botserver/src/llm/mod.rs
Rodrigo Rodriguez (Pragmatismo) 993049dcb8 feat: enforce config load errors and add dynamic LLM model handling
- Updated `BootstrapManager` to use `AppConfig::from_env().expect(...)` and `AppConfig::from_database(...).expect(...)` ensuring failures are explicit rather than silently ignored.
- Refactored error propagation in bootstrap flow to use `?` where appropriate, improving reliability of configuration loading.
- Added import of `llm_models` in `bot` module and introduced `ConfigManager` usage to fetch the LLM model identifier at runtime.
- Integrated dynamic LLM model handler selection via `llm_models::get_handler(&model)`.
- Replaced static environment variable retrieval for embedding configuration with runtime
2025-11-02 18:36:21 -03:00

226 lines
6.5 KiB
Rust

use async_trait::async_trait;
use futures::StreamExt;
use serde_json::Value;
use std::sync::Arc;
use tokio::sync::mpsc;
use crate::tools::ToolManager;
pub mod azure;
pub mod local;
pub mod anthropic;
#[async_trait]
pub trait LLMProvider: Send + Sync {
async fn generate(
&self,
prompt: &str,
config: &Value,
) -> Result<String, Box<dyn std::error::Error + Send + Sync>>;
async fn generate_stream(
&self,
prompt: &str,
config: &Value,
tx: mpsc::Sender<String>,
) -> Result<(), Box<dyn std::error::Error + Send + Sync>>;
async fn generate_with_tools(
&self,
prompt: &str,
config: &Value,
available_tools: &[String],
tool_manager: Arc<ToolManager>,
session_id: &str,
user_id: &str,
) -> Result<String, Box<dyn std::error::Error + Send + Sync>>;
async fn cancel_job(
&self,
session_id: &str,
) -> Result<(), Box<dyn std::error::Error + Send + Sync>>;
}
pub struct OpenAIClient {
client: reqwest::Client,
api_key: String,
base_url: String,
}
impl OpenAIClient {
pub fn new(api_key: String, base_url: Option<String>) -> Self {
Self {
client: reqwest::Client::new(),
api_key,
base_url: base_url.unwrap_or_else(|| "https://api.openai.com/v1".to_string()),
}
}
}
#[async_trait]
impl LLMProvider for OpenAIClient {
async fn generate(
&self,
prompt: &str,
_config: &Value,
) -> Result<String, Box<dyn std::error::Error + Send + Sync>> {
let response = self
.client
.post(&format!("{}/chat/completions", self.base_url))
.header("Authorization", format!("Bearer {}", self.api_key))
.json(&serde_json::json!({
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": prompt}],
"max_tokens": 1000
}))
.send()
.await?;
let result: Value = response.json().await?;
let raw_content = result["choices"][0]["message"]["content"]
.as_str()
.unwrap_or("");
// Define the end token we want to skip up to. Adjust the token string if needed.
let end_token = "final<|message|>";
let content = if let Some(pos) = raw_content.find(end_token) {
// Skip everything up to and including the end token.
raw_content[(pos + end_token.len())..].to_string()
} else {
// If the token is not found, return the full content.
raw_content.to_string()
};
Ok(content)
}
async fn generate_stream(
&self,
prompt: &str,
_config: &Value,
tx: mpsc::Sender<String>,
) -> Result<(), Box<dyn std::error::Error + Send + Sync>> {
let response = self
.client
.post(&format!("{}/chat/completions", self.base_url))
.header("Authorization", format!("Bearer {}", self.api_key))
.json(&serde_json::json!({
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": prompt}],
"max_tokens": 1000,
"stream": true
}))
.send()
.await?;
let mut stream = response.bytes_stream();
let mut buffer = String::new();
while let Some(chunk) = stream.next().await {
let chunk = chunk?;
let chunk_str = String::from_utf8_lossy(&chunk);
for line in chunk_str.lines() {
if line.starts_with("data: ") && !line.contains("[DONE]") {
if let Ok(data) = serde_json::from_str::<Value>(&line[6..]) {
if let Some(content) = data["choices"][0]["delta"]["content"].as_str() {
buffer.push_str(content);
let _ = tx.send(content.to_string()).await;
}
}
}
}
}
Ok(())
}
async fn generate_with_tools(
&self,
prompt: &str,
_config: &Value,
available_tools: &[String],
_tool_manager: Arc<ToolManager>,
_session_id: &str,
_user_id: &str,
) -> Result<String, Box<dyn std::error::Error + Send + Sync>> {
let tools_info = if available_tools.is_empty() {
String::new()
} else {
format!("\n\nAvailable tools: {}. You can suggest using these tools if they would help answer the user's question.", available_tools.join(", "))
};
let enhanced_prompt = format!("{}{}", prompt, tools_info);
self.generate(&enhanced_prompt, &Value::Null).await
}
async fn cancel_job(
&self,
_session_id: &str,
) -> Result<(), Box<dyn std::error::Error + Send + Sync>> {
// OpenAI doesn't support job cancellation
Ok(())
}
}
pub struct MockLLMProvider;
impl MockLLMProvider {
pub fn new() -> Self {
Self
}
}
#[async_trait]
impl LLMProvider for MockLLMProvider {
async fn generate(
&self,
prompt: &str,
_config: &Value,
) -> Result<String, Box<dyn std::error::Error + Send + Sync>> {
Ok(format!("Mock response to: {}", prompt))
}
async fn generate_stream(
&self,
prompt: &str,
_config: &Value,
tx: mpsc::Sender<String>,
) -> Result<(), Box<dyn std::error::Error + Send + Sync>> {
let response = format!("Mock stream response to: {}", prompt);
for word in response.split_whitespace() {
let _ = tx.send(format!("{} ", word)).await;
tokio::time::sleep(tokio::time::Duration::from_millis(100)).await;
}
Ok(())
}
async fn generate_with_tools(
&self,
prompt: &str,
_config: &Value,
available_tools: &[String],
_tool_manager: Arc<ToolManager>,
_session_id: &str,
_user_id: &str,
) -> Result<String, Box<dyn std::error::Error + Send + Sync>> {
let tools_list = if available_tools.is_empty() {
"no tools available".to_string()
} else {
available_tools.join(", ")
};
Ok(format!(
"Mock response with tools [{}] to: {}",
tools_list, prompt
))
}
async fn cancel_job(
&self,
_session_id: &str,
) -> Result<(), Box<dyn std::error::Error + Send + Sync>> {
// Mock implementation just logs the cancellation
Ok(())
}
}