dialoghelper

A Python library for programmatic dialog manipulation in Solveit, fast.ai's Dialog Engineering web application. It provides both user-callable functions and AI-accessible tools for creating, reading, updating, and managing dialog messages.

What is Solveit?

Solveit is a "Dialog Engineering" web application that combines interactive code execution with AI assistance. Unlike ChatGPT (pure chat) or Jupyter (pure code), Solveit merges both paradigms into a single workspace.

Core Concepts

• Instance: A persistent Linux container with your files and running kernels. Each user can have multiple instances.
• Dialog: An .ipynb file containing messages. Like a Jupyter notebook, but with AI integration. Each open dialog runs its own Python kernel.
• Message: The fundamental unit—similar to a Jupyter cell, but with three types:

Type	Purpose	Example
code	Python execution	print("hello")
note	Markdown documentation	# My Notes
prompt	AI interaction	"Explain this function"

How AI Context Works

When you send a prompt to the AI:

1. All messages above the current prompt are collected
2. Messages marked as "hidden" (skipped=True) are excluded
3. If context exceeds the model limit, oldest non-pinned messages are dropped
4. The AI sees code, outputs, notes, and previous prompts/responses

Key implications:

• Working at the bottom of a dialog = more context (all messages above)
• Working higher up = less context
• Pinning a message (p key) keeps it in context even when truncation occurs

Tools: AI-Callable Functions

Solveit lets the AI call Python functions directly. Users declare tools in messages using & followed by backticks:

&`my_function`                    # Expose single tool
&`[func1, func2, func3]`          # Expose multiple tools

When the AI needs to use a tool, Solveit executes it in the kernel and returns the result.

Installation

The latest version is always pre-installed in Solveit. To manually install (not recommended):

pip install dialoghelper

What is dialoghelper?

dialoghelper is a programmatic interface to Solveit dialogs. It enables:

• Dialog manipulation: Add, update, delete, and search messages
• AI tool integration: Expose functions as tools the AI can call
• Context generation: Convert folders, repos, and symbols into AI context
• Screen capture: Capture browser screenshots for AI analysis
• Tmux integration: Read terminal buffers from tmux sessions

Modules

Module	Source Notebook	Description
core	nbs/00_core.ipynb	Core dialog manipulation (add/update/delete messages, search, context helpers)
capture	nbs/01_capture.ipynb	Screen capture functionality for AI vision
inspecttools	nbs/02_inspecttools.ipynb	Symbol inspection (symsrc, getval, getdir, etc.)
tmux	nbs/03_tmux.ipynb	Tmux buffer reading tools
stdtools	—	Re-exports all tools from dialoghelper + fastcore.tools

Solveit Tools

Tools are functions the AI can call directly during a conversation. A function is usable as a tool if it has:

1. Type annotations for ALL parameters
2. A docstring describing what it does

# Valid tool
def greet(name: str) -> str:
    "Greet someone by name"
    return f"Hello, {name}!"

# Not a tool (missing type annotation)
def greet(name):
    "Greet someone by name"
    return f"Hello, {name}!"

# Not a tool (missing docstring)
def greet(name: str) -> str: return f"Hello, {name}!"

Exposing Tools to the AI

In a Solveit dialog, reference tools using & followed by backticks:

&`greet`                           # Single tool
&`[add_msg, update_msg, del_msg]`  # Multiple tools

Tool Info Functions

These functions add notes to your dialog listing available tools:

Function	Lists tools from
tool_info()	dialoghelper.core
fc_tool_info()	fastcore.tools (rg, sed, view, create, etc.)
inspect_tool_info()	dialoghelper.inspecttools
tmux_tool_info()	dialoghelper.tmux

Tools vs Programmatic Functions

Some functions are designed for AI tool use; others are meant to be called directly from code:

AI Tools	Programmatic Use
add_msg, update_msg, del_msg
find_msgs, read_msg, view_dlg	call_endp (raw endpoint access)
symsrc, getval, getdir	resolve (returns actual Python object)

Usage Examples

from dialoghelper import *

# Add a note message
add_msg("Hello from code!", msg_type='note')

# Add a code message
add_msg("print('Hello')", msg_type='code')

# Search for messages
results = find_msgs("pattern", msg_type='code')

# View entire dialog structure
print(view_dlg())

# Generate context from a folder
ctx_folder('.', types='py', max_total=5000)

Development: nbdev Project Structure

dialoghelper is an nbdev project. Notebooks are the source of truth—the .py files are auto-generated.

Notebook ↔ Python File Mapping

Notebook	Generated File
nbs/00_core.ipynb	dialoghelper/core.py
nbs/01_capture.ipynb	dialoghelper/capture.py
nbs/02_inspecttools.ipynb	dialoghelper/inspecttools.py
nbs/03_tmux.ipynb	dialoghelper/tmux.py

Workflow

1. Edit notebooks in nbs/
2. Run nbdev_export() to generate .py files
3. Never edit .py files directly—they'll be overwritten

License

Apache 2.0