ai-web-summarizer

week3/community-contributions/ai-web-summarizer/summarizer/fetcher.py

@@ -0,0 +1,23 @@
+import requests
+from bs4 import BeautifulSoup
+
+def fetch_web_content(url):
+    try:
+        response = requests.get(url)
+        response.raise_for_status()
+        
+        # Parse the HTML content
+        soup = BeautifulSoup(response.text, 'html.parser')
+        
+        # Extract readable text from the web page (ignoring scripts, styles, etc.)
+        page_text = soup.get_text(separator=' ', strip=True)
+        
+        return page_text[:5000]  # Limit to 5000 chars (API limitation)
+    except requests.exceptions.RequestException as e:
+        print(f"Error fetching the webpage: {e}")
+        return None
+
+if __name__ == "__main__":
+    url = "https://en.wikipedia.org/wiki/Natural_language_processing"
+    content = fetch_web_content(url)
+    print(content[:500])  # Print a sample of the content

week3/community-contributions/ai-web-summarizer/summarizer/summarizer.py

@@ -0,0 +1,85 @@
+import openai  # type: ignore
+import ollama
+import requests
+from utils.config import Config
+
+# Local Ollama API endpoint
+OLLAMA_API = "http://127.0.0.1:11434/api/chat"
+
+# Initialize OpenAI client with API key
+client = openai.Client(api_key=Config.OPENAI_API_KEY)
+
+def summarize_with_openai(text, model):
+    """Summarize text using OpenAI's GPT model."""
+    try:
+        response = client.chat.completions.create(
+            model=model,
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant that summarizes web pages."},
+                {"role": "user", "content": f"Summarize the following text: {text}"}
+            ],
+            max_tokens=300,
+            temperature=0.7
+        )
+        return response.choices[0].message.content
+    except Exception as e:
+        print(f"Error during OpenAI summarization: {e}")
+        return None
+
+def summarize_with_ollama_lib(text, model):
+    """Summarize text using Ollama Python library."""
+    try:
+        messages = [
+            {"role": "system", "content": "You are a helpful assistant that summarizes web pages."},
+            {"role": "user", "content": f"Summarize the following text: {text}"}
+        ]
+        response = ollama.chat(model=model, messages=messages)
+        return response['message']['content']
+    except Exception as e:
+        print(f"Error during Ollama summarization: {e}")
+        return None
+
+def summarize_with_ollama_api(text, model):
+    """Summarize text using local Ollama API."""
+    try:
+        payload = {
+            "model": model,
+            "messages": [
+                {"role": "system", "content": "You are a helpful assistant that summarizes web pages."},
+                {"role": "user", "content": f"Summarize the following text: {text}"}
+            ],
+            "stream": False  # Set to True for streaming responses
+        }
+        response = requests.post(OLLAMA_API, json=payload)
+        response_data = response.json()
+        return response_data.get('message', {}).get('content', 'No summary generated')
+    except Exception as e:
+        print(f"Error during Ollama API summarization: {e}")
+        return None
+
+def summarize_text(text, model, engine="openai"):
+    """Generic function to summarize text using the specified engine (openai/ollama-lib/ollama-api)."""
+    if engine == "openai":
+        return summarize_with_openai(text, model)
+    elif engine == "ollama-lib":
+        return summarize_with_ollama_lib(text, model)
+    elif engine == "ollama-api":
+        return summarize_with_ollama_api(text, model)
+    else:
+        print("Invalid engine specified. Use 'openai', 'ollama-lib', or 'ollama-api'.")
+        return None
+
+if __name__ == "__main__":
+    sample_text = "Artificial intelligence (AI) is intelligence demonstrated by machines, as opposed to the natural intelligence displayed by animals and humans."
+
+    # Summarize using OpenAI
+    openai_summary = summarize_text(sample_text, model="gpt-3.5-turbo", engine="openai")
+    print("OpenAI Summary:", openai_summary)
+
+    # Summarize using Ollama Python library
+    ollama_lib_summary = summarize_text(sample_text, model="deepseek-r1:1.5B", engine="ollama-lib")
+    print("Ollama Library Summary:", ollama_lib_summary)
+
+    # Summarize using local Ollama API
+    ollama_api_summary = summarize_text(sample_text, model="deepseek-r1:1.5B", engine="ollama-api")
+    print("Ollama API Summary:", ollama_api_summary)