Files
go-llm/v2/cmd/llm/commands.go
T
steve 34119e5a00
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CI / V2 Module (push) Successful in 2m14s
feat: add DeepSeek, Moonshot, xAI, Groq, Ollama; drop v1; migrate TUI to v2
Five OpenAI-compatible providers join the library as first-class constructors
(llm.DeepSeek, llm.Moonshot, llm.XAI, llm.Groq, llm.Ollama). Their wire-level
implementation is shared via a new v2/openaicompat package which is the
extracted guts of the old v2/openai provider; each provider supplies its own
Rules value to declare per-model constraints (e.g., DeepSeek Reasoner rejects
tools and temperature, Moonshot/xAI accept images only on *-vision* models,
Groq rejects audio input). v2/openai itself becomes a thin wrapper that sets
RestrictTemperature for o-series and gpt-5 models.

A new provider registry (v2/registry.go) exposes llm.Providers() and drives
the TUI's provider picker so adding a provider in future is a single-file
change.

The TUI at cmd/llm was migrated from v1 to v2 and moved to v2/cmd/llm. With
nothing else depending on v1, the v1 code at the repo root (all .go files,
schema/, internal/, provider/, root go.mod/go.sum) is deleted.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-24 13:34:39 +00:00

137 lines
3.8 KiB
Go

package main
import (
"context"
"encoding/base64"
"fmt"
"net/http"
"os"
"strings"
tea "github.com/charmbracelet/bubbletea"
llm "gitea.stevedudenhoeffer.com/steve/go-llm/v2"
)
// Message types for async operations.
// ChatResponseMsg contains the response from a chat completion.
type ChatResponseMsg struct {
Response llm.Response
Err error
}
// ToolExecutionMsg contains results from executing tool calls, one Message
// (RoleTool) per ToolCall, in the same order.
type ToolExecutionMsg struct {
Results []llm.Message
Err error
}
// ImageLoadedMsg contains a loaded image.
type ImageLoadedMsg struct {
Image llm.Image
Err error
}
// sendChatRequest sends a completion request with the current conversation,
// returning a ChatResponseMsg tea.Msg when the provider responds.
func sendChatRequest(model *llm.Model, messages []llm.Message, toolbox *llm.ToolBox, toolsEnabled bool, temperature *float64) tea.Cmd {
return func() tea.Msg {
opts := buildOpts(toolbox, toolsEnabled, temperature)
resp, err := model.Complete(context.Background(), messages, opts...)
return ChatResponseMsg{Response: resp, Err: err}
}
}
// executeTools runs each tool call via the toolbox and returns ToolExecutionMsg
// with one RoleTool Message per call, in the same order.
func executeTools(toolbox *llm.ToolBox, calls []llm.ToolCall) tea.Cmd {
return func() tea.Msg {
ctx := context.Background()
results, err := toolbox.ExecuteAll(ctx, calls)
return ToolExecutionMsg{Results: results, Err: err}
}
}
// buildOpts constructs RequestOptions from the current CLI state.
func buildOpts(toolbox *llm.ToolBox, toolsEnabled bool, temperature *float64) []llm.RequestOption {
var opts []llm.RequestOption
if toolsEnabled && toolbox != nil && len(toolbox.AllTools()) > 0 {
opts = append(opts, llm.WithTools(toolbox))
}
if temperature != nil {
opts = append(opts, llm.WithTemperature(*temperature))
}
return opts
}
// loadImageFromPath loads an image from a file path.
func loadImageFromPath(path string) tea.Cmd {
return func() tea.Msg {
path = strings.TrimSpace(path)
path = strings.Trim(path, "\"'")
data, err := os.ReadFile(path)
if err != nil {
return ImageLoadedMsg{Err: fmt.Errorf("failed to read image file: %w", err)}
}
contentType := http.DetectContentType(data)
if !strings.HasPrefix(contentType, "image/") {
return ImageLoadedMsg{Err: fmt.Errorf("file is not an image: %s", contentType)}
}
return ImageLoadedMsg{
Image: llm.Image{
Base64: base64.StdEncoding.EncodeToString(data),
ContentType: contentType,
},
}
}
}
// loadImageFromURL loads an image from a URL (kept as URL, not fetched).
func loadImageFromURL(url string) tea.Cmd {
return func() tea.Msg {
return ImageLoadedMsg{Image: llm.Image{URL: strings.TrimSpace(url)}}
}
}
// loadImageFromBase64 loads an image from base64 data (raw or data: URL).
func loadImageFromBase64(data string) tea.Cmd {
return func() tea.Msg {
data = strings.TrimSpace(data)
if strings.HasPrefix(data, "data:") {
parts := strings.SplitN(data, ",", 2)
if len(parts) != 2 {
return ImageLoadedMsg{Err: fmt.Errorf("invalid data URL format")}
}
mediaType := strings.TrimPrefix(parts[0], "data:")
mediaType = strings.TrimSuffix(mediaType, ";base64")
return ImageLoadedMsg{
Image: llm.Image{
Base64: parts[1],
ContentType: mediaType,
},
}
}
decoded, err := base64.StdEncoding.DecodeString(data)
if err != nil {
return ImageLoadedMsg{Err: fmt.Errorf("invalid base64 data: %w", err)}
}
contentType := http.DetectContentType(decoded)
if !strings.HasPrefix(contentType, "image/") {
return ImageLoadedMsg{Err: fmt.Errorf("data is not an image: %s", contentType)}
}
return ImageLoadedMsg{
Image: llm.Image{
Base64: data,
ContentType: contentType,
},
}
}
}