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https://github.com/vxcontrol/langchaingo.git
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Travis Cline
dff679c481
docs: complete basic chat application tutorial with progressive examples Completely rewrite the basic chat application tutorial with a structured, step-by-step approach: **Tutorial Documentation**: - Restructure tutorial into 6 clear progressive steps - Add proper setup instructions and prerequisites - Include code examples for each step with explanations - Improve clarity and flow from basic to advanced concepts **Complete Working Example**: - Add `examples/tutorial-basic-chat-app/` with full implementation - Include separate files for each tutorial step (step3-step6) - Add comprehensive README with usage instructions - Support multiple execution modes via command-line arguments **Progressive Implementation Steps**: - Step 3: Basic single-shot LLM interaction - Step 4: Interactive chat loop without memory - Step 5: Chat with manual conversation memory management - Step 6: Advanced chat using chains with automatic memory **Features Added**: - Go module setup with proper dependencies - Error handling and graceful exit functionality - Multiple chat implementations demonstrating different approaches - Clear documentation linking tutorial to working code - Support for running individual steps or complete implementation The tutorial now provides a complete learning path from basic LLM usage to sophisticated conversation management using LangChainGo's chains and memory systems.
34 lines
531 B
Go
34 lines
531 B
Go
package main
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import (
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"context"
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"fmt"
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"log"
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"github.com/tmc/langchaingo/llms"
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"github.com/tmc/langchaingo/llms/openai"
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)
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// Step 3: Basic Chat Application
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func basicChat() {
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// Initialize the OpenAI LLM
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llm, err := openai.New()
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if err != nil {
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log.Fatal(err)
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}
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// Create a context
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ctx := context.Background()
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// Send a message to the LLM
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response, err := llms.GenerateFromSinglePrompt(
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ctx,
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llm,
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"Hello! How can you help me today?",
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)
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if err != nil {
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log.Fatal(err)
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}
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fmt.Println("AI:", response)
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} |