rieon commited on
Commit
c5d6f8a
·
1 Parent(s): 3f72dd0
Files changed (1) hide show
  1. app.py +32 -32
app.py CHANGED
@@ -7,40 +7,40 @@ HF_MODEL_ID = "rieon/DeepCoder-14B-Preview-Suger"
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  # explicitly tell the client you want text-generation
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  client = InferenceClient(model=HF_MODEL_ID)
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- def respond(
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- message: str,
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- history: list[dict], # [{"role":"user"/"assistant","content":…}, …]
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- system_message: str,
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- max_tokens: int,
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- temperature: float,
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- top_p: float,
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- ):
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- # 1️⃣ Build one raw-text prompt from system + chat history + new user turn
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- prompt = system_message.strip() + "\n"
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- for msg in history:
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- role = msg["role"]
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- content = msg["content"]
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- if role == "user":
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- prompt += f"User: {content}\n"
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- elif role == "assistant":
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- prompt += f"Assistant: {content}\n"
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- prompt += f"User: {message}\nAssistant:"
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- # 2️⃣ Stream tokens from the text-generation endpoint
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- generated = ""
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- for chunk in client.text_generation(
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- prompt, # first positional arg
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- max_new_tokens=max_tokens,
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- temperature=temperature,
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- top_p=top_p,
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- stream=True,
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- ):
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- generated += chunk.generated_text
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- yield generated
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  def respond2(
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  message: str,
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- history: list[tuple[str, str]],
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  system_message: str,
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  max_tokens: int,
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  temperature: float,
@@ -48,8 +48,8 @@ def respond2(
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  ):
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  # assemble a single prompt from system message + history
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  prompt = system_message.strip() + "\n"
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- for user, bot in history:
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- prompt += f"User: {user}\nAssistant: {bot}\n"
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  prompt += f"User: {message}\nAssistant:"
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  # stream back tokens
 
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  # explicitly tell the client you want text-generation
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  client = InferenceClient(model=HF_MODEL_ID)
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+ # def respond(
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+ # message: str,
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+ # history: list[dict], # [{"role":"user"/"assistant","content":…}, …]
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+ # system_message: str,
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+ # max_tokens: int,
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+ # temperature: float,
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+ # top_p: float,
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+ # ):
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+ # # 1️⃣ Build one raw-text prompt from system + chat history + new user turn
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+ # prompt = system_message.strip() + "\n"
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+ # for msg in history:
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+ # role = msg["role"]
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+ # content = msg["content"]
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+ # if role == "user":
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+ # prompt += f"User: {content}\n"
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+ # elif role == "assistant":
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+ # prompt += f"Assistant: {content}\n"
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+ # prompt += f"User: {message}\nAssistant:"
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+ # # 2️⃣ Stream tokens from the text-generation endpoint
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+ # generated = ""
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+ # for chunk in client.text_generation(
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+ # prompt, # first positional arg
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+ # max_new_tokens=max_tokens,
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+ # temperature=temperature,
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+ # top_p=top_p,
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+ # stream=True,
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+ # ):
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+ # generated += chunk.generated_text
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+ # yield generated
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  def respond2(
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  message: str,
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+ history: list[dict],
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  system_message: str,
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  max_tokens: int,
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  temperature: float,
 
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  ):
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  # assemble a single prompt from system message + history
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  prompt = system_message.strip() + "\n"
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+ # for user, bot in history:
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+ # prompt += f"User: {user}\nAssistant: {bot}\n"
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  prompt += f"User: {message}\nAssistant:"
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  # stream back tokens