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use crate::gemini::generate_content::response::GeminiGenerateContentResponse;
use crate::openai::compact_response::response::OpenAiCompactResponse;
use crate::openai::compact_response::response::{
OpenAiCompactedResponseObject, ResponseBody as CompactResponseBody,
};
use crate::openai::compact_response::types as cpt;
use crate::openai::count_tokens::types as ot;
use crate::transform::openai::generate_content::openai_chat_completions::gemini::utils::{
gemini_function_response_to_text, json_object_to_string, prompt_feedback_refusal_text,
};
use crate::transform::openai::generate_content::openai_response::gemini::utils::{
gemini_citation_annotations, gemini_logprobs,
};
use crate::transform::openai::model_list::gemini::utils::openai_error_response_from_gemini;
use crate::transform::utils::TransformError;
impl TryFrom<GeminiGenerateContentResponse> for OpenAiCompactResponse {
type Error = TransformError;
fn try_from(value: GeminiGenerateContentResponse) -> Result<Self, TransformError> {
Ok(match value {
GeminiGenerateContentResponse::Success {
stats_code,
headers,
body,
} => {
let response_id = body.response_id.unwrap_or_else(|| "compact".to_string());
let prompt_feedback = body.prompt_feedback;
let mut output = Vec::new();
for (candidate_index, candidate) in
body.candidates.unwrap_or_default().into_iter().enumerate()
{
let mut message_content = Vec::new();
if let Some(content) = candidate.content.clone() {
for part in content.parts {
if let Some(text) = part.text
&& !text.is_empty()
{
message_content.push(
cpt::CompactedResponseMessageContent::OutputText(
ot::ResponseOutputText {
annotations: gemini_citation_annotations(
candidate.citation_metadata.as_ref(),
),
logprobs: gemini_logprobs(
candidate.logprobs_result.as_ref(),
),
text,
type_: ot::ResponseOutputTextType::OutputText,
},
),
);
}
if let Some(function_call) = part.function_call {
output.push(cpt::CompactedResponseOutputItem::FunctionToolCall(
ot::ResponseFunctionToolCall {
arguments: function_call
.args
.as_ref()
.map(json_object_to_string)
.unwrap_or_else(|| "{}".to_string()),
call_id: function_call.id.unwrap_or_else(|| {
format!(
"{}_candidate_{}_tool_call",
response_id, candidate_index
)
}),
name: function_call.name,
type_: ot::ResponseFunctionToolCallType::FunctionCall,
id: None,
status: Some(ot::ResponseItemStatus::Completed),
},
));
}
if let Some(function_response) = part.function_response {
output.push(cpt::CompactedResponseOutputItem::FunctionCallOutput(
ot::ResponseFunctionCallOutput {
call_id: function_response
.id
.clone()
.unwrap_or_else(|| function_response.name.clone()),
output: ot::ResponseFunctionCallOutputContent::Text(
gemini_function_response_to_text(function_response),
),
type_:
ot::ResponseFunctionCallOutputType::FunctionCallOutput,
id: None,
status: Some(ot::ResponseItemStatus::Completed),
},
));
}
if let Some(inline_data) = part.inline_data {
message_content.push(
cpt::CompactedResponseMessageContent::OutputText(
ot::ResponseOutputText {
annotations: Vec::new(),
logprobs: None,
text: format!(
"data:{};base64,{}",
inline_data.mime_type, inline_data.data
),
type_: ot::ResponseOutputTextType::OutputText,
},
),
);
}
if let Some(file_data) = part.file_data {
message_content.push(
cpt::CompactedResponseMessageContent::OutputText(
ot::ResponseOutputText {
annotations: Vec::new(),
logprobs: None,
text: file_data.file_uri,
type_: ot::ResponseOutputTextType::OutputText,
},
),
);
}
if let Some(executable_code) = part.executable_code {
message_content.push(
cpt::CompactedResponseMessageContent::OutputText(
ot::ResponseOutputText {
annotations: Vec::new(),
logprobs: None,
text: executable_code.code,
type_: ot::ResponseOutputTextType::OutputText,
},
),
);
}
if let Some(code_execution_result) = part.code_execution_result
&& let Some(output_text) = code_execution_result.output
&& !output_text.is_empty()
{
message_content.push(
cpt::CompactedResponseMessageContent::OutputText(
ot::ResponseOutputText {
annotations: Vec::new(),
logprobs: None,
text: output_text,
type_: ot::ResponseOutputTextType::OutputText,
},
),
);
}
}
}
if message_content.is_empty()
&& let Some(finish_message) = candidate.finish_message
&& !finish_message.is_empty()
{
message_content.push(cpt::CompactedResponseMessageContent::OutputText(
ot::ResponseOutputText {
annotations: Vec::new(),
logprobs: None,
text: finish_message,
type_: ot::ResponseOutputTextType::OutputText,
},
));
}
if !message_content.is_empty() {
let status = match candidate.finish_reason.as_ref() {
Some(
crate::gemini::generate_content::types::GeminiFinishReason::MaxTokens
| crate::gemini::generate_content::types::GeminiFinishReason::Safety
| crate::gemini::generate_content::types::GeminiFinishReason::Recitation
| crate::gemini::generate_content::types::GeminiFinishReason::Blocklist
| crate::gemini::generate_content::types::GeminiFinishReason::ProhibitedContent
| crate::gemini::generate_content::types::GeminiFinishReason::Spii
| crate::gemini::generate_content::types::GeminiFinishReason::ImageSafety
| crate::gemini::generate_content::types::GeminiFinishReason::ImageProhibitedContent
| crate::gemini::generate_content::types::GeminiFinishReason::ImageRecitation,
) => ot::ResponseItemStatus::Incomplete,
_ => ot::ResponseItemStatus::Completed,
};
output.push(cpt::CompactedResponseOutputItem::Message(
cpt::CompactedResponseMessage {
id: format!("{}_message_{}", response_id, candidate_index),
content: message_content,
role: cpt::CompactedResponseMessageRole::Assistant,
status,
type_: cpt::CompactedResponseMessageType::Message,
},
));
}
}
if output.is_empty()
&& let Some(refusal) = prompt_feedback_refusal_text(prompt_feedback.as_ref())
{
output.push(cpt::CompactedResponseOutputItem::Message(
cpt::CompactedResponseMessage {
id: format!("{}_message_0", response_id),
content: vec![cpt::CompactedResponseMessageContent::Refusal(
ot::ResponseOutputRefusal {
refusal,
type_: ot::ResponseOutputRefusalType::Refusal,
},
)],
role: cpt::CompactedResponseMessageRole::Assistant,
status: ot::ResponseItemStatus::Incomplete,
type_: cpt::CompactedResponseMessageType::Message,
},
));
}
let usage = body
.usage_metadata
.map(|usage| {
let input_tokens = usage
.prompt_token_count
.unwrap_or(0)
.saturating_add(usage.tool_use_prompt_token_count.unwrap_or(0));
let output_tokens = usage
.candidates_token_count
.unwrap_or(0)
.saturating_add(usage.thoughts_token_count.unwrap_or(0));
cpt::ResponseUsage {
input_tokens,
input_tokens_details: cpt::ResponseInputTokensDetails {
cached_tokens: usage.cached_content_token_count.unwrap_or(0),
},
output_tokens,
output_tokens_details: cpt::ResponseOutputTokensDetails {
reasoning_tokens: usage.thoughts_token_count.unwrap_or(0),
},
total_tokens: usage
.total_token_count
.unwrap_or_else(|| input_tokens.saturating_add(output_tokens)),
}
})
.unwrap_or(cpt::ResponseUsage {
input_tokens: 0,
input_tokens_details: cpt::ResponseInputTokensDetails { cached_tokens: 0 },
output_tokens: 0,
output_tokens_details: cpt::ResponseOutputTokensDetails {
reasoning_tokens: 0,
},
total_tokens: 0,
});
OpenAiCompactResponse::Success {
stats_code,
headers: crate::openai::types::OpenAiResponseHeaders {
extra: headers.extra,
},
body: CompactResponseBody {
id: response_id,
created_at: 0,
object: OpenAiCompactedResponseObject::ResponseCompaction,
output,
usage,
},
}
}
GeminiGenerateContentResponse::Error {
stats_code,
headers,
body,
} => OpenAiCompactResponse::Error {
stats_code,
headers: crate::openai::types::OpenAiResponseHeaders {
extra: headers.extra,
},
body: openai_error_response_from_gemini(stats_code, body),
},
})
}
}