Update main.py

main.py

@@ -1,37 +1,37 @@
-from flask import Flask, request, jsonify
-from langchain_community.llms import LlamaCpp
-import os 
-app = Flask(__name__)
-
-n_gpu_layers = 0
-n_batch = 1024
-
-
-llm = LlamaCpp(
-    model_path="Phi-3-mini-4k-instruct-q4.gguf",  # path to GGUF file
-    temperature=0.1,
-    n_gpu_layers=n_gpu_layers,
-    n_batch=n_batch,
-    verbose=True,
-    n_ctx=4096
-)
-file_size = os.stat('Phi-3-mini-4k-instruct-q4.gguf')
-print("model size ====> :", file_size.st_size, "bytes")
-
-
-@app.route('/', methods=['POST'])
-def get_skills():
-    cv_body = request.json.get('cv_body')
-
-    # Simple inference example
-    output = llm(
-        f"<|user|>\n{cv_body}<|end|>\n<|assistant|>Can you list the skills mentioned in the CV?<|end|>",
-        max_tokens=256,  # Generate up to 256 tokens
-        stop=["<|end|>"], 
-        echo=True,  # Whether to echo the prompt
-    )
-
-    return jsonify({'skills': output})
-
-if __name__ == '__main__':
+from flask import Flask, request, jsonify
+from langchain_community.llms import LlamaCpp
+import os 
+app = Flask(__name__)
+
+n_gpu_layers = 0
+n_batch = 1024
+
+
+llm = LlamaCpp(
+    model_path="Phi-3-mini-4k-instruct-q4.gguf",  # path to GGUF file
+    temperature=0.1,
+    n_gpu_layers=n_gpu_layers,
+    n_batch=n_batch,
+    verbose=True,
+    n_ctx=4096
+)
+file_size = os.stat('Phi-3-mini-4k-instruct-q4.gguf')
+print("model size ====> :", file_size.st_size, "bytes")
+
+
+@app.route('/', methods=['POST'])
+def get_skills():
+    cv_body = request.json.get('cv_body')
+
+    # Simple inference example
+    output = llm(
+        f"<|user|>\n{cv_body}<|end|>\n<|assistant|>Can you list the skills mentioned in the CV?<|end|>",
+        max_tokens=256,  # Generate up to 256 tokens
+        stop=["<|end|>"], 
+        echo=True,  # Whether to echo the prompt
+    )
+
+    return jsonify({'skills': output})
+
+if __name__ == '__main__':
     app.run()