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//! Language model implementation for the Anthropic provider.
use crate::core::capabilities::ModelName;
use crate::core::client::LanguageModelClient;
use crate::core::language_model::{
LanguageModelOptions, LanguageModelResponse, LanguageModelResponseContentType,
LanguageModelStreamChunk, ProviderStream,
};
use crate::core::messages::AssistantMessage;
use crate::core::tools::ToolDetails;
use crate::core::{LanguageModelStreamChunkType, ToolCallInfo};
use crate::extensions::Extensions;
use crate::providers::anthropic::Anthropic;
use crate::providers::anthropic::client::{
AnthropicContentBlock, AnthropicDelta, AnthropicMessageDeltaUsage, AnthropicOptions,
AnthropicStreamEvent,
};
use crate::providers::anthropic::extensions;
use crate::{core::language_model::LanguageModel, error::Result};
use async_trait::async_trait;
use futures::StreamExt;
use std::collections::HashMap;
#[async_trait]
impl<M: ModelName> LanguageModel for Anthropic<M> {
/// Returns the name of the model.
fn name(&self) -> String {
self.options.model.clone()
}
/// Generates text using the Anthropic provider.
async fn generate_text(
&mut self,
options: LanguageModelOptions,
) -> Result<LanguageModelResponse> {
let mut options: AnthropicOptions = options.into();
options.model = self.options.model.clone();
self.options = options;
let response = self.send(self.settings.base_url.clone()).await?;
let mut collected: Vec<LanguageModelResponseContentType> = Vec::new();
for out in response.content {
match out {
AnthropicContentBlock::Text { text, .. } => {
collected.push(LanguageModelResponseContentType::new(text));
}
AnthropicContentBlock::Thinking {
signature,
thinking,
} => {
let extensions = Extensions::default();
extensions
.get_mut::<extensions::AnthropicThinkingMetadata>()
.signature = Some(signature);
collected.push(LanguageModelResponseContentType::Reasoning {
content: thinking,
extensions,
});
}
AnthropicContentBlock::RedactedThinking { data } => {
collected.push(LanguageModelResponseContentType::Reasoning {
content: data,
extensions: Extensions::default(),
});
}
AnthropicContentBlock::ToolUse { id, input, name } => {
collected.push(LanguageModelResponseContentType::ToolCall(ToolCallInfo {
input,
tool: ToolDetails {
id: id.to_string(),
name: name.to_string(),
},
extensions: Extensions::default(),
}));
}
}
}
Ok(LanguageModelResponse {
contents: collected,
usage: Some(response.usage.into()),
})
}
/// Streams text using the Anthropic provider.
async fn stream_text(&mut self, options: LanguageModelOptions) -> Result<ProviderStream> {
let mut options: AnthropicOptions = options.into();
options.stream = Some(true);
options.model = self.options.model.clone();
self.options = options;
// Retry logic for rate limiting
let max_retries = 5;
let mut retry_count = 0;
let mut wait_time = std::time::Duration::from_secs(1);
let response = loop {
match self.send_and_stream(self.settings.base_url.clone()).await {
Ok(stream) => break stream,
Err(crate::error::Error::ApiError {
status_code: Some(status),
..
}) if status == reqwest::StatusCode::TOO_MANY_REQUESTS
&& retry_count < max_retries =>
{
retry_count += 1;
tokio::time::sleep(wait_time).await;
wait_time *= 2; // Exponential backoff
continue;
}
Err(e) => return Err(e),
}
};
#[derive(Default)]
struct StreamState {
content_blocks: HashMap<usize, AccumulatedBlock>,
usage: Option<AnthropicMessageDeltaUsage>,
}
#[derive(Debug)]
enum AccumulatedBlock {
Text(String),
Thinking {
thinking: String,
signature: Option<String>,
},
RedactedThinking(String),
ToolUse {
id: String,
name: String,
accumulated_json: String,
},
}
let stream = response.scan::<_, Result<Vec<LanguageModelStreamChunk>>, _, _>(
StreamState::default(),
|state, evt_res| {
let unsupported = |event: &str| {
vec![LanguageModelStreamChunk::Delta(
LanguageModelStreamChunkType::NotSupported(format!("AnthropicStreamEvent::{event}")),
)]
};
futures::future::ready({
match evt_res {
Ok(event) => match event {
AnthropicStreamEvent::MessageStart { .. } => {
Some(Ok(vec![LanguageModelStreamChunk::Delta(
LanguageModelStreamChunkType::Start,
)]))
}
AnthropicStreamEvent::ContentBlockStart {
index,
content_block,
} => match content_block {
AnthropicContentBlock::Text { .. } => {
state
.content_blocks
.insert(index, AccumulatedBlock::Text(String::new()));
Some(Ok(unsupported("ContentBlockStart::Text")))
}
AnthropicContentBlock::Thinking { .. } => {
state
.content_blocks
.insert(index, AccumulatedBlock::Thinking {
thinking: String::new(),
signature: None,
});
Some(Ok(unsupported("ContentBlockStart::Thinking")))
}
AnthropicContentBlock::RedactedThinking { data } => {
state.content_blocks.insert(
index,
AccumulatedBlock::RedactedThinking(data.clone()),
);
Some(Ok(unsupported("ContentBlockStart::RedactedThinking")))
}
AnthropicContentBlock::ToolUse { id, name, .. } => {
state.content_blocks.insert(
index,
AccumulatedBlock::ToolUse {
id,
name,
accumulated_json: String::new(),
},
);
Some(Ok(unsupported("ContentBlockStart::ToolUse")))
}
},
AnthropicStreamEvent::ContentBlockDelta { index, delta } => {
if let Some(block) = state.content_blocks.get_mut(&index) {
match (block, delta) {
(
AccumulatedBlock::Text(text),
AnthropicDelta::TextDelta { text: delta_text },
) => {
text.push_str(&delta_text);
Some(Ok(vec![LanguageModelStreamChunk::Delta(
LanguageModelStreamChunkType::Text(delta_text),
)]))
}
(
AccumulatedBlock::Thinking { thinking, .. },
AnthropicDelta::ThinkingDelta { thinking: delta_thinking },
) => {
thinking.push_str(&delta_thinking);
Some(Ok(vec![LanguageModelStreamChunk::Delta(
LanguageModelStreamChunkType::Text(delta_thinking),
)]))
}
(
AccumulatedBlock::Thinking { signature, .. },
AnthropicDelta::SignatureDelta { signature: delta_signature },
) => {
*signature = Some(delta_signature.clone());
Some(Ok(unsupported("SignatureDelta")))
}
(
AccumulatedBlock::ToolUse {
accumulated_json, ..
},
AnthropicDelta::ToolUseDelta { partial_json },
) => {
accumulated_json.push_str(&partial_json);
Some(Ok(vec![LanguageModelStreamChunk::Delta(
LanguageModelStreamChunkType::ToolCall(partial_json),
)]))
}
_ => Some(Ok(unsupported("ContentBlockDelta"))),
}
} else {
unreachable!("Anthropic accumulator must be initialized on AnthropicStreamEvent::ContentBlockStart")
}
}
AnthropicStreamEvent::ContentBlockStop { .. } => {
Some(Ok(unsupported("ContentBlockStop")))
}
AnthropicStreamEvent::MessageDelta { usage, .. } => {
state.usage = Some(usage);
Some(Ok(unsupported("MessageDelta")))
}
AnthropicStreamEvent::MessageStop => {
let mut collected = vec![];
for block in state.content_blocks.values() {
match block {
AccumulatedBlock::Text(text) => collected
.push(LanguageModelResponseContentType::new(text.clone())),
AccumulatedBlock::Thinking { thinking, signature } => {
let extensions = Extensions::default();
if let Some(sig) = signature {
extensions
.get_mut::<extensions::AnthropicThinkingMetadata>()
.signature = Some(sig.clone());
}
collected.push(LanguageModelResponseContentType::Reasoning {
content: thinking.clone(),
extensions,
})
}
AccumulatedBlock::RedactedThinking(data) => collected.push(
LanguageModelResponseContentType::Reasoning {
content: data.clone(),
extensions: Extensions::default(),
},
),
AccumulatedBlock::ToolUse {
id,
name,
accumulated_json,
} => {
let json_str = if accumulated_json.trim().is_empty() {
"{}"
} else {
accumulated_json
};
if let Ok(input) = serde_json::from_str(json_str) {
collected.push(
LanguageModelResponseContentType::ToolCall(
ToolCallInfo {
input,
tool: ToolDetails {
id: id.clone(),
name: name.clone(),
},
extensions: Extensions::default(),
},
),
);
} else {
collected.push(
LanguageModelResponseContentType::NotSupported(
format!(
"Invalid tool json: {accumulated_json}"
),
),
);
}
}
}
}
Some(Ok(collected
.into_iter()
.map(|ref c| {
LanguageModelStreamChunk::Done(AssistantMessage {
content: c.clone(),
usage: state.usage.clone().map(|usage| usage.into()),
})
})
.collect()))
}
AnthropicStreamEvent::Error { error } => {
let reason = format!("{}: {}", error.type_, error.message);
Some(Ok(vec![LanguageModelStreamChunk::Delta(
LanguageModelStreamChunkType::Failed(reason),
)]))
}
AnthropicStreamEvent::NotSupported(txt) => {
Some(Ok(vec![LanguageModelStreamChunk::Delta(
LanguageModelStreamChunkType::NotSupported(txt),
)]))
}
},
Err(e) => Some(Err(e)),
}})
},
);
Ok(Box::pin(stream))
}
}