updates

test-ollama/test.py

@@ -0,0 +1,55 @@
+import json
+import ollama
+import glob
+
+# Directory containing training data files
+training_data_path = 'fine-tuning/data/*1.json'
+
+# Load training data from multiple JSON files
+training_data = []
+for filepath in glob.glob(training_data_path):
+    with open(filepath, 'r') as file:
+        data = json.load(file)
+        training_data.extend(data)  # Assuming each file contains a list of Q&A pairs
+
+# Format the training data as a JSON string
+training_data_json = json.dumps(training_data, indent=2)
+
+# Define the modelfile content with the loaded training data
+modelfile_content = f"""
+FROM llama3.2
+
+# set the temperature to 1 [higher is more creative, lower is more coherent]
+PARAMETER temperature 1
+
+# set the system message
+SYSTEM \"\"\"
+You are an agriculutural assistant for farmers in India. Form the answer based on the following mentioned data otherwise give a generic answer:
+{training_data_json}
+\"\"\"
+"""
+
+print(modelfile_content)
+
+ollama.create(model='paani', modelfile=modelfile_content)
+
+
+# Initialize the chatbot
+while True:
+    # Prompt the user for input
+    user_input = input("\nYou: ")
+
+    # Check if the user wants to exit
+    if user_input.lower() in ["exit", "quit"]:
+        print("Exiting the chatbot. Goodbye!")
+        break
+
+    # Get and print the chatbot response
+    stream = ollama.chat(
+        model='paani',
+        messages=[{'role': 'user', 'content': user_input}],
+        stream=True,
+    )
+
+    for chunk in stream:
+        print(chunk['message']['content'], end='', flush=True)