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fix: promote provider-specific chat models in docs and new template
Replace UiPathChat references with UiPathChatAnthropicBedrock, UiPathChatBedrockConverse, UiPathAzureChatOpenAI, and UiPathChatVertex. Drop hardcoded model lists in favour of `uipath list-models`. Update the `uipath new` template to use UiPathChatAnthropicBedrock by default. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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‎docs/chat_models.md‎

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# Chat Models
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UiPath provides two chat models `UiPathAzureChatOpenAI` and `UiPathChat`. These are compatible with LangGraph as drop in replacements. You do not need to add tokens from OpenAI or Anthropic, usage of these chat models will consume `Agent Units` on your account.
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UiPath provides chat model classes compatible with LangChain and LangGraph as drop-in replacements. You do not need provider API keys — usage consumes Agent Units on your account.
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## UiPathAzureChatOpenAI
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To see the models available for your account, run:
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`UiPathAzureChatOpenAI` can be used as a drop in replacement for `ChatOpenAI` or `AzureChatOpenAI`.
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```bash
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uipath list-models
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```
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/// note
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`UiPathChat` and `UiPathAzureChatOpenAI` are legacy classes and will be phased out in a future release. `UiPathAzureChatOpenAI` has been renamed to `UiPathChatOpenAI` (same class, new name). When you can, migrate existing code to one of the provider-specific classes below.
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///
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### Example usage
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## UiPathChatOpenAI
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Here is a code that is using `ChatOpenAI`
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Drop-in replacement for `ChatOpenAI` or `AzureChatOpenAI`. This is the new name for `UiPathAzureChatOpenAI`.
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Original code using `ChatOpenAI`:
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```python
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from langchain_openai import ChatOpenAI
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)
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```
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You can simply change `ChatOpenAi` with `UiPathAzureChatOpenAI`, you don't have to provide an OpenAI token.
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Swap `ChatOpenAI` for `UiPathChatOpenAI` — no OpenAI token needed:
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```python
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from uipath_langchain.chat.models import UiPathAzureChatOpenAI
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from uipath_langchain.chat import UiPathChatOpenAI
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llm = UiPathAzureChatOpenAI(
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model="gpt-4.1-mini-2025-04-14",
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llm = UiPathChatOpenAI(
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model="<model>",
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temperature=0,
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max_tokens=4000,
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timeout=30,
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)
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```
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Currently, the following models can be used with `UiPathAzureChatOpenAI` (this list can be updated in the future):
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- `gpt-4`, `gpt-4-1106-Preview`, `gpt-4-32k`, `gpt-4-turbo-2024-04-09`, `gpt-4-vision-preview`, `gpt-4o-2024-05-13`, `gpt-4o-2024-08-06`, `gpt-4o-mini-2024-07-18`, `gpt-4.1-mini-2025-04-14`, `o3-mini-2025-01-31`
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## UiPathChat
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## UiPathChatAnthropicBedrock
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`UiPathChat` is a more versatile class that can suport models from diferent vendors including OpenAI.
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Drop-in replacement for `ChatAnthropic` (or `ChatBedrock` when using Anthropic models).
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### Example usage
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Given the following code:
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Original code using `ChatAnthropic`:
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```python
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from langchain_anthropic import ChatAnthropic
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)
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```
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You can replace it with `UiPathChat` like so:
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Swap for `UiPathChatAnthropicBedrock`:
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```python
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from uipath_langchain.chat.models import UiPathChat
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from uipath_langchain.chat import UiPathChatAnthropicBedrock
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llm = UiPathChat(
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model="anthropic.claude-3-opus-20240229-v1:0",
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llm = UiPathChatAnthropicBedrock(
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model_id="<model>",
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temperature=0,
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max_tokens=1024,
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timeout=None,
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```
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Currently the following models can be used with `UiPathChat` (this list can be updated in the future):
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## UiPathChatBedrockConverse
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- `anthropic.claude-3-5-sonnet-20240620-v1:0`, `anthropic.claude-3-5-sonnet-20241022-v2:0`, `anthropic.claude-3-7-sonnet-20250219-v1:0`, `anthropic.claude-3-haiku-20240307-v1:0`, `gemini-1.5-pro-001`, `gemini-2.0-flash-001`, `gpt-4o-2024-05-13`, `gpt-4o-2024-08-06`, `gpt-4o-2024-11-20`, `gpt-4o-mini-2024-07-18`, `o3-mini-2025-01-31`
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Drop-in replacement for `ChatBedrockConverse` from `langchain_aws`. Supports models from multiple providers via the AWS Bedrock Converse API.
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/// warning
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Please note that you may get errors related to data residency, as some models are not available on all regions.
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Original code using `ChatBedrockConverse`:
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Example: `[Enforced Region] No model configuration found for product uipath-python-sdk in EU using model anthropic.claude-3-opus-20240229-v1:0`.
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```python
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from langchain_aws import ChatBedrockConverse
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llm = ChatBedrockConverse(
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model="anthropic.claude-3-5-sonnet-20240620-v1:0",
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temperature=0,
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max_tokens=1024,
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# other params...
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)
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```
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Swap for `UiPathChatBedrockConverse`:
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```python
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from uipath_langchain.chat import UiPathChatBedrockConverse
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llm = UiPathChatBedrockConverse(
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model="<model>",
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temperature=0,
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max_tokens=1024,
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# other params...
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)
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```
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## UiPathChatVertex
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Drop-in replacement for `ChatGoogleGenerativeAI` or `ChatVertexAI`.
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Original code using `ChatGoogleGenerativeAI`:
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```python
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from langchain_google_genai import ChatGoogleGenerativeAI
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llm = ChatGoogleGenerativeAI(
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model="gemini-2.0-flash-001",
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temperature=0,
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max_tokens=1024,
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# other params...
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)
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```
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Swap for `UiPathChatVertex`:
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```python
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from uipath_langchain.chat import UiPathChatVertex
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llm = UiPathChatVertex(
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model="<model>",
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temperature=0,
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max_tokens=1024,
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# other params...
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)
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```
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/// warning
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Some models may not be available in all regions due to data residency restrictions. Use `uipath list-models` to see which models are available in your region.
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///

‎src/uipath_langchain/_cli/_templates/main.py.template‎

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from langchain_core.messages import HumanMessage, SystemMessage
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from langgraph.graph import START, StateGraph, END
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from uipath_langchain.chat import UiPathChat
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from uipath_langchain.chat import UiPathChatOpenAI
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from pydantic import BaseModel
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llm = UiPathChat(model="gpt-4o-mini-2024-07-18")
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llm = UiPathChatOpenAI(model="gpt-4o-2024-11-20")
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class GraphState(BaseModel):

‎src/uipath_langchain/_resources/REQUIRED_STRUCTURE.md‎

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### Required LLM Initialization
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Unless the user explicitly requests a different LLM provider, always use `UiPathChat`:
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Unless the user explicitly requests a different LLM provider, always use `UiPathChatOpenAI`:
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```python
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from uipath_langchain.chat import UiPathChat
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from uipath_langchain.chat import UiPathChatOpenAI
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llm = UiPathChat(model="gpt-4.1-mini-2025-04-14", temperature=0.7)
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llm = UiPathChatOpenAI(model="gpt-4o-2024-11-20", temperature=0.7)
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```
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**Alternative LLMs** (only use if explicitly requested):
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To list available models, run `uipath list-models`.
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**Alternative UiPath chat models** (require the matching extra: `uipath-langchain[bedrock]` or `uipath-langchain[vertex]`):
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- `UiPathChatAnthropicBedrock` for Anthropic models via AWS Bedrock
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- `UiPathChatBedrockConverse` for the AWS Bedrock Converse API (multi-provider)
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- `UiPathChatVertex` for Google Vertex AI models
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**Alternative LangChain LLMs** (only use if explicitly requested):
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- `ChatOpenAI` from `langchain_openai`
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- `ChatAnthropic` from `langchain_anthropic`
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- Other LangChain-compatible LLMs
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```python
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from langchain_core.messages import SystemMessage, HumanMessage
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from langgraph.graph import START, StateGraph, END
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from uipath_langchain.chat import UiPathChat
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from uipath_langchain.chat import UiPathChatOpenAI
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from pydantic import BaseModel
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# 1. Define Input, State, and Output models
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class Output(BaseModel):
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result: str
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# 2. Initialize UiPathChat LLM
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llm = UiPathChat(model="gpt-4.1-mini-2025-04-14", temperature=0.7)
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# 2. Initialize the LLM
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llm = UiPathChatOpenAI(model="gpt-4o-2024-11-20", temperature=0.7)
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# 3. Define agent nodes (async functions)
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async def process_node(state: State) -> State:

‎testcases/init-flow/expected_traces.json‎

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}
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},
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{
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"name": "UiPathChat",
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"name": "UiPathChatOpenAI",
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"attributes": {
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"openinference.span.kind": "LLM",
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"llm.provider": "uipath",
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"llm.provider": "openai",
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"llm.model_name": "*"
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}
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}

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