Update app.py

app.py

@@ -1,57 +1,62 @@
-import os
 import gradio as gr
 from openai import OpenAI
+from langchain_community.document_loaders import TextLoader
+from langchain_text_splitters import CharacterTextSplitter
+from langchain_community.vectorstores import FAISS
+from langchain_community.embeddings import FakeEmbeddings
+import os
 
-# Set your OpenRouter API key here
-openrouter_api_key = "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"
+# Load and split the text
+loader = TextLoader("mindmate.txt")
+documents = loader.load()
+text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
+split_docs = text_splitter.split_documents(documents)
+vector_db = FAISS.from_documents(split_docs, FakeEmbeddings(size=100))
 
-# Initialize the OpenAI client with OpenRouter settings
+# Set up OpenRouter with DeepSeek R1
 client = OpenAI(
     base_url="https://openrouter.ai/api/v1",
-    api_key=openrouter_api_key,
+    api_key="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"
 )
 
-# Function to get AI response
-def get_emotional_response(name, issue):
-    prompt = (
-        f"{name} is feeling emotionally low. Reason: {issue}. "
-        "Provide a supportive, warm, understanding, and emotionally intelligent response like a mental health companion."
-    )
+# Define system prompt
+SYSTEM_PROMPT = (
+    "You are a warm and emotionally intelligent mental health companion 🧠💛. "
+    "You deeply understand the user's problems and respond with empathy and clarity. "
+    "Provide comforting, short fixes as bullet points (•). "
+    "Keep responses clean – do not use markdown like ** or * anywhere. "
+    "Add emojis (🌟💪🌈🫶) to make it emotionally expressive. "
+    "Be soothing, friendly, and non-judgmental. Be on the user's side always. "
+    "Make sure the advice is helpful, practical, and to the point."
+)
 
-    try:
-        response = client.chat.completions.create(
-            model="deepseek/deepseek-r1:free",
-            messages=[
-                {"role": "system", "content": "You are a warm and emotionally intelligent mental health companion who deeply understands the user's problems and offers support with compassion and clarity. Your responses are emotionally supportive, straight to the point, and easy to understand. Instead of long explanations, you provide practical solutions in short, bullet-point formats, helping users feel heard, comforted, and gently guided toward healing without overwhelming them"},
-                {"role": "user", "content": prompt}
-            ],
-            temperature=0.7
-        )
-        return response.choices[0].message.content
-
-    except Exception as e:
-        return f"⚠️ Error: {str(e)}"
-
-# Gradio UI setup
-with gr.Blocks(theme=gr.themes.Base()) as demo:
-    gr.Markdown("""
-    # 🧠 MindMate: Your Mental Health Companion  
-    Share your feelings and let AI comfort you 💙  
-    *(Powered by DeepSeek R1 via OpenRouter)*
-    """)
+def chatbot(user_input):
+    docs = vector_db.similarity_search(user_input, k=2)
+    context = "\n\n".join([doc.page_content for doc in docs])
 
-    with gr.Row():
-        with gr.Column(scale=1):
-            name_input = gr.Textbox(label="Your Name", placeholder="e.g., Dhruvil", lines=1)
-            issue_input = gr.Textbox(label="What's troubling you today?", placeholder="Describe your emotions or situation...", lines=4)
+    response = client.chat.completions.create(
+        model="deepseek/deepseek-r1:free",
+        messages=[
+            {"role": "system", "content": SYSTEM_PROMPT},
+            {"role": "user", "content": f"Context:\n{context}\n\nUser Message:\n{user_input}"}
+        ]
+    )
 
-            submit_btn = gr.Button("🪄 Get Comfort")
-            clear_btn = gr.Button("🧹 Clear")
+    return response.choices[0].message.content
 
-        with gr.Column(scale=1):
-            output_box = gr.Textbox(label="MindMate Says:", lines=8)
+# Gradio UI
+def process_input(user_message):
+    return chatbot(user_message)
+
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("## 🧠 MindMate – Your Mental Health Companion 💛")
+    with gr.Row():
+        with gr.Column():
+            chatbot_input = gr.Textbox(lines=2, placeholder="Share what's on your mind...", label="How are you feeling today?")
+            send_button = gr.Button("Send")
+        with gr.Column():
+            chatbot_output = gr.Textbox(lines=10, label="MindMate's Response")
 
-    submit_btn.click(fn=get_emotional_response, inputs=[name_input, issue_input], outputs=output_box)
-    clear_btn.click(fn=lambda: ("", "", ""), inputs=[], outputs=[name_input, issue_input, output_box])
+    send_button.click(fn=process_input, inputs=chatbot_input, outputs=chatbot_output)
 
 demo.launch()