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chapter9/README.md

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| Example of benchmark creation for agent evaluation | [python script](create_benchmark.py) | x | x | x |
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| Test our agent against a benchmark dataset | [python script](run_benchmark.py) | x | x | x |
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| Prompt tracking with PromptWatch.io | [python script](prompt_tracking.py) | x | x | x |
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| Evaluate a result from an agent execution | [python script](result_evaluation.py) | | x | x |
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| Evaluate a result from an agent execution | [python script](result_evaluation.py) | x | x | x |
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| Evaluate a the trajectory in an agent execution | [python script](trajectory_evaluation.py) | x | x | x |
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| LLM search engine with vector store | [python script](serve_vector_store.py) | x | x | x |
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| LLM Webserver with Flask and Lanarky | [python script](chat.py) | x | x | x |

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