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BoundaryML · Jun 13, 2024 · 7dfaea5 · 7dfaea5
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diff --git a/engine/language-client-codegen/src/typescript/templates/client.js.j2 b/engine/language-client-codegen/src/typescript/templates/client.js.j2
@@ -4,7 +4,7 @@ import {
 } from "./types"
 import TypeBuilder from "./type_builder"
 
-type RecursivePartialNull<T> = T extends object
+export type RecursivePartialNull<T> = T extends object
   ? {
       [P in keyof T]?: RecursivePartialNull<T[P]>;
     }

diff --git a/integ-tests/ruby/baml_client/inlined.rb b/integ-tests/ruby/baml_client/inlined.rb
@@ -16,11 +16,7 @@ module Baml
   module Inlined
     FILE_MAP = {
 
-<<<<<<< HEAD
-        "clients.baml" => "retry_policy Bar {\n  max_retries 3\n  strategy {\n    type exponential_backoff\n  }\n}\n\nretry_policy Foo {\n  max_retries 3\n  strategy {\n    type constant_delay\n    delay_ms 100\n  }\n}\n\nclient<llm> GPT4 {\n  provider baml-openai-chat\n  options {\n    model gpt-4\n    api_key env.OPENAI_API_KEY\n  }\n} \n\n\nclient<llm> GPT4o {\n  provider baml-openai-chat\n  options {\n    model gpt-4o\n    api_key env.OPENAI_API_KEY\n  }\n} \n\n\nclient<llm> GPT4Turbo {\n  retry_policy Bar\n  provider baml-openai-chat\n  options {\n    model gpt-4-turbo\n    api_key env.OPENAI_API_KEY\n  }\n} \n\nclient<llm> GPT35 {\n  provider baml-openai-chat\n  options {\n    model \"gpt-3.5-turbo\"\n    api_key env.OPENAI_API_KEY\n  }\n}\n\nclient<llm> Ollama {\n  provider ollama\n  options {\n    model llama2\n    api_key \"\"\n  }\n}\n\nclient<llm> GPT35Azure {\n  provider azure-openai\n  options {\n    resource_name \"west-us-azure-baml\"\n    deployment_id \"gpt-35-turbo-default\"\n    // base_url \"https://west-us-azure-baml.openai.azure.com/openai/deployments/gpt-35-turbo-default\"\n    api_version \"2024-02-01\"\n    api_key env.AZURE_OPENAI_API_KEY\n  }\n}\n\nclient<llm> Gemini {\n  provider google-ai\n  options{\n    model \"gemini-1.5-pro-001\"\n    api_key env.GOOGLE_API_KEY\n  }\n}\n\n\nclient<llm> Claude {\n  provider anthropic\n  options {\n    model claude-3-haiku-20240307\n    api_key env.ANTHROPIC_API_KEY\n    max_tokens 1000\n  }\n}\n\nclient<llm> Resilient_SimpleSyntax {\n  retry_policy Foo\n  provider baml-fallback\n  options {\n    strategy [\n      GPT4Turbo\n      GPT35\n      Lottery_SimpleSyntax\n    ]\n  }\n} \n \nclient<llm> Lottery_SimpleSyntax {\n  provider baml-round-robin\n  options {\n    start 0\n    strategy [\n      GPT35\n      Claude\n    ]\n  }\n}\n",
-=======
         "clients.baml" => "retry_policy Bar {\n  max_retries 3\n  strategy {\n    type exponential_backoff\n  }\n}\n\nretry_policy Foo {\n  max_retries 3\n  strategy {\n    type constant_delay\n    delay_ms 100\n  }\n}\n\nclient<llm> GPT4 {\n  provider baml-openai-chat\n  options {\n    model gpt-4\n    api_key env.OPENAI_API_KEY\n  }\n} \n\n\nclient<llm> GPT4o {\n  provider baml-openai-chat\n  options {\n    model gpt-4o\n    api_key env.OPENAI_API_KEY\n  }\n} \n\n\nclient<llm> GPT4Turbo {\n  retry_policy Bar\n  provider baml-openai-chat\n  options {\n    model gpt-4-turbo\n    api_key env.OPENAI_API_KEY\n  }\n} \n\nclient<llm> GPT35 {\n  provider baml-openai-chat\n  options {\n    model \"gpt-3.5-turbo\"\n    api_key env.OPENAI_API_KEY\n  }\n}\n\nclient<llm> Ollama {\n  provider ollama\n  options {\n    model llama2\n  }\n}\n\nclient<llm> GPT35Azure {\n  provider azure-openai\n  options {\n    resource_name \"west-us-azure-baml\"\n    deployment_id \"gpt-35-turbo-default\"\n    // base_url \"https://west-us-azure-baml.openai.azure.com/openai/deployments/gpt-35-turbo-default\"\n    api_version \"2024-02-01\"\n    api_key env.AZURE_OPENAI_API_KEY\n  }\n}\n\nclient<llm> Gemini {\n  provider google-ai\n  options{\n    model \"gemini-1.5-pro-001\"\n    api_key env.GOOGLE_API_KEY\n  }\n}\n\n\nclient<llm> Claude {\n  provider anthropic\n  options {\n    model claude-3-haiku-20240307\n    api_key env.ANTHROPIC_API_KEY\n    max_tokens 1000\n  }\n}\n\nclient<llm> Resilient_SimpleSyntax {\n  retry_policy Foo\n  provider baml-fallback\n  options {\n    strategy [\n      GPT4Turbo\n      GPT35\n      Lottery_SimpleSyntax\n    ]\n  }\n} \n \nclient<llm> Lottery_SimpleSyntax {\n  provider baml-round-robin\n  options {\n    start 0\n    strategy [\n      GPT35\n      Claude\n    ]\n  }\n}\n",
->>>>>>> 9e1ec312 (Adding recursive defintions for nested classes (when streaming for partials).)
         "fiddle-examples/chain-of-thought.baml" => "class Email {\n    subject string\n    body string\n    from_address string\n}\n\nenum OrderStatus {\n    ORDERED\n    SHIPPED\n    DELIVERED\n    CANCELLED\n}\n\nclass OrderInfo {\n    order_status OrderStatus\n    tracking_number string?\n    estimated_arrival_date string?\n}\n\nfunction GetOrderInfo(email: Email) -> OrderInfo {\n  client GPT4\n  prompt #\"\n    Given the email below:\n\n    ```\n    from: {{email.from_address}}\n    Email Subject: {{email.subject}}\n    Email Body: {{email.body}}\n    ```\n\n    Extract this info from the email in JSON format:\n    {{ ctx.output_format }}\n\n    Before you output the JSON, please explain your\n    reasoning step-by-step. Here is an example on how to do this:\n    'If we think step by step we can see that ...\n     therefore the output JSON is:\n    {\n      ... the json schema ...\n    }'\n  \"#\n}",
         "fiddle-examples/chat-roles.baml" => "// This will be available as an enum in your Python and Typescript code.\nenum Category2 {\n    Refund\n    CancelOrder\n    TechnicalSupport\n    AccountIssue\n    Question\n}\n\nfunction ClassifyMessage2(input: string) -> Category {\n  client GPT4\n\n  prompt #\"\n    {{ _.role(\"system\") }}\n    // You can use _.role(\"system\") to indicate that this text should be a system message\n\n    Classify the following INPUT into ONE\n    of the following categories:\n\n    {{ ctx.output_format }}\n\n    {{ _.role(\"user\") }}\n    // And _.role(\"user\") to indicate that this text should be a user message\n\n    INPUT: {{ input }}\n\n    Response:\n  \"#\n}",
         "fiddle-examples/classify-message.baml" => "// This will be available as an enum in your Python and Typescript code.\nenum Category {\n    Refund\n    CancelOrder\n    TechnicalSupport\n    AccountIssue\n    Question\n}\n\nfunction ClassifyMessage(input: string) -> Category {\n  client GPT4\n\n  prompt #\"\n    Classify the following INPUT into ONE\n    of the following categories:\n\n    INPUT: {{ input }}\n\n    {{ ctx.output_format }}\n\n    Response:\n  \"#\n}",