| import os |
| import requests |
| import gradio as gr |
| from llama_cpp import Llama |
| from PyPDF2 import PdfReader |
| from sentence_transformers import SentenceTransformer |
| from sklearn.metrics.pairwise import cosine_similarity |
|
|
| |
| |
| |
| MODEL_URL = "https://huggingface.co/melsonop/mistral-chat-pdf/resolve/main/mistral-7b-instruct-v0.1.Q4_K_M.gguf" |
| MODEL_PATH = "mistral.gguf" |
|
|
| if not os.path.exists(MODEL_PATH): |
| print("🔄 Downloading Mistral model...") |
| with requests.get(MODEL_URL, stream=True) as r: |
| r.raise_for_status() |
| with open(MODEL_PATH, 'wb') as f: |
| for chunk in r.iter_content(chunk_size=8192): |
| f.write(chunk) |
| print("✅ Model downloaded successfully!") |
|
|
| llm = Llama( |
| model_path=MODEL_PATH, |
| n_ctx=2048, |
| n_threads=4, |
| n_batch=512, |
| verbose=False |
| ) |
|
|
| embed_model = SentenceTransformer("all-MiniLM-L6-v2") |
|
|
| |
| |
| |
| docs = [] |
| doc_embeddings = [] |
|
|
| def load_pdf(file): |
| global docs, doc_embeddings |
| if file is None: |
| return "❌ Please upload a valid PDF file." |
| |
| reader = PdfReader(file) |
| text = "" |
| for page in reader.pages: |
| text += page.extract_text() + "\n" |
|
|
| docs = text.split(". ") |
| doc_embeddings = embed_model.encode(docs) |
| return "✅ PDF loaded! You can now ask questions." |
|
|
| def chat_with_pdf(question): |
| if not docs: |
| return "❌ No PDF loaded yet. Please upload and load a PDF first." |
|
|
| question_embedding = embed_model.encode([question]) |
| similarities = cosine_similarity(question_embedding, doc_embeddings)[0] |
| top_indices = similarities.argsort()[-3:][::-1] |
| context = "\n".join([docs[i] for i in top_indices]) |
|
|
| prompt = f"""You are a helpful assistant. Use the context below to answer the question.\n\nContext:\n{context}\n\nQuestion: {question}\nAnswer:""" |
|
|
| output = llm(prompt=prompt, max_tokens=512, temperature=0.7) |
| return output['choices'][0]['text'].strip() |
|
|
| |
| |
| |
|
|
| with gr.Blocks() as demo: |
| gr.Markdown("# 🤖 Chat with Your PDF using Mistral 7B (GGUF)") |
| |
| pdf = gr.File(label="Upload PDF", file_types=[".pdf"]) |
| load_output = gr.Textbox(label="Status", interactive=False) |
| load_button = gr.Button("🔄 Load PDF") |
|
|
| question = gr.Textbox(label="Ask a Question") |
| answer = gr.Textbox(label="Answer") |
|
|
| load_button.click(load_pdf, inputs=[pdf], outputs=[load_output]) |
| question.submit(chat_with_pdf, inputs=[question], outputs=[answer]) |
|
|
| demo.launch() |
|
|
