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@@ -45,18 +45,19 @@ body:
|
||||
label: Steps to Reproduce
|
||||
description: Share the steps you took so that we can reproduce the issue. Reports without proper steps details will likely be closed.
|
||||
placeholder: |
|
||||
1. Run APIPark via the Docker image.
|
||||
2. Try configuring ...
|
||||
3. ...
|
||||
1. Run apinto via the Docker image.
|
||||
2. Create a Route with the Admin API.
|
||||
3. Try configuring ...
|
||||
4. ...
|
||||
validations:
|
||||
required: false
|
||||
required: true
|
||||
- type: textarea
|
||||
id: environment
|
||||
attributes:
|
||||
label: Environment
|
||||
description: Share your environment details. Reports without proper environment details will likely be closed.
|
||||
value: |
|
||||
- ApiPark version:
|
||||
- APINTO Dashboard version (run `apinto dashboard version`):
|
||||
- Operating system (run `uname -a`):
|
||||
validations:
|
||||
required: true
|
||||
@@ -1,5 +1,5 @@
|
||||
name: "Feature Request"
|
||||
description: Suggest an enhancement to APIPark.
|
||||
description: Suggest an enhancement to APINTO.
|
||||
title: "feat: As a user, I want to ..., so that ..."
|
||||
body:
|
||||
- type: markdown
|
||||
@@ -20,4 +20,4 @@ body:
|
||||
placeholder: |
|
||||
As a user, I want to ..., so that...
|
||||
validations:
|
||||
required: true
|
||||
required: true
|
||||
@@ -25,7 +25,7 @@ body:
|
||||
label: Environment
|
||||
description: Share your environment details. Reports without proper environment details will likely be closed.
|
||||
value: |
|
||||
- APIPark version:
|
||||
- APIPark version (run `apinto dashboard version`):
|
||||
- Operating system (run `uname -a`):
|
||||
validations:
|
||||
required: true
|
||||
@@ -25,7 +25,7 @@ jobs:
|
||||
echo "Build frontend..."
|
||||
cd ./frontend && pnpm run build
|
||||
- name: upload frontend release
|
||||
uses: actions/upload-artifact@v4
|
||||
uses: actions/upload-artifact@v2
|
||||
with:
|
||||
name: frontend-package
|
||||
path: frontend/dist
|
||||
@@ -41,7 +41,7 @@ jobs:
|
||||
- name: Checkout #Checkout代码
|
||||
uses: actions/checkout@v3
|
||||
- name: download frontend release
|
||||
uses: actions/download-artifact@v4
|
||||
uses: actions/download-artifact@v2
|
||||
with:
|
||||
name: frontend-package
|
||||
path: frontend/dist
|
||||
@@ -71,15 +71,10 @@ jobs:
|
||||
- uses: actions/checkout@v3
|
||||
|
||||
- name: download frontend release
|
||||
uses: actions/download-artifact@v4
|
||||
uses: actions/download-artifact@v2
|
||||
with:
|
||||
name: frontend-package
|
||||
path: frontend/dist
|
||||
# 设置 QEMU 以支持多架构构建
|
||||
- name: Set up QEMU
|
||||
uses: docker/setup-qemu-action@v3
|
||||
- name: Set up Docker Buildx
|
||||
uses: docker/setup-buildx-action@v3
|
||||
- name: Login Docker #登录docker
|
||||
uses: docker/login-action@v1
|
||||
with:
|
||||
|
||||
@@ -3,9 +3,4 @@
|
||||
/config.yml
|
||||
/build/
|
||||
/apipark
|
||||
.gitlab-ci.yml
|
||||
/.vscode/
|
||||
.air.toml
|
||||
/tmp/
|
||||
/work
|
||||
/cmd/
|
||||
/aoplatform
|
||||
|
||||
@@ -1,88 +0,0 @@
|
||||
variables:
|
||||
PATH: /opt/go-1.23/go/bin/:/opt/node-1.22/bin/:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/root/bin
|
||||
GOROOT: /opt/go-1.23/go
|
||||
GOPROXY: https://goproxy.cn
|
||||
VERSION: $CI_COMMIT_SHORT_SHA
|
||||
APP: apipark
|
||||
APP_PRE: ${APP}_${VERSION}
|
||||
BUILD_DIR: ${APP}-build
|
||||
DEPLOY_DESC: "DEV 环境"
|
||||
VIEW_ADDR: http://172.18.166.219:8288
|
||||
SAVE_DIR: /opt/${APP}
|
||||
NODE_OPTIONS: --max_old_space_size=8192
|
||||
|
||||
stages:
|
||||
# - notice
|
||||
- build
|
||||
- deploy
|
||||
- webhook
|
||||
#
|
||||
#feishu-informer: # 飞书回调
|
||||
# stage: notice
|
||||
# variables:
|
||||
# DIFF_URL: "$CI_MERGE_REQUEST_PROJECT_URL/-/merge_requests/$CI_MERGE_REQUEST_IID/diffs"
|
||||
# rules:
|
||||
# - if: $CI_PIPELINE_SOURCE=="merge_request_event" && $CI_COMMIT_BRANCH =~ "main-github-pro"
|
||||
# script:
|
||||
# - echo "merge request"
|
||||
# - |
|
||||
# curl -X POST -H "Content-Type: application/json" \
|
||||
# -d "{\"msg_type\":\"text\",\"content\":{\"text\":\"项目:${CI_PROJECT_NAME}\\n提交人:${GITLAB_USER_NAME}\\n提交信息:${CI_MERGE_REQUEST_TITLE}\\n合并分支信息:${CI_MERGE_REQUEST_SOURCE_BRANCH_NAME} -> ${CI_MERGE_REQUEST_TARGET_BRANCH_NAME}\\n差异性地址:${DIFF_URL}\\n请及时review代码\"}}" \
|
||||
# ${FEISHU_WEBHOOK}
|
||||
|
||||
builder:
|
||||
stage: build
|
||||
rules:
|
||||
- if: $CI_COMMIT_BRANCH == "main-github-pro" || $CI_COMMIT_BRANCH == "main"
|
||||
script:
|
||||
- set -e
|
||||
- |
|
||||
if [ ! -d "../artifacts" ]; then
|
||||
mkdir -p ../artifacts
|
||||
fi
|
||||
if [ -d "../artifacts/dist" ]; then
|
||||
cp -r ../artifacts/dist frontend/dist
|
||||
fi
|
||||
- |
|
||||
if [ -n "$(git diff --name-status HEAD~1 HEAD -- frontend)" ]; then
|
||||
./scripts/build.sh $BUILD_DIR ${VERSION} all ""
|
||||
else
|
||||
./scripts/build.sh $BUILD_DIR ${VERSION}
|
||||
fi
|
||||
if [ -d "frontend/dist" ]; then
|
||||
echo "copy frontend/dist to artifacts/dist"
|
||||
rm -fr ../artifacts/dist
|
||||
cp -r frontend/dist ../artifacts/dist
|
||||
fi
|
||||
cp $BUILD_DIR/${APP_PRE}_linux_amd64.tar.gz ${SAVE_DIR}
|
||||
|
||||
deployer:
|
||||
stage: deploy
|
||||
rules:
|
||||
- if: $CI_COMMIT_BRANCH == "main-github-pro" || $CI_COMMIT_BRANCH == "main"
|
||||
variables:
|
||||
APIPARK_GUEST_MODE: allow
|
||||
APIPARK_GUEST_ID: dklejrfbhjqwdh
|
||||
script:
|
||||
- cd ${SAVE_DIR};mkdir -p ${APP_PRE};tar -zxvf ${APP_PRE}_linux_amd64.tar.gz -C ${APP_PRE};cd ${APP_PRE};./install.sh ${SAVE_DIR};./run.sh restart;cd ${SAVE_DIR} && ./clean.sh ${APP_PRE}
|
||||
when: on_success
|
||||
success:
|
||||
stage: webhook
|
||||
rules:
|
||||
- if: $CI_COMMIT_BRANCH == "main-github-pro" || $CI_COMMIT_BRANCH == "main"
|
||||
script:
|
||||
- |
|
||||
curl -X POST -H "Content-Type: application/json" \
|
||||
-d "{\"msg_type\":\"text\",\"content\":{\"text\":\"最近一次提交:${CI_COMMIT_TITLE}\\n提交人:${GITLAB_USER_NAME}\\n项目:${CI_PROJECT_NAME}\\n环境:${DEPLOY_DESC}\\n更新部署完成.\\n访问地址:${VIEW_ADDR}\\n工作流地址:${CI_PIPELINE_URL}\"}}" \
|
||||
${FEISHU_WEBHOOK}
|
||||
when: on_success
|
||||
failure:
|
||||
stage: webhook
|
||||
rules:
|
||||
- if: $CI_COMMIT_BRANCH == "main-github-pro" || $CI_COMMIT_BRANCH == "main"
|
||||
script:
|
||||
- |
|
||||
curl -X POST -H "Content-Type: application/json" \
|
||||
-d "{\"msg_type\":\"text\",\"content\":{\"text\":\"最近一次提交:${CI_COMMIT_TITLE}\\n提交人:${GITLAB_USER_NAME}\\n项目:${CI_PROJECT_NAME}\\n环境:${DEPLOY_DESC}\\n更新部署失败,请及时到gitlab上查看\\n工作流地址:${CI_PIPELINE_URL}\"}}" \
|
||||
${FEISHU_WEBHOOK}
|
||||
when: on_failure
|
||||
@@ -1,55 +1,29 @@
|
||||

|
||||

|
||||
|
||||
<p align="center">
|
||||
<a href="/README.md">English</a>
|
||||
|
|
||||
<a href="/readme/readme-jp.md">日本語</a>
|
||||
English
|
||||
|
|
||||
<a href="/readme/readme-zh-cn.md">简体中文</a>
|
||||
|
|
||||
<a href="/readme/readme-zh-tw.md">繁體中文</a>
|
||||
</p>
|
||||
|
||||
<b>🦄 APIPark is an open-source, all-in-one AI gateway and API developer portal, helping developers and enterprises easily manage, integrate, and deploy AI services. APIPark is open-sourced under the Apache 2.0 license, which means it's free for commercial use!</b>
|
||||
APIPark is the world's first open-source enterprise API open platform, helping organizations quickly build internal API portals/marketplaces and enjoy ultimate forwarding performance, API observability, service governance, multi tenant management, subscription approval processes, and many other benefits.
|
||||
|
||||
<br>
|
||||
|
||||
✨ With APIPark, you can:
|
||||
1. Quickly connect to 100+ AI models, supporting all mainstream AI Companies!
|
||||
2. Combine AI models and prompt templates into APIs, such as creating a sentiment analysis API, translation API, or data analysis API based on OpenAI GPT-4 and some custom prompts.
|
||||
3. Standardize the data format of all AI API requests, so switching AI models or modifying prompts won’t affect your APP or microservices, simplifying your AI usage and maintenance costs.
|
||||
4. Share APIs within the team through APIPark's developer portal.
|
||||
5. Manage calling applications and API keys to ensure your API's security and stability.
|
||||
6. Monitor your AI API usage with clear charts.
|
||||
7. Quickly export API request logs to third-party logging platforms.
|
||||
# ✨ Quick Start
|
||||
APIPark is committed to providing one-stop API open and access products for global enterprises, and creating a new generation of API asset governance standards. APIPark is open sourced using the Apache 2.0 protocol.
|
||||
|
||||
<br>
|
||||
|
||||
✨ APIPark is also a powerful cloud-native API gateway:
|
||||
1. It outperforms Nginx with higher performance, supports cluster deployment, and handles large-scale traffic.
|
||||
2. Share REST APIs within the team, manage API call relationships, and prevent management costs and data breaches caused by chaotic API calls.
|
||||
APIPark is committed to addressing several key challenges that enterprises face in API management:
|
||||
- Complex API call relationships: Simplifies API interactions in complex system architectures.
|
||||
- Data usage tracking: Provides comprehensive API usage monitoring and reporting.
|
||||
- Compliance management: Ensure that APIs comply with organizational and regulatory standards.
|
||||
- Fault detection and troubleshooting: Simplify the identification and resolution of system issues.
|
||||
- Quantifying the Value of Data Assets: Enhancing the Visibility and Valuation of Data Assets.
|
||||
|
||||
|
||||
<br>
|
||||
|
||||
# 💌 Why Did We Build APIPark?
|
||||
Before building APIPark, we spent seven years developing an API development and automated testing platform with over 1 million developer users, 500+ enterprise customers, and multi-million-dollar investment from Sequoia Capital.
|
||||
|
||||
As AI and Agents evolved, we noticed many enterprises wanted to integrate AI into both internal and third-party APIs, enabling AI agents to perform more complex tasks beyond being just knowledge-based Q&A bots. Hence, we built APIPark—your all-in-one AI gateway and API developer portal to accelerate your AI API development and quickly build your product or AI agent!
|
||||
|
||||
<br>
|
||||
|
||||
# ✨ Quick Start
|
||||
APIPark is designed to solve the following problems:
|
||||
- Seamlessly connect to various AI models and package these AI capabilities into APIs for easy calling, significantly reducing the barrier to using AI models.
|
||||
- Manage complex AI & API call relationships.
|
||||
- Manage API creation, monitoring, and security.
|
||||
- Fault detection and troubleshooting: Simplifying system issue identification and resolution.
|
||||
- Quantify data asset value: Enhance the visibility and valuation of data assets.
|
||||
|
||||
<br>
|
||||
|
||||
😍 Deploying APIPark is incredibly simple. With just one command line, you can deploy your AI gateway and API developer portal in under 5 minutes.
|
||||
😍 APIPark deployment is very simple, just one command line can deploy your API open platform in 5 minutes.
|
||||
|
||||
```
|
||||
curl -sSO https://download.apipark.com/install/quick-start.sh ; bash quick-start.sh
|
||||
@@ -57,161 +31,131 @@ curl -sSO https://download.apipark.com/install/quick-start.sh ; bash quick-sta
|
||||
|
||||
<br>
|
||||
|
||||
# 🔥 Features
|
||||
# 🔥 characteristic
|
||||
<table>
|
||||
<tr>
|
||||
<th>
|
||||
Connect to 100+ AI models
|
||||
</th>
|
||||
<th>
|
||||
Unified API to use all AI
|
||||
</th>
|
||||
<tr>
|
||||
<th>
|
||||
Centralize management and display of all API services within the enterprise
|
||||
</th>
|
||||
<th>
|
||||
Covering the entire process of API design, release, operation, and deployment
|
||||
</th>
|
||||
|
||||
</tr>
|
||||
</tr>
|
||||
|
||||
<tr>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/10/AI-Gateway.png" />
|
||||
</td>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/10/Unified-API.png" />
|
||||
</td>
|
||||
</tr>
|
||||
|
||||
<tr>
|
||||
<th>
|
||||
Transform AI & Prompt to REST API
|
||||
</th>
|
||||
<th>
|
||||
API Developer Portal
|
||||
</th>
|
||||
|
||||
</tr>
|
||||
|
||||
<tr>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/10/Prompt-template.png" />
|
||||
</td>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/10/developer-portal.png" />
|
||||
</td>
|
||||
</tr>
|
||||
|
||||
<tr>
|
||||
<th>
|
||||
High Performance
|
||||
</th>
|
||||
<th>
|
||||
Manage API lifecycle
|
||||
</th>
|
||||
|
||||
</tr>
|
||||
|
||||
<tr>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/10/hyper-performance.png" />
|
||||
</td>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/08/Life-Cycle.png" />
|
||||
</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/08/%E9%A1%B5%E9%9D%A2-1.png" />
|
||||
API Service Square is one of the core functions of APIPark, aimed at solving the problem of scattered and chaotic management of APIs within enterprises. Through API Service Square, enterprises can display all API services on a unified platform, making it easy for different departments and teams to find and use the required API services.
|
||||
</td>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/08/Life-Cycle.png" />
|
||||
The API lifecycle management function helps enterprises standardize the API management process, manage API traffic forwarding and load balancing, and manage all API versions released to the public. Improve the quality and maintainability of APIs. Through this feature, enterprises can achieve efficient API development and stable operation, thereby supporting rapid business development and innovation.
|
||||
</td>
|
||||
</tr>
|
||||
|
||||
<tr>
|
||||
<th>
|
||||
Review subscription before allowing API requests
|
||||
</th>
|
||||
<th>
|
||||
Manage subscriber
|
||||
</th>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>
|
||||
Manage multiple tenants to ensure data isolation and security
|
||||
</th>
|
||||
<th>
|
||||
API resources need to be applied for and approved before they can be called
|
||||
</th>
|
||||
|
||||
<tr>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/08/Application.png" />
|
||||
</td>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/08/Multi-tenant.png" />
|
||||
</td>
|
||||
</tr>
|
||||
</tr>
|
||||
|
||||
<tr>
|
||||
<th>
|
||||
Logging
|
||||
</th>
|
||||
<th>
|
||||
Analysis
|
||||
</th>
|
||||
</tr>
|
||||
<tr>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/08/Multi-tenant.png" />
|
||||
The multi tenant management function provides enterprises with the ability to manage multiple tenants on the same platform. Each tenant can have independent resource, user, and permission settings, ensuring the isolation of data and operations, and helping to improve resource utilization efficiency and management convenience.
|
||||
</td>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/08/Application.png" />
|
||||
APIPark provides a process approval function for all API resources to avoid violating regulations or bypassing the platform to call APIs. The caller needs to first apply for API resources and wait for the service provider's approval before officially calling the API.
|
||||
</td>
|
||||
</tr>
|
||||
|
||||
<tr>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/08/Chart-1.png" />
|
||||
</td>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/08/Chart.png" />
|
||||
</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<th>
|
||||
Assist in troubleshooting API access at any given time through detailed call logs
|
||||
</th>
|
||||
<th>
|
||||
Rich statistical reports*
|
||||
</th>
|
||||
|
||||
</tr>
|
||||
|
||||
<tr>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/08/Chart-1.png" />
|
||||
The API call log function provides comprehensive logging capabilities for enterprises, detailing all relevant information of each API call. Through these logs, enterprises can quickly track and troubleshoot issues in API calls, ensuring stable system operation and data security.
|
||||
</td>
|
||||
<td width="50%">
|
||||
<img src="https://apipark.com/wp-content/uploads/2024/08/Chart.png" />
|
||||
By analyzing historical call data, APIPark can display the long-term call trends and performance changes of APIs, helping enterprises to conduct preventive maintenance before problems occur.
|
||||
</td>
|
||||
</tr>
|
||||
|
||||
</table>
|
||||
|
||||
<br>
|
||||
|
||||
# 🚀 Use Cases
|
||||
## Simplify AI Integration Costs
|
||||
- Connect to 100+ major models from all mainstream AI vendors, with standardized API calls requiring no additional adaptation work.
|
||||
- Combine AI models and prompt templates to create new AI APIs, simplifying AI API development.
|
||||
- Quickly share AI APIs within the team.
|
||||
|
||||
## Enhance Operational Efficiency
|
||||
- Quickly build an internal API developer portal.
|
||||
- Efficiently manage and call APIs.
|
||||
- Reduce complex system call relationships.
|
||||
|
||||
## Ensure Compliance and Security
|
||||
- Powerful service governance and compliance management features.
|
||||
- Granular permission management for application calls.
|
||||
- Ensure API call security and compliance, reducing enterprise risk.
|
||||
|
||||
## Simplify System Troubleshooting
|
||||
- Use monitoring and diagnostic tools to quickly identify and resolve issues.
|
||||
- Reduce downtime and improve system stability.
|
||||
|
||||
## Multi-Tenant Management and Flexible Subscription
|
||||
- Supports multi-tenant management to meet different business unit needs.
|
||||
- Flexible subscription and approval processes simplify API usage and management.
|
||||
|
||||
## Improve API Observability
|
||||
- Real-time monitoring and tracking of API usage.
|
||||
- Fully understand data flow to enhance data usage transparency.
|
||||
|
||||
<br>
|
||||
|
||||
# 🚩 Roadmap
|
||||
We’ve set exciting goals for APIPark: enabling everyone to quickly create their own products and AI agents using AI and APIs!
|
||||
# 🚩 Applicable scenarios
|
||||
## Improve operational efficiency
|
||||
- Quickly build an internal API portal.
|
||||
- Efficient management and API calling.
|
||||
- Reduce complex inter system call relationships.
|
||||
|
||||
To achieve this goal, we plan to add new features to APIPark, including:
|
||||
1. Integrating with API marketplaces such as Postman, RapidAPI, APISpace, APILayer, etc. You can directly use APIs from various API marketplaces through APIPark and make them smarter using AI.
|
||||
2. Integrating AI Agents such as Langchain, AgentGPT, Auto-GPT, Dify, and more, allowing AI Agents to access your internal or third-party APIs through APIPark to complete more complex tasks.
|
||||
3. Intelligent API orchestration: APIPark will provide a unified API entry point and automatically orchestrate multiple APIs to fulfill your requests based on the API content.
|
||||
## Ensure compliance and safety
|
||||
- Powerful service governance and compliance management capabilities.
|
||||
- Refine the management of application call permissions.
|
||||
- Ensure the security and compliance of API calls to reduce enterprise risks.
|
||||
|
||||
## Simplify system troubleshooting
|
||||
- Utilize monitoring and fault diagnosis tools to quickly identify and solve problems.
|
||||
- Reduce downtime and improve system stability.
|
||||
|
||||
## Multi tenant management and flexible subscriptions
|
||||
- Support multi tenant management to meet the needs of different business units.
|
||||
- Flexible subscription and approval processes simplify the use and management of APIs.
|
||||
|
||||
## Enhance API observability
|
||||
- Real time monitoring and tracking of API usage.
|
||||
- Fully grasp the flow of data and enhance the transparency of data usage.
|
||||
|
||||
## Enhance the value of data assets
|
||||
- Quantify and analyze API usage to better evaluate and enhance the value of data assets.
|
||||
- Provide data support for decision-making.
|
||||
|
||||
<br>
|
||||
|
||||
# 📕 Documentation
|
||||
Visit [APIPark Documentation](https://docs.apipark.com/docs/deploy) for detailed installation guides, API references, and usage instructions.
|
||||
# 🚀 One click deployment
|
||||
APIPark deployment is very simple, just one command line can deploy your API asset open platform in 5 minutes.
|
||||
|
||||
```
|
||||
curl -sSO https://download.apipark.com/install/quick-start.sh ; bash quick-start.sh
|
||||
```
|
||||
|
||||
<br>
|
||||
|
||||
# 🧾 License
|
||||
APIPark uses the Apache 2.0 License. For more details, please refer to the LICENSE file.
|
||||
## 📕 file
|
||||
Visit [APIPark Document]( https://docs.apipark.com/docs/install )Get detailed installation guides, API references, and usage instructions.
|
||||
|
||||
<br>
|
||||
|
||||
# 💌 Contact Us
|
||||
For enterprise-level features and professional technical support, contact our pre-sales experts for personalized demos, customized solutions, and pricing.
|
||||
## 🧾 licence
|
||||
APIPark uses the Apache 2.0 license. For more details, please refer to the LICENSE document.
|
||||
|
||||
|
||||
<br>
|
||||
|
||||
## 💌 contact us
|
||||
For enterprise level functionality and professional technical support, please contact pre-sales experts for personalized demonstrations, customized solutions, and pricing.
|
||||
|
||||
- Website: https://apipark.com
|
||||
- Email: contact@apipark.com
|
||||
- Email: dev@apipark.com
|
||||
|
||||
<br>
|
||||
|
||||
🙏 A big thanks to everyone who helped shape APIPark. We are thrilled to hear the community’s thoughts! Let’s make the world of APIs and AI stronger and more fun together. 🎉
|
||||
Thank you for choosing APIPark, the next-generation API Open platform.
|
||||
|
||||
@@ -1,22 +0,0 @@
|
||||
package ai_provider_local
|
||||
|
||||
import "time"
|
||||
|
||||
type Model struct {
|
||||
Name string `json:"name"`
|
||||
Model string `json:"model"`
|
||||
ModifiedAt time.Time `json:"modified_at"`
|
||||
Size int64 `json:"size"`
|
||||
Digest string `json:"digest"`
|
||||
Details ModelDetails `json:"details,omitempty"`
|
||||
}
|
||||
|
||||
// ModelDetails provides details about a model.
|
||||
type ModelDetails struct {
|
||||
ParentModel string `json:"parent_model"`
|
||||
Format string `json:"format"`
|
||||
Family string `json:"family"`
|
||||
Families []string `json:"families"`
|
||||
ParameterSize string `json:"parameter_size"`
|
||||
QuantizationLevel string `json:"quantization_level"`
|
||||
}
|
||||
@@ -1,336 +0,0 @@
|
||||
package ai_provider_local
|
||||
|
||||
import (
|
||||
"context"
|
||||
"fmt"
|
||||
"sync"
|
||||
|
||||
"github.com/ollama/ollama/progress"
|
||||
|
||||
"github.com/eolinker/eosc"
|
||||
"github.com/ollama/ollama/api"
|
||||
)
|
||||
|
||||
var (
|
||||
taskExecutor = NewAsyncExecutor(100)
|
||||
)
|
||||
|
||||
// Pipeline 结构体,表示每个用户的管道
|
||||
type Pipeline struct {
|
||||
id string
|
||||
channel chan PullMessage
|
||||
ctx context.Context
|
||||
cancel context.CancelFunc
|
||||
}
|
||||
|
||||
func (p *Pipeline) Message() <-chan PullMessage {
|
||||
return p.channel
|
||||
}
|
||||
|
||||
// AsyncExecutor 结构体,管理不同模型的管道和任务队列
|
||||
type AsyncExecutor struct {
|
||||
ctx context.Context
|
||||
cancel context.CancelFunc
|
||||
mu sync.Mutex
|
||||
pipelines map[string]*modelPipeline // 以模型为 key,存管道列表
|
||||
msgQueue chan messageTask // 消息队列
|
||||
}
|
||||
|
||||
type modelPipeline struct {
|
||||
ctx context.Context
|
||||
cancel context.CancelFunc
|
||||
pipelines eosc.Untyped[string, *Pipeline]
|
||||
pullFn PullCallback
|
||||
maxSize int
|
||||
}
|
||||
|
||||
func (m *modelPipeline) List() []*Pipeline {
|
||||
return m.pipelines.List()
|
||||
}
|
||||
|
||||
func (m *modelPipeline) Get(id string) (*Pipeline, bool) {
|
||||
return m.pipelines.Get(id)
|
||||
}
|
||||
|
||||
func (m *modelPipeline) Set(id string, p *Pipeline) error {
|
||||
_, ok := m.pipelines.Get(id)
|
||||
if !ok {
|
||||
if m.pipelines.Count() > m.maxSize {
|
||||
return fmt.Errorf("pipeline size exceed %d", m.maxSize)
|
||||
}
|
||||
}
|
||||
m.pipelines.Set(id, p)
|
||||
return nil
|
||||
}
|
||||
|
||||
func (m *modelPipeline) AddPipeline(id string) (*Pipeline, error) {
|
||||
ctx, cancel := context.WithCancel(m.ctx)
|
||||
pipeline := &Pipeline{
|
||||
ctx: ctx,
|
||||
cancel: cancel,
|
||||
id: id,
|
||||
channel: make(chan PullMessage, 10), // 带缓冲,防止阻塞
|
||||
}
|
||||
err := m.Set(id, pipeline)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
return pipeline, nil
|
||||
}
|
||||
|
||||
func (m *modelPipeline) Close() {
|
||||
m.cancel()
|
||||
ids := m.pipelines.Keys()
|
||||
for _, id := range ids {
|
||||
m.ClosePipeline(id)
|
||||
}
|
||||
return
|
||||
}
|
||||
|
||||
func (m *modelPipeline) ClosePipeline(id string) {
|
||||
// 关闭管道
|
||||
p, has := m.pipelines.Del(id)
|
||||
if !has {
|
||||
return
|
||||
}
|
||||
p.cancel()
|
||||
close(p.channel)
|
||||
}
|
||||
|
||||
func newModelPipeline(ctx context.Context, maxSize int) *modelPipeline {
|
||||
ctx, cancel := context.WithCancel(ctx)
|
||||
return &modelPipeline{
|
||||
pipelines: eosc.BuildUntyped[string, *Pipeline](),
|
||||
ctx: ctx,
|
||||
cancel: cancel,
|
||||
maxSize: maxSize,
|
||||
}
|
||||
}
|
||||
|
||||
// messageTask 结构体,包含模型名和消息内容
|
||||
type messageTask struct {
|
||||
message PullMessage
|
||||
}
|
||||
|
||||
type PullMessage struct {
|
||||
Model string
|
||||
Status string
|
||||
Digest string
|
||||
Total int64
|
||||
Completed int64
|
||||
Msg string
|
||||
}
|
||||
|
||||
// NewAsyncExecutor 创建一个新的异步任务执行器
|
||||
func NewAsyncExecutor(queueSize int) *AsyncExecutor {
|
||||
ctx, cancel := context.WithCancel(context.Background())
|
||||
executor := &AsyncExecutor{
|
||||
ctx: ctx,
|
||||
cancel: cancel,
|
||||
pipelines: make(map[string]*modelPipeline), // 以模型为 key,存管道列表
|
||||
msgQueue: make(chan messageTask, queueSize),
|
||||
}
|
||||
executor.StartMessageDistributor()
|
||||
|
||||
return executor
|
||||
}
|
||||
|
||||
func (e *AsyncExecutor) GetModelPipeline(model string) (*modelPipeline, bool) {
|
||||
e.mu.Lock()
|
||||
defer e.mu.Unlock()
|
||||
|
||||
mp, ok := e.pipelines[model]
|
||||
return mp, ok
|
||||
}
|
||||
|
||||
func (e *AsyncExecutor) SetModelPipeline(model string, mp *modelPipeline) {
|
||||
e.mu.Lock()
|
||||
defer e.mu.Unlock()
|
||||
e.pipelines[model] = mp
|
||||
}
|
||||
|
||||
// ClosePipeline 关闭管道并移除
|
||||
func (e *AsyncExecutor) ClosePipeline(model string, id string) {
|
||||
e.mu.Lock()
|
||||
defer e.mu.Unlock()
|
||||
mp, ok := e.pipelines[model]
|
||||
if !ok {
|
||||
return
|
||||
}
|
||||
mp.ClosePipeline(id)
|
||||
}
|
||||
|
||||
// CloseModelPipeline 关闭当前模型所有管道
|
||||
func (e *AsyncExecutor) CloseModelPipeline(model string) {
|
||||
e.mu.Lock()
|
||||
defer e.mu.Unlock()
|
||||
mp, ok := e.pipelines[model]
|
||||
if !ok {
|
||||
return
|
||||
}
|
||||
mp.Close()
|
||||
delete(e.pipelines, model)
|
||||
}
|
||||
|
||||
// StartMessageDistributor 启动消息分发器
|
||||
func (e *AsyncExecutor) StartMessageDistributor() {
|
||||
go func() {
|
||||
for task := range e.msgQueue {
|
||||
msg := task.message
|
||||
e.DistributeToModelPipelines(msg.Model, msg)
|
||||
if msg.Status == "error" || msg.Status == "success" {
|
||||
mp, has := e.GetModelPipeline(msg.Model)
|
||||
if has && mp.pullFn != nil {
|
||||
mp.pullFn(msg)
|
||||
}
|
||||
e.CloseModelPipeline(msg.Model)
|
||||
continue
|
||||
}
|
||||
}
|
||||
}()
|
||||
}
|
||||
|
||||
// DistributeToModelPipelines 仅将消息分发给指定模型的管道
|
||||
func (e *AsyncExecutor) DistributeToModelPipelines(model string, msg PullMessage) {
|
||||
e.mu.Lock()
|
||||
defer e.mu.Unlock()
|
||||
pipelines, ok := e.pipelines[model]
|
||||
if !ok {
|
||||
return
|
||||
}
|
||||
for _, pipeline := range pipelines.List() {
|
||||
select {
|
||||
case pipeline.channel <- msg:
|
||||
default:
|
||||
// 如果管道已满,跳过
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
type PullCallback func(msg PullMessage) error
|
||||
|
||||
func PullModel(model string, id string, fn PullCallback) (*Pipeline, error) {
|
||||
if client == nil {
|
||||
return nil, fmt.Errorf("client not initialized")
|
||||
}
|
||||
mp, has := taskExecutor.GetModelPipeline(model)
|
||||
if !has {
|
||||
mp = newModelPipeline(taskExecutor.ctx, 100)
|
||||
mp.pullFn = fn
|
||||
taskExecutor.SetModelPipeline(model, mp)
|
||||
}
|
||||
p, err := mp.AddPipeline(id)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
if !has {
|
||||
var status string
|
||||
bars := make(map[string]*progress.Bar)
|
||||
fn := func(resp api.ProgressResponse) error {
|
||||
if resp.Digest != "" {
|
||||
bar, ok := bars[resp.Digest]
|
||||
if !ok {
|
||||
bar = progress.NewBar(fmt.Sprintf("pulling %s...", resp.Digest[7:19]), resp.Total, resp.Completed)
|
||||
bars[resp.Digest] = bar
|
||||
}
|
||||
bar.Set(resp.Completed)
|
||||
|
||||
taskExecutor.msgQueue <- messageTask{
|
||||
message: PullMessage{
|
||||
Model: model,
|
||||
Digest: resp.Digest,
|
||||
Total: resp.Total,
|
||||
Completed: resp.Completed,
|
||||
Msg: bar.String(),
|
||||
Status: resp.Status,
|
||||
},
|
||||
}
|
||||
} else if status != resp.Status {
|
||||
taskExecutor.msgQueue <- messageTask{
|
||||
message: PullMessage{
|
||||
Model: model,
|
||||
Digest: resp.Digest,
|
||||
Total: resp.Total,
|
||||
Completed: resp.Completed,
|
||||
Msg: status,
|
||||
Status: resp.Status,
|
||||
},
|
||||
}
|
||||
}
|
||||
|
||||
return nil
|
||||
}
|
||||
go func() {
|
||||
err = client.Pull(mp.ctx, &api.PullRequest{Model: model}, fn)
|
||||
if err != nil {
|
||||
taskExecutor.msgQueue <- messageTask{
|
||||
message: PullMessage{
|
||||
Model: model,
|
||||
Status: "error",
|
||||
Digest: "",
|
||||
Total: 0,
|
||||
Completed: 0,
|
||||
Msg: err.Error(),
|
||||
},
|
||||
}
|
||||
}
|
||||
}()
|
||||
|
||||
}
|
||||
|
||||
return p, nil
|
||||
}
|
||||
|
||||
func StopPull(model string) {
|
||||
if client == nil {
|
||||
return
|
||||
}
|
||||
taskExecutor.CloseModelPipeline(model)
|
||||
}
|
||||
|
||||
func CancelPipeline(model string, id string) {
|
||||
taskExecutor.ClosePipeline(model, id)
|
||||
}
|
||||
|
||||
func RemoveModel(model string) error {
|
||||
if client == nil {
|
||||
return fmt.Errorf("client not initialized")
|
||||
}
|
||||
taskExecutor.CloseModelPipeline(model)
|
||||
err := client.Delete(context.Background(), &api.DeleteRequest{Model: model})
|
||||
if err != nil {
|
||||
if err.Error() == fmt.Sprintf("model '%s' not found", model) {
|
||||
return nil
|
||||
}
|
||||
}
|
||||
return err
|
||||
}
|
||||
|
||||
func ModelsInstalled() ([]Model, error) {
|
||||
if client == nil {
|
||||
return nil, fmt.Errorf("client not initialized")
|
||||
}
|
||||
result, err := client.List(context.Background())
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
models := make([]Model, 0, len(result.Models))
|
||||
for _, m := range result.Models {
|
||||
models = append(models, Model{
|
||||
Name: m.Name,
|
||||
Model: m.Model,
|
||||
ModifiedAt: m.ModifiedAt,
|
||||
Size: m.Size,
|
||||
Digest: m.Digest,
|
||||
Details: ModelDetails{
|
||||
ParentModel: m.Details.ParentModel,
|
||||
Format: m.Details.Format,
|
||||
Family: m.Details.Family,
|
||||
Families: m.Details.Families,
|
||||
ParameterSize: m.Details.ParameterSize,
|
||||
QuantizationLevel: m.Details.QuantizationLevel,
|
||||
},
|
||||
})
|
||||
}
|
||||
return models, nil
|
||||
}
|
||||
@@ -1,80 +0,0 @@
|
||||
package ai_provider_local
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"io"
|
||||
"net/http"
|
||||
"testing"
|
||||
|
||||
"github.com/gin-contrib/gzip"
|
||||
|
||||
"github.com/eolinker/eosc/log"
|
||||
|
||||
"github.com/google/uuid"
|
||||
|
||||
"github.com/gin-gonic/gin"
|
||||
)
|
||||
|
||||
func TestPullModel(t *testing.T) {
|
||||
// 创建 Gin 引擎
|
||||
r := gin.Default()
|
||||
r.Use(gzip.Gzip(gzip.DefaultCompression))
|
||||
// 设置路由,监听 "/stream" 路径
|
||||
r.GET("/stream", streamHandler)
|
||||
r.GET("/stop", stopPull)
|
||||
r.GET("/models", models)
|
||||
|
||||
// 启动 HTTP 服务器
|
||||
r.Run(":11180")
|
||||
}
|
||||
|
||||
func streamHandler(c *gin.Context) {
|
||||
// 创建一个通道,用于监测客户端关闭连接的信号
|
||||
model := c.Query("model")
|
||||
p, err := PullModel(model, uuid.NewString(), nil)
|
||||
if err != nil {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
|
||||
return
|
||||
}
|
||||
done := make(chan struct{})
|
||||
// 启动一个 goroutine 监听客户端关闭连接
|
||||
go func() {
|
||||
select {
|
||||
case <-c.Writer.CloseNotify():
|
||||
log.Info("client closed connection,close pipeline")
|
||||
taskExecutor.ClosePipeline(model, p.id)
|
||||
case <-done:
|
||||
}
|
||||
}()
|
||||
|
||||
c.Stream(func(w io.Writer) bool {
|
||||
select {
|
||||
case msg, ok := <-p.channel:
|
||||
if !ok {
|
||||
return false
|
||||
}
|
||||
_, err := w.Write([]byte(fmt.Sprintf("%s\n", msg.Msg)))
|
||||
if err != nil {
|
||||
log.Error("write message error: %v", err)
|
||||
return false
|
||||
}
|
||||
return true
|
||||
}
|
||||
})
|
||||
done <- struct{}{}
|
||||
}
|
||||
|
||||
func stopPull(c *gin.Context) {
|
||||
model := c.Query("model")
|
||||
StopPull(model)
|
||||
c.JSON(http.StatusOK, gin.H{"message": "stop pull model"})
|
||||
}
|
||||
|
||||
func models(c *gin.Context) {
|
||||
ms, err := ModelsInstalled()
|
||||
if err != nil {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
|
||||
return
|
||||
}
|
||||
c.JSON(http.StatusOK, gin.H{"models": ms})
|
||||
}
|
||||
@@ -1,31 +0,0 @@
|
||||
package ai_provider_local
|
||||
|
||||
import (
|
||||
"net/http"
|
||||
"net/url"
|
||||
|
||||
"github.com/ollama/ollama/api"
|
||||
)
|
||||
|
||||
var (
|
||||
client *api.Client
|
||||
ProviderLocal = "LocalModel"
|
||||
)
|
||||
|
||||
func ResetLocalAddress(address string) error {
|
||||
u, err := url.Parse(address)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
client = api.NewClient(u, http.DefaultClient)
|
||||
return nil
|
||||
}
|
||||
|
||||
var (
|
||||
LocalConfig = "{\n \"temperature\": \"\",\n \"top_p\": \"\",\n \"max_tokens\": \"\"\n}"
|
||||
LocalSvg = `<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="50" height="50" viewBox="0 0 50 50">
|
||||
<image id="椭圆_1_拷贝" data-name="椭圆 1 拷贝" x="5" y="4" width="42" height="38" xlink:href="data:img/png;base64,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"/>
|
||||
</svg>
|
||||
|
||||
`
|
||||
)
|
||||
@@ -1,70 +0,0 @@
|
||||
package ai_provider_local
|
||||
|
||||
import (
|
||||
"embed"
|
||||
"encoding/json"
|
||||
"strings"
|
||||
|
||||
"github.com/eolinker/eosc/log"
|
||||
)
|
||||
|
||||
var (
|
||||
//go:embed models.json
|
||||
modelsFs embed.FS
|
||||
modelCanInstall []ModelDetail
|
||||
modelVersion string
|
||||
modelTags = make(map[string][]ModelDetail)
|
||||
)
|
||||
|
||||
type ModelConfig struct {
|
||||
Models []ModelDetail `json:"models"`
|
||||
Version string `json:"version"`
|
||||
}
|
||||
|
||||
type ModelDetail struct {
|
||||
Id string `json:"id"`
|
||||
Name string `json:"name"`
|
||||
Description string `json:"description"`
|
||||
Size string `json:"size"`
|
||||
Digest string `json:"digest"`
|
||||
Provider string `json:"provider"`
|
||||
IsPopular bool `json:"is_popular"`
|
||||
Latest bool `json:"latest"`
|
||||
}
|
||||
|
||||
func init() {
|
||||
data, err := modelsFs.ReadFile("models.json")
|
||||
if err != nil {
|
||||
log.Info("read models.json error: ", err)
|
||||
return
|
||||
}
|
||||
var cfg ModelConfig
|
||||
err = json.Unmarshal(data, &cfg)
|
||||
if err != nil {
|
||||
log.Info("unmarshal models.json error: ", err)
|
||||
return
|
||||
}
|
||||
modelVersion = cfg.Version
|
||||
modelCanInstall = make([]ModelDetail, 0, len(cfg.Models))
|
||||
for _, model := range cfg.Models {
|
||||
if _, ok := modelTags[model.Id]; !ok {
|
||||
modelTags[model.Id] = make([]ModelDetail, 0)
|
||||
}
|
||||
names := strings.Split(model.Id, ":")
|
||||
|
||||
modelTags[names[0]] = append(modelTags[names[0]], model)
|
||||
if !model.Latest {
|
||||
continue
|
||||
}
|
||||
modelCanInstall = append(modelCanInstall, model)
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
func ModelsCanInstall() ([]ModelDetail, string) {
|
||||
return modelCanInstall, modelVersion
|
||||
}
|
||||
|
||||
func ModelsCanInstallById(id string) []ModelDetail {
|
||||
return modelTags[id]
|
||||
}
|
||||
@@ -1,7 +0,0 @@
|
||||
package ai_provider_local
|
||||
|
||||
import "testing"
|
||||
|
||||
func TestModels(t *testing.T) {
|
||||
t.Log(ModelsCanInstall())
|
||||
}
|
||||
@@ -1,21 +0,0 @@
|
||||
package entity
|
||||
|
||||
type AIModel struct {
|
||||
Model string `json:"model" yaml:"model"`
|
||||
Label map[string]string `json:"label" yaml:"label"`
|
||||
ModelType string `json:"model_type" yaml:"model_type"`
|
||||
Features []string `json:"features" yaml:"features"`
|
||||
ModelProperties map[string]string `json:"model_properties" yaml:"model_properties"`
|
||||
ParameterRules []ParameterRule `json:"parameter_rules" yaml:"parameter_rules"`
|
||||
}
|
||||
|
||||
type ParameterRule struct {
|
||||
Name string `json:"name" yaml:"name"`
|
||||
Default interface{} `json:"default" yaml:"default"`
|
||||
Label map[string]string `json:"label" yaml:"label"`
|
||||
Type string `json:"type" yaml:"type"`
|
||||
Min float64 `json:"min" yaml:"min"`
|
||||
Max float64 `json:"max" yaml:"max"`
|
||||
Precision int `json:"precision" yaml:"precision"`
|
||||
Required bool `json:"required" yaml:"required"`
|
||||
}
|
||||
@@ -1,50 +0,0 @@
|
||||
package entity
|
||||
|
||||
var (
|
||||
ModelTypeLLM = "llm"
|
||||
ModelTypeTextEmbedding = "text-embedding"
|
||||
ModelTypeSpeech2Text = "speech2text"
|
||||
ModelTypeTTS = "tts"
|
||||
ModelTypeModeration = "moderation"
|
||||
|
||||
LanguageEnglish = "en_US"
|
||||
LanguageChinese = "zh_Hans"
|
||||
)
|
||||
|
||||
type Provider struct {
|
||||
Provider string `json:"provider" yaml:"provider"`
|
||||
Label map[string]string `json:"label" yaml:"label"`
|
||||
Description map[string]string `json:"description" yaml:"description"`
|
||||
IconSmall map[string]string `json:"icon_small" yaml:"icon_small"`
|
||||
IconLarge map[string]string `json:"icon_large" yaml:"icon_large"`
|
||||
Background string `json:"background" yaml:"background"`
|
||||
Help Help `json:"help" yaml:"help"`
|
||||
SupportedModelTypes []string `json:"supported_model_types" yaml:"supported_model_types"`
|
||||
ProviderCredentialSchema ProviderCredentialSchema `json:"provider_credential_schema" yaml:"provider_credential_schema"`
|
||||
Default map[string]string `json:"default" yaml:"default"`
|
||||
Address string `json:"address" yaml:"address"`
|
||||
Recommend bool `json:"recommend" yaml:"recommend"`
|
||||
Sort int `json:"sort" yaml:"sort"`
|
||||
ModelConfig ModelConfig `json:"model_config" yaml:"model_config"`
|
||||
}
|
||||
type ModelConfig struct {
|
||||
AccessConfigurationStatus bool `json:"access_configuration_status" yaml:"access_configuration_status"`
|
||||
AccessConfigurationDemo string `json:"access_configuration_demo" yaml:"access_configuration_demo"`
|
||||
}
|
||||
|
||||
type ProviderCredentialSchema struct {
|
||||
CredentialFormSchemas []CredentialFormSchema `json:"credential_form_schemas" yaml:"credential_form_schemas"`
|
||||
}
|
||||
|
||||
type CredentialFormSchema struct {
|
||||
Variable string `json:"variable" yaml:"variable"`
|
||||
Label map[string]string `json:"label" yaml:"label"`
|
||||
Type string `json:"type" yaml:"type"`
|
||||
Required bool `json:"required" yaml:"required"`
|
||||
Placeholder map[string]string `json:"placeholder" yaml:"placeholder"`
|
||||
}
|
||||
|
||||
type Help struct {
|
||||
Title map[string]string `json:"title" yaml:"title"`
|
||||
URL map[string]string `json:"url" yaml:"url"`
|
||||
}
|
||||
@@ -1,11 +0,0 @@
|
||||
package model_runtime
|
||||
|
||||
import "testing"
|
||||
|
||||
func TestLoad(t *testing.T) {
|
||||
Load()
|
||||
for _, p := range Providers() {
|
||||
t.Logf("Provider: %s", p.ID())
|
||||
t.Log(p.DefaultModel("llm"))
|
||||
}
|
||||
}
|
||||
@@ -1,159 +0,0 @@
|
||||
package model_runtime
|
||||
|
||||
import (
|
||||
"embed"
|
||||
"encoding/json"
|
||||
"fmt"
|
||||
"strings"
|
||||
|
||||
"github.com/eolinker/eosc"
|
||||
)
|
||||
|
||||
func init() {
|
||||
Load()
|
||||
}
|
||||
|
||||
type IConfig interface {
|
||||
Check(cfg string) error
|
||||
GenConfig(target string, origin string) (string, error)
|
||||
DefaultConfig() string
|
||||
}
|
||||
|
||||
func NewConfig(cfg string, validator IParamValidator) *Config {
|
||||
return &Config{cfg: cfg, validator: validator}
|
||||
}
|
||||
|
||||
type Config struct {
|
||||
cfg string
|
||||
validator IParamValidator
|
||||
}
|
||||
|
||||
func (c *Config) Check(cfg string) error {
|
||||
data := make(map[string]interface{})
|
||||
err := json.Unmarshal([]byte(cfg), &data)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
if c.validator != nil {
|
||||
return c.validator.Valid(data)
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func (c *Config) GenConfig(target string, origin string) (string, error) {
|
||||
if target == "" {
|
||||
target = "{}"
|
||||
}
|
||||
if origin == "" {
|
||||
origin = "{}"
|
||||
}
|
||||
var targetData map[string]interface{}
|
||||
|
||||
err := json.Unmarshal([]byte(target), &targetData)
|
||||
if err != nil {
|
||||
return "", err
|
||||
}
|
||||
var originData map[string]interface{}
|
||||
err = json.Unmarshal([]byte(origin), &originData)
|
||||
if err != nil {
|
||||
return "", err
|
||||
}
|
||||
if c.validator == nil {
|
||||
c.validator = ParamValidator(nil)
|
||||
}
|
||||
|
||||
return c.validator.GenConfig(targetData, originData)
|
||||
}
|
||||
|
||||
func (c *Config) DefaultConfig() string {
|
||||
return c.cfg
|
||||
}
|
||||
|
||||
const (
|
||||
DirAssets = "assets"
|
||||
)
|
||||
|
||||
var (
|
||||
//go:embed model-providers/*
|
||||
providerDir embed.FS
|
||||
)
|
||||
|
||||
func Load() error {
|
||||
files, err := providerDir.ReadDir("model-providers")
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
for _, file := range files {
|
||||
if !file.IsDir() {
|
||||
continue
|
||||
}
|
||||
name := fmt.Sprintf("model-providers/%s", file.Name())
|
||||
if file.Name() == "customize" {
|
||||
continue
|
||||
}
|
||||
err = LoadProvider(name)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func LoadProvider(name string) error {
|
||||
files, err := providerDir.ReadDir(name)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
var providerFile string
|
||||
models := make(map[string]eosc.Untyped[string, string])
|
||||
for _, file := range files {
|
||||
if file.IsDir() {
|
||||
result, err := ReadFile(providerDir, fmt.Sprintf("%s/%s", name, file.Name()))
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
models[file.Name()] = result
|
||||
continue
|
||||
}
|
||||
if strings.HasSuffix(file.Name(), ".yaml") {
|
||||
data, err := providerDir.ReadFile(fmt.Sprintf("%s/%s", name, file.Name()))
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
providerFile = string(data)
|
||||
}
|
||||
}
|
||||
provider, err := NewProvider(providerFile, models)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
//gateway.RegisterDynamicResourceDriver(provider.ID(), gateway.Worker{
|
||||
// Profession: gateway.ProfessionAIProvider,
|
||||
// Driver: provider.ID(),
|
||||
//})
|
||||
Register(provider.ID(), provider)
|
||||
return nil
|
||||
}
|
||||
|
||||
func ReadFile(dir embed.FS, name string) (eosc.Untyped[string, string], error) {
|
||||
|
||||
files, err := dir.ReadDir(name)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
result := eosc.BuildUntyped[string, string]()
|
||||
for _, file := range files {
|
||||
if file.IsDir() {
|
||||
continue
|
||||
}
|
||||
if !strings.HasSuffix(file.Name(), ".yaml") && !strings.HasSuffix(file.Name(), ".svg") {
|
||||
continue
|
||||
}
|
||||
data, err := dir.ReadFile(fmt.Sprintf("%s/%s", name, file.Name()))
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("open file %s error: %w", file.Name(), err)
|
||||
}
|
||||
result.Set(file.Name(), string(data))
|
||||
}
|
||||
return result, nil
|
||||
}
|
||||
@@ -1,56 +0,0 @@
|
||||
package model_runtime
|
||||
|
||||
import (
|
||||
"github.com/eolinker/eosc"
|
||||
)
|
||||
|
||||
var (
|
||||
defaultManager = NewManager()
|
||||
)
|
||||
|
||||
type Manager struct {
|
||||
providers eosc.Untyped[string, IProvider]
|
||||
}
|
||||
|
||||
func NewManager() *Manager {
|
||||
return &Manager{providers: eosc.BuildUntyped[string, IProvider]()}
|
||||
}
|
||||
|
||||
func (m *Manager) Set(name string, driver IProvider) {
|
||||
m.providers.Set(name, driver)
|
||||
}
|
||||
|
||||
func (m *Manager) Get(name string) (IProvider, bool) {
|
||||
return m.providers.Get(name)
|
||||
}
|
||||
|
||||
func (m *Manager) Del(name string) {
|
||||
m.providers.Del(name)
|
||||
}
|
||||
|
||||
func (m *Manager) List() []IProvider {
|
||||
//list := m.providers.List()
|
||||
//sort.Slice(list, func(i, j int) bool {
|
||||
// if list[i].Sort() == list[j].Sort() {
|
||||
// return list[i].ID() < list[j].ID()
|
||||
// }
|
||||
// return list[i].Sort() < list[j].Sort()
|
||||
//})
|
||||
return m.providers.List()
|
||||
}
|
||||
|
||||
func Register(name string, driver IProvider) {
|
||||
defaultManager.Set(name, driver)
|
||||
}
|
||||
|
||||
func Remove(name string) {
|
||||
defaultManager.Del(name)
|
||||
}
|
||||
|
||||
func GetProvider(name string) (IProvider, bool) {
|
||||
return defaultManager.Get(name)
|
||||
}
|
||||
|
||||
func Providers() []IProvider {
|
||||
return defaultManager.List()
|
||||
}
|
||||
@@ -1,42 +0,0 @@
|
||||
provider: anthropic
|
||||
label:
|
||||
en_US: Anthropic
|
||||
description:
|
||||
en_US: Anthropic’s powerful models, such as Claude 3.
|
||||
zh_Hans: Anthropic 的强大模型,例如 Claude 3。
|
||||
icon_small:
|
||||
en_US: icon_s_en.svg
|
||||
icon_large:
|
||||
en_US: icon_l_en.svg
|
||||
background: "#F0F0EB"
|
||||
help:
|
||||
title:
|
||||
en_US: Get your API Key from Anthropic
|
||||
zh_Hans: 从 Anthropic 获取 API Key
|
||||
url:
|
||||
en_US: https://console.anthropic.com/account/keys
|
||||
supported_model_types:
|
||||
- llm
|
||||
configurate_methods:
|
||||
- predefined-model
|
||||
provider_credential_schema:
|
||||
credential_form_schemas:
|
||||
- variable: anthropic_api_key
|
||||
label:
|
||||
en_US: API Key
|
||||
type: secret-input
|
||||
required: true
|
||||
placeholder:
|
||||
zh_Hans: 在此输入您的 API Key
|
||||
en_US: Enter your API Key
|
||||
- variable: anthropic_api_url
|
||||
label:
|
||||
en_US: https://api.anthropic.com/v1/
|
||||
type: text-input
|
||||
required: false
|
||||
placeholder:
|
||||
zh_Hans: 在此输入您的 API URL
|
||||
en_US: Enter your API URL
|
||||
address: https://api.anthropic.com/v1/
|
||||
recommend: true
|
||||
sort: 2
|
||||
@@ -1,78 +0,0 @@
|
||||
<svg width="90" height="20" viewBox="0 0 90 20" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<g clip-path="url(#clip0_8587_60274)">
|
||||
<mask id="mask0_8587_60274" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="0" y="4" width="90" height="11">
|
||||
<path d="M89.375 4.99805H0V14.998H89.375V4.99805Z" fill="white"/>
|
||||
</mask>
|
||||
<g mask="url(#mask0_8587_60274)">
|
||||
<mask id="mask1_8587_60274" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="0" y="4" width="90" height="11">
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||||
<path d="M0 4.99609H89.375V14.9961H0V4.99609Z" fill="white"/>
|
||||
</mask>
|
||||
<g mask="url(#mask1_8587_60274)">
|
||||
<mask id="mask2_8587_60274" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="0" y="4" width="90" height="11">
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||||
<path d="M0 4.99414H89.375V14.9941H0V4.99414Z" fill="white"/>
|
||||
</mask>
|
||||
<g mask="url(#mask2_8587_60274)">
|
||||
<mask id="mask3_8587_60274" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="0" y="4" width="90" height="11">
|
||||
<path d="M0 4.99219H89.375V14.9922H0V4.99219Z" fill="white"/>
|
||||
</mask>
|
||||
<g mask="url(#mask3_8587_60274)">
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||||
<path d="M18.1273 11.9244L13.7773 5.15625H11.4297V14.825H13.4321V8.05688L17.7821 14.825H20.1297V5.15625H18.1273V11.9244Z" fill="black" fill-opacity="0.92"/>
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||||
</g>
|
||||
<mask id="mask4_8587_60274" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="0" y="4" width="90" height="11">
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||||
<path d="M0 4.99219H89.375V14.9922H0V4.99219Z" fill="white"/>
|
||||
</mask>
|
||||
<g mask="url(#mask4_8587_60274)">
|
||||
<path d="M21.7969 7.02094H25.0423V14.825H27.1139V7.02094H30.3594V5.15625H21.7969V7.02094Z" fill="black" fill-opacity="0.92"/>
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||||
</g>
|
||||
<mask id="mask5_8587_60274" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="0" y="4" width="90" height="11">
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<path d="M0 4.99219H89.375V14.9922H0V4.99219Z" fill="white"/>
|
||||
</mask>
|
||||
<g mask="url(#mask5_8587_60274)">
|
||||
<path d="M38.6442 9.00994H34.0871V5.15625H32.0156V14.825H34.0871V10.8746H38.6442V14.825H40.7156V5.15625H38.6442V9.00994Z" fill="black" fill-opacity="0.92"/>
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||||
</g>
|
||||
<mask id="mask6_8587_60274" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="0" y="4" width="90" height="11">
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||||
<path d="M0 4.99219H89.375V14.9922H0V4.99219Z" fill="white"/>
|
||||
</mask>
|
||||
<g mask="url(#mask6_8587_60274)">
|
||||
<path d="M45.3376 7.02094H47.893C48.9152 7.02094 49.4539 7.39387 49.4539 8.09831C49.4539 8.80275 48.9152 9.17569 47.893 9.17569H45.3376V7.02094ZM51.5259 8.09831C51.5259 6.27506 50.186 5.15625 47.9897 5.15625H43.2656V14.825H45.3376V11.0404H47.6443L49.7164 14.825H52.0094L49.715 10.7521C50.8666 10.3094 51.5259 9.37721 51.5259 8.09831Z" fill="black" fill-opacity="0.92"/>
|
||||
</g>
|
||||
<mask id="mask7_8587_60274" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="0" y="4" width="90" height="11">
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<path d="M0 4.99219H89.375V14.9922H0V4.99219Z" fill="white"/>
|
||||
</mask>
|
||||
<g mask="url(#mask7_8587_60274)">
|
||||
<path d="M57.8732 13.0565C56.2438 13.0565 55.2496 11.8963 55.2496 10.004C55.2496 8.08416 56.2438 6.92394 57.8732 6.92394C59.4887 6.92394 60.4691 8.08416 60.4691 10.004C60.4691 11.8963 59.4887 13.0565 57.8732 13.0565ZM57.8732 4.99023C55.0839 4.99023 53.1094 7.06206 53.1094 10.004C53.1094 12.9184 55.0839 14.9902 57.8732 14.9902C60.6486 14.9902 62.6094 12.9184 62.6094 10.004C62.6094 7.06206 60.6486 4.99023 57.8732 4.99023Z" fill="black" fill-opacity="0.92"/>
|
||||
</g>
|
||||
<mask id="mask8_8587_60274" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="0" y="4" width="90" height="11">
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<path d="M0 4.99219H89.375V14.9922H0V4.99219Z" fill="white"/>
|
||||
</mask>
|
||||
<g mask="url(#mask8_8587_60274)">
|
||||
<path d="M69.1794 9.45194H66.6233V7.02094H69.1794C70.2019 7.02094 70.7407 7.43532 70.7407 8.23644C70.7407 9.03756 70.2019 9.45194 69.1794 9.45194ZM69.2762 5.15625H64.5508V14.825H66.6233V11.3166H69.2762C71.473 11.3166 72.8133 10.1564 72.8133 8.23644C72.8133 6.3165 71.473 5.15625 69.2762 5.15625Z" fill="black" fill-opacity="0.92"/>
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||||
</g>
|
||||
<mask id="mask9_8587_60274" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="0" y="4" width="90" height="11">
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<path d="M0 4.99219H89.375V14.9922H0V4.99219Z" fill="white"/>
|
||||
</mask>
|
||||
<g mask="url(#mask9_8587_60274)">
|
||||
<path d="M86.8413 11.5786C86.4823 12.5179 85.7642 13.0565 84.7837 13.0565C83.1542 13.0565 82.16 11.8963 82.16 10.004C82.16 8.08416 83.1542 6.92394 84.7837 6.92394C85.7642 6.92394 86.4823 7.46261 86.8413 8.40183H89.0369C88.4984 6.33002 86.8827 4.99023 84.7837 4.99023C81.9942 4.99023 80.0195 7.06206 80.0195 10.004C80.0195 12.9184 81.9942 14.9902 84.7837 14.9902C86.8965 14.9902 88.5122 13.6366 89.0508 11.5786H86.8413Z" fill="black" fill-opacity="0.92"/>
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||||
</g>
|
||||
<mask id="mask10_8587_60274" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="0" y="4" width="90" height="11">
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<path d="M0 4.99219H89.375V14.9922H0V4.99219Z" fill="white"/>
|
||||
</mask>
|
||||
<g mask="url(#mask10_8587_60274)">
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||||
<path d="M73.6484 5.15625L77.5033 14.825H79.6172L75.7624 5.15625H73.6484Z" fill="black" fill-opacity="0.92"/>
|
||||
</g>
|
||||
<mask id="mask11_8587_60274" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="0" y="4" width="90" height="11">
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<path d="M0 4.99219H89.375V14.9922H0V4.99219Z" fill="white"/>
|
||||
</mask>
|
||||
<g mask="url(#mask11_8587_60274)">
|
||||
<path d="M3.64038 10.9989L4.95938 7.60106L6.27838 10.9989H3.64038ZM3.85422 5.15625L0 14.825H2.15505L2.9433 12.7946H6.97558L7.76371 14.825H9.91875L6.06453 5.15625H3.85422Z" fill="black" fill-opacity="0.92"/>
|
||||
</g>
|
||||
</g>
|
||||
</g>
|
||||
</g>
|
||||
</g>
|
||||
<defs>
|
||||
<clipPath id="clip0_8587_60274">
|
||||
<rect width="89.375" height="10" fill="white" transform="translate(0 5)"/>
|
||||
</clipPath>
|
||||
</defs>
|
||||
</svg>
|
||||
|
Before Width: | Height: | Size: 5.3 KiB |
@@ -1,4 +0,0 @@
|
||||
<svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<rect width="24" height="24" rx="6" fill="#CA9F7B"/>
|
||||
<path d="M15.3843 6.43481H12.9687L17.3739 17.5652H19.7896L15.3843 6.43481ZM8.40522 6.43481L4 17.5652H6.4633L7.36417 15.2279H11.9729L12.8737 17.5652H15.337L10.9318 6.43481H8.40522ZM8.16104 13.1607L9.66852 9.24907L11.176 13.1607H8.16104Z" fill="#191918"/>
|
||||
</svg>
|
||||
|
Before Width: | Height: | Size: 410 B |
@@ -1,8 +0,0 @@
|
||||
- claude-3-5-sonnet-20240620
|
||||
- claude-3-haiku-20240307
|
||||
- claude-3-opus-20240229
|
||||
- claude-3-sonnet-20240229
|
||||
- claude-2.1
|
||||
- claude-instant-1.2
|
||||
- claude-2
|
||||
- claude-instant-1
|
||||
@@ -1,36 +0,0 @@
|
||||
model: claude-2.1
|
||||
label:
|
||||
en_US: claude-2.1
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '8.00'
|
||||
output: '24.00'
|
||||
unit: '0.000001'
|
||||
currency: USD
|
||||
@@ -1,37 +0,0 @@
|
||||
model: claude-2
|
||||
label:
|
||||
en_US: claude-2
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 100000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '8.00'
|
||||
output: '24.00'
|
||||
unit: '0.000001'
|
||||
currency: USD
|
||||
deprecated: true
|
||||
@@ -1,38 +0,0 @@
|
||||
model: claude-3-5-haiku-20241022
|
||||
label:
|
||||
en_US: claude-3-5-haiku-20241022
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 8192
|
||||
min: 1
|
||||
max: 8192
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '1.00'
|
||||
output: '5.00'
|
||||
unit: '0.000001'
|
||||
currency: USD
|
||||
@@ -1,39 +0,0 @@
|
||||
model: claude-3-5-sonnet-20240620
|
||||
label:
|
||||
en_US: claude-3-5-sonnet-20240620
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 8192
|
||||
min: 1
|
||||
max: 8192
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '3.00'
|
||||
output: '15.00'
|
||||
unit: '0.000001'
|
||||
currency: USD
|
||||
@@ -1,40 +0,0 @@
|
||||
model: claude-3-5-sonnet-20241022
|
||||
label:
|
||||
en_US: claude-3-5-sonnet-20241022
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
- document
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 8192
|
||||
min: 1
|
||||
max: 8192
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '3.00'
|
||||
output: '15.00'
|
||||
unit: '0.000001'
|
||||
currency: USD
|
||||
@@ -1,39 +0,0 @@
|
||||
model: claude-3-haiku-20240307
|
||||
label:
|
||||
en_US: claude-3-haiku-20240307
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '0.25'
|
||||
output: '1.25'
|
||||
unit: '0.000001'
|
||||
currency: USD
|
||||
@@ -1,39 +0,0 @@
|
||||
model: claude-3-opus-20240229
|
||||
label:
|
||||
en_US: claude-3-opus-20240229
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '15.00'
|
||||
output: '75.00'
|
||||
unit: '0.000001'
|
||||
currency: USD
|
||||
@@ -1,39 +0,0 @@
|
||||
model: claude-3-sonnet-20240229
|
||||
label:
|
||||
en_US: claude-3-sonnet-20240229
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '3.00'
|
||||
output: '15.00'
|
||||
unit: '0.000001'
|
||||
currency: USD
|
||||
@@ -1,36 +0,0 @@
|
||||
model: claude-instant-1.2
|
||||
label:
|
||||
en_US: claude-instant-1.2
|
||||
model_type: llm
|
||||
features: [ ]
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 100000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '1.63'
|
||||
output: '5.51'
|
||||
unit: '0.000001'
|
||||
currency: USD
|
||||
deprecated: true
|
||||
@@ -1,36 +0,0 @@
|
||||
model: claude-instant-1
|
||||
label:
|
||||
en_US: claude-instant-1
|
||||
model_type: llm
|
||||
features: [ ]
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 100000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '1.63'
|
||||
output: '5.51'
|
||||
unit: '0.000001'
|
||||
currency: USD
|
||||
deprecated: true
|
||||
@@ -1,19 +0,0 @@
|
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@@ -1,38 +0,0 @@
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|
||||
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|
||||
en_US: Baichuan
|
||||
icon_small:
|
||||
en_US: icon_s_en.svg
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icon_large:
|
||||
en_US: icon_l_en.svg
|
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|
||||
help:
|
||||
title:
|
||||
en_US: Get your API Key from BAICHUAN AI
|
||||
zh_Hans: 从百川智能获取您的 API Key
|
||||
url:
|
||||
en_US: https://www.baichuan-ai.com
|
||||
supported_model_types:
|
||||
- llm
|
||||
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||||
configurate_methods:
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||||
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|
||||
provider_credential_schema:
|
||||
credential_form_schemas:
|
||||
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|
||||
label:
|
||||
en_US: API Key
|
||||
type: secret-input
|
||||
required: true
|
||||
placeholder:
|
||||
zh_Hans: 在此输入您的 API Key
|
||||
en_US: Enter your API Key
|
||||
- variable: base_url
|
||||
label:
|
||||
en_US: https://api.baichuan-ai.com/v1
|
||||
type: text-input
|
||||
required: false
|
||||
placeholder:
|
||||
zh_Hans: 在此输入您的 Base URL
|
||||
en_US: Enter your Base URL
|
||||
address: https://api.baichuan-ai.com/v1
|
||||
@@ -1,46 +0,0 @@
|
||||
model: baichuan2-53b
|
||||
label:
|
||||
en_US: Baichuan2-53B
|
||||
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|
||||
features:
|
||||
- agent-thought
|
||||
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|
||||
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||||
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||||
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|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
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|
||||
- name: max_tokens
|
||||
use_template: max_tokens
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||||
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||||
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|
||||
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||||
- name: frequency_penalty
|
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use_template: frequency_penalty
|
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|
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|
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|
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- name: with_search_enhance
|
||||
label:
|
||||
zh_Hans: 搜索增强
|
||||
en_US: Search Enhance
|
||||
type: boolean
|
||||
help:
|
||||
zh_Hans: 允许模型自行进行外部搜索,以增强生成结果。
|
||||
en_US: Allow the model to perform external search to enhance the generation results.
|
||||
required: false
|
||||
deprecated: true
|
||||
@@ -1,46 +0,0 @@
|
||||
model: baichuan2-turbo-192k
|
||||
label:
|
||||
en_US: Baichuan2-Turbo-192K
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 192000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 8000
|
||||
min: 1
|
||||
max: 192000
|
||||
- name: presence_penalty
|
||||
use_template: presence_penalty
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
default: 1
|
||||
min: 1
|
||||
max: 2
|
||||
- name: with_search_enhance
|
||||
label:
|
||||
zh_Hans: 搜索增强
|
||||
en_US: Search Enhance
|
||||
type: boolean
|
||||
help:
|
||||
zh_Hans: 允许模型自行进行外部搜索,以增强生成结果。
|
||||
en_US: Allow the model to perform external search to enhance the generation results.
|
||||
required: false
|
||||
deprecated: true
|
||||
@@ -1,41 +0,0 @@
|
||||
model: baichuan2-turbo
|
||||
label:
|
||||
en_US: Baichuan2-Turbo
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- multi-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 32000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
default: 0.3
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
default: 0.85
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
min: 0
|
||||
max: 20
|
||||
default: 5
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
default: 2048
|
||||
- name: with_search_enhance
|
||||
label:
|
||||
zh_Hans: 搜索增强
|
||||
en_US: Search Enhance
|
||||
type: boolean
|
||||
help:
|
||||
zh_Hans: 允许模型自行进行外部搜索,以增强生成结果。
|
||||
en_US: Allow the model to perform external search to enhance the generation results.
|
||||
required: false
|
||||
@@ -1,53 +0,0 @@
|
||||
model: baichuan3-turbo-128k
|
||||
label:
|
||||
en_US: Baichuan3-Turbo-128k
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- multi-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 128000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
default: 0.3
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
default: 0.85
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
min: 0
|
||||
max: 20
|
||||
default: 5
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
default: 2048
|
||||
- name: res_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
- name: with_search_enhance
|
||||
label:
|
||||
zh_Hans: 搜索增强
|
||||
en_US: Search Enhance
|
||||
type: boolean
|
||||
help:
|
||||
zh_Hans: 允许模型自行进行外部搜索,以增强生成结果。
|
||||
en_US: Allow the model to perform external search to enhance the generation results.
|
||||
required: false
|
||||
@@ -1,53 +0,0 @@
|
||||
model: baichuan3-turbo
|
||||
label:
|
||||
en_US: Baichuan3-Turbo
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- multi-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 32000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
default: 0.3
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
default: 0.85
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
min: 0
|
||||
max: 20
|
||||
default: 5
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
default: 2048
|
||||
- name: res_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
- name: with_search_enhance
|
||||
label:
|
||||
zh_Hans: 搜索增强
|
||||
en_US: Search Enhance
|
||||
type: boolean
|
||||
help:
|
||||
zh_Hans: 允许模型自行进行外部搜索,以增强生成结果。
|
||||
en_US: Allow the model to perform external search to enhance the generation results.
|
||||
required: false
|
||||
@@ -1,53 +0,0 @@
|
||||
model: baichuan4
|
||||
label:
|
||||
en_US: Baichuan4
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- multi-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 32000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
default: 0.3
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
default: 0.85
|
||||
- name: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
min: 0
|
||||
max: 20
|
||||
default: 5
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
default: 2048
|
||||
- name: res_format
|
||||
label:
|
||||
zh_Hans: 回复格式
|
||||
en_US: Response Format
|
||||
type: string
|
||||
help:
|
||||
zh_Hans: 指定模型必须输出的格式
|
||||
en_US: specifying the format that the model must output
|
||||
required: false
|
||||
options:
|
||||
- text
|
||||
- json_object
|
||||
- name: with_search_enhance
|
||||
label:
|
||||
zh_Hans: 搜索增强
|
||||
en_US: Search Enhance
|
||||
type: boolean
|
||||
help:
|
||||
zh_Hans: 允许模型自行进行外部搜索,以增强生成结果。
|
||||
en_US: Allow the model to perform external search to enhance the generation results.
|
||||
required: false
|
||||
|
Before Width: | Height: | Size: 6.8 KiB |
|
Before Width: | Height: | Size: 10 KiB |
@@ -1 +0,0 @@
|
||||
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||||
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|
||||
provider: bailian
|
||||
label:
|
||||
zh_Hans: 阿里云百炼
|
||||
en_US: BaiLian
|
||||
icon_small:
|
||||
en_US: icon_s_en.svg
|
||||
icon_large:
|
||||
zh_Hans: icon_l_zh.svg
|
||||
en_US: icon_l_en.svg
|
||||
background: "#EFF1FE"
|
||||
help:
|
||||
title:
|
||||
en_US: Get your API key from AliCloud
|
||||
zh_Hans: 从阿里云百炼获取 API Key
|
||||
url:
|
||||
en_US: https://bailian.console.aliyun.com/?apiKey=1#/api-key
|
||||
supported_model_types:
|
||||
- llm
|
||||
configurate_methods:
|
||||
- predefined-model
|
||||
- customizable-model
|
||||
provider_credential_schema:
|
||||
credential_form_schemas:
|
||||
- variable: api_key
|
||||
label:
|
||||
en_US: API Key
|
||||
type: secret-input
|
||||
required: true
|
||||
placeholder:
|
||||
zh_Hans: 在此输入您的 API Key
|
||||
en_US: Enter your API Key
|
||||
- variable: base_url
|
||||
label:
|
||||
en_US: https://dashscope.aliyuncs.com/compatible-mode/v1
|
||||
type: text-input
|
||||
required: false
|
||||
placeholder:
|
||||
zh_Hans: 在此输入您的 Base URL
|
||||
en_US: Enter your Base URL
|
||||
address: https://dashscope.aliyuncs.com/compatible-mode/v1
|
||||
@@ -1,14 +0,0 @@
|
||||
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|
||||
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provider: bedrock
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label:
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en_US: AWS Bedrock
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description:
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en_US: AWS Bedrock's models.
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icon_small:
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en_US: icon_s_en.svg
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icon_large:
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en_US: icon_l_en.svg
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help:
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title:
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en_US: Get your Access Key and Secret Access Key from AWS Console
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zh_Hans: Access Key
|
||||
type: secret-input
|
||||
placeholder:
|
||||
en_US: Enter your Access Key
|
||||
zh_Hans: 在此输入您的 Access Key
|
||||
- variable: aws_secret_access_key
|
||||
required: false
|
||||
label:
|
||||
en_US: Secret Access Key
|
||||
zh_Hans: Secret Access Key
|
||||
type: secret-input
|
||||
placeholder:
|
||||
en_US: Enter your Secret Access Key
|
||||
zh_Hans: 在此输入您的 Secret Access Key
|
||||
- variable: aws_region
|
||||
required: true
|
||||
label:
|
||||
en_US: AWS Region
|
||||
zh_Hans: AWS 地区
|
||||
type: select
|
||||
default: us-east-1
|
||||
options:
|
||||
- value: us-east-1
|
||||
label:
|
||||
en_US: US East (N. Virginia)
|
||||
zh_Hans: 美国东部 (弗吉尼亚北部)
|
||||
- value: us-west-2
|
||||
label:
|
||||
en_US: US West (Oregon)
|
||||
zh_Hans: 美国西部 (俄勒冈州)
|
||||
- value: ap-southeast-1
|
||||
label:
|
||||
en_US: Asia Pacific (Singapore)
|
||||
zh_Hans: 亚太地区 (新加坡)
|
||||
- value: ap-northeast-1
|
||||
label:
|
||||
en_US: Asia Pacific (Tokyo)
|
||||
zh_Hans: 亚太地区 (东京)
|
||||
- value: eu-central-1
|
||||
label:
|
||||
en_US: Europe (Frankfurt)
|
||||
zh_Hans: 欧洲 (法兰克福)
|
||||
- value: eu-west-2
|
||||
label:
|
||||
en_US: Eu west London (London)
|
||||
zh_Hans: 欧洲西部 (伦敦)
|
||||
- value: us-gov-west-1
|
||||
label:
|
||||
en_US: AWS GovCloud (US-West)
|
||||
zh_Hans: AWS GovCloud (US-West)
|
||||
- value: ap-southeast-2
|
||||
label:
|
||||
en_US: Asia Pacific (Sydney)
|
||||
zh_Hans: 亚太地区 (悉尼)
|
||||
- variable: model_for_validation
|
||||
required: false
|
||||
label:
|
||||
en_US: Available Model Name
|
||||
zh_Hans: 可用模型名称
|
||||
type: text-input
|
||||
placeholder:
|
||||
en_US: A model you have access to (e.g. amazon.titan-text-lite-v1) for validation.
|
||||
zh_Hans: 为了进行验证,请输入一个您可用的模型名称 (例如:amazon.titan-text-lite-v1)
|
||||
model_config:
|
||||
access_configuration_status: true
|
||||
access_configuration_demo: "{\"region\":\"\",\"model\":\"\"}"
|
||||
address: https://bedrock-runtime.amazonaws.com
|
||||
sort: 4
|
||||
recommend: true
|
||||
@@ -1,47 +0,0 @@
|
||||
model: ai21.j2-mid-v1
|
||||
label:
|
||||
en_US: J2 Mid V1
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 8191
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: topP
|
||||
use_template: top_p
|
||||
- name: maxTokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 2048
|
||||
min: 1
|
||||
max: 2048
|
||||
- name: count_penalty
|
||||
label:
|
||||
en_US: Count Penalty
|
||||
required: false
|
||||
type: float
|
||||
default: 0
|
||||
min: 0
|
||||
max: 1
|
||||
- name: presence_penalty
|
||||
label:
|
||||
en_US: Presence Penalty
|
||||
required: false
|
||||
type: float
|
||||
default: 0
|
||||
min: 0
|
||||
max: 5
|
||||
- name: frequency_penalty
|
||||
label:
|
||||
en_US: Frequency Penalty
|
||||
required: false
|
||||
type: float
|
||||
default: 0
|
||||
min: 0
|
||||
max: 500
|
||||
pricing:
|
||||
input: '0.00'
|
||||
output: '0.00'
|
||||
unit: '0.000001'
|
||||
currency: USD
|
||||
@@ -1,47 +0,0 @@
|
||||
model: ai21.j2-ultra-v1
|
||||
label:
|
||||
en_US: J2 Ultra V1
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 8191
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: topP
|
||||
use_template: top_p
|
||||
- name: maxTokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 2048
|
||||
min: 1
|
||||
max: 2048
|
||||
- name: count_penalty
|
||||
label:
|
||||
en_US: Count Penalty
|
||||
required: false
|
||||
type: float
|
||||
default: 0
|
||||
min: 0
|
||||
max: 1
|
||||
- name: presence_penalty
|
||||
label:
|
||||
en_US: Presence Penalty
|
||||
required: false
|
||||
type: float
|
||||
default: 0
|
||||
min: 0
|
||||
max: 5
|
||||
- name: frequency_penalty
|
||||
label:
|
||||
en_US: Frequency Penalty
|
||||
required: false
|
||||
type: float
|
||||
default: 0
|
||||
min: 0
|
||||
max: 500
|
||||
pricing:
|
||||
input: '0.00'
|
||||
output: '0.00'
|
||||
unit: '0.000001'
|
||||
currency: USD
|
||||
@@ -1,26 +0,0 @@
|
||||
model: ai21.jamba-1-5-large-v1:0
|
||||
label:
|
||||
en_US: Jamba 1.5 Large
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 256000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 2.0
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: max_gen_len
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
pricing:
|
||||
input: '0.002'
|
||||
output: '0.008'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,26 +0,0 @@
|
||||
model: ai21.jamba-1-5-mini-v1:0
|
||||
label:
|
||||
en_US: Jamba 1.5 Mini
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 256000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 2.0
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: max_gen_len
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
pricing:
|
||||
input: '0.0002'
|
||||
output: '0.0004'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,53 +0,0 @@
|
||||
model: amazon.nova-lite-v1:0
|
||||
label:
|
||||
en_US: Nova Lite V1
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
- vision
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 300000
|
||||
parameter_rules:
|
||||
- name: max_new_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 2048
|
||||
min: 1
|
||||
max: 5000
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.00006'
|
||||
output: '0.00024'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,52 +0,0 @@
|
||||
model: amazon.nova-micro-v1:0
|
||||
label:
|
||||
en_US: Nova Micro V1
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 128000
|
||||
parameter_rules:
|
||||
- name: max_new_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 2048
|
||||
min: 1
|
||||
max: 5000
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.000035'
|
||||
output: '0.00014'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,53 +0,0 @@
|
||||
model: amazon.nova-pro-v1:0
|
||||
label:
|
||||
en_US: Nova Pro V1
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
- vision
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 300000
|
||||
parameter_rules:
|
||||
- name: max_new_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 2048
|
||||
min: 1
|
||||
max: 5000
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.0008'
|
||||
output: '0.0032'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,23 +0,0 @@
|
||||
model: amazon.titan-text-express-v1
|
||||
label:
|
||||
en_US: Titan Text G1 - Express
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 8192
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: topP
|
||||
use_template: top_p
|
||||
- name: maxTokenCount
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 2048
|
||||
min: 1
|
||||
max: 8000
|
||||
pricing:
|
||||
input: '0.0008'
|
||||
output: '0.0016'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,23 +0,0 @@
|
||||
model: amazon.titan-text-lite-v1
|
||||
label:
|
||||
en_US: Titan Text G1 - Lite
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 4096
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: topP
|
||||
use_template: top_p
|
||||
- name: maxTokenCount
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 2048
|
||||
min: 1
|
||||
max: 2048
|
||||
pricing:
|
||||
input: '0.0003'
|
||||
output: '0.0004'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,60 +0,0 @@
|
||||
model: anthropic.claude-3-5-haiku-20241022-v1:0
|
||||
label:
|
||||
en_US: Claude 3.5 Haiku
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 8192
|
||||
min: 1
|
||||
max: 8192
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
# docs: https://docs.anthropic.com/claude/docs/system-prompts
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '0.001'
|
||||
output: '0.005'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,61 +0,0 @@
|
||||
model: anthropic.claude-3-haiku-20240307-v1:0
|
||||
label:
|
||||
en_US: Claude 3 Haiku
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
# docs: https://docs.anthropic.com/claude/docs/system-prompts
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '0.00025'
|
||||
output: '0.00125'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,61 +0,0 @@
|
||||
model: anthropic.claude-3-opus-20240229-v1:0
|
||||
label:
|
||||
en_US: Claude 3 Opus
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
# docs: https://docs.anthropic.com/claude/docs/system-prompts
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '0.015'
|
||||
output: '0.075'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,60 +0,0 @@
|
||||
model: anthropic.claude-3-5-sonnet-20240620-v1:0
|
||||
label:
|
||||
en_US: Claude 3.5 Sonnet
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '0.003'
|
||||
output: '0.015'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,60 +0,0 @@
|
||||
model: anthropic.claude-3-sonnet-20240229-v1:0
|
||||
label:
|
||||
en_US: Claude 3 Sonnet
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '0.003'
|
||||
output: '0.015'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,60 +0,0 @@
|
||||
model: anthropic.claude-3-5-sonnet-20241022-v2:0
|
||||
label:
|
||||
en_US: Claude 3.5 Sonnet V2
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 8192
|
||||
min: 1
|
||||
max: 8192
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '0.003'
|
||||
output: '0.015'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,52 +0,0 @@
|
||||
model: anthropic.claude-instant-v1
|
||||
label:
|
||||
en_US: Claude Instant 1
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 100000
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.0008'
|
||||
output: '0.0024'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,53 +0,0 @@
|
||||
model: anthropic.claude-v1
|
||||
label:
|
||||
en_US: Claude 1
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 100000
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.008'
|
||||
output: '0.024'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
deprecated: true
|
||||
@@ -1,54 +0,0 @@
|
||||
model: anthropic.claude-v2:1
|
||||
label:
|
||||
en_US: Claude 2.1
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '0.008'
|
||||
output: '0.024'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,54 +0,0 @@
|
||||
model: anthropic.claude-v2
|
||||
label:
|
||||
en_US: Claude 2
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 100000
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '0.008'
|
||||
output: '0.024'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,35 +0,0 @@
|
||||
model: cohere.command-light-text-v14
|
||||
label:
|
||||
en_US: Command Light Text V14
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 4096
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: p
|
||||
use_template: top_p
|
||||
- name: k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
min: 0
|
||||
max: 500
|
||||
default: 0
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
pricing:
|
||||
input: '0.0003'
|
||||
output: '0.0006'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,44 +0,0 @@
|
||||
model: cohere.command-r-plus-v1:0
|
||||
label:
|
||||
en_US: Command R+
|
||||
model_type: llm
|
||||
features:
|
||||
- tool-call
|
||||
#- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 128000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
max: 5.0
|
||||
- name: p
|
||||
use_template: top_p
|
||||
default: 0.75
|
||||
min: 0.01
|
||||
max: 0.99
|
||||
- name: k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
default: 0
|
||||
min: 0
|
||||
max: 500
|
||||
- name: presence_penalty
|
||||
use_template: presence_penalty
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
default: 1024
|
||||
max: 4096
|
||||
pricing:
|
||||
input: '3'
|
||||
output: '15'
|
||||
unit: '0.000001'
|
||||
currency: USD
|
||||
@@ -1,43 +0,0 @@
|
||||
model: cohere.command-r-v1:0
|
||||
label:
|
||||
en_US: Command R
|
||||
model_type: llm
|
||||
features:
|
||||
- tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 128000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
max: 5.0
|
||||
- name: p
|
||||
use_template: top_p
|
||||
default: 0.75
|
||||
min: 0.01
|
||||
max: 0.99
|
||||
- name: k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
default: 0
|
||||
min: 0
|
||||
max: 500
|
||||
- name: presence_penalty
|
||||
use_template: presence_penalty
|
||||
- name: frequency_penalty
|
||||
use_template: frequency_penalty
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
default: 1024
|
||||
max: 4096
|
||||
pricing:
|
||||
input: '0.5'
|
||||
output: '1.5'
|
||||
unit: '0.000001'
|
||||
currency: USD
|
||||
@@ -1,32 +0,0 @@
|
||||
model: cohere.command-text-v14
|
||||
label:
|
||||
en_US: Command Text V14
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 4096
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: p
|
||||
use_template: top_p
|
||||
- name: k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
pricing:
|
||||
input: '0.0015'
|
||||
output: '0.0020'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,59 +0,0 @@
|
||||
model: eu.anthropic.claude-3-haiku-20240307-v1:0
|
||||
label:
|
||||
en_US: Claude 3 Haiku(EU.Cross Region Inference)
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
# docs: https://docs.anthropic.com/claude/docs/system-prompts
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.00025'
|
||||
output: '0.00125'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,58 +0,0 @@
|
||||
model: eu.anthropic.claude-3-5-sonnet-20240620-v1:0
|
||||
label:
|
||||
en_US: Claude 3.5 Sonnet(EU.Cross Region Inference)
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.003'
|
||||
output: '0.015'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,58 +0,0 @@
|
||||
model: eu.anthropic.claude-3-sonnet-20240229-v1:0
|
||||
label:
|
||||
en_US: Claude 3 Sonnet(EU.Cross Region Inference)
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.003'
|
||||
output: '0.015'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,60 +0,0 @@
|
||||
model: eu.anthropic.claude-3-5-sonnet-20241022-v2:0
|
||||
label:
|
||||
en_US: Claude 3.5 Sonnet V2(EU.Cross Region Inference)
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '0.003'
|
||||
output: '0.015'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,23 +0,0 @@
|
||||
model: meta.llama2-13b-chat-v1
|
||||
label:
|
||||
en_US: Llama 2 Chat 13B
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 4096
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: max_gen_len
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 2048
|
||||
min: 1
|
||||
max: 2048
|
||||
pricing:
|
||||
input: '0.00075'
|
||||
output: '0.00100'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,23 +0,0 @@
|
||||
model: meta.llama2-70b-chat-v1
|
||||
label:
|
||||
en_US: Llama 2 Chat 70B
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 4096
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: max_gen_len
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 2048
|
||||
min: 1
|
||||
max: 2048
|
||||
pricing:
|
||||
input: '0.00195'
|
||||
output: '0.00256'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,25 +0,0 @@
|
||||
model: meta.llama3-1-405b-instruct-v1:0
|
||||
label:
|
||||
en_US: Llama 3.1 405B Instruct
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 128000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
default: 0.5
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
default: 0.9
|
||||
- name: max_gen_len
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 512
|
||||
min: 1
|
||||
max: 2048
|
||||
pricing:
|
||||
input: '0.00532'
|
||||
output: '0.016'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,25 +0,0 @@
|
||||
model: meta.llama3-1-70b-instruct-v1:0
|
||||
label:
|
||||
en_US: Llama 3.1 Instruct 70B
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 128000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
default: 0.5
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
default: 0.9
|
||||
- name: max_gen_len
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 512
|
||||
min: 1
|
||||
max: 2048
|
||||
pricing:
|
||||
input: '0.00265'
|
||||
output: '0.0035'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,25 +0,0 @@
|
||||
model: meta.llama3-1-8b-instruct-v1:0
|
||||
label:
|
||||
en_US: Llama 3.1 Instruct 8B
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 128000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
default: 0.5
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
default: 0.9
|
||||
- name: max_gen_len
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 512
|
||||
min: 1
|
||||
max: 2048
|
||||
pricing:
|
||||
input: '0.0003'
|
||||
output: '0.0006'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,23 +0,0 @@
|
||||
model: meta.llama3-70b-instruct-v1:0
|
||||
label:
|
||||
en_US: Llama 3 Instruct 70B
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 8192
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: max_gen_len
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 512
|
||||
min: 1
|
||||
max: 2048
|
||||
pricing:
|
||||
input: '0.00265'
|
||||
output: '0.0035'
|
||||
unit: '0.00001'
|
||||
currency: USD
|
||||
@@ -1,23 +0,0 @@
|
||||
model: meta.llama3-8b-instruct-v1:0
|
||||
label:
|
||||
en_US: Llama 3 Instruct 8B
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 8192
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: max_gen_len
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 512
|
||||
min: 1
|
||||
max: 2048
|
||||
pricing:
|
||||
input: '0.0004'
|
||||
output: '0.0006'
|
||||
unit: '0.0001'
|
||||
currency: USD
|
||||
@@ -1,39 +0,0 @@
|
||||
model: mistral.mistral-7b-instruct-v0:2
|
||||
label:
|
||||
en_US: Mistral 7B Instruct
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 32000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
default: 0.5
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
required: false
|
||||
default: 0.9
|
||||
- name: top_k
|
||||
use_template: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
default: 50
|
||||
max: 200
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 512
|
||||
min: 1
|
||||
max: 8192
|
||||
pricing:
|
||||
input: '0.00015'
|
||||
output: '0.0002'
|
||||
unit: '0.00001'
|
||||
currency: USD
|
||||
@@ -1,30 +0,0 @@
|
||||
model: mistral.mistral-large-2402-v1:0
|
||||
label:
|
||||
en_US: Mistral Large
|
||||
model_type: llm
|
||||
features:
|
||||
- tool-call
|
||||
- agent-thought
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 32000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
default: 0.7
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
required: false
|
||||
default: 1
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 512
|
||||
min: 1
|
||||
max: 4096
|
||||
pricing:
|
||||
input: '0.008'
|
||||
output: '0.024'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,29 +0,0 @@
|
||||
model: mistral.mistral-large-2407-v1:0
|
||||
label:
|
||||
en_US: Mistral Large 2 (24.07)
|
||||
model_type: llm
|
||||
features:
|
||||
- tool-call
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 128000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
default: 0.7
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
required: false
|
||||
default: 1
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 512
|
||||
min: 1
|
||||
max: 8192
|
||||
pricing:
|
||||
input: '0.003'
|
||||
output: '0.009'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,29 +0,0 @@
|
||||
model: mistral.mistral-small-2402-v1:0
|
||||
label:
|
||||
en_US: Mistral Small
|
||||
model_type: llm
|
||||
features:
|
||||
- tool-call
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 32000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
default: 0.7
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
required: false
|
||||
default: 1
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 512
|
||||
min: 1
|
||||
max: 4096
|
||||
pricing:
|
||||
input: '0.001'
|
||||
output: '0.03'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,39 +0,0 @@
|
||||
model: mistral.mixtral-8x7b-instruct-v0:1
|
||||
label:
|
||||
en_US: Mixtral 8X7B Instruct
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 32000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
default: 0.5
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
required: false
|
||||
default: 0.9
|
||||
- name: top_k
|
||||
use_template: top_k
|
||||
label:
|
||||
zh_Hans: 取样数量
|
||||
en_US: Top k
|
||||
type: int
|
||||
help:
|
||||
zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
|
||||
en_US: Only sample from the top K options for each subsequent token.
|
||||
required: false
|
||||
default: 50
|
||||
max: 200
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 512
|
||||
min: 1
|
||||
max: 8192
|
||||
pricing:
|
||||
input: '0.00045'
|
||||
output: '0.0007'
|
||||
unit: '0.00001'
|
||||
currency: USD
|
||||
@@ -1,53 +0,0 @@
|
||||
model: us.amazon.nova-lite-v1:0
|
||||
label:
|
||||
en_US: Nova Lite V1 (US.Cross Region Inference)
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
- vision
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 300000
|
||||
parameter_rules:
|
||||
- name: max_new_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 2048
|
||||
min: 1
|
||||
max: 5000
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.00006'
|
||||
output: '0.00024'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,52 +0,0 @@
|
||||
model: us.amazon.nova-micro-v1:0
|
||||
label:
|
||||
en_US: Nova Micro V1 (US.Cross Region Inference)
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 128000
|
||||
parameter_rules:
|
||||
- name: max_new_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 2048
|
||||
min: 1
|
||||
max: 5000
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.000035'
|
||||
output: '0.00014'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,53 +0,0 @@
|
||||
model: us.amazon.nova-pro-v1:0
|
||||
label:
|
||||
en_US: Nova Pro V1 (US.Cross Region Inference)
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
- vision
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 300000
|
||||
parameter_rules:
|
||||
- name: max_new_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 2048
|
||||
min: 1
|
||||
max: 5000
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.0008'
|
||||
output: '0.0032'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,60 +0,0 @@
|
||||
model: us.anthropic.claude-3-5-haiku-20241022-v1:0
|
||||
label:
|
||||
en_US: Claude 3.5 Haiku(US.Cross Region Inference)
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 8192
|
||||
min: 1
|
||||
max: 8192
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
# docs: https://docs.anthropic.com/claude/docs/system-prompts
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '0.001'
|
||||
output: '0.005'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,59 +0,0 @@
|
||||
model: us.anthropic.claude-3-haiku-20240307-v1:0
|
||||
label:
|
||||
en_US: Claude 3 Haiku(US.Cross Region Inference)
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
# docs: https://docs.anthropic.com/claude/docs/system-prompts
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.00025'
|
||||
output: '0.00125'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,59 +0,0 @@
|
||||
model: us.anthropic.claude-3-opus-20240229-v1:0
|
||||
label:
|
||||
en_US: Claude 3 Opus(US.Cross Region Inference)
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
# docs: https://docs.anthropic.com/claude/docs/system-prompts
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.015'
|
||||
output: '0.075'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,58 +0,0 @@
|
||||
model: us.anthropic.claude-3-5-sonnet-20240620-v1:0
|
||||
label:
|
||||
en_US: Claude 3.5 Sonnet(US.Cross Region Inference)
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.003'
|
||||
output: '0.015'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,58 +0,0 @@
|
||||
model: us.anthropic.claude-3-sonnet-20240229-v1:0
|
||||
label:
|
||||
en_US: Claude 3 Sonnet(US.Cross Region Inference)
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 4096
|
||||
min: 1
|
||||
max: 4096
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
pricing:
|
||||
input: '0.003'
|
||||
output: '0.015'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,60 +0,0 @@
|
||||
model: us.anthropic.claude-3-5-sonnet-20241022-v2:0
|
||||
label:
|
||||
en_US: Claude 3.5 Sonnet V2(US.Cross Region Inference)
|
||||
model_type: llm
|
||||
features:
|
||||
- agent-thought
|
||||
- vision
|
||||
- tool-call
|
||||
- stream-tool-call
|
||||
model_properties:
|
||||
mode: chat
|
||||
context_size: 200000
|
||||
# docs: https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-anthropic-claude-messages.html
|
||||
parameter_rules:
|
||||
- name: max_tokens
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
type: int
|
||||
default: 8192
|
||||
min: 1
|
||||
max: 8192
|
||||
help:
|
||||
zh_Hans: 停止前生成的最大令牌数。请注意,Anthropic Claude 模型可能会在达到 max_tokens 的值之前停止生成令牌。不同的 Anthropic Claude 模型对此参数具有不同的最大值。
|
||||
en_US: The maximum number of tokens to generate before stopping. Note that Anthropic Claude models might stop generating tokens before reaching the value of max_tokens. Different Anthropic Claude models have different maximum values for this parameter.
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
required: false
|
||||
type: float
|
||||
default: 1
|
||||
min: 0.0
|
||||
max: 1.0
|
||||
help:
|
||||
zh_Hans: 生成内容的随机性。
|
||||
en_US: The amount of randomness injected into the response.
|
||||
- name: top_p
|
||||
required: false
|
||||
type: float
|
||||
default: 0.999
|
||||
min: 0.000
|
||||
max: 1.000
|
||||
help:
|
||||
zh_Hans: 在核采样中,Anthropic Claude 按概率递减顺序计算每个后续标记的所有选项的累积分布,并在达到 top_p 指定的特定概率时将其切断。您应该更改温度或top_p,但不能同时更改两者。
|
||||
en_US: In nucleus sampling, Anthropic Claude computes the cumulative distribution over all the options for each subsequent token in decreasing probability order and cuts it off once it reaches a particular probability specified by top_p. You should alter either temperature or top_p, but not both.
|
||||
- name: top_k
|
||||
required: false
|
||||
type: int
|
||||
default: 0
|
||||
min: 0
|
||||
# tip docs from aws has error, max value is 500
|
||||
max: 500
|
||||
help:
|
||||
zh_Hans: 对于每个后续标记,仅从前 K 个选项中进行采样。使用 top_k 删除长尾低概率响应。
|
||||
en_US: Only sample from the top K options for each subsequent token. Use top_k to remove long tail low probability responses.
|
||||
- name: response_format
|
||||
use_template: response_format
|
||||
pricing:
|
||||
input: '0.003'
|
||||
output: '0.015'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,29 +0,0 @@
|
||||
model: us.meta.llama3-2-11b-instruct-v1:0
|
||||
label:
|
||||
en_US: US Meta Llama 3.2 11B Instruct
|
||||
model_type: llm
|
||||
features:
|
||||
- vision
|
||||
- tool-call
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 128000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
default: 0.5
|
||||
min: 0.0
|
||||
max: 1
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: max_gen_len
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 512
|
||||
min: 1
|
||||
max: 2048
|
||||
pricing:
|
||||
input: '0.00035'
|
||||
output: '0.00035'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,26 +0,0 @@
|
||||
model: us.meta.llama3-2-1b-instruct-v1:0
|
||||
label:
|
||||
en_US: US Meta Llama 3.2 1B Instruct
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 128000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
default: 0.5
|
||||
min: 0.0
|
||||
max: 1
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: max_gen_len
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 512
|
||||
min: 1
|
||||
max: 2048
|
||||
pricing:
|
||||
input: '0.0001'
|
||||
output: '0.0001'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||
@@ -1,26 +0,0 @@
|
||||
model: us.meta.llama3-2-3b-instruct-v1:0
|
||||
label:
|
||||
en_US: US Meta Llama 3.2 3B Instruct
|
||||
model_type: llm
|
||||
model_properties:
|
||||
mode: completion
|
||||
context_size: 128000
|
||||
parameter_rules:
|
||||
- name: temperature
|
||||
use_template: temperature
|
||||
default: 0.5
|
||||
min: 0.0
|
||||
max: 1
|
||||
- name: top_p
|
||||
use_template: top_p
|
||||
- name: max_gen_len
|
||||
use_template: max_tokens
|
||||
required: true
|
||||
default: 512
|
||||
min: 1
|
||||
max: 2048
|
||||
pricing:
|
||||
input: '0.00015'
|
||||
output: '0.00015'
|
||||
unit: '0.001'
|
||||
currency: USD
|
||||