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feat: added more Amazon Bedrock models and added SageMaker project (#141
) * feat: added AWS Bedrock provider and tests. TODO add Amazon Titan text and image models and Cohere models * updated Bedrock and added a project for SageMaker --------- Co-authored-by: Ty Augustine <[email protected]> Co-authored-by: Konstantin S <[email protected]>
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Feb 12, 2024
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32 changes: 32 additions & 0 deletions
32
src/libs/Providers/LangChain.Providers.Amazon.Bedrock/AmazonModelNames.cs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,32 @@ | ||
| namespace LangChain.Providers.Amazon.Bedrock | ||
| { | ||
| public static class AmazonModelIds | ||
| { | ||
| public static string AI21LabsJurassic2UltraV1 = "ai21.j2-ultra-v1"; | ||
| public static string AI21LabsJurassic2MidV1 = "ai21.j2-mid-v1"; | ||
|
|
||
| public static string AmazonTitanEmbeddingsG1TextV1 = "amazon.titan-embed-text-v1"; | ||
| public static string AmazonTitanTextG1LiteV1 = "amazon.titan-text-lite-v1"; | ||
| public static string AmazonTitanTextG1ExpressV1 = "amazon.titan-text-express-v1"; | ||
| public static string AmazonTitanImageGeneratorG1V1 = "amazon.titan-image-generator-v1"; | ||
| public static string AmazonTitanMultiModalEmbeddingsG1V1 = "amazon.titan-embed-image-v1"; | ||
|
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||
| public static string AnthropicClaude2_1 = "anthropic.claude-v2:1"; | ||
| public static string AnthropicClaude2 = "anthropic.claude-v2"; | ||
| public static string AnthropicClaude1_3 = "anthropic.claude-v1"; | ||
| public static string AnthropicClaudeInstant1_2 = "anthropic.claude-instant-v1"; | ||
|
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| public static string CohereCommand = "cohere.command-text-v14"; | ||
| public static string CohereCommandLight = "cohere.command-light-text-v14"; | ||
| public static string CohereEmbedEnglish= "cohere.embed-english-v3"; | ||
| public static string CohereEmbedMultilingual = "cohere.embed-multilingual-v3"; | ||
|
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| public static string MetaLlama2Chat13B = "meta.llama2-13b-chat-v1"; | ||
| public static string MetaLlama2Chat70B = "meta.llama2-70b-chat-v1"; | ||
| public static string MetaLlama213B = "meta.llama2-13b-v1"; //TODO i'm guessing the model id | ||
| public static string MetaLlama270B = "meta.llama2-70b-v1"; //TODO i'm guessing the model id | ||
|
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| public static string StabilityAISDXL0_8 = "stability.stable-diffusion-xl-v0"; | ||
| public static string StabilityAISDXL1_0 = "stability.stable-diffusion-xl-v1"; | ||
| } | ||
| } |
107 changes: 107 additions & 0 deletions
107
...s/Providers/LangChain.Providers.Amazon.Bedrock/Embeddings/AmazonTitanEmbeddingsRequest.cs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,107 @@ | ||
| using System.Text.Json.Nodes; | ||
| using Amazon.BedrockRuntime; | ||
| using Amazon.BedrockRuntime.Model; | ||
| using Amazon.Util; | ||
| using LangChain.TextSplitters; | ||
|
|
||
| namespace LangChain.Providers.Amazon.Bedrock.Embeddings; | ||
|
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| public class AmazonTitanEmbeddingsRequest : IBedrockEmbeddingsRequest | ||
| { | ||
| public async Task<float[][]> EmbedDocumentsAsync( | ||
| AmazonBedrockRuntimeClient client, | ||
| string[] texts, | ||
| BedrockEmbeddingsConfiguration configuration) | ||
| { | ||
| texts = texts ?? throw new ArgumentNullException(nameof(texts)); | ||
|
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| List<float> arrEmbeddings = []; | ||
| var inputText = string.Join(" ", texts); | ||
| var textSplitter = new RecursiveCharacterTextSplitter(chunkSize: 10_000); | ||
| var splitText = textSplitter.SplitText(inputText); | ||
|
|
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| foreach (var text in splitText) | ||
| { | ||
| try | ||
| { | ||
| string payload = new JsonObject | ||
| { | ||
| { "inputText", text }, | ||
| }.ToJsonString(); | ||
|
|
||
| InvokeModelResponse response = await client.InvokeModelAsync(new InvokeModelRequest() | ||
| { | ||
| ModelId = configuration.ModelId, | ||
| Body = AWSSDKUtils.GenerateMemoryStreamFromString(payload), | ||
| ContentType = "application/json", | ||
| Accept = "application/json" | ||
| }); | ||
|
|
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| if (response.HttpStatusCode == System.Net.HttpStatusCode.OK) | ||
| { | ||
| var body = JsonNode.Parse(response.Body); | ||
| var embeddings = body?["embedding"] | ||
| .AsArray() | ||
| .Select(x => (float)x.AsValue()) | ||
| .ToArray(); | ||
| arrEmbeddings.AddRange(embeddings); | ||
| } | ||
| else | ||
| { | ||
| Console.WriteLine("InvokeModelAsync failed with status code " + response.HttpStatusCode); | ||
| } | ||
| } | ||
| catch (AmazonBedrockRuntimeException e) | ||
| { | ||
| Console.WriteLine(e.Message); | ||
| } | ||
| } | ||
|
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| var result = arrEmbeddings.Select(f => (new[] { f })).ToArray(); | ||
|
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| return result; | ||
| } | ||
|
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| public async Task<float[]> EmbedQueryAsync( | ||
| AmazonBedrockRuntimeClient client, | ||
| string text, | ||
| BedrockEmbeddingsConfiguration configuration) | ||
| { | ||
| text = text ?? throw new ArgumentNullException(nameof(text)); | ||
| float[]? embeddings = []; | ||
|
|
||
| try | ||
| { | ||
| string payload = new JsonObject() | ||
| { | ||
| { "inputText", text }, | ||
| }.ToJsonString(); | ||
|
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| InvokeModelResponse response = await client.InvokeModelAsync(new InvokeModelRequest() | ||
| { | ||
| ModelId = configuration.ModelId, | ||
| Body = AWSSDKUtils.GenerateMemoryStreamFromString(payload), | ||
| ContentType = "application/json", | ||
| Accept = "application/json" | ||
| }); | ||
|
|
||
| if (response.HttpStatusCode == System.Net.HttpStatusCode.OK) | ||
| { | ||
| embeddings = JsonNode.Parse(response.Body)?["embedding"] | ||
| .AsArray() | ||
| .Select(x => (float)x.AsValue()) | ||
| .ToArray(); | ||
| } | ||
| else | ||
| { | ||
| Console.WriteLine("InvokeModelAsync failed with status code " + response.HttpStatusCode); | ||
| } | ||
| } | ||
| catch (AmazonBedrockRuntimeException e) | ||
| { | ||
| Console.WriteLine(e.Message); | ||
| } | ||
|
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| return embeddings; | ||
| } | ||
| } |
106 changes: 106 additions & 0 deletions
106
...s/LangChain.Providers.Amazon.Bedrock/Embeddings/AmazonTitanMultiModalEmbeddingsRequest.cs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,106 @@ | ||
| using System.Text; | ||
| using System.Text.Json; | ||
| using System.Text.Json.Nodes; | ||
| using Amazon.BedrockRuntime; | ||
| using Amazon.BedrockRuntime.Model; | ||
| using Amazon.Util; | ||
|
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| namespace LangChain.Providers.Amazon.Bedrock.Embeddings; | ||
|
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| public class AmazonTitanMultiModalEmbeddingsRequest : IBedrockEmbeddingsRequest | ||
| { | ||
| public async Task<float[][]> EmbedDocumentsAsync( | ||
| AmazonBedrockRuntimeClient client, | ||
| string[] texts, | ||
| BedrockEmbeddingsConfiguration configuration) | ||
| { | ||
| texts = texts ?? throw new ArgumentNullException(nameof(texts)); | ||
|
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| List<float> arrEmbeddings = []; | ||
| var inputText = string.Join(" ", texts); | ||
|
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| try | ||
| { | ||
| var payload = Encoding.UTF8.GetBytes( | ||
| JsonSerializer.Serialize(new | ||
| { | ||
| inputText = inputText, | ||
| inputImage = configuration.Base64Image | ||
| }) | ||
| ); | ||
|
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| InvokeModelResponse response = await client.InvokeModelAsync(new InvokeModelRequest() | ||
| { | ||
| ModelId = configuration.ModelId, | ||
| Body = new MemoryStream(payload), | ||
| ContentType = "application/json", | ||
| Accept = "application/json" | ||
| }); | ||
|
|
||
| if (response.HttpStatusCode == System.Net.HttpStatusCode.OK) | ||
| { | ||
| var body = JsonNode.Parse(response.Body); | ||
| var embeddings = body?["embedding"] | ||
| .AsArray() | ||
| .Select(x => (float)x.AsValue()) | ||
| .ToArray(); | ||
| arrEmbeddings.AddRange(embeddings); | ||
| } | ||
| else | ||
| { | ||
| Console.WriteLine("InvokeModelAsync failed with status code " + response.HttpStatusCode); | ||
| } | ||
| } | ||
| catch (AmazonBedrockRuntimeException e) | ||
| { | ||
| Console.WriteLine(e.Message); | ||
| } | ||
|
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| var result = arrEmbeddings.Select(f => (new[] { f })).ToArray(); | ||
|
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| return result; | ||
| } | ||
|
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| public async Task<float[]> EmbedQueryAsync( | ||
| AmazonBedrockRuntimeClient client, | ||
| string text, | ||
| BedrockEmbeddingsConfiguration configuration) | ||
| { | ||
| text = text ?? throw new ArgumentNullException(nameof(text)); | ||
| float[]? embeddings = []; | ||
|
|
||
| try | ||
| { | ||
| string payload = new JsonObject() | ||
| { | ||
| { "inputText", text }, | ||
| }.ToJsonString(); | ||
|
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| InvokeModelResponse response = await client.InvokeModelAsync(new InvokeModelRequest() | ||
| { | ||
| ModelId = configuration.ModelId, | ||
| Body = AWSSDKUtils.GenerateMemoryStreamFromString(payload), | ||
| ContentType = "application/json", | ||
| Accept = "application/json" | ||
| }); | ||
|
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||
| if (response.HttpStatusCode == System.Net.HttpStatusCode.OK) | ||
| { | ||
| embeddings = JsonNode.Parse(response.Body)?["embedding"] | ||
| .AsArray() | ||
| .Select(x => (float)x.AsValue()) | ||
| .ToArray(); | ||
| } | ||
| else | ||
| { | ||
| Console.WriteLine("InvokeModelAsync failed with status code " + response.HttpStatusCode); | ||
| } | ||
| } | ||
| catch (AmazonBedrockRuntimeException e) | ||
| { | ||
| Console.WriteLine(e.Message); | ||
| } | ||
|
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| return embeddings; | ||
| } | ||
| } |
61 changes: 61 additions & 0 deletions
61
src/libs/Providers/LangChain.Providers.Amazon.Bedrock/Embeddings/BedrockEmbeddings.cs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,61 @@ | ||
| using System.Diagnostics; | ||
|
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| namespace LangChain.Providers.Amazon.Bedrock.Embeddings; | ||
|
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| public class BedrockEmbeddings : BedrockEmbeddingsBase | ||
| { | ||
| private readonly BedrockEmbeddingsConfiguration _configuration; | ||
|
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| public BedrockEmbeddings(string modelId) | ||
| { | ||
| Id = modelId ?? throw new ArgumentException("ModelId is not defined", nameof(modelId)); | ||
| _configuration = new BedrockEmbeddingsConfiguration { ModelId = modelId }; | ||
| } | ||
|
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| public BedrockEmbeddings(string modelId, BedrockEmbeddingsConfiguration configuration) : this(modelId) | ||
| { | ||
| _configuration.Base64Image = configuration.Base64Image; | ||
| } | ||
|
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| public override async Task<float[][]> EmbedDocumentsAsync(string[] texts, CancellationToken cancellationToken = default) | ||
| { | ||
| var watch = Stopwatch.StartNew(); | ||
|
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| var response = await CreateCompletionAsync(texts, _configuration, cancellationToken).ConfigureAwait(false); | ||
|
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| watch.Stop(); | ||
|
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| // Unsupported | ||
| var usage = Usage.Empty with | ||
| { | ||
| Time = watch.Elapsed, | ||
| }; | ||
| lock (_usageLock) | ||
| { | ||
| TotalUsage += usage; | ||
| } | ||
|
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| return response; | ||
| } | ||
|
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| public override async Task<float[]> EmbedQueryAsync(string text, CancellationToken cancellationToken = default) | ||
| { | ||
| var watch = Stopwatch.StartNew(); | ||
|
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| var response = await CreateCompletionAsync(text, _configuration, cancellationToken).ConfigureAwait(false); | ||
|
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| watch.Stop(); | ||
|
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| // Unsupported | ||
| var usage = Usage.Empty with | ||
| { | ||
| Time = watch.Elapsed, | ||
| }; | ||
| lock (_usageLock) | ||
| { | ||
| TotalUsage += usage; | ||
| } | ||
|
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| return response; | ||
| } | ||
| } |
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