chat_seb_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain_openai import OpenAIEmbeddings\n",
    "\n",
    "from langchain.text_splitter import CharacterTextSplitter, RecursiveCharacterTextSplitter\n",
    "from langchain.chains import RetrievalQA,  ConversationalRetrievalChain\n",
    "from langchain.memory import ConversationBufferMemory\n",
    "\n",
    "from langchain_community.vectorstores import DocArrayInMemorySearch\n",
    "from langchain_community.document_loaders import TextLoader\n",
    "from langchain_openai import ChatOpenAI\n",
    "from langchain_community.document_loaders import PyPDFLoader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import openai\n",
    "import sys\n",
    "sys.path.append('../..')\n",
    "\n",
    "import panel as pn  # GUI\n",
    "pn.extension()\n",
    "\n",
    "openai.api_key  = os.environ['OPENAI_API_KEY']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "!tar cvfz "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gpt-3.5-turbo\n"
     ]
    }
   ],
   "source": [
    "import datetime\n",
    "current_date = datetime.datetime.now().date()\n",
    "if current_date < datetime.date(2023, 9, 2):\n",
    "    llm_name = \"gpt-3.5-turbo-0301\"\n",
    "else:\n",
    "    llm_name = \"gpt-3.5-turbo\"\n",
    "print(llm_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def load_db(file, chain_type, k):\n",
    "    # load documents\n",
    "    loader = PyPDFLoader(file)\n",
    "    documents = loader.load()\n",
    "    # split documents\n",
    "    text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=150)\n",
    "    docs = text_splitter.split_documents(documents)\n",
    "    # define embedding\n",
    "    embeddings = OpenAIEmbeddings()\n",
    "    # create vector database from data\n",
    "    db = DocArrayInMemorySearch.from_documents(docs, embeddings)\n",
    "    # define retriever\n",
    "    retriever = db.as_retriever(search_type=\"similarity\", search_kwargs={\"k\": k})\n",
    "    # create a chatbot chain. Memory is managed externally.\n",
    "    qa = ConversationalRetrievalChain.from_llm(\n",
    "        llm=ChatOpenAI(model_name=llm_name, temperature=0), \n",
    "        chain_type=chain_type, \n",
    "        retriever=retriever, \n",
    "        return_source_documents=True,\n",
    "        return_generated_question=True,\n",
    "    )\n",
    "    return qa \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import panel as pn\n",
    "import param\n",
    "\n",
    "class cbfs(param.Parameterized):\n",
    "    chat_history = param.List([])\n",
    "    answer = param.String(\"\")\n",
    "    db_query  = param.String(\"\")\n",
    "    db_response = param.List([])\n",
    "    \n",
    "    def __init__(self,  **params):\n",
    "        super(cbfs, self).__init__( **params)\n",
    "        self.panels = []\n",
    "        self.loaded_file = \"docs/hoffmann_et_al_2019.pdf\"\n",
    "        self.qa = load_db(self.loaded_file,\"stuff\", 4)\n",
    "    \n",
    "    def call_load_db(self, count):\n",
    "        if count == 0 or file_input.value is None:  # init or no file specified :\n",
    "            return pn.pane.Markdown(f\"Loaded File: {self.loaded_file}\")\n",
    "        else:\n",
    "            file_input.save(\"temp.pdf\")  # local copy\n",
    "            self.loaded_file = file_input.filename\n",
    "            button_load.button_style=\"outline\"\n",
    "            self.qa = load_db(\"temp.pdf\", \"stuff\", 4)\n",
    "            button_load.button_style=\"solid\"\n",
    "        self.clr_history()\n",
    "        return pn.pane.Markdown(f\"Loaded File: {self.loaded_file}\")\n",
    "\n",
    "    def convchain(self, query):\n",
    "        if not query:\n",
    "            return pn.WidgetBox(pn.Row('User:', pn.pane.Markdown(\"\", width=600)), scroll=True)\n",
    "        result = self.qa({\"question\": query, \"chat_history\": self.chat_history})\n",
    "        self.chat_history.extend([(query, result[\"answer\"])])\n",
    "        self.db_query = result[\"generated_question\"]\n",
    "        self.db_response = result[\"source_documents\"]\n",
    "        self.answer = result['answer'] \n",
    "        self.panels.extend([\n",
    "            pn.Row('User:', pn.pane.Markdown(query, width=600)),\n",
    "            pn.Row('ChatBot:', pn.pane.Markdown(self.answer, width=600, style={'background-color': '#F6F6F6'}))\n",
    "        ])\n",
    "        inp.value = ''  #clears loading indicator when cleared\n",
    "        return pn.WidgetBox(*self.panels,scroll=True)\n",
    "\n",
    "    @param.depends('db_query ', )\n",
    "    def get_lquest(self):\n",
    "        if not self.db_query :\n",
    "            return pn.Column(\n",
    "                pn.Row(pn.pane.Markdown(f\"Last question to DB:\", styles={'background-color': '#F6F6F6'})),\n",
    "                pn.Row(pn.pane.Str(\"no DB accesses so far\"))\n",
    "            )\n",
    "        return pn.Column(\n",
    "            pn.Row(pn.pane.Markdown(f\"DB query:\", styles={'background-color': '#F6F6F6'})),\n",
    "            pn.pane.Str(self.db_query )\n",
    "        )\n",
    "\n",
    "    @param.depends('db_response', )\n",
    "    def get_sources(self):\n",
    "        if not self.db_response:\n",
    "            return \n",
    "        rlist=[pn.Row(pn.pane.Markdown(f\"Result of DB lookup:\", styles={'background-color': '#F6F6F6'}))]\n",
    "        for doc in self.db_response:\n",
    "            rlist.append(pn.Row(pn.pane.Str(doc)))\n",
    "        return pn.WidgetBox(*rlist, width=600, scroll=True)\n",
    "\n",
    "    @param.depends('convchain', 'clr_history') \n",
    "    def get_chats(self):\n",
    "        if not self.chat_history:\n",
    "            return pn.WidgetBox(pn.Row(pn.pane.Str(\"No History Yet\")), width=600, scroll=True)\n",
    "        rlist=[pn.Row(pn.pane.Markdown(f\"Current Chat History variable\", styles={'background-color': '#F6F6F6'}))]\n",
    "        for exchange in self.chat_history:\n",
    "            rlist.append(pn.Row(pn.pane.Str(exchange)))\n",
    "        return pn.WidgetBox(*rlist, width=600, scroll=True)\n",
    "\n",
    "    def clr_history(self,count=0):\n",
    "        self.chat_history = []\n",
    "        return \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/pydantic/_migration.py:283: UserWarning: `pydantic.error_wrappers:ValidationError` has been moved to `pydantic:ValidationError`.\n",
      "  warnings.warn(f'`{import_path}` has been moved to `{new_location}`.')\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "<pre>Traceback (most recent call last):\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/pyviz_comms/__init__.py&quot;, line 340, in _handle_msg\n",
       "    self._on_msg(msg)\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/panel/viewable.py&quot;, line 478, in _on_msg\n",
       "    doc.unhold()\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/bokeh/document/document.py&quot;, line 776, in unhold\n",
       "    self.callbacks.unhold()\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/bokeh/document/callbacks.py&quot;, line 431, in unhold\n",
       "    self.trigger_on_change(event)\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/bokeh/document/callbacks.py&quot;, line 408, in trigger_on_change\n",
       "    invoke_with_curdoc(doc, event.callback_invoker)\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/bokeh/document/callbacks.py&quot;, line 443, in invoke_with_curdoc\n",
       "    return f()\n",
       "           ^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/bokeh/util/callback_manager.py&quot;, line 185, in invoke\n",
       "    callback(attr, old, new)\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/panel/reactive.py&quot;, line 471, in _comm_change\n",
       "    state._handle_exception(e)\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/panel/io/state.py&quot;, line 442, in _handle_exception\n",
       "    raise exception\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/panel/reactive.py&quot;, line 469, in _comm_change\n",
       "    self._schedule_change(doc, comm)\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/panel/reactive.py&quot;, line 451, in _schedule_change\n",
       "    self._change_event(doc)\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/panel/reactive.py&quot;, line 447, in _change_event\n",
       "    self._process_events(events)\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/panel/reactive.py&quot;, line 385, in _process_events\n",
       "    self.param.update(**self_events)\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/param/parameterized.py&quot;, line 2282, in update\n",
       "    restore = self_._update(*args, **kwargs)\n",
       "              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/param/parameterized.py&quot;, line 2322, in _update\n",
       "    self_._batch_call_watchers()\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/param/parameterized.py&quot;, line 2506, in _batch_call_watchers\n",
       "    self_._execute_watcher(watcher, events)\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/param/parameterized.py&quot;, line 2468, in _execute_watcher\n",
       "    watcher.fn(*args, **kwargs)\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/panel/param.py&quot;, line 865, in _replace_pane\n",
       "    new_object = self.eval(self.object)\n",
       "                 ^^^^^^^^^^^^^^^^^^^^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/panel/param.py&quot;, line 824, in eval\n",
       "    return eval_function_with_deps(function)\n",
       "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/param/parameterized.py&quot;, line 162, in eval_function_with_deps\n",
       "    return function(*args, **kwargs)\n",
       "           ^^^^^^^^^^^^^^^^^^^^^^^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/param/depends.py&quot;, line 41, in _depends\n",
       "    return func(*args, **kw)\n",
       "           ^^^^^^^^^^^^^^^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/param/reactive.py&quot;, line 431, in wrapped\n",
       "    return eval_fn()(*combined_args, **combined_kwargs)\n",
       "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
       "  File &quot;/var/folders/jl/yt17k74x37l_mv93mfg5h7n00000gn/T/ipykernel_33817/2068417428.py&quot;, line 31, in convchain\n",
       "    result = self.qa({&quot;question&quot;: query, &quot;chat_history&quot;: self.chat_history})\n",
       "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/langchain_core/_api/deprecation.py&quot;, line 142, in warning_emitting_wrapper\n",
       "    return wrapped(*args, **kwargs)\n",
       "           ^^^^^^^^^^^^^^^^^^^^^^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/langchain/chains/base.py&quot;, line 363, in __call__\n",
       "    return self.invoke(\n",
       "           ^^^^^^^^^^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/langchain/chains/base.py&quot;, line 162, in invoke\n",
       "    raise e\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/langchain/chains/base.py&quot;, line 156, in invoke\n",
       "    self._call(inputs, run_manager=run_manager)\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/langchain/chains/conversational_retrieval/base.py&quot;, line 155, in _call\n",
       "    docs = self._get_docs(new_question, inputs, run_manager=_run_manager)\n",
       "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/langchain/chains/conversational_retrieval/base.py&quot;, line 317, in _get_docs\n",
       "    docs = self.retriever.get_relevant_documents(\n",
       "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/langchain_core/retrievers.py&quot;, line 223, in get_relevant_documents\n",
       "    raise e\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/langchain_core/retrievers.py&quot;, line 216, in get_relevant_documents\n",
       "    result = self._get_relevant_documents(\n",
       "             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/langchain_core/vectorstores.py&quot;, line 654, in _get_relevant_documents\n",
       "    docs = self.vectorstore.similarity_search(query, **self.search_kwargs)\n",
       "           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/langchain_community/vectorstores/docarray/base.py&quot;, line 127, in similarity_search\n",
       "    results = self.similarity_search_with_score(query, k=k, **kwargs)\n",
       "              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/langchain_community/vectorstores/docarray/base.py&quot;, line 106, in similarity_search_with_score\n",
       "    query_doc = self.doc_cls(embedding=query_embedding)  # type: ignore\n",
       "                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
       "  File &quot;/Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages/pydantic/main.py&quot;, line 164, in __init__\n",
       "    __pydantic_self__.__pydantic_validator__.validate_python(data, self_instance=__pydantic_self__)\n",
       "pydantic_core._pydantic_core.ValidationError: 2 validation errors for DocArrayDoc\n",
       "text\n",
       "  Field required [type=missing, input_value={&#x27;embedding&#x27;: [-0.0093472... -0.022619765636242226]}, input_type=dict]\n",
       "    For further information visit https://errors.pydantic.dev/2.5/v/missing\n",
       "metadata\n",
       "  Field required [type=missing, input_value={&#x27;embedding&#x27;: [-0.0093472... -0.022619765636242226]}, input_type=dict]\n",
       "    For further information visit https://errors.pydantic.dev/2.5/v/missing\n",
       "</pre>\n"
      ]
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url(\\\"data:image/svg+xml;base64,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\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"id\":\"7095fc1a-e581-4705-8dd3-365edc53bad9\"},{\"id\":\"f1dba255-1198-4bf5-b4dd-4d757f3159d8\"},{\"id\":\"a16dcdc1-1c28-4f89-a50c-17c8574576b0\"},{\"id\":\"876fc4d9-ba06-459b-bde2-11fc3df8299e\"}],\"margin\":[5,10],\"align\":\"start\",\"label\":\"Clear History\"}},{\"type\":\"object\",\"name\":\"panel.models.markup.HTML\",\"id\":\"8bd0efc3-7ad3-4bc7-9bcf-73d11217472c\",\"attributes\":{\"css_classes\":[\"markdown\"],\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHN0eWxlPSJtYXJnaW46IGF1dG87IGJhY2tncm91bmQ6IG5vbmU7IGRpc3BsYXk6IGJsb2NrOyBzaGFwZS1yZW5kZXJpbmc6IGF1dG87IiB2aWV3Qm94PSIwIDAgMTAwIDEwMCIgcHJlc2VydmVBc3BlY3RSYXRpbz0ieE1pZFlNaWQiPiAgPGNpcmNsZSBjeD0iNTAiIGN5PSI1MCIgZmlsbD0ibm9uZSIgc3Ryb2tlPSIjYzNjM2MzIiBzdHJva2Utd2lkdGg9IjEwIiByPSIzNSIgc3Ryb2tlLWRhc2hhcnJheT0iMTY0LjkzMzYxNDMxMzQ2NDE1IDU2Ljk3Nzg3MTQzNzgyMTM4Ij4gICAgPGFuaW1hdGVUcmFuc2Zvcm0gYXR0cmlidXRlTmFtZT0idHJhbnNmb3JtIiB0eXBlPSJyb3RhdGUiIHJlcGVhdENvdW50PSJpbmRlZmluaXRlIiBkdXI9IjFzIiB2YWx1ZXM9IjAgNTAgNTA7MzYwIDUwIDUwIiBrZXlUaW1lcz0iMDsxIj48L2FuaW1hdGVUcmFuc2Zvcm0+ICA8L2NpcmNsZT48L3N2Zz4=\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"id\":\"7095fc1a-e581-4705-8dd3-365edc53bad9\"},{\"id\":\"3e8b1632-00cb-4d16-ae7e-a88f839542df\"},{\"id\":\"a16dcdc1-1c28-4f89-a50c-17c8574576b0\"},{\"id\":\"876fc4d9-ba06-459b-bde2-11fc3df8299e\"}],\"margin\":[5,10],\"align\":\"start\",\"text\":\"&lt;p&gt;Clears chat history. Can use to start a new topic&lt;/p&gt;\\n\"}}]}},{\"type\":\"object\",\"name\":\"Div\",\"id\":\"790f99f4-f630-49fd-8732-7e7b97045ad0\",\"attributes\":{\"name\":\"Divider00181\",\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"41b1e544-5c16-4c68-92be-52e6bfada0a0\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.3.6/dist/css/loading.css\"}},{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"32dd472a-5f60-47c3-88e3-2e4cfb107458\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.3.6/dist/css/divider.css\"}}],\"margin\":0,\"width_policy\":\"fit\",\"align\":\"start\",\"text\":\"<hr>\"}},{\"type\":\"object\",\"name\":\"Row\",\"id\":\"dcc39f44-cdeb-493a-acf0-2032e225ca6f\",\"attributes\":{\"name\":\"Row00184\",\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"id\":\"7095fc1a-e581-4705-8dd3-365edc53bad9\"},{\"id\":\"0ceab17e-1ad5-4320-b6d5-4cff971caed9\"},{\"id\":\"a16dcdc1-1c28-4f89-a50c-17c8574576b0\"},{\"id\":\"876fc4d9-ba06-459b-bde2-11fc3df8299e\"}],\"margin\":0,\"align\":\"start\",\"children\":[{\"type\":\"object\",\"name\":\"panel.models.markup.HTML\",\"id\":\"6990ff45-4597-4d4d-9143-151146aadf84\",\"attributes\":{\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"id\":\"7095fc1a-e581-4705-8dd3-365edc53bad9\"},{\"id\":\"a16dcdc1-1c28-4f89-a50c-17c8574576b0\"},{\"id\":\"876fc4d9-ba06-459b-bde2-11fc3df8299e\"}],\"width\":400,\"min_width\":400,\"margin\":[5,10],\"align\":\"start\",\"text\":\"&lt;img src=&quot;./img/convchain.jpg&quot;  style=&quot;max-width: 100%; max-height: 100%; object-fit: contain; width: 400px; height: auto;&quot;&gt;&lt;/img&gt;\"}}]}}]}}}}]}}]}},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"7babf762-0496-4d41-a294-79797020e08a\",\"attributes\":{\"plot_id\":\"d13bbc76-d144-414f-8a10-b8c3fe78b250\",\"comm_id\":\"ded9c20296d8428f82c1fab32456f37a\",\"client_comm_id\":\"ab7e64df5c07492ea11a99a284cc3a71\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"mode\",\"kind\":\"Any\",\"default\":\"warn\"},{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"copy_to_clipboard1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationAreaBase1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
       "  var render_items = [{\"docid\":\"26cabd9f-caaa-423a-baca-f54791121d54\",\"roots\":{\"d13bbc76-d144-414f-8a10-b8c3fe78b250\":\"a28e56c9-cd4b-4738-b9d8-8b2e29b82819\"},\"root_ids\":[\"d13bbc76-d144-414f-8a10-b8c3fe78b250\"]}];\n",
       "  var docs = Object.values(docs_json)\n",
       "  if (!docs) {\n",
       "    return\n",
       "  }\n",
       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
       "  function embed_document(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "    for (const render_item of render_items) {\n",
       "      for (const root_id of render_item.root_ids) {\n",
       "\tconst id_el = document.getElementById(root_id)\n",
       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
       "\t  const root_el = id_el.children[0]\n",
       "\t  root_el.id = root_el.id + '-rendered'\n",
       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  function get_bokeh(root) {\n",
       "    if (root.Bokeh === undefined) {\n",
       "      return null\n",
       "    } else if (root.Bokeh.version !== py_version) {\n",
       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
       "\treturn null\n",
       "      }\n",
       "      return root.Bokeh.versions.get(py_version);\n",
       "    } else if (root.Bokeh.version === py_version) {\n",
       "      return root.Bokeh\n",
       "    }\n",
       "    return null\n",
       "  }\n",
       "  function is_loaded(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
       "  }\n",
       "  if (is_loaded(root)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (is_loaded(root)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "\t  var Bokeh = get_bokeh(root)\n",
       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
       "\t  } else {\n",
       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
       "\t    embed_document(root)\n",
       "\t  }\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       "Column\n",
       "    [0] Row\n",
       "        [0] Markdown(str)\n",
       "    [1] Tabs\n",
       "        [0] Column\n",
       "            [0] Row\n",
       "                [0] TextInput(placeholder='Enter text here…')\n",
       "            [1] Divider()\n",
       "            [2] ParamFunction(function, _pane=WidgetBox, defer_load=False, height=300, loading_indicator=True)\n",
       "            [3] Divider()\n",
       "        [1] Column\n",
       "            [0] ParamMethod(method, _pane=Column, defer_load=False)\n",
       "            [1] Divider()\n",
       "            [2] ParamMethod(method, _pane=Str, defer_load=False)\n",
       "        [2] Column\n",
       "            [0] ParamMethod(method, _pane=WidgetBox, defer_load=False)\n",
       "            [1] Divider()\n",
       "        [3] Column\n",
       "            [0] Row\n",
       "                [0] FileInput(accept='.pdf')\n",
       "                [1] Button(button_type='primary', name='Load DB')\n",
       "                [2] ParamFunction(function, _pane=Markdown, defer_load=False)\n",
       "            [1] Row\n",
       "                [0] Button(button_type='warning', name='Clear History')\n",
       "                [1] Markdown(str)\n",
       "            [2] Divider()\n",
       "            [3] Row\n",
       "                [0] Image(str, width=400)"
      ]
     },
     "execution_count": 6,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "d13bbc76-d144-414f-8a10-b8c3fe78b250"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cb = cbfs()\n",
    "\n",
    "file_input = pn.widgets.FileInput(accept='.pdf')\n",
    "button_load = pn.widgets.Button(name=\"Load DB\", button_type='primary')\n",
    "button_clearhistory = pn.widgets.Button(name=\"Clear History\", button_type='warning')\n",
    "button_clearhistory.on_click(cb.clr_history)\n",
    "inp = pn.widgets.TextInput( placeholder='Enter text here…')\n",
    "\n",
    "bound_button_load = pn.bind(cb.call_load_db, button_load.param.clicks)\n",
    "conversation = pn.bind(cb.convchain, inp) \n",
    "\n",
    "jpg_pane = pn.pane.Image( './img/convchain.jpg')\n",
    "\n",
    "tab1 = pn.Column(\n",
    "    pn.Row(inp),\n",
    "    pn.layout.Divider(),\n",
    "    pn.panel(conversation,  loading_indicator=True, height=300),\n",
    "    pn.layout.Divider(),\n",
    ")\n",
    "tab2= pn.Column(\n",
    "    pn.panel(cb.get_lquest),\n",
    "    pn.layout.Divider(),\n",
    "    pn.panel(cb.get_sources ),\n",
    ")\n",
    "tab3= pn.Column(\n",
    "    pn.panel(cb.get_chats),\n",
    "    pn.layout.Divider(),\n",
    ")\n",
    "tab4=pn.Column(\n",
    "    pn.Row( file_input, button_load, bound_button_load),\n",
    "    pn.Row( button_clearhistory, pn.pane.Markdown(\"Clears chat history. Can use to start a new topic\" )),\n",
    "    pn.layout.Divider(),\n",
    "    pn.Row(jpg_pane.clone(width=400))\n",
    ")\n",
    "dashboard = pn.Column(\n",
    "    pn.Row(pn.pane.Markdown('# ChatWithYourData_Bot')),\n",
    "    pn.Tabs(('Conversation', tab1), ('Database', tab2), ('Chat History', tab3),('Configure', tab4))\n",
    ")\n",
    "dashboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pydantic in /Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages (2.5.3)\n",
      "Requirement already satisfied: annotated-types>=0.4.0 in /Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages (from pydantic) (0.6.0)\n",
      "Requirement already satisfied: pydantic-core==2.14.6 in /Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages (from pydantic) (2.14.6)\n",
      "Requirement already satisfied: typing-extensions>=4.6.1 in /Users/seb/anaconda3/envs/tutorials/lib/python3.11/site-packages (from pydantic) (4.9.0)\n"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "tutorials",
   "language": "python",
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  "language_info": {
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