multi URL

app.py

@@ -9,83 +9,99 @@ import requests
 
 
 # define the text summarizer function
-def text_prompt(request, system_role, page_url, contraseña, temp):
-    try:
-        headers = {'User-Agent': 'Chrome/83.0.4103.106'}
-        response = requests.get(page_url, headers=headers)
-        html = response.text
-
-        page = Article('')
-        page.set_html(html)
-        page.parse()
-
-    except Exception as e:
-        return "", f"--- An error occurred while processing the URL: {e} ---", ""
-    
+def text_prompt(request, system_role, page_urls_str, contrasenya, api_base, deployment_id, temp):
     tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
-    sentences = page.text.split('.')
-    
-    tokens = []
-    page_text = ""
-    
-    for sentence in sentences:
-        tokens.extend(tokenizer.tokenize(sentence))
-        
-        # Trim text to a maximum of 3100 tokens
-        if len(tokens) > 3100:
-            break
-        page_text += sentence + ". "
-        
-    # Delete the last space
-    page_text = page_text.strip()
-
-    num_tokens = len(tokens)
-
-    if num_tokens > 10 and contraseña.startswith("sk-"):
-        openai.api_key = contraseña
-        # get the response from openai API
+
+    page_urls = [page_url_str for page_url_str in page_urls_str.split("\n") if page_url_str]
+    if len(page_urls) == 0:
+        return "", "urls not found", ""
+
+    page_texts = []
+    response_texts = []
+    total_tokens = 0
+    for page_url in page_urls:
         try:
-            response = openai.ChatCompletion.create(
-                model="gpt-3.5-turbo",
-                messages=[
-                    {"role": "system", "content": system_role},
-                    {"role": "user", "content": request + "\n\n" + 'Text:\n\n"' + page_text + '\n"'}
-                ],
-                max_tokens=512,
-                temperature=temp,
-                top_p=1.0,
-            )
-            # get the response text
-            response_text = response['choices'][0]['message']['content']
-            total_tokens = response["usage"]["total_tokens"]
-
-            # clean the response text
-            response_text = re.sub(r'\s+', ' ', response_text)
-            response_text = f"#### [{page.title}]({page_url})\n\n{response_text.strip()}"
-            total_tokens_str = str(total_tokens) + " (${:.2f} USD)".format(total_tokens/1000*0.002)
-
-
-            return page.text, response_text, total_tokens_str
+            headers = {'User-Agent': 'Chrome/83.0.4103.106'}
+            response = requests.get(page_url, headers=headers)
+            html = response.text
+
+            page = Article('')
+            page.set_html(html)
+            page.parse()
+
         except Exception as e:
-            return page.text, f"--- An error occurred while processing the request: {e} ---", num_tokens
-    return page.text, "--- Check API-Key or Min number of tokens:", str(num_tokens)
+            return "", f"--- An error occurred while processing the URL: {e} ---", ""
+
+        sentences = page.text.split('.')
+
+        tokens = []
+        page_text = ""
+
+        for sentence in sentences:
+            tokens.extend(tokenizer.tokenize(sentence))
+
+            # Trim text to a maximum of 3100 tokens
+            if len(tokens) > 3100:
+                break
+            page_text += sentence + ". "
+
+        # Delete the last space
+        page_text = page_text.strip()
+
+        num_tokens = len(tokens)
+
+        if num_tokens > 10 and len(contrasenya) > 6 and len(deployment_id) > 6:
+            openai.api_type = "azure"
+            openai.api_version = "2023-03-15-preview"
+            openai.api_base = api_base
+            openai.api_key = contrasenya
+            # get the response from openai API
+            try:
+                response = openai.ChatCompletion.create(
+                    deployment_id=deployment_id,
+                    messages=[
+                        {"role": "system", "content": system_role},
+                        {"role": "user", "content": request + "\n\n" + 'Text:\n\n""""' + page_text + '\n""""'}
+                    ],
+                    max_tokens=4000,
+                    temperature=temp,
+                    top_p=1.0,
+                )
+                # get the response text
+                response_text = response['choices'][0]['message']['content']
+                total_tokens += response["usage"]["total_tokens"]
+
+                # clean the response text
+                response_text = re.sub(r'\s+', ' ', response_text)
+                response_text = f"#### [{page.title}]({page_url})\n\n{response_text.strip()}"
+
+                page_texts.append(page.text)
+                response_texts.append(response_text)
+            except Exception as e:
+                return page.text, f"--- An error occurred while processing the request: {e} ---", num_tokens
+        else:
+            return page.text, "--- Check API-Key or deployment_id or Min number of tokens:", str(num_tokens)
+
+    page_texts_str = "\n\n============\n".join([page_text for page_text in page_texts])
+    response_texts_str = "\n\n".join([response_text for response_text in response_texts])
+    total_tokens_str = str(total_tokens) + " (${:.2f} USD)".format(total_tokens / 1000 * 0.03)
+    return page_texts_str, response_texts_str, total_tokens_str
+
 
 # define the gradio interface
 iface = gr.Interface(
     fn=text_prompt,
     inputs=[gr.Textbox(lines=1, placeholder="Enter your prompt here...", label="Prompt:", type="text"),
             gr.Textbox(lines=1, placeholder="Enter your system-role description here...", label="System Role:", type="text"),
-            gr.Textbox(lines=1, placeholder="Enter the Article's URL here...", label="Article's URL to parse:", type="text"),
+            gr.Textbox(lines=10, placeholder="Enter the Articles' URLs here...", label="Articles' URLs to parse (one per line up to 10):", type="text"),
             gr.Textbox(lines=1, placeholder="Enter your API-key here...", label="API-Key:", type="password"),
-            gr.Slider(0.0,1.0, value=0.3, label="Temperature:")
+            gr.Textbox(lines=1, placeholder="Enter your Azure OpenAI endpoint here...", label="Endpoint:", type="text"),
+            gr.Textbox(lines=1, placeholder="Enter your model name here...", label="Deployment ID:", type="text"),
+            gr.Slider(0.0, 1.0, value=0.0, label="Temperature:")
             ],
     outputs=[gr.Textbox(label="Input:"), gr.Markdown(label="Output:"), gr.Markdown(label="Total Tokens:")],
-    examples=[["Resumen el siguiente texto en un máximo de 100 palabras.", "Actuar como consultor de negocio. La respuesta deberá aparentar ser novedosa. Formatea la respuesta en Markdown. El texto deberá ser traducido siempre al español. Deberás añadir al final una lista de topics del texto en forma de lista separada por comas.", "https://blog.google/outreach-initiatives/google-org/our-commitment-on-using-ai-to-accelerate-progress-on-global-development-goals/","",0.3],
-            ["Generate a summary of the following text. Give me an overview of the main business impact from the text following this template:\n- Summary:\n- Business Impact:\n- Companies:", "Act as a Business Consultant", "https://ai.googleblog.com/2019/10/quantum-supremacy-using-programmable.html","",0.7],
-            ["Generate the next insights based on the following text. Indicates N/A if the information is not available in the text.\n- Summary:\n- Acquisition Price:\n- Why is this important for the acquirer:\n- Business Line for the acquirer:\n- Tech Focus for the acquired (list):","Act as a Business Consultant", "https://techcrunch.com/2022/09/28/eqt-acquires-billtrust-a-company-automating-the-invoice-to-cash-process-for-1-7b/","",0.3]
-    ],
     title="ChatGPT info extraction from URL",
-    description="This tool allows querying the text retrieved from the URL with newspaper3k lib and using OpenAI's [gpt-3.5-turbo] engine.\nThe URL text can be referenced in the prompt as \"following text\".\nA GPT2 tokenizer is included to ensure that the 1.800 token limit for OpenAI queries is not exceeded. Provide a prompt with your request, the description for the system role, the url for text retrieval, your api-key and temperature to process the text."
+    description="This tool allows querying the text retrieved from the URL with newspaper3k lib and using MSFT Azure OpenAI's [gpt-3.5-turbo] engine.\nThe URL text can be referenced in the prompt as \"following text\".\nA GPT2 tokenizer is included to ensure that the 1.800 token limit for OpenAI queries is not exceeded. Provide a prompt with your request, the description for the system role, the url for text retrieval, your api-key and temperature to process the text."
 )
 
 # error capturing in integration as a component
@@ -94,7 +110,7 @@ error_message = ""
 
 try:
     iface.queue(concurrency_count=20)
-    iface.launch()
+    iface.launch(debug=True)
 except Exception as e:
     error_message = "An error occurred: " + str(e)
     iface.outputs[1].value = error_message