fix: use huggingface_hub 0.26-0.x with explicit router URL

app.py

@@ -130,12 +130,12 @@ def call_text_model(state: dict[str, Any], action: str, dice: dict[str, Any], tr
     hf_token = os.getenv("HF_TOKEN", "").strip()
     if hf_token:
         try:
-            client = InferenceClient(provider="hf-inference", api_key=hf_token)
+            client = InferenceClient(model="Qwen/Qwen2.5-7B-Instruct", token=hf_token, api_url="https://router.huggingface.co/hf-inference")
             messages = [
                 {"role": "system", "content": build_system_prompt()},
                 {"role": "user", "content": build_user_prompt(state, action, dice, trigger_gaslight)},
             ]
-            completion = client.chat_completion(model="Qwen/Qwen2.5-7B-Instruct", messages=messages, max_tokens=450, temperature=0.9)
+            completion = client.chat_completion(messages=messages, max_tokens=450, temperature=0.9)
             raw_text = completion.choices[0].message.content
             try:
                 return extract_json(raw_text)
@@ -331,8 +331,8 @@ def generate_image(prompt: str, state: dict[str, Any], dice_total: int) -> str:
     hf_token = os.getenv("HF_TOKEN", "").strip()
     if hf_token:
         try:
-            client = InferenceClient(provider="hf-inference", api_key=hf_token)
-            image = client.text_to_image(prompt, model="black-forest-labs/FLUX.1-schnell")
+            client = InferenceClient(model="black-forest-labs/FLUX.1-schnell", token=hf_token, api_url="https://router.huggingface.co/hf-inference")
+            image = client.text_to_image(prompt)
             buffered = io.BytesIO()
             image.save(buffered, format="PNG")
             img_str = base64.b64encode(buffered.getvalue()).decode("utf-8")

requirements.txt

@@ -1,6 +1,6 @@
 gradio==4.44.1
 starlette<1.0.0
 jinja2<3.1.5
-huggingface_hub>=1.0.0
+huggingface_hub>=0.26.0,<1.0.0
 requests>=2.32.0