34119e5a00
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>
137 lines
3.8 KiB
Go
137 lines
3.8 KiB
Go
package main
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import (
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"context"
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"encoding/base64"
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"fmt"
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"net/http"
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"os"
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"strings"
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tea "github.com/charmbracelet/bubbletea"
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llm "gitea.stevedudenhoeffer.com/steve/go-llm/v2"
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)
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// Message types for async operations.
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// ChatResponseMsg contains the response from a chat completion.
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type ChatResponseMsg struct {
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Response llm.Response
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Err error
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}
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// ToolExecutionMsg contains results from executing tool calls, one Message
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// (RoleTool) per ToolCall, in the same order.
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type ToolExecutionMsg struct {
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Results []llm.Message
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Err error
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}
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// ImageLoadedMsg contains a loaded image.
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type ImageLoadedMsg struct {
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Image llm.Image
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Err error
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}
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// sendChatRequest sends a completion request with the current conversation,
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// returning a ChatResponseMsg tea.Msg when the provider responds.
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func sendChatRequest(model *llm.Model, messages []llm.Message, toolbox *llm.ToolBox, toolsEnabled bool, temperature *float64) tea.Cmd {
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return func() tea.Msg {
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opts := buildOpts(toolbox, toolsEnabled, temperature)
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resp, err := model.Complete(context.Background(), messages, opts...)
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return ChatResponseMsg{Response: resp, Err: err}
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}
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}
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// executeTools runs each tool call via the toolbox and returns ToolExecutionMsg
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// with one RoleTool Message per call, in the same order.
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func executeTools(toolbox *llm.ToolBox, calls []llm.ToolCall) tea.Cmd {
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return func() tea.Msg {
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ctx := context.Background()
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results, err := toolbox.ExecuteAll(ctx, calls)
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return ToolExecutionMsg{Results: results, Err: err}
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}
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}
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// buildOpts constructs RequestOptions from the current CLI state.
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func buildOpts(toolbox *llm.ToolBox, toolsEnabled bool, temperature *float64) []llm.RequestOption {
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var opts []llm.RequestOption
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if toolsEnabled && toolbox != nil && len(toolbox.AllTools()) > 0 {
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opts = append(opts, llm.WithTools(toolbox))
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}
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if temperature != nil {
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opts = append(opts, llm.WithTemperature(*temperature))
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}
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return opts
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}
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// loadImageFromPath loads an image from a file path.
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func loadImageFromPath(path string) tea.Cmd {
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return func() tea.Msg {
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path = strings.TrimSpace(path)
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path = strings.Trim(path, "\"'")
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data, err := os.ReadFile(path)
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if err != nil {
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return ImageLoadedMsg{Err: fmt.Errorf("failed to read image file: %w", err)}
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}
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contentType := http.DetectContentType(data)
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if !strings.HasPrefix(contentType, "image/") {
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return ImageLoadedMsg{Err: fmt.Errorf("file is not an image: %s", contentType)}
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}
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return ImageLoadedMsg{
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Image: llm.Image{
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Base64: base64.StdEncoding.EncodeToString(data),
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ContentType: contentType,
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},
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}
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}
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}
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// loadImageFromURL loads an image from a URL (kept as URL, not fetched).
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func loadImageFromURL(url string) tea.Cmd {
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return func() tea.Msg {
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return ImageLoadedMsg{Image: llm.Image{URL: strings.TrimSpace(url)}}
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}
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}
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// loadImageFromBase64 loads an image from base64 data (raw or data: URL).
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func loadImageFromBase64(data string) tea.Cmd {
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return func() tea.Msg {
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data = strings.TrimSpace(data)
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if strings.HasPrefix(data, "data:") {
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parts := strings.SplitN(data, ",", 2)
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if len(parts) != 2 {
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return ImageLoadedMsg{Err: fmt.Errorf("invalid data URL format")}
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}
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mediaType := strings.TrimPrefix(parts[0], "data:")
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mediaType = strings.TrimSuffix(mediaType, ";base64")
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return ImageLoadedMsg{
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Image: llm.Image{
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Base64: parts[1],
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ContentType: mediaType,
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},
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}
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}
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decoded, err := base64.StdEncoding.DecodeString(data)
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if err != nil {
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return ImageLoadedMsg{Err: fmt.Errorf("invalid base64 data: %w", err)}
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}
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contentType := http.DetectContentType(decoded)
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if !strings.HasPrefix(contentType, "image/") {
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return ImageLoadedMsg{Err: fmt.Errorf("data is not an image: %s", contentType)}
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}
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return ImageLoadedMsg{
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Image: llm.Image{
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Base64: data,
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ContentType: contentType,
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},
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}
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}
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}
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