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https://github.com/soham2002/docuchat
DocuChatv1 using Colab, Pinecone, and Hugging Face, and DocuChatv2 with Streamlit, GeminiPro, and FAISS.
https://github.com/soham2002/docuchat
faiss gemini-pro huggingface langchain-python llama2 pinecone streamlit
Last synced: 19 days ago
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DocuChatv1 using Colab, Pinecone, and Hugging Face, and DocuChatv2 with Streamlit, GeminiPro, and FAISS.
- Host: GitHub
- URL: https://github.com/soham2002/docuchat
- Owner: soham2002
- Created: 2024-09-16T13:23:38.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-09-17T13:05:22.000Z (5 months ago)
- Last Synced: 2025-01-20T13:12:37.110Z (19 days ago)
- Topics: faiss, gemini-pro, huggingface, langchain-python, llama2, pinecone, streamlit
- Language: Python
- Homepage: https://docuchat-pdf.streamlit.app/
- Size: 222 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# DocuChat
### DocuChatv1
[Click Here](https://colab.research.google.com/drive/1cefEldBlukCTfm-x_Qpg3hgwompKm1qQ?usp=sharing) to view Google Colab based implimentation of a PDF Chat Bot where the Uploaded PDF is embedded into a VectorDB (here Pinecone) and proper search query to fetch desired answers from the uploaded PDF.
### DocuChatv2
[Click Here](https://docuchat-pdf.streamlit.app/) to view the deployed DocuChat Model with GeminiPro and FAISS VectorEmbedding.
## How to run DocuChatv1?
To use the DocuChatv1 in Google Colab,follow these steps:
1. Visit the Google colab file by clicking [here](https://colab.research.google.com/drive/1cefEldBlukCTfm-x_Qpg3hgwompKm1qQ?usp=sharing)
2. Create a copy of the Colab file on your drive
3. Generate Pinecone API Key:
1. Once logged in, navigate to the API Keys section in the Pinecone dashboard.
2. Click on Create API Key and copy the generated key.
5. Create a Pinecone Index:
1. Click on Create Index.
2. Choose an index name, set the dimension (e.g., 768 for BERT-based models), and specify the metric (e.g., cosine similarity).
3. Click Create.
6. Change the Index Name to your own Index Name
```bash
pc = Pinecone(api_key=PINECONE_API_KEY)
index_name = pc.Index('ragchat') #change it to your pinecone index name
from langchain.vectorstores import Pinecone as PC
os.environ['PINECONE_API_KEY']
docs_chunks = [t.page_content for t in docs]
pinecone_index = PC.from_texts(
docs_chunks,
embeddings,
index_name='ragchat' #change it to your Pinecone Index
)
```
6. Set Up Hugging Face API
1. Create a Hugging Face Account:
2. Go to Hugging Face and sign up or log in.
7. Generate Hugging Face Acess Token:
1. Navigate to the Settings section of your Hugging Face account.
2. Under Access Tokens, create a new token and copy it.
8. Add the API Keys to Colab:
1. Add all the API Keys to the Secrets section of your Colab File
9. Run all the cells of the Colab File
## How to run DocuChatv2?
To use the DocuChatv2 in your local system,follow these steps:
1. Install the required Python packages:
```bash
pip install requirements.txt
```
2. Create a .env file:
```bash
GEMINI_API_KEY = "Enter your Gemini Api Key"
```
4. Run the DocuChatv2 by running the following code in the terminal:
```bash
streamlit run app.py
```
5. You are good to go!
