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:[email protected]/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-1.5-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

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+[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, 159244, 162221, 165917, 169964, 172968, 174514, 176210, 177614, 179212, 180778, 184521, 188959, 193205, 196442, 199089, 201174, 204214, 205997, 207386, 209307, 210736, 212092, 213448, 214731, 216310, 217970, 219766, 221388, 222851, 224482, 225832, 227382, 229333, 230854, 232803, 234524, 236741, 238539, 240620, 242325, 244243, 245730, 247560, 248903, 250199, 251476, 253268, 254613, 256279, 257656, 258952, 260229, 261561, 262843, 264102, 265409, 266712, 268081, 269444, 270796, 272291, 273582, 274871, 276323, 277654, 278943, 280200, 281562, 282879, 284377, 285713, 287007, 288275, 289704, 291042, 292439, 293911, 295291, 296763, 298120, 299430, 300725, 302037, 303333, 304610, 306189, 307555, 309057, 310657, 311951, 313219, 314547, 315836, 317104, 318394, 319690, 320967, 322385, 323649, 325408, 326984, 328552, 331012, 332289, 334401, 337095, 338521, 340376, 342918, 344304, 345600, 347009, 348321, 349610, 350878, 352181, 353503, 354807, 356117, 357406, 358674, 360079, 361424, 362843, 364280, 365653, 367029, 368360, 369656, 371039, 372399, 373707, 375169, 376532, 377842, 379137, 380534, 381879, 383362, 384723, 386026, 387373, 388711, 390007, 391284, 392694, 394046, 395375, 396784, 398129, 399450, 400768, 402057, 403325, 404775, 406092, 407522, 408837, 410147, 411442, 412843, 414160, 415630, 416973, 418269, 419546, 420826, 422086, 423836, 425216, 426961, 428483, 429949, 431213, 432844, 434220, 436240, 438067, 439692, 441439, 443088, 445348, 446857, 448394, 449933, 451479, 453566, 455075, 456461, 457795, 459171, 460675, 462361, 463891, 465298, 467346, 469459, 471276, 473373, 474806, 476845, 478348, 480382, 481787, 483352, 484889, 487554, 490035, 491699, 493091, 494542, 496002, 497361, 498764, 500560, 502080, 503765, 505129, 506675, 508297, 509811, 511174, 512492, 513847, 515246, 516912, 518571, 519999, 521339, 522713, 524155, 525555, 527106, 528744, 530136, 531555, 533282, 534762, 536268, 537743, 540315, 541610, 543225, 545326, 547445, 548725, 551323, 553491, 554778, 557457, 558836, 560317, 562668, 564161, 565630, 566911, 569129, 570998, 572768, 574753, 576100, 577406, 578851, 580479, 581924, 583170, 584618, 586118, 587723, 589592, 590826, 592453, 594563, 596465, 598688, 600292, 601666, 603193, 604867, 606272, 607742, 609040, 610845, 612609, 614271, 615680, 617818, 619428, 620855, 622411, 623870, 625564, 629097, 630960, 633088, 634785, 637114, 638401, 639819, 641263, 642848, 644330, 646221, 647797, 649406, 650757, 652423, 654097, 656938, 658432, 660054, 661873, 664084, 665756, 667515, 668954, 670309, 671771, 673593, 675385, 677211, 678977, 680418, 681690, 683335, 685151, 686884, 688514, 690085, 691452, 694298, 698276, 702363, 706668, 710463, 713350, 716727, 717993, 719794, 721214, 722784, 724524, 726035, 727387, 729114, 732088, 733915, 735836, 737814, 739272, 741035, 742380, 743757, 745621, 747126, 749487, 751797, 754112, 755463]

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": 448,
+    "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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"manual": 1554, "theme_bright": 1555, "huggingfac": 1556, "bi": 1557, "about": 1558, "dialog_act": 1559, "case": 1560, "mesop_state_session_backend_file_base_dir": 1561, "use": 1562, "here": 1563, "general": 1564, "daterangepickerchangeev": 1565, "generation_config": 1566, "serious": 1567, "happen": 1568, "viewport_s": 1569, "max_token": 1570, "affin": 1571, "srv": 1572, "addit": 1573, "attract": 1574, "s9ag_yndl0m": 1575, "build": 1576, "direct": 1577, "v1": 1578, "100vh": 1579, "option": 1580, "screenshot": 1581, "remot": 1582, "home_pag": 1583, "claude_api_key": 1584, "datetim": 1585, "famili": 1586, "manag": 1587, "blank": 1588, "autocompleteopt": 1589, "selectselectionchangeev": 1590, "refus": 1591, "dark_mod": 1592, "queri": 1593, "overridden": 1594, "away": 1595, "liner": 1596, "logo": 1597, "on_upload": 1598, "video": 1599, "devic": 1600, "_or_": 1601, "250px": 1602, "inputev": 1603, "card_head": 1604, "port": 1605, "cloud": 1606, "captur": 1607, "divid": 1608, "anyth": 1609, 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"myapppath": 1789, "fraction": 1790, "earlier": 1791, "easier": 1792, "initial_input_valu": 1793, "png": 1794, "substr": 1795, "inadvert": 1796, "umd": 1797, "card_cont": 1798, "swap": 1799, "ttls": 1800, "provid": 1801, "constraint": 1802, "media": 1803, "contain": 1804, "regular": 1805, "proper": 1806, "who": 1807, "race": 1808, "strong": 1809, "lock": 1810, "milk": 1811, "collect": 1812, "copi": 1813, "jsdelivr": 1814, "native_textarea": 1815, "localhost": 1816, "wsgi": 1817, "asset": 1818, "mutat": 1819, "equival": 1820, "in": 1821, "connection_uri": 1822, "typeerror": 1823, "bg": 1824, "player": 1825, "framework": 1826, "youtub": 1827, "send": 1828, "ide": 1829, "startswith": 1830, "transmit": 1831, "demonstr": 1832, "simplest": 1833, "notic": 1834, "follow": 1835, "log": 1836, "steeper": 1837, "machin": 1838, "abstract": 1839, "llm_respons": 1840, "is_desktop": 1841, "colorto": 1842, "slidetogglechangeev": 1843, "kit": 1844, "pros": 1845, "avoid": 1846, "debugpi": 1847, "impos": 1848, "between": 1849, "ahd": 1850, "is_load": 1851, "0003": 1852}

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": {"b533d887-a12a-40e8-8757-99e7e60ee61e": {"__type__": "vector_store", "__data__": "{\"index_id\": \"b533d887-a12a-40e8-8757-99e7e60ee61e\", \"summary\": null, \"nodes_dict\": {\"36336cd9-b767-4990-8ca3-dc1e239de74b\": \"36336cd9-b767-4990-8ca3-dc1e239de74b\", \"512e7f6d-eb2b-470a-9942-b1f254ce4c5d\": \"512e7f6d-eb2b-470a-9942-b1f254ce4c5d\", \"bdeca4ed-43eb-46c7-96bc-a1b99ee309af\": \"bdeca4ed-43eb-46c7-96bc-a1b99ee309af\", \"95b821ce-9836-45d2-a4c1-508519adb30c\": \"95b821ce-9836-45d2-a4c1-508519adb30c\", \"d4f0a1f2-30b1-4035-a77e-45104110d252\": \"d4f0a1f2-30b1-4035-a77e-45104110d252\", \"66965201-2b05-4534-9075-198712a88086\": \"66965201-2b05-4534-9075-198712a88086\", \"d2226f67-55ac-432e-a8a3-9bfef7335960\": \"d2226f67-55ac-432e-a8a3-9bfef7335960\", \"6874a5fe-f399-4e4c-a01b-1719a3fedbbb\": \"6874a5fe-f399-4e4c-a01b-1719a3fedbbb\", \"0307c857-0357-4d6e-9f06-b71f162fd3b9\": \"0307c857-0357-4d6e-9f06-b71f162fd3b9\", \"5fa3430a-338a-4774-bb7c-b4f245e50ccf\": 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\"ae8a01f1-33fc-4a5a-8ba3-6520e14521c0\", \"fc5dae8d-81a1-4af8-a325-cb8dbc8c3f93\": \"fc5dae8d-81a1-4af8-a325-cb8dbc8c3f93\", \"42c7fab4-6c3e-434f-b1a7-9eacc8a22d62\": \"42c7fab4-6c3e-434f-b1a7-9eacc8a22d62\", \"df5391ce-ab3f-4c8f-84cc-42b748d2fe8a\": \"df5391ce-ab3f-4c8f-84cc-42b748d2fe8a\", \"a8da4484-6d0e-4e79-a7e3-4f7e5b998516\": \"a8da4484-6d0e-4e79-a7e3-4f7e5b998516\", \"ffa99677-200d-4da4-a465-7379b360cace\": \"ffa99677-200d-4da4-a465-7379b360cace\", \"a9ca3c21-84ba-4636-a863-c8341dcfb561\": \"a9ca3c21-84ba-4636-a863-c8341dcfb561\", \"71393f6f-1590-4bfc-a341-490634e4ab04\": \"71393f6f-1590-4bfc-a341-490634e4ab04\", \"3f6719cc-e899-4697-b691-1019587ca1c5\": \"3f6719cc-e899-4697-b691-1019587ca1c5\", \"359b6014-382e-4d0d-84e2-0fcb1185eb92\": \"359b6014-382e-4d0d-84e2-0fcb1185eb92\"}, \"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);