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Copy file name to clipboardExpand all lines: bedrock/basic/README.md
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@@ -4,7 +4,7 @@ A basic Bedrock workflow. Starts a workflow with a prompt, generates a response
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To run, first see `samples-python`[README.md](../../README.md), and `bedrock`[README.md](../README.md) for prerequisites specific to this sample. Once set up, run the following from this directory:
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1. Run the worker: `poetry run python run_worker.py`
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1. Run the worker: `uv run run_worker.py`
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2. In another terminal run the client with a prompt:
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e.g. `poetry run python send_message.py 'What animals are marsupials?'`
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e.g. `uv run send_message.py 'What animals are marsupials?'`
Copy file name to clipboardExpand all lines: bedrock/entity/README.md
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@@ -4,16 +4,16 @@ Multi-Turn Chat using an Entity Workflow. The workflow runs forever unless expli
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To run, first see `samples-python`[README.md](../../README.md), and `bedrock`[README.md](../README.md) for prerequisites specific to this sample. Once set up, run the following from this directory:
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1. Run the worker: `poetry run python run_worker.py`
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1. Run the worker: `uv run run_worker.py`
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2. In another terminal run the client with a prompt.
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Example: `poetry run python send_message.py 'What animals are marsupials?'`
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Example: `uv run send_message.py 'What animals are marsupials?'`
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3. View the worker's output for the response.
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4. Give followup prompts by signaling the workflow.
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Example: `poetry run python send_message.py 'Do they lay eggs?'`
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Example: `uv run send_message.py 'Do they lay eggs?'`
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5. Get the conversation history summary by querying the workflow.
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Example: `poetry run python get_history.py`
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6. To end the chat session, run `poetry run python end_chat.py`
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Example: `uv run get_history.py`
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6. To end the chat session, run `uv run end_chat.py`
Copy file name to clipboardExpand all lines: bedrock/signals_and_queries/README.md
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@@ -4,16 +4,16 @@ Adding signals & queries to the [basic Bedrock sample](../1_basic). Starts a wor
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To run, first see `samples-python`[README.md](../../README.md), and `bedrock`[README.md](../README.md) for prerequisites specific to this sample. Once set up, run the following from this directory:
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1. Run the worker: `poetry run python run_worker.py`
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1. Run the worker: `uv run run_worker.py`
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2. In another terminal run the client with a prompt.
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Example: `poetry run python send_message.py 'What animals are marsupials?'`
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Example: `uv run send_message.py 'What animals are marsupials?'`
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3. View the worker's output for the response.
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4. Give followup prompts by signaling the workflow.
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Example: `poetry run python send_message.py 'Do they lay eggs?'`
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Example: `uv run send_message.py 'Do they lay eggs?'`
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5. Get the conversation history by querying the workflow.
Copy file name to clipboardExpand all lines: cloud_export_to_parquet/README.md
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@@ -4,20 +4,20 @@ This is an example workflow to convert exported file from proto to parquet file.
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Please make sure your python is 3.9 above. For this sample, run:
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poetry install --with cloud_export_to_parquet
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uv sync --group=cloud-export-to-parquet
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Before you start, please modify workflow input in `create_schedule.py` with your s3 bucket and namespace. Also make sure you've the right AWS permission set up in your environment to allow this workflow read and write to your s3 bucket.
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To run, first see [README.md](../README.md) for prerequisites. Then, run the following from this directory to start the worker:
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```bash
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poetry run python run_worker.py
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uv run run_worker.py
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```
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This will start the worker. Then, in another terminal, run the following to execute the schedule:
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```bash
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poetry run python create_schedule.py
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uv run create_schedule.py
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```
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The workflow should convert exported file in your input s3 bucket to parquet in your specified location.
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