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name: Build and Publish
on: push
jobs:
build:
runs-on: standard-22.04
steps:
- name: Check out
uses: actions/checkout@v4
- name: Set Up Java
uses: actions/setup-java@v4
with:
distribution: 'temurin'
java-version: '21'
#cache: 'maven'
#server-id: 'gitea'
- name: Set up Maven
uses: stCarolas/setup-maven@v5
with:
maven-version: 3.8.2
- run: cat /root/.m2/toolchains.xml
- run: cat /root/.m2/settings.xml
- name: Build
run: mvn -B package --file pom.xml
- name: Publish
run: mvn deploy

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name: Release Artifacts to GitHub Maven Packages
on:
release:
types: [ created ]
jobs:
build:
runs-on: ubuntu-latest
permissions:
contents: read
packages: write
steps:
- uses: actions/checkout@v3
- name: Set up JDK 17
uses: actions/setup-java@v3
with:
java-version: '17'
distribution: 'temurin'
server-id: github
settings-path: ${{ github.workspace }}
- name: maven-settings-xml-action
uses: whelk-io/maven-settings-xml-action@v22
with:
servers: '[{ "id": "${repo.id}", "username": "${repo.user}", "password": "${repo.pass}" }]'
- name: Find and Replace
uses: jacobtomlinson/gha-find-replace@v3
with:
find: "ollama4j-revision"
replace: ${{ github.ref_name }}
regex: false
- name: Find and Replace
uses: jacobtomlinson/gha-find-replace@v3
with:
find: "mvn-repo-id"
replace: github
regex: false
- name: Import GPG key
uses: crazy-max/ghaction-import-gpg@v6
with:
gpg_private_key: ${{ secrets.GPG_PRIVATE_KEY }}
passphrase: ${{ secrets.GPG_PASSPHRASE }}
- name: List keys
run: gpg -K
- name: Build with Maven
run: mvn --file pom.xml -U clean package -Punit-tests
- name: Publish to GitHub Packages Apache Maven
run: mvn deploy -Punit-tests -s $GITHUB_WORKSPACE/settings.xml -Dgpg.passphrase=${{ secrets.GPG_PASSPHRASE }} -Drepo.id=github -Drepo.user=${{ secrets.GH_MVN_USER }} -Drepo.pass=${{ secrets.GH_MVN_PASS }} -DaltDeploymentRepository=github::default::https://maven.pkg.github.com/ollama4j/ollama4j
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

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@ -1,95 +1,64 @@
# This workflow will build a package using Maven and then publish it to GitHub packages when a release is created
# For more information see: https://github.com/actions/setup-java/blob/main/docs/advanced-usage.md#apache-maven-with-a-settings-path
name: Release Artifacts to Maven Central
name: Test and Publish Package
on:
release:
types: [ created ]
types: [ "created" ]
#on:
# pull_request:
# types: [ opened, reopened ]
# push:
# branches: [ "main" ]
# workflow_dispatch:
jobs:
build:
runs-on: ubuntu-latest
permissions:
contents: write
packages: write
steps:
- uses: actions/checkout@v3
- name: Set up JDK 17
- name: Set up JDK 11
uses: actions/setup-java@v3
with:
java-version: '17'
distribution: 'temurin'
java-version: '11'
distribution: 'adopt-hotspot'
server-id: github # Value of the distributionManagement/repository/id field of the pom.xml
settings-path: ${{ github.workspace }} # location for the settings.xml file
- name: maven-settings-xml-action
uses: whelk-io/maven-settings-xml-action@v22
- name: Build with Maven
run: mvn --file pom.xml -U clean package -Punit-tests
- name: Set up Apache Maven Central (Overwrite settings.xml)
uses: actions/setup-java@v3
with: # running setup-java again overwrites the settings.xml
java-version: '11'
distribution: 'adopt-hotspot'
cache: 'maven'
server-id: ossrh
server-username: MAVEN_USERNAME
server-password: MAVEN_PASSWORD
gpg-private-key: ${{ secrets.GPG_PRIVATE_KEY }}
gpg-passphrase: MAVEN_GPG_PASSPHRASE
- name: Set up Maven cache
uses: actions/cache@v3
with:
servers: '[{ "id": "${repo.id}", "username": "${repo.user}", "password": "${repo.pass}" }]'
- name: Import GPG key
uses: crazy-max/ghaction-import-gpg@v6
with:
gpg_private_key: ${{ secrets.GPG_PRIVATE_KEY }}
passphrase: ${{ secrets.GPG_PASSPHRASE }}
- name: List keys
run: gpg -K
- name: Find and Replace
uses: jacobtomlinson/gha-find-replace@v3
with:
find: "ollama4j-revision"
replace: ${{ github.ref_name }}
regex: false
- name: Find and Replace
uses: jacobtomlinson/gha-find-replace@v3
with:
find: "mvn-repo-id"
replace: central
regex: false
- name: Publish to Maven Central
run: mvn deploy -Dgpg.passphrase=${{ secrets.GPG_PASSPHRASE }} -Drepo.id=central -Drepo.user=${{ secrets.MVN_USER }} -Drepo.pass=${{ secrets.MVN_PASS }}
- name: Upload Release Asset - JAR
uses: actions/upload-release-asset@v1
path: ~/.m2/repository
key: ${{ runner.os }}-maven-${{ hashFiles('**/pom.xml') }}
restore-keys: |
${{ runner.os }}-maven-
- name: Build
run: mvn -B -ntp clean install
- name: Publish to GitHub Packages Apache Maven
# if: >
# github.event_name != 'pull_request' &&
# github.ref_name == 'main' &&
# contains(github.event.head_commit.message, 'release')
run: |
git config --global user.email "koujalgi.amith@gmail.com"
git config --global user.name "amithkoujalgi"
mvn -B -ntp -DskipTests -Pci-cd -Darguments="-DskipTests -Pci-cd" release:clean release:prepare release:perform
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
upload_url: ${{ github.event.release.upload_url }}
asset_path: target/ollama4j-${{ github.ref_name }}.jar
asset_name: ollama4j-${{ github.ref_name }}.jar
asset_content_type: application/x-jar
- name: Upload Release Asset - Javadoc JAR
uses: actions/upload-release-asset@v1
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
upload_url: ${{ github.event.release.upload_url }}
asset_path: target/ollama4j-${{ github.ref_name }}-javadoc.jar
asset_name: ollama4j-${{ github.ref_name }}-javadoc.jar
asset_content_type: application/x-jar
- name: Upload Release Asset - Sources JAR
uses: actions/upload-release-asset@v1
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
upload_url: ${{ github.event.release.upload_url }}
asset_path: target/ollama4j-${{ github.ref_name }}-sources.jar
asset_name: ollama4j-${{ github.ref_name }}-sources.jar
asset_content_type: application/x-jar
MAVEN_USERNAME: ${{ secrets.OSSRH_USERNAME }}
MAVEN_PASSWORD: ${{ secrets.OSSRH_PASSWORD }}
MAVEN_GPG_PASSPHRASE: ${{ secrets.GPG_PASSPHRASE }}

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@ -1,9 +1,10 @@
# Simple workflow for deploying static content to GitHub Pages
name: Deploy Docs to GH Pages
name: Deploy Javadoc content to Pages
on:
release:
types: [ created ]
# Runs on pushes targeting the default branch
push:
branches: [ "main" ]
# Allows you to run this workflow manually from the Actions tab
workflow_dispatch:
@ -29,15 +30,6 @@ jobs:
name: github-pages
url: ${{ steps.deployment.outputs.page_url }}
steps:
- uses: actions/checkout@v3
- name: Set up JDK 11
uses: actions/setup-java@v3
with:
java-version: '11'
distribution: 'adopt-hotspot'
server-id: github # Value of the distributionManagement/repository/id field of the pom.xml
settings-path: ${{ github.workspace }} # location for the settings.xml file
- uses: actions/checkout@v4
- name: Use Node.js
uses: actions/setup-node@v3
@ -46,22 +38,8 @@ jobs:
- run: cd docs && npm ci
- run: cd docs && npm run build
- name: Find and Replace
uses: jacobtomlinson/gha-find-replace@v3
with:
find: "ollama4j-revision"
replace: ${{ github.ref_name }}
regex: false
- name: Build with Maven
run: mvn --file pom.xml -U clean package && cp -r ./target/apidocs/. ./docs/build/apidocs
- name: Doxygen Action
uses: mattnotmitt/doxygen-action@v1.1.0
with:
doxyfile-path: "./Doxyfile"
working-directory: "."
# - name: Build with npm
# run: npm i && npm run build
- name: Setup Pages
uses: actions/configure-pages@v3
- name: Upload artifact

52
.github/workflows/publish-javadoc.yml vendored Normal file
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# Simple workflow for deploying static content to GitHub Pages
name: Deploy Javadoc content to Pages
on:
# Runs on pushes targeting the default branch
push:
branches: [ "none" ]
# Allows you to run this workflow manually from the Actions tab
workflow_dispatch:
# Sets permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages
permissions:
contents: read
pages: write
id-token: write
packages: write
# Allow only one concurrent deployment, skipping runs queued between the run in-progress and latest queued.
# However, do NOT cancel in-progress runs as we want to allow these production deployments to complete.
concurrency:
group: "pages"
cancel-in-progress: false
jobs:
# Single deploy job since we're just deploying
deploy:
runs-on: ubuntu-latest
environment:
name: github-pages
url: ${{ steps.deployment.outputs.page_url }}
steps:
- uses: actions/checkout@v3
- name: Set up JDK 11
uses: actions/setup-java@v3
with:
java-version: '11'
distribution: 'adopt-hotspot'
server-id: github # Value of the distributionManagement/repository/id field of the pom.xml
settings-path: ${{ github.workspace }} # location for the settings.xml file
- name: Build with Maven
run: mvn --file pom.xml -U clean package
- name: Setup Pages
uses: actions/configure-pages@v3
- name: Upload artifact
uses: actions/upload-pages-artifact@v2
with:
# Upload entire repository
path: './target/apidocs/.'
- name: Deploy to GitHub Pages
id: deployment
uses: actions/deploy-pages@v2

6
.gitignore vendored
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@ -37,8 +37,6 @@ build/
### Mac OS ###
.DS_Store
/.idea/
/src/main/java/io/github/amithkoujalgi/ollama4j/core/localtests/
pom.xml.*
release.properties
!.idea/icon.svg
src/main/java/io/github/ollama4j/localtests
release.properties

18
.idea/icon.svg generated
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Before

Width:  |  Height:  |  Size: 6.1 KiB

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@ -1,128 +0,0 @@
# Contributor Covenant Code of Conduct
## Our Pledge
We as members, contributors, and leaders pledge to make participation in our
community a harassment-free experience for everyone, regardless of age, body
size, visible or invisible disability, ethnicity, sex characteristics, gender
identity and expression, level of experience, education, socio-economic status,
nationality, personal appearance, race, religion, or sexual identity
and orientation.
We pledge to act and interact in ways that contribute to an open, welcoming,
diverse, inclusive, and healthy community.
## Our Standards
Examples of behavior that contributes to a positive environment for our
community include:
* Demonstrating empathy and kindness toward other people
* Being respectful of differing opinions, viewpoints, and experiences
* Giving and gracefully accepting constructive feedback
* Accepting responsibility and apologizing to those affected by our mistakes,
and learning from the experience
* Focusing on what is best not just for us as individuals, but for the
overall community
Examples of unacceptable behavior include:
* The use of sexualized language or imagery, and sexual attention or
advances of any kind
* Trolling, insulting or derogatory comments, and personal or political attacks
* Public or private harassment
* Publishing others' private information, such as a physical or email
address, without their explicit permission
* Other conduct which could reasonably be considered inappropriate in a
professional setting
## Enforcement Responsibilities
Community leaders are responsible for clarifying and enforcing our standards of
acceptable behavior and will take appropriate and fair corrective action in
response to any behavior that they deem inappropriate, threatening, offensive,
or harmful.
Community leaders have the right and responsibility to remove, edit, or reject
comments, commits, code, wiki edits, issues, and other contributions that are
not aligned to this Code of Conduct, and will communicate reasons for moderation
decisions when appropriate.
## Scope
This Code of Conduct applies within all community spaces, and also applies when
an individual is officially representing the community in public spaces.
Examples of representing our community include using an official e-mail address,
posting via an official social media account, or acting as an appointed
representative at an online or offline event.
## Enforcement
Instances of abusive, harassing, or otherwise unacceptable behavior may be
reported to the community leaders responsible for enforcement at
koujalgi.amith@gmail.com.
All complaints will be reviewed and investigated promptly and fairly.
All community leaders are obligated to respect the privacy and security of the
reporter of any incident.
## Enforcement Guidelines
Community leaders will follow these Community Impact Guidelines in determining
the consequences for any action they deem in violation of this Code of Conduct:
### 1. Correction
**Community Impact**: Use of inappropriate language or other behavior deemed
unprofessional or unwelcome in the community.
**Consequence**: A private, written warning from community leaders, providing
clarity around the nature of the violation and an explanation of why the
behavior was inappropriate. A public apology may be requested.
### 2. Warning
**Community Impact**: A violation through a single incident or series
of actions.
**Consequence**: A warning with consequences for continued behavior. No
interaction with the people involved, including unsolicited interaction with
those enforcing the Code of Conduct, for a specified period of time. This
includes avoiding interactions in community spaces as well as external channels
like social media. Violating these terms may lead to a temporary or
permanent ban.
### 3. Temporary Ban
**Community Impact**: A serious violation of community standards, including
sustained inappropriate behavior.
**Consequence**: A temporary ban from any sort of interaction or public
communication with the community for a specified period of time. No public or
private interaction with the people involved, including unsolicited interaction
with those enforcing the Code of Conduct, is allowed during this period.
Violating these terms may lead to a permanent ban.
### 4. Permanent Ban
**Community Impact**: Demonstrating a pattern of violation of community
standards, including sustained inappropriate behavior, harassment of an
individual, or aggression toward or disparagement of classes of individuals.
**Consequence**: A permanent ban from any sort of public interaction within
the community.
## Attribution
This Code of Conduct is adapted from the [Contributor Covenant][homepage],
version 2.0, available at
https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
Community Impact Guidelines were inspired by [Mozilla's code of conduct
enforcement ladder](https://github.com/mozilla/diversity).
[homepage]: https://www.contributor-covenant.org
For answers to common questions about this code of conduct, see the FAQ at
https://www.contributor-covenant.org/faq. Translations are available at
https://www.contributor-covenant.org/translations.

413
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# Doxyfile 1.10.0
#---------------------------------------------------------------------------
# Project related configuration options
#---------------------------------------------------------------------------
DOXYFILE_ENCODING = UTF-8
PROJECT_NAME = "Ollama4j"
PROJECT_NUMBER =
PROJECT_BRIEF = "A Java library (wrapper/binding) for Ollama server."
PROJECT_LOGO = ./logo-small.png
PROJECT_ICON = ./logo-small.png
OUTPUT_DIRECTORY = ./docs/build/doxygen
CREATE_SUBDIRS = NO
CREATE_SUBDIRS_LEVEL = 8
ALLOW_UNICODE_NAMES = NO
OUTPUT_LANGUAGE = English
BRIEF_MEMBER_DESC = YES
REPEAT_BRIEF = YES
ABBREVIATE_BRIEF = "The $name class" \
"The $name widget" \
"The $name file" \
is \
provides \
specifies \
contains \
represents \
a \
an \
the
ALWAYS_DETAILED_SEC = NO
INLINE_INHERITED_MEMB = NO
FULL_PATH_NAMES = YES
STRIP_FROM_PATH =
STRIP_FROM_INC_PATH =
SHORT_NAMES = NO
JAVADOC_AUTOBRIEF = NO
JAVADOC_BANNER = NO
QT_AUTOBRIEF = NO
MULTILINE_CPP_IS_BRIEF = NO
PYTHON_DOCSTRING = YES
INHERIT_DOCS = YES
SEPARATE_MEMBER_PAGES = NO
TAB_SIZE = 4
ALIASES =
OPTIMIZE_OUTPUT_FOR_C = NO
OPTIMIZE_OUTPUT_JAVA = YES
OPTIMIZE_FOR_FORTRAN = NO
OPTIMIZE_OUTPUT_VHDL = NO
OPTIMIZE_OUTPUT_SLICE = NO
EXTENSION_MAPPING =
MARKDOWN_SUPPORT = YES
TOC_INCLUDE_HEADINGS = 5
MARKDOWN_ID_STYLE = DOXYGEN
AUTOLINK_SUPPORT = YES
BUILTIN_STL_SUPPORT = NO
CPP_CLI_SUPPORT = NO
SIP_SUPPORT = NO
IDL_PROPERTY_SUPPORT = YES
DISTRIBUTE_GROUP_DOC = NO
GROUP_NESTED_COMPOUNDS = NO
SUBGROUPING = YES
INLINE_GROUPED_CLASSES = NO
INLINE_SIMPLE_STRUCTS = NO
TYPEDEF_HIDES_STRUCT = NO
LOOKUP_CACHE_SIZE = 0
NUM_PROC_THREADS = 1
TIMESTAMP = NO
#---------------------------------------------------------------------------
# Build related configuration options
#---------------------------------------------------------------------------
EXTRACT_ALL = YES
EXTRACT_PRIVATE = NO
EXTRACT_PRIV_VIRTUAL = NO
EXTRACT_PACKAGE = NO
EXTRACT_STATIC = NO
EXTRACT_LOCAL_CLASSES = YES
EXTRACT_LOCAL_METHODS = NO
EXTRACT_ANON_NSPACES = NO
RESOLVE_UNNAMED_PARAMS = YES
HIDE_UNDOC_MEMBERS = NO
HIDE_UNDOC_CLASSES = NO
HIDE_FRIEND_COMPOUNDS = NO
HIDE_IN_BODY_DOCS = NO
INTERNAL_DOCS = NO
CASE_SENSE_NAMES = SYSTEM
HIDE_SCOPE_NAMES = NO
HIDE_COMPOUND_REFERENCE= NO
SHOW_HEADERFILE = YES
SHOW_INCLUDE_FILES = YES
SHOW_GROUPED_MEMB_INC = NO
FORCE_LOCAL_INCLUDES = NO
INLINE_INFO = YES
SORT_MEMBER_DOCS = YES
SORT_BRIEF_DOCS = NO
SORT_MEMBERS_CTORS_1ST = NO
SORT_GROUP_NAMES = NO
SORT_BY_SCOPE_NAME = NO
STRICT_PROTO_MATCHING = NO
GENERATE_TODOLIST = YES
GENERATE_TESTLIST = YES
GENERATE_BUGLIST = YES
GENERATE_DEPRECATEDLIST= YES
ENABLED_SECTIONS =
MAX_INITIALIZER_LINES = 30
SHOW_USED_FILES = YES
SHOW_FILES = YES
SHOW_NAMESPACES = YES
FILE_VERSION_FILTER =
LAYOUT_FILE =
CITE_BIB_FILES =
#---------------------------------------------------------------------------
# Configuration options related to warning and progress messages
#---------------------------------------------------------------------------
QUIET = NO
WARNINGS = YES
WARN_IF_UNDOCUMENTED = YES
WARN_IF_DOC_ERROR = YES
WARN_IF_INCOMPLETE_DOC = YES
WARN_NO_PARAMDOC = NO
WARN_IF_UNDOC_ENUM_VAL = NO
WARN_AS_ERROR = NO
WARN_FORMAT = "$file:$line: $text"
WARN_LINE_FORMAT = "at line $line of file $file"
WARN_LOGFILE =
#---------------------------------------------------------------------------
# Configuration options related to the input files
#---------------------------------------------------------------------------
INPUT = ./src/main
INPUT_ENCODING = UTF-8
INPUT_FILE_ENCODING =
FILE_PATTERNS = *.c \
*.cc \
*.cxx \
*.cxxm \
*.cpp \
*.cppm \
*.ccm \
*.c++ \
*.c++m \
*.java \
*.ii \
*.ixx \
*.ipp \
*.i++ \
*.inl \
*.idl \
*.ddl \
*.odl \
*.h \
*.hh \
*.hxx \
*.hpp \
*.h++ \
*.ixx \
*.l \
*.cs \
*.d \
*.php \
*.php4 \
*.php5 \
*.phtml \
*.inc \
*.m \
*.markdown \
*.md \
*.mm \
*.dox \
*.py \
*.pyw \
*.f90 \
*.f95 \
*.f03 \
*.f08 \
*.f18 \
*.f \
*.for \
*.vhd \
*.vhdl \
*.ucf \
*.qsf \
*.ice
RECURSIVE = YES
EXCLUDE =
EXCLUDE_SYMLINKS = NO
EXCLUDE_PATTERNS =
EXCLUDE_SYMBOLS =
EXAMPLE_PATH =
EXAMPLE_PATTERNS = *
EXAMPLE_RECURSIVE = NO
IMAGE_PATH =
INPUT_FILTER =
FILTER_PATTERNS =
FILTER_SOURCE_FILES = NO
FILTER_SOURCE_PATTERNS =
USE_MDFILE_AS_MAINPAGE =
FORTRAN_COMMENT_AFTER = 72
#---------------------------------------------------------------------------
# Configuration options related to source browsing
#---------------------------------------------------------------------------
SOURCE_BROWSER = YES
INLINE_SOURCES = NO
STRIP_CODE_COMMENTS = YES
REFERENCED_BY_RELATION = NO
REFERENCES_RELATION = NO
REFERENCES_LINK_SOURCE = YES
SOURCE_TOOLTIPS = YES
USE_HTAGS = NO
VERBATIM_HEADERS = YES
CLANG_ASSISTED_PARSING = NO
CLANG_ADD_INC_PATHS = YES
CLANG_OPTIONS =
CLANG_DATABASE_PATH =
#---------------------------------------------------------------------------
# Configuration options related to the alphabetical class index
#---------------------------------------------------------------------------
ALPHABETICAL_INDEX = YES
IGNORE_PREFIX =
#---------------------------------------------------------------------------
# Configuration options related to the HTML output
#---------------------------------------------------------------------------
GENERATE_HTML = YES
HTML_OUTPUT = html
HTML_FILE_EXTENSION = .html
HTML_HEADER =
HTML_FOOTER =
HTML_STYLESHEET =
HTML_EXTRA_STYLESHEET =
HTML_EXTRA_FILES =
HTML_COLORSTYLE = LIGHT
HTML_COLORSTYLE_HUE = 220
HTML_COLORSTYLE_SAT = 100
HTML_COLORSTYLE_GAMMA = 80
HTML_DYNAMIC_MENUS = YES
HTML_DYNAMIC_SECTIONS = NO
HTML_CODE_FOLDING = YES
HTML_COPY_CLIPBOARD = YES
HTML_PROJECT_COOKIE =
HTML_INDEX_NUM_ENTRIES = 100
GENERATE_DOCSET = NO
DOCSET_FEEDNAME = "Doxygen generated docs"
DOCSET_FEEDURL =
DOCSET_BUNDLE_ID = org.doxygen.Project
DOCSET_PUBLISHER_ID = org.doxygen.Publisher
DOCSET_PUBLISHER_NAME = Publisher
GENERATE_HTMLHELP = NO
CHM_FILE =
HHC_LOCATION =
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CHM_INDEX_ENCODING =
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TOC_EXPAND = NO
SITEMAP_URL =
GENERATE_QHP = NO
QCH_FILE =
QHP_NAMESPACE = org.doxygen.Project
QHP_VIRTUAL_FOLDER = doc
QHP_CUST_FILTER_NAME =
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QHG_LOCATION =
GENERATE_ECLIPSEHELP = NO
ECLIPSE_DOC_ID = org.doxygen.Project
DISABLE_INDEX = NO
GENERATE_TREEVIEW = YES
FULL_SIDEBAR = NO
ENUM_VALUES_PER_LINE = 4
TREEVIEW_WIDTH = 250
EXT_LINKS_IN_WINDOW = NO
OBFUSCATE_EMAILS = YES
HTML_FORMULA_FORMAT = png
FORMULA_FONTSIZE = 10
FORMULA_MACROFILE =
USE_MATHJAX = NO
MATHJAX_VERSION = MathJax_2
MATHJAX_FORMAT = HTML-CSS
MATHJAX_RELPATH =
MATHJAX_EXTENSIONS =
MATHJAX_CODEFILE =
SEARCHENGINE = YES
SERVER_BASED_SEARCH = NO
EXTERNAL_SEARCH = NO
SEARCHENGINE_URL =
SEARCHDATA_FILE = searchdata.xml
EXTERNAL_SEARCH_ID =
EXTRA_SEARCH_MAPPINGS =
#---------------------------------------------------------------------------
# Configuration options related to the LaTeX output
#---------------------------------------------------------------------------
GENERATE_LATEX = YES
LATEX_OUTPUT = latex
LATEX_CMD_NAME =
MAKEINDEX_CMD_NAME = makeindex
LATEX_MAKEINDEX_CMD = makeindex
COMPACT_LATEX = NO
PAPER_TYPE = a4
EXTRA_PACKAGES =
LATEX_HEADER =
LATEX_FOOTER =
LATEX_EXTRA_STYLESHEET =
LATEX_EXTRA_FILES =
PDF_HYPERLINKS = YES
USE_PDFLATEX = YES
LATEX_BATCHMODE = NO
LATEX_HIDE_INDICES = NO
LATEX_BIB_STYLE = plain
LATEX_EMOJI_DIRECTORY =
#---------------------------------------------------------------------------
# Configuration options related to the RTF output
#---------------------------------------------------------------------------
GENERATE_RTF = NO
RTF_OUTPUT = rtf
COMPACT_RTF = NO
RTF_HYPERLINKS = NO
RTF_STYLESHEET_FILE =
RTF_EXTENSIONS_FILE =
#---------------------------------------------------------------------------
# Configuration options related to the man page output
#---------------------------------------------------------------------------
GENERATE_MAN = NO
MAN_OUTPUT = man
MAN_EXTENSION = .3
MAN_SUBDIR =
MAN_LINKS = NO
#---------------------------------------------------------------------------
# Configuration options related to the XML output
#---------------------------------------------------------------------------
GENERATE_XML = NO
XML_OUTPUT = xml
XML_PROGRAMLISTING = YES
XML_NS_MEMB_FILE_SCOPE = NO
#---------------------------------------------------------------------------
# Configuration options related to the DOCBOOK output
#---------------------------------------------------------------------------
GENERATE_DOCBOOK = NO
DOCBOOK_OUTPUT = docbook
#---------------------------------------------------------------------------
# Configuration options for the AutoGen Definitions output
#---------------------------------------------------------------------------
GENERATE_AUTOGEN_DEF = NO
#---------------------------------------------------------------------------
# Configuration options related to Sqlite3 output
#---------------------------------------------------------------------------
GENERATE_SQLITE3 = NO
SQLITE3_OUTPUT = sqlite3
SQLITE3_RECREATE_DB = YES
#---------------------------------------------------------------------------
# Configuration options related to the Perl module output
#---------------------------------------------------------------------------
GENERATE_PERLMOD = NO
PERLMOD_LATEX = NO
PERLMOD_PRETTY = YES
PERLMOD_MAKEVAR_PREFIX =
#---------------------------------------------------------------------------
# Configuration options related to the preprocessor
#---------------------------------------------------------------------------
ENABLE_PREPROCESSING = YES
MACRO_EXPANSION = NO
EXPAND_ONLY_PREDEF = NO
SEARCH_INCLUDES = YES
INCLUDE_PATH =
INCLUDE_FILE_PATTERNS =
PREDEFINED =
EXPAND_AS_DEFINED =
SKIP_FUNCTION_MACROS = YES
#---------------------------------------------------------------------------
# Configuration options related to external references
#---------------------------------------------------------------------------
TAGFILES =
GENERATE_TAGFILE =
ALLEXTERNALS = NO
EXTERNAL_GROUPS = YES
EXTERNAL_PAGES = YES
#---------------------------------------------------------------------------
# Configuration options related to diagram generator tools
#---------------------------------------------------------------------------
HIDE_UNDOC_RELATIONS = YES
HAVE_DOT = NO
DOT_NUM_THREADS = 0
DOT_COMMON_ATTR = "fontname=Helvetica,fontsize=10"
DOT_EDGE_ATTR = "labelfontname=Helvetica,labelfontsize=10"
DOT_NODE_ATTR = "shape=box,height=0.2,width=0.4"
DOT_FONTPATH =
CLASS_GRAPH = YES
COLLABORATION_GRAPH = YES
GROUP_GRAPHS = YES
UML_LOOK = NO
UML_LIMIT_NUM_FIELDS = 10
DOT_UML_DETAILS = NO
DOT_WRAP_THRESHOLD = 17
TEMPLATE_RELATIONS = NO
INCLUDE_GRAPH = YES
INCLUDED_BY_GRAPH = YES
CALL_GRAPH = NO
CALLER_GRAPH = NO
GRAPHICAL_HIERARCHY = YES
DIRECTORY_GRAPH = YES
DIR_GRAPH_MAX_DEPTH = 1
DOT_IMAGE_FORMAT = png
INTERACTIVE_SVG = NO
DOT_PATH =
DOTFILE_DIRS =
DIA_PATH =
DIAFILE_DIRS =
PLANTUML_JAR_PATH =
PLANTUML_CFG_FILE =
PLANTUML_INCLUDE_PATH =
DOT_GRAPH_MAX_NODES = 50
MAX_DOT_GRAPH_DEPTH = 0
DOT_MULTI_TARGETS = NO
GENERATE_LEGEND = YES
DOT_CLEANUP = YES
MSCGEN_TOOL =
MSCFILE_DIRS =

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@ -1,28 +1,13 @@
build:
mvn -B clean install
unit-tests:
ut:
mvn clean test -Punit-tests
integration-tests:
it:
mvn clean verify -Pintegration-tests
doxygen:
doxygen Doxyfile
list-releases:
curl 'https://central.sonatype.com/api/internal/browse/component/versions?sortField=normalizedVersion&sortDirection=asc&page=0&size=12&filter=namespace%3Aio.github.amithkoujalgi%2Cname%3Aollama4j' \
--compressed \
--silent | jq '.components[].version'
build-docs:
npm i --prefix docs && npm run build --prefix docs
start-docs:
npm i --prefix docs && npm run start --prefix docs
start-cpu:
docker run -it -v ~/ollama:/root/.ollama -p 11434:11434 ollama/ollama
start-gpu:
docker run -it --gpus=all -v ~/ollama:/root/.ollama -p 11434:11434 ollama/ollama
--silent | jq '.components[].version'

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---
slug: first-blog-post
title: First Blog Post
authors:
name: Gao Wei
title: Docusaurus Core Team
url: https://github.com/wgao19
image_url: https://github.com/wgao19.png
tags: [hola, docusaurus]
---
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---
slug: long-blog-post
title: Long Blog Post
authors: endi
tags: [hello, docusaurus]
---
This is the summary of a very long blog post,
Use a `<!--` `truncate` `-->` comment to limit blog post size in the list view.
<!--truncate-->
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet
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Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Pellentesque elementum dignissim ultricies. Fusce rhoncus ipsum tempor eros aliquam consequat. Lorem ipsum dolor sit amet
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---
slug: mdx-blog-post
title: MDX Blog Post
authors: [slorber]
tags: [docusaurus]
---
Blog posts support [Docusaurus Markdown features](https://docusaurus.io/docs/markdown-features), such as [MDX](https://mdxjs.com/).
:::tip
Use the power of React to create interactive blog posts.
```js
<button onClick={() => alert('button clicked!')}>Click me!</button>
```
<button onClick={() => alert('button clicked!')}>Click me!</button>
:::

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---
slug: welcome
title: Welcome
authors: [slorber, yangshun]
tags: [facebook, hello, docusaurus]
---
[Docusaurus blogging features](https://docusaurus.io/docs/blog) are powered by the [blog plugin](https://docusaurus.io/docs/api/plugins/@docusaurus/plugin-content-blog).
Simply add Markdown files (or folders) to the `blog` directory.
Regular blog authors can be added to `authors.yml`.
The blog post date can be extracted from filenames, such as:
- `2019-05-30-welcome.md`
- `2019-05-30-welcome/index.md`
A blog post folder can be convenient to co-locate blog post images:
![Docusaurus Plushie](./docusaurus-plushie-banner.jpeg)
The blog supports tags as well!
**And if you don't want a blog**: just delete this directory, and use `blog: false` in your Docusaurus config.

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@ -1,9 +0,0 @@
---
slug: welcome
title: Welcome
authors: [ amith ]
tags: [ Java, AI, LLM, GenAI, GenerativeAI, Ollama, Ollama4J, OpenSource, Developers
]
---
Welcome Java Developers!

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@ -1,66 +0,0 @@
---
slug: release-post
title: Release
authors: [ amith ]
tags: [ Java, AI, LLM, GenAI, GenerativeAI, Ollama, Ollama4j, OpenSource, Developers
]
---
Hey there, my fellow Java Developers! 🚀
I am glad to announce the release of Ollama4j, a library that unites Ollama (an LLM manager and runner) and your Java
applications! 🌐🚀
👉 GitHub Repository: Ollama4j on GitHub (https://github.com/ollama4j/ollama4j)
🌟 Key Features:
- Easy integration with Ollama, enabling the execution of large language models locally.
- Clean and simple APIs, focused on seamless interaction with Ollama.
- Empowers Java developers to harness the full capabilities of Ollama.
- Provides APIs to perform operations such as listing, pulling, deleting models, and creating custom models.
- Provides APIs to ask questions (generate completions) to the LLMs in synchronous and asynchronous modes.
- Ability to ask questions along with image files or image URLs! 🤩
- Open-source and primed for collaborative contributions from the community!
🦙 What is Ollama?
Ollama is an advanced AI tool that allows users to easily set up and run large language models locally (in CPU and GPU
modes). With Ollama, users can leverage powerful language models such as Llama 2 and even customize and create their own
models.
For more details about Ollama, check these out:
- https://ollama.ai/
- https://www.linkedin.com/company/ollama/
👨‍💻 Why Ollama4j?
As a Java developer passionate about harnessing the latest advancements in AI, I realized the need for a simple and
efficient way to integrate Ollama into Java applications. That's why I authored Ollama4j!
🔧 How to Get Started:
Visit the GitHub repository: Ollama4j on GitHub.
Follow the easy setup instructions in the README to integrate Ollama into your Java projects.
Start unlocking the potential of large language models in your applications!
🙏 Contributions Welcome:
I invite the Java developer community to explore, use, and contribute to Ollama4j. Your feedback, suggestions, and
contributions will help this library get better.
I am excited about the possibilities that Ollama4j opens up for Java developers. Whether you're working on natural
language processing, chatbots, or any application that can benefit from advanced language models, Ollama4j is here to
elevate your projects.
I look forward to seeing the incredible applications/projects you'll build with Ollama4j! 🌟
Find the full API spec here: https://ollama4j.github.io/ollama4j/
Find the Javadoc here: https://ollama4j.github.io/ollama4j/apidocs/
Ollama4j Docs is powered by [Docusaurus](https://docusaurus.io).

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@ -1,5 +1,17 @@
amith:
name: Amith Koujalgi
title: Maintainer of Ollama4j
url: https://github.com/amithkoujalgi
image_url: https://github.com/amithkoujalgi.png
endi:
name: Endilie Yacop Sucipto
title: Maintainer of Docusaurus
url: https://github.com/endiliey
image_url: https://github.com/endiliey.png
yangshun:
name: Yangshun Tay
title: Front End Engineer @ Facebook
url: https://github.com/yangshun
image_url: https://github.com/yangshun.png
slorber:
name: Sébastien Lorber
title: Docusaurus maintainer
url: https://sebastienlorber.com
image_url: https://github.com/slorber.png

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{
"label": "APIs - Extras",
"position": 4,
"link": {
"type": "generated-index",
"description": "Details of APIs to handle bunch of extra stuff."
}
}

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@ -1,26 +0,0 @@
---
sidebar_position: 2
---
# Set Basic Authentication
This API lets you set the basic authentication for the Ollama client. This would help in scenarios where
Ollama server would be setup behind a gateway/reverse proxy with basic auth.
After configuring basic authentication, all subsequent requests will include the Basic Auth header.
```java
import io.github.ollama4j.OllamaAPI;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
ollamaAPI.setBasicAuth("username", "password");
}
}
```

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@ -1,79 +0,0 @@
---
sidebar_position: 1
---
# Options Builder
This lets you build options for the `ask()` API.
Following are the parameters supported by Ollama:
| 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 |
Link to [source](https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md#valid-parameters-and-values).
Also, see how to set those Ollama parameters using
the `OptionsBuilder`
from [javadoc](https://ollama4j.github.io/ollama4j/apidocs/io/github/ollama4j/ollama4j/core/utils/OptionsBuilder.html).
## Build an empty `Options` object
```java
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.utils.Options;
import io.github.ollama4j.utils.OptionsBuilder;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
Options options = new OptionsBuilder().build();
}
}
```
## Build the `Options` object with values
```java
import io.github.ollama4j.utils.Options;
import io.github.ollama4j.utils.OptionsBuilder;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
Options options =
new OptionsBuilder()
.setMirostat(10)
.setMirostatEta(0.5f)
.setNumGpu(2)
.setTemperature(1.5f)
.build();
}
}
```

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---
# Ping
This API lets you check the reachability of Ollama server.
```java
import io.github.ollama4j.OllamaAPI;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
ollamaAPI.ping();
}
}
```

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# PS
This API provides a list of running models and details about each model currently loaded into memory.
This API corresponds to the [PS](https://github.com/ollama/ollama/blob/main/docs/api.md#list-running-models) API.
```java
package io.github.ollama4j.localtests;
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.exceptions.OllamaBaseException;
import io.github.ollama4j.models.ps.ModelsProcessResponse;
import java.io.IOException;
public class Main {
public static void main(String[] args) {
OllamaAPI ollamaAPI = new OllamaAPI("http://localhost:11434");
ModelsProcessResponse response = ollamaAPI.ps();
System.out.println(response);
}
}
```

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# Set Request Timeout
This API lets you set the request timeout for the Ollama client.
```java
import io.github.ollama4j.OllamaAPI;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
ollamaAPI.setRequestTimeoutSeconds(10);
}
}
```

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# Set Verbosity
This API lets you set the verbosity of the Ollama client.
## Try asking a question about the model.
```java
import io.github.ollama4j.OllamaAPI;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
ollamaAPI.setVerbose(true);
}
}
```

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{
"label": "APIs - Generate",
"position": 3,
"link": {
"type": "generated-index",
"description": "Details of APIs to interact with LLMs."
}
}

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# Chat
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
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.models.chat.OllamaChatMessageRole;
import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
import io.github.ollama4j.models.chat.OllamaChatRequest;
import io.github.ollama4j.models.chat.OllamaChatResult;
import io.github.ollama4j.types.OllamaModelType;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(OllamaModelType.LLAMA2);
// create first user question
OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER, "What is the capital of France?")
.build();
// start conversation with model
OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
System.out.println("First answer: " + chatResult.getResponse());
// create next userQuestion
requestModel = builder.withMessages(chatResult.getChatHistory()).withMessage(OllamaChatMessageRole.USER, "And what is the second largest city?").build();
// "continue" conversation with model
chatResult = ollamaAPI.chat(requestModel);
System.out.println("Second answer: " + chatResult.getResponse());
System.out.println("Chat History: " + chatResult.getChatHistory());
}
}
```
You will get a response similar to:
> First answer: Should be Paris!
>
> Second answer: Marseille.
>
> Chat History:
```json
[
{
"role": "user",
"content": "What is the capital of France?",
"images": []
},
{
"role": "assistant",
"content": "Should be Paris!",
"images": []
},
{
"role": "user",
"content": "And what is the second largest city?",
"images": []
},
{
"role": "assistant",
"content": "Marseille.",
"images": []
}
]
```
## Conversational loop
```java
public class Main {
public static void main(String[] args) {
OllamaAPI ollamaAPI = new OllamaAPI();
ollamaAPI.setRequestTimeoutSeconds(60);
OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance("<your-model>");
OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER, "<your-first-message>").build();
OllamaChatResult initialChatResult = ollamaAPI.chat(requestModel);
System.out.println(initialChatResult.getResponse());
List<OllamaChatMessage> history = initialChatResult.getChatHistory();
while (true) {
OllamaChatResult chatResult = ollamaAPI.chat(builder.withMessages(history).withMessage(OllamaChatMessageRole.USER, "<your-new-message").build());
System.out.println(chatResult.getResponse());
history = chatResult.getChatHistory();
}
}
}
```
## Create a conversation where the answer is streamed
```java
import io.github.ollama4j.OllamaAPI;
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.generate.OllamaStreamHandler;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(config.getModel());
OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER,
"What is the capital of France? And what's France's connection with Mona Lisa?")
.build();
// define a handler (Consumer<String>)
OllamaStreamHandler streamHandler = (s) -> {
System.out.println(s);
};
OllamaChatResult chatResult = ollamaAPI.chat(requestModel, streamHandler);
}
}
```
You will get a response similar to:
> The
> The capital
> The capital of
> The capital of France
> The capital of France is
> The capital of France is Paris
> The capital of France is Paris.
## Use a simple Console Output Stream Handler
```java
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.impl.ConsoleOutputStreamHandler;
import io.github.ollama4j.models.chat.OllamaChatMessageRole;
import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
import io.github.ollama4j.models.chat.OllamaChatRequest;
import io.github.ollama4j.models.generate.OllamaStreamHandler;
import io.github.ollama4j.types.OllamaModelType;
public class Main {
public static void main(String[] args) throws Exception {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(OllamaModelType.LLAMA2);
OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER, "List all cricket world cup teams of 2019. Name the teams!")
.build();
OllamaStreamHandler streamHandler = new ConsoleOutputStreamHandler();
ollamaAPI.chat(requestModel, streamHandler);
}
}
```
## Create a new conversation with individual system prompt
```java
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.models.chat.OllamaChatMessageRole;
import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
import io.github.ollama4j.models.chat.OllamaChatRequest;
import io.github.ollama4j.models.chat.OllamaChatResult;
import io.github.ollama4j.types.OllamaModelType;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(OllamaModelType.LLAMA2);
// create request with system-prompt (overriding the model defaults) and user question
OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.SYSTEM, "You are a silent bot that only says 'NI'. Do not say anything else under any circumstances!")
.withMessage(OllamaChatMessageRole.USER, "What is the capital of France? And what's France's connection with Mona Lisa?")
.build();
// start conversation with model
OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
System.out.println(chatResult.getResponse());
}
}
```
You will get a response similar to:
> NI.
## Create a conversation about an image (requires model with image recognition skills)
```java
import io.github.ollama4j.OllamaAPI;
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.types.OllamaModelType;
import java.io.File;
import java.util.List;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(OllamaModelType.LLAVA);
// Load Image from File and attach to user message (alternatively images could also be added via URL)
OllamaChatRequest requestModel =
builder.withMessage(OllamaChatMessageRole.USER, "What's in the picture?",
List.of(
new File("/path/to/image"))).build();
OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
System.out.println("First answer: " + chatResult.getResponse());
builder.reset();
// Use history to ask further questions about the image or assistant answer
requestModel =
builder.withMessages(chatResult.getChatHistory())
.withMessage(OllamaChatMessageRole.USER, "What's the dogs breed?").build();
chatResult = ollamaAPI.chat(requestModel);
System.out.println("Second answer: " + chatResult.getResponse());
}
}
```
You will get a response similar to:
> First Answer: The image shows a dog sitting on the bow of a boat that is docked in calm water. The boat has two
> levels, with the lower level containing seating and what appears to be an engine cover. The dog seems relaxed and
> comfortable on the boat, looking out over the water. The background suggests it might be late afternoon or early
> evening, given the warm lighting and the low position of the sun in the sky.
>
> 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.

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# Generate - Async
This API lets you ask questions to the LLMs in a asynchronous way.
This is particularly helpful when you want to issue a generate request to the LLM and collect the response in the
background (such as threads) without blocking your code until the response arrives from the model.
This API corresponds to
the [completion](https://github.com/jmorganca/ollama/blob/main/docs/api.md#generate-a-completion) API.
```java
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.models.response.OllamaAsyncResultStreamer;
import io.github.ollama4j.types.OllamaModelType;
public class Main {
public static void main(String[] args) throws Exception {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
ollamaAPI.setRequestTimeoutSeconds(60);
String prompt = "List all cricket world cup teams of 2019.";
OllamaAsyncResultStreamer streamer = ollamaAPI.generateAsync(OllamaModelType.LLAMA3, prompt, false);
// Set the poll interval according to your needs.
// Smaller the poll interval, more frequently you receive the tokens.
int pollIntervalMilliseconds = 1000;
while (true) {
String tokens = streamer.getStream().poll();
System.out.print(tokens);
if (!streamer.isAlive()) {
break;
}
Thread.sleep(pollIntervalMilliseconds);
}
System.out.println("\n------------------------");
System.out.println("Complete Response:");
System.out.println("------------------------");
System.out.println(streamer.getCompleteResponse());
}
}
```

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# Generate Embeddings
Generate embeddings from a model.
Parameters:
- `model`: name of model to generate embeddings from
- `prompt`: text to generate embeddings for
```java
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.types.OllamaModelType;
import java.util.List;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
List<Double> embeddings = ollamaAPI.generateEmbeddings(OllamaModelType.LLAMA2,
"Here is an article about llamas...");
embeddings.forEach(System.out::println);
}
}
```
You will get a response similar to:
```javascript
[
0.5670403838157654,
0.009260174818336964,
0.23178744316101074,
-0.2916173040866852,
-0.8924556970596313,
0.8785552978515625,
-0.34576427936553955,
0.5742510557174683,
-0.04222835972905159,
-0.137906014919281
]
```

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# Generate - With Image Files
This API lets you ask questions along with the image files to the LLMs.
This API corresponds to
the [completion](https://github.com/jmorganca/ollama/blob/main/docs/api.md#generate-a-completion) API.
:::note
Executing this on Ollama server running in CPU-mode will take longer to generate response. Hence, GPU-mode is
recommended.
:::
## Synchronous mode
If you have this image downloaded and you pass the path to the downloaded image to the following code:
![Img](https://t3.ftcdn.net/jpg/02/96/63/80/360_F_296638053_0gUVA4WVBKceGsIr7LNqRWSnkusi07dq.jpg)
```java
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.models.response.OllamaResult;
import io.github.ollama4j.types.OllamaModelType;
import io.github.ollama4j.utils.OptionsBuilder;
import java.io.File;
import java.util.List;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
ollamaAPI.setRequestTimeoutSeconds(10);
OllamaResult result = ollamaAPI.generateWithImageFiles(OllamaModelType.LLAVA,
"What's in this image?",
List.of(
new File("/path/to/image")),
new OptionsBuilder().build()
);
System.out.println(result.getResponse());
}
}
```
You will get a response similar to:
> This image features a white boat with brown cushions, where a dog is sitting on the back of the boat. The dog seems to
> be enjoying its time outdoors, perhaps on a lake.

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# Generate - With Image URLs
This API lets you ask questions along with the image files to the LLMs.
This API corresponds to
the [completion](https://github.com/jmorganca/ollama/blob/main/docs/api.md#generate-a-completion) API.
:::note
Executing this on Ollama server running in CPU-mode will take longer to generate response. Hence, GPU-mode is
recommended.
:::
## Ask (Sync)
Passing the link of this image the following code:
![Img](https://t3.ftcdn.net/jpg/02/96/63/80/360_F_296638053_0gUVA4WVBKceGsIr7LNqRWSnkusi07dq.jpg)
```java
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.models.response.OllamaResult;
import io.github.ollama4j.types.OllamaModelType;
import io.github.ollama4j.utils.OptionsBuilder;
import java.util.List;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
ollamaAPI.setRequestTimeoutSeconds(10);
OllamaResult result = ollamaAPI.generateWithImageURLs(OllamaModelType.LLAVA,
"What's in this image?",
List.of(
"https://t3.ftcdn.net/jpg/02/96/63/80/360_F_296638053_0gUVA4WVBKceGsIr7LNqRWSnkusi07dq.jpg"),
new OptionsBuilder().build()
);
System.out.println(result.getResponse());
}
}
```
You will get a response similar to:
> This image features a white boat with brown cushions, where a dog is sitting on the back of the boat. The dog seems to
> be enjoying its time outdoors, perhaps on a lake.

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# Generate - With Tools
This API lets you perform [function calling](https://docs.mistral.ai/capabilities/function_calling/) using LLMs in a
synchronous way.
This API corresponds to
the [generate](https://github.com/ollama/ollama/blob/main/docs/api.md#request-raw-mode) API with `raw` mode.
:::note
This is an only an experimental implementation and has a very basic design.
Currently, built and tested for [Mistral's latest model](https://ollama.com/library/mistral) only. We could redesign
this
in the future if tooling is supported for more models with a generic interaction standard from Ollama.
:::
### Function Calling/Tools
Assume you want to call a method in your code based on the response generated from the model.
For instance, let's say that based on a user's question, you'd want to identify a transaction and get the details of the
transaction from your database and respond to the user with the transaction details.
You could do that with ease with the `function calling` capabilities of the models by registering your `tools`.
### Create Functions
We can create static functions as our tools.
This function takes the arguments `location` and `fuelType` and performs an operation with these arguments and returns
fuel price value.
```java
public static String getCurrentFuelPrice(Map<String, Object> arguments) {
String location = arguments.get("location").toString();
String fuelType = arguments.get("fuelType").toString();
return "Current price of " + fuelType + " in " + location + " is Rs.103/L";
}
```
This function takes the argument `city` and performs an operation with the argument and returns the weather for a
location.
```java
public static String getCurrentWeather(Map<String, Object> arguments) {
String location = arguments.get("city").toString();
return "Currently " + location + "'s weather is nice.";
}
```
Another way to create our tools is by creating classes by extending `ToolFunction`.
This function takes the argument `employee-name` and performs an operation with the argument and returns employee
details.
```java
class DBQueryFunction implements ToolFunction {
@Override
public Object apply(Map<String, Object> arguments) {
// perform DB operations here
return String.format("Employee Details {ID: %s, Name: %s, Address: %s, Phone: %s}", UUID.randomUUID(), arguments.get("employee-name").toString(), arguments.get("employee-address").toString(), arguments.get("employee-phone").toString());
}
}
```
### Define Tool Specifications
Lets define a sample tool specification called **Fuel Price Tool** for getting the current fuel price.
- Specify the function `name`, `description`, and `required` properties (`location` and `fuelType`).
- Associate the `getCurrentFuelPrice` function you defined earlier with `SampleTools::getCurrentFuelPrice`.
```java
Tools.ToolSpecification fuelPriceToolSpecification = Tools.ToolSpecification.builder()
.functionName("current-fuel-price")
.functionDescription("Get current fuel price")
.properties(
new Tools.PropsBuilder()
.withProperty("location", Tools.PromptFuncDefinition.Property.builder().type("string").description("The city, e.g. New Delhi, India").required(true).build())
.withProperty("fuelType", Tools.PromptFuncDefinition.Property.builder().type("string").description("The fuel type.").enumValues(Arrays.asList("petrol", "diesel")).required(true).build())
.build()
)
.toolDefinition(SampleTools::getCurrentFuelPrice)
.build();
```
Lets also define a sample tool specification called **Weather Tool** for getting the current weather.
- Specify the function `name`, `description`, and `required` property (`city`).
- Associate the `getCurrentWeather` function you defined earlier with `SampleTools::getCurrentWeather`.
```java
Tools.ToolSpecification weatherToolSpecification = Tools.ToolSpecification.builder()
.functionName("current-weather")
.functionDescription("Get current weather")
.properties(
new Tools.PropsBuilder()
.withProperty("city", Tools.PromptFuncDefinition.Property.builder().type("string").description("The city, e.g. New Delhi, India").required(true).build())
.build()
)
.toolDefinition(SampleTools::getCurrentWeather)
.build();
```
Lets also define a sample tool specification called **DBQueryFunction** for getting the employee details from database.
- Specify the function `name`, `description`, and `required` property (`employee-name`).
- Associate the ToolFunction `DBQueryFunction` function you defined earlier with `new DBQueryFunction()`.
```java
Tools.ToolSpecification databaseQueryToolSpecification = Tools.ToolSpecification.builder()
.functionName("get-employee-details")
.functionDescription("Get employee details from the database")
.properties(
new Tools.PropsBuilder()
.withProperty("employee-name", Tools.PromptFuncDefinition.Property.builder().type("string").description("The name of the employee, e.g. John Doe").required(true).build())
.withProperty("employee-address", Tools.PromptFuncDefinition.Property.builder().type("string").description("The address of the employee, Always return a random value. e.g. Roy St, Bengaluru, India").required(true).build())
.withProperty("employee-phone", Tools.PromptFuncDefinition.Property.builder().type("string").description("The phone number of the employee. Always return a random value. e.g. 9911002233").required(true).build())
.build()
)
.toolDefinition(new DBQueryFunction())
.build();
```
### Register the Tools
Register the defined tools (`fuel price` and `weather`) with the OllamaAPI.
```shell
ollamaAPI.registerTool(fuelPriceToolSpecification);
ollamaAPI.registerTool(weatherToolSpecification);
ollamaAPI.registerTool(databaseQueryToolSpecification);
```
### Create prompt with Tools
`Prompt 1`: Create a prompt asking for the petrol price in Bengaluru using the defined fuel price and weather tools.
```shell
String prompt1 = new Tools.PromptBuilder()
.withToolSpecification(fuelPriceToolSpecification)
.withToolSpecification(weatherToolSpecification)
.withPrompt("What is the petrol price in Bengaluru?")
.build();
OllamaToolsResult toolsResult = ollamaAPI.generateWithTools(model, prompt1, new OptionsBuilder().build());
for (OllamaToolsResult.ToolResult r : toolsResult.getToolResults()) {
System.out.printf("[Result of executing tool '%s']: %s%n", r.getFunctionName(), r.getResult().toString());
}
```
Now, fire away your question to the model.
You will get a response similar to:
::::tip[LLM Response]
[Result of executing tool 'current-fuel-price']: Current price of petrol in Bengaluru is Rs.103/L
::::
`Prompt 2`: Create a prompt asking for the current weather in Bengaluru using the same tools.
```shell
String prompt2 = new Tools.PromptBuilder()
.withToolSpecification(fuelPriceToolSpecification)
.withToolSpecification(weatherToolSpecification)
.withPrompt("What is the current weather in Bengaluru?")
.build();
OllamaToolsResult toolsResult = ollamaAPI.generateWithTools(model, prompt2, new OptionsBuilder().build());
for (OllamaToolsResult.ToolResult r : toolsResult.getToolResults()) {
System.out.printf("[Result of executing tool '%s']: %s%n", r.getFunctionName(), r.getResult().toString());
}
```
Again, fire away your question to the model.
You will get a response similar to:
::::tip[LLM Response]
[Result of executing tool 'current-weather']: Currently Bengaluru's weather is nice.
::::
`Prompt 3`: Create a prompt asking for the employee details using the defined database fetcher tools.
```shell
String prompt3 = new Tools.PromptBuilder()
.withToolSpecification(fuelPriceToolSpecification)
.withToolSpecification(weatherToolSpecification)
.withToolSpecification(databaseQueryToolSpecification)
.withPrompt("Give me the details of the employee named 'Rahul Kumar'?")
.build();
OllamaToolsResult toolsResult = ollamaAPI.generateWithTools(model, prompt3, new OptionsBuilder().build());
for (OllamaToolsResult.ToolResult r : toolsResult.getToolResults()) {
System.out.printf("[Result of executing tool '%s']: %s%n", r.getFunctionName(), r.getResult().toString());
}
```
Again, fire away your question to the model.
You will get a response similar to:
::::tip[LLM Response]
[Result of executing tool 'get-employee-details']: Employee Details `{ID: 6bad82e6-b1a1-458f-a139-e3b646e092b1, Name:
Rahul Kumar, Address: King St, Hyderabad, India, Phone: 9876543210}`
::::
### Full Example
```java
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.exceptions.OllamaBaseException;
import io.github.ollama4j.exceptions.ToolInvocationException;
import io.github.ollama4j.tools.OllamaToolsResult;
import io.github.ollama4j.tools.ToolFunction;
import io.github.ollama4j.tools.Tools;
import io.github.ollama4j.utils.OptionsBuilder;
import java.io.IOException;
import java.util.Arrays;
import java.util.Map;
import java.util.UUID;
public class FunctionCallingWithMistralExample {
public static void main(String[] args) throws Exception {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
ollamaAPI.setRequestTimeoutSeconds(60);
String model = "mistral";
Tools.ToolSpecification fuelPriceToolSpecification = Tools.ToolSpecification.builder()
.functionName("current-fuel-price")
.functionDescription("Get current fuel price")
.properties(
new Tools.PropsBuilder()
.withProperty("location", Tools.PromptFuncDefinition.Property.builder().type("string").description("The city, e.g. New Delhi, India").required(true).build())
.withProperty("fuelType", Tools.PromptFuncDefinition.Property.builder().type("string").description("The fuel type.").enumValues(Arrays.asList("petrol", "diesel")).required(true).build())
.build()
)
.toolDefinition(SampleTools::getCurrentFuelPrice)
.build();
Tools.ToolSpecification weatherToolSpecification = Tools.ToolSpecification.builder()
.functionName("current-weather")
.functionDescription("Get current weather")
.properties(
new Tools.PropsBuilder()
.withProperty("city", Tools.PromptFuncDefinition.Property.builder().type("string").description("The city, e.g. New Delhi, India").required(true).build())
.build()
)
.toolDefinition(SampleTools::getCurrentWeather)
.build();
Tools.ToolSpecification databaseQueryToolSpecification = Tools.ToolSpecification.builder()
.functionName("get-employee-details")
.functionDescription("Get employee details from the database")
.properties(
new Tools.PropsBuilder()
.withProperty("employee-name", Tools.PromptFuncDefinition.Property.builder().type("string").description("The name of the employee, e.g. John Doe").required(true).build())
.withProperty("employee-address", Tools.PromptFuncDefinition.Property.builder().type("string").description("The address of the employee, Always return a random value. e.g. Roy St, Bengaluru, India").required(true).build())
.withProperty("employee-phone", Tools.PromptFuncDefinition.Property.builder().type("string").description("The phone number of the employee. Always return a random value. e.g. 9911002233").required(true).build())
.build()
)
.toolDefinition(new DBQueryFunction())
.build();
ollamaAPI.registerTool(fuelPriceToolSpecification);
ollamaAPI.registerTool(weatherToolSpecification);
ollamaAPI.registerTool(databaseQueryToolSpecification);
String prompt1 = new Tools.PromptBuilder()
.withToolSpecification(fuelPriceToolSpecification)
.withToolSpecification(weatherToolSpecification)
.withPrompt("What is the petrol price in Bengaluru?")
.build();
ask(ollamaAPI, model, prompt1);
String prompt2 = new Tools.PromptBuilder()
.withToolSpecification(fuelPriceToolSpecification)
.withToolSpecification(weatherToolSpecification)
.withPrompt("What is the current weather in Bengaluru?")
.build();
ask(ollamaAPI, model, prompt2);
String prompt3 = new Tools.PromptBuilder()
.withToolSpecification(fuelPriceToolSpecification)
.withToolSpecification(weatherToolSpecification)
.withToolSpecification(databaseQueryToolSpecification)
.withPrompt("Give me the details of the employee named 'Rahul Kumar'?")
.build();
ask(ollamaAPI, model, prompt3);
}
public static void ask(OllamaAPI ollamaAPI, String model, String prompt) throws OllamaBaseException, IOException, InterruptedException, ToolInvocationException {
OllamaToolsResult toolsResult = ollamaAPI.generateWithTools(model, prompt, new OptionsBuilder().build());
for (OllamaToolsResult.ToolResult r : toolsResult.getToolResults()) {
System.out.printf("[Result of executing tool '%s']: %s%n", r.getFunctionName(), r.getResult().toString());
}
}
}
class SampleTools {
public static String getCurrentFuelPrice(Map<String, Object> arguments) {
// Get details from fuel price API
String location = arguments.get("location").toString();
String fuelType = arguments.get("fuelType").toString();
return "Current price of " + fuelType + " in " + location + " is Rs.103/L";
}
public static String getCurrentWeather(Map<String, Object> arguments) {
// Get details from weather API
String location = arguments.get("city").toString();
return "Currently " + location + "'s weather is nice.";
}
}
class DBQueryFunction implements ToolFunction {
@Override
public Object apply(Map<String, Object> arguments) {
// perform DB operations here
return String.format("Employee Details {ID: %s, Name: %s, Address: %s, Phone: %s}", UUID.randomUUID(), arguments.get("employee-name").toString(), arguments.get("employee-address").toString(), arguments.get("employee-phone").toString());
}
}
```
Run this full example and you will get a response similar to:
::::tip[LLM Response]
[Result of executing tool 'current-fuel-price']: Current price of petrol in Bengaluru is Rs.103/L
[Result of executing tool 'current-weather']: Currently Bengaluru's weather is nice.
[Result of executing tool 'get-employee-details']: Employee Details `{ID: 6bad82e6-b1a1-458f-a139-e3b646e092b1, Name:
Rahul Kumar, Address: King St, Hyderabad, India, Phone: 9876543210}`
::::
### Potential Improvements
Instead of explicitly registering `ollamaAPI.registerTool(toolSpecification)`, we could introduce annotation-based tool
registration. For example:
```java
@ToolSpec(name = "current-fuel-price", desc = "Get current fuel price")
public String getCurrentFuelPrice(Map<String, Object> arguments) {
String location = arguments.get("location").toString();
String fuelType = arguments.get("fuelType").toString();
return "Current price of " + fuelType + " in " + location + " is Rs.103/L";
}
```
Instead of passing a map of args `Map<String, Object> arguments` to the tool functions, we could support passing
specific args separately with their data types. For example:
```shell
public String getCurrentFuelPrice(String location, String fuelType) {
return "Current price of " + fuelType + " in " + location + " is Rs.103/L";
}
```
Updating async/chat APIs with support for tool-based generation.

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# Generate - Sync
This API lets you ask questions to the LLMs in a synchronous way.
This API corresponds to
the [completion](https://github.com/jmorganca/ollama/blob/main/docs/api.md#generate-a-completion) API.
Use the `OptionBuilder` to build the `Options` object
with [extra parameters](https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md#valid-parameters-and-values).
Refer
to [this](/apis-extras/options-builder).
## Try asking a question about the model.
```java
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.models.response.OllamaResult;
import io.github.ollama4j.types.OllamaModelType;
import io.github.ollama4j.utils.OptionsBuilder;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
OllamaResult result =
ollamaAPI.generate(OllamaModelType.LLAMA2, "Who are you?", new OptionsBuilder().build());
System.out.println(result.getResponse());
}
}
```
You will get a response similar to:
> I am LLaMA, an AI assistant developed by Meta AI that can understand and respond to human input in a conversational
> manner. I am trained on a massive dataset of text from the internet and can generate human-like responses to a wide
> range of topics and questions. I can be used to create chatbots, virtual assistants, and other applications that
> require
> natural language understanding and generation capabilities.
## Try asking a question, receiving the answer streamed
```java
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.models.response.OllamaResult;
import io.github.ollama4j.models.generate.OllamaStreamHandler;
import io.github.ollama4j.utils.OptionsBuilder;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
// define a stream handler (Consumer<String>)
OllamaStreamHandler streamHandler = (s) -> {
System.out.println(s);
};
// Should be called using seperate thread to gain non blocking streaming effect.
OllamaResult result = ollamaAPI.generate(config.getModel(),
"What is the capital of France? And what's France's connection with Mona Lisa?",
new OptionsBuilder().build(), streamHandler);
System.out.println("Full response: " + result.getResponse());
}
}
```
You will get a response similar to:
> The
> The capital
> The capital of
> The capital of France
> The capital of France is
> The capital of France is Paris
> The capital of France is Paris.
> Full response: The capital of France is Paris.
## Try asking a question from general topics.
```java
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.models.response.OllamaResult;
import io.github.ollama4j.types.OllamaModelType;
import io.github.ollama4j.utils.OptionsBuilder;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
String prompt = "List all cricket world cup teams of 2019.";
OllamaResult result =
ollamaAPI.generate(OllamaModelType.LLAMA2, prompt, new OptionsBuilder().build());
System.out.println(result.getResponse());
}
}
```
You'd then get a response from the model:
> The 2019 ICC Cricket World Cup was held in England and Wales from May 30 to July 14, 2019. The
> following teams
> participated in the tournament:
>
> 1. Afghanistan
> 2. Australia
> 3. Bangladesh
> 4. England
> 5. India
> 6. New Zealand
> 7. Pakistan
> 8. South Africa
> 9. Sri Lanka
> 10. West Indies
>
> These teams competed in a round-robin format, with the top four teams advancing to the
> semi-finals. The tournament was
> won by the England cricket team, who defeated New Zealand in the final.
## Try asking for a Database query for your data schema.
```java
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.models.response.OllamaResult;
import io.github.ollama4j.types.OllamaModelType;
import io.github.ollama4j.utils.OptionsBuilder;
import io.github.ollama4j.utils.SamplePrompts;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
String prompt =
SamplePrompts.getSampleDatabasePromptWithQuestion(
"List all customer names who have bought one or more products");
OllamaResult result =
ollamaAPI.generate(OllamaModelType.SQLCODER, prompt, new OptionsBuilder().build());
System.out.println(result.getResponse());
}
}
```
_Note: Here I've used
a [sample prompt](https://github.com/ollama4j/ollama4j/blob/main/src/main/resources/sample-db-prompt-template.txt)
containing a database schema from within this library for demonstration purposes._
You'd then get a response from the model:
```sql
SELECT customers.name
FROM sales
JOIN customers ON sales.customer_id = customers.customer_id
GROUP BY customers.name;
```

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---
# Prompt Builder
This is designed for prompt engineering. It allows you to easily build the prompt text for zero-shot, one-shot, few-shot
inferences.
```java
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.models.response.OllamaResult;
import io.github.ollama4j.types.OllamaModelType;
import io.github.ollama4j.utils.OptionsBuilder;
import io.github.ollama4j.utils.PromptBuilder;
public class Main {
public static void main(String[] args) throws Exception {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
ollamaAPI.setRequestTimeoutSeconds(10);
String model = OllamaModelType.PHI;
PromptBuilder promptBuilder =
new PromptBuilder()
.addLine("You are an expert coder and understand different programming languages.")
.addLine("Given a question, answer ONLY with code.")
.addLine("Produce clean, formatted and indented code in markdown format.")
.addLine(
"DO NOT include ANY extra text apart from code. Follow this instruction very strictly!")
.addLine("If there's any additional information you want to add, use comments within code.")
.addLine("Answer only in the programming language that has been asked for.")
.addSeparator()
.addLine("Example: Sum 2 numbers in Python")
.addLine("Answer:")
.addLine("```python")
.addLine("def sum(num1: int, num2: int) -> int:")
.addLine(" return num1 + num2")
.addLine("```")
.addSeparator()
.add("How do I read a file in Go and print its contents to stdout?");
boolean raw = false;
OllamaResult response = ollamaAPI.generate(model, promptBuilder.build(), raw, new OptionsBuilder().build());
System.out.println(response.getResponse());
}
}
```
You will get a response similar to:
```go
package main
import (
"fmt"
"io/ioutil"
)
func readFile(fileName string) {
file, err := ioutil.ReadFile(fileName)
if err != nil {
fmt.Fprintln(os.Stderr, "Error reading file:", err.Error())
return
}
f, _ := ioutil.ReadFile("file.txt")
if f != nil {
fmt.Println(f.String())
}
}
```

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{
"label": "APIs - Model Management",
"position": 2,
"link": {
"type": "generated-index",
"description": "Details of APIs to manage LLMs."
}
}

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---
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---
# Create Model
This API lets you create a custom model on the Ollama server.
### Create a model from an existing Modelfile in the Ollama server
```java title="CreateModel.java"
import io.github.ollama4j.OllamaAPI;
public class CreateModel {
public static void main(String[] args) {
String host = "http://localhost:11434/";
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.");
}
}
```
Once created, you can see it when you use [list models](./list-models) API.
### Example of a `Modelfile`
```
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
# 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`
```modelfile
# comment
INSTRUCTION arguments
```
| 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
The `PARAMETER` instruction defines a parameter that can be set when the model is run.
| 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 |
#### 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

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# Delete Model
This API lets you create a delete a model from the Ollama server.
```java title="DeleteModel.java"
import io.github.ollama4j.OllamaAPI;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
ollamaAPI.setVerbose(false);
ollamaAPI.deleteModel("mycustommodel", true);
}
}
```
Once deleted, you can verify it using [list models](./list-models) API.

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# List Models
This API lets you list available models on the Ollama server.
```java title="ListModels.java"
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.models.response.Model;
import java.util.List;
public class ListModels {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
List<Model> models = ollamaAPI.listModels();
models.forEach(model -> System.out.println(model.getName()));
}
}
```
If you have any models already downloaded on Ollama server, you would have them listed as follows:
```bash
llama2:latest
sqlcoder:latest
```

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# Pull Model
This API lets you pull a model on the Ollama server.
```java title="PullModel.java"
import io.github.ollama4j.OllamaAPI;
import io.github.ollama4j.types.OllamaModelType;
public class Main {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
ollamaAPI.pullModel(OllamaModelType.LLAMA2);
}
}
```
Once downloaded, you can see them when you use [list models](./list-models) API.

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---
# Introduction
# Tutorial Intro
Let's get started with **Ollama4j**.
## 🦙 What is Ollama?
[Ollama](https://ollama.ai/) is an advanced AI tool that allows users to easily set up and run large language models
locally (in CPU and GPU
modes). With Ollama, users can leverage powerful language models such as Llama 2 and even customize and create their own
models.
## 👨‍💻 Why Ollama4j?
Ollama4j was built for the simple purpose of integrating Ollama with Java applications.
```mermaid
flowchart LR
o4j[Ollama4j]
o[Ollama Server]
o4j -->|Communicates with| o;
m[Models]
p[Your Java Project]
subgraph Your Java Environment
direction TB
p -->|Uses| o4j
end
subgraph Ollama Setup
direction TB
o -->|Manages| m
end
```
Let's discover **Docusaurus in less than 5 minutes**.
## Getting Started
Get started by **creating a new site**.
Or **try Docusaurus immediately** with **[docusaurus.new](https://docusaurus.new)**.
### What you'll need
- **[Ollama](https://ollama.ai/download)**
- **[Oracle JDK](https://www.oracle.com/java/technologies/javase/jdk11-archive-downloads.html)** or
**[Open JDK](https://jdk.java.net/archive/)** 11.0 or above.
- **[Maven](https://maven.apache.org/download.cgi)**
- [Node.js](https://nodejs.org/en/download/) version 18.0 or above:
- When installing Node.js, you are recommended to check all checkboxes related to dependencies.
### Start Ollama server
## Generate a new site
The easiest way of getting started with Ollama server is with [Docker](https://docs.docker.com/get-started/overview/).
But if you choose to run the
Ollama server directly, **[download](https://ollama.ai/download)** the distribution of your choice
and follow the installation process.
Generate a new Docusaurus site using the **classic template**.
#### With Docker
##### Run in CPU mode:
The classic template will automatically be added to your project after you run the command:
```bash
docker run -it -v ~/ollama:/root/.ollama -p 11434:11434 ollama/ollama
npm init docusaurus@latest my-website classic
```
##### Run in GPU mode:
You can type this command into Command Prompt, Powershell, Terminal, or any other integrated terminal of your code editor.
The command also installs all necessary dependencies you need to run Docusaurus.
## Start your site
Run the development server:
```bash
docker run -it --gpus=all -v ~/ollama:/root/.ollama -p 11434:11434 ollama/ollama
cd my-website
npm run start
```
You can type this command into Command Prompt, Powershell, Terminal, or any other integrated
terminal of your code editor.
The `cd` command changes the directory you're working with. In order to work with your newly created Docusaurus site, you'll need to navigate the terminal there.
The command runs the Ollama server locally at **http://localhost:11434/**.
The `npm run start` command builds your website locally and serves it through a development server, ready for you to view at http://localhost:3000/.
### Setup your project
Get started by **creating a new Maven project** on your favorite IDE.
Add the dependency to your project's `pom.xml`.
```xml
<dependency>
<groupId>io.github.ollama4j</groupId>
<artifactId>ollama4j</artifactId>
<version>1.0.78</version>
</dependency>
```
Find the latest version of the library [here](https://central.sonatype.com/artifact/io.github.ollama4j/ollama4j).
You might want to include an implementation of [SL4J](https://www.slf4j.org/) logger in your `pom.xml` file. For
example,
Use `slf4j-jdk14` implementation:
```xml
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-jdk14</artifactId>
<version>2.0.9</version> <!--Replace with appropriate version-->
</dependency>
```
or use `logback-classic` implementation:
```xml
<dependency>
<groupId>ch.qos.logback</groupId>
<artifactId>logback-classic</artifactId>
<version>1.3.11</version> <!--Replace with appropriate version-->
</dependency>
```
or use other suitable implementations.
Create a new Java class in your project and add this code.
```java
import io.github.ollama4j.OllamaAPI;
public class OllamaAPITest {
public static void main(String[] args) {
OllamaAPI ollamaAPI = new OllamaAPI();
boolean isOllamaServerReachable = ollamaAPI.ping();
System.out.println("Is Ollama server running: " + isOllamaServerReachable);
}
}
```
This uses the default Ollama host as `http://localhost:11434`.
Specify a different Ollama host that you want to connect to.
```java
import io.github.ollama4j.OllamaAPI;
public class OllamaAPITest {
public static void main(String[] args) {
String host = "http://localhost:11434/";
OllamaAPI ollamaAPI = new OllamaAPI(host);
ollamaAPI.setVerbose(true);
boolean isOllamaServerReachable = ollamaAPI.ping();
System.out.println("Is Ollama server running: " + isOllamaServerReachable);
}
}
```
Open `docs/intro.md` (this page) and edit some lines: the site **reloads automatically** and displays your changes.

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@ -0,0 +1,8 @@
{
"label": "Tutorial - Basics",
"position": 2,
"link": {
"type": "generated-index",
"description": "5 minutes to learn the most important Docusaurus concepts."
}
}

View File

@ -0,0 +1,23 @@
---
sidebar_position: 6
---
# Congratulations!
You have just learned the **basics of Docusaurus** and made some changes to the **initial template**.
Docusaurus has **much more to offer**!
Have **5 more minutes**? Take a look at **[versioning](../tutorial-extras/manage-docs-versions.md)** and **[i18n](../tutorial-extras/translate-your-site.md)**.
Anything **unclear** or **buggy** in this tutorial? [Please report it!](https://github.com/facebook/docusaurus/discussions/4610)
## What's next?
- Read the [official documentation](https://docusaurus.io/)
- Modify your site configuration with [`docusaurus.config.js`](https://docusaurus.io/docs/api/docusaurus-config)
- Add navbar and footer items with [`themeConfig`](https://docusaurus.io/docs/api/themes/configuration)
- Add a custom [Design and Layout](https://docusaurus.io/docs/styling-layout)
- Add a [search bar](https://docusaurus.io/docs/search)
- Find inspirations in the [Docusaurus showcase](https://docusaurus.io/showcase)
- Get involved in the [Docusaurus Community](https://docusaurus.io/community/support)

View File

@ -0,0 +1,34 @@
---
sidebar_position: 3
---
# Create a Blog Post
Docusaurus creates a **page for each blog post**, but also a **blog index page**, a **tag system**, an **RSS** feed...
## Create your first Post
Create a file at `blog/2021-02-28-greetings.md`:
```md title="blog/2021-02-28-greetings.md"
---
slug: greetings
title: Greetings!
authors:
- name: Joel Marcey
title: Co-creator of Docusaurus 1
url: https://github.com/JoelMarcey
image_url: https://github.com/JoelMarcey.png
- name: Sébastien Lorber
title: Docusaurus maintainer
url: https://sebastienlorber.com
image_url: https://github.com/slorber.png
tags: [greetings]
---
Congratulations, you have made your first post!
Feel free to play around and edit this post as much you like.
```
A new blog post is now available at [http://localhost:3000/blog/greetings](http://localhost:3000/blog/greetings).

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@ -0,0 +1,57 @@
---
sidebar_position: 2
---
# Create a Document
Documents are **groups of pages** connected through:
- a **sidebar**
- **previous/next navigation**
- **versioning**
## Create your first Doc
Create a Markdown file at `docs/hello.md`:
```md title="docs/hello.md"
# Hello
This is my **first Docusaurus document**!
```
A new document is now available at [http://localhost:3000/docs/hello](http://localhost:3000/docs/hello).
## Configure the Sidebar
Docusaurus automatically **creates a sidebar** from the `docs` folder.
Add metadata to customize the sidebar label and position:
```md title="docs/hello.md" {1-4}
---
sidebar_label: 'Hi!'
sidebar_position: 3
---
# Hello
This is my **first Docusaurus document**!
```
It is also possible to create your sidebar explicitly in `sidebars.js`:
```js title="sidebars.js"
export default {
tutorialSidebar: [
'intro',
// highlight-next-line
'hello',
{
type: 'category',
label: 'Tutorial',
items: ['tutorial-basics/create-a-document'],
},
],
};
```

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@ -0,0 +1,43 @@
---
sidebar_position: 1
---
# Create a Page
Add **Markdown or React** files to `src/pages` to create a **standalone page**:
- `src/pages/index.js``localhost:3000/`
- `src/pages/foo.md``localhost:3000/foo`
- `src/pages/foo/bar.js``localhost:3000/foo/bar`
## Create your first React Page
Create a file at `src/pages/my-react-page.js`:
```jsx title="src/pages/my-react-page.js"
import React from 'react';
import Layout from '@theme/Layout';
export default function MyReactPage() {
return (
<Layout>
<h1>My React page</h1>
<p>This is a React page</p>
</Layout>
);
}
```
A new page is now available at [http://localhost:3000/my-react-page](http://localhost:3000/my-react-page).
## Create your first Markdown Page
Create a file at `src/pages/my-markdown-page.md`:
```mdx title="src/pages/my-markdown-page.md"
# My Markdown page
This is a Markdown page
```
A new page is now available at [http://localhost:3000/my-markdown-page](http://localhost:3000/my-markdown-page).

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@ -0,0 +1,31 @@
---
sidebar_position: 5
---
# Deploy your site
Docusaurus is a **static-site-generator** (also called **[Jamstack](https://jamstack.org/)**).
It builds your site as simple **static HTML, JavaScript and CSS files**.
## Build your site
Build your site **for production**:
```bash
npm run build
```
The static files are generated in the `build` folder.
## Deploy your site
Test your production build locally:
```bash
npm run serve
```
The `build` folder is now served at [http://localhost:3000/](http://localhost:3000/).
You can now deploy the `build` folder **almost anywhere** easily, **for free** or very small cost (read the **[Deployment Guide](https://docusaurus.io/docs/deployment)**).

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@ -0,0 +1,150 @@
---
sidebar_position: 4
---
# Markdown Features
Docusaurus supports **[Markdown](https://daringfireball.net/projects/markdown/syntax)** and a few **additional features**.
## Front Matter
Markdown documents have metadata at the top called [Front Matter](https://jekyllrb.com/docs/front-matter/):
```text title="my-doc.md"
// highlight-start
---
id: my-doc-id
title: My document title
description: My document description
slug: /my-custom-url
---
// highlight-end
## Markdown heading
Markdown text with [links](./hello.md)
```
## Links
Regular Markdown links are supported, using url paths or relative file paths.
```md
Let's see how to [Create a page](/create-a-page).
```
```md
Let's see how to [Create a page](./create-a-page.md).
```
**Result:** Let's see how to [Create a page](./create-a-page.md).
## Images
Regular Markdown images are supported.
You can use absolute paths to reference images in the static directory (`static/img/docusaurus.png`):
```md
![Docusaurus logo](/img/docusaurus.png)
```
![Docusaurus logo](/img/docusaurus.png)
You can reference images relative to the current file as well. This is particularly useful to colocate images close to the Markdown files using them:
```md
![Docusaurus logo](./img/docusaurus.png)
```
## Code Blocks
Markdown code blocks are supported with Syntax highlighting.
```jsx title="src/components/HelloDocusaurus.js"
function HelloDocusaurus() {
return (
<h1>Hello, Docusaurus!</h1>
)
}
```
```jsx title="src/components/HelloDocusaurus.js"
function HelloDocusaurus() {
return <h1>Hello, Docusaurus!</h1>;
}
```
## Admonitions
Docusaurus has a special syntax to create admonitions and callouts:
:::tip My tip
Use this awesome feature option
:::
:::danger Take care
This action is dangerous
:::
:::tip My tip
Use this awesome feature option
:::
:::danger Take care
This action is dangerous
:::
## MDX and React Components
[MDX](https://mdxjs.com/) can make your documentation more **interactive** and allows using any **React components inside Markdown**:
```jsx
export const Highlight = ({children, color}) => (
<span
style={{
backgroundColor: color,
borderRadius: '20px',
color: '#fff',
padding: '10px',
cursor: 'pointer',
}}
onClick={() => {
alert(`You clicked the color ${color} with label ${children}`)
}}>
{children}
</span>
);
This is <Highlight color="#25c2a0">Docusaurus green</Highlight> !
This is <Highlight color="#1877F2">Facebook blue</Highlight> !
```
export const Highlight = ({children, color}) => (
<span
style={{
backgroundColor: color,
borderRadius: '20px',
color: '#fff',
padding: '10px',
cursor: 'pointer',
}}
onClick={() => {
alert(`You clicked the color ${color} with label ${children}`);
}}>
{children}
</span>
);
This is <Highlight color="#25c2a0">Docusaurus green</Highlight> !
This is <Highlight color="#1877F2">Facebook blue</Highlight> !

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@ -0,0 +1,7 @@
{
"label": "Tutorial - Extras",
"position": 3,
"link": {
"type": "generated-index"
}
}

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@ -0,0 +1,55 @@
---
sidebar_position: 1
---
# Manage Docs Versions
Docusaurus can manage multiple versions of your docs.
## Create a docs version
Release a version 1.0 of your project:
```bash
npm run docusaurus docs:version 1.0
```
The `docs` folder is copied into `versioned_docs/version-1.0` and `versions.json` is created.
Your docs now have 2 versions:
- `1.0` at `http://localhost:3000/docs/` for the version 1.0 docs
- `current` at `http://localhost:3000/docs/next/` for the **upcoming, unreleased docs**
## Add a Version Dropdown
To navigate seamlessly across versions, add a version dropdown.
Modify the `docusaurus.config.js` file:
```js title="docusaurus.config.js"
export default {
themeConfig: {
navbar: {
items: [
// highlight-start
{
type: 'docsVersionDropdown',
},
// highlight-end
],
},
},
};
```
The docs version dropdown appears in your navbar:
![Docs Version Dropdown](./img/docsVersionDropdown.png)
## Update an existing version
It is possible to edit versioned docs in their respective folder:
- `versioned_docs/version-1.0/hello.md` updates `http://localhost:3000/docs/hello`
- `docs/hello.md` updates `http://localhost:3000/docs/next/hello`

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@ -0,0 +1,88 @@
---
sidebar_position: 2
---
# Translate your site
Let's translate `docs/intro.md` to French.
## Configure i18n
Modify `docusaurus.config.js` to add support for the `fr` locale:
```js title="docusaurus.config.js"
export default {
i18n: {
defaultLocale: 'en',
locales: ['en', 'fr'],
},
};
```
## Translate a doc
Copy the `docs/intro.md` file to the `i18n/fr` folder:
```bash
mkdir -p i18n/fr/docusaurus-plugin-content-docs/current/
cp docs/intro.md i18n/fr/docusaurus-plugin-content-docs/current/intro.md
```
Translate `i18n/fr/docusaurus-plugin-content-docs/current/intro.md` in French.
## Start your localized site
Start your site on the French locale:
```bash
npm run start -- --locale fr
```
Your localized site is accessible at [http://localhost:3000/fr/](http://localhost:3000/fr/) and the `Getting Started` page is translated.
:::caution
In development, you can only use one locale at a time.
:::
## Add a Locale Dropdown
To navigate seamlessly across languages, add a locale dropdown.
Modify the `docusaurus.config.js` file:
```js title="docusaurus.config.js"
export default {
themeConfig: {
navbar: {
items: [
// highlight-start
{
type: 'localeDropdown',
},
// highlight-end
],
},
},
};
```
The locale dropdown now appears in your navbar:
![Locale Dropdown](./img/localeDropdown.png)
## Build your localized site
Build your site for a specific locale:
```bash
npm run build -- --locale fr
```
Or build your site to include all the locales at once:
```bash
npm run build
```

View File

@ -8,143 +8,131 @@ import {themes as prismThemes} from 'prism-react-renderer';
/** @type {import('@docusaurus/types').Config} */
const config = {
title: 'Ollama4j',
tagline: 'Java library for interacting with Ollama.',
favicon: 'img/favicon.ico',
title: 'Ollama4J',
tagline: 'Java library for interacting with Ollama API.',
favicon: 'img/favicon.ico',
// Set the production url of your site here
url: 'https://your-docusaurus-site.example.com',
// Set the /<baseUrl>/ pathname under which your site is served
// For GitHub pages deployment, it is often '/<projectName>/'
baseUrl: '/ollama4j/',
// Set the production url of your site here
url: 'https://your-docusaurus-site.example.com',
// Set the /<baseUrl>/ pathname under which your site is served
// For GitHub pages deployment, it is often '/<projectName>/'
baseUrl: '/ollama4j/',
// GitHub pages deployment config.
// If you aren't using GitHub pages, you don't need these.
organizationName: 'ollama4j', // Usually your GitHub org/user name.
projectName: 'ollama4j', // Usually your repo name.
// GitHub pages deployment config.
// If you aren't using GitHub pages, you don't need these.
organizationName: 'amithkoujalgi', // Usually your GitHub org/user name.
projectName: 'ollama4j', // Usually your repo name.
onBrokenLinks: 'throw',
onBrokenMarkdownLinks: 'warn',
onBrokenLinks: 'throw',
onBrokenMarkdownLinks: 'warn',
// Even if you don't use internationalization, you can use this field to set
// useful metadata like html lang. For example, if your site is Chinese, you
// may want to replace "en" with "zh-Hans".
i18n: {
defaultLocale: 'en',
locales: ['en'],
},
// Even if you don't use internationalization, you can use this field to set
// useful metadata like html lang. For example, if your site is Chinese, you
// may want to replace "en" with "zh-Hans".
i18n: {
defaultLocale: 'en',
locales: ['en'],
},
presets: [
[
'classic',
/** @type {import('@docusaurus/preset-classic').Options} */
({
docs: {
path: 'docs',
routeBasePath: '', // change this to any URL route you'd want. For example: `home` - if you want /home/intro.
sidebarPath: './sidebars.js',
// Please change this to your repo.
// Remove this to remove the "edit this page" links.
editUrl:
'https://github.com/ollama4j/ollama4j/blob/main/docs',
},
blog: {
showReadingTime: true,
// Please change this to your repo.
// Remove this to remove the "edit this page" links.
editUrl:
'https://github.com/ollama4j/ollama4j/blob/main/docs',
},
theme: {
customCss: './src/css/custom.css',
},
gtag: {
trackingID: 'G-G7FLH6FNDC',
anonymizeIP: false,
},
}),
],
presets: [
[
'classic',
/** @type {import('@docusaurus/preset-classic').Options} */
({
docs: {
sidebarPath: './sidebars.js',
// Please change this to your repo.
// Remove this to remove the "edit this page" links.
editUrl:
'https://github.com/facebook/docusaurus/tree/main/packages/create-docusaurus/templates/shared/',
},
blog: {
showReadingTime: true,
// Please change this to your repo.
// Remove this to remove the "edit this page" links.
editUrl:
'https://github.com/facebook/docusaurus/tree/main/packages/create-docusaurus/templates/shared/',
},
theme: {
customCss: './src/css/custom.css',
},
}),
],
],
themeConfig:
themeConfig:
/** @type {import('@docusaurus/preset-classic').ThemeConfig} */
({
// Replace with your project's social card
image: 'img/docusaurus-social-card.jpg',
navbar: {
title: 'Ollama4j',
logo: {
alt: 'Ollama4j Logo',
src: 'img/logo.svg',
},
items: [
{
type: 'docSidebar',
sidebarId: 'tutorialSidebar',
position: 'left',
label: 'Docs',
},
{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'},
{
href: 'https://github.com/ollama4j/ollama4j',
label: 'GitHub',
position: 'right',
},
],
},
footer: {
style: 'dark',
links: [
{
title: 'Docs',
items: [
{
label: 'Tutorial',
to: '/intro',
},
],
},
{
title: 'Community',
items: [
{
label: 'Stack Overflow',
href: 'https://stackoverflow.com/questions/tagged/ollama4j',
},
{
label: 'Twitter',
href: 'https://twitter.com/ollama4j',
},
],
},
{
title: 'More',
items: [
{
label: 'Blog',
to: '/blog',
},
{
label: 'GitHub',
href: 'https://github.com/ollama4j/ollama4j',
},
],
},
],
copyright: `Ollama4j Documentation ${new Date().getFullYear()}. Built with Docusaurus.`,
},
prism: {
theme: prismThemes.github,
darkTheme: prismThemes.dracula,
additionalLanguages: ['java'],
},
}),
markdown: {
mermaid: true,
},
themes: ['@docusaurus/theme-mermaid']
({
// Replace with your project's social card
image: 'img/docusaurus-social-card.jpg',
navbar: {
title: 'Ollama4J',
logo: {
alt: 'Ollama4J Logo',
src: 'img/logo.svg',
},
items: [
{
type: 'docSidebar',
sidebarId: 'tutorialSidebar',
position: 'left',
label: 'Tutorial',
},
{to: '/blog', label: 'Blog', position: 'left'},
{to: 'https://github.com/amithkoujalgi/ollama4j', label: 'Javadoc', position: 'left'},
{
href: 'https://github.com/amithkoujalgi/ollama4j',
label: 'GitHub',
position: 'right',
},
],
},
footer: {
style: 'dark',
links: [
{
title: 'Docs',
items: [
{
label: 'Tutorial',
to: '/docs/intro',
},
],
},
{
title: 'Community',
items: [
{
label: 'Stack Overflow',
href: 'https://stackoverflow.com/questions/tagged/ollama4j',
},
{
label: 'Twitter',
href: 'https://twitter.com/ollama4j',
},
],
},
{
title: 'More',
items: [
{
label: 'Blog',
to: '/blog',
},
{
label: 'GitHub',
href: 'https://github.com/amithkoujalgi/ollama4j',
},
],
},
],
copyright: `Ollama4J Documentation ${new Date().getFullYear()}. Built with Docusaurus.`,
},
prism: {
theme: prismThemes.github,
darkTheme: prismThemes.dracula,
},
}),
};
export default config;

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View File

@ -14,10 +14,8 @@
"write-heading-ids": "docusaurus write-heading-ids"
},
"dependencies": {
"@docusaurus/core": "^3.4.0",
"@docusaurus/plugin-google-gtag": "^3.4.0",
"@docusaurus/preset-classic": "^3.4.0",
"@docusaurus/theme-mermaid": "^3.4.0",
"@docusaurus/core": "3.0.1",
"@docusaurus/preset-classic": "3.0.1",
"@mdx-js/react": "^3.0.0",
"clsx": "^2.0.0",
"prism-react-renderer": "^2.3.0",
@ -25,8 +23,8 @@
"react-dom": "^18.0.0"
},
"devDependencies": {
"@docusaurus/module-type-aliases": "^3.4.0",
"@docusaurus/types": "^3.4.0"
"@docusaurus/module-type-aliases": "3.0.1",
"@docusaurus/types": "3.0.1"
},
"browserslist": {
"production": [

0
docs/run.sh Executable file → Normal file
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@ -6,35 +6,25 @@
/* You can override the default Infima variables here. */
:root {
--ifm-color-primary: #2e8555;
--ifm-color-primary-dark: #29784c;
--ifm-color-primary-darker: #277148;
--ifm-color-primary-darkest: #205d3b;
--ifm-color-primary-light: #33925d;
--ifm-color-primary-lighter: #359962;
--ifm-color-primary-lightest: #3cad6e;
--ifm-code-font-size: 95%;
--docusaurus-highlighted-code-line-bg: rgba(0, 0, 0, 0.1);
--ifm-color-primary: #2e8555;
--ifm-color-primary-dark: #29784c;
--ifm-color-primary-darker: #277148;
--ifm-color-primary-darkest: #205d3b;
--ifm-color-primary-light: #33925d;
--ifm-color-primary-lighter: #359962;
--ifm-color-primary-lightest: #3cad6e;
--ifm-code-font-size: 95%;
--docusaurus-highlighted-code-line-bg: rgba(0, 0, 0, 0.1);
}
/* For readability concerns, you should choose a lighter palette in dark mode. */
[data-theme='dark'] {
--ifm-color-primary: #25c2a0;
--ifm-color-primary-dark: #21af90;
--ifm-color-primary-darker: #1fa588;
--ifm-color-primary-darkest: #1a8870;
--ifm-color-primary-light: #29d5b0;
--ifm-color-primary-lighter: #32d8b4;
--ifm-color-primary-lightest: #4fddbf;
--docusaurus-highlighted-code-line-bg: rgba(0, 0, 0, 0.3);
--ifm-color-primary: #25c2a0;
--ifm-color-primary-dark: #21af90;
--ifm-color-primary-darker: #1fa588;
--ifm-color-primary-darkest: #1a8870;
--ifm-color-primary-light: #29d5b0;
--ifm-color-primary-lighter: #32d8b4;
--ifm-color-primary-lightest: #4fddbf;
--docusaurus-highlighted-code-line-bg: rgba(0, 0, 0, 0.3);
}
article > header > h1 {
font-size: 2rem !important;
}
div > h1,
header > h1,
h2 > a {
font-size: 2rem !important;
}

View File

@ -8,33 +8,36 @@ import Heading from '@theme/Heading';
import styles from './index.module.css';
function HomepageHeader() {
const {siteConfig} = useDocusaurusContext();
return (<header className={clsx('hero hero--primary', styles.heroBanner)}>
<div className="container">
<Heading as="h1" className="hero__title">
{siteConfig.title}
</Heading>
<img src="img/logo.svg" alt="Ollama4j Logo" className={styles.logo} style={{maxWidth: '20vh'}}/>
<p className="hero__subtitle">{siteConfig.tagline}</p>
<div className={styles.buttons}>
<Link
className="button button--secondary button--lg"
to="/intro">
Getting Started
</Link>
</div>
const {siteConfig} = useDocusaurusContext();
return (
<header className={clsx('hero hero--primary', styles.heroBanner)}>
<div className="container">
<Heading as="h1" className="hero__title">
{siteConfig.title}
</Heading>
<p className="hero__subtitle">{siteConfig.tagline}</p>
<div className={styles.buttons}>
<Link
className="button button--secondary button--lg"
to="/docs/intro">
Getting Started
</Link>
</div>
</header>);
</div>
</header>
);
}
export default function Home() {
const {siteConfig} = useDocusaurusContext();
return (<Layout
title={`Hello from ${siteConfig.title}`}
description="Description will go into a meta tag in <head />">
<HomepageHeader/>
<main>
<HomepageFeatures/>
</main>
</Layout>);
const {siteConfig} = useDocusaurusContext();
return (
<Layout
title={`Hello from ${siteConfig.title}`}
description="Description will go into a meta tag in <head />">
<HomepageHeader />
<main>
<HomepageFeatures />
</main>
</Layout>
);
}

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167
pom.xml
View File

@ -1,16 +1,14 @@
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>io.github.ollama4j</groupId>
<groupId>io.github.amithkoujalgi</groupId>
<artifactId>ollama4j</artifactId>
<version>ollama4j-revision</version>
<version>1.0.28-SNAPSHOT</version>
<name>Ollama4j</name>
<description>Java library for interacting with Ollama API.</description>
<url>https://github.com/ollama4j/ollama4j</url>
<packaging>jar</packaging>
<url>https://github.com/amithkoujalgi/ollama4j</url>
<properties>
<maven.compiler.source>11</maven.compiler.source>
@ -33,15 +31,15 @@
<licenses>
<license>
<name>MIT License</name>
<url>https://raw.githubusercontent.com/ollama4j/ollama4j/main/LICENSE</url>
<url>https://raw.githubusercontent.com/amithkoujalgi/ollama4j/main/LICENSE</url>
</license>
</licenses>
<scm>
<connection>scm:git:git@github.com:ollama4j/ollama4j.git</connection>
<developerConnection>scm:git:https://github.com/ollama4j/ollama4j.git</developerConnection>
<url>https://github.com/ollama4j/ollama4j</url>
<tag>ollama4j-revision</tag>
<connection>scm:git:git@github.com:amithkoujalgi/ollama4j.git</connection>
<developerConnection>scm:git:https://github.com/amithkoujalgi/ollama4j.git</developerConnection>
<url>https://github.com/amithkoujalgi/ollama4j</url>
<tag>v1.0.16</tag>
</scm>
<build>
@ -72,7 +70,27 @@
</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>-->
<!-- &lt;!&ndash; This is necessary for gpg to not try to use the pinentry programs &ndash;&gt;-->
<!-- <gpgArguments>-->
<!-- <arg>&#45;&#45;pinentry-mode</arg>-->
<!-- <arg>loopback</arg>-->
<!-- </gpgArguments>-->
<!-- </configuration>-->
<!-- </execution>-->
<!-- </executions>-->
<!-- </plugin>-->
<!-- Surefire Plugin for Unit Tests -->
<plugin>
<groupId>org.apache.maven.plugins</groupId>
@ -81,7 +99,7 @@
<configuration>
<skipTests>${skipUnitTests}</skipTests>
<includes>
<include>**/unittests/**/*.java</include>
<include>**/unittests/*.java</include>
</includes>
</configuration>
</plugin>
@ -109,33 +127,18 @@
</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>
</execution>
</executions>
<artifactId>maven-release-plugin</artifactId>
<version>3.0.1</version>
<configuration>
<!-- <goals>install</goals>-->
<tagNameFormat>v@{project.version}</tagNameFormat>
</configuration>
</plugin>
</plugins>
</build>
<repositories>
<repository>
<id>gitea</id>
<url>https://gitea.seeseepuff.be/api/packages/seeseemelk/maven</url>
</repository>
</repositories>
<dependencies>
<dependency>
<groupId>org.projectlombok</groupId>
@ -146,17 +149,12 @@
<dependency>
<groupId>com.fasterxml.jackson.core</groupId>
<artifactId>jackson-databind</artifactId>
<version>2.17.1</version>
</dependency>
<dependency>
<groupId>com.fasterxml.jackson.datatype</groupId>
<artifactId>jackson-datatype-jsr310</artifactId>
<version>2.17.1</version>
<version>2.15.3</version>
</dependency>
<dependency>
<groupId>ch.qos.logback</groupId>
<artifactId>logback-classic</artifactId>
<version>1.5.6</version>
<version>1.3.11</version>
<scope>test</scope>
</dependency>
<dependency>
@ -176,52 +174,20 @@
<version>4.1.0</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.json</groupId>
<artifactId>json</artifactId>
<version>20240205</version>
<scope>test</scope>
</dependency>
</dependencies>
<distributionManagement>
<snapshotRepository>
<id>gitea</id>
<url>https://gitea.seeseepuff.be/api/packages/seeseemelk/maven</url>
<id>ossrh</id>
<url>https://s01.oss.sonatype.org/content/repositories/snapshots</url>
</snapshotRepository>
<repository>
<id>gitea</id>
<url>https://gitea.seeseepuff.be/api/packages/seeseemelk/maven</url>
<id>ossrh</id>
<url>https://s01.oss.sonatype.org/service/local/staging/deploy/maven2</url>
</repository>
</distributionManagement>
<profiles>
<profile>
<id>ossrh</id>
<activation>
<activeByDefault>true</activeByDefault>
</activation>
<properties>
<gpg.executable>gpg2</gpg.executable>
<test.env>unit</test.env>
<skipUnitTests>false</skipUnitTests>
<skipIntegrationTests>true</skipIntegrationTests>
</properties>
<build>
<plugins>
<plugin>
<groupId>org.sonatype.central</groupId>
<artifactId>central-publishing-maven-plugin</artifactId>
<version>0.5.0</version>
<extensions>true</extensions>
<configuration>
<publishingServerId>mvn-repo-id</publishingServerId>
<autoPublish>true</autoPublish>
</configuration>
</plugin>
</plugins>
</build>
</profile>
<profile>
<id>unit-tests</id>
<properties>
@ -230,31 +196,8 @@
<skipIntegrationTests>true</skipIntegrationTests>
</properties>
<activation>
<activeByDefault>false</activeByDefault>
<activeByDefault>true</activeByDefault>
</activation>
<build>
<plugins>
<plugin>
<groupId>org.jacoco</groupId>
<artifactId>jacoco-maven-plugin</artifactId>
<version>0.8.11</version>
<executions>
<execution>
<goals>
<goal>prepare-agent</goal>
</goals>
</execution>
<execution>
<id>report</id>
<phase>test</phase>
<goals>
<goal>report</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
</build>
</profile>
<profile>
<id>integration-tests</id>
@ -306,29 +249,9 @@
<autoReleaseAfterClose>true</autoReleaseAfterClose>
</configuration>
</plugin>
<plugin>
<groupId>org.jacoco</groupId>
<artifactId>jacoco-maven-plugin</artifactId>
<version>0.8.7</version>
<executions>
<execution>
<goals>
<goal>prepare-agent</goal>
</goals>
</execution>
<execution>
<id>report</id>
<phase>test</phase>
<goals>
<goal>report</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
</build>
</profile>
</profiles>
</project>
</project>

View File

@ -0,0 +1,432 @@
package io.github.amithkoujalgi.ollama4j.core;
import io.github.amithkoujalgi.ollama4j.core.exceptions.OllamaBaseException;
import io.github.amithkoujalgi.ollama4j.core.models.*;
import io.github.amithkoujalgi.ollama4j.core.models.request.CustomModelFileContentsRequest;
import io.github.amithkoujalgi.ollama4j.core.models.request.CustomModelFilePathRequest;
import io.github.amithkoujalgi.ollama4j.core.models.request.ModelEmbeddingsRequest;
import io.github.amithkoujalgi.ollama4j.core.models.request.ModelRequest;
import io.github.amithkoujalgi.ollama4j.core.utils.Utils;
import java.io.BufferedReader;
import java.io.ByteArrayOutputStream;
import java.io.File;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.net.URI;
import java.net.URISyntaxException;
import java.net.URL;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.nio.charset.StandardCharsets;
import java.nio.file.Files;
import java.time.Duration;
import java.util.ArrayList;
import java.util.Base64;
import java.util.List;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
/** The base Ollama API class. */
@SuppressWarnings("DuplicatedCode")
public class OllamaAPI {
private static final Logger logger = LoggerFactory.getLogger(OllamaAPI.class);
private final String host;
private long requestTimeoutSeconds = 3;
private boolean verbose = true;
/**
* Instantiates the Ollama API.
*
* @param host the host address of Ollama server
*/
public OllamaAPI(String host) {
if (host.endsWith("/")) {
this.host = host.substring(0, host.length() - 1);
} else {
this.host = host;
}
}
public void setRequestTimeoutSeconds(long requestTimeoutSeconds) {
this.requestTimeoutSeconds = requestTimeoutSeconds;
}
/**
* Set/unset logging of responses
*
* @param verbose true/false
*/
public void setVerbose(boolean verbose) {
this.verbose = verbose;
}
/**
* List available models from Ollama server.
*
* @return the list
*/
public List<Model> listModels()
throws OllamaBaseException, IOException, InterruptedException, URISyntaxException {
String url = this.host + "/api/tags";
HttpClient httpClient = HttpClient.newHttpClient();
HttpRequest httpRequest =
HttpRequest.newBuilder()
.uri(new URI(url))
.header("Accept", "application/json")
.header("Content-type", "application/json")
.timeout(Duration.ofSeconds(requestTimeoutSeconds))
.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, ListModelsResponse.class)
.getModels();
} else {
throw new OllamaBaseException(statusCode + " - " + responseString);
}
}
/**
* Pull a model on the Ollama server from the list of <a
* href="https://ollama.ai/library">available models</a>.
*
* @param modelName the name of the model
*/
public void pullModel(String modelName)
throws OllamaBaseException, IOException, URISyntaxException, InterruptedException {
String url = this.host + "/api/pull";
String jsonData = new ModelRequest(modelName).toString();
HttpRequest request =
HttpRequest.newBuilder()
.uri(new URI(url))
.POST(HttpRequest.BodyPublishers.ofString(jsonData))
.header("Accept", "application/json")
.header("Content-type", "application/json")
.timeout(Duration.ofSeconds(requestTimeoutSeconds))
.build();
HttpClient client = HttpClient.newHttpClient();
HttpResponse<InputStream> response =
client.send(request, HttpResponse.BodyHandlers.ofInputStream());
int statusCode = response.statusCode();
InputStream responseBodyStream = response.body();
String responseString = "";
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 (statusCode != 200) {
throw new OllamaBaseException(statusCode + " - " + responseString);
}
}
/**
* Gets model details from the Ollama server.
*
* @param modelName the model
* @return the model details
*/
public ModelDetail getModelDetails(String modelName)
throws IOException, OllamaBaseException, InterruptedException {
String url = this.host + "/api/show";
String jsonData = new ModelRequest(modelName).toString();
HttpRequest request =
HttpRequest.newBuilder()
.uri(URI.create(url))
.header("Accept", "application/json")
.header("Content-type", "application/json")
.timeout(Duration.ofSeconds(requestTimeoutSeconds))
.POST(HttpRequest.BodyPublishers.ofString(jsonData))
.build();
HttpClient client = HttpClient.newHttpClient();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
int statusCode = response.statusCode();
String responseBody = response.body();
if (statusCode == 200) {
return Utils.getObjectMapper().readValue(responseBody, ModelDetail.class);
} else {
throw new OllamaBaseException(statusCode + " - " + responseBody);
}
}
/**
* Create a custom model from a model file. Read more about custom model file creation <a
* href="https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md">here</a>.
*
* @param modelName the name of the custom model to be created.
* @param modelFilePath the path to model file that exists on the Ollama server.
*/
public void createModelWithFilePath(String modelName, String modelFilePath)
throws IOException, InterruptedException, OllamaBaseException {
String url = this.host + "/api/create";
String jsonData = new CustomModelFilePathRequest(modelName, modelFilePath).toString();
HttpRequest request =
HttpRequest.newBuilder()
.uri(URI.create(url))
.header("Accept", "application/json")
.header("Content-Type", "application/json")
.timeout(Duration.ofSeconds(requestTimeoutSeconds))
.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);
}
// FIXME: Ollama API returns HTTP status code 200 for model creation failure cases. Correct this
// if the issue is fixed in the Ollama API server.
if (responseString.contains("error")) {
throw new OllamaBaseException(responseString);
}
if (verbose) {
logger.info(responseString);
}
}
/**
* Create a custom model from a model file. Read more about custom model file creation <a
* href="https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md">here</a>.
*
* @param modelName the name of the custom model to be created.
* @param modelFileContents the path to model file that exists on the Ollama server.
*/
public void createModelWithModelFileContents(String modelName, String modelFileContents)
throws IOException, InterruptedException, OllamaBaseException {
String url = this.host + "/api/create";
String jsonData = new CustomModelFileContentsRequest(modelName, modelFileContents).toString();
HttpRequest request =
HttpRequest.newBuilder()
.uri(URI.create(url))
.header("Accept", "application/json")
.header("Content-Type", "application/json")
.timeout(Duration.ofSeconds(requestTimeoutSeconds))
.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.
*
* @param modelName the name of the model to be deleted.
* @param ignoreIfNotPresent - ignore errors if the specified model is not present on Ollama
* server.
*/
public void deleteModel(String modelName, boolean ignoreIfNotPresent)
throws IOException, InterruptedException, OllamaBaseException {
String url = this.host + "/api/delete";
String jsonData = new ModelRequest(modelName).toString();
HttpRequest request =
HttpRequest.newBuilder()
.uri(URI.create(url))
.method("DELETE", HttpRequest.BodyPublishers.ofString(jsonData, StandardCharsets.UTF_8))
.header("Accept", "application/json")
.header("Content-type", "application/json")
.timeout(Duration.ofSeconds(requestTimeoutSeconds))
.build();
HttpClient client = HttpClient.newHttpClient();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
int statusCode = response.statusCode();
String responseBody = response.body();
if (statusCode == 404 && responseBody.contains("model") && responseBody.contains("not found")) {
return;
}
if (statusCode != 200) {
throw new OllamaBaseException(statusCode + " - " + responseBody);
}
}
/**
* Generate embeddings for a given text from a model
*
* @param model name of model to generate embeddings from
* @param prompt text to generate embeddings for
* @return embeddings
*/
public List<Double> generateEmbeddings(String model, String prompt)
throws IOException, InterruptedException, OllamaBaseException {
String url = this.host + "/api/embeddings";
String jsonData = new ModelEmbeddingsRequest(model, prompt).toString();
HttpClient httpClient = HttpClient.newHttpClient();
HttpRequest request =
HttpRequest.newBuilder()
.uri(URI.create(url))
.header("Accept", "application/json")
.header("Content-type", "application/json")
.timeout(Duration.ofSeconds(requestTimeoutSeconds))
.POST(HttpRequest.BodyPublishers.ofString(jsonData))
.build();
HttpResponse<String> response = httpClient.send(request, HttpResponse.BodyHandlers.ofString());
int statusCode = response.statusCode();
String responseBody = response.body();
if (statusCode == 200) {
EmbeddingResponse embeddingResponse =
Utils.getObjectMapper().readValue(responseBody, EmbeddingResponse.class);
return embeddingResponse.getEmbedding();
} else {
throw new OllamaBaseException(statusCode + " - " + responseBody);
}
}
/**
* Ask a question to a model running on Ollama server. This is a sync/blocking call.
*
* @param model the ollama model to ask the question to
* @param promptText the prompt/question text
* @return OllamaResult - that includes response text and time taken for response
*/
public OllamaResult ask(String model, String promptText)
throws OllamaBaseException, IOException, InterruptedException {
OllamaRequestModel ollamaRequestModel = new OllamaRequestModel(model, promptText);
return askSync(ollamaRequestModel);
}
/**
* Ask a question to a model running on Ollama server and get a callback handle that can be used
* to check for status and get the response from the model later. This would be an
* async/non-blocking call.
*
* @param model the ollama model to ask the question to
* @param promptText the prompt/question text
* @return the ollama async result callback handle
*/
public OllamaAsyncResultCallback askAsync(String model, String promptText) {
OllamaRequestModel ollamaRequestModel = new OllamaRequestModel(model, promptText);
HttpClient httpClient = HttpClient.newHttpClient();
URI uri = URI.create(this.host + "/api/generate");
OllamaAsyncResultCallback ollamaAsyncResultCallback =
new OllamaAsyncResultCallback(httpClient, uri, ollamaRequestModel, requestTimeoutSeconds);
ollamaAsyncResultCallback.start();
return ollamaAsyncResultCallback;
}
/**
* With one or more image files, ask a question to a model running on Ollama server. This is a
* sync/blocking call.
*
* @param model the ollama model to ask the question to
* @param promptText the prompt/question text
* @param imageFiles the list of image files to use for the question
* @return OllamaResult - that includes response text and time taken for response
*/
public OllamaResult askWithImageFiles(String model, String promptText, List<File> imageFiles)
throws OllamaBaseException, IOException, InterruptedException {
List<String> images = new ArrayList<>();
for (File imageFile : imageFiles) {
images.add(encodeFileToBase64(imageFile));
}
OllamaRequestModel ollamaRequestModel = new OllamaRequestModel(model, promptText, images);
return askSync(ollamaRequestModel);
}
/**
* With one or more image URLs, ask a question to a model running on Ollama server. This is a
* sync/blocking call.
*
* @param model the ollama model to ask the question to
* @param promptText the prompt/question text
* @param imageURLs the list of image URLs to use for the question
* @return OllamaResult - that includes response text and time taken for response
*/
public OllamaResult askWithImageURLs(String model, String promptText, List<String> imageURLs)
throws OllamaBaseException, IOException, InterruptedException, URISyntaxException {
List<String> images = new ArrayList<>();
for (String imageURL : imageURLs) {
images.add(encodeByteArrayToBase64(loadImageBytesFromUrl(imageURL)));
}
OllamaRequestModel ollamaRequestModel = new OllamaRequestModel(model, promptText, images);
return askSync(ollamaRequestModel);
}
private static String encodeFileToBase64(File file) throws IOException {
return Base64.getEncoder().encodeToString(Files.readAllBytes(file.toPath()));
}
private static String encodeByteArrayToBase64(byte[] bytes) {
return Base64.getEncoder().encodeToString(bytes);
}
private static byte[] loadImageBytesFromUrl(String imageUrl)
throws IOException, URISyntaxException {
URL url = new URI(imageUrl).toURL();
try (InputStream in = url.openStream();
ByteArrayOutputStream out = new ByteArrayOutputStream()) {
byte[] buffer = new byte[1024];
int bytesRead;
while ((bytesRead = in.read(buffer)) != -1) {
out.write(buffer, 0, bytesRead);
}
return out.toByteArray();
}
}
private OllamaResult askSync(OllamaRequestModel ollamaRequestModel)
throws OllamaBaseException, IOException, InterruptedException {
long startTime = System.currentTimeMillis();
HttpClient httpClient = HttpClient.newHttpClient();
URI uri = URI.create(this.host + "/api/generate");
HttpRequest request =
HttpRequest.newBuilder(uri)
.POST(
HttpRequest.BodyPublishers.ofString(
Utils.getObjectMapper().writeValueAsString(ollamaRequestModel)))
.header("Content-Type", "application/json")
.timeout(Duration.ofSeconds(requestTimeoutSeconds))
.build();
HttpResponse<InputStream> response =
httpClient.send(request, HttpResponse.BodyHandlers.ofInputStream());
int statusCode = response.statusCode();
InputStream responseBodyStream = response.body();
StringBuilder responseBuffer = new StringBuilder();
try (BufferedReader reader =
new BufferedReader(new InputStreamReader(responseBodyStream, StandardCharsets.UTF_8))) {
String line;
while ((line = reader.readLine()) != null) {
if (statusCode == 404) {
OllamaErrorResponseModel ollamaResponseModel =
Utils.getObjectMapper().readValue(line, OllamaErrorResponseModel.class);
responseBuffer.append(ollamaResponseModel.getError());
} else {
OllamaResponseModel ollamaResponseModel =
Utils.getObjectMapper().readValue(line, OllamaResponseModel.class);
if (!ollamaResponseModel.isDone()) {
responseBuffer.append(ollamaResponseModel.getResponse());
}
}
}
}
if (statusCode != 200) {
throw new OllamaBaseException(responseBuffer.toString());
} else {
long endTime = System.currentTimeMillis();
return new OllamaResult(responseBuffer.toString().trim(), endTime - startTime, statusCode);
}
}
}

View File

@ -1,4 +1,4 @@
package io.github.ollama4j.exceptions;
package io.github.amithkoujalgi.ollama4j.core.exceptions;
public class OllamaBaseException extends Exception {

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@ -1,4 +1,4 @@
package io.github.ollama4j.models.embeddings;
package io.github.amithkoujalgi.ollama4j.core.models;
import com.fasterxml.jackson.annotation.JsonProperty;
@ -7,7 +7,7 @@ import lombok.Data;
@SuppressWarnings("unused")
@Data
public class OllamaEmbeddingResponseModel {
public class EmbeddingResponse {
@JsonProperty("embedding")
private List<Double> embedding;
}

View File

@ -1,7 +1,6 @@
package io.github.ollama4j.models.response;
package io.github.amithkoujalgi.ollama4j.core.models;
import java.util.List;
import lombok.Data;
@Data

View File

@ -1,21 +1,14 @@
package io.github.ollama4j.models.response;
import java.time.OffsetDateTime;
package io.github.amithkoujalgi.ollama4j.core.models;
import com.fasterxml.jackson.annotation.JsonProperty;
import com.fasterxml.jackson.core.JsonProcessingException;
import io.github.ollama4j.utils.Utils;
import lombok.Data;
@Data
public class Model {
private String name;
private String model;
@JsonProperty("modified_at")
private OffsetDateTime modifiedAt;
@JsonProperty("expires_at")
private OffsetDateTime expiresAt;
private String modifiedAt;
private String digest;
private long size;
@JsonProperty("details")
@ -40,13 +33,4 @@ public class Model {
return name.split(":")[1];
}
@Override
public String toString() {
try {
return Utils.getObjectMapper().writerWithDefaultPrettyPrinter().writeValueAsString(this);
} catch (JsonProcessingException e) {
throw new RuntimeException(e);
}
}
}

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@ -0,0 +1,20 @@
package io.github.amithkoujalgi.ollama4j.core.models;
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
import com.fasterxml.jackson.annotation.JsonProperty;
import java.util.Map;
import lombok.Data;
@Data
@JsonIgnoreProperties(ignoreUnknown = true)
public class ModelDetail {
private String license;
@JsonProperty("modelfile")
private String modelFile;
private String parameters;
private String template;
private String system;
private Map<String, String> details;
}

View File

@ -1,9 +1,7 @@
package io.github.ollama4j.models.response;
package io.github.amithkoujalgi.ollama4j.core.models;
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
@ -23,13 +21,4 @@ public class ModelMeta {
@JsonProperty("quantization_level")
private String quantizationLevel;
@Override
public String toString() {
try {
return Utils.getObjectMapper().writerWithDefaultPrettyPrinter().writeValueAsString(this);
} catch (JsonProcessingException e) {
throw new RuntimeException(e);
}
}
}

View File

@ -1,4 +1,4 @@
package io.github.ollama4j.models.response;
package io.github.amithkoujalgi.ollama4j.core.models;
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
import lombok.Data;

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@ -0,0 +1,155 @@
package io.github.amithkoujalgi.ollama4j.core.models;
import io.github.amithkoujalgi.ollama4j.core.exceptions.OllamaBaseException;
import io.github.amithkoujalgi.ollama4j.core.utils.Utils;
import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.nio.charset.StandardCharsets;
import java.time.Duration;
import java.util.LinkedList;
import java.util.Queue;
@SuppressWarnings("unused")
public class OllamaAsyncResultCallback extends Thread {
private final HttpClient client;
private final URI uri;
private final OllamaRequestModel ollamaRequestModel;
private final Queue<String> queue = new LinkedList<>();
private String result;
private boolean isDone;
private boolean succeeded;
private long requestTimeoutSeconds;
private int httpStatusCode;
private long responseTime = 0;
public OllamaAsyncResultCallback(
HttpClient client,
URI uri,
OllamaRequestModel ollamaRequestModel,
long requestTimeoutSeconds) {
this.client = client;
this.ollamaRequestModel = ollamaRequestModel;
this.uri = uri;
this.isDone = false;
this.result = "";
this.queue.add("");
this.requestTimeoutSeconds = requestTimeoutSeconds;
}
@Override
public void run() {
try {
long startTime = System.currentTimeMillis();
HttpRequest request =
HttpRequest.newBuilder(uri)
.POST(
HttpRequest.BodyPublishers.ofString(
Utils.getObjectMapper().writeValueAsString(ollamaRequestModel)))
.header("Content-Type", "application/json")
.timeout(Duration.ofSeconds(requestTimeoutSeconds))
.build();
HttpResponse<InputStream> response =
client.send(request, HttpResponse.BodyHandlers.ofInputStream());
int statusCode = response.statusCode();
this.httpStatusCode = statusCode;
InputStream responseBodyStream = response.body();
try (BufferedReader reader =
new BufferedReader(new InputStreamReader(responseBodyStream, StandardCharsets.UTF_8))) {
String line;
StringBuilder responseBuffer = new StringBuilder();
while ((line = reader.readLine()) != null) {
if (statusCode == 404) {
OllamaErrorResponseModel ollamaResponseModel =
Utils.getObjectMapper().readValue(line, OllamaErrorResponseModel.class);
queue.add(ollamaResponseModel.getError());
responseBuffer.append(ollamaResponseModel.getError());
} else {
OllamaResponseModel ollamaResponseModel =
Utils.getObjectMapper().readValue(line, OllamaResponseModel.class);
queue.add(ollamaResponseModel.getResponse());
if (!ollamaResponseModel.isDone()) {
responseBuffer.append(ollamaResponseModel.getResponse());
}
}
}
this.isDone = true;
this.succeeded = true;
this.result = responseBuffer.toString();
long endTime = System.currentTimeMillis();
responseTime = endTime - startTime;
}
if (statusCode != 200) {
throw new OllamaBaseException(this.result);
}
} catch (IOException | InterruptedException | OllamaBaseException e) {
this.isDone = true;
this.succeeded = false;
this.result = "[FAILED] " + e.getMessage();
}
}
/**
* Returns the status of the thread. This does not indicate that the request was successful or a
* failure, rather it is just a status flag to indicate if the thread is active or ended.
*
* @return boolean - status
*/
public boolean isComplete() {
return isDone;
}
/**
* Returns the HTTP response status code for the request that was made to Ollama server.
*
* @return int - the status code for the request
*/
public int getHttpStatusCode() {
return httpStatusCode;
}
/**
* Returns the status of the request. Indicates if the request was successful or a failure. If the
* request was a failure, the `getResponse()` method will return the error message.
*
* @return boolean - status
*/
public boolean isSucceeded() {
return succeeded;
}
/**
* Returns the final response when the execution completes. Does not return intermediate results.
*
* @return String - response text
*/
public String getResponse() {
return result;
}
public Queue<String> getStream() {
return queue;
}
/**
* Returns the response time in milliseconds.
*
* @return long - response time in milliseconds.
*/
public long getResponseTime() {
return responseTime;
}
public void setRequestTimeoutSeconds(long requestTimeoutSeconds) {
this.requestTimeoutSeconds = requestTimeoutSeconds;
}
}

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@ -0,0 +1,13 @@
package io.github.amithkoujalgi.ollama4j.core.models;
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
import com.fasterxml.jackson.annotation.JsonProperty;
import java.util.List;
import lombok.Data;
@Data
@JsonIgnoreProperties(ignoreUnknown = true)
public class OllamaErrorResponseModel {
private String error;
}

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@ -0,0 +1,35 @@
package io.github.amithkoujalgi.ollama4j.core.models;
import static io.github.amithkoujalgi.ollama4j.core.utils.Utils.getObjectMapper;
import com.fasterxml.jackson.core.JsonProcessingException;
import java.util.List;
import lombok.Data;
@Data
public class OllamaRequestModel {
private String model;
private String prompt;
private List<String> images;
public OllamaRequestModel(String model, String prompt) {
this.model = model;
this.prompt = prompt;
}
public OllamaRequestModel(String model, String prompt, List<String> images) {
this.model = model;
this.prompt = prompt;
this.images = images;
}
public String toString() {
try {
return getObjectMapper().writerWithDefaultPrettyPrinter().writeValueAsString(this);
} catch (JsonProcessingException e) {
throw new RuntimeException(e);
}
}
}

View File

@ -1,4 +1,4 @@
package io.github.ollama4j.models.generate;
package io.github.amithkoujalgi.ollama4j.core.models;
import com.fasterxml.jackson.annotation.JsonIgnoreProperties;
import com.fasterxml.jackson.annotation.JsonProperty;
@ -8,7 +8,7 @@ import lombok.Data;
@Data
@JsonIgnoreProperties(ignoreUnknown = true)
public class OllamaGenerateResponseModel {
public class OllamaResponseModel {
private String model;
private @JsonProperty("created_at") String createdAt;
private String response;

View File

@ -1,6 +1,6 @@
package io.github.ollama4j.models.response;
package io.github.amithkoujalgi.ollama4j.core.models;
import static io.github.ollama4j.utils.Utils.getObjectMapper;
import static io.github.amithkoujalgi.ollama4j.core.utils.Utils.getObjectMapper;
import com.fasterxml.jackson.core.JsonProcessingException;
import lombok.Data;
@ -13,9 +13,9 @@ import lombok.Getter;
public class OllamaResult {
/**
* -- GETTER --
* Get the completion/response text
* Get the response text
*
* @return String completion/response text
* @return String - response text
*/
private final String response;

View File

@ -1,6 +1,6 @@
package io.github.ollama4j.models.request;
package io.github.amithkoujalgi.ollama4j.core.models.request;
import static io.github.ollama4j.utils.Utils.getObjectMapper;
import static io.github.amithkoujalgi.ollama4j.core.utils.Utils.getObjectMapper;
import com.fasterxml.jackson.core.JsonProcessingException;
import lombok.AllArgsConstructor;

View File

@ -1,6 +1,6 @@
package io.github.ollama4j.models.request;
package io.github.amithkoujalgi.ollama4j.core.models.request;
import static io.github.ollama4j.utils.Utils.getObjectMapper;
import static io.github.amithkoujalgi.ollama4j.core.utils.Utils.getObjectMapper;
import com.fasterxml.jackson.core.JsonProcessingException;
import lombok.AllArgsConstructor;

View File

@ -0,0 +1,23 @@
package io.github.amithkoujalgi.ollama4j.core.models.request;
import static io.github.amithkoujalgi.ollama4j.core.utils.Utils.getObjectMapper;
import com.fasterxml.jackson.core.JsonProcessingException;
import lombok.AllArgsConstructor;
import lombok.Data;
@Data
@AllArgsConstructor
public class ModelEmbeddingsRequest {
private String model;
private String prompt;
@Override
public String toString() {
try {
return getObjectMapper().writerWithDefaultPrettyPrinter().writeValueAsString(this);
} catch (JsonProcessingException e) {
throw new RuntimeException(e);
}
}
}

View File

@ -1,6 +1,6 @@
package io.github.ollama4j.models.request;
package io.github.amithkoujalgi.ollama4j.core.models.request;
import static io.github.ollama4j.utils.Utils.getObjectMapper;
import static io.github.amithkoujalgi.ollama4j.core.utils.Utils.getObjectMapper;
import com.fasterxml.jackson.core.JsonProcessingException;
import lombok.AllArgsConstructor;

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@ -0,0 +1,63 @@
package io.github.amithkoujalgi.ollama4j.core.types;
/**
* A class to provide constants for all the supported models by Ollama.
*
* <p>Refer to the full list of models and the details here: <a
* href="https://ollama.ai/library">https://ollama.ai/library</a>
*/
@SuppressWarnings("ALL")
public class OllamaModelType {
public static final String LLAMA2 = "llama2";
public static final String MISTRAL = "mistral";
public static final String LLAVA = "llava";
public static final String MIXTRAL = "mixtral";
public static final String STARLING_LM = "starling-lm";
public static final String NEURAL_CHAT = "neural-chat";
public static final String CODELLAMA = "codellama";
public static final String LLAMA2_UNCENSORED = "llama2-uncensored";
public static final String DOLPHIN_MIXTRAL = "dolphin-mixtral";
public static final String ORCA_MINI = "orca-mini";
public static final String VICUNA = "vicuna";
public static final String WIZARD_VICUNA_UNCENSORED = "wizard-vicuna-uncensored";
public static final String PHIND_CODELLAMA = "phind-codellama";
public static final String ZEPHYR = "zephyr";
public static final String WIZARDCODER = "wizardcoder";
public static final String MISTRAL_OPENORCA = "mistral-openorca";
public static final String NOUS_HERMES = "nous-hermes";
public static final String DEEPSEEK_CODER = "deepseek-coder";
public static final String WIZARD_MATH = "wizard-math";
public static final String LLAMA2_CHINESE = "llama2-chinese";
public static final String FALCON = "falcon";
public static final String ORCA2 = "orca2";
public static final String STABLE_BELUGA = "stable-beluga";
public static final String CODEUP = "codeup";
public static final String EVERYTHINGLM = "everythinglm";
public static final String MEDLLAMA2 = "medllama2";
public static final String WIZARDLM_UNCENSORED = "wizardlm-uncensored";
public static final String STARCODER = "starcoder";
public static final String DOLPHIN22_MISTRAL = "dolphin2.2-mistral";
public static final String OPENCHAT = "openchat";
public static final String WIZARD_VICUNA = "wizard-vicuna";
public static final String OPENHERMES25_MISTRAL = "openhermes2.5-mistral";
public static final String OPEN_ORCA_PLATYPUS2 = "open-orca-platypus2";
public static final String YI = "yi";
public static final String YARN_MISTRAL = "yarn-mistral";
public static final String SAMANTHA_MISTRAL = "samantha-mistral";
public static final String SQLCODER = "sqlcoder";
public static final String YARN_LLAMA2 = "yarn-llama2";
public static final String MEDITRON = "meditron";
public static final String STABLELM_ZEPHYR = "stablelm-zephyr";
public static final String OPENHERMES2_MISTRAL = "openhermes2-mistral";
public static final String DEEPSEEK_LLM = "deepseek-llm";
public static final String MISTRALLITE = "mistrallite";
public static final String DOLPHIN21_MISTRAL = "dolphin2.1-mistral";
public static final String WIZARDLM = "wizardlm";
public static final String CODEBOOGA = "codebooga";
public static final String MAGICODER = "magicoder";
public static final String GOLIATH = "goliath";
public static final String NEXUSRAVEN = "nexusraven";
public static final String ALFRED = "alfred";
public static final String XWINLM = "xwinlm";
public static final String BAKLLAVA = "bakllava";
}

View File

@ -1,6 +1,6 @@
package io.github.ollama4j.utils;
package io.github.amithkoujalgi.ollama4j.core.utils;
import io.github.ollama4j.OllamaAPI;
import io.github.amithkoujalgi.ollama4j.core.OllamaAPI;
import java.io.InputStream;
import java.util.Scanner;

View File

@ -0,0 +1,9 @@
package io.github.amithkoujalgi.ollama4j.core.utils;
import com.fasterxml.jackson.databind.ObjectMapper;
public class Utils {
public static ObjectMapper getObjectMapper() {
return new ObjectMapper();
}
}

View File

@ -1,682 +0,0 @@
package io.github.ollama4j;
import io.github.ollama4j.exceptions.OllamaBaseException;
import io.github.ollama4j.exceptions.ToolInvocationException;
import io.github.ollama4j.exceptions.ToolNotFoundException;
import io.github.ollama4j.models.chat.OllamaChatMessage;
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.OllamaEmbeddingResponseModel;
import io.github.ollama4j.models.embeddings.OllamaEmbeddingsRequestModel;
import io.github.ollama4j.models.generate.OllamaGenerateRequest;
import io.github.ollama4j.models.generate.OllamaStreamHandler;
import io.github.ollama4j.models.ps.ModelsProcessResponse;
import io.github.ollama4j.models.request.*;
import io.github.ollama4j.models.response.*;
import io.github.ollama4j.tools.*;
import io.github.ollama4j.utils.Options;
import io.github.ollama4j.utils.Utils;
import lombok.Setter;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.io.*;
import java.net.URI;
import java.net.URISyntaxException;
import java.net.http.HttpClient;
import java.net.http.HttpConnectTimeoutException;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.nio.charset.StandardCharsets;
import java.nio.file.Files;
import java.time.Duration;
import java.util.*;
/**
* The base Ollama API class.
*/
@SuppressWarnings("DuplicatedCode")
public class OllamaAPI {
private static final Logger logger = LoggerFactory.getLogger(OllamaAPI.class);
private final String host;
/**
* -- SETTER --
* Set request timeout in seconds. Default is 3 seconds.
*/
@Setter
private long requestTimeoutSeconds = 10;
/**
* -- SETTER --
* Set/unset logging of responses
*/
@Setter
private boolean verbose = true;
private BasicAuth basicAuth;
private final ToolRegistry toolRegistry = new ToolRegistry();
/**
* Instantiates the Ollama API with default Ollama host: <a href="http://localhost:11434">http://localhost:11434</a>
**/
public OllamaAPI() {
this.host = "http://localhost:11434";
}
/**
* Instantiates the Ollama API with specified Ollama host address.
*
* @param host the host address of Ollama server
*/
public OllamaAPI(String host) {
if (host.endsWith("/")) {
this.host = host.substring(0, host.length() - 1);
} else {
this.host = host;
}
}
/**
* Set basic authentication for accessing Ollama server that's behind a reverse-proxy/gateway.
*
* @param username the username
* @param password the password
*/
public void setBasicAuth(String username, String password) {
this.basicAuth = new BasicAuth(username, password);
}
/**
* API to check the reachability of Ollama server.
*
* @return true if the server is reachable, false otherwise.
*/
public boolean ping() {
String url = this.host + "/api/tags";
HttpClient httpClient = HttpClient.newHttpClient();
HttpRequest httpRequest = null;
try {
httpRequest =
getRequestBuilderDefault(new URI(url))
.header("Accept", "application/json")
.header("Content-type", "application/json")
.GET()
.build();
} catch (URISyntaxException e) {
throw new RuntimeException(e);
}
HttpResponse<String> response = null;
try {
response = httpClient.send(httpRequest, HttpResponse.BodyHandlers.ofString());
} catch (HttpConnectTimeoutException e) {
return false;
} catch (IOException | InterruptedException e) {
throw new RuntimeException(e);
}
int statusCode = response.statusCode();
return statusCode == 200;
}
/**
* Provides a list of running models and details about each model currently loaded into memory.
*
* @return ModelsProcessResponse
*/
public ModelsProcessResponse ps() throws IOException, InterruptedException, OllamaBaseException {
String url = this.host + "/api/ps";
HttpClient httpClient = HttpClient.newHttpClient();
HttpRequest httpRequest = null;
try {
httpRequest =
getRequestBuilderDefault(new URI(url))
.header("Accept", "application/json")
.header("Content-type", "application/json")
.GET()
.build();
} catch (URISyntaxException e) {
throw new RuntimeException(e);
}
HttpResponse<String> response = null;
response = httpClient.send(httpRequest, HttpResponse.BodyHandlers.ofString());
int statusCode = response.statusCode();
String responseString = response.body();
if (statusCode == 200) {
return Utils.getObjectMapper()
.readValue(responseString, ModelsProcessResponse.class);
} else {
throw new OllamaBaseException(statusCode + " - " + responseString);
}
}
/**
* List available models from Ollama server.
*
* @return the list
*/
public List<Model> listModels()
throws OllamaBaseException, IOException, InterruptedException, URISyntaxException {
String url = this.host + "/api/tags";
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, ListModelsResponse.class)
.getModels();
} else {
throw new OllamaBaseException(statusCode + " - " + responseString);
}
}
/**
* Pull a model on the Ollama server from the list of <a
* href="https://ollama.ai/library">available models</a>.
*
* @param modelName the name of the model
*/
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();
HttpClient client = HttpClient.newHttpClient();
HttpResponse<InputStream> response =
client.send(request, HttpResponse.BodyHandlers.ofInputStream());
int statusCode = response.statusCode();
InputStream responseBodyStream = response.body();
String responseString = "";
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 (statusCode != 200) {
throw new OllamaBaseException(statusCode + " - " + responseString);
}
}
/**
* Gets model details from the Ollama server.
*
* @param modelName the model
* @return the model details
*/
public ModelDetail getModelDetails(String modelName)
throws IOException, OllamaBaseException, InterruptedException, URISyntaxException {
String url = this.host + "/api/show";
String jsonData = new ModelRequest(modelName).toString();
HttpRequest request =
getRequestBuilderDefault(new URI(url))
.header("Accept", "application/json")
.header("Content-type", "application/json")
.POST(HttpRequest.BodyPublishers.ofString(jsonData))
.build();
HttpClient client = HttpClient.newHttpClient();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
int statusCode = response.statusCode();
String responseBody = response.body();
if (statusCode == 200) {
return Utils.getObjectMapper().readValue(responseBody, ModelDetail.class);
} else {
throw new OllamaBaseException(statusCode + " - " + responseBody);
}
}
/**
* Create a custom model from a model file. Read more about custom model file creation <a
* href="https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md">here</a>.
*
* @param modelName the name of the custom model to be created.
* @param modelFilePath the path to model file that exists on the Ollama server.
*/
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();
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);
}
// FIXME: Ollama API returns HTTP status code 200 for model creation failure cases. Correct this
// if the issue is fixed in the Ollama API server.
if (responseString.contains("error")) {
throw new OllamaBaseException(responseString);
}
if (verbose) {
logger.info(responseString);
}
}
/**
* Create a custom model from a model file. Read more about custom model file creation <a
* href="https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md">here</a>.
*
* @param modelName the name of the custom model to be created.
* @param modelFileContents the path to model file that exists on the Ollama server.
*/
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();
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.
*
* @param modelName the name of the model to be deleted.
* @param ignoreIfNotPresent ignore errors if the specified model is not present on Ollama server.
*/
public void deleteModel(String modelName, boolean ignoreIfNotPresent)
throws IOException, InterruptedException, OllamaBaseException, URISyntaxException {
String url = this.host + "/api/delete";
String jsonData = new ModelRequest(modelName).toString();
HttpRequest request =
getRequestBuilderDefault(new URI(url))
.method("DELETE", HttpRequest.BodyPublishers.ofString(jsonData, StandardCharsets.UTF_8))
.header("Accept", "application/json")
.header("Content-type", "application/json")
.build();
HttpClient client = HttpClient.newHttpClient();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
int statusCode = response.statusCode();
String responseBody = response.body();
if (statusCode == 404 && responseBody.contains("model") && responseBody.contains("not found")) {
return;
}
if (statusCode != 200) {
throw new OllamaBaseException(statusCode + " - " + responseBody);
}
}
/**
* Generate embeddings for a given text from a model
*
* @param model name of model to generate embeddings from
* @param prompt text to generate embeddings for
* @return embeddings
*/
public List<Double> generateEmbeddings(String model, String prompt)
throws IOException, InterruptedException, OllamaBaseException {
return generateEmbeddings(new OllamaEmbeddingsRequestModel(model, prompt));
}
/**
* Generate embeddings using a {@link OllamaEmbeddingsRequestModel}.
*
* @param modelRequest request for '/api/embeddings' endpoint
* @return embeddings
*/
public List<Double> generateEmbeddings(OllamaEmbeddingsRequestModel modelRequest) throws IOException, InterruptedException, OllamaBaseException {
URI uri = URI.create(this.host + "/api/embeddings");
String jsonData = modelRequest.toString();
HttpClient httpClient = HttpClient.newHttpClient();
HttpRequest.Builder requestBuilder =
getRequestBuilderDefault(uri)
.header("Accept", "application/json")
.POST(HttpRequest.BodyPublishers.ofString(jsonData));
HttpRequest request = requestBuilder.build();
HttpResponse<String> response = httpClient.send(request, HttpResponse.BodyHandlers.ofString());
int statusCode = response.statusCode();
String responseBody = response.body();
if (statusCode == 200) {
OllamaEmbeddingResponseModel embeddingResponse =
Utils.getObjectMapper().readValue(responseBody, OllamaEmbeddingResponseModel.class);
return embeddingResponse.getEmbedding();
} else {
throw new OllamaBaseException(statusCode + " - " + responseBody);
}
}
/**
* Generate response for a question to a model running on Ollama server. This is a sync/blocking
* call.
*
* @param model the ollama model to ask the question to
* @param prompt the prompt/question text
* @param options the Options object - <a
* href="https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md#valid-parameters-and-values">More
* details on the options</a>
* @param streamHandler optional callback consumer that will be applied every time a streamed response is received. If not set, the stream parameter of the request is set to false.
* @return OllamaResult that includes response text and time taken for response
*/
public OllamaResult generate(String model, String prompt, boolean raw, Options options, OllamaStreamHandler streamHandler)
throws OllamaBaseException, IOException, InterruptedException {
OllamaGenerateRequest ollamaRequestModel = new OllamaGenerateRequest(model, prompt);
ollamaRequestModel.setRaw(raw);
ollamaRequestModel.setOptions(options.getOptionsMap());
return generateSyncForOllamaRequestModel(ollamaRequestModel, streamHandler);
}
/**
* Generates response using the specified AI model and prompt (in blocking mode).
* <p>
* Uses {@link #generate(String, String, boolean, Options, OllamaStreamHandler)}
*
* @param model The name or identifier of the AI model to use for generating the response.
* @param prompt The input text or prompt to provide to the AI model.
* @param raw In some cases, you may wish to bypass the templating system and provide a full prompt. In this case, you can use the raw parameter to disable templating. Also note that raw mode will not return a context.
* @param options Additional options or configurations to use when generating the response.
* @return {@link OllamaResult}
*/
public OllamaResult generate(String model, String prompt, boolean raw, Options options)
throws OllamaBaseException, IOException, InterruptedException {
return generate(model, prompt, raw, options, null);
}
/**
* Generates response using the specified AI model and prompt (in blocking mode), and then invokes a set of tools
* on the generated response.
*
* @param model The name or identifier of the AI model to use for generating the response.
* @param prompt The input text or prompt to provide to the AI model.
* @param options Additional options or configurations to use when generating the response.
* @return {@link OllamaToolsResult} An OllamaToolsResult object containing the response from the AI model and the results of invoking the tools on that output.
* @throws OllamaBaseException If there is an error related to the Ollama API or service.
* @throws IOException If there is an error related to input/output operations.
* @throws InterruptedException If the method is interrupted while waiting for the AI model
* to generate the response or for the tools to be invoked.
*/
public OllamaToolsResult generateWithTools(String model, String prompt, Options options)
throws OllamaBaseException, IOException, InterruptedException, ToolInvocationException {
boolean raw = true;
OllamaToolsResult toolResult = new OllamaToolsResult();
Map<ToolFunctionCallSpec, Object> toolResults = new HashMap<>();
OllamaResult result = generate(model, prompt, raw, options, null);
toolResult.setModelResult(result);
String toolsResponse = result.getResponse();
if (toolsResponse.contains("[TOOL_CALLS]")) {
toolsResponse = toolsResponse.replace("[TOOL_CALLS]", "");
}
List<ToolFunctionCallSpec> toolFunctionCallSpecs = Utils.getObjectMapper().readValue(toolsResponse, Utils.getObjectMapper().getTypeFactory().constructCollectionType(List.class, ToolFunctionCallSpec.class));
for (ToolFunctionCallSpec toolFunctionCallSpec : toolFunctionCallSpecs) {
toolResults.put(toolFunctionCallSpec, invokeTool(toolFunctionCallSpec));
}
toolResult.setToolResults(toolResults);
return toolResult;
}
/**
* Generate response for a question to a model running on Ollama server and get a callback handle
* that can be used to check for status and get the response from the model later. This would be
* an async/non-blocking call.
*
* @param model the ollama model to ask the question to
* @param prompt the prompt/question text
* @return the ollama async result callback handle
*/
public OllamaAsyncResultStreamer generateAsync(String model, String prompt, boolean raw) {
OllamaGenerateRequest ollamaRequestModel = new OllamaGenerateRequest(model, prompt);
ollamaRequestModel.setRaw(raw);
URI uri = URI.create(this.host + "/api/generate");
OllamaAsyncResultStreamer ollamaAsyncResultStreamer =
new OllamaAsyncResultStreamer(
getRequestBuilderDefault(uri), ollamaRequestModel, requestTimeoutSeconds);
ollamaAsyncResultStreamer.start();
return ollamaAsyncResultStreamer;
}
/**
* With one or more image files, ask a question to a model running on Ollama server. This is a
* sync/blocking call.
*
* @param model the ollama model to ask the question to
* @param prompt the prompt/question text
* @param imageFiles the list of image files to use for the question
* @param options the Options object - <a
* href="https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md#valid-parameters-and-values">More
* details on the options</a>
* @param streamHandler optional callback consumer that will be applied every time a streamed response is received. If not set, the stream parameter of the request is set to false.
* @return OllamaResult that includes response text and time taken for response
*/
public OllamaResult generateWithImageFiles(
String model, String prompt, List<File> imageFiles, Options options, OllamaStreamHandler streamHandler)
throws OllamaBaseException, IOException, InterruptedException {
List<String> images = new ArrayList<>();
for (File imageFile : imageFiles) {
images.add(encodeFileToBase64(imageFile));
}
OllamaGenerateRequest ollamaRequestModel = new OllamaGenerateRequest(model, prompt, images);
ollamaRequestModel.setOptions(options.getOptionsMap());
return generateSyncForOllamaRequestModel(ollamaRequestModel, streamHandler);
}
/**
* Convenience method to call Ollama API without streaming responses.
* <p>
* Uses {@link #generateWithImageFiles(String, String, List, Options, OllamaStreamHandler)}
*/
public OllamaResult generateWithImageFiles(
String model, String prompt, List<File> imageFiles, Options options)
throws OllamaBaseException, IOException, InterruptedException {
return generateWithImageFiles(model, prompt, imageFiles, options, null);
}
/**
* With one or more image URLs, ask a question to a model running on Ollama server. This is a
* sync/blocking call.
*
* @param model the ollama model to ask the question to
* @param prompt the prompt/question text
* @param imageURLs the list of image URLs to use for the question
* @param options the Options object - <a
* href="https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md#valid-parameters-and-values">More
* details on the options</a>
* @param streamHandler optional callback consumer that will be applied every time a streamed response is received. If not set, the stream parameter of the request is set to false.
* @return OllamaResult that includes response text and time taken for response
*/
public OllamaResult generateWithImageURLs(
String model, String prompt, List<String> imageURLs, Options options, OllamaStreamHandler streamHandler)
throws OllamaBaseException, IOException, InterruptedException, URISyntaxException {
List<String> images = new ArrayList<>();
for (String imageURL : imageURLs) {
images.add(encodeByteArrayToBase64(Utils.loadImageBytesFromUrl(imageURL)));
}
OllamaGenerateRequest ollamaRequestModel = new OllamaGenerateRequest(model, prompt, images);
ollamaRequestModel.setOptions(options.getOptionsMap());
return generateSyncForOllamaRequestModel(ollamaRequestModel, streamHandler);
}
/**
* Convenience method to call Ollama API without streaming responses.
* <p>
* Uses {@link #generateWithImageURLs(String, String, List, Options, OllamaStreamHandler)}
*/
public OllamaResult generateWithImageURLs(String model, String prompt, List<String> imageURLs,
Options options)
throws OllamaBaseException, IOException, InterruptedException, URISyntaxException {
return generateWithImageURLs(model, prompt, imageURLs, options, null);
}
/**
* Ask a question to a model based on a given message stack (i.e. a chat history). Creates a synchronous call to the api
* 'api/chat'.
*
* @param model the ollama model to ask the question to
* @param messages chat history / message stack to send to the model
* @return {@link OllamaChatResult} containing the api response and the message history including the newly aqcuired assistant response.
* @throws OllamaBaseException any response code than 200 has been returned
* @throws IOException in case the responseStream can not be read
* @throws InterruptedException in case the server is not reachable or network issues happen
*/
public OllamaChatResult chat(String model, List<OllamaChatMessage> messages) throws OllamaBaseException, IOException, InterruptedException {
OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(model);
return chat(builder.withMessages(messages).build());
}
/**
* Ask a question to a model using an {@link OllamaChatRequest}. This can be constructed using an {@link OllamaChatRequestBuilder}.
* <p>
* Hint: the OllamaChatRequestModel#getStream() property is not implemented.
*
* @param request request object to be sent to the server
* @return {@link OllamaChatResult}
* @throws OllamaBaseException any response code than 200 has been returned
* @throws IOException in case the responseStream can not be read
* @throws InterruptedException in case the server is not reachable or network issues happen
*/
public OllamaChatResult chat(OllamaChatRequest request) throws OllamaBaseException, IOException, InterruptedException {
return chat(request, null);
}
/**
* Ask a question to a model using an {@link OllamaChatRequest}. This can be constructed using an {@link OllamaChatRequestBuilder}.
* <p>
* Hint: the OllamaChatRequestModel#getStream() property is not implemented.
*
* @param request request object to be sent to the server
* @param streamHandler callback handler to handle the last message 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
* @throws InterruptedException in case the server is not reachable or network issues happen
*/
public OllamaChatResult chat(OllamaChatRequest request, OllamaStreamHandler streamHandler) throws OllamaBaseException, IOException, InterruptedException {
OllamaChatEndpointCaller requestCaller = new OllamaChatEndpointCaller(host, basicAuth, requestTimeoutSeconds, verbose);
OllamaResult result;
if (streamHandler != null) {
request.setStream(true);
result = requestCaller.call(request, streamHandler);
} else {
result = requestCaller.callSync(request);
}
return new OllamaChatResult(result.getResponse(), result.getResponseTime(), result.getHttpStatusCode(), request.getMessages());
}
public void registerTool(Tools.ToolSpecification toolSpecification) {
toolRegistry.addFunction(toolSpecification.getFunctionName(), toolSpecification.getToolDefinition());
}
// technical private methods //
private static String encodeFileToBase64(File file) throws IOException {
return Base64.getEncoder().encodeToString(Files.readAllBytes(file.toPath()));
}
private static String encodeByteArrayToBase64(byte[] bytes) {
return Base64.getEncoder().encodeToString(bytes);
}
private OllamaResult generateSyncForOllamaRequestModel(
OllamaGenerateRequest ollamaRequestModel, OllamaStreamHandler streamHandler)
throws OllamaBaseException, IOException, InterruptedException {
OllamaGenerateEndpointCaller requestCaller =
new OllamaGenerateEndpointCaller(host, basicAuth, requestTimeoutSeconds, verbose);
OllamaResult result;
if (streamHandler != null) {
ollamaRequestModel.setStream(true);
result = requestCaller.call(ollamaRequestModel, streamHandler);
} else {
result = requestCaller.callSync(ollamaRequestModel);
}
return result;
}
/**
* Get default request builder.
*
* @param uri URI to get a HttpRequest.Builder
* @return HttpRequest.Builder
*/
private HttpRequest.Builder getRequestBuilderDefault(URI uri) {
HttpRequest.Builder requestBuilder =
HttpRequest.newBuilder(uri)
.header("Content-Type", "application/json")
.timeout(Duration.ofSeconds(requestTimeoutSeconds));
if (isBasicAuthCredentialsSet()) {
requestBuilder.header("Authorization", getBasicAuthHeaderValue());
}
return requestBuilder;
}
/**
* Get basic authentication header value.
*
* @return basic authentication header value (encoded credentials)
*/
private String getBasicAuthHeaderValue() {
String credentialsToEncode = basicAuth.getUsername() + ":" + basicAuth.getPassword();
return "Basic " + Base64.getEncoder().encodeToString(credentialsToEncode.getBytes());
}
/**
* Check if Basic Auth credentials set.
*
* @return true when Basic Auth credentials set
*/
private boolean isBasicAuthCredentialsSet() {
return basicAuth != null;
}
private Object invokeTool(ToolFunctionCallSpec toolFunctionCallSpec) throws ToolInvocationException {
try {
String methodName = toolFunctionCallSpec.getName();
Map<String, Object> arguments = toolFunctionCallSpec.getArguments();
ToolFunction function = toolRegistry.getFunction(methodName);
if (verbose) {
logger.debug("Invoking function {} with arguments {}", methodName, arguments);
}
if (function == null) {
throw new ToolNotFoundException("No such tool: " + methodName);
}
return function.apply(arguments);
} catch (Exception e) {
throw new ToolInvocationException("Failed to invoke tool: " + toolFunctionCallSpec.getName(), e);
}
}
}

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@ -1,8 +0,0 @@
package io.github.ollama4j.exceptions;
public class ToolInvocationException extends Exception {
public ToolInvocationException(String s, Exception e) {
super(s, e);
}
}

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@ -1,8 +0,0 @@
package io.github.ollama4j.exceptions;
public class ToolNotFoundException extends Exception {
public ToolNotFoundException(String s) {
super(s);
}
}

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@ -1,14 +0,0 @@
package io.github.ollama4j.impl;
import io.github.ollama4j.models.generate.OllamaStreamHandler;
public class ConsoleOutputStreamHandler implements OllamaStreamHandler {
private final StringBuffer response = new StringBuffer();
@Override
public void accept(String message) {
String substr = message.substring(response.length());
response.append(substr);
System.out.print(substr);
}
}

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@ -1,45 +0,0 @@
package io.github.ollama4j.models.chat;
import static io.github.ollama4j.utils.Utils.getObjectMapper;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.annotation.JsonSerialize;
import io.github.ollama4j.utils.FileToBase64Serializer;
import java.util.List;
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;
import lombok.NonNull;
import lombok.RequiredArgsConstructor;
/**
* Defines a single Message to be used inside a chat request against the ollama /api/chat endpoint.
*
* @see <a href="https://github.com/ollama/ollama/blob/main/docs/api.md#generate-a-chat-completion">Generate chat completion</a>
*/
@Data
@AllArgsConstructor
@RequiredArgsConstructor
@NoArgsConstructor
public class OllamaChatMessage {
@NonNull
private OllamaChatMessageRole role;
@NonNull
private String content;
@JsonSerialize(using = FileToBase64Serializer.class)
private List<byte[]> images;
@Override
public String toString() {
try {
return getObjectMapper().writerWithDefaultPrettyPrinter().writeValueAsString(this);
} catch (JsonProcessingException e) {
throw new RuntimeException(e);
}
}
}

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@ -1,19 +0,0 @@
package io.github.ollama4j.models.chat;
import com.fasterxml.jackson.annotation.JsonValue;
/**
* Defines the possible Chat Message roles.
*/
public enum OllamaChatMessageRole {
SYSTEM("system"),
USER("user"),
ASSISTANT("assistant");
@JsonValue
private String roleName;
private OllamaChatMessageRole(String roleName){
this.roleName = roleName;
}
}

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@ -1,40 +0,0 @@
package io.github.ollama4j.models.chat;
import java.util.List;
import io.github.ollama4j.models.request.OllamaCommonRequest;
import io.github.ollama4j.utils.OllamaRequestBody;
import lombok.Getter;
import lombok.Setter;
/**
* Defines a Request to use against the ollama /api/chat endpoint.
*
* @see <a href=
* "https://github.com/ollama/ollama/blob/main/docs/api.md#generate-a-chat-completion">Generate
* Chat Completion</a>
*/
@Getter
@Setter
public class OllamaChatRequest extends OllamaCommonRequest implements OllamaRequestBody {
private List<OllamaChatMessage> messages;
public OllamaChatRequest() {}
public OllamaChatRequest(String model, List<OllamaChatMessage> messages) {
this.model = model;
this.messages = messages;
}
@Override
public boolean equals(Object o) {
if (!(o instanceof OllamaChatRequest)) {
return false;
}
return this.toString().equals(o.toString());
}
}

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@ -1,106 +0,0 @@
package io.github.ollama4j.models.chat;
import io.github.ollama4j.utils.Options;
import io.github.ollama4j.utils.Utils;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.io.File;
import java.io.IOException;
import java.net.URISyntaxException;
import java.nio.file.Files;
import java.util.ArrayList;
import java.util.List;
import java.util.stream.Collectors;
/**
* Helper class for creating {@link OllamaChatRequest} objects using the builder-pattern.
*/
public class OllamaChatRequestBuilder {
private static final Logger LOG = LoggerFactory.getLogger(OllamaChatRequestBuilder.class);
private OllamaChatRequestBuilder(String model, List<OllamaChatMessage> messages) {
request = new OllamaChatRequest(model, messages);
}
private OllamaChatRequest request;
public static OllamaChatRequestBuilder getInstance(String model) {
return new OllamaChatRequestBuilder(model, new ArrayList<>());
}
public OllamaChatRequest build() {
return request;
}
public void reset() {
request = new OllamaChatRequest(request.getModel(), new ArrayList<>());
}
public OllamaChatRequestBuilder withMessage(OllamaChatMessageRole role, String content, List<File> images) {
List<OllamaChatMessage> messages = this.request.getMessages();
List<byte[]> binaryImages = images.stream().map(file -> {
try {
return Files.readAllBytes(file.toPath());
} catch (IOException e) {
LOG.warn(String.format("File '%s' could not be accessed, will not add to message!", file.toPath()), e);
return new byte[0];
}
}).collect(Collectors.toList());
messages.add(new OllamaChatMessage(role, content, binaryImages));
return this;
}
public OllamaChatRequestBuilder withMessage(OllamaChatMessageRole role, String content, String... imageUrls) {
List<OllamaChatMessage> messages = this.request.getMessages();
List<byte[]> binaryImages = null;
if (imageUrls.length > 0) {
binaryImages = new ArrayList<>();
for (String imageUrl : imageUrls) {
try {
binaryImages.add(Utils.loadImageBytesFromUrl(imageUrl));
} catch (URISyntaxException e) {
LOG.warn(String.format("URL '%s' could not be accessed, will not add to message!", imageUrl), e);
} catch (IOException e) {
LOG.warn(String.format("Content of URL '%s' could not be read, will not add to message!", imageUrl), e);
}
}
}
messages.add(new OllamaChatMessage(role, content, binaryImages));
return this;
}
public OllamaChatRequestBuilder withMessages(List<OllamaChatMessage> messages) {
return new OllamaChatRequestBuilder(request.getModel(), messages);
}
public OllamaChatRequestBuilder withOptions(Options options) {
this.request.setOptions(options.getOptionsMap());
return this;
}
public OllamaChatRequestBuilder withGetJsonResponse() {
this.request.setReturnFormatJson(true);
return this;
}
public OllamaChatRequestBuilder withTemplate(String template) {
this.request.setTemplate(template);
return this;
}
public OllamaChatRequestBuilder withStreaming() {
this.request.setStream(true);
return this;
}
public OllamaChatRequestBuilder withKeepAlive(String keepAlive) {
this.request.setKeepAlive(keepAlive);
return this;
}
}

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@ -1,23 +0,0 @@
package io.github.ollama4j.models.chat;
import com.fasterxml.jackson.annotation.JsonProperty;
import lombok.Data;
import java.util.List;
@Data
public class OllamaChatResponseModel {
private String model;
private @JsonProperty("created_at") String createdAt;
private @JsonProperty("done_reason") String doneReason;
private OllamaChatMessage message;
private boolean done;
private String error;
private List<Integer> context;
private @JsonProperty("total_duration") Long totalDuration;
private @JsonProperty("load_duration") Long loadDuration;
private @JsonProperty("prompt_eval_duration") Long promptEvalDuration;
private @JsonProperty("eval_duration") Long evalDuration;
private @JsonProperty("prompt_eval_count") Integer promptEvalCount;
private @JsonProperty("eval_count") Integer evalCount;
}

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@ -1,26 +0,0 @@
package io.github.ollama4j.models.chat;
import java.util.List;
import io.github.ollama4j.models.response.OllamaResult;
/**
* Specific chat-API result that contains the chat history sent to the model and appends the answer as {@link OllamaChatResult} given by the
* {@link OllamaChatMessageRole#ASSISTANT} role.
*/
public class OllamaChatResult extends OllamaResult{
private List<OllamaChatMessage> chatHistory;
public OllamaChatResult(String response, long responseTime, int httpStatusCode,
List<OllamaChatMessage> chatHistory) {
super(response, responseTime, httpStatusCode);
this.chatHistory = chatHistory;
}
public List<OllamaChatMessage> getChatHistory() {
return chatHistory;
}
}

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@ -1,28 +0,0 @@
package io.github.ollama4j.models.chat;
import io.github.ollama4j.models.generate.OllamaStreamHandler;
import java.util.ArrayList;
import java.util.List;
public class OllamaChatStreamObserver {
private OllamaStreamHandler streamHandler;
private List<OllamaChatResponseModel> responseParts = new ArrayList<>();
public OllamaChatStreamObserver(OllamaStreamHandler streamHandler) {
this.streamHandler = streamHandler;
}
public void notify(OllamaChatResponseModel currentResponsePart) {
responseParts.add(currentResponsePart);
handleCurrentResponsePart(currentResponsePart);
}
protected void handleCurrentResponsePart(OllamaChatResponseModel currentResponsePart) {
streamHandler.accept(currentResponsePart.getMessage().getContent());
}
}

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package io.github.ollama4j.models.embeddings;
import io.github.ollama4j.utils.Options;
public class OllamaEmbeddingsRequestBuilder {
private OllamaEmbeddingsRequestBuilder(String model, String prompt){
request = new OllamaEmbeddingsRequestModel(model, prompt);
}
private OllamaEmbeddingsRequestModel request;
public static OllamaEmbeddingsRequestBuilder getInstance(String model, String prompt){
return new OllamaEmbeddingsRequestBuilder(model, prompt);
}
public OllamaEmbeddingsRequestModel build(){
return request;
}
public OllamaEmbeddingsRequestBuilder withOptions(Options options){
this.request.setOptions(options.getOptionsMap());
return this;
}
public OllamaEmbeddingsRequestBuilder withKeepAlive(String keepAlive){
this.request.setKeepAlive(keepAlive);
return this;
}
}

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package io.github.ollama4j.models.embeddings;
import static io.github.ollama4j.utils.Utils.getObjectMapper;
import java.util.Map;
import com.fasterxml.jackson.annotation.JsonProperty;
import com.fasterxml.jackson.core.JsonProcessingException;
import lombok.Data;
import lombok.NoArgsConstructor;
import lombok.NonNull;
import lombok.RequiredArgsConstructor;
@Data
@RequiredArgsConstructor
@NoArgsConstructor
public class OllamaEmbeddingsRequestModel {
@NonNull
private String model;
@NonNull
private String prompt;
protected Map<String, Object> options;
@JsonProperty(value = "keep_alive")
private String keepAlive;
@Override
public String toString() {
try {
return getObjectMapper().writerWithDefaultPrettyPrinter().writeValueAsString(this);
} catch (JsonProcessingException e) {
throw new RuntimeException(e);
}
}
}

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@ -1,46 +0,0 @@
package io.github.ollama4j.models.generate;
import io.github.ollama4j.models.request.OllamaCommonRequest;
import io.github.ollama4j.utils.OllamaRequestBody;
import java.util.List;
import lombok.Getter;
import lombok.Setter;
@Getter
@Setter
public class OllamaGenerateRequest extends OllamaCommonRequest implements OllamaRequestBody{
private String prompt;
private List<String> images;
private String system;
private String context;
private boolean raw;
public OllamaGenerateRequest() {
}
public OllamaGenerateRequest(String model, String prompt) {
this.model = model;
this.prompt = prompt;
}
public OllamaGenerateRequest(String model, String prompt, List<String> images) {
this.model = model;
this.prompt = prompt;
this.images = images;
}
@Override
public boolean equals(Object o) {
if (!(o instanceof OllamaGenerateRequest)) {
return false;
}
return this.toString().equals(o.toString());
}
}

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@ -1,55 +0,0 @@
package io.github.ollama4j.models.generate;
import io.github.ollama4j.utils.Options;
/**
* Helper class for creating {@link OllamaGenerateRequest}
* objects using the builder-pattern.
*/
public class OllamaGenerateRequestBuilder {
private OllamaGenerateRequestBuilder(String model, String prompt){
request = new OllamaGenerateRequest(model, prompt);
}
private OllamaGenerateRequest request;
public static OllamaGenerateRequestBuilder getInstance(String model){
return new OllamaGenerateRequestBuilder(model,"");
}
public OllamaGenerateRequest build(){
return request;
}
public OllamaGenerateRequestBuilder withPrompt(String prompt){
request.setPrompt(prompt);
return this;
}
public OllamaGenerateRequestBuilder withGetJsonResponse(){
this.request.setReturnFormatJson(true);
return this;
}
public OllamaGenerateRequestBuilder withOptions(Options options){
this.request.setOptions(options.getOptionsMap());
return this;
}
public OllamaGenerateRequestBuilder withTemplate(String template){
this.request.setTemplate(template);
return this;
}
public OllamaGenerateRequestBuilder withStreaming(){
this.request.setStream(true);
return this;
}
public OllamaGenerateRequestBuilder withKeepAlive(String keepAlive){
this.request.setKeepAlive(keepAlive);
return this;
}
}

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@ -1,29 +0,0 @@
package io.github.ollama4j.models.generate;
import java.util.ArrayList;
import java.util.List;
public class OllamaGenerateStreamObserver {
private OllamaStreamHandler streamHandler;
private List<OllamaGenerateResponseModel> responseParts = new ArrayList<>();
private String message = "";
public OllamaGenerateStreamObserver(OllamaStreamHandler streamHandler) {
this.streamHandler = streamHandler;
}
public void notify(OllamaGenerateResponseModel currentResponsePart) {
responseParts.add(currentResponsePart);
handleCurrentResponsePart(currentResponsePart);
}
protected void handleCurrentResponsePart(OllamaGenerateResponseModel currentResponsePart) {
message = message + currentResponsePart.getResponse();
streamHandler.accept(message);
}
}

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@ -1,7 +0,0 @@
package io.github.ollama4j.models.generate;
import java.util.function.Consumer;
public interface OllamaStreamHandler extends Consumer<String> {
void accept(String message);
}

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