Initial commit

.bolt/config.json

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+{
+  "template": "node"
+}

.gitignore

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+node_modules

Dockerfile

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+FROM python:3.9-slim
+
+WORKDIR /code
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from fastapi import FastAPI
+from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering
+from pydantic import BaseModel
+import torch
+
+app = FastAPI()
+
+# Load model and processor
+processor = AutoProcessor.from_pretrained("microsoft/OmniParser")
+model = AutoModelForVisualQuestionAnswering.from_pretrained("microsoft/OmniParser")
+
+class Query(BaseModel):
+    image_url: str
+    question: str
+
+@app.post("/predict")
+async def predict(query: Query):
+    # Process the image and question
+    inputs = processor(images=query.image_url, text=query.question, return_tensors="pt")
+    outputs = model(**inputs)
+    
+    # Get the predicted answer
+    predicted_answer = processor.decode(outputs.logits.argmax(-1)[0], skip_special_tokens=True)
+    
+    return {"answer": predicted_answer}
+
+@app.get("/")
+async def root():
+    return {"message": "OmniParser API is running. Use /predict endpoint for predictions."}

index.js

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+// run `node index.js` in the terminal
+
+console.log(`Hello Node.js v${process.versions.node}!`);

package-lock.json

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+{
+  "name": "node-starter",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "node-starter"
+    }
+  }
+}

package.json

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+{
+  "name": "node-starter",
+  "private": true,
+  "scripts": {
+    "test": "echo \"Error: no test specified\" && exit 1"
+  }
+}

requirements.txt

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+fastapi==0.68.0
+uvicorn==0.15.0
+torch==2.0.0
+transformers
+pydantic
+python-multipart