Add application file

.gitignore

@@ -0,0 +1,2 @@
+env
+.env

.vscode/settings.json

@@ -0,0 +1,3 @@
+{
+    "python.formatting.provider": "black"
+}

Makefile

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+push:
+	git add .
+	git commit -m "🙈"
+	git push
+
+
+install: ## [DEVELOPMENT] Install the API dependencies
+	virtualenv env; \
+	source env/bin/activate; \
+	pip install -r requirements.txt; \
+	pip install -r requirements-test.txt
+	@echo "Done, run '\033[0;31msource env/bin/activate\033[0m' to activate the virtual environment"
+
+run: ## [DEVELOPMENT] Run the streamlit app
+	streamlit run app.py

README.md

@@ -1,8 +1,8 @@
 ---
 title: Infinite Memory Chatgpt
-emoji: ⚡
-colorFrom: blue
-colorTo: purple
+emoji: 📚
+colorFrom: red
+colorTo: indigo
 sdk: streamlit
 sdk_version: 1.17.0
 app_file: app.py
@@ -11,3 +11,5 @@ license: mit
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+https://embedbase.xyz

app.py

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+import streamlit as st
+
+try:
+    import dotenv
+except ImportError:
+    pass
+
+dotenv.load_dotenv()
+import openai
+import os
+import streamlit.components.v1 as components
+import requests
+import asyncio
+
+openai.api_key = os.getenv("OPENAI_API_KEY")
+embedbase_api_key = os.getenv("EMBEDBASE_API_KEY")
+
+URL = "https://embedbase-hosted-usx5gpslaq-uc.a.run.app"
+local_history = []
+
+
+async def add_to_dataset(dataset_id: str, data: str):
+    response = requests.post(
+        f"{URL}/v1/{dataset_id}",
+        headers={
+            "Content-Type": "application/json",
+            "Authorization": "Bearer " + embedbase_api_key,
+        },
+        json={
+            "documents": [
+                {
+                    "data": data,
+                },
+            ],
+        },
+    )
+    response.raise_for_status()
+    return response.json()
+
+
+async def search_dataset(dataset_id: str, query: str, limit: int = 3):
+    response = requests.post(
+        f"{URL}/v1/{dataset_id}/search",
+        headers={
+            "Content-Type": "application/json",
+            "Authorization": "Bearer " + embedbase_api_key,
+        },
+        json={
+            "query": query,
+            "top_k": limit,
+        },
+    )
+    response.raise_for_status()
+    return response.json()
+
+
+async def chat(user_input: str, conversation_name: str) -> str:
+    local_history.append(user_input)
+
+    history = await search_dataset(
+        f"infinite-pt-{conversation_name}",
+        # searching using last 4 messages from local history
+        "\n\n---\n\n".join(local_history[-4:]),
+        limit=3,
+    )
+    print("history", history)
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {
+                "role": "system",
+                "content": "You are a helpful assistant.",
+            },
+            *[
+                {
+                    "role": "assistant",
+                    "content": h["data"],
+                }
+                for h in history["similarities"][-5:]
+            ],
+            {"role": "user", "content": user_input},
+        ],
+    )
+    message = response.choices[0]["message"]
+    await add_to_dataset(f"infinite-pt-{conversation_name}", message["content"])
+
+    local_history.append(message)
+
+    return message["content"]
+
+
+from datetime import datetime
+
+# conversation name is date like ddmmyy_hhmmss
+# conversation_name = datetime.now().strftime("%d%m%y_%H%M%S")
+conversation_name = st.text_input("Conversation name", "purpose")
+
+# eg not local dev
+if not os.getenv("OPENAI_API_KEY"):
+    embedbase_api_key = st.text_input(
+        "Your Embedbase key", "get it here <https://app.embedbase.xyz/signup>"
+    )
+    openai_key = st.text_input(
+        "Your OpenAI key", "get it here <https://platform.openai.com/account/api-keys>"
+    )
+    openai.api_key = openai_key
+user_input = st.text_input("You", "How can I reach maximum happiness this year?")
+if st.button("Send"):
+    infinite_pt_response = asyncio.run(chat(user_input, conversation_name))
+    st.markdown(
+        f"""
+        Infinite-PT
+        """
+    )
+    st.write(infinite_pt_response)
+
+components.html(
+    """
+<script>
+const doc = window.parent.document;
+buttons = Array.from(doc.querySelectorAll('button[kind=primary]'));
+const send = buttons.find(el => el.innerText === 'Send');
+doc.addEventListener('keydown', function(e) {
+    switch (e.keyCode) {
+        case 13:
+            send.click();
+            break;
+    }
+});
+</script>
+""",
+    height=0,
+    width=0,
+)
+
+
+st.markdown(
+    """
+    [Source code](https://huggingface.co/spaces/louis030195/infinite-memory-chatgpt)
+    """
+)
+
+st.markdown(
+    """
+    Built with ❤️ by [louis030195](https://louis030195.com).
+    """
+)
+
+st.markdown(
+    """
+    Powered by [Embedbase](https://embedbase.xyz).
+    """
+)

requirements-test.txt

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+black
+mypy
+pylint
+pytest-cov
+pytest-xdist
+pytest
+ipykernel
+ipywidgets
+httpx
+trio
+pytest-asyncio
+watchdog
+python-dotenv

requirements.txt

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+streamlit
+openai
+tenacity
+python-dotenv