Feature rag e2e

.cursor/rules/branch-development.mdc

@@ -0,0 +1,8 @@
+---
+description: 
+globs: 
+alwaysApply: true
+---
+You always prefer to use branch development. Before writing any code - you create a feature branch to hold those changes. 
+
+After you are done - provide instructions in a "MERGE.md" file that explains how to merge the changes back to main with both a GitHub PR route and a GitHub CLI route.

.cursor/rules/frontend-rule.mdc

@@ -10,4 +10,29 @@ alwaysApply: false
 - When asking the user for sensitive information - you must use password style text-entry boxes in the UI.
 - You should use Next.js as it works best with Vercel. 
 - This frontend will ultimately be deployed on Vercel, but it should be possible to test locally. 
-- Always provide users with a way to run the created UI once you have created it.
+- Always provide users with a way to run the created UI once you have created it.
+- The UI should mimic studio ghibli aesthetic using the following rules
+    - Design Style
+        - Use soft earth-tone colors and watercolor-like backgrounds.
+        - Use rounded corners (`border-radius: 12px+`) and soft drop shadows.
+        - Apply natural textures, paper-like backgrounds, and grain overlays.
+
+    - Typography
+        - Use fonts like 'Quicksand', 'Noto Serif JP', or 'Garamond' for a whimsical, storybook feel.
+        - Avoid modern, harsh sans-serif fonts.
+
+    - Components
+        - All buttons should look hand-drawn, with hover animations that glow or float.
+        - Inputs should be wide and softly bordered with illustrated icons.
+
+    - Layout
+        - Layouts should be centered with parchment or wooden-framed containers.
+        - Avoid sterile grids — allow white space and natural asymmetry.
+
+    - Animations
+        - Use Framer Motion for soft transitions, magical fades, and bouncy effects.
+        - Animations should mimic nature: floating, glowing, or breezy motion.
+
+    - Vibes
+        - Every page should feel like it came from a storybook or nature journal.
+        - Prioritize playfulness, calm, and natural wonder.

MERGE.md

@@ -0,0 +1,44 @@
+# How to Merge Your Feature Branch Back to Main
+
+This project uses branch-based development. Follow these steps to merge your feature branch (e.g., `feature-rag-e2e`) back to `main`.
+
+---
+
+## 1. GitHub Pull Request (Recommended)
+
+1. **Push your branch to GitHub** (if you haven't already):
+   ```bash
+   git push origin feature-rag-e2e
+   ```
+2. **Go to your repository on GitHub.**
+3. **Click "Compare & pull request"** next to your branch.
+4. **Review the changes** and add a descriptive title and summary.
+5. **Click "Create pull request".**
+6. After review, **click "Merge pull request"** to merge into `main`.
+7. (Optional) **Delete the feature branch** on GitHub after merging.
+
+---
+
+## 2. GitHub CLI (Command Line)
+
+1. **Push your branch to GitHub** (if you haven't already):
+   ```bash
+   git push origin feature-rag-e2e
+   ```
+2. **Create a pull request from the CLI:**
+   ```bash
+   gh pr create --base main --head feature-rag-e2e --fill
+   ```
+3. **Merge the pull request from the CLI:**
+   ```bash
+   gh pr merge --merge
+   ```
+4. (Optional) **Delete the local and remote feature branch:**
+   ```bash
+   git branch -d feature-rag-e2e
+   git push origin --delete feature-rag-e2e
+   ```
+
+---
+
+**Note:** Always ensure all tests pass and your branch is up to date with `main` before merging. 

README.md

@@ -178,7 +178,7 @@ Check it out 👇
 
 A big shoutout to the @AI Makerspace for all making this possible. Couldn't have done it without the incredible community there. 🤗🙏
 
-Looking forward to building with the community! 🙌✨ Here's to many more creations ahead! 🥂🎉
+Looking forward to building with the community! 🙌✨ Here's to many more creations ahead! 🥂🎉
 
 Who else is diving into the world of AI? Let's connect! 🌐💡
 

aimakerspace/openai_utils/chatmodel.py

@@ -0,0 +1,45 @@
+from openai import OpenAI, AsyncOpenAI
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+
+class ChatOpenAI:
+    def __init__(self, model_name: str = "gpt-4o-mini", api_key: str = None):
+        self.model_name = model_name
+        self.openai_api_key = api_key or os.getenv("OPENAI_API_KEY")
+        if self.openai_api_key is None:
+            raise ValueError("OPENAI_API_KEY is not set")
+
+    def run(self, messages, text_only: bool = True, **kwargs):
+        if not isinstance(messages, list):
+            raise ValueError("messages must be a list")
+
+        client = OpenAI(api_key=self.openai_api_key)
+        response = client.chat.completions.create(
+            model=self.model_name, messages=messages, **kwargs
+        )
+
+        if text_only:
+            return response.choices[0].message.content
+
+        return response
+
+    async def astream(self, messages, **kwargs):
+        if not isinstance(messages, list):
+            raise ValueError("messages must be a list")
+
+        client = AsyncOpenAI(api_key=self.openai_api_key)
+
+        stream = await client.chat.completions.create(
+            model=self.model_name,
+            messages=messages,
+            stream=True,
+            **kwargs
+        )
+
+        async for chunk in stream:
+            content = chunk.choices[0].delta.content
+            if content is not None:
+                yield content

aimakerspace/openai_utils/embedding.py

@@ -0,0 +1,57 @@
+from dotenv import load_dotenv
+from openai import AsyncOpenAI, OpenAI
+import openai
+from typing import List
+import os
+import asyncio
+
+
+class EmbeddingModel:
+    def __init__(self, embeddings_model_name: str = "text-embedding-3-small", api_key: str = None):
+        load_dotenv()
+        self.openai_api_key = api_key or os.getenv("OPENAI_API_KEY")
+        if self.openai_api_key is None:
+            raise ValueError(
+                "OPENAI_API_KEY environment variable is not set. Please set it to your OpenAI API key."
+            )
+        self.async_client = AsyncOpenAI(api_key=self.openai_api_key)
+        self.client = OpenAI(api_key=self.openai_api_key)
+        self.embeddings_model_name = embeddings_model_name
+
+    async def async_get_embeddings(self, list_of_text: List[str]) -> List[List[float]]:
+        embedding_response = await self.async_client.embeddings.create(
+            input=list_of_text, model=self.embeddings_model_name
+        )
+
+        return [embeddings.embedding for embeddings in embedding_response.data]
+
+    async def async_get_embedding(self, text: str) -> List[float]:
+        embedding = await self.async_client.embeddings.create(
+            input=text, model=self.embeddings_model_name
+        )
+
+        return embedding.data[0].embedding
+
+    def get_embeddings(self, list_of_text: List[str]) -> List[List[float]]:
+        embedding_response = self.client.embeddings.create(
+            input=list_of_text, model=self.embeddings_model_name
+        )
+
+        return [embeddings.embedding for embeddings in embedding_response.data]
+
+    def get_embedding(self, text: str) -> List[float]:
+        embedding = self.client.embeddings.create(
+            input=text, model=self.embeddings_model_name
+        )
+
+        return embedding.data[0].embedding
+
+
+if __name__ == "__main__":
+    embedding_model = EmbeddingModel()
+    print(asyncio.run(embedding_model.async_get_embedding("Hello, world!")))
+    print(
+        asyncio.run(
+            embedding_model.async_get_embeddings(["Hello, world!", "Goodbye, world!"])
+        )
+    )

aimakerspace/openai_utils/prompts.py

@@ -0,0 +1,78 @@
+import re
+
+
+class BasePrompt:
+    def __init__(self, prompt):
+        """
+        Initializes the BasePrompt object with a prompt template.
+
+        :param prompt: A string that can contain placeholders within curly braces
+        """
+        self.prompt = prompt
+        self._pattern = re.compile(r"\{([^}]+)\}")
+
+    def format_prompt(self, **kwargs):
+        """
+        Formats the prompt string using the keyword arguments provided.
+
+        :param kwargs: The values to substitute into the prompt string
+        :return: The formatted prompt string
+        """
+        matches = self._pattern.findall(self.prompt)
+        return self.prompt.format(**{match: kwargs.get(match, "") for match in matches})
+
+    def get_input_variables(self):
+        """
+        Gets the list of input variable names from the prompt string.
+
+        :return: List of input variable names
+        """
+        return self._pattern.findall(self.prompt)
+
+
+class RolePrompt(BasePrompt):
+    def __init__(self, prompt, role: str):
+        """
+        Initializes the RolePrompt object with a prompt template and a role.
+
+        :param prompt: A string that can contain placeholders within curly braces
+        :param role: The role for the message ('system', 'user', or 'assistant')
+        """
+        super().__init__(prompt)
+        self.role = role
+
+    def create_message(self, format=True, **kwargs):
+        """
+        Creates a message dictionary with a role and a formatted message.
+
+        :param kwargs: The values to substitute into the prompt string
+        :return: Dictionary containing the role and the formatted message
+        """
+        if format:
+            return {"role": self.role, "content": self.format_prompt(**kwargs)}
+
+        return {"role": self.role, "content": self.prompt}
+
+
+class SystemRolePrompt(RolePrompt):
+    def __init__(self, prompt: str):
+        super().__init__(prompt, "system")
+
+
+class UserRolePrompt(RolePrompt):
+    def __init__(self, prompt: str):
+        super().__init__(prompt, "user")
+
+
+class AssistantRolePrompt(RolePrompt):
+    def __init__(self, prompt: str):
+        super().__init__(prompt, "assistant")
+
+
+if __name__ == "__main__":
+    prompt = BasePrompt("Hello {name}, you are {age} years old")
+    print(prompt.format_prompt(name="John", age=30))
+
+    prompt = SystemRolePrompt("Hello {name}, you are {age} years old")
+    print(prompt.create_message(name="John", age=30))
+    print(prompt.get_input_variables())