| --- |
| title: Template Final Assignment |
| emoji: 🕵🏻♂️ |
| colorFrom: indigo |
| colorTo: indigo |
| sdk: gradio |
| sdk_version: 5.25.2 |
| app_file: app.py |
| pinned: false |
| hf_oauth: true |
| |
| hf_oauth_expiration_minutes: 480 |
| --- |
| |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |
|
|
| ## 🚀 Quick Start |
|
|
| 1. Clone the repository: |
| ```bash |
| git clone https://huggingface.co/spaces/Lucas-C-R/Agents |
| cd Agents |
| ``` |
|
|
| 2. Create and activate a virtual environment: |
| - Linux: |
| ```bash |
| python3 -m venv .venv |
| source .venv/bin/activate |
| ``` |
|
|
| - Windows: |
| ```bash |
| python -m venv .venv |
| .venv\Scripts\activate |
| ``` |
|
|
| 1. Install dependencies: |
| ```bash |
| pip install -r requirements.txt |
| ``` |
|
|
| 1. Configure environment variables: |
| ```bash |
| # API Keys |
| export OPENAI_API_KEY="sk-proj-..." # Your OpenAI API key |
| export TAVILY_API_KEY="tvly-dev-..." # Your Tavily API key |
| export GROQ_API_KEY="gsk_..." # Your Groq API key |
| export HF_TOKEN="hf_..." # Your Hugging Face token |
| |
| # Space Configuration |
| export SPACE_ID="<your user>/<space name>" # Your Hugging Face space ID |
| |
| # Supabase Configuration |
| export SUPABASE_URL="your_supabase_url" # Your Supabase project URL |
| export SUPABASE_KEY="your_supabase_key" # Your Supabase API key |
| ``` |
|
|
| 5. Run the application: |
| ```bash |
| python app.py |
| ``` |
|
|
| ## 🔧 Detailed Configuration |
|
|
| ### 1. Supabase Setup |
|
|
| 1. Create an organization on [Supabase](https://supabase.com/) |
| 2. Create a new project |
| 3. Set up a password and select the nearest region |
| 4. In the "Project Overview" tab, locate the "Project API" section |
| 5. Copy the Project URL to the `SUPABASE_URL` environment variable |
| 6. Copy the API Key to the `SUPABASE_KEY` environment variable |
|
|
| ### 2. Database Configuration |
|
|
| Execute the following SQL in the Supabase SQL editor: |
|
|
| ```sql |
| create extension if not exists vector; |
| create table if not exists documents ( |
| id uuid primary key default gen_random_uuid(), |
| content text, |
| metadata jsonb, |
| embedding vector(768) |
| ); |
| |
| DROP FUNCTION IF EXISTS match_documents_langchain(vector, integer); |
| |
| create or replace function match_documents_langchain( |
| query_embedding vector(768), |
| match_count int default 5 |
| ) |
| returns table ( |
| id uuid, |
| content text, |
| metadata jsonb, |
| similarity float |
| ) |
| as $$ |
| begin |
| return query |
| select |
| documents.id, |
| documents.content, |
| documents.metadata, |
| 1 - (documents.embedding <=> query_embedding) as similarity |
| from documents |
| order by documents.embedding <=> query_embedding |
| limit match_count; |
| end; |
| $$ language plpgsql; |
| ``` |
|
|
| ### 3. Data Import |
|
|
| 1. Access the "Table Editor" tab in Supabase |
| 2. Select the "documents" table |
| 3. Click on "Import data from CSV" |
| 4. Select the `supabase_docs.csv` file from the project directory |
| 5. Click "Import data" and wait for completion |
|
|
| ## 📝 License |
|
|
| This project is under the MIT License. See the LICENSE file for more details. |
