Fixed raw urls for compose.yaml

Author: themoenen

generator/generate_docs.py

@@ -3,6 +3,8 @@
 
 Usage:
     python3 generator/generate_docs.py
+    python3 generator/generate_docs.py --update
+    python3 generator/generate_docs.py --update-after
 
 """
 
@@ -20,6 +22,10 @@
 
 
 if __name__ == "__main__":
+    args = sys.argv[1:]
+    if "--update" in args:
+        distribute()
+        sys.exit()
 
     # For openad-toolkit repo
     oad_update_readme()
@@ -34,7 +40,6 @@
     # Other files
     generate_commands_csv()
 
-    args = sys.argv[1:]
-    if "--update" in args:
+    if "--update-after" in args:
         print("\n\n\n\n")
         distribute()

generator/methods/generate_model_docs.py

@@ -1,5 +1,3 @@
-# python3 docs/generate_model_docs.py
-
 import os
 import re
 import pandas as pd
@@ -76,6 +74,10 @@ def scrape_repos():
     results = []
     for _, row in df.iterrows():
         repo_url = row["Repository"]
+        # Raw URL:                    https://github.com/acceleratedscience/<repo_name>/raw/main/<filename>
+        # Forwards to: https://raw.githubusercontent.com/acceleratedscience/<repo_name>/main/<filename>
+        # The first URL can't be downloaded using curl, so we need to use the second one
+        repo_url_raw = repo_url.replace("github.com", "raw.githubusercontent.com")
         name = row["Name"]
         try:
             # Scrape the README.md file
@@ -95,13 +97,13 @@ def scrape_repos():
             description = parse_description(readme_text, repo_name)
 
             # Check support for Docker (Dockerfile)
-            dockerfile_url = f"{repo_url}/raw/main/Dockerfile"
+            dockerfile_url = f"{repo_url_raw}/main/Dockerfile"
             dockerfile_exists = (
                 requests.get(dockerfile_url, timeout=10).status_code == 200
             )
 
             # Check support for Docker compose (compose.yaml)
-            compose_yml_url = f"{repo_url}/raw/main/compose.yaml"
+            compose_yml_url = f"{repo_url_raw}/main/compose.yaml"
             compose_exists = (
                 requests.get(compose_yml_url, timeout=10).status_code == 200
             )
@@ -124,6 +126,7 @@ def scrape_repos():
                     "title": title,
                     "repo_name": repo_name,
                     "url": repo_url,
+                    "compose_yml_url": compose_yml_url,
                     "description": description,
                     "support:docker": dockerfile_exists,
                     "support:compose": compose_exists,
@@ -228,9 +231,10 @@ def generate_md(model_data):
         repo_name = model["repo_name"]
         service_name = repo_name.replace("openad-service-", "").replace("-", "_")
         url = model["url"]
+        compose_yml_url = model["compose_yml_url"]
         btn_github = f"[:carbon-icn-github: {repo_name}]({url}){{ .md-button }}"
         btn_compose = (
-            f"[compose.yml]({url}/raw/main/compose.yaml){{ .md-button .md-button--primary download='compose.yml' }}"
+            f"[compose.yml]({compose_yml_url}){{ .md-button .md-button--primary download='compose.yml' }}"
             if model["support:compose"]
             else "--REMOVE-LINE--"
         )
@@ -250,7 +254,7 @@ def generate_md(model_data):
         docker_compose_instructions = (
             "Quick start with Docker Compose:\n"
             "```\n"
-            f"curl -O {url}/raw/main/compose.yaml\n"
+            f"curl -O {compose_yml_url}\n"
             "```\n"
             "```\n"
             f"docker compose create\n"

main/docs/model-service/available-models.md

@@ -19,7 +19,7 @@ Go to [Deploying Models](deploying-models.md) for more detailed deployment optio
 <div markdown>
 
 [:carbon-icn-github: openad-service-smi-ted](https://github.com/acceleratedscience/openad-service-smi-ted){ .md-button }
-[compose.yml](https://github.com/acceleratedscience/openad-service-smi-ted/raw/main/compose.yaml){ .md-button .md-button--primary download='compose.yml' }
+[compose.yml](https://raw.githubusercontent.com/acceleratedscience/openad-service-smi-ted/main/compose.yaml){ .md-button .md-button--primary download='compose.yml' }
 [Instructions](/docs/model-service/deploying-models/#deployment-via-container-composeyaml-recommended){ .md-button .md-button--tertiary }  
 
 This OpenAD service provides access to the **SMILES-based Transformer Encoder-Decoder** (SMILES-TED), which is an encoder-decoder model pre-trained on a curated dataset of 91 million SMILES samples sourced from PubChem, equivalent to 4 billion molecular tokens. SMI-TED supports various complex tasks, including quantum property prediction, with two main variants ( 289 M and 8 × 289 M ).
@@ -38,7 +38,7 @@ Support for:
 
 Quick start with Docker Compose:
 ```
-curl -O https://github.com/acceleratedscience/openad-service-smi-ted/raw/main/compose.yaml
+curl -O https://raw.githubusercontent.com/acceleratedscience/openad-service-smi-ted/main/compose.yaml
 ```
 ```
 docker compose create
@@ -60,7 +60,7 @@ catalog model service from remote 'http://127.0.0.1:8080' as smi_ted
 <div markdown>
 
 [:carbon-icn-github: openad-service-bmfm-sm](https://github.com/acceleratedscience/openad-service-bmfm-sm){ .md-button }
-[compose.yml](https://github.com/acceleratedscience/openad-service-bmfm-sm/raw/main/compose.yaml){ .md-button .md-button--primary download='compose.yml' }
+[compose.yml](https://raw.githubusercontent.com/acceleratedscience/openad-service-bmfm-sm/main/compose.yaml){ .md-button .md-button--primary download='compose.yml' }
 [Instructions](/docs/model-service/deploying-models/#deployment-via-container-composeyaml-recommended){ .md-button .md-button--tertiary }  
 
 This OpenAD service provides access to the **Biomedmultiview** foundation model with checkpoints for the following properties:
@@ -84,7 +84,7 @@ Support for:
 
 Quick start with Docker Compose:
 ```
-curl -O https://github.com/acceleratedscience/openad-service-bmfm-sm/raw/main/compose.yaml
+curl -O https://raw.githubusercontent.com/acceleratedscience/openad-service-bmfm-sm/main/compose.yaml
 ```
 ```
 docker compose create
@@ -106,7 +106,7 @@ catalog model service from remote 'http://127.0.0.1:8080' as bmfm_sm
 <div markdown>
 
 [:carbon-icn-github: openad-service-bmfm-pm](https://github.com/acceleratedscience/openad-service-bmfm-pm){ .md-button }
-[compose.yml](https://github.com/acceleratedscience/openad-service-bmfm-pm/raw/main/compose.yaml){ .md-button .md-button--primary download='compose.yml' }
+[compose.yml](https://raw.githubusercontent.com/acceleratedscience/openad-service-bmfm-pm/main/compose.yaml){ .md-button .md-button--primary download='compose.yml' }
 [Instructions](/docs/model-service/deploying-models/#deployment-via-container-composeyaml-recommended){ .md-button .md-button--tertiary }  
 
 This OpenAD service provides access to the **Biomedmultialignment** foundation model with checkpoints for the following properties:
@@ -126,7 +126,7 @@ Support for:
 
 Quick start with Docker Compose:
 ```
-curl -O https://github.com/acceleratedscience/openad-service-bmfm-pm/raw/main/compose.yaml
+curl -O https://raw.githubusercontent.com/acceleratedscience/openad-service-bmfm-pm/main/compose.yaml
 ```
 ```
 docker compose create
@@ -148,7 +148,7 @@ catalog model service from remote 'http://127.0.0.1:8080' as bmfm_pm
 <div markdown>
 
 [:carbon-icn-github: openad-service-reinvent4](https://github.com/acceleratedscience/openad-service-reinvent4){ .md-button }
-[compose.yml](https://github.com/acceleratedscience/openad-service-reinvent4/raw/main/compose.yaml){ .md-button .md-button--primary download='compose.yml' }
+[compose.yml](https://raw.githubusercontent.com/acceleratedscience/openad-service-reinvent4/main/compose.yaml){ .md-button .md-button--primary download='compose.yml' }
 [Instructions](/docs/model-service/deploying-models/#deployment-via-container-composeyaml-recommended){ .md-button .md-button--tertiary }  
 
 This OpenAD service provides access to the **REINVENT 4** molecular design tool, which is used for de novo design, scaffold hopping, R-group replacement, linker design, molecule optimization, and other small molecule design tasks. REINVENT uses a Reinforcement Learning (RL) algorithm to generate optimized molecules compliant with a user-defined property profile defined as a multi-component score. Transfer Learning (TL) can be used to create or pre-train a model that generates molecules closer to a set of input molecules. 
@@ -166,7 +166,7 @@ Support for:
 
 Quick start with Docker Compose:
 ```
-curl -O https://github.com/acceleratedscience/openad-service-reinvent4/raw/main/compose.yaml
+curl -O https://raw.githubusercontent.com/acceleratedscience/openad-service-reinvent4/main/compose.yaml
 ```
 ```
 docker compose create