initial commit

.gitignore

@@ -160,3 +160,6 @@ cython_debug/
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
+
+cursor_prompts/
+uv.lock

app.py

@@ -0,0 +1,36 @@
+import streamlit as st
+import weave
+from dotenv import load_dotenv
+
+from guardrails_genie.llm import OpenAIModel
+
+load_dotenv()
+weave.init(project_name="guardrails-genie")
+
+st.title("Echo Bot")
+
+# Initialize chat history
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+llm_model = OpenAIModel(model_name="gpt-4o-mini")
+
+# Display chat messages from history on app rerun
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# React to user input
+if prompt := st.chat_input("What is up?"):
+    # Display user message in chat message container
+    st.chat_message("user").markdown(prompt)
+    # Add user message to chat history
+    st.session_state.messages.append({"role": "user", "content": prompt})
+
+    response = llm_model.predict(prompt, messages=st.session_state.messages)
+    response = response.choices[0].message.content
+    # Display assistant response in chat message container
+    with st.chat_message("assistant"):
+        st.markdown(response)
+    # Add assistant response to chat history
+    st.session_state.messages.append({"role": "assistant", "content": response})

guardrails_genie/llm.py

@@ -0,0 +1,43 @@
+from typing import Optional, Union
+
+import weave
+from openai import OpenAI
+from openai.types.chat import ChatCompletion
+
+
+class OpenAIModel(weave.Model):
+    model_name: str
+    _openai_client: OpenAI
+
+    def __init__(self, model_name: str = "gpt-4o") -> None:
+        super().__init__(model_name=model_name)
+        self._openai_client = OpenAI()
+
+    @weave.op()
+    def create_messages(
+        self,
+        user_prompts: Union[str, list[str]],
+        system_prompt: Optional[str] = None,
+        messages: Optional[list[dict]] = None,
+    ) -> list[dict]:
+        user_prompts = [user_prompts] if isinstance(user_prompts, str) else user_prompts
+        messages = list(messages) if isinstance(messages, dict) else []
+        for user_prompt in user_prompts:
+            messages.append({"role": "user", "content": user_prompt})
+        if system_prompt is not None:
+            messages = [{"role": "system", "content": system_prompt}] + messages
+        return messages
+
+    @weave.op()
+    def predict(
+        self,
+        user_prompts: Union[str, list[str]],
+        system_prompt: Optional[str] = None,
+        messages: Optional[list[dict]] = None,
+        **kwargs,
+    ) -> ChatCompletion:
+        messages = self.create_messages(user_prompts, system_prompt, messages)
+        response = self._openai_client.chat.completions.create(
+            model=self.model_name, messages=messages, **kwargs
+        )
+        return response

pyproject.toml

@@ -0,0 +1,22 @@
+[project]
+name = "guardrails-genie"
+version = "0.0.1"
+description = ""
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+    "google-generativeai>=0.8.3",
+    "openai>=1.52.2",
+    "isort>=5.13.2",
+    "black>=24.10.0",
+    "ruff>=0.6.9",
+    "pip>=24.2",
+    "uv>=0.4.20",
+    "weave>=0.51.19",
+    "streamlit>=1.40.1",
+    "python-dotenv>=1.0.1",
+    "watchdog>=6.0.0",
+]
+
+[tool.setuptools]
+py-modules = ["guardrails_genie"]