Update README.md

README.md

@@ -1,3 +1,110 @@
----
-license: gpl-3.0
----
+---
+license: gpl-3.0
+datasets:
+- lmsys/lmsys-chat-1m
+language:
+- en
+---
+
+# V2L (Vector-to-Language) — Beta
+
+V2L is a two-stage architecture for mapping semantic embeddings into natural language.
+It consists of:
+
+1. **Semantic Mapper** — aligns source embeddings with target embedding space.
+2. **Embedding Decoder** — generates text from target-space embeddings.
+
+This repo provides **example `.pt` files** and training scripts to explore the architecture.
+All checkpoints included here are *beta examples* — lightweight, but functional.
+
+---
+
+## Project Structure
+
+* **`main.py`** — trains the **Semantic Mapper** (x-emb → y-emb) with cosine embedding loss.
+* **`decoder.py`** — trains the **Embedding Decoder** (y-emb → target text) using strict teacher forcing.
+* **`formatter.py`** — formats raw chat JSON into `(source, target)` pairs.
+* **`pre_embed.py`** — generates sentence embeddings and saves them to `chat_embeddings.pt`.
+* **`test_chat.py`** — runs an interactive CLI chatbot with the trained mapper + decoder.
+* **`test_embed.py`** — quick embedding throughput benchmark.
+* **`test_full.py`** — **end-to-end script that trains both the mapper and the decoder in a single run**.
+* **`testcuda.py`** — checks CUDA device availability.
+
+---
+
+## Workflow
+
+1. **Format dataset**
+
+   ```bash
+   python formatter.py
+   ```
+
+   Produces `chat_1turn.csv`.
+
+2. **Precompute embeddings**
+
+   ```bash
+   python pre_embed.py
+   ```
+
+   Produces `chat_embeddings.pt`.
+
+3. **Train mapper**
+
+   ```bash
+   python main.py
+   ```
+
+   Produces `semantic_mapper.pth`.
+
+4. **Train decoder**
+
+   ```bash
+   python decoder.py
+   ```
+
+   Produces `embedding_decoder.pth`.
+
+5. **Chat interactively**
+
+   ```bash
+   python test_chat.py
+   ```
+
+➡️ Alternatively, run **`test_full.py`** to train **both mapper and decoder** in one script and then test generation end-to-end.
+
+---
+
+## Checkpoints
+
+* **`semantic_mapper.pth`** — maps source embeddings into target embedding space.
+* **`embedding_decoder.pth`** — GRU-based text generator conditioned on embeddings.
+
+> All `.pt` files in this repo are example checkpoints. They do work, but are not trained to full convergence.
+
+---
+
+## Dataset Note
+
+Due to technical constraints, the dataset is **not included** in this repo.
+All scripts assume data derived from **[lmsys/lmsys-chat-1m](https://huggingface.co/datasets/lmsys/lmsys-chat-1m)**, but filtered to **English-only** and cleaned of formatting artifacts.
+
+---
+
+## Example
+
+```python
+from test_chat import chat
+chat()   # Starts interactive loop
+```
+
+Sample run:
+
+```
+User: Hi
+Bot: Hello! How are you?
+```
+
+---
+