fix: login page refresh multiple times

add default router when create new rest service

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -45,19 +45,18 @@ 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 apinto via the Docker image.
-              2. Create a Route with the Admin API.
-              3. Try configuring ...
-              4. ...
+              1. Run APIPark via the Docker image.
+              2. Try configuring ...
+              3. ...
       validations:
-          required: true
+          required: false
     - type: textarea
       id: environment
       attributes:
           label: Environment
           description: Share your environment details. Reports without proper environment details will likely be closed.
           value: |
-              - APINTO Dashboard version (run `apinto dashboard version`):
+              - APINTO Dashboard version:
               - Operating system (run `uname -a`):
       validations:
           required: true

.github/ISSUE_TEMPLATE/feature_request.yml

@@ -1,5 +1,5 @@
 name: "Feature Request"
-description: Suggest an enhancement to APINTO.
+description: Suggest an enhancement to APIPark.
 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

.github/ISSUE_TEMPLATE/request_help.yml

@@ -25,7 +25,7 @@ body:
       label: Environment
       description: Share your environment details. Reports without proper environment details will likely be closed.
       value: |
-        - APIPark version (run `apinto dashboard version`):
+        - APIPark version:
         - Operating system (run `uname -a`):
     validations:
       required: true

.github/workflows/release.yaml

@@ -25,7 +25,7 @@ jobs:
           echo "Build frontend..."
           cd ./frontend && pnpm run build
       - name: upload frontend release
-        uses: actions/upload-artifact@v2
+        uses: actions/upload-artifact@v3
         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@v2
+        uses: actions/download-artifact@v3
         with:
           name: frontend-package
           path: frontend/dist
@@ -71,7 +71,7 @@ jobs:
       - uses: actions/checkout@v3
 
       - name: download frontend release
-        uses: actions/download-artifact@v2
+        uses: actions/download-artifact@v3
         with:
           name: frontend-package
           path: frontend/dist

.gitignore

@@ -3,4 +3,4 @@
 /config.yml
 /build/
 /apipark
-/aoplatform
+.gitlab-ci.yml

.vscode/settings.json

@@ -0,0 +1,9 @@
+{
+    "cSpell.words": [
+        "Antd",
+        "apinto",
+        "Apipark",
+        "logsettings",
+        "resourcesettings"
+    ]
+}

README.md

@@ -1,29 +1,55 @@
-![image]( https://github.com/user-attachments/assets/96e36db5-2733-49c8-8e1e-ecbcc60a3943 )
+![image](https://github.com/user-attachments/assets/96e36db5-2733-49c8-8e1e-ecbcc60a3943)
 
 <p align="center">
-  English
+  <a href="/README.md">English</a>
+  | 
+  <a href="/readme/readme-jp.md">日本語</a>
   | 
   <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>
 
-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.
+<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>
 
 <br>
 
-# ✨  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.
+✨ 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.
 
-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>
+
+✨ 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.
 
 
 <br>
 
-😍 APIPark deployment is very simple, just one command line can deploy your API open platform in 5 minutes.
+# 💌 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.
 
 ```
 curl -sSO  https://download.apipark.com/install/quick-start.sh ;  bash quick-start.sh
@@ -31,131 +57,161 @@ curl -sSO  https://download.apipark.com/install/quick-start.sh ;  bash quick-sta
 
 <br>
 
-# 🔥  characteristic
+# 🔥 Features
 <table>
-<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>
+    <th>
+      Connect to 100+ AI models
+    </th>
+    <th>
+      Unified API to use all AI
+    </th>
 
-</tr>
+  </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>
+    <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>
-<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>
+    <th>
+      Review subscription before allowing API requests
+    </th>
+    <th>
+      Manage subscriber
+    </th>
+  </tr>
 
-</tr>
+  <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>
-<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>
+    <th>
+      Logging
+    </th>
+    <th>
+      Analysis
+    </th>
+  </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>
+  <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>
   
 </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>
 
-# 🚩 Applicable scenarios
-## Improve operational efficiency
-- Quickly build an internal API portal.
-- Efficient management and API calling.
-- Reduce complex inter system call relationships.
+# 🚩 Roadmap
+We’ve set exciting goals for APIPark: enabling everyone to quickly create their own products and AI agents using AI and APIs!
 
-## 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.
+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.
 
 <br>
 
-# 🚀 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
-```
+# 📕 Documentation
+Visit [APIPark Documentation](https://docs.apipark.com/docs/deploy) for detailed installation guides, API references, and usage instructions.
 
 <br>
 
-## 📕 file
-Visit [APIPark Document]（ https://docs.apipark.com/docs/install ）Get detailed installation guides, API references, and usage instructions.
+# 🧾 License
+APIPark uses the Apache 2.0 License. For more details, please refer to the LICENSE file.
 
 <br>
 
-## 🧾 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.
+# 💌 Contact Us
+For enterprise-level features and professional technical support, contact our pre-sales experts for personalized demos, customized solutions, and pricing.
 
 - Website: https://apipark.com
 - Email: dev@apipark.com
 
 <br>
 
-Thank you for choosing APIPark, the next-generation API Open platform.
+🙏 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. 🎉

ai-provider/model-runtime/entity/ai-model.go

@@ -0,0 +1,21 @@
+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"`
+}

ai-provider/model-runtime/entity/provider.go

@@ -0,0 +1,45 @@
+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"`
+}
+
+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"`
+}

ai-provider/model-runtime/load_test.go

@@ -0,0 +1,11 @@
+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"))
+	}
+}

ai-provider/model-runtime/loader.go

@@ -0,0 +1,144 @@
+package model_runtime
+
+import (
+	"embed"
+	"encoding/json"
+	"fmt"
+	"strings"
+
+	"github.com/APIParkLab/APIPark/gateway"
+
+	"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
+	}
+	return c.validator.Valid(data)
+}
+
+func (c *Config) GenConfig(target string, origin string) (string, error) {
+	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
+	}
+	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())
+		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
+}

ai-provider/model-runtime/manager.go

@@ -0,0 +1,52 @@
+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 GetProvider(name string) (IProvider, bool) {
+	return defaultManager.Get(name)
+}
+
+func Providers() []IProvider {
+	return defaultManager.List()
+}

ai-provider/model-runtime/model-providers/authropic/anthropic.yaml

@@ -0,0 +1,42 @@
+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: API URL
+      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
+recommend: true
+sort: 2

ai-provider/model-runtime/model-providers/authropic/assets/icon_l_en.svg

@@ -0,0 +1,78 @@
+<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">
+<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">
+<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)">
+<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"/>
+</g>
+<mask id="mask4_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(#mask4_8587_60274)">
+<path d="M21.7969 7.02094H25.0423V14.825H27.1139V7.02094H30.3594V5.15625H21.7969V7.02094Z" fill="black" fill-opacity="0.92"/>
+</g>
+<mask id="mask5_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(#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"/>
+</g>
+<mask id="mask6_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(#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">
+<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">
+<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"/>
+</g>
+<mask id="mask9_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(#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"/>
+</g>
+<mask id="mask10_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(#mask10_8587_60274)">
+<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">
+<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>

ai-provider/model-runtime/model-providers/authropic/assets/icon_s_en.svg

@@ -0,0 +1,4 @@
+<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>

ai-provider/model-runtime/model-providers/authropic/llm/_position.yaml

@@ -0,0 +1,8 @@
+- 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

ai-provider/model-runtime/model-providers/authropic/llm/claude-2.1.yaml

@@ -0,0 +1,36 @@
+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

ai-provider/model-runtime/model-providers/authropic/llm/claude-2.yaml

@@ -0,0 +1,37 @@
+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

ai-provider/model-runtime/model-providers/authropic/llm/claude-3-5-sonnet-20240620.yaml

@@ -0,0 +1,39 @@
+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

ai-provider/model-runtime/model-providers/authropic/llm/claude-3-haiku-20240307.yaml

@@ -0,0 +1,39 @@
+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

ai-provider/model-runtime/model-providers/authropic/llm/claude-3-opus-20240229.yaml

@@ -0,0 +1,39 @@
+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

ai-provider/model-runtime/model-providers/authropic/llm/claude-3-sonnet-20240229.yaml

@@ -0,0 +1,39 @@
+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

ai-provider/model-runtime/model-providers/authropic/llm/claude-instant-1.2.yaml

@@ -0,0 +1,36 @@
+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

ai-provider/model-runtime/model-providers/authropic/llm/claude-instant-1.yaml

@@ -0,0 +1,36 @@
+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

ai-provider/model-runtime/model-providers/baichuan/assets/icon_l_en.svg

@@ -0,0 +1,19 @@
+<svg width="130" height="24" viewBox="0 0 130 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path fill-rule="evenodd" clip-rule="evenodd" d="M9.58154 1.7793H6.52779L4.34655 6.20409V17.7335L1.91602 22.2206H7.21333L9.58154 17.7335V1.7793ZM11.5761 1.7793H16.8111V22.2206H11.5761V1.7793ZM23.9166 1.7793H18.6816V6.01712H23.9166V1.7793ZM23.9166 7.38818H18.6816V22.2206H23.9166V7.38818Z" fill="url(#paint0_radial_11622_96091)"/>
+<path d="M129.722 6.83203V18H127.482V6.83203H129.722Z" fill="#FF6A34"/>
+<path d="M123.196 15.872H118.748L118.012 18H115.66L119.676 6.81604H122.284L126.3 18H123.932L123.196 15.872ZM122.588 14.08L120.972 9.40804L119.356 14.08H122.588Z" fill="#FF6A34"/>
+<path d="M110.962 18H108.722L103.65 10.336V18H101.41V6.81598H103.65L108.722 14.496V6.81598H110.962V18Z" fill="#FF6A34"/>
+<path d="M97.1258 15.872H92.6778L91.9418 18H89.5898L93.6058 6.81604H96.2138L100.23 18H97.8618L97.1258 15.872ZM96.5178 14.08L94.9018 9.40804L93.2858 14.08H96.5178Z" fill="#FF6A34"/>
+<path d="M81.6482 6.83203V13.744C81.6482 14.5014 81.8455 15.0827 82.2402 15.488C82.6349 15.8827 83.1895 16.08 83.9042 16.08C84.6295 16.08 85.1895 15.8827 85.5842 15.488C85.9789 15.0827 86.1762 14.5014 86.1762 13.744V6.83203H88.4322V13.728C88.4322 14.6774 88.2242 15.4827 87.8082 16.144C87.4029 16.7947 86.8535 17.2854 86.1602 17.616C85.4775 17.9467 84.7149 18.112 83.8722 18.112C83.0402 18.112 82.2829 17.9467 81.6002 17.616C80.9282 17.2854 80.3949 16.7947 80.0002 16.144C79.6055 15.4827 79.4082 14.6774 79.4082 13.728V6.83203H81.6482Z" fill="#FF6A34"/>
+<path d="M77.557 6.83203V18H75.317V13.248H70.533V18H68.293V6.83203H70.533V11.424H75.317V6.83203H77.557Z" fill="#FF6A34"/>
+<path d="M55.7871 12.4C55.7871 11.3013 56.0324 10.32 56.5231 9.45599C57.0244 8.58132 57.7018 7.90399 58.5551 7.42399C59.4191 6.93332 60.3844 6.68799 61.4511 6.68799C62.6991 6.68799 63.7924 7.00799 64.7311 7.64799C65.6698 8.28799 66.3258 9.17332 66.6991 10.304H64.1231C63.8671 9.77065 63.5044 9.37065 63.0351 9.10399C62.5764 8.83732 62.0431 8.70399 61.4351 8.70399C60.7844 8.70399 60.2031 8.85865 59.6911 9.16799C59.1898 9.46665 58.7951 9.89332 58.5071 10.448C58.2298 11.0027 58.0911 11.6533 58.0911 12.4C58.0911 13.136 58.2298 13.7867 58.5071 14.352C58.7951 14.9067 59.1898 15.3387 59.6911 15.648C60.2031 15.9467 60.7844 16.096 61.4351 16.096C62.0431 16.096 62.5764 15.9627 63.0351 15.696C63.5044 15.4187 63.8671 15.0133 64.1231 14.48H66.6991C66.3258 15.6213 65.6698 16.512 64.7311 17.152C63.8031 17.7813 62.7098 18.096 61.4511 18.096C60.3844 18.096 59.4191 17.856 58.5551 17.376C57.7018 16.8853 57.0244 16.208 56.5231 15.344C56.0324 14.48 55.7871 13.4987 55.7871 12.4Z" fill="#FF6A34"/>
+<path d="M54.4373 6.83203V18H52.1973V6.83203H54.4373Z" fill="#FF6A34"/>
+<path d="M47.913 15.872H43.465L42.729 18H40.377L44.393 6.81598H47.001L51.017 18H48.649L47.913 15.872ZM47.305 14.08L45.689 9.40798L44.073 14.08H47.305Z" fill="#FF6A34"/>
+<path d="M37.4395 12.272C38.0688 12.3893 38.5862 12.704 38.9915 13.216C39.3968 13.728 39.5995 14.3146 39.5995 14.976C39.5995 15.5733 39.4502 16.1013 39.1515 16.56C38.8635 17.008 38.4422 17.36 37.8875 17.616C37.3328 17.872 36.6768 18 35.9195 18H31.1035V6.83197H35.7115C36.4688 6.83197 37.1195 6.95464 37.6635 7.19997C38.2182 7.4453 38.6342 7.78664 38.9115 8.22397C39.1995 8.6613 39.3435 9.1573 39.3435 9.71197C39.3435 10.3626 39.1675 10.9066 38.8155 11.344C38.4742 11.7813 38.0155 12.0906 37.4395 12.272ZM33.3435 11.44H35.3915C35.9248 11.44 36.3355 11.3226 36.6235 11.088C36.9115 10.8426 37.0555 10.496 37.0555 10.048C37.0555 9.59997 36.9115 9.2533 36.6235 9.00797C36.3355 8.76264 35.9248 8.63997 35.3915 8.63997H33.3435V11.44ZM35.5995 16.176C36.1435 16.176 36.5648 16.048 36.8635 15.792C37.1728 15.536 37.3275 15.1733 37.3275 14.704C37.3275 14.224 37.1675 13.8506 36.8475 13.584C36.5275 13.3066 36.0955 13.168 35.5515 13.168H33.3435V16.176H35.5995Z" fill="#FF6A34"/>
+<defs>
+<radialGradient id="paint0_radial_11622_96091" cx="0" cy="0" r="1" gradientUnits="userSpaceOnUse" gradientTransform="translate(6.5 5.5) rotate(45) scale(20.5061 22.0704)">
+<stop stop-color="#FEBD3F"/>
+<stop offset="0.77608" stop-color="#FF6933"/>
+</radialGradient>
+</defs>
+</svg>

ai-provider/model-runtime/model-providers/baichuan/assets/icon_s_en.svg

@@ -0,0 +1,11 @@
+<svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+<g id="Baichuan">
+<path id="Union" fill-rule="evenodd" clip-rule="evenodd" d="M8.58154 1.7793H5.52779L3.34655 6.20409V17.7335L0.916016 22.2206H6.21333L8.58154 17.7335V1.7793ZM10.5761 1.7793H15.8111V22.2206H10.5761V1.7793ZM22.9166 1.7793H17.6816V6.01712H22.9166V1.7793ZM22.9166 7.38818H17.6816V22.2206H22.9166V7.38818Z" fill="url(#paint0_radial_11622_96084)"/>
+</g>
+<defs>
+<radialGradient id="paint0_radial_11622_96084" cx="0" cy="0" r="1" gradientUnits="userSpaceOnUse" gradientTransform="translate(5.5 5.5) rotate(45) scale(20.5061 22.0704)">
+<stop stop-color="#FEBD3F"/>
+<stop offset="0.77608" stop-color="#FF6933"/>
+</radialGradient>
+</defs>
+</svg>

ai-provider/model-runtime/model-providers/baichuan/baichuan.yaml

@@ -0,0 +1,30 @@
+provider: baichuan
+label:
+  en_US: Baichuan
+icon_small:
+  en_US: icon_s_en.svg
+icon_large:
+  en_US: icon_l_en.svg
+background: "#FFF6F2"
+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
+  - text-embedding
+configurate_methods:
+  - predefined-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
+address: https://api.baichuan-ai.com

ai-provider/model-runtime/model-providers/baichuan/llm/baichuan2-53b.yaml

@@ -0,0 +1,46 @@
+model: baichuan2-53b
+label:
+  en_US: Baichuan2-53B
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 32000
+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: 1000
+    min: 1
+    max: 4000
+  - 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

ai-provider/model-runtime/model-providers/baichuan/llm/baichuan2-turbo-192k.yaml

@@ -0,0 +1,46 @@
+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

ai-provider/model-runtime/model-providers/baichuan/llm/baichuan2-turbo.yaml

@@ -0,0 +1,41 @@
+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

ai-provider/model-runtime/model-providers/baichuan/llm/baichuan3-turbo-128k.yaml

@@ -0,0 +1,53 @@
+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

ai-provider/model-runtime/model-providers/baichuan/llm/baichuan3-turbo.yaml

@@ -0,0 +1,53 @@
+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

ai-provider/model-runtime/model-providers/baichuan/llm/baichuan4.yaml

@@ -0,0 +1,53 @@
+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

ai-provider/model-runtime/model-providers/bedrock/assets/icon_l_en.svg

@@ -0,0 +1,14 @@
+<svg width="140" height="24" viewBox="0 0 140 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path d="M131.701 17.9999V6.8999H133.876V13.6049L136.531 10.3349H139.141L135.976 13.9949L139.381 17.9999H136.711L133.876 14.5049V17.9999H131.701Z" fill="#252F3E"/>
+<path d="M129.847 17.6699C129.577 17.8299 129.252 17.9499 128.872 18.0299C128.492 18.1199 128.097 18.1649 127.687 18.1649C126.467 18.1649 125.532 17.8249 124.882 17.1449C124.242 16.4649 123.922 15.4849 123.922 14.2049C123.922 12.9349 124.262 11.9449 124.942 11.2349C125.622 10.5249 126.567 10.1699 127.777 10.1699C128.507 10.1699 129.182 10.3299 129.802 10.6499V12.1049C129.212 11.9349 128.672 11.8499 128.182 11.8499C127.482 11.8499 126.967 12.0299 126.637 12.3899C126.307 12.7399 126.142 13.2999 126.142 14.0699V14.2799C126.142 15.0399 126.302 15.5999 126.622 15.9599C126.952 16.3099 127.457 16.4849 128.137 16.4849C128.627 16.4849 129.197 16.3949 129.847 16.2149V17.6699Z" fill="#252F3E"/>
+<path d="M118.51 18.2249C117.32 18.2249 116.39 17.8699 115.72 17.1599C115.05 16.4399 114.715 15.4399 114.715 14.1599C114.715 12.8899 115.05 11.8999 115.72 11.1899C116.39 10.4699 117.32 10.1099 118.51 10.1099C119.7 10.1099 120.63 10.4699 121.3 11.1899C121.97 11.8999 122.305 12.8899 122.305 14.1599C122.305 15.4399 121.97 16.4399 121.3 17.1599C120.63 17.8699 119.7 18.2249 118.51 18.2249ZM118.51 16.5449C119.56 16.5449 120.085 15.7499 120.085 14.1599C120.085 12.5799 119.56 11.7899 118.51 11.7899C117.46 11.7899 116.935 12.5799 116.935 14.1599C116.935 15.7499 117.46 16.5449 118.51 16.5449Z" fill="#252F3E"/>
+<path d="M108.727 17.9998V10.3348H110.527L110.797 11.4748C111.197 11.0348 111.572 10.7248 111.922 10.5448C112.282 10.3548 112.662 10.2598 113.062 10.2598C113.252 10.2598 113.452 10.2748 113.662 10.3048V12.3298C113.382 12.2698 113.072 12.2398 112.732 12.2398C112.082 12.2398 111.477 12.3548 110.917 12.5848V17.9998H108.727Z" fill="#252F3E"/>
+<path d="M104.417 17.9999L104.237 17.3249C103.617 17.8849 102.882 18.1649 102.032 18.1649C101.402 18.1649 100.847 18.0099 100.367 17.6999C99.8866 17.3799 99.5116 16.9199 99.2416 16.3199C98.9816 15.7199 98.8516 15.0149 98.8516 14.2049C98.8516 12.9649 99.1466 11.9749 99.7366 11.2349C100.327 10.4849 101.107 10.1099 102.077 10.1099C102.867 10.1099 103.552 10.3349 104.132 10.7849V6.8999H106.322V17.9999H104.417ZM102.752 16.5149C103.232 16.5149 103.692 16.3749 104.132 16.0949V12.1349C103.702 11.8849 103.207 11.7599 102.647 11.7599C102.117 11.7599 101.722 11.9599 101.462 12.3599C101.202 12.7499 101.072 13.3449 101.072 14.1449C101.072 14.9449 101.207 15.5399 101.477 15.9299C101.757 16.3199 102.182 16.5149 102.752 16.5149Z" fill="#252F3E"/>
+<path d="M92.4625 14.6999C92.5025 15.3599 92.7025 15.8399 93.0625 16.1399C93.4225 16.4299 93.9875 16.5749 94.7575 16.5749C95.4275 16.5749 96.2075 16.4499 97.0975 16.1999V17.6549C96.7475 17.8349 96.3275 17.9749 95.8375 18.0749C95.3575 18.1749 94.8575 18.2249 94.3375 18.2249C93.0675 18.2249 92.0975 17.8799 91.4275 17.1899C90.7675 16.4999 90.4375 15.4899 90.4375 14.1599C90.4375 12.8799 90.7675 11.8849 91.4275 11.1749C92.0875 10.4649 93.0025 10.1099 94.1725 10.1099C95.1625 10.1099 95.9225 10.3849 96.4525 10.9349C96.9925 11.4749 97.2625 12.2499 97.2625 13.2599C97.2625 13.4799 97.2475 13.7299 97.2175 14.0099C97.1875 14.2899 97.1525 14.5199 97.1125 14.6999H92.4625ZM94.0975 11.6249C93.6075 11.6249 93.2175 11.7749 92.9275 12.0749C92.6475 12.3649 92.4875 12.7899 92.4475 13.3499H95.3875V13.0949C95.3875 12.1149 94.9575 11.6249 94.0975 11.6249Z" fill="#252F3E"/>
+<path d="M81.1992 18V7.60498H84.9342C85.9342 7.60498 86.7392 7.85998 87.3492 8.36998C87.9692 8.87998 88.2792 9.54498 88.2792 10.365C88.2792 10.875 88.1592 11.315 87.9192 11.685C87.6892 12.045 87.3442 12.325 86.8842 12.525C87.5242 12.715 88.0092 13.03 88.3392 13.47C88.6792 13.9 88.8492 14.43 88.8492 15.06C88.8492 15.96 88.5142 16.675 87.8442 17.205C87.1742 17.735 86.2742 18 85.1442 18H81.1992ZM83.3292 13.47V16.395H85.0992C86.1192 16.395 86.6292 15.915 86.6292 14.955C86.6292 13.965 86.0842 13.47 84.9942 13.47H83.3292ZM83.3292 9.20998V11.94H84.6342C85.6042 11.94 86.0892 11.49 86.0892 10.59C86.0892 9.66998 85.6442 9.20998 84.7542 9.20998H83.3292Z" fill="#252F3E"/>
+<path fill-rule="evenodd" clip-rule="evenodd" d="M62.0002 20.4425L58.6644 21.5548L57.3636 20.6872L58.7799 20.2142L58.3454 18.9107L55.9143 19.7206L55.1251 19.1953V15.4374C55.1251 15.1775 54.9779 14.9396 54.7456 14.8227L52.375 13.6375V10.3621L54.4376 9.33087L56.5001 10.3621V12.6873C56.5001 12.9486 56.6472 13.1864 56.8796 13.3033L59.6297 14.6783L60.2457 13.4477L57.8751 12.2624V10.3621L60.2457 9.17824C60.4781 9.06136 60.6252 8.82349 60.6252 8.56223V6.49969H59.2502V8.13735L57.1876 9.16862L55.1251 8.13735V4.80566L56.5001 3.88852V6.49969H57.8751V2.97275L58.6644 2.44612L62.0002 3.55851V20.4425ZM69.5628 18.8749C69.941 18.8749 70.2504 19.1829 70.2504 19.5624C70.2504 19.9419 69.941 20.2499 69.5628 20.2499C69.1847 20.2499 68.8753 19.9419 68.8753 19.5624C68.8753 19.1829 69.1847 18.8749 69.5628 18.8749ZM68.1878 3.74964C68.566 3.74964 68.8753 4.05765 68.8753 4.43715C68.8753 4.81666 68.566 5.12467 68.1878 5.12467C67.8097 5.12467 67.5003 4.81666 67.5003 4.43715C67.5003 4.05765 67.8097 3.74964 68.1878 3.74964ZM70.9379 11.9998C71.316 11.9998 71.6254 12.3078 71.6254 12.6873C71.6254 13.0668 71.316 13.3748 70.9379 13.3748C70.5597 13.3748 70.2504 13.0668 70.2504 12.6873C70.2504 12.3078 70.5597 11.9998 70.9379 11.9998ZM69.0018 13.3748C69.2865 14.1737 70.0427 14.7498 70.9379 14.7498C72.075 14.7498 73.0004 13.8258 73.0004 12.6873C73.0004 11.5502 72.075 10.6248 70.9379 10.6248C70.0427 10.6248 69.2865 11.2023 69.0018 11.9998H63.3752V9.24974H68.1878C68.5673 9.24974 68.8753 8.94311 68.8753 8.56223V6.37319C69.6742 6.08856 70.2504 5.3323 70.2504 4.43715C70.2504 3.30001 69.325 2.37462 68.1878 2.37462C67.0507 2.37462 66.1253 3.30001 66.1253 4.43715C66.1253 5.3323 66.7014 6.08856 67.5003 6.37319V7.87472H63.3752V3.06213C63.3752 2.7665 63.1855 2.50387 62.905 2.41037L58.7799 1.03534C58.5778 0.967964 58.3578 0.998214 58.1818 1.11509L54.0567 3.86514C53.8656 3.99302 53.7501 4.20752 53.7501 4.43715V8.13735L51.3795 9.32262C51.1471 9.4395 51 9.67738 51 9.93726V14.0623C51 14.3236 51.1471 14.5615 51.3795 14.6783L53.7501 15.8622V19.5624C53.7501 19.7921 53.8656 20.0079 54.0567 20.1344L58.1818 22.8845C58.2959 22.9615 58.4279 23 58.5626 23C58.6355 23 58.7084 22.989 58.7799 22.9642L62.905 21.5892C63.1855 21.4971 63.3752 21.2345 63.3752 20.9375V17.4999H66.5282L67.7011 18.6742L67.7189 18.6563C67.5842 18.9313 67.5003 19.2366 67.5003 19.5624C67.5003 20.6996 68.4257 21.625 69.5628 21.625C70.7 21.625 71.6254 20.6996 71.6254 19.5624C71.6254 18.4253 70.7 17.4999 69.5628 17.4999C69.2356 17.4999 68.9303 17.5838 68.6567 17.7199L68.6746 17.702L67.2996 16.327C67.1703 16.1977 66.9957 16.1249 66.8128 16.1249H63.3752V13.3748H69.0018Z" fill="#252F3E"/>
+<line x1="43.25" y1="4" x2="43.25" y2="20" stroke="black" stroke-opacity="0.08" stroke-width="0.5"/>
+<path d="M9.89554 9.62679C9.89554 10.0589 9.94226 10.4093 10.024 10.6663C10.1175 10.9232 10.2342 11.2035 10.3978 11.5072C10.4562 11.6006 10.4795 11.6941 10.4795 11.7758C10.4795 11.8926 10.4094 12.0094 10.2576 12.1262L9.52179 12.6168C9.41667 12.6869 9.31156 12.7219 9.21812 12.7219C9.10132 12.7219 8.98453 12.6635 8.86773 12.5584C8.70422 12.3832 8.56406 12.1963 8.44726 12.0094C8.33047 11.8109 8.21367 11.589 8.0852 11.3203C7.17419 12.3949 6.02958 12.9321 4.65139 12.9321C3.6703 12.9321 2.88777 12.6518 2.31546 12.0912C1.74316 11.5306 1.45117 10.7831 1.45117 9.84871C1.45117 8.85594 1.80156 8.05004 2.51402 7.4427C3.22647 6.83536 4.17252 6.53169 5.37552 6.53169C5.77263 6.53169 6.18142 6.56673 6.61356 6.62513C7.04571 6.68353 7.48954 6.77697 7.95672 6.88208V6.02947C7.95672 5.14182 7.76985 4.5228 7.40778 4.16073C7.03403 3.79866 6.40333 3.62347 5.504 3.62347C5.09521 3.62347 4.67475 3.67019 4.2426 3.7753C3.81046 3.88042 3.38999 4.00889 2.9812 4.17241C2.79433 4.25417 2.65417 4.30089 2.57242 4.32424C2.49066 4.3476 2.43226 4.35928 2.38554 4.35928C2.22203 4.35928 2.14027 4.24249 2.14027 3.99722V3.42491C2.14027 3.23804 2.16363 3.09788 2.22203 3.01613C2.28042 2.93437 2.38554 2.85261 2.54906 2.77085C2.95784 2.56062 3.44839 2.38543 4.02069 2.24527C4.59299 2.09344 5.20033 2.02336 5.84271 2.02336C7.23258 2.02336 8.24871 2.33871 8.90277 2.96941C9.54515 3.60011 9.87218 4.55784 9.87218 5.8426V9.62679H9.89554ZM5.15361 11.4021C5.53904 11.4021 5.93615 11.332 6.35661 11.1919C6.77708 11.0517 7.15083 10.7948 7.46618 10.4444C7.65305 10.2225 7.79321 9.97718 7.86328 9.69687C7.93336 9.41656 7.98008 9.07785 7.98008 8.68074V8.1902C7.64137 8.10844 7.2793 8.03836 6.90555 7.99165C6.53181 7.94493 6.16974 7.92157 5.80767 7.92157C5.02514 7.92157 4.45283 8.0734 4.06741 8.38875C3.68198 8.7041 3.49511 9.14793 3.49511 9.73191C3.49511 10.2809 3.63526 10.6896 3.92725 10.9699C4.20756 11.2619 4.61635 11.4021 5.15361 11.4021ZM14.5323 12.6635C14.3221 12.6635 14.182 12.6285 14.0885 12.5467C13.9951 12.4766 13.9133 12.3131 13.8432 12.0912L11.0985 3.06285C11.0285 2.82925 10.9934 2.67742 10.9934 2.59566C10.9934 2.40879 11.0869 2.30367 11.2737 2.30367H12.4183C12.6402 2.30367 12.7921 2.33871 12.8738 2.42047C12.9673 2.49054 13.0374 2.65406 13.1074 2.87597L15.0696 10.6079L16.8916 2.87597C16.95 2.64238 17.0201 2.49054 17.1135 2.42047C17.207 2.35039 17.3705 2.30367 17.5807 2.30367H18.5151C18.737 2.30367 18.8888 2.33871 18.9823 2.42047C19.0757 2.49054 19.1575 2.65406 19.2042 2.87597L21.0496 10.7013L23.0701 2.87597C23.1402 2.64238 23.222 2.49054 23.3037 2.42047C23.3972 2.35039 23.549 2.30367 23.7592 2.30367H24.8454C25.0323 2.30367 25.1374 2.39711 25.1374 2.59566C25.1374 2.65406 25.1258 2.71246 25.1141 2.78253C25.1024 2.85261 25.079 2.94605 25.0323 3.07453L22.2175 12.1029C22.1475 12.3365 22.0657 12.4883 21.9723 12.5584C21.8788 12.6285 21.727 12.6752 21.5284 12.6752H20.524C20.3021 12.6752 20.1502 12.6401 20.0568 12.5584C19.9634 12.4766 19.8816 12.3248 19.8349 12.0912L18.0246 4.55784L16.2259 12.0795C16.1675 12.3131 16.0974 12.4649 16.004 12.5467C15.9105 12.6285 15.747 12.6635 15.5368 12.6635H14.5323ZM29.5407 12.9788C28.9333 12.9788 28.326 12.9088 27.742 12.7686C27.158 12.6285 26.7025 12.4766 26.3988 12.3014C26.212 12.1963 26.0835 12.0795 26.0368 11.9744C25.9901 11.8693 25.9667 11.7525 25.9667 11.6474V11.0517C25.9667 10.8064 26.0601 10.6896 26.2353 10.6896C26.3054 10.6896 26.3755 10.7013 26.4456 10.7247C26.5156 10.748 26.6208 10.7948 26.7375 10.8415C27.1347 11.0167 27.5668 11.1568 28.0223 11.2503C28.4895 11.3437 28.945 11.3904 29.4122 11.3904C30.148 11.3904 30.7203 11.2619 31.1174 11.005C31.5145 10.748 31.7247 10.3743 31.7247 9.89542C31.7247 9.56839 31.6196 9.29976 31.4094 9.07785C31.1992 8.85594 30.8021 8.65738 30.2298 8.47051L28.5362 7.94493C27.6836 7.6763 27.0529 7.27919 26.6675 6.75361C26.282 6.2397 26.0835 5.6674 26.0835 5.06006C26.0835 4.56952 26.1886 4.13737 26.3988 3.76362C26.6091 3.38987 26.8894 3.06285 27.2398 2.80589C27.5902 2.53726 27.9873 2.33871 28.4545 2.19855C28.9216 2.0584 29.4122 2 29.9261 2C30.183 2 30.4517 2.01168 30.7086 2.04672C30.9773 2.08176 31.2225 2.12848 31.4678 2.17519C31.7014 2.23359 31.9233 2.29199 32.1335 2.36207C32.3438 2.43215 32.5073 2.50222 32.6241 2.5723C32.7876 2.66574 32.9044 2.75918 32.9745 2.86429C33.0445 2.95773 33.0796 3.0862 33.0796 3.24972V3.79866C33.0796 4.04393 32.9861 4.17241 32.811 4.17241C32.7175 4.17241 32.5657 4.12569 32.3671 4.03225C31.7014 3.72858 30.9539 3.57675 30.1246 3.57675C29.4589 3.57675 28.9333 3.68187 28.5712 3.90378C28.2092 4.12569 28.0223 4.4644 28.0223 4.94326C28.0223 5.27029 28.1391 5.5506 28.3727 5.77252C28.6063 5.99443 29.0384 6.21634 29.6575 6.4149L31.316 6.94048C32.1569 7.20911 32.7642 7.58286 33.1263 8.06172C33.4884 8.54059 33.6636 9.08953 33.6636 9.69687C33.6636 10.1991 33.5584 10.6546 33.3599 11.0517C33.1497 11.4488 32.8693 11.7992 32.5073 12.0795C32.1452 12.3715 31.7131 12.5817 31.2108 12.7336C30.6853 12.8971 30.1363 12.9788 29.5407 12.9788Z" fill="#252F3E"/>
+<path fill-rule="evenodd" clip-rule="evenodd" d="M31.749 18.6553C27.9064 21.4934 22.3235 23.0001 17.5232 23.0001C10.7957 23.0001 4.73399 20.5123 0.155575 16.3778C-0.206494 16.0507 0.120536 15.6069 0.552682 15.8639C5.50484 18.737 11.6133 20.4773 17.932 20.4773C22.195 20.4773 26.8786 19.5896 31.1883 17.7676C31.8307 17.4756 32.3797 18.1881 31.749 18.6553Z" fill="#FF9900"/>
+<path fill-rule="evenodd" clip-rule="evenodd" d="M33.3507 16.833C32.8601 16.2023 30.1037 16.5293 28.854 16.6811C28.4803 16.7278 28.4219 16.4008 28.7606 16.1555C30.9564 14.6138 34.5654 15.0577 34.9858 15.5716C35.4063 16.0971 34.869 19.7062 32.8134 21.4347C32.4981 21.7034 32.1944 21.5632 32.3345 21.2128C32.8017 20.0565 33.8412 17.452 33.3507 16.833Z" fill="#FF9900"/>
+</svg>

ai-provider/model-runtime/model-providers/bedrock/assets/icon_s_en.svg

@@ -0,0 +1,15 @@
+<svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
+<g clip-path="url(#clip0_16762_59518)">
+<path d="M12.6667 0H3.33333C1.49238 0 0 1.49238 0 3.33333V12.6667C0 14.5076 1.49238 16 3.33333 16H12.6667C14.5076 16 16 14.5076 16 12.6667V3.33333C16 1.49238 14.5076 0 12.6667 0Z" fill="url(#paint0_linear_16762_59518)"/>
+<path fill-rule="evenodd" clip-rule="evenodd" d="M7.99984 12.093L6.3825 12.6323L5.75184 12.2116L6.4385 11.9823L6.22784 11.3503L5.04917 11.743L4.6665 11.4883V9.66631C4.6665 9.54031 4.59517 9.42497 4.4825 9.3683L3.33317 8.79364V7.20564L4.33317 6.70564L5.33317 7.20564V8.33297C5.33317 8.45964 5.4045 8.57497 5.51717 8.63164L6.8505 9.29831L7.14917 8.70164L5.99984 8.12697V7.20564L7.14917 6.63164C7.26184 6.57497 7.33317 6.45964 7.33317 6.33297V5.33297H6.6665V6.12697L5.6665 6.62697L4.6665 6.12697V4.51164L5.33317 4.06697V5.33297H5.99984V3.62297L6.3825 3.36764L7.99984 3.90697V12.093ZM11.6665 11.333C11.8498 11.333 11.9998 11.4823 11.9998 11.6663C11.9998 11.8503 11.8498 11.9996 11.6665 11.9996C11.4832 11.9996 11.3332 11.8503 11.3332 11.6663C11.3332 11.4823 11.4832 11.333 11.6665 11.333ZM10.9998 3.99964C11.1832 3.99964 11.3332 4.14897 11.3332 4.33297C11.3332 4.51697 11.1832 4.6663 10.9998 4.6663C10.8165 4.6663 10.6665 4.51697 10.6665 4.33297C10.6665 4.14897 10.8165 3.99964 10.9998 3.99964ZM12.3332 7.99964C12.5165 7.99964 12.6665 8.14897 12.6665 8.33297C12.6665 8.51697 12.5165 8.66631 12.3332 8.66631C12.1498 8.66631 11.9998 8.51697 11.9998 8.33297C11.9998 8.14897 12.1498 7.99964 12.3332 7.99964ZM11.3945 8.66631C11.5325 9.05364 11.8992 9.33297 12.3332 9.33297C12.8845 9.33297 13.3332 8.88497 13.3332 8.33297C13.3332 7.78164 12.8845 7.33297 12.3332 7.33297C11.8992 7.33297 11.5325 7.61297 11.3945 7.99964H8.6665V6.66631H10.9998C11.1838 6.66631 11.3332 6.51764 11.3332 6.33297V5.27164C11.7205 5.13364 11.9998 4.76697 11.9998 4.33297C11.9998 3.78164 11.5512 3.33297 10.9998 3.33297C10.4485 3.33297 9.99984 3.78164 9.99984 4.33297C9.99984 4.76697 10.2792 5.13364 10.6665 5.27164V5.99964H8.6665V3.6663C8.6665 3.52297 8.5745 3.39564 8.4385 3.3503L6.4385 2.68364C6.3405 2.65097 6.23384 2.66564 6.1485 2.7223L4.1485 4.05564C4.05584 4.11764 3.99984 4.22164 3.99984 4.33297V6.12697L2.8505 6.70164C2.73784 6.75831 2.6665 6.87364 2.6665 6.99964V8.99964C2.6665 9.12631 2.73784 9.24164 2.8505 9.29831L3.99984 9.87231V11.6663C3.99984 11.7776 4.05584 11.8823 4.1485 11.9436L6.1485 13.277C6.20384 13.3143 6.26784 13.333 6.33317 13.333C6.3685 13.333 6.40384 13.3276 6.4385 13.3156L8.4385 12.649C8.5745 12.6043 8.6665 12.477 8.6665 12.333V10.6663H10.1952L10.7638 11.2356L10.7725 11.227C10.7072 11.3603 10.6665 11.5083 10.6665 11.6663C10.6665 12.2176 11.1152 12.6663 11.6665 12.6663C12.2178 12.6663 12.6665 12.2176 12.6665 11.6663C12.6665 11.115 12.2178 10.6663 11.6665 10.6663C11.5078 10.6663 11.3598 10.707 11.2272 10.773L11.2358 10.7643L10.5692 10.0976C10.5065 10.035 10.4218 9.99964 10.3332 9.99964H8.6665V8.66631H11.3945Z" fill="white"/>
+</g>
+<defs>
+<linearGradient id="paint0_linear_16762_59518" x1="0" y1="1600" x2="1600" y2="0" gradientUnits="userSpaceOnUse">
+<stop stop-color="#055F4E"/>
+<stop offset="1" stop-color="#56C0A7"/>
+</linearGradient>
+<clipPath id="clip0_16762_59518">
+<rect width="16" height="16" fill="white"/>
+</clipPath>
+</defs>
+</svg>

ai-provider/model-runtime/model-providers/bedrock/bedrock.yaml

@@ -0,0 +1,92 @@
+provider: bedrock
+label:
+  en_US: AWS Bedrock
+description:
+  en_US: AWS Bedrock's models.
+icon_small:
+  en_US: icon_s_en.svg
+icon_large:
+  en_US: icon_l_en.svg
+background: "#FCFDFF"
+help:
+  title:
+    en_US: Get your Access Key and Secret Access Key from AWS Console
+  url:
+    en_US: https://console.aws.amazon.com/
+supported_model_types:
+  - llm
+  - text-embedding
+configurate_methods:
+  - predefined-model
+provider_credential_schema:
+  credential_form_schemas:
+    - variable: aws_access_key_id
+      required: false
+      label:
+        en_US: Access Key (If not provided, credentials are obtained from the running environment.)
+        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)
+address: https://bedrock-runtime.amazonaws.com
+sort: 4
+recommend: true

ai-provider/model-runtime/model-providers/bedrock/llm/ai21.j2-mid-v1.yaml

@@ -0,0 +1,47 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/ai21.j2-ultra-v1.yaml

@@ -0,0 +1,47 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/amazon.titan-text-express-v1.yaml

@@ -0,0 +1,23 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/amazon.titan-text-lite-v1.yaml

@@ -0,0 +1,23 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/anthropic.claude-3-haiku-v1.yaml

@@ -0,0 +1,61 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/anthropic.claude-3-opus-v1.yaml

@@ -0,0 +1,61 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/anthropic.claude-3-sonnet-v1.5.yaml

@@ -0,0 +1,60 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/anthropic.claude-3-sonnet-v1.yaml

@@ -0,0 +1,60 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/anthropic.claude-instant-v1.yaml

@@ -0,0 +1,52 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/anthropic.claude-v1.yaml

@@ -0,0 +1,53 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/anthropic.claude-v2.1.yaml

@@ -0,0 +1,54 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/anthropic.claude-v2.yaml

@@ -0,0 +1,54 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/cohere.command-light-text-v14.yaml

@@ -0,0 +1,35 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/cohere.command-r-plus-v1.0.yaml

@@ -0,0 +1,44 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/cohere.command-r-v1.0.yaml

@@ -0,0 +1,43 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/cohere.command-text-v14.yaml

@@ -0,0 +1,32 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/eu.anthropic.claude-3-haiku-v1.yaml

@@ -0,0 +1,59 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/eu.anthropic.claude-3-sonnet-v1.5.yaml

@@ -0,0 +1,58 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/eu.anthropic.claude-3-sonnet-v1.yaml

@@ -0,0 +1,58 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/meta.llama2-13b-chat-v1.yaml

@@ -0,0 +1,23 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/meta.llama2-70b-chat-v1.yaml

@@ -0,0 +1,23 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/meta.llama3-1-405b-instruct-v1.0.yaml

@@ -0,0 +1,25 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/meta.llama3-1-70b-instruct-v1.0.yaml

@@ -0,0 +1,25 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/meta.llama3-1-8b-instruct-v1.0.yaml

@@ -0,0 +1,25 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/meta.llama3-70b-instruct-v1.yaml

@@ -0,0 +1,23 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/meta.llama3-8b-instruct-v1.yaml

@@ -0,0 +1,23 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/mistral.mistral-7b-instruct-v0.2.yaml

@@ -0,0 +1,39 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/mistral.mistral-large-2402-v1.0.yaml

@@ -0,0 +1,30 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/mistral.mistral-large-2407-v1.0.yaml

@@ -0,0 +1,29 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/mistral.mistral-small-2402-v1.0.yaml

@@ -0,0 +1,29 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/mistral.mixtral-8x7b-instruct-v0.1.yaml

@@ -0,0 +1,39 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/us.anthropic.claude-3-haiku-v1.yaml

@@ -0,0 +1,59 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/us.anthropic.claude-3-opus-v1.yaml

@@ -0,0 +1,59 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/us.anthropic.claude-3-sonnet-v1.5.yaml

@@ -0,0 +1,58 @@
+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

ai-provider/model-runtime/model-providers/bedrock/llm/us.anthropic.claude-3-sonnet-v1.yaml

@@ -0,0 +1,58 @@
+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

ai-provider/model-runtime/model-providers/chatglm/assets/icon_s_en.svg

@@ -0,0 +1,9 @@
+<svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+<mask id="mask0_8587_60212" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="1" y="2" width="23" height="21">
+<path d="M23.8 2H1V22.4H23.8V2Z" fill="white"/>
+</mask>
+<g mask="url(#mask0_8587_60212)">
+<path fill-rule="evenodd" clip-rule="evenodd" d="M3.86378 14.4544C3.86378 13.0981 4.67438 11.737 6.25923 10.6634C7.83827 9.59364 10.0864 8.89368 12.6282 8.89368C15.17 8.89368 17.4182 9.59364 18.9972 10.6634C19.7966 11.2049 20.399 11.8196 20.7998 12.4699C21.2873 11.5802 21.4969 10.6351 21.3835 9.69252C21.3759 9.62928 21.3824 9.56766 21.4005 9.5106C21.0758 9.21852 20.7259 8.94624 20.3558 8.69556C18.3272 7.32126 15.5915 6.50964 12.6282 6.50964C9.66497 6.50964 6.92918 7.32126 4.90058 8.69556C2.8778 10.0659 1.45703 12.0812 1.45703 14.4544C1.45703 16.8275 2.8778 18.8428 4.90058 20.2132C6.92918 21.5875 9.66497 22.3991 12.6282 22.3991C15.5915 22.3991 18.3272 21.5875 20.3558 20.2132C22.3786 18.8428 23.7994 16.8275 23.7994 14.4544C23.7994 12.9455 23.225 11.5813 22.2868 10.4355C22.2377 11.4917 21.8621 12.5072 21.238 13.43C21.3409 13.7686 21.3926 14.1116 21.3926 14.4544C21.3926 15.8107 20.582 17.1717 18.9972 18.2453C17.4182 19.3151 15.17 20.015 12.6282 20.015C10.0864 20.015 7.83827 19.3151 6.25923 18.2453C4.67438 17.1717 3.86378 15.8107 3.86378 14.4544Z" fill="#3762FF"/>
+<path fill-rule="evenodd" clip-rule="evenodd" d="M3.84445 11.6838C3.20239 13.4885 3.35368 15.1156 4.18868 16.2838C5.02368 17.452 6.52281 18.1339 8.45459 18.1334C10.3826 18.133 12.6296 17.44 14.6939 15.9922C16.7581 14.5444 18.1643 12.6753 18.8052 10.8739C19.4473 9.0692 19.2959 7.44206 18.461 6.27392C17.626 5.10572 16.1269 4.42389 14.1951 4.42431C12.267 4.42475 10.0201 5.11774 7.95575 6.56552C5.89152 8.01332 4.48529 9.8825 3.84445 11.6838ZM1.53559 10.8778C2.36374 8.55002 4.11254 6.28976 6.54117 4.58645C8.96981 2.88312 11.7029 1.99995 14.1945 1.99939C16.6825 1.99884 19.0426 2.8912 20.4589 4.87263C21.8752 6.85406 21.941 9.35564 21.1141 11.6799C20.2859 14.0077 18.5371 16.2679 16.1085 17.9713C13.6798 19.6746 10.9468 20.5578 8.45513 20.5584C5.9672 20.5589 3.60706 19.6665 2.19075 17.6851C0.774446 15.7036 0.708677 13.2021 1.53559 10.8778Z" fill="#1041F3"/>
+</g>
+</svg>

ai-provider/model-runtime/model-providers/chatglm/chatglm.yaml

@@ -0,0 +1,29 @@
+provider: chatglm
+label:
+  en_US: ChatGLM
+icon_small:
+  en_US: icon_s_en.svg
+icon_large:
+  en_US: icon_l_en.svg
+background: "#F4F7FF"
+help:
+  title:
+    en_US: Deploy ChatGLM to your local
+    zh_Hans: 部署您的本地 ChatGLM
+  url:
+    en_US: https://github.com/THUDM/ChatGLM3
+supported_model_types:
+  - llm
+configurate_methods:
+  - predefined-model
+provider_credential_schema:
+  credential_form_schemas:
+    - variable: api_base
+      label:
+        en_US: API URL
+      type: text-input
+      required: true
+      placeholder:
+        zh_Hans: 在此输入您的 API URL
+        en_US: Enter your API URL
+address: https://api.openai.com

ai-provider/model-runtime/model-providers/chatglm/llm/chatglm2-6b-32k.yaml

@@ -0,0 +1,21 @@
+model: chatglm2-6b-32k
+label:
+  en_US: ChatGLM2-6B-32K
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 32000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+    required: false
+  - name: max_tokens
+    use_template: max_tokens
+    required: true
+    default: 2000
+    min: 1
+    max: 32000

ai-provider/model-runtime/model-providers/chatglm/llm/chatglm2-6b.yaml

@@ -0,0 +1,21 @@
+model: chatglm2-6b
+label:
+  en_US: ChatGLM2-6B
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 2000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+    required: false
+  - name: max_tokens
+    use_template: max_tokens
+    required: true
+    default: 256
+    min: 1
+    max: 2000

ai-provider/model-runtime/model-providers/chatglm/llm/chatglm3-6b-32k.yaml

@@ -0,0 +1,22 @@
+model: chatglm3-6b-32k
+label:
+  en_US: ChatGLM3-6B-32K
+model_type: llm
+features:
+  - tool-call
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 32000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+    required: false
+  - name: max_tokens
+    use_template: max_tokens
+    required: true
+    default: 8000
+    min: 1
+    max: 32000

ai-provider/model-runtime/model-providers/chatglm/llm/chatglm3-6b.yaml

@@ -0,0 +1,22 @@
+model: chatglm3-6b
+label:
+  en_US: ChatGLM3-6B
+model_type: llm
+features:
+  - tool-call
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 8000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+    required: false
+  - name: max_tokens
+    use_template: max_tokens
+    required: true
+    default: 256
+    min: 1
+    max: 8000

ai-provider/model-runtime/model-providers/cohere/assets/icon_l_en.svg

@@ -0,0 +1,11 @@
+<svg width="120" height="24" viewBox="0 0 120 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path d="M34.4917 21.9129C37.4378 21.9129 40.0162 20.4398 41.0355 17.4656C41.2334 16.8701 40.9496 16.4743 40.384 16.4743H39.2787C38.7689 16.4743 38.4292 16.7002 38.2013 17.1818C37.3239 18.9108 36.1047 19.5324 34.5757 19.5324C31.8553 19.5324 30.1844 17.6335 30.1844 14.4616C30.1844 11.2896 31.9133 9.39083 34.5177 9.39083C36.1046 9.39083 37.4079 10.0704 38.2293 11.6854C38.4852 12.1671 38.795 12.3929 39.3067 12.3929H40.412C40.9776 12.3929 41.2614 12.0251 41.0635 11.4855C39.8742 8.25556 37.2099 7.01035 34.4917 7.01035C30.3843 7.01035 27.3242 10.0424 27.3242 14.4616C27.3242 18.8808 30.2424 21.9129 34.4917 21.9129ZM108.627 13.1584C108.995 10.75 110.638 9.24892 112.876 9.24892C115.115 9.24892 116.786 10.7779 116.983 13.1584H108.627ZM112.99 21.9129C115.596 21.9129 118.203 20.6956 119.478 17.9474C119.79 17.2958 119.506 16.8421 118.94 16.8421H117.892C117.383 16.8421 117.071 17.0679 116.816 17.5216C115.966 19.0227 114.493 19.6463 112.992 19.6463C110.414 19.6463 108.743 17.8894 108.545 15.0292H118.943C119.508 15.0292 119.878 14.7174 119.878 14.1219C119.764 9.67465 116.876 7.01235 112.88 7.01235C108.885 7.01235 105.713 9.90251 105.713 14.4636C105.713 19.0247 108.801 21.9148 112.994 21.9148L112.99 21.9129ZM96.5025 14.8313H97.4378C98.0035 14.8313 98.3152 14.5196 98.4012 13.9239C98.9409 10.0964 101.182 9.5887 103.564 9.70264C104.074 9.72661 104.491 9.33487 104.491 8.82319V7.94575C104.491 7.38012 104.208 7.03833 103.642 7.01035C101.533 6.9304 99.6525 7.65393 98.5651 9.70264C98.5052 9.81455 98.3373 9.78458 98.3233 9.65866L98.1474 8.11365C98.0915 7.54801 97.7796 7.26418 97.212 7.26418H92.9347C92.435 7.26418 92.0272 7.66993 92.0272 8.17161V8.6533C92.0272 9.15298 92.433 9.56072 92.9347 9.56072H94.6916C95.1912 9.56072 95.599 9.96646 95.599 10.4681V13.9239C95.599 14.4236 96.0048 14.8313 96.5064 14.8313H96.5025ZM92.6788 21.631H101.545C102.111 21.631 102.453 21.2913 102.453 20.7236V20.2418C102.453 19.6762 102.113 19.3345 101.545 19.3345H99.2787C98.7131 19.3345 98.3712 18.9947 98.3712 18.4271V16.8681C98.3712 16.3024 98.0315 15.9606 97.4638 15.9606H96.5005C95.9348 15.9606 95.593 16.3004 95.593 16.8681V18.4271C95.593 18.9927 95.2532 19.3345 94.6856 19.3345H92.6749C92.1092 19.3345 91.7674 19.6743 91.7674 20.2418V20.7236C91.7674 21.2893 92.1073 21.631 92.6749 21.631H92.6788ZM78.9955 13.1604C79.3633 10.752 81.0062 9.25092 83.2449 9.25092C85.4834 9.25092 87.1544 10.7799 87.3522 13.1604H78.9955ZM83.3587 21.9148C85.9651 21.9148 88.5714 20.6977 89.8466 17.9493C90.1585 17.2978 89.8746 16.844 89.309 16.844H88.2617C87.7519 16.844 87.4402 17.0699 87.1844 17.5236C86.3349 19.0247 84.8618 19.6482 83.3607 19.6482C80.7824 19.6482 79.1115 17.8914 78.9136 15.0313H89.311C89.8766 15.0313 90.2464 14.7194 90.2464 14.1238C90.1324 9.67665 87.2443 7.01434 83.2488 7.01434C79.2533 7.01434 76.0814 9.9045 76.0814 14.4656C76.0814 19.0266 79.1694 21.9168 83.3628 21.9168L83.3587 21.9148ZM50.5835 21.9148C54.8329 21.9148 57.8649 18.7708 57.8649 14.4636C57.8649 10.1563 54.8329 7.01235 50.5835 7.01235C46.3342 7.01235 43.3022 10.2143 43.3022 14.4636C43.3022 15.455 43.472 16.5602 43.9816 17.7775C44.2375 18.3731 44.7192 18.4571 45.2289 18.0892L46.0504 17.4936C46.4761 17.1818 46.588 16.8141 46.4461 16.2765C46.2202 15.5689 46.1623 14.9453 46.1623 14.4076C46.1623 11.4335 47.9472 9.39283 50.5815 9.39283C53.2159 9.39283 55.0007 11.4035 55.0007 14.4636C55.0007 17.5236 53.2439 19.5344 50.6375 19.5344C49.7301 19.5344 48.8806 19.3645 47.8612 18.5989C47.4355 18.2592 47.0397 18.2032 46.586 18.5429L45.9624 18.9967C45.4527 19.3645 45.3968 19.8741 45.8764 20.2718C47.3496 21.4611 49.0485 21.9148 50.5795 21.9148H50.5835ZM61.4606 21.631H62.3961C62.8957 21.631 63.3035 21.2252 63.3035 20.7236V13.9539C63.3035 11.0937 64.8324 9.39283 67.213 9.39283C69.3656 9.39283 70.6128 10.8099 70.6128 13.4163V20.7255C70.6128 21.2252 71.0186 21.633 71.5203 21.633H72.4836C72.9833 21.633 73.391 21.2272 73.391 20.7255V12.9625C73.391 9.13899 71.4363 7.01434 68.1224 7.01434C65.8659 7.01434 64.5327 7.93776 63.5373 9.22294C63.4613 9.32088 63.3075 9.26691 63.3075 9.14499V2.99092C63.3014 2.48924 62.8957 2.0835 62.3961 2.0835H61.4606C60.9609 2.0835 60.5532 2.48924 60.5532 2.99092V20.7236C60.5532 21.2232 60.959 21.631 61.4606 21.631Z" fill="#39594D"/>
+<mask id="mask0_13223_52628" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="1" y="2" width="20" height="20">
+<path d="M20.8354 2.08319H1.00195V21.9165H20.8354V2.08319Z" fill="white"/>
+</mask>
+<g mask="url(#mask0_13223_52628)">
+<path fill-rule="evenodd" clip-rule="evenodd" d="M7.42768 13.8921C7.96151 13.8921 9.02342 13.8628 10.4912 13.2585C12.2017 12.5542 15.6047 11.2758 18.0597 9.96274C19.7765 9.04432 20.5291 7.82964 20.5291 6.19387C20.5291 3.92362 18.6887 2.08319 16.4185 2.08319H6.90643C3.64547 2.08319 1.00195 4.72669 1.00195 7.98763C1.00195 11.2486 3.47706 13.8921 7.42768 13.8921Z" fill="#39594D"/>
+<path fill-rule="evenodd" clip-rule="evenodd" d="M9.03711 17.958C9.03711 16.3596 9.99942 14.9184 11.4758 14.3057L14.4713 13.0625C17.5013 11.805 20.8364 14.0316 20.8364 17.3123C20.8364 19.8539 18.7755 21.9141 16.2338 21.9134L12.9906 21.9126C10.807 21.912 9.03711 20.1417 9.03711 17.958Z" fill="#D18EE2"/>
+<path d="M4.40571 14.6705C2.5259 14.6705 1.00195 16.1943 1.00195 18.0741V18.515C1.00195 20.3947 2.52584 21.9186 4.40565 21.9186C6.28547 21.9186 7.80941 20.3947 7.80941 18.515V18.0741C7.80941 16.1943 6.28552 14.6705 4.40571 14.6705Z" fill="#FF7759"/>
+</g>
+</svg>

ai-provider/model-runtime/model-providers/cohere/assets/icon_s_en.svg

@@ -0,0 +1,16 @@
+<svg width="22" height="22" viewBox="0 0 22 22" fill="none" xmlns="http://www.w3.org/2000/svg">
+<g id="Clip path group">
+<mask id="mask0_13224_9519" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="0" y="0" width="22" height="22">
+<g id="clip0_2207_90691">
+<path id="Vector" d="M21.5 0.5H0.5V21.5H21.5V0.5Z" fill="white"/>
+</g>
+</mask>
+<g mask="url(#mask0_13224_9519)">
+<g id="Group">
+<path id="Vector_2" fill-rule="evenodd" clip-rule="evenodd" d="M7.30367 13.0035C7.8689 13.0035 8.99327 12.9725 10.5474 12.3326C12.3585 11.587 15.9617 10.2334 18.561 8.84305C20.3788 7.8706 21.1757 6.58448 21.1757 4.85248C21.1757 2.44869 19.2271 0.5 16.8233 0.5H6.75176C3.299 0.5 0.5 3.299 0.5 6.75176C0.5 10.2045 3.12069 13.0035 7.30367 13.0035Z" fill="#39594D"/>
+<path id="Vector_3" fill-rule="evenodd" clip-rule="evenodd" d="M9.00732 17.3086C9.00732 15.6162 10.0262 14.0902 11.5894 13.4414L14.7612 12.1251C17.9694 10.7936 21.5006 13.1513 21.5006 16.6249C21.5006 19.316 19.3185 21.4974 16.6273 21.4967L13.1933 21.4958C10.8813 21.4952 9.00732 19.6207 9.00732 17.3086Z" fill="#D18EE2"/>
+<path id="Vector_4" d="M4.10396 13.8277C2.11358 13.8277 0.5 15.4411 0.5 17.4315V17.8984C0.5 19.8887 2.11352 21.5022 4.1039 21.5022C6.09428 21.5022 7.70785 19.8887 7.70785 17.8984V17.4315C7.70785 15.4411 6.09434 13.8277 4.10396 13.8277Z" fill="#FF7759"/>
+</g>
+</g>
+</g>
+</svg>

ai-provider/model-runtime/model-providers/cohere/cohere.yaml

@@ -0,0 +1,35 @@
+provider: cohere
+label:
+  zh_Hans: Cohere
+  en_US: Cohere
+icon_small:
+  en_US: icon_s_en.svg
+icon_large:
+  en_US: icon_l_en.svg
+background: "#ECE9E3"
+help:
+  title:
+    en_US: Get your API key from cohere
+    zh_Hans: 从 cohere 获取 API Key
+  url:
+    en_US: https://dashboard.cohere.com/api-keys
+supported_model_types:
+  - llm
+  - text-embedding
+  - rerank
+configurate_methods:
+  - predefined-model
+  - customizable-model
+provider_credential_schema:
+  credential_form_schemas:
+    - variable: api_key
+      label:
+        zh_Hans: API Key
+        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
+      show_on: [ ]
+address: https://api.cohere.com

ai-provider/model-runtime/model-providers/cohere/llm/command-chat.yaml

@@ -0,0 +1,62 @@
+model: command-chat
+label:
+  zh_Hans: command-chat
+  en_US: command-chat
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 4096
+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: max_tokens
+    use_template: max_tokens
+    default: 1024
+    max: 4096
+  - name: preamble_override
+    label:
+      zh_Hans: 前导文本
+      en_US: Preamble
+    type: string
+    help:
+      zh_Hans: 当指定时，将使用提供的前导文本替换默认的 Cohere 前导文本。
+      en_US: When specified, the default Cohere preamble will be replaced with the provided one.
+    required: false
+  - name: prompt_truncation
+    label:
+      zh_Hans: 提示截断
+      en_US: Prompt Truncation
+    type: string
+    help:
+      zh_Hans: 指定如何构造 Prompt。当 prompt_truncation 设置为 "AUTO" 时，将会丢弃一些来自聊天记录的元素，以尝试构造一个符合模型上下文长度限制的 Prompt。
+      en_US: Dictates how the prompt will be constructed. With prompt_truncation set to "AUTO", some elements from chat histories will be dropped in an attempt to construct a prompt that fits within the model's context length limit.
+    required: true
+    default: 'AUTO'
+    options:
+      - 'AUTO'
+      - 'OFF'
+pricing:
+  input: '1.0'
+  output: '2.0'
+  unit: '0.000001'
+  currency: USD

ai-provider/model-runtime/model-providers/cohere/llm/command-light-chat.yaml

@@ -0,0 +1,62 @@
+model: command-light-chat
+label:
+  zh_Hans: command-light-chat
+  en_US: command-light-chat
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 4096
+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: max_tokens
+    use_template: max_tokens
+    default: 1024
+    max: 4096
+  - name: preamble_override
+    label:
+      zh_Hans: 前导文本
+      en_US: Preamble
+    type: string
+    help:
+      zh_Hans: 当指定时，将使用提供的前导文本替换默认的 Cohere 前导文本。
+      en_US: When specified, the default Cohere preamble will be replaced with the provided one.
+    required: false
+  - name: prompt_truncation
+    label:
+      zh_Hans: 提示截断
+      en_US: Prompt Truncation
+    type: string
+    help:
+      zh_Hans: 指定如何构造 Prompt。当 prompt_truncation 设置为 "AUTO" 时，将会丢弃一些来自聊天记录的元素，以尝试构造一个符合模型上下文长度限制的 Prompt。
+      en_US: Dictates how the prompt will be constructed. With prompt_truncation set to "AUTO", some elements from chat histories will be dropped in an attempt to construct a prompt that fits within the model's context length limit.
+    required: true
+    default: 'AUTO'
+    options:
+      - 'AUTO'
+      - 'OFF'
+pricing:
+  input: '0.3'
+  output: '0.6'
+  unit: '0.000001'
+  currency: USD

ai-provider/model-runtime/model-providers/cohere/llm/command-light-nightly-chat.yaml

@@ -0,0 +1,62 @@
+model: command-light-nightly-chat
+label:
+  zh_Hans: command-light-nightly-chat
+  en_US: command-light-nightly-chat
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 4096
+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: max_tokens
+    use_template: max_tokens
+    default: 1024
+    max: 4096
+  - name: preamble_override
+    label:
+      zh_Hans: 前导文本
+      en_US: Preamble
+    type: string
+    help:
+      zh_Hans: 当指定时，将使用提供的前导文本替换默认的 Cohere 前导文本。
+      en_US: When specified, the default Cohere preamble will be replaced with the provided one.
+    required: false
+  - name: prompt_truncation
+    label:
+      zh_Hans: 提示截断
+      en_US: Prompt Truncation
+    type: string
+    help:
+      zh_Hans: 指定如何构造 Prompt。当 prompt_truncation 设置为 "AUTO" 时，将会丢弃一些来自聊天记录的元素，以尝试构造一个符合模型上下文长度限制的 Prompt。
+      en_US: Dictates how the prompt will be constructed. With prompt_truncation set to "AUTO", some elements from chat histories will be dropped in an attempt to construct a prompt that fits within the model's context length limit.
+    required: true
+    default: 'AUTO'
+    options:
+      - 'AUTO'
+      - 'OFF'
+pricing:
+  input: '0.3'
+  output: '0.6'
+  unit: '0.000001'
+  currency: USD

ai-provider/model-runtime/model-providers/cohere/llm/command-light-nightly.yaml

@@ -0,0 +1,44 @@
+model: command-light-nightly
+label:
+  zh_Hans: command-light-nightly
+  en_US: command-light-nightly
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: completion
+  context_size: 4096
+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: '0.3'
+  output: '0.6'
+  unit: '0.000001'
+  currency: USD

ai-provider/model-runtime/model-providers/cohere/llm/command-light.yaml

@@ -0,0 +1,44 @@
+model: command-light
+label:
+  zh_Hans: command-light
+  en_US: command-light
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: completion
+  context_size: 4096
+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: '0.3'
+  output: '0.6'
+  unit: '0.000001'
+  currency: USD

ai-provider/model-runtime/model-providers/cohere/llm/command-nightly-chat.yaml

@@ -0,0 +1,62 @@
+model: command-nightly-chat
+label:
+  zh_Hans: command-nightly-chat
+  en_US: command-nightly-chat
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 4096
+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: max_tokens
+    use_template: max_tokens
+    default: 1024
+    max: 4096
+  - name: preamble_override
+    label:
+      zh_Hans: 前导文本
+      en_US: Preamble
+    type: string
+    help:
+      zh_Hans: 当指定时，将使用提供的前导文本替换默认的 Cohere 前导文本。
+      en_US: When specified, the default Cohere preamble will be replaced with the provided one.
+    required: false
+  - name: prompt_truncation
+    label:
+      zh_Hans: 提示截断
+      en_US: Prompt Truncation
+    type: string
+    help:
+      zh_Hans: 指定如何构造 Prompt。当 prompt_truncation 设置为 "AUTO" 时，将会丢弃一些来自聊天记录的元素，以尝试构造一个符合模型上下文长度限制的 Prompt。
+      en_US: Dictates how the prompt will be constructed. With prompt_truncation set to "AUTO", some elements from chat histories will be dropped in an attempt to construct a prompt that fits within the model's context length limit.
+    required: true
+    default: 'AUTO'
+    options:
+      - 'AUTO'
+      - 'OFF'
+pricing:
+  input: '1.0'
+  output: '2.0'
+  unit: '0.000001'
+  currency: USD

ai-provider/model-runtime/model-providers/cohere/llm/command-nightly.yaml

@@ -0,0 +1,44 @@
+model: command-nightly
+label:
+  zh_Hans: command-nightly
+  en_US: command-nightly
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: completion
+  context_size: 4096
+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: '1.0'
+  output: '2.0'
+  unit: '0.000001'
+  currency: USD

ai-provider/model-runtime/model-providers/cohere/llm/command-r-plus.yaml

@@ -0,0 +1,45 @@
+model: command-r-plus
+label:
+  en_US: command-r-plus
+model_type: llm
+features:
+  - multi-tool-call
+  - agent-thought
+  - 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

ai-provider/model-runtime/model-providers/cohere/llm/command-r.yaml

@@ -0,0 +1,45 @@
+model: command-r
+label:
+  en_US: command-r
+model_type: llm
+features:
+  - multi-tool-call
+  - agent-thought
+  - 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: '0.5'
+  output: '1.5'
+  unit: '0.000001'
+  currency: USD

ai-provider/model-runtime/model-providers/cohere/llm/command.yaml

@@ -0,0 +1,44 @@
+model: command
+label:
+  zh_Hans: command
+  en_US: command
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: completion
+  context_size: 4096
+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: '1.0'
+  output: '2.0'
+  unit: '0.000001'
+  currency: USD

ai-provider/model-runtime/model-providers/deepseek/assets/icon_l_en.svg

@@ -0,0 +1,22 @@
+<svg width="195.000000" height="41.359375" viewBox="0 0 195 41.3594" fill="none" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
+	<desc>
+			Created with Pixso.
+	</desc>
+	<defs>
+		<clipPath id="clip30_2029">
+			<rect id="_图层_1" width="134.577469" height="25.511124" transform="translate(60.422485 10.022217)" fill="white"/>
+		</clipPath>
+	</defs>
+	<g clip-path="url(#clip30_2029)">
+		<path id="path" d="M119.508 30.113L117.562 30.113L117.562 27.0967L119.508 27.0967C120.713 27.0967 121.931 26.7961 122.715 25.9614C123.5 25.1265 123.796 23.8464 123.796 22.5664C123.796 21.2864 123.512 20.0063 122.715 19.1716C121.919 18.3369 120.713 18.0364 119.508 18.0364C118.302 18.0364 117.085 18.3369 116.3 19.1716C115.515 20.0063 115.219 21.2864 115.219 22.5664L115.219 34.9551L111.806 34.9551L111.806 15.031L115.219 15.031L115.219 16.2998L115.845 16.2998C115.913 16.2219 115.981 16.1553 116.049 16.0884C116.903 15.3093 118.211 15.031 119.496 15.031C121.51 15.031 123.523 15.532 124.843 16.9233C126.162 18.3145 126.629 20.4517 126.629 22.5776C126.629 24.7036 126.151 26.8296 124.843 28.2319C123.535 29.6345 121.51 30.113 119.508 30.113Z" fill-rule="nonzero" fill="#4D6BFE"/>
+		<path id="path" d="M67.5664 15.5654L69.5117 15.5654L69.5117 18.5818L67.5664 18.5818C66.3606 18.5818 65.1434 18.8823 64.3585 19.717C63.5736 20.552 63.2778 21.832 63.2778 23.1121C63.2778 24.3921 63.5623 25.6721 64.3585 26.5068C65.1548 27.3418 66.3606 27.6423 67.5664 27.6423C68.7722 27.6423 69.9895 27.3418 70.7744 26.5068C71.5593 25.6721 71.8551 24.3921 71.8551 23.1121L71.8551 10.7124L75.2677 10.7124L75.2677 30.6475L71.8551 30.6475L71.8551 29.3787L71.2294 29.3787C71.1611 29.4565 71.0929 29.5234 71.0247 29.5901C70.1715 30.3691 68.8633 30.6475 67.5779 30.6475C65.5643 30.6475 63.5509 30.1467 62.2313 28.7554C60.9117 27.364 60.4453 25.2268 60.4453 23.1008C60.4453 20.9749 60.9231 18.8489 62.2313 17.4465C63.5509 16.0552 65.5643 15.5654 67.5664 15.5654Z" fill-rule="nonzero" fill="#4D6BFE"/>
+		<path id="path" d="M92.3881 22.845L92.3881 24.0581L83.299 24.0581L83.299 21.6428L89.328 21.6428C89.1914 20.7634 88.8729 19.9397 88.3042 19.3386C87.4851 18.4705 86.2224 18.1589 84.9711 18.1589C83.7198 18.1589 82.4572 18.4705 81.6381 19.3386C80.819 20.2068 80.5232 21.5315 80.5232 22.845C80.5232 24.1582 80.819 25.4939 81.6381 26.3511C82.4572 27.208 83.7198 27.531 84.9711 27.531C86.2224 27.531 87.4851 27.2192 88.3042 26.3511C88.418 26.2285 88.5203 26.095 88.6227 25.9614L91.9899 25.9614C91.6941 27.0078 91.2277 27.9539 90.5225 28.6885C89.1573 30.1243 87.0529 30.6475 84.9711 30.6475C82.8894 30.6475 80.7849 30.1355 79.4198 28.6885C78.0547 27.2415 77.5542 25.0376 77.5542 22.845C77.5542 20.6521 78.0433 18.437 79.4198 17.0012C80.7963 15.5654 82.8894 15.0422 84.9711 15.0422C87.0529 15.0422 89.1573 15.5542 90.5225 17.0012C91.8988 18.4482 92.3881 20.6521 92.3881 22.845Z" fill-rule="nonzero" fill="#4D6BFE"/>
+		<path id="path" d="M109.52 22.845L109.52 24.0581L100.431 24.0581L100.431 21.6428L106.46 21.6428C106.323 20.7634 106.005 19.9397 105.436 19.3386C104.617 18.4705 103.354 18.1589 102.103 18.1589C100.852 18.1589 99.5889 18.4705 98.7698 19.3386C97.9507 20.2068 97.6549 21.5315 97.6549 22.845C97.6549 24.1582 97.9507 25.4939 98.7698 26.3511C99.5889 27.208 100.852 27.531 102.103 27.531C103.354 27.531 104.617 27.2192 105.436 26.3511C105.55 26.2285 105.652 26.095 105.754 25.9614L109.122 25.9614C108.826 27.0078 108.359 27.9539 107.654 28.6885C106.289 30.1243 104.185 30.6475 102.103 30.6475C100.021 30.6475 97.9166 30.1355 96.5515 28.6885C95.1864 27.2415 94.6859 25.0376 94.6859 22.845C94.6859 20.6521 95.175 18.437 96.5515 17.0012C97.928 15.5654 100.021 15.0422 102.103 15.0422C104.185 15.0422 106.289 15.5542 107.654 17.0012C109.031 18.4482 109.52 20.6521 109.52 22.845Z" fill-rule="nonzero" fill="#4D6BFE"/>
+		<path id="path" d="M136.355 30.6475C138.437 30.6475 140.541 30.3469 141.906 29.49C143.271 28.6328 143.772 27.3306 143.772 26.0393C143.772 24.7483 143.282 23.4348 141.906 22.5889C140.541 21.7429 138.437 21.4312 136.355 21.4312C135.467 21.4312 134.648 21.3088 134.068 20.9861C133.488 20.6521 133.272 20.1511 133.272 19.6504C133.272 19.1494 133.477 18.6375 134.068 18.3147C134.648 17.9807 135.547 17.8694 136.434 17.8694C137.322 17.8694 138.22 17.9919 138.801 18.3147C139.381 18.6487 139.597 19.1494 139.597 19.6504L143.066 19.6504C143.066 18.3591 142.623 17.0457 141.383 16.2C140.143 15.354 138.243 15.0422 136.355 15.0422C134.466 15.0422 132.567 15.3428 131.327 16.2C130.087 17.0569 129.643 18.3591 129.643 19.6504C129.643 20.9414 130.087 22.2549 131.327 23.1008C132.567 23.9468 134.466 24.2585 136.355 24.2585C137.333 24.2585 138.414 24.3809 139.062 24.7036C139.711 25.0266 139.938 25.5386 139.938 26.0393C139.938 26.5403 139.711 27.0522 139.062 27.375C138.414 27.6978 137.424 27.8203 136.446 27.8203C135.467 27.8203 134.466 27.6978 133.829 27.375C133.192 27.0522 132.953 26.5403 132.953 26.0393L128.949 26.0393C128.949 27.3306 129.438 28.644 130.815 29.49C132.191 30.3359 134.273 30.6475 136.355 30.6475Z" fill-rule="nonzero" fill="#4D6BFE"/>
+		<path id="path" d="M160.903 22.845L160.903 24.0581L151.814 24.0581L151.814 21.6428L157.843 21.6428C157.707 20.7634 157.388 19.9397 156.82 19.3386C156 18.4705 154.738 18.1589 153.486 18.1589C152.235 18.1589 150.972 18.4705 150.153 19.3386C149.334 20.2068 149.039 21.5315 149.039 22.845C149.039 24.1582 149.334 25.4939 150.153 26.3511C150.972 27.208 152.235 27.531 153.486 27.531C154.738 27.531 156 27.2192 156.82 26.3511C156.933 26.2285 157.036 26.095 157.138 25.9614L160.505 25.9614C160.209 27.0078 159.743 27.9539 159.038 28.6885C157.673 30.1243 155.568 30.6475 153.486 30.6475C151.405 30.6475 149.3 30.1355 147.935 28.6885C146.57 27.2415 146.07 25.0376 146.07 22.845C146.07 20.6521 146.559 18.437 147.935 17.0012C149.312 15.5654 151.405 15.0422 153.486 15.0422C155.568 15.0422 157.673 15.5542 159.038 17.0012C160.414 18.4482 160.903 20.6521 160.903 22.845Z" fill-rule="nonzero" fill="#4D6BFE"/>
+		<path id="path" d="M178.035 22.845L178.035 24.0581L168.946 24.0581L168.946 21.6428L174.975 21.6428C174.839 20.7634 174.52 19.9397 173.951 19.3386C173.132 18.4705 171.87 18.1589 170.618 18.1589C169.367 18.1589 168.104 18.4705 167.285 19.3386C166.466 20.2068 166.17 21.5315 166.17 22.845C166.17 24.1582 166.466 25.4939 167.285 26.3511C168.104 27.208 169.367 27.531 170.618 27.531C171.87 27.531 173.132 27.2192 173.951 26.3511C174.065 26.2285 174.167 26.095 174.27 25.9614L177.637 25.9614C177.341 27.0078 176.875 27.9539 176.17 28.6885C174.804 30.1243 172.7 30.6475 170.618 30.6475C168.536 30.6475 166.432 30.1355 165.067 28.6885C163.702 27.2415 163.201 25.0376 163.201 22.845C163.201 20.6521 163.69 18.437 165.067 17.0012C166.443 15.5654 168.536 15.0422 170.618 15.0422C172.7 15.0422 174.804 15.5542 176.17 17.0012C177.546 18.4482 178.035 20.6521 178.035 22.845Z" fill-rule="nonzero" fill="#4D6BFE"/>
+		<rect id="rect" x="180.321533" y="10.022217" width="3.412687" height="20.625223" fill="#4D6BFE"/>
+		<path id="polygon" d="M189.559 22.3772L195.155 30.6475L190.935 30.6475L185.338 22.3772L190.935 15.7322L195.155 15.7322L189.559 22.3772Z" fill-rule="nonzero" fill="#4D6BFE"/>
+	</g>
+	<path id="path" d="M55.6128 3.47119C55.0175 3.17944 54.7611 3.73535 54.413 4.01782C54.2939 4.10889 54.1932 4.22729 54.0924 4.33667C53.2223 5.26587 52.2057 5.87646 50.8776 5.80347C48.9359 5.69409 47.2781 6.30469 45.8126 7.78979C45.5012 5.9585 44.4663 4.86499 42.8909 4.16357C42.0667 3.79907 41.2332 3.43457 40.6561 2.64185C40.2532 2.07715 40.1432 1.44849 39.9418 0.828857C39.8135 0.455322 39.6853 0.0725098 39.2548 0.00878906C38.7877 -0.0639648 38.6045 0.327637 38.4213 0.655762C37.6886 1.99512 37.4047 3.47119 37.4321 4.96533C37.4962 8.32739 38.9159 11.0059 41.7369 12.9102C42.0575 13.1289 42.1399 13.3474 42.0392 13.6665C41.8468 14.3225 41.6178 14.9602 41.4164 15.6162C41.2881 16.0354 41.0957 16.1265 40.647 15.9441C39.0991 15.2974 37.7618 14.3406 36.5803 13.1836C34.5745 11.2429 32.761 9.10181 30.4988 7.42529C29.9675 7.03345 29.4363 6.66919 28.8867 6.32275C26.5786 4.08154 29.189 2.24097 29.7935 2.02246C30.4254 1.79468 30.0133 1.01099 27.9708 1.02026C25.9283 1.0293 24.0599 1.71265 21.6786 2.62378C21.3306 2.7605 20.9641 2.8606 20.5886 2.94263C18.4271 2.53271 16.1831 2.44141 13.8384 2.70581C9.42371 3.19775 5.89758 5.28418 3.30554 8.84668C0.191406 13.1289 -0.54126 17.9941 0.356323 23.0691C1.29968 28.4172 4.02905 32.8452 8.22388 36.3076C12.5745 39.8972 17.5845 41.6558 23.2997 41.3186C26.771 41.1182 30.6361 40.6536 34.9958 36.9636C36.0948 37.5103 37.2489 37.7288 39.1632 37.8928C40.6378 38.0295 42.0575 37.8201 43.1565 37.5923C44.8784 37.2278 44.7594 35.6333 44.1366 35.3418C39.09 32.9912 40.1981 33.9478 39.1907 33.1733C41.7552 30.1394 45.6204 26.9868 47.1316 16.7732C47.2506 15.9624 47.1499 15.4521 47.1316 14.7961C47.1224 14.3953 47.214 14.2405 47.672 14.1948C48.9359 14.0491 50.1632 13.7029 51.2898 13.0833C54.5596 11.2976 55.8784 8.36377 56.1898 4.84692C56.2357 4.30933 56.1807 3.75342 55.6128 3.47119ZM27.119 35.123C22.2281 31.2783 19.856 30.0117 18.8759 30.0664C17.96 30.1211 18.1249 31.1689 18.3263 31.8523C18.537 32.5264 18.8118 32.9912 19.1964 33.5833C19.462 33.9751 19.6453 34.5581 18.9309 34.9956C17.3555 35.9705 14.6169 34.6675 14.4886 34.6038C11.3014 32.7268 8.63611 30.2485 6.75842 26.8594C4.94495 23.5974 3.89172 20.0989 3.71765 16.3633C3.67188 15.4614 3.9375 15.1423 4.83508 14.9785C6.0166 14.7598 7.23474 14.7141 8.41626 14.8872C13.408 15.6162 17.6577 17.8484 21.2206 21.3835C23.2539 23.397 24.7926 25.8025 26.3772 28.1531C28.0624 30.6494 29.8759 33.0276 32.184 34.9773C32.9991 35.6606 33.6494 36.1799 34.2722 36.5627C32.3947 36.7722 29.2622 36.8179 27.119 35.123ZM29.4637 20.0442C29.4637 19.6433 29.7843 19.3245 30.1874 19.3245C30.2789 19.3245 30.3613 19.3425 30.4346 19.3699C30.5354 19.4065 30.627 19.4612 30.7002 19.543C30.8285 19.6707 30.9017 19.8528 30.9017 20.0442C30.9017 20.4451 30.5812 20.7639 30.1782 20.7639C29.7751 20.7639 29.4637 20.4451 29.4637 20.0442ZM36.7452 23.7798C36.2781 23.9712 35.811 24.135 35.3622 24.1533C34.6661 24.1897 33.9059 23.9072 33.4938 23.561C32.8527 23.0234 32.3947 22.7229 32.2023 21.7844C32.1199 21.3835 32.1656 20.7639 32.239 20.4087C32.4038 19.6433 32.2206 19.1514 31.6803 18.7048C31.2406 18.3403 30.6819 18.2402 30.0682 18.2402C29.8392 18.2402 29.6287 18.1399 29.4729 18.0579C29.2164 17.9304 29.0059 17.6116 29.2073 17.2197C29.2714 17.0923 29.5829 16.7825 29.6561 16.7278C30.4896 16.2539 31.4513 16.4089 32.3397 16.7642C33.1641 17.1013 33.7869 17.7209 34.6844 18.5955C35.6003 19.6523 35.7651 19.9441 36.2872 20.7366C36.6995 21.3562 37.075 21.9939 37.3314 22.7229C37.4871 23.1785 37.2856 23.552 36.7452 23.7798Z" fill-rule="nonzero" fill="#4D6BFE"/>
+</svg>

ai-provider/model-runtime/model-providers/deepseek/assets/icon_s_en.svg

@@ -0,0 +1,3 @@
+<svg width="50" height="50" viewBox="0 0 50 50" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" xml:space="preserve" xmlns:serif="http://www.serif.com/" style="fill-rule:evenodd;clip-rule:evenodd;stroke-linejoin:round;stroke-miterlimit:2;">
+    <path id="path" d="M55.613,3.471C55.018,3.179 54.761,3.735 54.413,4.018C54.294,4.109 54.193,4.227 54.092,4.337C53.222,5.266 52.206,5.876 50.878,5.803C48.936,5.694 47.278,6.305 45.813,7.79C45.501,5.959 44.466,4.865 42.891,4.164C42.067,3.799 41.233,3.435 40.656,2.642C40.253,2.077 40.143,1.448 39.942,0.829C39.814,0.455 39.685,0.073 39.255,0.009C38.788,-0.064 38.605,0.328 38.421,0.656C37.689,1.995 37.405,3.471 37.432,4.965C37.496,8.327 38.916,11.006 41.737,12.91C42.058,13.129 42.14,13.347 42.039,13.666C41.847,14.323 41.618,14.96 41.416,15.616C41.288,16.035 41.096,16.127 40.647,15.944C39.099,15.297 37.762,14.341 36.58,13.184C34.575,11.243 32.761,9.102 30.499,7.425C29.968,7.033 29.436,6.669 28.887,6.323C26.579,4.082 29.189,2.241 29.794,2.022C30.425,1.795 30.013,1.011 27.971,1.02C25.928,1.029 24.06,1.713 21.679,2.624C21.331,2.761 20.964,2.861 20.589,2.943C18.427,2.533 16.183,2.441 13.838,2.706C9.424,3.198 5.898,5.284 3.306,8.847C0.191,13.129 -0.541,17.994 0.356,23.069C1.3,28.417 4.029,32.845 8.224,36.308C12.575,39.897 17.584,41.656 23.3,41.319C26.771,41.118 30.636,40.654 34.996,36.964C36.095,37.51 37.249,37.729 39.163,37.893C40.638,38.03 42.058,37.82 43.157,37.592C44.878,37.228 44.759,35.633 44.137,35.342C39.09,32.991 40.198,33.948 39.191,33.173C41.755,30.139 45.62,26.987 47.132,16.773C47.251,15.962 47.15,15.452 47.132,14.796C47.122,14.395 47.214,14.241 47.672,14.195C48.936,14.049 50.163,13.703 51.29,13.083C54.56,11.298 55.878,8.364 56.19,4.847C56.236,4.309 56.181,3.753 55.613,3.471ZM27.119,35.123C22.228,31.278 19.856,30.012 18.876,30.066C17.96,30.121 18.125,31.169 18.326,31.852C18.537,32.526 18.812,32.991 19.196,33.583C19.462,33.975 19.645,34.558 18.931,34.996C17.356,35.971 14.617,34.667 14.489,34.604C11.301,32.727 8.636,30.249 6.758,26.859C4.945,23.597 3.892,20.099 3.718,16.363C3.672,15.461 3.938,15.142 4.835,14.979C6.017,14.76 7.235,14.714 8.416,14.887C13.408,15.616 17.658,17.848 21.221,21.384C23.254,23.397 24.793,25.802 26.377,28.153C28.062,30.649 29.876,33.028 32.184,34.977C32.999,35.661 33.649,36.18 34.272,36.563C32.395,36.772 29.262,36.818 27.119,35.123ZM29.464,20.044C29.464,19.643 29.784,19.325 30.187,19.325C30.279,19.325 30.361,19.343 30.435,19.37C30.535,19.407 30.627,19.461 30.7,19.543C30.828,19.671 30.902,19.853 30.902,20.044C30.902,20.445 30.581,20.764 30.178,20.764C29.775,20.764 29.464,20.445 29.464,20.044ZM36.745,23.78C36.278,23.971 35.811,24.135 35.362,24.153C34.666,24.19 33.906,23.907 33.494,23.561C32.853,23.023 32.395,22.723 32.202,21.784C32.12,21.384 32.166,20.764 32.239,20.409C32.404,19.643 32.221,19.151 31.68,18.705C31.241,18.34 30.682,18.24 30.068,18.24C29.839,18.24 29.629,18.14 29.473,18.058C29.216,17.93 29.006,17.612 29.207,17.22C29.271,17.092 29.583,16.783 29.656,16.728C30.49,16.254 31.451,16.409 32.34,16.764C33.164,17.101 33.787,17.721 34.684,18.596C35.6,19.652 35.765,19.944 36.287,20.737C36.7,21.356 37.075,21.994 37.331,22.723C37.487,23.179 37.286,23.552 36.745,23.78Z" style="fill:rgb(77,107,254);fill-rule:nonzero;"/>
+</svg>

ai-provider/model-runtime/model-providers/deepseek/deepseek.yaml

@@ -0,0 +1,33 @@
+provider: deepseek
+label:
+  en_US: deepseek
+  zh_Hans: 深度求索
+description:
+  en_US: Models provided by deepseek, such as deepseek-chat、deepseek-coder.
+  zh_Hans: 深度求索提供的模型，例如 deepseek-chat、deepseek-coder 。
+icon_small:
+  en_US: icon_s_en.svg
+icon_large:
+  en_US: icon_l_en.svg
+background: "#c0cdff"
+help:
+  title:
+    en_US: Get your API Key from deepseek
+    zh_Hans: 从深度求索获取 API Key
+  url:
+    en_US: https://platform.deepseek.com/api_keys
+supported_model_types:
+  - llm
+configurate_methods:
+  - predefined-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
+address: https://api.deepseek.com

ai-provider/model-runtime/model-providers/deepseek/llm/deepseek-chat.yaml

@@ -0,0 +1,78 @@
+model: deepseek-chat
+label:
+  zh_Hans: deepseek-chat
+  en_US: deepseek-chat
+model_type: llm
+features:
+  - agent-thought
+  - multi-tool-call
+  - stream-tool-call
+model_properties:
+  mode: chat
+  context_size: 128000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    type: float
+    default: 1
+    min: 0.0
+    max: 2.0
+    help:
+      zh_Hans: 控制生成结果的多样性和随机性。数值越小，越严谨；数值越大，越发散。
+      en_US: Control the diversity and randomness of generated results. The smaller the value, the more rigorous it is; the larger the value, the more divergent it is.
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 4096
+    min: 1
+    max: 8192
+    help:
+      zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。
+      en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
+  - name: top_p
+    use_template: top_p
+    type: float
+    default: 1
+    min: 0.01
+    max: 1.00
+    help:
+      zh_Hans: 控制生成结果的随机性。数值越小，随机性越弱；数值越大，随机性越强。一般而言，top_p 和 temperature 两个参数选择一个进行调整即可。
+      en_US: Control the randomness of generated results. The smaller the value, the weaker the randomness; the larger the value, the stronger the randomness. Generally speaking, you can adjust one of the two parameters top_p and temperature.
+  - name: logprobs
+    help:
+      zh_Hans: 是否返回所输出 token 的对数概率。如果为 true，则在 message 的 content 中返回每个输出 token 的对数概率。
+      en_US: Whether to return the log probability of the output token. If true, returns the log probability of each output token in the content of message .
+    type: boolean
+  - name: top_logprobs
+    type: int
+    default: 0
+    min: 0
+    max: 20
+    help:
+      zh_Hans: 一个介于 0 到 20 之间的整数 N，指定每个输出位置返回输出概率 top N 的 token，且返回这些 token 的对数概率。指定此参数时，logprobs 必须为 true。
+      en_US: An integer N between 0 and 20, specifying that each output position returns the top N tokens with output probability, and returns the logarithmic probability of these tokens. When specifying this parameter, logprobs must be true.
+  - name: frequency_penalty
+    use_template: frequency_penalty
+    default: 0
+    min: -2.0
+    max: 2.0
+    help:
+      zh_Hans: 介于 -2.0 和 2.0 之间的数字。如果该值为正，那么新 token 会根据其在已有文本中的出现频率受到相应的惩罚，降低模型重复相同内容的可能性。
+      en_US: A number between -2.0 and 2.0. If the value is positive, new tokens are penalized based on their frequency of occurrence in existing text, reducing the likelihood that the model will repeat the same content.
+  - name: response_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
+pricing:
+  input: '1'
+  output: '2'
+  unit: '0.000001'
+  currency: RMB

ai-provider/model-runtime/model-providers/deepseek/llm/deepseek-coder.yaml

@@ -0,0 +1,28 @@
+model: deepseek-coder
+label:
+  zh_Hans: deepseek-coder
+  en_US: deepseek-coder
+model_type: llm
+features:
+  - agent-thought
+  - multi-tool-call
+  - stream-tool-call
+model_properties:
+  mode: chat
+  context_size: 128000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    min: 0
+    max: 1
+    default: 0.5
+  - name: top_p
+    use_template: top_p
+    min: 0
+    max: 1
+    default: 1
+  - name: max_tokens
+    use_template: max_tokens
+    min: 1
+    max: 4096
+    default: 1024

ai-provider/model-runtime/model-providers/fakegpt/assets/icon_l_en.svg

@@ -0,0 +1,23 @@
+<?xml version="1.0" encoding="utf-8"?>
+
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<!-- Uploaded to: SVG Repo, www.svgrepo.com, Generator: SVG Repo Mixer Tools -->
+<svg version="1.1" id="_x32_" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"
+     width="800px" height="800px" viewBox="0 0 512 512"  xml:space="preserve">
+<style type="text/css">
+<![CDATA[
+	.st0{fill:#000000;}
+]]>
+</style>
+    <g>
+	<path class="st0" d="M485.016,220.691c12.422-8.422,22.188-57.266,7.797-87.016c-26.859,28.125-80.109,49.859-142,72.922
+		c-64.656,24.078-71.531,41.859-94.813,42.172c-23.297-0.313-30.156-18.094-94.813-42.172c-61.891-23.063-115.141-44.797-142-72.922
+		c-14.406,29.75-4.625,78.594,7.781,87.016C13.484,214.332,0,210.051,0,210.051s3.813,68.172,33.25,106.563
+		c24.953,32.547,86.984,72.906,145.828,58.828c62.219-14.875,62.344-41.406,76.922-41.266c14.563-0.141,14.688,26.391,76.906,41.266
+		c58.844,14.078,120.875-26.281,145.844-58.828C508.156,278.223,512,210.051,512,210.051S498.5,214.332,485.016,220.691z
+		 M131.438,318.848c-25.109-11.641-46.063-37.422-43.188-73.891c12.813,5.078,48.844,9.406,69.094,17.281
+		c23,8.953,46.031,23.984,48.922,41.25C205.313,317.879,170.75,337.066,131.438,318.848z M380.563,318.848
+		c-39.344,18.219-73.875-0.969-74.828-15.359c2.891-17.266,25.891-32.297,48.922-41.25c20.25-7.875,56.281-12.203,69.094-17.281
+		C426.625,281.426,405.656,307.207,380.563,318.848z"/>
+</g>
+</svg>

ai-provider/model-runtime/model-providers/fakegpt/assets/icon_s_en.svg

@@ -0,0 +1,23 @@
+<?xml version="1.0" encoding="utf-8"?>
+
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<!-- Uploaded to: SVG Repo, www.svgrepo.com, Generator: SVG Repo Mixer Tools -->
+<svg version="1.1" id="_x32_" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"
+     width="800px" height="800px" viewBox="0 0 512 512"  xml:space="preserve">
+<style type="text/css">
+<![CDATA[
+	.st0{fill:#000000;}
+]]>
+</style>
+    <g>
+	<path class="st0" d="M485.016,220.691c12.422-8.422,22.188-57.266,7.797-87.016c-26.859,28.125-80.109,49.859-142,72.922
+		c-64.656,24.078-71.531,41.859-94.813,42.172c-23.297-0.313-30.156-18.094-94.813-42.172c-61.891-23.063-115.141-44.797-142-72.922
+		c-14.406,29.75-4.625,78.594,7.781,87.016C13.484,214.332,0,210.051,0,210.051s3.813,68.172,33.25,106.563
+		c24.953,32.547,86.984,72.906,145.828,58.828c62.219-14.875,62.344-41.406,76.922-41.266c14.563-0.141,14.688,26.391,76.906,41.266
+		c58.844,14.078,120.875-26.281,145.844-58.828C508.156,278.223,512,210.051,512,210.051S498.5,214.332,485.016,220.691z
+		 M131.438,318.848c-25.109-11.641-46.063-37.422-43.188-73.891c12.813,5.078,48.844,9.406,69.094,17.281
+		c23,8.953,46.031,23.984,48.922,41.25C205.313,317.879,170.75,337.066,131.438,318.848z M380.563,318.848
+		c-39.344,18.219-73.875-0.969-74.828-15.359c2.891-17.266,25.891-32.297,48.922-41.25c20.25-7.875,56.281-12.203,69.094-17.281
+		C426.625,281.426,405.656,307.207,380.563,318.848z"/>
+</g>
+</svg>

ai-provider/model-runtime/model-providers/fakegpt/fakegpt.yaml

@@ -0,0 +1,30 @@
+provider: fakegpt
+label:
+  en_US: FakeGPT
+description:
+  en_US: FakeGPT is a fake model provider that does not actually connect to any model service. It is useful for testing and development purposes.
+icon_small:
+  en_US: icon_s_en.svg
+icon_large:
+  en_US: icon_l_en.svg
+background: "#FCFDFF"
+help:
+  title:
+    en_US: Get your Access Details from Google
+  url:
+    en_US: https://apipark.com
+supported_model_types:
+  - llm
+  - text-embedding
+configurate_methods:
+  - predefined-model
+provider_credential_schema:
+  credential_form_schemas:
+    - variable: apikey
+      label:
+        en_US: API Key
+      type: secret-input
+      required: true
+      placeholder:
+        en_US: Enter your API key
+address: https://apipark.com

ai-provider/model-runtime/model-providers/fakegpt/llm/fakegpt-1.0.yaml

@@ -0,0 +1,51 @@
+model: fakegpt-1.0
+label:
+  en_US: FakeGPT 1.0
+model_type: llm
+features:
+  - agent-thought
+  - vision
+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。
+      en_US: The maximum number of tokens to generate before stopping.
+  - 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，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, 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.
+