updatded

app.py

@@ -1,49 +0,0 @@
-from flask import Flask, request, jsonify
-from flask_cors import CORS
-import torch
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import logging
-import os
-
-MIN_TRANSFORMERS_VERSION = '4.25.1'
-
-# Check transformers version
-import transformers
-assert transformers.__version__ >= MIN_TRANSFORMERS_VERSION, f'Please upgrade transformers to version {MIN_TRANSFORMERS_VERSION} or higher.'
-
-# Initialize tokenizer and model from local directory
-model_dir = "./"
-tokenizer = AutoTokenizer.from_pretrained(model_dir)
-model = AutoModelForCausalLM.from_pretrained(model_dir, torch_dtype=torch.bfloat16)
-
-app = Flask(__name__)
-CORS(app)  # Enable CORS
-
-logging.basicConfig(level=logging.DEBUG)
-
-def generate_response(prompt):
-    inputs = tokenizer(prompt, return_tensors='pt').to(model.device)
-    input_length = inputs.input_ids.shape[1]
-    outputs = model.generate(
-        **inputs, max_new_tokens=128, do_sample=True, temperature=0.7, top_p=0.7, top_k=50, return_dict_in_generate=True
-    )
-    token = outputs.sequences[0, input_length:]
-    output_str = tokenizer.decode(token, skip_special_tokens=True)
-    return output_str
-
-@app.route('/chat', methods=['POST'])
-def chat():
-    logging.debug("Received a POST request")
-    data = request.json
-    logging.debug(f"Request data: {data}")
-    user_input = data.get("message", "")
-    prompt = f"<human>: {user_input}\n<bot>:"
-    response = generate_response(prompt)
-    logging.debug(f"Generated response: {response}")
-    return jsonify({"response": response})
-
-if __name__ == "__main__":
-    # Get the port from environment variable or default to 5000
-    port = int(os.getenv("PORT", 5000))
-    logging.info(f"Starting Flask app on port {port}")
-    app.run(debug=True, host="0.0.0.0", port=port)

chat-bot

@@ -0,0 +1 @@
+Subproject commit 1f613fd4bb9a83fc7f0f03e34db07691642b77f0

requirements.txt

@@ -1,4 +0,0 @@
-flask
-flask-cors
-torch
-transformers