Commit

Dockerfile

@@ -0,0 +1,39 @@
+FROM python:3.10.15-bullseye
+
+RUN apt-get update && \
+    apt-get install -y \
+    # General dependencies
+    locales \
+    locales-all && \
+    # Clean local repository of package files since they won't be needed anymore.
+    # Make sure this line is called after all apt-get update/install commands have
+    # run.
+    apt-get clean && \
+    # Also delete the index files which we also don't need anymore.
+    rm -rf /var/lib/apt/lists/*
+
+ENV LC_ALL en_US.UTF-8
+ENV LANG en_US.UTF-8
+ENV LANGUAGE en_US.UTF-8
+
+# Create and activate virtual environment
+RUN python -m venv /opt/venv
+ENV PATH="/opt/venv/bin:$PATH"
+
+# Install dependencies
+COPY requirements.txt .
+RUN pip install -r requirements.txt
+
+# Create non-root user and give write access to /opt/venv
+RUN groupadd -g 900 mesop && \
+    useradd -u 900 -s /bin/bash -g mesop mesop && \
+    chown -R mesop:mesop /opt/venv && chmod -R 777 /opt/venv
+
+USER mesop
+
+# Add app code here
+COPY . /srv/mesop-app
+WORKDIR /srv/mesop-app
+
+# Run Mesop through gunicorn. Should be available at localhost:8080
+CMD ["gunicorn", "--bind", "0.0.0.0:8080", "main:me"]

README.md

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+---
+title: Mesop Doc Bot
+emoji: 👓
+colorFrom: red
+colorTo: yellow
+sdk: docker
+pinned: false
+license: apache-2.0
+app_port: 8080
+---
+
+# Docbot
+
+Answers questions grounded based on docs
+
+## Setup
+
+From workspace root:
+
+```sh
+rm -rf ai/docbot/venv && \
+virtualenv --python python3 ai/docbot/venv && \
+source ai/docbot/venv/bin/activate && \
+pip install -r ai/docbot/requirements.txt
+```
+
+## How to use
+
+**Run app**:
+
+```sh
+mesop chat.py
+```
+
+**Create index**:
+
+```sh
+python docs_index.py --build-index
+```
+
+**Load (or create, if it doesn't exist yet) index**:
+
+```sh
+python docs_index.py
+```
+
+## Evals
+
+**Record eval results**
+
+```py
+$ python recorder.py --out-dir gen/evals/one_source
+```
+
+**View eval results**
+
+```py
+$ EVAL_DIR=gen/evals/no_source_1 EVAL_DIR_2=gen/evals/one_source mesop eval_viewer.py
+```
+
+## Roadmap
+
+TODOs:
+
+- Respect dark themes into frame
+- Auto-focus into prompt (via post message) _DONE_
+- Support ESC to close iframe _DONE_
+- Do evals against suggested questions _DONE_
+- Prompt engineer
+  - Do not show code _skip_
+  - File new issue if asking for feature that doesn't exist _skip_
+
+MAYBE:
+
+- Ask Mesop to consolidate sources from the same page
+
+### UX
+
+- Scroll to specific part of text? DONE
+- Show code (syntax highlighting)
+- Don't show sources which are not cited? done
+- Renumber?? done
+- File GitHub issue if the response isn't good DONE
+
+### APIs
+
+- Use Google embedding API? done
+
+### Indexing
+
+- Index GitHub issues / discussions?
+  - https://docs.llamaindex.ai/en/stable/examples/usecases/github_issue_analysis/
+- DONE filter out blog posts? (the --- mark settings)
+- DONE filter out internal docs, e.g. bazel commands
+- DONE set title for all pages OR retrieve title by using mkdocs.yml??
+- Maybe load in the code snippets? Depends on whether that's a goal.
+
+### Docs TODOs:
+
+- Why doesn't mesop have this new feature? attribute is missing

citation.js

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+import {
+  LitElement,
+  html,
+  css,
+} from 'https://cdn.jsdelivr.net/gh/lit/dist@3/core/lit-core.min.js';
+
+class CitationComponent extends LitElement {
+  static styles = css`
+    a {
+      display: block;
+      text-decoration: none;
+      color: var(--sys-on-surface);
+    }
+
+    .container {
+      background: var(--sys-surface-container-high);
+      border-radius: 12px;
+    }
+
+    .container:hover {
+      background: var(--sys-surface-container-highest);
+    }
+  `;
+
+  static properties = {
+    url: {type: String},
+  };
+
+  constructor() {
+    super();
+    this.url = '';
+  }
+
+  render() {
+    return html`
+      <a class="container" href="${this.url}" target="_blank">
+        <slot></slot>
+      </a>
+    `;
+  }
+
+  _onClick() {
+    window.open(this.url, '_blank');
+    console.log('open url', this.url);
+  }
+}
+
+customElements.define('citation-component', CitationComponent);

deploy_to_hf.sh

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+#!/bin/bash
+
+set -e
+
+error_handler() {
+    echo "Error: An error occurred. Exiting script."
+    exit 1
+}
+
+# Set up error handling
+trap error_handler ERR
+
+if [ $# -eq 0 ]; then
+    echo "Error: Please provide a destination path as an argument."
+    exit 1
+fi
+
+DEST_PATH="$1"
+
+if [ ! -d "$DEST_PATH" ]; then
+    echo "Destination path does not exist. Creating it now."
+    mkdir -p "$DEST_PATH"
+fi
+
+# Build the docs index
+cd ai/docbot && python docs_index.py --build-index && cd -
+
+# Get the path of this script which is the demo dir.
+DEMO_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
+cp -R "$DEMO_DIR/" "$DEST_PATH"
+echo "Demo files have been copied to $DEST_PATH"
+cd "$DEST_PATH/docbot"
+echo "Changed directory to $DEST_PATH"
+
+git init
+git branch -m main
+git config user.name github-actions[bot]
+git config user.email github-actions[bot]@users.noreply.github.com
+echo "Configured git user"
+git add .
+git commit -m "Commit"
+git remote add hf https://wwwillchen:$HF_TOKEN@huggingface.co/spaces/wwwillchen/mesop-docs-bot || true
+git push --force --set-upstream hf main
+
+echo "Pushed to: https://huggingface.co/spaces/wwwillchen/mesop-docs-bot. Check the logs to see that it's deployed correctly."

docs_index.py

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+import os
+import sys
+
+import nest_asyncio
+import Stemmer
+from llama_index.core import (
+  PromptTemplate,
+  Settings,
+  SimpleDirectoryReader,
+  StorageContext,
+  VectorStoreIndex,
+  load_index_from_storage,
+)
+from llama_index.core.node_parser import SentenceSplitter
+from llama_index.core.query_engine import CitationQueryEngine
+from llama_index.core.retrievers import QueryFusionRetriever
+from llama_index.core.schema import NodeWithScore as NodeWithScore
+from llama_index.embeddings.google import GeminiEmbedding
+from llama_index.llms.gemini import Gemini
+from llama_index.retrievers.bm25 import BM25Retriever
+
+import mesop as me
+
+nest_asyncio.apply()
+
+CITATION_QA_TEMPLATE = PromptTemplate(
+  "Please provide an answer based solely on the provided sources. "
+  "When referencing information from a source, "
+  "cite the appropriate source(s) using their corresponding numbers. "
+  "Every answer should include at least one source citation. "
+  "Only cite a source when you are explicitly referencing it. "
+  "If you are sure NONE of the sources are helpful, then say: 'Sorry, I didn't find any docs about this.'"
+  "If you are not sure if any of the sources are helpful, then say: 'You might find this helpful', where 'this' is the source's title.'"
+  "DO NOT say Source 1, Source 2, etc. Only reference sources like this: [1], [2], etc."
+  "I want you to pick just ONE source to answer the question."
+  "For example:\n"
+  "Source 1:\n"
+  "The sky is red in the evening and blue in the morning.\n"
+  "Source 2:\n"
+  "Water is wet when the sky is red.\n"
+  "Query: When is water wet?\n"
+  "Answer: Water will be wet when the sky is red [2], "
+  "which occurs in the evening [1].\n"
+  "Now it's your turn. Below are several numbered sources of information:"
+  "\n------\n"
+  "{context_str}"
+  "\n------\n"
+  "Query: {query_str}\n"
+  "Answer: "
+)
+
+os.environ["GOOGLE_API_KEY"] = os.environ["GEMINI_API_KEY"]
+
+
+def get_meta(file_path: str) -> dict[str, str]:
+  with open(file_path) as f:
+    title = f.readline().strip()
+    if title.startswith("# "):
+      title = title[2:]
+    else:
+      title = (
+        file_path.split("/")[-1]
+        .replace(".md", "")
+        .replace("-", " ")
+        .capitalize()
+      )
+
+  file_path = file_path.replace(".md", "")
+  CONST = "../../docs/"
+  docs_index = file_path.index(CONST)
+  docs_path = file_path[docs_index + len(CONST) :]
+
+  url = "https://mesop-dev.github.io/mesop/" + docs_path
+
+  print(f"URL: {url}")
+  return {
+    "url": url,
+    "title": title,
+  }
+
+
+embed_model = GeminiEmbedding(
+  model_name="models/text-embedding-004", api_key=os.environ["GOOGLE_API_KEY"]
+)
+Settings.embed_model = embed_model
+
+PERSIST_DIR = "./gen"
+
+
+def build_or_load_index():
+  if not os.path.exists(PERSIST_DIR) or "--build-index" in sys.argv:
+    print("Building index")
+
+    documents = SimpleDirectoryReader(
+      "../../docs/",
+      required_exts=[
+        ".md",
+      ],
+      exclude=[
+        "showcase.md",
+        "demo.md",
+        "blog",
+        "internal",
+      ],
+      file_metadata=get_meta,
+      recursive=True,
+    ).load_data()
+    for doc in documents:
+      doc.excluded_llm_metadata_keys = ["url"]
+    splitter = SentenceSplitter(chunk_size=512)
+
+    nodes = splitter.get_nodes_from_documents(documents)
+    bm25_retriever = BM25Retriever.from_defaults(
+      nodes=nodes,
+      similarity_top_k=5,
+      # Optional: We can pass in the stemmer and set the language for stopwords
+      # This is important for removing stopwords and stemming the query + text
+      # The default is english for both
+      stemmer=Stemmer.Stemmer("english"),
+      language="english",
+    )
+    bm25_retriever.persist(PERSIST_DIR + "/bm25_retriever")
+
+    index = VectorStoreIndex.from_documents(documents, embed_model=embed_model)
+    index.storage_context.persist(persist_dir=PERSIST_DIR)
+    return index, bm25_retriever
+  else:
+    print("Loading index")
+    bm25_retriever = BM25Retriever.from_persist_dir(
+      PERSIST_DIR + "/bm25_retriever"
+    )
+    storage_context = StorageContext.from_defaults(persist_dir=PERSIST_DIR)
+    index = load_index_from_storage(storage_context)
+    return index, bm25_retriever
+
+
+if me.runtime().is_hot_reload_in_progress:
+  print("Hot reload - skip building index!")
+  query_engine = me._query_engine
+  bm25_retriever = me._bm25_retriever
+
+else:
+  index, bm25_retriever = build_or_load_index()
+  llm = Gemini(model="models/gemini-flash-latest")
+  retriever = QueryFusionRetriever(
+    [
+      index.as_retriever(similarity_top_k=5),
+      bm25_retriever,
+    ],
+    llm=llm,
+    num_queries=1,
+    use_async=True,
+    similarity_top_k=5,
+  )
+  query_engine = CitationQueryEngine.from_args(
+    index,
+    retriever=retriever,
+    llm=llm,
+    citation_qa_template=CITATION_QA_TEMPLATE,
+    similarity_top_k=5,
+    embedding_model=embed_model,
+    streaming=True,
+  )
+
+  blocking_query_engine = CitationQueryEngine.from_args(
+    index,
+    retriever=retriever,
+    llm=llm,
+    citation_qa_template=CITATION_QA_TEMPLATE,
+    similarity_top_k=5,
+    embedding_model=embed_model,
+    streaming=False,
+  )
+  # TODO: replace with proper mechanism for persisting objects
+  # across hot reloads
+  me._query_engine = query_engine
+  me._bm25_retriever = bm25_retriever
+
+
+NEWLINE = "\n"
+
+
+def ask(query: str):
+  return query_engine.query(query)
+
+
+def retrieve(query: str):
+  return bm25_retriever.retrieve(query)

eval_viewer.py

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+import itertools
+import os
+import sys
+import urllib.parse
+from dataclasses import dataclass, field
+
+import mesop as me
+
+# Get the directory from the environment variable
+EVAL_DIR = os.environ.get("EVAL_DIR")
+
+if EVAL_DIR:
+  print(f"Directory set to: {EVAL_DIR}")
+else:
+  print(
+    "No directory specified. Exiting! Set the EVAL_DIR environment variable."
+  )
+  sys.exit(1)
+
+EVAL_DIR_2 = os.environ.get("EVAL_DIR_2")
+
+if EVAL_DIR_2:
+  print(f"Eval directory 2 set to: {EVAL_DIR_2}")
+
+
+@dataclass
+class Item:
+  query: str = ""
+  input: str = ""
+  output: str = ""
+
+
+@dataclass
+class EvalGroup:
+  items: list[Item] = field(default_factory=list)
+
+
+@me.stateclass
+class State:
+  directories: list[str]
+  group_1: EvalGroup
+  group_2: EvalGroup
+
+
+def load_eval_dir(eval_dir: str):
+  # Read all directories from args.dir
+  directories = [
+    d for d in os.listdir(eval_dir) if os.path.isdir(os.path.join(eval_dir, d))
+  ]
+  items: list[Item] = []
+  for dir in directories:
+    input_path = os.path.join(eval_dir, dir, "input.txt")
+    output_path = os.path.join(eval_dir, dir, "output.txt")
+
+    with open(input_path) as f:
+      input_content = f.read()
+    with open(output_path) as f:
+      output_content = f.read()
+
+    item = Item(
+      input=input_content,
+      output=output_content,
+      query=urllib.parse.unquote(dir),
+    )
+    items.append(item)
+  return items
+
+
+def on_load(e: me.LoadEvent):
+  state = me.state(State)
+  assert EVAL_DIR
+  state.group_1.items = load_eval_dir(EVAL_DIR)
+  if EVAL_DIR_2:
+    state.group_2.items = load_eval_dir(EVAL_DIR_2)
+    print("state.group_2.items", state.group_2.items)
+
+  # Store the directories in the state for later use
+  # me.state(State).directories = directories
+
+
+@me.page(
+  on_load=on_load,
+  security_policy=me.SecurityPolicy(
+    allowed_script_srcs=[
+      "https://cdn.jsdelivr.net",
+    ]
+  ),
+)
+def index():
+  state = me.state(State)
+  with scrollable():
+    with me.box(
+      style=me.Style(
+        margin=me.Margin.symmetric(horizontal="auto", vertical=24),
+        # background="white",
+        padding=me.Padding.symmetric(horizontal=16),
+      )
+    ):
+      me.text("Eval viewer", type="headline-3")
+      me.text(f"Group 1: {len(state.group_1.items)} items")
+      me.text(f"Group 2: {len(state.group_2.items)} items")
+
+      # Zip group_1 and group_2 items
+      zipped_items = list(
+        itertools.zip_longest(
+          state.group_1.items, state.group_2.items, fillvalue=None
+        )
+      )
+      with me.box(
+        style=me.Style(
+          display="grid",
+          grid_template_columns="160px 300px 1fr 300px 1fr"
+          if state.group_2.items
+          else "160px 1fr 1fr",
+          gap=16,
+        )
+      ):
+        # Header
+        me.text("Query", style=me.Style(font_weight=500))
+        me.text("Input (1)", style=me.Style(font_weight=500))
+        me.text("Output (1)", style=me.Style(font_weight=500))
+        if state.group_2.items:
+          me.text("Input (2)", style=me.Style(font_weight=500))
+          me.text("Output (2)", style=me.Style(font_weight=500))
+        # Body
+        for item_1, item_2 in zipped_items:
+          if item_1:
+            me.text(item_1.query, style=me.Style(font_weight=500))
+            me.markdown(
+              item_1.input, style=me.Style(overflow_y="auto", max_height=400)
+            )
+            me.text(item_1.output)
+
+          if item_2:
+            me.markdown(
+              item_2.input, style=me.Style(overflow_y="auto", max_height=400)
+            )
+            me.text(item_2.output)
+
+
+@me.web_component(path="./scrollable.js")
+def scrollable(
+  *,
+  key: str | None = None,
+):
+  return me.insert_web_component(
+    name="scrollable-component",
+    key=key,
+  )

frame_listener.js

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+// Listen for 'focus' message from the parent window
+window.addEventListener('message', function (event) {
+  if (event.data === 'focus') {
+    // Find the textarea element
+    const textarea = document.querySelector('textarea');
+    console.log('focusing on textarea', textarea);
+    // If the textarea is found, focus on it
+    if (textarea) {
+      textarea.focus();
+    } else {
+      console.warn('Textarea not found for focus');
+    }
+  }
+});
+
+window.addEventListener('keydown', function (event) {
+  if (event.key === 'Escape') {
+    if (document.activeElement) {
+      document.activeElement.blur();
+    }
+    // Send a message to the parent window to close this iframe
+    window.parent.postMessage('closeDocbot', '*');
+  }
+});

gen/bm25_retriever/corpus.mmindex.json

@@ -0,0 +1 @@
+[0, 1458, 2833, 4188, 5580, 6906, 8205, 9686, 11068, 12431, 13999, 15367, 16714, 17934, 19236, 20471, 22878, 24507, 26058, 28184, 30194, 33572, 36486, 37986, 39471, 40953, 42418, 44129, 45501, 47145, 49547, 51007, 52519, 54023, 55430, 56659, 58025, 59680, 60903, 62275, 63498, 65003, 66443, 67784, 69104, 70495, 72006, 73285, 74717, 76542, 77978, 79705, 81240, 82584, 83917, 85277, 86601, 87872, 89416, 91005, 92302, 93737, 95007, 96455, 97720, 99707, 101635, 102990, 104599, 106332, 110817, 112868, 114374, 117415, 118959, 120369, 121851, 123486, 126141, 130040, 134190, 138342, 142357, 146522, 149451, 151091, 152510, 154113, 155674, 159233, 162297, 165993, 170040, 173044, 174590, 176286, 177690, 179288, 180854, 184597, 189035, 193281, 196518, 199165, 201250, 204290, 206073, 207462, 209383, 210812, 212168, 213524, 214807, 216386, 218046, 219842, 221464, 222927, 224558, 225908, 227458, 229409, 230930, 232879, 234600, 236817, 238615, 240696, 242401, 244319, 245806, 247636, 248979, 250275, 251552, 253344, 254689, 256355, 257732, 259028, 260305, 261637, 262919, 264178, 265485, 266788, 268157, 269520, 270872, 272367, 273658, 274947, 276399, 277730, 279019, 280276, 281638, 282955, 284453, 285789, 287083, 288351, 289780, 291118, 292515, 293987, 295367, 296839, 298196, 299506, 300801, 302113, 303409, 304686, 306265, 307631, 309133, 310733, 312027, 313295, 314623, 315912, 317180, 318470, 319766, 321043, 322461, 323725, 325484, 327060, 328628, 331088, 332365, 334477, 337171, 338597, 340452, 342994, 344380, 345676, 347085, 348397, 349686, 350954, 352257, 353579, 354883, 356193, 357482, 358750, 360155, 361500, 362919, 364356, 365729, 367105, 368436, 369732, 371115, 372475, 373783, 375245, 376608, 377918, 379213, 380610, 381955, 383438, 384799, 386102, 387449, 388787, 390083, 391360, 392770, 394122, 395451, 396860, 398205, 399526, 400844, 402133, 403401, 404851, 406168, 407598, 408913, 410223, 411518, 412919, 414236, 415706, 417049, 418345, 419622, 420902, 422162, 423912, 425292, 427037, 428559, 430025, 431289, 432920, 434296, 436316, 438143, 439768, 441515, 443164, 445424, 446933, 448470, 450009, 451555, 453642, 455151, 456537, 457871, 459247, 460751, 462437, 464156, 465563, 467611, 469724, 471541, 473638, 475071, 477110, 478613, 480647, 482052, 483617, 485154, 487819, 490300, 491964, 493356, 494807, 496267, 497626, 499029, 500825, 502345, 504030, 505394, 506940, 508562, 510076, 511439, 512757, 514112, 515511, 517177, 518836, 520264, 521604, 522978, 524420, 525820, 527371, 529009, 530401, 531820, 533547, 535027, 536533, 538008, 540580, 541875, 543490, 545591, 547710, 548990, 551588, 553756, 555043, 557722, 559101, 560582, 562933, 564426, 565895, 567176, 569394, 571263, 573033, 575018, 576365, 577671, 579116, 580744, 582189, 583435, 584883, 586383, 587988, 589857, 591091, 592718, 594828, 596730, 598953, 600557, 601931, 603458, 605132, 606537, 608007, 609305, 611110, 612874, 614536, 615945, 618083, 619693, 621120, 622676, 624135, 625829, 629362, 631225, 632730, 634091, 635630, 637253, 638772, 640171, 641914, 643519, 645258, 646673, 648607, 650345, 652476, 653982, 656110, 657807, 660136, 661423, 662841, 664285, 665870, 667352, 669243, 670819, 672428, 673779, 675445, 677119, 679960, 681454, 683076, 684895, 687106, 688778, 690537, 691976, 693331, 694793, 696615, 698407, 700233, 701999, 703440, 704712, 706357, 708173, 709906, 711536, 713107, 714474, 717320, 721298, 725385, 729690, 733485, 736372, 739749, 741015, 742816, 744236, 745806, 747546, 749057, 750409, 752136, 755110, 756937, 758858, 760836, 762294, 764057, 765402, 766779, 768643, 770148, 772509, 774819, 777134, 778485]

gen/bm25_retriever/params.index.json

@@ -0,0 +1,11 @@
+{
+    "k1": 1.5,
+    "b": 0.75,
+    "delta": 0.5,
+    "method": "lucene",
+    "idf_method": "lucene",
+    "dtype": "float32",
+    "int_dtype": "int32",
+    "num_docs": 462,
+    "version": "0.1.10"
+}

gen/bm25_retriever/retriever.json

@@ -0,0 +1,4 @@
+{
+  "similarity_top_k": 5,
+  "verbose": false
+}

gen/bm25_retriever/vocab.index.json

@@ -0,0 +1 @@
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"dark_mod": 1556, "principl": 1557, "39": 1558, "term": 1559, "interfac": 1560, "general": 1561, "resiz": 1562, "break": 1563, "trace": 1564, "paradigm": 1565, "respons": 1566, "perform": 1567, "send_messag": 1568, "link_compon": 1569, "me": 1570, "notic": 1571, "hashtag": 1572, "front": 1573, "admin": 1574, "subtl": 1575, "contribut": 1576, "client": 1577, "progressbaranimationendev": 1578, "finish": 1579, "individu": 1580, "nestedst": 1581, "bottom": 1582, "statement": 1583, "txt": 1584, "footgun": 1585, "dictionari": 1586, "metadata": 1587, "have": 1588, "credenti": 1589, "think": 1590, "callback": 1591, "process": 1592, "detect_object": 1593, "typeerror": 1594, "print": 1595, "kind": 1596, "person": 1597, "framework": 1598, "doesn": 1599, "you": 1600, "doe": 1601, "refin": 1602, "mesop_websockets_en": 1603, "content_slide_toggl": 1604, "appli": 1605, "myapppath": 1606, "headlin": 1607, "do": 1608, "theme_var": 1609, "tosurl": 1610, "max_output_token": 1611, "use": 1612, "explain": 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"scratch": 1852, "entir": 1853, "__native__": 1854, "8192": 1855, "localhost": 1856, "say": 1857, "scroll": 1858, "co": 1859, "equival": 1860, "zone": 1861, "defer": 1862, "empti": 1863, "render": 1864, "sure": 1865, "sonnet": 1866, "align": 1867, "status_cod": 1868, "beginn": 1869, "sdk": 1870, "hamburg": 1871, "postgresql": 1872, "modul": 1873, "rather": 1874, "socket": 1875, "symmetr": 1876, "deprec": 1877, "auto": 1878, "switcher": 1879, "confirm": 1880, "814": 1881, "annot": 1882, "particular": 1883, "just": 1884, "content__inn": 1885, "intuit": 1886, "buffer": 1887, "ref_src": 1888, "1fr": 1889, "www": 1890, "sort": 1891, "background_color": 1892, "mesop_state_sess": 1893, "simpl": 1894, "mesop_colab_getting_start": 1895, "anatomi": 1896, "option": 1897, "choos": 1898, "on_input": 1899, "mesop_state_session_backend_sql_connection_uri": 1900, "dozen": 1901}

gen/graph_store.json

@@ -0,0 +1 @@
+{"graph_dict": {}}

gen/image__vector_store.json

@@ -0,0 +1 @@
+{"embedding_dict": {}, "text_id_to_ref_doc_id": {}, "metadata_dict": {}}

gen/index_store.json

@@ -0,0 +1 @@
+{"index_store/data": {"cddb75d8-1788-48b2-acd4-15b83e3a44c4": {"__type__": "vector_store", "__data__": "{\"index_id\": \"cddb75d8-1788-48b2-acd4-15b83e3a44c4\", \"summary\": null, \"nodes_dict\": {\"d01a41e6-8420-480a-9ce5-e6bebec77cf7\": \"d01a41e6-8420-480a-9ce5-e6bebec77cf7\", \"79bd125c-1828-4d70-a69f-0995989efca2\": \"79bd125c-1828-4d70-a69f-0995989efca2\", \"7176af37-87b6-4a26-b1f7-789c1a608b96\": \"7176af37-87b6-4a26-b1f7-789c1a608b96\", \"42b4b67d-87c2-45d7-bca5-275fdcc012fd\": \"42b4b67d-87c2-45d7-bca5-275fdcc012fd\", \"fbcc3ff6-0f89-4a3f-b1e0-a270380c0e32\": \"fbcc3ff6-0f89-4a3f-b1e0-a270380c0e32\", \"e6ed9231-df03-4f37-a120-84153a732c01\": \"e6ed9231-df03-4f37-a120-84153a732c01\", \"03ed8b20-9a76-4742-8336-fa453a6b2508\": \"03ed8b20-9a76-4742-8336-fa453a6b2508\", \"7c1ac6a1-2e24-4ee9-8bfa-9d9c37e03129\": \"7c1ac6a1-2e24-4ee9-8bfa-9d9c37e03129\", \"a6f2f452-48cc-43f4-ad9b-51b2bd49a35d\": \"a6f2f452-48cc-43f4-ad9b-51b2bd49a35d\", \"dc782681-b3fb-4224-9a6c-efecff98d416\": 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\"aeb0e70c-4de7-4610-86dc-e7ffcdfd9d03\": \"aeb0e70c-4de7-4610-86dc-e7ffcdfd9d03\", \"13f0e884-c935-4a61-9094-9682b234b730\": \"13f0e884-c935-4a61-9094-9682b234b730\", \"fbb62f9b-7501-4d68-b63b-8544825159cf\": \"fbb62f9b-7501-4d68-b63b-8544825159cf\", \"833b5770-321f-45aa-874f-4719393ebbc9\": \"833b5770-321f-45aa-874f-4719393ebbc9\", \"61593909-2f1d-4017-a399-d70f05c109eb\": \"61593909-2f1d-4017-a399-d70f05c109eb\", \"76917744-563f-4c5d-919f-e8720f689931\": \"76917744-563f-4c5d-919f-e8720f689931\", \"c751dd3d-f3fb-4da3-a34d-f93d5d4c1f98\": \"c751dd3d-f3fb-4da3-a34d-f93d5d4c1f98\", \"f83e25af-c71f-444f-bc25-825e0601e16d\": \"f83e25af-c71f-444f-bc25-825e0601e16d\", \"70ca824e-85e5-4685-98be-3423fdcd0e33\": \"70ca824e-85e5-4685-98be-3423fdcd0e33\", \"77eb0421-3cf7-433c-884d-4a11d10cb03a\": \"77eb0421-3cf7-433c-884d-4a11d10cb03a\", \"dfd6a6b0-3a4e-498b-bc2e-efe455a32ac1\": \"dfd6a6b0-3a4e-498b-bc2e-efe455a32ac1\", \"351d6e3e-8575-4fac-ba46-afdfd7ff051f\": \"351d6e3e-8575-4fac-ba46-afdfd7ff051f\", \"47cf9e55-c3bc-4cbf-ab4c-84d7f1c78afd\": \"47cf9e55-c3bc-4cbf-ab4c-84d7f1c78afd\", \"d7e58600-54ca-4e14-85dd-687491d66f55\": \"d7e58600-54ca-4e14-85dd-687491d66f55\", \"19dd198d-910d-47cb-9242-cf6c6d4bf090\": \"19dd198d-910d-47cb-9242-cf6c6d4bf090\", \"5582b18d-3474-466d-94c5-46be330f0944\": \"5582b18d-3474-466d-94c5-46be330f0944\", \"c6c3bb43-7d8b-4359-83e1-8bdfe39a2ec8\": \"c6c3bb43-7d8b-4359-83e1-8bdfe39a2ec8\", \"6f56d628-93d6-4faa-a7df-405f3a303cc6\": \"6f56d628-93d6-4faa-a7df-405f3a303cc6\", \"d0521004-4fc2-4368-9c7c-8e3f8e5d563a\": \"d0521004-4fc2-4368-9c7c-8e3f8e5d563a\", \"75aa6827-904e-4c81-ad9c-a857c6ffb1d5\": \"75aa6827-904e-4c81-ad9c-a857c6ffb1d5\", \"b42612ad-cff7-4cef-8088-56117315dc07\": \"b42612ad-cff7-4cef-8088-56117315dc07\", \"28f23e94-93ff-4eca-b285-14043251046f\": \"28f23e94-93ff-4eca-b285-14043251046f\", \"f5ea57f5-d52b-423f-94fc-63cfaf51aa23\": \"f5ea57f5-d52b-423f-94fc-63cfaf51aa23\", \"7dec0367-03c8-4be0-822f-682c5cd2dc99\": \"7dec0367-03c8-4be0-822f-682c5cd2dc99\", \"ab42878e-ba0c-4769-b6d0-cb7f39b9df9d\": \"ab42878e-ba0c-4769-b6d0-cb7f39b9df9d\", \"63bec14d-9281-4251-aa76-a53663dce909\": \"63bec14d-9281-4251-aa76-a53663dce909\", \"e651f565-17c1-4d19-baa7-7166f49763c0\": \"e651f565-17c1-4d19-baa7-7166f49763c0\", \"68de84ce-4665-482a-9260-dc942cc13e25\": \"68de84ce-4665-482a-9260-dc942cc13e25\", \"bf798134-b4f2-49ce-a6c5-30b4b492dd6c\": \"bf798134-b4f2-49ce-a6c5-30b4b492dd6c\", \"1713aa9b-7fbc-4152-8eed-a4576afb41eb\": \"1713aa9b-7fbc-4152-8eed-a4576afb41eb\", \"f2d6f155-1b64-453a-ae85-8948dab7a60d\": \"f2d6f155-1b64-453a-ae85-8948dab7a60d\", \"c9d9b143-8d10-4b33-bdb0-de32f5360d85\": \"c9d9b143-8d10-4b33-bdb0-de32f5360d85\", \"660218b0-0ab6-4f24-887b-72719e39e8c4\": \"660218b0-0ab6-4f24-887b-72719e39e8c4\", \"44150852-6f59-4d56-9dbb-64d980c43054\": \"44150852-6f59-4d56-9dbb-64d980c43054\", \"f917e233-29f8-4248-af3a-36b3550087ad\": \"f917e233-29f8-4248-af3a-36b3550087ad\"}, \"doc_id_dict\": {}, \"embeddings_dict\": {}}"}}}

main.py

@@ -0,0 +1,643 @@
+import random
+import re
+import time
+import urllib.parse
+from dataclasses import dataclass, field
+from typing import Generator, Literal
+
+from docs_index import NodeWithScore, ask, retrieve
+
+import mesop as me
+
+
+def on_load(e: me.LoadEvent):
+  state = me.state(State)
+  state.examples = random.sample(EXAMPLES, 3)
+  if "prompt" in me.query_params:
+    state.initial_input = me.query_params["prompt"]
+  me.set_theme_mode("system")
+  yield
+  me.focus_component(key=f"input-{len(state.output)}")
+  yield
+
+
+@me.page(
+  on_load=on_load,
+  security_policy=me.SecurityPolicy(
+    allowed_script_srcs=[
+      "https://cdn.jsdelivr.net",
+    ],
+    allowed_iframe_parents=[
+      "https://huggingface.co",
+      "https://mesop-dev.github.io",
+      "http://localhost:*",
+    ],
+  ),
+  title="Mesop Docs Chat",
+)
+def page():
+  frame_listener()
+  return chat()
+
+
+Role = Literal["user", "assistant"]
+
+_ROLE_USER = "user"
+_ROLE_ASSISTANT = "assistant"
+
+_BOT_USER_DEFAULT = "Mesop Docs Bot"
+
+_COLOR_BACKGROUND = me.theme_var("background")
+
+_DEFAULT_PADDING = me.Padding.all(12)
+
+_LABEL_BUTTON = "send"
+_LABEL_BUTTON_IN_PROGRESS = "pending"
+_LABEL_INPUT = "Ask Mesop Docs Bot"
+
+_STYLE_APP_CONTAINER = me.Style(
+  background=_COLOR_BACKGROUND,
+  display="flex",
+  flex_direction="column",
+  height="100%",
+)
+_STYLE_TITLE = me.Style(padding=me.Padding(left=10))
+_STYLE_CHAT_BOX = me.Style(
+  height="100%",
+  overflow_y="scroll",
+  padding=_DEFAULT_PADDING,
+  background=me.theme_var("background"),
+)
+
+_STYLE_CHAT_BUTTON = me.Style(margin=me.Margin(top=8, left=8))
+_STYLE_CHAT_BUBBLE_NAME = me.Style(
+  font_weight="bold",
+  font_size="13px",
+  padding=me.Padding(left=15, right=15, bottom=5),
+)
+
+
+def _make_style_chat_ui_container() -> me.Style:
+  return me.Style(
+    flex_grow=1,
+    display="grid",
+    grid_template_columns="repeat(1, 1fr)",
+    grid_template_rows="5fr 1fr",
+    margin=me.Margin.symmetric(vertical=0, horizontal="auto"),
+    width="min(100%)",
+    background=_COLOR_BACKGROUND,
+    box_shadow=(
+      "0 3px 1px -2px #0003, 0 2px 2px #00000024, 0 1px 5px #0000001f"
+    ),
+    padding=me.Padding(top=3, left=12, right=12),
+  )
+
+
+@dataclass(kw_only=True)
+class Chunk:
+  content: str = ""
+  citation_numbers: list[int] = field(default_factory=list)
+
+
+@dataclass(kw_only=True)
+class ChatMessage:
+  """Chat message metadata."""
+
+  role: Role = "user"
+  content: str = ""
+  chunks: list[Chunk] = field(default_factory=list)
+
+
+@dataclass(kw_only=True)
+class Citation:
+  number: int = 0
+  original_numbers: list[int] = field(default_factory=list)
+  url: str = ""
+  title: str = ""
+  breadcrumbs: list[str] = field(default_factory=list)
+  content: str = ""
+
+
+@me.stateclass
+class State:
+  input: str
+  initial_input: str
+  output: list[ChatMessage]
+  citations: list[Citation]
+  intermediate_citations: list[Citation]
+  in_progress: bool = False
+  examples: list[str]
+
+
+def on_blur(e: me.InputBlurEvent):
+  state = me.state(State)
+  state.input = e.value
+
+
+mesop_questions = [
+  "How can I reset an input component?",
+  "Show me how to style a component",
+  "Create a multi-page app",
+  "Is it possible to create custom components?",
+  "Implement authentication",
+  "Deploy a Mesop app",
+  "Optimize performance",
+  "Can I use JavaScript libraries in Mesop?",
+  "Stream UI updates from an LLM API",
+  "Debug a Mesop application",
+  "Is Mesop ready for production use?",
+  "Create a mobile-friendly and responsive UI",
+  "Handle asynchronous operations",
+  "Implement dark mode",
+  "Add tooltips to Mesop components",
+  "Render a pandas DataFrame as a table",
+  "Add charts",
+  "Handle file uploads",
+]
+
+EXAMPLES = [
+  *mesop_questions,
+  "How do I create a streaming chat UI?",
+  "How do I install Mesop?",
+  "How is Mesop different from other UI frameworks?",
+]
+
+
+def on_click_submit(e: me.ClickEvent) -> Generator[None, None, None]:
+  yield from submit()
+
+
+def on_input(e: me.InputEvent) -> Generator[None, None, None]:
+  state = me.state(State)
+  if len(e.value) > 2:
+    nodes = retrieve(e.value)
+    citations = get_citations(nodes)
+    citation_by_breadcrumb = {
+      tuple(citation.breadcrumbs): citation for citation in citations
+    }
+    state.intermediate_citations = list(citation_by_breadcrumb.values())
+    yield
+  if not e.value.endswith("\n"):
+    return
+  state.input = e.value
+
+  yield from submit()
+  me.focus_component(key=f"input-{len(state.output)}")
+  yield
+
+
+def submit():
+  state = me.state(State)
+  if state.in_progress or not state.input:
+    return
+  input = state.input
+  state.input = ""
+  yield
+
+  state.output = []
+  output = state.output
+  output.append(ChatMessage(role=_ROLE_USER, content=input))
+  state.in_progress = True
+  yield
+
+  start_time = time.time()
+  output_message = transform(input, state.output)
+  assistant_message = ChatMessage(role=_ROLE_ASSISTANT)
+  output.append(assistant_message)
+  state.output = output
+
+  for content in output_message:
+    assistant_message.content += content
+
+    if (time.time() - start_time) >= 0.75:
+      start_time = time.time()
+      transform_to_chunks(assistant_message)
+      yield
+  transform_to_chunks(assistant_message)
+  state.in_progress = False
+  me.focus_component(key=f"input-{len(state.output)}")
+  yield
+
+
+# TODO: handle the case where [4,5]
+def transform_to_chunks(message: ChatMessage):
+  message.chunks = []
+  # Split the message content into chunks based on citations
+  chunks = re.split(r"(\[\d+(?:,\s*\d+)*\])", message.content)
+  # Initialize variables
+  current_chunk = ""
+  current_citations: list[int] = []
+
+  # Process each chunk
+  for chunk in chunks:
+    if re.match(r"\[\d+(?:,\s*\d+)*\]", chunk):
+      try:
+        # Remove brackets and split by comma
+        citation_numbers = [int(num.strip()) for num in chunk[1:-1].split(",")]
+        current_citations.extend(citation_numbers)
+      except Exception:
+        print("Error: Unable to parse citation numbers")
+    else:
+      # If it's text content
+      if current_chunk:
+        # If there's existing content, create a new chunk
+        message.chunks.append(
+          Chunk(
+            content=current_chunk,
+            citation_numbers=map_citation_numbers(current_citations),
+          )
+        )
+        current_chunk = ""
+        current_citations = []
+      # Add the new content
+      current_chunk += chunk
+
+  # Add the last chunk if there's any remaining content
+  if current_chunk:
+    message.chunks.append(
+      Chunk(
+        content=current_chunk,
+        citation_numbers=map_citation_numbers(current_citations),
+      )
+    )
+
+
+def map_citation_numbers(citation_numbers: list[int]) -> list[int]:
+  return citation_numbers
+
+
+def chat(
+  title: str | None = None,
+  bot_user: str = _BOT_USER_DEFAULT,
+):
+  state = me.state(State)
+
+  def toggle_theme(e: me.ClickEvent):
+    if me.theme_brightness() == "light":
+      me.set_theme_mode("dark")
+    else:
+      me.set_theme_mode("light")
+
+  with me.box(style=_STYLE_APP_CONTAINER):
+    with me.content_button(
+      type="icon",
+      style=me.Style(position="absolute", left=8, top=12),
+      on_click=toggle_theme,
+    ):
+      me.icon("light_mode" if me.theme_brightness() == "dark" else "dark_mode")
+    with me.box(
+      style=me.Style(
+        display="flex",
+        flex_direction="row",
+        padding=me.Padding.all(8),
+        background=me.theme_var("background"),
+        width="100%",
+        border=me.Border.all(
+          me.BorderSide(width=0, style="solid", color="black")
+        ),
+        box_shadow="0 10px 20px #0000000a, 0 2px 6px #0000000a, 0 0 1px #0000000a",
+      )
+    ):
+      with me.box(style=me.Style(flex_grow=1)):
+        me.native_textarea(
+          value=state.initial_input,
+          placeholder=_LABEL_INPUT,
+          key=f"input-{len(state.output)}",
+          on_blur=on_blur,
+          on_input=on_input,
+          style=me.Style(
+            color=me.theme_var("on-background"),
+            padding=me.Padding(top=16, left=48),
+            background=me.theme_var("background"),
+            letter_spacing="0.07px",
+            outline="none",
+            width="100%",
+            overflow_y="auto",
+            border=me.Border.all(
+              me.BorderSide(style="none"),
+            ),
+          ),
+        )
+      with me.content_button(
+        color="primary",
+        type="flat",
+        disabled=state.in_progress,
+        on_click=on_click_submit,
+        style=_STYLE_CHAT_BUTTON,
+      ):
+        me.icon(
+          _LABEL_BUTTON_IN_PROGRESS if state.in_progress else _LABEL_BUTTON
+        )
+
+    with me.box(style=_make_style_chat_ui_container()):
+      if title:
+        me.text(title, type="headline-5", style=_STYLE_TITLE)
+      with me.box(style=_STYLE_CHAT_BOX):
+        if not state.output and not state.intermediate_citations:
+          me.text(
+            "Welcome to Mesop Docs Bot! Ask me anything about Mesop.",
+            style=me.Style(
+              margin=me.Margin(bottom=24),
+              font_weight=500,
+            ),
+          )
+          with me.box(
+            style=me.Style(
+              display="flex",
+              flex_direction="column",
+              gap=24,
+            )
+          ):
+            for example in state.examples:
+              example_box(example)
+        if not state.output and state.intermediate_citations:
+          with me.box(
+            style=me.Style(
+              padding=me.Padding(top=16),
+              display="flex",
+              flex_direction="column",
+              gap=16,
+            ),
+          ):
+            for citation in state.intermediate_citations:
+              with citation_box(url=citation.url):
+                citation_content(
+                  Citation(
+                    url=citation.url,
+                    title=citation.title,
+                    breadcrumbs=citation.breadcrumbs,
+                    original_numbers=citation.original_numbers,
+                    content=citation.content,
+                    number=0,
+                  )
+                )
+        for msg in state.output:
+          with me.box(
+            style=me.Style(
+              display="flex", flex_direction="column", align_items="start"
+            )
+          ):
+            if msg.role == _ROLE_ASSISTANT:
+              me.text(bot_user, style=_STYLE_CHAT_BUBBLE_NAME)
+            else:
+              me.text("You", style=_STYLE_CHAT_BUBBLE_NAME)
+            with me.box(
+              style=me.Style(
+                width="100%",
+                font_size="16px",
+                line_height="1.5",
+                border_radius="15px",
+                padding=me.Padding(right=15, left=15, bottom=3),
+                margin=me.Margin(bottom=10),
+              )
+            ):
+              if msg.role == _ROLE_USER:
+                me.text(
+                  msg.content, style=me.Style(margin=me.Margin(bottom=16))
+                )
+              else:
+                if state.in_progress:
+                  me.progress_spinner()
+                used_citation_numbers: set[int] = set()
+
+                for chunk in msg.chunks:
+                  me.text(
+                    chunk.content,
+                    style=me.Style(white_space="pre-wrap", display="inline"),
+                  )
+                  if chunk.citation_numbers:
+                    with me.box(
+                      style=me.Style(
+                        display="inline-flex",
+                        flex_direction="row",
+                        gap=4,
+                        margin=me.Margin.symmetric(horizontal=6),
+                      )
+                    ):
+                      for citation_number in chunk.citation_numbers:
+                        used_citation_numbers.add(citation_number)
+
+                        citation_tooltip(
+                          get_citation_number(
+                            citation_number, used_citation_numbers
+                          )
+                        )
+
+                with me.box(
+                  style=me.Style(
+                    padding=me.Padding(top=16),
+                    display="flex",
+                    flex_direction="column",
+                    gap=16,
+                  ),
+                ):
+                  for citation in state.citations:
+                    if citation.number in used_citation_numbers:
+                      with citation_box(url=citation.url):
+                        citation_content(
+                          Citation(
+                            url=citation.url,
+                            title=citation.title,
+                            breadcrumbs=citation.breadcrumbs,
+                            original_numbers=citation.original_numbers,
+                            content=citation.content,
+                            number=get_citation_number(
+                              citation.number, used_citation_numbers
+                            ),
+                          )
+                        )
+                if not me.state(State).in_progress:
+                  with me.box(
+                    style=me.Style(
+                      display="flex",
+                      flex_direction="row",
+                      gap=4,
+                      margin=me.Margin(top=16),
+                    )
+                  ):
+                    NEWLINE = "\n"
+                    me.text("Is there an issue with this this response?")
+                    me.link(
+                      text="File an issue",
+                      url="https://github.com/mesop-dev/mesop/issues/new?assignees=&labels=bug,chatbot&projects=&title=Bad%20chatbot%20response&body="
+                      + urllib.parse.quote(f"""
+What was the issue with the chatbot response?
+
+---
+Original content:
+
+__Prompt:__
+{state.output[0].content}
+
+__Response:__
+{state.output[-1].content}
+
+__Citations:__
+
+{NEWLINE.join([f"1. {citation.url}" for citation in state.citations])}
+"""),
+                      style=me.Style(
+                        color=me.theme_var("primary"),
+                        text_decoration="none",
+                      ),
+                      open_in_new_tab=True,
+                    )
+
+
+def citation_tooltip(citation_number: int):
+  state = me.state(State)
+  with me.box(style=me.Style(display="inline-block")):
+    with me.tooltip(
+      message=state.citations[citation_number - 1].title,
+      position="below",
+    ):
+      me.text(
+        f"{citation_number}",
+        style=me.Style(
+          background=me.theme_var("surface-variant"),
+          padding=me.Padding.symmetric(horizontal=5),
+          border_radius="6px",
+          font_weight=500,
+        ),
+      )
+
+
+@me.web_component(path="./citation.js")
+def citation_box(
+  *,
+  url: str,
+  key: str | None = None,
+):
+  return me.insert_web_component(
+    name="citation-component",
+    key=key,
+    properties={
+      "url": url,
+      "active": True,
+    },
+  )
+
+
+def citation_content(citation: Citation):
+  with me.box(
+    style=me.Style(
+      display="flex",
+      flex_direction="column",
+      padding=me.Padding.symmetric(vertical=8, horizontal=16),
+      cursor="pointer",
+    ),
+  ):
+    with me.box(
+      style=me.Style(
+        display="flex",
+        flex_direction="row",
+        gap=4,
+        align_items="start",
+      )
+    ):
+      if citation.number:
+        me.text(
+          f"{citation.number}", style=me.Style(font_weight=500, font_size=18)
+        )
+      me.icon(
+        icon="description",
+        style=me.Style(font_size=20, padding=me.Padding(top=3, left=3)),
+      )
+
+      me.text(citation.title)
+    with me.box(
+      style=me.Style(
+        display="flex",
+        flex_direction="row",
+        gap=8,
+        font_size="14px",
+        font_weight=500,
+      )
+    ):
+      for breadcrumb in citation.breadcrumbs:
+        me.text(breadcrumb)
+        if breadcrumb != citation.breadcrumbs[-1]:
+          me.text(" > ")
+
+
+def example_box(example: str):
+  with me.box(
+    style=me.Style(
+      background=me.theme_var("secondary-container"),
+      border_radius="12px",
+      padding=me.Padding(left=16, right=16, top=16, bottom=16),
+      cursor="pointer",
+    ),
+    key=example,
+    on_click=on_click_example,
+  ):
+    me.text(example)
+
+
+def on_click_example(e: me.ClickEvent) -> Generator[None, None, None]:
+  state = me.state(State)
+  state.input = e.key
+  yield from submit()
+
+
+def transform(
+  message: str, history: list[ChatMessage]
+) -> Generator[str, None, None]:
+  response = ask(message)
+  citations = get_citations(response.source_nodes)
+
+  me.state(State).citations = citations
+  yield from response.response_gen
+
+
+def get_citations(source_nodes: list[NodeWithScore]) -> list[Citation]:
+  citations: list[Citation] = []
+
+  for i, source_node in enumerate(source_nodes):
+    url: str = source_node.node.metadata.get("url", "")
+    breadcrumbs = url.split("https://mesop-dev.github.io/mesop/")[-1].split("/")
+    title = source_node.node.metadata.get("title", "")
+    content_lines = source_node.node.get_content().split("\n")
+
+    for line in content_lines[2:]:
+      if line and not line.startswith("```"):
+        break
+    if len(content_lines) > 2:
+      fragment: str = (
+        "#:~:text="
+        + urllib.parse.quote(content_lines[1])
+        + ",-"
+        # Just take the first two words of the line to avoid
+        # mismatching (e.g. URLs).
+        + urllib.parse.quote(" ".join(line.split(" ")[:2]))
+      )
+    else:
+      fragment = ""
+    citations.append(
+      Citation(
+        url=url + fragment,
+        breadcrumbs=breadcrumbs,
+        title=title,
+        number=i + 1,
+      )
+    )
+  return citations
+
+
+def get_citation_number(
+  citation_number: int, used_citation_numbers: set[int]
+) -> int:
+  number = 0
+  for n in used_citation_numbers:
+    number += 1  # noqa: SIM113
+    if n == citation_number:
+      return number
+  raise ValueError(f"Citation number {citation_number} not found")
+
+
+@me.web_component(path="./frame_listener.js")
+def frame_listener(
+  *,
+  key: str | None = None,
+):
+  pass

pyproject.toml

@@ -0,0 +1,31 @@
+[project]
+name = "docbot"
+version = "0.1.0"
+description = "A chatbot for docs"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+    "gunicorn>=23.0.0",
+    "nest-asyncio>=1.6.0",
+    "llama-index==0.10.68",
+    "google-generativeai>=0.5.4",
+    "llama-index-llms-gemini==0.2.0",
+    "llama-index-embeddings-google==0.1.6",
+    "llama-index-retrievers-bm25==0.2.2",
+    "mesop>=1.0.0",
+]
+
+# uv required properties:
+
+[tool.uv]
+dev-dependencies = []
+
+[tool.uv.workspace]
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+# See: https://github.com/astral-sh/uv/issues/6293
+[tool.hatch.build.targets.wheel]
+packages = ["."]

recorder.py

@@ -0,0 +1,130 @@
+# Create a folder at out_dir + query (percent encoded)
+import argparse
+import os
+import sys
+import urllib.parse
+
+from docs_index import blocking_query_engine
+from llama_index.core.instrumentation import get_dispatcher
+from llama_index.core.instrumentation.event_handlers import BaseEventHandler
+from llama_index.core.instrumentation.events.llm import (
+  LLMChatEndEvent,
+  LLMCompletionEndEvent,
+)
+
+
+class ModelEventHandler(BaseEventHandler):
+  @classmethod
+  def class_name(cls) -> str:
+    """Class name."""
+    return "ModelEventHandler"
+
+  def handle(self, event) -> None:
+    """Logic for handling event."""
+    if isinstance(event, LLMCompletionEndEvent):
+      print(f"LLM Prompt length: {len(event.prompt)}")
+      print(f"LLM Prompt CONTENT: {event.prompt}")
+      print(f"LLM Completion: {event.response.text!s}")
+    elif isinstance(event, LLMChatEndEvent):
+      messages_str = "\n".join([str(x.content) for x in event.messages])
+      print(f"LLM Input Messages RAW: {event.messages}")
+      print(f"LLM Input Messages length: {len(messages_str)}")
+      print(f"LLM Input Messages CONTENT: {messages_str}")
+      print(f"LLM Response: {event.response.message.content!s}")
+
+      # Create a folder for the query
+      query_folder = os.path.join(args.out_dir, urllib.parse.quote(query))
+      os.makedirs(query_folder, exist_ok=True)
+      print(f"Created folder for query: {query_folder}")
+
+      # Save the LLM input and output to files
+      with open(os.path.join(query_folder, "input.txt"), "w") as f:
+        f.write(messages_str)
+      with open(os.path.join(query_folder, "output.txt"), "w") as f:
+        f.write(str(event.response.message.content))
+
+
+# root dispatcher
+root_dispatcher = get_dispatcher()
+
+# register event handler
+root_dispatcher.add_event_handler(ModelEventHandler())
+
+QUERIES = [
+  "How can I reset an input component?",
+  "Show me how to style a component",
+  "Create a multi-page app",
+  "Is it possible to create custom components?",
+  "Implement authentication",
+  "Deploy a Mesop app",
+  "Optimize performance",
+  "Can I use JavaScript libraries in Mesop?",
+  "Stream UI updates from an LLM API",
+  "Debug a Mesop application",
+  "Is Mesop ready for production use?",
+  "Create a mobile-friendly and responsive UI",
+  "Handle asynchronous operations",
+  "Implement dark mode",
+  "Add tooltips to Mesop components",
+  "Render a pandas DataFrame as a table",
+  "Add charts",
+  "Handle file uploads",
+]
+
+# QUERIES = [
+#   "How do I test a Mesop application?",
+#   "What components are available in Mesop?",
+#   "How can I reset a text input field in Mesop?",
+#   "Show me how to style a component in Mesop",
+#   "Create a multi-page app using Mesop",
+#   "Is it possible to create custom components in Mesop?",
+#   "Implement authentication in a Mesop app",
+#   "How do I call an API from a Mesop application?",
+#   "What's the process for deploying a Mesop app?",
+#   "Optimize performance in a Mesop application",
+#   "Implement a datepicker in Mesop",
+#   "Can I use JavaScript libraries with Mesop?",
+#   "Implement real-time updates in a Mesop app",
+#   "Stream UI updates from an LLM API in Mesop",
+#   "Debug a Mesop application",
+#   "Is Mesop ready for production use?",
+#   "Implement form validation in Mesop",
+#   "Create a mobile-friendly Mesop app",
+#   "Handle asynchronous operations in Mesop",
+#   "Implement dark mode in a Mesop application",
+#   "Add keyboard shortcuts to a Mesop app",
+#   "Implement drag and drop functionality in Mesop",
+#   "Create an infinite scroll feature in Mesop",
+#   "How to make a row of components in Mesop",
+#   "Add tooltips to Mesop components",
+#   "Render a pandas DataFrame in a Mesop app",
+#   "Add charts to a Mesop application",
+#   "Create a table component in Mesop",
+#   "Handle file uploads in a Mesop app",
+#   "Use command-line flags with a Mesop application",
+#   "Create a clickable link in Mesop",
+#   "Implement a download link in a Mesop app",
+# ]
+
+
+parser = argparse.ArgumentParser(
+  description="Process queries and record model events."
+)
+parser.add_argument(
+  "--out-dir", type=str, help="Output directory for recorded events"
+)
+args = parser.parse_args()
+
+if args.out_dir:
+  print(f"Output directory set to: {args.out_dir}")
+
+  # Create the output directory if it doesn't exist
+  os.makedirs(args.out_dir, exist_ok=True)
+  print(f"Created output directory: {args.out_dir}")
+else:
+  print("No output directory specified. Exiting! Specify with --out-dir")
+  sys.exit(1)
+
+
+for query in QUERIES:
+  blocking_query_engine.query(query)

requirements.txt

@@ -0,0 +1,374 @@
+# This file was autogenerated by uv via the following command:
+#    uv pip compile pyproject.toml -o requirements.txt
+absl-py==2.1.0
+    # via mesop
+aiohappyeyeballs==2.4.0
+    # via aiohttp
+aiohttp==3.10.11
+    # via
+    #   llama-index-core
+    #   llama-index-legacy
+aiosignal==1.3.1
+    # via aiohttp
+annotated-types==0.7.0
+    # via pydantic
+anyio==4.4.0
+    # via
+    #   httpx
+    #   openai
+async-timeout==4.0.3
+    # via aiohttp
+attrs==24.2.0
+    # via aiohttp
+beautifulsoup4==4.12.3
+    # via llama-index-readers-file
+blinker==1.8.2
+    # via flask
+bm25s==0.1.10
+    # via llama-index-retrievers-bm25
+cachetools==5.5.0
+    # via google-auth
+certifi==2024.8.30
+    # via
+    #   httpcore
+    #   httpx
+    #   requests
+charset-normalizer==3.3.2
+    # via requests
+click==8.1.7
+    # via
+    #   flask
+    #   nltk
+dataclasses-json==0.6.7
+    # via
+    #   llama-index-core
+    #   llama-index-legacy
+deepdiff==6.7.1
+    # via mesop
+deprecated==1.2.14
+    # via
+    #   llama-index-core
+    #   llama-index-legacy
+dirtyjson==1.0.8
+    # via
+    #   llama-index-core
+    #   llama-index-legacy
+distro==1.9.0
+    # via openai
+exceptiongroup==1.2.2
+    # via anyio
+flask==3.0.3
+    # via mesop
+frozenlist==1.4.1
+    # via
+    #   aiohttp
+    #   aiosignal
+fsspec==2024.6.1
+    # via
+    #   llama-index-core
+    #   llama-index-legacy
+google-ai-generativelanguage==0.6.4
+    # via google-generativeai
+google-api-core==2.19.1
+    # via
+    #   google-ai-generativelanguage
+    #   google-api-python-client
+    #   google-generativeai
+google-api-python-client==2.142.0
+    # via google-generativeai
+google-auth==2.34.0
+    # via
+    #   google-ai-generativelanguage
+    #   google-api-core
+    #   google-api-python-client
+    #   google-auth-httplib2
+    #   google-generativeai
+google-auth-httplib2==0.2.0
+    # via google-api-python-client
+google-generativeai==0.5.4
+    # via
+    #   docbot (pyproject.toml)
+    #   llama-index-embeddings-google
+    #   llama-index-llms-gemini
+googleapis-common-protos==1.63.2
+    # via
+    #   google-api-core
+    #   grpcio-status
+greenlet==3.0.3
+    # via sqlalchemy
+grpcio==1.66.0
+    # via
+    #   google-api-core
+    #   grpcio-status
+grpcio-status==1.62.3
+    # via google-api-core
+gunicorn==23.0.0
+    # via docbot (pyproject.toml)
+h11==0.14.0
+    # via httpcore
+httpcore==1.0.5
+    # via httpx
+httplib2==0.22.0
+    # via
+    #   google-api-python-client
+    #   google-auth-httplib2
+httpx==0.27.0
+    # via
+    #   llama-cloud
+    #   llama-index-core
+    #   llama-index-legacy
+    #   openai
+idna==3.8
+    # via
+    #   anyio
+    #   httpx
+    #   requests
+    #   yarl
+itsdangerous==2.2.0
+    # via flask
+jinja2==3.1.4
+    # via flask
+jiter==0.5.0
+    # via openai
+joblib==1.4.2
+    # via nltk
+llama-cloud==0.0.15
+    # via llama-index-indices-managed-llama-cloud
+llama-index==0.10.68
+    # via docbot (pyproject.toml)
+llama-index-agent-openai==0.2.9
+    # via
+    #   llama-index
+    #   llama-index-program-openai
+llama-index-cli==0.1.13
+    # via llama-index
+llama-index-core==0.10.68.post1
+    # via
+    #   llama-index
+    #   llama-index-agent-openai
+    #   llama-index-cli
+    #   llama-index-embeddings-google
+    #   llama-index-embeddings-openai
+    #   llama-index-indices-managed-llama-cloud
+    #   llama-index-llms-gemini
+    #   llama-index-llms-openai
+    #   llama-index-multi-modal-llms-openai
+    #   llama-index-program-openai
+    #   llama-index-question-gen-openai
+    #   llama-index-readers-file
+    #   llama-index-readers-llama-parse
+    #   llama-index-retrievers-bm25
+    #   llama-parse
+llama-index-embeddings-google==0.1.6
+    # via docbot (pyproject.toml)
+llama-index-embeddings-openai==0.1.11
+    # via
+    #   llama-index
+    #   llama-index-cli
+llama-index-indices-managed-llama-cloud==0.2.7
+    # via llama-index
+llama-index-legacy==0.9.48.post3
+    # via llama-index
+llama-index-llms-gemini==0.2.0
+    # via docbot (pyproject.toml)
+llama-index-llms-openai==0.1.31
+    # via
+    #   llama-index
+    #   llama-index-agent-openai
+    #   llama-index-cli
+    #   llama-index-multi-modal-llms-openai
+    #   llama-index-program-openai
+    #   llama-index-question-gen-openai
+llama-index-multi-modal-llms-openai==0.1.9
+    # via llama-index
+llama-index-program-openai==0.1.7
+    # via
+    #   llama-index
+    #   llama-index-question-gen-openai
+llama-index-question-gen-openai==0.1.3
+    # via llama-index
+llama-index-readers-file==0.1.33
+    # via llama-index
+llama-index-readers-llama-parse==0.1.6
+    # via llama-index
+llama-index-retrievers-bm25==0.2.2
+    # via docbot (pyproject.toml)
+llama-parse==0.4.9
+    # via llama-index-readers-llama-parse
+markupsafe==2.1.5
+    # via
+    #   jinja2
+    #   werkzeug
+marshmallow==3.22.0
+    # via dataclasses-json
+mesop==1.0.0
+    # via docbot (pyproject.toml)
+msgpack==1.0.8
+    # via mesop
+multidict==6.0.5
+    # via
+    #   aiohttp
+    #   yarl
+mypy-extensions==1.0.0
+    # via typing-inspect
+nest-asyncio==1.6.0
+    # via
+    #   docbot (pyproject.toml)
+    #   llama-index-core
+    #   llama-index-legacy
+networkx==3.3
+    # via
+    #   llama-index-core
+    #   llama-index-legacy
+nltk==3.9.1
+    # via
+    #   llama-index-core
+    #   llama-index-legacy
+numpy==1.26.4
+    # via
+    #   bm25s
+    #   llama-index-core
+    #   llama-index-legacy
+    #   pandas
+    #   scipy
+openai==1.42.0
+    # via
+    #   llama-index-agent-openai
+    #   llama-index-legacy
+    #   llama-index-llms-openai
+ordered-set==4.1.0
+    # via deepdiff
+packaging==24.1
+    # via
+    #   gunicorn
+    #   marshmallow
+pandas==2.2.2
+    # via
+    #   llama-index-core
+    #   llama-index-legacy
+pillow==10.4.0
+    # via
+    #   llama-index-core
+    #   llama-index-llms-gemini
+propcache==0.3.0
+    # via yarl
+proto-plus==1.24.0
+    # via
+    #   google-ai-generativelanguage
+    #   google-api-core
+protobuf==4.25.4
+    # via
+    #   google-ai-generativelanguage
+    #   google-api-core
+    #   google-generativeai
+    #   googleapis-common-protos
+    #   grpcio-status
+    #   mesop
+    #   proto-plus
+pyasn1==0.6.0
+    # via
+    #   pyasn1-modules
+    #   rsa
+pyasn1-modules==0.4.0
+    # via google-auth
+pydantic==2.8.2
+    # via
+    #   google-generativeai
+    #   llama-cloud
+    #   llama-index-core
+    #   mesop
+    #   openai
+pydantic-core==2.20.1
+    # via pydantic
+pyparsing==3.1.4
+    # via httplib2
+pypdf==4.3.1
+    # via llama-index-readers-file
+pystemmer==2.2.0.1
+    # via llama-index-retrievers-bm25
+python-dateutil==2.9.0.post0
+    # via pandas
+python-dotenv==1.0.1
+    # via mesop
+pytz==2024.1
+    # via pandas
+pyyaml==6.0.2
+    # via llama-index-core
+regex==2024.7.24
+    # via
+    #   nltk
+    #   tiktoken
+requests==2.32.3
+    # via
+    #   google-api-core
+    #   llama-index-core
+    #   llama-index-legacy
+    #   tiktoken
+rsa==4.9
+    # via google-auth
+scipy==1.14.1
+    # via bm25s
+six==1.16.0
+    # via python-dateutil
+sniffio==1.3.1
+    # via
+    #   anyio
+    #   httpx
+    #   openai
+soupsieve==2.6
+    # via beautifulsoup4
+sqlalchemy==2.0.32
+    # via
+    #   llama-index-core
+    #   llama-index-legacy
+striprtf==0.0.26
+    # via llama-index-readers-file
+tenacity==8.5.0
+    # via
+    #   llama-index-core
+    #   llama-index-legacy
+tiktoken==0.7.0
+    # via
+    #   llama-index-core
+    #   llama-index-legacy
+tqdm==4.66.5
+    # via
+    #   google-generativeai
+    #   llama-index-core
+    #   nltk
+    #   openai
+typing-extensions==4.12.2
+    # via
+    #   anyio
+    #   google-generativeai
+    #   llama-index-core
+    #   llama-index-legacy
+    #   openai
+    #   pydantic
+    #   pydantic-core
+    #   pypdf
+    #   sqlalchemy
+    #   typing-inspect
+typing-inspect==0.9.0
+    # via
+    #   dataclasses-json
+    #   llama-index-core
+    #   llama-index-legacy
+tzdata==2024.1
+    # via pandas
+uritemplate==4.1.1
+    # via google-api-python-client
+urllib3==2.2.2
+    # via requests
+watchdog==4.0.2
+    # via mesop
+werkzeug==3.0.6
+    # via
+    #   flask
+    #   mesop
+wrapt==1.16.0
+    # via
+    #   deprecated
+    #   llama-index-core
+yarl==1.18.3
+    # via aiohttp

scrollable.js

@@ -0,0 +1,21 @@
+import {
+  LitElement,
+  html,
+  css,
+} from 'https://cdn.jsdelivr.net/gh/lit/dist@3/core/lit-core.min.js';
+
+class ScrollableComponent extends LitElement {
+  renderRoot() {
+    return this;
+  }
+  firstUpdated() {
+    // this.focus();
+  }
+  render() {
+    this.tabIndex = 0;
+    this.style.overflowY = 'auto';
+    this.style.outline = 'none';
+  }
+}
+
+customElements.define('scrollable-component', ScrollableComponent);