space issue fix

Dockerfile

@@ -23,37 +23,23 @@ RUN pip install --no-cache-dir -r requirements.txt
 # Hugging Face + model tools
 RUN pip install --no-cache-dir huggingface-hub sentencepiece accelerate sacremoses
 
-# Hugging Face cache environment
-ENV HF_HOME=/models/huggingface \
-    TRANSFORMERS_CACHE=/models/huggingface \
-    HUGGINGFACE_HUB_CACHE=/models/huggingface \
-    HF_HUB_CACHE=/models/huggingface
-
-# Create cache dir with proper permissions
-RUN mkdir -p /models/huggingface && \
-    chmod -R 777 /models/huggingface && \
-    chown -R 1000:1000 /models/huggingface
-
-# Pre-download models at build time (MedBridge AI specific models)
-RUN python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='microsoft/BioGPT-Large')" \
- && python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='google/vit-base-patch16-224')" \
- && find /models/huggingface -name '*.lock' -delete
-
-# Preload tokenizers (avoid runtime delays)
-RUN python -c "from transformers import AutoTokenizer; AutoTokenizer.from_pretrained('microsoft/BioGPT-Large', use_fast=True)" \
- && python -c "from transformers import ViTFeatureExtractor; ViTFeatureExtractor.from_pretrained('google/vit-base-patch16-224')"
+# Hugging Face cache environment (using /tmp for runtime downloads)
+ENV HF_HOME=/tmp/huggingface \
+    TRANSFORMERS_CACHE=/tmp/huggingface \
+    HUGGINGFACE_HUB_CACHE=/tmp/huggingface \
+    HF_HUB_CACHE=/tmp/huggingface
+
+# Create cache dir with proper permissions (using /tmp for Hugging Face Spaces)
+RUN mkdir -p /tmp/huggingface && \
+    chmod -R 777 /tmp/huggingface
+
+# Models will be downloaded at runtime to avoid exceeding storage limit
 
 # Copy project files
 COPY . .
 
-# Fix permissions for runtime
-RUN chmod -R 777 /models/huggingface
-
 # Expose agent port
 EXPOSE 7860
 
-# Run agent as non-root for security
-USER 1000
-
 CMD ["python", "app.py"]
 

app.py

@@ -34,7 +34,7 @@ agent = Agent(
     name=AGENT_NAME,
     seed=AGENT_SEED,
     port=7860,
-    endpoint=["http://localhost:7860/submit"],
+    endpoint=["https://nexusbert-medbridge.hf.space/submit"],
 )
 
 fund_agent_if_low(agent.wallet.address())
@@ -250,11 +250,11 @@ async def handle_message(ctx: Context, sender: str, msg: ChatMessage):
                     result = analyze_medical_image(response.content)
                     response_message = create_text_chat(result)
                     await ctx.send(sender, response_message)
-                else:
+        else:
                     result = process_medical_query(item.text)
                     response_message = create_text_chat(result)
                     await ctx.send(sender, response_message)
-            except Exception as e:
+    except Exception as e:
                 error_msg = create_text_chat(
                     f"Error processing your request: {str(e)}"
                 )