vibin
This commit is contained in:
1
.gitignore
vendored
1
.gitignore
vendored
@@ -2,3 +2,4 @@
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__pycache__
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uv.lock
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colorforth_bootslop_002.md
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md_gen
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@@ -1,4 +1,4 @@
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**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.
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**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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@@ -8,9 +8,10 @@
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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
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- `ai_client.py` - unified provider wrapper, model listing, session management, send
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- `aggregate.py` - reads config, collects files/screenshots/discussion, writes numbered `.md` files to `output_dir/md_gen/`
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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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@@ -22,21 +23,41 @@
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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)`
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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. Sessions are stateful within a run (chat history maintained), `Reset` clears them
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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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205
ai_client.py
205
ai_client.py
@@ -11,6 +11,13 @@ _gemini_chat = None
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_anthropic_client = None
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_anthropic_history: list[dict] = []
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# Injected by gui.py - called when AI wants to run a command.
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# Signature: (script: str) -> str | None
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# Returns the output string if approved, None if rejected.
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confirm_and_run_callback = None
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MAX_TOOL_ROUNDS = 5
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def _load_credentials() -> dict:
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with open("credentials.toml", "rb") as f:
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return tomllib.load(f)
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@@ -61,21 +68,139 @@ def _list_anthropic_models() -> list[str]:
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models.append(m.id)
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return sorted(models)
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# --------------------------------------------------------- tool definition
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TOOL_NAME = "run_powershell"
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_ANTHROPIC_TOOLS = [
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{
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"name": TOOL_NAME,
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"description": (
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"Run a PowerShell script within the project base_dir. "
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"Use this to create, edit, rename, or delete files and directories. "
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"The working directory is set to base_dir automatically. "
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"Always prefer targeted edits over full rewrites where possible. "
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"stdout and stderr are returned to you as the result."
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),
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"input_schema": {
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"type": "object",
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"properties": {
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"script": {
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"type": "string",
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"description": "The PowerShell script to execute."
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}
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},
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"required": ["script"]
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}
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}
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]
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def _gemini_tool_declaration():
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from google.genai import types
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return types.Tool(
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function_declarations=[
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types.FunctionDeclaration(
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name=TOOL_NAME,
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description=(
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"Run a PowerShell script within the project base_dir. "
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"Use this to create, edit, rename, or delete files and directories. "
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"The working directory is set to base_dir automatically. "
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"stdout and stderr are returned to you as the result."
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),
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parameters=types.Schema(
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type=types.Type.OBJECT,
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properties={
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"script": types.Schema(
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type=types.Type.STRING,
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description="The PowerShell script to execute."
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)
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},
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required=["script"]
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)
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)
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]
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)
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def _run_script(script: str, base_dir: str) -> str:
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"""
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Delegate to the GUI confirmation callback.
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Returns result string (stdout/stderr) or a rejection message.
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"""
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if confirm_and_run_callback is None:
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return "ERROR: no confirmation handler registered"
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result = confirm_and_run_callback(script, base_dir)
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if result is None:
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return "USER REJECTED: command was not executed"
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return result
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# ------------------------------------------------------------------ gemini
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def _ensure_gemini_chat():
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global _gemini_client, _gemini_chat
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if _gemini_chat is None:
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def _ensure_gemini_client():
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global _gemini_client
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if _gemini_client is None:
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from google import genai
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creds = _load_credentials()
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_gemini_client = genai.Client(api_key=creds["gemini"]["api_key"])
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_gemini_chat = _gemini_client.chats.create(model=_model)
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def _send_gemini(md_content: str, user_message: str) -> str:
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_ensure_gemini_chat()
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def _send_gemini(md_content: str, user_message: str, base_dir: str) -> str:
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global _gemini_chat
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from google import genai
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from google.genai import types
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_ensure_gemini_client()
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# Gemini chats don't support mutating tools after creation,
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# so we recreate if None (reset_session clears it).
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if _gemini_chat is None:
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_gemini_chat = _gemini_client.chats.create(
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model=_model,
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config=types.GenerateContentConfig(
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tools=[_gemini_tool_declaration()]
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)
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)
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full_message = f"<context>\n{md_content}\n</context>\n\n{user_message}"
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response = _gemini_chat.send_message(full_message)
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return response.text
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for _ in range(MAX_TOOL_ROUNDS):
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# Collect all function calls in this response
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tool_calls = [
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part.function_call
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for candidate in response.candidates
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for part in candidate.content.parts
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if part.function_call is not None
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]
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if not tool_calls:
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break
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# Execute each tool call and collect results
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function_responses = []
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for fc in tool_calls:
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if fc.name == TOOL_NAME:
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script = fc.args.get("script", "")
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output = _run_script(script, base_dir)
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function_responses.append(
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types.Part.from_function_response(
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name=TOOL_NAME,
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response={"output": output}
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)
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)
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if not function_responses:
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break
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response = _gemini_chat.send_message(function_responses)
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# Extract text from final response
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text_parts = [
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part.text
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for candidate in response.candidates
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for part in candidate.content.parts
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if hasattr(part, "text") and part.text
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]
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return "\n".join(text_parts)
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# ------------------------------------------------------------------ anthropic
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@@ -86,25 +211,65 @@ def _ensure_anthropic_client():
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creds = _load_credentials()
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_anthropic_client = anthropic.Anthropic(api_key=creds["anthropic"]["api_key"])
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def _send_anthropic(md_content: str, user_message: str) -> str:
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def _send_anthropic(md_content: str, user_message: str, base_dir: str) -> str:
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global _anthropic_history
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import anthropic
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_ensure_anthropic_client()
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full_message = f"<context>\n{md_content}\n</context>\n\n{user_message}"
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_anthropic_history.append({"role": "user", "content": full_message})
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response = _anthropic_client.messages.create(
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model=_model,
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max_tokens=8096,
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messages=_anthropic_history
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)
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reply = response.content[0].text
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_anthropic_history.append({"role": "assistant", "content": reply})
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return reply
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for _ in range(MAX_TOOL_ROUNDS):
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response = _anthropic_client.messages.create(
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model=_model,
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max_tokens=8096,
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tools=_ANTHROPIC_TOOLS,
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messages=_anthropic_history
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)
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# Always record the assistant turn
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_anthropic_history.append({
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"role": "assistant",
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"content": response.content
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})
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if response.stop_reason != "tool_use":
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break
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# Process tool calls
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tool_results = []
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for block in response.content:
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if block.type == "tool_use" and block.name == TOOL_NAME:
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script = block.input.get("script", "")
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output = _run_script(script, base_dir)
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tool_results.append({
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"type": "tool_result",
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"tool_use_id": block.id,
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"content": output
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})
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if not tool_results:
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break
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_anthropic_history.append({
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"role": "user",
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"content": tool_results
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})
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# Extract final text
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text_parts = [
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block.text
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for block in response.content
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if hasattr(block, "text") and block.text
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]
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return "\n".join(text_parts)
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# ------------------------------------------------------------------ unified send
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def send(md_content: str, user_message: str) -> str:
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def send(md_content: str, user_message: str, base_dir: str = ".") -> str:
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if _provider == "gemini":
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return _send_gemini(md_content, user_message)
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return _send_gemini(md_content, user_message, base_dir)
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elif _provider == "anthropic":
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return _send_anthropic(md_content, user_message)
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raise ValueError(f"unknown provider: {_provider}")
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return _send_anthropic(md_content, user_message, base_dir)
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raise ValueError(f"unknown provider: {_provider}")
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14
config.toml
14
config.toml
@@ -5,13 +5,13 @@ output_dir = "./md_gen"
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[files]
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base_dir = "C:/projects/manual_slop"
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paths = [
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"config.toml",
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"ai_client.py",
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"aggregate.py",
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"gemini.py",
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"gui.py",
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"pyproject.toml",
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"MainContext.md"
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"config.toml",
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"ai_client.py",
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"aggregate.py",
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"gemini.py",
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"gui.py",
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"pyproject.toml",
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"MainContext.md",
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]
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[screenshots]
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236
gui.py
236
gui.py
@@ -1,4 +1,3 @@
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# gui.py
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import dearpygui.dearpygui as dpg
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import tomllib
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import tomli_w
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@@ -7,30 +6,108 @@ from pathlib import Path
|
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from tkinter import filedialog, Tk
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import aggregate
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import ai_client
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import shell_runner
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CONFIG_PATH = Path("config.toml")
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PROVIDERS = ["gemini", "anthropic"]
|
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|
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|
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def load_config() -> dict:
|
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with open(CONFIG_PATH, "rb") as f:
|
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return tomllib.load(f)
|
||||
|
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def save_config(config: dict):
|
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with open(CONFIG_PATH, "wb") as f:
|
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tomli_w.dump(config, f)
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|
||||
def hide_tk_root() -> Tk:
|
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root = Tk()
|
||||
root.withdraw()
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root.wm_attributes("-topmost", True)
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return root
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||||
|
||||
|
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class ConfirmDialog:
|
||||
"""
|
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Modal confirmation window for a proposed PowerShell script.
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Background thread calls wait(), which blocks on a threading.Event.
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Main render loop detects _pending_dialog and calls show() on the next frame.
|
||||
User clicks Approve or Reject, which sets the event and unblocks the thread.
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"""
|
||||
|
||||
_next_id = 0
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||||
|
||||
def __init__(self, script: str, base_dir: str):
|
||||
ConfirmDialog._next_id += 1
|
||||
self._uid = ConfirmDialog._next_id
|
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self._tag = f"confirm_dlg_{self._uid}"
|
||||
self._script = script
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||||
self._base_dir = base_dir
|
||||
self._event = threading.Event()
|
||||
self._approved = False
|
||||
|
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def show(self):
|
||||
"""Called from main thread only."""
|
||||
w, h = 700, 440
|
||||
vp_w = dpg.get_viewport_width()
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||||
vp_h = dpg.get_viewport_height()
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||||
px = max(0, (vp_w - w) // 2)
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||||
py = max(0, (vp_h - h) // 2)
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||||
|
||||
with dpg.window(
|
||||
label=f"Approve PowerShell Command #{self._uid}",
|
||||
tag=self._tag,
|
||||
modal=True,
|
||||
no_close=True,
|
||||
pos=(px, py),
|
||||
width=w,
|
||||
height=h,
|
||||
):
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||||
dpg.add_text("The AI wants to run the following PowerShell script:")
|
||||
dpg.add_text(f"base_dir: {self._base_dir}", color=(200, 200, 100))
|
||||
dpg.add_separator()
|
||||
dpg.add_input_text(
|
||||
tag=f"{self._tag}_script",
|
||||
default_value=self._script,
|
||||
multiline=True,
|
||||
width=-1,
|
||||
height=-72,
|
||||
readonly=False,
|
||||
)
|
||||
dpg.add_separator()
|
||||
with dpg.group(horizontal=True):
|
||||
dpg.add_button(label="Approve & Run", callback=self._cb_approve)
|
||||
dpg.add_button(label="Reject", callback=self._cb_reject)
|
||||
|
||||
def _cb_approve(self):
|
||||
self._script = dpg.get_value(f"{self._tag}_script")
|
||||
self._approved = True
|
||||
self._event.set()
|
||||
dpg.delete_item(self._tag)
|
||||
|
||||
def _cb_reject(self):
|
||||
self._approved = False
|
||||
self._event.set()
|
||||
dpg.delete_item(self._tag)
|
||||
|
||||
def wait(self) -> tuple[bool, str]:
|
||||
"""Called from background thread. Blocks until user acts."""
|
||||
self._event.wait()
|
||||
return self._approved, self._script
|
||||
|
||||
|
||||
class App:
|
||||
def __init__(self):
|
||||
self.config = load_config()
|
||||
self.files: list[str] = list(self.config["files"].get("paths", []))
|
||||
self.screenshots: list[str] = list(self.config.get("screenshots", {}).get("paths", []))
|
||||
self.history: list[str] = list(self.config.get("discussion", {}).get("history", []))
|
||||
self.screenshots: list[str] = list(
|
||||
self.config.get("screenshots", {}).get("paths", [])
|
||||
)
|
||||
self.history: list[str] = list(
|
||||
self.config.get("discussion", {}).get("history", [])
|
||||
)
|
||||
|
||||
ai_cfg = self.config.get("ai", {})
|
||||
self.current_provider: str = ai_cfg.get("provider", "gemini")
|
||||
@@ -44,9 +121,63 @@ class App:
|
||||
self.send_thread: threading.Thread | None = None
|
||||
self.models_thread: threading.Thread | None = None
|
||||
|
||||
ai_client.set_provider(self.current_provider, self.current_model)
|
||||
self._pending_dialog: ConfirmDialog | None = None
|
||||
self._pending_dialog_lock = threading.Lock()
|
||||
|
||||
# ------------------------------------------------------------------ helpers
|
||||
self._tool_log: list[tuple[str, str]] = []
|
||||
|
||||
ai_client.set_provider(self.current_provider, self.current_model)
|
||||
ai_client.confirm_and_run_callback = self._confirm_and_run
|
||||
|
||||
# ---------------------------------------------------------------- tool execution
|
||||
|
||||
def _confirm_and_run(self, script: str, base_dir: str) -> str | None:
|
||||
dialog = ConfirmDialog(script, base_dir)
|
||||
|
||||
with self._pending_dialog_lock:
|
||||
self._pending_dialog = dialog
|
||||
|
||||
approved, final_script = dialog.wait()
|
||||
|
||||
if not approved:
|
||||
self._append_tool_log(final_script, "REJECTED by user")
|
||||
return None
|
||||
|
||||
self._update_status("running powershell...")
|
||||
output = shell_runner.run_powershell(final_script, base_dir)
|
||||
self._append_tool_log(final_script, output)
|
||||
self._update_status("powershell done, awaiting AI...")
|
||||
return output
|
||||
|
||||
def _append_tool_log(self, script: str, result: str):
|
||||
self._tool_log.append((script, result))
|
||||
self._rebuild_tool_log()
|
||||
|
||||
def _rebuild_tool_log(self):
|
||||
if not dpg.does_item_exist("tool_log_scroll"):
|
||||
return
|
||||
dpg.delete_item("tool_log_scroll", children_only=True)
|
||||
for i, (script, result) in enumerate(self._tool_log, 1):
|
||||
with dpg.group(parent="tool_log_scroll"):
|
||||
dpg.add_text(f"Call #{i}", color=(140, 200, 255))
|
||||
dpg.add_input_text(
|
||||
default_value=script,
|
||||
multiline=True,
|
||||
readonly=True,
|
||||
width=-1,
|
||||
height=72,
|
||||
)
|
||||
dpg.add_text("Result:", color=(180, 255, 180))
|
||||
dpg.add_input_text(
|
||||
default_value=result,
|
||||
multiline=True,
|
||||
readonly=True,
|
||||
width=-1,
|
||||
height=72,
|
||||
)
|
||||
dpg.add_separator()
|
||||
|
||||
# ---------------------------------------------------------------- helpers
|
||||
|
||||
def _flush_to_config(self):
|
||||
self.config["output"]["namespace"] = dpg.get_value("namespace")
|
||||
@@ -62,7 +193,7 @@ class App:
|
||||
self.config["discussion"] = {"history": self.history}
|
||||
self.config["ai"] = {
|
||||
"provider": self.current_provider,
|
||||
"model": self.current_model
|
||||
"model": self.current_model,
|
||||
}
|
||||
|
||||
def _do_generate(self) -> tuple[str, Path]:
|
||||
@@ -87,9 +218,7 @@ class App:
|
||||
for i, f in enumerate(self.files):
|
||||
with dpg.group(horizontal=True, parent="files_scroll"):
|
||||
dpg.add_button(
|
||||
label="x",
|
||||
width=24,
|
||||
callback=self._make_remove_file_cb(i)
|
||||
label="x", width=24, callback=self._make_remove_file_cb(i)
|
||||
)
|
||||
dpg.add_text(f)
|
||||
|
||||
@@ -100,9 +229,7 @@ class App:
|
||||
for i, s in enumerate(self.screenshots):
|
||||
with dpg.group(horizontal=True, parent="shots_scroll"):
|
||||
dpg.add_button(
|
||||
label="x",
|
||||
width=24,
|
||||
callback=self._make_remove_shot_cb(i)
|
||||
label="x", width=24, callback=self._make_remove_shot_cb(i)
|
||||
)
|
||||
dpg.add_text(s)
|
||||
|
||||
@@ -133,6 +260,7 @@ class App:
|
||||
|
||||
def _fetch_models(self, provider: str):
|
||||
self._update_status("fetching models...")
|
||||
|
||||
def do_fetch():
|
||||
try:
|
||||
models = ai_client.list_models(provider)
|
||||
@@ -141,6 +269,7 @@ class App:
|
||||
self._update_status(f"models loaded: {len(models)}")
|
||||
except Exception as e:
|
||||
self._update_status(f"model fetch error: {e}")
|
||||
|
||||
self.models_thread = threading.Thread(target=do_fetch, daemon=True)
|
||||
self.models_thread.start()
|
||||
|
||||
@@ -193,7 +322,10 @@ class App:
|
||||
root = hide_tk_root()
|
||||
paths = filedialog.askopenfilenames(
|
||||
title="Select Screenshots",
|
||||
filetypes=[("Images", "*.png *.jpg *.jpeg *.gif *.bmp *.webp"), ("All", "*.*")]
|
||||
filetypes=[
|
||||
("Images", "*.png *.jpg *.jpeg *.gif *.bmp *.webp"),
|
||||
("All", "*.*"),
|
||||
],
|
||||
)
|
||||
root.destroy()
|
||||
for p in paths:
|
||||
@@ -224,6 +356,8 @@ class App:
|
||||
|
||||
def cb_reset_session(self):
|
||||
ai_client.reset_session()
|
||||
self._tool_log.clear()
|
||||
self._rebuild_tool_log()
|
||||
self._update_status("session reset")
|
||||
self._update_response("")
|
||||
|
||||
@@ -237,12 +371,14 @@ class App:
|
||||
except Exception as e:
|
||||
self._update_status(f"generate error: {e}")
|
||||
return
|
||||
|
||||
self._update_status("sending...")
|
||||
user_msg = dpg.get_value("ai_input")
|
||||
base_dir = dpg.get_value("files_base_dir")
|
||||
|
||||
def do_send():
|
||||
try:
|
||||
response = ai_client.send(self.last_md, user_msg)
|
||||
response = ai_client.send(self.last_md, user_msg, base_dir)
|
||||
self._update_response(response)
|
||||
self._update_status("done")
|
||||
except Exception as e:
|
||||
@@ -270,6 +406,10 @@ class App:
|
||||
def cb_fetch_models(self):
|
||||
self._fetch_models(self.current_provider)
|
||||
|
||||
def cb_clear_tool_log(self):
|
||||
self._tool_log.clear()
|
||||
self._rebuild_tool_log()
|
||||
|
||||
# ---------------------------------------------------------------- build ui
|
||||
|
||||
def _build_ui(self):
|
||||
@@ -280,19 +420,19 @@ class App:
|
||||
pos=(8, 8),
|
||||
width=400,
|
||||
height=200,
|
||||
no_close=True
|
||||
no_close=True,
|
||||
):
|
||||
dpg.add_text("Namespace")
|
||||
dpg.add_input_text(
|
||||
tag="namespace",
|
||||
default_value=self.config["output"]["namespace"],
|
||||
width=-1
|
||||
width=-1,
|
||||
)
|
||||
dpg.add_text("Output Dir")
|
||||
dpg.add_input_text(
|
||||
tag="output_dir",
|
||||
default_value=self.config["output"]["output_dir"],
|
||||
width=-1
|
||||
width=-1,
|
||||
)
|
||||
with dpg.group(horizontal=True):
|
||||
dpg.add_button(label="Browse Output Dir", callback=self.cb_browse_output)
|
||||
@@ -304,16 +444,18 @@ class App:
|
||||
pos=(8, 216),
|
||||
width=400,
|
||||
height=500,
|
||||
no_close=True
|
||||
no_close=True,
|
||||
):
|
||||
dpg.add_text("Base Dir")
|
||||
with dpg.group(horizontal=True):
|
||||
dpg.add_input_text(
|
||||
tag="files_base_dir",
|
||||
default_value=self.config["files"]["base_dir"],
|
||||
width=-220
|
||||
width=-220,
|
||||
)
|
||||
dpg.add_button(
|
||||
label="Browse##filesbase", callback=self.cb_browse_files_base
|
||||
)
|
||||
dpg.add_button(label="Browse##filesbase", callback=self.cb_browse_files_base)
|
||||
dpg.add_separator()
|
||||
dpg.add_text("Paths")
|
||||
with dpg.child_window(tag="files_scroll", height=-64, border=True):
|
||||
@@ -330,16 +472,18 @@ class App:
|
||||
pos=(416, 8),
|
||||
width=400,
|
||||
height=500,
|
||||
no_close=True
|
||||
no_close=True,
|
||||
):
|
||||
dpg.add_text("Base Dir")
|
||||
with dpg.group(horizontal=True):
|
||||
dpg.add_input_text(
|
||||
tag="shots_base_dir",
|
||||
default_value=self.config.get("screenshots", {}).get("base_dir", "."),
|
||||
width=-220
|
||||
width=-220,
|
||||
)
|
||||
dpg.add_button(
|
||||
label="Browse##shotsbase", callback=self.cb_browse_shots_base
|
||||
)
|
||||
dpg.add_button(label="Browse##shotsbase", callback=self.cb_browse_shots_base)
|
||||
dpg.add_separator()
|
||||
dpg.add_text("Paths")
|
||||
with dpg.child_window(tag="shots_scroll", height=-48, border=True):
|
||||
@@ -354,14 +498,14 @@ class App:
|
||||
pos=(824, 8),
|
||||
width=400,
|
||||
height=500,
|
||||
no_close=True
|
||||
no_close=True,
|
||||
):
|
||||
dpg.add_input_text(
|
||||
tag="discussion_box",
|
||||
default_value="\n---\n".join(self.history),
|
||||
multiline=True,
|
||||
width=-1,
|
||||
height=-64
|
||||
height=-64,
|
||||
)
|
||||
dpg.add_separator()
|
||||
with dpg.group(horizontal=True):
|
||||
@@ -375,7 +519,7 @@ class App:
|
||||
pos=(1232, 8),
|
||||
width=420,
|
||||
height=280,
|
||||
no_close=True
|
||||
no_close=True,
|
||||
):
|
||||
dpg.add_text("Provider")
|
||||
dpg.add_combo(
|
||||
@@ -383,7 +527,7 @@ class App:
|
||||
items=PROVIDERS,
|
||||
default_value=self.current_provider,
|
||||
width=-1,
|
||||
callback=self.cb_provider_changed
|
||||
callback=self.cb_provider_changed,
|
||||
)
|
||||
dpg.add_separator()
|
||||
with dpg.group(horizontal=True):
|
||||
@@ -395,7 +539,7 @@ class App:
|
||||
default_value=self.current_model,
|
||||
width=-1,
|
||||
num_items=6,
|
||||
callback=self.cb_model_changed
|
||||
callback=self.cb_model_changed,
|
||||
)
|
||||
dpg.add_separator()
|
||||
dpg.add_text("Status: idle", tag="ai_status")
|
||||
@@ -406,13 +550,13 @@ class App:
|
||||
pos=(1232, 296),
|
||||
width=420,
|
||||
height=280,
|
||||
no_close=True
|
||||
no_close=True,
|
||||
):
|
||||
dpg.add_input_text(
|
||||
tag="ai_input",
|
||||
multiline=True,
|
||||
width=-1,
|
||||
height=-64
|
||||
height=-64,
|
||||
)
|
||||
dpg.add_separator()
|
||||
with dpg.group(horizontal=True):
|
||||
@@ -425,21 +569,36 @@ class App:
|
||||
tag="win_response",
|
||||
pos=(1232, 584),
|
||||
width=420,
|
||||
height=400,
|
||||
no_close=True
|
||||
height=300,
|
||||
no_close=True,
|
||||
):
|
||||
dpg.add_input_text(
|
||||
tag="ai_response",
|
||||
multiline=True,
|
||||
readonly=True,
|
||||
width=-1,
|
||||
height=-1
|
||||
height=-1,
|
||||
)
|
||||
|
||||
with dpg.window(
|
||||
label="Tool Calls",
|
||||
tag="win_tool_log",
|
||||
pos=(1232, 892),
|
||||
width=420,
|
||||
height=300,
|
||||
no_close=True,
|
||||
):
|
||||
with dpg.group(horizontal=True):
|
||||
dpg.add_text("Tool call history")
|
||||
dpg.add_button(label="Clear", callback=self.cb_clear_tool_log)
|
||||
dpg.add_separator()
|
||||
with dpg.child_window(tag="tool_log_scroll", height=-1, border=False):
|
||||
pass
|
||||
|
||||
def run(self):
|
||||
dpg.create_context()
|
||||
dpg.configure_app(docking=True, docking_space=True)
|
||||
dpg.create_viewport(title="manual slop", width=1600, height=900)
|
||||
dpg.create_viewport(title="manual slop", width=1680, height=1200)
|
||||
dpg.setup_dearpygui()
|
||||
dpg.show_viewport()
|
||||
dpg.maximize_viewport()
|
||||
@@ -447,6 +606,13 @@ class App:
|
||||
self._fetch_models(self.current_provider)
|
||||
|
||||
while dpg.is_dearpygui_running():
|
||||
# Show any pending confirmation dialog on the main thread
|
||||
with self._pending_dialog_lock:
|
||||
dialog = self._pending_dialog
|
||||
self._pending_dialog = None
|
||||
if dialog is not None:
|
||||
dialog.show()
|
||||
|
||||
dpg.render_dearpygui_frame()
|
||||
|
||||
dpg.destroy_context()
|
||||
@@ -458,4 +624,4 @@ def main():
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
main()
|
||||
36
shell_runner.py
Normal file
36
shell_runner.py
Normal file
@@ -0,0 +1,36 @@
|
||||
import subprocess
|
||||
import shlex
|
||||
from pathlib import Path
|
||||
|
||||
TIMEOUT_SECONDS = 60
|
||||
|
||||
def run_powershell(script: str, base_dir: str) -> str:
|
||||
"""
|
||||
Run a PowerShell script with working directory set to base_dir.
|
||||
Returns a string combining stdout, stderr, and exit code.
|
||||
Raises nothing - all errors are captured into the return string.
|
||||
"""
|
||||
# Prepend Set-Location so the AI doesn't need to worry about cwd
|
||||
full_script = f"Set-Location -LiteralPath '{base_dir}'\n{script}"
|
||||
|
||||
try:
|
||||
result = subprocess.run(
|
||||
["powershell", "-NoProfile", "-NonInteractive", "-Command", full_script],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=TIMEOUT_SECONDS,
|
||||
cwd=base_dir
|
||||
)
|
||||
parts = []
|
||||
if result.stdout.strip():
|
||||
parts.append(f"STDOUT:\n{result.stdout.strip()}")
|
||||
if result.stderr.strip():
|
||||
parts.append(f"STDERR:\n{result.stderr.strip()}")
|
||||
parts.append(f"EXIT CODE: {result.returncode}")
|
||||
return "\n".join(parts) if parts else f"EXIT CODE: {result.returncode}"
|
||||
except subprocess.TimeoutExpired:
|
||||
return f"ERROR: command timed out after {TIMEOUT_SECONDS}s"
|
||||
except FileNotFoundError:
|
||||
return "ERROR: powershell executable not found"
|
||||
except Exception as e:
|
||||
return f"ERROR: {e}"
|
||||
Reference in New Issue
Block a user