test

app.py

@@ -0,0 +1,171 @@
+import gradio as gr
+import os
+from math import exp
+from tenacity import retry, wait_random_exponential, stop_after_attempt
+from langchain_core.messages import HumanMessage, SystemMessage
+import tiktoken
+from langchain_openai import ChatOpenAI
+
+class OpenAIChat(ChatOpenAI):
+    """Openai chatbot LLM."""
+    def __init__(
+            self,
+            model_name: str = "gpt-4o",
+            temperature: float = 1,
+            top_p: float = 1,
+            presence_penalty: float = 0,
+            frequency_penalty: float = 0,
+            max_tokens: int = 2000,
+            cache: bool = False,
+            seed: int = 42
+    ):
+        """Initialize azure chat LLM."""
+        super(ChatOpenAI, self).__init__(
+            model_name=model_name,
+            openai_api_key=os.getenv("openai_api"),
+            temperature=temperature,
+            
+            max_tokens=max_tokens,
+            model_kwargs={"presence_penalty": presence_penalty,
+                          "frequency_penalty": frequency_penalty,
+                          "logprobs": True,
+                          "seed": seed,
+                          "top_p": top_p,
+                          },
+            cache=cache
+        )
+
+
+
+model_name = "gpt-4o"
+tokenizer = tiktoken.encoding_for_model("gpt-4o")
+tokens = ["Yes", "No"]
+ids = [tokenizer.encode(token)[0] for token in tokens]
+model = OpenAIChat(model_name=model_name).bind(logit_bias=dict((id, 1) for id in ids))
+
+system_prompt = """
+You are an assistant to decide if a statement is as the similar format of the example statements.
+In general, a statement has complete information, its positive, 
+If the statement is ambigious, often seems like a follow up, or need more backgroud or context to understand, its negative.
+If a statement is positive, reply Yes, otherwise reply No. Do not reply the reasoning, just Yes or No.
+
+Here are some positive and negative examples:
+
+[S]: Top ten trucks with best fuel mileage.
+[A]: Yes
+
+[S]: Which battery electric vehicle travelled the most distance this year?
+[A]: Yes
+
+[S]: Show me a list of all customer visits from yesterday.
+[A]: Yes
+
+[S]: What is the average fuel usage per 100km?
+[A]: Yes
+
+[S]: Best month with the lowest idle.
+[A]: Yes
+
+[S]: Best month with the lowest idle.
+[A]: Yes
+
+[S]: What was the idle each month this year?
+[A]: Yes
+
+
+[S]: How about the TwinTaxi?
+[A]: No
+This one is No since it doesn't specify what thing about the TwinTaxi
+
+[S]: Group services.
+[A]: No
+This one is No since it doesn't specify thing about Group services.
+
+[S]: Last week.
+[A]: No
+This one is No since it doesn't specify last week for what?
+
+[S]: Yes, it is.
+[A]: No
+This one is No since it doesn't specify what thing is confirmed.
+
+[S]: And the mileage?
+[A]: No
+This one is No since it doesn't specify mileage for what.
+
+[S]: Details, please.
+[A]: No
+This one is No since it doesn't specify details for what.
+"""
+
+prompt = """
+Now Answer this statament:
+[S]: {statement}
+[A]: 
+"""
+
+
+@retry(wait=wait_random_exponential(min=1, max=40), stop=stop_after_attempt(3))
+def statement_valid(statement):
+    user_prompt = prompt.format(statement=statement)
+    messages = [
+    SystemMessage(
+        content=system_prompt
+    ),
+    HumanMessage(
+        content=user_prompt
+    ),
+    ]
+    response = model.invoke(messages)
+    return (
+        statement,
+        response.content.strip(),
+        response.response_metadata['logprobs']['content'][0]['logprob']
+    )
+
+
+def make_pred(statement: str) -> str:
+    _, prediction, logprob = statement_valid(statement)
+    probability = exp(logprob)
+    yes_probability = probability * -1 + 1 if prediction == "No" else probability
+    if yes_probability > 0.5:
+        return "No need to rephrase, send in the original question."
+    return "Need to be rephrased with chat hist"
+
+
+def get_question_examples():
+    examples=[
+        "And the mileage?", 
+        "I mean last week.", 
+        "How about the B123?",
+        "No need rephrases examples: ", 
+        "Top ten trucks with best fuel mileage.", 
+        "What trucks in motion have no driver assigned?", 
+        "What group is vehicle Blueberry in?"
+    ]
+    return examples
+
+
+with gr.Blocks() as demo:
+    with gr.Row(equal_height=False):
+        input_statement = gr.Textbox(placeholder="type your statement", label="Prompt")
+        reponse = gr.Textbox(placeholder=None, label="AI Response", lines=5)
+        gr.Examples(
+                    examples=get_question_examples(),
+                    inputs=[input_statement],
+                    fn=None,
+                    outputs=None,
+                    cache_examples=False,
+                    label="Question Examples"
+        ) 
+        
+    btn = gr.Button("run", variant="primary")
+
+    btn.click(
+        fn=make_pred, 
+        inputs=[
+            input_statement,
+        ],
+        outputs=[reponse]
+    )
+demo.launch(share=False)

requirements.txt

@@ -0,0 +1,4 @@
+langchain==0.1.11
+langchain-openai
+langchain-community
+openai==1.13.3