feat(scripts): add scripts to help adding new models to the gallery (#2789)

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

scripts/latest_hf.py

@@ -0,0 +1,35 @@
+## Gets latest GGUF models from HF:
+## Example:
+## local-ai run hermes-2-theta-llama-3-8b
+## OPENAI_BASE_URL="http://192.168.xx.xx:8080" python scripts/latest_hf.py   
+
+import requests
+import subprocess
+import os
+import sys
+# get current directory where the script is
+current_dir = os.path.dirname(os.path.realpath(__file__))
+
+def get_latest_model():
+    search_term = "GGUF"
+    if sys.argv[1]:
+        search_term = sys.argv[1]
+    url = "https://huggingface.co/api/models"
+    params = {"sort": "lastModified", "direction": -1, "limit": 30, "search": search_term}
+    response = requests.get(url, params=params)
+
+    if response.status_code == 200:
+        models = response.json()
+        if models:
+            for model in models:
+                print(f"Model: {model['modelId']}")
+                subprocess.run(["python", current_dir+"/model_gallery_info.py", model['modelId']])
+                
+        else:
+            print("No models found.")
+    else:
+        print(f"Failed to fetch models. Status code: {response.status_code}")
+
+
+if __name__ == "__main__":
+    get_latest_model()

scripts/model_gallery_info.py

@@ -0,0 +1,113 @@
+## This script simply help pull off some info from the HF api
+## to speed up addition of new models to the gallery.
+## It accepts as input a repo_id and returns part of the YAML data
+## Use it as:
+## OPENAI_BASE_URL="<api_url>" OPENAI_MODEL="" python .github/add_model.py mradermacher/HaloMaidRP-v1.33-15B-L3-i1-GGUF
+## Example: 
+# local-ai run hermes-2-theta-llama-3-8b
+# OPENAI_BASE_URL="http://192.168.xx.xx:8080" OPENAI_MODEL="hermes-2-theta-llama-3-8b" python scripts/model_gallery_info.py mradermacher/HaloMaidRP-v1.33-15B-L3-i1-GGUF
+
+import sys
+import os
+from openai import OpenAI
+from huggingface_hub import HfFileSystem, get_paths_info
+
+templated_yaml = """
+- !!merge <<: *llama3
+  name: "{model_name}"
+  urls:
+    - https://huggingface.co/{repo_id}
+  description: |
+    {description}
+  overrides:
+    parameters:
+      model: {file_name}
+  files:
+    - filename: {file_name}
+      sha256: {checksum}
+      uri: huggingface://{repo_id}/{file_name}
+"""
+
+client = OpenAI()
+
+model = os.environ.get("OPENAI_MODEL", "hermes-2-theta-llama-3-8b")
+
+
+def summarize(text: str) -> str:
+    chat_completion = client.chat.completions.create(
+        messages=[
+            {
+                "role": "user",
+                "content": "You are a bot which extracts the description of the LLM model from the following text. Return ONLY the description of the model, and nothing else.\n" + text,
+            },
+        ],
+        model=model,
+    )
+
+    return chat_completion.choices[0].message.content
+
+def format_description(description):
+    return '\n    '.join(description.split('\n'))
+
+# Example usage
+if __name__ == "__main__":
+    # Get repoid from argv[0]
+    repo_id = sys.argv[1]
+    token = ""  # Replace with your Hugging Face token if needed
+
+    fs = HfFileSystem()
+    all_files = fs.ls(repo_id, detail=False)
+
+    print(all_files)
+
+    # Find a file that has Q4_K in the name
+    file_path = None
+    file_name = None
+    readmeFile = None
+    for file in all_files:
+        print(f"File found: {file}")
+        if "readme" in file.lower():
+            readmeFile = file
+            print(f"Found README file: {readmeFile}")
+        if "q4_k_m" in file.lower():
+            file_path = file
+
+    
+    if file_path is None:
+        print("No file with Q4_K_M found, using the first file in the list.")
+        exit(1)    
+
+
+    # Extract file from full path (is the last element)
+    if file_path is not None:
+        file_name = file_path.split("/")[-1]
+    
+
+    model_name = repo_id.split("/")[-1]
+
+    checksum = None
+    for file in get_paths_info(repo_id, [file_name], repo_type='model'):
+        try:
+            checksum = file.lfs.sha256
+            break
+        except Exception as e:
+            print(f'Error from Hugging Face Hub: {str(e)}', file=sys.stderr)
+            sys.exit(2)
+
+    print(checksum)
+    print(file_name)
+    print(file_path)
+
+    summarized_readme = ""
+
+    if readmeFile:
+        # If there is a README file, read it
+        readme = fs.read_text(readmeFile)
+        summarized_readme = summarize(readme)
+        summarized_readme = format_description(summarized_readme)
+
+    print("Model correctly processed")
+    ## Append to the result YAML file
+    with open("result.yaml", "a") as f:
+        f.write(templated_yaml.format(model_name=model_name.lower().replace("-GGUF","").replace("-gguf",""), repo_id=repo_id, description=summarized_readme, file_name=file_name, checksum=checksum, file_path=file_path))
+