feat(llm): add multimodal ContentPart/Parts + per-provider serialization

Message gains an optional Parts []ContentPart alongside the existing
plain-text Content, so a turn can carry text plus image/video
attachments. Content stays the single source of truth for every
existing text-only caller (sidebar.go, memory_tools.go, etc. are
untouched); Parts only matters to a provider client when non-empty.

openai and llamacpp (both OpenAI-compatible) serialize Parts into the
standard text/image_url content-array shape; llamacpp additionally
passes video through as a best-effort video_url part, since llama.cpp
itself has no video support but the whole point of this client is the
user's own OpenAI-compatible server sitting in front of a
video-capable model — the server decides whether it understands it,
not this client. anthropic converts image parts to its base64 image
content block, and rejects a video part outright with a clear error:
the Messages API has no video block type at all, so sending one would
just produce a confusing 400 instead.

ProviderCapabilities gains SupportsVideo, true only for llamacpp.
This commit is contained in:
Victor Hugo Vargas Servin 2026-07-16 22:23:54 -07:00
parent 42a415fb7d
commit 2f6f5fab1c
5 changed files with 181 additions and 17 deletions

View file

@ -275,6 +275,7 @@ func (c *Client) Capabilities() llm.ProviderCapabilities {
return llm.ProviderCapabilities{ return llm.ProviderCapabilities{
SupportsTools: true, SupportsTools: true,
SupportsVision: true, SupportsVision: true,
SupportsVideo: false,
SupportsJSON: true, SupportsJSON: true,
MaxContextWindow: c.contextWindow, MaxContextWindow: c.contextWindow,
} }
@ -323,7 +324,29 @@ func (c *Client) buildRequest(req llm.CompletionRequest, stream bool) (io.Reader
Content: m.Content, Content: m.Content,
}) })
case llm.RoleUser: case llm.RoleUser:
appendUserBlock(anthropicContentBlock{Type: "text", Text: m.Content}) if len(m.Parts) == 0 {
appendUserBlock(anthropicContentBlock{Type: "text", Text: m.Content})
break
}
for _, p := range m.Parts {
switch p.Type {
case "text":
appendUserBlock(anthropicContentBlock{Type: "text", Text: p.Text})
case "image":
appendUserBlock(anthropicContentBlock{
Type: "image",
Source: &anthropicImageSource{
Type: "base64",
MediaType: p.MimeType,
Data: stripDataURIPrefix(p.MediaURL),
},
})
case "video":
return nil, fmt.Errorf("anthropic: video attachments are not supported by the Messages API")
default:
return nil, fmt.Errorf("anthropic: unknown content part type %q", p.Type)
}
}
case llm.RoleAssistant: case llm.RoleAssistant:
var blocks []anthropicContentBlock var blocks []anthropicContentBlock
if strings.TrimSpace(m.Content) != "" { if strings.TrimSpace(m.Content) != "" {
@ -518,13 +541,32 @@ type anthropicMessage struct {
} }
type anthropicContentBlock struct { type anthropicContentBlock struct {
Type string `json:"type"` Type string `json:"type"`
Text string `json:"text,omitempty"` Text string `json:"text,omitempty"`
ID string `json:"id,omitempty"` ID string `json:"id,omitempty"`
Name string `json:"name,omitempty"` Name string `json:"name,omitempty"`
Input json.RawMessage `json:"input,omitempty"` Input json.RawMessage `json:"input,omitempty"`
ToolUseID string `json:"tool_use_id,omitempty"` ToolUseID string `json:"tool_use_id,omitempty"`
Content string `json:"content,omitempty"` Content string `json:"content,omitempty"`
Source *anthropicImageSource `json:"source,omitempty"`
}
// anthropicImageSource is an "image" content block's base64-encoded payload.
type anthropicImageSource struct {
Type string `json:"type"` // always "base64"
MediaType string `json:"media_type"`
Data string `json:"data"`
}
// stripDataURIPrefix strips a "data:<mime>;base64," prefix from a data URI,
// leaving just the base64 payload Anthropic's image source expects. Returns
// the input unchanged if it isn't a data URI (e.g. a caller passed a raw
// base64 string directly).
func stripDataURIPrefix(mediaURL string) string {
if idx := strings.Index(mediaURL, ";base64,"); idx != -1 {
return mediaURL[idx+len(";base64,"):]
}
return mediaURL
} }
type anthropicTool struct { type anthropicTool struct {

View file

@ -322,7 +322,8 @@ func (c *Client) Name() string {
func (c *Client) Capabilities() llm.ProviderCapabilities { func (c *Client) Capabilities() llm.ProviderCapabilities {
return llm.ProviderCapabilities{ return llm.ProviderCapabilities{
SupportsTools: true, SupportsTools: true,
SupportsVision: false, SupportsVision: true,
SupportsVideo: true,
SupportsJSON: true, SupportsJSON: true,
MaxContextWindow: c.contextWindow, MaxContextWindow: c.contextWindow,
} }
@ -332,9 +333,13 @@ func (c *Client) Capabilities() llm.ProviderCapabilities {
func (c *Client) buildRequest(req llm.CompletionRequest, stream bool) (io.Reader, error) { func (c *Client) buildRequest(req llm.CompletionRequest, stream bool) (io.Reader, error) {
messages := make([]llamaMessage, len(req.Messages)) messages := make([]llamaMessage, len(req.Messages))
for i, m := range req.Messages { for i, m := range req.Messages {
content, err := buildContentValue(m)
if err != nil {
return nil, err
}
messages[i] = llamaMessage{ messages[i] = llamaMessage{
Role: string(m.Role), Role: string(m.Role),
Content: m.Content, Content: content,
ToolCallID: m.ToolCallID, ToolCallID: m.ToolCallID,
Name: m.Name, Name: m.Name,
} }
@ -477,13 +482,58 @@ type llamaStreamOptions struct {
} }
type llamaMessage struct { type llamaMessage struct {
Role string `json:"role"` Role string `json:"role"`
Content string `json:"content"` // Content is either a plain string (the common case) or a
// []llamaContentPart when the source llm.Message carried Parts - see
// buildContentValue.
Content interface{} `json:"content"`
ToolCallID string `json:"tool_call_id,omitempty"` ToolCallID string `json:"tool_call_id,omitempty"`
Name string `json:"name,omitempty"` Name string `json:"name,omitempty"`
ToolCalls []llamaToolCall `json:"tool_calls,omitempty"` ToolCalls []llamaToolCall `json:"tool_calls,omitempty"`
} }
// llamaContentPart is one block of a multipart "content" array, following
// the same OpenAI-compatible shape llama.cpp's server accepts for
// vision-capable models (e.g. Qwen2-VL via its mmproj).
type llamaContentPart struct {
Type string `json:"type"`
Text string `json:"text,omitempty"`
ImageURL *llamaMediaURL `json:"image_url,omitempty"`
VideoURL *llamaMediaURL `json:"video_url,omitempty"`
}
type llamaMediaURL struct {
URL string `json:"url"`
}
// buildContentValue converts an llm.Message's Parts into the OpenAI-style
// multipart content shape, or falls back to the plain Content string when
// there are no Parts. Unlike the openai/anthropic clients, a video part is
// passed through as a "video_url" block rather than rejected: llama.cpp
// itself has no video support, but this client's whole reason to exist is
// the user's own OpenAI-compatible server sitting in front of a
// video-capable model, so the server - not this client - is what decides
// whether it understands it.
func buildContentValue(m llm.Message) (interface{}, error) {
if len(m.Parts) == 0 {
return m.Content, nil
}
parts := make([]llamaContentPart, 0, len(m.Parts))
for _, p := range m.Parts {
switch p.Type {
case "text":
parts = append(parts, llamaContentPart{Type: "text", Text: p.Text})
case "image":
parts = append(parts, llamaContentPart{Type: "image_url", ImageURL: &llamaMediaURL{URL: p.MediaURL}})
case "video":
parts = append(parts, llamaContentPart{Type: "video_url", VideoURL: &llamaMediaURL{URL: p.MediaURL}})
default:
return nil, fmt.Errorf("llamacpp: unknown content part type %q", p.Type)
}
}
return parts, nil
}
type llamaTool struct { type llamaTool struct {
Type string `json:"type"` Type string `json:"type"`
Function json.RawMessage `json:"function"` Function json.RawMessage `json:"function"`

View file

@ -25,8 +25,11 @@ func TestClient_Capabilities(t *testing.T) {
if !caps.SupportsTools { if !caps.SupportsTools {
t.Error("expected SupportsTools to be true") t.Error("expected SupportsTools to be true")
} }
if caps.SupportsVision { if !caps.SupportsVision {
t.Error("expected SupportsVision to be false") t.Error("expected SupportsVision to be true")
}
if !caps.SupportsVideo {
t.Error("expected SupportsVideo to be true")
} }
} }

View file

@ -243,6 +243,7 @@ func (c *Client) Capabilities() llm.ProviderCapabilities {
return llm.ProviderCapabilities{ return llm.ProviderCapabilities{
SupportsTools: true, SupportsTools: true,
SupportsVision: true, SupportsVision: true,
SupportsVideo: false,
SupportsJSON: true, SupportsJSON: true,
MaxContextWindow: 128000, MaxContextWindow: 128000,
} }
@ -253,9 +254,13 @@ func (c *Client) buildRequest(req llm.CompletionRequest, stream bool) (io.Reader
// Convert messages to OpenAI format // Convert messages to OpenAI format
messages := make([]openaiMessage, len(req.Messages)) messages := make([]openaiMessage, len(req.Messages))
for i, m := range req.Messages { for i, m := range req.Messages {
content, err := buildContentValue(m)
if err != nil {
return nil, err
}
messages[i] = openaiMessage{ messages[i] = openaiMessage{
Role: string(m.Role), Role: string(m.Role),
Content: m.Content, Content: content,
ToolCallID: m.ToolCallID, ToolCallID: m.ToolCallID,
Name: m.Name, Name: m.Name,
} }
@ -378,13 +383,54 @@ type openaiStreamOptions struct {
} }
type openaiMessage struct { type openaiMessage struct {
Role string `json:"role"` Role string `json:"role"`
Content string `json:"content"` // Content is either a plain string (the common case) or a
// []openaiContentPart when the source llm.Message carried Parts - see
// buildContentValue.
Content interface{} `json:"content"`
ToolCallID string `json:"tool_call_id,omitempty"` ToolCallID string `json:"tool_call_id,omitempty"`
Name string `json:"name,omitempty"` Name string `json:"name,omitempty"`
ToolCalls []openaiToolCall `json:"tool_calls,omitempty"` ToolCalls []openaiToolCall `json:"tool_calls,omitempty"`
} }
// openaiContentPart is one block of a multipart "content" array, following
// the same shape OpenAI's vision-capable chat completions endpoint expects.
type openaiContentPart struct {
Type string `json:"type"`
Text string `json:"text,omitempty"`
ImageURL *openaiMediaURL `json:"image_url,omitempty"`
}
type openaiMediaURL struct {
URL string `json:"url"`
}
// buildContentValue converts an llm.Message's Parts into the OpenAI
// multipart content shape, or falls back to the plain Content string when
// there are no Parts - existing callers building a plain-text Message are
// completely unaffected. A video part is rejected outright: OpenAI's chat
// completions API has no video content type, so sending one would just
// produce a confusing API error instead of this clear one.
func buildContentValue(m llm.Message) (interface{}, error) {
if len(m.Parts) == 0 {
return m.Content, nil
}
parts := make([]openaiContentPart, 0, len(m.Parts))
for _, p := range m.Parts {
switch p.Type {
case "text":
parts = append(parts, openaiContentPart{Type: "text", Text: p.Text})
case "image":
parts = append(parts, openaiContentPart{Type: "image_url", ImageURL: &openaiMediaURL{URL: p.MediaURL}})
case "video":
return nil, fmt.Errorf("openai: video attachments are not supported by the chat completions API")
default:
return nil, fmt.Errorf("openai: unknown content part type %q", p.Type)
}
}
return parts, nil
}
type openaiTool struct { type openaiTool struct {
Type string `json:"type"` Type string `json:"type"`
Function json.RawMessage `json:"function"` Function json.RawMessage `json:"function"`

View file

@ -29,12 +29,35 @@ type Message struct {
// rejected by) the chat template - the model loses track of what it // rejected by) the chat template - the model loses track of what it
// already asked for and re-attempts it, or restarts from scratch. // already asked for and re-attempts it, or restarts from scratch.
ToolCalls []ToolCall `json:"tool_calls,omitempty"` ToolCalls []ToolCall `json:"tool_calls,omitempty"`
// Parts, when non-empty, carries a multimodal message (text plus
// image/video attachments) and takes precedence over Content when a
// provider client serializes the wire request. Content should still be
// set to a plain-text rendition even when Parts is used, since it's what
// storage/logging/history reconstruction read - Parts only matters for
// the live request that actually goes out to the model.
Parts []ContentPart `json:"parts,omitempty"`
}
// ContentPart is one piece of a multimodal message.
type ContentPart struct {
// Type is "text", "image", or "video".
Type string `json:"type"`
// Text is set when Type == "text".
Text string `json:"text,omitempty"`
// MediaURL is set when Type == "image"/"video": either a data URI
// (data:<mime>;base64,<...>) or an http(s) URL.
MediaURL string `json:"media_url,omitempty"`
// MimeType is the media's MIME type (e.g. "image/png"), split out
// separately from MediaURL so providers that need it apart from the data
// URI (e.g. Anthropic's base64 media_type field) don't have to re-parse it.
MimeType string `json:"mime_type,omitempty"`
} }
// ProviderCapabilities describes what a model supports. // ProviderCapabilities describes what a model supports.
type ProviderCapabilities struct { type ProviderCapabilities struct {
SupportsTools bool `json:"supports_tools"` SupportsTools bool `json:"supports_tools"`
SupportsVision bool `json:"supports_vision"` SupportsVision bool `json:"supports_vision"`
SupportsVideo bool `json:"supports_video"`
SupportsJSON bool `json:"supports_json"` SupportsJSON bool `json:"supports_json"`
MaxContextWindow int `json:"max_context_window"` MaxContextWindow int `json:"max_context_window"`
} }