Update app.py

app.py

@@ -271,38 +271,30 @@ def generate_chunked_response(prompt, model, max_tokens=10000, num_calls=3, temp
     print(f"Final clean response: {final_response[:100]}...")
     return final_response
 
-def duckduckgo_search(query, safe="on", region=None, language=None, time=None, filetype=None, site=None, inurl=None, intitle=None, intext=None, related=None, info=None, define=None):
+def duckduckgo_search(query,time=None):
     params = {
-        "q": query,
-        "safe": safe,
-        "region": region,
-        "language": language,
-        "time": time,
-        "filetype": filetype,
-        "site": site,
-        "inurl": inurl,
-        "intitle": intitle,
-        "intext": intext,
-        "related": related,
-        "info": info,
-        "define": define
-   }
-   with DDGS() as ddgs:
-       results = ddgs.text(query, params=params, max_results=5)
-   return results
+       "q": query,
+       "region": region,
+       "language": language,
+       "time": time,
+     }
+    with DDGS() as ddgs:
+        results = ddgs.text(query, params=params, max_results=5)
+    return results
 
 class CitingSources(BaseModel):
     sources: List[str] = Field(
         ...,
         description="List of sources to cite. Should be an URL of the source."
     )
-
-def chatbot_interface(message, history, use_web_search, model, temperature, num_calls, safe, region, language, time, filetype, site, inurl, intitle, intext, related, info, define):
+def chatbot_interface(message, history, use_web_search, model, temperature, num_calls, region, language, time):
     if not message.strip():
         return "", history
+
     history = history + [(message, "")]
+
     try:
-        for response in respond(message, history, model, temperature, num_calls, use_web_search, safe, region, language, time, filetype, site, inurl, intitle, intext, related, info, define):
+        for response in respond(message, history, model, temperature, num_calls, use_web_search, region, language, time):
             history[-1] = (message, response)
             yield history
     except gr.CancelledError:
@@ -321,19 +313,21 @@ def retry_last_response(history, use_web_search, model, temperature, num_calls):
     
     return chatbot_interface(last_user_msg, history, use_web_search, model, temperature, num_calls)
 
-def respond(message, history, model, temperature, num_calls, use_web_search, safe, region, language, time, filetype, site, inurl, intitle, intext, related, info, define):
+def respond(message, history, model, temperature, num_calls, use_web_search, region, language, time, selected_docs):
     logging.info(f"User Query: {message}")
     logging.info(f"Model Used: {model}")
     logging.info(f"Search Type: {'Web Search' if use_web_search else 'PDF Search'}")
-   
+
+    logging.info(f"Selected Documents: {selected_docs}")
+
     try:
         if use_web_search:
-            for main_content, sources in get_response_with_search(message, model, num_calls=num_calls, temperature=temperature, safe=safe, region=region, language=language, time=time, filetype=filetype, site=site, inurl=inurl, intitle=intitle, intext=intext, related=related, info=info, define=define):
+            for main_content, sources in get_response_with_search(message, model, num_calls=num_calls, temperature=temperature, region=region, language=language, time=time):
                 response = f"{main_content}\n\n{sources}"
                 first_line = response.split('\n')[0] if response else ''
-                logging.info(f"Generated Response (first line): {first_line}")
+#                logging.info(f"Generated Response (first line): {first_line}")
                 yield response
-       else:
+        else:
             embed = get_embeddings()
             if os.path.exists("faiss_database"):
                 database = FAISS.load_local("faiss_database", embed, allow_dangerous_deserialization=True)
@@ -431,20 +425,16 @@ After writing the document, please provide a list of sources used in your respon
     if not full_response:
         yield "I apologize, but I couldn't generate a response at this time. Please try again later."
 
-def get_response_with_search(query, model, num_calls=3, temperature=0.2, safe="on", region=None, language=None, time=None, filetype=None, site=None, inurl=None, intitle=None, intext=None, related=None, info=None, define=None):
-    search_results = duckduckgo_search(query, safe=safe, region=region, language=language, time=time, filetype=filetype, site=site, inurl=inurl, intitle=intitle, intext=intext, related=related, info=info, define=define)
-    web_search_database = create_web_search_vectors(search_results)
-    if not web_search_database:
-        yield "No web search results available. Please try again.", ""
-        return
-    retriever = web_search_database.as_retriever(search_kwargs={"k": 5})
-    relevant_docs = retriever.get_relevant_documents(query)
-    context = "\n".join([doc.page_content for doc in relevant_docs])
-    prompt = f"""Using the following context from web search results:
+def get_response_with_search(query, model, num_calls=3, temperature=0.2, region=None, language=None, time=None):
+    search_results = duckduckgo_search(query)
+    context = "\n".join(f"{result['title']}\n{result['body']}\nSource: {result['href']}\n" 
+                        for result in search_results if 'body' in result)
+    
+    prompt = f"""Using the following context:
 {context}
 Write a detailed and complete research document that fulfills the following user request: '{query}'
 After writing the document, please provide a list of sources used in your response."""
-    
+
     if model == "@cf/meta/llama-3.1-8b-instruct":
         # Use Cloudflare API
         for response in get_response_from_cloudflare(prompt="", context=context, query=query, num_calls=num_calls, temperature=temperature, search_type="web"):
@@ -460,7 +450,7 @@ After writing the document, please provide a list of sources used in your respon
                 max_tokens=10000,
                 temperature=temperature,
                 stream=True,
-           ):
+            ):
                 if message.choices and message.choices[0].delta and message.choices[0].delta.content:
                     chunk = message.choices[0].delta.content
                     main_content += chunk
@@ -591,24 +581,14 @@ demo = gr.ChatInterface(
         gr.Dropdown(choices=MODELS, label="Select Model", value=MODELS[3]),
         gr.Slider(minimum=0.1, maximum=1.0, value=0.2, step=0.1, label="Temperature"),
         gr.Slider(minimum=1, maximum=5, value=1, step=1, label="Number of API Calls"),
-        use_web_search,
-        document_selector,
-        gr.Dropdown(choices=instruction_choices, label="Select Entity Type for Summary", value="None"),
-        gr.Checkbox(label="Safe Search", value=True),
         gr.Textbox(label="Region", placeholder="US"),
         gr.Textbox(label="Language", placeholder="en"),
         gr.Textbox(label="Time", placeholder="d"),
-        gr.Textbox(label="Filetype", placeholder="pdf"),
-        gr.Textbox(label="Site", placeholder="github.com"),
-        gr.Textbox(label="Inurl", placeholder="github.com"),
-        gr.Textbox(label="Intitle", placeholder="github"),
-        gr.Textbox(label="Intext", placeholder="github"),
-        gr.Textbox(label="Related", placeholder="github.com"),
-        gr.Textbox(label="Info", placeholder="github.com"),
-        gr.Textbox(label="Define", placeholder="github")
+        use_web_search,
+        document_selector
     ],
     title="AI-powered Web Search and PDF Chat Assistant",
-    description="Chat with your PDFs, use web search to answer questions, or generate summaries. Select an Entity Type for Summary to generate a specific summary.",
+    description="Chat with your PDFs or use web search to answer questions. Toggle between Web Search and PDF Chat in Additional Inputs below.",
     theme=gr.themes.Soft(
         primary_hue="orange",
         secondary_hue="amber",
@@ -637,12 +617,12 @@ demo = gr.ChatInterface(
     analytics_enabled=False,
     textbox=gr.Textbox(placeholder=custom_placeholder, container=False, scale=7),
     chatbot = gr.Chatbot(  
-        show_copy_button=True,
-        likeable=True,
-        layout="bubble",
-        height=400,
-        value=initial_conversation()
-    )
+    show_copy_button=True,
+    likeable=True,
+    layout="bubble",
+    height=400,
+    value=initial_conversation()
+)
 )
 
 # Add file upload functionality