🔵 Master CMS Template_Reskin

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Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo. Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo.

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When OpenAI launched ChatGPT, people thought, ‘This is interesting.’ What’s blown me away is how quickly it’s evolved into something transformational.

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1func (agent *LLMAgent) StreamCompletion(
2	ctx context.Context,
3	request *CompletionRequest,
4	tokens chan<- Token,
5) error {
6	modelsToTry := agent.getModelsToTry()
7
8	for i, model := range modelsToTry {
9		hasReceivedFirstToken, err := agent.tryStreamSingleModel(ctx, request, model, tokens)
10		if err == nil {
11			return nil // Success
12		}
13
14		// Only retry if we haven't started streaming and have more models to try
15		if !hasReceivedFirstToken && i < len(modelsToTry)-1 {
16			continue
17		}
18
19		return err
20	}
21
22	return fmt.Errorf("all models failed to stream completion")
23}

Below the code from GitHub:

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	typeModelCategorystring

	const (
	FastModelCategory="fast"
	SmartModelCategory="smart"
	ReasoningModelCategory="reasoning"
	)

	funcGetModelForCategory(categoryModelCategory, platformModelPlatform) ModelType {
	switchplatform {
	caseModelPlatformOpenAI:
	switchcategory {
	caseFast: returnModelTypeGPT4_1_Mini
	caseSmart: returnModelTypeGPT4_1
	caseReasoning: returnModelTypeO_3
	}
	caseModelPlatformAnthropic:
	switchcategory {
	caseFast: returnModelTypeClaude3_5_Haiku
	caseSmart: returnModelTypeClaude4_Sonnet
	caseReasoning: returnModelTypeClaude4_Opus
	}
	// ... additional platforms
	}
	returnModelTypeGPT_4_1// sensible default
	}

Table code is below:

Model	Forecasting model	Best for
N-Week Average	Averages past N weeks to project future demand.	Stable demand with minimal fluctuations
N-Week Average with Momentum	Applies a line of best fit to past N weeks, weighting recent weeks more heavily.	Gradual shifts in workload over time Seasonal Model
Seasonal Model	Analyzes yearly patterns to predict seasonal fluctuations.	Predictable high/low demand cycles
Prophet Model	Uses machine learning to model trends, seasonality, and events.	Dynamic environments with long-term demand shifts

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Something something AI template and RFP template