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LLM refactor, NPU ollama based, publisher update json query to llm

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This commit is contained in:
Luciano Gervasoni
2025-04-23 16:35:50 +02:00
parent 8ea3ec1bda
commit e5c574ba33
7 changed files with 123 additions and 34 deletions
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73
app_urls/fetcher/src/llm.py
View File

@@ -1,24 +1,75 @@
import ollama
import os
import requests
import json
from .logger import get_logger
logger = get_logger()
class OllamaClient():
def __init__(self):
self.client = ollama.Client(host=os.getenv("ENDPOINT_OLLAMA", "https://ollamamodel.matitos.org"))
self.host = os.getenv("ENDPOINT_OLLAMA", "https://ollamamodel.matitos.org")
self.client = ollama.Client(host=self.host)
def _get_default_model(self):
return "llama3.2:3b"
return os.getenv("OLLAMA_MODEL_DEFAULT", "llama3.2:3b")
def get_models(self):
models = sorted([m.model for m in self.client.list().models])
if (self._get_default_model() in models):
return [self._get_default_model()] + [m for m in models if m != self._get_default_model()]
else:
return models
try:
# Get models
models = sorted([m.model for m in self.client.list().models])
# r = requests.get( os.path.join(endpoint, "models") )
# r.json().get("models")
# Default within it?
if (self._get_default_model() in models):
return [self._get_default_model()] + [m for m in models if m != self._get_default_model()]
else:
return models
except Exception as e:
return []
def get_prompt(self):
return ("Rewrite the text below into a clear and concise summary of one paragraph maximum, presenting the key points as if they are newly written insights. "
def get_prompt(self, content):
return "Provide, in one sentence each, the who, what, when, where, why, and a detailed summary of the content below:\n\n{}".format(content)
return "First, provide a detailed summary of the content below in one paragraph. Second, specify in one sentence each the who, what, when, where and why of the story. Do not mention or reference the original text, its source, or any phrases like 'According to' or 'The text states':\n\n{}".format(content)
return "First, provide a summary of the content below in one paragraph. Second, specify the Who, What, When, Where and Why of the story:\n\n{}".format(content)
# First, provide a summary of the content below in one paragraph. Second, specify the who, what, when, where and why of the story in one sentence each. Do not mention or reference the original text, its source, or any phrases like 'According to' or 'The text states':
'''
return ("Rewrite the content below into a clear and concise summary of one paragraph maximum, presenting the key points as if they are newly written insights. "
"Do not mention or reference the original text, its source, or any phrases like 'According to' or 'The text states'. "
"Write in a natural, standalone format that feels like an original explanation. "
"Keep it brief, engaging, informative, in the style of a news article: \n"
"Keep it brief, engaging, informative, in the style of a news article:\n\n{}".format(content)
)
'''
def generate(self, model, prompt, format=None):
try:
# Generate response
response = self.client.generate(model=model, prompt=prompt, format=format)
# Extract response
response = response.response
# Json? -> Dict
if (format == "json"):
# Dict
response = json.loads(response)
# Force unload
r = requests.post( os.path.join(self.host, "unload_model") )
except Exception as e:
logger.warning("Exception while generating LLM response: {}".format(str(e)))
if (format == "json"):
response = {}
else:
response = None
# Text
return response
def generate_stream(self, model, prompt):
try:
# Generate response
response = self.client.generate(model=model, prompt=prompt, format="json", stream=True)
# Streamed chunks
for chunk in response:
yield chunk.response
# Force unload
r = requests.post( os.path.join(self.host, "unload_model") )
except Exception as e:
logger.warning("Exception while generating LLM response: {}".format(str(e)))

57
app_urls/fetcher/src/publisher.py
View File

@@ -100,14 +100,51 @@ class Publisher():
if (url_content.valid_content is False):
logger.warning("Ghost - URL Content is not valid for URL ID: {} {}".format(url_id, url.url))
return
###########################################
client_llm = OllamaClient()
# Model
model = client_llm.get_models()[0]
# Prompt
prompt = client_llm.get_prompt(url_content.content)
# Generate content
generated_content_dict = client_llm.generate(model, prompt, format="json")
logger.debug("Generated content: {}".format(generated_content_dict))
model = "llama3.2:3b"
prompt = "Rewrite the text below into a clear and concise summary, presenting the key points as if they are newly written insights. Do not mention or reference the original text, its source, or any phrases like 'According to' or 'The text states'. Instead, write in a natural, standalone format that feels like an original explanation. Keep it brief, engaging, informative, in the style of a news article, and no longer than a paragraph:"
###########################################
# Get where description
generated_content_where = generated_content_dict.get("where")
# Prompt to extract address / location
prompt = 'Only answer with the location or address which can be extracted from this description: "{}"'.format(generated_content_where)
# LLM
extracted_location = client_llm.generate(model, prompt, format=None)
logger.debug("Estimated location: {}".format(extracted_location))
# OSM API
params = {
'q': extracted_location,
'format': 'json',
'addressdetails': 1,
'limit': 1
}
ollama_msg = {"role": "user", "content": "{}\n{}".format(prompt, url_content.content)}
response = OllamaClient().client.chat(model=model, messages=[ollama_msg])
response = requests.get('https://nominatim.openstreetmap.org/search', params=params, headers={'User-Agent': 'App'})
list_data = response.json()
if (len(list_data) > 0):
data = list_data[0]
location_url = "https://openstreetmap.org/{}/{}".format(data.get("osm_type"), data.get("osm_id"))
else:
location_url = None
###########################################
article_summary = response["message"]["content"]
# Parse generated content
summary, five_w = "", ""
for k, v in generated_content_dict.items():
if ("summary" in k.lower()):
summary = v
else:
five_w += "{}: {}\n".format(k.capitalize(), v)
# Aggregate generated content
generated_content = "{}\n\n{}".format(summary, five_w)
################################################################################################
if (url_content.image_main_url is None) or (requests.get(url_content.image_main_url).status_code != 200):
@@ -117,10 +154,18 @@ class Publisher():
else:
photo_url = url_content.image_main_url
# HTML: Generate content
html_data = "".join([ "<p>{}</p>".format(t) for t in generated_content.split("\n") ])
# HTML: Add location if available
if (location_url is not None):
html_data += '<p><a href="{}">Estimated location</a></p>'.format(location_url)
# HTML: Add source
html_data += '<p><a href="{}">Source</a></p>'.format(url.url)
post_data = {
# "slug": "hey-short",
"title": url_content.title,
"html": "".join([ "<p>{}</p>".format(t) for t in article_summary.split("\n") ]) + '<a href="{}">Source</a>'.format(url.url),
"html": html_data,
#"meta_title": "",
#"meta_description": "",
"feature_image": photo_url,

3
app_urls/fetcher/templates/url_detail.html
View File

@@ -278,8 +278,7 @@
<!-- Input field with a default value -->
<label for="custom-input-{{ url_item.id }}">Prompt:</label>
<textarea id="custom-input-{{ url_item.id }}" class="form-control mb-2" rows="5">{{ prompt }}
{{ url_item.url }}</textarea>
<textarea id="custom-input-{{ url_item.id }}" class="form-control mb-2" rows="5">{{ prompt }}</textarea>
<div class="d-flex align-items-center">
<!-- Fetch details button -->

16
app_urls/fetcher/views.py
View File

@@ -14,16 +14,6 @@ import json
####################################################################################################
def llm(request):
def stream_response(model, text):
msg_content = {
"role": "user",
"content": text,
}
response = OllamaClient().client.chat(model=model, messages=[msg_content], stream=True)
for chunk in response:
yield chunk["message"]["content"] # Stream each chunk of text
if request.method == 'POST':
try:
body_data = json.loads(request.body)
@@ -33,7 +23,7 @@ def llm(request):
if message is None:
return JsonResponse({'error': 'No message found in request'}, status=400)
return StreamingHttpResponse(stream_response(model, message), content_type="text/plain")
return StreamingHttpResponse(OllamaClient().generate_stream(model, message), content_type="text/plain")
except json.JSONDecodeError:
return JsonResponse({'error': 'Invalid JSON'}, status=400)
@@ -55,13 +45,15 @@ def url_detail_view(request, id):
url_content = {}
ollama = OllamaClient()
# prompt_content = "{}\n{}\n{}".format(url_content.title, url_content.description, url_content.content)
prompt_content = "{}".format(url_content.content)
context = {
'url_item': url_item,
'sources': url_sources,
'searches': url_searches,
'models': ollama.get_models(),
'prompt': ollama.get_prompt(),
'prompt': ollama.get_prompt(prompt_content),
'url_content': url_content,
'url_canonical': url_canonical,
}