mirror of https://github.com/Shubhamsaboo/awesome-llm-apps.git synced 2026-03-09 07:25:00 -05:00

Files

Raoul Scalise 3a85fa8924 Ambrogio: Code improvements

Modified files:
- llm_apps_with_memory_tutorials/ai_arxiv_agent_memory/ai_arxiv_agent_memory.py
- advanced_tools_frameworks/cursor_ai_experiments/multi_agent_researcher.py
- advanced_tools_frameworks/local_llama3.1_tool_use/llama3_tool_use.py
- rag_tutorials/rag_chain/app.py
- rag_tutorials/hybrid_search_rag/main.py

2025-02-13 21:59:11 +01:00

app.py

Ambrogio: Code improvements

2025-02-13 21:59:11 +01:00

README.md

Updated streamlit UI

2025-01-14 20:28:18 +05:30

requirements.txt

rag_chain added to rag_tutorials

2025-01-13 19:35:36 +05:30

README.md

PharmaQuery

Overview

PharmaQuery is an advanced Pharmaceutical Insight Retrieval System designed to help users gain meaningful insights from research papers and documents in the pharmaceutical domain.

Demo

https://github.com/user-attachments/assets/c12ee305-86fe-4f71-9219-57c7f438f291

Features

Natural Language Querying: Ask complex questions about the pharmaceutical industry and get concise, accurate answers.
Custom Database: Upload your own research documents to enhance the retrieval system's knowledge base.
Similarity Search: Retrieves the most relevant documents for your query using AI embeddings.
Streamlit Interface: User-friendly interface for queries and document uploads.

Technologies Used

Programming Language: Python 3.10+
Framework: LangChain
Database: ChromaDB
Models:
- Embeddings: Google Gemini API (embedding-001)
- Chat: Google Gemini API (gemini-1.5-pro)
PDF Processing: PyPDFLoader
Document Splitter: SentenceTransformersTokenTextSplitter

Requirements

Install Dependencies:
```
pip install -r requirements.txt
```
Run the Application:
```
streamlit run app.py
```
Use the Application:
- Paste your Google API Key in the sidebar.
- Enter your query in the main interface.
- Optionally, upload research papers in the sidebar to enhance the database.

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