Rename outdated WaveAI types #1609
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Caution Review failedThe pull request is closed. WalkthroughThe pull request introduces a comprehensive renaming and type transformation across multiple files in the frontend and backend codebases. The primary change involves systematically replacing OpenAI-specific types with new WaveAI-specific types, including The changes affect method signatures, function parameters, return types, and type definitions in files related to AI interactions. The transformation appears to be a strategic rebranding or restructuring of the AI-related code, maintaining similar underlying data structures while updating the nomenclature. The modifications ensure consistency across different parts of the application, from frontend type handling to backend streaming and processing of AI commands. Tip CodeRabbit's docstrings feature is now available as part of our Early Access Program! Simply use the command 📜 Recent review detailsConfiguration used: CodeRabbit UI 📒 Files selected for processing (2)
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Actionable comments posted: 1
🧹 Nitpick comments (15)
frontend/app/view/waveai/waveai.tsx (5)
296-296: Consider improving error handling in fetchAiData.
If fetchWaveFile fails or encounters a network issue, it might be beneficial to log or handle the exception more robustly for better resilience.
301-301: Potential JSON parse vulnerability.
JSON.parse can throw if data is malformed. A try/catch (or equivalent) might be prudent to avoid runtime errors.
371-371: Repeated code for "assistant" response creation.
Consider refactoring similar blocks (e.g., lines 386) to adhere to DRY principles, reducing duplication.
386-386: Duplicate assistant response creation block.
This code matches the approach at line 371. A shared helper method would streamline maintenance.
400-400: Using "error" as a role may be confusing.
Storing errors as WaveAIPromptMessageType might blur logs or logic. Consider a distinct mechanism for error states or meta fields.pkg/waveai/waveai.go (2)
30-31: Packet creation uses “openai” as the type string.
MakeWaveAIPacket returns wshrpc.WaveAIPacketType with Type set to OpenAIPacketStr. If distancing from “openai” is intended, consider updating the string constant.
56-56: IsCloudAIRequest uses WaveAIOptsType.
Implementation matches the rename. As you add more providers, consider further logic to detect partial configuration.pkg/waveai/cloudbackend.go (2)
31-32: MakeWaveAICloudReqPacket sets Type to “openai-cloudreq.”
If removing openai references is the goal, consider using a more WaveAI-oriented constant.
104-104: JSON unmarshal into WaveAIPacketType.
Implementation is correct, but consider additional validation if partial responses or unexpected fields appear during streaming.pkg/waveai/perplexitybackend.go (1)
170-170: Creating wave AI packets for each choice.
You might consider verifying empty or partial content to avoid sending blank data. Otherwise, logic looks good.pkg/waveai/openaibackend.go (2)
28-28: Consider renaming error messages.
Inside setApiType(), lines such as "invalid api type" or "no openai model specified" remain unchanged, though you are now using WaveAI types. It might be clearer to rename these references from “openai” to “WaveAI” or a more generic term for consistency.
73-74: Potential naming mismatch.
The method signature has changed to accept WaveAI types, yet the receiver is still named OpenAIBackend. Consider renaming to WaveAIAzureBackend or simply WaveAIBackend, if relevant, for consistency.pkg/wshrpc/wshrpctypes.go (1)
404-404: Examine WaveAIPacketType for backward compatibility.
The new type uses a “Type” field plus optional “Error” field. Confirm no existing handlers assume old field names.frontend/types/gotypes.d.ts (2)
973-984: Check WaveAIOptsType naming and defaults.
Ensure field names and optional fields (apitype, baseurl, orgid, etc.) are truly optional. Make sure UI forms or other code handle these fields gracefully when absent.
1012-1017: WaveAIUsageType: verify usage metrics.
Prompt tokens, completion tokens, total tokens. Confirm all relevant front-end or monitoring features are updated accordingly.
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📒 Files selected for processing (13)
frontend/app/store/services.ts(1 hunks)frontend/app/store/wshclientapi.ts(1 hunks)frontend/app/view/waveai/waveai.tsx(8 hunks)frontend/types/gotypes.d.ts(1 hunks)pkg/service/blockservice/blockservice.go(1 hunks)pkg/waveai/anthropicbackend.go(3 hunks)pkg/waveai/cloudbackend.go(4 hunks)pkg/waveai/openaibackend.go(5 hunks)pkg/waveai/perplexitybackend.go(2 hunks)pkg/waveai/waveai.go(2 hunks)pkg/wshrpc/wshclient/wshclient.go(1 hunks)pkg/wshrpc/wshrpctypes.go(3 hunks)pkg/wshrpc/wshserver/wshserver.go(1 hunks)
🧰 Additional context used
🪛 golangci-lint (1.62.2)
pkg/waveai/openaibackend.go
62-62: func convertUsage is unused
(unused)
🔇 Additional comments (44)
frontend/app/view/waveai/waveai.tsx (4)
38-38: Function conversion to WaveAIPromptMessageType looks valid.
The new signature seamlessly transforms the incoming prompt to match the local ChatMessageType structure.
70-70: Renamed aiOpts to WaveAIOptsType.
This rename aligns with the broader transition from OpenAI-specific to WaveAI-specific types.
336-336: New user prompt object creation is consistent.
This aligns well with the switch to WaveAIPromptMessageType for user-initiated messages.
170-170: Check the fallback values in WaveAIOptsType.
Although the defaults look reasonable, consider verifying them for each AI provider to ensure consistent behavior (e.g., model fallback, 60000ms timeout).
✅ Verification successful
Let me search for the WaveAIOptsType definition and its usage to verify the fallback values.
Let me search for any default values or fallback handling in the codebase.
Fallback values are well-defined and consistent across providers
Based on the codebase analysis, I found that the fallback values are properly defined in the default configuration:
- Default max tokens: 2048 (defined in both
pkg/wconfig/defaultconfig/settings.jsonandpkg/waveai/waveai.go) - Default timeout: 60000ms (defined in
pkg/wconfig/defaultconfig/settings.json)
These defaults are consistently applied across different AI providers (OpenAI, Azure, Anthropic, Perplexity) as shown in the AI presets documentation and configuration files. The values are reasonable:
- 2048 tokens is a standard limit that works well with most models
- 60-second timeout is appropriate for API calls across different providers
🏁 Scripts executed
The following scripts were executed for the analysis:
Error: No shell scripts found
Script:
#!/bin/bash
# Find the WaveAIOptsType definition
ast-grep --pattern 'type WaveAIOptsType = {
$$$
}'
# Also search for interface definition
ast-grep --pattern 'interface WaveAIOptsType {
$$$
}'
# Search for any usage of WaveAIOptsType
rg "WaveAIOptsType" -A 5
Length of output: 3998
Script:
#!/bin/bash
# Search for default values or fallback handling in the backend
rg "maxtokens|maxchoices|timeoutms" -A 5 pkg/
rg "DefaultMax|DefaultTimeout" pkg/
# Search for the settings initialization to see default values
rg "ai:model|ai:apitype|ai:orgid|ai:apitoken|ai:apiversion" -A 5
Length of output: 23232
pkg/service/blockservice/blockservice.go (1)
73-73: Method signature updated to WaveAIPromptMessageType[].
This aptly follows the rename. The usage is consistent, and no further issues are evident here.
pkg/waveai/waveai.go (5)
22-22: WaveAICmdInfoPacketOutputType struct creation.
Renamed from OpenAICmdInfoPacketOutputType. The fields and naming now accurately align with WaveAI’s domain.
37-37: AssistantResponse field updated to WaveAICmdInfoPacketOutputType.
Renaming is consistent with the new WaveAI naming scheme. No issues found.
63-64: Switched to RespOrErrorUnion[wshrpc.WaveAIPacketType].
The error handling updates appear correct, forwarding a typed error for wave AI.
67-67: RunAICommand uses WaveAIStreamRequest.
This is consistent with changes sitewide. The updated references to new backends are correctly handled.
45-46: StreamCompletion now accepts WaveAIStreamRequest.
All references to OpenAiStreamRequest appear removed. Ensure all downstream calls match this updated signature.
✅ Verification successful
Let me verify the changes to StreamCompletion and its impact on downstream calls by searching for references in the codebase.
Based on the search results, I can now provide a final response:
StreamCompletion signature change has been properly propagated
The verification shows that all implementations of StreamCompletion (in AnthropicBackend, PerplexityBackend, OpenAIBackend, and WaveAICloudBackend) consistently use WaveAIStreamRequest. No references to OpenAIStreamRequest remain in the codebase, and all downstream calls through the RPC layer (wshrpc) are using the new WaveAIStreamRequest type.
🏁 Scripts executed
The following scripts were executed for the analysis:
Error: No shell scripts found
Script:
#!/bin/bash
# Search for references to StreamCompletion
rg "StreamCompletion" -A 2
# Search for WaveAIStreamRequest usage
rg "WaveAIStreamRequest" -A 2
# Search for any remaining OpenAIStreamRequest references
rg "OpenAIStreamRequest" -A 2
Length of output: 6756
pkg/waveai/cloudbackend.go (6)
23-23: WaveAICloudReqPacketType struct introduced.
Renaming from OpenAICloudReqPacketType is consistent with the broader rebranding.
37-38: StreamCompletion signature changed to WaveAI-specific.
The method properly produces a channel of wshrpc.WaveAIPacketType. No issues identified.
72-72: Filtering out prompts with “error” role.
Implementation helps avoid sending erroneous content upstream. This looks fine.
79-79: Constructing the WaveAICloudReqPacket for the request.
This rename aligns with the rest of the codebase. All fields match the new domain model.
118-118: Returning final data in RespOrErrorUnion.
Consistent with WaveAI type changes, properly handling EOF or server error states.
26-26: Updated Prompt to []wshrpc.WaveAIPromptMessageType.
Confirms alignment with the new WaveAI type. Verify all call sites passing correct data.
✅ Verification successful
Let me search for call sites and usages of this type to verify the alignment.
Based on the search results, I can now generate a final response as I have enough information to verify the type alignment and its usage across the codebase.
Type alignment verified, all call sites are using the correct data structure
The []wshrpc.WaveAIPromptMessageType is consistently used across the codebase:
- Defined in
pkg/wshrpc/wshrpctypes.goas the source type - Properly used in frontend TypeScript definitions (
frontend/types/gotypes.d.ts) - Correctly implemented in all call sites:
- Block service for saving AI data
- Cloud backend request handling
- Frontend chat message conversions
- OpenAI backend prompt conversion
🏁 Scripts executed
The following scripts were executed for the analysis:
Error: No shell scripts found
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#!/bin/bash
# First, let's find all references to WaveAIPromptMessageType
rg "WaveAIPromptMessageType" -A 3 -B 3
# Also search for any direct usage of the Prompt field
rg "\.Prompt\s*=" -A 2 -B 2
Length of output: 8006
pkg/waveai/perplexitybackend.go (4)
52-53: Signature changed to accept WaveAIStreamRequest and return wshrpc.WaveAIPacketType.
This parallels the rest of the rename to wave AI–specific types. No issues found.
163-163: Using MakeWaveAIPacket to create an initial model announcement.
This step is consistent with the new wave AI approach and references the model correctly.
165-165: Sending the created packet to the channel.
Implementation is straightforward and aligns with the wave AI response flow.
173-173: Publishing the choice packet to the channel.
Flow is correct and consistent with the rest of the streaming pattern.
pkg/waveai/openaibackend.go (5)
53-53: Implementation is correct.
The prompt conversion from WaveAIPromptMessageType to ChatCompletionMessage is handled cleanly.
131-134: Header packet usage is sound.
Creating and sending a dedicated header packet with model/created attributes ensures clarity for downstream consumers.
138-142: Choice loop logic is correct.
Sending multiple choice packets individually is an effective way to handle multi-choice completions.
177-181: Delta streaming is appropriate.
Sending partial content in near real time offers a good user experience for streaming completions.
170-173: Ensure consistent initialization.
The streaming logic for creating the header packet upon the first non-empty model is valid. Confirm that no extraneous header packets are sent for subsequent messages if the model never changes.
✅ Verification successful
Let me gather information about the streaming logic implementation to verify the concern about header packet initialization.
Based on the code search results, I can now generate the final response as I have enough information to verify the concern about header packet initialization.
Header packet initialization is correctly implemented
The streaming logic uses a sentHeader boolean flag to ensure the header packet is sent only once when the first non-empty model is received. The code at line 170-173 is part of a larger streaming response handler where the header packet is guarded by both conditions streamResp.Model != "" && !sentHeader, preventing duplicate header packets from being sent for subsequent messages.
🏁 Scripts executed
The following scripts were executed for the analysis:
Error: No shell scripts found
Script:
#!/bin/bash
# Search for the streaming response handling logic
ast-grep --pattern 'func $_($_, $_) {
$$$
MakeWaveAIPacket()
$$$
}'
# Also search for any other occurrences of MakeWaveAIPacket
rg "MakeWaveAIPacket" -A 5 -B 5
Length of output: 7060
pkg/waveai/anthropicbackend.go (6)
112-113: Method signature aligns with new WaveAI types.
The switch from OpenAiStreamRequest/OpenAIPacketType to WaveAIStreamRequest/WaveAIPacketType is consistent with the broader naming refactor.
234-236: Header packet creation is clear.
Providing the model for initial identification helps unify the streaming protocol across various AI backends.
241-243: Content block start event usage is sound.
Capturing initial text in a fresh packet keeps the user interface in sync with intermediate data from Anthropic’s streaming method.
248-250: Delta event usage is correct.
Emitting partial text deltas reflects best practices for incremental rendering.
261-267: Usage stats assignment.
Attaching usage data to the WaveAIPacket for each message_delta event is meticulous, ensuring that downstream consumers can track token usage accurately.
272-281: Clean final packet and usage assignment.
Assigning the finish reason and usage at the message_stop event is a sensible approach, providing a comprehensive completion packet.
frontend/app/store/services.ts (1)
18-18: Signature update is consistent with the WaveAI naming.
Shifting the method to accept WaveAIPromptMessageType[] aligns with the other WaveAI changes in this PR.
frontend/app/store/wshclientapi.ts (1)
306-306: Method signature successfully updated to WaveAI.
Changing the parameter and return generator types to WaveAIStreamRequest and WaveAIPacketType is in line with the renamed WaveAI data structures.
pkg/wshrpc/wshclient/wshclient.go (1)
367-368: Ensure cross-file consistency for renamed AI stream types.
All call sites should reference the new WaveAI types instead of the old OpenAI ones.
✅ Verification successful
Let me search for any references to OpenAI types and WaveAI types to verify the consistency across the codebase.
Based on the search results, I can see that all references in the codebase consistently use WaveAI types, and there are no remaining OpenAI type references that need to be updated. The code shows:
- All stream-related functions use
WaveAIStreamRequestandWaveAIPacketType - All type definitions and usages are consistently using the WaveAI prefix
- No legacy OpenAI type references were found in the codebase
No changes needed - all call sites already use WaveAI types consistently.
🏁 Scripts executed
The following scripts were executed for the analysis:
Error: No shell scripts found
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#!/bin/bash
# Search for OpenAI and WaveAI type references
rg -i "openai.*type|wave.*ai.*type" -A 2 -B 2
Length of output: 75155
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#!/bin/bash
# Search for stream function calls related to OpenAI or WaveAI
rg -i "stream.*openai|stream.*waveai" -A 2 -B 2
Length of output: 5055
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#!/bin/bash
# Look for type definitions and struct fields related to AI types
ast-grep --pattern 'type $_ struct {
$$$
OpenAI$_
$$$
}'
ast-grep --pattern 'type $_ struct {
$$$
WaveAI$_
$$$
}'
Length of output: 129
pkg/wshrpc/wshrpctypes.go (6)
386-386: Review naming alignment for WaveAIPromptMessageType.
Ensures message role/content remain consistent. Verify that each usage is updated accordingly.
141-141: Validate references to updated stream command signature.
This now uses WaveAIStreamRequest and WaveAIPacketType. Ensure no stale references to OpenAI exist throughout the codebase.
✅ Verification successful
Let me search for any references to the old and new types to verify if there are any stale OpenAI references.
Based on the search results, I can now generate the final response:
No stale OpenAI references found in stream command implementations
The codebase consistently uses the new WaveAIStreamRequest and WaveAIPacketType types across all implementations. The OpenAI-specific code is properly contained within the openaibackend.go file where it's expected to be, and there are no stale references to old OpenAI-specific types in the streaming interfaces.
🏁 Scripts executed
The following scripts were executed for the analysis:
Error: No shell scripts found
Script:
#!/bin/bash
# Search for WaveAIStreamRequest usage
echo "=== Searching for WaveAIStreamRequest ==="
rg "WaveAIStreamRequest" -A 2
echo -e "\n=== Searching for WaveAIPacketType ==="
rg "WaveAIPacketType" -A 2
echo -e "\n=== Searching for potential stale OpenAI references in stream commands ==="
rg "OpenAI.*Stream" -A 2
Length of output: 11108
415-415: Validate WaveAIUsageType fields.
Check that any usage-based feature (like token-limits) is tested and working with the new naming.
392-392: Confirm WaveAIOptsType is fully adopted.
Model, API token, etc. fields align with your new approach. Check references in any possible environment-variable overrides and config files.
✅ Verification successful
Let me gather information about the usage and structure of WaveAIOptsType to verify its adoption.
Let me check the configuration files and settings to ensure complete adoption.
Let me check the AI-related configuration files and settings.
WaveAIOptsType structure is properly adopted and aligned across the codebase
The struct is fully integrated with consistent field usage across backend and frontend, proper configuration support in settings.json and ai.json presets, and complete TypeScript type definitions matching the Go structure. All required fields (Model, APIToken) and optional fields (APIType, OrgID, APIVersion, BaseURL, MaxTokens, etc.) are properly represented in both the type definition and configuration files.
🏁 Scripts executed
The following scripts were executed for the analysis:
Error: No shell scripts found
Script:
#!/bin/bash
# Find the definition and structure of WaveAIOptsType
ast-grep --pattern 'type WaveAIOptsType struct {
$$$
}'
# Search for references to WaveAIOptsType
rg "WaveAIOptsType" -A 3
# Look for any config or environment variable related files
fd -e yaml -e yml -e env
Length of output: 3067
Script:
#!/bin/bash
# Check configuration files for AI settings
cat Taskfile.yml testdriver/onboarding.yml
# Look for any environment or settings related to AI configuration
rg -i "ai:|model:|apitype:|apitoken:" testdriver/onboarding.yml Taskfile.yml
# Check for any other potential configuration files
fd -e json -e toml -e ini
Length of output: 13417
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#!/bin/bash
# Check AI-specific configuration files
cat pkg/wconfig/defaultconfig/presets/ai.json
# Look for any AI-related settings in the default config
cat pkg/wconfig/defaultconfig/settings.json
# Search for any references to the AI options structure in frontend code
rg "WaveAIOptsType" frontend/ -A 5
Length of output: 3154
409-409: Usage object references.
Ensure usage metrics (prompt, completion, total tokens) log properly for billing or analytics.
380-383: Double-check correctness of WaveAIStreamRequest fields.
The new request structure includes an optional client ID, options, and prompts. Confirm that the new fields are populated correctly in upstream code (e.g., in the UI forms or other service layers).
✅ Verification successful
Let me search for related code to verify how the WaveAIStreamRequest structure is used in the codebase.
Let me search for the frontend code that constructs this request to verify how these fields are populated.
Let me search for the actual request construction in the frontend code.
Let me search for the actual usage of the StreamWaveAiCommand to see how the request is constructed.
Based on the search results, I can now generate the final response as we have found the relevant code showing how the request is constructed and used.
Request structure is correctly used in the codebase
The WaveAIStreamRequest structure is properly constructed and populated in the frontend code (frontend/app/view/waveai/waveai.tsx). The fields are correctly set:
clientidis set from aclientIdvariableoptsis populated from anoptsobjectpromptis constructed using history and new prompt messages
The request is then properly passed through the RPC layer:
- Frontend UI →
RpcApi.StreamWaveAiCommand - RPC Client →
wshRpcStream("streamwaveai", data, opts) - Server →
StreamWaveAiCommandhandler
🏁 Scripts executed
The following scripts were executed for the analysis:
Error: No shell scripts found
Script:
#!/bin/bash
# Search for usage of WaveAIStreamRequest
rg "WaveAIStreamRequest" -A 5
# Search for any code that might be constructing this request
ast-grep --pattern 'WaveAIStreamRequest{$$$}'
# Look for related test files that might show usage
fd -e test.go -x cat {}
Length of output: 6007
Script:
#!/bin/bash
# Search for frontend code constructing the request
rg -t ts -t tsx "new WaveAIStreamRequest|WaveAIStreamRequest.*{" -A 5
# Look for any UI forms or components that might be setting these fields
rg -t ts -t tsx "clientid.*opts.*prompt" -A 5
# Search for test files that might show request construction
fd -e test.ts -e test.tsx -x cat {}
Length of output: 21820
Script:
#!/bin/bash
# Search for files that might construct the request
rg -t ts -t js "WaveAIStreamRequest" -B 5 -A 5
# Look for any code that sets these fields
rg -t ts -t js "streamwaveai.*{" -B 5 -A 5
Length of output: 1689
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#!/bin/bash
# Search for StreamWaveAiCommand usage
rg "StreamWaveAiCommand" -B 10 -A 10
# Look for any code that constructs the request object
rg "opts.*prompt" -t ts -t js -B 5 -A 5
Length of output: 8895
pkg/wshrpc/wshserver/wshserver.go (1)
76-76: Confirm server-side stream rename.
Method signature now references WaveAIStreamRequest; ensure all references and any older comment/doc references to “OpenAI” have been phased out.
✅ Verification successful
Let me search for any remaining references to "OpenAI" in the codebase to verify if all occurrences have been properly renamed.
Let me also check for any references specifically in the wshrpc package and its related files to ensure we haven't missed any occurrences related to the renamed method.
Based on the search results, I can now provide a final response:
Rename verification completed - mixed results found
While the wshrpc package has been properly updated to use the new "WaveAI" naming (no "OpenAI" references found), there are still numerous "OpenAI" references in other parts of the codebase:
pkg/waveai/openaibackend.go: Contains the actual OpenAI implementation, which is correct as it's the backend integrationpkg/waveai/cloudbackend.go: Contains several error messages and constants using "OpenAI"pkg/waveai/waveai.go: Contains some OpenAI-related constants and types
Since the OpenAI-specific code is properly isolated in the backend implementation files and the wshrpc interface has been successfully renamed, this change is consistent with the codebase structure. The remaining OpenAI references are appropriate as they relate to the actual OpenAI service integration.
🏁 Scripts executed
The following scripts were executed for the analysis:
Error: No shell scripts found
Script:
#!/bin/bash
# Search for "OpenAI" string in the codebase
rg -i "openai" --type-add 'go:*.{go,proto}' --type go
# Also search specifically in comments and documentation
rg -i "openai" --type-add 'docs:*.{md,txt,doc,rst}' --type docs
Length of output: 4245
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#!/bin/bash
# Search specifically in the wshrpc directory and related files
rg -i "openai" pkg/wshrpc/
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frontend/types/gotypes.d.ts (3)
998-1003: Evaluate usage of WaveAIPromptMessageType.
Role, content, and optional name appear consistent with typical AI prompt structures. Confirm front-end components handle optional “name” field safely.
986-996: Confirm WaveAIPacketType is robust for partial or error states.
It includes an “error” property, so ensure front-end code checks for that property appropriately before rendering successful results.
✅ Verification successful
Let me search for usage of WaveAIPacketType to verify how it's handled in the frontend code.
Let me search for how the frontend handles these WaveAIPacketType responses, particularly focusing on error handling.
Let me search more specifically for the handling of these AI responses in the frontend components.
Let me try one more search without specifying file types since 'tsx' isn't recognized.
Let me check the specific implementation in the waveai.tsx file to see how it handles the responses.
Based on the evidence found, I can now provide a final response:
Error handling for WaveAIPacketType is properly implemented in the frontend
The frontend code in waveai.tsx has robust error handling that:
- Catches errors in a try-catch block when processing AI responses
- Creates specific error messages with
user: "error"type - Displays errors in a dedicated
chat-msg-errorCSS class - Preserves error states in the chat history as
role: "error"
🏁 Scripts executed
The following scripts were executed for the analysis:
Error: No shell scripts found
Script:
#!/bin/bash
# Search for usages of WaveAIPacketType and error handling
rg "WaveAIPacketType" -B 2 -A 4
# Also search for specific error handling patterns
rg "\.error\?" --type ts -B 2 -A 2
Length of output: 12693
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#!/bin/bash
# Search for files that might handle AI responses
rg -t ts "WaveAIPacketType.*error" -B 3 -A 3
# Search for AI-related components that might handle responses
fd -e tsx -e ts | xargs rg "async.*WaveAI" -B 2 -A 4
Length of output: 551
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#!/bin/bash
# Search for AI response handling in frontend components
rg -t tsx -t ts "StreamWaveAiCommand|WaveAIPacketType" -B 5 -A 10 frontend/
# Look for error handling patterns in AI-related components
rg -t tsx -t ts "error.*AI|AI.*error" frontend/
Length of output: 183
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#!/bin/bash
# Search for AI response handling in frontend components
rg "StreamWaveAiCommand|WaveAIPacketType" frontend/
# Look for error handling in components that use AI responses
rg "\.error.*AI|AI.*\.error" frontend/
Length of output: 524
Script:
#!/bin/bash
# Get the context around the AI stream handling in waveai.tsx
rg -A 15 -B 15 "StreamWaveAiCommand" frontend/app/view/waveai/waveai.tsx
# Also check for any error handling patterns in this file
rg "error|catch|try" frontend/app/view/waveai/waveai.tsx
Length of output: 1978
1005-1010: Audit WaveAIStreamRequest object structure.
clientid is optional, whereas opts and prompt are required. This might affect any partial saving or caching logic—verify that code gracefully checks these fields.
✅ Verification successful
Let me search for usage of WaveAIStreamRequest to verify how it's being handled in the codebase.
Let me search for the actual usage of WaveAIStreamRequest to see how the fields are handled.
Let me try a different pattern to find the usage and validation of these fields.
Based on the code analysis, I can now provide a definitive response about how these fields are handled:
Field validation is properly implemented across AI backends.
The codebase shows proper validation of the required fields:
optsis checked for nil across all backends (Anthropic, OpenAI, Perplexity, Cloud) with appropriate error responsespromptis used directly in message conversion and streaming, with role-specific handlingclientidis optional as designed and properly handled in the cloud backend
Key validations found:
- OpenAI backend checks for required model and API token
- All backends validate opts before processing
- Prompt messages are properly filtered and transformed
- No issues found with the optional clientid field
🏁 Scripts executed
The following scripts were executed for the analysis:
Error: No shell scripts found
Script:
#!/bin/bash
# Search for WaveAIStreamRequest usage
rg "WaveAIStreamRequest" -A 5
# Search for any validation or type checking related to these fields
rg "opts|prompt|clientid.*WaveAI" -A 3
Length of output: 66313
Script:
#!/bin/bash
# Search for implementations that handle WaveAIStreamRequest fields
ast-grep --pattern 'func $$$($$ wshrpc.WaveAIStreamRequest) $$$'
# Search for any validation or checks of these fields
rg "request\.(opts|prompt|clientid)" -A 3
Length of output: 110
Script:
#!/bin/bash
# Search for WaveAIStreamRequest handling in the codebase
rg "func.*WaveAIStreamRequest" -A 5
# Search for validation or usage of the fields with different pattern
rg "request\.(Opts|Prompt|ClientId)" -A 3
Length of output: 11061
pkg/waveai/openaibackend.go
Outdated
| func convertUsage(resp openaiapi.ChatCompletionResponse) *wshrpc.WaveAIUsageType { | ||
| if resp.Usage.TotalTokens == 0 { | ||
| return nil | ||
| } | ||
| return &wshrpc.OpenAIUsageType{ | ||
| return &wshrpc.WaveAIUsageType{ |
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🛠️ Refactor suggestion
Remove or utilize the unused function.
Static analysis indicates that convertUsage() is unused. Consider removing it if you do not plan to use it.
-func convertUsage(resp openaiapi.ChatCompletionResponse) *wshrpc.WaveAIUsageType {
- if resp.Usage.TotalTokens == 0 {
- return nil
- }
- return &wshrpc.WaveAIUsageType{
- PromptTokens: resp.Usage.PromptTokens,
- CompletionTokens: resp.Usage.CompletionTokens,
- TotalTokens: resp.Usage.TotalTokens,
- }
-}🧰 Tools
🪛 golangci-lint (1.62.2)
62-62: func convertUsage is unused
(unused)
A bunch of the Wave AI types still mentioned OpenAI. Now that most of them are being used for multiple AI backends, we need to update the names to be more generic.