use async_trait::async_trait;
use futures_util::Stream;
use std::pin::Pin;
use serde::Deserialize;
use serde_json::json;
use crate::schema::Message;
use crate::RunnableConfig;
use crate::core::language_models::{BaseChatModel, BaseLanguageModel, LLMResult, TokenUsage};
use crate::core::runnables::Runnable;
use crate::callbacks::{RunTree, RunType};
use crate::language_models::openai::sse::SSEParser;
use super::OllamaConfig;
pub struct OllamaChat {
config: OllamaConfig,
client: reqwest::Client,
}
impl OllamaChat {
pub fn new(model: impl Into<String>) -> Self {
Self {
config: OllamaConfig::new(model),
client: reqwest::Client::new(),
}
}
pub fn with_config(config: OllamaConfig) -> Self {
Self {
config,
client: reqwest::Client::new(),
}
}
pub fn from_env() -> Self {
Self::with_config(OllamaConfig::from_env())
}
fn message_to_openai_format(message: &Message) -> serde_json::Value {
match &message.message_type {
crate::schema::MessageType::System => json!({
"role": "system",
"content": message.content,
}),
crate::schema::MessageType::Human => json!({
"role": "user",
"content": message.content,
}),
crate::schema::MessageType::AI => json!({
"role": "assistant",
"content": message.content,
}),
crate::schema::MessageType::Tool { tool_call_id } => json!({
"role": "tool",
"tool_call_id": tool_call_id,
"content": message.content,
}),
}
}
fn build_request_body(&self, messages: Vec<Message>, stream: bool) -> serde_json::Value {
let formatted_messages: Vec<serde_json::Value> = messages
.iter()
.map(Self::message_to_openai_format)
.collect();
let mut body = json!({
"model": self.config.model,
"messages": formatted_messages,
"stream": stream,
});
if let Some(temp) = self.config.temperature {
body["temperature"] = json!(temp);
}
if let Some(max) = self.config.max_tokens {
body["max_tokens"] = json!(max);
}
if let Some(top_p) = self.config.top_p {
body["top_p"] = json!(top_p);
}
body
}
async fn chat_internal(&self, messages: Vec<Message>) -> Result<LLMResult, OllamaError> {
let url = format!("{}/chat/completions", self.config.base_url);
let body = self.build_request_body(messages, false);
let response = self.client
.post(&url)
.header("Content-Type", "application/json")
.json(&body)
.send()
.await
.map_err(|e| OllamaError::Http(e.to_string()))?;
let status = response.status();
if !status.is_success() {
let error_text = response.text().await.unwrap_or_default();
return Err(OllamaError::Api(format!("HTTP {}: {}", status, error_text)));
}
let chat_response: OllamaChatResponse = response
.json()
.await
.map_err(|e| OllamaError::Parse(e.to_string()))?;
let message = &chat_response.choices[0].message;
Ok(LLMResult {
content: message.content.clone(),
model: chat_response.model,
token_usage: chat_response.usage.map(|u| TokenUsage {
prompt_tokens: u.prompt_tokens,
completion_tokens: u.completion_tokens,
total_tokens: u.total_tokens,
}),
tool_calls: None,
})
}
async fn stream_chat_internal(
&self,
messages: Vec<Message>,
) -> Result<Pin<Box<dyn Stream<Item = Result<String, OllamaError>> + Send>>, OllamaError> {
use futures_util::StreamExt;
let url = format!("{}/chat/completions", self.config.base_url);
let body = self.build_request_body(messages, true);
let response = self.client
.post(&url)
.header("Content-Type", "application/json")
.json(&body)
.send()
.await
.map_err(|e| OllamaError::Http(e.to_string()))?;
let status = response.status();
if !status.is_success() {
let error_text = response.text().await.unwrap_or_default();
return Err(OllamaError::Api(format!("HTTP {}: {}", status, error_text)));
}
let byte_stream = response.bytes_stream();
let stream = byte_stream
.then(|chunk_result| async move {
let mut parser = SSEParser::new();
match chunk_result {
Ok(bytes) => {
let chunk_str = String::from_utf8_lossy(&bytes);
let events = parser.parse(&chunk_str);
for event in events {
if event.is_done() {
return None;
}
if let Ok(Some(chunk)) = event.parse_openai_chunk() {
if let Some(choice) = chunk.choices.first() {
if let Some(content) = &choice.delta.content {
return Some(Ok(content.clone()));
}
}
}
}
None
},
Err(e) => Some(Err(OllamaError::Http(e.to_string()))),
}
})
.filter_map(|x| async move { x });
Ok(Box::pin(stream))
}
}
#[async_trait]
impl Runnable<Vec<Message>, LLMResult> for OllamaChat {
type Error = OllamaError;
async fn invoke(
&self,
input: Vec<Message>,
config: Option<RunnableConfig>,
) -> Result<LLMResult, Self::Error> {
self.chat(input, config).await
}
async fn stream(
&self,
_input: Vec<Message>,
_config: Option<RunnableConfig>,
) -> Result<Pin<Box<dyn Stream<Item = Result<LLMResult, Self::Error>> + Send>>, Self::Error> {
unimplemented!("流式聊天尚未实现")
}
}
#[async_trait]
impl BaseLanguageModel<Vec<Message>, LLMResult> for OllamaChat {
fn model_name(&self) -> &str {
&self.config.model
}
fn get_num_tokens(&self, text: &str) -> usize {
text.len() / 4
}
fn temperature(&self) -> Option<f32> {
self.config.temperature
}
fn max_tokens(&self) -> Option<usize> {
self.config.max_tokens
}
fn with_temperature(mut self, temp: f32) -> Self {
self.config.temperature = Some(temp);
self
}
fn with_max_tokens(mut self, max: usize) -> Self {
self.config.max_tokens = Some(max);
self
}
}
#[async_trait]
impl BaseChatModel for OllamaChat {
async fn chat(
&self,
messages: Vec<Message>,
config: Option<RunnableConfig>,
) -> Result<LLMResult, Self::Error> {
let run_name = config.as_ref()
.and_then(|c| c.run_name.clone())
.unwrap_or_else(|| format!("{}:chat", self.config.model));
let mut run = RunTree::new(
run_name,
RunType::Llm,
json!({
"messages": messages.iter().map(|m| m.content.clone()).collect::<Vec<_>>(),
"model": self.config.model,
}),
);
if let Some(ref cfg) = config {
for tag in &cfg.tags {
run = run.with_tag(tag.clone());
}
for (key, value) in &cfg.metadata {
run = run.with_metadata(key.clone(), value.clone());
}
}
if let Some(ref cfg) = config {
if let Some(ref callbacks) = cfg.callbacks {
for handler in callbacks.handlers() {
handler.on_llm_start(&run, &messages).await;
}
}
}
let result = self.chat_internal(messages.clone()).await;
match result {
Ok(response) => {
run.end(json!({
"content": &response.content,
"model": &response.model,
"token_usage": &response.token_usage,
}));
if let Some(ref cfg) = config {
if let Some(ref callbacks) = cfg.callbacks {
for handler in callbacks.handlers() {
handler.on_llm_end(&run, &response.content).await;
}
}
}
Ok(response)
}
Err(e) => {
run.end_with_error(e.to_string());
if let Some(ref cfg) = config {
if let Some(ref callbacks) = cfg.callbacks {
for handler in callbacks.handlers() {
handler.on_llm_error(&run, &e.to_string()).await;
}
}
}
Err(e)
}
}
}
async fn stream_chat(
&self,
messages: Vec<Message>,
config: Option<RunnableConfig>,
) -> Result<Pin<Box<dyn Stream<Item = Result<String, Self::Error>> + Send>>, Self::Error> {
let run_name = config.as_ref()
.and_then(|c| c.run_name.clone())
.unwrap_or_else(|| format!("{}:stream", self.config.model));
let run = RunTree::new(
run_name,
RunType::Llm,
json!({
"messages": messages.len(),
"model": self.config.model,
}),
);
if let Some(ref cfg) = config {
if let Some(ref callbacks) = cfg.callbacks {
for handler in callbacks.handlers() {
handler.on_llm_start(&run, &messages).await;
}
}
}
let stream = self.stream_chat_internal(messages).await?;
let callbacks = config.and_then(|c| c.callbacks);
let stream = Box::pin(futures_util::stream::StreamExt::map(stream, move |token_result| {
if let Some(ref cbs) = callbacks {
if let Ok(ref token) = token_result {
for handler in cbs.handlers() {
let _ = handler.on_llm_new_token(&run, token);
}
}
}
token_result
}));
Ok(stream)
}
}
#[derive(Debug)]
pub enum OllamaError {
Http(String),
Api(String),
Parse(String),
}
impl std::fmt::Display for OllamaError {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
match self {
OllamaError::Http(msg) => write!(f, "HTTP error: {}", msg),
OllamaError::Api(msg) => write!(f, "API error: {}", msg),
OllamaError::Parse(msg) => write!(f, "Parse error: {}", msg),
}
}
}
impl std::error::Error for OllamaError {}
#[derive(Debug, Deserialize)]
struct OllamaChatResponse {
id: String,
object: String,
created: i64,
model: String,
choices: Vec<OllamaChoice>,
usage: Option<OllamaUsage>,
}
#[derive(Debug, Deserialize)]
struct OllamaChoice {
index: i32,
message: OllamaMessage,
finish_reason: String,
}
#[derive(Debug, Deserialize)]
struct OllamaMessage {
role: String,
content: String,
}
#[derive(Debug, Deserialize)]
struct OllamaUsage {
prompt_tokens: usize,
completion_tokens: usize,
total_tokens: usize,
}