95 lines
3.1 KiB
Markdown
95 lines
3.1 KiB
Markdown
# Parallel Batch Translation Process
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This project demonstrates using PocketFlow's async and parallel features (`AsyncFlow`, `AsyncParallelBatchNode`) to translate a document into multiple languages concurrently.
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- Check out the [Substack Post Tutorial](https://pocketflow.substack.com/p/parallel-llm-calls-from-scratch-tutorial) for more!
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## Goal
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Translate `../../README.md` into multiple languages (Chinese, Spanish, etc.) in parallel, saving each to a file in the `translations/` directory. The main goal is to compare execution time against a sequential process.
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## Getting Started
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1. Install requirements:
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```bash
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pip install -r requirements.txt
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```
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2. Set API Key:
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Set the environment variable for your Anthropic API key.
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```bash
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export ANTHROPIC_API_KEY="your-api-key-here"
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```
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*(Replace `"your-api-key-here"` with your actual key)*
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*(Alternatively, place `ANTHROPIC_API_KEY=your-api-key-here` in a `.env` file)*
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3. Verify API Key (Optional):
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Run a quick check using the utility script.
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```bash
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python utils.py
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```
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*(Note: This requires a valid API key to be set.)*
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4. Run the translation process:
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```bash
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python main.py
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```
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## How It Works
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The implementation uses an `AsyncParallelBatchNode` that processes translation requests concurrently. The `TranslateTextNodeParallel`:
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1. Prepares batches, pairing the source text with each target language.
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2. Executes translation calls to the LLM for all languages concurrently using `async` operations.
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3. Saves the translated content to individual files (`translations/README_LANGUAGE.md`).
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This approach leverages `asyncio` and parallel execution to speed up I/O-bound tasks like multiple API calls.
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## Example Output & Comparison
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Running this parallel version significantly reduces the total time compared to a sequential approach:
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```
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# --- Sequential Run Output (from pocketflow-batch) ---
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Starting sequential translation into 8 languages...
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Translated Chinese text
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...
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Translated Korean text
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Saved translation to translations/README_CHINESE.md
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...
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Saved translation to translations/README_KOREAN.md
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Total sequential translation time: ~1136 seconds
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=== Translation Complete ===
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Translations saved to: translations
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============================
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# --- Parallel Run Output (this example) ---
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Starting parallel translation into 8 languages...
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Translated French text
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Translated Portuguese text
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... # Messages may appear interleaved
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Translated Spanish text
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Saved translation to translations/README_CHINESE.md
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...
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Saved translation to translations/README_KOREAN.md
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Total parallel translation time: ~209 seconds
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=== Translation Complete ===
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Translations saved to: translations
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============================
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```
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*(Actual times will vary based on API response speed and system.)*
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## Files
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- [`main.py`](./main.py): Implements the parallel batch translation node and flow.
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- [`utils.py`](./utils.py): Async wrapper for calling the Anthropic model.
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- [`requirements.txt`](./requirements.txt): Project dependencies (includes `aiofiles`).
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- [`translations/`](./translations/): Output directory (created automatically).
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