create app.py with perspective taking, chatbot, and foundationretriever

app.py

@@ -0,0 +1,75 @@
+import os
+import gradio as gr
+from huggingface_hub import InferenceClient
+from retriever import find_similar_foundations
+
+# -------------------------------------------------------------------
+# 1. Setup client for chatbot
+# -------------------------------------------------------------------
+# Use my token stored as a Space secret for inference
+client = InferenceClient(
+    provider="featherless-ai",
+    api_key=os.environ["HF_TOKEN"]
+)
+
+
+# -------------------------------------------------------------------
+# 2. Chatbot function
+# -------------------------------------------------------------------
+def chat_with_model(message, history):
+    messages = []
+    for user_msg, bot_msg in history:
+        messages.append({"role": "user", "content": user_msg})
+        if bot_msg:
+            messages.append({"role": "assistant", "content": bot_msg})
+
+    messages.append({"role": "user", "content": message})
+
+    response = client.chat.completions.create(
+        model="mistralai/Mistral-7B-Instruct-v0.2",
+        messages=messages,
+        max_tokens=512,
+    )
+
+    reply = response.choices[0].message.content
+    history.append((message, reply))
+    return history, history
+
+
+# -------------------------------------------------------------------
+# 3. Foundations Retriever function (for UI)
+# -------------------------------------------------------------------
+def retrieve_foundations(query, top_k):
+    results = find_similar_foundations(query, top_k=top_k)
+    output = "\n\n".join(
+        [f"**{r['rank']}. {r['title']}**\n{r['purpose']}\n(similarity: {r['similarity']:.4f})"
+         for r in results]
+    )
+    return output
+
+
+# -------------------------------------------------------------------
+# 4. Gradio Interface
+# -------------------------------------------------------------------
+with gr.Blocks() as demo:
+    gr.Markdown("# Mistral Perspective Chatbot & Foundation Finder")
+
+    with gr.Tab("💬 Chatbot"):
+        chatbot = gr.Chatbot()
+        msg = gr.Textbox(placeholder="Ask me anything...", show_label=False)
+        state = gr.State([])  # keeps conversation history
+        msg.submit(chat_with_model, [msg, state], [chatbot, state])
+
+
+    with gr.Tab("🔎 Find Aligned Foundations"):
+        perspective = gr.Textbox(
+            label="Enter your philanthropic perspective",
+            placeholder="e.g. Environmental philanthropist emphasizing animal protection while fostering children's education"
+        )
+        top_k = gr.Slider(1, 5, value=2, step=1, label="Number of results")
+        output = gr.Dataframe(headers=["Title", "Purpose", "similarity"], wrap=True)
+
+        btn = gr.Button("Find Foundations")
+        btn.click(fn=retrieve_foundations, inputs=[perspective, top_k], outputs=output)
+
+demo.launch(server_name="0.0.0.0", server_port=7860)