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cargo clippy (#660)
This commit is contained in:
Adil Hafeez
GitHub
parent
c75e7606f9
commit
ca95ffb63d
62 changed files with 1864 additions and 1187 deletions
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@ -38,7 +38,7 @@ impl TryFrom<AnthropicMessagesRequest> for ChatCompletionsRequest {
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}
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// Convert tools and tool choice
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let openai_tools = req.tools.map(|tools| convert_anthropic_tools(tools));
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let openai_tools = req.tools.map(convert_anthropic_tools);
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let (openai_tool_choice, parallel_tool_calls) =
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convert_anthropic_tool_choice(req.tool_choice);
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@ -218,18 +218,18 @@ impl TryFrom<MessagesMessage> for Vec<Message> {
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}
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// Role Conversions
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impl Into<Role> for MessagesRole {
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fn into(self) -> Role {
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match self {
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impl From<MessagesRole> for Role {
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fn from(val: MessagesRole) -> Self {
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match val {
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MessagesRole::User => Role::User,
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MessagesRole::Assistant => Role::Assistant,
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}
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}
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}
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impl Into<MessagesStopReason> for FinishReason {
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fn into(self) -> MessagesStopReason {
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match self {
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impl From<FinishReason> for MessagesStopReason {
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fn from(val: FinishReason) -> Self {
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match val {
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FinishReason::Stop => MessagesStopReason::EndTurn,
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FinishReason::Length => MessagesStopReason::MaxTokens,
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FinishReason::ToolCalls => MessagesStopReason::ToolUse,
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@ -239,11 +239,11 @@ impl Into<MessagesStopReason> for FinishReason {
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}
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}
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impl Into<MessagesUsage> for Usage {
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fn into(self) -> MessagesUsage {
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impl From<Usage> for MessagesUsage {
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fn from(val: Usage) -> Self {
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MessagesUsage {
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input_tokens: self.prompt_tokens,
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output_tokens: self.completion_tokens,
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input_tokens: val.prompt_tokens,
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output_tokens: val.completion_tokens,
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cache_creation_input_tokens: None,
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cache_read_input_tokens: None,
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}
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@ -251,9 +251,9 @@ impl Into<MessagesUsage> for Usage {
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}
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// System Prompt Conversions
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impl Into<Message> for MessagesSystemPrompt {
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fn into(self) -> Message {
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let system_content = match self {
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impl From<MessagesSystemPrompt> for Message {
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fn from(val: MessagesSystemPrompt) -> Self {
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let system_content = match val {
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MessagesSystemPrompt::Single(text) => MessageContent::Text(text),
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MessagesSystemPrompt::Blocks(blocks) => MessageContent::Text(blocks.extract_text()),
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};
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@ -384,12 +384,8 @@ impl TryFrom<MessagesMessage> for BedrockMessage {
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ToolResultContent::Blocks(blocks) => {
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let mut result_blocks = Vec::new();
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for result_block in blocks {
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match result_block {
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crate::apis::anthropic::MessagesContentBlock::Text { text, .. } => {
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result_blocks.push(ToolResultContentBlock::Text { text });
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}
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// For now, skip other content types in tool results
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_ => {}
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if let crate::apis::anthropic::MessagesContentBlock::Text { text, .. } = result_block {
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result_blocks.push(ToolResultContentBlock::Text { text });
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}
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}
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result_blocks
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@ -14,7 +14,8 @@ use crate::apis::openai::{
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};
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use crate::apis::openai_responses::{
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ResponsesAPIRequest, InputContent, InputItem, InputParam, MessageRole, Modality, ReasoningEffort, Tool as ResponsesTool, ToolChoice as ResponsesToolChoice
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InputContent, InputItem, InputParam, MessageRole, Modality, ReasoningEffort,
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ResponsesAPIRequest, Tool as ResponsesTool, ToolChoice as ResponsesToolChoice,
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};
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use crate::clients::TransformError;
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use crate::transforms::lib::ExtractText;
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@ -27,9 +28,9 @@ type AnthropicMessagesRequest = MessagesRequest;
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// MAIN REQUEST TRANSFORMATIONS
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// ============================================================================
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impl Into<MessagesSystemPrompt> for Message {
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fn into(self) -> MessagesSystemPrompt {
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let system_text = match self.content {
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impl From<Message> for MessagesSystemPrompt {
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fn from(val: Message) -> Self {
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let system_text = match val.content {
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MessageContent::Text(text) => text,
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MessageContent::Parts(parts) => parts.extract_text(),
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};
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@ -163,7 +164,7 @@ impl TryFrom<Message> for BedrockMessage {
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let has_tool_calls = message
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.tool_calls
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.as_ref()
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.map_or(false, |calls| !calls.is_empty());
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.is_some_and(|calls| !calls.is_empty());
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// Add text content if it's non-empty, or if we have no tool calls (to avoid empty content)
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if !text_content.is_empty() {
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@ -252,7 +253,6 @@ impl TryFrom<ResponsesAPIRequest> for ChatCompletionsRequest {
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type Error = TransformError;
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fn try_from(req: ResponsesAPIRequest) -> Result<Self, Self::Error> {
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// Convert input to messages
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let messages = match req.input {
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InputParam::Text(text) => {
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@ -282,50 +282,27 @@ impl TryFrom<ResponsesAPIRequest> for ChatCompletionsRequest {
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// Convert each input item
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for item in items {
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match item {
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InputItem::Message(input_msg) => {
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let role = match input_msg.role {
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MessageRole::User => Role::User,
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MessageRole::Assistant => Role::Assistant,
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MessageRole::System => Role::System,
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MessageRole::Developer => Role::System, // Map developer to system
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};
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if let InputItem::Message(input_msg) = item {
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let role = match input_msg.role {
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MessageRole::User => Role::User,
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MessageRole::Assistant => Role::Assistant,
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MessageRole::System => Role::System,
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MessageRole::Developer => Role::System, // Map developer to system
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};
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// Convert content based on MessageContent type
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let content = match &input_msg.content {
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crate::apis::openai_responses::MessageContent::Text(text) => {
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// Simple text content
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MessageContent::Text(text.clone())
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}
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crate::apis::openai_responses::MessageContent::Items(content_items) => {
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// Check if it's a single text item (can use simple text format)
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if content_items.len() == 1 {
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if let InputContent::InputText { text } = &content_items[0] {
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MessageContent::Text(text.clone())
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} else {
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// Single non-text item - use parts format
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MessageContent::Parts(
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content_items.iter()
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.filter_map(|c| match c {
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InputContent::InputText { text } => {
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Some(crate::apis::openai::ContentPart::Text { text: text.clone() })
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}
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InputContent::InputImage { image_url, .. } => {
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Some(crate::apis::openai::ContentPart::ImageUrl {
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image_url: crate::apis::openai::ImageUrl {
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url: image_url.clone(),
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detail: None,
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}
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})
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}
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InputContent::InputFile { .. } => None, // Skip files for now
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InputContent::InputAudio { .. } => None, // Skip audio for now
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})
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.collect()
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)
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}
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// Convert content based on MessageContent type
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let content = match &input_msg.content {
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crate::apis::openai_responses::MessageContent::Text(text) => {
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// Simple text content
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MessageContent::Text(text.clone())
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}
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crate::apis::openai_responses::MessageContent::Items(content_items) => {
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// Check if it's a single text item (can use simple text format)
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if content_items.len() == 1 {
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if let InputContent::InputText { text } = &content_items[0] {
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MessageContent::Text(text.clone())
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} else {
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// Multiple content items - convert to parts
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// Single non-text item - use parts format
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MessageContent::Parts(
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content_items.iter()
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.filter_map(|c| match c {
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@ -346,20 +323,41 @@ impl TryFrom<ResponsesAPIRequest> for ChatCompletionsRequest {
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.collect()
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)
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}
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} else {
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// Multiple content items - convert to parts
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MessageContent::Parts(
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content_items
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.iter()
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.filter_map(|c| match c {
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InputContent::InputText { text } => {
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Some(crate::apis::openai::ContentPart::Text {
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text: text.clone(),
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})
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}
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InputContent::InputImage { image_url, .. } => Some(
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crate::apis::openai::ContentPart::ImageUrl {
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image_url: crate::apis::openai::ImageUrl {
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url: image_url.clone(),
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detail: None,
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},
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},
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),
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InputContent::InputFile { .. } => None, // Skip files for now
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InputContent::InputAudio { .. } => None, // Skip audio for now
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})
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.collect(),
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)
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}
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};
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}
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};
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converted_messages.push(Message {
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role,
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content,
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name: None,
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tool_call_id: None,
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tool_calls: None,
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});
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}
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// Skip non-message items (references, outputs) for now
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// These would need special handling in chat completions format
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_ => {}
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converted_messages.push(Message {
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role,
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content,
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name: None,
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tool_call_id: None,
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tool_calls: None,
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});
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}
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}
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@ -474,7 +472,7 @@ impl TryFrom<ChatCompletionsRequest> for AnthropicMessagesRequest {
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}
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// Convert tools and tool choice
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let anthropic_tools = req.tools.map(|tools| convert_openai_tools(tools));
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let anthropic_tools = req.tools.map(convert_openai_tools);
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let anthropic_tool_choice =
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convert_openai_tool_choice(req.tool_choice, req.parallel_tool_calls);
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