Upload folder using huggingface_hub

.env

@@ -0,0 +1,3 @@
+OPENAI_API_KEY='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'
+PINECONE_ENV='gcp-starter'
+PINECONE_API_KEY='9c64a98d-d7d3-4409-b108-c294a7a8c469s'

.ipynb_checkpoints/gradio-app-checkpoint.ipynb

@@ -0,0 +1,98 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7860\n",
+      "Running on public URL: https://0e417036a0cfaf8a4d.gradio.live\n",
+      "\n",
+      "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"https://0e417036a0cfaf8a4d.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import gradio as gr\n",
+    "\n",
+    "def takeinput(name):\n",
+    "    str_input =  \"Hello {name} how are you?\"\n",
+    "    return str_input\n",
+    "\n",
+    "demo = gr.Interface(\n",
+    "        fn=takeinput,\n",
+    "        inputs=[\"text\"],\n",
+    "        outputs=[\"text\"]\n",
+    ")\n",
+    "\n",
+    "demo.launch(share=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

.ipynb_checkpoints/langchain-app-checkpoint.ipynb

@@ -0,0 +1,55 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import gradio as gr\n",
+    "from dotenv import load_dotenv, find_dotenv\n",
+    "_ = load_dotenv(find_dotenv())\n",
+    "\n",
+    "from langchain.chains import ConversationChain\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.memory import ConversationBufferMemory\n",
+    "\n",
+    "llm = ChatOpenAI(temperature=0.0)\n",
+    "memory = ConversationBufferMemory()\n",
+    "conversion = ConversationChain(\n",
+    "    llm=llm,\n",
+    "    memory=memory,\n",
+    "    verbose=False\n",
+    ")\n",
+    "\n",
+    "def takeinput(input_str):\n",
+    "    output_str = conversion.predict(input=input_str)\n",
+    "    return output_str\n",
+    "\n",
+    "demo = gr.Interface(\n",
+    "        fn=takeinput,\n",
+    "        inputs=[\"text\"],\n",
+    "        outputs=[\"text\"]\n",
+    ")\n",
+    "\n",
+    "demo.launch(share=True)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

README.md

@@ -1,12 +1,6 @@
 ---
-title: Gradio Langchain Simple UI
-emoji: 📊
-colorFrom: blue
-colorTo: blue
+title: Gradio_Langchain_Simple_UI
+app_file: langchain-app.ipynb
 sdk: gradio
 sdk_version: 3.46.0
-app_file: app.py
-pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

langchain-app.ipynb

@@ -0,0 +1,99 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7863\n",
+      "Running on public URL: https://cf43e4871c9bab7308.gradio.live\n",
+      "\n",
+      "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"https://cf43e4871c9bab7308.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import gradio as gr\n",
+    "from dotenv import load_dotenv, find_dotenv\n",
+    "_ = load_dotenv(find_dotenv())\n",
+    "\n",
+    "from langchain.chains import ConversationChain\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.memory import ConversationBufferMemory\n",
+    "\n",
+    "llm = ChatOpenAI(temperature=0.0)\n",
+    "memory = ConversationBufferMemory()\n",
+    "conversion = ConversationChain(\n",
+    "    llm=llm,\n",
+    "    memory=memory,\n",
+    "    verbose=False\n",
+    ")\n",
+    "\n",
+    "def takeinput(input_str):\n",
+    "    output_str = conversion.predict(input=input_str)\n",
+    "    return output_str\n",
+    "\n",
+    "demo = gr.Interface(\n",
+    "        fn=takeinput,\n",
+    "        inputs=[\"text\"],\n",
+    "        outputs=[\"text\"]\n",
+    ")\n",
+    "\n",
+    "demo.launch(share=True)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}