Upload folder using huggingface_hub

.env

@@ -0,0 +1 @@
+OPENAI_API_KEY = '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'

.ipynb_checkpoints/Untitled-checkpoint.ipynb

@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

.ipynb_checkpoints/Untitled1-checkpoint.ipynb

@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

.ipynb_checkpoints/Untitled2-checkpoint.ipynb

@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

.ipynb_checkpoints/Untitled3-checkpoint.ipynb

@@ -0,0 +1,65 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f32c4a15-cc74-4a43-8af1-1d3b783f1fa1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import openai\n",
+    "import os\n",
+    "\n",
+    "from dotenv import load_dotenv, find_dotenv\n",
+    "_ = load_dotenv(find_dotenv())\n",
+    "openai.api_key = os.environ['OPENAI_API_KEY']\n",
+    "MODEL_NAME = 'gpt-3.5-turbo'\n",
+    "\n",
+    "class Assigment3:\n",
+    "    input_val = ''\n",
+    "    def __init__(self, model):\n",
+    "        self.model = model\n",
+    "        \n",
+    "    def get_input(self):\n",
+    "        self.input_val = input('Enter your message')\n",
+    "\n",
+    "    def get_completion(self):\n",
+    "        messages = [{\n",
+    "            'role': 'user',\n",
+    "            'content': self.input_val\n",
+    "        }]\n",
+    "        response = openai.ChatCompletion.create(\n",
+    "            model=self.model,\n",
+    "            messages=messages,\n",
+    "            temperature=0\n",
+    "        )\n",
+    "        return response.choices[0].message.count\n",
+    "\n",
+    "    \n",
+    "obj = Assigment3(MODEL_NAME)\n",
+    "print(obj.get_completion())"
+   ]
+  }
+ ],
+ "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": 5
+}

.ipynb_checkpoints/assignment3-checkpoint.py

@@ -0,0 +1,31 @@
+import openai
+import os
+
+from dotenv import load_dotenv, find_dotenv
+_ = load_dotenv(find_dotenv())
+openai.api_key = os.environ['OPENAI_API_KEY']
+MODEL_NAME = 'gpt-3.5-turbo'
+
+class Assigment3:
+    input_val = ''
+    def __init__(self, model):
+        self.model = model
+        
+    def get_input(self):
+        self.input_val = input('Enter your message')
+
+    def get_completion(self):
+        messages = [{
+            'role': 'user',
+            'content': self.input_val
+        }]
+        response = openai.ChatCompletion.create(
+            model=self.model,
+            messages=messages,
+            temperature=0
+        )
+        return response.choices[0].message.count
+
+    
+obj = Assigment3(MODEL_NAME)
+print(obj.get_completion())

.ipynb_checkpoints/assignment_3-checkpoint.ipynb

@@ -0,0 +1,65 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f32c4a15-cc74-4a43-8af1-1d3b783f1fa1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import openai\n",
+    "import os\n",
+    "\n",
+    "from dotenv import load_dotenv, find_dotenv\n",
+    "_ = load_dotenv(find_dotenv())\n",
+    "openai.api_key = os.environ['OPENAI_API_KEY']\n",
+    "MODEL_NAME = 'gpt-3.5-turbo'\n",
+    "\n",
+    "class Assigment3:\n",
+    "    input_val = ''\n",
+    "    def __init__(self, model):\n",
+    "        self.model = model\n",
+    "        \n",
+    "    def get_input(self):\n",
+    "        self.input_val = input('Enter your message')\n",
+    "\n",
+    "    def get_completion(self):\n",
+    "        messages = [{\n",
+    "            'role': 'user',\n",
+    "            'content': self.input_val\n",
+    "        }]\n",
+    "        response = openai.ChatCompletion.create(\n",
+    "            model=self.model,\n",
+    "            messages=messages,\n",
+    "            temperature=0\n",
+    "        )\n",
+    "        return response.choices[0].message.count\n",
+    "\n",
+    "    \n",
+    "obj = Assigment3(MODEL_NAME)\n",
+    "print(obj.get_completion())"
+   ]
+  }
+ ],
+ "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": 5
+}

.ipynb_checkpoints/assignment_3-checkpoint.py

@@ -0,0 +1,29 @@
+import openai
+import os
+
+openai.api_key = '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'
+MODEL_NAME = 'gpt-3.5-turbo'
+
+class Assigment3:
+    input_val = ''
+    def __init__(self, model):
+        self.model = model
+        
+    def get_input(self):
+        self.input_val = input('Enter your message')
+
+    def get_completion(self):
+        messages = [{
+            'role': 'user',
+            'content': self.input_val
+        }]
+        response = openai.ChatCompletion.create(
+            model=self.model,
+            messages=messages,
+            temperature=0
+        )
+        return response.choices[0].message.count
+
+    
+obj = Assigment3(MODEL_NAME)
+print(obj.get_completion())

README.md

@@ -1,12 +1,6 @@
 ---
-title: Simple Langchain Gradio App
-emoji: 💻
-colorFrom: blue
-colorTo: green
+title: Simple_Langchain_Gradio_App
+app_file: langchain-app.py
 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

Untitled.ipynb

@@ -0,0 +1,86 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "34b50665-3063-4b26-b496-ca1633e8a38e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Enter your message who is sushant godse?\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "I'm sorry, but I couldn't find any information about a person named Sushant Godse. It's possible that this person may not be widely known or may not have a significant online presence.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import openai\n",
+    "import os\n",
+    "\n",
+    "openai.api_key = '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'\n",
+    "MODEL_NAME = 'gpt-3.5-turbo'\n",
+    "\n",
+    "class Assigment3:\n",
+    "    input_val = ''\n",
+    "    def __init__(self, model):\n",
+    "        self.model = model\n",
+    "        \n",
+    "    def get_input(self):\n",
+    "        self.input_val = input('Enter your message')\n",
+    "\n",
+    "    def get_completion(self):\n",
+    "        messages = [{\n",
+    "            'role': 'user',\n",
+    "            'content': self.input_val\n",
+    "        }]\n",
+    "        response = openai.ChatCompletion.create(\n",
+    "            model=self.model,\n",
+    "            messages=messages,\n",
+    "            temperature=0\n",
+    "        )\n",
+    "        return response.choices[0].message['content']\n",
+    "    \n",
+    "obj = Assigment3(MODEL_NAME)\n",
+    "obj.get_input()\n",
+    "print(obj.get_completion())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "575f233a-32e5-4700-8874-b7bf9428a51b",
+   "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": 5
+}

Untitled1.ipynb

@@ -0,0 +1,99 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "a05e9e6e-7a2b-4e02-a37a-678f065092f9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "To guide a model towards the desired output and avoid irrelevant or incorrect responses, it is important to provide clear and specific instructions, even if they are longer and provide more clarity and context.\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "import openai\n",
+    "import os\n",
+    "\n",
+    "openai.api_key = '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'\n",
+    "MODEL_NAME = 'gpt-3.5-turbo'\n",
+    "\n",
+    "TEXT = f\"\"\"\n",
+    "You should express what you want a model to do by \\\n",
+    "providing instructions that are as clear and \\\n",
+    "specific as you can possibly make them. \\\n",
+    "This will guide the model towards the desired output, \\\n",
+    "and reduce the chances of receiving irrelevent \\\n",
+    "or incorrec5 responses. Don't confuse writing a \\\n",
+    "clear prompt with writing a short prompt. \\\n",
+    "In many case, longer prompts provide more clearity \\\n",
+    "and context for the model, which can lead to \\\n",
+    "more detailed and relevant outputs.\n",
+    "\"\"\"\n",
+    "\n",
+    "PROMPT = f\"\"\"\n",
+    "summarize the text delimited by triple backticks\\\n",
+    "into a single sentence.\n",
+    "```{TEXT}```\n",
+    "\"\"\"\n",
+    "\n",
+    "class Assigment4:\n",
+    "    input_val = ''\n",
+    "    def __init__(self, model):\n",
+    "        self.model = model\n",
+    "        \n",
+    "    def get_input(self):\n",
+    "        self.input_val = input('Enter your message')\n",
+    "\n",
+    "    def get_completion(self, prompt):\n",
+    "        messages = [{\n",
+    "            'role': 'user',\n",
+    "            'content': prompt\n",
+    "        }]\n",
+    "        response = openai.ChatCompletion.create(\n",
+    "            model=self.model,\n",
+    "            messages=messages,\n",
+    "            temperature=0\n",
+    "        )\n",
+    "        return response.choices[0].message['content']\n",
+    "\n",
+    "    \n",
+    "obj = Assigment4(MODEL_NAME)\n",
+    "print(obj.get_completion(PROMPT))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d3bb3a9b-d418-484b-81c0-33515dba32c9",
+   "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": 5
+}

Untitled2.ipynb

@@ -0,0 +1,127 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "95d56fde-3f1a-482f-aa25-40687d16e5dc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{\n",
+      "  \"books\": [\n",
+      "    {\n",
+      "      \"book_id\": 1,\n",
+      "      \"title\": \"The Enigma of Elysium\",\n",
+      "      \"author\": \"Aria Nightshade\",\n",
+      "      \"genre\": \"Fantasy\"\n",
+      "    },\n",
+      "    {\n",
+      "      \"book_id\": 2,\n",
+      "      \"title\": \"Shadows of Serendipity\",\n",
+      "      \"author\": \"Elijah Blackwood\",\n",
+      "      \"genre\": \"Mystery\"\n",
+      "    },\n",
+      "    {\n",
+      "      \"book_id\": 3,\n",
+      "      \"title\": \"Whispers in the Wind\",\n",
+      "      \"author\": \"Luna Silvermoon\",\n",
+      "      \"genre\": \"Romance\"\n",
+      "    }\n",
+      "  ]\n",
+      "}\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "import openai\n",
+    "import os\n",
+    "\n",
+    "openai.api_key = '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'\n",
+    "MODEL_NAME = 'gpt-3.5-turbo'\n",
+    "\n",
+    "# TEXT = f\"\"\"\n",
+    "# You should express what you want a model to do by \\\n",
+    "# providing instructions that are as clear and \\\n",
+    "# specific as you can possibly make them. \\\n",
+    "# This will guide the model towards the desired output, \\\n",
+    "# and reduce the chances of receiving irrelevent \\\n",
+    "# or incorrec5 responses. Don't confuse writing a \\\n",
+    "# clear prompt with writing a short prompt. \\\n",
+    "# In many case, longer prompts provide more clearity \\\n",
+    "# and context for the model, which can lead to \\\n",
+    "# more detailed and relevant outputs.\n",
+    "# \"\"\"\n",
+    "\n",
+    "# PROMPT = f\"\"\"\n",
+    "# summarize the text delimited by triple backticks\\\n",
+    "# into a single sentence.\n",
+    "# ```{TEXT}```\n",
+    "# \"\"\"\n",
+    "\n",
+    "PROMPT = f\"\"\"\n",
+    "Generate a list of three made-up book titles along \\\n",
+    "with their authors and genres.\n",
+    "Provide them in JSON format with the following keys:\n",
+    "book_id, title, author, genre.\n",
+    "\"\"\"\n",
+    "\n",
+    "class Assignment4:\n",
+    "    input_val = ''\n",
+    "    def __init__(self, model):\n",
+    "        self.model = model\n",
+    "        \n",
+    "    def get_input(self):\n",
+    "        self.input_val = input('Enter your message')\n",
+    "\n",
+    "    def get_completion(self, prompt):\n",
+    "        messages = [{\n",
+    "            'role': 'user',\n",
+    "            'content': prompt\n",
+    "        }]\n",
+    "        response = openai.ChatCompletion.create(\n",
+    "            model=self.model,\n",
+    "            messages=messages,\n",
+    "            temperature=0\n",
+    "        )\n",
+    "        return response.choices[0].message['content']\n",
+    "\n",
+    "    \n",
+    "obj = Assignment4(MODEL_NAME)\n",
+    "print(obj.get_completion(PROMPT))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fc90ad16-7a94-42ef-bdd4-9ec176da6210",
+   "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": 5
+}

assignment3.ipynb

@@ -0,0 +1,31 @@
+import openai
+import os
+
+from dotenv import load_dotenv, find_dotenv
+_ = load_dotenv(find_dotenv())
+openai.api_key = os.environ['OPENAI_API_KEY']
+MODEL_NAME = 'gpt-3.5-turbo'
+
+class Assigment3:
+    input_val = ''
+    def __init__(self, model):
+        self.model = model
+        
+    def get_input(self):
+        self.input_val = input('Enter your message')
+
+    def get_completion(self):
+        messages = [{
+            'role': 'user',
+            'content': self.input_val
+        }]
+        response = openai.ChatCompletion.create(
+            model=self.model,
+            messages=messages,
+            temperature=0
+        )
+        return response.choices[0].message.count
+
+    
+obj = Assigment3(MODEL_NAME)
+print(obj.get_completion())

assignment_3.ipynb

@@ -0,0 +1,89 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "f32c4a15-cc74-4a43-8af1-1d3b783f1fa1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Enter your message what is circumference on earth\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The circumference of the Earth is approximately 40,075 kilometers (24,901 miles).\n"
+     ]
+    }
+   ],
+   "source": [
+    "import openai\n",
+    "import os\n",
+    "\n",
+    "from dotenv import load_dotenv, find_dotenv\n",
+    "_ = load_dotenv(find_dotenv())\n",
+    "openai.api_key = os.environ['OPENAI_API_KEY']\n",
+    "MODEL_NAME = 'gpt-3.5-turbo'\n",
+    "\n",
+    "class Assigment3:\n",
+    "    input_val = ''\n",
+    "    def __init__(self, model):\n",
+    "        self.model = model\n",
+    "        \n",
+    "    def get_input(self):\n",
+    "        self.input_val = input('Enter your message')\n",
+    "\n",
+    "    def get_completion(self):\n",
+    "        messages = [{\n",
+    "            'role': 'user',\n",
+    "            'content': self.input_val\n",
+    "        }]\n",
+    "        response = openai.ChatCompletion.create(\n",
+    "            model=self.model,\n",
+    "            messages=messages,\n",
+    "            temperature=0\n",
+    "        )\n",
+    "        return response.choices[0].message.content\n",
+    "\n",
+    "    \n",
+    "obj = Assigment3(MODEL_NAME)\n",
+    "obj.get_input()\n",
+    "print(obj.get_completion())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "00443343-be7e-41e7-8a72-f2ebf8273622",
+   "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": 5
+}

langchain-app.py

@@ -0,0 +1,28 @@
+import os
+import gradio as gr
+from dotenv import load_dotenv, find_dotenv
+_ = load_dotenv(find_dotenv())
+
+from langchain.chains import ConversationChain
+from langchain.chat_models import ChatOpenAI
+from langchain.memory import ConversationBufferMemory
+
+llm = ChatOpenAI(temperature=0.0)
+memory = ConversationBufferMemory()
+conversion = ConversationChain(
+    llm=llm,
+    memory=memory,
+    verbose=False
+)
+
+def takeinput(name):
+    output_str = conversion.predict(input=name)
+    return output_str
+
+demo = gr.Interface(
+        fn=takeinput,
+        inputs=["text"],
+        outputs=["text"]
+)
+
+demo.launch(share=True)