* add grok coder free model to cline provider (#5808)
* add free grok-coder-free model to cline provider
* add changeset
* fix typo
* checkpoints class created
* Added saveCheckpoint to Checkpoint class
* Rebased and updated for new ClineMessages
* Moved things around, started on saveCheckpoint
* implemented handler for checking and initializing the checkpointTracker if not already done
* Moved restoreCheckpoint and handleSucessfullRestore to checkpoints class
* Moved presentMultiDiff, not yet connected
* Migrated doesLatestTaskCompletionHaveNewChanges and compelted migration on presentMultifileDiff
* Better init handling
* moved fileContextTracker to new checkpoints class
* Checkpoints state management
* refactoring and cleanup in saveCheckpoint, init handler
* More saveCheckpoint refactoring
* Added sayTs return to say function for better async clineMessages updates
* Refactor checkpoint system with timestamp tracking and dependency separation
* More refactoring
* Friendship ended with checkpointTracker, checkpointManager is new best friend
* Better error handling
* checkpointTrackerErrorMessage > checkpointManagerErrorMessage
* Addressed possible race condition with message(Ts)
* Better error handling and 15s timeout changes
* Remove checkpoint delegation methods and call checkpoint manager directly
* updating checkpoints protos
* cleanup
* Restored autoApprove entry to task class
* cleanup
* cleanup
* Post-rebase fixes
* Migrated timeout and state changes from PR #5015
* Extract toolExecutor callback functions to private methods for readability
* Updated info/error messages to use HostProvider
* post rebase fixes
* Compare/diff button fix
* Fix lint errors
* Update webview-ui/src/components/chat/task-header/TaskHeader.tsx
Co-authored-by: Bee <68532117+abeatrix@users.noreply.github.com>
* Update src/integrations/checkpoints/index.ts
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Fixed bad merge, updated focus change for compatability with new say()
* Fixed error message propagation issue
---------
Co-authored-by: pashpashpash <nik@cline.bot>
Co-authored-by: Kevin Bond <kevin@Mac.hsd1.ca.comcast.net>
Co-authored-by: Kevin Bond <kevin@Kevins-MacBook-Pro.local>
Co-authored-by: Bee <68532117+abeatrix@users.noreply.github.com>
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
- Recognize GPT-5 IDs (including openai/gpt-5) in model family detection and variants
- Add GPT-5 (OpenAI) to integration matrix and unit tests
- Update snapshot test instructions to use npm run test:unit -- --update-snapshots
- Fix PromptBuilder: don’t early-return on missing params; init to [] to keep output consistent
- Tidy test diff formatting (braces, explicit returns)
- Polish load_mcp_documentation tool description
* Add 200k context window variant for Claude Sonnet 4 to OpenRouter and Cline providers
* v3.26.7 Release Notes
* Fix grok-code-fast-1 info
* v3.27.0 Release Notes
* Add new kimi model to groq and moonshot providers
* v3.27.1 Release Notes
* adding new kimi model to groq and moonshot providers
* added fireworks provider too
* fixing fireworks test
---------
Co-authored-by: Saoud Rizwan <7799382+saoudrizwan@users.noreply.github.com>
* Fixed issue where slash command feature would remove first word after the command name
* Removed slashCommandsQueryRef
* Add fix for mentions as well
* Updated mentions test
---------
Co-authored-by: Kevin Bond <kevin@Kevins-MacBook-Pro.local>
Some environments do not return a value for the vscode machine ID.
For these cases we are generating a UUID. But the UUID was not being stored, so a new one was being created everytime the extension started.
Start storing the generated ID in the global state.
I am changing the name of the key to be more descriptive, because we only want to store the generated ID. If there is an actual machine ID, we should just use that and not store it. The old key name was only ever been read, it was never written, so this will have no affect on existing users.
* fix: only focus chat input when in chat view
- Only focus chat input when chat view is visible, not when hidden (in other view)
- Wrap onDone callback in arrow function for consistency
- Replace inline styles with Tailwind classes for button container
* update gap value
Remove process.env.CI check and rely only on IS_DEV flag to determine whether to use development or production PostHog configuration.
This is because process.env.CI is always true during the publish GitHub workflow.
* Add telemetry tracking for terminal hang detection and user interventions
- Add terminal hang detection with configurable timeouts for buffer stuck, stream timeout, and completion waiting stages
- Track user interventions when clicking "Process while Running" button
- Add telemetry for terminal output failures with specific failure reasons
- Implement comprehensive monitoring of terminal process lifecycle events
- Add metrics for shell integration usage and terminal operation performance
* Remove Shortcut of Cline from its title
* Remove Shortcut of Cline from its title
* Remove Shortcut of Cline from its title
* docs: Update Claude Code documentation to include Pro plans alongside Max plans
* Add JetBrains installation documentation
- Create comprehensive installation guide for JetBrains IDEs
- Include both marketplace and manual installation methods
- Document supported IDEs and key differences from VSCode
- Add alpha status note and terminal integration limitations
- Update docs.json navigation to include new page
* Add images to JetBrains installation documentation
- Add demo GIF showing Cline in action in JetBrains IDE
- Add screenshot of JetBrains marketplace download page
- Add screenshot of Install Plugin from Disk dialog
- Add screenshot of file selection dialog with zip file
- Complete visual walkthrough of installation process
* Update JetBrains demo to high-quality GIF
- Replace jetbrains-demo.gif with jetbrains-demo-hifi.gif
- Improved visual quality for better user experience
* Add JetBrains settings dialog screenshot
- Add screenshot showing the main settings dialog
- Provides visual guidance for accessing IDE settings
- Complete visual walkthrough now includes 5 screenshots
* Add JetBrains logo and finalize documentation
- Add JetBrains logo at top of page with proper styling
- Update content with user revisions (BYOK note, streamlined structure)
- Complete visual installation walkthrough with 5 images
- Ready for PR review
* Update early access messaging
- Change from 'You're getting early access' to 'Cline is in early access'
- More professional and product-focused messaging
- Maintains excitement while being clearer about the product status
* Update installation link for Cline plugin
---------
Co-authored-by: pashpashpash <nik@cline.bot>
* docs: Update Claude Code documentation to include Pro plans alongside Max plans
* Add JetBrains installation documentation
- Create comprehensive installation guide for JetBrains IDEs
- Include both marketplace and manual installation methods
- Document supported IDEs and key differences from VSCode
- Add alpha status note and terminal integration limitations
- Update docs.json navigation to include new page
* Add images to JetBrains installation documentation
- Add demo GIF showing Cline in action in JetBrains IDE
- Add screenshot of JetBrains marketplace download page
- Add screenshot of Install Plugin from Disk dialog
- Add screenshot of file selection dialog with zip file
- Complete visual walkthrough of installation process
* Update JetBrains demo to high-quality GIF
- Replace jetbrains-demo.gif with jetbrains-demo-hifi.gif
- Improved visual quality for better user experience
* Add JetBrains settings dialog screenshot
- Add screenshot showing the main settings dialog
- Provides visual guidance for accessing IDE settings
- Complete visual walkthrough now includes 5 screenshots
* Add JetBrains logo and finalize documentation
- Add JetBrains logo at top of page with proper styling
- Update content with user revisions (BYOK note, streamlined structure)
- Complete visual installation walkthrough with 5 images
- Ready for PR review
- Add "retry" action type to ButtonActionType
- Update api_req_failed button config to use retry action with disabled sending
- Implement retry handler in useMessageHandlers to send simple approval and clear input state
Add properties to the telemetry events for the host environment name and version.
Add a .create() function to the TelemetryService because we can't use async in the constructor. (Getting the host platform version is async).
getMachineId was not returning the correct value and a new distint ID was getting generated every time the extension started.
Add tests and logging for distinctId.ts
* Add TASK_PROGRESS_PARAMETER to various tools and update descriptions
- Introduced TASK_PROGRESS_PARAMETER to enhance task tracking across multiple tools.
- Updated tool descriptions for clarity and consistency, including detailed instructions and usage examples.
- Adjusted existing parameters to improve user guidance and ensure proper tool functionality.
* update snapshots
* do not remove new lines within section around divider
---------
Co-authored-by: abeatrix <beatrix@cline.bot>
* Fix write_to_file tool diff streaming
* Fix discrepencies with original tool execution logic
* Fix attempt completion command leading to 'ask promise was ignored' error
* Fix input not being cleared when hitting approve button
* Pass all options to the handlers
* Do not pass all options
* Have onRetryAttempt as a common option
* Update the Gemini CLI
* Throw a RetriableError and extract retry delays from the error responses
* Add changeset
* Throw a RetriableError if extracting the delay fails
* Improve parseRetryDelay
* Add fallback
* Refactor services architecture with provider pattern and factory classes
- Extract telemetry, error handling, and feature flags into separate service modules
- Implement provider pattern with factory classes for better abstraction
- Move PostHog-specific implementations to dedicated provider classes
- Add interfaces for telemetry, error, and feature flags providers
- Update imports across codebase to use new service structure
- Add unit tests for telemetry service
* Refactor service providers and centralize distinct ID management
- Move provider interfaces to dedicated providers/ subdirectories
- Extract distinct ID management to shared logging/distinctId module
- Simplify PostHogClientProvider by removing distinct ID parameter
- Update service factories to use centralized distinct ID
- Reorganize test files to __tests__/ directories
- Remove redundant distinct ID handling across services
* merge main
* clean up
* add grok coder free model to cline provider (#5808)
* add free grok-coder-free model to cline provider
* add changeset
* fix typo
* v3.26.6 Release Notes (#5788)
* changeset version bump
* Updating CHANGELOG.md format
* Update CHANGELOG.md for version 3.26.6 with user-friendly descriptions
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: github-actions <github-actions@github.com>
Co-authored-by: pashpashpash <nik@cline.bot>
* Remove top padding from ActionButtons component (#5806)
Eliminate unnecessary top padding in the chat view.
* removing middle out from params to or / cline providers (#5811)
* Dify.ai integration (#5761)
* add focus chain settings to statemanager initialize function (#5798)
* add custom gpt-5 system prompt (#5757)
* gpt-5 system prompt
* add changeset
* Focus chain telemetry tweaks (#5810)
Co-authored-by: Kevin Bond <kevin@Kevins-MacBook-Pro.local>
* Remove eslint-rules test patterns from Mocha spec configuration (#5812)
Update the "spec" array in .mocharc.json to exclude "eslint-rules/__tests__/**/*.test.ts",
as that directory has been removed.
* Increase horizontal margin in AutoApproveBar component (#5813)
Update the mx-[5px] to mx-[15px] in the div's className to adjust horizontal spacing for improved layout alignment.
* fix: remove hardcoded Ollama host from options (#5816)
* fix: remove hardcoded Ollama host from options
Updates the Ollama handler to remove the hardcoded "http://localhost:11434" as the `ollamaBaseUrl` fallback option for the host to allow the Ollama SDK to handle the default endpoint configured on users' machine.
Reason: Ollama allows cross-origin requests from 127.0.0.1 and 0.0.0.0 by default. However, when we use localhost, the browser would resolve it through DNS, which can result in different IP addresses.
Docs: https://github.com/ollama/ollama/blob/main/docs/faq.md#how-can-i-expose-ollama-on-my-network
* add changeset
* deep-planning prompt PowerShell (#5699)
* Windows/Powershell specific deep planning prompt changes
* Prompt adjustments
---------
Co-authored-by: Kevin Bond <kevin@Kevins-MacBook-Pro.local>
* Changes to condenseToolResponse & summarizeTask prompting (#5817)
* Condense & deep planning prompt adjustments
* Removed ps prompting ready for PR
* rebase
* Fixed typo on one word
---------
Co-authored-by: Kevin Bond <kevin@Kevins-MacBook-Pro.local>
* rename CacheService to StateManager (#5681)
* rename CacheService to StateManager
* fix types
* infer state key types from existing interfaces (#5815)
* fix: AutoApproveModal positioning and scrolling behavior (#5819)
* fix: AutoApproveModal positioning and scrolling behavior
- Add dynamic positioning calculation to prevent modal overflow
- Implement proper flex layout with scrollable content container
- Ensure minimum usable height and top margin constraints
- Fix modal positioning when button is near viewport edges
* Add changeset
* clean up
* template-based system prompt (#5731)
* Refactor system prompt architecture with new template-based system
- Move existing system prompt files to legacy directory
- Implement new modular system with PromptBuilder, PromptRegistry, and TemplateEngine
- Add component-based prompt structure with reusable parts (capabilities, rules, tool_use, etc.)
- Create variant-specific templates for generic and next-gen models
- Add comprehensive test suite with snapshots for different model configurations
- Introduce template engine with placeholder support for dynamic prompt generation
* Refactor system prompt architecture with modular tool definitions
- Extract tool specifications into dedicated modules under tools/
- Add ClineToolSet class for managing tool variants by model family
- Restructure prompt components with centralized index exports
- Update prompt builder and registry to support new tool architecture
- Reorganize shared utilities and type definitions
- Update all test snapshots to reflect new prompt structure
* Update snapshots
* reorg
* Update template format
* clean up
* typos
* focus chain section
* fix task progress in attempt_completion
* Implement tool retrieval with fallback options in PromptBuilder
- Added `getToolByNameWithFallback` and `getToolsForVariantWithFallback` methods to `ClineToolSet` for improved tool resolution.
- Updated `getToolsPrompts` in `PromptBuilder` to utilize these new methods, allowing for better handling of tool requests with fallback to generic tools.
- Enhanced sorting and filtering of tools based on context requirements and requested order.
* update fild structure
* clean up
* fix static test string
* Update snapshot names
* Update unit test
* Remove unused placeholders and update docs
* Update README on how to add new tool
* Remove task_progress reference from attempt_completion tool description when focus chain is disabled
* Upgrade posthog-node to v5.8.0 and add exception filtering
- Update posthog-node from v4.8.1 to v5.8.0
- Add EventMessage import for type safety
- Implement posthogEventFilter to only capture exceptions from Cline extension
- Filter exceptions by checking for "cline" in error messages or "saoudrizwan" in stack frames
* Use env var keys
- Add PostHogClientConfig to ErrorProviderFactory with proper validation
- Update PostHogErrorProvider to use dedicated client instead of shared one
- Add API key validation in PostHogFeatureFlagsProvider before client creation
- Enhance error handling with fallback to NoOpErrorProvider instead of throwing
- Standardize configuration passing across telemetry, error, and feature flag services
* Upadte filter
* update filter
* update imports
* use secret
* disable enableExceptionAutocapture
* removes vscode.env.machineId
* initializeDistinctId
* use get trap as workaround
* on exit
---------
Co-authored-by: pashpashpash <nik@cline.bot>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: github-actions <github-actions@github.com>
Co-authored-by: Toshii <94262432+0xToshii@users.noreply.github.com>
Co-authored-by: Yunus Emre AYHAN <ayhanyunusemre@gmail.com>
Co-authored-by: celestial-vault <58194240+celestial-vault@users.noreply.github.com>
Co-authored-by: canvrno <46584286+canvrno@users.noreply.github.com>
Co-authored-by: Kevin Bond <kevin@Kevins-MacBook-Pro.local>
* Adding frequency penalty for gemini models
* Adding frequency penalty for gemini models
* Adding frequency penalty for gemini models
* Adding frequency penalty for gemini models
* Adding frequency penalty for gemini models
Cline-core is setting some of these values in the models proto to the javascript Number.MAX_SAFE_VALUE, which won't fit in int32, so these protobuf messages fail to serialize to and can't be transported.
Just change all the int32s in this file to int64 beceause this is the second time this same issue has occured.
Fixes:
```
2025-08-28 16:30:03,824 [ 3479] WARN - bot.cline.services.ProtoBusProxyService - Stream cline.ModelsService.subscribeToOpenRouterModels encountered error
io.grpc.StatusException: INTERNAL: invalid int32: 9007199254740991
at io.grpc.Status.asException(Status.java:548)
at io.grpc.kotlin.ClientCalls$rpcImpl$1$1$1.onClose(ClientCalls.kt:300)
at io.grpc.internal.ClientCallImpl.closeObserver(ClientCallImpl.java:564)
at io.grpc.internal.ClientCallImpl.access$100(ClientCallImpl.java:72)
at io.grpc.internal.ClientCallImpl$ClientStreamListenerImpl$1StreamClosed.runInternal(ClientCallImpl.java:729)
at io.grpc.internal.ClientCallImpl$ClientStreamListenerImpl$1StreamClosed.runInContext(ClientCallImpl.java:710)
at io.grpc.internal.ContextRunnable.run(ContextRunnable.java:37)
at io.grpc.internal.SerializingExecutor.run(SerializingExecutor.java:133)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1144)
at java.base/java.util.concurrent.ThreadPoolExecutor$Wor
```
* fix: Harden PromptRegistry with health checks and generic fallback
- Perform registry health check after loading (validate GENERIC, log counts/warnings)
- Always try GENERIC when family-specific variant is missing
- Enhance error diagnostics with available variants and registry state
- Ensure GENERIC variant exists; create minimal fallback if loading fails
- Minor test style cleanup and variants index update to support reliability
* simpilfy
* variants
* Fix import
* type safe
* remove lazy loading
* load and set variants
* fix import location
* fix: sap provider - show models when resource group field is empty
* fix: sap provider - show models when resource group field is empty
* fix: sap provider - show models when resource group field is empty
* Update snapshots for system prompt tests
- Add detailed README.md explaining integration test workflow, snapshot testing, and troubleshooting
- Unit tests should fail when snapshots are mismatched
- Update all test snapshots across different model configurations (Anthropic Claude, OpenAI GPT)
- Refresh section title comparison data for prompt structure validation
- Improve test documentation with clear examples and failure handling guidance
* make old prompts static
* Fix old vs new comparasion mismatch
* Remove action buttons from showing for followup and plan_mode_respond
Set primaryText, secondaryText, and primaryAction to undefined for followup and plan_mode_respond button configurations to disable default approve/reject behavior.
* add changeset
* add grok coder free model to cline provider (#5808)
* add free grok-coder-free model to cline provider
* add changeset
* fix typo
* v3.26.6 Release Notes (#5788)
* changeset version bump
* Updating CHANGELOG.md format
* Update CHANGELOG.md for version 3.26.6 with user-friendly descriptions
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: github-actions <github-actions@github.com>
Co-authored-by: pashpashpash <nik@cline.bot>
* Remove top padding from ActionButtons component (#5806)
Eliminate unnecessary top padding in the chat view.
* removing middle out from params to or / cline providers (#5811)
* Dify.ai integration (#5761)
* add focus chain settings to statemanager initialize function (#5798)
* add custom gpt-5 system prompt (#5757)
* gpt-5 system prompt
* add changeset
* Focus chain telemetry tweaks (#5810)
Co-authored-by: Kevin Bond <kevin@Kevins-MacBook-Pro.local>
* Remove eslint-rules test patterns from Mocha spec configuration (#5812)
Update the "spec" array in .mocharc.json to exclude "eslint-rules/__tests__/**/*.test.ts",
as that directory has been removed.
* Increase horizontal margin in AutoApproveBar component (#5813)
Update the mx-[5px] to mx-[15px] in the div's className to adjust horizontal spacing for improved layout alignment.
* fix: remove hardcoded Ollama host from options (#5816)
* fix: remove hardcoded Ollama host from options
Updates the Ollama handler to remove the hardcoded "http://localhost:11434" as the `ollamaBaseUrl` fallback option for the host to allow the Ollama SDK to handle the default endpoint configured on users' machine.
Reason: Ollama allows cross-origin requests from 127.0.0.1 and 0.0.0.0 by default. However, when we use localhost, the browser would resolve it through DNS, which can result in different IP addresses.
Docs: https://github.com/ollama/ollama/blob/main/docs/faq.md#how-can-i-expose-ollama-on-my-network
* add changeset
* deep-planning prompt PowerShell (#5699)
* Windows/Powershell specific deep planning prompt changes
* Prompt adjustments
---------
Co-authored-by: Kevin Bond <kevin@Kevins-MacBook-Pro.local>
* Changes to condenseToolResponse & summarizeTask prompting (#5817)
* Condense & deep planning prompt adjustments
* Removed ps prompting ready for PR
* rebase
* Fixed typo on one word
---------
Co-authored-by: Kevin Bond <kevin@Kevins-MacBook-Pro.local>
* rename CacheService to StateManager (#5681)
* rename CacheService to StateManager
* fix types
* infer state key types from existing interfaces (#5815)
* fix: AutoApproveModal positioning and scrolling behavior (#5819)
* fix: AutoApproveModal positioning and scrolling behavior
- Add dynamic positioning calculation to prevent modal overflow
- Implement proper flex layout with scrollable content container
- Ensure minimum usable height and top margin constraints
- Fix modal positioning when button is near viewport edges
* Add changeset
* clean up
* template-based system prompt (#5731)
* Refactor system prompt architecture with new template-based system
- Move existing system prompt files to legacy directory
- Implement new modular system with PromptBuilder, PromptRegistry, and TemplateEngine
- Add component-based prompt structure with reusable parts (capabilities, rules, tool_use, etc.)
- Create variant-specific templates for generic and next-gen models
- Add comprehensive test suite with snapshots for different model configurations
- Introduce template engine with placeholder support for dynamic prompt generation
* Refactor system prompt architecture with modular tool definitions
- Extract tool specifications into dedicated modules under tools/
- Add ClineToolSet class for managing tool variants by model family
- Restructure prompt components with centralized index exports
- Update prompt builder and registry to support new tool architecture
- Reorganize shared utilities and type definitions
- Update all test snapshots to reflect new prompt structure
* Update snapshots
* reorg
* Update template format
* clean up
* typos
* focus chain section
* fix task progress in attempt_completion
* Implement tool retrieval with fallback options in PromptBuilder
- Added `getToolByNameWithFallback` and `getToolsForVariantWithFallback` methods to `ClineToolSet` for improved tool resolution.
- Updated `getToolsPrompts` in `PromptBuilder` to utilize these new methods, allowing for better handling of tool requests with fallback to generic tools.
- Enhanced sorting and filtering of tools based on context requirements and requested order.
* update fild structure
* clean up
* fix static test string
* Update snapshot names
* Update unit test
* Remove unused placeholders and update docs
* Update README on how to add new tool
* Remove task_progress reference from attempt_completion tool description when focus chain is disabled
* consolidate field declarations for globalstate, workspacestate, and secret keys
* remove old cacheservice file
* read_file tool call change for all models (#5830)
* feat: refactor UseCustomPrompt into reusable component, add to Ollama (#5818)
* feat: refactor UseCustomPrompt into reusable component, add to Ollama
Refactor custom prompt checkbox functionality from LMStudioProvider and OllamaProvider into a shared UseCustomPrompt component to reduce code duplication and improve maintainability.
* Add changeset
* replace key with providerId
* clean up
* Rename UseCustomPrompt to UseCustomPromptCheckbox and update imports
Rename UseCustomPrompt.tsx to UseCustomPromptCheckbox.tsx for better clarity
and update import paths in LMStudioProvider and OllamaProvider components.
* use StateManager in auxilary access of cline state instead of using vscode api directly
* fix default formatter that was erroneously changed
* feat: sap provider - support orchestration mode (#5541)
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap ai core - add orchestration
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - support orchestration modee
* feat: sap provider - support orchestration modee
* feat: sap provider - support orchestration modee
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: support doorway mapping semantic model [CCSTAHEL-2197]
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* Update docs/provider-config/sap-aicore.mdx
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* feat: sap provider - support orchestration model
* feat: support doorway mapping semantic model [CCSTAHEL-2197]
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* fix converse api image data to base64 string.
Signed-off-by: Lize Cai <lize.cai@sap.com>
---------
Signed-off-by: Lize Cai <lize.cai@sap.com>
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
Co-authored-by: Lize Cai <lize.cai@sap.com>
* add in new sap field from main merge in the right place
---------
Signed-off-by: Lize Cai <lize.cai@sap.com>
Co-authored-by: pashpashpash <nik@cline.bot>
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
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Co-authored-by: Yunus Emre AYHAN <ayhanyunusemre@gmail.com>
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Co-authored-by: Lize Cai <lize.cai@sap.com>
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap ai core - add orchestration
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - support orchestration modee
* feat: sap provider - support orchestration modee
* feat: sap provider - support orchestration modee
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: support doorway mapping semantic model [CCSTAHEL-2197]
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* Update docs/provider-config/sap-aicore.mdx
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* feat: sap provider - support orchestration model
* feat: support doorway mapping semantic model [CCSTAHEL-2197]
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* feat: sap provider - support orchestration model
* fix converse api image data to base64 string.
Signed-off-by: Lize Cai <lize.cai@sap.com>
---------
Signed-off-by: Lize Cai <lize.cai@sap.com>
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
Co-authored-by: Lize Cai <lize.cai@sap.com>
* feat: refactor UseCustomPrompt into reusable component, add to Ollama
Refactor custom prompt checkbox functionality from LMStudioProvider and OllamaProvider into a shared UseCustomPrompt component to reduce code duplication and improve maintainability.
* Add changeset
* replace key with providerId
* clean up
* Rename UseCustomPrompt to UseCustomPromptCheckbox and update imports
Rename UseCustomPrompt.tsx to UseCustomPromptCheckbox.tsx for better clarity
and update import paths in LMStudioProvider and OllamaProvider components.
* Refactor system prompt architecture with new template-based system
- Move existing system prompt files to legacy directory
- Implement new modular system with PromptBuilder, PromptRegistry, and TemplateEngine
- Add component-based prompt structure with reusable parts (capabilities, rules, tool_use, etc.)
- Create variant-specific templates for generic and next-gen models
- Add comprehensive test suite with snapshots for different model configurations
- Introduce template engine with placeholder support for dynamic prompt generation
* Refactor system prompt architecture with modular tool definitions
- Extract tool specifications into dedicated modules under tools/
- Add ClineToolSet class for managing tool variants by model family
- Restructure prompt components with centralized index exports
- Update prompt builder and registry to support new tool architecture
- Reorganize shared utilities and type definitions
- Update all test snapshots to reflect new prompt structure
* Update snapshots
* reorg
* Update template format
* clean up
* typos
* focus chain section
* fix task progress in attempt_completion
* Implement tool retrieval with fallback options in PromptBuilder
- Added `getToolByNameWithFallback` and `getToolsForVariantWithFallback` methods to `ClineToolSet` for improved tool resolution.
- Updated `getToolsPrompts` in `PromptBuilder` to utilize these new methods, allowing for better handling of tool requests with fallback to generic tools.
- Enhanced sorting and filtering of tools based on context requirements and requested order.
* update fild structure
* clean up
* fix static test string
* Update snapshot names
* Update unit test
* Remove unused placeholders and update docs
* Update README on how to add new tool
* Remove task_progress reference from attempt_completion tool description when focus chain is disabled
* Condense & deep planning prompt adjustments
* Removed ps prompting ready for PR
* rebase
* Fixed typo on one word
---------
Co-authored-by: Kevin Bond <kevin@Kevins-MacBook-Pro.local>
* fix: remove hardcoded Ollama host from options
Updates the Ollama handler to remove the hardcoded "http://localhost:11434" as the `ollamaBaseUrl` fallback option for the host to allow the Ollama SDK to handle the default endpoint configured on users' machine.
Reason: Ollama allows cross-origin requests from 127.0.0.1 and 0.0.0.0 by default. However, when we use localhost, the browser would resolve it through DNS, which can result in different IP addresses.
Docs: https://github.com/ollama/ollama/blob/main/docs/faq.md#how-can-i-expose-ollama-on-my-network
* add changeset
* use css variables for highlight styling and remove theme subscription along with vscode theme to highlight pipeline logic
* changeset
* Remove monaco-vscode-textmate-theme-converter
* Remove unnecessary markdown css
* Remove package-lock.json from version control
* re-add package-lock
---------
Co-authored-by: Saoud Rizwan <7799382+saoudrizwan@users.noreply.github.com>
* Pass all options to the handlers
* Add changeset
* Do not pass all options
* Have onRetryAttempt as a common option
* Do not duplicate the onRetryAttempt definition
* feat: Integrate Qwen Code API with OAuth authentication
- Add Qwen Code API provider with OAuth2 authentication flow
- Implement QwenCodeProvider component for settings UI
- Add qwenCodeOauthPath to CacheService state management
- Update protobuf models with QWEN_CODE provider type
- Fix protobuf enum values (VSCODE_LM changed from 15 to 33)
- Add comprehensive API configuration conversion support
- Update build scripts to use system protoc for Windows compatibility
- Optimize VSIX packaging by excluding reference codebase
- Follow camelCase convention: qwen_code_oauth_path qwenCodeOauthPath
* docs: Add Qwen Code API integration documentation
- Document OAuth2 authentication flow and features
- Highlight enterprise-grade security capabilities
- Include setup instructions for credential management
- Emphasize automatic token refresh and caching features
* cleanup: Clean up build configuration for production release
- Revert protoc path to use grpc-tools instead of exposing system path
- Restore vscode:prepublish script for proper VS Code marketplace publication
- Remove reference codebase exclusion from .vscodeignore for cleaner packaging
* refactor: Remove Windows platform check from build-proto script
- Remove unnecessary isWindows variable and platform-specific logic
- Simplify TS_PROTO_PLUGIN to use standard require.resolve approach
- Improve cross-platform compatibility and code clarity
* restore: Restore Windows platform check in build-proto script
- Add back isWindows platform detection variable
- Restore Windows-specific TS_PROTO_PLUGIN logic using .cmd file
- Maintain cross-platform compatibility for Windows builds
* Update ApiOptions.tsx
* Remove Qwen Code API integration section
* Revert README
* Fix protos order
* Revert change
* Remove validation for qwen code
---------
Co-authored-by: Ara <arafat.da.khan@gmail.com>
Co-authored-by: Saoud Rizwan <7799382+saoudrizwan@users.noreply.github.com>
* remove middle out for gpt5
* refactor: using standard family identifier functions
* fix: making sure to lowercase all model ids
* changeset
---------
Co-authored-by: pashpashpash <nik@nugbase.com>
* feat: sap provider - support reasoning effort for open ai models
* feat: sap provider - support reasoning effort for open ai models
* feat: sap provider - support reasoning effort for open ai models
* feat: sap provider - support reasoning effort for open ai models
* feat: sap provider - support reasoning effort for open ai models
* fix converse api image data to base64 string.
Signed-off-by: Lize Cai <lize.cai@sap.com>
* add test cases
Signed-off-by: Lize Cai <lize.cai@sap.com>
---------
Signed-off-by: Lize Cai <lize.cai@sap.com>
- Updated contextWindow for deepseek-chat and deepseek-reasoner models from 64_000 to 128_000
- Modified context-window-utils.ts to handle DeepSeek models with 128K context window instead of 64K
- This change aligns with DeepSeek's official API documentation and improves model performance
* changeset version bump
* Updating CHANGELOG.md format
* Update CHANGELOG.md for version 3.26.3 release
- Add user-friendly descriptions for compact system prompt feature
- Add proper version formatting with brackets
- Improve clarity of LM Studio and token usage tracking features
* package lock
* changelog
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: github-actions <github-actions@github.com>
Co-authored-by: pashpashpash <nik@cline.bot>
* Build the extension on every commit push
* Publish using the vsix path
* Fix tag resolution
* Remove `while ;`
* Remove test trigger
* use while true;
* Update package.json
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Use high capacity runner
* add if check to only run in the Cline repo
* Conditionally select a runner
---------
Co-authored-by: Dennise Bartlett <bartlett.dc.1@gmail.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Add compact system prompt for local models
- Introduce compact system prompt for local models (lm studio, ollama)
- Add ApiProviderInfo { modelId, providerId } to API
- Persist promptType in global state and propagate to webview
(updateSettings, state keys/helpers, ExtensionMessage, UI context)
- Wire provider info through task pipeline to buildSystemPrompt
* isLocalModelFamily
* Add custom prompt support and LM Studio API improvements
* Enable token usage tracking in LM Studio stream responses
This change adds the stream_options parameter with include_usage: true to LM Studio API requests, allowing the system to receive token usage information along with streaming responses. This enables better tracking of token consumption for LM Studio model interactions.
* update compact system prompt
* feat: Support compact system prompt for LM studio models and token usage tracking
* clean up
* Update UI helper text
* fix: improve OpenRouter model info parsing
Refactor OpenRouter model fetching to include `OpenRouterRawModelInfo` and `OpenRouterSupportedParams` types for better clarity and type safety. This allows for more accurate parsing of model capabilities, including support for "thinking" (reasoning) configurations.
The thinking config is now only set if the model explicitly supports the `include_reasoning` parameter. Additionally, the budget slider in the UI is now displayed for OpenRouter models that support thinking, not just specific Claude models. This provides a more dynamic and accurate representation of model features.
* add changelog
* Set thinking budget for stream
* fix: add support to *.go files in deep-planning feature
* fix: add support to *.go files in deep-planning feature
* adding go to the todos section
---------
Co-authored-by: 0xtoshii <94262432+0xToshii@users.noreply.github.com>
* Change default strict plan mode setting to enabled
- Updated default from false to true in state-helpers.ts (primary backend default)
- Updated fallback default in controller/index.ts (Task initialization)
- Updated frontend default in ExtensionStateContext.tsx for consistency
- Fixed linting issue with forEach callback return value
- New users will now have strict plan mode enabled by default
- Prevents file edits in Plan Mode, enforcing cleaner separation of planning vs execution
* added changeset
---------
Co-authored-by: pashpashpash <nik@cline.bot>
* truncate first user message
* base swapping
* linting
* menu
* apply biome fixes and add back in removed comments
* undo biome invalid changes
* updating feature section comment
* button to enable auto compact just for next gen models
* fix
* fix default model id
* fix tests
* Add changeset for fireworks provider fix
* add docs for fireworks provider
* add empty line to doc
* format
* fix model selector
* remove unnecessary
* fix test
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
* feat: sap provider - show deployed models from the ai core service instance alongside sap provider's supported models in cline
Keep previous clineMessages if the incoming state targets the same currentTaskItem and has no messages, preventing message loss on state sync/refresh while still accepting new messages when present.
* feat(telemetry): Add MCP tool usage tracking
This commit introduces telemetry for MCP tool calls to monitor usage, success rates, and errors.
- Adds a new telemetry event 'task.mcp_tool_called'.
- Captures the server name, tool name, and status (started, success, error).
- Integrates telemetry calls into the McpHub to track tool execution lifecycle.
* chore: Add changeset for MCP telemetry
* refactor(telemetry): Clean up MCP tool usage tracking
This commit refactors the MCP tool usage tracking to be cleaner and more efficient.
- Removes null checks for 'ulid' in the 'callTool' method.
- Passes argument keys to the telemetry service for better monitoring without compromising user privacy.
* feat(telemetry): Add rules and workflow usage tracking
This commit implements telemetry tracking for Cline rules and workflow interactions to understand user engagement patterns:
- Add captureSlashCommandUsed() method to track slash command and workflow activations
- Add captureClineRuleToggled() method to track rule toggle events
- Update parseSlashCommands() to require ULID parameter and track command usage
- Add telemetry calls to toggleClineRule() with proper path sanitization
- Distinguish between builtin commands and workflow types
- Include task ULID context for tracking rule changes within tasks
- Sanitize file paths to include only filenames for privacy protection
* chore: Add changeset for rules and workflow telemetry
* Update src/core/controller/file/toggleClineRule.ts
Co-authored-by: Bee <68532117+abeatrix@users.noreply.github.com>
* Apply suggestion from @Copilot
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* fixed import lol
* added more consistent event name to match the events type
---------
Co-authored-by: Bee <68532117+abeatrix@users.noreply.github.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
The context window is now being set to `Number.MAX_SAFE_INTEGER` to represent infinity. https://github.com/cline/cline/blob/01c4ead15548c906cc690ef030ee447720ccb5b0/src/shared/api.ts#L219-L220
However, this is larger than the max value of int32 and cannot be serialized over the ProtoBus. Update the max token and context window sizes to be int64.
```2025-08-14 18:28:36,492 [ 4334] WARN - bot.cline.services.ProtoBusProxyService - Stream cline.ModelsService.subscribeToOpenRouterModels encountered error
io.grpc.StatusException: INTERNAL: invalid int32: 9007199254740991
at io.grpc.Status.asException(Status.java:548)
at io.grpc.kotlin.ClientCalls$rpcImpl$1$1$1.onClose(ClientCalls.kt:300)
at io.grpc.internal.ClientCallImpl.closeObserver(ClientCallImpl.java:564)
at io.grpc.internal.ClientCallImpl.access$100(ClientCallImpl.java:72)
at io.grpc.internal.ClientCallImpl$ClientStreamListenerImpl$1StreamClosed.runInternal(ClientCallImpl.java:729)
at io.grpc.internal.ClientCallImpl$ClientStreamListenerImpl$1StreamClosed.runInContext(ClientCallImpl.java:710)
at io.grpc.internal.ContextRunnable.run(ContextRunnable.java:37)
at io.grpc.internal.SerializingExecutor.run(SerializingExecutor.java:133)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1144)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:642)
at java.base/java.lang.Thread.run(Thread.java:1583)
```
When the user clicks on a directory file mention, it should open that directory in the explorer panel in the IDE. Add an RPC for this to the host bridge.
I had to change the logic to check if the mention is a directory or not because the current check was not working properly anymore. So, just file.stat to check if its a directory instead of checking if the path ends in /.
* changeset version bump
* Updating CHANGELOG.md format
* Update CHANGELOG.md and announcement for version 3.26.0
- Add user-friendly descriptions for Z AI provider, Cline Sonic Alpha model, LM Studio improvements, and Ollama fixes
- Include attribution for external contributor @jues
- Update announcement component with new 3.26 features
- Move previous 3.25 features to Previous Updates section
* announcement
* announcement
---------
Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: github-actions <github-actions@github.com>
Co-authored-by: pashpashpash <nik@cline.bot>
* microwave alpha stealth model
* microwave alpha stealth model
* swapped name to sonic
* pricing set to zero
* added case for sonic model to set temperature settings
* bumping max tokens to 16k for sonic
* sonic model does not have image support
---------
Co-authored-by: abeatrix <beatrix@cline.bot>
Add an RPC that returns details about the currently active editor. Right now it just returns the file path.
Update the place where this is used.
Remove commented out code that references `vscode.window.activeTextEditor`.
* Remove unused files
I used knip to find unused code- these files are not referenced anywhere in the codebase.
Dead code is a maintence burden, I am removing this unused code.
* Add knip config file
Add knip file with entry points for the extension, cline-core and the ProtoBus and HostBridge services.
Exclude test files, etc.
Exclude the `src/shared` directory because knip can't analyze the webview-ui react app properly.
* Apply suggestion from @ellipsis-dev[bot]
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Formatting
* Get the extension version from the ExtensionContext
The extension packageJson is available from the ExtensionContext, don't need to do `vscode.extensions.getExtension`.
---------
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Enable biome rules: noUnusedVariables, noUnusedFunctionParameters, noUnusedImports
* Apply new rules with format
* remove unused currentReplaceContent
* update nextTerminalId
* fix all format issues
* update biome config
* add back applyContextOptimizations and killAllChromeBrowsers
- Added --write flag to biome format command in postprotos script
- This automatically fixes formatting issues instead of just reporting them
- Prevents build failures due to quote style and other formatting inconsistencies
* Support LM Studio local models with max tokens set
Add configurable max tokens parameter for LM Studio provider across proto definitions, API handlers, storage, and UI components. Improved error handling for model fetching to use v0 api.
* changeset added
* clean up
* update
* Use loaded context length for LM Studio model configuration
- Add loaded_context_length field to LMStudioApiModel interface
- Prioritize loaded_context_length over max_context_length in UI
- Update context window display to show actual loaded context
- Refactor model selection logic and endpoint memoization
- Auto-update max tokens when loaded context differs from config
* Add DropdownContainer
* fix: request_id extraction in ClineError handling
Add back the removed fallback chain to extract request_id from multiple possible locations
in error objects, checking error.request_id and error.response.request_id
before falling back to the existing header extraction method.
* fix: override initial error struct with real request_id instead of overriding request_id with undefined
---------
Co-authored-by: Auroter <seangherardi@gmail.com>
* Add support for Z AI GLM-4.5 and GLM-4.5 air
* Add changeset for Z AI provider
* add entrypoints for Z AI provider, add cacheReadsPrice and cacheWritesPrice
* fix old naming convention
* fix value in proto
* fix proto conversion and secret persistence
* Fix GitHub Actions errors: Add zaiApiKey and zaiApiLine to state-helpers.ts and remove unused state.ts
- Added missing zaiApiKey to readStateFromDisk, resetGlobalState functions and apiConfiguration object
- Added missing zaiApiLine to readStateFromDisk and apiConfiguration object
- Removed unused state.ts file that was causing ESLint errors with direct VS Code API calls
- All type definitions for zaiApiKey and zaiApiLine were already present in state-keys.ts
- This resolves the TypeScript errors in GitHub Actions for CacheService.ts
---------
Co-authored-by: wangshan <shan.wang@aminer.cn>
Co-authored-by: Ara <arafat.da.khan@gmail.com>
* Migrate to Biome for linting/formatting and simplify hooks
- Add biome.jsonc and @biomejs CLI; configure VS Code to use Biome for format/fix and imports
- Replace verbose Husky pre-commit with lint-staged runner
- Remove ESLint setup and custom rule package (no-direct-vscode-api) and its tests
- Update package.json/package-lock and webview-ui package to reflect tooling change
- Add VS Code host typings and grit definitions under src/hosts
Rationale: unify lint/format tooling, speed up pre-commit checks, and reduce maintenance overhead from custom ESLint rules.
* remove eslint dependencies
* preserve eslint rules
* clean up
* update files list
* add docs
* fix build
* clean up
* update VSCode API usage detection in Grit rule
This commit updates the Grit rule for detecting VSCode API usage:
- Narrow down the list of monitored VSCode API methods
- Add more specific diagnostic messages for direct API usage
- Introduce a new check for `workspaceFolders` property
- Exclude `src/extension.ts` from the Grit rule in Biome configuration
The changes aim to improve code abstraction and provide clearer guidance for replacing direct VSCode API calls.
* adds new cacheService rule
* add back pre-commit
* Remove ESLint custom rule and update linting references
Remove custom ESLint rule for VSCode state API enforcement along with its tests, remove ESLint extension recommendation, and update documentation to use generic "linter" terminology instead of ESLint-specific references.
* update vscode.d.ts for IntelliSense
* remove format on save
* clean up default values
* update to 2.1.4
* buf lint
* format
* Switch the DiffViewProvider to use the util `openFile`
This part of the work to migrate the vscode API calls `vscode.window.tabGroups.close`,
`vscode.window.tabGroups.all` and `vscode.window.activeTextEditor` to the host bridge.
`openFile` contains logic that uses these APIs to avoid re-avoiding tabs in the IDE. The end goal
is to move all this logic into `vscode/hostbridge/showTextDocument.ts`.
I am going to switch all the places that use `showTextDocument` over to use `openFile`.
Once everywhere that was using `showTextDocument` has been switched, and is verified to
work the same as before I will move the tab logic in `vscode/hostbridge/showTextDocument.ts`.
* Update src/integrations/editor/DiffViewProvider.ts
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Switch export-markdown to use the util `openFile`.
* Apply suggestion from @ellipsis-dev[bot]
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Move tab logic into vscode/showTextDocument
---------
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
- Extract getPackageDefinition() from loadProtoDescriptorSet() in proto-utils
- Add int64 encoding option to handle numbers properly
- Create test-hostbridge-server.ts with mock gRPC service implementations
- Add -h flag to runclinecore.sh to start test server
- Include testing.md documentation for cline rules
* adding option to have custom requesty base url
fix
changeset
* finish state changes
* cleanup
---------
Co-authored-by: John Costa <john@requesty.ai>
* feat: Use hostbridge machine ID for posthog distinctId across hosts; VS Code only settings link in warning,, generic warning on other hosts.
* fix: block cline-core until hostbridge health is SERVING; exit on failure; initialize telemetry PostHog with hostbridge machineId;
* fix: posthog prefer host-provided UUID when running via HostBridge; fall back to VS Code's machineId, then a random UUID
* fix: add logging to waitForHostBridgeReady
* fix: log error in initialize
* Allow hosts to trigger the 'Add to Cline' action
Other platforms need a way to trigger the context menu actions and commands that are available currently in Vscode.
Add a service to the ProtoBus for this called `CommandService`, currently it just has the 'Add to Cline' action.
IDEs that are running cline with cline-core can trigger these actions and commands over gRPC.
Move the code for handling the 'Add to Cline' out of extension.ts into
`src/controller/commands/addToCline.ts`. This same handler will be used for the RPC.
Switch the handler over to use the proto Diagnostics types as it is host-agnostic.
* Fix getDiagnostics.test.ts on windows.
Use `toPosix()` on the fspath.
* Update src/extension.ts
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
---------
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
These utils will be to build the 'Add to Cline' context menu action for external hosts. The context menu action only deals with diagnostics for a single file, so the current utils need to be adapted.
Export util functions for converting vscode diagnostics to Host Bridge diagnostics.
Export a util for converting diagnostics for a single file from `diagnostics/index.ts`.
* Close page to stop e2e test on teardown
* Configure Playwright to retain videos on failure and simplify teardown
- Enable video recording that only saves on test failures
- Remove complex cleanup logic from global teardown
- Streamline server shutdown to not block teardown process
* change build.js to build.mjs which fixes ES module load error
* speed up
---------
Co-authored-by: Brian Pierce <brian@cline.bot>
* base
* working state reduction & summarization flow wo duplicate calls
* stop injecting into user message
* focus on latest message
* edge case for cancelled stream post summarization tool call
* fix merge
* Add 1m context window model variant for claude sonnet 4
* Fix cost calculation for 1m tier
* Add new 1m context window announcement
* Create beige-bobcats-watch.md
* Add bedrock support for 1m context
`cline-core` cannot depend on its environment being set up properly
by its parent process. Run the terminal commands in a login shell so
that the PATH etc. will be setup correctly.
* Change the host bridge RPC closeDiff to closeAllDiffs
In the vscode diff view provider when the diff is closed, it
closes _all_ open diff views.
I thought in the HostBridge, we would just only be closing the
current diff, but we do need to close all the open diff view
because there can be checkpoint diffs open as well.
* Update proto/host/diff.proto
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Update src/integrations/editor/DiffViewProvider.ts
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
---------
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Move the logic for showing the multi-file diffs out of the Task class which >2000 lines long.
Split the logic up into functions, add tests.
Use try/finally to ensure that `sendRelinquishControlEvent` is always sent when the function returns.
* Fix warning about use of !!
* Fix tests
Remove asserts on console logs because they are not able to be stubbed properly.
Move test file to correct directory.
* Formatting
* fix: request_id was being incorrectly extracted from the API response -- it can always be found in the response header under X-Request-ID
* fix: leave error alone, no need to re-create it
* Update src/services/error/ClineError.ts
Co-authored-by: Bee <68532117+abeatrix@users.noreply.github.com>
---------
Co-authored-by: Bee <68532117+abeatrix@users.noreply.github.com>
* Add VSCode theme colors to Tailwind config
- Add comprehensive VSCode theme color palette to Tailwind config
- Replace hardcoded VSCode CSS variables with Tailwind utility classes for HomeHeader
- Update button and text styling to use new theme-aware classes
* format
Guard ActionButtons when no task; fix scroll deps/empty state
- Return null from ActionButtons if no task to avoid rendering controls without context
- Add missing setExpandedRows dependency and remove unnecessary deps to prevent stale closures and re-renders
- Hide “scroll to bottom” button when there are no messages
- Clean up unused index-tracking logic in scrollToMessage
Add an RPC to the Host Bridge to open a diff for multiple files, this is
used when comparing check points or to display the changes cline has made
when it is finished editing.
Switch the file mentions unit test to an integration test because
now it is pulling vscode dependencies and they cannot be mocked
in the unit tests.
* Refactor action buttons: centralize state, remove useButtonState
- Replace useButtonState hook with centralized ButtonConfig logic in ActionButtons, mapping task/ask/tool states to button enablement and labels
- Update ActionButtons API to accept task, messages, mode; compute streaming/enablement internally; remove isStreaming prop
- Always render ActionButtons from ChatView; adjust props accordingly
- Update useIsStreaming call to pass task instead of enableButtons/primaryText
- Clean up useMessageHandlers to reset UI state consistently (input, quotes, files, images, autoscroll)
- Remove deprecated hook and align types
Why: unify and simplify button behavior across task lifecycle, reduce duplicated state/props, and make streaming/approval flows more predictable.
* clean up
* Refactor input clearing and streaming detection logic
This commit:
- Separates input clearing logic into a separate useEffect in ActionButtons
- Removes StreamingIndicator component and its useIsStreaming hook
* Revert newly added button states
Remove switch_to_act_mode button config and associated plan mode conditionals in getButtonConfig function, will do any UI change in follow-up
* simplify further
* Add test suite for button configuration logic
This commit introduces a new test file for the `buttonConfig` module, covering various scenarios such as:
- Default button configurations
- Streaming and partial message handling
- Error recovery states
- Tool approval states
- Command execution states
- Specific ask state configurations
- API request state testing
The tests ensure robust button configuration selection based on different message types and states.
* update button styles
* move rest of state to cacheService
* finish moving state to cache
* remove console logs
* fix types
* don't type cast
* add eslint rule banning use of direct storage apis
* fix types
* move vscode state eslint rule to separate rule since it's error and the others aren't
* fix eslint rules parsing
The diff view is supposed to return any new errors or warnings after the
file is edited. The ExternalDiffViewProvider was just returning *all*
the errors.
When the DiffViewProvider is being reset, reset *all* the properties.
Add unit tests for diagnostics functionality
Refactoring:
- Move diagnostics into the parent DiffViewProvider, remove duplicate implementations in VscodeDiffViewProvider and ExternalDiffViewProvider
- Move duplicated code for converting FileDiagnostics to string to `diagnosticsToProblemsString`.
- Use a single implementation of `getDiagnostics` and `diagnosticsToProblemsString` using the HostBridge protos.
* remove workspace tracker
* remove console log
* fix search when clicking folder option
* create enum for searchType
* use hostbridge for active files
* use util function for relative path
* Fix into interests error where false security warning is being triggered
* Don't use activate() in cline-core
Have separate code paths to set up the extension and cline-core.
This means the cline-core is not running all the vscode setup and is
only using one `Controller` (the one from the WebviewProvider).
Move the shared logic into common.ts.
* Comments and logging
* fix: mode switch styling
Replace the use of `--vscode-toolbar-hoverBackground` which is a `-hoverBackground` that tends to be transperant or opacity change on some themes. Replace it with `-background` which uses solid color instead. See https://code.visualstudio.com/api/references/theme-color
- Update Plan/Act mode switch colors var for better visibility across themes
- Remove hover effects from switch options
- Add background classes to active switch options
* changeset added
* add: caching support for bedrock (claude)
* refactor: gemini message handling to adhere closer to original implementation (and make implicit caching clear)
* remove: unused bedrock conversion functions
* fix: payload for converse stream (older claude models)
remove: caching support flag for older claude models
* add: changeset
* Update package-lock.json
* fix: show credits purchase component when user runs out of credits and we receive 402 status from server
* revert unnecessary change
* Create many-adults-end.md
The ExternalWebviewProvider has to return /something/ for `getWebview()` or
the rest of the code thinks that is not set up and it won't generate the HTML
for IntelliJ.
The Vscode webview panel, `resolveWebview()` and other Vscode specific parts are
planned to be moved out of the WebviewProvider and into VscodeWebviewProvider,
but that depends other changes to how the webview is initialized in extension.ts
to need to happen first.
Move the WebviewProvider out of index.ts and into a file name `WebviewProvider`,
this follows best practises.
* feat: add client-specific targeting for addToInput events
- Add client-specific targeting for addToInput events
- Update subscribeToAddToInput to accept client ID parameter
- Replace global event broadcasting with targeted client messaging
- Remove automatic sidebar focus when adding code to chat
- Use last active webview instance for context menu actions
- Maintain backward compatibility with subscription management
* add changeset
* remove debug profiler
* e2e test
* add type
* Add e2e test
* update teardown
* preparing for gpt5 release
* Update generic system prompt with needs_more_exploration param for plan mode
* changeset
---------
Co-authored-by: Saoud Rizwan <7799382+saoudrizwan@users.noreply.github.com>
* feat: migrate diff edit diagnostics to hostbridge; Migrate diagnostics functionality from direct VS Code API calls to the hostbridge layer to enable multi-host support (VS Code + IntelliJ).
* remove test logging
* refactor: migrate diagnostics to workspace service and host separation
* Add walkthrough button and enable quick wins for new users
- Add openWalkthrough RPC method to ui.proto
- Enable quick wins display for users with <3 tasks in history
- Add "Take a Tour" button in HomeHeader when quick wins are shown
- Update WelcomeSection to pass shouldShowQuickWins prop to HomeHeader
* Adding Gpt-oss through groq
* Adding Gpt-oss through groq
* Support prompt caching and thinking for Opus 4.1
* Support prompt caching and thinking for Opus 4.1
* Support prompt caching and thinking for Opus 4.1
- Remove teardown dependency on e2e tests to fix execution order
- Move server cleanup before file operations in teardown
- Add proper error handling and logging for cleanup operations
There is one place in the McpHub that sends messages mcp notification messages directly to the webview (not using the ProtoBus).
There is nowhere in the webview that is listening for this message, so this code is not doing anything.
* kimi working
* fixed description rendering
* nit
* changeset
* revert openai version in package.json
* revert package-lock.json
* added space back in
* maintained previous protofield map order
* fixed import error due to location change from main
* updated Mode import for BasetenModelPicker
* revert readme since baseten is openai compatible
* refactored extensionStateContext
* added didOutputUsage flag
* fixed frontend loading
* no support for images on llama
* shifted VSCode Option order
* deleted typo
---------
Co-authored-by: Alex Ker <alexker@mac.mynetworksettings.com>
Co-authored-by: Alex Ker <alexker@Alexs-MacBook-Pro.local>
* Simplify the GrpcHandler
* Use two functions handleUnaryRequest and handleStreamingRequest, instead of creating a GrpcHandler object and calling class methods on it.
* Remove redundant try/catch and empty finally blocks. Each of the two handler functions has it's own try/catch.
* Each of the two functions is responsible for posting the result to the webview- Instead of unary and streaming responses being handled at different levels.
* Use the GrpcRequest and GrpcCancel types.
* Update comment
* fix: clear streamingFailedMessage when user manually retries
- Clear streamingFailedMessage when user manually retries
- Convert imports to type-only where appropriate
- Reorder imports for better organization
- Add explicit type annotations for better type safety
- Move node:timers/promises import to top
* add changeset
* merge main and reset fail flag
* revert autoformat
**Centralize callback URI management** through the HostProvider instead of having it in multiple places in the codebase.
**Simplify error handling** by making the callback URI required rather than optional
The changes are related to **authentication callback URI handling** in the Cline extension. Here's what's being modified:
- Simplified callback URI retrieval
- Changed return type from `Promise<string | undefined>` to `Promise<string>`
- Now throws an error if AuthHandler is not enabled instead of returning undefined
- Added a new `getCallbackUri` property that returns a `Promise<string>`
- This allows the host provider to supply callback URIs for authentication
- Implemented callback URI provider
- Updated to use HostProvider for callback URI
- Updated to match new signature
* feat: support file mentions with spaces using quoted syntax
This change allows users to reference files with spaces in their names, which was previously impossible due to the space-delimited mention syntax.
File names with spaces can be @ mentioned by quoting the file name, e.g. @"/path with spaces/file.txt".
- Update mention regex in `src/shared/context-mentions.ts` to accept quoted file paths
- Add support for quoted file paths that can contain spaces.
- Allow multiple trailing punctuation chars; previously only a single limited punctuation characters were allowed.
- Maintain support for unquoted paths, URLs, git hashes, and special keywords
- Update `src/core/mentions/index.ts` to handle quoted file names in mention parsing
- Process quoted file paths by removing quotes when accessing the file system
- Preserve existing functionality for all other mention types
- Update `webview-ui/src/utils/context-mentions.ts` to auto-quote file names with spaces
- `insertMention()` and `insertMentionDirectly()` now wrap file paths containing spaces in quotes
- Non-file mentions (URLs, keywords) remain unquoted
- Add comprehensive unit tests:
- New test file `src/core/mentions/__tests__/index.test.ts` covering all mention types
- New test file `webview-ui/src/utils/__tests__/context-mentions.test.ts` for webview mention insertion
- Expanded `src/shared/__tests__/context-mentions.test.ts` to cover quoted paths and edge cases
* Use const instead of var
- Replace fixed 100ms timeout with pWaitFor polling mechanism
- Set 2-second timeout with 50ms polling interval
- Test now waits exactly as long as needed for tabs to be created
* Move remaining uses of vscode.window.show*Message to the HostBridge
Switch over the remaining uses.
Turn on the linter check to prevent these APIs being reintroduced later.
Exclude test files from the linter check.
* Update unit test
- Replace database icon with MCP server icon (codicon-server)
- Remove shadow-sm class for a flatter appearance
- Maintain consistent button styling with VSCodeButton components
- Add tooltips using HeroTooltip
* Fix errors in tests:
```
[TerminalProcess] Terminal ID: Cline
Error capturing terminal output: Error: Failed to read from clipboard: HostProvider not setup. Call HostProvider.initialize() first.
at readTextFromClipboard (/Users/sjf/cline/out/src/utils/env.js:39:15)
at getLatestTerminalOutput (/Users/sjf/cline/out/src/integrations/terminal/get-latest-output.js:35:69)
at TerminalProcess.emitCurrentTerminalContents (/Users/sjf/cline/out/src/integrations/terminal/TerminalProcess.js:26:92)
at TerminalProcess.runWithoutShellIntegration (/Users/sjf/cline/out/src/integrations/terminal/TerminalProcess.js:366:20)
at async TerminalProcess.run (/Users/sjf/cline/out/src/integrations/terminal/TerminalProcess.js:47:13)
✔ should execute a command that lists files
[TerminalProcess] Starting command: "sleep 0.5 && echo 'Done sleeping'"
[TerminalProcess] Shell integration available: false
[TerminalProcess] Terminal ID: Cline
Error capturing terminal output: Error: Failed to read from clipboard: HostProvider not setup. Call HostProvider.initialize() first.
at readTextFromClipboard (/Users/sjf/cline/out/src/utils/env.js:39:15)
at getLatestTerminalOutput (/Users/sjf/cline/out/src/integrations/terminal/get-latest-output.js:35:69)
at TerminalProcess.emitCurrentTerminalContents (/Users/sjf/cline/out/src/integrations/terminal/TerminalProcess.js:26:92)
at TerminalProcess.runWithoutShellIntegration (/Users/sjf/cline/out/src/integrations/terminal/TerminalProcess.js:366:20)
at async TerminalProcess.run (/Users/sjf/cline/out/src/integrations/terminal/TerminalProcess.js:47:13)
at async Context.<anonymous> (/Users/sjf/cline/out/src/integrations/terminal/TerminalProcess.test.js:119:13)
FakeTimers: clearTimeout was invoked to clear a native timer instead of one created by this library.
To automatically clean-up native timers, use `shouldClearNativeTimers`.
✔ should handle a longer running command (3007ms)
[TerminalProcess] Starting command: "echo 'Line 1' 'Line 2'"
[TerminalProcess] Shell integration available: false
[TerminalProcess] Terminal ID: Cline
Error capturing terminal output: Error: Failed to read from clipboard: HostProvider not setup. Call HostProvider.initialize() first.
at readTextFromClipboard (/Users/sjf/cline/out/src/utils/env.js:39:15)
at getLatestTerminalOutput (/Users/sjf/cline/out/src/integrations/terminal/get-latest-output.js:35:69)
at TerminalProcess.emitCurrentTerminalContents (/Users/sjf/cline/out/src/integrations/terminal/TerminalProcess.js:26:92)
at TerminalProcess.runWithoutShellIntegration (/Users/sjf/cline/out/src/integrations/terminal/TerminalProcess.js:366:20)
at async TerminalProcess.run (/Users/sjf/cline/out/src/integrations/terminal/TerminalProcess.js:47:13)
✔ should execute a command with arguments
[TerminalProcess] Starting command: "echo "Line 1" && echo 'Line 2'"
[TerminalProcess] Shell integration available: false
[TerminalProcess] Terminal ID: Cline
Error capturing terminal output: Error: Failed to read from clipboard: HostProvider not setup. Call HostProvider.initialize() first.
at readTextFromClipboard (/Users/sjf/cline/out/src/utils/env.js:39:15)
at getLatestTerminalOutput (/Users/sjf/cline/out/src/integrations/terminal/get-latest-output.js:35:69)
at TerminalProcess.emitCurrentTerminalContents (/Users/sjf/cline/out/src/integrations/terminal/TerminalProcess.js:26:92)
at TerminalProcess.runWithoutShellIntegration (/Users/sjf/cline/out/src/integrations/terminal/TerminalProcess.js:366:20)
at async TerminalProcess.run (/Users/sjf/cline/out/src/integrations/terminal/TerminalProcess.js:47:13)
✔ should execute a command with quotes
```
* Create brown-papayas-protect.md
---------
Co-authored-by: Saoud Rizwan <7799382+saoudrizwan@users.noreply.github.com>
* feat: use auth callback handling with custom AuthHandler
- Add AuthHandler class to manage OAuth flow with local HTTP server
- Move callback logic from extension.ts to SharingUriHandler, making that shared between the original and new authentication ways
- Enabling Custom HTTP for "core only" environments
- Async starting and stopping HTTP server
* test: Fix and re-enable unit tests
Re-enable unit tests in CI workflow that were previously disabled
The cline-api test requires VSCode SDK which cannot be easily mocked in unit tests,
so it has been moved to integration tests where the full VSCode environment is available.
The @google/genai module is ES6-only which causes issues when running integration tests
compiled to CommonJS. A mock implementation has been added and the module resolution
is intercepted in test-setup.js to use the mock instead.
The bedrock unit tests for getModelId() functionality are removed as they were failing
and fixing them is out of scope for this PR.
- Move cline-api.test.ts from exports to test directory as it depends on VSCode SDK
- Add gemini-mock.test.ts to mock @google/genai ES6 module for CommonJS compatibility
- Add module interception in test-setup.js to redirect @google/genai to mock
- Remove failing bedrock unit tests introduced in PR #4209 (out of scope)
* Update src/api/providers/__tests__/bedrock.test.ts
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Formatting
---------
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* fix: E2E test stability by reordering sidebar and notification setup
- Extract editor menu locator to variable for better readability
- Move sidebar opening to page fixture to ensure it's available earlier
- Wait for chat input visibility before disabling notifications
- Prevents race conditions in test initialization
* fix
* remove chatSettings object
* use cache for apiCongfiguration state
* add state persistence debounced, batch state updates, make setters synchronous
* fix types after merge conflicts
* fix global state reset
* remove clearCache; make dispose function private; remove vscode api dependency; call reInitialize in reset functions instead of dispose/initialize
When the webview is built wuth build:test:
* don't compact the compiled code
* don't minify
* use inline source maps (the embedded JCEF browser can't load source maps from .map files).
* fix: use Uri.from to generate valid diff URI
* fix the conflicts for VscodeDiffViewProvider.ts has been moved
---------
Co-authored-by: wangyj20 <wangyj20@asiainfo.com>
* refactor: e2e test setup to use Playwright projects with global server
- Replace globalSetup/globalTeardown with Playwright projects configuration
- Rename setup.ts to global.setup.ts and teardown.ts to global.teardown.ts
- Convert ClineApiServerMock to use shared global server instance
- Add proper dependency management between setup, tests, and cleanup phases
- Improve server connection tracking and cleanup handling
* Rename Playwright test project names to match
* IS_DEV
* update helpers
- Rename isGitHubAction to isCI for broader CI detection
- Adjust timeout logic to use CI or Windows conditions
- Reduce expect timeout from 40s/20s to 5s/2s for faster feedback
- Decrease streaming chunk delay from 50ms to 20ms in server mock
* Add mock api service and E2E test infrastructure
- Create AuthServiceMock for testing with mock user data and API responses
- Add AuthProvider interface to standardize authentication providers
- Implement E2E test fixtures with mock server and workspace setup
- Add comprehensive E2E tests for authentication and core functionality
- Export DEFAULT_CLINE_APP_URL config and make getEnvironmentConfig more flexible
- Update AuthService to use mock implementation during E2E tests
* format
* import
* refactor mock server
* rename data
* wait for text
* wait for edit
* increase timeout for windows
* clean up
* rename test and add orgs
* Move the OutputChannel to the HostProvider
Replace `OutputChannel.appendLine` with `HostProvider.logToChannel`.
Remove places where the cline OutputChannel was being passed around. Now it is stored in the HostProvider, so we don't need to do this.
# Conflicts:
# src/hosts/vscode/VscodeWebviewProvider.ts
* Dont log the timestamp in logger.ts, the cline-core logger already outputs the timestamp
* Fix imports
* Add Huawei Cloud MaaS Provider
* Fix case error
* Add missing modelid
* add huawei specific modelId and modelInfo
* add huawei specific model id and model info in state.proto
* more huawei maas specific change
* refactor & fix: improve account view with better states management
The previous AccountView implementation suffered from several critical state management issues:
- Incorrect info on display: The active account is not ready when component is mounted because the fetching only start on mount but doesn't get reset correctly
- Excessive re-renders: All data was fetched on component mount, causing cascading state updates
- Race conditions: Multiple concurrent API calls and state dependencies created unpredictable behavior, e.g. 403 rate limits errors
- Monolithic state management: All account data, organizations, and auth state was managed in a single massive component
- Poor user experience: Users saw empty states and loading flickers when switching between organizations
- Tight coupling: User and org info logic was deeply embedded within the account view that cause Effect dependency loops
Solution: Centralized Authentication Context
- Extracted auth logic into dedicated ClineAuthContext with organizations state management
- Eliminated prop drilling by providing clineUser, organizations, and activeOrganization at the context level
- Reduced component re-renders by managing auth state separately from UI state
- Performed authentication guard at higher level and only displays user account to authenticated user. The component will get dismounted when user is not autheticated.
- Move handleSignIn and handleSignout into individual functions instead as they are regular functions with no state dependency
* 60secs
* Optimize state updates in AccountView to prevent unnecessary re-renders
Remove conditional checks before setState calls and use functional updates
with deep equality comparison to avoid redundant state changes and
dependency array bloat in useCallback hooks.
* add docs
* fix format
* fix error test
* setuser on logout
* Fix styled-components prop warnings
- Fix styled-components shouldForwardProp warnings by filtering non-DOM props
- Clean up unused imports in ChatTextArea and other components
* use mjs
* later
* remove unused imports
* Fix: webview panel state change steals focus
Fix webview visibility detection to check both visible and active states before taking focus. If a panel is visible but not active (focused), it should not steals editor focus.
Also removes unused import & add type imports
* add changeset
* Improve token counting for Claude models in VSCode LM provider
- Reorder imports for better organization
- Add extractTextFromMessage helper method
- Add isClaudeModel detection method
- Use 4:1 character-to-token ratio for Claude models instead of VSCode's inaccurate counting
- Fallback to existing VSCode LM token counting for non-Claude models
* Update version to 3.18.3-r1 and refactor token calculation in VsCodeLmHandler
* 3.19.5-r1
* Add smart jobs impress changeset for VSCode LM API token counting fix
---------
Co-authored-by: Jonathan Barazany <jbarazany@microsoft.com>
* Add a check to the proto scripts to warn about using int64 types.
Javascript cannot represent the full range of int64. So, when the protos are deserialized from JSON int64's are converted to strings. The typescript code is expecting a number and not a string, and this causes errors.
This was noticed before now because in the vscode protobus and hostbridge, the proto messages are not serialized and deserialized, they are just passed around as JS objects.
However, in IntelliJ the protos are serialized when they are sent through the ProtoBus. When the response messages contains and int64, it is deserialized to a string instead of a number for safety. This is causes parts of Cline to fail in IntelliJ, e.g. the task history view won't load because `Task.getTotalTasksSize()` returns a string when it is expecting a number.
* Make checkProtos shorter
* Update scripts/build-proto.mjs
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Update scripts/build-proto.mjs
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Update scripts/build-proto.mjs
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Fix typo
* Fix typo
* Fix bad merge
---------
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* feat: add openFile host bridge for vscode.open command
* fix: simplify openFile hostbridge to follow gRPC best practices:
- Remove success boolean field from OpenFileResponse proto
- Use gRPC exceptions for error handling instead of success/failure booleans
- Simplify hostbridge implementation to just move existing vscode.open code
* fix: remove create wrapper from openFile call
* fix proto merge conflict
* Use npm `open` to open URLs in the external browser
# Conflicts:
# src/utils/env.ts
# Conflicts:
# src/utils/env.ts
* Change log statement
* Use the simple-open-url module to open URLs in the system browser.
Log failures of ProtoBus RPCs
* Remove vscode hostbridge handler for openExternal
* Rm unused imports
* Switch back to `open` module.
Update esbuild.js to ES6 and move to esbuild.mjs
* Update src/utils/env.ts
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* remove IS_DEV from e2e setup build
---------
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
Co-authored-by: abeatrix <beatrix@cline.bot>
* Reorganized proto directory structure to match package naming convention
Moved cline package protos from the proto directory to proto/cline/ directory
Host package protos remain in proto/host/ directory
Updated all import statements across codebase to reflect new proto paths
Removed proto linter exception for package/directory mismatch rule
Fix Vscode proto indexing errors by setting the proto path in the Vscode settings.
* Update imports to use new package
Update imports from @shared/proto/<thing> to @share/proto/cline/<thing>
* Fix Qwen API option inconsistency
Refactor Qwen API region handling with enum and improved type safety
Changes:
- Replace string literals with QwenApiRegions enum for better type safety
- Add default region initialization in QwenHandler constructor
- Extract useChinaApi() method for cleaner conditional logic
- Update UI dropdown to use enum values with proper memoization
- Improve code maintainability and reduce magic strings
* changeset added
* Apply suggestions from code review
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* fix type with conversion
* Refactor Qwen model defaults to use first model dynamically
Move type definitions and enums after model objects and set default
models by selecting the first key from each model object instead of
hardcoding specific model IDs.
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Fix organization state reset when switching between accounts
Move user authentication check into getUserOrganizations callback to properly reset state when switching between personal and organization accounts. This prevents stale organization data from persisting across account switches.
* add changeset
* Add error handling and refactor credit display components
Fix issues with balance display out of sync on org change or when API calls received 405 (rate limited) error
- Add error handling for failed API calls in getUserCredits and getOrganizationCredits
- Extract animated credit display logic into reusable StyledCreditDisplay component
- Simplify AccountView by removing inline credit animation code
- Improve organization state management and loading behavior
* Apply suggestions from code review
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* format
* reset on mount
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Fix for files being deleted when switching modes or closing tasks
* changeset
* Added check to see if we are waiting for API response
* More targetted fix
* Create hot-onions-promise.md
* Delete .changeset/hot-onions-promise.md
---------
Co-authored-by: Kevin Bond <kevin@Kevins-MacBook-Pro.local>
Co-authored-by: Saoud Rizwan <7799382+saoudrizwan@users.noreply.github.com>
- Fix AccountView state management when user is not authenticated or is authenticated after the webview is loaded
- Add proper loading state reset and conditional data fetching
* Display credit balance for all accounts
The credit balance display was previously only shown for personal accounts. This change removes the check for `activeOrganization === null` and displays the credit balance and "Add Credits" button for all account types, including organization accounts. A divider is added above the balance section for visual separation once the backend change is deployed.
* changeset
* Improve refresh logic
Refactors the `AccountView` component to properly display and manage credits for both user and organization accounts. It introduces the `getOrganizationCredits` API call to fetch organization-specific credits and updates the UI accordingly. The refresh logic has also been improved to ensure data consistency and prevent unnecessary API calls.
Key changes:
- Implemented `getOrganizationCredits` to fetch credits for the active organization.
- Modified the credit display to show organization credits when an organization is active.
- Updated the refresh logic to use `useCallback` and `debounce` for better performance and to prevent race conditions.
- Added a periodic refresh to update account data every 30 seconds.
- Improved error handling and loading state management.
- Removed the interval ref and replaced it with a simpler useEffect for periodic refresh.
- Added last fetch time to the UI.
* clean up
* deepEqual
* org management
* prevent race condition
* Remove compiled files that were committed by mistake
* Don't JSON encode the grpc message request.
The original grpc-client-base.ts encoded the request message using
```
function encodeRequest(request: any): any {
if (request === null || request === undefined) {
return {}
} else if (typeof request.toJSON === "function") {
return request.toJSON()
} else if (typeof request === "object") {
return { ...request }
} else {
return { value: request }
}
```
But the request object don't have a .toJSON method, so it was not actually converting them
to JSON properly.
Don't JSON encode request to keeo the same behaviour as before.
* Update gitignore
* fix: Generate type-safe code for the Vscode Protobus service
This commit establishes a fully type-safe ProtoBus system by fixing the streaming
response handler type definitions and completing the protobuf-driven architecture.
Key improvements:
• **Complete type safety**: ProtoBus is now completely type-safe with compile-time
validation of all gRPC service definitions, request/response types, and handler
signatures
• **Simplified message creation**: No longer need to manually call `Message.create({...})`
- the generated code handles message instantiation automatically
• **Automated proto parsing**: Eliminated manual parsing of proto files - the build
system now automatically generates TypeScript definitions from protobuf schemas
• **Proto files as source of truth**: Service names, method names, and message types
are now definitively controlled by the proto files, ensuring consistency across
the entire codebase
• **Handler type checking**: ProtoBus handlers are fully type-checked including:
- Request and response type validation
- Handler method name verification against proto definitions
- Streaming vs unary handler signature enforcement
This establishes a robust, type-safe foundation for all gRPC communication between
the extension host and webview components.
* Remove commented out code in script
* Just call handlers directly
* Fix CLINE_ENVIRONMENT configuration not being passed to webview
## Problem
The CLINE_ENVIRONMENT configuration set in launch.json was not being properly passed to the webview, causing the webview to break when trying to access environment-specific configurations.
This resulted in:
Webview using incorrect API URLs (always defaulting to production)
Broken authentication flows in development/staging environments
Inconsistent behavior between the main extension and webview components
## Root Cause
The issue occurred because:
Duplicate Configuration Logic: The webview had its own separate config.ts file that was trying to read process.env.CLINE_ENVIRONMENT directly
Environment Variable Propagation: While Vite was configured to pass CLINE_ENVIRONMENT to the build process, the webview's runtime code couldn't access this environment variable properly
Configuration Mismatch: The main extension and webview were using different configuration sources, leading to inconsistent environment settings
* fix credit uri
* replace apiBaseUrl with appBaseUrl
* local option
* fallback changed to app
* change to app url
* merge fixes
---------
Co-authored-by: 0xtoshii <94262432+0xToshii@users.noreply.github.com>
* refactor(hosts): Simplify the host provider interface for callers
- Streamline API to reduce complexity for consuming code
- Update all references across core, controller, and integration modules
- Consolidate provider patterns for easier usage
- Rename host-providers.ts to host-provider.ts
# Conflicts:
# src/core/controller/index.ts
# src/extension.ts
# src/integrations/git/commit-message-generator.ts
* Add comment
* In the tests, reset the HostProvider to prevent it complaining that it is being reinitialized
* Update comment
* Fix imports
* Refactor: Git commit message generation as a module
Implement Git commit message generation as a module
Refactors the Git commit message generation functionality into a separate module for better organization and maintainability.
The changes include:
- Moving the commit message generation logic from `src/core/controller/index.ts` to a new module `src/integrations/git/commit-message-generator.ts`.
- Adding a command to abort commit message generation.
- Updating the `cline.generateGitCommitMessage` command to use the new module.
- Adding a context key to disable the generate commit message button when a commit is generating.
This refactoring improves the codebase by:
- Separating concerns: The commit message generation logic is now isolated in its own module, making it easier to understand and maintain.
- Improving testability: The new module can be tested independently of the controller.
- Promoting code reuse: The commit message generation logic can be reused in other parts of the application if needed.
* clean up
* changeset added
* Pass the system prompt through a file when using Claude Code
* Support older versions and return better errors
* Add tests
* Add changeset
* Remove outdated docs
* Use a unique file name and clean the file
* Address comments
* Diable checkpoints on tasks where the init timed out, fix settings link
* early warning message
* Added checkpointTrackerErrorMessage to HistoryItem
* Updated some comments related to checkpoints timeouts
* changeset, timer cleanup
* timer cleanup
* add provider handler options types and only pass those fields when building
* use separate fields for plan and act mode for ephemeral model settings
* post merge issues fixed: bedrock and cline api build handlers; current mode reading in controller/index.ts; adding a couple fields to welcomeView migration
* add in moonshotApiKey to settings-conversion after main merge
* fix type errors
* fix frontend types
* fix code after merge conflicts; switch groq provider to plan/act paradigm
* consolidate to Mode type
* remove promise resolve
* move huggingface provider into the new schema
* add new providers to migration function
* use normalizeApiConfiguration for settings menu provider value to avoid undefined state error
* Fix the structure for the hosts package.
Right now we support two host platforms: vscode using the internal host bridge service (inside the same process), and other platforms using the external host bridge (using gRPC over local sockets).
The structure of the two packages should mirror each other
```
hosts/
vscode/
VscodeDiffViewProvider
VscodeWebViewProvider
etc ...
external/
ExternalDiffViewProvider
ExternalWebViewProvider
etc ...
```
* Fix imports
* Fix imports
* Fix imports
* Add eslint check for more vscode API calls
Add eslint checks to prevent vscode API calls from being reintroduced after they were switched to the host bridge.
The ones that are not enabled are not completely migrated, so they are not turned on because it would cause too many warnings, and make developers used to ignoring them.
* Update eslint-rules/no-direct-vscode-api.js
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Update warning message text
* Move the check for if the file is being included in the linter check or not into its own function
---------
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* fix: disabled servers should not be started
* refactor to dedupe
* add changeset
* Update moody-crabs-relate.md
* minor comment tweaks
* use unknown instead of any
* Move logic to save the diff document and get the diff content to the platform specific diff view providers.
Add getDocumentText to the diff service.
The ExternalDiffViewProvider should be using its activeDiffEditorId (not the activeDiffEditor, which is the vscode Editor object)
* Check activeDiffEditorId
* Update src/integrations/editor/DiffViewProvider.ts
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Use await with this.saveDocument()
* Remove test file
---------
Co-authored-by: ellipsis-dev[bot] <65095814+ellipsis-dev[bot]@users.noreply.github.com>
* Use await when calling async function showMessage.
Use await when calling `windowClient.showMessage`, otherwise the caller doesn't wait for the request to complete and any exceptions are lost.
For the host bridge RPCs, you don't need to do `ShowMessageRequest.create({...})`, you can just pass the request directly like: `{...}. The Message.create() was needed for the ProtoBus because of the way it was implemented, it couldn't be type-checked by the compiled. It's not needed elsewhere.
* Dont use await, because it blocks until the message is dismissed
* Dont need `?.selectedOption`, the response cannot be null
* Dont use await
* Add truncate document to the hostbridge diff service.
# Conflicts:
# src/standalone/ExternalDiffviewProvider.ts
* Fix typo
* Add host bridge rpcs for the diff service
* Add saveDocument and closeDiff to the host bridge.
* Formatting
* Use the host bridge in ExternalDiffviewProvider
* Make comments less verbose
* Unify error handling and display
Several improvements to error handling and reporting within the Cline extension, focusing on providing more informative error messages to the user and improving telemetry data.
- **Error Handling:**
- Introduces a `ClineError` class to encapsulate Cline-specific errors, providing structured data about the error (status code, request ID, etc.).
- The `ErrorService` now creates and logs `ClineError` instances, improving error reporting to Sentry and telemetry.
- Removes redundant error formatting logic from `src/core/task/utils.ts`, relying on the `ClineError` class for consistent error representation.
- The Cline API handler now throws the raw error, allowing the `ClineError` class to handle the error formatting.
- **UI Improvements:**
- Introduces new UI components (`ErrorRow`, `ErrorBlockTitle`) to display error messages in a more user-friendly format within the chat interface.
- Displays credit limit errors with detailed information and a link to purchase credits.
- Improves the display of rate limit errors and authentication errors.
- Adds specific handling for PowerShell-related errors, providing a link to a troubleshooting guide.
- **Telemetry:**
- Captures provider API errors using `ClineError` data, providing more detailed information about the error in telemetry reports.
- **Other Changes:**
- Fixes an import path in `src/services/posthog/PostHogClientProvider.ts`.
- Adds tests for the new UI components.
- Adds `error` field to `ClineMessage` to transport `ClineError` instances to the webview.
These changes aim to provide a better user experience by displaying more informative error messages and improving the overall reliability of the Cline extension.
* include provider id
* includes model and provider id
* fix test
* return gracefully for empty response
* Handle auth state changes in all extension windows
Addresses an issue where authentication state changes (login/logout) were not being properly propagated across all extension windows.
The `onDidChange` event handler for `clineAccountId` secret now checks if the secret was added/updated (login) or removed (logout).
- If the secret exists, `restoreRefreshTokenAndRetrieveAuthInfo` is called to restore auth info (login from another window).
- If the secret is removed, `handleDeauth` is called to handle logout for all windows.
This ensures that all extension windows are kept in sync with the current authentication state.
* changeset
* Add a way to reset state for the platform specific diff view providers.
Add the abstract method `resetDiffView()` to the DiffViewProvider.
On Vscode it reset the active diff editor and decorations.
On External diff view providers, it reset the diff editor ID.
* Add a way to truncate the document to the platform specific diff view providers.
This is used when the last update is recieved to remove any content from the bottom of the document.
* Move `closeDiffView` to the platform specific diff view classes.
* Update comment
* Use await for async function
* Move setting the cursor position into replaceText
* Move the logic to scroll the diff editor window into the platform specific classes.
Move the current logic into the VscodeDiffViewProvider.
The ExternalDiffViewProvider will use the host bridge to scroll the editor tab. But for now it doesn't do anything.
* Add comment
* Remove log messages
<important>If using the direct approach, pipe outputs through `cat` to avoid interactive terminals. If the user's shell is not bash/zsh, adjust the command and chaining
syntax accordingly.</important>
```powershell
$B=$null;foreach($cin'main','master','origin/main','origin/master'){gitrev-parse--verify-q$c*>$null;if($LASTEXITCODE-eq0){$B=$c;break}};if(-not$B){$B='HEAD'};functionr([string]$b){gitrev-parse--abbrev-refHEAD;'=== STATUS ===';gitstatus--porcelain|cat;'=== COMMIT MESSAGES ===';gitlog"$b"..HEAD--oneline|cat;'=== CHANGED FILES ===';gitdiff "$b"--name-only|cat;'=== FULL DIFF ===';gitdiff "$b"|cat};$out=r $B|Out-String;$lines=($out-split"`r?`n").Count;if($lines-gt500){$out|Set-Content-NoNewlinecline-git-analysis.temp;'::OUTPUT_FILE=cline-git-analysis.temp'}else{$out}
```
## Step 2: Silent, Structured Analysis Phase
- Analyze all git output without providing commentary or narration
**Important:** All bug reports must be reproducible using Claude 3.5 Sonnet. Cline uses complex prompts so less capable models may not work as expected.
- type:textarea
id:what-happened
attributes:
label:What happened?
description:Also tell us, what did you expect to happen?
placeholder:Tell us what you see!
validations:
required:true
- type:textarea
id:steps
attributes:
label:Steps to reproduce
description:How do you trigger this bug? Please walk us through it step by step.
value:|
1.
2.
3.
validations:
required:true
- type:textarea
id:logs
attributes:
label:Relevant API REQUEST output
description:Please copy and paste any relevant output. This will be automatically formatted into code, so no need for backticks.
render:shell
- type:input
id:provider-model
attributes:
label:Provider/Model
description:What provider and model were you using when the issue occurred?
description:Propose a new feature or improvement, and optionally offer to implement feature as a contributor
labels:["proposal"]
body:
- type:markdown
attributes:
value:|
**Feature Proposal & Contribution for Cline**
Thank you for proposing a feature or improvement for Cline! This template helps us understand the problem, evaluate the solution, and coordinate implementation.
**For detailed proposals:** Please provide comprehensive information to enable fast prioritization and discussion.
**For contribution offers:** You can indicate your willingness to implement the feature yourself.
Before submitting:
- Search existing [Issues](https://github.com/cline/cline/issues) and [Discussions](https://github.com/cline/cline/discussions) to avoid duplicates
- Read the [Contributing Guide](https://github.com/cline/cline/blob/main/CONTRIBUTING.md) if you plan to contribute
- Don't start implementation until the proposal is reviewed and approved
- type:textarea
id:problem-description
attributes:
label:What problem does this solve?
description:|
Describe the problem clearly from a user's point of view. Focus on why this matters, who it affects, and when it occurs.
✅ Good examples:
- "LLM provider returns 400 error when nearing the context window instead of truncating"
- "Submit button is invisible in dark mode"
- "Users can't easily share their Cline configurations with team members"
❌ Avoid vague descriptions:
- "Performance is bad"
- "UI needs work"
Your description should include:
- Who is affected?
- When does it happen?
- What's the current vs expected behavior?
- What is the impact?
placeholder:Be specific about the problem, who it affects, and the impact.
validations:
required:true
- type:textarea
id:proposed-solution
attributes:
label:What's the proposed solution?
description:|
Describe how the problem should be solved. Be specific about UX, system behavior, and any flows that would change.
✅ Good examples:
- "Add error handling immediately after attempting to create the llm stream and retry after manually truncating"
- "Update button styling to ensure contrast in all themes"
- "Add export/import functionality in settings with JSON format"
❌ Avoid vague solutions:
- "Improve performance"
- "Fix the bug"
Your solution should include:
- What exactly will change?
- How will users interact with it?
- What's the expected outcome?
placeholder:Describe the proposed changes and how they solve the problem.
validations:
required:false
- type:dropdown
id:contribution-intent
attributes:
label:Are you interested in implementing this?
description:Let us know if you'd like to contribute to this feature
options:
- "No, just proposing the idea"
- "Yes, I'd like to implement this myself"
- "Yes, I'd like to collaborate with others"
- "Maybe, depending on complexity and guidance"
validations:
required:false
- type:textarea
id:implementation-approach
attributes:
label:Implementation approach (if contributing)
description:|
**Only fill this out if you selected "Yes" above.**
How do you plan to implement this? Include:
- High-level technical approach
- Files/components that would be affected
- Any new dependencies required
- Potential challenges or considerations you've identified
This helps us provide better guidance and ensures alignment before you start coding.
placeholder:"My implementation approach would be..."
- type:checkboxes
id:checklist
attributes:
label:Proposal checklist
options:
- label:I've checked for existing issues or related proposals
required:true
- label:I understand this needs review before implementation can start
required:true
- type:checkboxes
id:contribution-checklist
attributes:
label:Contribution checklist (if contributing)
description:Only check these if you plan to contribute
options:
- label:I've read the [Contributing Guide](https://github.com/cline/cline/blob/main/CONTRIBUTING.md)
- label:I'm willing to make changes based on feedback
- label:I understand the code review process and requirements
⚠️ Important: Before submitting this PR, please ensure you have:
-Opened an issue and discussed your proposed changes with the community / contributors
-Received approval from a core Cline contributor prior to proceeding with the implementation
- Link the associated issue in the "Related Issue" section
-For feature requests: Created a discussion in our Feature Requests discussions board https://github.com/cline/cline/discussions/categories/feature-requests and received approval from core maintainers before implementation
-For all changes: Link the associated issue/discussion in the "Related Issue" section below
Limited exceptions:
Small bug fixes, typo corrections, minor wording improvements, or simple type fixes that don't change functionality may be submitted directly.
Small bug fixes, typo corrections, minor wording improvements, or simple type fixes that don't change functionality may be submitted directly without prior discussion.
Why this requirement?
We deeply appreciate all community contributions - they are the core reason we're able to operate successfully and keep innovating! We welcome community input and want to make it as easy as possible for people to submit quality work. This process helps our core maintainers review new ideas faster and saves contributor time by ensuring you have the go-ahead before spending time on implementation.
We deeply appreciate all community contributions - they are essential to Cline's success! To ensure the best use of everyone's time and maintain project direction, we use our Feature Requests discussions board to gauge community interest and validate feature ideas before implementation begins. This helps us focus development efforts on features that will benefit the most users.
@@ -14,14 +14,11 @@ Bug reports help make Cline better for everyone! Before creating a new issue, pl
## Before Contributing
All contributions must begin with a GitHub Issue, unless the change is for small bug fixes, typo corrections, minor wording improvements, or simple type fixes that don't change functionality.
@@ -30,9 +30,9 @@ English | <a href="https://github.com/cline/cline/blob/main/locales/es/README.md
</table>
</div>
Meet Cline (pronounced /klaɪn/, like "Klein"), an AI assistant that can use your **CLI** a**N**d **E**ditor.
Meet Cline, an AI assistant that can use your **CLI** a**N**d **E**ditor.
Thanks to[Claude 3.7 Sonnet's agentic coding capabilities](https://www.anthropic.com/claude/sonnet),Cline can handle complex software development tasks step-by-step. With tools that let him create & edit files, explore large projects, use the browser, and execute terminal commands (after you grant permission), he can assist you in ways that go beyond code completion or tech support. Cline can even use the Model Context Protocol (MCP) to create new tools and extend his own capabilities. While autonomous AI scripts traditionally run in sandboxed environments, this extension provides a human-in-the-loop GUI to approve every file change and terminal command, providing a safe and accessible way to explore the potential of agentic AI.
Thanks to[Claude Sonnet's agentic coding capabilities](https://www.anthropic.com/claude/sonnet),Cline can handle complex software development tasks step-by-step. With tools that let him create & edit files, explore large projects, use the browser, and execute terminal commands (after you grant permission), he can assist you in ways that go beyond code completion or tech support. Cline can even use the Model Context Protocol (MCP) to create new tools and extend his own capabilities. While autonomous AI scripts traditionally run in sandboxed environments, this extension provides a human-in-the-loop GUI to approve every file change and terminal command, providing a safe and accessible way to explore the potential of agentic AI.
1. Enter your task and add images to convert mockups into functional apps or fix bugs with screenshots.
2. Cline starts by analyzing your file structure & source code ASTs, running regex searches, and reading relevant files to get up to speed in existing projects. By carefully managing what information is added to context, Cline can provide valuable assistance even for large, complex projects without overwhelming the context window.
@@ -87,7 +87,7 @@ All changes made by Cline are recorded in your file's Timeline, providing an eas
### Use the Browser
With Claude 3.5 Sonnet's new [Computer Use](https://www.anthropic.com/news/3-5-models-and-computer-use) capability, Cline can launch a browser, click elements, type text, and scroll, capturing screenshots and console logs at each step. This allows for interactive debugging, end-to-end testing, and even general web use! This gives him autonomy to fixing visual bugs and runtime issues without you needing to handhold and copy-pasting error logs yourself.
With Claude Sonnet's new [Computer Use](https://www.anthropic.com/news/3-5-models-and-computer-use) capability, Cline can launch a browser, click elements, type text, and scroll, capturing screenshots and console logs at each step. This allows for interactive debugging, end-to-end testing, and even general web use! This gives him autonomy to fixing visual bugs and runtime issues without you needing to handhold and copy-pasting error logs yourself.
Try asking Cline to "test the app", and watch as he runs a command like `npm run dev`, launches your locally running dev server in a browser, and performs a series of tests to confirm that everything works. [See a demo here.](https://x.com/sdrzn/status/1850880547825823989)
Cline monitors token usage during your conversation. When you're getting close to the limit, he:
1. Creates a comprehensive summary of everything that's happened
2. Preserves all the technical details, code changes, and decisions
3. Replaces the conversation history with the summary
4. Continues exactly where he left off
You'll see a summarization tool call when this happens, showing the total cost like any other api call in the chat view.
## Why This Matters
Previously, Cline would truncate older messages when hitting context limits. This meant losing important context from earlier in the conversation.
Now with summarization:
- All technical decisions and code patterns are preserved
- File changes and project context remain intact
- Cline remembers everything he's done
- You can work on much larger projects without interruption
<Tip>
Context Summarization synergizes beautifully with [Focus Chain](/features/focus-chain). When Focus Chain is enabled, todo lists persist across summarizations. This means Cline can work on long-horizon tasks that span multiple context windows while staying on track with the todo list guiding him through each reset.
</Tip>
## Technical Details
The summarization happens through your configured API provider using the same model you're already using. It leverages prompt caching to minimize costs.
1. Cline uses a [summarization prompt](https://github.com/cline/cline/blob/main/src/core/prompts/contextManagement.ts) to request a summary of the conversation.
2. Once the summary is generated, Cline replaces the conversation history with a [continuation prompt](https://github.com/cline/cline/blob/main/src/core/prompts/contextManagement.ts#L69) that asks Cline to keep working and provides the summary as context.
Different models have different context window thresholds for when auto-summarization kicks in. You can see how thresholds are determined in [context-window-utils.ts](https://github.com/cline/cline/blob/main/src/core/context/context-management/context-window-utils.ts).
## Cost Considerations
Summarization leverages your existing prompt cache from the conversation, so it costs about the same as any other tool call.
Since most input tokens are already cached, you're primarily paying for the summary generation (output tokens), making it very cost-effective.
## Restoring Context with Checkpoints
You can use [checkpoints](/features/checkpoints) to restore your task state from before a summarization occurred. This means you never truly lose context - you can always roll back to previous versions of your conversation.
<Note>
Editing a message before a summarization tool call will work similarly to a checkpoint, allowing you to restore the conversation to that point.
</Note>
## Next Generation Model Support
Auto Compact uses advanced LLM-based summarization which we've found works significantly better for next-generation models. We currently support this feature for the following models:
- **Claude 4 series**
- **Gemini 2.5 series**
- **GPT-5**
- **Grok 4**
<Note>
When using other models, Cline automatically falls back to the standard rule-based context truncation method, even if Auto Compact is enabled in settings.
@@ -11,7 +11,19 @@ You can create a rule by clicking the `+` button in the Rules tab. This will ope
Once you save the file:
- Your rule will be stored in the `.clinerules/` directory in your project (if it's a Workspace Rule)
- Or in the `Documents/Cline/Rules` directory (if it's a Global Rule).
- Or in the Global Rules directory (if it's a Global Rule):
### Global Rules Directory Location
The location of your Global Rules directory depends on your operating system:
| Operating System | Default Location | Notes |
|------------------|------------------|-------|
| **Windows** | `Documents\Cline\Rules` | Uses system Documents folder |
| **macOS** | `~/Documents/Cline/Rules` | Uses user Documents folder |
| **Linux/WSL** | `~/Documents/Cline/Rules` | May fall back to `~/Cline/Rules` on some systems |
> **Note for Linux/WSL users**: If you don't find your global rules in `~/Documents/Cline/Rules`, check `~/Cline/Rules` as the location may vary depending on your system configuration and whether the Documents directory exists.
You can also have Cline create a rule for you by using the [`/newrule` slash command](/features/slash-commands/new-rule) in the chat.
<Note>Due to VS Code quirks, to drag and drop files into the Cline chat input, you need to hold `Shift` while dragging.</Note>
Dragging and dropping workspace files into Cline will automatically create a [file mention](/features/at-mentions/file-mentions). This allows you to reference the file in your conversation without needing to type out the path.
### Dragging from Finder/File Explorer
You can drag files directly from your system's file manager into Cline:
Focus Chain is a task management enhancement feature in Cline that provides automatic todo list management with real-time progress tracking throughout your tasks.
alt="Focus Chain todo list management with real-time progress tracking"
/>
</Frame>
This enables Cline to work on long-horizon tasks, seamlessly managing the context sent to LLMs, and keeping Cline on track across many context window resets.
<Tip>
Focus Chain works particularly well with Cline's [Deep Planning slash command](/features/slash-commands/deep-planning), providing seamless progress tracking for implementation tasks created through the [planning process](/features/plan-and-act).
</Tip>
## Key Features
### Automatic Todo List Generation
Cline analyzes your task and automatically creates a comprehensive todo list with:
- Clear, actionable items in markdown checklist format
- Logical breakdown of complex tasks into manageable steps
- Real-time updates as work progresses
### User-Editable Todo Lists
Todo lists are stored as editable markdown files:
- Direct editing through your preferred markdown editor
- Automatic detection of changes you make
- Seamless integration back into Cline's workflow
- Quick access through the edit button in the task header
### Visual Progress Tracking
The task header displays clear progress indicators:
- **Step counters** showing current progress (e.g., "3/8")
- **Completed items** clearly marked with checkmarks
- **Current work** highlighted with indicators
- **Expandable view** to see the full todo list
### Smart Reminder System
Configurable reminders ensure todo lists stay current:
- Default reminder every 6 messages (customizable 1-100)
- Automatic prompts when switching from Plan Mode to Act Mode
- User-triggered updates when todo lists are manually edited
`/deep-planning` transforms Cline into a meticulous architect who investigates your codebase, asks clarifying questions, and creates a comprehensive implementation plan before writing a single line of code.
alt="Deep Planning command in action showing investigation and planning process"
/>
</Frame>
When you use `/deep-planning`, Cline follows a four-step process that mirrors how senior developers approach complex features: thorough investigation, discussion & clarification of requirements, detailed planning, and structured task creation with progress tracking.
## The Four-Step Process
### Step 1: Silent Investigation
Cline becomes a detective, silently exploring your codebase to understand its structure, patterns, and constraints. He examines source files, analyzes import patterns, discovers class hierarchies, and identifies technical debt markers. No commentary, no narration - just focused research.
During this phase, Cline runs commands like:
- Finding all class and function definitions across your codebase
- Analyzing import patterns to understand dependencies
- Discovering project structure and file organization
- Identifying TODOs and technical debt
### Step 2: Discussion and Questions
Once Cline understands your codebase, he asks targeted questions that will shape the implementation. These aren't generic questions - they're specific to your project and the feature you're building.
Questions might cover:
- Clarifying ambiguous requirements
- Choosing between equally valid implementation approaches
- Confirming assumptions about system behavior
- Understanding preferences for technical decisions
### Step 3: Implementation Plan Document
Cline creates a structured markdown document (`implementation_plan.md`) that serves as your implementation blueprint. This isn't a vague outline - it's a detailed specification with exact file paths, function signatures, and implementation order.
The plan includes eight comprehensive sections:
- **Overview**: The goal and high-level approach
- **Types**: Complete type definitions and data structures
- **Files**: Exact files to create, modify, or delete
- **Functions**: New and modified functions with signatures
- **Classes**: Class modifications and inheritance details
- **Dependencies**: Package requirements and versions
- **Testing**: Validation strategies and test requirements
Cline creates a new task that references the plan document and includes trackable implementation steps. The task comes with specific commands to read each section of the plan, ensuring the implementing agent (whether that's you or Cline in Act Mode) can navigate the blueprint efficiently.
<Tip>
Deep Planning works beautifully with [Focus Chain](/features/focus-chain). The implementation steps automatically become a todo list with real-time progress tracking, keeping complex projects organized and on track.
</Tip>
## Using Deep Planning
Start a deep planning session by typing `/deep-planning` followed by your feature description:
```
/deep-planning Add user authentication with JWT tokens and role-based access control
```
Cline will begin his investigation immediately. You'll see him reading files and running commands to understand your codebase. Once he's gathered enough context, he'll engage you in discussion before creating the plan.
## Example Workflow
Here's how I use `/deep-planning` for a real feature:
<Steps>
<Step title="Initiate Planning">
I type `/deep-planning implement a caching layer for API responses`
</Step>
<Step title="Silent Investigation">
Cline explores my codebase, examining:
- Current API structure and endpoints
- Existing data flow patterns
- Database queries and performance bottlenecks
- Configuration and environment setup
</Step>
<Step title="Targeted Discussion">
Cline asks me:
- "Should we use Redis or in-memory caching?"
- "What's the acceptable cache staleness for user data?"
- "Do you need cache invalidation webhooks?"
</Step>
<Step title="Plan Creation">
Cline generates `implementation_plan.md` with:
- Cache service class specifications
- Redis connection configuration
- Modified API endpoints with caching logic
- Cache key generation strategies
- TTL configurations for different data types
</Step>
<Step title="Task Generation">
Cline creates a new task with:
- Reference to the implementation plan
- Commands to read specific sections
- Trackable todo items for each implementation step
- Request to switch to Act Mode for execution
</Step>
</Steps>
## Integration with Plan/Act Mode
Deep Planning is designed to work seamlessly with [Plan/Act Mode](/features/plan-and-act):
- Use `/deep-planning` in Plan Mode for the investigation and planning phases
- The generated task requests switching to Act Mode for implementation
- Focus Chain automatically tracks progress through the implementation steps
This separation ensures planning stays focused on architecture while implementation stays focused on execution.
## Best Practices
### When to Use Deep Planning
Use `/deep-planning` for:
- Features touching multiple parts of your codebase
- Refactoring efforts that need systematic execution
- Any feature where you'd normally spend time whiteboarding
### Making the Most of Investigation
Let Cline complete his investigation thoroughly. The quality of the plan directly correlates with how well he understands your codebase. If you have specific areas he should examine, mention them in your initial request.
### Reviewing the Plan
Always review `implementation_plan.md` before starting implementation. The plan is comprehensive but not immutable - you can edit it directly if needed. Think of it as a collaborative document between you and Cline.
### Tracking Progress
With Focus Chain enabled, your implementation progress displays in the task header. Each completed step gets checked off automatically as Cline works through the plan, giving you real-time visibility into complex implementations.
## Inspiration
I use `/deep-planning` whenever I'm about to build something that would normally require a design document. Recent examples from my workflow:
- **Migrating authentication systems**: Deep Planning mapped every endpoint, identified all authentication touchpoints, and created a migration plan that avoided breaking changes.
- **Adding real-time features**: The plan covered WebSocket integration, event handling, state synchronization, and fallback mechanisms for disconnections.
- **Database schema refactoring**: Cline identified all affected queries, created migration scripts, and planned the rollout to minimize downtime.
- **API versioning implementation**: The plan detailed route changes, backward compatibility layers, deprecation notices, and client migration paths.
The power of `/deep-planning` is that it forces thoughtful architecture before implementation. It's like having a senior developer review your approach before you write code, except that developer has perfect knowledge of your entire codebase.
<Note>
Deep Planning requires models with strong reasoning capabilities. It works best with the latest generation of models, like GPT-5, Claude 4, Gemini 2.5, or Grok 4. Smaller models may struggle with the comprehensive analysis required.
</Note>
For simpler tasks that don't require extensive planning, consider using [/newtask](/features/slash-commands/new-task) to create focused tasks with context, or jump straight into implementation if the path forward is clear.
description: "Welcome to Cline, your AI-powered coding companion! This guide will help you quickly set up your development environment and begin your coding journey with ease."
---
> 💡 **Tip:** If you're completely new to coding, take your time with each step. There's no rush — Cline is here to guide you!
> **Tip:** If you're completely new to coding, take your time with each step. There's no rush — Cline is here to guide you!
### 🚀 Getting Started
### Getting Started
Before you jump into coding, make sure you have these essentials ready:
@@ -15,9 +15,9 @@ A popular, free, and powerful code editor.
- [<u>Download VS Code</u>](https://code.visualstudio.com/)
📺 **Recommended YouTube Tutorial:** [<u>How to Install VS Code</u>](https://www.youtube.com/watch?v=MlIzFUI1QGA)
**Recommended YouTube Tutorial:** [<u>How to Install VS Code</u>](https://www.youtube.com/watch?v=MlIzFUI1QGA)
> ✅ **Pro Tip:** Install VS Code in your Applications folder (macOS) or Program Files (Windows) for easy access from your dock or start menu.
> **Pro Tip:** Install VS Code in your Applications folder (macOS) or Program Files (Windows) for easy access from your dock or start menu.
- `Documents/Cline/workout-app` _(e.g., for a fitness tracking app)_
- `Documents/Cline/portfolio-website` _(e.g., to showcase your work)_
> 💡 **Tip:** Keeping your projects organized from the start will save you time and confusion later!
> **Tip:** Keeping your projects organized from the start will save you time and confusion later!
#### 3. **Install the Cline VS Code Extension**
@@ -39,9 +39,9 @@ Enhance your coding workflow by installing the Cline extension directly within V
- Get Started with Cline Extension Tutorial
📺 **Recommended YouTube Tutorial:** [<u>How To Install Extensions in VS Code</u>](https://www.youtube.com/watch?v=E7trgwZa-mk)
**Recommended YouTube Tutorial:** [<u>How To Install Extensions in VS Code</u>](https://www.youtube.com/watch?v=E7trgwZa-mk)
> ✅ **Pro Tip:** After installing, reload VS Code to ensure the extension is activated properly.
> **Pro Tip:** After installing, reload VS Code to ensure the extension is activated properly.
#### 4. **Essential Development Tools**
@@ -51,9 +51,9 @@ Basic software required for coding efficiently:
- Node.js
- Git
👉 [<u>Follow our detailed guide on Installing Essential Development Tools with step-by-step help from Cline.</u>](https://docs.cline.bot/getting-started/installing-dev-essentials#installing-dev-essentials)
[<u>Follow our detailed guide on Installing Essential Development Tools with step-by-step help from Cline.</u>](https://docs.cline.bot/getting-started/installing-dev-essentials#installing-dev-essentials)
📺 **Recommended YouTube Tutorials for Manual Installation:**
**Recommended YouTube Tutorials for Manual Installation:**
- **For macOS:**
- [<u>Install Homebrew on Mac</u>](https://www.youtube.com/watch?v=hwGNgVbqasc)
@@ -63,6 +63,6 @@ Basic software required for coding efficiently:
- [<u>Install Git on Windows 10/11 (2024)</u>](https://www.youtube.com/watch?v=yjxv1HuRQy0)
- [<u>Install Node.js in Windows 10/11</u>](https://www.youtube.com/watch?v=uCgAuOYpJd0)
> ⚠️ **Note:** If you run into permission issues during installation, try running your terminal or command prompt as an administrator.
> **Note:** If you run into permission issues during installation, try running your terminal or command prompt as an administrator.
🎉 You're all set! Dive in and start coding smarter and faster with **Cline**.
You're all set! Dive in and start coding smarter and faster with **Cline**.
style={{ width: "200px", height: "auto", margin: "0 auto 20px auto", display: "block" }}
/>
</Frame>
Cline for JetBrains works almost identically to Cline in VSCode. All the core features work properly: diff editing, using tools, logging in with different providers, MCP servers, Cline rules and workflows, and more.
alt="Cline running in JetBrains IDE showing AI assistance"
/>
</Frame>
<Note>Cline for JetBrains is in early access. All core features are functional, with ongoing improvements based on user feedback.</Note>
## Installation
As part of our early access program, Cline for JetBrains is available through direct download before its official marketplace release. You'll need to install it manually from a downloaded file:
### Manual Installation from Disk
1. **Download the Plugin:**
- Go to [https://plugins.jetbrains.com/plugin/28247-cline/versions/eap](https://plugins.jetbrains.com/plugin/28247-cline/versions/eap)
alt="File selection dialog showing Cline plugin zip file"
/>
</Frame>
- Restart your IDE when prompted
## Getting Started with Cline
After installation, you'll find Cline in your IDE:
1. **Open Cline:**
- Look for the Cline tool window (usually on the right side)
- Or go to **View** → **Tool Windows** → **Cline**
2. **Sign In (optional, BYOK is also available):**
- Click **Sign In** in the Cline panel
- You'll be taken to [app.cline.bot](https://app.cline.bot) to create your account
- No credit card needed to get started with free credits
3. **Start Coding:**
- Try this first prompt: "Hey Cline! Can you help me create a simple Hello World program in this project?"
## Key Differences from VSCode
While Cline for JetBrains includes all the same powerful features, there's one important difference to be aware of:
**Terminal Integration:** The terminal inside JetBrains isn't integrated with Cline the same way it is in VSCode. Cline can execute commands, but the output will only appear in the webview if you expand the **Command Output** section.
This means:
- Commands still run successfully
- You can see the output by clicking to expand Command Output in the chat
- Terminal commands work the same way, just with a different display
## What Works
Everything else works exactly like VSCode:
- **Diff Editing:** Cline can read, write, and edit files with the same precision
- **Tool Usage:** All of Cline's tools (file operations, web browsing, etc.) work identically
- **API Providers:** Connect to Anthropic, OpenAI, local models, and more
- **MCP Servers:** Full support for Model Context Protocol servers
- **Cline Rules:** Custom instructions and workflows work the same way
- **@ Mentions:** Reference files, folders, problems, and more
- **Drag & Drop:** Add files and images to conversations
## Tips for JetBrains Users
- **Project Context:** Cline automatically understands your project structure, just like in VSCode
- **Language Support:** Cline works with any language your JetBrains IDE supports
- **Debugging Help:** Share error messages and stack traces directly in the chat
- **Code Review:** Ask Cline to review your code changes before committing
## Troubleshooting
If you don't see the Cline tool window after installation:
- Restart your IDE completely
- Check **View** → **Tool Windows** → **Cline**
- Ensure the plugin is enabled in **Settings** → **Plugins**
Having other issues? Join our [Discord community](https://discord.gg/cline) for help from the team and other users.
## Next Steps
Now that you have Cline installed, you might want to:
- Learn about [model selection](/getting-started/model-selection-guide) to choose the best AI provider
- Explore [@ mentions](/features/at-mentions/overview) to reference files and context efficiently
- Set up [Cline rules](/features/cline-rules) for your specific workflow
- Try [MCP servers](/mcp/mcp-overview) to extend Cline's capabilities
@@ -9,13 +9,13 @@ description: "Cline is a VS Code extension that brings AI-powered coding assista
- **VS Code Marketplace (Recommended):** Fastest method for standard VS Code and Cursor users.
- **Open VSX Registry:** For VS Code-compatible editors like VSCodium.
### 🛠️ VS Code Marketplace: Step-by-Step Setup
### VS Code Marketplace: Step-by-Step Setup
Follow these steps to get Cline up and running:
1. **Open VS Code:** Launch the VS Code application.
> ⚠️ **Note:** If VS Code shows "Running extensions might...", click "Allow".
> **Note:** If VS Code shows "Running extensions might...", click "Allow".
2. **Open Your Cline Folder:** In VS Code, open the Cline folder you created in Documents.
3. **Navigate to Extensions:** Click on the Extensions icon in the Activity Bar on the side of VS Code (`Ctrl + Shift + X` or `Cmd + Shift + X`).
@@ -34,9 +34,9 @@ Follow these steps to get Cline up and running:
- Or, use the command palette (`Ctrl/Cmd + Shift + P`) and type "Cline: Open In New Tab" for a better view.
3. **Troubleshooting:** If you don't see the Cline icon, try restarting VS Code.
> ✅ **Pro Tip:** You should see the Cline chat window appear in your VS Code editor!
> **Pro Tip:** You should see the Cline chat window appear in your VS Code editor!
### 🌐 Open VSX Registry
### Open VSX Registry
For VS Code-compatible editors without Marketplace access (like VSCodium and Windsurf):
@@ -46,7 +46,7 @@ For VS Code-compatible editors without Marketplace access (like VSCodium and Win
4. Select "Cline" by saoudrizwan and click **Install**.
5. Reload if prompted.
### 👤 Creating Your Cline Account
### Creating Your Cline Account
Now that you have Cline installed, let's get you set up with your account:
@@ -61,7 +61,7 @@ Now that you have Cline installed, let's get you set up with your account:
- Google Gemini 2.0 Flash
- And more — all through your Cline account.
### 💻 Your First Interaction with Cline
### Your First Interaction with Cline
You're ready to start building! Copy and paste this prompt into the Cline chat window:
@@ -69,15 +69,15 @@ You're ready to start building! Copy and paste this prompt into the Cline chat w
Hey Cline! Could you help me create a new project folder called "hello-world" in my Cline directory and make a simple webpage that says "Hello World" in big blue text?
```
> ✅ **Pro Tip:** Cline will help you create the project folder and set up your first webpage!
> **Pro Tip:** Cline will help you create the project folder and set up your first webpage!
### 🧩 Tips for Working with Cline
### Tips for Working with Cline
- **Ask Questions:** If you're unsure about something, ask Cline!
- **Use Screenshots:** Cline can understand images — show him what you're working on.
- **Copy and Paste Errors:** Share error messages in the chat for solutions.
- **Speak Plainly:** Use your own words — Cline will translate them into code.
### 🫂 Still Struggling?
### Still Struggling?
Join our Discord community and engage with our team and other Cline users directly.
Here are the core tools you'll need for development:
@@ -17,9 +17,9 @@ Here are the core tools you'll need for development:
- Chocolatey for Windows
- apt/yum for Linux
> 💡 **Tip:** These tools are the foundation of your developer toolkit. Installing them properly will set you up for success!
> **Tip:** These tools are the foundation of your developer toolkit. Installing them properly will set you up for success!
### 🚀 Let Cline Install Everything
### Let Cline Install Everything
Copy one of these prompts based on your operating system and paste it into **Cline**:
@@ -41,9 +41,9 @@ Hello Cline! I need help setting up my Windows PC for software development. Coul
Hello Cline! I need help setting up my Linux system for software development. Could you please help me install the essential development tools like Node.js, Git, and any other core utilities that are commonly needed for coding? I'd like you to guide me through the process step-by-step.
```
> ✅ **Pro Tip:** Cline will show you each command before running it. You stay in control the entire time!
> **Pro Tip:** Cline will show you each command before running it. You stay in control the entire time!
### 🔍 What Will Happen
### What Will Happen
Cline will guide you through the following steps:
@@ -52,9 +52,9 @@ Cline will guide you through the following steps:
3. Showing you the exact command before it runs (you approve each step!)
4. Verifying each installation is successful
> ⚠️ **Note:** You might need to enter your computer's password for some installations. This is normal!
> **Note:** You might need to enter your computer's password for some installations. This is normal!
### 💡 Why These Tools Are Important
### Why These Tools Are Important
- **Node.js & npm:**
- Build websites with frameworks like React or Next.js
@@ -68,15 +68,15 @@ Cline will guide you through the following steps:
- Quickly install and update development tools
- Keep your environment organized and up to date
### 🧩 Notes
### Notes
> 💡 **Tip:** The installation process is interactive — Cline will guide you step by step!
> **Tip:** The installation process is interactive — Cline will guide you step by step!
- All commands are shown to you for approval before they run.
- If you run into any issues, Cline will help troubleshoot them.
- You may need to enter your computer's password for certain steps.
New models drop constantly, so this guide focuses on what's working well with Cline right now. We'll keep it updated as the landscape shifts.
Think of a context window as your AI assistant's working memory - similar to RAM in a computer. It determines how much information the model can "remember" and process at once during your conversation. This includes:
## Current Top Models
- Your code files and conversations
- The assistant's responses
- Any documentation or additional context provided
| Model | Context Window | Input Price* | Output Price* | Best For |
Context windows are measured in tokens (roughly 3/4 of a word in English). Different models have different context window sizes:
*Per million tokens
- Claude 3.5 Sonnet: 200K tokens
- DeepSeek Models: 128K tokens
- Gemini Flash 2.0: 1M tokens
- Gemini 1.5 Pro: 2M tokens
## Budget Options
When you reach the limit of your context window, older information needs to be removed to make room for new information - just like clearing RAM to run new programs. This is why sometimes AI assistants might seem to "forget" earlier parts of your conversation.
| Gemini 1.5 Pro | $0.00 | $0.00 | 2M | Large context processing |
### Open Source Advantages
- **Multiple providers** compete to host them
- **Cheaper pricing** due to competition
- **Provider choice** - switch if one goes down
- **Faster innovation** cycles
\*Costs per million tokens
### Open Source Models Available
- **Qwen3 Coder** (Apache 2.0)
- **Z AI GLM 4.5** (MIT)
- **Kimi K2** (Open source)
- **DeepSeek series** (Various licenses)
### Top Picks for 2025
## Quick Decision Matrix
1. **Claude 3.5 Sonnet**
- Best overall code implementation
- Most reliable tool usage
- Expensive but worth it for critical code
2. **DeepSeek R1**
- Exceptional planning & reasoning
- Great value pricing
3. **o3-mini**
- Strong for planning with adjustable reasoning
- Three reasoning modes for different needs
- Requires OpenAI Tier 3 API access
- 200K context window
4. **DeepSeek V3**
- Reliable code implementation
- Great for daily coding
- Cost-effective for implementation
5. **Gemini Flash 2.0**
- Massive 1M context window
- Improved speed and performance
- Good all-around capabilities
| If you want... | Use this |
|----------------|----------|
| Something that just works | Claude Sonnet 4 |
| To save money | DeepSeek V3 or Qwen3 variants |
| Huge context windows | Gemini 2.5 Pro or Claude Sonnet 4 |
| Open source | Qwen3 Coder, Z AI GLM 4.5, or Kimi K2 |
| Latest tech | GPT-5 |
| Speed | Qwen3 Coder on Cerebras (fastest available) |
### Best Models by Mode (Plan or Act)
## What Others Are Using
#### Planning
Check [OpenRouter's Cline usage stats](https://openrouter.ai/apps?url=https%3A%2F%2Fcline.bot%2F) to see real usage patterns from the community.
1. **DeepSeek R1**
- Best reasoning capabilities in class
- Excellent at breaking down complex tasks
- Strong math/algorithm planning
- MoE architecture helps with reasoning
2. **o3-mini (high reasoning)**
- Three reasoning levels:
- High: Complex planning
- Medium: Daily tasks
- Low: Quick ideas
- 200K context helps with large projects
3. **Gemini Flash 2.0**
- Massive context window for complex planning
- Strong reasoning capabilities
- Good with multi-step tasks
## Context Management
#### Acting (coding)
Cline automatically handles context limits with [auto-compact](/features/auto-compact). When you approach your model's limit, Cline summarizes the conversation to keep working. You don't need to micromanage this.
1. **Claude 3.5 Sonnet**
- Best code quality
- Most reliable with Cline tools
- Worth the premium for critical code
2. **DeepSeek V3**
- Nearly Sonnet-level code quality
- Better API stability than R1
- Great for daily coding
- Strong tool usage
3. **Gemini 1.5 Pro**
- 2M context window
- Good with complex codebases
- Reliable API
- Strong multi-file understanding
## The Bottom Line
### A Note on Local Models
Start with **Claude Sonnet 4** if you want reliability. Experiment with **open source options** once you're comfortable to find the best fit for your workflow and budget.
While running models locally might seem appealing for cost savings, we currently don't recommend any local models for use with Cline. [Local models are significantly less reliable](https://docs.cline.bot/running-models-locally/read-me-first) at using Cline's essential tools and typically retain only 1-26% of the original model's capabilities. The full cloud version of DeepSeek-R1, for example, is 671B parameters - local versions are drastically simplified copies that struggle with complex tasks and tool usage. Even with high-end hardware (RTX 3070+, 32GB+ RAM), you'll experience slower responses, less reliable tool execution, and reduced capabilities. For the best development experience, we recommend sticking with the cloud models listed above.
### Key Takeaways
1. **Plan vs Act Matters**: Choose models based on task type
2. **Real Performance > Benchmarks**: Focus on actual Cline performance
3. **Mix & Match**: Use different models for planning and implementation
4. **Cost vs Quality**: Premium models worth it for critical code
5. **Keep Backups**: Have alternatives ready for API issues
_\*Note: Based on real usage patterns and community feedback rather than just benchmarks. Your experience may vary. This is not an exhaustive list of all the models available for use within Cline._
The landscape moves fast - these recommendations reflect what's working now, but keep an eye on new releases.
description: "Context is key to getting the most out of Cline"
---
> 💡 **Quick Reference**
> **Quick Reference**
>
> - Context = The information Cline knows about your project
> - Context Window = How much information Cline can hold at once
@@ -38,7 +38,7 @@ Cline actively builds context in two ways:
- Guide focus areas
- Share design thoughts and requirements
💡 **Key Point**: Cline isn't passive - it actively seeks to understand your project. You can either let it explore or guide its focus, especially in [Plan](https://docs.cline.bot/features/plan-and-act) mode.
**Key Point**: Cline isn't passive - it actively seeks to understand your project. You can either let it explore or guide its focus, especially in [Plan Mode](/features/plan-and-act).
### Context & Context Windows
@@ -53,12 +53,13 @@ Think of context like a whiteboard you and Cline share:
- **Context Window** is the size of the whiteboard itself:
- Measured in tokens (1 token ≈ 3/4 of an English word)
- Each model has a fixed size:
- Claude 3.5 Sonnet: 200,000 tokens
- DeepSeek: 64,000 tokens
- When the whiteboard is full, you need to erase (clear context) to write more
- [How Cline manages context under the hood](https://cline.bot/blog/understanding-the-new-context-window-progress-bar-in-cline)
- Claude Sonnet 4: 1,000,000 tokens
- Qwen3 Coder: 256,000 tokens
- Gemini 2.5 Pro: 1,000,000+ tokens
- GPT-5: 400,000 tokens
- When the whiteboard is full, Cline automatically summarizes the conversation to free up space
⚠️ **Important**: Having a large context window (like Claude's 200k tokens) doesn't mean you should fill it completely. Just like a cluttered whiteboard, too much information can make it harder to focus on what's important.
**Important**: Having a large context window doesn't mean you should fill it completely. Models start degrading around 400-500K tokens even if they claim higher limits. Just like a cluttered whiteboard, too much information can make it harder to focus on what's important.
## Understanding the Context Window Progress Bar
@@ -76,7 +77,7 @@ Cline provides a visual way to monitor your context window usage through a progr
- ↑ shows input tokens (what you've sent to the LLM)
- ↓ shows output tokens (what the LLM has generated)
- The progress bar visualizes how much of your context window you've used
- The total shows your model's maximum capacity (e.g., 200k for Claude 3.5-Sonnet)
- The total shows your model's maximum capacity (e.g., 1M for Claude Sonnet 4)
### When to Watch the Bar
@@ -85,7 +86,33 @@ Cline provides a visual way to monitor your context window usage through a progr
- Before starting complex tasks
- When Cline seems to lose context
💡 **Tip**: Consider starting a fresh session when usage reaches 70-80% to maintain optimal performance.
**Tip**: With [Auto Compact](/features/auto-compact), Cline can now handle long conversations automatically. When combined with [Focus Chain](/features/focus-chain), you can work on complex projects that span multiple context windows without losing progress.
## Automatic Context Management
Cline includes intelligent features to manage context automatically:
### Default Settings You Should Keep On
**Focus Chain** - Enabled by default in v3.25. Cline generates a todo list at task start and keeps it in context so the thread doesn't drift. You can edit the markdown to add or reorder steps and Cline will adapt. [Learn more about Focus Chain](/features/focus-chain).
**Auto Compact** - Always on. As the context window reaches its limit, Cline creates a comprehensive summary, replaces the bloated history, and continues where it left off. Decisions, code changes, and state are preserved. [Learn more about Auto Compact](/features/auto-compact).
## Advanced Context Tools
When you need more control over context management:
### Deep Planning (`/deep-planning`)
For substantial features, refactors, or integrations. Cline investigates your codebase, asks targeted questions, then writes `implementation_plan.md`. It creates a fresh task with distilled, high-value context. [Learn more about Deep Planning](/features/slash-commands/deep-planning).
### New Task (`/newtask`)
At natural transition points, packages only what matters into a fresh task. Clean slate for implementation after research, or crisp handoff between teammates. [Learn more about New Task](/features/slash-commands/new-task).
### Smol (`/smol`)
Compress the conversation in place to keep momentum. Ideal during debugging or exploratory work when you don't want to break flow. [Learn more about Smol](/features/slash-commands/smol).
### Memory Bank + .clinerules
For non-trivial projects. The Memory Bank captures project knowledge as Markdown in your repo. `.clinerules` are version-controlled instructions that align Cline's behavior with your team. [Learn more about Memory Bank](/prompting/cline-memory-bank) and [Cline Rules](/features/cline-rules).
## Working with Context Files
@@ -93,12 +120,12 @@ Context files help maintain understanding across sessions. They serve as documen
- Document requirements, constraints, and decisions
@@ -151,9 +178,19 @@ Context files help maintain understanding across sessions. They serve as documen
- Use Plan mode for complex discussions
- Start fresh sessions when needed
3. **Team Projects**
- Share common context files (consider using [.clinerules](https://docs.cline.bot/features/cline-rules) files in project roots)
- Share common context files (consider using [.clinerules](/features/cline-rules) files in project roots)
- Document architectural decisions
- Maintain consistent patterns
- Keep documentation current
Remember: The goal is to help Cline maintain consistent understanding of your project across sessions.
## Bonus Context Tips
- You can @ links and have the webpage's context added to Cline (docs, blogs, etc.)
- Utilize MCP servers to pull in context from your external knowledge bases
- Screenshots can be used as context for models that support image inputs
## The Bottom Line
Cline already does a lot of context work for you - [Focus Chain](/features/focus-chain), [Auto Compact](/features/auto-compact), and the planning flow are designed to keep the thread intact across long horizons. The goal is to help Cline maintain consistent understanding of your project across sessions.
Remember: The goal is to keep only what matters in view, at every step.
description: "An introduction to Cline, your AI-powered development assistant in VS Code."
---
Cline is an AI development assistant which integrates with Microsoft Visual Studio Code. It provides an interface between your IDE and LLMs facilitating code development, increasing productivity and lowering the barrier to entry for new coders. Depending on permissions, Cline can read/write files, execute commands, use your web browser, and expand its capabilities with Model Context Protocol servers.
Cline is an open source AI coding agent that brings frontier AI models directly to your VS Code editor. Unlike autocomplete tools, Cline is a true coding agent that can understand entire codebases, plan complex changes, and execute multi-step tasks.
What makes Cline distinctive is its thoughtful approach to code generation and its extensive integration capabilities. Rather than simply generating code snippets, Cline collaborates with developers by planning solutions step-by-step, maintaining awareness of the entire development environment, and requiring explicit approval for all changes. It can understand large codebases, accelerate onboarding for new engineers, and connect with hundreds of tools through its Model Context Protocol Marketplace, enabling everything from streamlined project deployments to automated incident response—all through natural language commands.
## Open Source AI Coding, Uncompromised
Cline gives you direct, transparent access to frontier AI with no limits, no surprises, and no model ecosystem lock-in. See every decision. Choose any model. Control your costs.
### Complete Transparency
Watch in real-time as Cline reads files, considers approaches, and proposes changes. Every decision is visible, every edit reviewable before it's made. This isn't just "explainable AI" - it's complete transparency.
### Your Models, Your Control
Use Claude for complex reasoning, Gemini for massive contexts, or Qwen3 Coder for efficiency. Switch instantly as new models launch. Your API keys, your choice. No gatekeeping innovation.
### Built for Real Engineering
Cline can:
- **Read and write files** across your entire codebase
- **Execute terminal commands** and debug errors
- **Plan complex features** before writing code
- **Connect to external systems** through MCP servers
- **Understand large codebases** with intelligent context management
## Plan & Act Mode
Cline explores your codebase and works with you to create comprehensive plans before writing a single line of code, ensuring it understands the full context of your project.
**Plan Mode** for complex tasks - Cline explores, asks questions, and creates detailed implementation plans.
**Act Mode** for execution - Cline implements the plan with full transparency and control.
## Zero Trust by Design
Your code never touches our servers. Cline runs entirely client-side with your API keys, making it the only option for enterprises with strict security requirements.
**Open source** means your security team can review every line. See exactly how Cline works, what it sends to AI providers, and how decisions are made.
## Key Features
### Focus Chain
Automatic todo list management with real-time progress tracking throughout your tasks. Keeps Cline on track across long projects.
### Auto Compact
When conversations get long, Cline automatically summarizes to preserve context while freeing up space to continue working.
### Deep Planning
For complex features, Cline investigates your codebase, asks clarifying questions, and creates comprehensive implementation plans.
### MCP Integration
Connect to databases, APIs, and documentation through the Model Context Protocol. Cline becomes your bridge to any external system.
### .clinerules
Define project-specific instructions that Cline follows including coding standards, architecture patterns, or team conventions.
## Why Developers Choose Cline
**100% Open Source** - Every line of code on GitHub. 48k+ stars from developers who've read it, improved it, and trust it with their work.
**No Inference Games** - We don't profit from AI usage. While others limit context or route to cheaper models, we give you unrestricted access to any model's full capabilities.
**Future-Proof by Design** - New model released? Use it immediately. Cline works with any AI provider, any model.
**True Visibility** - See every file read, every decision considered, every token used.
## Getting Started
Ready to experience AI coding without limits? [Install Cline](/getting-started/installing-cline) and start with our [Model Selection Guide](/getting-started/model-selection-guide) to choose the right AI model for your needs.
These directories allow users to sort the servers by various criteria such as downloads, date, stars, and use case. Each entry provides information such as features, tools, and configuration instructions.
To help make Cline better for everyone, we collect anonymous usage data that helps us understand how developers are using our open-source AI coding agent. This feedback loop is crucial for improving Cline's capabilities and user experience.
To help make Cline better for everyone, we collect usage data that helps us understand how developers are using our open-source AI coding agent. This feedback loop is crucial for improving Cline's capabilities and user experience.
We use PostHog, an open-source analytics platform, for data collection and analysis. Our telemetry implementation is fully transparent - you can review the [source code](https://github.com/cline/cline/blob/main/src/services/posthog/telemetry/TelemetryService.ts) to see exactly what we track.
### Tracking Policy
Privacy is our priority. All collected data is anonymized before being sent to PostHog, with no personally identifiable information (PII) included. Your code, prompts, and conversation content always remain private and are never collected.
Privacy is our priority. By default, all collected data is anonymized. If you log in with a Cline account, your telemetry data will be associated with your account to help us improve the product and provide better support when you encounter issues. Your code, prompts, and conversation content always remain private and are never collected.
### What We Track
We collect basic anonymous usage data including:
We collect basic usage data including:
**Task Interactions:** When tasks start and finish, conversation flow (without content)\
**Mode and Tool Usage:** Switches between plan/act modes, which tools are being used\
@@ -28,7 +28,7 @@ For complete transparency, you can inspect our [telemetry implementation](https:
Telemetry in Cline is entirely optional:
- When you update or install our VS Code extension, you'll see a message about our anonymous telemetry
- When you update or install our VS Code extension, you'll see a message about our telemetry
- You can change your preference anytime in settings
Cline also respects VS Code's global telemetry settings. If you've disabled telemetry at the VS Code level, Cline's telemetry will automatically be disabled as well.
description: "Learn how to set up AWS Bedrock with Cline using credentials authentication. This guide covers AWS environment setup, regional access verification, and secure integration with the Cline VS Code extension."
title: "API Key (Simple Setup)"
sidebarTitle: "API Key"
description: "Set up AWS Bedrock with Cline using Bedrock API Keys. Simplest setup for individual developers to access frontier models."
---
### Overview
@@ -121,14 +122,14 @@ You can create a custom IAM policy with these permissions and attach it to your
### Conclusion
By following these steps, your enterprise team can securely integrate AWS Bedrock with the Cline VS Code extension to accelerate development:
By following these steps, you can quickly integrate AWS Bedrock with the Cline VS Code extension to accelerate development:
1. **Prepare Your AWS Environment:** Create or use a secure IAM role/user, attach the `AmazonBedrockLimitedAccess` policy, and ensure necessary permissions.
1. **Prepare Your AWS Environment:** Create a Bedrock API Key with the necessary permissions.
2. **Verify Region and Model Access:** Confirm that your selected region supports your required models.
3. **Configure Cline in VS Code:** Install and set up Cline with your AWS credentials and choose an appropriate model.
3. **Configure Cline in VS Code:** Install and set up Cline with your AWS API Key and choose an appropriate model.
4. **Implement Security and Monitoring:** Use best practices for IAM, network security, monitoring, and cost management.
For further details, consult the [AWS Bedrock Documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html) and coordinate with your internal cloud team. Happy coding!
For further details, consult the [AWS Bedrock Documentation](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html). Happy coding!
description: "Learn how to configure AWS Bedrock to use AWS Profiles for authentication with Cline, focusing on SSO/Federated roles for secure access."
title: "CLI Profile (SSO)"
sidebarTitle: "CLI Profile (SSO)"
description: "Configure AWS Bedrock to use AWS CLI profiles for authentication with Cline. Best for SSO/federated roles and secure enterprise access."
description: "Learn how to set up AWS Bedrock with Cline using credentials authentication. This guide covers AWS environment setup, regional access verification, and secure integration with the Cline VS Code extension."
title: "IAM Credentials"
sidebarTitle: "IAM Credentials"
description: "Set up AWS Bedrock with Cline using IAM Access Key and Secret Key credentials. Best for enterprise environments with established IAM policies."
description: "Learn how to configure and use Cerebras's ultra-fast inference with Cline. Experience up to 2,600 tokens per second with wafer-scale chip architecture and real-time reasoning models."
---
Cerebras delivers the world's fastest AI inference through their revolutionary wafer-scale chip architecture. Unlike traditional GPUs that shuttle model weights from external memory, Cerebras stores entire models on-chip, eliminating bandwidth bottlenecks and achieving speeds up to 2,600 tokens per second—often 20x faster than GPUs.
1. **Sign Up/Sign In:** Go to [Cerebras Cloud](https://cloud.cerebras.ai/) and create an account or sign in.
2. **Navigate to API Keys:** Access the API keys section in your dashboard.
3. **Create a Key:** Generate a new API key. Give it a descriptive name (e.g., "Cline").
4. **Copy the Key:** Copy the API key immediately. Store it securely.
### Supported Models
Cline supports the following Cerebras models:
- `qwen-3-coder-480b-free` (Free tier) - High-performance coding model at no cost
- `qwen-3-coder-480b` - Flagship 480B parameter coding model
- `qwen-3-235b-a22b-instruct-2507` - Advanced instruction-following model
- `qwen-3-235b-a22b-thinking-2507` - Reasoning model with step-by-step thinking
- `llama-3.3-70b` - Meta's Llama 3.3 model optimized for speed
- `qwen-3-32b` - Compact yet powerful model for general tasks
### Configuration in Cline
1. **Open Cline Settings:** Click the settings icon (⚙️) in the Cline panel.
2. **Select Provider:** Choose "Cerebras" from the "API Provider" dropdown.
3. **Enter API Key:** Paste your Cerebras API key into the "Cerebras API Key" field.
4. **Select Model:** Choose your desired model from the "Model" dropdown.
5. **(Optional) Custom Base URL:** Most users won't need to adjust this setting.
### Cerebras's Wafer-Scale Advantage
Cerebras has fundamentally reimagined AI hardware architecture to solve the inference speed problem:
#### Wafer-Scale Architecture
Traditional GPUs use separate chips for compute and memory, forcing them to constantly shuttle model weights back and forth. Cerebras built the world's largest AI chip—a wafer-scale engine that stores entire models on-chip. No external memory, no bandwidth bottlenecks, no waiting.
#### Revolutionary Speed
- **Up to 2,600 tokens per second** - often 20x faster than GPUs
- **Single-second reasoning** - what used to take minutes now happens instantly
- **Real-time applications** - reasoning models become practical for interactive use
Cerebras discovered that **faster inference enables smarter AI**. Modern reasoning models generate thousands of tokens as "internal monologue" before answering. On traditional hardware, this takes too long for real-time use. Cerebras makes reasoning models fast enough for everyday applications.
#### Quality Without Compromise
Unlike other speed optimizations that sacrifice accuracy, Cerebras maintains full model quality while delivering unprecedented speed. You get the intelligence of frontier models with the responsiveness of lightweight ones.
Learn more about Cerebras's technology in their blog posts:
- [The Cerebras Scaling Law: Faster Inference Is Smarter AI](https://www.cerebras.ai/blog/the-cerebras-scaling-law-faster-inference-is-smarter-ai)
- Access to Qwen3-Coder with fast, high-context completions
- Up to 24 million tokens per day
- Ideal for indie developers and weekend projects
- 3-4 hours of uninterrupted coding per day
#### Code Max ($200/month)
- Heavy coding workflow support
- Up to 120 million tokens per day
- Perfect for full-time development and multi-agent systems
- No weekly limits, no IDE lock-in
### Special Features
#### Free Tier
The `qwen-3-coder-480b-free` model provides access to high-performance inference at no cost—unique among speed-focused providers.
#### Real-Time Reasoning
Reasoning models like `qwen-3-235b-a22b-thinking-2507` can complete complex multi-step reasoning in under a second, making them practical for interactive development workflows.
#### Coding Specialization
Qwen3-Coder models are specifically optimized for programming tasks, delivering performance comparable to Claude Sonnet 4 and GPT-4.1 in coding benchmarks.
#### No IDE Lock-In
Works with any OpenAI-compatible tool—Cursor, Continue.dev, Cline, or any other editor that supports OpenAI endpoints.
### Tips and Notes
- **Speed Advantage:** Cerebras excels at making reasoning models practical for real-time use. Perfect for agentic workflows that require multiple LLM calls.
- **Free Tier:** Start with the free model to experience Cerebras speed before upgrading to paid plans.
- **Context Windows:** Models support context windows ranging from 64K to 128K tokens for including substantial code context.
- **Rate Limits:** Generous rate limits designed for development workflows. Check your dashboard for current limits.
- **Pricing:** Competitive pricing with significant speed advantages. Visit [Cerebras Cloud](https://cloud.cerebras.ai/) for current rates.
- **Real-Time Applications:** Ideal for applications where AI response time matters—code generation, debugging, and interactive development.
@@ -35,26 +35,8 @@ First, you'll need to install and authenticate Claude Code on your system:
<br />
<Accordion title="Windows Setup">
On Windows, Cline supports integrating with Claude Code through WSL.
Windows doesn't support long commands, and Claude Code only accepts the system prompt through a flag, which means we can't properly prompt Claude through Claude Code. Anthropic is [working on a workaround to streamline this](https://github.com/anthropics/claude-code/issues/3411).
1. **Make sure you have WSL set-up**. You can follow [this](https://code.visualstudio.com/docs/remote/wsl#_installation) guide to do it.
2. **Open VSCode from WSL** and verify it's properly set-up. You should see an indicator in the bottom left that says "WSL". You can find an image of the indicator [here](https://code.visualstudio.com/docs/remote/wsl#_from-the-wsl-terminal).
3. Install Cline within WSL and make sure it shows the following:
description: "Learn how to configure and use ByteDance's Doubao AI models with Cline. Experience advanced reasoning, multimodal capabilities, and cost-effective inference with Chinese language optimization."
---
Doubao is ByteDance's flagship AI model series, featuring innovative sparse Mixture-of-Experts (MoE) architecture that delivers performance equivalent to much larger models while maintaining cost efficiency. With over 13 million users and advanced multimodal capabilities, Doubao offers competitive alternatives to Western AI systems with particular strength in Chinese language processing.
1. **Sign Up/Sign In:** Visit the [Volcano Engine Console](https://console.volcengine.com/). Create an account or sign in.
2. **Navigate to Model Service:** Access the AI model service section in the console.
3. **Create API Key:** Generate a new API key for the Doubao service.
4. **Copy the Key:** Copy the API key immediately and store it securely. You may not be able to view it again.
### Supported Models
Cline supports the following Doubao models:
- `doubao-seed-1-6-250615` (Default) - General purpose model with balanced performance
- `doubao-seed-1-6-thinking-250715` - Enhanced reasoning model with step-by-step thinking
- `doubao-seed-1-6-flash-250715` - Speed-optimized model for fast inference
All models feature:
- **128,000 token context window** for extensive document processing
- **32,768 max output tokens** for comprehensive responses
- **Image input support** for multimodal applications
- **Prompt caching** with 80% discount on cached reads
### Configuration in Cline
1. **Open Cline Settings:** Click the settings icon (⚙️) in the Cline panel.
2. **Select Provider:** Choose "Doubao" from the "API Provider" dropdown.
3. **Enter API Key:** Paste your Doubao API key into the "Doubao API Key" field.
4. **Select Model:** Choose your desired model from the "Model" dropdown.
**Note:** Doubao uses the base URL `https://ark.cn-beijing.volces.com/api/v3` and servers are located in Beijing, China.
### ByteDance's AI Innovation
Doubao represents ByteDance's strategic entry into the AI model space with several key innovations:
#### Sparse Mixture-of-Experts Architecture
Doubao 1.5 Pro employs an innovative sparse MoE framework where 20 billion activated parameters deliver performance equivalent to a 140-billion-parameter dense model. This architecture significantly reduces operational costs while maintaining high performance standards.
#### Extended Context Processing
With context windows ranging from 32,000 to 256,000 tokens, Doubao excels at processing long-form content including legal documents, academic research, market reports, and creative content generation.
#### Multimodal Excellence
- **Advanced Visual Processing:** Enhanced visual reasoning, document recognition, and fine-grained information understanding
- **Integrated Speech:** Seamless speech and text token integration with superior emotional continuity
- **Document Analysis:** Comprehensive document summarization and content processing capabilities
#### Chinese Language Optimization
Doubao was specifically trained for Chinese language fluency and cultural relevance, providing significant advantages for Chinese-speaking users and applications requiring deep cultural context understanding.
#### Cost Efficiency
Doubao maintains pricing approximately **half the cost of comparable OpenAI offerings**, making advanced AI more accessible while establishing competitive market positioning.
### Special Features
#### Reasoning Models
The `doubao-seed-1-6-thinking-250715` model offers enhanced reasoning capabilities with step-by-step thinking processes, making it ideal for complex problem-solving tasks.
#### Multimodal Capabilities
Unlike traditional cascaded approaches, Doubao integrates speech and text processing seamlessly, enabling more natural voice interactions and comprehensive document analysis.
#### Prompt Caching
All models support prompt caching with significant cost savings (80% discount on cached reads), making repeated queries more economical.
#### ByteDance Ecosystem Integration
Doubao integrates vertically with ByteDance properties including TikTok (Douyin), Toutiao, and Feishu, enabling seamless workflow integration across the ecosystem.
### Performance and Benchmarks
Doubao-1.5 Pro-AS1 Preview has demonstrated superior performance compared to OpenAI's O1-preview on specific benchmarks, including surpassing O1 models on AIME tests. The model continues to improve through reinforcement learning, with performance expected to enhance over time.
### Tips and Notes
- **Regional Advantage:** Optimized for Chinese language and cultural contexts, making it ideal for Chinese-speaking users and markets.
- **Cost Effectiveness:** Approximately 50% lower cost than comparable Western AI models while maintaining competitive performance.
- **Context Windows:** Large context windows (up to 256K tokens) enable processing of extensive documents and codebases.
- **Multimodal Applications:** Strong visual and speech processing capabilities make it suitable for diverse multimedia applications.
- **Server Location:** Servers located in Beijing, China - consider latency implications for global users.
- **Ecosystem Benefits:** Integration with ByteDance services provides additional workflow advantages for users of TikTok, Toutiao, and Feishu.
- **Pricing:** Check the Volcano Engine console for current pricing information and regional availability.
description: "Learn how to configure and use Fireworks AI models with Cline. Access high-performance open-source language models with fast, cost-effective APIs."
---
Cline supports accessing models through the Fireworks AI platform, which offers fast, cost-effective access to a wide range of state-of-the-art open-source language models. Built for speed and reliability, Fireworks AI provides serverless deployment options with OpenAI-compatible APIs and context windows up to 256,000 tokens.
description: "Learn how to configure and use Fireworks AI's lightning-fast inference platform with Cline. Experience up to 4x faster inference speeds with optimized models and competitive pricing."
---
Fireworks AI is a leading infrastructure platform for generative AI that focuses on delivering exceptional performance through optimized inference capabilities. With up to 4x faster inference speeds than alternative platforms and support for over 40 different AI models, Fireworks eliminates the operational complexity of running AI models at scale.
- **Pay-per-GPU-second billing** with no extra charges for start-up times
- **OpenAI API compatibility** for seamless integration
### Pricing Structure
Fireworks AI uses a usage-based pricing model with competitive rates:
#### Text and Vision Models (2025)
| Parameter Count | Price per 1M Input Tokens |
|---|---|
| Less than 4B parameters | $0.10 |
| 4B - 16B parameters | $0.20 |
| More than 16B parameters | $0.90 |
| MoE 0B - 56B parameters | $0.50 |
#### Fine-Tuning Services
| Base Model Size | Price per 1M Training Tokens |
|---|---|
| Up to 16B parameters | $0.50 |
| 16.1B - 80B parameters | $3.00 |
| DeepSeek R1 / V3 | $10.00 |
#### Dedicated Deployments
| GPU Type | Price per Hour |
|---|---|
| A100 80GB | $2.90 |
| H100 80GB | $5.80 |
| H200 141GB | $6.99 |
| B200 180GB | $11.99 |
| AMD MI300X | $4.99 |
### Special Features
#### Fine-Tuning Capabilities
Fireworks offers sophisticated fine-tuning services accessible through CLI interface, supporting JSON-formatted data from databases like MongoDB Atlas. Fine-tuned models cost the same as base models for inference.
#### Developer Experience
- **Browser playground** for direct model interaction
- **REST API** with OpenAI compatibility
- **Comprehensive cookbook** with ready-to-use recipes
- **Multiple deployment options** from serverless to dedicated GPUs
#### Enterprise Features
- **HIPAA and SOC 2 Type II compliance** for regulated industries
- **Self-serve onboarding** for developers
- **Enterprise sales** for larger deployments
- **Post-paid billing options** and Business tier
#### Reasoning Model Support
Advanced support for reasoning models with `<think>` tag processing and reasoning content extraction, making complex multi-step reasoning practical for real-time applications.
description: "Learn how to configure and use Groq's lightning-fast inference with Cline. Access models from OpenAI, Meta, DeepSeek, and more on Groq's purpose-built LPU architecture."
---
Groq provides ultra-fast AI inference through their custom LPU™ (Language Processing Unit) architecture, purpose-built for inference rather than adapted from training hardware. Groq hosts open-source models from various providers including OpenAI, Meta, DeepSeek, Moonshot AI, and others.
1. **Open Cline Settings:** Click the settings icon (⚙️) in the Cline panel.
2. **Select Provider:** Choose "Groq" from the "API Provider" dropdown.
3. **Enter API Key:** Paste your Groq API key into the "Groq API Key" field.
4. **Select Model:** Choose your desired model from the "Model" dropdown.
### Groq's Speed Revolution
Groq's LPU architecture delivers several key advantages over traditional GPU-based inference:
#### LPU Architecture
Unlike GPUs that are adapted from training workloads, Groq's LPU is purpose-built for inference. This eliminates architectural bottlenecks that create latency in traditional systems.
#### Unmatched Speed
- **Sub-millisecond latency** that stays consistent across traffic, regions, and workloads
@@ -10,7 +10,7 @@ Cline supports accessing models through the [Requesty](https://www.requesty.ai/)
### Getting an API Key
1. **Sign Up/Sign In:** Go to the [Requesty website](https://www.requesty.ai/) and create an account or sign in.
2. **Get API Key:** You can get an API key from the [API Management](https://app.requesty.ai/manage-api) section of your Requesty dashboard.
2. **Get API Key:** You can get an API key from the [API Management](https://app.requesty.ai/api-keys) section of your Requesty dashboard.
### Supported Models
@@ -26,7 +26,7 @@ Requesty provides access to a wide range of models. Cline will automatically fet
### Tips and Notes
- **Optimizations**: Requesty offers a range of in-flight cost optimizations to lower your costs.
- **Unified and simplified billing**: Unrestricted access to all providers and models, automatic balance top ups and more via a single [API key](https://app.requesty.ai/manage-api).
- **Unified and simplified billing**: Unrestricted access to all providers and models, automatic balance top ups and more via a single [API key](https://app.requesty.ai/api-keys).
- **Cost tracking**: Track cost per model, coding language, changed file, and more via the [Cost dashboard](https://app.requesty.ai/cost-management) or the [Requesty VS Code extension](https://marketplace.visualstudio.com/items?itemName=Requesty.requesty).
- **Stats and logs**: See your [coding stats dashboard](https://app.requesty.ai/usage-stats) or go through your [LLM interaction logs](https://app.requesty.ai/logs).
- **Fallback policies**: Keep your LLM working for you with fallback policies when providers are down.
description: "Learn how to configure and use LLM models from Generative AI Hub in SAP AI Core with Cline."
---
SAP AI Core and the generative AI hub help you to integrate LLMs and AI into new business processes in a cost-efficient manner.
**Website:** [SAP Help Portal](https://help.sap.com/docs/sap-ai-core/sap-ai-core-service-guide/what-is-sap-ai-core)
> 💡 **Information**
>
> SAP AI Core, and Generative AI Hub, are offerings from SAP BTP.
> You need an active SAP BTP contract and a existing subaccount with a SAP AI Core instance with the `extended` service plan (For more details about SAP AI Core service plans and their capabilities, see the [Service Plans documentation](https://help.sap.com/docs/sap-ai-core/sap-ai-core-service-guide/service-plans)) to perform these steps.
### Getting a Service Binding
1. **Access:** Go to your subaccount via [BTP Cloud Cockpit](cockpit.btp.cloud.sap/cockpit)
2. **Create a Service Binding:** Go to "Instances and Subscriptions", select your SAP AI Core service instance and click on Service Bindings > Create.
3. **Copy the Service Binding:** Copy the service binding values.
### Supported Models
SAP AI Core supports a large and growing number of models.
Refer to the [Generative AI Hub Supported Models page](https://me.sap.com/notes/3437766) for the complete and up-to-date list.
### Configuration in Cline
1. **Open Cline Settings:** Click the settings icon (⚙️) in the Cline panel.
2. **Select Provider:** Choose "SAP AI Core" from the "API Provider" dropdown.
3. **Enter Client Id:** Add the `.clientid` field from the service binding into the "AI Core Client Id" field.
4. **Enter Client Secret:** Add the `.clientsecret` field from the service binding into the "AI Core Client Secret" field.
5. **Enter Base URL:** Add the `.serviceurls.AI_API_URL` field from the service binding into the "AI Core Base URL" field.
6. **Enter Auth URL:** Add the `.url` field from the service binding into the "AI Core Auth URL" field.
7. **Enter Resource Group:** Add the resource group where you have your model deployments. See [Create a Deployment for a Generative AI Model](https://help.sap.com/docs/sap-ai-core/sap-ai-core-service-guide/create-deployment-for-generative-ai-model-in-sap-ai-core).
8. **Configure Orchestration Mode:** If you have an `extended` service plan, the "Orchestration Mode" checkbox will automatically appear.
9. **Select Model:** Choose your desired model from the "Model" dropdown.
### Orchestration Mode vs Native API
**Orchestration Mode:**
- **Simplified usage:** Provides access to all available models without requiring individual deployments using the [Harmonized API](https://help.sap.com/docs/sap-ai-core/sap-ai-core-service-guide/harmonized-api)
**Native API Mode:**
- **Manual deployments:** Requires manual model deployment and management in your SAP AI Core service instance
### Tips and Notes
- **Service Plan Requirement:** You must have the SAP AI Core `extended` service plan to use LLMs with Cline. Other service plans do not provide access to Generative AI Hub.
- **Orchestration Mode (Recommended):** Keep Orchestration Mode enabled for the simplest setup. It provides automatic access to all available models without requiring manual deployments.
- **Native API Mode:** Only disable Orchestration Mode if you have specific requirements that necessitate direct AI Core API access or need features not supported by the orchestration mode.
- **When using Native API Mode:**
- **Model Selection:** The model dropdown displays models in two separate lists:
- **Deployed Models:** These models are already deployed in your specified resource group and are ready to use immediately.
- **Not Deployed Models:** These models don't have active deployments in your specified resource group. You won't be able to use these models until you create deployments for them in SAP AI Core.
- **Creating Deployments:** To use a model that has not been deployed yet, you'll need to create a deployment in your SAP AI Core service instance. See [Create a Deployment for a Generative AI Model](https://help.sap.com/docs/sap-ai-core/sap-ai-core-service-guide/create-deployment-for-generative-ai-model-in-sap-ai-core) for instructions.
#### Configuring Reasoning Effort for OpenAI Models
When using OpenAI reasoning models (such as o1, o3, o3-mini, o4-mini) through SAP AI Core, you can control the reasoning effort to balance performance and cost:
1. **Open Cline Settings:** Click the settings icon (⚙️) in the Cline panel.
2. **Navigate to Features:** Go to the "Features" section in the settings.
- **Low:** Faster responses with lower token usage, suitable for simpler tasks
- **Medium:** Balanced performance and token usage for most tasks
- **High:** More thorough analysis with higher token usage, better for complex reasoning tasks
> 💡 **Note**
>
> This setting only applies when using OpenAI reasoning models (o1, o3, o3-mini, o4-mini, gpt-5, etc.) deployed through SAP AI Core. Other models will ignore this setting.
description: "Use Vercel AI Gateway in Cline to reach 100+ models from one endpoint with routing, retries, and spend observability."
---
Vercel AI Gateway gives you a single API to access models from many providers. You switch by model id without swapping SDKs or juggling multiple keys. Cline integrates directly so you can pick a Gateway model in the dropdown, use it like any other provider, and see token and cache usage in the stream.
Useful links:
- Team dashboard: https://vercel.com/d?to=%2F%5Bteam%5D%2F%7E%2Fai
- Automatic retries and fallbacks that you configure on the dashboard
- Spend monitoring with requests by model, token counts, cache usage, latency percentiles, and cost
- OpenAI-compatible surface so existing clients work
## Getting an API Key
1. Sign in at https://vercel.com
2. Dashboard → AI Gateway → API Keys → Create key
3. Copy the key
For more on authentication and OIDC options, see https://vercel.com/docs/ai-gateway/authentication
## Configuration in Cline
1. Open Cline settings
2. Select **Vercel AI Gateway** as the API Provider
3. Paste your Gateway API Key
4. Pick a model from the list. Cline fetches the catalog automatically. You can also paste an exact id
Notes:
- Model ids often follow `provider/model`. Copy the exact id from the catalog
Examples:
- `openai/gpt-5`
- `anthropic/claude-sonnet-4`
- `google/gemini-2.5-pro`
- `groq/llama-3.1-70b`
- `deepseek/deepseek-v3`
## Observability you can act on
<Frame>
<img src="https://assets.vercel.com/image/upload/v1753121283/gateway-overhead-dark_zhqwwj.svg" alt="Vercel AI Gateway observability with requests by model, tokens, cache, latency, and cost." />
</Frame>
What to watch:
- Requests by model - confirm routing and adoption
- Tokens - input vs output, including reasoning if exposed
- Cache - cached input and cache creation tokens
- Latency - p75 duration and p75 time to first token
- Cost - per project and per model
Use it to:
- Compare output tokens per request before and after a model change
- Validate cache strategy by tracking cache reads and write creation
- Catch TTFT regressions during experiments
- Align budgets with real usage
## Supported models
The gateway supports a large and changing set of models. Cline pulls the list from the Gateway API and caches it locally. For the current catalog, see https://vercel.com/ai-gateway/models
## Tips
<Tip>
Use separate gateway keys per environment (dev, staging, prod). It keeps dashboards clean and budgets isolated.
</Tip>
<Note>
Pricing is pass-through at provider list price. Bring-your-own key has 0% markup. You still pay provider and processing fees.
</Note>
<Info>
Vercel does not add rate limits. Upstream providers may. New accounts receive $5 credits every 30 days until the first payment.
</Info>
## Troubleshooting
- 401 - send the Gateway key to the Gateway endpoint, not an upstream URL
- 404 model - copy the exact id from the Vercel catalog
- Slow first token - check p75 TTFT in the dashboard and try a model optimized for streaming
- Cost spikes - break down by model in the dashboard and cap or route traffic
## Inspiration
- Multi-model evals - swap only the model id in Cline and compare latency and output tokens
- Progressive rollout - route a small percent to a new model in the dashboard and ramp with metrics
- Budget enforcement - set per-project limits without code changes
description: "Learn how to configure and use Z AI's GLM-4.5 models with Cline. Experience advanced hybrid reasoning, agentic capabilities, and open-source excellence with regional optimization."
---
Z AI (formerly Zhipu AI) offers the groundbreaking GLM-4.5 series, featuring hybrid reasoning capabilities and agentic AI design. Released in July 2025, these models excel in unified reasoning, coding, and intelligent agent applications while maintaining open-source accessibility under MIT license.
This dual-mode architecture represents an "agent-native" design philosophy that adapts processing intensity based on query complexity.
#### Exceptional Performance
GLM-4.5 achieves a comprehensive score of **63.2** across 12 benchmarks spanning agentic tasks, reasoning, and coding challenges, securing **3rd place** among all proprietary and open-source models. GLM-4.5-Air maintains competitive performance with a score of **59.8** while delivering superior efficiency.
#### Mixture of Experts Excellence
The sophisticated MoE architecture optimizes performance while maintaining computational efficiency:
- **GLM-4.5:** 355B total parameters with 32B active parameters
- **GLM-4.5-Air:** 106B total parameters with 12B active parameters
#### Extended Context Capabilities
The 128,000-token context window enables comprehensive understanding of lengthy documents and codebases, with real-world testing confirming effective processing of nearly 2,000-line codebases while maintaining remarkable performance.
#### Open-Source Leadership
Released under MIT license, GLM-4.5 provides researchers and developers with access to state-of-the-art capabilities without proprietary restrictions, including base models, hybrid reasoning versions, and optimized FP8 variants.
The region setting determines both API endpoint and available models, with automatic filtering to ensure compatibility with your selected region.
### Special Features
#### Agentic Capabilities
GLM-4.5's unified architecture makes it particularly suitable for complex intelligent agent applications requiring integrated reasoning, coding, and tool utilization capabilities.
#### Comprehensive Benchmarking
Performance evaluation encompasses:
- **3 agentic task benchmarks**
- **7 reasoning benchmarks**
- **2 coding benchmarks**
This comprehensive assessment demonstrates versatility across diverse AI applications.
#### Developer Integration
Models support integration through multiple frameworks:
- **transformers**
- **vLLM**
- **SGLang**
Complete with dedicated model code, tool parser, and reasoning parser implementations.
### Performance Comparisons
#### vs Claude 4 Sonnet
GLM-4.5 shows competitive performance in agentic coding and reasoning tasks, though Claude Sonnet 4 maintains advantages in coding success rates and autonomous multi-feature application development.
#### vs GPT-4.5
GLM-4.5 ranks competitively in reasoning and agent benchmarks, with GPT-4.5 generally leading in raw task accuracy on professional benchmarks like MMLU and AIME.
### Tips and Notes
- **Region Selection:** Choose the appropriate region for optimal performance and compliance with local regulations.
- **Model Selection:** GLM-4.5 for maximum performance, GLM-4.5-Air for efficiency and mainstream hardware compatibility.
- **Context Advantage:** Large 128K context window enables processing of substantial codebases and documents.
- **Open Source Benefits:** MIT license enables both commercial use and secondary development.
- **Agentic Applications:** Particularly strong for applications requiring reasoning, coding, and tool usage integration.
- **Hybrid Reasoning:** Use Thinking Mode for complex problems, Non-Thinking Mode for simple queries.
- **API Compatibility:** OpenAI-compatible API provides streaming responses and usage reporting.
- **Framework Support:** Multiple integration options available for different deployment scenarios.
If you're using Windows and still experiencing issues with shell integration after trying the previous steps, it's recommended you use Git Bash (or PowerShell).
If commands fail silently:
### Git Bash
Git Bash is a terminal emulator that provides a Unix-like command line experience on Windows. To use Git Bash, you need to:
1. Download and run the Git for Windows installer from [https://git-scm.com/downloads/win](https://git-scm.com/downloads/win)
2. Quit and re-open VSCode
3. Press `Ctrl + Shift + P` to open the Command Palette
4. Type "Terminal: Select Default Profile" and choose it
5. Select "Git Bash"
### PowerShell
If you'd still like to use PowerShell, make sure you're using an updated version (at least v7+).
- Check your current PowerShell version by running: `$PSVersionTable.PSVersion`
- If your version is below 7, [update PowerShell](https://learn.microsoft.com/en-us/powershell/scripting/whats-new/migrating-from-windows-powershell-51-to-powershell-7?view=powershell-7.4#installing-powershell-7).
You may also need to adjust your PowerShell execution policy. By default, PowerShell restricts script execution for security reasons.
#### Understanding PowerShell Execution Policies
PowerShell uses execution policies to determine which scripts can run on your system. Here are the most common policies:
- `Restricted`: No PowerShell scripts can run. This is the default setting.
- `AllSigned`: All scripts, including local ones, must be signed by a trusted publisher.
- `RemoteSigned`: Scripts created locally can run, but scripts downloaded from the internet must be signed.
- `Unrestricted`: No restrictions. Any script can run, though you will be warned before running internet-downloaded scripts.
For development work in VSCode, the `RemoteSigned` policy is generally recommended. It allows locally created scripts to run without restrictions while maintaining security for downloaded scripts. To learn more about PowerShell execution policies and understand the security implications of changing them, visit Microsoft's documentation: [About Execution Policies](https://learn.microsoft.com/en-us/powershell/module/microsoft.powershell.core/about/about_execution_policies).
#### Steps to Change the Execution Policy
1. Open PowerShell as an Administrator: Press `Win + X` and select "Windows PowerShell (Administrator)" or "Windows Terminal (Administrator)".
2. Check Current Execution Policy by running this command:
```powershell
Get-ExecutionPolicy
```
- If the output is already `RemoteSigned`, `Unrestricted`, or `Bypass`, you likely don't need to change your execution policy. These policies should allow shell integration to work.
- If the output is `Restricted` or `AllSigned`, you may need to change your policy to enable shell integration.
3. Change the Execution Policy by running the following command:
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