Daniel Marques commited on
Commit
e845546
1 Parent(s): b775dc2

feat: add stream

Browse files
Files changed (3) hide show
  1. main.py +3 -3
  2. run_localGPT.py +3 -2
  3. static/index.html +3 -3
main.py CHANGED
@@ -44,8 +44,8 @@ DB = Chroma(
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  RETRIEVER = DB.as_retriever()
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- LLM = load_model(device_type=DEVICE_TYPE, model_id=MODEL_ID, model_basename=MODEL_BASENAME, stream=False)
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- prompt, memory = get_prompt_template(promptTemplate_type="llama", history=False)
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  template = """you are a helpful, respectful and honest assistant.
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  Your name is Katara llma. You should only use the source documents provided to answer the questions.
@@ -118,7 +118,7 @@ def run_ingest_route():
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  )
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  RETRIEVER = DB.as_retriever()
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- prompt, memory = get_prompt_template(promptTemplate_type="llama", history=False)
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  QA = RetrievalQA.from_chain_type(
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  llm=LLM,
 
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  RETRIEVER = DB.as_retriever()
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+ LLM = load_model(device_type=DEVICE_TYPE, model_id=MODEL_ID, model_basename=MODEL_BASENAME)
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+ prompt, memory = get_prompt_template(promptTemplate_type="llama", history=True)
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  template = """you are a helpful, respectful and honest assistant.
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  Your name is Katara llma. You should only use the source documents provided to answer the questions.
 
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  )
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  RETRIEVER = DB.as_retriever()
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+ prompt, memory = get_prompt_template(promptTemplate_type="llama", history=True)
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  QA = RetrievalQA.from_chain_type(
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  llm=LLM,
run_localGPT.py CHANGED
@@ -38,7 +38,7 @@ from constants import (
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- def load_model(device_type, model_id, model_basename=None, LOGGING=logging, stream=False):
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  """
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  Select a model for text generation using the HuggingFace library.
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  If you are running this for the first time, it will download a model for you.
@@ -56,7 +56,6 @@ def load_model(device_type, model_id, model_basename=None, LOGGING=logging, stre
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  Raises:
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  ValueError: If an unsupported model or device type is provided.
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  """
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- streamer = TextStreamer(tokenizer, skip_prompt=stream)
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  logging.info(f"Loading Model: {model_id}, on: {device_type}")
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  logging.info("This action can take a few minutes!")
@@ -80,6 +79,8 @@ def load_model(device_type, model_id, model_basename=None, LOGGING=logging, stre
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  # Create a pipeline for text generation
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  pipe = pipeline(
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  "text-generation",
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  model=model,
 
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+ def load_model(device_type, model_id, model_basename=None, LOGGING=logging):
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  """
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  Select a model for text generation using the HuggingFace library.
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  If you are running this for the first time, it will download a model for you.
 
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  Raises:
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  ValueError: If an unsupported model or device type is provided.
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  """
 
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  logging.info(f"Loading Model: {model_id}, on: {device_type}")
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  logging.info("This action can take a few minutes!")
 
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  # Create a pipeline for text generation
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+ streamer = TextStreamer(tokenizer, skip_prompt=True)
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+
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  pipe = pipeline(
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  "text-generation",
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  model=model,
static/index.html CHANGED
@@ -6,7 +6,7 @@
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  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
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  <!-- Bootstrap CSS -->
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- <link rel="icon" type="image" href="static\social_icons\favicon.png" />
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  <script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
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  <link
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  href="https://cdn.jsdelivr.net/npm/bootstrap@5.1.3/dist/css/bootstrap.min.css"
@@ -20,7 +20,7 @@
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  crossorigin="anonymous"
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  ></script>
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- <title>localGPT</title>
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  </head>
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  <style>
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  @import url("https://fonts.googleapis.com/css2?family=Play:wght@400;700&display=swap");
@@ -56,7 +56,7 @@
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  }
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  </script>
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  <div class="container">
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- <div class="titlegpt">KATARA LLMA</div>
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  <button
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  type="button"
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  style="
 
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  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
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  <!-- Bootstrap CSS -->
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+ <!-- <link rel="icon" type="image" href="static\social_icons\favicon.png" /> -->
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  <script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
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  <link
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  href="https://cdn.jsdelivr.net/npm/bootstrap@5.1.3/dist/css/bootstrap.min.css"
 
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  crossorigin="anonymous"
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  ></script>
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+ <title>Katara llama</title>
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  </head>
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  <style>
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  @import url("https://fonts.googleapis.com/css2?family=Play:wght@400;700&display=swap");
 
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  }
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  </script>
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  <div class="container">
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+ <div class="titlegpt">Katara llama</div>
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  <button
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  type="button"
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  style="