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app.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from flask import Flask, jsonify, request, send_file\n",
+    "from gtts import gTTS\n",
+    "from langchain.chains import ConversationalRetrievalChain\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.document_loaders import TextLoader\n",
+    "from langchain.embeddings import OpenAIEmbeddings\n",
+    "from langchain.indexes import VectorstoreIndexCreator\n",
+    "from langchain.indexes.vectorstore import VectorStoreIndexWrapper\n",
+    "from langchain.vectorstores import Chroma\n",
+    "from langchain.memory import ConversationBufferMemory\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "os.environ[\"OPENAI_API_KEY\"] = \"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\"\n",
+    "PERSIST = False"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "app = Flask(__name__)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "query = None\n",
+    "\n",
+    "\n",
+    "def main_func(message , history):\n",
+    "  chat_history = []\n",
+    "  if PERSIST and os.path.exists(\"persist\"):\n",
+    "    print(\"Reusing index...\\n\")\n",
+    "    vectorstore = Chroma(persist_directory=\"persist\", embedding_function=OpenAIEmbeddings())\n",
+    "    index = VectorStoreIndexWrapper(vectorstore=vectorstore)\n",
+    "  else:\n",
+    "    loader = TextLoader(\"data11.txt\")\n",
+    "    if PERSIST:\n",
+    "      index = VectorstoreIndexCreator(vectorstore_kwargs={\"persist_directory\":\"persist\"}).from_loaders([loader])\n",
+    "    else:\n",
+    "      index = VectorstoreIndexCreator().from_loaders([loader])\n",
+    "  print(index)\n",
+    "\n",
+    "  memory = ConversationBufferMemory(memory_key=\"chat_history\", return_messages=True)\n",
+    "  chain = ConversationalRetrievalChain.from_llm(llm=ChatOpenAI(), retriever=index.vectorstore.as_retriever(), memory=memory, verbose=True)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "AssertionError",
+     "evalue": "View function mapping is overwriting an existing endpoint function: generate_text",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
+      "Cell \u001b[1;32mIn[8], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[38;5;129;43m@app\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mroute\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m/generate-text/<query>\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmethods\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mPOST\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m      2\u001b[0m \u001b[38;5;28;43;01mdef\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;21;43mgenerate_text\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mquery\u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[0;32m      3\u001b[0m \u001b[43m    \u001b[49m\u001b[43mresult\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mchain\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mquestion\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mquery\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mchat_history\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43m]\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m      4\u001b[0m \u001b[43m    \u001b[49m\u001b[43mgenerated_text\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mresult\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43manswer\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\n",
+      "File \u001b[1;32mc:\\Users\\SABARI HARI\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\flask\\sansio\\scaffold.py:366\u001b[0m, in \u001b[0;36mScaffold.route.<locals>.decorator\u001b[1;34m(f)\u001b[0m\n\u001b[0;32m    364\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdecorator\u001b[39m(f: T_route) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m T_route:\n\u001b[0;32m    365\u001b[0m     endpoint \u001b[38;5;241m=\u001b[39m options\u001b[38;5;241m.\u001b[39mpop(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mendpoint\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m--> 366\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43madd_url_rule\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrule\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mendpoint\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    367\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m f\n",
+      "File \u001b[1;32mc:\\Users\\SABARI HARI\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\flask\\sansio\\scaffold.py:46\u001b[0m, in \u001b[0;36msetupmethod.<locals>.wrapper_func\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m     44\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapper_func\u001b[39m(\u001b[38;5;28mself\u001b[39m: Scaffold, \u001b[38;5;241m*\u001b[39margs: t\u001b[38;5;241m.\u001b[39mAny, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: t\u001b[38;5;241m.\u001b[39mAny) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m t\u001b[38;5;241m.\u001b[39mAny:\n\u001b[0;32m     45\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_setup_finished(f_name)\n\u001b[1;32m---> 46\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[1;32mc:\\Users\\SABARI HARI\\AppData\\Local\\Programs\\Python\\Python311\\Lib\\site-packages\\flask\\sansio\\app.py:661\u001b[0m, in \u001b[0;36mApp.add_url_rule\u001b[1;34m(self, rule, endpoint, view_func, provide_automatic_options, **options)\u001b[0m\n\u001b[0;32m    659\u001b[0m old_func \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mview_functions\u001b[38;5;241m.\u001b[39mget(endpoint)\n\u001b[0;32m    660\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m old_func \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m old_func \u001b[38;5;241m!=\u001b[39m view_func:\n\u001b[1;32m--> 661\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mAssertionError\u001b[39;00m(\n\u001b[0;32m    662\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mView function mapping is overwriting an existing\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    663\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m endpoint function: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mendpoint\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    664\u001b[0m     )\n\u001b[0;32m    665\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mview_functions[endpoint] \u001b[38;5;241m=\u001b[39m view_func\n",
+      "\u001b[1;31mAssertionError\u001b[0m: View function mapping is overwriting an existing endpoint function: generate_text"
+     ]
+    }
+   ],
+   "source": [
+    "@app.route('/generate-text/<query>', methods=['POST'])\n",
+    "def generate_text(query):\n",
+    "    result = chain({\"question\": query, \"chat_history\": []})\n",
+    "    generated_text = result['answer']\n",
+    "\n",
+    "    tts = gTTS(text=generated_text, lang='en')\n",
+    "    tts.save(\"output.mp3\")\n",
+    "\n",
+    "    return jsonify({\n",
+    "        'generated_text': generated_text,\n",
+    "        'audio_url': request.host_url + 'audio'\n",
+    "    })\n",
+    "\n",
+    "@app.route('/audio')\n",
+    "def get_audio():\n",
+    "    return send_file(\"output.mp3\", as_attachment=True)\n",
+    "\n",
+    "if __name__ == \"__main__\":\n",
+    "    app.run(debug=True)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": 2
+}

app.py

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+from flask import Flask, jsonify, request, send_file
+from gtts import gTTS
+from langchain.chains import ConversationalRetrievalChain
+from langchain.chat_models import ChatOpenAI
+from langchain.document_loaders import TextLoader
+from langchain.embeddings import OpenAIEmbeddings
+from langchain.indexes import VectorstoreIndexCreator
+from langchain.indexes.vectorstore import VectorStoreIndexWrapper
+from langchain.vectorstores import Chroma
+from langchain.memory import ConversationBufferMemory
+import os
+
+app = Flask(__name__)
+os.environ["OPENAI_API_KEY"] = "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"
+PERSIST = True
+
+query = None  
+
+def main_func(message, history):
+    global query  
+    chat_history = history  
+    if PERSIST and os.path.exists("persist"):
+        print("Reusing index...\n")
+        vectorstore = Chroma(persist_directory="persist", embedding_function=OpenAIEmbeddings())
+        index = VectorStoreIndexWrapper(vectorstore=vectorstore)
+    else:
+        loader = TextLoader("new.txt")
+        if PERSIST:
+            index = VectorstoreIndexCreator(vectorstore_kwargs={"persist_directory": "persist"}).from_loaders([loader])
+        else:
+            index = VectorstoreIndexCreator().from_loaders([loader])
+
+    print(index)
+
+    memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
+    chain = ConversationalRetrievalChain.from_llm(llm=ChatOpenAI(), retriever=index.vectorstore.as_retriever(), memory=memory, verbose=True)
+
+    query = message
+    result = chain({"question": query, "chat_history": chat_history})
+    print(result['answer'])
+    chat_history.append((query, result['answer']))
+    return result['answer']
+
+@app.route('/generate-text/<input_text>', methods=['POST'])
+def generate_text(input_text):
+    global query  
+    generated_text = main_func(input_text, [])
+
+    tts = gTTS(text=generated_text, lang='en')
+    tts.save("output.mp3")
+
+    return jsonify({
+        'generated_text': generated_text,
+        'audio_url': request.host_url + 'audio'
+    })
+
+@app.route('/audio')
+def get_audio():
+    return send_file("output.mp3", as_attachment=True)
+
+if __name__ == "__main__":
+    app.run(debug=True)