64 lines
5.0 KiB
Markdown
64 lines
5.0 KiB
Markdown
**manual_slop** is a local GUI tool for manually curating and sending context to AI APIs. It aggregates files, screenshots, and discussion history into a structured markdown file and sends it to a chosen AI provider with a user-written message. The AI can also execute PowerShell scripts within the project directory, with user confirmation required before each execution.
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**Stack:**
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- `dearpygui` - GUI with docking/floating/resizable panels
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- `google-genai` - Gemini API
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- `anthropic` - Anthropic API
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- `tomli-w` - TOML writing
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- `uv` - package/env management
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**Files:**
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- `gui.py` - main GUI, `App` class, all panels, all callbacks, confirmation dialog
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- `ai_client.py` - unified provider wrapper, model listing, session management, send, tool/function-call loop
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- `aggregate.py` - reads config, collects files/screenshots/discussion, writes numbered `.md` files to `output_dir`
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- `shell_runner.py` - subprocess wrapper that runs PowerShell scripts sandboxed to `base_dir`, returns stdout/stderr/exit code as a string
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- `config.toml` - namespace, output_dir, files paths+base_dir, screenshots paths+base_dir, discussion history array, ai provider+model
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- `credentials.toml` - gemini api_key, anthropic api_key
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**GUI Panels:**
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- **Config** - namespace, output dir, save
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- **Files** - base_dir, scrollable path list with remove, add file(s), add wildcard
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- **Screenshots** - base_dir, scrollable path list with remove, add screenshot(s)
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- **Discussion History** - multiline text box, `---` as separator between excerpts, save splits on `---` back into toml array
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- **Provider** - provider combo (gemini/anthropic), model listbox populated from API, fetch models button, status line
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- **Message** - multiline input, Gen+Send button, MD Only button, Reset session button
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- **Response** - readonly multiline displaying last AI response
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- **Tool Calls** - scrollable log of every PowerShell tool call the AI made, showing script and result; Clear button
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**AI Tool Use (PowerShell):**
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- Both Gemini and Anthropic are configured with a `run_powershell` tool/function declaration
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- When the AI wants to edit or create files it emits a tool call with a `script` string
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- `ai_client` runs a loop (max `MAX_TOOL_ROUNDS = 5`) feeding tool results back until the AI stops calling tools
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- Before any script runs, `gui.py` shows a modal `ConfirmDialog` on the main thread; the background send thread blocks on a `threading.Event` until the user clicks Approve or Reject
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- The dialog displays `base_dir`, shows the script in an editable text box (allowing last-second tweaks), and has Approve & Run / Reject buttons
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- On approval the (possibly edited) script is passed to `shell_runner.run_powershell()` which prepends `Set-Location -LiteralPath '<base_dir>'` and runs it via `powershell -NoProfile -NonInteractive -Command`
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- stdout, stderr, and exit code are returned to the AI as the tool result
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- Rejections return `"USER REJECTED: command was not executed"` to the AI
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- All tool calls (script + result/rejection) are appended to `_tool_log` and displayed in the Tool Calls panel
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**Data flow:**
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1. GUI edits are held in `App` state lists (`self.files`, `self.screenshots`, `self.history`) and dpg widget values
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2. `_flush_to_config()` pulls all widget values into `self.config` dict
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3. `_do_generate()` calls `_flush_to_config()`, saves `config.toml`, calls `aggregate.run(config)` which writes the md and returns `(markdown_str, path)`
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4. `cb_generate_send()` calls `_do_generate()` then threads a call to `ai_client.send(md, message, base_dir)`
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5. `ai_client.send()` prepends the md as a `<context>` block to the user message and sends via the active provider chat session
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6. If the AI responds with tool calls, the loop handles them (with GUI confirmation) before returning the final text response
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7. Sessions are stateful within a run (chat history maintained), `Reset` clears them and the tool log
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**Config persistence:**
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- Every send and save writes `config.toml` with current state including selected provider and model under `[ai]`
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- Discussion history is stored as a TOML array of strings in `[discussion] history`
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- File and screenshot paths are stored as TOML arrays, support absolute paths, relative paths from base_dir, and `**/*` wildcards
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**Threading model:**
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- DPG render loop runs on the main thread
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- AI sends and model fetches run on daemon background threads
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- `_pending_dialog` (guarded by a `threading.Lock`) is set by the background thread and consumed by the render loop each frame, calling `dialog.show()` on the main thread
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- `dialog.wait()` blocks the background thread on a `threading.Event` until the user acts
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**Known extension points:**
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- Add more providers by adding a section to `credentials.toml`, a `_list_*` and `_send_*` function in `ai_client.py`, and the provider name to the `PROVIDERS` list in `gui.py`
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- System prompt support could be added as a field in `config.toml` and passed in `ai_client.send()`
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- Discussion history excerpts could be individually toggleable for inclusion in the generated md
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- `MAX_TOOL_ROUNDS` in `ai_client.py` caps agentic loops at 5 rounds; adjustable
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