Update app.py
Browse files
app.py
CHANGED
@@ -4,6 +4,7 @@ import json
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from bs4 import BeautifulSoup
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import requests
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css = '''
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.gradio-container{max-width: 1000px !important}
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h1{text-align:center}
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@@ -12,34 +13,35 @@ footer {
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}
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'''
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soup = BeautifulSoup(html_content, 'html.parser')
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for tag in soup(["script", "style", "header", "footer"]):
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tag.extract()
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return soup.get_text(strip=True)
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all_results = []
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max_chars_per_page = 8000
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with requests.Session() as session:
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url="https://www.google.com/search",
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headers={"User-Agent": "Mozilla/5.0
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params={"q":
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timeout=5,
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verify=
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)
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soup = BeautifulSoup(
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result_block = soup.find_all("div", attrs={"class": "g"})
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for result in result_block:
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link = result.find("a", href=True)
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link = link["href"]
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try:
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visible_text =
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if len(visible_text) > max_chars_per_page:
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visible_text = visible_text[:max_chars_per_page]
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all_results.append({"link": link, "text": visible_text})
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@@ -47,36 +49,33 @@ def search(query):
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all_results.append({"link": link, "text": None})
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return all_results
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client_gemma = InferenceClient("mistralai/Mistral-7B-Instruct-v0.3")
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client_mixtral = InferenceClient("NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO")
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client_llama = InferenceClient("meta-llama/Meta-Llama-3-8B-Instruct")
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func_caller = []
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user_prompt = message
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functions_metadata = [
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{"type": "function", "function": {"name": "web_search", "description": "Search query on
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]
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for msg in history:
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response = client_gemma.chat_completion(
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response = str(response)
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try:
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response = response[int(response.find("{")):int(response.rindex("}"))+1]
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except:
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response = response[int(response.find("{")):(int(response.rfind("}"))+1)]
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response = response.replace("\\n", "")
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response = response.replace("\\'", "'")
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response = response.replace('\\"', '"')
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response = response.replace('\\', '')
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print(f"\n{response}")
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try:
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@@ -84,14 +83,14 @@ def respond(message, history):
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if json_data["name"] == "web_search":
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query = json_data["arguments"]["query"]
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gr.Info("Searching Web")
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web_results =
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gr.Info("Extracting relevant Info")
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messages =
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for msg in history:
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messages += f"\nuser\n{str(msg[0])}"
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messages += f"\nassistant\n{str(msg[1])}"
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messages+=f"\nuser\n{message}\nweb_result\n{
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stream = client_mixtral.text_generation(messages, max_new_tokens=2000, do_sample=True, stream=True, details=True, return_full_text=False)
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output = ""
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for response in stream:
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@@ -99,11 +98,11 @@ def respond(message, history):
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output += response.token.text
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yield output
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else:
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messages =
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for msg in history:
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messages += f"\nuser\n{str(msg[0])}"
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messages += f"\nassistant\n{str(msg[1])}"
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messages+=f"\nuser\n{message}\nassistant\n"
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stream = client_llama.text_generation(messages, max_new_tokens=2000, do_sample=True, stream=True, details=True, return_full_text=False)
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output = ""
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for response in stream:
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@@ -111,11 +110,11 @@ def respond(message, history):
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output += response.token.text
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yield output
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except:
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messages =
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for msg in history:
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messages += f"\nuser\n{str(msg[0])}"
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messages += f"\nassistant\n{str(msg[1])}"
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messages+=f"\nuser\n{message}\nassistant\n"
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stream = client_llama.text_generation(messages, max_new_tokens=2000, do_sample=True, stream=True, details=True, return_full_text=False)
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output = ""
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for response in stream:
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@@ -123,8 +122,9 @@ def respond(message, history):
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output += response.token.text
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yield output
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demo = gr.ChatInterface(
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fn=
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chatbot=gr.Chatbot(),
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description=" ",
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textbox=gr.Textbox(),
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@@ -133,4 +133,5 @@ demo = gr.ChatInterface(
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css=css,
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theme="allenai/gradio-theme",
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)
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demo.launch(share=True)
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from bs4 import BeautifulSoup
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import requests
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# Custom CSS for Gradio app
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css = '''
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.gradio-container{max-width: 1000px !important}
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h1{text-align:center}
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}
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'''
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# Function to extract text from a webpage
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def get_text_from_html(html_content):
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soup = BeautifulSoup(html_content, 'html.parser')
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for tag in soup(["script", "style", "header", "footer"]):
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tag.extract()
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return soup.get_text(strip=True)
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# Function to perform a web search
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def perform_search(query):
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search_term = query
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all_results = []
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max_chars_per_page = 8000
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with requests.Session() as session:
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response = session.get(
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url="https://www.google.com/search",
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headers={"User-Agent": "Mozilla/5.0"},
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params={"q": search_term, "num": 3, "udm": 14},
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timeout=5,
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verify=False,
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)
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response.raise_for_status()
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soup = BeautifulSoup(response.text, "html.parser")
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result_block = soup.find_all("div", attrs={"class": "g"})
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for result in result_block:
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link = result.find("a", href=True)["href"]
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try:
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webpage_response = session.get(link, headers={"User-Agent": "Mozilla/5.0"}, timeout=5, verify=False)
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webpage_response.raise_for_status()
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visible_text = get_text_from_html(webpage_response.text)
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if len(visible_text) > max_chars_per_page:
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visible_text = visible_text[:max_chars_per_page]
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all_results.append({"link": link, "text": visible_text})
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all_results.append({"link": link, "text": None})
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return all_results
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# Initialize inference clients
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client_gemma = InferenceClient("mistralai/Mistral-7B-Instruct-v0.3")
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client_mixtral = InferenceClient("NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO")
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client_llama = InferenceClient("meta-llama/Meta-Llama-3-8B-Instruct")
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# Function to handle responses
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def chat_response(message, history):
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func_calls = []
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user_prompt = message
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functions_metadata = [
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{"type": "function", "function": {"name": "web_search", "description": "Search query on Google", "parameters": {"type": "object", "properties": {"query": {"type": "string", "description": "Web search query"}}, "required": ["query"]}}},
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]
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for msg in history:
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func_calls.append({"role": "user", "content": f"{str(msg[0])}"})
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func_calls.append({"role": "assistant", "content": f"{str(msg[1])}"})
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func_calls.append({"role": "user", "content": f'[SYSTEM] You are a helpful assistant. You have access to the following functions: \n {str(functions_metadata)}\n\nTo use these functions respond with:\n<functioncall> {{ "name": "function_name", "arguments": {{ "arg_1": "value_1", "arg_1": "value_1", ... }} }} </functioncall> [USER] {message}'})
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response = client_gemma.chat_completion(func_calls, max_tokens=200)
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response = str(response)
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try:
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response = response[int(response.find("{")):int(response.rindex("}"))+1]
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except:
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response = response[int(response.find("{")):(int(response.rfind("}"))+1)]
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response = response.replace("\\n", "").replace("\\'", "'").replace('\\"', '"').replace('\\', '')
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print(f"\n{response}")
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try:
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if json_data["name"] == "web_search":
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query = json_data["arguments"]["query"]
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gr.Info("Searching Web")
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web_results = perform_search(query)
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gr.Info("Extracting relevant Info")
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web_summary = ' '.join([f"Link: {res['link']}\nText: {res['text']}\n\n" for res in web_results if res['text']])
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messages = "system\nWeb Dac uses the user agents of Mozilla, AppleWebKit, and Safari browsers for chat responses and human context mimicking."
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for msg in history:
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messages += f"\nuser\n{str(msg[0])}"
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messages += f"\nassistant\n{str(msg[1])}"
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messages += f"\nuser\n{message}\nweb_result\n{web_summary}\nassistant\n"
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stream = client_mixtral.text_generation(messages, max_new_tokens=2000, do_sample=True, stream=True, details=True, return_full_text=False)
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output = ""
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for response in stream:
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output += response.token.text
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yield output
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else:
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messages = "system\nWeb Dac uses the user agents of Mozilla, AppleWebKit, and Safari browsers for chat responses and human context mimicking."
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for msg in history:
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messages += f"\nuser\n{str(msg[0])}"
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messages += f"\nassistant\n{str(msg[1])}"
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messages += f"\nuser\n{message}\nassistant\n"
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stream = client_llama.text_generation(messages, max_new_tokens=2000, do_sample=True, stream=True, details=True, return_full_text=False)
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output = ""
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for response in stream:
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output += response.token.text
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yield output
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except:
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messages = "system\nWeb Dac uses the user agents of Mozilla, AppleWebKit, and Safari browsers for chat responses and human context mimicking."
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for msg in history:
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messages += f"\nuser\n{str(msg[0])}"
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messages += f"\nassistant\n{str(msg[1])}"
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messages += f"\nuser\n{message}\nassistant\n"
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stream = client_llama.text_generation(messages, max_new_tokens=2000, do_sample=True, stream=True, details=True, return_full_text=False)
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output = ""
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for response in stream:
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output += response.token.text
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yield output
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# Create Gradio interface
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demo = gr.ChatInterface(
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fn=chat_response,
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chatbot=gr.Chatbot(),
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description=" ",
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textbox=gr.Textbox(),
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css=css,
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theme="allenai/gradio-theme",
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)
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demo.launch(share=True)
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