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@@ -33,7 +33,7 @@ class OllamaGenerator:
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The title for the blog is {self.inner_title}.
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The title for the blog is {self.inner_title}.
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Do not output the title in the markdown.
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Do not output the title in the markdown.
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The basis for the content of the blog is:
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The basis for the content of the blog is:
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{self.content}
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<blog>{self.content}</blog>
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"""
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"""
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def split_into_chunks(self, text, chunk_size=100):
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def split_into_chunks(self, text, chunk_size=100):
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@@ -127,10 +127,11 @@ class OllamaGenerator:
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you are more professional and will attempt to tone these down
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you are more professional and will attempt to tone these down
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As this person produce the final version of this blog as a markdown document
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As this person produce the final version of this blog as a markdown document
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keeping in mind the context provided by the previous drafts.
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keeping in mind the context provided by the previous drafts.
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You are to produce the content not placeholders for further editors
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The title for the blog is {self.inner_title}.
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The title for the blog is {self.inner_title}.
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Do not output the title in the markdown. Avoid repeated sentences
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Do not output the title in the markdown. Avoid repeated sentences
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The basis for the content of the blog is:
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The basis for the content of the blog is:
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{self.content}
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<blog>{self.content}</blog>
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"""
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"""
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try:
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try:
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query_embed = self.ollama_client.embed(model=self.embed_model, input=prompt_system)['embeddings']
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query_embed = self.ollama_client.embed(model=self.embed_model, input=prompt_system)['embeddings']
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@@ -139,7 +140,7 @@ class OllamaGenerator:
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print("Showing pertinent info from drafts used in final edited edition")
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print("Showing pertinent info from drafts used in final edited edition")
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pertinent_draft_info = '\n\n'.join(collection.query(query_embeddings=query_embed, n_results=100)['documents'][0])
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pertinent_draft_info = '\n\n'.join(collection.query(query_embeddings=query_embed, n_results=100)['documents'][0])
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#print(pertinent_draft_info)
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#print(pertinent_draft_info)
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prompt_human = f"""Generate the final, 3000 word, draft of the blog using this information from the drafts: {pertinent_draft_info}
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prompt_human = f"""Generate the final, 3000 word, draft of the blog using this information from the drafts: <context>{pertinent_draft_info}</context>
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- Only output in markdown, do not wrap in markdown tags, Only provide the draft not a commentary on the drafts in the context
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- Only output in markdown, do not wrap in markdown tags, Only provide the draft not a commentary on the drafts in the context
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"""
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"""
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print("Generating final document")
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print("Generating final document")
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