Spaces:
Running
on
T4
Running
on
T4
File size: 3,166 Bytes
947aa12 8ce4d25 947aa12 8ce4d25 947aa12 8ce4d25 947aa12 8ce4d25 be59b6e 8ce4d25 be59b6e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 |
---
title: ColPali 🤝 Vespa - Visual Retrieval
short_description: Visual Retrieval with ColPali and Vespa
emoji: 👀
colorFrom: purple
colorTo: blue
sdk: gradio
sdk_version: 4.44.0
app_file: main.py
pinned: false
license: apache-2.0
models:
- vidore/colpaligemma-3b-pt-448-base
- vidore/colpali-v1.2
preload_from_hub:
- vidore/colpaligemma-3b-pt-448-base config.json,model-00001-of-00002.safetensors,model-00002-of-00002.safetensors,model.safetensors.index.json,preprocessor_config.json,special_tokens_map.json,tokenizer.json,tokenizer_config.json 12c59eb7e23bc4c26876f7be7c17760d5d3a1ffa
- vidore/colpali-v1.2 adapter_config.json,adapter_model.safetensors,preprocessor_config.json,special_tokens_map.json,tokenizer.json,tokenizer_config.json 9912ce6f8a462d8cf2269f5606eabbd2784e764f
---
<!-- Copyright Vespa.ai. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. -->
<picture>
<source media="(prefers-color-scheme: dark)" srcset="https://assets.vespa.ai/logos/Vespa-logo-green-RGB.svg">
<source media="(prefers-color-scheme: light)" srcset="https://assets.vespa.ai/logos/Vespa-logo-dark-RGB.svg">
<img alt="#Vespa" width="200" src="https://assets.vespa.ai/logos/Vespa-logo-dark-RGB.svg" style="margin-bottom: 25px;">
</picture>
# Visual Retrieval ColPali
# Developing
First, install `uv`:
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```
Then, in this directory, run:
```bash
uv sync --extra dev
```
This will generate a virtual environment with the required dependencies at `.venv`.
To activate the virtual environment, run:
```bash
source .venv/bin/activate
```
And run development server:
```bash
python hello.py
```
## Preparation
First, set up your `.env` file by renaming `.env.example` to `.env` and filling in the required values.
(Token can be shared with 1password, `HF_TOKEN` is personal and must be created at huggingface)
If you are just connecting to a deployed Vespa app, you can skip to [Connecting to the Vespa app](#connecting-to-the-vespa-app-and-querying).
### Deploying the Vespa app
To deploy the Vespa app, run:
```bash
python deploy_vespa_app.py --tenant_name mytenant --vespa_application_name myapp --token_id_write mytokenid_write --token_id_read mytokenid_read
```
You should get an output like:
```bash
Found token endpoint: https://abcde.z.vespa-app.cloud
````
### Feeding the data
#### Dependencies
In addition to the python dependencies, you also need `poppler`
On Mac:
```bash
brew install poppler
```
First, you need to create a huggingface token, after you have accepted the term to use the model at https://huggingface.co/google/paligemma-3b-mix-448.
Add the token to your environment variables as `HF_TOKEN`:
```bash
export HF_TOKEN=yourtoken
```
To feed the data, run:
```bash
python feed_vespa.py --vespa_app_url https://myapp.z.vespa-app.cloud --vespa_cloud_secret_token mysecrettoken
```
### Connecting to the Vespa app and querying
As a first step, you can run the `query_vespa.py` script to run some sample queries against the Vespa app:
```bash
python query_vespa.py
```
### Starting the front-end
```bash
python main.py
``` |