnight
|
||||
|
||||
# Fine-grant permission
|
||||
# https://docs.github.com/en/actions/security-for-github-actions/security-guides/automatic-token-authentication#modifying-the-permissions-for-the-github_token
|
||||
permissions:
|
||||
issues: write
|
||||
|
||||
jobs:
|
||||
close-issues:
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
issues: write
|
||||
pull-requests: write
|
||||
steps:
|
||||
- uses: actions/stale@v5
|
||||
with:
|
||||
exempt-issue-labels: "refactor,help wanted,good first issue,research,bug"
|
||||
days-before-issue-stale: 7 # Issues become stale after 7 days
|
||||
days-before-issue-close: 15 # Issues close 15 days after being marked stale
|
||||
stale-issue-label: "stale"
|
||||
close-issue-message: "This issue was closed because it has been inactive for 15 days since being marked as stale."
|
||||
days-before-pr-stale: -1 # PRs are not handled
|
||||
days-before-pr-close: -1 # PRs are not handled
|
||||
operations-per-run: 10000
|
||||
repo-token: ${{ secrets.GITHUB_TOKEN }}
|
||||
8
.github/workflows/label-issue-stale.yml
vendored
8
.github/workflows/label-issue-stale.yml
vendored
@@ -1,4 +1,4 @@
|
||||
name: Mark stale issues and pull requests
|
||||
name: Mark stale issues
|
||||
|
||||
on:
|
||||
workflow_dispatch: # for manual run
|
||||
@@ -8,21 +8,17 @@ on:
|
||||
permissions:
|
||||
contents: write # only for delete-branch option
|
||||
issues: write
|
||||
pull-requests: write
|
||||
|
||||
jobs:
|
||||
stale:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Mark stale issues and pull requests
|
||||
- name: Mark stale issues
|
||||
uses: actions/stale@v8
|
||||
with:
|
||||
repo-token: ${{ github.token }}
|
||||
days-before-stale: 15
|
||||
stale-issue-message: 'This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs.'
|
||||
stale-pr-message: 'This pull request has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs.'
|
||||
days-before-close: 7
|
||||
stale-issue-label: 'stale'
|
||||
exempt-issue-labels: 'pinned,security'
|
||||
stale-pr-label: 'stale'
|
||||
exempt-pr-labels: 'work-in-progress'
|
||||
|
||||
8
.github/workflows/publish-docs.yml
vendored
8
.github/workflows/publish-docs.yml
vendored
@@ -1,5 +1,5 @@
|
||||
# Simple workflow for deploying static content to GitHub Pages
|
||||
name: Deploy Docs to GH Pages
|
||||
name: Publish Docs to GH Pages
|
||||
|
||||
on:
|
||||
release:
|
||||
@@ -63,12 +63,12 @@ jobs:
|
||||
working-directory: "."
|
||||
|
||||
- name: Setup Pages
|
||||
uses: actions/configure-pages@v3
|
||||
uses: actions/configure-pages@v5
|
||||
- name: Upload artifact
|
||||
uses: actions/upload-pages-artifact@v2
|
||||
uses: actions/upload-pages-artifact@v3
|
||||
with:
|
||||
# Upload entire repository
|
||||
path: './docs/build/.'
|
||||
- name: Deploy to GitHub Pages
|
||||
id: deployment
|
||||
uses: actions/deploy-pages@v2
|
||||
uses: actions/deploy-pages@v4
|
||||
|
||||
36
.github/workflows/run-tests.yml
vendored
Normal file
36
.github/workflows/run-tests.yml
vendored
Normal file
@@ -0,0 +1,36 @@
|
||||
name: Run Unit and Integration Tests
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
|
||||
workflow_dispatch:
|
||||
inputs:
|
||||
branch:
|
||||
description: 'Branch name to run the tests on'
|
||||
required: true
|
||||
default: 'main'
|
||||
|
||||
jobs:
|
||||
run-tests:
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
with:
|
||||
ref: ${{ github.event.inputs.branch }}
|
||||
|
||||
- name: Set up JDK 17
|
||||
uses: actions/setup-java@v3
|
||||
with:
|
||||
java-version: '17'
|
||||
distribution: 'temurin'
|
||||
server-id: github
|
||||
settings-path: ${{ github.workspace }}
|
||||
|
||||
- name: Run unit tests
|
||||
run: mvn clean test -Punit-tests
|
||||
|
||||
- name: Run integration tests
|
||||
run: mvn clean verify -Pintegration-tests
|
||||
95
README.md
95
README.md
@@ -31,8 +31,11 @@ Find more details on the [website](https://ollama4j.github.io/ollama4j/).
|
||||
|
||||
|
||||
[](https://codecov.io/gh/ollama4j/ollama4j)
|
||||
|
||||
[](https://github.com/ollama4j/ollama4j/actions/workflows/run-tests.yml)
|
||||
|
||||
|
||||
|
||||
</div>
|
||||
|
||||
[//]: # ()
|
||||
@@ -45,6 +48,7 @@ Find more details on the [website](https://ollama4j.github.io/ollama4j/).
|
||||
- [Requirements](#requirements)
|
||||
- [Installation](#installation)
|
||||
- [API Spec](https://ollama4j.github.io/ollama4j/category/apis---model-management)
|
||||
- [Examples](#examples)
|
||||
- [Javadoc](https://ollama4j.github.io/ollama4j/apidocs/)
|
||||
- [Development](#development)
|
||||
- [Contributions](#get-involved)
|
||||
@@ -73,61 +77,6 @@ Find more details on the [website](https://ollama4j.github.io/ollama4j/).
|
||||
<img src="https://img.shields.io/badge/v0.3.0-green.svg?style=for-the-badge&labelColor=gray&label=Ollama&color=blue" alt=""/>
|
||||
</a>
|
||||
|
||||
<table>
|
||||
<tr>
|
||||
<td>
|
||||
|
||||
<a href="https://ollama.ai/" target="_blank">Local Installation</a>
|
||||
|
||||
</td>
|
||||
|
||||
<td>
|
||||
|
||||
<a href="https://hub.docker.com/r/ollama/ollama" target="_blank">Docker Installation</a>
|
||||
|
||||
</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td>
|
||||
|
||||
<a href="https://ollama.com/download/Ollama-darwin.zip" target="_blank">Download for macOS</a>
|
||||
|
||||
<a href="https://ollama.com/download/OllamaSetup.exe" target="_blank">Download for Windows</a>
|
||||
|
||||
Install on Linux
|
||||
|
||||
```shell
|
||||
curl -fsSL https://ollama.com/install.sh | sh
|
||||
```
|
||||
|
||||
</td>
|
||||
<td>
|
||||
|
||||
|
||||
|
||||
CPU only
|
||||
|
||||
```shell
|
||||
docker run -d -p 11434:11434 \
|
||||
-v ollama:/root/.ollama \
|
||||
--name ollama \
|
||||
ollama/ollama
|
||||
```
|
||||
|
||||
NVIDIA GPU
|
||||
|
||||
```shell
|
||||
docker run -d -p 11434:11434 \
|
||||
--gpus=all \
|
||||
-v ollama:/root/.ollama \
|
||||
--name ollama \
|
||||
ollama/ollama
|
||||
```
|
||||
|
||||
</td>
|
||||
</tr>
|
||||
</table>
|
||||
|
||||
## Installation
|
||||
|
||||
> [!NOTE]
|
||||
@@ -153,7 +102,7 @@ In your Maven project, add this dependency:
|
||||
<dependency>
|
||||
<groupId>io.github.ollama4j</groupId>
|
||||
<artifactId>ollama4j</artifactId>
|
||||
<version>1.0.89</version>
|
||||
<version>1.0.93</version>
|
||||
</dependency>
|
||||
```
|
||||
|
||||
@@ -209,7 +158,7 @@ In your Maven project, add this dependency:
|
||||
<dependency>
|
||||
<groupId>io.github.ollama4j</groupId>
|
||||
<artifactId>ollama4j</artifactId>
|
||||
<version>1.0.89</version>
|
||||
<version>1.0.93</version>
|
||||
</dependency>
|
||||
```
|
||||
|
||||
@@ -219,7 +168,7 @@ In your Maven project, add this dependency:
|
||||
|
||||
```groovy
|
||||
dependencies {
|
||||
implementation 'io.github.ollama4j:ollama4j:1.0.79'
|
||||
implementation 'io.github.ollama4j:ollama4j:1.0.93'
|
||||
}
|
||||
```
|
||||
|
||||
@@ -266,25 +215,29 @@ make integration-tests
|
||||
|
||||
Newer artifacts are published via GitHub Actions CI workflow when a new release is created from `main` branch.
|
||||
|
||||
## Examples
|
||||
|
||||
The `ollama4j-examples` repository contains examples for using the Ollama4j library. You can explore it [here](https://github.com/ollama4j/ollama4j-examples).
|
||||
|
||||
## ⭐ Give us a Star!
|
||||
|
||||
If you like or are using this project to build your own, please give us a star. It's a free way to show your support.
|
||||
|
||||
## Who's using Ollama4j?
|
||||
|
||||
| # | Project Name | Description | Link |
|
||||
|---|-------------------|---------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| 1 | Datafaker | A library to generate fake data | [GitHub](https://github.com/datafaker-net/datafaker-experimental/tree/main/ollama-api) |
|
||||
| 2 | Vaadin Web UI | UI-Tester for interactions with Ollama via ollama4j | [GitHub](https://github.com/TEAMPB/ollama4j-vaadin-ui) |
|
||||
| 3 | ollama-translator | A Minecraft 1.20.6 Spigot plugin that translates all messages into a specific target language via Ollama | [GitHub](https://github.com/liebki/ollama-translator) |
|
||||
| 4 | AI Player | A Minecraft mod that adds an intelligent "second player" to the game | [GitHub](https://github.com/shasankp000/AI-Player), <br/> [Reddit Thread](https://www.reddit.com/r/fabricmc/comments/1e65x5s/comment/ldr2vcf/) |
|
||||
| 5 | Ollama4j Web UI | A web UI for Ollama written in Java using Spring Boot, Vaadin, and Ollama4j | [GitHub](https://github.com/ollama4j/ollama4j-web-ui) |
|
||||
| 6 | JnsCLI | A command-line tool for Jenkins that manages jobs, builds, and configurations, with AI-powered error analysis | [GitHub](https://github.com/mirum8/jnscli) |
|
||||
| 7 | Katie Backend | An open-source AI-based question-answering platform for accessing private domain knowledge | [GitHub](https://github.com/wyona/katie-backend) |
|
||||
| 8 | TeleLlama3 Bot | A question-answering Telegram bot | [Repo](https://git.hiast.edu.sy/mohamadbashar.disoki/telellama3-bot) |
|
||||
| 9 | moqui-wechat | A moqui-wechat component | [GitHub](https://github.com/heguangyong/moqui-wechat) |
|
||||
| 10 | B4X | A set of simple and powerful RAD tool for Desktop and Server development | [Website](https://www.b4x.com/android/forum/threads/ollama4j-library-pnd_ollama4j-your-local-offline-llm-like-chatgpt.165003/) |
|
||||
|
||||
| # | Project Name | Description | Link |
|
||||
|----|-------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|
||||
| 1 | Datafaker | A library to generate fake data | [GitHub](https://github.com/datafaker-net/datafaker-experimental/tree/main/ollama-api) |
|
||||
| 2 | Vaadin Web UI | UI-Tester for interactions with Ollama via ollama4j | [GitHub](https://github.com/TEAMPB/ollama4j-vaadin-ui) |
|
||||
| 3 | ollama-translator | A Minecraft 1.20.6 Spigot plugin that translates all messages into a specific target language via Ollama | [GitHub](https://github.com/liebki/ollama-translator) |
|
||||
| 4 | AI Player | A Minecraft mod that adds an intelligent "second player" to the game | [Website](https://modrinth.com/mod/ai-player), [GitHub](https://github.com/shasankp000/AI-Player), <br/> [Reddit Thread](https://www.reddit.com/r/fabricmc/comments/1e65x5s/comment/ldr2vcf/) |
|
||||
| 5 | Ollama4j Web UI | A web UI for Ollama written in Java using Spring Boot, Vaadin, and Ollama4j | [GitHub](https://github.com/ollama4j/ollama4j-web-ui) |
|
||||
| 6 | JnsCLI | A command-line tool for Jenkins that manages jobs, builds, and configurations, with AI-powered error analysis | [GitHub](https://github.com/mirum8/jnscli) |
|
||||
| 7 | Katie Backend | An open-source AI-based question-answering platform for accessing private domain knowledge | [GitHub](https://github.com/wyona/katie-backend) |
|
||||
| 8 | TeleLlama3 Bot | A question-answering Telegram bot | [Repo](https://git.hiast.edu.sy/mohamadbashar.disoki/telellama3-bot) |
|
||||
| 9 | moqui-wechat | A moqui-wechat component | [GitHub](https://github.com/heguangyong/moqui-wechat) |
|
||||
| 10 | B4X | A set of simple and powerful RAD tool for Desktop and Server development | [Website](https://www.b4x.com/android/forum/threads/ollama4j-library-pnd_ollama4j-your-local-offline-llm-like-chatgpt.165003/) |
|
||||
| 11 | Research Article | Article: `Large language model based mutations in genetic improvement` - published on National Library of Medicine (National Center for Biotechnology Information) | [Website](https://pmc.ncbi.nlm.nih.gov/articles/PMC11750896/) |
|
||||
|
||||
## Traction
|
||||
|
||||
|
||||
@@ -7,6 +7,8 @@ sidebar_position: 7
|
||||
This API lets you create a conversation with LLMs. Using this API enables you to ask questions to the model including
|
||||
information using the history of already asked questions and the respective answers.
|
||||
|
||||
|
||||
|
||||
## Create a new conversation and use chat history to augment follow up questions
|
||||
|
||||
```java
|
||||
@@ -269,4 +271,12 @@ You will get a response similar to:
|
||||
> Second Answer: Based on the image, it's difficult to definitively determine the breed of the dog. However, the dog
|
||||
> appears to be medium-sized with a short coat and a brown coloration, which might suggest that it is a Golden Retriever
|
||||
> or a similar breed. Without more details like ear shape and tail length, it's not possible to identify the exact breed
|
||||
> confidently.
|
||||
> confidently.
|
||||
|
||||
|
||||
[//]: # (Generated using: https://emgithub.com/)
|
||||
<iframe style={{ width: '100%', height: '919px', border: 'none' }} allow="clipboard-write" src="https://emgithub.com/iframe.html?target=https%3A%2F%2Fgithub.com%2Follama4j%2Follama4j-examples%2Fblob%2Fmain%2Fsrc%2Fmain%2Fjava%2Fio%2Fgithub%2Follama4j%2Fexamples%2FChatExample.java&style=default&type=code&showBorder=on&showLineNumbers=on&showFileMeta=on&showFullPath=on&showCopy=on" />
|
||||
|
||||
<a href="https://github.com/ollama4j/ollama4j-examples/blob/main/src/main/java/io/github/ollama4j/examples/ChatExample.java" target="_blank">
|
||||
View ChatExample.java on GitHub
|
||||
</a>
|
||||
@@ -6,7 +6,7 @@ sidebar_position: 5
|
||||
|
||||
This API lets you create a custom model on the Ollama server.
|
||||
|
||||
### Create a model from an existing Modelfile in the Ollama server
|
||||
### Create a custom model from an existing model in the Ollama server
|
||||
|
||||
```java title="CreateModel.java"
|
||||
import io.github.ollama4j.OllamaAPI;
|
||||
@@ -19,144 +19,220 @@ public class CreateModel {
|
||||
|
||||
OllamaAPI ollamaAPI = new OllamaAPI(host);
|
||||
|
||||
ollamaAPI.createModelWithFilePath("mario", "/path/to/mario/modelfile/on/ollama-server");
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Create a model by passing the contents of Modelfile
|
||||
|
||||
```java title="CreateModel.java"
|
||||
public class CreateModel {
|
||||
|
||||
public static void main(String[] args) {
|
||||
|
||||
String host = "http://localhost:11434/";
|
||||
|
||||
OllamaAPI ollamaAPI = new OllamaAPI(host);
|
||||
|
||||
ollamaAPI.createModelWithModelFileContents("mario", "FROM llama2\nSYSTEM You are mario from Super Mario Bros.");
|
||||
ollamaAPI.createModel(CustomModelRequest.builder().model("mario").from("llama3.2:latest").system("You are Mario from Super Mario Bros.").build());
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
Once created, you can see it when you use [list models](./list-models) API.
|
||||
|
||||
### Example of a `Modelfile`
|
||||
[Read more](https://github.com/ollama/ollama/blob/main/docs/api.md#create-a-model) about custom model creation and the parameters available for model creation.
|
||||
|
||||
```
|
||||
FROM llama2
|
||||
# sets the temperature to 1 [higher is more creative, lower is more coherent]
|
||||
PARAMETER temperature 1
|
||||
# sets the context window size to 4096, this controls how many tokens the LLM can use as context to generate the next token
|
||||
PARAMETER num_ctx 4096
|
||||
[//]: # ()
|
||||
[//]: # (### Example of a `Modelfile`)
|
||||
|
||||
# sets a custom system message to specify the behavior of the chat assistant
|
||||
SYSTEM You are Mario from super mario bros, acting as an assistant.
|
||||
```
|
||||
[//]: # ()
|
||||
[//]: # (```)
|
||||
|
||||
### Format of the `Modelfile`
|
||||
[//]: # (FROM llama2)
|
||||
|
||||
```modelfile
|
||||
# comment
|
||||
INSTRUCTION arguments
|
||||
```
|
||||
[//]: # (# sets the temperature to 1 [higher is more creative, lower is more coherent])
|
||||
|
||||
| Instruction | Description |
|
||||
|-------------------------------------|----------------------------------------------------------------|
|
||||
| [`FROM`](#from-required) (required) | Defines the base model to use. |
|
||||
| [`PARAMETER`](#parameter) | Sets the parameters for how Ollama will run the model. |
|
||||
| [`TEMPLATE`](#template) | The full prompt template to be sent to the model. |
|
||||
| [`SYSTEM`](#system) | Specifies the system message that will be set in the template. |
|
||||
| [`ADAPTER`](#adapter) | Defines the (Q)LoRA adapters to apply to the model. |
|
||||
| [`LICENSE`](#license) | Specifies the legal license. |
|
||||
[//]: # (PARAMETER temperature 1)
|
||||
|
||||
#### PARAMETER
|
||||
[//]: # (# sets the context window size to 4096, this controls how many tokens the LLM can use as context to generate the next token)
|
||||
|
||||
The `PARAMETER` instruction defines a parameter that can be set when the model is run.
|
||||
[//]: # (PARAMETER num_ctx 4096)
|
||||
|
||||
| Parameter | Description | Value Type | Example Usage |
|
||||
|----------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|----------------------|
|
||||
| mirostat | Enable Mirostat sampling for controlling perplexity. (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0) | int | mirostat 0 |
|
||||
| mirostat_eta | Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments, while a higher learning rate will make the algorithm more responsive. (Default: 0.1) | float | mirostat_eta 0.1 |
|
||||
| mirostat_tau | Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text. (Default: 5.0) | float | mirostat_tau 5.0 |
|
||||
| num_ctx | Sets the size of the context window used to generate the next token. (Default: 2048) | int | num_ctx 4096 |
|
||||
| num_gqa | The number of GQA groups in the transformer layer. Required for some models, for example it is 8 for llama2:70b | int | num_gqa 1 |
|
||||
| num_gpu | The number of layers to send to the GPU(s). On macOS it defaults to 1 to enable metal support, 0 to disable. | int | num_gpu 50 |
|
||||
| num_thread | Sets the number of threads to use during computation. By default, Ollama will detect this for optimal performance. It is recommended to set this value to the number of physical CPU cores your system has (as opposed to the logical number of cores). | int | num_thread 8 |
|
||||
| repeat_last_n | Sets how far back for the model to look back to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx) | int | repeat_last_n 64 |
|
||||
| repeat_penalty | Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1) | float | repeat_penalty 1.1 |
|
||||
| temperature | The temperature of the model. Increasing the temperature will make the model answer more creatively. (Default: 0.8) | float | temperature 0.7 |
|
||||
| seed | Sets the random number seed to use for generation. Setting this to a specific number will make the model generate the same text for the same prompt. (Default: 0) | int | seed 42 |
|
||||
| stop | Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return. Multiple stop patterns may be set by specifying multiple separate `stop` parameters in a modelfile. | string | stop "AI assistant:" |
|
||||
| tfs_z | Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting. (default: 1) | float | tfs_z 1 |
|
||||
| num_predict | Maximum number of tokens to predict when generating text. (Default: 128, -1 = infinite generation, -2 = fill context) | int | num_predict 42 |
|
||||
| top_k | Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. (Default: 40) | int | top_k 40 |
|
||||
| top_p | Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.9) | float | top_p 0.9 |
|
||||
[//]: # ()
|
||||
[//]: # (# sets a custom system message to specify the behavior of the chat assistant)
|
||||
|
||||
#### TEMPLATE
|
||||
[//]: # (SYSTEM You are Mario from super mario bros, acting as an assistant.)
|
||||
|
||||
`TEMPLATE` of the full prompt template to be passed into the model. It may include (optionally) a system message and a
|
||||
user's prompt. This is used to create a full custom prompt, and syntax may be model specific. You can usually find the
|
||||
template for a given model in the readme for that model.
|
||||
[//]: # (```)
|
||||
|
||||
#### Template Variables
|
||||
[//]: # ()
|
||||
[//]: # (### Format of the `Modelfile`)
|
||||
|
||||
| Variable | Description |
|
||||
|-----------------|---------------------------------------------------------------------------------------------------------------|
|
||||
| `{{ .System }}` | The system message used to specify custom behavior, this must also be set in the Modelfile as an instruction. |
|
||||
| `{{ .Prompt }}` | The incoming prompt, this is not specified in the model file and will be set based on input. |
|
||||
| `{{ .First }}` | A boolean value used to render specific template information for the first generation of a session. |
|
||||
[//]: # ()
|
||||
[//]: # (```modelfile)
|
||||
|
||||
```modelfile
|
||||
TEMPLATE """
|
||||
{{- if .First }}
|
||||
### System:
|
||||
{{ .System }}
|
||||
{{- end }}
|
||||
[//]: # (# comment)
|
||||
|
||||
### User:
|
||||
{{ .Prompt }}
|
||||
[//]: # (INSTRUCTION arguments)
|
||||
|
||||
### Response:
|
||||
"""
|
||||
[//]: # (```)
|
||||
|
||||
SYSTEM """<system message>"""
|
||||
```
|
||||
[//]: # ()
|
||||
[//]: # (| Instruction | Description |)
|
||||
|
||||
### SYSTEM
|
||||
[//]: # (|-------------------------------------|----------------------------------------------------------------|)
|
||||
|
||||
The `SYSTEM` instruction specifies the system message to be used in the template, if applicable.
|
||||
[//]: # (| [`FROM`](#from-required) (required) | Defines the base model to use. |)
|
||||
|
||||
```modelfile
|
||||
SYSTEM """<system message>"""
|
||||
```
|
||||
[//]: # (| [`PARAMETER`](#parameter) | Sets the parameters for how Ollama will run the model. |)
|
||||
|
||||
### ADAPTER
|
||||
[//]: # (| [`TEMPLATE`](#template) | The full prompt template to be sent to the model. |)
|
||||
|
||||
The `ADAPTER` instruction specifies the LoRA adapter to apply to the base model. The value of this instruction should be
|
||||
an absolute path or a path relative to the Modelfile and the file must be in a GGML file format. The adapter should be
|
||||
tuned from the base model otherwise the behaviour is undefined.
|
||||
[//]: # (| [`SYSTEM`](#system) | Specifies the system message that will be set in the template. |)
|
||||
|
||||
```modelfile
|
||||
ADAPTER ./ollama-lora.bin
|
||||
```
|
||||
[//]: # (| [`ADAPTER`](#adapter) | Defines the (Q)LoRA adapters to apply to the model. |)
|
||||
|
||||
### LICENSE
|
||||
[//]: # (| [`LICENSE`](#license) | Specifies the legal license. |)
|
||||
|
||||
The `LICENSE` instruction allows you to specify the legal license under which the model used with this Modelfile is
|
||||
shared or distributed.
|
||||
[//]: # ()
|
||||
[//]: # (#### PARAMETER)
|
||||
|
||||
```modelfile
|
||||
LICENSE """
|
||||
<license text>
|
||||
"""
|
||||
```
|
||||
[//]: # ()
|
||||
[//]: # (The `PARAMETER` instruction defines a parameter that can be set when the model is run.)
|
||||
|
||||
## Notes
|
||||
[//]: # ()
|
||||
[//]: # (| Parameter | Description | Value Type | Example Usage |)
|
||||
|
||||
- the **`Modelfile` is not case sensitive**. In the examples, uppercase instructions are used to make it easier to
|
||||
distinguish it from arguments.
|
||||
- Instructions can be in any order. In the examples, the `FROM` instruction is first to keep it easily readable.
|
||||
[//]: # (|----------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------|----------------------|)
|
||||
|
||||
Read more about Modelfile: https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md
|
||||
[//]: # (| mirostat | Enable Mirostat sampling for controlling perplexity. (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0) | int | mirostat 0 |)
|
||||
|
||||
[//]: # (| mirostat_eta | Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments, while a higher learning rate will make the algorithm more responsive. (Default: 0.1) | float | mirostat_eta 0.1 |)
|
||||
|
||||
[//]: # (| mirostat_tau | Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text. (Default: 5.0) | float | mirostat_tau 5.0 |)
|
||||
|
||||
[//]: # (| num_ctx | Sets the size of the context window used to generate the next token. (Default: 2048) | int | num_ctx 4096 |)
|
||||
|
||||
[//]: # (| num_gqa | The number of GQA groups in the transformer layer. Required for some models, for example it is 8 for llama2:70b | int | num_gqa 1 |)
|
||||
|
||||
[//]: # (| num_gpu | The number of layers to send to the GPU(s). On macOS it defaults to 1 to enable metal support, 0 to disable. | int | num_gpu 50 |)
|
||||
|
||||
[//]: # (| num_thread | Sets the number of threads to use during computation. By default, Ollama will detect this for optimal performance. It is recommended to set this value to the number of physical CPU cores your system has (as opposed to the logical number of cores). | int | num_thread 8 |)
|
||||
|
||||
[//]: # (| repeat_last_n | Sets how far back for the model to look back to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx) | int | repeat_last_n 64 |)
|
||||
|
||||
[//]: # (| repeat_penalty | Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1) | float | repeat_penalty 1.1 |)
|
||||
|
||||
[//]: # (| temperature | The temperature of the model. Increasing the temperature will make the model answer more creatively. (Default: 0.8) | float | temperature 0.7 |)
|
||||
|
||||
[//]: # (| seed | Sets the random number seed to use for generation. Setting this to a specific number will make the model generate the same text for the same prompt. (Default: 0) | int | seed 42 |)
|
||||
|
||||
[//]: # (| stop | Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return. Multiple stop patterns may be set by specifying multiple separate `stop` parameters in a modelfile. | string | stop "AI assistant:" |)
|
||||
|
||||
[//]: # (| tfs_z | Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting. (default: 1) | float | tfs_z 1 |)
|
||||
|
||||
[//]: # (| num_predict | Maximum number of tokens to predict when generating text. (Default: 128, -1 = infinite generation, -2 = fill context) | int | num_predict 42 |)
|
||||
|
||||
[//]: # (| top_k | Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. (Default: 40) | int | top_k 40 |)
|
||||
|
||||
[//]: # (| top_p | Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.9) | float | top_p 0.9 |)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (#### TEMPLATE)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (`TEMPLATE` of the full prompt template to be passed into the model. It may include (optionally) a system message and a)
|
||||
|
||||
[//]: # (user's prompt. This is used to create a full custom prompt, and syntax may be model specific. You can usually find the)
|
||||
|
||||
[//]: # (template for a given model in the readme for that model.)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (#### Template Variables)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (| Variable | Description |)
|
||||
|
||||
[//]: # (|-----------------|---------------------------------------------------------------------------------------------------------------|)
|
||||
|
||||
[//]: # (| `{{ .System }}` | The system message used to specify custom behavior, this must also be set in the Modelfile as an instruction. |)
|
||||
|
||||
[//]: # (| `{{ .Prompt }}` | The incoming prompt, this is not specified in the model file and will be set based on input. |)
|
||||
|
||||
[//]: # (| `{{ .First }}` | A boolean value used to render specific template information for the first generation of a session. |)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (```modelfile)
|
||||
|
||||
[//]: # (TEMPLATE """)
|
||||
|
||||
[//]: # ({{- if .First }})
|
||||
|
||||
[//]: # (### System:)
|
||||
|
||||
[//]: # ({{ .System }})
|
||||
|
||||
[//]: # ({{- end }})
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (### User:)
|
||||
|
||||
[//]: # ({{ .Prompt }})
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (### Response:)
|
||||
|
||||
[//]: # (""")
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (SYSTEM """<system message>""")
|
||||
|
||||
[//]: # (```)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (### SYSTEM)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (The `SYSTEM` instruction specifies the system message to be used in the template, if applicable.)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (```modelfile)
|
||||
|
||||
[//]: # (SYSTEM """<system message>""")
|
||||
|
||||
[//]: # (```)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (### ADAPTER)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (The `ADAPTER` instruction specifies the LoRA adapter to apply to the base model. The value of this instruction should be)
|
||||
|
||||
[//]: # (an absolute path or a path relative to the Modelfile and the file must be in a GGML file format. The adapter should be)
|
||||
|
||||
[//]: # (tuned from the base model otherwise the behaviour is undefined.)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (```modelfile)
|
||||
|
||||
[//]: # (ADAPTER ./ollama-lora.bin)
|
||||
|
||||
[//]: # (```)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (### LICENSE)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (The `LICENSE` instruction allows you to specify the legal license under which the model used with this Modelfile is)
|
||||
|
||||
[//]: # (shared or distributed.)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (```modelfile)
|
||||
|
||||
[//]: # (LICENSE """)
|
||||
|
||||
[//]: # (<license text>)
|
||||
|
||||
[//]: # (""")
|
||||
|
||||
[//]: # (```)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (## Notes)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (- the **`Modelfile` is not case sensitive**. In the examples, uppercase instructions are used to make it easier to)
|
||||
|
||||
[//]: # ( distinguish it from arguments.)
|
||||
|
||||
[//]: # (- Instructions can be in any order. In the examples, the `FROM` instruction is first to keep it easily readable.)
|
||||
|
||||
[//]: # ()
|
||||
[//]: # (Read more about Modelfile: https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md)
|
||||
@@ -84,6 +84,7 @@ const config = {
|
||||
position: 'left',
|
||||
label: 'Docs',
|
||||
},
|
||||
{to: 'https://github.com/ollama4j/ollama4j-examples', label: 'Examples', position: 'left'},
|
||||
{to: 'https://ollama4j.github.io/ollama4j/apidocs/', label: 'Javadoc', position: 'left'},
|
||||
{to: 'https://ollama4j.github.io/ollama4j/doxygen/html/', label: 'Doxygen', position: 'left'},
|
||||
{to: '/blog', label: 'Blog', position: 'left'},
|
||||
@@ -106,6 +107,15 @@ const config = {
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
title: 'Usage',
|
||||
items: [
|
||||
{
|
||||
label: 'Examples',
|
||||
to: 'https://github.com/ollama4j/ollama4j-examples',
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
title: 'Community',
|
||||
items: [
|
||||
|
||||
492
docs/package-lock.json
generated
492
docs/package-lock.json
generated
@@ -4242,9 +4242,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/body-parser": {
|
||||
"version": "1.20.2",
|
||||
"resolved": "https://registry.npmjs.org/body-parser/-/body-parser-1.20.2.tgz",
|
||||
"integrity": "sha512-ml9pReCu3M61kGlqoTm2umSXTlRTuGTx0bfYj+uIUKKYycG5NtSbeetV3faSU6R7ajOPw0g/J1PvK4qNy7s5bA==",
|
||||
"version": "1.20.3",
|
||||
"resolved": "https://registry.npmjs.org/body-parser/-/body-parser-1.20.3.tgz",
|
||||
"integrity": "sha512-7rAxByjUMqQ3/bHJy7D6OGXvx/MMc4IqBn/X0fcM1QUcAItpZrBEYhWGem+tzXH90c+G01ypMcYJBO9Y30203g==",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"bytes": "3.1.2",
|
||||
@@ -4255,7 +4255,7 @@
|
||||
"http-errors": "2.0.0",
|
||||
"iconv-lite": "0.4.24",
|
||||
"on-finished": "2.4.1",
|
||||
"qs": "6.11.0",
|
||||
"qs": "6.13.0",
|
||||
"raw-body": "2.5.2",
|
||||
"type-is": "~1.6.18",
|
||||
"unpipe": "1.0.0"
|
||||
@@ -4446,6 +4446,35 @@
|
||||
"url": "https://github.com/sponsors/ljharb"
|
||||
}
|
||||
},
|
||||
"node_modules/call-bind-apply-helpers": {
|
||||
"version": "1.0.2",
|
||||
"resolved": "https://registry.npmjs.org/call-bind-apply-helpers/-/call-bind-apply-helpers-1.0.2.tgz",
|
||||
"integrity": "sha512-Sp1ablJ0ivDkSzjcaJdxEunN5/XvksFJ2sMBFfq6x0ryhQV/2b/KwFe21cMpmHtPOSij8K99/wSfoEuTObmuMQ==",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"es-errors": "^1.3.0",
|
||||
"function-bind": "^1.1.2"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">= 0.4"
|
||||
}
|
||||
},
|
||||
"node_modules/call-bound": {
|
||||
"version": "1.0.4",
|
||||
"resolved": "https://registry.npmjs.org/call-bound/-/call-bound-1.0.4.tgz",
|
||||
"integrity": "sha512-+ys997U96po4Kx/ABpBCqhA9EuxJaQWDQg7295H4hBphv3IZg0boBKuwYpt4YXp6MZ5AmZQnU/tyMTlRpaSejg==",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"call-bind-apply-helpers": "^1.0.2",
|
||||
"get-intrinsic": "^1.3.0"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">= 0.4"
|
||||
},
|
||||
"funding": {
|
||||
"url": "https://github.com/sponsors/ljharb"
|
||||
}
|
||||
},
|
||||
"node_modules/callsites": {
|
||||
"version": "3.1.0",
|
||||
"resolved": "https://registry.npmjs.org/callsites/-/callsites-3.1.0.tgz",
|
||||
@@ -4945,9 +4974,9 @@
|
||||
"integrity": "sha512-Kvp459HrV2FEJ1CAsi1Ku+MY3kasH19TFykTz2xWmMeq6bk2NU3XXvfJ+Q61m0xktWwt+1HSYf3JZsTms3aRJg=="
|
||||
},
|
||||
"node_modules/cookie": {
|
||||
"version": "0.6.0",
|
||||
"resolved": "https://registry.npmjs.org/cookie/-/cookie-0.6.0.tgz",
|
||||
"integrity": "sha512-U71cyTamuh1CRNCfpGY6to28lxvNwPG4Guz/EVjgf3Jmzv0vlDp1atT9eS5dDjMYHucpHbWns6Lwf3BKz6svdw==",
|
||||
"version": "0.7.1",
|
||||
"resolved": "https://registry.npmjs.org/cookie/-/cookie-0.7.1.tgz",
|
||||
"integrity": "sha512-6DnInpx7SJ2AK3+CTUE/ZM0vWTUboZCegxhC2xiIydHR9jNuTAASBrfEpHhiGOZw/nX51bHt6YQl8jsGo4y/0w==",
|
||||
"license": "MIT",
|
||||
"engines": {
|
||||
"node": ">= 0.6"
|
||||
@@ -5103,9 +5132,10 @@
|
||||
}
|
||||
},
|
||||
"node_modules/cross-spawn": {
|
||||
"version": "7.0.3",
|
||||
"resolved": "https://registry.npmjs.org/cross-spawn/-/cross-spawn-7.0.3.tgz",
|
||||
"integrity": "sha512-iRDPJKUPVEND7dHPO8rkbOnPpyDygcDFtWjpeWNCgy8WP2rXcxXL8TskReQl6OrB2G7+UJrags1q15Fudc7G6w==",
|
||||
"version": "7.0.6",
|
||||
"resolved": "https://registry.npmjs.org/cross-spawn/-/cross-spawn-7.0.6.tgz",
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"side-channel": "^1.0.6"
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@@ -13786,9 +13873,10 @@
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"version": "0.18.0",
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"license": "MIT",
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"dependencies": {
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"debug": "2.6.9",
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"depd": "2.0.0",
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@@ -13812,6 +13900,7 @@
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"version": "2.6.9",
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"ms": "2.0.0"
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@@ -13819,48 +13908,62 @@
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"node_modules/send/node_modules/debug/node_modules/ms": {
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"version": "2.0.0",
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"resolved": "https://registry.npmjs.org/ms/-/ms-2.0.0.tgz",
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"license": "MIT"
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},
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"node_modules/send/node_modules/encodeurl": {
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"engines": {
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"node": ">= 0.8"
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"license": "MIT"
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"engines": {
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"randombytes": "^2.1.0"
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"bytes": "3.0.0",
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"mime-types": "2.1.18",
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"minimatch": "3.1.2",
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"path-is-inside": "1.0.2",
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"path-to-regexp": "2.2.1",
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"path-to-regexp": "3.3.0",
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"range-parser": "1.2.0"
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}
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},
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"node_modules/serve-handler/node_modules/path-to-regexp": {
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"version": "2.2.1",
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"resolved": "https://registry.npmjs.org/path-to-regexp/-/path-to-regexp-2.2.1.tgz",
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"integrity": "sha512-gu9bD6Ta5bwGrrU8muHzVOBFFREpp2iRkVfhBJahwJ6p6Xw20SjT0MxLnwkjOibQmGSYhiUnf2FLe7k+jcFmGQ=="
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"version": "3.3.0",
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"resolved": "https://registry.npmjs.org/path-to-regexp/-/path-to-regexp-3.3.0.tgz",
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"integrity": "sha512-qyCH421YQPS2WFDxDjftfc1ZR5WKQzVzqsp4n9M2kQhVOo/ByahFoUNJfl58kOcEGfQ//7weFTDhm+ss8Ecxgw==",
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"license": "MIT"
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},
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"node_modules/serve-index": {
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"version": "1.9.1",
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@@ -13933,14 +14036,15 @@
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}
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},
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"node_modules/serve-static": {
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"version": "1.15.0",
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"resolved": "https://registry.npmjs.org/serve-static/-/serve-static-1.15.0.tgz",
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"integrity": "sha512-XGuRDNjXUijsUL0vl6nSD7cwURuzEgglbOaFuZM9g3kwDXOWVTck0jLzjPzGD+TazWbboZYu52/9/XPdUgne9g==",
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"version": "1.16.2",
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"resolved": "https://registry.npmjs.org/serve-static/-/serve-static-1.16.2.tgz",
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"integrity": "sha512-VqpjJZKadQB/PEbEwvFdO43Ax5dFBZ2UECszz8bQ7pi7wt//PWe1P6MN7eCnjsatYtBT6EuiClbjSWP2WrIoTw==",
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"license": "MIT",
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"dependencies": {
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"encodeurl": "~1.0.2",
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"encodeurl": "~2.0.0",
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"escape-html": "~1.0.3",
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"parseurl": "~1.3.3",
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"send": "0.18.0"
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"send": "0.19.0"
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},
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"engines": {
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"node": ">= 0.8.0"
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@@ -13966,7 +14070,8 @@
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"node_modules/setprototypeof": {
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"version": "1.2.0",
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"resolved": "https://registry.npmjs.org/setprototypeof/-/setprototypeof-1.2.0.tgz",
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"integrity": "sha512-E5LDX7Wrp85Kil5bhZv46j8jOeboKq5JMmYM3gVGdGH8xFpPWXUMsNrlODCrkoxMEeNi/XZIwuRvY4XNwYMJpw=="
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"integrity": "sha512-E5LDX7Wrp85Kil5bhZv46j8jOeboKq5JMmYM3gVGdGH8xFpPWXUMsNrlODCrkoxMEeNi/XZIwuRvY4XNwYMJpw==",
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"license": "ISC"
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},
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"node_modules/shallow-clone": {
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"version": "3.0.1",
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@@ -14028,15 +14133,69 @@
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}
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"node_modules/side-channel": {
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"version": "1.0.6",
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"resolved": "https://registry.npmjs.org/side-channel/-/side-channel-1.0.6.tgz",
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"version": "1.1.0",
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"resolved": "https://registry.npmjs.org/side-channel/-/side-channel-1.1.0.tgz",
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"integrity": "sha512-ZX99e6tRweoUXqR+VBrslhda51Nh5MTQwou5tnUDgbtyM0dBgmhEDtWGP/xbKn6hqfPRHujUNwz5fy/wbbhnpw==",
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"license": "MIT",
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"dependencies": {
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"call-bind": "^1.0.7",
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"es-errors": "^1.3.0",
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"get-intrinsic": "^1.2.4",
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"object-inspect": "^1.13.1"
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"object-inspect": "^1.13.3",
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"side-channel-list": "^1.0.0",
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"side-channel-map": "^1.0.1",
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"side-channel-weakmap": "^1.0.2"
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},
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"engines": {
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"node": ">= 0.4"
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},
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"funding": {
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"url": "https://github.com/sponsors/ljharb"
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}
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"node_modules/side-channel-list": {
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"version": "1.0.0",
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"license": "MIT",
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"dependencies": {
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"es-errors": "^1.3.0",
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"object-inspect": "^1.13.3"
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},
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"engines": {
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"node": ">= 0.4"
|
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},
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"funding": {
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"url": "https://github.com/sponsors/ljharb"
|
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}
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},
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"node_modules/side-channel-map": {
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"version": "1.0.1",
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"resolved": "https://registry.npmjs.org/side-channel-map/-/side-channel-map-1.0.1.tgz",
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"license": "MIT",
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"dependencies": {
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"call-bound": "^1.0.2",
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"es-errors": "^1.3.0",
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"get-intrinsic": "^1.2.5",
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"object-inspect": "^1.13.3"
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},
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"engines": {
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"node": ">= 0.4"
|
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},
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"funding": {
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"url": "https://github.com/sponsors/ljharb"
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}
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},
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"node_modules/side-channel-weakmap": {
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"version": "1.0.2",
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"resolved": "https://registry.npmjs.org/side-channel-weakmap/-/side-channel-weakmap-1.0.2.tgz",
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"integrity": "sha512-WPS/HvHQTYnHisLo9McqBHOJk2FkHO/tlpvldyrnem4aeQp4hai3gythswg6p01oSoTl58rcpiFAjF2br2Ak2A==",
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"license": "MIT",
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"dependencies": {
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"call-bound": "^1.0.2",
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"es-errors": "^1.3.0",
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"get-intrinsic": "^1.2.5",
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"object-inspect": "^1.13.3",
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"side-channel-map": "^1.0.1"
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},
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"engines": {
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"node": ">= 0.4"
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@@ -14227,6 +14386,7 @@
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"version": "2.0.1",
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"resolved": "https://registry.npmjs.org/statuses/-/statuses-2.0.1.tgz",
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"integrity": "sha512-RwNA9Z/7PrK06rYLIzFMlaF+l73iwpzsqRIFgbMLbTcLD6cOao82TaWefPXQvB2fOC4AjuYSEndS7N/mTCbkdQ==",
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"license": "MIT",
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"engines": {
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"node": ">= 0.8"
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}
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@@ -14616,6 +14776,7 @@
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"version": "1.0.1",
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"resolved": "https://registry.npmjs.org/toidentifier/-/toidentifier-1.0.1.tgz",
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"integrity": "sha512-o5sSPKEkg/DIQNmH43V0/uerLrpzVedkUh8tGNvaeXpfpuwjKenlSox/2O/BTlZUtEe+JG7s5YhEz608PlAHRA==",
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"license": "MIT",
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"engines": {
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"node": ">=0.6"
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}
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@@ -14906,6 +15067,7 @@
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"version": "1.0.0",
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"resolved": "https://registry.npmjs.org/unpipe/-/unpipe-1.0.0.tgz",
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"integrity": "sha512-pjy2bYhSsufwWlKwPc+l3cN7+wuJlK6uz0YdJEOlQDbl6jo/YlPi4mb8agUkVC8BF7V8NuzeyPNqRksA3hztKQ==",
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"license": "MIT",
|
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"engines": {
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"node": ">= 0.8"
|
||||
}
|
||||
|
||||
92
pom.xml
92
pom.xml
@@ -13,8 +13,8 @@
|
||||
<packaging>jar</packaging>
|
||||
|
||||
<properties>
|
||||
<maven.compiler.source>11</maven.compiler.source>
|
||||
<maven.compiler.target>11</maven.compiler.target>
|
||||
<maven.compiler.release>11</maven.compiler.release>
|
||||
<project.build.outputTimestamp>${git.commit.time}</project.build.outputTimestamp><!-- populated via git-commit-id-plugin -->
|
||||
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
|
||||
<maven-surefire-plugin.version>3.0.0-M5</maven-surefire-plugin.version>
|
||||
<maven-failsafe-plugin.version>3.0.0-M5</maven-failsafe-plugin.version>
|
||||
@@ -49,7 +49,7 @@
|
||||
<plugin>
|
||||
<groupId>org.apache.maven.plugins</groupId>
|
||||
<artifactId>maven-source-plugin</artifactId>
|
||||
<version>3.3.0</version>
|
||||
<version>3.3.1</version>
|
||||
<executions>
|
||||
<execution>
|
||||
<id>attach-sources</id>
|
||||
@@ -62,7 +62,7 @@
|
||||
<plugin>
|
||||
<groupId>org.apache.maven.plugins</groupId>
|
||||
<artifactId>maven-javadoc-plugin</artifactId>
|
||||
<version>3.5.0</version>
|
||||
<version>3.11.2</version>
|
||||
<configuration>
|
||||
<!-- to disable the "missing" warnings. Remove the doclint to enable warnings-->
|
||||
<doclint>all,-missing</doclint>
|
||||
@@ -70,9 +70,13 @@
|
||||
<executions>
|
||||
<execution>
|
||||
<id>attach-javadocs</id>
|
||||
<phase>package</phase>
|
||||
<goals>
|
||||
<goal>jar</goal>
|
||||
</goals>
|
||||
<configuration>
|
||||
<outputDirectory>${project.build.directory}</outputDirectory>
|
||||
</configuration>
|
||||
</execution>
|
||||
</executions>
|
||||
</plugin>
|
||||
@@ -114,7 +118,6 @@
|
||||
</executions>
|
||||
</plugin>
|
||||
|
||||
|
||||
<plugin>
|
||||
<groupId>org.apache.maven.plugins</groupId>
|
||||
<artifactId>maven-gpg-plugin</artifactId>
|
||||
@@ -130,7 +133,36 @@
|
||||
</executions>
|
||||
</plugin>
|
||||
|
||||
<plugin>
|
||||
<groupId>io.github.git-commit-id</groupId>
|
||||
<artifactId>git-commit-id-maven-plugin</artifactId>
|
||||
<version>9.0.1</version>
|
||||
<executions>
|
||||
<execution>
|
||||
<goals>
|
||||
<goal>revision</goal>
|
||||
</goals>
|
||||
</execution>
|
||||
</executions>
|
||||
<configuration>
|
||||
<dateFormat>yyyy-MM-dd'T'HH:mm:ss'Z'</dateFormat>
|
||||
<dateFormatTimeZone>Etc/UTC</dateFormatTimeZone>
|
||||
</configuration>
|
||||
</plugin>
|
||||
</plugins>
|
||||
|
||||
<pluginManagement>
|
||||
<plugins>
|
||||
<plugin>
|
||||
<artifactId>maven-compiler-plugin</artifactId>
|
||||
<version>3.14.0</version>
|
||||
</plugin>
|
||||
<plugin>
|
||||
<artifactId>maven-jar-plugin</artifactId>
|
||||
<version>3.4.2</version>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</pluginManagement>
|
||||
</build>
|
||||
|
||||
<dependencies>
|
||||
@@ -184,6 +216,13 @@
|
||||
<version>20240205</version>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
|
||||
<dependency>
|
||||
<groupId>org.testcontainers</groupId>
|
||||
<artifactId>ollama</artifactId>
|
||||
<version>1.20.2</version>
|
||||
<scope>test</scope>
|
||||
</dependency>
|
||||
</dependencies>
|
||||
|
||||
<distributionManagement>
|
||||
@@ -225,6 +264,7 @@
|
||||
<test.env>unit</test.env>
|
||||
<skipUnitTests>false</skipUnitTests>
|
||||
<skipIntegrationTests>true</skipIntegrationTests>
|
||||
<skipGpgPluginDuringTests>true</skipGpgPluginDuringTests>
|
||||
</properties>
|
||||
<activation>
|
||||
<activeByDefault>false</activeByDefault>
|
||||
@@ -250,6 +290,23 @@
|
||||
</execution>
|
||||
</executions>
|
||||
</plugin>
|
||||
<plugin>
|
||||
<groupId>org.apache.maven.plugins</groupId>
|
||||
<artifactId>maven-gpg-plugin</artifactId>
|
||||
<version>1.5</version>
|
||||
<executions>
|
||||
<execution>
|
||||
<id>sign-artifacts</id>
|
||||
<phase>verify</phase>
|
||||
<goals>
|
||||
<goal>sign</goal>
|
||||
</goals>
|
||||
<configuration>
|
||||
<skip>${skipGpgPluginDuringTests}</skip>
|
||||
</configuration>
|
||||
</execution>
|
||||
</executions>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</build>
|
||||
</profile>
|
||||
@@ -259,7 +316,29 @@
|
||||
<test.env>integration</test.env>
|
||||
<skipUnitTests>true</skipUnitTests>
|
||||
<skipIntegrationTests>false</skipIntegrationTests>
|
||||
<skipGpgPluginDuringTests>true</skipGpgPluginDuringTests>
|
||||
</properties>
|
||||
<build>
|
||||
<plugins>
|
||||
<plugin>
|
||||
<groupId>org.apache.maven.plugins</groupId>
|
||||
<artifactId>maven-gpg-plugin</artifactId>
|
||||
<version>1.5</version>
|
||||
<executions>
|
||||
<execution>
|
||||
<id>sign-artifacts</id>
|
||||
<phase>verify</phase>
|
||||
<goals>
|
||||
<goal>sign</goal>
|
||||
</goals>
|
||||
<configuration>
|
||||
<skip>${skipGpgPluginDuringTests}</skip>
|
||||
</configuration>
|
||||
</execution>
|
||||
</executions>
|
||||
</plugin>
|
||||
</plugins>
|
||||
</build>
|
||||
</profile>
|
||||
<profile>
|
||||
<id>ci-cd</id>
|
||||
@@ -303,7 +382,6 @@
|
||||
<autoReleaseAfterClose>true</autoReleaseAfterClose>
|
||||
</configuration>
|
||||
</plugin>
|
||||
|
||||
<plugin>
|
||||
<groupId>org.jacoco</groupId>
|
||||
<artifactId>jacoco-maven-plugin</artifactId>
|
||||
@@ -328,4 +406,4 @@
|
||||
</profile>
|
||||
</profiles>
|
||||
|
||||
</project>
|
||||
</project>
|
||||
|
||||
@@ -1,14 +1,17 @@
|
||||
package io.github.ollama4j;
|
||||
|
||||
import com.fasterxml.jackson.core.JsonParseException;
|
||||
import com.fasterxml.jackson.databind.JsonNode;
|
||||
import com.fasterxml.jackson.databind.ObjectMapper;
|
||||
import io.github.ollama4j.exceptions.OllamaBaseException;
|
||||
import io.github.ollama4j.exceptions.RoleNotFoundException;
|
||||
import io.github.ollama4j.exceptions.ToolInvocationException;
|
||||
import io.github.ollama4j.exceptions.ToolNotFoundException;
|
||||
import io.github.ollama4j.models.chat.*;
|
||||
import io.github.ollama4j.models.embeddings.OllamaEmbedRequestModel;
|
||||
import io.github.ollama4j.models.embeddings.OllamaEmbedResponseModel;
|
||||
import io.github.ollama4j.models.embeddings.OllamaEmbeddingResponseModel;
|
||||
import io.github.ollama4j.models.embeddings.OllamaEmbeddingsRequestModel;
|
||||
import io.github.ollama4j.models.embeddings.OllamaEmbedResponseModel;
|
||||
import io.github.ollama4j.models.generate.OllamaGenerateRequest;
|
||||
import io.github.ollama4j.models.generate.OllamaStreamHandler;
|
||||
import io.github.ollama4j.models.generate.OllamaTokenHandler;
|
||||
@@ -22,6 +25,12 @@ import io.github.ollama4j.tools.annotations.ToolSpec;
|
||||
import io.github.ollama4j.utils.Options;
|
||||
import io.github.ollama4j.utils.Utils;
|
||||
import lombok.Setter;
|
||||
import org.jsoup.Jsoup;
|
||||
import org.jsoup.nodes.Document;
|
||||
import org.jsoup.nodes.Element;
|
||||
import org.jsoup.select.Elements;
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
|
||||
import java.io.*;
|
||||
import java.lang.reflect.InvocationTargetException;
|
||||
@@ -39,13 +48,6 @@ import java.time.Duration;
|
||||
import java.util.*;
|
||||
import java.util.stream.Collectors;
|
||||
|
||||
import org.slf4j.Logger;
|
||||
import org.slf4j.LoggerFactory;
|
||||
import org.jsoup.Jsoup;
|
||||
import org.jsoup.nodes.Document;
|
||||
import org.jsoup.nodes.Element;
|
||||
import org.jsoup.select.Elements;
|
||||
|
||||
/**
|
||||
* The base Ollama API class.
|
||||
*/
|
||||
@@ -92,6 +94,9 @@ public class OllamaAPI {
|
||||
} else {
|
||||
this.host = host;
|
||||
}
|
||||
if (this.verbose) {
|
||||
logger.info("Ollama API initialized with host: " + this.host);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -318,26 +323,58 @@ public class OllamaAPI {
|
||||
public void pullModel(String modelName) throws OllamaBaseException, IOException, URISyntaxException, InterruptedException {
|
||||
String url = this.host + "/api/pull";
|
||||
String jsonData = new ModelRequest(modelName).toString();
|
||||
HttpRequest request = getRequestBuilderDefault(new URI(url)).POST(HttpRequest.BodyPublishers.ofString(jsonData)).header("Accept", "application/json").header("Content-type", "application/json").build();
|
||||
HttpRequest request = getRequestBuilderDefault(new URI(url))
|
||||
.POST(HttpRequest.BodyPublishers.ofString(jsonData))
|
||||
.header("Accept", "application/json")
|
||||
.header("Content-type", "application/json")
|
||||
.build();
|
||||
HttpClient client = HttpClient.newHttpClient();
|
||||
HttpResponse<InputStream> response = client.send(request, HttpResponse.BodyHandlers.ofInputStream());
|
||||
int statusCode = response.statusCode();
|
||||
InputStream responseBodyStream = response.body();
|
||||
String responseString = "";
|
||||
boolean success = false; // Flag to check the pull success.
|
||||
try (BufferedReader reader = new BufferedReader(new InputStreamReader(responseBodyStream, StandardCharsets.UTF_8))) {
|
||||
String line;
|
||||
while ((line = reader.readLine()) != null) {
|
||||
ModelPullResponse modelPullResponse = Utils.getObjectMapper().readValue(line, ModelPullResponse.class);
|
||||
if (verbose) {
|
||||
logger.info(modelPullResponse.getStatus());
|
||||
if (modelPullResponse != null && modelPullResponse.getStatus() != null) {
|
||||
if (verbose) {
|
||||
logger.info(modelName + ": " + modelPullResponse.getStatus());
|
||||
}
|
||||
// Check if status is "success" and set success flag to true.
|
||||
if ("success".equalsIgnoreCase(modelPullResponse.getStatus())) {
|
||||
success = true;
|
||||
}
|
||||
} else {
|
||||
logger.error("Received null or invalid status for model pull.");
|
||||
}
|
||||
}
|
||||
}
|
||||
if (!success) {
|
||||
logger.error("Model pull failed or returned invalid status.");
|
||||
throw new OllamaBaseException("Model pull failed or returned invalid status.");
|
||||
}
|
||||
if (statusCode != 200) {
|
||||
throw new OllamaBaseException(statusCode + " - " + responseString);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
public String getVersion() throws URISyntaxException, IOException, InterruptedException, OllamaBaseException {
|
||||
String url = this.host + "/api/version";
|
||||
HttpClient httpClient = HttpClient.newHttpClient();
|
||||
HttpRequest httpRequest = getRequestBuilderDefault(new URI(url)).header("Accept", "application/json").header("Content-type", "application/json").GET().build();
|
||||
HttpResponse<String> response = httpClient.send(httpRequest, HttpResponse.BodyHandlers.ofString());
|
||||
int statusCode = response.statusCode();
|
||||
String responseString = response.body();
|
||||
if (statusCode == 200) {
|
||||
return Utils.getObjectMapper().readValue(responseString, OllamaVersion.class).getVersion();
|
||||
} else {
|
||||
throw new OllamaBaseException(statusCode + " - " + responseString);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Pulls a model using the specified Ollama library model tag.
|
||||
* The model is identified by a name and a tag, which are combined into a single identifier
|
||||
@@ -391,6 +428,7 @@ public class OllamaAPI {
|
||||
* @throws InterruptedException if the operation is interrupted
|
||||
* @throws URISyntaxException if the URI for the request is malformed
|
||||
*/
|
||||
@Deprecated
|
||||
public void createModelWithFilePath(String modelName, String modelFilePath) throws IOException, InterruptedException, OllamaBaseException, URISyntaxException {
|
||||
String url = this.host + "/api/create";
|
||||
String jsonData = new CustomModelFilePathRequest(modelName, modelFilePath).toString();
|
||||
@@ -423,6 +461,7 @@ public class OllamaAPI {
|
||||
* @throws InterruptedException if the operation is interrupted
|
||||
* @throws URISyntaxException if the URI for the request is malformed
|
||||
*/
|
||||
@Deprecated
|
||||
public void createModelWithModelFileContents(String modelName, String modelFileContents) throws IOException, InterruptedException, OllamaBaseException, URISyntaxException {
|
||||
String url = this.host + "/api/create";
|
||||
String jsonData = new CustomModelFileContentsRequest(modelName, modelFileContents).toString();
|
||||
@@ -442,6 +481,35 @@ public class OllamaAPI {
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a custom model. Read more about custom model creation <a
|
||||
* href="https://github.com/ollama/ollama/blob/main/docs/api.md#create-a-model">here</a>.
|
||||
*
|
||||
* @param customModelRequest custom model spec
|
||||
* @throws OllamaBaseException if the response indicates an error status
|
||||
* @throws IOException if an I/O error occurs during the HTTP request
|
||||
* @throws InterruptedException if the operation is interrupted
|
||||
* @throws URISyntaxException if the URI for the request is malformed
|
||||
*/
|
||||
public void createModel(CustomModelRequest customModelRequest) throws IOException, InterruptedException, OllamaBaseException, URISyntaxException {
|
||||
String url = this.host + "/api/create";
|
||||
String jsonData = customModelRequest.toString();
|
||||
HttpRequest request = getRequestBuilderDefault(new URI(url)).header("Accept", "application/json").header("Content-Type", "application/json").POST(HttpRequest.BodyPublishers.ofString(jsonData, StandardCharsets.UTF_8)).build();
|
||||
HttpClient client = HttpClient.newHttpClient();
|
||||
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
|
||||
int statusCode = response.statusCode();
|
||||
String responseString = response.body();
|
||||
if (statusCode != 200) {
|
||||
throw new OllamaBaseException(statusCode + " - " + responseString);
|
||||
}
|
||||
if (responseString.contains("error")) {
|
||||
throw new OllamaBaseException(responseString);
|
||||
}
|
||||
if (verbose) {
|
||||
logger.info(responseString);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Delete a model from Ollama server.
|
||||
*
|
||||
@@ -610,9 +678,9 @@ public class OllamaAPI {
|
||||
OllamaToolsResult toolResult = new OllamaToolsResult();
|
||||
Map<ToolFunctionCallSpec, Object> toolResults = new HashMap<>();
|
||||
|
||||
if(!prompt.startsWith("[AVAILABLE_TOOLS]")){
|
||||
if (!prompt.startsWith("[AVAILABLE_TOOLS]")) {
|
||||
final Tools.PromptBuilder promptBuilder = new Tools.PromptBuilder();
|
||||
for(Tools.ToolSpecification spec : toolRegistry.getRegisteredSpecs()) {
|
||||
for (Tools.ToolSpecification spec : toolRegistry.getRegisteredSpecs()) {
|
||||
promptBuilder.withToolSpecification(spec);
|
||||
}
|
||||
promptBuilder.withPrompt(prompt);
|
||||
@@ -627,7 +695,22 @@ public class OllamaAPI {
|
||||
toolsResponse = toolsResponse.replace("[TOOL_CALLS]", "");
|
||||
}
|
||||
|
||||
List<ToolFunctionCallSpec> toolFunctionCallSpecs = Utils.getObjectMapper().readValue(toolsResponse, Utils.getObjectMapper().getTypeFactory().constructCollectionType(List.class, ToolFunctionCallSpec.class));
|
||||
List<ToolFunctionCallSpec> toolFunctionCallSpecs = new ArrayList<>();
|
||||
ObjectMapper objectMapper = Utils.getObjectMapper();
|
||||
|
||||
if (!toolsResponse.isEmpty()) {
|
||||
try {
|
||||
// Try to parse the string to see if it's a valid JSON
|
||||
JsonNode jsonNode = objectMapper.readTree(toolsResponse);
|
||||
} catch (JsonParseException e) {
|
||||
logger.warn("Response from model does not contain any tool calls. Returning the response as is.");
|
||||
return toolResult;
|
||||
}
|
||||
toolFunctionCallSpecs = objectMapper.readValue(
|
||||
toolsResponse,
|
||||
objectMapper.getTypeFactory().constructCollectionType(List.class, ToolFunctionCallSpec.class)
|
||||
);
|
||||
}
|
||||
for (ToolFunctionCallSpec toolFunctionCallSpec : toolFunctionCallSpecs) {
|
||||
toolResults.put(toolFunctionCallSpec, invokeTool(toolFunctionCallSpec));
|
||||
}
|
||||
@@ -794,8 +877,8 @@ public class OllamaAPI {
|
||||
* <p>
|
||||
* Hint: the OllamaChatRequestModel#getStream() property is not implemented.
|
||||
*
|
||||
* @param request request object to be sent to the server
|
||||
* @param tokenHandler callback handler to handle the last token from stream (caution: all previous messages from stream will be concatenated)
|
||||
* @param request request object to be sent to the server
|
||||
* @param tokenHandler callback handler to handle the last token from stream (caution: all previous messages from stream will be concatenated)
|
||||
* @return {@link OllamaChatResult}
|
||||
* @throws OllamaBaseException any response code than 200 has been returned
|
||||
* @throws IOException in case the responseStream can not be read
|
||||
@@ -821,13 +904,13 @@ public class OllamaAPI {
|
||||
// check if toolCallIsWanted
|
||||
List<OllamaChatToolCalls> toolCalls = result.getResponseModel().getMessage().getToolCalls();
|
||||
int toolCallTries = 0;
|
||||
while(toolCalls != null && !toolCalls.isEmpty() && toolCallTries < maxChatToolCallRetries){
|
||||
for (OllamaChatToolCalls toolCall : toolCalls){
|
||||
while (toolCalls != null && !toolCalls.isEmpty() && toolCallTries < maxChatToolCallRetries) {
|
||||
for (OllamaChatToolCalls toolCall : toolCalls) {
|
||||
String toolName = toolCall.getFunction().getName();
|
||||
ToolFunction toolFunction = toolRegistry.getToolFunction(toolName);
|
||||
Map<String, Object> arguments = toolCall.getFunction().getArguments();
|
||||
Object res = toolFunction.apply(arguments);
|
||||
request.getMessages().add(new OllamaChatMessage(OllamaChatMessageRole.TOOL,"[TOOL_RESULTS]" + toolName + "(" + arguments.keySet() +") : " + res + "[/TOOL_RESULTS]"));
|
||||
request.getMessages().add(new OllamaChatMessage(OllamaChatMessageRole.TOOL, "[TOOL_RESULTS]" + toolName + "(" + arguments.keySet() + ") : " + res + "[/TOOL_RESULTS]"));
|
||||
}
|
||||
|
||||
if (tokenHandler != null) {
|
||||
@@ -842,12 +925,41 @@ public class OllamaAPI {
|
||||
return result;
|
||||
}
|
||||
|
||||
/**
|
||||
* Registers a single tool in the tool registry using the provided tool specification.
|
||||
*
|
||||
* @param toolSpecification the specification of the tool to register. It contains the
|
||||
* tool's function name and other relevant information.
|
||||
*/
|
||||
public void registerTool(Tools.ToolSpecification toolSpecification) {
|
||||
toolRegistry.addTool(toolSpecification.getFunctionName(), toolSpecification);
|
||||
if (this.verbose) {
|
||||
logger.debug("Registered tool: {}", toolSpecification.getFunctionName());
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Registers multiple tools in the tool registry using a list of tool specifications.
|
||||
* Iterates over the list and adds each tool specification to the registry.
|
||||
*
|
||||
* @param toolSpecifications a list of tool specifications to register. Each specification
|
||||
* contains information about a tool, such as its function name.
|
||||
*/
|
||||
public void registerTools(List<Tools.ToolSpecification> toolSpecifications) {
|
||||
for (Tools.ToolSpecification toolSpecification : toolSpecifications) {
|
||||
toolRegistry.addTool(toolSpecification.getFunctionName(), toolSpecification);
|
||||
}
|
||||
}
|
||||
|
||||
public void registerAnnotatedTools() {
|
||||
/**
|
||||
* Registers tools based on the annotations found on the methods of the caller's class and its providers.
|
||||
* This method scans the caller's class for the {@link OllamaToolService} annotation and recursively registers
|
||||
* annotated tools from all the providers specified in the annotation.
|
||||
*
|
||||
* @throws IllegalStateException if the caller's class is not annotated with {@link OllamaToolService}.
|
||||
* @throws RuntimeException if any reflection-based instantiation or invocation fails.
|
||||
*/
|
||||
public void registerAnnotatedTools() {
|
||||
try {
|
||||
Class<?> callerClass = null;
|
||||
try {
|
||||
@@ -865,70 +977,52 @@ public class OllamaAPI {
|
||||
for (Class<?> provider : providers) {
|
||||
registerAnnotatedTools(provider.getDeclaredConstructor().newInstance());
|
||||
}
|
||||
} catch (InstantiationException | NoSuchMethodException | IllegalAccessException | InvocationTargetException e) {
|
||||
} catch (InstantiationException | NoSuchMethodException | IllegalAccessException |
|
||||
InvocationTargetException e) {
|
||||
throw new RuntimeException(e);
|
||||
}
|
||||
}
|
||||
|
||||
public void registerAnnotatedTools(Object object) {
|
||||
/**
|
||||
* Registers tools based on the annotations found on the methods of the provided object.
|
||||
* This method scans the methods of the given object and registers tools using the {@link ToolSpec} annotation
|
||||
* and associated {@link ToolProperty} annotations. It constructs tool specifications and stores them in a tool registry.
|
||||
*
|
||||
* @param object the object whose methods are to be inspected for annotated tools.
|
||||
* @throws RuntimeException if any reflection-based instantiation or invocation fails.
|
||||
*/
|
||||
public void registerAnnotatedTools(Object object) {
|
||||
Class<?> objectClass = object.getClass();
|
||||
Method[] methods = objectClass.getMethods();
|
||||
for(Method m : methods) {
|
||||
for (Method m : methods) {
|
||||
ToolSpec toolSpec = m.getDeclaredAnnotation(ToolSpec.class);
|
||||
if(toolSpec == null){
|
||||
if (toolSpec == null) {
|
||||
continue;
|
||||
}
|
||||
String operationName = !toolSpec.name().isBlank() ? toolSpec.name() : m.getName();
|
||||
String operationDesc = !toolSpec.desc().isBlank() ? toolSpec.desc() : operationName;
|
||||
|
||||
final Tools.PropsBuilder propsBuilder = new Tools.PropsBuilder();
|
||||
LinkedHashMap<String,String> methodParams = new LinkedHashMap<>();
|
||||
LinkedHashMap<String, String> methodParams = new LinkedHashMap<>();
|
||||
for (Parameter parameter : m.getParameters()) {
|
||||
final ToolProperty toolPropertyAnn = parameter.getDeclaredAnnotation(ToolProperty.class);
|
||||
String propType = parameter.getType().getTypeName();
|
||||
if(toolPropertyAnn == null) {
|
||||
methodParams.put(parameter.getName(),null);
|
||||
if (toolPropertyAnn == null) {
|
||||
methodParams.put(parameter.getName(), null);
|
||||
continue;
|
||||
}
|
||||
String propName = !toolPropertyAnn.name().isBlank() ? toolPropertyAnn.name() : parameter.getName();
|
||||
methodParams.put(propName,propType);
|
||||
propsBuilder.withProperty(propName,Tools.PromptFuncDefinition.Property.builder()
|
||||
.type(propType)
|
||||
.description(toolPropertyAnn.desc())
|
||||
.required(toolPropertyAnn.required())
|
||||
.build());
|
||||
methodParams.put(propName, propType);
|
||||
propsBuilder.withProperty(propName, Tools.PromptFuncDefinition.Property.builder().type(propType).description(toolPropertyAnn.desc()).required(toolPropertyAnn.required()).build());
|
||||
}
|
||||
final Map<String, Tools.PromptFuncDefinition.Property> params = propsBuilder.build();
|
||||
List<String> reqProps = params.entrySet().stream()
|
||||
.filter(e -> e.getValue().isRequired())
|
||||
.map(Map.Entry::getKey)
|
||||
.collect(Collectors.toList());
|
||||
List<String> reqProps = params.entrySet().stream().filter(e -> e.getValue().isRequired()).map(Map.Entry::getKey).collect(Collectors.toList());
|
||||
|
||||
Tools.ToolSpecification toolSpecification = Tools.ToolSpecification.builder()
|
||||
.functionName(operationName)
|
||||
.functionDescription(operationDesc)
|
||||
.toolPrompt(
|
||||
Tools.PromptFuncDefinition.builder().type("function").function(
|
||||
Tools.PromptFuncDefinition.PromptFuncSpec.builder()
|
||||
.name(operationName)
|
||||
.description(operationDesc)
|
||||
.parameters(
|
||||
Tools.PromptFuncDefinition.Parameters.builder()
|
||||
.type("object")
|
||||
.properties(
|
||||
params
|
||||
)
|
||||
.required(reqProps)
|
||||
.build()
|
||||
).build()
|
||||
).build()
|
||||
)
|
||||
.build();
|
||||
Tools.ToolSpecification toolSpecification = Tools.ToolSpecification.builder().functionName(operationName).functionDescription(operationDesc).toolPrompt(Tools.PromptFuncDefinition.builder().type("function").function(Tools.PromptFuncDefinition.PromptFuncSpec.builder().name(operationName).description(operationDesc).parameters(Tools.PromptFuncDefinition.Parameters.builder().type("object").properties(params).required(reqProps).build()).build()).build()).build();
|
||||
|
||||
ReflectionalToolFunction reflectionalToolFunction =
|
||||
new ReflectionalToolFunction(object, m, methodParams);
|
||||
ReflectionalToolFunction reflectionalToolFunction = new ReflectionalToolFunction(object, m, methodParams);
|
||||
toolSpecification.setToolFunction(reflectionalToolFunction);
|
||||
toolRegistry.addTool(toolSpecification.getFunctionName(),toolSpecification);
|
||||
toolRegistry.addTool(toolSpecification.getFunctionName(), toolSpecification);
|
||||
}
|
||||
|
||||
}
|
||||
@@ -966,14 +1060,39 @@ public class OllamaAPI {
|
||||
|
||||
// technical private methods //
|
||||
|
||||
/**
|
||||
* Utility method to encode a file into a Base64 encoded string.
|
||||
*
|
||||
* @param file the file to be encoded into Base64.
|
||||
* @return a Base64 encoded string representing the contents of the file.
|
||||
* @throws IOException if an I/O error occurs during reading the file.
|
||||
*/
|
||||
private static String encodeFileToBase64(File file) throws IOException {
|
||||
return Base64.getEncoder().encodeToString(Files.readAllBytes(file.toPath()));
|
||||
}
|
||||
|
||||
/**
|
||||
* Utility method to encode a byte array into a Base64 encoded string.
|
||||
*
|
||||
* @param bytes the byte array to be encoded into Base64.
|
||||
* @return a Base64 encoded string representing the byte array.
|
||||
*/
|
||||
private static String encodeByteArrayToBase64(byte[] bytes) {
|
||||
return Base64.getEncoder().encodeToString(bytes);
|
||||
}
|
||||
|
||||
/**
|
||||
* Generates a request for the Ollama API and returns the result.
|
||||
* This method synchronously calls the Ollama API. If a stream handler is provided,
|
||||
* the request will be streamed; otherwise, a regular synchronous request will be made.
|
||||
*
|
||||
* @param ollamaRequestModel the request model containing necessary parameters for the Ollama API request.
|
||||
* @param streamHandler the stream handler to process streaming responses, or null for non-streaming requests.
|
||||
* @return the result of the Ollama API request.
|
||||
* @throws OllamaBaseException if the request fails due to an issue with the Ollama API.
|
||||
* @throws IOException if an I/O error occurs during the request process.
|
||||
* @throws InterruptedException if the thread is interrupted during the request.
|
||||
*/
|
||||
private OllamaResult generateSyncForOllamaRequestModel(OllamaGenerateRequest ollamaRequestModel, OllamaStreamHandler streamHandler) throws OllamaBaseException, IOException, InterruptedException {
|
||||
OllamaGenerateEndpointCaller requestCaller = new OllamaGenerateEndpointCaller(host, basicAuth, requestTimeoutSeconds, verbose);
|
||||
OllamaResult result;
|
||||
@@ -986,6 +1105,7 @@ public class OllamaAPI {
|
||||
return result;
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Get default request builder.
|
||||
*
|
||||
@@ -1028,7 +1148,7 @@ public class OllamaAPI {
|
||||
logger.debug("Invoking function {} with arguments {}", methodName, arguments);
|
||||
}
|
||||
if (function == null) {
|
||||
throw new ToolNotFoundException("No such tool: " + methodName);
|
||||
throw new ToolNotFoundException("No such tool: " + methodName + ". Please register the tool before invoking it.");
|
||||
}
|
||||
return function.apply(arguments);
|
||||
} catch (Exception e) {
|
||||
|
||||
@@ -28,9 +28,9 @@ public class OllamaChatMessageRole {
|
||||
}
|
||||
|
||||
public static OllamaChatMessageRole newCustomRole(String roleName) {
|
||||
OllamaChatMessageRole customRole = new OllamaChatMessageRole(roleName);
|
||||
roles.add(customRole);
|
||||
return customRole;
|
||||
// OllamaChatMessageRole customRole = new OllamaChatMessageRole(roleName);
|
||||
// roles.add(customRole);
|
||||
return new OllamaChatMessageRole(roleName);
|
||||
}
|
||||
|
||||
public static List<OllamaChatMessageRole> getRoles() {
|
||||
|
||||
@@ -14,10 +14,9 @@ import static io.github.ollama4j.utils.Utils.getObjectMapper;
|
||||
@Getter
|
||||
public class OllamaChatResult {
|
||||
|
||||
private final List<OllamaChatMessage> chatHistory;
|
||||
|
||||
private List<OllamaChatMessage> chatHistory;
|
||||
|
||||
private OllamaChatResponseModel responseModel;
|
||||
private final OllamaChatResponseModel responseModel;
|
||||
|
||||
public OllamaChatResult(OllamaChatResponseModel responseModel, List<OllamaChatMessage> chatHistory) {
|
||||
this.chatHistory = chatHistory;
|
||||
|
||||
@@ -5,7 +5,7 @@ import io.github.ollama4j.utils.Options;
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* Builderclass to easily create Requests for Embedding models using ollama.
|
||||
* Builder class to easily create Requests for Embedding models using ollama.
|
||||
*/
|
||||
public class OllamaEmbedRequestBuilder {
|
||||
|
||||
|
||||
@@ -0,0 +1,45 @@
|
||||
package io.github.ollama4j.models.request;
|
||||
|
||||
import static io.github.ollama4j.utils.Utils.getObjectMapper;
|
||||
|
||||
import com.fasterxml.jackson.core.JsonProcessingException;
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Data;
|
||||
import lombok.Data;
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Builder;
|
||||
|
||||
import java.util.List;
|
||||
import java.util.Map;
|
||||
|
||||
|
||||
@Data
|
||||
@AllArgsConstructor
|
||||
@Builder
|
||||
public class CustomModelRequest {
|
||||
private String model;
|
||||
private String from;
|
||||
private Map<String, String> files;
|
||||
private Map<String, String> adapters;
|
||||
private String template;
|
||||
private Object license; // Using Object to handle both String and List<String>
|
||||
private String system;
|
||||
private Map<String, Object> parameters;
|
||||
private List<Object> messages;
|
||||
private Boolean stream;
|
||||
private Boolean quantize;
|
||||
|
||||
public CustomModelRequest() {
|
||||
this.stream = true;
|
||||
this.quantize = false;
|
||||
}
|
||||
|
||||
@Override
|
||||
public String toString() {
|
||||
try {
|
||||
return getObjectMapper().writerWithDefaultPrettyPrinter().writeValueAsString(this);
|
||||
} catch (JsonProcessingException e) {
|
||||
throw new RuntimeException(e);
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -2,12 +2,14 @@ package io.github.ollama4j.models.response;
|
||||
|
||||
import java.time.OffsetDateTime;
|
||||
|
||||
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
|
||||
import com.fasterxml.jackson.annotation.JsonProperty;
|
||||
import com.fasterxml.jackson.core.JsonProcessingException;
|
||||
import io.github.ollama4j.utils.Utils;
|
||||
import lombok.Data;
|
||||
|
||||
@Data
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public class Model {
|
||||
|
||||
private String name;
|
||||
|
||||
@@ -0,0 +1,10 @@
|
||||
package io.github.ollama4j.models.response;
|
||||
|
||||
import lombok.Data;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
@Data
|
||||
public class OllamaVersion {
|
||||
private String version;
|
||||
}
|
||||
@@ -1,5 +1,6 @@
|
||||
package io.github.ollama4j.tools;
|
||||
|
||||
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
|
||||
import lombok.AllArgsConstructor;
|
||||
import lombok.Data;
|
||||
import lombok.NoArgsConstructor;
|
||||
@@ -9,8 +10,9 @@ import java.util.Map;
|
||||
@Data
|
||||
@NoArgsConstructor
|
||||
@AllArgsConstructor
|
||||
@JsonIgnoreProperties(ignoreUnknown = true)
|
||||
public class OllamaToolCallsFunction
|
||||
{
|
||||
private String name;
|
||||
private Map<String,Object> arguments;
|
||||
}
|
||||
}
|
||||
@@ -18,6 +18,9 @@ public class OllamaToolsResult {
|
||||
|
||||
public List<ToolResult> getToolResults() {
|
||||
List<ToolResult> results = new ArrayList<>();
|
||||
if (this.toolResults == null) {
|
||||
return results;
|
||||
}
|
||||
for (Map.Entry<ToolFunctionCallSpec, Object> r : this.toolResults.entrySet()) {
|
||||
results.add(new ToolResult(r.getKey().getName(), r.getKey().getArguments(), r.getValue()));
|
||||
}
|
||||
|
||||
@@ -0,0 +1,239 @@
|
||||
package io.github.ollama4j.integrationtests;
|
||||
|
||||
import io.github.ollama4j.OllamaAPI;
|
||||
import io.github.ollama4j.exceptions.OllamaBaseException;
|
||||
import io.github.ollama4j.models.chat.OllamaChatMessageRole;
|
||||
import io.github.ollama4j.models.chat.OllamaChatRequest;
|
||||
import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
|
||||
import io.github.ollama4j.models.chat.OllamaChatResult;
|
||||
import io.github.ollama4j.models.embeddings.OllamaEmbedResponseModel;
|
||||
import io.github.ollama4j.models.response.LibraryModel;
|
||||
import io.github.ollama4j.models.response.Model;
|
||||
import io.github.ollama4j.models.response.ModelDetail;
|
||||
import io.github.ollama4j.models.response.OllamaResult;
|
||||
import io.github.ollama4j.utils.OptionsBuilder;
|
||||
import org.junit.jupiter.api.BeforeAll;
|
||||
import org.junit.jupiter.api.Order;
|
||||
import org.junit.jupiter.api.Test;
|
||||
import org.testcontainers.ollama.OllamaContainer;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.net.ConnectException;
|
||||
import java.net.URISyntaxException;
|
||||
import java.util.ArrayList;
|
||||
import java.util.Arrays;
|
||||
import java.util.List;
|
||||
|
||||
import static org.junit.jupiter.api.Assertions.*;
|
||||
|
||||
@SuppressWarnings("HttpUrlsUsage")
|
||||
public class OllamaAPIIntegrationTest {
|
||||
|
||||
private static OllamaContainer ollama;
|
||||
private static OllamaAPI api;
|
||||
|
||||
@BeforeAll
|
||||
public static void setUp() {
|
||||
String version = "0.5.13";
|
||||
int internalPort = 11434;
|
||||
int mappedPort = 11435;
|
||||
ollama = new OllamaContainer("ollama/ollama:" + version);
|
||||
ollama.addExposedPort(internalPort);
|
||||
List<String> portBindings = new ArrayList<>();
|
||||
portBindings.add(mappedPort + ":" + internalPort);
|
||||
ollama.setPortBindings(portBindings);
|
||||
ollama.start();
|
||||
api = new OllamaAPI("http://" + ollama.getHost() + ":" + ollama.getMappedPort(internalPort));
|
||||
api.setRequestTimeoutSeconds(60);
|
||||
}
|
||||
|
||||
@Test
|
||||
@Order(1)
|
||||
void testWrongEndpoint() {
|
||||
OllamaAPI ollamaAPI = new OllamaAPI("http://wrong-host:11434");
|
||||
assertThrows(ConnectException.class, ollamaAPI::listModels);
|
||||
}
|
||||
|
||||
@Test
|
||||
@Order(1)
|
||||
public void testVersionAPI() throws URISyntaxException, IOException, OllamaBaseException, InterruptedException {
|
||||
String expectedVersion = ollama.getDockerImageName().split(":")[1];
|
||||
String actualVersion = api.getVersion();
|
||||
assertEquals(expectedVersion, actualVersion, "Version should match the Docker image version");
|
||||
}
|
||||
|
||||
@Test
|
||||
@Order(2)
|
||||
public void testListModelsAPI() throws URISyntaxException, IOException, OllamaBaseException, InterruptedException {
|
||||
// Fetch the list of models
|
||||
List<Model> models = api.listModels();
|
||||
// Assert that the models list is not null
|
||||
assertNotNull(models, "Models should not be null");
|
||||
// Assert that models list is either empty or contains more than 0 models
|
||||
assertTrue(models.size() >= 0, "Models list should be empty or contain elements");
|
||||
}
|
||||
|
||||
@Test
|
||||
@Order(2)
|
||||
void testListModelsFromLibrary() throws OllamaBaseException, IOException, URISyntaxException, InterruptedException {
|
||||
List<LibraryModel> models = api.listModelsFromLibrary();
|
||||
assertNotNull(models);
|
||||
assertFalse(models.isEmpty());
|
||||
}
|
||||
|
||||
@Test
|
||||
@Order(3)
|
||||
public void testPullModelAPI() throws URISyntaxException, IOException, OllamaBaseException, InterruptedException {
|
||||
api.pullModel("all-minilm");
|
||||
List<Model> models = api.listModels();
|
||||
assertNotNull(models, "Models should not be null");
|
||||
assertFalse(models.isEmpty(), "Models list should contain elements");
|
||||
}
|
||||
|
||||
@Test
|
||||
@Order(4)
|
||||
void testListModelDetails() throws IOException, OllamaBaseException, URISyntaxException, InterruptedException {
|
||||
String embeddingModelMinilm = "all-minilm";
|
||||
api.pullModel(embeddingModelMinilm);
|
||||
ModelDetail modelDetails = api.getModelDetails("all-minilm");
|
||||
assertNotNull(modelDetails);
|
||||
assertTrue(modelDetails.getModelFile().contains(embeddingModelMinilm));
|
||||
}
|
||||
|
||||
@Test
|
||||
@Order(5)
|
||||
public void testGenerateEmbeddings() throws Exception {
|
||||
String embeddingModelMinilm = "all-minilm";
|
||||
api.pullModel(embeddingModelMinilm);
|
||||
OllamaEmbedResponseModel embeddings = api.embed(embeddingModelMinilm, Arrays.asList("Why is the sky blue?", "Why is the grass green?"));
|
||||
assertNotNull(embeddings, "Embeddings should not be null");
|
||||
assertFalse(embeddings.getEmbeddings().isEmpty(), "Embeddings should not be empty");
|
||||
}
|
||||
|
||||
@Test
|
||||
@Order(6)
|
||||
void testAskModelWithDefaultOptions() throws OllamaBaseException, IOException, InterruptedException, URISyntaxException {
|
||||
String chatModel = "qwen2.5:0.5b";
|
||||
api.pullModel(chatModel);
|
||||
OllamaResult result =
|
||||
api.generate(
|
||||
chatModel,
|
||||
"What is the capital of France? And what's France's connection with Mona Lisa?",
|
||||
false,
|
||||
new OptionsBuilder().build());
|
||||
assertNotNull(result);
|
||||
assertNotNull(result.getResponse());
|
||||
assertFalse(result.getResponse().isEmpty());
|
||||
}
|
||||
|
||||
@Test
|
||||
@Order(7)
|
||||
void testAskModelWithDefaultOptionsStreamed() throws OllamaBaseException, IOException, URISyntaxException, InterruptedException {
|
||||
String chatModel = "qwen2.5:0.5b";
|
||||
api.pullModel(chatModel);
|
||||
StringBuffer sb = new StringBuffer();
|
||||
OllamaResult result = api.generate(chatModel,
|
||||
"What is the capital of France? And what's France's connection with Mona Lisa?",
|
||||
false,
|
||||
new OptionsBuilder().build(), (s) -> {
|
||||
System.out.println(s);
|
||||
String substring = s.substring(sb.toString().length(), s.length());
|
||||
System.out.println(substring);
|
||||
sb.append(substring);
|
||||
});
|
||||
|
||||
assertNotNull(result);
|
||||
assertNotNull(result.getResponse());
|
||||
assertFalse(result.getResponse().isEmpty());
|
||||
assertEquals(sb.toString().trim(), result.getResponse().trim());
|
||||
}
|
||||
|
||||
@Test
|
||||
@Order(8)
|
||||
void testAskModelWithOptions() throws OllamaBaseException, IOException, URISyntaxException, InterruptedException {
|
||||
String chatModel = "qwen2.5:0.5b-instruct";
|
||||
api.pullModel(chatModel);
|
||||
|
||||
OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(chatModel);
|
||||
OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.SYSTEM, "You are a helpful assistant who can generate random person's first and last names in the format [First name, Last name].")
|
||||
.build();
|
||||
requestModel = builder.withMessages(requestModel.getMessages())
|
||||
.withMessage(OllamaChatMessageRole.USER, "Give me a cool name")
|
||||
.withOptions(new OptionsBuilder().setTemperature(0.5f).build()).build();
|
||||
OllamaChatResult chatResult = api.chat(requestModel);
|
||||
|
||||
assertNotNull(chatResult);
|
||||
assertNotNull(chatResult.getResponseModel());
|
||||
assertFalse(chatResult.getResponseModel().getMessage().getContent().isEmpty());
|
||||
}
|
||||
|
||||
@Test
|
||||
@Order(9)
|
||||
void testChatWithSystemPrompt() throws OllamaBaseException, IOException, URISyntaxException, InterruptedException {
|
||||
String chatModel = "llama3.2:1b";
|
||||
api.pullModel(chatModel);
|
||||
OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(chatModel);
|
||||
OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.SYSTEM,
|
||||
"You are a silent bot that only says 'Shush'. Do not say anything else under any circumstances!")
|
||||
.withMessage(OllamaChatMessageRole.USER,
|
||||
"What's something that's brown and sticky?")
|
||||
.withOptions(new OptionsBuilder().setTemperature(0.8f).build())
|
||||
.build();
|
||||
|
||||
OllamaChatResult chatResult = api.chat(requestModel);
|
||||
assertNotNull(chatResult);
|
||||
assertNotNull(chatResult.getResponseModel());
|
||||
assertNotNull(chatResult.getResponseModel().getMessage());
|
||||
assertFalse(chatResult.getResponseModel().getMessage().getContent().isBlank());
|
||||
assertTrue(chatResult.getResponseModel().getMessage().getContent().contains("Shush"));
|
||||
assertEquals(3, chatResult.getChatHistory().size());
|
||||
}
|
||||
|
||||
@Test
|
||||
@Order(10)
|
||||
public void testChat() throws Exception {
|
||||
String chatModel = "qwen2.5:0.5b";
|
||||
api.pullModel(chatModel);
|
||||
OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(chatModel);
|
||||
|
||||
// Create the initial user question
|
||||
OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER, "What is the capital of France?")
|
||||
.build();
|
||||
|
||||
// Start conversation with model
|
||||
OllamaChatResult chatResult = api.chat(requestModel);
|
||||
|
||||
assertTrue(
|
||||
chatResult.getChatHistory().stream()
|
||||
.anyMatch(chat -> chat.getContent().contains("Paris")),
|
||||
"Expected chat history to contain 'Paris'"
|
||||
);
|
||||
|
||||
// Create the next user question: second largest city
|
||||
requestModel = builder.withMessages(chatResult.getChatHistory())
|
||||
.withMessage(OllamaChatMessageRole.USER, "And what is its official language?")
|
||||
.build();
|
||||
|
||||
// Continue conversation with model
|
||||
chatResult = api.chat(requestModel);
|
||||
|
||||
assertTrue(
|
||||
chatResult.getChatHistory().stream()
|
||||
.anyMatch(chat -> chat.getContent().contains("French")),
|
||||
"Expected chat history to contain 'French'"
|
||||
);
|
||||
|
||||
// Create the next user question: the third question
|
||||
requestModel = builder.withMessages(chatResult.getChatHistory())
|
||||
.withMessage(OllamaChatMessageRole.USER, "What is the largest river in France?")
|
||||
.build();
|
||||
|
||||
// Continue conversation with the model for the third question
|
||||
chatResult = api.chat(requestModel);
|
||||
|
||||
// verify the result
|
||||
assertNotNull(chatResult, "Chat result should not be null");
|
||||
assertTrue(chatResult.getChatHistory().size() > 2, "Chat history should contain more than two messages");
|
||||
assertTrue(chatResult.getChatHistory().get(chatResult.getChatHistory().size() - 1).getContent().contains("river"), "Response should be related to river");
|
||||
}
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
@@ -6,6 +6,7 @@ import io.github.ollama4j.exceptions.RoleNotFoundException;
|
||||
import io.github.ollama4j.models.chat.OllamaChatMessageRole;
|
||||
import io.github.ollama4j.models.embeddings.OllamaEmbedRequestModel;
|
||||
import io.github.ollama4j.models.embeddings.OllamaEmbedResponseModel;
|
||||
import io.github.ollama4j.models.request.CustomModelRequest;
|
||||
import io.github.ollama4j.models.response.ModelDetail;
|
||||
import io.github.ollama4j.models.response.OllamaAsyncResultStreamer;
|
||||
import io.github.ollama4j.models.response.OllamaResult;
|
||||
@@ -52,12 +53,11 @@ class TestMockedAPIs {
|
||||
@Test
|
||||
void testCreateModel() {
|
||||
OllamaAPI ollamaAPI = Mockito.mock(OllamaAPI.class);
|
||||
String model = OllamaModelType.LLAMA2;
|
||||
String modelFilePath = "FROM llama2\nSYSTEM You are mario from Super Mario Bros.";
|
||||
CustomModelRequest customModelRequest = CustomModelRequest.builder().model("mario").from("llama3.2:latest").system("You are Mario from Super Mario Bros.").build();
|
||||
try {
|
||||
doNothing().when(ollamaAPI).createModelWithModelFileContents(model, modelFilePath);
|
||||
ollamaAPI.createModelWithModelFileContents(model, modelFilePath);
|
||||
verify(ollamaAPI, times(1)).createModelWithModelFileContents(model, modelFilePath);
|
||||
doNothing().when(ollamaAPI).createModel(customModelRequest);
|
||||
ollamaAPI.createModel(customModelRequest);
|
||||
verify(ollamaAPI, times(1)).createModel(customModelRequest);
|
||||
} catch (IOException | OllamaBaseException | InterruptedException | URISyntaxException e) {
|
||||
throw new RuntimeException(e);
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user