Create app.py

app.py

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+import streamlit as st
+import os
+import numpy as np
+from sentence_transformers import SentenceTransformer
+import faiss
+from openai import OpenAI
+from PIL import Image
+
+class IntegratedChatSystem:
+    def __init__(self, api_key: str, model_name: str, embedding_dim: int = 384):
+        self.api_key = api_key
+        self.model_name = model_name
+        self.embedding_model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
+        self.embedding_dim = embedding_dim
+        self.index = faiss.IndexFlatIP(embedding_dim)
+        self.metadata = []
+        self.client = OpenAI(api_key=api_key)
+
+    def _add_to_index(self, vector: np.ndarray, metadata: dict):
+        self.index.add(vector)
+        self.metadata.append(metadata)
+
+    def add_image(self, image_path: str, context_text: str):
+        filename = os.path.basename(image_path)
+        if not os.path.exists(image_path):
+            raise FileNotFoundError(f"Image not found: {image_path}")
+        embedding = self.embedding_model.encode(context_text)
+        embedding = np.expand_dims(embedding, axis=0)
+        self._add_to_index(embedding, {"filepath": filename, "context": context_text})
+
+    def chat(self, user_message: str, similarity_threshold: float = 0.7, top_k: int = 3):
+        message_embedding = self.embedding_model.encode(user_message)
+        message_embedding = np.expand_dims(message_embedding, axis=0)
+        distances, indices = self.index.search(message_embedding, top_k)
+        relevant_images = [
+            self.metadata[i] for i, distance in zip(indices[0], distances[0]) 
+            if i != -1 and distance >= similarity_threshold
+        ]
+
+        system_prompt = """You are an assistant chatbot. You should help the user by answering their question."""
+        
+        enhanced_message = user_message
+        if relevant_images:
+            image_contexts = "\n".join(f"- {img['context']}" for img in relevant_images)
+            enhanced_message = f"{user_message}\n\nContext from relevant images:\n{image_contexts}"
+
+        try:
+            completion = self.client.chat_completions.create(
+                model=self.model_name,
+                messages=[
+                    {"role": "system", "content": system_prompt},
+                    {"role": "user", "content": enhanced_message}
+                ]
+            )
+            
+            response = completion.choices[0].message.content
+
+            return {
+                "response": response,
+                "images": relevant_images if relevant_images else None
+            }
+            
+        except Exception as e:
+            print(f"Error calling OpenAI API: {str(e)}")
+            return {
+                "response": "I apologize, but I encountered an error processing your request.",
+                "images": None
+            }
+
+# Initialize the chat system
+api_key = "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"
+model_name = "ft:gpt-3.5-turbo-0125:brenin::AlVMkeUb"
+chat_system = IntegratedChatSystem(api_key, model_name)
+
+# Add images
+image_folder = "images"
+chat_system.add_image(os.path.join(image_folder, "sequence diagram.png"), "A diagram showing the sequence of how it is supposed to work")
+chat_system.add_image(os.path.join(image_folder, "UX workflow.png"), "A flowchart of showing the UX workflow")
+
+# Streamlit UI
+st.title("Chat with Integrated Image Context")
+
+st.sidebar.title("Chat System")
+user_message = st.text_input("Your message:", placeholder="Type your message here...")
+
+if st.button("Send"):
+    if user_message.strip():
+        result = chat_system.chat(user_message)
+        st.write(f"**Assistant:** {result['response']}")
+        
+        if result["images"]:
+            st.write("Relevant Images:")
+            for img in result["images"]:
+                image_path = os.path.join(image_folder, img["filepath"])
+                if os.path.exists(image_path):
+                    st.image(Image.open(image_path), caption=img["context"])
+                else:
+                    st.write(f"Image not found: {img['filepath']}")
+    else:
+        st.error("Please enter a message.")
+