Feature/llm multi prompt

chains/llm.go

@@ -2,6 +2,7 @@ package chains
 
 import (
 	"context"
+	"fmt"
 
 	"github.com/tmc/langchaingo/callbacks"
 	"github.com/tmc/langchaingo/llms"
@@ -11,14 +12,19 @@ import (
 	"github.com/tmc/langchaingo/schema"
 )
 
-const _llmChainDefaultOutputKey = "text"
+const (
+	_llmChainDefaultOutputKey     = "text"
+	_llmChainMultiPromptOutputKey = "choices"
+)
 
 type LLMChain struct {
 	Prompt           prompts.FormatPrompter
 	LLM              llms.Model
 	Memory           schema.Memory
 	CallbacksHandler callbacks.Handler
 	OutputParser     schema.OutputParser[any]
+	// When enabled usesMultiplePrompts will not 'flatten' the prompt into a single message.
+	useMultiPrompt bool
 
 	OutputKey string
 }
@@ -41,11 +47,17 @@ func NewLLMChain(llm llms.Model, prompt prompts.FormatPrompter, opts ...ChainCal
 		Memory:           memory.NewSimple(),
 		OutputKey:        _llmChainDefaultOutputKey,
 		CallbacksHandler: opt.CallbackHandler,
+		useMultiPrompt:   false,
 	}
 
 	return chain
 }
 
+func (c *LLMChain) EnableMultiPrompt() {
+	c.useMultiPrompt = true
+	c.OutputKey = _llmChainMultiPromptOutputKey
+}
+
 // Call formats the prompts with the input values, generates using the llm, and parses
 // the output from the llm with the output parser. This function should not be called
 // directly, use rather the Call or Run function if the prompt only requires one input
@@ -56,17 +68,27 @@ func (c LLMChain) Call(ctx context.Context, values map[string]any, options ...Ch
 		return nil, err
 	}
 
-	result, err := llms.GenerateFromSinglePrompt(ctx, c.LLM, promptValue.String(), getLLMCallOptions(options...)...)
-	if err != nil {
-		return nil, err
-	}
-
-	finalOutput, err := c.OutputParser.ParseWithPrompt(result, promptValue)
-	if err != nil {
-		return nil, err
+	llmsOptions := getLLMCallOptions(options...)
+	var llmOutput any
+	if c.useMultiPrompt {
+		llmsReponse, err := c.LLM.GenerateContent(ctx, chatMessagesToLLmMessageContent(promptValue.Messages()), llmsOptions...)
+		if err != nil {
+			return nil, fmt.Errorf("llm generate content: %w", err)
+		}
+
+		llmOutput = llmsReponse.Choices
+	} else {
+		resp, err := llms.GenerateFromSinglePrompt(ctx, c.LLM, promptValue.String(), llmsOptions...)
+		if err != nil {
+			return nil, err
+		}
+
+		llmOutput, err = c.OutputParser.ParseWithPrompt(resp, promptValue)
+		if err != nil {
+			return nil, err
+		}
 	}
-
-	return map[string]any{c.OutputKey: finalOutput}, nil
+	return map[string]any{c.OutputKey: llmOutput}, nil
 }
 
 // GetMemory returns the memory.
@@ -87,3 +109,22 @@ func (c LLMChain) GetInputKeys() []string {
 func (c LLMChain) GetOutputKeys() []string {
 	return []string{c.OutputKey}
 }
+
+// Convert ChatMessage to MessageContent.
+// Each ChatMessage is directly converted to a MessageContent with the same content and type.
+func chatMessagesToLLmMessageContent(chatMessages []llms.ChatMessage) []llms.MessageContent {
+	msgs := make([]llms.MessageContent, len(chatMessages))
+	for idx, m := range chatMessages {
+		msgs[idx] = chatMessageToLLm(m)
+	}
+	return msgs
+}
+
+func chatMessageToLLm(in llms.ChatMessage) llms.MessageContent {
+	return llms.MessageContent{
+		Parts: []llms.ContentPart{
+			llms.TextContent{Text: in.GetContent()},
+		},
+		Role: in.GetType(),
+	}
+}

examples/anthropic-tool-call-example/anthropic-tool-call-example.go

@@ -87,7 +87,6 @@ func main() {
 		log.Fatal(err)
 	}
 	fmt.Println(resp.Choices[0].Content)
-
 }
 
 // executeToolCalls executes the tool calls in the response and returns the

examples/llamafile-completion-example/llamafile_completion_example.go

@@ -9,13 +9,11 @@ import (
 )
 
 func main() {
-
 	options := []llamafile.Option{
 		llamafile.WithEmbeddingSize(2048),
 		llamafile.WithTemperature(0.8),
 	}
 	llm, err := llamafile.New(options...)
-
 	if err != nil {
 		panic(err)
 	}
@@ -35,7 +33,6 @@ func main() {
 			fmt.Print(string(chunk))
 			return nil
 		}))
-
 	if err != nil {
 		panic(err)
 	}

examples/llm-chain-multi-prompt-example/README.md

@@ -0,0 +1,35 @@
+# LLM Chain Multi Prompt Example
+
+Welcome to this cheerful example of using LLM (Language Model) chains with LangChain in Go! 🎉
+
+This example demonstrates how to create and use LLM chains for various natural language processing tasks. Let's dive in and see what exciting things we can do!
+
+## What Does This Example Do?
+
+1. **Company Name Generation** 🏢
+   - We create an LLM chain that generates a company name based on a product.
+   - It uses a simple prompt template: "What is a good name for a company that makes {{.product}}?"
+   - We run this chain with "socks" as input and get a creative company name suggestion!
+
+2. **Text Translation** 🌍
+   - We set up another LLM chain for translating text between languages.
+   - The prompt template asks to translate from one language to another.
+   - We demonstrate translating "I love programming" from English to French.
+
+## How It Works
+
+1. We start by setting up an OpenAI LLM (Language Model).
+2. For each task, we create a `PromptTemplate` with placeholders for inputs.
+3. We then create `LLMChain` instances combining the LLM and the prompt templates.
+4. For single-input chains, we use the `Run` function.
+5. For multi-input chains, we use the `Call` function with a map of inputs.
+
+## Running the Example
+
+When you run this example, you'll see:
+1. A suggested company name for a sock manufacturer.
+2. The French translation of "I love programming".
+
+It's a fun and practical demonstration of how LLM chains can be used for creative and linguistic tasks!
+
+Happy coding, and enjoy exploring the world of LLM chains with Go! 🚀👨‍💻👩‍💻

examples/llm-chain-multi-prompt-example/go.mod

@@ -0,0 +1,39 @@
+module github.com/tmc/langchaingo/examples/llm-chain-multi-prompt-example
+
+go 1.22.0
+
+toolchain go1.22.1
+
+require github.com/tmc/langchaingo v0.1.13-pre.0
+
+require (
+	github.com/Masterminds/goutils v1.1.1 // indirect
+	github.com/Masterminds/semver/v3 v3.2.0 // indirect
+	github.com/Masterminds/sprig/v3 v3.2.3 // indirect
+	github.com/dlclark/regexp2 v1.10.0 // indirect
+	github.com/dustin/go-humanize v1.0.1 // indirect
+	github.com/google/uuid v1.6.0 // indirect
+	github.com/goph/emperror v0.17.2 // indirect
+	github.com/huandu/xstrings v1.3.3 // indirect
+	github.com/imdario/mergo v0.3.13 // indirect
+	github.com/json-iterator/go v1.1.12 // indirect
+	github.com/mitchellh/copystructure v1.0.0 // indirect
+	github.com/mitchellh/reflectwalk v1.0.0 // indirect
+	github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd // indirect
+	github.com/modern-go/reflect2 v1.0.2 // indirect
+	github.com/nikolalohinski/gonja v1.5.3 // indirect
+	github.com/pelletier/go-toml/v2 v2.0.9 // indirect
+	github.com/pkg/errors v0.9.1 // indirect
+	github.com/pkoukk/tiktoken-go v0.1.6 // indirect
+	github.com/shopspring/decimal v1.2.0 // indirect
+	github.com/sirupsen/logrus v1.9.3 // indirect
+	github.com/spf13/cast v1.3.1 // indirect
+	github.com/yargevad/filepathx v1.0.0 // indirect
+	go.starlark.net v0.0.0-20230302034142-4b1e35fe2254 // indirect
+	golang.org/x/crypto v0.23.0 // indirect
+	golang.org/x/exp v0.0.0-20230713183714-613f0c0eb8a1 // indirect
+	golang.org/x/sys v0.20.0 // indirect
+	gopkg.in/yaml.v3 v3.0.1 // indirect
+)
+
+replace github.com/tmc/langchaingo => ../..