init

.idea/.gitignore

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+# Default ignored files
+/shelf/
+/workspace.xml

.idea/hugging-face.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="jdk" jdkName="Python 3.13" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.13" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.13" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/hugging-face.iml" filepath="$PROJECT_DIR$/.idea/hugging-face.iml" />
+    </modules>
+  </component>
+</project>

app.py

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+from flask import Flask, request, jsonify
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+app = Flask(__name__)
+
+MODEL_NAME = "meta-llama/Llama-2-7b-chat-hf"  # Ensure you have access!
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, use_auth_token=True)
+model = AutoModelForCausalLM.from_pretrained(
+    MODEL_NAME, torch_dtype=torch.float16, device_map="auto", use_auth_token=True
+)
+
+@app.route('/generate', methods=['POST'])
+def generate():
+    user_request = request.json.get("query")
+    if not user_request:
+        return jsonify({"error": "No query provided"}), 400
+
+    mongo_query = generate_mongo_query(user_request)
+    return jsonify({"mongo_query": mongo_query})
+
+def generate_mongo_query(user_request):
+    prompt = f"Convert this request to a MongoDB query: {user_request}"
+    inputs = tokenizer(prompt, return_tensors="pt").to("cuda" if torch.cuda.is_available() else "cpu")
+    output = model.generate(**inputs, max_length=150)
+    return tokenizer.decode(output[0], skip_special_tokens=True)
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=7860)

dockerfile

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+# Use an official lightweight Python image
+FROM python:3.10
+
+# Set working directory
+WORKDIR /app
+
+# Copy files to container
+COPY app.py requirements.txt /app/
+
+# Install dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Expose port for Flask
+EXPOSE 7860
+
+# Run the Flask app
+CMD ["python", "app.py"]

requirements.txt

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+flask
+torch
+transformers
+accelerate
+sentencepiece
+huggingface_hub