Improved localdocs documentation (#762)

* Improved localdocs documentation

* Improved localdocs documentation

* Improved localdocs documentation

* Improved localdocs documentation

gpt4all-bindings/python/docs/gpt4all_chat.md

@@ -9,30 +9,53 @@ It is optimized to run 7-13B parameter LLMs on the CPU's of any computer running
 GPT4All Chat Plugins allow you to expand the capabilities of Local LLMs. All plugins are compatible with the
 chat clients server mode.
 
-### LocalDocs Plugin (Chat With Your Data)
+### LocalDocs Plugin (Chat With Your Data, PrivateGPT)
 LocalDocs is a GPT4All plugin that allows you to chat with your local files and data.
 It allows you to utilize powerful local LLMs to chat with private data without any data leaving your computer or server.
 When using LocalDocs, your LLM will cite the sources that most likely contributed to a given output. Note, even an LLM equipped with LocalDocs can hallucinate.
 
 #### Enabling LocalDocs
-1. Install the latest version of GPT4All Chat from https://gpt4all.io.
+1. Install the latest version of GPT4All Chat from [GPT4All Website](https://gpt4all.io).
-2. Go to `Settings > the LocalDocs tab`.
+2. Go to `Settings > LocalDocs tab`.
 3. Configure a collection (folder) on your computer that contains the files your LLM should have access to. You can alter the contents of the folder/directory at anytime. As you
 add more files to your collection, your LLM will dynamically be able to access them.
 4. Spin up a chat session with any LLM (including external ones like ChatGPT but warning data will leave your machine!)
-5. At the top right, click the database icon and select which collection you want your LLM to know about.
+5. At the top right, click the database icon and select which collection you want your LLM to know about during your chat session.
-6. Start chatting! 
 
-### How it works
+
+
+#### How LocalDocs Works
 LocalDocs works by maintaining an index of all data in the directory your collection is linked to. This index
 consists of small chunks of each document that the LLM can receive as additional input when you ask it a question.
-This helps it respond to your queries with knowledge about the contents of your data.
+The general technique this plugin uses is called [Retrieval Augmented Generation](https://arxiv.org/abs/2005.11401).
-The number of chunks and the size of each chunk can be configured in the LocalDocs plugin settings tab.
-For indexing speed purposes, LocalDocs uses pre-deep-learning n-gram and tfidf based retrieval when deciding
-what documents your LLM should have as context in response to a question. You'll find its of comparable quality
-with embedding based retrieval approaches but magnitudes faster to ingest data. Don't worry, embedding based semantic
-search for retrieval is on the roadmap for those with more powerful computers - pick up the feature on Github!
 
+These document chunks help your LLM respond to queries with knowledge about the contents of your data.
+The number of chunks and the size of each chunk can be configured in the LocalDocs plugin settings tab.
+For indexing speed purposes, LocalDocs uses pre-deep-learning n-gram and TF-IDF based retrieval when deciding
+what document chunks your LLM should use as context. You'll find its of comparable quality
+with embedding based retrieval approaches but magnitudes faster to ingest data.
+
+LocalDocs supports the following file types:
+```json
+["txt", "doc", "docx", "pdf", "rtf", "odt", "html", "htm",
+    "xls", "xlsx", "csv", "ods", "ppt", "pptx", "odp", "xml", "json", "log", "md", "tex", "asc", "wks",
+    "wpd", "wps", "wri", "xhtml", "xht", "xslt", "yaml", "yml", "dtd", "sgml", "tsv", "strings", "resx",
+    "plist", "properties", "ini", "config", "bat", "sh", "ps1", "cmd", "awk", "sed", "vbs", "ics", "mht",
+    "mhtml", "epub", "djvu", "azw", "azw3", "mobi", "fb2", "prc", "lit", "lrf", "tcr", "pdb", "oxps",
+    "xps", "pages", "numbers", "key", "keynote", "abw", "zabw", "123", "wk1", "wk3", "wk4", "wk5", "wq1",
+    "wq2", "xlw", "xlr", "dif", "slk", "sylk", "wb1", "wb2", "wb3", "qpw", "wdb", "wks", "wku", "wr1",
+    "wrk", "xlk", "xlt", "xltm", "xltx", "xlsm", "xla", "xlam", "xll", "xld", "xlv", "xlw", "xlc", "xlm",
+    "xlt", "xln"]
+```
+
+#### LocalDocs Limitations
+LocalDocs allows your LLM to have context about the contents of your documentation collection. LocalDocs currently cannot:
+- Answer metadata queries about your documents (e.g. `What documents do you know about?`)
+- Summarize *all* of your documents. It can however write a summary informed by the contents of your documents.
+
+#### LocalDocs Roadmap
+- Embedding based semantic search for retrieval. 
+- Customize model fine-tuned with retrieval in the loop.
 
 ## Server Mode