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Run like this from the langroid repo:

uv run examples/basic/chat-search.py -m groq/deepseek-r1-distill-llama-70b

Example screenshot:

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Run like this from the langroid-examples repo after setting up the env

uv run examples/basic/tool-extract-short-example.py -m ollama/mistral-small

Sample output:

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Install Langroid and run this doc-chat example script from the examples/ folder:

uv run examples/docqa/chat.py https://arxiv.org/pdf/2501.12948

Example output:

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# Simple example of getting bsky data via `atproto` python client
# 
# First install: atproto, python-dotenv

# See python client docs here:
    # https://github.com/MarshalX/atproto
# 
from atproto import Client, IdResolver

import os

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// Zed settings
//
// For information on how to configure Zed, see the Zed
// documentation: https://zed.dev/docs/configuring-zed
//
// To see all of Zed's default settings without changing your
// custom settings, run the `open default settings` command
// from the command palette or from `Zed` application menu.
{
  // The settings for slash commands.

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from typing import Any, Callable, cast, Optional, Union
import textwrap
import chainlit as cl
from datetime import datetime
from chainlit.sync import run_sync
from chainlit.message import AskMessageBase, AskUserMessage, MessageStepType
from chainlit.types import AskSpec
from chainlit.step import StepDict
from chainlit.config import config
from chainlit.telemetry import trace_event

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/Users/pchalasani/Git/langroid-examples/.venv/lib/python3.11/site-packages/langroid/parsing/docu │
│ ment_parser.py:301 in iterate_pages                                                              │
│                                                                                                  │
│   298 │   def iterate_pages(self) -> Generator[Tuple[int, Any], None, None]:  # type: ignore     │
│   299 │   │   from unstructured.partition.pdf import partition_pdf                               │
│   300 │   │                                                                                      │
│ ❱ 301 │   │   elements = partition_pdf(file=self.doc_bytes, include_page_breaks=True)            │
│   302 │   │   for i, el in enumerate(elements):                                                  │
│   303 │   │   │   yield i, el                                                                    │
│   304                                                                                            │

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import blankly
from blankly import StrategyState
import numpy as np


def trade(state: StrategyState):
    '''
    Example of how to decide a trade based on ALL assets
    '''
    symbols = state.symbol

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'''
Example of using blankly to decide trade based on all asset prices using a global state-list
'''
import blankly
import numpy as np

# global list of StrategyStates, one per symbol (price_event)
states = []

def trade():

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<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
    <modelVersion>4.0.0</modelVersion>
    <groupId>com.yahoo.floura</groupId>
    <artifactId>floura</artifactId>
    <version>2.0.0</version>
    <packaging>jar</packaging>
    <name>floura</name>
    <properties>
        <maven.compiler.source>1.7</maven.compiler.source>