The initial commit

.gitignore

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+history/
+main.py
+pageHistory.py

README.md

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+# Chat with Ollama
+
+
+## 1. Introduction
+This is a simple chatbot application that allows you to chat with Ollama.
+
+<img src="assets/ollama.png" alt="drawing" width="100"/>
+
+Ollama is a lightweight, open-source, and easy-to-use chatbot framework. 
+Ollama supports a list of models available on [ollama.com/library](https://ollama.com/library 'ollama model library')
+
+<img src="assets/streamlit.png" alt="drawing" width="150"/>
+
+Streamlit is a Python library for building web applications.
+The website can be found as [streamlit.io](https://streamlit.io 'streamlit website')
+
+
+
+
+
+
+## 2. Usage
+### Prerequisites
+
+Install Ollama from [ollama.ai](https://ollama.ai 'ollama website'), and open at background.
+
+### Run a chat page
+1. Install the required packages
+   ```
+   pip install ollama streamlit
+   ```
+2. Run the page for chat
+   ```
+   streamlit run pageOllama.py
+   ```
+3. Chat with Ollama
+
+
+### Additions
+Can add the pre-defined prompt within 'promptTemp.md' file for instructing the AI model.

pageOllama.py

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+# %%
+import ollama
+import streamlit as st
+import os
+
+###########################################
+#            Helper functions           #
+###########################################
+
+def get_ollama_model(model_name):
+    try:
+        # First check if Ollam service is running
+        response = ollama.list()
+        if not response or 'models' not in response:
+            st.warning("No models found in Ollama response")
+
+        models = [model.model.split(':')[0] for model in response.models]
+        if not models:
+            st.warning("No models installed. Please install models in the Settings tab")
+        return models
+    except ConnectionRefusedError:
+        st.warning("Can not connect to Ollama. Please ensure Ollama is running on your system")
+        return []
+    except Exception as e:
+        st.error(f"An error occurred: {str(e)}")
+        st.info("Try running 'ollama serve' in your terminal")
+        return []
+
+def get_prompt():
+    with open("promptTemp.md", "r") as file:
+        return file.read()
+
+
+###########################################
+#            Streamlit page               #
+###########################################
+
+def page_chat():
+    st.title("Chat with Ollama")
+    st.image("assets/ollama.png", width=200)
+    model = st.selectbox("Select a model", 
+                              get_ollama_model(""),
+                              index = 0,
+                              help = "Select the available model to use for chat")
+    # Initialize chat history in session state if it doesn't exist
+    # --> The system prompt is added to the chat history
+    #     The prompt is defined in the Prompts.md file
+    #     The prompt is added as the first message in the chat history
+    #     The chat history is stored in the session state
+    #     The chat history is cleared when the Clear Chat button is clicked
+
+    if "messages" not in st.session_state:
+        st.session_state.messages = []
+        # Add the pre-defined promt as the first message
+        st.session_state.messages.append({"role":"system", "content":get_prompt()})
+
+    # Add clear chat button
+    if st.button("Clear Chat"):
+        st.session_state.messages = []
+        # Re-add the pre-defined prompt after clearing the chat history
+        st.session_state.messages.append({"role":"system", "content":get_prompt()})
+        st.rerun()
+
+    # Display the chat messages
+    for message in st.session_state.messages:
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"])
+
+    # Accept user input
+    if prompt:= st.chat_input("what can I help you with?"):
+        # Display the user message in the chat message container
+        with st.chat_message("user"):
+            st.markdown(prompt)
+        # Add user message to the caht history
+        st.session_state.messages.append({"role":"user", "content":prompt})
+
+        try:
+            with st.chat_message("assistant"):
+                message_placeholder = st.empty()
+                response =ollama.chat(
+                    model= model, # Use selected model
+                    messages = [{"role": m["role"], "content": m["content"]}
+                                 for m in st.session_state.messages],
+                                 stream=True,
+                )
+                full_response = ""
+                for chunk in response: # Assuming response is an iterable of message chunks
+                    full_response += chunk['message']['content']
+                    message_placeholder.markdown(full_response)
+
+            # Add assistant response to the chat history
+            st.session_state.messages.append({"role":"assistant", "content":full_response})
+
+        except Exception as e:
+            st.error(f"An error occurred: {str(e)}")
+            st.info("make sure Ollama is running locally with the required model.")
+
+
+if __name__ == "__main__":
+    page_chat()
+
+
+
+