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1 | 1 | # Docs Agent |
2 | 2 |
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3 | 3 | The Docs Agent project enables [PaLM API][genai-doc-site] users to launch a chat application |
4 | | -on a Linux-based host machine using their own set of documents as a source dataset. |
| 4 | +on a Linux host machine using their documents as a dataset. |
5 | 5 |
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6 | | -**Note**: If you're interested in setting up and launching the Docs Agent sample app on your |
7 | | -host machine, see the [Set up Docs Agent][set-up-docs-agent] section below. |
| 6 | +**Note**: If you want to set up and launch the Docs Agent sample app on your host machine, |
| 7 | +check out the [Set up Docs Agent][set-up-docs-agent] section below. |
8 | 8 |
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9 | 9 | ## Overview |
10 | 10 |
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11 | | -The Docs Agent sample app is being developed to demonstrate an AI-powered chatbot application |
| 11 | +The Docs Agent project is being developed to demonstrate an AI-powered chatbot application |
12 | 12 | (including a backend server and web UI) that can answer questions specific to any product, |
13 | | -service, or topic that has a great quantity of information available as documentation (which |
14 | | -can be from various sources such as Markdown, HTML, Google Docs, chat conversations, etc.). |
| 13 | +service, or topic that has a large amount of information available in documentation (which |
| 14 | +can be from various sources such as Markdown, HTML, Google Docs, Gmail, PDF, etc.). |
15 | 15 |
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16 | 16 | The main goal of the Docs Agent project is: |
17 | 17 |
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18 | | -- You can supply your own set of documents to enable a PaLM 2 model to synthesize useful, |
| 18 | +- You can supply your own set of documents to enable a PaLM 2 model to generate useful, |
19 | 19 | relevant, and accurate responses that are grounded on the documented information. |
20 | 20 |
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21 | 21 | The Docs Agent sample app is designed to be easily set up and configured in a Linux environment |
22 | 22 | and is required that you have access to Google’s [PaLM API][genai-doc-site]. |
23 | 23 |
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24 | | -Keep in mind that this approach is not to “fine-tune” an LLM (large language model) |
25 | | -itself, but the Docs Agent sample app uses a mixture of prompt engineering and |
26 | | -embeddings techniques on top of a publicly available LLM model such as PaLM 2. |
| 24 | +Keep in mind that this approach does not involve “fine-tuning” an LLM (large language model). |
| 25 | +Instead, the Docs Agent sample app uses a mixture of prompt engineering and embedding techniques, |
| 26 | +also known as Retrieval Augmented Generation (RAG), on top of a publicly available LLM model |
| 27 | +like PaLM 2. |
27 | 28 |
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28 | 29 |  |
29 | 30 |
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@@ -310,6 +311,10 @@ The project includes Apps Script files that allow you to convert various sources |
310 | 311 | use these Markdown files as additional input sources for Docs Agent. For more information, see the |
311 | 312 | [`README`][apps-script-readme] file in the `apps_script` directory. |
312 | 313 |
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| 314 | + |
| 315 | + |
| 316 | +**Figure 7**. Docs Agent's pre-processing flow for various doc types. |
| 317 | + |
313 | 318 | ## Issues identified |
314 | 319 |
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315 | 320 | The following issues have been identified and need to be worked on: |
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