tgpt

Routes user queries to free AI providers (Phind, Isou, KoboldAI) without requiring API keys by implementing a provider abstraction pattern that handles authentication, endpoint routing, and response parsing for each provider independently. The architecture maintains a provider registry in main.go (lines 66-80) that maps provider names to their respective HTTP clients and response handlers, enabling seamless switching between free and paid providers without code changes.

Maintains conversation history across multiple interactions using a ThreadID-based context management system that stores previous messages in the Params structure (PrevMessages field). The interactive mode (-i/--interactive) implements a command-line REPL that preserves conversation state between user inputs, enabling the AI to reference earlier messages and maintain coherent multi-turn dialogue without manual context injection.

Implements a provider registry pattern where each provider (Phind, Isou, KoboldAI, OpenAI, Gemini, etc.) is registered with its own HTTP client and response handler. The architecture uses a provider abstraction layer that decouples provider-specific logic from the core CLI, enabling new providers to be added by implementing a standard interface. The implementation in main.go (lines 66-80) shows how providers are mapped to their handlers, and each provider handles authentication, request formatting, and response parsing independently.

Supports local AI model inference via Ollama, a self-hosted model runner that allows users to run open-source models (Llama, Mistral, etc.) on their own hardware. The implementation treats Ollama as a provider in the registry, routing requests to a local Ollama instance via HTTP API. This enables offline operation and full data privacy, as all inference happens locally without sending data to external providers.

Supports configuration through multiple channels: command-line flags (e.g., -p/--provider, -k/--api-key), environment variables (AI_PROVIDER, AI_API_KEY), and configuration files (tgpt.json). The system implements a precedence hierarchy where CLI flags override environment variables, which override config file settings. This enables flexible configuration for different use cases (single invocation, session-wide, or persistent).

Supports HTTP/HTTPS proxy configuration via environment variables (HTTP_PROXY, HTTPS_PROXY) or configuration files, enabling tgpt to route requests through corporate proxies or VPNs. The system integrates proxy settings into the HTTP client initialization, allowing transparent proxy support without code changes. This is essential for users in restricted network environments.

Generates executable shell commands from natural language descriptions using the -s/--shell flag, which routes requests through a specialized handler that formats prompts to produce shell-safe output. The implementation includes a preprompt mechanism that instructs the AI to generate only valid shell syntax, and the output is presented to the user for review before execution, providing a safety checkpoint against malicious or incorrect command generation.

Generates code snippets in response to natural language requests using the -c/--code flag, which applies syntax highlighting to the output based on detected language. The implementation uses a preprompt mechanism to instruct the AI to generate code with language markers, and the output handler parses these markers to apply terminal-compatible syntax highlighting via ANSI color codes, making generated code immediately readable and copyable.

Generates images from text descriptions using the -img/--image flag, routing requests to configurable image generation providers (Pollinations by default, Arta as alternative). The ImageParams structure encapsulates image-specific parameters (ImgRatio, ImgNegativePrompt, ImgCount, Width, Height, Out) and the implementation handles provider-specific API differences, allowing users to switch image providers via configuration without code changes. Generated images are saved to disk with customizable output paths.

Accepts input from stdin via shell pipes, allowing users to pass file contents, command output, or other data as context for AI queries. The implementation reads from stdin when no direct arguments are provided, enabling patterns like `cat file.txt | tgpt 'explain this code'` or `git diff | tgpt 'summarize changes'`. This integrates tgpt into Unix pipelines, making it composable with existing command-line tools.

Provides flexible output formatting through multiple flags: streaming output by default (showing response as it arrives), quiet mode (-q/--quiet) for suppressing loading animations, and whole text mode (-w/--whole) for buffering the complete response before display. The implementation uses a conditional output handler that either streams chunks as they arrive from the provider or buffers the entire response, allowing users to choose between real-time feedback and clean final output based on their use case.

Distributes pre-compiled binaries for multiple platforms (Linux, macOS, Windows, FreeBSD) via package managers (Arch Linux, FreeBSD, Scoop, Chocolatey) and direct download scripts. The implementation includes a self-update mechanism (-u/--update flag) that checks for new versions and updates the binary in-place, eliminating the need for manual version management. The version is tracked in version.txt and compared against remote releases.

Supports configuration through multiple layers: environment variables (AI_PROVIDER, AI_API_KEY) for default settings, command-line flags for per-execution overrides, and configuration files for persistent settings. The implementation reads environment variables first, then applies CLI flag overrides, allowing users to set defaults globally while maintaining flexibility for individual commands. Proxy configuration is also supported via environment variables or configuration files.

Exposes provider-specific parameters (Temperature, Top_p, Max_length) through the Params structure, allowing users to fine-tune AI model behavior. The implementation passes these parameters directly to the provider's API, enabling control over response randomness (temperature), diversity (top_p), and length (max_length). Different providers may support different subsets of these parameters, and the implementation handles provider-specific variations.