3d3bd3c9f9
Files sent as m.file Matrix messages are now downloaded, MIME-detected, and forwarded to LLM providers alongside the conversation context, similar to how m.image is already handled. - OpenAI provider: sends files inline as base64 data URLs - Anthropic provider: skips files with a warning (library limitation) - OpenAI-compat provider: skips files with a warning (library limitation) Controller routing respects the existing prefix requirement setting. MIME detection expanded to cover PDF, text, code, and document formats. Docs updated to reflect file support and known limitations. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
51 lines
1.7 KiB
Rust
51 lines
1.7 KiB
Rust
use anthropic::types::{
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ContentBlock, ImageSource, Message, MessagesRequest, MessagesRequestBuilder, Role,
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};
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use crate::conversation::llm::{
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Author as LLMAuthor, Message as LLMMessage, MessageContent as LLMMessageContent,
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};
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pub(super) fn create_anthropic_message_request(llm_messages: Vec<LLMMessage>) -> MessagesRequest {
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let mut messages = vec![];
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for message in llm_messages {
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let role = match message.author {
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LLMAuthor::User => Role::User,
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LLMAuthor::Assistant => Role::Assistant,
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LLMAuthor::Prompt => {
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continue;
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}
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};
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let content = match &message.content {
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LLMMessageContent::Text(text) => vec![ContentBlock::Text { text: text.clone() }],
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LLMMessageContent::Image(image_details) => {
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vec![ContentBlock::Image {
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source: ImageSource::Base64 {
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media_type: image_details.mime.to_string(),
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data: crate::utils::base64::base64_encode(&image_details.data),
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},
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}]
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}
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LLMMessageContent::File(file_details) => {
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tracing::warn!(
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"The Anthropic provider's library does not support file/document content. This file message ({}) will be skipped.",
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file_details.filename(),
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);
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continue;
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}
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};
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let message = Message { role, content };
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messages.push(message);
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}
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MessagesRequestBuilder::default()
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.messages(messages)
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.stream(false)
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.build()
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.expect("Failed to build messages request")
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}
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