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Shane
2025-05-01 19:24:20 +10:00
parent 022b52a8a7
commit 90be324fe4
2 changed files with 57 additions and 42 deletions
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foodie_utils.py
+40 -41
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@@ -137,7 +137,7 @@ def generate_article_tweet(author, post, persona):
author_handle = f"@{author['username']}"
prompt = (
f"Craft a sharp tweet (under 280 characters) for {author_handle} with the voice of '{persona}'. "
f"Craft a sharp tweet (under 230 characters) for {author_handle} with the voice of '{persona}'. "
f"Distill the essence of the article '{title}' and include the raw URL '{url}' at the end. "
f"Make it bold, spark curiosity, and invite engagement with a human touch. "
f"Swap 'elevate' for dynamic terms like 'ignite' or 'unleash'. "
@@ -414,53 +414,46 @@ def get_image(search_query):
logging.error(f"Pixabay image fetch failed for query '{search_query}': {e}")
return None, None, None, None
def generate_image_query(content):
prompt = (
"Given the following content, generate a concise image search query (max 5 words) that would likely yield relevant, visually appealing images on platforms like Flickr or Pixabay. "
"Identify and prioritize specific entities like brand names or unique terms over abstract or generic concepts. "
"Focus on concrete, visual concepts related to food, dining, or restaurants. "
"Also provide relevance keywords (max 5 words) to filter results, using general themes related to the content. "
"Return the result as a JSON object with 'search' and 'relevance' keys.\n\n"
"Content:\n"
f"{content}\n\n"
"Example output:\n"
"```json\n"
"{\n"
" \"search\": \"Wingstop dining\",\n"
" \"relevance\": \"fast food dining\"\n"
"}\n```"
)
def generate_image_query(title, summary):
try:
prompt = (
"Given the following article title and summary, generate a concise image search query (max 5 words) to find a relevant image. "
"Also provide a list of relevance keywords (max 5 words) that should be associated with the image. "
"Return the result as a JSON object with 'search' and 'relevance' keys.\n\n"
f"Title: {title}\n\n"
f"Summary: {summary}\n\n"
"Example output:\n"
"```json\n"
"{\"search\": \"Italian cuisine trends\", \"relevance\": \"pasta wine dining culture\"}\n"
"```"
)
response = client.chat.completions.create(
model=LIGHT_TASK_MODEL,
messages=[
{"role": "system", "content": "You are a helpful assistant that generates concise image search queries."},
{"role": "user", "content": prompt}
{"role": "system", "content": prompt},
{"role": "user", "content": "Generate an image search query and relevance keywords."}
],
max_tokens=100,
temperature=0.5
)
raw_response = response.choices[0].message.content
logging.debug(f"Raw GPT image query response: '{raw_response}'")
# Extract JSON from the response
json_match = re.search(r'```json\n([\s\S]*?)\n```', raw_response)
if not json_match:
logging.warning(f"Failed to parse image query JSON from GPT response: {raw_response}")
return "food dining", ["dining", "trends"]
logging.warning(f"Failed to parse image query JSON: {raw_response}")
return title, [], True
query_data = json.loads(json_match.group(1))
search_query = query_data.get("search", "food dining")
relevance_keywords = query_data.get("relevance", ["dining", "trends"])
search_query = query_data.get("search", title)
relevance_keywords = query_data.get("relevance", "").split()
logging.debug(f"Image query from content: {query_data}")
return search_query, relevance_keywords
# Log the JSON object in a single line
log_json = json.dumps(query_data).replace('\n', ' ').replace('\r', ' ')
logging.debug(f"Image query from content: {log_json}")
return search_query, relevance_keywords, False
except Exception as e:
logging.warning(f"Failed to generate image query: {e}. Using fallback.")
return "food dining", ["dining", "trends"]
logging.warning(f"Image query generation failed: {e}. Using title as fallback.")
return title, [], True
def smart_image_and_filter(title, summary):
try:
@@ -655,6 +648,7 @@ def summarize_with_gpt4o(content, source_name, link, interest_score=0, extra_pro
full_prompt = (
f"{prompt}\n\n"
f"Do not include the article title in the summary.\n\n"
f"{extra_prompt}\n\n"
f"Avoid using the word 'elevate'—use more humanized language like 'level up' or 'bring to life'.\n"
f"Content to summarize:\n{content}\n\n"
@@ -673,6 +667,14 @@ def summarize_with_gpt4o(content, source_name, link, interest_score=0, extra_pro
)
summary = response.choices[0].message.content.strip()
# Post-process to remove the original title if it still appears
# Extract the title from the content (assuming it's the first line or part of the prompt)
# For simplicity, we can pass the title as an additional parameter if needed
# Here, we'll assume the title is passed via the calling function (e.g., from foodie_automator_rss.py)
# For now, we'll use a placeholder for the title removal logic
# In foodie_automator_rss.py, the title is available as entry.title
# We'll handle the title removal in the calling script instead
logging.info(f"Processed summary (Persona: {persona}): {summary}")
return summary
@@ -682,13 +684,12 @@ def summarize_with_gpt4o(content, source_name, link, interest_score=0, extra_pro
def insert_link_naturally(summary, source_name, source_url):
try:
# Log the input summary to debug its structure
logging.info(f"Input summary to insert_link_naturally: {summary!r}")
prompt = (
"Take this summary and insert a single HTML link naturally into one paragraph (randomly chosen). "
"Use the format '<a href=\"{source_url}\">{source_name}</a>' and weave it into the text seamlessly, "
"e.g., 'The latest scoop from {source_name} reveals...' or '{source_name} uncovers this wild shift.' "
"e.g., 'The latest scoop from {source_name} reveals...' or '{source_name} shares this insight.' "
"Vary the phrasing creatively to avoid repetition (don’t always use 'dives into'). "
"Place the link at a sentence boundary (after a period, not within numbers like '6.30am' or '1.5'). "
"Maintain the original tone, flow, and paragraph structure, preserving all existing newlines exactly as they are. "
@@ -711,10 +712,7 @@ def insert_link_naturally(summary, source_name, source_url):
new_summary = response.choices[0].message.content.strip()
link_pattern = f'<a href="{source_url}">{source_name}</a>'
if new_summary and new_summary.count(link_pattern) == 1:
# Normalize paragraph separation to ensure a single \n break
# Split by newlines, but do not filter out paragraphs to preserve the count
paragraphs = new_summary.split('\n')
# Strip each paragraph, but keep all paragraphs even if empty
paragraphs = [p.strip() for p in paragraphs]
new_summary = '\n'.join(paragraphs)
logging.info(f"Summary with naturally embedded link (normalized): {new_summary!r}")
@@ -733,11 +731,12 @@ def insert_link_naturally(summary, source_name, source_url):
return summary
target_para = random.choice([p for p in paragraphs if p.strip()])
link_pattern = f'<a href="{source_url}">{source_name}</a>'
phrases = [
f"The scoop from {link_pattern} spills the details",
f"{link_pattern} uncovers this wild shift",
f"This gem via {link_pattern} drops some truth",
f"{link_pattern} breaks down the buzz"
f"Learn more from {link_pattern}",
f"{link_pattern} shares this insight",
f"Discover more at {link_pattern}",
f"Check out {link_pattern} for details"
]
insertion_phrase = random.choice(phrases)