mirror of
https://github.com/vxcontrol/langchaingo.git
synced 2026-07-18 10:45:37 -04:00
feat: update AWS SDK dependencies and enhance caching support
- Upgraded various AWS SDK dependencies in go.mod and go.sum files to their latest versions, improving compatibility and performance. - Introduced automatic caching support for specific Anthropic models, optimizing token usage and reducing costs. - Refactored message processing to include caching logic, ensuring seamless integration with existing functionalities. - Removed deprecated models from tests and updated test cases to validate new caching features and model support.
This commit is contained in:
Dmitry Ng
@@ -5,21 +5,22 @@ go 1.24.1
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require github.com/vxcontrol/langchaingo v0.1.14-update.1
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require (
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github.com/aws/aws-sdk-go-v2 v1.36.5 // indirect
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github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.6.11 // indirect
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github.com/aws/aws-sdk-go-v2/config v1.29.4 // indirect
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github.com/aws/aws-sdk-go-v2/credentials v1.17.61 // indirect
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github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.16.30 // indirect
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github.com/aws/aws-sdk-go-v2/internal/configsources v1.3.36 // indirect
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github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.6.36 // indirect
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github.com/aws/aws-sdk-go-v2/internal/ini v1.8.2 // indirect
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github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.31.0 // indirect
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github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.12.3 // indirect
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github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.12.15 // indirect
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github.com/aws/aws-sdk-go-v2/service/sso v1.25.0 // indirect
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github.com/aws/aws-sdk-go-v2/service/ssooidc v1.29.0 // indirect
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github.com/aws/aws-sdk-go-v2/service/sts v1.33.16 // indirect
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github.com/aws/smithy-go v1.22.4 // indirect
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github.com/aws/aws-sdk-go-v2 v1.41.2 // indirect
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github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.7.5 // indirect
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github.com/aws/aws-sdk-go-v2/config v1.32.10 // indirect
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github.com/aws/aws-sdk-go-v2/credentials v1.19.10 // indirect
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github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.18.18 // indirect
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github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.18 // indirect
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github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.18 // indirect
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github.com/aws/aws-sdk-go-v2/internal/ini v1.8.4 // indirect
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github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.50.0 // indirect
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github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.13.5 // indirect
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github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.13.18 // indirect
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github.com/aws/aws-sdk-go-v2/service/signin v1.0.6 // indirect
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github.com/aws/aws-sdk-go-v2/service/sso v1.30.11 // indirect
|
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github.com/aws/aws-sdk-go-v2/service/ssooidc v1.35.15 // indirect
|
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github.com/aws/aws-sdk-go-v2/service/sts v1.41.7 // indirect
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github.com/aws/smithy-go v1.24.1 // indirect
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github.com/dlclark/regexp2 v1.11.4 // indirect
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github.com/google/uuid v1.6.0 // indirect
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github.com/pkoukk/tiktoken-go v0.1.8 // indirect
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@@ -1,33 +1,35 @@
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github.com/aws/aws-sdk-go-v2 v1.36.5 h1:0OF9RiEMEdDdZEMqF9MRjevyxAQcf6gY+E7vwBILFj0=
|
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github.com/aws/aws-sdk-go-v2 v1.36.5/go.mod h1:EYrzvCCN9CMUTa5+6lf6MM4tq3Zjp8UhSGR/cBsjai0=
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github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.6.11 h1:12SpdwU8Djs+YGklkinSSlcrPyj3H4VifVsKf78KbwA=
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github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.6.11/go.mod h1:dd+Lkp6YmMryke+qxW/VnKyhMBDTYP41Q2Bb+6gNZgY=
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github.com/aws/aws-sdk-go-v2/config v1.29.4 h1:ObNqKsDYFGr2WxnoXKOhCvTlf3HhwtoGgc+KmZ4H5yg=
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github.com/aws/aws-sdk-go-v2/config v1.29.4/go.mod h1:j2/AF7j/qxVmsNIChw1tWfsVKOayJoGRDjg1Tgq7NPk=
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github.com/aws/aws-sdk-go-v2/credentials v1.17.61 h1:Hd/uX6Wo2iUW1JWII+rmyCD7MMhOe7ALwQXN6sKDd1o=
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github.com/aws/aws-sdk-go-v2/credentials v1.17.61/go.mod h1:L7vaLkwHY1qgW0gG1zG0z/X0sQ5tpIY5iI13+j3qI80=
|
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github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.16.30 h1:x793wxmUWVDhshP8WW2mlnXuFrO4cOd3HLBroh1paFw=
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github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.16.30/go.mod h1:Jpne2tDnYiFascUEs2AWHJL9Yp7A5ZVy3TNyxaAjD6M=
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github.com/aws/aws-sdk-go-v2/internal/configsources v1.3.36 h1:SsytQyTMHMDPspp+spo7XwXTP44aJZZAC7fBV2C5+5s=
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github.com/aws/aws-sdk-go-v2/internal/configsources v1.3.36/go.mod h1:Q1lnJArKRXkenyog6+Y+zr7WDpk4e6XlR6gs20bbeNo=
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github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.6.36 h1:i2vNHQiXUvKhs3quBR6aqlgJaiaexz/aNvdCktW/kAM=
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github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.6.36/go.mod h1:UdyGa7Q91id/sdyHPwth+043HhmP6yP9MBHgbZM0xo8=
|
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github.com/aws/aws-sdk-go-v2/internal/ini v1.8.2 h1:Pg9URiobXy85kgFev3og2CuOZ8JZUBENF+dcgWBaYNk=
|
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github.com/aws/aws-sdk-go-v2/internal/ini v1.8.2/go.mod h1:FbtygfRFze9usAadmnGJNc8KsP346kEe+y2/oyhGAGc=
|
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github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.31.0 h1:BbtWSM9690zWbSOuJjBm7t7SIqDWhHPhKKQLhqxL+ac=
|
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github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.31.0/go.mod h1:XHkvWM72+3dn5ox7yG0/yBEnQ2y0SMLCaXE/t96rv0I=
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github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.12.3 h1:eAh2A4b5IzM/lum78bZ590jy36+d/aFLgKF/4Vd1xPE=
|
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github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.12.3/go.mod h1:0yKJC/kb8sAnmlYa6Zs3QVYqaC8ug2AbnNChv5Ox3uA=
|
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github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.12.15 h1:dM9/92u2F1JbDaGooxTq18wmmFzbJRfXfVfy96/1CXM=
|
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github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.12.15/go.mod h1:SwFBy2vjtA0vZbjjaFtfN045boopadnoVPhu4Fv66vY=
|
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github.com/aws/aws-sdk-go-v2/service/sso v1.25.0 h1:2U9sF8nKy7UgyEeLiZTRg6ShBS22z8UnYpV6aRFL0is=
|
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github.com/aws/aws-sdk-go-v2/service/sso v1.25.0/go.mod h1:qs4a9T5EMLl/Cajiw2TcbNt2UNo/Hqlyp+GiuG4CFDI=
|
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github.com/aws/aws-sdk-go-v2/service/ssooidc v1.29.0 h1:wjAdc85cXdQR5uLx5FwWvGIHm4OPJhTyzUHU8craXtE=
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.29.0/go.mod h1:MlYRNmYu/fGPoxBQVvBYr9nyr948aY/WLUvwBMBJubs=
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.33.16 h1:BHEK2Q/7CMRMCb3nySi/w8UbIcPhKvYP5s1xf8/izn0=
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.33.16/go.mod h1:cQnB8CUnxbMU82JvlqjKR2HBOm3fe9pWorWBza6MBJ4=
|
||||
github.com/aws/smithy-go v1.22.4 h1:uqXzVZNuNexwc/xrh6Tb56u89WDlJY6HS+KC0S4QSjw=
|
||||
github.com/aws/smithy-go v1.22.4/go.mod h1:t1ufH5HMublsJYulve2RKmHDC15xu1f26kHCp/HgceI=
|
||||
github.com/aws/aws-sdk-go-v2 v1.41.2 h1:LuT2rzqNQsauaGkPK/7813XxcZ3o3yePY0Iy891T2ls=
|
||||
github.com/aws/aws-sdk-go-v2 v1.41.2/go.mod h1:IvvlAZQXvTXznUPfRVfryiG1fbzE2NGK6m9u39YQ+S4=
|
||||
github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.7.5 h1:zWFmPmgw4sveAYi1mRqG+E/g0461cJ5M4bJ8/nc6d3Q=
|
||||
github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.7.5/go.mod h1:nVUlMLVV8ycXSb7mSkcNu9e3v/1TJq2RTlrPwhYWr5c=
|
||||
github.com/aws/aws-sdk-go-v2/config v1.32.10 h1:9DMthfO6XWZYLfzZglAgW5Fyou2nRI5CuV44sTedKBI=
|
||||
github.com/aws/aws-sdk-go-v2/config v1.32.10/go.mod h1:2rUIOnA2JaiqYmSKYmRJlcMWy6qTj1vuRFscppSBMcw=
|
||||
github.com/aws/aws-sdk-go-v2/credentials v1.19.10 h1:EEhmEUFCE1Yhl7vDhNOI5OCL/iKMdkkYFTRpZXNw7m8=
|
||||
github.com/aws/aws-sdk-go-v2/credentials v1.19.10/go.mod h1:RnnlFCAlxQCkN2Q379B67USkBMu1PipEEiibzYN5UTE=
|
||||
github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.18.18 h1:Ii4s+Sq3yDfaMLpjrJsqD6SmG/Wq/P5L/hw2qa78UAY=
|
||||
github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.18.18/go.mod h1:6x81qnY++ovptLE6nWQeWrpXxbnlIex+4H4eYYGcqfc=
|
||||
github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.18 h1:F43zk1vemYIqPAwhjTjYIz0irU2EY7sOb/F5eJ3HuyM=
|
||||
github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.18/go.mod h1:w1jdlZXrGKaJcNoL+Nnrj+k5wlpGXqnNrKoP22HvAug=
|
||||
github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.18 h1:xCeWVjj0ki0l3nruoyP2slHsGArMxeiiaoPN5QZH6YQ=
|
||||
github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.18/go.mod h1:r/eLGuGCBw6l36ZRWiw6PaZwPXb6YOj+i/7MizNl5/k=
|
||||
github.com/aws/aws-sdk-go-v2/internal/ini v1.8.4 h1:WKuaxf++XKWlHWu9ECbMlha8WOEGm0OUEZqm4K/Gcfk=
|
||||
github.com/aws/aws-sdk-go-v2/internal/ini v1.8.4/go.mod h1:ZWy7j6v1vWGmPReu0iSGvRiise4YI5SkR3OHKTZ6Wuc=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.50.0 h1:TDKR8ACRw7G+GFaQlhoy6biu+8q6ZtSddQCy9avMdMI=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.50.0/go.mod h1:XlhOh5Ax/lesqN4aZCUgj9vVJed5VoXYHHFYGAlJEwU=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.13.5 h1:CeY9LUdur+Dxoeldqoun6y4WtJ3RQtzk0JMP2gfUay0=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.13.5/go.mod h1:AZLZf2fMaahW5s/wMRciu1sYbdsikT/UHwbUjOdEVTc=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.13.18 h1:LTRCYFlnnKFlKsyIQxKhJuDuA3ZkrDQMRYm6rXiHlLY=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.13.18/go.mod h1:XhwkgGG6bHSd00nO/mexWTcTjgd6PjuvWQMqSn2UaEk=
|
||||
github.com/aws/aws-sdk-go-v2/service/signin v1.0.6 h1:MzORe+J94I+hYu2a6XmV5yC9huoTv8NRcCrUNedDypQ=
|
||||
github.com/aws/aws-sdk-go-v2/service/signin v1.0.6/go.mod h1:hXzcHLARD7GeWnifd8j9RWqtfIgxj4/cAtIVIK7hg8g=
|
||||
github.com/aws/aws-sdk-go-v2/service/sso v1.30.11 h1:7oGD8KPfBOJGXiCoRKrrrQkbvCp8N++u36hrLMPey6o=
|
||||
github.com/aws/aws-sdk-go-v2/service/sso v1.30.11/go.mod h1:0DO9B5EUJQlIDif+XJRWCljZRKsAFKh3gpFz7UnDtOo=
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.35.15 h1:edCcNp9eGIUDUCrzoCu1jWAXLGFIizeqkdkKgRlJwWc=
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.35.15/go.mod h1:lyRQKED9xWfgkYC/wmmYfv7iVIM68Z5OQ88ZdcV1QbU=
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.41.7 h1:NITQpgo9A5NrDZ57uOWj+abvXSb83BbyggcUBVksN7c=
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.41.7/go.mod h1:sks5UWBhEuWYDPdwlnRFn1w7xWdH29Jcpe+/PJQefEs=
|
||||
github.com/aws/smithy-go v1.24.1 h1:VbyeNfmYkWoxMVpGUAbQumkODcYmfMRfZ8yQiH30SK0=
|
||||
github.com/aws/smithy-go v1.24.1/go.mod h1:LEj2LM3rBRQJxPZTB4KuzZkaZYnZPnvgIhb4pu07mx0=
|
||||
github.com/davecgh/go-spew v1.1.2-0.20180830191138-d8f796af33cc h1:U9qPSI2PIWSS1VwoXQT9A3Wy9MM3WgvqSxFWenqJduM=
|
||||
github.com/davecgh/go-spew v1.1.2-0.20180830191138-d8f796af33cc/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
|
||||
github.com/dlclark/regexp2 v1.11.4 h1:rPYF9/LECdNymJufQKmri9gV604RvvABwgOA8un7yAo=
|
||||
|
||||
@@ -5,21 +5,22 @@ go 1.24.1
|
||||
require github.com/vxcontrol/langchaingo v0.1.14-update.1
|
||||
|
||||
require (
|
||||
github.com/aws/aws-sdk-go-v2 v1.36.5 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.6.11 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/config v1.29.4 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/credentials v1.17.61 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.16.30 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/internal/configsources v1.3.36 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.6.36 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/internal/ini v1.8.2 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.31.0 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.12.3 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.12.15 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/sso v1.25.0 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.29.0 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.33.16 // indirect
|
||||
github.com/aws/smithy-go v1.22.4 // indirect
|
||||
github.com/aws/aws-sdk-go-v2 v1.41.2 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.7.5 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/config v1.32.10 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/credentials v1.19.10 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.18.18 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.18 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.18 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/internal/ini v1.8.4 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.50.0 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.13.5 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.13.18 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/signin v1.0.6 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/sso v1.30.11 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.35.15 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.41.7 // indirect
|
||||
github.com/aws/smithy-go v1.24.1 // indirect
|
||||
github.com/dlclark/regexp2 v1.11.4 // indirect
|
||||
github.com/google/uuid v1.6.0 // indirect
|
||||
github.com/pkoukk/tiktoken-go v0.1.8 // indirect
|
||||
|
||||
@@ -1,33 +1,35 @@
|
||||
github.com/aws/aws-sdk-go-v2 v1.36.5 h1:0OF9RiEMEdDdZEMqF9MRjevyxAQcf6gY+E7vwBILFj0=
|
||||
github.com/aws/aws-sdk-go-v2 v1.36.5/go.mod h1:EYrzvCCN9CMUTa5+6lf6MM4tq3Zjp8UhSGR/cBsjai0=
|
||||
github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.6.11 h1:12SpdwU8Djs+YGklkinSSlcrPyj3H4VifVsKf78KbwA=
|
||||
github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.6.11/go.mod h1:dd+Lkp6YmMryke+qxW/VnKyhMBDTYP41Q2Bb+6gNZgY=
|
||||
github.com/aws/aws-sdk-go-v2/config v1.29.4 h1:ObNqKsDYFGr2WxnoXKOhCvTlf3HhwtoGgc+KmZ4H5yg=
|
||||
github.com/aws/aws-sdk-go-v2/config v1.29.4/go.mod h1:j2/AF7j/qxVmsNIChw1tWfsVKOayJoGRDjg1Tgq7NPk=
|
||||
github.com/aws/aws-sdk-go-v2/credentials v1.17.61 h1:Hd/uX6Wo2iUW1JWII+rmyCD7MMhOe7ALwQXN6sKDd1o=
|
||||
github.com/aws/aws-sdk-go-v2/credentials v1.17.61/go.mod h1:L7vaLkwHY1qgW0gG1zG0z/X0sQ5tpIY5iI13+j3qI80=
|
||||
github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.16.30 h1:x793wxmUWVDhshP8WW2mlnXuFrO4cOd3HLBroh1paFw=
|
||||
github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.16.30/go.mod h1:Jpne2tDnYiFascUEs2AWHJL9Yp7A5ZVy3TNyxaAjD6M=
|
||||
github.com/aws/aws-sdk-go-v2/internal/configsources v1.3.36 h1:SsytQyTMHMDPspp+spo7XwXTP44aJZZAC7fBV2C5+5s=
|
||||
github.com/aws/aws-sdk-go-v2/internal/configsources v1.3.36/go.mod h1:Q1lnJArKRXkenyog6+Y+zr7WDpk4e6XlR6gs20bbeNo=
|
||||
github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.6.36 h1:i2vNHQiXUvKhs3quBR6aqlgJaiaexz/aNvdCktW/kAM=
|
||||
github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.6.36/go.mod h1:UdyGa7Q91id/sdyHPwth+043HhmP6yP9MBHgbZM0xo8=
|
||||
github.com/aws/aws-sdk-go-v2/internal/ini v1.8.2 h1:Pg9URiobXy85kgFev3og2CuOZ8JZUBENF+dcgWBaYNk=
|
||||
github.com/aws/aws-sdk-go-v2/internal/ini v1.8.2/go.mod h1:FbtygfRFze9usAadmnGJNc8KsP346kEe+y2/oyhGAGc=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.31.0 h1:BbtWSM9690zWbSOuJjBm7t7SIqDWhHPhKKQLhqxL+ac=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.31.0/go.mod h1:XHkvWM72+3dn5ox7yG0/yBEnQ2y0SMLCaXE/t96rv0I=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.12.3 h1:eAh2A4b5IzM/lum78bZ590jy36+d/aFLgKF/4Vd1xPE=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.12.3/go.mod h1:0yKJC/kb8sAnmlYa6Zs3QVYqaC8ug2AbnNChv5Ox3uA=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.12.15 h1:dM9/92u2F1JbDaGooxTq18wmmFzbJRfXfVfy96/1CXM=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.12.15/go.mod h1:SwFBy2vjtA0vZbjjaFtfN045boopadnoVPhu4Fv66vY=
|
||||
github.com/aws/aws-sdk-go-v2/service/sso v1.25.0 h1:2U9sF8nKy7UgyEeLiZTRg6ShBS22z8UnYpV6aRFL0is=
|
||||
github.com/aws/aws-sdk-go-v2/service/sso v1.25.0/go.mod h1:qs4a9T5EMLl/Cajiw2TcbNt2UNo/Hqlyp+GiuG4CFDI=
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.29.0 h1:wjAdc85cXdQR5uLx5FwWvGIHm4OPJhTyzUHU8craXtE=
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.29.0/go.mod h1:MlYRNmYu/fGPoxBQVvBYr9nyr948aY/WLUvwBMBJubs=
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.33.16 h1:BHEK2Q/7CMRMCb3nySi/w8UbIcPhKvYP5s1xf8/izn0=
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.33.16/go.mod h1:cQnB8CUnxbMU82JvlqjKR2HBOm3fe9pWorWBza6MBJ4=
|
||||
github.com/aws/smithy-go v1.22.4 h1:uqXzVZNuNexwc/xrh6Tb56u89WDlJY6HS+KC0S4QSjw=
|
||||
github.com/aws/smithy-go v1.22.4/go.mod h1:t1ufH5HMublsJYulve2RKmHDC15xu1f26kHCp/HgceI=
|
||||
github.com/aws/aws-sdk-go-v2 v1.41.2 h1:LuT2rzqNQsauaGkPK/7813XxcZ3o3yePY0Iy891T2ls=
|
||||
github.com/aws/aws-sdk-go-v2 v1.41.2/go.mod h1:IvvlAZQXvTXznUPfRVfryiG1fbzE2NGK6m9u39YQ+S4=
|
||||
github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.7.5 h1:zWFmPmgw4sveAYi1mRqG+E/g0461cJ5M4bJ8/nc6d3Q=
|
||||
github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.7.5/go.mod h1:nVUlMLVV8ycXSb7mSkcNu9e3v/1TJq2RTlrPwhYWr5c=
|
||||
github.com/aws/aws-sdk-go-v2/config v1.32.10 h1:9DMthfO6XWZYLfzZglAgW5Fyou2nRI5CuV44sTedKBI=
|
||||
github.com/aws/aws-sdk-go-v2/config v1.32.10/go.mod h1:2rUIOnA2JaiqYmSKYmRJlcMWy6qTj1vuRFscppSBMcw=
|
||||
github.com/aws/aws-sdk-go-v2/credentials v1.19.10 h1:EEhmEUFCE1Yhl7vDhNOI5OCL/iKMdkkYFTRpZXNw7m8=
|
||||
github.com/aws/aws-sdk-go-v2/credentials v1.19.10/go.mod h1:RnnlFCAlxQCkN2Q379B67USkBMu1PipEEiibzYN5UTE=
|
||||
github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.18.18 h1:Ii4s+Sq3yDfaMLpjrJsqD6SmG/Wq/P5L/hw2qa78UAY=
|
||||
github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.18.18/go.mod h1:6x81qnY++ovptLE6nWQeWrpXxbnlIex+4H4eYYGcqfc=
|
||||
github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.18 h1:F43zk1vemYIqPAwhjTjYIz0irU2EY7sOb/F5eJ3HuyM=
|
||||
github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.18/go.mod h1:w1jdlZXrGKaJcNoL+Nnrj+k5wlpGXqnNrKoP22HvAug=
|
||||
github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.18 h1:xCeWVjj0ki0l3nruoyP2slHsGArMxeiiaoPN5QZH6YQ=
|
||||
github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.18/go.mod h1:r/eLGuGCBw6l36ZRWiw6PaZwPXb6YOj+i/7MizNl5/k=
|
||||
github.com/aws/aws-sdk-go-v2/internal/ini v1.8.4 h1:WKuaxf++XKWlHWu9ECbMlha8WOEGm0OUEZqm4K/Gcfk=
|
||||
github.com/aws/aws-sdk-go-v2/internal/ini v1.8.4/go.mod h1:ZWy7j6v1vWGmPReu0iSGvRiise4YI5SkR3OHKTZ6Wuc=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.50.0 h1:TDKR8ACRw7G+GFaQlhoy6biu+8q6ZtSddQCy9avMdMI=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.50.0/go.mod h1:XlhOh5Ax/lesqN4aZCUgj9vVJed5VoXYHHFYGAlJEwU=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.13.5 h1:CeY9LUdur+Dxoeldqoun6y4WtJ3RQtzk0JMP2gfUay0=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.13.5/go.mod h1:AZLZf2fMaahW5s/wMRciu1sYbdsikT/UHwbUjOdEVTc=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.13.18 h1:LTRCYFlnnKFlKsyIQxKhJuDuA3ZkrDQMRYm6rXiHlLY=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.13.18/go.mod h1:XhwkgGG6bHSd00nO/mexWTcTjgd6PjuvWQMqSn2UaEk=
|
||||
github.com/aws/aws-sdk-go-v2/service/signin v1.0.6 h1:MzORe+J94I+hYu2a6XmV5yC9huoTv8NRcCrUNedDypQ=
|
||||
github.com/aws/aws-sdk-go-v2/service/signin v1.0.6/go.mod h1:hXzcHLARD7GeWnifd8j9RWqtfIgxj4/cAtIVIK7hg8g=
|
||||
github.com/aws/aws-sdk-go-v2/service/sso v1.30.11 h1:7oGD8KPfBOJGXiCoRKrrrQkbvCp8N++u36hrLMPey6o=
|
||||
github.com/aws/aws-sdk-go-v2/service/sso v1.30.11/go.mod h1:0DO9B5EUJQlIDif+XJRWCljZRKsAFKh3gpFz7UnDtOo=
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.35.15 h1:edCcNp9eGIUDUCrzoCu1jWAXLGFIizeqkdkKgRlJwWc=
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.35.15/go.mod h1:lyRQKED9xWfgkYC/wmmYfv7iVIM68Z5OQ88ZdcV1QbU=
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.41.7 h1:NITQpgo9A5NrDZ57uOWj+abvXSb83BbyggcUBVksN7c=
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.41.7/go.mod h1:sks5UWBhEuWYDPdwlnRFn1w7xWdH29Jcpe+/PJQefEs=
|
||||
github.com/aws/smithy-go v1.24.1 h1:VbyeNfmYkWoxMVpGUAbQumkODcYmfMRfZ8yQiH30SK0=
|
||||
github.com/aws/smithy-go v1.24.1/go.mod h1:LEj2LM3rBRQJxPZTB4KuzZkaZYnZPnvgIhb4pu07mx0=
|
||||
github.com/davecgh/go-spew v1.1.2-0.20180830191138-d8f796af33cc h1:U9qPSI2PIWSS1VwoXQT9A3Wy9MM3WgvqSxFWenqJduM=
|
||||
github.com/davecgh/go-spew v1.1.2-0.20180830191138-d8f796af33cc/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
|
||||
github.com/dlclark/regexp2 v1.11.4 h1:rPYF9/LECdNymJufQKmri9gV604RvvABwgOA8un7yAo=
|
||||
|
||||
@@ -56,13 +56,13 @@ require (
|
||||
require (
|
||||
cloud.google.com/go/aiplatform v1.85.0
|
||||
cloud.google.com/go/vertexai v0.12.0
|
||||
github.com/aws/aws-sdk-go-v2 v1.36.5
|
||||
github.com/aws/aws-sdk-go-v2/config v1.29.4
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockagent v1.44.2
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockagentruntime v1.45.2
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.31.0
|
||||
github.com/aws/aws-sdk-go-v2 v1.41.2
|
||||
github.com/aws/aws-sdk-go-v2/config v1.32.10
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockagent v1.52.4
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockagentruntime v1.51.4
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.50.0
|
||||
github.com/aws/aws-sdk-go-v2/service/s3 v1.78.2
|
||||
github.com/aws/smithy-go v1.22.4
|
||||
github.com/aws/smithy-go v1.24.1
|
||||
golang.org/x/oauth2 v0.30.0
|
||||
google.golang.org/api v0.238.0
|
||||
google.golang.org/grpc v1.73.0
|
||||
@@ -127,20 +127,21 @@ require (
|
||||
cloud.google.com/go/compute/metadata v0.7.0 // indirect
|
||||
cloud.google.com/go/iam v1.5.2 // indirect
|
||||
cloud.google.com/go/longrunning v0.6.7 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.6.11 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/credentials v1.17.61 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.16.30 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/internal/configsources v1.3.36 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.6.36 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/internal/ini v1.8.2 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.7.5 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/credentials v1.19.10 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.18.18 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.18 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.18 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/internal/ini v1.8.4 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/internal/v4a v1.3.34 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.12.3 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.13.5 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/checksum v1.7.0 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.12.15 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.13.18 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/s3shared v1.18.15 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/sso v1.25.0 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.29.0 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.33.16 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/signin v1.0.6 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/sso v1.30.11 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.35.15 // indirect
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.41.7 // indirect
|
||||
github.com/bahlo/generic-list-go v0.2.0 // indirect
|
||||
github.com/buger/jsonparser v1.1.1 // indirect
|
||||
github.com/google/s2a-go v0.1.9 // indirect
|
||||
|
||||
@@ -78,46 +78,82 @@ github.com/asaskevich/govalidator v0.0.0-20230301143203-a9d515a09cc2/go.mod h1:W
|
||||
github.com/aws/aws-sdk-go v1.42.27/go.mod h1:OGr6lGMAKGlG9CVrYnWYDKIyb829c6EVBRjxqjmPepc=
|
||||
github.com/aws/aws-sdk-go-v2 v1.36.5 h1:0OF9RiEMEdDdZEMqF9MRjevyxAQcf6gY+E7vwBILFj0=
|
||||
github.com/aws/aws-sdk-go-v2 v1.36.5/go.mod h1:EYrzvCCN9CMUTa5+6lf6MM4tq3Zjp8UhSGR/cBsjai0=
|
||||
github.com/aws/aws-sdk-go-v2 v1.41.2 h1:LuT2rzqNQsauaGkPK/7813XxcZ3o3yePY0Iy891T2ls=
|
||||
github.com/aws/aws-sdk-go-v2 v1.41.2/go.mod h1:IvvlAZQXvTXznUPfRVfryiG1fbzE2NGK6m9u39YQ+S4=
|
||||
github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.6.11 h1:12SpdwU8Djs+YGklkinSSlcrPyj3H4VifVsKf78KbwA=
|
||||
github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.6.11/go.mod h1:dd+Lkp6YmMryke+qxW/VnKyhMBDTYP41Q2Bb+6gNZgY=
|
||||
github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.7.5 h1:zWFmPmgw4sveAYi1mRqG+E/g0461cJ5M4bJ8/nc6d3Q=
|
||||
github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.7.5/go.mod h1:nVUlMLVV8ycXSb7mSkcNu9e3v/1TJq2RTlrPwhYWr5c=
|
||||
github.com/aws/aws-sdk-go-v2/config v1.29.4 h1:ObNqKsDYFGr2WxnoXKOhCvTlf3HhwtoGgc+KmZ4H5yg=
|
||||
github.com/aws/aws-sdk-go-v2/config v1.29.4/go.mod h1:j2/AF7j/qxVmsNIChw1tWfsVKOayJoGRDjg1Tgq7NPk=
|
||||
github.com/aws/aws-sdk-go-v2/config v1.32.10 h1:9DMthfO6XWZYLfzZglAgW5Fyou2nRI5CuV44sTedKBI=
|
||||
github.com/aws/aws-sdk-go-v2/config v1.32.10/go.mod h1:2rUIOnA2JaiqYmSKYmRJlcMWy6qTj1vuRFscppSBMcw=
|
||||
github.com/aws/aws-sdk-go-v2/credentials v1.17.61 h1:Hd/uX6Wo2iUW1JWII+rmyCD7MMhOe7ALwQXN6sKDd1o=
|
||||
github.com/aws/aws-sdk-go-v2/credentials v1.17.61/go.mod h1:L7vaLkwHY1qgW0gG1zG0z/X0sQ5tpIY5iI13+j3qI80=
|
||||
github.com/aws/aws-sdk-go-v2/credentials v1.19.10 h1:EEhmEUFCE1Yhl7vDhNOI5OCL/iKMdkkYFTRpZXNw7m8=
|
||||
github.com/aws/aws-sdk-go-v2/credentials v1.19.10/go.mod h1:RnnlFCAlxQCkN2Q379B67USkBMu1PipEEiibzYN5UTE=
|
||||
github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.16.30 h1:x793wxmUWVDhshP8WW2mlnXuFrO4cOd3HLBroh1paFw=
|
||||
github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.16.30/go.mod h1:Jpne2tDnYiFascUEs2AWHJL9Yp7A5ZVy3TNyxaAjD6M=
|
||||
github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.18.18 h1:Ii4s+Sq3yDfaMLpjrJsqD6SmG/Wq/P5L/hw2qa78UAY=
|
||||
github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.18.18/go.mod h1:6x81qnY++ovptLE6nWQeWrpXxbnlIex+4H4eYYGcqfc=
|
||||
github.com/aws/aws-sdk-go-v2/internal/configsources v1.3.36 h1:SsytQyTMHMDPspp+spo7XwXTP44aJZZAC7fBV2C5+5s=
|
||||
github.com/aws/aws-sdk-go-v2/internal/configsources v1.3.36/go.mod h1:Q1lnJArKRXkenyog6+Y+zr7WDpk4e6XlR6gs20bbeNo=
|
||||
github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.18 h1:F43zk1vemYIqPAwhjTjYIz0irU2EY7sOb/F5eJ3HuyM=
|
||||
github.com/aws/aws-sdk-go-v2/internal/configsources v1.4.18/go.mod h1:w1jdlZXrGKaJcNoL+Nnrj+k5wlpGXqnNrKoP22HvAug=
|
||||
github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.6.36 h1:i2vNHQiXUvKhs3quBR6aqlgJaiaexz/aNvdCktW/kAM=
|
||||
github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.6.36/go.mod h1:UdyGa7Q91id/sdyHPwth+043HhmP6yP9MBHgbZM0xo8=
|
||||
github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.18 h1:xCeWVjj0ki0l3nruoyP2slHsGArMxeiiaoPN5QZH6YQ=
|
||||
github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.18/go.mod h1:r/eLGuGCBw6l36ZRWiw6PaZwPXb6YOj+i/7MizNl5/k=
|
||||
github.com/aws/aws-sdk-go-v2/internal/ini v1.8.2 h1:Pg9URiobXy85kgFev3og2CuOZ8JZUBENF+dcgWBaYNk=
|
||||
github.com/aws/aws-sdk-go-v2/internal/ini v1.8.2/go.mod h1:FbtygfRFze9usAadmnGJNc8KsP346kEe+y2/oyhGAGc=
|
||||
github.com/aws/aws-sdk-go-v2/internal/ini v1.8.4 h1:WKuaxf++XKWlHWu9ECbMlha8WOEGm0OUEZqm4K/Gcfk=
|
||||
github.com/aws/aws-sdk-go-v2/internal/ini v1.8.4/go.mod h1:ZWy7j6v1vWGmPReu0iSGvRiise4YI5SkR3OHKTZ6Wuc=
|
||||
github.com/aws/aws-sdk-go-v2/internal/v4a v1.3.34 h1:ZNTqv4nIdE/DiBfUUfXcLZ/Spcuz+RjeziUtNJackkM=
|
||||
github.com/aws/aws-sdk-go-v2/internal/v4a v1.3.34/go.mod h1:zf7Vcd1ViW7cPqYWEHLHJkS50X0JS2IKz9Cgaj6ugrs=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockagent v1.44.2 h1:gedxMyluRPy1ENN1dlOM7rK8Jek1wUvpA9z1Cz2s9N4=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockagent v1.44.2/go.mod h1:8zZaELHNLx6LNNfMrzCtVVsOFFKP1905FKmsSFuhArM=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockagent v1.52.4 h1:i5WL+AoS/AhMscsWkH6akQfJIujCVjbWiBwW36XheVk=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockagent v1.52.4/go.mod h1:8bRM14bpnsP+IzbJMlW0245dDZb0BFBuy0POlammksA=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockagentruntime v1.45.2 h1:bTaJuyz2i4XvlxMLBzXpdw9rjth9noDMKHB+lh/w3kk=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockagentruntime v1.45.2/go.mod h1:J/EFJdG12RxcljWx7vSgfx7L5rVuKpZHmFYO/SXTxKc=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockagentruntime v1.51.4 h1:oeSeyDAM2KQxu9bylfGZIspla7yXa6/59+Br3IvgNvQ=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockagentruntime v1.51.4/go.mod h1:eF5QHzRKSt9xvuxNlXC4QgH2+9JUGUWb8KND0+f5f2E=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.31.0 h1:BbtWSM9690zWbSOuJjBm7t7SIqDWhHPhKKQLhqxL+ac=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.31.0/go.mod h1:XHkvWM72+3dn5ox7yG0/yBEnQ2y0SMLCaXE/t96rv0I=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.50.0 h1:TDKR8ACRw7G+GFaQlhoy6biu+8q6ZtSddQCy9avMdMI=
|
||||
github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.50.0/go.mod h1:XlhOh5Ax/lesqN4aZCUgj9vVJed5VoXYHHFYGAlJEwU=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.12.3 h1:eAh2A4b5IzM/lum78bZ590jy36+d/aFLgKF/4Vd1xPE=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.12.3/go.mod h1:0yKJC/kb8sAnmlYa6Zs3QVYqaC8ug2AbnNChv5Ox3uA=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.13.5 h1:CeY9LUdur+Dxoeldqoun6y4WtJ3RQtzk0JMP2gfUay0=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.13.5/go.mod h1:AZLZf2fMaahW5s/wMRciu1sYbdsikT/UHwbUjOdEVTc=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/checksum v1.7.0 h1:lguz0bmOoGzozP9XfRJR1QIayEYo+2vP/No3OfLF0pU=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/checksum v1.7.0/go.mod h1:iu6FSzgt+M2/x3Dk8zhycdIcHjEFb36IS8HVUVFoMg0=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.12.15 h1:dM9/92u2F1JbDaGooxTq18wmmFzbJRfXfVfy96/1CXM=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.12.15/go.mod h1:SwFBy2vjtA0vZbjjaFtfN045boopadnoVPhu4Fv66vY=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.13.18 h1:LTRCYFlnnKFlKsyIQxKhJuDuA3ZkrDQMRYm6rXiHlLY=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.13.18/go.mod h1:XhwkgGG6bHSd00nO/mexWTcTjgd6PjuvWQMqSn2UaEk=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/s3shared v1.18.15 h1:moLQUoVq91LiqT1nbvzDukyqAlCv89ZmwaHw/ZFlFZg=
|
||||
github.com/aws/aws-sdk-go-v2/service/internal/s3shared v1.18.15/go.mod h1:ZH34PJUc8ApjBIfgQCFvkWcUDBtl/WTD+uiYHjd8igA=
|
||||
github.com/aws/aws-sdk-go-v2/service/s3 v1.78.2 h1:jIiopHEV22b4yQP2q36Y0OmwLbsxNWdWwfZRR5QRRO4=
|
||||
github.com/aws/aws-sdk-go-v2/service/s3 v1.78.2/go.mod h1:U5SNqwhXB3Xe6F47kXvWihPl/ilGaEDe8HD/50Z9wxc=
|
||||
github.com/aws/aws-sdk-go-v2/service/signin v1.0.6 h1:MzORe+J94I+hYu2a6XmV5yC9huoTv8NRcCrUNedDypQ=
|
||||
github.com/aws/aws-sdk-go-v2/service/signin v1.0.6/go.mod h1:hXzcHLARD7GeWnifd8j9RWqtfIgxj4/cAtIVIK7hg8g=
|
||||
github.com/aws/aws-sdk-go-v2/service/sso v1.25.0 h1:2U9sF8nKy7UgyEeLiZTRg6ShBS22z8UnYpV6aRFL0is=
|
||||
github.com/aws/aws-sdk-go-v2/service/sso v1.25.0/go.mod h1:qs4a9T5EMLl/Cajiw2TcbNt2UNo/Hqlyp+GiuG4CFDI=
|
||||
github.com/aws/aws-sdk-go-v2/service/sso v1.30.11 h1:7oGD8KPfBOJGXiCoRKrrrQkbvCp8N++u36hrLMPey6o=
|
||||
github.com/aws/aws-sdk-go-v2/service/sso v1.30.11/go.mod h1:0DO9B5EUJQlIDif+XJRWCljZRKsAFKh3gpFz7UnDtOo=
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.29.0 h1:wjAdc85cXdQR5uLx5FwWvGIHm4OPJhTyzUHU8craXtE=
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.29.0/go.mod h1:MlYRNmYu/fGPoxBQVvBYr9nyr948aY/WLUvwBMBJubs=
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.35.15 h1:edCcNp9eGIUDUCrzoCu1jWAXLGFIizeqkdkKgRlJwWc=
|
||||
github.com/aws/aws-sdk-go-v2/service/ssooidc v1.35.15/go.mod h1:lyRQKED9xWfgkYC/wmmYfv7iVIM68Z5OQ88ZdcV1QbU=
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.33.16 h1:BHEK2Q/7CMRMCb3nySi/w8UbIcPhKvYP5s1xf8/izn0=
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.33.16/go.mod h1:cQnB8CUnxbMU82JvlqjKR2HBOm3fe9pWorWBza6MBJ4=
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.41.7 h1:NITQpgo9A5NrDZ57uOWj+abvXSb83BbyggcUBVksN7c=
|
||||
github.com/aws/aws-sdk-go-v2/service/sts v1.41.7/go.mod h1:sks5UWBhEuWYDPdwlnRFn1w7xWdH29Jcpe+/PJQefEs=
|
||||
github.com/aws/smithy-go v1.22.4 h1:uqXzVZNuNexwc/xrh6Tb56u89WDlJY6HS+KC0S4QSjw=
|
||||
github.com/aws/smithy-go v1.22.4/go.mod h1:t1ufH5HMublsJYulve2RKmHDC15xu1f26kHCp/HgceI=
|
||||
github.com/aws/smithy-go v1.24.1 h1:VbyeNfmYkWoxMVpGUAbQumkODcYmfMRfZ8yQiH30SK0=
|
||||
github.com/aws/smithy-go v1.24.1/go.mod h1:LEj2LM3rBRQJxPZTB4KuzZkaZYnZPnvgIhb4pu07mx0=
|
||||
github.com/aymerick/douceur v0.2.0 h1:Mv+mAeH1Q+n9Fr+oyamOlAkUNPWPlA8PPGR0QAaYuPk=
|
||||
github.com/aymerick/douceur v0.2.0/go.mod h1:wlT5vV2O3h55X9m7iVYN0TBM0NH/MmbLnd30/FjWUq4=
|
||||
github.com/aymerick/raymond v2.0.3-0.20180322193309-b565731e1464+incompatible/go.mod h1:osfaiScAUVup+UC9Nfq76eWqDhXlp+4UYaA8uhTBO6g=
|
||||
|
||||
+704
-109
@@ -1,130 +1,725 @@
|
||||
# AWS Bedrock LLM Provider
|
||||
|
||||
A comprehensive Go implementation for AWS Bedrock LLM models with support for multiple providers, streaming, tool calling, and multimodal capabilities.
|
||||
Production-ready Go client for AWS Bedrock with support for 40+ models from 13 providers.
|
||||
|
||||
## Features
|
||||
## Architecture Overview
|
||||
|
||||
### 🤖 **Extensive Model Support**
|
||||
- **AI21**: Jamba 1.5 Large/Mini, Jamba Instruct
|
||||
- **Amazon**: Nova Premier/Pro/Lite/Micro, Titan Text Premier
|
||||
- **Anthropic**: Claude 4 Opus/Sonnet, Claude 3.7 Sonnet, Claude 3.5 Haiku/Sonnet
|
||||
- **Cohere**: Command-R, Command-R+, Command Text/Light
|
||||
- **Meta**: Llama 3.3 70B, Llama 3.1 8B, Llama 3 70B/8B
|
||||
- **DeepSeek**: R1
|
||||
|
||||
### 🚀 **Advanced Capabilities**
|
||||
- **Streaming**: Real-time response streaming for most models
|
||||
- **Tool Calling**: Full function calling support with streaming
|
||||
- **Reasoning**: Extended thinking support for Claude 3.7+ and Nova models
|
||||
- **Multimodal**: Text, image, and document processing
|
||||
- **Two APIs**: Modern Converse API + Legacy model-specific APIs
|
||||
|
||||
## Quick Start
|
||||
|
||||
```go
|
||||
import "github.com/vxcontrol/langchaingo/llms/bedrock"
|
||||
|
||||
// Basic usage
|
||||
llm, err := bedrock.New()
|
||||
|
||||
// With Converse API (recommended)
|
||||
llm, err := bedrock.New(
|
||||
bedrock.WithConverseAPI(),
|
||||
bedrock.WithModel(bedrock.ModelAnthropicClaudeSonnet4),
|
||||
)
|
||||
|
||||
resp, err := llm.GenerateContent(ctx, messages)
|
||||
```mermaid
|
||||
graph TB
|
||||
Client[Client Code] --> LLM[bedrock.LLM]
|
||||
LLM --> Processing[Message Processing]
|
||||
Processing --> Legacy[Legacy API Client]
|
||||
Processing --> Converse[Converse API Client]
|
||||
Legacy --> Anthropic[provider_anthropic.go]
|
||||
Legacy --> Nova[provider_nova.go]
|
||||
Legacy --> Others[provider_*.go]
|
||||
Converse --> ConverseClient[ConverseClient]
|
||||
Anthropic --> AWS[AWS SDK]
|
||||
Nova --> AWS
|
||||
Others --> AWS
|
||||
ConverseClient --> AWS
|
||||
```
|
||||
|
||||
## Streaming
|
||||
### Three-Layer Design
|
||||
|
||||
**Why this architecture?**
|
||||
|
||||
1. **Public API Layer** (`bedrockllm.go`)
|
||||
- Single entry point: `bedrock.LLM`
|
||||
- Hides complexity of dual API support
|
||||
- Manages automatic caching logic
|
||||
|
||||
2. **Message Processing Layer** (`processMessages()`)
|
||||
- Converts `llms.MessageContent` → `bedrockclient.Message`
|
||||
- Handles tool calls, reasoning, multimodal content
|
||||
- Applies automatic cache control insertion
|
||||
|
||||
3. **Internal Client Layer** (`internal/bedrockclient/`)
|
||||
- Provider-specific implementations
|
||||
- AWS SDK interaction
|
||||
- Response parsing and streaming
|
||||
|
||||
## Dual API Strategy
|
||||
|
||||
### Why Two APIs?
|
||||
|
||||
**Legacy API** (InvokeModel/InvokeModelWithResponseStream):
|
||||
- Direct access to model-specific features
|
||||
- Anthropic cache_control format support
|
||||
- Broader model compatibility
|
||||
- **Use when**: Model not supported by Converse API
|
||||
|
||||
**Converse API** (Converse/ConverseStream):
|
||||
- Unified interface across all models
|
||||
- Native cachePoint support (AWS SDK types)
|
||||
- Better error handling
|
||||
- **Use when**: Building new applications (recommended)
|
||||
|
||||
**Decision Point**: `useConverseAPI` flag in `LLM` struct
|
||||
|
||||
```mermaid
|
||||
flowchart LR
|
||||
A[GenerateContent] --> B{useConverseAPI?}
|
||||
B -->|true| C[generateContentWithConverseAPI]
|
||||
B -->|false| D[generateContentWithLegacyAPI]
|
||||
C --> E[ConverseClient]
|
||||
D --> F[Provider Detection]
|
||||
F --> G[createAnthropicCompletion]
|
||||
F --> H[createNovaCompletion]
|
||||
F --> I[create*Completion]
|
||||
```
|
||||
|
||||
## Automatic Prompt Caching
|
||||
|
||||
### How It Works
|
||||
|
||||
**Challenge**: Anthropic's prompt caching requires manual cache control wrappers on client side.
|
||||
|
||||
**Solution**: Automatic cache point insertion for Claude 4.x models.
|
||||
|
||||
```mermaid
|
||||
sequenceDiagram
|
||||
participant Client
|
||||
participant LLM
|
||||
participant Processing
|
||||
participant API
|
||||
|
||||
Client->>LLM: GenerateContent(messages)
|
||||
LLM->>LLM: supportsCaching(modelID)?
|
||||
alt Claude 4.x model
|
||||
LLM->>Processing: processMessagesWithCaching(autoCaching=true)
|
||||
Processing->>Processing: applyAutomaticCaching()
|
||||
Note over Processing: Add cache control to<br/>last assistant/tool message
|
||||
else Other model
|
||||
LLM->>Processing: processMessagesWithCaching(autoCaching=false)
|
||||
end
|
||||
Processing->>API: Send with cache points
|
||||
API-->>LLM: Response with cache metrics
|
||||
```
|
||||
|
||||
**Implementation**:
|
||||
- `supportsCaching()`: Pattern matching on model ID (`claude-opus-4`, `claude-sonnet-4`, `claude-haiku-4`)
|
||||
- `applyAutomaticCaching()`: Adds `CacheControl{Type: "ephemeral", TTL: "5m"}` to last cacheable message (assistant or tool response)
|
||||
- **Why last message?** Caches conversation history before new user input
|
||||
- **TTL Options**: 5 minutes (default) or 1 hour (configurable via `EphemeralCacheOneHour()`)
|
||||
|
||||
**Benefits**:
|
||||
- 90% cost reduction on cached tokens
|
||||
- Zero client code changes with automatic caching
|
||||
- Works with both Legacy and Converse APIs
|
||||
- Supports both manual (`WithCacheControl()`) and automatic (`WithAutomaticCaching()`) modes
|
||||
|
||||
## Tool Calling Implementation
|
||||
|
||||
### Provider-Specific Differences
|
||||
|
||||
**Why different implementations?**
|
||||
|
||||
Different providers use different formats for tool inputs in Converse API:
|
||||
|
||||
| Provider | Input Format | Handled By |
|
||||
|----------|-------------|------------|
|
||||
| Anthropic | Native JSON objects | `map[string]any` direct |
|
||||
| Nova | Native JSON objects | `map[string]any` direct |
|
||||
| Cohere | Native JSON objects | `map[string]any` direct |
|
||||
| GLM (Z.AI) | **String-based** | Not supported |
|
||||
|
||||
**Problems with specific models**:
|
||||
- **GLM (Z.AI)**: Backend expects tool input as string, not JSON object. This breaks Converse API spec.
|
||||
- **AI21 Jamba**: Very hard rate limits prevent extensive testing of tool calling capabilities.
|
||||
- **Meta Llama 3.3/3.1 70B/170B**: Unstable behavior when processing tool call results.
|
||||
- **Mistral Magistral Small**: Tool calling not supported.
|
||||
- **Moonshot Kimi K2-Thinking**: Unstable tool calling behavior in streaming mode.
|
||||
- **Qwen3-VL**: Unstable tool calling in streaming mode.
|
||||
|
||||
**Solution**: Models with backend issues or instability are excluded from tool calling tests.
|
||||
|
||||
### convertToolCallInput() Logic
|
||||
|
||||
**Why this function exists?**
|
||||
|
||||
AWS SDK requires Smithy-compatible types for `document.NewLazyDocument()`. Standard Go types from `json.Unmarshal` aren't always compatible.
|
||||
|
||||
```go
|
||||
streamingFunc := func(ctx context.Context, chunk streaming.Chunk) error {
|
||||
fmt.Print(chunk.Content)
|
||||
return nil
|
||||
func convertToolCallInput(args any) (any, error) {
|
||||
// 1. Check Smithy compatibility (structs with `document` tags)
|
||||
if isSmithyValidObject(args) {
|
||||
return args, nil
|
||||
}
|
||||
|
||||
// 2. Re-encode to normalize types for Smithy SDK
|
||||
// Uses UseNumber() to preserve numeric precision during JSON roundtrip
|
||||
jsonBytes := bytes.NewBuffer(nil)
|
||||
json.NewEncoder(jsonBytes).Encode(args)
|
||||
|
||||
decoder := json.NewDecoder(jsonBytes)
|
||||
decoder.UseNumber() // Preserves large numbers accurately
|
||||
|
||||
var jsonValue any
|
||||
decoder.Decode(&jsonValue)
|
||||
return jsonValue, nil
|
||||
}
|
||||
```
|
||||
|
||||
**Why UseNumber()?**
|
||||
|
||||
Preserves numeric precision for large integers that might overflow float64. The `json.Number` type is properly handled by Smithy SDK's document encoding.
|
||||
|
||||
### Document Unmarshal for Tool Responses
|
||||
|
||||
**Why `UnmarshalSmithyDocument()`?**
|
||||
|
||||
When extracting tool call from response, `block.Value.Input` is `document.LazyDocument`, not plain Go type:
|
||||
|
||||
```go
|
||||
// WRONG: json.Marshal on document - loses type info
|
||||
argsJSON, _ := json.Marshal(block.Value.Input)
|
||||
|
||||
// CORRECT: Unmarshal document first
|
||||
var inputData any
|
||||
block.Value.Input.UnmarshalSmithyDocument(&inputData)
|
||||
argsJSON, _ := json.Marshal(inputData)
|
||||
```
|
||||
|
||||
## Reasoning (Thinking) Support
|
||||
|
||||
### Models Supporting Reasoning
|
||||
|
||||
**Converse API**:
|
||||
- Claude 4.6, 4.5, 4.1, 4.0 (Opus, Sonnet, Haiku)
|
||||
- DeepSeek R1
|
||||
- OpenAI GPT OSS (120B, 20B)
|
||||
- Moonshot Kimi K2-Thinking
|
||||
|
||||
**Legacy API**:
|
||||
- Claude 4.5, 4.1, 4.0 (Opus, Sonnet, Haiku)
|
||||
- Claude 3.7 Sonnet
|
||||
|
||||
**Why these models?**
|
||||
|
||||
Extended thinking/reasoning capabilities are model-specific features. DeepSeek R1, OpenAI OSS, and Moonshot models provide reasoning through Converse API, while Anthropic models support both APIs.
|
||||
|
||||
### Message Structure with Reasoning
|
||||
|
||||
```mermaid
|
||||
flowchart TB
|
||||
A[AI Message with Reasoning] --> B{Legacy or Converse?}
|
||||
B -->|Legacy API| C[Add thinking/redacted_thinking blocks<br/>BEFORE text content]
|
||||
B -->|Converse API| D[Add ReasoningContent blocks<br/>with signature/redacted]
|
||||
C --> E[anthropicTextGenerationInputContent array]
|
||||
D --> F[types.ContentBlock array]
|
||||
```
|
||||
|
||||
**Why order matters?**
|
||||
|
||||
Anthropic API spec requires thinking blocks before text blocks in assistant messages.
|
||||
|
||||
### Signature Preservation
|
||||
|
||||
**Challenge**: Reasoning signatures must round-trip through conversations.
|
||||
|
||||
**Solution**: Store in `reasoning.ContentReasoning.Signature` field, re-insert on next turn.
|
||||
|
||||
```go
|
||||
// Receive
|
||||
choice.Reasoning.Signature = []byte(...)
|
||||
|
||||
// Send back
|
||||
llms.TextPartWithReasoning(content, reasoning)
|
||||
```
|
||||
|
||||
## Message Processing Pipeline
|
||||
|
||||
```mermaid
|
||||
flowchart LR
|
||||
A[llms.MessageContent] --> B[processMessagesWithCaching]
|
||||
B --> C{autoCaching?}
|
||||
C -->|true| D[applyAutomaticCaching]
|
||||
C -->|false| E[bedrockclient.Message array]
|
||||
D --> E
|
||||
E --> F{API Type}
|
||||
F -->|Legacy| G[Provider-specific format]
|
||||
F -->|Converse| H[types.Message]
|
||||
G --> I[InvokeModel]
|
||||
H --> J[Converse]
|
||||
```
|
||||
|
||||
### Key Transformations
|
||||
|
||||
**llms.MessageContent → bedrockclient.Message**:
|
||||
- Role mapping (System/Human/AI/Tool → provider format)
|
||||
- Content type detection (Text/Binary/ToolCall/ToolResponse)
|
||||
- Reasoning extraction and formatting
|
||||
- Cache control attachment
|
||||
|
||||
**bedrockclient.Message → AWS Request**:
|
||||
- Legacy: JSON serialization with provider schemas
|
||||
- Converse: AWS SDK types with document encoding
|
||||
|
||||
## Adding New Models
|
||||
|
||||
### Step-by-Step Process
|
||||
|
||||
1. **Add Model Constant** (`models_list.go`)
|
||||
```go
|
||||
// Include: Description, max tokens, languages, use cases
|
||||
ModelNewProvider = "provider.model-id"
|
||||
```
|
||||
|
||||
2. **Update Provider Detection** (if new provider)
|
||||
```go
|
||||
// bedrockclient.go
|
||||
case strings.Contains(modelID, "newprovider"):
|
||||
return "newprovider"
|
||||
```
|
||||
|
||||
3. **Implement Provider** (`internal/bedrockclient/provider_new.go`)
|
||||
```go
|
||||
func createNewProviderCompletion(ctx, client, modelID, messages, options) {
|
||||
// 1. Convert messages to provider format
|
||||
// 2. Build request payload
|
||||
// 3. Call InvokeModel
|
||||
// 4. Parse response
|
||||
// 5. Return llms.ContentResponse
|
||||
}
|
||||
```
|
||||
|
||||
4. **Register in Switch** (`bedrockclient.go`)
|
||||
```go
|
||||
case "newprovider":
|
||||
return createNewProviderCompletion(...)
|
||||
```
|
||||
|
||||
5. **Add Tests** (`bedrockllm_test.go`)
|
||||
- Add model to `TestAmazonOutputConverseAPI` models list (if Converse API supported)
|
||||
- Add model to `TestAmazonOutputLegacyAPI` models list (Legacy API)
|
||||
- Add model to `TestAmazonStreamingOutputConverseAPI` (if streaming supported)
|
||||
- Add model to `TestAmazonStreamingOutputLegacyAPI` (if streaming with Legacy API supported)
|
||||
- Add model to `TestAmazonToolCallingConverseAPI` (if tools supported)
|
||||
- Add model to `TestAmazonToolCallingLegacyAPI` (if tools with Legacy API supported)
|
||||
- Add model to `TestAmazonReasoningConverseAPI` (if reasoning/thinking supported)
|
||||
- Add model to `TestAmazonReasoningLegacyAPI` (if reasoning with Legacy API supported)
|
||||
|
||||
6. **Record HTTP Interactions**
|
||||
```bash
|
||||
HTTPRR_RECORD=. go test -v -run TestNewModel
|
||||
```
|
||||
|
||||
### Provider Implementation Checklist
|
||||
|
||||
- [ ] Input struct with all parameters (Temperature, TopP, MaxTokens, etc.)
|
||||
- [ ] Output struct matching API response
|
||||
- [ ] Streaming struct if model supports streaming
|
||||
- [ ] Error handling for provider-specific errors
|
||||
- [ ] Token usage extraction
|
||||
- [ ] Stop reason mapping
|
||||
|
||||
## Testing Strategy
|
||||
|
||||
### Why httprr?
|
||||
|
||||
**Problem**: Integration tests require AWS credentials and cost money.
|
||||
|
||||
**Solution**: Record HTTP interactions once, replay for fast tests.
|
||||
|
||||
```bash
|
||||
# Record new interactions
|
||||
HTTPRR_RECORD=. go test -v -run TestName
|
||||
|
||||
# Debug during recording
|
||||
HTTPRR_RECORD=. HTTPRR_DEBUG=true go test -v -run TestName
|
||||
|
||||
# Replay (default)
|
||||
go test -v -run TestName
|
||||
```
|
||||
|
||||
### Test Organization
|
||||
|
||||
**Test File**:
|
||||
|
||||
1. **bedrockllm_test.go**: Integration tests (requires AWS credentials)
|
||||
- Model output validation (Converse and Legacy API)
|
||||
- Streaming behavior (Converse and Legacy API)
|
||||
- Tool calling workflows (Converse and Legacy API, with streaming variants)
|
||||
- Reasoning roundtrips (Converse and Legacy API, with streaming variants)
|
||||
- Caching metrics (automatic and manual caching)
|
||||
- Extended thinking with tool calls
|
||||
- Multi-turn caching with tools
|
||||
- Client creation with different credential types (long-lived, bearer token)
|
||||
|
||||
2. **bedrockllm_unit_test.go**: Unit tests (no credentials)
|
||||
- Message processing logic
|
||||
- Option configuration
|
||||
- Cache control application
|
||||
- Provider detection
|
||||
|
||||
**Why separate files?**
|
||||
|
||||
- Unit tests run in CI without credentials
|
||||
- Integration tests record once, replay forever
|
||||
- Tool tests validate complex workflows
|
||||
|
||||
### Testing Non-Deterministic Tool Calls
|
||||
|
||||
**Challenge**: `map[string]any` serialization order is non-deterministic.
|
||||
|
||||
```go
|
||||
// First run: {"a": 15, "b": 8}
|
||||
// Second run: {"b": 8, "a": 15} // Different order!
|
||||
```
|
||||
|
||||
**Solution**: Skip second request in replay mode (`isReplaying` check).
|
||||
|
||||
```go
|
||||
if isReplaying {
|
||||
return nil // Don't send tool result
|
||||
}
|
||||
```
|
||||
|
||||
## Error Handling
|
||||
|
||||
### Error Mapping Strategy
|
||||
|
||||
**Why custom mapping?**
|
||||
|
||||
AWS errors are provider-specific strings. Need standardized codes for client logic.
|
||||
|
||||
```go
|
||||
// errors.go
|
||||
bedrockErrorMappings = []errorMapping{
|
||||
{patterns: []string{"throttlingexception"}, code: llms.ErrCodeRateLimit},
|
||||
{patterns: []string{"accessdenied"}, code: llms.ErrCodeAuthentication},
|
||||
// ...
|
||||
}
|
||||
```
|
||||
|
||||
**Usage**:
|
||||
```go
|
||||
if llmErr, ok := err.(*llms.Error); ok {
|
||||
switch llmErr.Code {
|
||||
case llms.ErrCodeRateLimit:
|
||||
// Implement backoff
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Streaming Implementation
|
||||
|
||||
### Event Processing Pattern
|
||||
|
||||
**Both APIs use AWS SDK event streams**, but different event types:
|
||||
|
||||
**Legacy API**:
|
||||
```go
|
||||
// Anthropic: streamingCompletionResponseChunk
|
||||
types: message_start, content_block_delta, message_delta, message_stop
|
||||
```
|
||||
|
||||
**Converse API**:
|
||||
```go
|
||||
// AWS SDK types
|
||||
ConverseStreamOutputMemberContentBlockDelta
|
||||
ConverseStreamOutputMemberContentBlockStart
|
||||
ConverseStreamOutputMemberContentBlockStop
|
||||
```
|
||||
|
||||
### Tool Call Streaming Accumulation
|
||||
|
||||
**Why accumulation needed?**
|
||||
|
||||
Tool arguments arrive in chunks:
|
||||
|
||||
```go
|
||||
// Chunk 1: {"operation"
|
||||
// Chunk 2: :"multiply","a"
|
||||
// Chunk 3: :15,"b":8}
|
||||
```
|
||||
|
||||
**Solution**: Accumulate in `streaming.ToolCall` map, send complete call at `ContentBlockStop`.
|
||||
|
||||
## Maintenance Guidelines
|
||||
|
||||
### When to Use Legacy vs Converse API
|
||||
|
||||
**Use Legacy API**:
|
||||
- Model doesn't support Converse API
|
||||
- Need Anthropic-specific cache_control format
|
||||
- Debugging provider-specific issues
|
||||
|
||||
**Use Converse API**:
|
||||
- Default for new implementations
|
||||
- Better error messages
|
||||
- Unified tool calling
|
||||
- Native cachePoint support
|
||||
|
||||
### Adding Caching Support
|
||||
|
||||
**Criteria**:
|
||||
1. Model must support Anthropic prompt caching (currently only Claude 4.x)
|
||||
2. Add pattern to `supportsCaching()` in `bedrockllm.go`:
|
||||
```go
|
||||
cachingPatterns := []string{
|
||||
"claude-opus-4",
|
||||
"claude-sonnet-4",
|
||||
"claude-haiku-4",
|
||||
"claude-new-4", // Add new model pattern
|
||||
}
|
||||
```
|
||||
3. Ensure model supports minimum 1024 tokens threshold for cache activation
|
||||
4. Add tests in `TestAmazonAutomaticCachingConverseAPI` and `TestAmazonAutomaticCachingLegacyAPI`
|
||||
|
||||
### Common Pitfalls
|
||||
|
||||
**1. Forgetting to handle nil FunctionCall**
|
||||
```go
|
||||
// BAD
|
||||
Name: part.FunctionCall.Name // Panic if nil
|
||||
|
||||
// GOOD
|
||||
if part.FunctionCall == nil {
|
||||
return errors.New("missing function call")
|
||||
}
|
||||
```
|
||||
|
||||
**2. Ignoring marshal errors**
|
||||
```go
|
||||
// BAD
|
||||
argsJSON, _ := json.Marshal(data)
|
||||
|
||||
// GOOD
|
||||
argsJSON, err := json.Marshal(data)
|
||||
if err != nil {
|
||||
return fmt.Errorf("marshal failed: %w", err)
|
||||
}
|
||||
```
|
||||
|
||||
**3. Not checking tool call arguments validity**
|
||||
```go
|
||||
// BAD - may pass invalid JSON to tool
|
||||
toolCall.FunctionCall.Arguments // No validation
|
||||
|
||||
// GOOD - validate tool arguments can be parsed
|
||||
var args map[string]any
|
||||
if err := json.Unmarshal([]byte(toolCall.FunctionCall.Arguments), &args); err != nil {
|
||||
return fmt.Errorf("invalid tool arguments: %w", err)
|
||||
}
|
||||
```
|
||||
|
||||
## File Organization
|
||||
|
||||
```
|
||||
llms/bedrock/
|
||||
├── bedrockllm.go # Main LLM implementation, message processing, caching
|
||||
├── bedrockllm_option.go # Configuration options
|
||||
├── bedrockllm_test.go # Integration tests (httprr recorded)
|
||||
├── bedrockllm_unit_test.go # Unit tests (no AWS required)
|
||||
├── models_list.go # Model constants and documentation
|
||||
├── errors.go # Error mapping
|
||||
├── doc.go # Package documentation
|
||||
├── tool_call_test.go # Tool call processing tests
|
||||
├── llmtest_test.go # LLM interface compliance tests
|
||||
└── internal/bedrockclient/
|
||||
├── bedrockclient.go # Legacy API client
|
||||
├── bedrockclient_converse.go # Converse API client
|
||||
├── bedrockclient_util.go # Smithy validation
|
||||
├── bedrockclient_test.go # Client tests
|
||||
├── bedrockclient_integration_test.go # Client integration tests
|
||||
├── provider_anthropic.go # Anthropic-specific implementation
|
||||
├── provider_nova.go # Nova-specific implementation
|
||||
├── provider_*.go # Other providers
|
||||
└── *_test.go # Provider tests
|
||||
```
|
||||
|
||||
## Key Design Decisions
|
||||
|
||||
### Why Separate Provider Files?
|
||||
|
||||
**Problem**: Single file would be 5000+ lines with mixed concerns.
|
||||
|
||||
**Solution**: Each provider in separate file with consistent interface.
|
||||
|
||||
**Benefits**:
|
||||
- Easy to add new providers
|
||||
- Clear separation of model-specific logic
|
||||
- Isolated testing
|
||||
|
||||
### Why Two Cache Control Formats?
|
||||
|
||||
**Legacy API**: Anthropic's `cache_control` in message content
|
||||
```json
|
||||
{
|
||||
"type": "text",
|
||||
"text": "...",
|
||||
"cache_control": {"type": "ephemeral", "ttl": "5m"}
|
||||
}
|
||||
```
|
||||
|
||||
**Converse API**: AWS's `cachePoint` blocks
|
||||
```json
|
||||
{
|
||||
"content": [
|
||||
{"text": "..."},
|
||||
{"cachePoint": {"type": "default", "ttl": "fiveMinutes"}}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
**Why support both?**
|
||||
- Legacy API: Anthropic `cache_control` format required (embedded in content blocks)
|
||||
- Converse API: AWS `cachePoint` format required (separate content block type)
|
||||
- Automatic caching abstracts the difference by using appropriate format based on API
|
||||
|
||||
### Message Processing: Content Parts to Messages
|
||||
|
||||
**Key Insight**: `llms.MessageContent` supports multiple content parts (text, images, tool calls), but provider APIs may require them as separate messages or flattened arrays.
|
||||
|
||||
**Processing Flow**:
|
||||
```go
|
||||
// Input: Single MessageContent with multiple parts
|
||||
llms.MessageContent{
|
||||
Role: llms.ChatMessageTypeHuman,
|
||||
Parts: [TextPart("Describe"), BinaryPart(imageData)]
|
||||
}
|
||||
|
||||
resp, err := llm.GenerateContent(ctx, messages,
|
||||
llms.WithStreamingFunc(streamingFunc),
|
||||
)
|
||||
// Output: Flat message array for provider API
|
||||
[
|
||||
Message{Type: "text", Content: "Describe"},
|
||||
Message{Type: "image", Content: base64Data, MimeType: "image/jpeg"}
|
||||
]
|
||||
```
|
||||
|
||||
## Tool Calling
|
||||
**Why flatten?**
|
||||
- Anthropic Legacy API: Requires flat content array per message
|
||||
- Nova/other providers: Each content type is separate array element
|
||||
- Simplifies provider-specific serialization logic
|
||||
|
||||
```go
|
||||
tools := []llms.Tool{{
|
||||
Type: "function",
|
||||
Function: &llms.FunctionDefinition{
|
||||
Name: "calculator",
|
||||
Description: "Perform arithmetic operations",
|
||||
Parameters: map[string]any{
|
||||
"type": "object",
|
||||
"properties": map[string]any{
|
||||
"operation": map[string]any{
|
||||
"type": "string",
|
||||
"enum": []string{"add", "subtract", "multiply", "divide"},
|
||||
},
|
||||
"a": map[string]any{"type": "number"},
|
||||
"b": map[string]any{"type": "number"},
|
||||
},
|
||||
"required": []string{"operation", "a", "b"},
|
||||
},
|
||||
},
|
||||
}}
|
||||
## Debugging Guide
|
||||
|
||||
resp, err := llm.GenerateContent(ctx, messages,
|
||||
llms.WithTools(tools),
|
||||
)
|
||||
```
|
||||
|
||||
## Configuration Options
|
||||
|
||||
```go
|
||||
// Custom AWS client
|
||||
client := bedrockruntime.NewFromConfig(cfg)
|
||||
llm, err := bedrock.New(bedrock.WithClient(client))
|
||||
|
||||
// Model selection
|
||||
llm, err := bedrock.New(bedrock.WithModel(bedrock.ModelAmazonNovaProV1))
|
||||
|
||||
// Enable Converse API (recommended for new applications)
|
||||
llm, err := bedrock.New(bedrock.WithConverseAPI())
|
||||
|
||||
// Callback handler
|
||||
llm, err := bedrock.New(bedrock.WithCallback(handler))
|
||||
```
|
||||
|
||||
## Key Differences
|
||||
|
||||
### Converse API vs Legacy API
|
||||
- **Converse API**: Unified interface, better tool calling, reasoning support
|
||||
- **Legacy API**: Direct model-specific implementations, broader model compatibility
|
||||
|
||||
### Model Capabilities
|
||||
- **Tool Calling**: Nova, Anthropic Claude 4/3.7/3.5, Cohere Command-R+
|
||||
- **Reasoning**: Anthropic Claude 4/3.7, Amazon Nova models
|
||||
- **Streaming**: Most models (except AI21 Jamba series)
|
||||
- **Multimodal**: Nova Pro/Lite, Claude models
|
||||
|
||||
## Environment Setup
|
||||
### Enable HTTP Logging
|
||||
|
||||
```bash
|
||||
export AWS_ACCESS_KEY_ID=your_access_key
|
||||
export AWS_SECRET_ACCESS_KEY=your_secret_key
|
||||
export AWS_REGION=us-east-1
|
||||
HTTPRR_DEBUG=true go test -v -run TestName
|
||||
```
|
||||
|
||||
## Testing
|
||||
### Check Cache Metrics
|
||||
|
||||
```bash
|
||||
# Basic functionality
|
||||
go test -v -run TestAmazonOutput
|
||||
|
||||
# Streaming support
|
||||
go test -v -run TestAmazonStreamingOutput
|
||||
|
||||
# Tool calling
|
||||
go test -v -run TestAmazonToolCalling
|
||||
```go
|
||||
resp.Choices[0].GenerationInfo["CacheReadInputTokens"] // Tokens read from cache
|
||||
resp.Choices[0].GenerationInfo["CacheCreationInputTokens"] // Tokens written to cache
|
||||
```
|
||||
|
||||
For comprehensive examples, see the [examples directory](../../examples/) in the langchaingo repository.
|
||||
### Validate Tool Call Arguments
|
||||
|
||||
Look for empty `Arguments` in logs - indicates parsing issue:
|
||||
```go
|
||||
if len(arguments) == 0 {
|
||||
// Check FunctionCall.Arguments JSON validity
|
||||
}
|
||||
```
|
||||
|
||||
### Common Errors
|
||||
|
||||
**"unsupported message type"**
|
||||
- Added new ContentPart type without handling in processMessages()
|
||||
|
||||
**"role not supported"**
|
||||
- Provider doesn't support message role (e.g., Function role)
|
||||
|
||||
**"completed due to max_tokens"**
|
||||
- Increase MaxTokens in request
|
||||
|
||||
**"cached HTTP response not found"**
|
||||
- httprr recording changed, re-record with `HTTPRR_RECORD=.`
|
||||
|
||||
## Performance Considerations
|
||||
|
||||
### Automatic Caching Impact
|
||||
|
||||
**First request**: Cache creation overhead (~50ms)
|
||||
**Subsequent requests**: 90% token cost reduction, ~20% latency reduction
|
||||
|
||||
**Best for**:
|
||||
- Long conversations (3+ turns)
|
||||
- Large system prompts (>1024 tokens)
|
||||
- Repeated context (tools, RAG documents)
|
||||
|
||||
### Streaming Latency
|
||||
|
||||
**Time to first token**: 200-500ms (depending on model)
|
||||
**Chunk frequency**: Every 20-50ms
|
||||
|
||||
**Use streaming when**:
|
||||
- User-facing chat interfaces
|
||||
- Long responses (>500 tokens)
|
||||
- Real-time feedback needed
|
||||
|
||||
## Future Enhancements
|
||||
|
||||
### Potential Improvements
|
||||
|
||||
1. **Converse API Migration**
|
||||
- Move all models to Converse API
|
||||
- Deprecate Legacy API providers
|
||||
- Why: Simpler maintenance, better consistency
|
||||
|
||||
2. **Smart Cache TTL Selection**
|
||||
- 5m for short conversations
|
||||
- 1h for long sessions
|
||||
- Why: Optimize cost vs cache hit rate
|
||||
|
||||
3. **Parallel Tool Calls**
|
||||
- Support multiple simultaneous tools
|
||||
- Why: Some models return parallel tool calls
|
||||
|
||||
4. **Structured Output**
|
||||
- JSON schema validation
|
||||
- Why: Type-safe responses
|
||||
|
||||
## Contributing
|
||||
|
||||
### Before Adding Features
|
||||
|
||||
1. Check if Converse API supports it natively
|
||||
2. Consider impact on both API paths
|
||||
3. Add tests for both streaming and non-streaming
|
||||
4. Update httprr recordings
|
||||
|
||||
### Code Review Checklist
|
||||
|
||||
- [ ] Error handling for all AWS SDK calls
|
||||
- [ ] Nil checks for optional fields
|
||||
- [ ] Cache control doesn't break non-caching models
|
||||
- [ ] Tool calling tested with real model
|
||||
- [ ] httprr recordings committed
|
||||
- [ ] Documentation updated
|
||||
|
||||
## Supported Model Matrix
|
||||
|
||||
| Provider | Tool Calling | Reasoning | Streaming | Multimodal | Caching |
|
||||
|----------|-------------|-----------|-----------|------------|---------|
|
||||
| Claude 4.6 | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
| Claude 4.5 | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
| Claude 4.1 | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
| Claude 4.0 | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
| Claude 3.7 | ✅ | ✅ | ✅ | ❌ | ❌ |
|
||||
| Claude 3.5 | ✅ | ❌ | ✅ | ❌ | ❌ |
|
||||
| Nova 2/Pro/Lite | ✅ | ❌ | ✅ | ✅ | ❌ |
|
||||
| Llama 4 | Limited | ❌ | ✅ | ✅ | ❌ |
|
||||
| Cohere R+ | ✅ | ❌ | ✅ | ❌ | ❌ |
|
||||
| DeepSeek V3.2 | ✅ | ❌ | ✅ | ❌ | ❌ |
|
||||
| DeepSeek R1 | ❌ | ✅ | ✅ | ❌ | ❌ |
|
||||
| AI21 Jamba | Limited* | ❌ | ✅** | ❌ | ❌ |
|
||||
| OpenAI GPT (OSS) | ✅ | ✅ | ✅ | ❌ | ❌ |
|
||||
| Qwen3 | Varies*** | ❌ | ✅ | Some | ❌ |
|
||||
| Mistral | ✅**** | ❌ | ✅ | ❌ | ❌ |
|
||||
| Moonshot Kimi | ✅***** | ✅ | ✅ | ❌ | ❌ |
|
||||
| GLM-4.7 | ❌****** | ❌ | ✅ | ❌ | ❌ |
|
||||
|
||||
*AI21 Jamba: Rate limits prevent extensive tool calling testing
|
||||
**AI21 Jamba: Streaming supported only with Converse API
|
||||
***Qwen3: Most models support tools, except Qwen3-VL (unstable in streaming)
|
||||
****Mistral: Large3 and Large2402 support tools, MagistralSmall2509 does not
|
||||
*****Moonshot: K2.5 supports tools, K2-Thinking is unstable
|
||||
******GLM models: Backend incompatibility with Converse API tool format (requires string instead of JSON)
|
||||
|
||||
See `models_list.go` for complete model list and detailed capabilities.
|
||||
|
||||
@@ -1,200 +0,0 @@
|
||||
package bedrock_test
|
||||
|
||||
import (
|
||||
"context"
|
||||
"encoding/json"
|
||||
"net/http"
|
||||
"os"
|
||||
"testing"
|
||||
|
||||
"github.com/stretchr/testify/require"
|
||||
"github.com/vxcontrol/langchaingo/internal/httprr"
|
||||
"github.com/vxcontrol/langchaingo/llms"
|
||||
"github.com/vxcontrol/langchaingo/llms/bedrock"
|
||||
)
|
||||
|
||||
func TestBedrockAnthropicToolCalling(t *testing.T) { //nolint:funlen
|
||||
ctx := context.Background()
|
||||
|
||||
httprr.SkipIfNoCredentialsAndRecordingMissing(t, "AWS_ACCESS_KEY_ID")
|
||||
|
||||
rr := httprr.OpenForTest(t, http.DefaultTransport)
|
||||
defer rr.Close()
|
||||
|
||||
// Only run tests in parallel when not recording (to avoid rate limits)
|
||||
if !rr.Recording() {
|
||||
t.Parallel()
|
||||
}
|
||||
|
||||
// Configure AWS client to use httprr transport
|
||||
client, err := setUpTestWithTransport(rr)
|
||||
if err != nil {
|
||||
t.Fatal(err)
|
||||
}
|
||||
|
||||
llm, err := bedrock.New(bedrock.WithClient(client))
|
||||
if err != nil {
|
||||
t.Fatal(err)
|
||||
}
|
||||
|
||||
// Define a weather tool
|
||||
weatherTool := llms.Tool{
|
||||
Type: "function",
|
||||
Function: &llms.FunctionDefinition{
|
||||
Name: "get_weather",
|
||||
Description: "Get the current weather for a location",
|
||||
Parameters: map[string]any{
|
||||
"type": "object",
|
||||
"properties": map[string]any{
|
||||
"location": map[string]any{
|
||||
"type": "string",
|
||||
"description": "The city and state, e.g. San Francisco, CA",
|
||||
},
|
||||
"unit": map[string]any{
|
||||
"type": "string",
|
||||
"enum": []string{"celsius", "fahrenheit"},
|
||||
"description": "The unit of temperature",
|
||||
},
|
||||
},
|
||||
"required": []string{"location"},
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
t.Run("Anthropic Claude 3 with tool calling", func(t *testing.T) {
|
||||
// Skip if not recording and no credentials
|
||||
if !rr.Recording() && !hasAWSCredentials() {
|
||||
t.Skip("Skipping test: no AWS credentials and not recording")
|
||||
}
|
||||
|
||||
msgs := []llms.MessageContent{
|
||||
llms.TextParts(llms.ChatMessageTypeHuman, "What's the weather like in New York?"),
|
||||
}
|
||||
|
||||
resp, err := llm.GenerateContent(ctx, msgs,
|
||||
llms.WithModel(bedrock.ModelAnthropicClaudeHaiku45),
|
||||
llms.WithTools([]llms.Tool{weatherTool}),
|
||||
llms.WithMaxTokens(512),
|
||||
)
|
||||
if err != nil {
|
||||
t.Fatal(err)
|
||||
}
|
||||
|
||||
require.NotNil(t, resp)
|
||||
require.NotEmpty(t, resp.Choices)
|
||||
|
||||
// Check if the model wants to use the tool
|
||||
choice := resp.Choices[0]
|
||||
if len(choice.ToolCalls) > 0 {
|
||||
t.Logf("Model requested tool call: %+v", choice.ToolCalls[0])
|
||||
|
||||
// Verify tool call structure
|
||||
toolCall := choice.ToolCalls[0]
|
||||
require.Equal(t, "function", toolCall.Type)
|
||||
require.NotNil(t, toolCall.FunctionCall)
|
||||
require.Equal(t, "get_weather", toolCall.FunctionCall.Name)
|
||||
|
||||
// Parse arguments
|
||||
var args map[string]any
|
||||
err := json.Unmarshal([]byte(toolCall.FunctionCall.Arguments), &args)
|
||||
require.NoError(t, err)
|
||||
require.Contains(t, args, "location")
|
||||
|
||||
// Add assistant response with tool call
|
||||
assistantResponse := llms.MessageContent{
|
||||
Role: llms.ChatMessageTypeAI,
|
||||
Parts: []llms.ContentPart{
|
||||
llms.ToolCall{
|
||||
ID: toolCall.ID,
|
||||
Type: toolCall.Type,
|
||||
FunctionCall: &llms.FunctionCall{
|
||||
Name: toolCall.FunctionCall.Name,
|
||||
Arguments: toolCall.FunctionCall.Arguments,
|
||||
},
|
||||
},
|
||||
},
|
||||
}
|
||||
msgs = append(msgs, assistantResponse)
|
||||
|
||||
// Add tool response
|
||||
toolResponse := llms.MessageContent{
|
||||
Role: llms.ChatMessageTypeTool,
|
||||
Parts: []llms.ContentPart{
|
||||
llms.ToolCallResponse{
|
||||
ToolCallID: toolCall.ID,
|
||||
Name: "get_weather",
|
||||
Content: "It's currently 72°F and sunny in New York",
|
||||
},
|
||||
},
|
||||
}
|
||||
msgs = append(msgs, toolResponse)
|
||||
|
||||
resp2, err := llm.GenerateContent(ctx, msgs,
|
||||
llms.WithModel(bedrock.ModelAnthropicClaudeHaiku45),
|
||||
llms.WithMaxTokens(512),
|
||||
)
|
||||
require.NoError(t, err)
|
||||
require.NotNil(t, resp2)
|
||||
require.NotEmpty(t, resp2.Choices)
|
||||
|
||||
t.Logf("Final response: %s", resp2.Choices[0].Content)
|
||||
} else {
|
||||
t.Logf("Model response without tool call: %s", choice.Content)
|
||||
}
|
||||
})
|
||||
|
||||
t.Run("Multiple tools", func(t *testing.T) {
|
||||
// Skip if not recording and no credentials
|
||||
if !rr.Recording() && !hasAWSCredentials() {
|
||||
t.Skip("Skipping test: no AWS credentials and not recording")
|
||||
}
|
||||
|
||||
calculatorTool := llms.Tool{
|
||||
Type: "function",
|
||||
Function: &llms.FunctionDefinition{
|
||||
Name: "calculate",
|
||||
Description: "Perform mathematical calculations",
|
||||
Parameters: map[string]any{
|
||||
"type": "object",
|
||||
"properties": map[string]any{
|
||||
"expression": map[string]any{
|
||||
"type": "string",
|
||||
"description": "The mathematical expression to evaluate",
|
||||
},
|
||||
},
|
||||
"required": []string{"expression"},
|
||||
},
|
||||
},
|
||||
}
|
||||
|
||||
msgs := []llms.MessageContent{
|
||||
llms.TextParts(llms.ChatMessageTypeHuman, "What's 123 * 456 and what's the weather in Paris?"),
|
||||
}
|
||||
|
||||
resp, err := llm.GenerateContent(ctx, msgs,
|
||||
llms.WithModel(bedrock.ModelAnthropicClaudeHaiku45),
|
||||
llms.WithTools([]llms.Tool{weatherTool, calculatorTool}),
|
||||
llms.WithMaxTokens(512),
|
||||
)
|
||||
if err != nil {
|
||||
t.Fatal(err)
|
||||
}
|
||||
|
||||
require.NotNil(t, resp)
|
||||
require.NotEmpty(t, resp.Choices)
|
||||
|
||||
// Check for multiple tool calls
|
||||
choice := resp.Choices[0]
|
||||
t.Logf("Number of tool calls: %d", len(choice.ToolCalls))
|
||||
for i, tc := range choice.ToolCalls {
|
||||
t.Logf("Tool call %d: %s(%s)", i, tc.FunctionCall.Name, tc.FunctionCall.Arguments)
|
||||
}
|
||||
})
|
||||
}
|
||||
|
||||
func hasAWSCredentials() bool {
|
||||
// Check if AWS credentials are available
|
||||
_, hasKey := os.LookupEnv("AWS_ACCESS_KEY_ID")
|
||||
_, hasProfile := os.LookupEnv("AWS_PROFILE")
|
||||
return hasKey || hasProfile
|
||||
}
|
||||
+157
-17
@@ -4,6 +4,9 @@ import (
|
||||
"context"
|
||||
"encoding/json"
|
||||
"errors"
|
||||
"fmt"
|
||||
"strings"
|
||||
"time"
|
||||
|
||||
"github.com/vxcontrol/langchaingo/callbacks"
|
||||
"github.com/vxcontrol/langchaingo/llms"
|
||||
@@ -17,11 +20,12 @@ const defaultModel = ModelAnthropicClaudeHaiku45
|
||||
|
||||
// LLM is a Bedrock LLM implementation.
|
||||
type LLM struct {
|
||||
modelID string
|
||||
client *bedrockclient.Client
|
||||
converseClient *bedrockclient.ConverseClient
|
||||
useConverseAPI bool
|
||||
CallbacksHandler callbacks.Handler
|
||||
modelID string
|
||||
client *bedrockclient.Client
|
||||
converseClient *bedrockclient.ConverseClient
|
||||
useConverseAPI bool
|
||||
enableAutoCaching bool
|
||||
CallbacksHandler callbacks.Handler
|
||||
}
|
||||
|
||||
// New creates a new Bedrock LLM implementation.
|
||||
@@ -36,11 +40,12 @@ func NewWithContext(ctx context.Context, opts ...Option) (*LLM, error) {
|
||||
return nil, err
|
||||
}
|
||||
return &LLM{
|
||||
client: c,
|
||||
converseClient: converseC,
|
||||
useConverseAPI: o.useConverseAPI,
|
||||
modelID: o.modelID,
|
||||
CallbacksHandler: o.callbackHandler,
|
||||
client: c,
|
||||
converseClient: converseC,
|
||||
useConverseAPI: o.useConverseAPI,
|
||||
enableAutoCaching: o.enableAutoCaching,
|
||||
modelID: o.modelID,
|
||||
CallbacksHandler: o.callbackHandler,
|
||||
}, nil
|
||||
}
|
||||
|
||||
@@ -97,11 +102,19 @@ func (l *LLM) GenerateContent(ctx context.Context, messages []llms.MessageConten
|
||||
|
||||
// generateContentWithConverseAPI uses the unified Converse API
|
||||
func (l *LLM) generateContentWithConverseAPI(ctx context.Context, messages []llms.MessageContent, opts llms.CallOptions) (*llms.ContentResponse, error) {
|
||||
m, err := processMessages(messages)
|
||||
// Apply automatic caching to bedrock messages if enabled
|
||||
shouldAutoCache := l.enableAutoCaching && l.supportsCaching(opts.Model)
|
||||
m, err := processMessagesWithCaching(messages, shouldAutoCache)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
// Check if caching should be enabled
|
||||
// Caching is enabled if either:
|
||||
// 1. Automatic caching is enabled and model supports it
|
||||
// 2. Manual cache control is present in messages
|
||||
enableCaching := shouldAutoCache || checkIfCachingRequested(messages)
|
||||
|
||||
// Build Converse input
|
||||
input := &bedrockclient.ConverseInput{
|
||||
ModelID: opts.Model,
|
||||
@@ -109,6 +122,7 @@ func (l *LLM) generateContentWithConverseAPI(ctx context.Context, messages []llm
|
||||
Tools: opts.Tools,
|
||||
StreamingFunc: opts.StreamingFunc,
|
||||
ReasoningConfig: opts.Reasoning,
|
||||
EnableCaching: enableCaching,
|
||||
}
|
||||
|
||||
// Set inference parameters
|
||||
@@ -142,7 +156,9 @@ func (l *LLM) generateContentWithConverseAPI(ctx context.Context, messages []llm
|
||||
|
||||
// generateContentWithLegacyAPI uses the original model-specific implementations
|
||||
func (l *LLM) generateContentWithLegacyAPI(ctx context.Context, messages []llms.MessageContent, opts llms.CallOptions) (*llms.ContentResponse, error) {
|
||||
m, err := processMessages(messages)
|
||||
// Apply automatic caching to bedrock messages if enabled
|
||||
shouldAutoCache := l.enableAutoCaching && l.supportsCaching(opts.Model)
|
||||
m, err := processMessagesWithCaching(messages, shouldAutoCache)
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
@@ -163,16 +179,45 @@ func (l *LLM) generateContentWithLegacyAPI(ctx context.Context, messages []llms.
|
||||
}
|
||||
|
||||
func processMessages(messages []llms.MessageContent) ([]bedrockclient.Message, error) {
|
||||
return processMessagesWithCaching(messages, false)
|
||||
}
|
||||
|
||||
func processMessagesWithCaching(messages []llms.MessageContent, autoCaching bool) ([]bedrockclient.Message, error) {
|
||||
bedrockMsgs := make([]bedrockclient.Message, 0, len(messages))
|
||||
|
||||
for _, m := range messages {
|
||||
for _, part := range m.Parts {
|
||||
switch part := part.(type) {
|
||||
case CachedContent:
|
||||
// Handle cached content with cache control
|
||||
cacheControl := convertCacheControl(part.CacheControl)
|
||||
// Process the wrapped content
|
||||
switch wrapped := part.ContentPart.(type) {
|
||||
case llms.TextContent:
|
||||
bedrockMsgs = append(bedrockMsgs, bedrockclient.Message{
|
||||
Role: m.Role,
|
||||
Content: wrapped.Text,
|
||||
Type: "text",
|
||||
Reasoning: wrapped.Reasoning,
|
||||
CacheControl: cacheControl,
|
||||
})
|
||||
case llms.BinaryContent:
|
||||
bedrockMsgs = append(bedrockMsgs, bedrockclient.Message{
|
||||
Role: m.Role,
|
||||
Content: string(wrapped.Data),
|
||||
MimeType: wrapped.MIMEType,
|
||||
Type: "image",
|
||||
CacheControl: cacheControl,
|
||||
})
|
||||
default:
|
||||
return nil, errors.New("unsupported cached content type")
|
||||
}
|
||||
case llms.TextContent:
|
||||
bedrockMsgs = append(bedrockMsgs, bedrockclient.Message{
|
||||
Role: m.Role,
|
||||
Content: part.Text,
|
||||
Type: "text",
|
||||
Role: m.Role,
|
||||
Content: part.Text,
|
||||
Type: "text",
|
||||
Reasoning: part.Reasoning,
|
||||
})
|
||||
case llms.BinaryContent:
|
||||
bedrockMsgs = append(bedrockMsgs, bedrockclient.Message{
|
||||
@@ -182,10 +227,13 @@ func processMessages(messages []llms.MessageContent) ([]bedrockclient.Message, e
|
||||
Type: "image",
|
||||
})
|
||||
case llms.ToolCall:
|
||||
if part.FunctionCall == nil {
|
||||
return nil, errors.New("tool call missing function call data")
|
||||
}
|
||||
var arguments map[string]any
|
||||
if part.FunctionCall != nil {
|
||||
if part.FunctionCall.Arguments != "" {
|
||||
if err := json.Unmarshal([]byte(part.FunctionCall.Arguments), &arguments); err != nil {
|
||||
return nil, err
|
||||
return nil, fmt.Errorf("failed to unmarshal tool call arguments: %w", err)
|
||||
}
|
||||
}
|
||||
bedrockMsgs = append(bedrockMsgs, bedrockclient.Message{
|
||||
@@ -208,11 +256,103 @@ func processMessages(messages []llms.MessageContent) ([]bedrockclient.Message, e
|
||||
},
|
||||
})
|
||||
default:
|
||||
// Check if it's unknown type - might be a specific provider type
|
||||
return nil, errors.New("unsupported message type")
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Apply automatic caching if requested
|
||||
if autoCaching {
|
||||
applyAutomaticCaching(bedrockMsgs)
|
||||
}
|
||||
|
||||
return bedrockMsgs, nil
|
||||
}
|
||||
|
||||
// applyAutomaticCaching adds cache control to the last assistant or tool message
|
||||
// to enable conversation history caching without manual intervention.
|
||||
func applyAutomaticCaching(messages []bedrockclient.Message) {
|
||||
if len(messages) == 0 {
|
||||
return
|
||||
}
|
||||
|
||||
// Find the last assistant or tool message before the current user turn
|
||||
lastCacheableIdx := -1
|
||||
for i := len(messages) - 1; i >= 0; i-- {
|
||||
// Skip the last message if it's from human (current turn)
|
||||
if i == len(messages)-1 && messages[i].Role == llms.ChatMessageTypeHuman {
|
||||
continue
|
||||
}
|
||||
// Find last assistant or tool message
|
||||
if messages[i].Role == llms.ChatMessageTypeAI || messages[i].Role == llms.ChatMessageTypeTool {
|
||||
lastCacheableIdx = i
|
||||
break
|
||||
}
|
||||
}
|
||||
|
||||
if lastCacheableIdx == -1 {
|
||||
return
|
||||
}
|
||||
|
||||
// Add cache control to the selected message
|
||||
if messages[lastCacheableIdx].CacheControl == nil {
|
||||
messages[lastCacheableIdx].CacheControl = &bedrockclient.CacheControl{
|
||||
Type: "ephemeral",
|
||||
TTL: "5m",
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// convertCacheControl converts shared llms.CacheControl to Bedrock-specific format
|
||||
func convertCacheControl(llmCache *llms.CacheControl) *bedrockclient.CacheControl {
|
||||
if llmCache == nil {
|
||||
return nil
|
||||
}
|
||||
|
||||
bedrockCache := &bedrockclient.CacheControl{
|
||||
Type: llmCache.Type,
|
||||
}
|
||||
|
||||
// Convert duration to TTL string
|
||||
if llmCache.Duration > 0 {
|
||||
if llmCache.Duration >= time.Hour {
|
||||
bedrockCache.TTL = "1h"
|
||||
} else {
|
||||
bedrockCache.TTL = "5m"
|
||||
}
|
||||
}
|
||||
|
||||
return bedrockCache
|
||||
}
|
||||
|
||||
// checkIfCachingRequested checks if any messages contain CachedContent
|
||||
func checkIfCachingRequested(messages []llms.MessageContent) bool {
|
||||
for _, msg := range messages {
|
||||
for _, part := range msg.Parts {
|
||||
if _, ok := part.(CachedContent); ok {
|
||||
return true
|
||||
}
|
||||
}
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
// supportsCaching checks if the model supports prompt caching
|
||||
func (l *LLM) supportsCaching(modelID string) bool {
|
||||
// All Claude 4.x models support prompt caching (Opus, Sonnet, Haiku)
|
||||
cachingPatterns := []string{
|
||||
"claude-opus-4",
|
||||
"claude-sonnet-4",
|
||||
"claude-haiku-4",
|
||||
}
|
||||
|
||||
for _, pattern := range cachingPatterns {
|
||||
if strings.Contains(modelID, pattern) {
|
||||
return true
|
||||
}
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
var _ llms.Model = (*LLM)(nil)
|
||||
|
||||
@@ -1,7 +1,10 @@
|
||||
package bedrock
|
||||
|
||||
import (
|
||||
"time"
|
||||
|
||||
"github.com/vxcontrol/langchaingo/callbacks"
|
||||
"github.com/vxcontrol/langchaingo/llms"
|
||||
|
||||
"github.com/aws/aws-sdk-go-v2/service/bedrockruntime"
|
||||
)
|
||||
@@ -10,11 +13,12 @@ import (
|
||||
type Option func(*options)
|
||||
|
||||
type options struct {
|
||||
modelProvider string
|
||||
modelID string
|
||||
client *bedrockruntime.Client
|
||||
callbackHandler callbacks.Handler
|
||||
useConverseAPI bool
|
||||
modelProvider string
|
||||
modelID string
|
||||
client *bedrockruntime.Client
|
||||
callbackHandler callbacks.Handler
|
||||
useConverseAPI bool
|
||||
enableAutoCaching bool
|
||||
}
|
||||
|
||||
// WithModel allows setting a custom modelId.
|
||||
@@ -67,13 +71,95 @@ func WithCallback(callbackHandler callbacks.Handler) Option {
|
||||
// - Reasoning content support for Claude 3.7+ and Nova models
|
||||
// - Multimodal input support (text, images, documents)
|
||||
// - Better error handling and response consistency
|
||||
// - Prompt caching support via cachePoint (requires AWS SDK types)
|
||||
//
|
||||
// Supported models: All Anthropic Claude, Amazon Nova, Meta Llama,
|
||||
// Cohere Command, and AI21 Jamba models available through Bedrock.
|
||||
//
|
||||
// Note: This is the recommended approach for new applications.
|
||||
//
|
||||
// Prompt Caching:
|
||||
// - Legacy API (InvokeModel) supports Anthropic's cache_control format
|
||||
// - Converse API supports cachePoint via SystemContentBlockMemberCachePoint
|
||||
// - Cache metrics are returned in response.Usage (CacheReadInputTokens, CacheWriteInputTokens)
|
||||
// - Requires minimum tokens per checkpoint (1024 for Sonnet 4.5, 4096 for Haiku 4.5)
|
||||
// - Supports 5m and 1h TTL for Claude 4.x models
|
||||
func WithConverseAPI() Option {
|
||||
return func(o *options) {
|
||||
o.useConverseAPI = true
|
||||
}
|
||||
}
|
||||
|
||||
// WithAutomaticCaching enables automatic prompt caching for supported Anthropic models.
|
||||
//
|
||||
// When enabled, caching is automatically applied for models matching these patterns:
|
||||
// - claude-opus-4 (includes 4.6, 4.5, 4.1, 4.0)
|
||||
// - claude-sonnet-4 (includes 4.6, 4.5, 4.0)
|
||||
// - claude-haiku-4 (includes 4.5)
|
||||
//
|
||||
// The caching strategy automatically:
|
||||
// - Adds cache points to system prompts
|
||||
// - Adds cache points to conversation history (last message before new user input)
|
||||
// - Uses ephemeral 5-minute TTL by default
|
||||
//
|
||||
// Benefits:
|
||||
// - 90% cost reduction on cached input tokens
|
||||
// - No manual cache control wrapper needed on client side
|
||||
// - Transparent caching without modifying message chains
|
||||
//
|
||||
// Note: Automatic caching works with both Legacy and Converse APIs.
|
||||
func WithAutomaticCaching() Option {
|
||||
return func(o *options) {
|
||||
o.enableAutoCaching = true
|
||||
}
|
||||
}
|
||||
|
||||
// EphemeralCache creates a standard ephemeral cache control for Bedrock with 5-minute duration.
|
||||
func EphemeralCache() *llms.CacheControl {
|
||||
return &llms.CacheControl{
|
||||
Type: "ephemeral",
|
||||
Duration: 5 * time.Minute,
|
||||
}
|
||||
}
|
||||
|
||||
// EphemeralCacheOneHour creates a 1-hour ephemeral cache control for Bedrock.
|
||||
// Supported by Claude Opus 4.5, Haiku 4.5, and Sonnet 4.5.
|
||||
func EphemeralCacheOneHour() *llms.CacheControl {
|
||||
return &llms.CacheControl{
|
||||
Type: "ephemeral",
|
||||
Duration: time.Hour,
|
||||
}
|
||||
}
|
||||
|
||||
// CachedContent represents content with caching instructions for Bedrock.
|
||||
// This wraps any ContentPart and adds cache control metadata.
|
||||
//
|
||||
// Note: For most use cases, prefer using bedrock.WithAutomaticCaching() option
|
||||
// which automatically applies caching to supported Anthropic models (Claude 4.x).
|
||||
// This manual wrapper is only needed for fine-grained cache control.
|
||||
//
|
||||
// Automatic caching is supported in both Legacy and Converse APIs.
|
||||
type CachedContent struct {
|
||||
llms.ContentPart
|
||||
CacheControl *llms.CacheControl `json:"cache_control,omitempty"`
|
||||
}
|
||||
|
||||
// WithCacheControl wraps content with cache control instructions for Bedrock.
|
||||
// This allows explicit control over what content should be cached.
|
||||
//
|
||||
// Recommended: Use bedrock.WithAutomaticCaching() option instead for transparent caching.
|
||||
//
|
||||
// Manual usage (when fine-grained control is needed):
|
||||
//
|
||||
// bedrock.WithCacheControl(
|
||||
// llms.TextPart("long context..."),
|
||||
// bedrock.EphemeralCache(),
|
||||
// )
|
||||
//
|
||||
// Supported models: Claude Opus 4, Sonnet 4, Haiku 4 and their variants.
|
||||
func WithCacheControl(content llms.ContentPart, control *llms.CacheControl) CachedContent {
|
||||
return CachedContent{
|
||||
ContentPart: content,
|
||||
CacheControl: control,
|
||||
}
|
||||
}
|
||||
|
||||
+1539
-25
File diff suppressed because it is too large
Load Diff
@@ -177,6 +177,14 @@ func TestOptions(t *testing.T) {
|
||||
t.Error("WithConverseAPI() did not enable Converse API")
|
||||
}
|
||||
})
|
||||
|
||||
t.Run("WithAutomaticCaching", func(t *testing.T) {
|
||||
opts := &options{}
|
||||
WithAutomaticCaching()(opts)
|
||||
if !opts.enableAutoCaching {
|
||||
t.Error("WithAutomaticCaching() did not enable automatic caching")
|
||||
}
|
||||
})
|
||||
}
|
||||
|
||||
func TestModelConstants(t *testing.T) {
|
||||
@@ -189,6 +197,8 @@ func TestModelConstants(t *testing.T) {
|
||||
ModelAmazonNovaProV1,
|
||||
ModelAmazonNovaLiteV1,
|
||||
ModelAmazonNovaMicroV1,
|
||||
ModelAnthropicClaudeOpus46,
|
||||
ModelAnthropicClaudeSonnet46,
|
||||
ModelAnthropicClaudeOpus45,
|
||||
ModelAnthropicClaudeHaiku45,
|
||||
ModelAnthropicClaudeSonnet45,
|
||||
@@ -248,3 +258,260 @@ func (h *testCallbackHandler) HandleRetrieverStart(ctx context.Context, query st
|
||||
func (h *testCallbackHandler) HandleRetrieverEnd(ctx context.Context, query string, documents []schema.Document) {
|
||||
}
|
||||
func (h *testCallbackHandler) HandleStreamingFunc(ctx context.Context, chunk streaming.Chunk) {}
|
||||
|
||||
// TestSupportsCaching tests the supportsCaching method
|
||||
func TestSupportsCaching(t *testing.T) {
|
||||
llm := &LLM{}
|
||||
|
||||
tests := []struct {
|
||||
name string
|
||||
modelID string
|
||||
expected bool
|
||||
}{
|
||||
{
|
||||
name: "Claude Opus 4.6 supports caching",
|
||||
modelID: ModelAnthropicClaudeOpus46,
|
||||
expected: true,
|
||||
},
|
||||
{
|
||||
name: "Claude Sonnet 4.6 supports caching",
|
||||
modelID: ModelAnthropicClaudeSonnet46,
|
||||
expected: true,
|
||||
},
|
||||
{
|
||||
name: "Claude Opus 4.5 supports caching",
|
||||
modelID: ModelAnthropicClaudeOpus45,
|
||||
expected: true,
|
||||
},
|
||||
{
|
||||
name: "Claude Haiku 4.5 supports caching",
|
||||
modelID: ModelAnthropicClaudeHaiku45,
|
||||
expected: true,
|
||||
},
|
||||
{
|
||||
name: "Claude Sonnet 4.5 supports caching",
|
||||
modelID: ModelAnthropicClaudeSonnet45,
|
||||
expected: true,
|
||||
},
|
||||
{
|
||||
name: "Claude Opus 4.1 supports caching",
|
||||
modelID: ModelAnthropicClaudeOpus41,
|
||||
expected: true,
|
||||
},
|
||||
{
|
||||
name: "Claude Opus 4 supports caching",
|
||||
modelID: ModelAnthropicClaudeOpus4,
|
||||
expected: true,
|
||||
},
|
||||
{
|
||||
name: "Claude Sonnet 4 supports caching",
|
||||
modelID: ModelAnthropicClaudeSonnet4,
|
||||
expected: true,
|
||||
},
|
||||
{
|
||||
name: "Claude 3.7 Sonnet does not support caching",
|
||||
modelID: ModelAnthropicClaude37Sonnet,
|
||||
expected: false,
|
||||
},
|
||||
{
|
||||
name: "Claude 3.5 Haiku does not support caching",
|
||||
modelID: ModelAnthropicClaude35Haiku,
|
||||
expected: false,
|
||||
},
|
||||
{
|
||||
name: "Amazon Nova does not support caching",
|
||||
modelID: ModelAmazonNovaProV1,
|
||||
expected: false,
|
||||
},
|
||||
{
|
||||
name: "Meta Llama does not support caching",
|
||||
modelID: ModelMetaLlama3370bInstructV1,
|
||||
expected: false,
|
||||
},
|
||||
}
|
||||
|
||||
for _, tt := range tests {
|
||||
t.Run(tt.name, func(t *testing.T) {
|
||||
result := llm.supportsCaching(tt.modelID)
|
||||
if result != tt.expected {
|
||||
t.Errorf("supportsCaching(%s) = %v, want %v", tt.modelID, result, tt.expected)
|
||||
}
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
// TestApplyAutomaticCaching tests the applyAutomaticCaching function
|
||||
func TestApplyAutomaticCaching(t *testing.T) {
|
||||
tests := []struct {
|
||||
name string
|
||||
messages []bedrockclient.Message
|
||||
expectedCacheIdx int
|
||||
expectNoCaching bool
|
||||
}{
|
||||
{
|
||||
name: "cache applied to last assistant message",
|
||||
messages: []bedrockclient.Message{
|
||||
{Role: llms.ChatMessageTypeHuman, Type: "text", Content: "Hello"},
|
||||
{Role: llms.ChatMessageTypeAI, Type: "text", Content: "Hi there"},
|
||||
{Role: llms.ChatMessageTypeHuman, Type: "text", Content: "How are you?"},
|
||||
},
|
||||
expectedCacheIdx: 1,
|
||||
},
|
||||
{
|
||||
name: "cache applied to tool result before human message",
|
||||
messages: []bedrockclient.Message{
|
||||
{Role: llms.ChatMessageTypeHuman, Type: "text", Content: "What's the weather?"},
|
||||
{Role: llms.ChatMessageTypeAI, Type: "tool_use"},
|
||||
{Role: llms.ChatMessageTypeTool, Type: "tool_result", Content: "72F"},
|
||||
{Role: llms.ChatMessageTypeHuman, Type: "text", Content: "Thanks"},
|
||||
},
|
||||
expectedCacheIdx: 2,
|
||||
},
|
||||
{
|
||||
name: "no caching for single human message",
|
||||
messages: []bedrockclient.Message{
|
||||
{Role: llms.ChatMessageTypeHuman, Type: "text", Content: "Hello"},
|
||||
},
|
||||
expectNoCaching: true,
|
||||
},
|
||||
{
|
||||
name: "no caching when last message is system",
|
||||
messages: []bedrockclient.Message{
|
||||
{Role: llms.ChatMessageTypeSystem, Type: "text", Content: "You are helpful"},
|
||||
},
|
||||
expectNoCaching: true,
|
||||
},
|
||||
{
|
||||
name: "cache applied to assistant message before final human",
|
||||
messages: []bedrockclient.Message{
|
||||
{Role: llms.ChatMessageTypeSystem, Type: "text", Content: "System"},
|
||||
{Role: llms.ChatMessageTypeHuman, Type: "text", Content: "Hello"},
|
||||
{Role: llms.ChatMessageTypeAI, Type: "text", Content: "Hi"},
|
||||
{Role: llms.ChatMessageTypeHuman, Type: "text", Content: "Tell me more"},
|
||||
},
|
||||
expectedCacheIdx: 2,
|
||||
},
|
||||
{
|
||||
name: "empty messages",
|
||||
messages: []bedrockclient.Message{},
|
||||
expectNoCaching: true,
|
||||
},
|
||||
}
|
||||
|
||||
for _, tt := range tests {
|
||||
t.Run(tt.name, func(t *testing.T) {
|
||||
// Make a copy to avoid modifying test data
|
||||
messages := make([]bedrockclient.Message, len(tt.messages))
|
||||
copy(messages, tt.messages)
|
||||
|
||||
applyAutomaticCaching(messages)
|
||||
|
||||
if tt.expectNoCaching {
|
||||
// Verify no cache control was added
|
||||
for i, msg := range messages {
|
||||
if msg.CacheControl != nil {
|
||||
t.Errorf("Expected no cache control, but found at index %d", i)
|
||||
}
|
||||
}
|
||||
} else {
|
||||
// Verify cache control was added to expected message
|
||||
if messages[tt.expectedCacheIdx].CacheControl == nil {
|
||||
t.Errorf("Expected cache control at index %d, but not found", tt.expectedCacheIdx)
|
||||
} else {
|
||||
if messages[tt.expectedCacheIdx].CacheControl.Type != "ephemeral" {
|
||||
t.Errorf("Expected cache type 'ephemeral', got '%s'", messages[tt.expectedCacheIdx].CacheControl.Type)
|
||||
}
|
||||
if messages[tt.expectedCacheIdx].CacheControl.TTL != "5m" {
|
||||
t.Errorf("Expected TTL '5m', got '%s'", messages[tt.expectedCacheIdx].CacheControl.TTL)
|
||||
}
|
||||
}
|
||||
|
||||
// Verify no other messages have cache control
|
||||
for i := range messages {
|
||||
if i != tt.expectedCacheIdx && messages[i].CacheControl != nil {
|
||||
t.Errorf("Unexpected cache control at index %d (expected only at %d)", i, tt.expectedCacheIdx)
|
||||
}
|
||||
}
|
||||
}
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
// TestProcessMessagesWithCaching tests the processMessagesWithCaching function
|
||||
func TestProcessMessagesWithCaching(t *testing.T) {
|
||||
tests := []struct {
|
||||
name string
|
||||
messages []llms.MessageContent
|
||||
autoCaching bool
|
||||
expectCache bool
|
||||
cacheAtIndex int
|
||||
}{
|
||||
{
|
||||
name: "automatic caching enabled",
|
||||
messages: []llms.MessageContent{
|
||||
{
|
||||
Role: llms.ChatMessageTypeHuman,
|
||||
Parts: []llms.ContentPart{
|
||||
llms.TextContent{Text: "Hello"},
|
||||
},
|
||||
},
|
||||
{
|
||||
Role: llms.ChatMessageTypeAI,
|
||||
Parts: []llms.ContentPart{
|
||||
llms.TextContent{Text: "Hi there"},
|
||||
},
|
||||
},
|
||||
{
|
||||
Role: llms.ChatMessageTypeHuman,
|
||||
Parts: []llms.ContentPart{
|
||||
llms.TextContent{Text: "How are you?"},
|
||||
},
|
||||
},
|
||||
},
|
||||
autoCaching: true,
|
||||
expectCache: true,
|
||||
cacheAtIndex: 1,
|
||||
},
|
||||
{
|
||||
name: "automatic caching disabled",
|
||||
messages: []llms.MessageContent{
|
||||
{
|
||||
Role: llms.ChatMessageTypeHuman,
|
||||
Parts: []llms.ContentPart{
|
||||
llms.TextContent{Text: "Hello"},
|
||||
},
|
||||
},
|
||||
{
|
||||
Role: llms.ChatMessageTypeAI,
|
||||
Parts: []llms.ContentPart{
|
||||
llms.TextContent{Text: "Hi there"},
|
||||
},
|
||||
},
|
||||
},
|
||||
autoCaching: false,
|
||||
expectCache: false,
|
||||
},
|
||||
}
|
||||
|
||||
for _, tt := range tests {
|
||||
t.Run(tt.name, func(t *testing.T) {
|
||||
result, err := processMessagesWithCaching(tt.messages, tt.autoCaching)
|
||||
if err != nil {
|
||||
t.Errorf("processMessagesWithCaching() error = %v", err)
|
||||
return
|
||||
}
|
||||
|
||||
if tt.expectCache {
|
||||
if result[tt.cacheAtIndex].CacheControl == nil {
|
||||
t.Errorf("Expected cache control at index %d, but not found", tt.cacheAtIndex)
|
||||
}
|
||||
} else {
|
||||
for i, msg := range result {
|
||||
if msg.CacheControl != nil {
|
||||
t.Errorf("Unexpected cache control at index %d", i)
|
||||
}
|
||||
}
|
||||
}
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
@@ -0,0 +1,208 @@
|
||||
// Package bedrock provides AWS Bedrock integration for LangChainGo.
|
||||
//
|
||||
// # Overview
|
||||
//
|
||||
// This package implements LLM client for AWS Bedrock, supporting multiple model providers
|
||||
// including Anthropic Claude, Amazon Nova, Meta Llama, Cohere, AI21, and DeepSeek.
|
||||
//
|
||||
// # Architecture
|
||||
//
|
||||
// The package consists of three layers:
|
||||
//
|
||||
// 1. Public API Layer (bedrockllm.go): Exposes bedrock.LLM and bedrock.New() constructor
|
||||
// 2. Message Processing Layer: Converts llms.MessageContent to provider-specific formats
|
||||
// 3. Internal Client Layer (internal/bedrockclient): Handles AWS SDK interactions
|
||||
//
|
||||
// Two API modes are supported:
|
||||
//
|
||||
// - Legacy API: Model-specific implementations via InvokeModel/InvokeModelWithResponseStream
|
||||
// - Converse API: Unified implementation via Converse/ConverseStream (recommended)
|
||||
//
|
||||
// # Basic Usage
|
||||
//
|
||||
// Create a Bedrock client:
|
||||
//
|
||||
// import "github.com/vxcontrol/langchaingo/llms/bedrock"
|
||||
//
|
||||
// llm, err := bedrock.New(
|
||||
// bedrock.WithModel(bedrock.ModelAnthropicClaudeSonnet45),
|
||||
// bedrock.WithConverseAPI(),
|
||||
// )
|
||||
//
|
||||
// Generate content:
|
||||
//
|
||||
// messages := []llms.MessageContent{
|
||||
// llms.TextParts(llms.ChatMessageTypeHuman, "Hello!"),
|
||||
// }
|
||||
// resp, err := llm.GenerateContent(ctx, messages,
|
||||
// llms.WithMaxTokens(1024),
|
||||
// )
|
||||
//
|
||||
// # Automatic Prompt Caching
|
||||
//
|
||||
// For Claude 4.x models (Opus 4, Sonnet 4, Haiku 4), automatic caching is available:
|
||||
//
|
||||
// llm, err := bedrock.New(
|
||||
// bedrock.WithModel(bedrock.ModelAnthropicClaudeSonnet45),
|
||||
// bedrock.WithConverseAPI(),
|
||||
// bedrock.WithAutomaticCaching(), // Enable automatic caching
|
||||
// )
|
||||
//
|
||||
// When enabled, the client automatically:
|
||||
// - Detects Claude 4.x models by model ID patterns (anthropic.claude-opus-4, sonnet-4, haiku-4)
|
||||
// - Adds cache points to the last assistant or tool message before new user input
|
||||
// - Uses ephemeral 5-minute TTL by default
|
||||
// - Works transparently without modifying client code
|
||||
//
|
||||
// Benefits:
|
||||
// - 90% cost reduction on cached input tokens
|
||||
// - No manual cache control wrappers needed
|
||||
// - Automatic conversation history caching
|
||||
//
|
||||
// Manual caching (for fine-grained control):
|
||||
//
|
||||
// messages := []llms.MessageContent{
|
||||
// {
|
||||
// Role: llms.ChatMessageTypeAI,
|
||||
// Parts: []llms.ContentPart{
|
||||
// bedrock.WithCacheControl(
|
||||
// llms.TextPart("long context..."),
|
||||
// bedrock.EphemeralCache(),
|
||||
// ),
|
||||
// },
|
||||
// },
|
||||
// }
|
||||
//
|
||||
// # Tool Calling
|
||||
//
|
||||
// Both APIs support tool calling for compatible models:
|
||||
//
|
||||
// tools := []llms.Tool{
|
||||
// {
|
||||
// Type: "function",
|
||||
// Function: &llms.FunctionDefinition{
|
||||
// Name: "get_weather",
|
||||
// Description: "Get weather for location",
|
||||
// Parameters: map[string]any{...},
|
||||
// },
|
||||
// },
|
||||
// }
|
||||
//
|
||||
// resp, err := llm.GenerateContent(ctx, messages,
|
||||
// llms.WithTools(tools),
|
||||
// )
|
||||
//
|
||||
// # Reasoning Support
|
||||
//
|
||||
// Claude 4.x and 3.7 models support reasoning (thinking) mode:
|
||||
//
|
||||
// resp, err := llm.GenerateContent(ctx, messages,
|
||||
// llms.WithReasoning(llms.ReasoningMedium, 2048),
|
||||
// )
|
||||
//
|
||||
// // Access reasoning content
|
||||
// if resp.Choices[0].Reasoning != nil {
|
||||
// fmt.Println(resp.Choices[0].Reasoning.Content)
|
||||
// }
|
||||
//
|
||||
// # Streaming
|
||||
//
|
||||
// Both APIs support streaming responses:
|
||||
//
|
||||
// streamFunc := func(ctx context.Context, chunk streaming.Chunk) error {
|
||||
// switch chunk.Type {
|
||||
// case streaming.ChunkTypeText:
|
||||
// fmt.Print(chunk.Content)
|
||||
// case streaming.ChunkTypeReasoning:
|
||||
// fmt.Println("Thinking:", chunk.Reasoning.Content)
|
||||
// case streaming.ChunkTypeToolCall:
|
||||
// fmt.Println("Tool:", chunk.ToolCall.Name)
|
||||
// }
|
||||
// return nil
|
||||
// }
|
||||
//
|
||||
// resp, err := llm.GenerateContent(ctx, messages,
|
||||
// llms.WithStreamingFunc(streamFunc),
|
||||
// )
|
||||
//
|
||||
// # Supported Models
|
||||
//
|
||||
// See models_list.go for complete list. Major providers:
|
||||
//
|
||||
// - Anthropic: Claude 4.6 (Opus, Sonnet), Claude 4.5, 4.1, 4, 3.7, 3.5
|
||||
// - Amazon: Nova 2 Lite, Nova Premier, Nova Pro, Nova Lite, Nova Micro
|
||||
// - Meta: Llama 4, Llama 3.3, 3.2, 3.1, 3
|
||||
// - Cohere: Command R, Command R+
|
||||
// - AI21: Jamba 1.5 Large, Mini
|
||||
// - DeepSeek: R1
|
||||
// - OpenAI: GPT-OSS-120B, GPT-OSS-20B
|
||||
// - Qwen: Qwen3 Next, Qwen3 VL, Qwen3 32B, Qwen3 Coder (30B, Next)
|
||||
// - Mistral: Large 3, Magistral Small
|
||||
// - Moonshot: Kimi K2.5, Kimi K2 Thinking
|
||||
// - Z.AI: GLM-4.7, GLM-4.7-Flash
|
||||
//
|
||||
// # Error Handling
|
||||
//
|
||||
// Provider-specific errors are mapped to standardized error codes:
|
||||
//
|
||||
// resp, err := llm.GenerateContent(ctx, messages)
|
||||
// if err != nil {
|
||||
// if llmErr, ok := err.(*llms.Error); ok {
|
||||
// switch llmErr.Code {
|
||||
// case llms.ErrCodeRateLimit:
|
||||
// // Handle rate limiting
|
||||
// case llms.ErrCodeAuthentication:
|
||||
// // Handle auth errors
|
||||
// }
|
||||
// }
|
||||
// }
|
||||
//
|
||||
// See errors.go for complete error mapping.
|
||||
//
|
||||
// # AWS Configuration
|
||||
//
|
||||
// The client uses AWS SDK v2 configuration:
|
||||
//
|
||||
// - Credentials: From environment (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY) or AWS config
|
||||
// - Region: From environment (AWS_REGION) or default config
|
||||
// - Custom configuration: Use bedrock.WithClient() with pre-configured bedrockruntime.Client
|
||||
//
|
||||
// # Performance Considerations
|
||||
//
|
||||
// - Converse API is recommended for new applications (unified, better error handling)
|
||||
// - Automatic caching reduces costs by 90% for cached tokens (Claude 4.x only)
|
||||
// - Streaming reduces latency for interactive applications
|
||||
// - Minimum cache checkpoint: 1024 tokens (Sonnet 4.5), 4096 tokens (Haiku 4.5)
|
||||
//
|
||||
// # Maintenance
|
||||
//
|
||||
// When adding new models:
|
||||
// 1. Add model constant to models_list.go with documentation
|
||||
// 2. Update provider detection in internal/bedrockclient/bedrockclient.go if needed
|
||||
// 3. Add provider-specific implementation in internal/bedrockclient/provider_*.go
|
||||
// 4. Update tests in bedrockllm_test.go to include new model
|
||||
// 5. For caching support, add pattern to supportsCaching() method
|
||||
//
|
||||
// When updating API:
|
||||
// 1. Converse API changes go to internal/bedrockclient/bedrockclient_converse.go
|
||||
// 2. Legacy API changes go to internal/bedrockclient/provider_*.go
|
||||
// 3. Message processing changes go to bedrockllm.go (processMessages, processMessagesWithCaching)
|
||||
// 4. Always maintain backward compatibility
|
||||
// 5. Add integration tests with httprr recording
|
||||
//
|
||||
// # Testing
|
||||
//
|
||||
// Tests use httprr for HTTP recording/replay:
|
||||
//
|
||||
// - Integration tests: bedrockllm_test.go (requires AWS credentials)
|
||||
// - Unit tests: bedrockllm_unit_test.go (no credentials needed)
|
||||
// - Tool calling: bedrock_tool_integration_test.go
|
||||
//
|
||||
// Recording new HTTP interactions:
|
||||
//
|
||||
// HTTPRR_RECORD=. go test -v -run TestName ./llms/bedrock/
|
||||
//
|
||||
// Debug HTTP interactions:
|
||||
//
|
||||
// HTTPRR_RECORD=. HTTPRR_DEBUG=true go test -v -run TestName ./llms/bedrock/
|
||||
package bedrock
|
||||
@@ -6,6 +6,7 @@ import (
|
||||
"strings"
|
||||
|
||||
"github.com/vxcontrol/langchaingo/llms"
|
||||
"github.com/vxcontrol/langchaingo/llms/reasoning"
|
||||
|
||||
"github.com/aws/aws-sdk-go-v2/service/bedrockruntime"
|
||||
)
|
||||
@@ -31,6 +32,16 @@ type Message struct {
|
||||
// Tool calling fields
|
||||
ToolCall *ToolCall `json:"tool_call,omitempty"`
|
||||
ToolResult *ToolResult `json:"tool_result,omitempty"`
|
||||
// Reasoning contains thinking content for AI messages
|
||||
Reasoning *reasoning.ContentReasoning `json:"reasoning,omitempty"`
|
||||
// CacheControl for prompt caching (used by Legacy Anthropic API)
|
||||
CacheControl *CacheControl `json:"cache_control,omitempty"`
|
||||
}
|
||||
|
||||
// CacheControl represents cache configuration for prompt caching
|
||||
type CacheControl struct {
|
||||
Type string `json:"type"`
|
||||
TTL string `json:"ttl,omitempty"`
|
||||
}
|
||||
|
||||
// ToolCall represents a function call request from the model
|
||||
|
||||
@@ -60,6 +60,7 @@ type ConverseInput struct {
|
||||
Tools []llms.Tool
|
||||
StreamingFunc streaming.Callback
|
||||
ReasoningConfig *llms.ReasoningConfig
|
||||
EnableCaching bool
|
||||
}
|
||||
|
||||
type converseThinkingPayload struct {
|
||||
@@ -94,6 +95,11 @@ func (c *ConverseClient) buildConverseInput(input *ConverseInput) (*bedrockrunti
|
||||
inferenceConfig.StopSequences = input.StopSequences
|
||||
}
|
||||
|
||||
// Add cachePoint to messages if caching is enabled
|
||||
if input.EnableCaching && len(converseMessages) > 0 {
|
||||
c.addCachePointToMessages(converseMessages)
|
||||
}
|
||||
|
||||
converseInput := &bedrockruntime.ConverseInput{
|
||||
ModelId: aws.String(input.ModelID),
|
||||
Messages: converseMessages,
|
||||
@@ -102,6 +108,15 @@ func (c *ConverseClient) buildConverseInput(input *ConverseInput) (*bedrockrunti
|
||||
|
||||
// Add system prompts if any
|
||||
if len(systemPrompts) > 0 {
|
||||
// Add cachePoint after system if caching is enabled
|
||||
if input.EnableCaching {
|
||||
systemPrompts = append(systemPrompts, &types.SystemContentBlockMemberCachePoint{
|
||||
Value: types.CachePointBlock{
|
||||
Type: types.CachePointTypeDefault,
|
||||
Ttl: types.CacheTTLFiveMinutes,
|
||||
},
|
||||
})
|
||||
}
|
||||
converseInput.System = systemPrompts
|
||||
}
|
||||
|
||||
@@ -152,6 +167,20 @@ func (c *ConverseClient) convertMessages(messages []Message) ([]types.Message, [
|
||||
if err != nil {
|
||||
return nil, nil, err
|
||||
}
|
||||
// Add cachePoint if message has cache control
|
||||
if msg.CacheControl != nil {
|
||||
cacheBlock := types.CachePointBlock{
|
||||
Type: types.CachePointTypeDefault,
|
||||
}
|
||||
if msg.CacheControl.TTL == "1h" {
|
||||
cacheBlock.Ttl = types.CacheTTLOneHour
|
||||
} else {
|
||||
cacheBlock.Ttl = types.CacheTTLFiveMinutes
|
||||
}
|
||||
converseMsg.Content = append(converseMsg.Content, &types.ContentBlockMemberCachePoint{
|
||||
Value: cacheBlock,
|
||||
})
|
||||
}
|
||||
converseMessages = append(converseMessages, converseMsg)
|
||||
case llms.ChatMessageTypeTool:
|
||||
converseMsg, err := c.convertToolMessage(msg)
|
||||
@@ -165,6 +194,22 @@ func (c *ConverseClient) convertMessages(messages []Message) ([]types.Message, [
|
||||
return converseMessages, systemPrompts, nil
|
||||
}
|
||||
|
||||
// addCachePointToMessages adds cachePoint to the last message for conversation history caching
|
||||
func (c *ConverseClient) addCachePointToMessages(messages []types.Message) {
|
||||
if len(messages) == 0 {
|
||||
return
|
||||
}
|
||||
|
||||
// Add cachePoint to the last message's content
|
||||
lastMsg := &messages[len(messages)-1]
|
||||
lastMsg.Content = append(lastMsg.Content, &types.ContentBlockMemberCachePoint{
|
||||
Value: types.CachePointBlock{
|
||||
Type: types.CachePointTypeDefault,
|
||||
Ttl: types.CacheTTLFiveMinutes,
|
||||
},
|
||||
})
|
||||
}
|
||||
|
||||
// convertUserOrAssistantMessage converts user or assistant messages
|
||||
func (c *ConverseClient) convertUserOrAssistantMessage(msg Message) (types.Message, error) {
|
||||
var role types.ConversationRole
|
||||
@@ -176,6 +221,31 @@ func (c *ConverseClient) convertUserOrAssistantMessage(msg Message) (types.Messa
|
||||
|
||||
var contentBlocks []types.ContentBlock
|
||||
|
||||
// For AI messages with reasoning, add reasoning blocks first
|
||||
if msg.Role == llms.ChatMessageTypeAI && msg.Reasoning != nil {
|
||||
// Add thinking block if present
|
||||
if msg.Reasoning.Content != "" || len(msg.Reasoning.Signature) > 0 {
|
||||
reasoningBlock := types.ReasoningContentBlockMemberReasoningText{
|
||||
Value: types.ReasoningTextBlock{
|
||||
Text: ptrStringOrNil(msg.Reasoning.Content),
|
||||
Signature: ptrStringOrNil(string(msg.Reasoning.Signature)),
|
||||
},
|
||||
}
|
||||
contentBlocks = append(contentBlocks, &types.ContentBlockMemberReasoningContent{
|
||||
Value: &reasoningBlock,
|
||||
})
|
||||
}
|
||||
// Add redacted thinking block if present
|
||||
if len(msg.Reasoning.RedactedContent) > 0 {
|
||||
redactedBlock := types.ReasoningContentBlockMemberRedactedContent{
|
||||
Value: msg.Reasoning.RedactedContent,
|
||||
}
|
||||
contentBlocks = append(contentBlocks, &types.ContentBlockMemberReasoningContent{
|
||||
Value: &redactedBlock,
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
// Handle text content
|
||||
if msg.Content != "" {
|
||||
contentBlocks = append(contentBlocks, &types.ContentBlockMemberText{
|
||||
@@ -205,9 +275,11 @@ func (c *ConverseClient) convertToolCallInput(args any) (any, error) {
|
||||
return args, nil
|
||||
}
|
||||
|
||||
// Convert to Smithy-compatible format by re-encoding through JSON
|
||||
// This handles types like map[string]any with interface{} values
|
||||
jsonBytes := bytes.NewBuffer(nil)
|
||||
if err := json.NewEncoder(jsonBytes).Encode(args); err != nil {
|
||||
return nil, err
|
||||
return nil, fmt.Errorf("failed to encode arguments: %w", err)
|
||||
}
|
||||
|
||||
jsonDecoder := json.NewDecoder(jsonBytes)
|
||||
@@ -215,7 +287,7 @@ func (c *ConverseClient) convertToolCallInput(args any) (any, error) {
|
||||
|
||||
var jsonValue any
|
||||
if err := jsonDecoder.Decode(&jsonValue); err != nil {
|
||||
return nil, err
|
||||
return nil, fmt.Errorf("failed to decode arguments: %w", err)
|
||||
}
|
||||
|
||||
return jsonValue, nil
|
||||
@@ -315,6 +387,8 @@ func (c *ConverseClient) handleStreamingResponse(ctx context.Context, input *bed
|
||||
func (c *ConverseClient) processStreamingResponse(ctx context.Context, response *bedrockruntime.ConverseStreamOutput, callback streaming.Callback) (*llms.ContentResponse, error) {
|
||||
var fullContent strings.Builder
|
||||
var reasoningContent strings.Builder
|
||||
var signature bytes.Buffer
|
||||
var redactedContent bytes.Buffer
|
||||
var toolCalls []llms.ToolCall
|
||||
currentToolCalls := make(map[string]*streaming.ToolCall) // Track streaming tool calls by ID
|
||||
|
||||
@@ -352,9 +426,13 @@ func (c *ConverseClient) processStreamingResponse(ctx context.Context, response
|
||||
return nil, err
|
||||
}
|
||||
case *types.ReasoningContentBlockDeltaMemberRedactedContent:
|
||||
// TODO: not supported yet
|
||||
if len(block.Value) > 0 {
|
||||
redactedContent.Write(block.Value)
|
||||
}
|
||||
case *types.ReasoningContentBlockDeltaMemberSignature:
|
||||
// TODO: not supported yet
|
||||
if len(block.Value) > 0 {
|
||||
signature.WriteString(block.Value)
|
||||
}
|
||||
}
|
||||
}
|
||||
case *types.ContentBlockDeltaMemberToolUse:
|
||||
@@ -433,11 +511,20 @@ func (c *ConverseClient) processStreamingResponse(ctx context.Context, response
|
||||
return nil, fmt.Errorf("stream error: %w", err)
|
||||
}
|
||||
|
||||
var sig []byte
|
||||
if signature.Len() > 0 {
|
||||
sig = signature.Bytes()
|
||||
}
|
||||
var redacted []byte
|
||||
if redactedContent.Len() > 0 {
|
||||
redacted = redactedContent.Bytes()
|
||||
}
|
||||
|
||||
choice := &llms.ContentChoice{
|
||||
Content: fullContent.String(),
|
||||
ToolCalls: toolCalls,
|
||||
GenerationInfo: make(map[string]any),
|
||||
Reasoning: c.processReasoning(reasoningContent.String()),
|
||||
Reasoning: c.processReasoning(reasoningContent.String(), sig, redacted),
|
||||
}
|
||||
|
||||
result := &llms.ContentResponse{
|
||||
@@ -447,13 +534,15 @@ func (c *ConverseClient) processStreamingResponse(ctx context.Context, response
|
||||
return result, nil
|
||||
}
|
||||
|
||||
func (c *ConverseClient) processReasoning(reasoningContent string) *reasoning.ContentReasoning {
|
||||
if reasoningContent == "" {
|
||||
func (c *ConverseClient) processReasoning(reasoningContent string, signature []byte, redactedContent []byte) *reasoning.ContentReasoning {
|
||||
if reasoningContent == "" && len(signature) == 0 && len(redactedContent) == 0 {
|
||||
return nil
|
||||
}
|
||||
|
||||
return &reasoning.ContentReasoning{
|
||||
Content: reasoningContent,
|
||||
Content: reasoningContent,
|
||||
Signature: signature,
|
||||
RedactedContent: redactedContent,
|
||||
}
|
||||
}
|
||||
|
||||
@@ -477,7 +566,17 @@ func (c *ConverseClient) convertConverseResponse(response *bedrockruntime.Conver
|
||||
choice.Content += block.Value
|
||||
case *types.ContentBlockMemberToolUse:
|
||||
// Convert tool use to ToolCall
|
||||
argsJSON, _ := json.Marshal(block.Value.Input)
|
||||
// Extract input from document.LazyDocument
|
||||
var inputData any
|
||||
if block.Value.Input != nil {
|
||||
if err := block.Value.Input.UnmarshalSmithyDocument(&inputData); err != nil {
|
||||
return nil, fmt.Errorf("failed to unmarshal tool input document: %w", err)
|
||||
}
|
||||
}
|
||||
argsJSON, err := json.Marshal(inputData)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("failed to marshal tool input to JSON: %w", err)
|
||||
}
|
||||
toolCall := llms.ToolCall{
|
||||
ID: *block.Value.ToolUseId,
|
||||
Type: "function",
|
||||
@@ -488,14 +587,28 @@ func (c *ConverseClient) convertConverseResponse(response *bedrockruntime.Conver
|
||||
}
|
||||
choice.ToolCalls = append(choice.ToolCalls, toolCall)
|
||||
case *types.ContentBlockMemberReasoningContent:
|
||||
// The block.Value is of type ReasoningContentBlock, not string
|
||||
// TODO: Extract text from reasoning block when AWS SDK exposes it
|
||||
// The block.Value is of type ReasoningContentBlock
|
||||
switch content := block.Value.(type) {
|
||||
case *types.ReasoningContentBlockMemberReasoningText:
|
||||
choice.Reasoning = c.processReasoning(*content.Value.Text)
|
||||
_ = content.Value.Signature // TODO: not supported yet
|
||||
reasoningText := ""
|
||||
if content.Value.Text != nil {
|
||||
reasoningText = *content.Value.Text
|
||||
}
|
||||
var sig []byte
|
||||
if content.Value.Signature != nil {
|
||||
sig = []byte(*content.Value.Signature)
|
||||
}
|
||||
choice.Reasoning = c.processReasoning(reasoningText, sig, nil)
|
||||
case *types.ReasoningContentBlockMemberRedactedContent:
|
||||
// TODO: not supported yet
|
||||
var redacted []byte
|
||||
if len(content.Value) > 0 {
|
||||
redacted = content.Value
|
||||
}
|
||||
if choice.Reasoning == nil {
|
||||
choice.Reasoning = c.processReasoning("", nil, redacted)
|
||||
} else {
|
||||
choice.Reasoning.RedactedContent = redacted
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -508,12 +621,25 @@ func (c *ConverseClient) convertConverseResponse(response *bedrockruntime.Conver
|
||||
if response.Usage != nil {
|
||||
if response.Usage.InputTokens != nil {
|
||||
choice.GenerationInfo["input_tokens"] = *response.Usage.InputTokens
|
||||
choice.GenerationInfo["PromptTokens"] = *response.Usage.InputTokens
|
||||
}
|
||||
if response.Usage.OutputTokens != nil {
|
||||
choice.GenerationInfo["output_tokens"] = *response.Usage.OutputTokens
|
||||
choice.GenerationInfo["CompletionTokens"] = *response.Usage.OutputTokens
|
||||
}
|
||||
if response.Usage.TotalTokens != nil {
|
||||
choice.GenerationInfo["total_tokens"] = *response.Usage.TotalTokens
|
||||
choice.GenerationInfo["TotalTokens"] = *response.Usage.TotalTokens
|
||||
}
|
||||
// Add cache metrics if available
|
||||
if response.Usage.CacheReadInputTokens != nil {
|
||||
choice.GenerationInfo["cacheReadInputTokens"] = *response.Usage.CacheReadInputTokens
|
||||
choice.GenerationInfo["CacheReadInputTokens"] = *response.Usage.CacheReadInputTokens
|
||||
choice.GenerationInfo["PromptCachedTokens"] = *response.Usage.CacheReadInputTokens
|
||||
}
|
||||
if response.Usage.CacheWriteInputTokens != nil {
|
||||
choice.GenerationInfo["cacheWriteInputTokens"] = *response.Usage.CacheWriteInputTokens
|
||||
choice.GenerationInfo["CacheCreationInputTokens"] = *response.Usage.CacheWriteInputTokens
|
||||
}
|
||||
}
|
||||
|
||||
@@ -530,7 +656,11 @@ func (c *ConverseClient) supportsReasoning(modelID string) bool {
|
||||
reasoningModels := []string{
|
||||
"anthropic.claude-opus-4-",
|
||||
"anthropic.claude-sonnet-4-",
|
||||
"anthropic.claude-haiku-4-",
|
||||
"anthropic.claude-3-7-",
|
||||
"openai.gpt-oss-120b",
|
||||
"openai.gpt-oss-20b",
|
||||
"moonshot.kimi-k2-thinking",
|
||||
}
|
||||
|
||||
for _, model := range reasoningModels {
|
||||
@@ -540,3 +670,10 @@ func (c *ConverseClient) supportsReasoning(modelID string) bool {
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
func ptrStringOrNil(s string) *string {
|
||||
if s == "" {
|
||||
return nil
|
||||
}
|
||||
return &s
|
||||
}
|
||||
|
||||
@@ -176,8 +176,14 @@ func TestClient_CreateCompletion(t *testing.T) {
|
||||
},
|
||||
StopReason: AnthropicCompletionReasonEndTurn,
|
||||
Usage: struct {
|
||||
InputTokens int32 `json:"input_tokens"`
|
||||
OutputTokens int32 `json:"output_tokens"`
|
||||
InputTokens int32 `json:"input_tokens"`
|
||||
OutputTokens int32 `json:"output_tokens"`
|
||||
CacheCreationInputTokens int32 `json:"cache_creation_input_tokens,omitempty"`
|
||||
CacheReadInputTokens int32 `json:"cache_read_input_tokens,omitempty"`
|
||||
CacheCreation struct {
|
||||
Ephemeral5mInputTokens int32 `json:"ephemeral_5m_input_tokens,omitempty"`
|
||||
Ephemeral1hInputTokens int32 `json:"ephemeral_1h_input_tokens,omitempty"`
|
||||
} `json:"cache_creation,omitempty"`
|
||||
}{
|
||||
InputTokens: 10,
|
||||
OutputTokens: 5,
|
||||
@@ -470,6 +476,7 @@ func TestClient_CreateCompletion_Streaming(t *testing.T) {
|
||||
StopReason string `json:"stop_reason"`
|
||||
StopSequence any `json:"stop_sequence"`
|
||||
Thinking string `json:"thinking,omitempty"`
|
||||
Signature string `json:"signature,omitempty"`
|
||||
}{
|
||||
Type: "text_delta",
|
||||
Text: "Once upon a time, ",
|
||||
@@ -485,6 +492,7 @@ func TestClient_CreateCompletion_Streaming(t *testing.T) {
|
||||
StopReason string `json:"stop_reason"`
|
||||
StopSequence any `json:"stop_sequence"`
|
||||
Thinking string `json:"thinking,omitempty"`
|
||||
Signature string `json:"signature,omitempty"`
|
||||
}{
|
||||
Type: "text_delta",
|
||||
Text: "there was a brave knight.",
|
||||
@@ -499,6 +507,7 @@ func TestClient_CreateCompletion_Streaming(t *testing.T) {
|
||||
StopReason string `json:"stop_reason"`
|
||||
StopSequence any `json:"stop_sequence"`
|
||||
Thinking string `json:"thinking,omitempty"`
|
||||
Signature string `json:"signature,omitempty"`
|
||||
}{
|
||||
StopReason: AnthropicCompletionReasonEndTurn,
|
||||
},
|
||||
@@ -792,6 +801,7 @@ func TestClient_CreateCompletion_StreamingCancellation(t *testing.T) {
|
||||
StopReason string `json:"stop_reason"`
|
||||
StopSequence any `json:"stop_sequence"`
|
||||
Thinking string `json:"thinking,omitempty"`
|
||||
Signature string `json:"signature,omitempty"`
|
||||
}{
|
||||
Type: "text_delta",
|
||||
Text: fmt.Sprintf("Chunk %d ", i),
|
||||
|
||||
@@ -675,8 +675,14 @@ func TestAnthropicResponseParsing(t *testing.T) {
|
||||
StopReason: AnthropicCompletionReasonEndTurn,
|
||||
StopSequence: "",
|
||||
Usage: struct {
|
||||
InputTokens int32 `json:"input_tokens"`
|
||||
OutputTokens int32 `json:"output_tokens"`
|
||||
InputTokens int32 `json:"input_tokens"`
|
||||
OutputTokens int32 `json:"output_tokens"`
|
||||
CacheCreationInputTokens int32 `json:"cache_creation_input_tokens,omitempty"`
|
||||
CacheReadInputTokens int32 `json:"cache_read_input_tokens,omitempty"`
|
||||
CacheCreation struct {
|
||||
Ephemeral5mInputTokens int32 `json:"ephemeral_5m_input_tokens,omitempty"`
|
||||
Ephemeral1hInputTokens int32 `json:"ephemeral_1h_input_tokens,omitempty"`
|
||||
} `json:"cache_creation,omitempty"`
|
||||
}{
|
||||
InputTokens: 10,
|
||||
OutputTokens: 15,
|
||||
@@ -777,6 +783,7 @@ func TestAnthropicStreamingResponseChunk(t *testing.T) {
|
||||
StopReason string `json:"stop_reason"`
|
||||
StopSequence any `json:"stop_sequence"`
|
||||
Thinking string `json:"thinking,omitempty"`
|
||||
Signature string `json:"signature,omitempty"`
|
||||
}{
|
||||
Type: "text_delta",
|
||||
Text: "Hello, how can I help you today?",
|
||||
@@ -794,6 +801,7 @@ func TestAnthropicStreamingResponseChunk(t *testing.T) {
|
||||
StopReason string `json:"stop_reason"`
|
||||
StopSequence any `json:"stop_sequence"`
|
||||
Thinking string `json:"thinking,omitempty"`
|
||||
Signature string `json:"signature,omitempty"`
|
||||
}{
|
||||
StopReason: AnthropicCompletionReasonEndTurn,
|
||||
},
|
||||
|
||||
@@ -37,7 +37,7 @@ type anthropicBinGenerationInputSource struct {
|
||||
// anthropicTextGenerationInputContent is a single message in the input.
|
||||
type anthropicTextGenerationInputContent struct {
|
||||
// The type of the content. Required.
|
||||
// One of: "text", "image", "tool_use", "tool_result"
|
||||
// One of: "text", "image", "tool_use", "tool_result", "thinking", "redacted_thinking"
|
||||
Type string `json:"type"`
|
||||
// The source of the content. Required if type is "image"
|
||||
Source *anthropicBinGenerationInputSource `json:"source,omitempty"`
|
||||
@@ -50,6 +50,17 @@ type anthropicTextGenerationInputContent struct {
|
||||
// Tool result fields
|
||||
ToolUseID string `json:"tool_use_id,omitempty"`
|
||||
Content string `json:"content,omitempty"`
|
||||
// Thinking fields
|
||||
Thinking string `json:"thinking,omitempty"`
|
||||
Signature string `json:"signature,omitempty"`
|
||||
Data string `json:"data,omitempty"`
|
||||
// Cache control for prompt caching (Bedrock supports Anthropic cache_control format)
|
||||
CacheControl *anthropicCacheControl `json:"cache_control,omitempty"`
|
||||
}
|
||||
|
||||
type anthropicCacheControl struct {
|
||||
Type string `json:"type"`
|
||||
TTL string `json:"ttl,omitempty"`
|
||||
}
|
||||
|
||||
type anthropicTextGenerationInputMessage struct {
|
||||
@@ -68,7 +79,8 @@ type anthropicTextGenerationInput struct {
|
||||
// The maximum number of tokens to generate per result. Required
|
||||
MaxTokens int `json:"max_tokens"`
|
||||
// The system prompt to use. Optional
|
||||
System string `json:"system,omitempty"`
|
||||
// Can be string or []anthropicTextGenerationInputContent for caching support
|
||||
System any `json:"system,omitempty"`
|
||||
// The messages to use. Required
|
||||
Messages []*anthropicTextGenerationInputMessage `json:"messages"`
|
||||
// The amount of randomness injected into the response. Optional, default = 1
|
||||
@@ -88,9 +100,10 @@ type anthropicTextGenerationInput struct {
|
||||
}
|
||||
|
||||
type anthropicTool struct {
|
||||
Name string `json:"name"`
|
||||
Description string `json:"description,omitempty"`
|
||||
InputSchema any `json:"input_schema,omitempty"`
|
||||
Name string `json:"name"`
|
||||
Description string `json:"description,omitempty"`
|
||||
InputSchema any `json:"input_schema,omitempty"`
|
||||
CacheControl *anthropicCacheControl `json:"cache_control,omitempty"`
|
||||
}
|
||||
|
||||
type anthropicThinkingPayload struct {
|
||||
@@ -114,19 +127,27 @@ type anthropicTextGenerationOutput struct {
|
||||
StopReason string `json:"stop_reason"`
|
||||
// Which custom stop sequence was matched, if any.
|
||||
StopSequence string `json:"stop_sequence"`
|
||||
Usage struct {
|
||||
InputTokens int32 `json:"input_tokens"`
|
||||
OutputTokens int32 `json:"output_tokens"`
|
||||
Usage struct {
|
||||
InputTokens int32 `json:"input_tokens"`
|
||||
OutputTokens int32 `json:"output_tokens"`
|
||||
CacheCreationInputTokens int32 `json:"cache_creation_input_tokens,omitempty"`
|
||||
CacheReadInputTokens int32 `json:"cache_read_input_tokens,omitempty"`
|
||||
CacheCreation struct {
|
||||
Ephemeral5mInputTokens int32 `json:"ephemeral_5m_input_tokens,omitempty"`
|
||||
Ephemeral1hInputTokens int32 `json:"ephemeral_1h_input_tokens,omitempty"`
|
||||
} `json:"cache_creation,omitempty"`
|
||||
} `json:"usage"`
|
||||
}
|
||||
|
||||
type anthropicContentBlock struct {
|
||||
Type string `json:"type"`
|
||||
Text string `json:"text,omitempty"`
|
||||
ID string `json:"id,omitempty"`
|
||||
Name string `json:"name,omitempty"`
|
||||
Input map[string]any `json:"input,omitempty"`
|
||||
Thinking string `json:"thinking,omitempty"`
|
||||
Type string `json:"type"`
|
||||
Text string `json:"text,omitempty"`
|
||||
ID string `json:"id,omitempty"`
|
||||
Name string `json:"name,omitempty"`
|
||||
Input map[string]any `json:"input,omitempty"`
|
||||
Thinking string `json:"thinking,omitempty"`
|
||||
Signature string `json:"signature,omitempty"`
|
||||
Data string `json:"data,omitempty"`
|
||||
}
|
||||
|
||||
// Finish reason for the completion of the generation.
|
||||
@@ -176,10 +197,16 @@ func createAnthropicCompletion(ctx context.Context,
|
||||
}
|
||||
}
|
||||
|
||||
// Prepare system prompt - omit if empty
|
||||
var system any
|
||||
if systemPrompt != "" {
|
||||
system = systemPrompt
|
||||
}
|
||||
|
||||
input := anthropicTextGenerationInput{
|
||||
AnthropicVersion: AnthropicLatestVersion,
|
||||
MaxTokens: getMaxTokens(options.MaxTokens, 2048),
|
||||
System: systemPrompt,
|
||||
System: system,
|
||||
Messages: inputContents,
|
||||
Temperature: options.Temperature,
|
||||
TopP: options.TopP,
|
||||
@@ -244,6 +271,8 @@ func createAnthropicCompletion(ctx context.Context,
|
||||
// Group content blocks by type for this choice
|
||||
var textContent string
|
||||
var reasoningContent string
|
||||
var signature []byte
|
||||
var redactedContent []byte
|
||||
var toolCalls []llms.ToolCall
|
||||
|
||||
for _, c := range output.Content {
|
||||
@@ -252,6 +281,13 @@ func createAnthropicCompletion(ctx context.Context,
|
||||
textContent += c.Text
|
||||
case "thinking":
|
||||
reasoningContent += c.Thinking
|
||||
if len(c.Signature) > 0 {
|
||||
signature = []byte(c.Signature)
|
||||
}
|
||||
case "redacted_thinking":
|
||||
if len(c.Data) > 0 {
|
||||
redactedContent = []byte(c.Data)
|
||||
}
|
||||
case "tool_use":
|
||||
argumentsJSON, err := json.Marshal(c.Input)
|
||||
if err != nil {
|
||||
@@ -271,16 +307,21 @@ func createAnthropicCompletion(ctx context.Context,
|
||||
// Create single choice with all content
|
||||
choice := &llms.ContentChoice{
|
||||
Content: textContent,
|
||||
Reasoning: processReasoning(reasoningContent),
|
||||
Reasoning: processReasoning(reasoningContent, signature, redactedContent),
|
||||
ToolCalls: toolCalls,
|
||||
StopReason: output.StopReason,
|
||||
GenerationInfo: map[string]any{
|
||||
"input_tokens": output.Usage.InputTokens,
|
||||
"output_tokens": output.Usage.OutputTokens,
|
||||
// Standardized field names for cross-provider compatibility
|
||||
"input_tokens": output.Usage.InputTokens,
|
||||
"output_tokens": output.Usage.OutputTokens,
|
||||
"PromptTokens": output.Usage.InputTokens,
|
||||
"CompletionTokens": output.Usage.OutputTokens,
|
||||
"TotalTokens": output.Usage.InputTokens + output.Usage.OutputTokens,
|
||||
// Cache metrics
|
||||
"CacheReadInputTokens": output.Usage.CacheReadInputTokens,
|
||||
"CacheCreationInputTokens": output.Usage.CacheCreationInputTokens,
|
||||
"CacheCreationEphemeral5mInputTokens": output.Usage.CacheCreation.Ephemeral5mInputTokens,
|
||||
"CacheCreationEphemeral1hInputTokens": output.Usage.CacheCreation.Ephemeral1hInputTokens,
|
||||
"PromptCachedTokens": output.Usage.CacheReadInputTokens,
|
||||
},
|
||||
}
|
||||
Contentchoices = append(Contentchoices, choice)
|
||||
@@ -290,13 +331,15 @@ func createAnthropicCompletion(ctx context.Context,
|
||||
}, nil
|
||||
}
|
||||
|
||||
func processReasoning(reasoningContent string) *reasoning.ContentReasoning {
|
||||
if reasoningContent == "" {
|
||||
func processReasoning(reasoningContent string, signature []byte, redactedContent []byte) *reasoning.ContentReasoning {
|
||||
if reasoningContent == "" && len(signature) == 0 && len(redactedContent) == 0 {
|
||||
return nil
|
||||
}
|
||||
|
||||
return &reasoning.ContentReasoning{
|
||||
Content: reasoningContent,
|
||||
Content: reasoningContent,
|
||||
Signature: signature,
|
||||
RedactedContent: redactedContent,
|
||||
}
|
||||
}
|
||||
|
||||
@@ -310,6 +353,7 @@ type streamingCompletionResponseChunk struct {
|
||||
StopReason string `json:"stop_reason"`
|
||||
StopSequence any `json:"stop_sequence"`
|
||||
Thinking string `json:"thinking,omitempty"`
|
||||
Signature string `json:"signature,omitempty"`
|
||||
} `json:"delta"`
|
||||
ContentBlock struct {
|
||||
Type string `json:"type"`
|
||||
@@ -356,6 +400,7 @@ func parseStreamingCompletionResponse(ctx context.Context, client *bedrockruntim
|
||||
contentchoices := []*llms.ContentChoice{{GenerationInfo: map[string]any{}}}
|
||||
var currentToolCall *streaming.ToolCall
|
||||
var toolCalls []llms.ToolCall
|
||||
var signature strings.Builder
|
||||
|
||||
for e := range stream.Events() {
|
||||
if err = stream.Err(); err != nil {
|
||||
@@ -399,6 +444,13 @@ func parseStreamingCompletionResponse(ctx context.Context, client *bedrockruntim
|
||||
}
|
||||
contentchoices[0].Reasoning = appendReasoning(contentchoices[0].Reasoning, resp.Delta.Thinking)
|
||||
}
|
||||
if resp.Delta.Signature != "" {
|
||||
signature.WriteString(resp.Delta.Signature)
|
||||
}
|
||||
case "signature_delta":
|
||||
if resp.Delta.Signature != "" {
|
||||
signature.WriteString(resp.Delta.Signature)
|
||||
}
|
||||
case "input_json_delta":
|
||||
if currentToolCall != nil {
|
||||
// Bedrock already sends deltas in PartialJSON, not full accumulated JSON
|
||||
@@ -451,6 +503,11 @@ func parseStreamingCompletionResponse(ctx context.Context, client *bedrockruntim
|
||||
// Add tool calls to the final response
|
||||
contentchoices[0].ToolCalls = toolCalls
|
||||
|
||||
// Add signature to reasoning if accumulated
|
||||
if signature.Len() > 0 && contentchoices[0].Reasoning != nil {
|
||||
contentchoices[0].Reasoning.Signature = []byte(signature.String())
|
||||
}
|
||||
|
||||
return &llms.ContentResponse{
|
||||
Choices: contentchoices,
|
||||
}, nil
|
||||
@@ -458,7 +515,7 @@ func parseStreamingCompletionResponse(ctx context.Context, client *bedrockruntim
|
||||
|
||||
func appendReasoning(reasoning *reasoning.ContentReasoning, reasoningContent string) *reasoning.ContentReasoning {
|
||||
if reasoning == nil {
|
||||
return processReasoning(reasoningContent)
|
||||
return processReasoning(reasoningContent, nil, nil)
|
||||
}
|
||||
|
||||
reasoning.Content += reasoningContent
|
||||
@@ -507,6 +564,29 @@ func processInputMessagesAnthropic(messages []Message) ([]*anthropicTextGenerati
|
||||
}
|
||||
content := make([]anthropicTextGenerationInputContent, 0, len(chunk))
|
||||
for _, message := range chunk {
|
||||
// For AI messages with reasoning, add thinking blocks before text
|
||||
if message.Role == llms.ChatMessageTypeAI && message.Reasoning != nil {
|
||||
// Add thinking block if present
|
||||
if message.Reasoning.Content != "" || len(message.Reasoning.Signature) > 0 {
|
||||
thinkingBlock := anthropicTextGenerationInputContent{
|
||||
Type: "thinking",
|
||||
Thinking: message.Reasoning.Content,
|
||||
}
|
||||
if len(message.Reasoning.Signature) > 0 {
|
||||
thinkingBlock.Signature = string(message.Reasoning.Signature)
|
||||
}
|
||||
content = append(content, thinkingBlock)
|
||||
}
|
||||
// Add redacted_thinking block if present
|
||||
if len(message.Reasoning.RedactedContent) > 0 {
|
||||
redactedBlock := anthropicTextGenerationInputContent{
|
||||
Type: "redacted_thinking",
|
||||
Data: string(message.Reasoning.RedactedContent),
|
||||
}
|
||||
content = append(content, redactedBlock)
|
||||
}
|
||||
}
|
||||
// Add regular content (text, tool_use, tool_result, etc.)
|
||||
content = append(content, getAnthropicInputContent(message))
|
||||
}
|
||||
inputContents = append(inputContents, &anthropicTextGenerationInputMessage{
|
||||
@@ -547,6 +627,12 @@ func getAnthropicInputContent(message Message) anthropicTextGenerationInputConte
|
||||
Type: message.Type,
|
||||
Text: message.Content,
|
||||
}
|
||||
if message.CacheControl != nil {
|
||||
c.CacheControl = &anthropicCacheControl{
|
||||
Type: message.CacheControl.Type,
|
||||
TTL: message.CacheControl.TTL,
|
||||
}
|
||||
}
|
||||
case AnthropicMessageTypeImage:
|
||||
c = anthropicTextGenerationInputContent{
|
||||
Type: message.Type,
|
||||
@@ -572,6 +658,12 @@ func getAnthropicInputContent(message Message) anthropicTextGenerationInputConte
|
||||
ToolUseID: message.ToolResult.ToolCallID,
|
||||
Content: message.ToolResult.Content,
|
||||
}
|
||||
if message.CacheControl != nil {
|
||||
c.CacheControl = &anthropicCacheControl{
|
||||
Type: message.CacheControl.Type,
|
||||
TTL: message.CacheControl.TTL,
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
return c
|
||||
|
||||
+91
-14
@@ -65,6 +65,24 @@ const (
|
||||
// Languages: 200+ languages.
|
||||
ModelAmazonNovaMicroV1 = "us.amazon.nova-micro-v1:0"
|
||||
|
||||
// Claude Opus 4.6 is the world's best model for coding, enterprise agents, and professional work.
|
||||
// It excels at agentic workflows, orchestrating complex tasks across dozens of tools with industry-leading
|
||||
// reliability. It handles the full lifecycle from architecture to deployment, delivers the deepest reasoning
|
||||
// for security workflows, and is Anthropic's most capable model for financial workflows and computer use.
|
||||
//
|
||||
// Max tokens: 1M (beta)
|
||||
// Languages: English, French, Modern Standard Arabic, Mandarin Chinese, Hindi, Spanish, Portuguese, Korean, Japanese, German, Russian, Polish, and other languages.
|
||||
ModelAnthropicClaudeOpus46 = "us.anthropic.claude-opus-4-6-v1"
|
||||
|
||||
// Claude Sonnet 4.6 delivers frontier intelligence at scale—built for coding, agents, and enterprise workflows.
|
||||
// It excels at complex, multi-step tasks requiring sustained reasoning and adaptive decision-making, handles
|
||||
// iterative development work with complex codebases, and brings professional-grade analysis with memory to
|
||||
// maintain context across files. Step-change improvement in creating spreadsheets, slides, and docs.
|
||||
//
|
||||
// Max tokens: 1M (beta)
|
||||
// Languages: English, French, Modern Standard Arabic, Mandarin Chinese, Hindi, Spanish, Portuguese, Korean, Japanese, German, Russian, Polish, and other languages.
|
||||
ModelAnthropicClaudeSonnet46 = "us.anthropic.claude-sonnet-4-6"
|
||||
|
||||
// Claude Opus 4.5 is the next generation of Anthropic's most intelligent model, an industry leader
|
||||
// across coding, agents, computer use, and enterprise workflows. It can confidently deliver multi-day
|
||||
// software development projects in hours, working independently with technical depth.
|
||||
@@ -219,6 +237,17 @@ const (
|
||||
// Languages: English.
|
||||
ModelMetaLlama38bInstructV1 = "meta.llama3-8b-instruct-v1:0"
|
||||
|
||||
// DeepSeek-V3.2 harmonizes high computational efficiency with superior reasoning and agent performance.
|
||||
// It builds on DeepSeek Sparse Attention for long-context efficiency, a scalable reinforcement learning framework,
|
||||
// and a large-scale agentic task synthesis pipeline. This model excels at long-context reasoning and agentic tasks,
|
||||
// efficiently handling extended inputs while maintaining strong accuracy. Its sparse attention design enables it to
|
||||
// process complex, multi-step workflows without excessive compute costs. Targets long-context reasoning,
|
||||
// tool-using agents, and efficient deployment in production environments.
|
||||
//
|
||||
// Max tokens: 164k
|
||||
// Languages: English, Chinese.
|
||||
ModelDeepSeekV32 = "deepseek.v3.2"
|
||||
|
||||
// DeepSeek-R1 provides customers a state-of-the-art reasoning model, optimized for general reasoning tasks,
|
||||
// math, science, and code generation. This model is created by DeepSeek and developed through a combination
|
||||
// of cold-start data and reinforcement learning. DeepSeek-R1 is a text-only model supporting English and Chinese.
|
||||
@@ -243,38 +272,54 @@ const (
|
||||
// Languages: English.
|
||||
ModelOpenAIGptOss20BV1 = "openai.gpt-oss-20b-1:0"
|
||||
|
||||
// Qwen3 Next 80B A3B is an 80B-parameter MixtureOfExperts (MOE) language model (3B active) optimized
|
||||
// for instruction following and ultra-long-context tasks. It delivers flagship-level reasoning, coding,
|
||||
// and agent performance with only 3B active parameters per token.
|
||||
// Qwen3 Next 80B A3B turns cutting-edge MoE and hybrid attention into a practical, ultra-long-context assistant
|
||||
// that scales from everyday chat to million-token workflows. It delivers flagship-level reasoning, coding,
|
||||
// and agent performance with only 3B active parameters per token. Ideal for long-context summarization,
|
||||
// code generation/refactoring, enterprise knowledge QA, and stable agentic workflows with tools.
|
||||
//
|
||||
// Max tokens: 256k
|
||||
// Languages: English, Chinese.
|
||||
ModelQwen3Next80BA3B = "qwen.qwen3-next-80b-a3b"
|
||||
|
||||
// Qwen3 VL 235B A22B is a 235B-parameter MoE vision-language flagship model (about 22B active) for
|
||||
// high-end multimodal tasks, combining strong text generation with advanced visual perception,
|
||||
// 2D/3D spatial grounding, long-context document/video understanding, and multilingual OCR over very long contexts.
|
||||
// Qwen3 VL 235B A22B is a frontier vision-language model that sees, reads, and reasons across images, documents,
|
||||
// and long videos at massive scale. Its 235B-parameter MoE architecture (≈22B active) delivers state-of-the-art
|
||||
// multimodal understanding, OCR, and spatial reasoning over contexts reaching hundreds of thousands of tokens.
|
||||
// Ideal for document intelligence (OCR + layout), multimodal RAG, visual QA, and UI/scene understanding.
|
||||
//
|
||||
// Max tokens: 256k
|
||||
// Languages: English, Chinese.
|
||||
ModelQwen3VL235BA22B = "qwen.qwen3-vl-235b-a22b"
|
||||
|
||||
// Qwen3 32B (dense) is a balanced dense model offering strong reasoning and general-purpose performance
|
||||
// with simple, predictable deployment across standard infra. It delivers performance that surpasses many
|
||||
// larger models and proves highly versatile across reasoning, coding, and research use cases.
|
||||
// Qwen3 32B is a balanced dense model that offers strong reasoning and general-purpose performance with
|
||||
// straightforward deployment on standard infrastructure. Despite its smaller size compared to frontier-scale
|
||||
// models, Qwen3-32B delivers performance that surpasses many larger models, and proves highly versatile across
|
||||
// reasoning, coding, and research use cases. Its balance of capability, cost efficiency, and operational
|
||||
// simplicity has made it one of the most practical and widely deployable models in the Qwen3 family.
|
||||
//
|
||||
// Max tokens: 16384
|
||||
// Languages: English, Chinese.
|
||||
ModelQwen332BV1 = "qwen.qwen3-32b-v1:0"
|
||||
|
||||
// Qwen3-Coder-30B-A3B-Instruct delivers strong coding and reasoning performance in a compact MoE design.
|
||||
// It excels at "vibe coding," natural-language-first programming, debugging, SQL generation, and other
|
||||
// development workflows, while being lightweight enough to run on single high-memory GPUs or small clusters.
|
||||
// Qwen3-Coder-30B-A3B-Instruct delivers strong coding and reasoning performance in a compact MoE design, making
|
||||
// it one of the most widely adopted models in the Qwen3-Coder series. It has become a favorite among developers
|
||||
// and enterprises seeking a practical balance between cost and capability. The model excels at "vibe coding,"
|
||||
// natural-language-first programming, debugging, SQL generation, and other development workflows, while being
|
||||
// lightweight enough to run on single high-memory GPUs or small clusters.
|
||||
//
|
||||
// Max tokens: 262144
|
||||
// Languages: English, Chinese.
|
||||
ModelQwen3Coder30BA3BV1 = "qwen.qwen3-coder-30b-a3b-v1:0"
|
||||
|
||||
// Qwen3-Coder-Next is an open-weight language model built specifically for coding, with strong performance
|
||||
// on large-scale software engineering and agentic coding benchmarks. It uses a hybrid Mixture-of-Experts
|
||||
// architecture to offer high capability at relatively modest active parameter counts, improving efficiency
|
||||
// for real-world deployments. Optimized for tool use and function calling, making it suitable as the core
|
||||
// of coding agents that interact with shells, editors, issue trackers, and other developer tools.
|
||||
//
|
||||
// Max tokens: 256k
|
||||
// Languages: English, Chinese.
|
||||
ModelQwen3CoderNext = "qwen.qwen3-coder-next"
|
||||
|
||||
// Mistral Large 3 is Mistral's most advanced open-weight multimodal model, combining a granular
|
||||
// Mixture-of-Experts architecture (673B total parameters with 39B active, plus a 2.5B vision encoder)
|
||||
// and a 256k context window to deliver state-of-the-art reliability, long-context reasoning, and
|
||||
@@ -299,11 +344,43 @@ const (
|
||||
// Languages: English, French, German, Spanish, Chinese, Japanese, and multiple other languages.
|
||||
ModelMistralLarge2402V1 = "mistral.mistral-large-2402-v1:0"
|
||||
|
||||
// Kimi K2.5 brings together strong vision, language, and code capabilities in a single natively multimodal
|
||||
// architecture. It handles complex tasks that mix images and text—such as generating code from UI mockups
|
||||
// or analyzing visual documents—with high accuracy. The model's "thinking" mode enables deep, deliberate reasoning,
|
||||
// while "instant" mode provides fast responses for interactive use. Its built-in support for tool use and agent
|
||||
// orchestration makes it highly effective for building sophisticated multimodal assistants.
|
||||
//
|
||||
// Max tokens: 256k
|
||||
// Languages: English, Chinese.
|
||||
ModelMoonshotKimiK25 = "moonshotai.kimi-k2.5"
|
||||
|
||||
// Kimi K2 Thinking is Moonshot AI's flagship "thinking agent" model, designed for deep, tool-augmented reasoning.
|
||||
// Its 1T-parameter MoE architecture (32B active) powers state-of-the-art performance on long-horizon tasks.
|
||||
// Native INT4 quantization and a 256K context window enable serious research- and agent-style workloads with practical hardware.
|
||||
// Its 1T-parameter MoE architecture (32B active) powers state-of-the-art performance on long-horizon tasks like
|
||||
// HLE and BrowseComp. Native INT4 quantization and a 256K context window enable serious research- and agent-style
|
||||
// workloads with practical hardware. Ideal for long-horizon planning with tools, complex coding and debugging,
|
||||
// research agents over large corpora, and workflows needing 200-300-step stable tool orchestration.
|
||||
//
|
||||
// Max tokens: 256k
|
||||
// Languages: Multilingual (including Chinese and English).
|
||||
ModelMoonshotKimiK2Thinking = "moonshot.kimi-k2-thinking"
|
||||
|
||||
// GLM-4.7 is a general-purpose language model in the GLM family with a focus on generating clean, modern
|
||||
// front-end code and web interfaces. It can turn natural-language descriptions into structured HTML, CSS,
|
||||
// and JavaScript while also supporting standard text and reasoning tasks. The model is positioned for developers
|
||||
// who want high-quality UI outputs alongside general conversational and coding abilities. It remains compatible
|
||||
// with typical LLM use cases such as question answering, summarization, and dialogue.
|
||||
//
|
||||
// Max tokens: 203k
|
||||
// Languages: English, Chinese.
|
||||
ModelGLM47 = "zai.glm-4.7"
|
||||
|
||||
// GLM-4.7-Flash is a lightweight variant of GLM-4.7, using a mixture-of-experts architecture to reduce
|
||||
// resource requirements while maintaining strong output quality. It is designed for scenarios where low latency
|
||||
// and cost efficiency are important, such as interactive assistants or high-traffic services. The model retains
|
||||
// the core text and code generation capabilities of GLM-4.7 in a smaller active-parameter footprint.
|
||||
// A practical choice when deployment constraints limit the use of larger models.
|
||||
//
|
||||
// Max tokens: 203k
|
||||
// Languages: English, Chinese.
|
||||
ModelGLM47Flash = "zai.glm-4.7-flash"
|
||||
)
|
||||
|
||||
+44
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Generated
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+322
-112
@@ -1,5 +1,5 @@
|
||||
httprr trace v1
|
||||
451 444
|
||||
451 451
|
||||
POST https://bedrock-runtime.us-east-1.amazonaws.com/model/ai21.jamba-1-5-large-v1%3A0/converse HTTP/1.1
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||||
Host: bedrock-runtime.us-east-1.amazonaws.com
|
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User-Agent: langchaingo-httprr
|
||||
@@ -8,12 +8,12 @@ Authorization: AWS4-HMAC-SHA256 test-api-key
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Content-Type: application/json
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||||
|
||||
{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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||||
Content-Length: 279
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Content-Type: application/json
|
||||
Date: Fri, 23 Jan 2026 13:17:22 GMT
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Date: Tue, 03 Mar 2026 15:43:20 GMT
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{"metrics":{"latencyMs":512},"output":{"message":{"content":[{"text":" AI: Machines simulating human intelligence for problem-solving and decision-making."}],"role":"assistant"}},"stopReason":"end_turn","usage":{"inputTokens":25,"outputTokens":17,"serverToolUsage":{},"totalTokens":42}}450 432
|
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/ai21.jamba-1-5-mini-v1%3A0/converse HTTP/1.1
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||||
Host: bedrock-runtime.us-east-1.amazonaws.com
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User-Agent: langchaingo-httprr
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@@ -22,12 +22,12 @@ Authorization: AWS4-HMAC-SHA256 test-api-key
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Content-Type: application/json
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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|
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.amazon.nova-2-lite-v1%3A0/converse HTTP/1.1
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Host: bedrock-runtime.us-east-1.amazonaws.com
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User-Agent: langchaingo-httprr
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.amazon.nova-premier-v1%3A0/converse HTTP/1.1
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Host: bedrock-runtime.us-east-1.amazonaws.com
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User-Agent: langchaingo-httprr
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@@ -50,12 +50,12 @@ Authorization: AWS4-HMAC-SHA256 test-api-key
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Content-Type: application/json
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|
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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Content-Length: 262
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Content-Length: 259
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Date: Fri, 23 Jan 2026 13:17:27 GMT
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||||
Date: Tue, 03 Mar 2026 15:43:39 GMT
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||||
|
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{"metrics":{"latencyMs":556},"output":{"message":{"content":[{"text":"AI mimics human intelligence using computers and algorithms."}],"role":"assistant"}},"stopReason":"end_turn","usage":{"inputTokens":50,"outputTokens":10,"serverToolUsage":{},"totalTokens":60}}449 428
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||||
POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.amazon.nova-pro-v1%3A0/converse HTTP/1.1
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Host: bedrock-runtime.us-east-1.amazonaws.com
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User-Agent: langchaingo-httprr
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Content-Type: application/json
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.amazon.nova-lite-v1%3A0/converse HTTP/1.1
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Host: bedrock-runtime.us-east-1.amazonaws.com
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.amazon.nova-micro-v1%3A0/converse HTTP/1.1
|
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Host: bedrock-runtime.us-east-1.amazonaws.com
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User-Agent: langchaingo-httprr
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@@ -92,13 +92,13 @@ Authorization: AWS4-HMAC-SHA256 test-api-key
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-opus-4-5-20251101-v1%3A0/converse HTTP/1.1
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Host: bedrock-runtime.us-east-1.amazonaws.com
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Host: bedrock-runtime.us-east-1.amazonaws.com
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Host: bedrock-runtime.us-east-1.amazonaws.com
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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Host: bedrock-runtime.us-east-1.amazonaws.com
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Host: bedrock-runtime.us-east-1.amazonaws.com
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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Host: bedrock-runtime.us-east-1.amazonaws.com
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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Host: bedrock-runtime.us-east-1.amazonaws.com
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/qwen.qwen3-vl-235b-a22b/converse HTTP/1.1
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/qwen.qwen3-32b-v1%3A0/converse HTTP/1.1
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/qwen.qwen3-coder-30b-a3b-v1%3A0/converse HTTP/1.1
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/qwen.qwen3-coder-next/converse HTTP/1.1
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Explain AI in 10 words or less."}],"role":"user"}],"system":[{"text":"You know all about AI."}]}HTTP/2.0 200 OK
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Date: Tue, 03 Mar 2026 15:47:54 GMT
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||||
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httprr trace v1
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770 1360
|
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-sonnet-4-5-20250929-v1%3A0/converse HTTP/1.1
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Host: bedrock-runtime.us-east-1.amazonaws.com
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{"additionalModelRequestFields":{"thinking":{"type":"enabled","budget_tokens":2048}},"inferenceConfig":{"maxTokens":4096,"temperature":1},"messages":[{"content":[{"text":"Calculate (5 + 3) and then multiply by 2"}],"role":"user"}],"toolConfig":{"toolChoice":{"auto":{}},"tools":[{"toolSpec":{"description":"Perform a calculation","inputSchema":{"json":{"properties":{"expression":{"type":"string"}},"required":["expression"],"type":"object"}},"name":"calculate"}}]}}HTTP/2.0 200 OK
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Content-Length: 1194
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X-Amzn-Requestid: ed53c3b5-af84-49b0-8450-c098606f9f2c
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httprr trace v1
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762 1364
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-sonnet-4-5-20250929-v1%3A0/converse HTTP/1.1
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527 1404
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-sonnet-4-5-20250929-v1%3A0/converse HTTP/1.1
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{"additionalModelRequestFields":{"thinking":{"type":"enabled","budget_tokens":2048}},"inferenceConfig":{"maxTokens":4096,"temperature":1},"messages":[{"content":[{"text":"Solve: If x + 5 = 12, what is x?"}],"role":"user"}]}HTTP/2.0 200 OK
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-sonnet-4-5-20250929-v1%3A0/converse HTTP/1.1
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{"additionalModelRequestFields":{"thinking":{"type":"enabled","budget_tokens":2048}},"inferenceConfig":{"maxTokens":4096,"temperature":1},"messages":[{"content":[{"text":"Solve: If x + 5 = 12, what is x?"}],"role":"user"},{"content":[{"reasoningContent":{"reasoningText":{"signature":"EtsCCkgICxABGAIqQMt8Bg6o0aVrq4MmAJZgYta5Z8bVZNBUhOsdnH4JwJwP/KJ23ntE98IHRBIyhkom0srp1sAyxXNBxu7qeqA1PgISDFKlasvZZJat+NR5PxoM9UzILoRa9dHsYKzIIjAvm+MOyk5AkVWOj7A8NAZ6H08wY534kfC9pm+8ZKX3+b2bKENW0e6t1UEHR5wdhmgqwAE5YySKQOaQfuig4tYQcVtr6Ucu0D2fL/X043zMlMOSkdRIsaDJZYoC+50POh4eI1PDl4SYU5DjGILMh6Gp6oaIbBQqWEDAfrHK9uxX1w76aQN1TyAqwXj/h7O176pPe4AcZmswUMAJLHf6zm72fcHkYW9YBffXtdg4zExE2Cm7+BFB9MlZlX24XduPS0RaMCmuOnmaxr42GMluSr8Ypk0m/YypKxvq42ANrleYE0V/VtbOwEfZldAaxCQz+MT0NG0YAQ==","text":"This is a simple algebra problem. I need to solve for x.\n\nx + 5 = 12\n\nTo isolate x, I need to subtract 5 from both sides:\nx + 5 - 5 = 12 - 5\nx = 7\n\nLet me check: 7 + 5 = 12 ✓"}}},{"text":"To solve for x, I need to isolate it on one side of the equation.\n\n**Given:** x + 5 = 12\n\n**Subtract 5 from both sides:**\nx + 5 - 5 = 12 - 5\nx = 7\n\n**Answer: x = 7**\n\nTo check: 7 + 5 = 12 ✓"}],"role":"assistant"},{"content":[{"text":"Now solve x + 10 = 25"}],"role":"user"}]}HTTP/2.0 200 OK
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httprr trace v1
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541 1706
|
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-sonnet-4-5-20250929-v1%3A0/invoke HTTP/1.1
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{"model":"claude-sonnet-4-5-20250929","id":"msg_bdrk_01FykvttgnQcwwgLMQEdjj1W","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"This is a simple linear equation. I need to solve for x.\n\nx + 5 = 12\n\nTo isolate x, I need to subtract 5 from both sides:\n\nx + 5 - 5 = 12 - 5\nx = 7\n\nLet me check: 7 + 5 = 12 ✓\n\nSo x = 7.","signature":"EucCCkgICxABGAIqQA1Bs3baE052D2zQoHInNj5chu5V28bC8iGMxs4Q3y0QuX/GjIuSBU8uIG9B3Ubn3IH0Dvf3GmyXYSOfDpfDi4ISDAogsxtiB6K7iW17zRoMDOSJMkSqATjOIcQiIjBrkoASTvvyjDByWFulTijqi+O89nC4KM6wvodmJw6MTLz7tEPsuRNWJD0rxBLq9UwqzAG4CiH4kXWSUlH4msIVzWsKGQ/ABCkntCY84C2bS+/FljjYBbjbv4rvvkYdidm3J45hEoyRX+kbFj/uLSOG9FrBmA1pmwG094TdtMbkHjNpEd0gH49H1AxcR21dfC+20XAbXHutRghdNUrTjxuWOmJneewnzbw7s0T9zmZcbyTi2DtPkgnHQbhCj3WY+SKjYt+/+FuPS6XzfQWRI7N48Dw1Iq1IZuTYhtwwfsCJzGNeY8sOttoJyoyKeg4U9D+IYhpgubnq9MLySYJtoyQYAQ=="},{"type":"text","text":"To solve for x, I need to isolate it on one side of the equation.\n\n**Given:** x + 5 = 12\n\n**Subtract 5 from both sides:**\nx + 5 - 5 = 12 - 5\nx = 7\n\n**Check:** 7 + 5 = 12 ✓\n\n**Answer: x = 7**"}],"stop_reason":"end_turn","stop_sequence":null,"usage":{"input_tokens":53,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":189}}1614 1715
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|
||||
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||||
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{"model":"claude-sonnet-4-5-20250929","id":"msg_bdrk_0161y4yYkmqTWMLv4CGdxRLa","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"This is a similar problem to the previous one. I need to solve for x by isolating it.\n\nGiven: x + 10 = 25\n\nSubtract 10 from both sides:\nx + 10 - 10 = 25 - 10\nx = 15\n\nCheck: 15 + 10 = 25 ✓","signature":"EugCCkgICxABGAIqQE/DRbSu9PlP18yKbTvX0erRBolLraq5Qw6ygJoy3ioGt0SCtRD6jcV0LBh0QKsUCDUf2A6ylAC04NVN7nrohBESDEIgyuoCpRLIEF1n6BoMfNwR1uoA2GUmrx9YIjD9kpJBJy0gWHbPWJelJ874z1ylEDwwJFP3EmUF4jJT25fYG2zci7VEgnuyrtGRrK4qzQHIU8jfQ1rO3dO8HbUQNR196LeHkDZx03SdnkhiFdvGcHBsxRtmTYiH32VMWY5e9AtAmYGDYZdfTy1eYgAtllLHSfMOPSMcHSsGIRIpjyW0ssPzYkO6wZG46JGuVKK6ZxcJ/MI7LyAetwdPHk6GaLujj+Ao+qKWC5dsmF4xAvhJBbyIXWd19csNbFGzhml7r2gFwO3+9ESG34wQub7zxjuQIJyRyHhqzHeHp3OVyCKuHS5oSc9ykQ/of4P2+yBCnA13LMWCuqo1jTVFzh7SGAE="},{"type":"text","text":"To solve for x, I need to isolate it on one side of the equation.\n\n**Given:** x + 10 = 25\n\n**Subtract 10 from both sides:**\nx + 10 - 10 = 25 - 10\nx = 15\n\n**Check:** 15 + 10 = 25 ✓\n\n**Answer: x = 15**"}],"stop_reason":"end_turn","stop_sequence":null,"usage":{"input_tokens":159,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":0},"output_tokens":182}}
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{"metrics":{"latencyMs":436},"output":{"message":{"content":[{"text":"15 * 8 = 120"}],"role":"assistant"}},"stopReason":"end_turn","usage":{"inputTokens":1055,"outputTokens":10,"serverToolUsage":{},"totalTokens":1065}}861 1015
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.amazon.nova-premier-v1%3A0/converse HTTP/1.1
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@@ -36,26 +36,26 @@ Authorization: AWS4-HMAC-SHA256 test-api-key
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{"metrics":{"latencyMs":3113},"output":{"message":{"content":[{"text":"<thinking>The user wants to multiply 15 by 8. The calculator tool can handle this as it supports multiplication operations. I'll use the calculator with the provided numbers.</thinking>\n\n"},{"toolUse":{"input":{"a":15,"b":8,"operation":"multiply"},"name":"calculator","toolUseId":"tooluse_qpz9K2ctQq6lXj7mWJr31Q"}}],"role":"assistant"}},"stopReason":"tool_use","usage":{"inputTokens":777,"outputTokens":66,"serverToolUsage":{},"totalTokens":843}}1101 1011
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{"metrics":{"latencyMs":4485},"output":{"message":{"content":[{"text":"<thinking>The user's request is to calculate 15 multiplied by 8. Since multiplication is one of the basic arithmetic operations supported by the calculator tool, I can proceed directly. First, I'll verify that both numbers are integers and the operation is valid. The calculator requires parameters: operation (string), a (number), and b (number). Here, operation=\"multiply\", a=15, and b=8 all meet the required data types. No other tools are needed as this is a straightforward multiplication problem.</thinking>\n\n"},{"toolUse":{"input":{"a":15,"b":8,"operation":"multiply"},"name":"calculator","toolUseId":"tooluse_GAVVsg1gytFgCDl6AnVVwL"}}],"role":"assistant"}},"stopReason":"tool_use","usage":{"inputTokens":777,"outputTokens":137,"serverToolUsage":{},"totalTokens":914}}1140 768
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Calculate 15 * 8"}],"role":"user"},{"content":[{"toolUse":{"input":{},"name":"calculator","toolUseId":"tooluse_qpz9K2ctQq6lXj7mWJr31Q"}}],"role":"assistant"},{"content":[{"toolResult":{"content":[{"text":"120"}],"toolUseId":"tooluse_qpz9K2ctQq6lXj7mWJr31Q"}}],"role":"user"}],"toolConfig":{"toolChoice":{"auto":{}},"tools":[{"toolSpec":{"description":"A calculator that can perform basic arithmetic operations","inputSchema":{"json":{"type":"object","properties":{"operation":{"type":"string","description":"The operation to perform","enum":["add","subtract","multiply","divide"]},"a":{"type":"number","description":"First number"},"b":{"type":"number","description":"Second number"}},"required":["operation","a","b"]}},"name":"calculator"}}]}}HTTP/2.0 200 OK
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Content-Length: 846
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Calculate 15 * 8"}],"role":"user"},{"content":[{"toolUse":{"input":{"a":"15","b":"8","operation":"multiply"},"name":"calculator","toolUseId":"tooluse_GAVVsg1gytFgCDl6AnVVwL"}}],"role":"assistant"},{"content":[{"toolResult":{"content":[{"text":"120"}],"toolUseId":"tooluse_GAVVsg1gytFgCDl6AnVVwL"}}],"role":"user"}],"toolConfig":{"toolChoice":{"auto":{}},"tools":[{"toolSpec":{"description":"A calculator that can perform basic arithmetic operations","inputSchema":{"json":{"type":"object","properties":{"operation":{"type":"string","description":"The operation to perform","enum":["add","subtract","multiply","divide"]},"a":{"type":"number","description":"First number"},"b":{"type":"number","description":"Second number"}},"required":["operation","a","b"]}},"name":"calculator"}}]}}HTTP/2.0 200 OK
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.amazon.nova-pro-v1%3A0/converse HTTP/1.1
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Host: bedrock-runtime.us-east-1.amazonaws.com
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@@ -64,26 +64,26 @@ Authorization: AWS4-HMAC-SHA256 test-api-key
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|
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Calculate 15 * 8"}],"role":"user"}],"toolConfig":{"toolChoice":{"auto":{}},"tools":[{"toolSpec":{"description":"A calculator that can perform basic arithmetic operations","inputSchema":{"json":{"type":"object","properties":{"operation":{"type":"string","description":"The operation to perform","enum":["add","subtract","multiply","divide"]},"a":{"type":"number","description":"First number"},"b":{"type":"number","description":"Second number"}},"required":["operation","a","b"]}},"name":"calculator"}}]}}HTTP/2.0 200 OK
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Host: bedrock-runtime.us-east-1.amazonaws.com
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{"metrics":{"latencyMs":554},"output":{"message":{"content":[{"text":"The result of 15 * 8 is 120."}],"role":"assistant"}},"stopReason":"end_turn","usage":{"inputTokens":503,"outputTokens":15,"serverToolUsage":{},"totalTokens":518}}858 626
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.amazon.nova-lite-v1%3A0/converse HTTP/1.1
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Host: bedrock-runtime.us-east-1.amazonaws.com
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/mistral.mistral-large-3-675b-instruct/converse HTTP/1.1
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/mistral.mistral-large-3-675b-instruct/converse HTTP/1.1
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Host: bedrock-runtime.us-east-1.amazonaws.com
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/mistral.mistral-large-2402-v1%3A0/converse HTTP/1.1
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Calculate 15 * 8"}],"role":"user"}],"toolConfig":{"toolChoice":{"auto":{}},"tools":[{"toolSpec":{"description":"A calculator that can perform basic arithmetic operations","inputSchema":{"json":{"type":"object","properties":{"operation":{"type":"string","description":"The operation to perform","enum":["add","subtract","multiply","divide"]},"a":{"type":"number","description":"First number"},"b":{"type":"number","description":"Second number"}},"required":["operation","a","b"]}},"name":"calculator"}}]}}HTTP/2.0 200 OK
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/mistral.mistral-large-2402-v1%3A0/converse HTTP/1.1
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/moonshotai.kimi-k2.5/converse HTTP/1.1
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Calculate 15 * 8"}],"role":"user"}],"toolConfig":{"toolChoice":{"auto":{}},"tools":[{"toolSpec":{"description":"A calculator that can perform basic arithmetic operations","inputSchema":{"json":{"type":"object","properties":{"operation":{"type":"string","description":"The operation to perform","enum":["add","subtract","multiply","divide"]},"a":{"type":"number","description":"First number"},"b":{"type":"number","description":"Second number"}},"required":["operation","a","b"]}},"name":"calculator"}}]}}HTTP/2.0 200 OK
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/moonshotai.kimi-k2.5/converse HTTP/1.1
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BIN
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httprr trace v1
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821 762
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-haiku-4-5-20251001-v1%3A0/invoke HTTP/1.1
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-haiku-4-5-20251001-v1%3A0/invoke HTTP/1.1
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httprr trace v1
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367 586
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-sonnet-4-5-20250929-v1%3A0/converse HTTP/1.1
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+15
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httprr trace v1
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367 586
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POST https://bedrock-runtime.us-east-1.amazonaws.com/model/us.anthropic.claude-sonnet-4-5-20250929-v1%3A0/converse HTTP/1.1
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Host: bedrock-runtime.us-east-1.amazonaws.com
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User-Agent: langchaingo-httprr
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Content-Type: application/json
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{"inferenceConfig":{"maxTokens":512},"messages":[{"content":[{"text":"Hello, how are you?"}],"role":"user"}]}HTTP/2.0 200 OK
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Reference in New Issue
Block a user