llmchain 0.1.3

A Rust framework for large language models, inspired by LangChain
Documentation 
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// Copyright 2023 Shafish Labs.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

use anyhow::Result;

pub struct EmbeddingResult {
    // Usage
    pub prompt_tokens: u32,
    pub total_tokens: u32,

    pub embeddings: Vec<Vec<f32>>,
}

#[derive(Default, Debug)]
pub struct GenerateResult {
    // Usage
    pub prompt_tokens: u32,
    pub completion_tokens: u32,
    pub total_tokens: u32,

    pub generation: String,
}

pub struct ChatResult {
    pub role: String,
    pub content: String,
}

#[async_trait::async_trait]
pub trait LLM: Send + Sync {
    async fn embedding(&self, inputs: Vec<String>) -> Result<EmbeddingResult>;
    async fn generate(&self, input: &str) -> Result<GenerateResult>;
    async fn chat(&self, _input: Vec<String>) -> Result<Vec<ChatResult>> {
        unimplemented!("")
    }
}