Add all project files

.gitignore

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+# Exclude .venv directory
+.venv/
+# Exclude files in pages folder
+pages/*
+.DS_Store

app.py

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+from pydantic import BaseModel, Field
+import subprocess
+
+import streamlit as st
+
+import ollama
+from ollama import ChatResponse
+
+MODEL = '<model>' # Type "ollama list" in terminal to see available models
+
+class PythonScript(BaseModel):
+    script: str = Field(description="The Python script to be executed.")
+    comments: str = Field(description="Any additional notes or comments about the script.")
+    external_libraries: list[str] = Field(description="List of external libraries used in the script.")
+
+
+class LLM:
+    def __init__(self, system_message: str, model: str = MODEL):
+        self.system_message = system_message
+        self.messages = [
+            {"role": "system", "content": system_message}
+        ]
+        self.model = model
+
+    def generate(self, message: str, format: str) -> ChatResponse:
+        """
+        Generate a chat response using the Ollama model.
+
+        This method appends the user message to the conversation history, sends it to the
+        Ollama chat model, and appends the assistant's response back to the history.
+
+        Args:
+            message (str): The user's input message to send to the chat model.
+            format (str): The desired format for the response output.
+
+        Returns:
+            ChatResponse: The complete response object from the Ollama chat model,
+                         containing the assistant's reply and metadata.
+
+        Note:
+            The method uses a low temperature (0.1) for more deterministic responses
+            and automatically maintains conversation history in self.messages.
+        """
+        self.messages.append({"role": "user", "content": message})
+
+        response: ChatResponse = ollama.chat(
+            model=self.model,
+            messages=self.messages,
+            format=format,
+            options={'temperature': 0.1}
+        )
+        self.messages.append({"role": "assistant", "content": response.message.content})
+        return response
+
+
+# Initialize chat history in session state
+if 'chat_history' not in st.session_state:
+    st.session_state.chat_history = []
+if 'current_code' not in st.session_state:
+    st.session_state.current_code = None
+if 'current_comments' not in st.session_state:
+    st.session_state.current_comments = None
+if 'current_libraries' not in st.session_state:
+    st.session_state.current_libraries = []
+
+st.title("Python Script Generator Chat")
+
+# Display chat history
+for i, (role, message) in enumerate(st.session_state.chat_history):
+    if role == 'user':
+        st.chat_message("user").write(message)
+    else:
+        st.chat_message("assistant").write(message)
+
+user_input = st.chat_input("Describe what you want help doing or give feedback on the script")
+
+if user_input:
+    st.session_state.chat_history.append(('user', user_input))
+    st.chat_message("user").write(user_input)
+    # Build system message and conversation context
+    system_message = """
+    You are a Python coder. Your task is to construct a Python script based on the user's input and feedback.
+    The script should be in a form of a Streamlit app, so make use of the Streamlit library for user interface elements. 
+    Example: If a user want to upload a file, user st.file_uploader. If the user wants to input text, use st.text_input. Etc.
+    **IMPORTANT! The user can not change anything in the script, only interact with it via Streamlit UI elements.** 
+    Therefore, don't user placeholders like "your_file" or "your_text". Instead, use Streamlit UI elements to get the input from the user.
+    If the user gives feedback, improve the previous script accordingly.
+    """
+    # Build conversation context
+    conversation = "\n".join([
+        f"User: {msg}" if role == 'user' else f"Assistant: {msg}"
+        for role, msg in st.session_state.chat_history
+    ])
+    llm = LLM(system_message=system_message)
+    response = llm.generate(conversation, format=PythonScript.model_json_schema())
+    answer = PythonScript.model_validate_json(response.message.content)
+    code = answer.script
+    comments = answer.comments
+    libraries = answer.external_libraries
+    st.session_state.current_code = code
+    st.session_state.current_comments = comments
+    st.session_state.current_libraries = libraries
+    st.session_state.chat_history.append(('assistant', comments + "\n\n" + code))
+    st.chat_message("assistant").write(comments)
+    st.code(code, language='python')
+    for library in libraries:
+        try:
+            __import__(library)
+        except ImportError:
+            st.write(f"Installing {library}...")
+            subprocess.check_call(["pip", "install", library])
+    with open("pages/user_app.py", "w") as f:
+        f.write(code)
+
+elif st.session_state.current_code:
+    st.chat_message("assistant").write(st.session_state.current_comments)
+    with st.expander("View the code"):
+        st.code(st.session_state.current_code, language='python')

requirements.txt

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+altair==5.5.0
+annotated-types==0.7.0
+anyio==4.9.0
+attrs==25.3.0
+blinker==1.9.0
+cachetools==5.5.2
+certifi==2025.4.26
+charset-normalizer==3.4.2
+click==8.2.1
+exceptiongroup==1.3.0
+gitdb==4.0.12
+GitPython==3.1.44
+h11==0.16.0
+httpcore==1.0.9
+httpx==0.28.1
+idna==3.10
+Jinja2==3.1.6
+jsonschema==4.24.0
+jsonschema-specifications==2025.4.1
+MarkupSafe==3.0.2
+narwhals==1.41.1
+numpy==2.2.6
+ollama==0.5.1
+packaging==24.2
+pandas==2.3.0
+pillow==11.2.1
+protobuf==6.31.1
+pyarrow==20.0.0
+pydantic==2.11.5
+pydantic_core==2.33.2
+pydeck==0.9.1
+python-dateutil==2.9.0.post0
+pytz==2025.2
+referencing==0.36.2
+requests==2.32.3
+rpds-py==0.25.1
+six==1.17.0
+smmap==5.0.2
+sniffio==1.3.1
+streamlit==1.45.1
+tenacity==9.1.2
+toml==0.10.2
+tornado==6.5.1
+typing-inspection==0.4.1
+typing_extensions==4.14.0
+tzdata==2025.2
+urllib3==2.4.0