Add brochure code.

.gitignore

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+# Github's default gitignore for Python
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+llms/
+llms.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+.idea/
+
+# Added this to ignore models downloaded from HF
+model_cache/
+# Ignore finder files
+.DS_Store
+/.DS_Store
+
+# Ignore Chroma vector database
+vector_db/
+products_vectorstore/
+
+# And ignore any pickle files made during the course
+*.pkl
+
+# ignore gradio private files
+.gradio
+/.gradio
+
+# ignore diagnostics reports
+**/report.txt
+
+# ignore optimized C++ code from being checked into repo
+week4/optimized
+week4/simple

app.py

@@ -1,7 +1,67 @@
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+from typing import TypedDict, Annotated, Optional
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
+import requests
+from bs4 import BeautifulSoup
+from dotenv import load_dotenv
+from pydantic import BaseModel, Field
+
+from runnable_with_tools import RunnableWithTools
+from langchain_anthropic import ChatAnthropic
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.tools import tool
+
+class WebPage(BaseModel):
+    """ Information about a web page, including its title, content and useful links """
+    url: str = Field(description="URL of this web page")
+    title: Optional[str] = Field(default=None, description="The web page title")
+    content: Optional[str] = Field(default=None, description="Web page content")
+    links: list[str] = Field(default_factory=list, description="the useful links on this web page")
+
+@tool
+def get_web_page(url: Annotated[str, 'the url of the web page']) -> Annotated[WebPage, 'information on the web page']:
+    """ Retrieve information about a web page, including its title, content and useful links """
+    print(f'Retrieving {url}')
+    response = requests.get(url)
+    soup = BeautifulSoup(response.content, 'html.parser')
+    title = soup.title.string if soup.title else None
+    content = None
+    if soup.body:
+        for irrelevant in soup.body(["script", "style", "img", "input"]):
+            irrelevant.decompose()
+        content = soup.body.get_text(separator="\n", strip=True)
+    links = [link.get('href') for link in soup.find_all('a') if link.get('href') is not None]
+    return WebPage(url=url, title=title, content=content, links=links)
+
+TOOLS = {
+    "get_web_page": get_web_page
+}
+
+def make_brochure(company_name: str, company_web_site: str) -> str:
+    system = """
+    You are an assistant that can crate company brochure from company's web site.
+    You can do this in a few steps:
+    1. Retrieve web page information from the provide company web site url
+    2. Find out the links that are useful for making company brochure
+    3. Retrieve web page information from these links
+    4. Create a company brochure from information on these wwn pages 
+    """
+
+    user = """
+    Please create a company brochure for {company_name}. Its web site url is {company_web_site}
+    """
+
+    prompt_template = ChatPromptTemplate.from_messages([
+        ('system', system),
+        ('user', user)
+    ])
+    prompt = prompt_template.invoke({'company_name': company_name, 'company_web_site': company_web_site})
+    return model_with_tools.invoke(prompt.to_messages(), max_depth=20).content
+
+load_dotenv()
+model = ChatAnthropic(model="claude-3-5-haiku-20241022", temperature=0)
+model_with_tools = RunnableWithTools(bound=model.bind_tools([get_web_page]), tools=TOOLS)
+
+demo = gr.Interface(fn=make_brochure, inputs=["text", "text"], outputs="markdown", flagging_mode="never")
 demo.launch()

requirements.txt

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+python-dotenv
+jupyterlab
+ipywidgets
+requests
+numpy
+pandas
+scipy
+scikit-learn
+matplotlib
+gensim
+transformers
+tqdm
+openai
+gradio
+langchain
+tiktoken
+faiss-cpu
+langchain-openai
+langchain-anthropic
+langchain_chroma
+langchain[docarray]
+datasets
+sentencepiece
+matplotlib
+google-generativeai
+anthropic
+scikit-learn
+chromadb
+plotly
+jupyter-dash
+beautifulsoup4
+pydub
+modal
+ollama
+accelerate
+sentencepiece
+bitsandbytes
+psutil
+setuptools
+speedtest-cli

runnable_with_tools.py

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+from typing import Optional, Any, Callable
+
+from langchain_community.vectorstores.pgvector import BaseModel
+from pydantic import ConfigDict
+
+from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
+from langchain_core.runnables import RunnableSerializable, RunnableConfig, Runnable
+from langchain_core.runnables.utils import Input, Output
+from langchain_core.tools import BaseTool
+
+class RunnableWithTools(RunnableSerializable[Input, Output]):
+    bound: Runnable[Input, Output]
+    tools: dict[str, BaseTool]
+
+    model_config = ConfigDict(
+        arbitrary_types_allowed=True,
+    )
+
+    def invoke(
+        self,
+        input: Input,
+        config: Optional[RunnableConfig] = None,
+        max_depth: Optional[int] = 3,
+        **kwargs: Any
+    ) -> Output:
+        depth = 0
+        message = None
+        while depth < max_depth:
+            message = self.bound.invoke(input)
+            if isinstance(message, AIMessage) and message.tool_calls and self.tools:
+                text = ''
+                if isinstance(message.content, list) and 'text' in message.content[0]:
+                    text += message.content[0]['text']
+                elif isinstance(message.content, str):
+                    text += message.content
+                # input.append(AIMessage(content=text, **message.additional_kwargs))
+                input.append(message)
+
+                text = ''
+                for tool_call in message.tool_calls:
+                    selected_tool = self.tools[tool_call["name"].lower()]
+                    if selected_tool:
+                        tool_msg = selected_tool.invoke(tool_call)
+                        if isinstance(tool_msg, BaseModel):
+                            tool_msg = tool_msg.model_dump()
+                        else:
+                            tool_msg = str(tool_msg)
+                        text += '\n' + tool_msg
+                    input.append(ToolMessage(tool_call_id=tool_call['id'], content=text))
+                depth += 1
+            else:
+                break
+
+        return message
+