BETTERVIEW

.gitignore

@@ -1,14 +1,8 @@
-.gradio/
-
-# Byte-compiled / optimized / DLL files
+# Python
 __pycache__/
 *.py[cod]
 *$py.class
-
-# C extensions
 *.so
-
-# Distribution / packaging
 .Python
 build/
 develop-eggs/
@@ -22,141 +16,70 @@ parts/
 sdist/
 var/
 wheels/
-share/python-wheels/
 *.egg-info/
 .installed.cfg
 *.egg
-MANIFEST
 
-# PyInstaller
-#  Usually these files are written by a python script from a template
-#  before PyInstaller builds the exe, so as to inject date/other infos into it.
-*.manifest
-*.spec
+# Virtual Environment
+venv/
+env/
+ENV/
+.env
+.venv
+env.bak/
+venv.bak/
+
+# IDE specific files
+.idea/
+.vscode/
+*.swp
+*.swo
+.DS_Store
+.vs/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# Gradio
+flagged/
+gradio_cached_examples/
+
+# Logs
+*.log
+logs/
+*.out
 
-# Installer logs
-pip-log.txt
-pip-delete-this-directory.txt
+# Local development settings
+.env.local
+.env.development.local
+.env.test.local
+.env.production.local
 
-# Unit test / coverage reports
+# Coverage reports
 htmlcov/
 .tox/
-.nox/
 .coverage
 .coverage.*
 .cache
 nosetests.xml
 coverage.xml
 *.cover
-*.py,cover
 .hypothesis/
-.pytest_cache/
-cover/
-
-# Translations
-*.mo
-*.pot
-
-# Django stuff:
-*.log
-local_settings.py
-db.sqlite3
-db.sqlite3-journal
-
-# Flask stuff:
-instance/
-.webassets-cache
-
-# Scrapy stuff:
-.scrapy
-
-# Sphinx documentation
-docs/_build/
-
-# PyBuilder
-.pybuilder/
-target/
-
-# Jupyter Notebook
-.ipynb_checkpoints
-
-# IPython
-profile_default/
-ipython_config.py
-
-# pyenv
-#   For a library or package, you might want to ignore these files since the code is
-#   intended to run in multiple environments; otherwise, check them in:
-# .python-version
-
-# pipenv
-#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
-#   However, in case of collaboration, if having platform-specific dependencies or dependencies
-#   having no cross-platform support, pipenv may install dependencies that don't work, or not
-#   install all needed dependencies.
-#Pipfile.lock
-
-# poetry
-#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
-#   This is especially recommended for binary packages to ensure reproducibility, and is more
-#   commonly ignored for libraries.
-#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
-#poetry.lock
-
-# pdm
-#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
-#pdm.lock
-#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
-#   in version control.
-#   https://pdm.fming.dev/#use-with-ide
-.pdm.toml
-
-# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
-__pypackages__/
 
-# Celery stuff
-celerybeat-schedule
-celerybeat.pid
-
-# SageMath parsed files
-*.sage.py
-
-# Environments
-.env
-.venv
-env/
-venv/
-ENV/
-env.bak/
-venv.bak/
-
-# Spyder project settings
-.spyderproject
-.spyproject
-
-# Rope project settings
-.ropeproject
-
-# mkdocs documentation
-/site
-
-# mypy
-.mypy_cache/
-.dmypy.json
-dmypy.json
-
-# Pyre type checker
-.pyre/
-
-# pytype static type analyzer
-.pytype/
-
-# Cython debug symbols
-cython_debug/
-
-# PyCharm
-#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
-#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
-#  and can be added to the global gitignore or merged into this file.  For a more nuclear
-#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
-#.idea/
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg

.pre-commit-config.yaml

@@ -13,13 +13,18 @@ repos:
         args: ["--fix=lf"]
       - id: requirements-txt-fixer
       - id: trailing-whitespace
-  - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.8.6
+  - repo: https://github.com/myint/docformatter
+    rev: v1.7.5
     hooks:
-      - id: ruff
-        args: ["--fix"]
+      - id: docformatter
+        args: ["--in-place"]
+  - repo: https://github.com/pycqa/isort
+    rev: 5.13.2
+    hooks:
+      - id: isort
+        args: ["--profile", "black"]
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.14.1
+    rev: v1.13.0
     hooks:
       - id: mypy
         args: ["--ignore-missing-imports"]
@@ -30,3 +35,30 @@ repos:
             "types-PyYAML",
             "types-pytz",
           ]
+  - repo: https://github.com/psf/black
+    rev: 24.10.0
+    hooks:
+      - id: black
+        language_version: python3.10
+        args: ["--line-length", "119"]
+  - repo: https://github.com/charliermarsh/ruff-pre-commit
+    rev: v0.7.4
+    hooks:
+      - id: ruff
+  - repo: https://github.com/kynan/nbstripout
+    rev: 0.8.1
+    hooks:
+      - id: nbstripout
+        args:
+          [
+            "--extra-keys",
+            "metadata.interpreter metadata.kernelspec cell.metadata.pycharm",
+          ]
+  - repo: https://github.com/nbQA-dev/nbQA
+    rev: 1.9.1
+    hooks:
+      - id: nbqa-black
+      - id: nbqa-pyupgrade
+        args: ["--py37-plus"]
+      - id: nbqa-isort
+        args: ["--float-to-top"]

.vscode/extensions.json

@@ -1,8 +0,0 @@
-{
-    "recommendations": [
-        "ms-python.python",
-        "charliermarsh.ruff",
-        "streetsidesoftware.code-spell-checker",
-        "tamasfe.even-better-toml"
-    ]
-}

.vscode/settings.json

@@ -2,15 +2,29 @@
     "editor.formatOnSave": true,
     "files.insertFinalNewline": false,
     "[python]": {
-        "editor.defaultFormatter": "charliermarsh.ruff",
+        "editor.defaultFormatter": "ms-python.black-formatter",
         "editor.formatOnType": true,
         "editor.codeActionsOnSave": {
-            "source.fixAll.ruff": "explicit"
+            "source.organizeImports": "explicit"
         }
     },
     "[jupyter]": {
         "files.insertFinalNewline": false
     },
+    "black-formatter.args": [
+        "--line-length=119"
+    ],
+    "isort.args": ["--profile", "black"],
+    "flake8.args": [
+        "--max-line-length=119"
+    ],
+    "ruff.lint.args": [
+        "--line-length=119"
+    ],
     "notebook.output.scrolling": true,
-    "notebook.formatOnSave.enabled": true
+    "notebook.formatOnCellExecution": true,
+    "notebook.formatOnSave.enabled": true,
+        "notebook.codeActionsOnSave": {
+            "source.organizeImports": "explicit"
+        }
 }

README.md

@@ -4,10 +4,10 @@ emoji: 🏢
 colorFrom: indigo
 colorTo: indigo
 sdk: gradio
-sdk_version: 5.12.0
+sdk_version: 5.7.0
 app_file: app.py
 pinned: false
 disable_embedding: true
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -1,77 +1,77 @@
-from app_lumaai import demo as demo_lumaai
+import gradio as gr
+
+from app_playai import demo as demo_playai
+from app_allenai import demo as demo_allenai
 from app_claude import demo as demo_claude
-from app_cohere import demo as demo_cohere
-from app_fal import demo as demo_fal
+from app_experimental import demo as demo_experimental
 from app_fireworks import demo as demo_fireworks
-from app_meta import demo as demo_meta
-from app_perplexity import demo as demo_perplexity
-from app_playai import demo as demo_playai
-from app_replicate import demo as demo_replicate
-from app_sambanova import demo as demo_sambanova
-from app_together import demo as demo_together
-from app_xai import demo as demo_grok
-from app_qwen import demo as demo_qwen
-from app_crew import demo as demo_crew
-from app_hyperbolic import demo as demo_hyperbolic
-from app_openai import demo as demo_openai
-from app_gemini_camera import demo as demo_gemini_camera
-from app_gemini_coder import demo as demo_gemini_coder
+from app_flux import demo as demo_flux
 from app_gemini import demo as demo_gemini
-from app_gemini_voice import demo as demo_gemini_voice
-from app_hyperbolic_coder import demo as demo_hyperbolic_coder
-from app_smolagents import demo as demo_smolagents
 from app_groq import demo as demo_groq
-from app_groq_coder import demo as demo_groq_coder
-from app_openai_coder import demo as demo_openai_coder
-from app_langchain import demo as demo_langchain
+from app_hyperbolic import demo as demo_hyperbolic
+from app_ltx_video import demo as demo_ltx_video
+from app_marco_o1 import demo as demo_marco_o1
 from app_mistral import demo as demo_mistral
-from app_minimax import demo as demo_minimax
-from app_minimax_coder import demo as demo_minimax_coder
 from app_nvidia import demo as demo_nvidia
-from app_deepseek import demo as demo_deepseek
-from utils import get_app
+from app_openai import demo as demo_openai
+from app_perplexity import demo as demo_perplexity
+from app_qwen import demo as demo_qwen
+from app_sambanova import demo as demo_sambanova
+from app_together import demo as demo_together
+from app_xai import demo as demo_grok
+
+with gr.Blocks(fill_height=True) as demo:
+    with gr.Tab("PlayAI"):
+        demo_playai.render()
+    with gr.Tab("Grok"):
+        demo_grok.render()
+    with gr.Tab("Hyperbolic"):
+        demo_hyperbolic.render()
+        gr.Markdown(
+            """
+        <div>
+            <img src="https://storage.googleapis.com/public-arena-asset/hyperbolic_logo.png" alt="Hyperbolic Logo" style="height: 50px; margin-right: 10px;">
+        </div>
 
-# Create mapping of providers to their demos
-PROVIDERS = {
-    "Gemini Coder": demo_gemini_coder,
-    "DeepSeek Coder": demo_deepseek,
-    "Minimax Coder": demo_minimax_coder,
-    "NVIDIA": demo_nvidia,
-    "Minimax": demo_minimax,
-    "Gemini Camera": demo_gemini_camera,
-    "Mistral": demo_mistral,
-    "Langchain Agent": demo_langchain,
-    "OpenAI Coder": demo_openai_coder,
-    "OpenAI": demo_openai,
-    "Gemini": demo_gemini,
-    "Gemini Voice": demo_gemini_voice,
-    "Groq Coder": demo_groq_coder,
-    "Hyperbolic Coder": demo_hyperbolic_coder,
-    "SmolAgents": demo_smolagents,
-    "Qwen": demo_qwen,
-    "Hyperbolic": demo_hyperbolic,
-    "CrewAI": demo_crew,
-    "LumaAI": demo_lumaai,
-    "Grok": demo_grok,
-    "Cohere": demo_cohere,
-    "SambaNova": demo_sambanova,
-    "Fireworks": demo_fireworks,
-    "Together": demo_together,
-    "Groq": demo_groq,
-    "Meta Llama": demo_meta,
-    "Replicate": demo_replicate,
-    "Fal": demo_fal,
-    "PlayAI": demo_playai,
-    "Claude": demo_claude,
-    "Perplexity": demo_perplexity,
-}
+        **Note:** This model is supported by Hyperbolic. Build your AI apps at [Hyperbolic](https://app.hyperbolic.xyz/).
+        """
+        )
+    with gr.Tab("Gemini"):
+        demo_gemini.render()
+    with gr.Tab("ChatGPT"):
+        demo_openai.render()
+    with gr.Tab("Claude"):
+        demo_claude.render()
+    with gr.Tab("Qwen"):
+        demo_qwen.render()
+    with gr.Tab("Allen AI"):
+        demo_allenai.render()
+    with gr.Tab("Perplexity"):
+        demo_perplexity.render()
+    with gr.Tab("Experimental"):
+        demo_experimental.render()
+    with gr.Tab("Meta Llama"):
+        demo_sambanova.render()
+        gr.Markdown(
+            "**Note:** You need to use a SambaNova API key from [SambaNova Cloud](https://cloud.sambanova.ai/)."
+        )
+    with gr.Tab("Marco-o1"):
+        demo_marco_o1.render()
+    with gr.Tab("LTX Video"):
+        demo_ltx_video.render()
+    with gr.Tab("Groq"):
+        demo_groq.render()
+    with gr.Tab("Mistral"):
+        demo_mistral.render()
+    with gr.Tab("Fireworks"):
+        demo_fireworks.render()
+    with gr.Tab("Together"):
+        demo_together.render()
+    with gr.Tab("NVIDIA"):
+        demo_nvidia.render()
+    with gr.Tab("Flux"):
+        demo_flux.render()
 
-demo = get_app(
-    models=list(PROVIDERS.keys()),
-    default_model="Gemini Coder",
-    src=PROVIDERS,
-    dropdown_label="Select Provider",
-)
 
 if __name__ == "__main__":
-    demo.queue(api_open=False).launch(show_api=False)
+    demo.queue(api_open=False).launch(ssr_mode=False, show_api=False)

app_allenai.py

@@ -1,8 +1,10 @@
-import gradio as gr
 from gradio_client import Client
+import gradio as gr
 
-MODELS = {"OLMo-2-1124-13B-Instruct": "akhaliq/olmo-anychat", "Llama-3.1-Tulu-3-8B": "akhaliq/allen-test"}
-
+MODELS = {
+    "OLMo-2-1124-13B-Instruct": "akhaliq/olmo-anychat",
+    "Llama-3.1-Tulu-3-8B": "akhaliq/allen-test"
+}
 
 def create_chat_fn(client):
     def chat(message, history):
@@ -14,48 +16,51 @@ def create_chat_fn(client):
             top_k=40,
             repetition_penalty=1.1,
             top_p=0.95,
-            api_name="/chat",
+            api_name="/chat"
         )
         return response
-
     return chat
 
-
 def set_client_for_session(model_name, request: gr.Request):
     headers = {}
-    if request and hasattr(request, "request") and hasattr(request.request, "headers"):
-        x_ip_token = request.request.headers.get("x-ip-token")
+    if request and hasattr(request, 'request') and hasattr(request.request, 'headers'):
+        x_ip_token = request.request.headers.get('x-ip-token')
         if x_ip_token:
             headers["X-IP-Token"] = x_ip_token
-
+    
     return Client(MODELS[model_name], headers=headers)
 
-
 def safe_chat_fn(message, history, client):
     if client is None:
         return "Error: Client not initialized. Please refresh the page."
     return create_chat_fn(client)(message, history)
 
-
 with gr.Blocks() as demo:
+    
     client = gr.State()
-
+    
     model_dropdown = gr.Dropdown(
-        choices=list(MODELS.keys()), value="OLMo-2-1124-13B-Instruct", label="Select Model", interactive=True
+        choices=list(MODELS.keys()),
+        value="OLMo-2-1124-13B-Instruct",
+        label="Select Model",
+        interactive=True
     )
-
-    chat_interface = gr.ChatInterface(fn=safe_chat_fn, additional_inputs=[client])
-
+    
+    chat_interface = gr.ChatInterface(
+        fn=safe_chat_fn,
+        additional_inputs=[client]
+    )
+    
     # Update client when model changes
     def update_model(model_name, request):
         return set_client_for_session(model_name, request)
-
+    
     model_dropdown.change(
         fn=update_model,
         inputs=[model_dropdown],
         outputs=[client],
     )
-
+    
     # Initialize client on page load
     demo.load(
         fn=set_client_for_session,
@@ -63,5 +68,6 @@ with gr.Blocks() as demo:
         outputs=client,
     )
 
-if __name__ == "__main__":
-    demo.launch()
+demo = demo
+
+

app_cohere.py

@@ -1,21 +0,0 @@
-import os
-
-import cohere_gradio
-
-from utils import get_app
-
-demo = get_app(
-    models=[
-        "command-r",
-        "command-r-08-2024",
-        "command-r-plus",
-        "command-r-plus-08-2024",
-        "command-r7b-12-2024",
-    ],
-    default_model="command-r7b-12-2024",
-    src=cohere_gradio.registry,
-    accept_token=not os.getenv("COHERE_API_KEY"),
-)
-
-if __name__ == "__main__":
-    demo.launch()

app_compare.py

@@ -1,210 +0,0 @@
-import os
-
-import google.generativeai as genai
-import gradio as gr
-import openai
-from anthropic import Anthropic
-from openai import OpenAI  # Add explicit OpenAI import
-
-
-def get_all_models():
-    """Get all available models from the registries."""
-    return [
-        "SambaNova: Meta-Llama-3.2-1B-Instruct",
-        "SambaNova: Meta-Llama-3.2-3B-Instruct",
-        "SambaNova: Llama-3.2-11B-Vision-Instruct",
-        "SambaNova: Llama-3.2-90B-Vision-Instruct",
-        "SambaNova: Meta-Llama-3.1-8B-Instruct",
-        "SambaNova: Meta-Llama-3.1-70B-Instruct",
-        "SambaNova: Meta-Llama-3.1-405B-Instruct",
-        "Hyperbolic: Qwen/Qwen2.5-Coder-32B-Instruct",
-        "Hyperbolic: meta-llama/Llama-3.2-3B-Instruct",
-        "Hyperbolic: meta-llama/Meta-Llama-3.1-8B-Instruct",
-        "Hyperbolic: meta-llama/Meta-Llama-3.1-70B-Instruct",
-        "Hyperbolic: meta-llama/Meta-Llama-3-70B-Instruct",
-        "Hyperbolic: NousResearch/Hermes-3-Llama-3.1-70B",
-        "Hyperbolic: Qwen/Qwen2.5-72B-Instruct",
-        "Hyperbolic: deepseek-ai/DeepSeek-V2.5",
-        "Hyperbolic: meta-llama/Meta-Llama-3.1-405B-Instruct",
-    ]
-
-
-def generate_discussion_prompt(original_question: str, previous_responses: list[str]) -> str:
-    """Generate a prompt for models to discuss and build upon previous
-    responses.
-    """
-    prompt = f"""You are participating in a multi-AI discussion about this question: "{original_question}"
-
-Previous responses from other AI models:
-{chr(10).join(f"- {response}" for response in previous_responses)}
-
-Please provide your perspective while:
-1. Acknowledging key insights from previous responses
-2. Adding any missing important points
-3. Respectfully noting if you disagree with anything and explaining why
-4. Building towards a complete answer
-
-Keep your response focused and concise (max 3-4 paragraphs)."""
-    return prompt
-
-
-def generate_consensus_prompt(original_question: str, discussion_history: list[str]) -> str:
-    """Generate a prompt for final consensus building."""
-    return f"""Review this multi-AI discussion about: "{original_question}"
-
-Discussion history:
-{chr(10).join(discussion_history)}
-
-As a final synthesizer, please:
-1. Identify the key points where all models agreed
-2. Explain how any disagreements were resolved
-3. Present a clear, unified answer that represents our collective best understanding
-4. Note any remaining uncertainties or caveats
-
-Keep the final consensus concise but complete."""
-
-
-def chat_with_openai(model: str, messages: list[dict], api_key: str | None) -> str:
-    import openai
-
-    client = openai.OpenAI(api_key=api_key)
-    response = client.chat.completions.create(model=model, messages=messages)
-    return response.choices[0].message.content
-
-
-def chat_with_anthropic(messages: list[dict], api_key: str | None) -> str:
-    """Chat with Anthropic's Claude model."""
-    client = Anthropic(api_key=api_key)
-    response = client.messages.create(model="claude-3-sonnet-20240229", messages=messages, max_tokens=1024)
-    return response.content[0].text
-
-
-def chat_with_gemini(messages: list[dict], api_key: str | None) -> str:
-    """Chat with Gemini Pro model."""
-    genai.configure(api_key=api_key)
-    model = genai.GenerativeModel("gemini-pro")
-
-    # Convert messages to Gemini format
-    gemini_messages = []
-    for msg in messages:
-        role = "user" if msg["role"] == "user" else "model"
-        gemini_messages.append({"role": role, "parts": [msg["content"]]})
-
-    response = model.generate_content([m["parts"][0] for m in gemini_messages])
-    return response.text
-
-
-def chat_with_sambanova(
-    messages: list[dict], api_key: str | None, model_name: str = "Llama-3.2-90B-Vision-Instruct"
-) -> str:
-    """Chat with SambaNova's models using their OpenAI-compatible API."""
-    client = openai.OpenAI(
-        api_key=api_key,
-        base_url="https://api.sambanova.ai/v1",
-    )
-
-    response = client.chat.completions.create(
-        model=model_name,
-        messages=messages,
-        temperature=0.1,
-        top_p=0.1,  # Use the specific model name passed in
-    )
-    return response.choices[0].message.content
-
-
-def chat_with_hyperbolic(
-    messages: list[dict], api_key: str | None, model_name: str = "Qwen/Qwen2.5-Coder-32B-Instruct"
-) -> str:
-    """Chat with Hyperbolic's models using their OpenAI-compatible API."""
-    client = OpenAI(api_key=api_key, base_url="https://api.hyperbolic.xyz/v1")
-
-    # Add system message to the start of the messages list
-    full_messages = [
-        {"role": "system", "content": "You are a helpful assistant. Be descriptive and clear."},
-        *messages,
-    ]
-
-    response = client.chat.completions.create(
-        model=model_name,  # Use the specific model name passed in
-        messages=full_messages,
-        temperature=0.7,
-        max_tokens=1024,
-    )
-    return response.choices[0].message.content
-
-
-def multi_model_consensus(
-    question: str, selected_models: list[str], rounds: int = 3, progress: gr.Progress = gr.Progress()
-) -> list[tuple[str, str]]:
-    if not selected_models:
-        raise gr.Error("Please select at least one model to chat with.")
-
-    chat_history = []
-    progress(0, desc="Getting responses from all models...")
-
-    # Get responses from all models in parallel
-    for i, model in enumerate(selected_models):
-        provider, model_name = model.split(": ", 1)
-        progress((i + 1) / len(selected_models), desc=f"Getting response from {model}...")
-
-        try:
-            if provider == "Anthropic":
-                api_key = os.getenv("ANTHROPIC_API_KEY")
-                response = chat_with_anthropic(messages=[{"role": "user", "content": question}], api_key=api_key)
-            elif provider == "SambaNova":
-                api_key = os.getenv("SAMBANOVA_API_KEY")
-                response = chat_with_sambanova(
-                    messages=[
-                        {"role": "system", "content": "You are a helpful assistant"},
-                        {"role": "user", "content": question},
-                    ],
-                    api_key=api_key,
-                    model_name=model_name,
-                )
-            elif provider == "Hyperbolic":
-                api_key = os.getenv("HYPERBOLIC_API_KEY")
-                response = chat_with_hyperbolic(
-                    messages=[{"role": "user", "content": question}],
-                    api_key=api_key,
-                    model_name=model_name,
-                )
-            else:  # Gemini
-                api_key = os.getenv("GEMINI_API_KEY")
-                response = chat_with_gemini(messages=[{"role": "user", "content": question}], api_key=api_key)
-
-            chat_history.append((model, response))
-        except Exception as e:
-            chat_history.append((model, f"Error: {e!s}"))
-
-    progress(1.0, desc="Done!")
-    return chat_history
-
-
-with gr.Blocks() as demo:
-    gr.Markdown("# Model Response Comparison")
-    gr.Markdown("""Select multiple models to compare their responses""")
-
-    with gr.Row():
-        with gr.Column():
-            model_selector = gr.Dropdown(
-                choices=get_all_models(),
-                multiselect=True,
-                label="Select Models",
-                info="Choose models to compare",
-                value=["SambaNova: Llama-3.2-90B-Vision-Instruct", "Hyperbolic: Qwen/Qwen2.5-Coder-32B-Instruct"],
-            )
-
-    chatbot = gr.Chatbot(height=600, label="Model Responses")
-    msg = gr.Textbox(label="Prompt", placeholder="Ask a question to compare model responses...")
-
-    def respond(message, selected_models):
-        chat_history = multi_model_consensus(message, selected_models, rounds=1)
-        return chat_history
-
-    msg.submit(respond, [msg, model_selector], [chatbot])
-
-for fn in demo.fns.values():
-    fn.api_name = False
-
-if __name__ == "__main__":
-    demo.launch()

app_crew.py

@@ -1,8 +0,0 @@
-import ai_gradio
-import gradio as gr
-
-demo = gr.load(
-    name="crewai:gpt-4-turbo",
-    crew_type="article",  # or 'support'
-    src=ai_gradio.registry,
-)

app_deepseek.py

@@ -1,23 +0,0 @@
-import ai_gradio
-
-from utils_ai_gradio import get_app
-
-# Get the hyperbolic models but keep their full names for loading
-DEEPSEEK_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("deepseek:")]
-
-# Create display names without the prefix
-DEEPSEEK_MODELS_DISPLAY = [k.replace("deepseek:", "") for k in DEEPSEEK_MODELS_FULL]
-
-
-# Create and launch the interface using get_app utility
-demo = get_app(
-    models=DEEPSEEK_MODELS_FULL,  # Use the full names with prefix
-    default_model=DEEPSEEK_MODELS_FULL[-1],
-    dropdown_label="Select DeepSeek Model",
-    choices=DEEPSEEK_MODELS_DISPLAY,  # Display names without prefix
-    fill_height=True,
-    coder=True,
-)
-
-if __name__ == "__main__":
-    demo.launch()

app_experimental.py

@@ -1,5 +1,6 @@
 import os
 import random
+from typing import Dict, List
 
 import google.generativeai as genai
 import gradio as gr
@@ -30,10 +31,9 @@ def get_all_models():
     ]
 
 
-def generate_discussion_prompt(original_question: str, previous_responses: list[str]) -> str:
+def generate_discussion_prompt(original_question: str, previous_responses: List[str]) -> str:
     """Generate a prompt for models to discuss and build upon previous
-    responses.
-    """
+    responses."""
     prompt = f"""You are participating in a multi-AI discussion about this question: "{original_question}"
 
 Previous responses from other AI models:
@@ -49,7 +49,7 @@ Keep your response focused and concise (max 3-4 paragraphs)."""
     return prompt
 
 
-def generate_consensus_prompt(original_question: str, discussion_history: list[str]) -> str:
+def generate_consensus_prompt(original_question: str, discussion_history: List[str]) -> str:
     """Generate a prompt for final consensus building."""
     return f"""Review this multi-AI discussion about: "{original_question}"
 
@@ -65,7 +65,7 @@ As a final synthesizer, please:
 Keep the final consensus concise but complete."""
 
 
-def chat_with_openai(model: str, messages: list[dict], api_key: str | None) -> str:
+def chat_with_openai(model: str, messages: List[Dict], api_key: str | None) -> str:
     import openai
 
     client = openai.OpenAI(api_key=api_key)
@@ -73,14 +73,14 @@ def chat_with_openai(model: str, messages: list[dict], api_key: str | None) -> s
     return response.choices[0].message.content
 
 
-def chat_with_anthropic(messages: list[dict], api_key: str | None) -> str:
+def chat_with_anthropic(messages: List[Dict], api_key: str | None) -> str:
     """Chat with Anthropic's Claude model."""
     client = Anthropic(api_key=api_key)
     response = client.messages.create(model="claude-3-sonnet-20240229", messages=messages, max_tokens=1024)
     return response.content[0].text
 
 
-def chat_with_gemini(messages: list[dict], api_key: str | None) -> str:
+def chat_with_gemini(messages: List[Dict], api_key: str | None) -> str:
     """Chat with Gemini Pro model."""
     genai.configure(api_key=api_key)
     model = genai.GenerativeModel("gemini-pro")
@@ -96,7 +96,7 @@ def chat_with_gemini(messages: list[dict], api_key: str | None) -> str:
 
 
 def chat_with_sambanova(
-    messages: list[dict], api_key: str | None, model_name: str = "Llama-3.2-90B-Vision-Instruct"
+    messages: List[Dict], api_key: str | None, model_name: str = "Llama-3.2-90B-Vision-Instruct"
 ) -> str:
     """Chat with SambaNova's models using their OpenAI-compatible API."""
     client = openai.OpenAI(
@@ -105,16 +105,13 @@ def chat_with_sambanova(
     )
 
     response = client.chat.completions.create(
-        model=model_name,
-        messages=messages,
-        temperature=0.1,
-        top_p=0.1,  # Use the specific model name passed in
+        model=model_name, messages=messages, temperature=0.1, top_p=0.1  # Use the specific model name passed in
     )
     return response.choices[0].message.content
 
 
 def chat_with_hyperbolic(
-    messages: list[dict], api_key: str | None, model_name: str = "Qwen/Qwen2.5-Coder-32B-Instruct"
+    messages: List[Dict], api_key: str | None, model_name: str = "Qwen/Qwen2.5-Coder-32B-Instruct"
 ) -> str:
     """Chat with Hyperbolic's models using their OpenAI-compatible API."""
     client = OpenAI(api_key=api_key, base_url="https://api.hyperbolic.xyz/v1")
@@ -135,7 +132,7 @@ def chat_with_hyperbolic(
 
 
 def multi_model_consensus(
-    question: str, selected_models: list[str], rounds: int = 3, progress: gr.Progress = gr.Progress()
+    question: str, selected_models: List[str], rounds: int = 3, progress: gr.Progress = gr.Progress()
 ) -> list[tuple[str, str]]:
     if not selected_models:
         raise gr.Error("Please select at least one model to chat with.")
@@ -249,7 +246,7 @@ def multi_model_consensus(
                 messages=[{"role": "user", "content": consensus_prompt}], api_key=api_key
             )
     except Exception as e:
-        final_consensus = f"Error getting consensus from {model}: {e!s}"
+        final_consensus = f"Error getting consensus from {model}: {str(e)}"
 
     chat_history.append(("Final Consensus", final_consensus))
 

app_fireworks.py

@@ -8,9 +8,8 @@ demo = get_app(
     models=[
         "f1-preview",
         "f1-mini-preview",
-        "llama-v3p3-70b-instruct",
     ],
-    default_model="llama-v3p3-70b-instruct",
+    default_model="f1-preview",
     src=fireworks_gradio.registry,
     accept_token=not os.getenv("FIREWORKS_API_KEY"),
 )

app_replicate.py → app_flux.py

@@ -8,9 +8,8 @@ demo = get_app(
         "black-forest-labs/flux-canny-pro",
         "black-forest-labs/flux-fill-pro",
         "black-forest-labs/flux-depth-dev",
-        "tencent/hunyuan-video:140176772be3b423d14fdaf5403e6d4e38b85646ccad0c3fd2ed07c211f0cad1",
     ],
-    default_model="tencent/hunyuan-video:140176772be3b423d14fdaf5403e6d4e38b85646ccad0c3fd2ed07c211f0cad1",
+    default_model="black-forest-labs/flux-depth-pro",
     src=replicate_gradio.registry,
 )
 

app_gemini.py

@@ -1,21 +1,20 @@
-import ai_gradio
+import os
 
-from utils_ai_gradio import get_app
+import gemini_gradio
 
-# Get the Gemini models but keep their full names for loading
-GEMINI_MODELS_FULL = [k for k in ai_gradio.registry if k.startswith("gemini:")]
+from utils import get_app
 
-# Create display names without the prefix
-GEMINI_MODELS_DISPLAY = [k.replace("gemini:", "") for k in GEMINI_MODELS_FULL]
-
-# Create and launch the interface using get_app utility
 demo = get_app(
-    models=GEMINI_MODELS_FULL,  # Use the full names with prefix
-    default_model=GEMINI_MODELS_FULL[-1],
-    dropdown_label="Select Gemini Model",
-    choices=GEMINI_MODELS_DISPLAY,  # Display names without prefix
-    src=ai_gradio.registry,
-    fill_height=True,
+    models=[
+        "gemini-1.5-flash",
+        "gemini-1.5-flash-8b",
+        "gemini-1.5-pro",
+        "gemini-exp-1114",
+        "gemini-exp-1121",
+    ],
+    default_model="gemini-1.5-flash",
+    src=gemini_gradio.registry,
+    accept_token=not os.getenv("GEMINI_API_KEY"),
 )
 
 if __name__ == "__main__":

app_gemini_camera.py

@@ -1,23 +0,0 @@
-import ai_gradio
-
-from utils_ai_gradio import get_app
-
-# Get the Gemini models but keep their full names for loading
-GEMINI_MODELS_FULL = [k for k in ai_gradio.registry if k.startswith("gemini:")]
-
-# Create display names without the prefix
-GEMINI_MODELS_DISPLAY = [k.replace("gemini:", "") for k in GEMINI_MODELS_FULL]
-
-# Create and launch the interface using get_app utility
-demo = get_app(
-    models=GEMINI_MODELS_FULL,  # Use the full names with prefix
-    default_model=GEMINI_MODELS_FULL[-2],
-    dropdown_label="Select Gemini Model",
-    choices=GEMINI_MODELS_DISPLAY,  # Display names without prefix
-    src=ai_gradio.registry,
-    camera=True,
-    fill_height=True,
-)
-
-if __name__ == "__main__":
-    demo.launch()

app_gemini_coder.py

@@ -1,23 +0,0 @@
-import ai_gradio
-
-from utils_ai_gradio import get_app
-
-# Get the Gemini models but keep their full names for loading
-GEMINI_MODELS_FULL = [k for k in ai_gradio.registry if k.startswith("gemini:")]
-
-# Create display names without the prefix
-GEMINI_MODELS_DISPLAY = [k.replace("gemini:", "") for k in GEMINI_MODELS_FULL]
-
-# Create and launch the interface using get_app utility
-demo = get_app(
-    models=GEMINI_MODELS_FULL,  # Use the full names with prefix
-    default_model=GEMINI_MODELS_FULL[-1],
-    dropdown_label="Select Gemini Model",
-    choices=GEMINI_MODELS_DISPLAY,  # Display names without prefix
-    src=ai_gradio.registry,
-    fill_height=True,
-    coder=True,
-)
-
-if __name__ == "__main__":
-    demo.launch()

app_gemini_voice.py

@@ -1,23 +0,0 @@
-import ai_gradio
-
-from utils_ai_gradio import get_app
-
-# Get the Gemini models but keep their full names for loading
-GEMINI_MODELS_FULL = [k for k in ai_gradio.registry if k.startswith("gemini:")]
-
-# Create display names without the prefix
-GEMINI_MODELS_DISPLAY = [k.replace("gemini:", "") for k in GEMINI_MODELS_FULL]
-
-# Create and launch the interface using get_app utility
-demo = get_app(
-    models=GEMINI_MODELS_FULL,  # Use the full names with prefix
-    default_model=GEMINI_MODELS_FULL[-2],
-    dropdown_label="Select Gemini Model",
-    choices=GEMINI_MODELS_DISPLAY,  # Display names without prefix
-    src=ai_gradio.registry,
-    enable_voice=True,
-    fill_height=True,
-)
-
-if __name__ == "__main__":
-    demo.launch()

app_groq.py

@@ -1,20 +1,24 @@
-import ai_gradio
+import os
 
-from utils_ai_gradio import get_app
+import groq_gradio
 
-# Get the Groq models from the registry
-GROQ_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("groq:")]
-
-# Create display names without the prefix
-GROQ_MODELS_DISPLAY = [k.replace("groq:", "") for k in GROQ_MODELS_FULL]
+from utils import get_app
 
 demo = get_app(
-    models=GROQ_MODELS_FULL,
-    default_model=GROQ_MODELS_FULL[-2],
-    src=ai_gradio.registry,
-    dropdown_label="Select Groq Model",
-    choices=GROQ_MODELS_DISPLAY,
-    fill_height=True,
+    models=[
+        "llama3-groq-8b-8192-tool-use-preview",
+        "llama3-groq-70b-8192-tool-use-preview",
+        "llama-3.2-1b-preview",
+        "llama-3.2-3b-preview",
+        "llama-3.2-11b-vision-preview",
+        "llama-3.2-90b-vision-preview",
+        "mixtral-8x7b-32768",
+        "gemma2-9b-it",
+        "gemma-7b-it",
+    ],
+    default_model="llama3-groq-70b-8192-tool-use-preview",
+    src=groq_gradio.registry,
+    accept_token=not os.getenv("GROQ_API_KEY"),
 )
 
 if __name__ == "__main__":

app_groq_coder.py

@@ -1,23 +0,0 @@
-import ai_gradio
-
-from utils_ai_gradio import get_app
-
-# Get the Groq models but keep their full names for loading
-GROQ_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("groq:")]
-
-# Create display names without the prefix
-GROQ_MODELS_DISPLAY = [k.replace("groq:", "") for k in GROQ_MODELS_FULL]
-
-# Create and launch the interface using get_app utility
-demo = get_app(
-    models=GROQ_MODELS_FULL,  # Use the full names with prefix
-    default_model=GROQ_MODELS_FULL[-2],
-    dropdown_label="Select Groq Model",
-    choices=GROQ_MODELS_DISPLAY,  # Display names without prefix
-    fill_height=True,
-    coder=True,
-)
-
-
-if __name__ == "__main__":
-    demo.launch()

app_huggingface.py

@@ -1,67 +1,75 @@
+from gradio_client import Client
 import gradio as gr
-from gradio_client import Client, handle_file
+import os
 
-MODELS = {"SmolVLM-Instruct": "akhaliq/SmolVLM-Instruct"}
 
+MODELS = {
+    "SmolVLM-Instruct": "akhaliq/SmolVLM-Instruct"
+}
 
 def create_chat_fn(client):
-    def chat(message, history):
-        # Extract text and files from the message
-        text = message.get("text", "")
-        files = message.get("files", [])
-
-        # Handle file uploads if present
-        processed_files = [handle_file(f) for f in files]
-
+    def chat(message, history, files=[]):
         response = client.predict(
-            message={"text": text, "files": processed_files},
+            message={"text": message, "files": files},
             system_prompt="You are a helpful AI assistant.",
             temperature=0.7,
             max_new_tokens=1024,
             top_k=40,
             repetition_penalty=1.1,
             top_p=0.95,
-            api_name="/chat",
+            api_name="/chat"
         )
         return response
-
     return chat
 
-
 def set_client_for_session(model_name, request: gr.Request):
     headers = {}
-    if request and hasattr(request, "headers"):
-        x_ip_token = request.headers.get("x-ip-token")
+    if request and hasattr(request, 'headers'):
+        x_ip_token = request.headers.get('x-ip-token')
         if x_ip_token:
             headers["X-IP-Token"] = x_ip_token
-
+    
     return Client(MODELS[model_name], headers=headers)
 
-
 def safe_chat_fn(message, history, client):
     if client is None:
         return "Error: Client not initialized. Please refresh the page."
     try:
         return create_chat_fn(client)(message, history)
     except Exception as e:
-        print(f"Error during chat: {e!s}")
-        return f"Error during chat: {e!s}"
-
+        print(f"Error during chat: {str(e)}")
+        return f"Error during chat: {str(e)}"
 
 with gr.Blocks() as demo:
+    
     client = gr.State()
-
+    
     model_dropdown = gr.Dropdown(
-        choices=list(MODELS.keys()), value="SmolVLM-Instruct", label="Select Model", interactive=True
+        choices=list(MODELS.keys()),
+        value="SmolVLM-Instruct",
+        label="Select Model",
+        interactive=True
     )
-
-    chat_interface = gr.ChatInterface(fn=safe_chat_fn, additional_inputs=[client], multimodal=True)
-
+    
+    chat_interface = gr.ChatInterface(
+        fn=safe_chat_fn,
+        additional_inputs=[client],
+        multimodal=True
+    )
+    
     # Update client when model changes
-    model_dropdown.change(fn=set_client_for_session, inputs=[model_dropdown], outputs=[client])
-
+    model_dropdown.change(
+        fn=set_client_for_session,
+        inputs=[model_dropdown],
+        outputs=[client]
+    )
+    
     # Initialize client on page load
-    demo.load(fn=set_client_for_session, inputs=[gr.State("SmolVLM-Instruct")], outputs=[client])
+    demo.load(
+        fn=set_client_for_session,
+        inputs=[gr.State("SmolVLM-Instruct")],
+        outputs=[client]
+    )
+
+demo = demo
 
-if __name__ == "__main__":
-    demo.launch()

app_hyperbolic.py

@@ -1,19 +1,26 @@
-import ai_gradio
+import os
 
-from utils_ai_gradio import get_app
+import hyperbolic_gradio
 
-# Get the hyperbolic models but keep their full names for loading
-HYPERBOLIC_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("hyperbolic:")]
+from utils import get_app
 
-# Create display names without the prefix
-HYPERBOLIC_MODELS_DISPLAY = [k.replace("hyperbolic:", "") for k in HYPERBOLIC_MODELS_FULL]
-
-
-# Create and launch the interface using get_app utility
 demo = get_app(
-    models=HYPERBOLIC_MODELS_FULL,  # Use the full names with prefix
-    default_model=HYPERBOLIC_MODELS_FULL[-1],
-    dropdown_label="Select Hyperbolic Model",
-    choices=HYPERBOLIC_MODELS_DISPLAY,  # Display names without prefix
-    fill_height=True,
+    models=[
+        "Qwen/Qwen2.5-Coder-32B-Instruct",
+        "meta-llama/Llama-3.2-3B-Instruct",
+        "meta-llama/Meta-Llama-3.1-8B-Instruct",
+        "meta-llama/Meta-Llama-3.1-70B-Instruct",
+        "meta-llama/Meta-Llama-3-70B-Instruct",
+        "NousResearch/Hermes-3-Llama-3.1-70B",
+        "Qwen/Qwen2.5-72B-Instruct",
+        "deepseek-ai/DeepSeek-V2.5",
+        "meta-llama/Meta-Llama-3.1-405B-Instruct",
+        "Qwen/QwQ-32B-Preview",
+    ],
+    default_model="Qwen/QwQ-32B-Preview",
+    src=hyperbolic_gradio.registry,
+    accept_token=not os.getenv("HYPERBOLIC_API_KEY"),
 )
+
+if __name__ == "__main__":
+    demo.launch()

app_hyperbolic_coder.py

@@ -1,20 +0,0 @@
-import ai_gradio
-
-from utils_ai_gradio import get_app
-
-# Get the hyperbolic models but keep their full names for loading
-HYPERBOLIC_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("hyperbolic:")]
-
-# Create display names without the prefix
-HYPERBOLIC_MODELS_DISPLAY = [k.replace("hyperbolic:", "") for k in HYPERBOLIC_MODELS_FULL]
-
-
-# Create and launch the interface using get_app utility
-demo = get_app(
-    models=HYPERBOLIC_MODELS_FULL,  # Use the full names with prefix
-    default_model=HYPERBOLIC_MODELS_FULL[-1],
-    dropdown_label="Select Hyperbolic Model",
-    choices=HYPERBOLIC_MODELS_DISPLAY,  # Display names without prefix
-    fill_height=True,
-    coder=True,
-)

app_langchain.py

@@ -1,23 +0,0 @@
-import ai_gradio
-
-from utils_ai_gradio import get_app
-
-# Get the hyperbolic models but keep their full names for loading
-LANGCHAIN_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("langchain:")]
-
-# Create display names without the prefix
-LANGCHAIN_MODELS_DISPLAY = [k.replace("langchain:", "") for k in LANGCHAIN_MODELS_FULL]
-
-
-# Create and launch the interface using get_app utility
-demo = get_app(
-    models=LANGCHAIN_MODELS_FULL,  # Use the full names with prefix
-    default_model=LANGCHAIN_MODELS_FULL[0],
-    dropdown_label="Select Langchain Model",
-    choices=LANGCHAIN_MODELS_DISPLAY,  # Display names without prefix
-    fill_height=True,
-)
-
-if __name__ == "__main__":
-    demo.launch()
-

app_fal.py → app_ltx_video.py

@@ -6,9 +6,8 @@ demo = get_app(
     models=[
         "fal-ai/ltx-video",
         "fal-ai/ltx-video/image-to-video",
-        "fal-ai/luma-photon",
     ],
-    default_model="fal-ai/luma-photon",
+    default_model="fal-ai/ltx-video/image-to-video",
     src=fal_gradio.registry,
 )
 

app_lumaai.py

@@ -1,7 +0,0 @@
-import gradio as gr
-import lumaai_gradio
-
-demo = gr.load(
-    name="dream-machine",
-    src=lumaai_gradio.registry,
-)

app_meta.py

@@ -1,6 +0,0 @@
-import gradio as gr
-
-demo = gr.load("models/meta-llama/Llama-3.3-70B-Instruct")
-
-if __name__ == "__main__":
-    demo.launch()

app_mindsearch.py

@@ -1,12 +0,0 @@
-import gradio as gr
-
-# Load the Gradio space
-demo = gr.load(name="internlm/MindSearch", src="spaces")
-
-# Disable API access for all functions
-if hasattr(demo, "fns"):
-    for fn in demo.fns.values():
-        fn.api_name = False
-
-if __name__ == "__main__":
-    demo.launch()

app_minimax.py

@@ -1,22 +0,0 @@
-import ai_gradio
-
-from utils_ai_gradio import get_app
-
-# Get the hyperbolic models but keep their full names for loading
-MINIMAX_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("minimax:")]
-
-# Create display names without the prefix
-MINIMAX_MODELS_DISPLAY = [k.replace("minimax:", "") for k in MINIMAX_MODELS_FULL]
-
-
-# Create and launch the interface using get_app utility
-demo = get_app(
-    models=MINIMAX_MODELS_FULL,  # Use the full names with prefix
-    default_model=MINIMAX_MODELS_FULL[0],
-    dropdown_label="Select Minimax Model",
-    choices=MINIMAX_MODELS_DISPLAY,  # Display names without prefix
-    fill_height=True,
-)
-
-if __name__ == "__main__":
-    demo.launch()

app_minimax_coder.py

@@ -1,23 +0,0 @@
-import ai_gradio
-
-from utils_ai_gradio import get_app
-
-# Get the hyperbolic models but keep their full names for loading
-MINIMAX_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("minimax:")]
-
-# Create display names without the prefix
-MINIMAX_MODELS_DISPLAY = [k.replace("minimax:", "") for k in MINIMAX_MODELS_FULL]
-
-
-# Create and launch the interface using get_app utility
-demo = get_app(
-    models=MINIMAX_MODELS_FULL,  # Use the full names with prefix
-    default_model=MINIMAX_MODELS_FULL[0],
-    dropdown_label="Select Minimax Model",
-    choices=MINIMAX_MODELS_DISPLAY,  # Display names without prefix
-    fill_height=True,
-    coder=True
-)
-
-if __name__ == "__main__":
-    demo.launch()

app_mistral.py

@@ -1,22 +1,26 @@
-import ai_gradio
+import os
 
-from utils_ai_gradio import get_app
+import mistral_gradio
 
-# Get the mistral models but keep their full names for loading
-MISTRAL_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("mistral:")]
+from utils import get_app
 
-# Create display names without the prefix
-MISTRAL_MODELS_DISPLAY = [k.replace("mistral:", "") for k in MISTRAL_MODELS_FULL]
-
-
-# Create and launch the interface using get_app utility
 demo = get_app(
-    models=MISTRAL_MODELS_FULL,  # Use the full names with prefix
-    default_model=MISTRAL_MODELS_FULL[5],
-    dropdown_label="Select Mistral Model",
-    choices=MISTRAL_MODELS_DISPLAY,  # Display names without prefix
-    fill_height=True,
-    coder=True
+    models=[
+        "mistral-large-latest",
+        "pixtral-large-latest",
+        "ministral-3b-latest",
+        "ministral-8b-latest",
+        "mistral-small-latest",
+        "codestral-latest",
+        "mistral-embed",
+        "mistral-moderation-latest",
+        "pixtral-12b-2409",
+        "open-mistral-nemo",
+        "open-codestral-mamba",
+    ],
+    default_model="pixtral-large-latest",
+    src=mistral_gradio.registry,
+    accept_token=not os.getenv("MISTRAL_API_KEY"),
 )
 
 if __name__ == "__main__":

app_moondream.py

@@ -1,13 +0,0 @@
-import gradio as gr
-
-# Load the Gradio space
-demo = gr.load(name="akhaliq/moondream", src="spaces")
-
-
-# Disable API access for all functions
-if hasattr(demo, "fns"):
-    for fn in demo.fns.values():
-        fn.api_name = False
-
-if __name__ == "__main__":
-    demo.launch()

app_nvidia.py

@@ -1,21 +1,51 @@
-import ai_gradio
+import os
 
-from utils_ai_gradio import get_app
+import nvidia_gradio
 
-# Get the nvidia models but keep their full names for loading
-NVIDIA_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("nvidia:")]
+from utils import get_app
 
-# Create display names without the prefix
-NVIDIA_MODELS_DISPLAY = [k.replace("nvidia:", "") for k in NVIDIA_MODELS_FULL]
-
-
-# Create and launch the interface using get_app utility
 demo = get_app(
-    models=NVIDIA_MODELS_FULL,  # Use the full names with prefix
-    default_model=NVIDIA_MODELS_FULL[0],
-    dropdown_label="Select Nvidia Model",
-    choices=NVIDIA_MODELS_DISPLAY,  # Display names without prefix
-    fill_height=True,
+    models=[
+        "nvidia/llama3-chatqa-1.5-70b",
+        "nvidia/llama3-chatqa-1.5-8b",
+        "nvidia-nemotron-4-340b-instruct",
+        "meta/llama-3.1-70b-instruct",
+        "meta/codellama-70b",
+        "meta/llama2-70b",
+        "meta/llama3-8b",
+        "meta/llama3-70b",
+        "mistralai/codestral-22b-instruct-v0.1",
+        "mistralai/mathstral-7b-v0.1",
+        "mistralai/mistral-large-2-instruct",
+        "mistralai/mistral-7b-instruct",
+        "mistralai/mistral-7b-instruct-v0.3",
+        "mistralai/mixtral-8x7b-instruct",
+        "mistralai/mixtral-8x22b-instruct",
+        "mistralai/mistral-large",
+        "google/gemma-2b",
+        "google/gemma-7b",
+        "google/gemma-2-2b-it",
+        "google/gemma-2-9b-it",
+        "google/gemma-2-27b-it",
+        "google/codegemma-1.1-7b",
+        "google/codegemma-7b",
+        "google/recurrentgemma-2b",
+        "google/shieldgemma-9b",
+        "microsoft/phi-3-medium-128k-instruct",
+        "microsoft/phi-3-medium-4k-instruct",
+        "microsoft/phi-3-mini-128k-instruct",
+        "microsoft/phi-3-mini-4k-instruct",
+        "microsoft/phi-3-small-128k-instruct",
+        "microsoft/phi-3-small-8k-instruct",
+        "qwen/qwen2-7b-instruct",
+        "databricks/dbrx-instruct",
+        "deepseek-ai/deepseek-coder-6.7b-instruct",
+        "upstage/solar-10.7b-instruct",
+        "snowflake/arctic",
+    ],
+    default_model="meta/llama-3.1-70b-instruct",
+    src=nvidia_gradio.registry,
+    accept_token=not os.getenv("NVIDIA_API_KEY"),
 )
 
 if __name__ == "__main__":

app_omini.py

@@ -1,10 +0,0 @@
-import gradio as gr
-
-# Load the Gradio space
-demo = gr.load(name="Yuanshi/OminiControl", src="spaces")
-
-
-# Disable API access for all functions
-if hasattr(demo, "fns"):
-    for fn in demo.fns.values():
-        fn.api_name = False

app_openai.py

@@ -1,20 +1,33 @@
-import ai_gradio
+import os
 
-from utils_ai_gradio import get_app
+import openai_gradio
 
-# Get the OpenAI models but keep their full names for loading
-OPENAI_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("openai:")]
+from utils import get_app
 
-# Create display names without the prefix
-OPENAI_MODELS_DISPLAY = [k.replace("openai:", "") for k in OPENAI_MODELS_FULL]
-
-# Create and launch the interface using get_app utility
 demo = get_app(
-    models=OPENAI_MODELS_FULL,  # Use the full names with prefix
-    default_model=OPENAI_MODELS_FULL[-1],
-    dropdown_label="Select OpenAI Model",
-    choices=OPENAI_MODELS_DISPLAY,  # Display names without prefix
-    fill_height=True,
+    models=[
+        "gpt-4o-2024-11-20",
+        "gpt-4o",
+        "gpt-4o-2024-08-06",
+        "gpt-4o-2024-05-13",
+        "chatgpt-4o-latest",
+        "gpt-4o-mini",
+        "gpt-4o-mini-2024-07-18",
+        "o1-preview",
+        "o1-preview-2024-09-12",
+        "o1-mini",
+        "o1-mini-2024-09-12",
+        "gpt-4-turbo",
+        "gpt-4-turbo-2024-04-09",
+        "gpt-4-turbo-preview",
+        "gpt-4-0125-preview",
+        "gpt-4-1106-preview",
+        "gpt-4",
+        "gpt-4-0613",
+    ],
+    default_model="gpt-4o-2024-11-20",
+    src=openai_gradio.registry,
+    accept_token=not os.getenv("OPENAI_API_KEY"),
 )
 
 if __name__ == "__main__":

app_openai_coder.py

@@ -1,22 +0,0 @@
-import ai_gradio
-
-from utils_ai_gradio import get_app
-
-# Get the OpenAI models but keep their full names for loading
-OPENAI_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("openai:")]
-
-# Create display names without the prefix
-OPENAI_MODELS_DISPLAY = [k.replace("openai:", "") for k in OPENAI_MODELS_FULL]
-
-# Create and launch the interface using get_app utility
-demo = get_app(
-    models=OPENAI_MODELS_FULL,  # Use the full names with prefix
-    default_model=OPENAI_MODELS_FULL[5],
-    dropdown_label="Select OpenAI Model",
-    choices=OPENAI_MODELS_DISPLAY,  # Display names without prefix
-    fill_height=True,
-    coder=True,
-)
-
-if __name__ == "__main__":
-    demo.launch()

app_openai_voice.py

@@ -1,23 +0,0 @@
-import os
-
-import openai_gradio
-
-from utils import get_app
-
-demo = get_app(
-    models=[
-        "gpt-4o-realtime-preview",
-        "gpt-4o-realtime-preview-2024-12-17",
-        "gpt-4o-realtime-preview-2024-10-01",
-        "gpt-4o-mini-realtime-preview",
-        "gpt-4o-mini-realtime-preview-2024-12-17",
-    ],
-    default_model="gpt-4o-mini-realtime-preview-2024-12-17",
-    src=openai_gradio.registry,
-    accept_token=not os.getenv("OPENAI_API_KEY"),
-    twilio_sid=os.getenv("TWILIO_SID_OPENAI"),
-    twilio_token=os.getenv("TWILIO_AUTH_OPENAI"),
-)
-
-if __name__ == "__main__":
-    demo.launch()

app_paligemma.py

@@ -1,78 +0,0 @@
-import gradio as gr
-from gradio_client import Client, handle_file
-
-MODELS = {"Paligemma-10B": "akhaliq/paligemma2-10b-ft-docci-448"}
-
-
-def create_chat_fn(client, system_prompt, temperature, max_tokens, top_k, rep_penalty, top_p):
-    def chat(message, history):
-        text = message.get("text", "")
-        files = message.get("files", [])
-        processed_files = [handle_file(f) for f in files]
-
-        response = client.predict(
-            message={"text": text, "files": processed_files},
-            system_prompt=system_prompt,
-            temperature=temperature,
-            max_new_tokens=max_tokens,
-            top_k=top_k,
-            repetition_penalty=rep_penalty,
-            top_p=top_p,
-            api_name="/chat",
-        )
-        return response
-
-    return chat
-
-
-def set_client_for_session(model_name, request: gr.Request):
-    headers = {}
-    if request and hasattr(request, "headers"):
-        x_ip_token = request.headers.get("x-ip-token")
-        if x_ip_token:
-            headers["X-IP-Token"] = x_ip_token
-
-    return Client(MODELS[model_name], headers=headers)
-
-
-def safe_chat_fn(message, history, client, system_prompt, temperature, max_tokens, top_k, rep_penalty, top_p):
-    if client is None:
-        return "Error: Client not initialized. Please refresh the page."
-    try:
-        return create_chat_fn(client, system_prompt, temperature, max_tokens, top_k, rep_penalty, top_p)(
-            message, history
-        )
-    except Exception as e:
-        print(f"Error during chat: {e!s}")
-        return f"Error during chat: {e!s}"
-
-
-with gr.Blocks() as demo:
-    client = gr.State()
-
-    with gr.Accordion("Advanced Settings", open=False):
-        system_prompt = gr.Textbox(value="You are a helpful AI assistant.", label="System Prompt")
-        with gr.Row():
-            temperature = gr.Slider(minimum=0.0, maximum=2.0, value=0.7, label="Temperature")
-            top_p = gr.Slider(minimum=0.0, maximum=1.0, value=0.95, label="Top P")
-        with gr.Row():
-            top_k = gr.Slider(minimum=1, maximum=100, value=40, step=1, label="Top K")
-            rep_penalty = gr.Slider(minimum=1.0, maximum=2.0, value=1.1, label="Repetition Penalty")
-        max_tokens = gr.Slider(minimum=64, maximum=4096, value=1024, step=64, label="Max Tokens")
-
-    chat_interface = gr.ChatInterface(
-        fn=safe_chat_fn,
-        additional_inputs=[client, system_prompt, temperature, max_tokens, top_k, rep_penalty, top_p],
-        multimodal=True,
-    )
-
-    # Initialize client on page load with default model
-    demo.load(fn=set_client_for_session, inputs=[gr.State("Paligemma-10B")], outputs=[client])  # Using default model
-
-# Move the API access check here, after demo is defined
-if hasattr(demo, "fns"):
-    for fn in demo.fns.values():
-        fn.api_name = False
-
-if __name__ == "__main__":
-    demo.launch()

app_playai.py

@@ -1,10 +1,7 @@
 import gradio as gr
 import playai_gradio
 
-demo = gr.load(
-    name="PlayDialog",
+demo =gr.load(
+    name='PlayDialog',
     src=playai_gradio.registry,
-)
-
-for fn in demo.fns.values():
-    fn.api_name = False
+)

app_qwen.py

@@ -16,9 +16,8 @@ demo = get_app(
         "qwen1.5-14b-chat",
         "qwen1.5-7b-chat",
         "qwq-32b-preview",
-        "qvq-72b-preview",
     ],
-    default_model="qvq-72b-preview",
+    default_model="qwq-32b-preview",
     src=dashscope_gradio.registry,
     accept_token=not os.getenv("DASHSCOPE_API_KEY"),
 )

app_sailor.py

@@ -1,9 +0,0 @@
-import gradio as gr
-import spaces
-import transformers_gradio
-
-demo = gr.load(name="sail/Sailor2-20B-Chat", src=transformers_gradio.registry)
-demo.fn = spaces.GPU()(demo.fn)
-
-for fn in demo.fns.values():
-    fn.api_name = False

app_sambanova.py

@@ -13,12 +13,8 @@ demo = get_app(
         "Meta-Llama-3.1-8B-Instruct",
         "Meta-Llama-3.1-70B-Instruct",
         "Meta-Llama-3.1-405B-Instruct",
-        "Qwen2.5-72B-Instruct",
-        "Qwen2.5-Coder-32B-Instruct",
-        "Meta-Llama-3.3-70B-Instruct",
-        "QwQ-32B-Preview",
     ],
-    default_model="QwQ-32B-Preview",
+    default_model="Llama-3.2-90B-Vision-Instruct",
     src=sambanova_gradio.registry,
     accept_token=not os.getenv("SAMBANOVA_API_KEY"),
     multimodal=True,

app_showui.py

@@ -1,10 +0,0 @@
-import gradio as gr
-
-# Load the Gradio space
-demo = gr.load(name="showlab/ShowUI", src="spaces")
-
-
-# Disable API access for all functions
-if hasattr(demo, "fns"):
-    for fn in demo.fns.values():
-        fn.api_name = False

app_smolagents.py

@@ -1,19 +0,0 @@
-import ai_gradio
-
-from utils_ai_gradio import get_app
-
-SMOLAGENTS_MODELS_FULL = [k for k in ai_gradio.registry.keys() if k.startswith("smolagents:")]
-
-
-SMOLAGENTS_MODELS_DISPLAY = [k.replace("smolagents:", "") for k in SMOLAGENTS_MODELS_FULL]
-
-demo = get_app(
-    models=SMOLAGENTS_MODELS_FULL,  # Use the full names with prefix
-    default_model=SMOLAGENTS_MODELS_FULL[-1],
-    dropdown_label="Select SmolAgents Model",
-    choices=SMOLAGENTS_MODELS_DISPLAY,  # Display names without prefix
-    fill_height=True,
-)
-
-if __name__ == "__main__":
-    demo.launch()

app_together.py

@@ -40,9 +40,8 @@ demo = get_app(
         "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
         "togethercomputer/StripedHyena-Nous-7B",
         "upstage/SOLAR-10.7B-Instruct-v1.0",
-        "meta-llama/Llama-3.3-70B-Instruct-Turbo",
     ],
-    default_model="meta-llama/Llama-3.3-70B-Instruct-Turbo",
+    default_model="meta-llama/Llama-3.2-11B-Vision-Instruct-Turbo",
     src=together_gradio.registry,
     accept_token=not os.getenv("TOGETHER_API_KEY"),
     multimodal=True,

app_transformers.py

@@ -1,11 +0,0 @@
-import gradio as gr
-
-demo = gr.load(name="akhaliq/phi-4", src="spaces")
-
-# Disable API access for all functions
-if hasattr(demo, "fns"):
-    for fn in demo.fns.values():
-        fn.api_name = False
-
-if __name__ == "__main__":
-    demo.launch()

app_trellis.py

@@ -1,10 +0,0 @@
-import gradio as gr
-
-# Load the Gradio space
-demo = gr.load(name="JeffreyXiang/TRELLIS", src="spaces")
-
-
-# Disable API access for all functions
-if hasattr(demo, "fns"):
-    for fn in demo.fns.values():
-        fn.api_name = False

app_xai.py

@@ -8,10 +8,8 @@ demo = get_app(
     models=[
         "grok-beta",
         "grok-vision-beta",
-        "grok-2-vision-1212",
-        "grok-2-1212",
     ],
-    default_model="grok-2-vision-1212",
+    default_model="grok-vision-beta",
     src=xai_gradio.registry,
     accept_token=not os.getenv("XAI_API_KEY"),
 )

pre-requirements.txt

@@ -0,0 +1 @@
+git+https://github.com/AK391/transformers-gradio.git

pyproject.toml

@@ -10,35 +10,20 @@ dependencies = [
     "dashscope-gradio",
     "fal-gradio",
     "fireworks-gradio",
-    "gemini-gradio>=0.0.3",
-    "gradio-webrtc>=0.0.28",
-    "gradio>=5.12.0",
+    "gemini-gradio>=0.0.1",
+    "gradio>=5.7.0",
     "groq-gradio>=0.0.2",
-    "hyperbolic-gradio>=0.0.5",
-    "mistral-gradio",
+    "hyperbolic-gradio>=0.0.4",
+    "mistral-gradio>=0.0.2",
     "nvidia-gradio",
-    "openai-gradio>=0.0.6",
+    "openai-gradio>=0.0.4",
     "perplexity-gradio>=0.0.1",
-    "python-dotenv>=1.0.1",
     "replicate-gradio",
     "sambanova-gradio>=0.1.9",
+    "spaces>=0.30.4",
     "together-gradio>=0.0.1",
-    "websockets>=14.1",
+    "torch==2.4.0",
     "xai-gradio>=0.0.2",
-    "numba>=0.60.0",
-    "llvmlite>=0.43.0",
-    "librosa>=0.10.2.post1",
-    "twilio>=9.4.2",
-    "playai-gradio",
-    "lumaai-gradio",
-    "cohere-gradio",
-    "crewai>=0.95.0",
-    "instructor>=1.7.2",
-    "crewai-tools>=0.25.8",
-    "langchain>=0.3.14",
-    "chromadb>=0.5.23",
-    "openai>=1.55.0",
-    "ai-gradio[crewai,deepseek,gemini,groq,hyperbolic,openai,smolagents,transformers, langchain, mistral,minimax,nvidia]>=0.2.25",
 ]
 
 [tool.uv.sources]
@@ -49,29 +34,62 @@ nvidia-gradio = { git = "https://github.com/AK391/nvidia-gradio.git" }
 dashscope-gradio = { git = "https://github.com/AK391/dashscope-gradio.git" }
 fal-gradio = { git = "https://github.com/AK391/fal-gradio.git" }
 replicate-gradio = { git = "https://github.com/AK391/replicate-gradio.git" }
-mistral-gradio = { git = "https://github.com/AK391/mistral-gradio.git" }
-playai-gradio = { git = "https://github.com/AK391/playai-gradio.git" }
-lumaai-gradio = { git = "https://github.com/AK391/lumaai-gradio.git" }
-cohere-gradio = { git = "https://github.com/AK391/cohere-gradio.git" }
 
 [tool.ruff]
+# Enable pycodestyle (`E`) and Pyflakes (`F`) codes by default.
+select = ["E", "F"]
+ignore = ["E501"] # line too long (black is taking care of this)
 line-length = 119
-
-[tool.ruff.lint]
-select = [
+fixable = [
+    "A",
+    "B",
+    "C",
+    "D",
     "E",
     "F",
-    #"I",
+    "G",
+    "I",
     "N",
+    "Q",
     "S",
     "T",
-    "UP",
     "W",
+    "ANN",
+    "ARG",
+    "BLE",
+    "COM",
+    "DJ",
+    "DTZ",
+    "EM",
+    "ERA",
+    "EXE",
+    "FBT",
+    "ICN",
+    "INP",
+    "ISC",
+    "NPY",
+    "PD",
+    "PGH",
+    "PIE",
+    "PL",
+    "PT",
+    "PTH",
+    "PYI",
+    "RET",
+    "RSE",
+    "RUF",
+    "SIM",
+    "SLF",
+    "TCH",
+    "TID",
+    "TRY",
+    "UP",
+    "YTT",
 ]
-ignore = ["T201"]
-unfixable = [
-    "F401", # unused-import
-]
 
-[tool.ruff.format]
-docstring-code-format = true
+[tool.isort]
+profile = "black"
+line_length = 119
+
+[tool.black]
+line-length = 119