Spaces:
Running
on
Zero
Running
on
Zero
Update chatbot.py
Browse files- chatbot.py +26 -32
chatbot.py
CHANGED
@@ -230,14 +230,14 @@ def extract_text_from_webpage(html_content):
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"""Extracts visible text from HTML content using BeautifulSoup."""
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soup = BeautifulSoup(html_content, "html.parser")
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# Remove unwanted tags
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for tag in soup(["script", "style", "header", "footer", "nav"]):
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tag.extract()
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# Get the remaining visible text
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visible_text = soup.get_text(strip=True)
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return visible_text
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# Perform a Google search and return the results
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def search(term, num_results=
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"""Performs a Google search and returns the results."""
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escaped_term = urllib.parse.quote_plus(term)
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start = 0
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@@ -246,43 +246,37 @@ def search(term, num_results=2, lang="en", advanced=True, timeout=5, safe="activ
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max_chars_per_page = 8000 # Adjust this value based on your token limit and average webpage length
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with requests.Session() as session:
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headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/111.0"},
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params={
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"q": term,
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"num": num_results
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"start": start,
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"udm": 14,
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},
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timeout=timeout,
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verify=ssl_verify,
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webpage = session.get(link, headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/111.0"})
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webpage.raise_for_status()
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visible_text = extract_text_from_webpage(webpage.text)
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# Truncate text if it's too long
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start += len(result_block)
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return all_results
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# Format the prompt for the language model
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"""Extracts visible text from HTML content using BeautifulSoup."""
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soup = BeautifulSoup(html_content, "html.parser")
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# Remove unwanted tags
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for tag in soup(["script", "style", "header", "footer", "nav", "form", "svg"]):
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tag.extract()
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# Get the remaining visible text
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visible_text = soup.get_text(strip=True)
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return visible_text
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# Perform a Google search and return the results
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def search(term, num_results=3, lang="en", advanced=True, timeout=5, safe="active", ssl_verify=None):
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"""Performs a Google search and returns the results."""
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escaped_term = urllib.parse.quote_plus(term)
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start = 0
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max_chars_per_page = 8000 # Adjust this value based on your token limit and average webpage length
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with requests.Session() as session:
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resp = session.get(
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url="https://www.google.com/search",
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headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/111.0"},
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params={
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"q": term,
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"num": num_results,
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"udm": 14,
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},
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timeout=timeout,
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verify=ssl_verify,
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)
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resp.raise_for_status()
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soup = BeautifulSoup(resp.text, "html.parser")
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result_block = soup.find_all("div", attrs={"class": "g"})
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for result in result_block:
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link = result.find("a", href=True)
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if link:
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link = link["href"]
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try:
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webpage = session.get(link, headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/111.0"})
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webpage.raise_for_status()
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visible_text = extract_text_from_webpage(webpage.text)
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# Truncate text if it's too long
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if len(visible_text) > max_chars_per_page:
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visible_text = visible_text[:max_chars_per_page]
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all_results.append({"link": link, "text": visible_text})
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except requests.exceptions.RequestException as e:
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print(f"Error fetching or processing {link}: {e}")
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all_results.append({"link": link, "text": None})
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else:
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all_results.append({"link": None, "text": None})
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return all_results
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# Format the prompt for the language model
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