manual_slop/MainContext.md

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.

Stack:

• dearpygui - GUI with docking/floating/resizable panels
• google-genai - Gemini API
• anthropic - Anthropic API
• tomli-w - TOML writing
• uv - package/env management

Files:

• gui.py - main GUI, App class, all panels, all callbacks
• ai_client.py - unified provider wrapper, model listing, session management, send
• aggregate.py - reads config, collects files/screenshots/discussion, writes numbered .md files to output_dir/md_gen/
• config.toml - namespace, output_dir, files paths+base_dir, screenshots paths+base_dir, discussion history array, ai provider+model
• credentials.toml - gemini api_key, anthropic api_key

GUI Panels:

• Config - namespace, output dir, save
• Files - base_dir, scrollable path list with remove, add file(s), add wildcard
• Screenshots - base_dir, scrollable path list with remove, add screenshot(s)
• Discussion History - multiline text box, --- as separator between excerpts, save splits on --- back into toml array
• Provider - provider combo (gemini/anthropic), model listbox populated from API, fetch models button, status line
• Message - multiline input, Gen+Send button, MD Only button, Reset session button
• Response - readonly multiline displaying last AI response

Data flow:

1. GUI edits are held in App state lists (self.files, self.screenshots, self.history) and dpg widget values
2. _flush_to_config() pulls all widget values into self.config dict
3. _do_generate() calls _flush_to_config(), saves config.toml, calls aggregate.run(config) which writes the md and returns (markdown_str, path)
4. cb_generate_send() calls _do_generate() then threads a call to ai_client.send(md, message)
5. ai_client.send() prepends the md as a <context> block to the user message and sends via the active provider chat session
6. Sessions are stateful within a run (chat history maintained), Reset clears them

Config persistence:

• Every send and save writes config.toml with current state including selected provider and model under [ai]
• Discussion history is stored as a TOML array of strings in [discussion] history
• File and screenshot paths are stored as TOML arrays, support absolute paths, relative paths from base_dir, and **/* wildcards

Known extension points:

• 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
• System prompt support could be added as a field in config.toml and passed in ai_client.send()
• Discussion history excerpts could be individually toggleable for inclusion in the generated md