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Update app.py
Browse files
app.py
CHANGED
@@ -29,7 +29,7 @@ def search(query):
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with requests.Session() as session:
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resp = 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": term, "num": 3, "udm": 14},
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timeout=5,
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verify=None,
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@@ -41,7 +41,7 @@ def search(query):
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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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webpage = session.get(link, headers={"User-Agent": "Mozilla/5.0"}, timeout=5, verify=False)
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webpage.raise_for_status()
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visible_text = extract_text_from_webpage(webpage.text)
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if len(visible_text) > max_chars_per_page:
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@@ -52,7 +52,7 @@ def search(query):
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return all_results
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# Initialize inference clients for different models
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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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@@ -87,7 +87,7 @@ def respond(message, history):
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messages.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} {vqa}'})
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# Call the LLM for response generation
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response =
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response = str(response)
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try:
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response = response[int(response.find("{")):int(response.index("</"))]
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with requests.Session() as session:
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resp = session.get(
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url="https://www.google.com/search",
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headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/111.0"},
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params={"q": term, "num": 3, "udm": 14},
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timeout=5,
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verify=None,
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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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webpage = session.get(link, headers={"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0) Gecko/20100101 Firefox/111.0"}, timeout=5, verify=False)
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webpage.raise_for_status()
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visible_text = extract_text_from_webpage(webpage.text)
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if len(visible_text) > max_chars_per_page:
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return all_results
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# Initialize inference clients for different models
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client_gemma = InferenceClient("google/gemma-1.1-7b-it")
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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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messages.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} {vqa}'})
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# Call the LLM for response generation
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response = client_gemma.chat_completion(messages, max_tokens=150)
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response = str(response)
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try:
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response = response[int(response.find("{")):int(response.index("</"))]
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