Metadata-Version: 2.4
Name: mypackage_anshita
Version: 0.1.1
Summary: A flexible chatbot package with vector embeddings and prompt handling using Ollama and FAISS
Home-page: https://github.com/yourusername/mypackage_anshita
Author: Anshita Bhatnagar
Author-email: your_email@example.com
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: ollama
Requires-Dist: faiss-cpu
Requires-Dist: numpy
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# 🧠 mypackage_anshita

`mypackage_anshita` is a Python package built with ❤️ using Ollama models. It supports:

- 💬 Prompt-based text generation using models like `gemma:2b`, `llama2`, and more
- 🔍 Vector-based document embedding + semantic search using FAISS
- ⚙️ Model flexibility for generation and embeddings
## 🚀 Installation

Install directly from PyPI:

```bash
pip install mypackage-anshita

📌 **Why this?** → Shows users how to install your package easily.

---

### ✅ 3. Features

```markdown
## 🔥 Features

- `PromptRunner` class for prompt-based responses from various models
- `DocumentEmbedder` class for embedding documents and performing vector-based search
- Uses Ollama + FAISS + NumPy
- Tested with Gemma, LLaMA2, and other local models via Ollama
## 💡 Usage Example

### Generate Text with PromptRunner

```python
from mypackage_anshita import PromptRunner

runner = PromptRunner(model='gemma:2b')
response = runner.run_prompt("What is the theory of relativity?")
print(response)
from mypackage_anshita import DocumentEmbedder

docs = ["Marie Curie won two Nobel Prizes.", "Einstein created the theory of relativity."]
embedder = DocumentEmbedder()
embedder.embed_text(docs)

results = embedder.search("radioactivity")
print(results)

📌 **Why this?** → Shows users how to *actually use* your package in code.

---

### ✅ 5. Author Info

```markdown
## 👩‍💻 Author

**Anshita Bhatnagar**  
Made with 💕 during internship  
Built using LangChain, Ollama, FAISS and Streamlit
## 📄 License

MIT License
