Update app.py

app.py

@@ -7,6 +7,13 @@ import os
 # Environment variables and configurations
 huggingface_token = os.environ.get("HUGGINGFACE_TOKEN")
 
+MODELS = [
+    "mistralai/Mistral-7B-Instruct-v0.3",
+    "mistralai/Mixtral-8x7B-Instruct-v0.1",
+    "mistralai/Mistral-Nemo-Instruct-2407",
+    "llama-3-70b"
+]
+
 def get_web_search_results(query: str, max_results: int = 10) -> List[Dict[str, str]]:
     try:
         results = DDGS().text(query, max_results=max_results)
@@ -14,7 +21,7 @@ def get_web_search_results(query: str, max_results: int = 10) -> List[Dict[str,
     except Exception as e:
         return [{"error": f"An error occurred during web search: {str(e)}"}]
 
-def summarize_results(query: str, search_results: List[Dict[str, str]]) -> str:
+def summarize_results(query: str, search_results: List[Dict[str, str]], model: str) -> str:
     try:
         context = "\n\n".join([f"Title: {result['title']}\nContent: {result['body']}" for result in search_results])
         
@@ -27,7 +34,7 @@ def summarize_results(query: str, search_results: List[Dict[str, str]]) -> str:
 
         Article:"""
         
-        summary = DDGS().chat(prompt, model='llama-3-70b')
+        summary = DDGS().chat(prompt, model="llama-3-70b")
         return summary
     except Exception as e:
         return f"An error occurred during summarization: {str(e)}"
@@ -51,35 +58,77 @@ def rephrase_query(previous_response: str, new_query: str) -> str:
     response = client.text_generation(prompt, max_new_tokens=100, temperature=0.7)
     return response
 
-def web_search_and_summarize(input_text: str, chat_history: List[Tuple[str, str]]) -> Tuple[str, List[Tuple[str, str]]]:
+def respond(message, chat_history, model, temperature, num_api_calls):
+    rephrased_query = message
     if chat_history:
         previous_response = chat_history[-1][1]
-        rephrased_query = rephrase_query(previous_response, input_text)
-    else:
-        rephrased_query = input_text
-
-    search_results = get_web_search_results(rephrased_query)
-    if "error" in search_results[0]:
-        summary = search_results[0]["error"]
-    else:
-        summary = summarize_results(rephrased_query, search_results)
-    
-    chat_history.append((input_text, summary))
-    return summary, chat_history
-
-iface = gr.Interface(
-    fn=web_search_and_summarize,
-    inputs=[
-        gr.Textbox(lines=2, placeholder="Enter your query here..."),
-        gr.State([])
+        rephrased_query = rephrase_query(previous_response, message)
+
+    final_summary = ""
+    for _ in range(num_api_calls):
+        search_results = get_web_search_results(rephrased_query)
+        if "error" in search_results[0]:
+            final_summary += search_results[0]["error"] + "\n"
+        else:
+            summary = summarize_results(rephrased_query, search_results, model)
+            final_summary += summary + "\n\n"
+
+    return final_summary
+
+def initial_conversation():
+    return [
+        ("Hello! How can I assist you today?", "Welcome! I'm your AI-powered Web Search and PDF Chat Assistant. I can help you find information on the web, summarize content, and analyze PDF documents. What would you like to know?")
+    ]
+
+css = """
+Your custom CSS here
+"""
+
+custom_placeholder = "Ask me anything about web content or uploaded PDFs..."
+
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        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")
     ],
-    outputs=[
-        gr.Textbox(label="Response"),
-        gr.State()
+    title="AI-powered Web Search and PDF Chat Assistant",
+    description="This AI-powered Web Search and PDF Chat Assistant combines real-time web search capabilities with advanced language processing. It can analyze web content and PDF documents, providing detailed summaries and engaging in in-depth conversations about the information it discovers. Whether you're researching a topic, seeking current news, or exploring document contents, this tool offers intelligent, context-aware responses to your queries.",
+    theme=gr.themes.Soft(
+        primary_hue="orange",
+        secondary_hue="amber",
+        neutral_hue="gray",
+        font=[gr.themes.GoogleFont("Exo"), "ui-sans-serif", "system-ui", "sans-serif"]
+    ).set(
+        body_background_fill_dark="#0c0505",
+        block_background_fill_dark="#0c0505",
+        block_border_width="1px",
+        block_title_background_fill_dark="#1b0f0f",
+        input_background_fill_dark="#140b0b",
+        button_secondary_background_fill_dark="#140b0b",
+        border_color_accent_dark="#1b0f0f",
+        border_color_primary_dark="#1b0f0f",
+        background_fill_secondary_dark="#0c0505",
+        color_accent_soft_dark="transparent",
+        code_background_fill_dark="#140b0b"
+    ),
+    css=css,
+    examples=[
+        ["Tell me about the contents of the uploaded PDFs."],
+        ["What are the main topics discussed in the documents?"],
+        ["Can you summarize the key points from the PDFs?"]
     ],
-    title="DuckDuckGo Web Search and Summary",
-    description="Enter a query to get a summary based on web search results using DuckDuckGo.",
-    allow_flagging="never"
+    cache_examples=False,
+    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()
+    )
 )
 
-iface.launch()
+demo.launch()