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https://github.com/ollama/ollama.git
synced 2026-09-21 13:38:14 -05:00
lint: clean up current tree (#17456)
This commit is contained in:
@@ -474,7 +474,6 @@ func (s *Session) executeToolCalls(ctx context.Context, runID string, opts RunOp
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batch := toolBatchResult{
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messages: make([]api.Message, 0, len(calls)),
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}
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projectedMessages := append([]api.Message(nil), messages...)
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// Pre-compute the full-history token estimate once per batch instead of
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// re-marshaling the entire history for each tool call. Per-call deltas
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// (tool messages already appended this batch) are tracked in batchTokens
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@@ -530,7 +529,6 @@ func (s *Session) executeToolCalls(ctx context.Context, runID string, opts RunOp
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for _, plan := range plans {
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msg := s.toolMessageForContext(plan.toolName, plan.call.ID, content, opts, historyTokens+batchTokens)
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batch.messages = append(batch.messages, msg)
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projectedMessages = append(projectedMessages, msg)
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batchTokens += estimateMessagesTokens([]api.Message{msg})
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deniedContent := msg.Content
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if emitErr := s.emit(newToolFinished(meta, "denied", plan.call.ID, plan.toolName, "", plan.args, deniedContent, deniedContent)); emitErr != nil {
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@@ -559,7 +557,6 @@ func (s *Session) executeToolCalls(ctx context.Context, runID string, opts RunOp
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content := fmt.Sprintf("Error: unknown tool: %s", toolName)
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msg := s.toolMessageForContext(toolName, call.ID, content, opts, historyTokens+batchTokens)
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batch.messages = append(batch.messages, msg)
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projectedMessages = append(projectedMessages, msg)
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batchTokens += estimateMessagesTokens([]api.Message{msg})
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content = msg.Content
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if toolOutputFullyOmitted(content) {
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@@ -580,7 +577,6 @@ func (s *Session) executeToolCalls(ctx context.Context, runID string, opts RunOp
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rawContent := fmt.Sprintf("Error: %v", err)
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msg := s.toolMessageForContext(toolName, call.ID, rawContent, opts, historyTokens+batchTokens)
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batch.messages = append(batch.messages, msg)
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projectedMessages = append(projectedMessages, msg)
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batchTokens += estimateMessagesTokens([]api.Message{msg})
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content := msg.Content
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if toolOutputFullyOmitted(content) {
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@@ -609,7 +605,6 @@ func (s *Session) executeToolCalls(ctx context.Context, runID string, opts RunOp
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msg := s.toolMessageForContext(toolName, call.ID, rawContent, opts, historyTokens+batchTokens)
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batch.messages = append(batch.messages, msg)
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projectedMessages = append(projectedMessages, msg)
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batchTokens += estimateMessagesTokens([]api.Message{msg})
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content := msg.Content
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@@ -637,7 +632,6 @@ func (s *Session) disabledToolCalls(ctx context.Context, runID string, opts RunO
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batch := toolBatchResult{
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messages: make([]api.Message, 0, len(calls)),
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}
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projectedMessages := append([]api.Message(nil), messages...)
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historyTokens := s.estimateRunPromptTokens(opts, messages)
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batchTokens := 0
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for _, call := range calls {
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@@ -645,7 +639,6 @@ func (s *Session) disabledToolCalls(ctx context.Context, runID string, opts RunO
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args := call.Function.Arguments.ToMap()
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msg := s.toolMessageForContext(toolName, call.ID, toolExecutionDisabledMessage, opts, historyTokens+batchTokens)
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batch.messages = append(batch.messages, msg)
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projectedMessages = append(projectedMessages, msg)
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batchTokens += estimateMessagesTokens([]api.Message{msg})
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if emitErr := s.emitIgnoringCanceled(ctx, newToolFinished(meta, "disabled", call.ID, toolName, "", args, msg.Content, msg.Content)); emitErr != nil {
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return toolBatchResult{}, emitErr
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+1
-1
@@ -696,7 +696,7 @@ type CreateRequest struct {
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Renderer string `json:"renderer,omitempty"`
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// Parser is the name of the parser used to parse the output of the request.
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Parser string `json:"parser,omitempty"`
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Parser string `json:"parser,omitempty"`
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// Requires is the minimum version of Ollama required by the model.
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Requires string `json:"requires,omitempty"`
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+1
-25
@@ -178,32 +178,12 @@ func agentSkillSystemContext(catalog *coreagent.SkillCatalog, registry *coreagen
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return catalog.SystemContext()
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}
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func selectAgentModel(ctx context.Context, client *api.Client, current string) (string, error) {
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models, err := agentModelOptions(ctx, client)
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if err != nil {
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return "", err
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}
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if len(models) == 0 {
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return "", errors.New("no models available, run 'ollama pull <model>' first")
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}
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items := agentSelectionItems(models)
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switch {
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case launch.DefaultSingleSelectorWithUpdates != nil:
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return launch.DefaultSingleSelectorWithUpdates("Select model to run:", items, current, nil)
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case launch.DefaultSingleSelector != nil:
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return launch.DefaultSingleSelector("Select model to run:", items, current)
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default:
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return "", errors.New("no selector configured")
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}
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}
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func agentSelectionItems(models []agentchat.ModelOption) []launch.SelectionItem {
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items := make([]launch.SelectionItem, 0, len(models))
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for _, model := range models {
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items = append(items, launch.SelectionItem{
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Name: model.Name,
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Description: agentSelectionDescription(model),
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Description: strings.TrimSpace(model.Description),
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Recommended: model.Recommended,
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AvailabilityBadge: model.AvailabilityBadge,
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})
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@@ -211,10 +191,6 @@ func agentSelectionItems(models []agentchat.ModelOption) []launch.SelectionItem
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return items
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}
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func agentSelectionDescription(model agentchat.ModelOption) string {
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return strings.TrimSpace(model.Description)
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}
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var agentGetwd = os.Getwd
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func agentWorkingDir() string {
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@@ -19,8 +19,10 @@ const (
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// lagunaToolJSON is the get_weather tool as serialized into <available_tools>,
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// matching lagunaWeatherTool().
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const lagunaToolJSON = `{"type": "function", "function": {"name": "get_weather", "description": "Get weather", "parameters": {"type": "object", "required": ["location"], "properties": {"location": {"type": "string", "description": "City"}}}}}`
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const lagunaMathToolJSON = `{"type": "function", "function": {"name": "add", "description": "Add numbers", "parameters": {"type": "object", "required": ["a", "b"], "properties": {"a": {"type": "number", "description": "First number"}, "b": {"type": "number", "description": "Second number"}}}}}`
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const (
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lagunaToolJSON = `{"type": "function", "function": {"name": "get_weather", "description": "Get weather", "parameters": {"type": "object", "required": ["location"], "properties": {"location": {"type": "string", "description": "City"}}}}}`
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lagunaMathToolJSON = `{"type": "function", "function": {"name": "add", "description": "Add numbers", "parameters": {"type": "object", "required": ["a", "b"], "properties": {"a": {"type": "number", "description": "First number"}, "b": {"type": "number", "description": "Second number"}}}}}`
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)
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// TestLagunaRendererReferenceFlowCoverage checks the renderer against byte-for-byte
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// expected output from the Laguna v2 chat template. VERIFY_JINJA2=1 also verifies
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