replace links in markdown with href, remove old issue from doc

app.py

@@ -23,13 +23,13 @@ with gr.Blocks(title="RFD3 Test") as demo:
     gr.Markdown("# RFdiffusion3 for Protein Backbone generation 🧬 ")
 
     with gr.Row():
-        gr.Markdown("""When the Baker lab released the first version of [RFdiffusion](https://www.nature.com/articles/s41586-023-06415-8), they opened up new avenues for protein design. 
+        gr.Markdown("""When the Baker lab released the first version of <a href="https://www.nature.com/articles/s41586-023-06415-8" target="_blank">RFdiffusion</a>, they opened up new avenues for protein design. 
                     The model was based on the previous structure prediction architectures, yet employing the diffusion framework typical of image generation models.
                     It showed impressive results in generating protein backbones for motif scaffolding and binder design.
         
                     
                     
-                    Now in its third version, [RFD3](https://pubmed.ncbi.nlm.nih.gov/41000976/) can create binders for an extended set of targets, from DNA/RNA to small molecules, and allows advanced conditiong.
+                    Now in its third version, <a href="https://pubmed.ncbi.nlm.nih.gov/41000976/" target="_blank">RFD3</a> can create binders for an extended set of targets, from DNA/RNA to small molecules, and allows advanced conditiong.
                     This space allows you to run backbone generation jobs using Hugging Face's hardware and download the results!
                     
                     
@@ -42,25 +42,25 @@ with gr.Blocks(title="RFD3 Test") as demo:
 
     gr.Markdown("""
                 Hugging Face spaces is a great tool to build quick machine learning demos and expose interfaces for popular models. This space runs the RFD3 model with a convenient interface for input configurations and inference parameters.
-                The green `Running on ZERO` at the top of the page indicates that this space runs on Hugging Face's [ZeroGPU technology](https://huggingface.co/docs/hub/en/spaces-zerogpu). This means that all jobs are run on NVIDIA H200 GPUs and that the number of GPUs allocated to this space scale automatically based on demand.
+                The green `Running on ZERO` at the top of the page indicates that this space runs on Hugging Face's <a href="https://huggingface.co/docs/hub/en/spaces-zerogpu" target="_blank">ZeroGPU technology</a>. This means that all jobs are run on NVIDIA H200 GPUs and that the number of GPUs allocated to this space scale automatically based on demand.
                 
                 There are three steps to setting up a job.
-                - First, create an input specification for your generation job. This is a yaml or json file with details on targeted motifs, scaffolds and generation parameters that gets passed to RFD3's CLI as `inputs`. Check out [RFD3's documentation and tutorials](https://rosettacommons.github.io/foundry/models/rfd3/input.html) to learn how to compose this file!
+                - First, create an input specification for your generation job. This is a yaml or json file with details on targeted motifs, scaffolds and generation parameters that gets passed to RFD3's CLI as `inputs`. Check out <a href="https://rosettacommons.github.io/foundry/models/rfd3/input.html" target="_blank">RFD3's documentation and tutorials</a> to learn how to compose this file!
                 - Second, upload a PDB file containing your target/scaffold structure to condition the generation or leave empty for unconditional generation.
-                - Third, Select the number of batches and designs per batch for your job. These are passed as CLI arguments to RFD3. Advanced CLI arguments can be added in the "Advanced Options" section. While most of these arguments can be kept at their default value, some  related to the inference sampler can provide improvements for [protein-protein interaction (PPI) workflows](https://rosettacommons.github.io/foundry/models/rfd3/ppi_design_tutorial.html). Here is a list of other [CLI arguments](https://rosettacommons.github.io/foundry/models/rfd3/input.html#cli-arguments).
+                - Third, Select the number of batches and designs per batch for your job. These are passed as CLI arguments to RFD3. Advanced CLI arguments can be added in the "Advanced Options" section. While most of these arguments can be kept at their default value, some  related to the inference sampler can provide improvements for <a href="https://rosettacommons.github.io/foundry/models/rfd3/ppi_design_tutorial.html" target="_blank">protein-protein interaction (PPI) workflows</a>. Here is a list of other <a href="https://rosettacommons.github.io/foundry/models/rfd3/input.html#cli-arguments" target="_blank">CLI arguments</a>.
 
                 
                 Individual jobs On ZeroGPU spaces are limited to 240 seconds for PRO users or members of an organization. Hence, make sure that you are logged in before launching a job to avoid errors and keep the number of designs per run manageable.
                 While the time taken significantly depends on the configuration run, here are some numbers to guide you:
-                - RFD3's PPI tutorial, designing a 190-270 aa binder for a 149 aa motif on the [human insulin receptor](https://www.rcsb.org/structure/4ZXB)
+                - RFD3's PPI tutorial, designing a 190-270 aa binder for a 149 aa motif on the <a href="https://www.rcsb.org/structure/4ZXB" target="_blank">human insulin receptor</a>
                 generated a batch of 8 designs every 60 seconds, a batch of 16 every 95 seconds.
                 - RFD3's complex nucleic acid tutorial, scaffolding a DNA-binding motif of 8 residues into a 150 aa binder,
                 generated a batch of 8 designs every 52 seconds.
                 - RDF3's enzyme design tutorial, scaffolding the active site of drosophila's alcohol dehydrogenase into a 180-200 aa enzyme, generated a batch of 8 designs every 60 seconds.
                 
                 
-                Example files for these three tutorials can be found in the [`examples` directory of this repo](https://huggingface.co/spaces/hugging-science/RFdiffusion3/tree/main/examples). They are 
-                all taken from [RFD3's amazing Github repository.](https://github.com/RosettaCommons/foundry/tree/production/models/rfd3). This space pairs well with the [companion LigandMPNN space](https://huggingface.co/spaces/hugging-science/LigandMPNN) for inverse folding!
+                Example files for these three tutorials can be found in the <a href="https://huggingface.co/spaces/hugging-science/RFdiffusion3/tree/main/examples" target="_blank">`examples` directory of this repo</a>. They are 
+                all taken from <a href="https://github.com/RosettaCommons/foundry/tree/production/models/rfd3" target="_blank">RFD3's amazing Github repository.</a> This space pairs well with the <a href="https://huggingface.co/spaces/hugging-science/LigandMPNN" target="_blank">companion LigandMPNN space</a> for inverse folding!
 
                 """)
 

issues_doc.md

@@ -1,14 +1,4 @@
-
-# Issue 1: redownloading model weights at every restart/ code upload
-
-- I'm trying to make it so that pushing new code (editing app.py) and building again does not need to redownload the weights
-- In a space like BoltzGen, all the installation happens in requirements.txt. downloading Boltzgen downloads the weights. This means that when I push app.py code, HF detects that requirements.txt did not change, it pulls the built image from cache and there is no need for redownload
-- In my space, this is not the case, pip install rc-foundry is cached (from requirements.txt) but I need to run the command "foundry install rfd3 ligandmpnn rf3" to download the weights. I do the installation in the header of app.py. This means that the installation reruns every code push to app.py
-- I considered fixing this using Docker instead of Gradio as I could create a Docker image with the weights downloaded but Docker is not compatible with ZeroGPU, needed for the hackathon
-- I tried to use persistent storage using ./data to store the weights but persistent storage is only available at runtime not during build so I get a "Permission Denied" error.
-- This problem is annoying for development but not really once the space is done and is being used as there will be no more code pushes.
-
-# Issue 2: not able to integrate gradio_molecule3D to visualize outputs
+# Issue 1: not able to integrate gradio_molecule3D to visualize outputs
 
 - I wanted to visualize the output of RFD3 in a widget in the HF space. I got it to work on a minimal example with a custom pdb file (not using RFD3)
 - once I tried to integrate the 2, it wouldnt work because gradio_molecule3d and rc-foundry require conflicting versions of gradio: gradio_molecule3d requires <6 while rc-foundry requires 6.5.1.