SimpleChatTCRV: Add simple readme in place of detailed one
Gives quick overview of the features, given that the original readme (now docs/details.md++) got created over a period of disjoined time as features got added.
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# Progress
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by Humans for All.
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Look into source files and git logs for the details, this is a partial changelog of stuff already done
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and some of the things that one may look at in the future.
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# SimpleChat / AnveshikaSallap
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by Humans for All.
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## Quickstart
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### Server
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From the root directory of llama.cpp source code repo containing build / tools / ... sub directories
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Start ai engine / server using
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```bash
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build/bin/llama-server -m <path/to/model.gguf> \
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--path tools/server/public_simplechat --jinja
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```
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- `--jinja` enables tool‑calling support
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- `--mmproj <path/to/mmproj.gguf>` enables vision support
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- `--port <port number>` use if a custom port is needed
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If one needs web related access / tool calls dont forget to run
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```bash
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cd tools/server/public_simplechat/local.tools; python3 ./simpleproxy.py --config simpleproxy.json
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```
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- `--debug True` enables debug mode which captures internet handshake data.
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### Client
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1. Open `http://127.0.0.1:PORT/index.html` in a browser
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2. Select / Create a chat session
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- set a suitable system prompt, if needed
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- modify **settings**, if needed
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- **Restore** loads last autosaved session with same name
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3. Enter the query, press **Enter**
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- use **Shift‑Enter** for newline
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- include images if required (ai vision models)
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4. View any streamed ai response (if enabled and supported)
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5. If a tool call is requested
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- verify / edit the tool call details before triggering the same
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- one can even ask ai to rethink on the tool call requested,
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by sending a appropriate user response instead of a tool call response.
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- tool call is executed using browser's web worker or simpleproxy
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- tool call response is placed in user input area (with color coding)
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- verify / edit the tool call response, before submit same back to ai
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- tool response initially assigned `TOOL-TEMP` role, promoted to `TOOL` upon submit
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- based on got response, if needed one can rerun tool call with modified arguments
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- *at any time there can be one pending tool call wrt a chat session*
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6. **Delete / Copy** available via popover menu for each message
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7. **Clear** / **+ New** chat with provided buttons, as needed
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## Overview
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A lightweight ai chat client with a web front-end that supports multiple chat sessions, vision, reasoning and tool calling.
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- Supports multiple independent chat sessions with
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- One‑shot or streamed (default) responses
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- Custom settings and system prompts per session
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- Automatic local autosave (restorable on next load)
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- can handshake with `/completions` or `/chat/completions` (default) endpoints
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- Supports peeking at model's reasoning live
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- if model streams the same and
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- streaming mode is enabled in settings (default)
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- Supports vision / image / multimodal ai models
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- attach image files as part of user chat messages
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- handshaked as `image_url`s in chat message content array along with text
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- supports multi-image uploads per message
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- images displayed inline in the chat history
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- specify `mmproj` file via `-mmproj` or using `-hf`
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- specify `-batch-size` and `-ubatch-size` if needed
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- Built-in support for GenAI models that expose tool calling
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- includes a bunch of useful builtin tool calls, without needing any additional setup
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- direct browser based tool calls include
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- `sys_date_time`, `simple_calculator`, `run_javascript_function_code`, `data_store_*`, `external_ai`
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- except for external_ai, these are run from within a web worker context to isolate main context from them
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- data_store brings in browser IndexedDB based persistant key/value storage across sessions
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- along with included python based simpleproxy.py
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- `search_web_text`, `fetch_web_url_raw`, `fetch_html_text`, `fetch_pdf_as_text`, `fetch_xml_filtered`
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- these built‑in tool calls (via SimpleProxy) help fetch PDFs, HTML, XML or perform web search
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- PDF tool also returns an outline with numbering
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- result is truncated to `iResultMaxDataLength` (default 128 kB)
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- helps isolate these functionality into a separate vm running locally or otherwise, if needed
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- supports whitelisting of `allowed.schemes` and `allowed.domains` through `simpleproxy.json`
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- supports a bearer token shared between server and client for auth
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- needs https support, for better security wrt this flow, avoided now given mostly local use
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- follows a safety first design and lets the user
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- verify and optionally edit the tool call requests, before executing the same
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- verify and optionally edit the tool call response, before submitting the same
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- user can update the settings for auto executing these actions, if needed
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- external_ai allows invoking a separate fresh ai instance
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- ai could run self modified targeted versions of itself/... with custom system prompts and user messages as needed
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- user can bring in an ai instance with additional compute access, which should be used only if needed
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- tool calling is currently kept disabled in such a instance
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- Client side Sliding window Context control, using `iRecentUserMsgCnt`, helps limit context sent to ai model
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- Optional auto trimming of trailing garbage from model outputs
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- Follows responsive design to try adapt to any screen size
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- built using plain html + css + javascript and python
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- no additional dependencies that one needs to keep track of
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- except for pypdf, if pdf support needed. automaticaly drops pdf tool call if pypdf missing
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- fits within ~260KB even in uncompressed source form (including simpleproxy.py)
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- easily extend with additional tool calls using either javascript or python, for additional functionality
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Start exploring / experimenting with your favorite ai models and thier capabilities.
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## Configuration / Settings
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One can modify the session configuration using Settings UI. All the settings and more are also exposed in the browser console via `document['gMe']`.
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### Settings Groups
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| Group | Purpose |
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|---------|---------|
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| `chatProps` | ApiEndpoint, streaming, sliding window, ... |
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| `tools` | `enabled`, `proxyUrl`, `proxyAuthInsecure`, search URL/template & drop rules, max data length, timeouts |
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| `apiRequestOptions` | `temperature`, `max_tokens`, `frequency_penalty`, `presence_penalty`, `cache_prompt`, ... |
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| `headers` | `Content-Type`, `Authorization`, ... |
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### Some specific settings
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- **Ai Server** (`baseURL`)
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- ai server (llama-server) address
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- default is `http://127.0.0.1:PORT`
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- **Stream** (`stream`)
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- `true` for live streaming, `false` for oneshot
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- **Client side Sliding Window** (`iRecentUserMsgCnt`)
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- `-1` : send full history
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- `0` : only system prompt
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- `>0` : last N user messages after the most recent system prompt
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- **Cache Prompt** (`cache_prompt`)
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- enables server‑side caching of system prompt and history
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- **Tool Call Timeout** (`toolCallResponseTimeoutMS`)
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- 200s by default
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- **Tool call Auto** (`autoSecs`)
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- seconds to wait before auto-triggering tool calls and auto-submitting tool responses
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- default is 0 ie manual
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- **Trim Garbage** (`bTrimGarbage`)
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- Removes repeated trailing text
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## Debugging Tips
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- **Local TCPdump**
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- `sudo tcpdump -i lo -s 0 -vvv -A host 127.0.0.1 and port 8080`
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- **Browser DevTools**
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- inspect `document['gMe']` for session state
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- **Reset Tool Call**
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- delete any assistant response after the tool call handshake
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- next wrt the last tool message
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- set role back to `TOOL-TEMP`
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- edit the response as needed
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- delete the same
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- user will be given option to edit and retrigger the tool call
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- submit the new response
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## At the end
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A thank you to all open source and open model developers, who strive for the common good.
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