Shreyas094
commited on
Commit
•
58ed008
1
Parent(s):
6e35de4
Update app.py
Browse files
app.py
CHANGED
@@ -143,23 +143,24 @@ def create_web_search_vectors(search_results):
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return FAISS.from_documents(documents, embed)
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def summarize_article(article, model, system_prompt,
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prompt = f"""Using the following article:
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Title: {article
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Content (excerpt): {article
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URL: {article
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# Calculate input tokens (this is an approximation, you might need a more accurate method)
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input_tokens = len(prompt.split()) // 4
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# Calculate
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try:
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response = client.chat_completion(
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return FAISS.from_documents(documents, embed)
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def summarize_article(article, content, query, model, system_prompt, client, temperature=0.2):
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prompt = f"""Using the following article:
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Title: {article.get('title', 'No Title Available')}
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Content (excerpt): {article.get('body', '')[:2000]} # Truncate if too long
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URL: {article.get('href', 'No URL Available')}
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And based on the following web search context (excerpt):
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{content[:2000]} # Truncate if too long
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Write a detailed and complete research document. The document should include:
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1. An introduction
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2. Key findings from both the article and search context
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3. A conclusion that directly answers the user's request: '{query}'."""
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# Calculate token usage and model limits
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input_tokens = len(prompt.split()) // 4 # Approximate token count
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model_token_limit = MODEL_TOKEN_LIMITS.get(model, 8192) # Default limit is 8192 if model is not found
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max_new_tokens = min(model_token_limit - input_tokens, 6500) # Cap output tokens to avoid exceeding limits
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try:
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response = client.chat_completion(
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