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Runtime error
Runtime error
Update app.py
Browse files
app.py
CHANGED
@@ -7,7 +7,7 @@ from threading import Timer
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HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN")
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def get_available_free(use_cache = False):
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if use_cache:
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if os.path.exists("data.csv"):
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print("Loading data from file...")
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return pd.read_csv("data.csv").to_dict(orient='list')
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models_dict = InferenceClient(token=HUGGINGFACE_TOKEN).list_deployed_models("text-generation-inference")
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@@ -30,7 +30,7 @@ def get_available_free(use_cache = False):
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vision_available = True
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pro_sub = False
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try:
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InferenceClient(m, timeout=
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text_available = True
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except Exception as e:
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print(e)
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@@ -40,10 +40,10 @@ def get_available_free(use_cache = False):
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print("Rate Limited!!")
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if os.path.exists("data.csv"):
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print("Loading data from file...")
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return pd.read_csv("data.csv").to_dict(orient='list')
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return []
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try:
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InferenceClient(m, timeout=
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chat_available = True
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except Exception as e:
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print(e)
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@@ -60,7 +60,7 @@ def get_available_free(use_cache = False):
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models_conclusion["Chat Completion"].append("---" if (pro_sub or (not chat_available and not text_available)) else ("β" if chat_available else "β"))
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models_conclusion["Text Completion"].append("---" if (pro_sub or (not chat_available and not text_available)) else ("β" if text_available else "β"))
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models_conclusion["Vision"].append("β" if vision_available else "β")
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pd.DataFrame(models_conclusion).to_csv("data.csv", index=False)
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return models_conclusion
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def update_data(use_cache = False):
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HUGGINGFACE_TOKEN = os.environ.get("HUGGINGFACE_TOKEN")
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def get_available_free(use_cache = False):
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if use_cache:
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if os.path.exists("./data.csv"):
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print("Loading data from file...")
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return pd.read_csv("data.csv").to_dict(orient='list')
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models_dict = InferenceClient(token=HUGGINGFACE_TOKEN).list_deployed_models("text-generation-inference")
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vision_available = True
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pro_sub = False
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try:
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InferenceClient(m, timeout=120, token=HUGGINGFACE_TOKEN).text_generation("Hi.", max_new_tokens=1)
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text_available = True
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except Exception as e:
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print(e)
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print("Rate Limited!!")
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if os.path.exists("data.csv"):
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print("Loading data from file...")
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return pd.read_csv("./data.csv").to_dict(orient='list')
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return []
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try:
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InferenceClient(m, timeout=120).chat_completion(messages=[{'role': 'user', 'content': 'Hi.'}], max_tokens=1)
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chat_available = True
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except Exception as e:
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print(e)
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models_conclusion["Chat Completion"].append("---" if (pro_sub or (not chat_available and not text_available)) else ("β" if chat_available else "β"))
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models_conclusion["Text Completion"].append("---" if (pro_sub or (not chat_available and not text_available)) else ("β" if text_available else "β"))
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models_conclusion["Vision"].append("β" if vision_available else "β")
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pd.DataFrame(models_conclusion).to_csv("./data.csv", index=False)
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return models_conclusion
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def update_data(use_cache = False):
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