6Genix commited on
Commit
6efe883
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1 Parent(s): 8d4fe18

Switched to using DeepSeek-V3 for both Engineer and Analyst pipelines for text generation. Updated references to ensure compatibility and performance with the model.

Browse files
Files changed (2) hide show
  1. README.md +41 -4
  2. app.py +5 -7
README.md CHANGED
@@ -1,14 +1,51 @@
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  ---
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  title: MultiAgent XAI Demo
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- emoji: 🐨
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  colorFrom: blue
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- colorTo: blue
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  sdk: streamlit
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  sdk_version: 1.41.1
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  app_file: app.py
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  pinned: false
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  license: mit
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- short_description: Text-based multi-agent conversation demo
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  ---
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  title: MultiAgent XAI Demo
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+ emoji: 🤖
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  colorFrom: blue
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+ colorTo: green
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  sdk: streamlit
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  sdk_version: 1.41.1
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  app_file: app.py
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  pinned: false
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  license: mit
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+ short_description: A demo showcasing multi-agent conversational AI using Microsoft PHI-4 for generating technical and analytical insights.
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  ---
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+ ## MultiAgent XAI Demo
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+
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+ This demo leverages the `microsoft/phi-4` language model for simulating a conversation between two roles: an Engineer and an Analyst. The goal is to collaboratively address user-provided queries and produce actionable insights.
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+
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+ ### Features
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+ - **Engineer Role**: Provides concise, technical solutions.
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+ - **Analyst Role**: Offers data-driven recommendations to complement the Engineer's response.
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+ - **Natural Dialogue**: Facilitates a three-turn conversation between the roles.
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+ - **Actionable Summary**: Generates a final plan summarizing key insights.
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+
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+ ### How It Works
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+ 1. The user enters a query.
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+ 2. The Engineer and Analyst respond alternately, building on each other's inputs.
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+ 3. A final summary is generated, integrating technical and analytical perspectives.
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+
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+ ### Technology Stack
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+ - **Streamlit**: Interactive web interface.
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+ - **Hugging Face Transformers**: Using `pipeline` with the `microsoft/phi-4` model for text generation.
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+
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+ ### Getting Started
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+ 1. Clone this repository:
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+ ```bash
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+ git clone <repository-url>
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+ ```
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+ 2. Install dependencies:
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+ ```bash
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+ pip install -r requirements.txt
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+ ```
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+ 3. Run the application:
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+ ```bash
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+ streamlit run app.py
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+ ```
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+
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+ ### Configuration Reference
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+ Refer to the [Hugging Face Spaces Config Reference](https://huggingface.co/docs/hub/spaces-config-reference) for deployment options.
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+
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+ ### License
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+ This project is licensed under the MIT License. See the LICENSE file for details.
app.py CHANGED
@@ -8,20 +8,20 @@ from transformers import pipeline
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  @st.cache_resource
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  def load_model_engineer():
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- # Engineer: Microsoft PHI-4 via pipeline
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  engineer_pipeline = pipeline(
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  "text-generation",
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- model="microsoft/phi-4",
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  trust_remote_code=True
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  )
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  return engineer_pipeline
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  @st.cache_resource
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  def load_model_analyst():
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- # Analyst: Microsoft PHI-4 via pipeline
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  analyst_pipeline = pipeline(
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  "text-generation",
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- model="microsoft/phi-4",
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  trust_remote_code=True
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  )
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  return analyst_pipeline
@@ -103,6 +103,4 @@ if st.button("Generate Responses"):
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  # Summarize the final plan
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  with st.spinner("Generating the final plan..."):
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- final_plan = summarize_conversation(st.session_state.conversation)
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- st.session_state.conversation.append(("Summary", final_plan))
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- st.markdown(final_plan)
 
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  @st.cache_resource
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  def load_model_engineer():
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+ # Engineer: DeepSeek-V5 via pipeline
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  engineer_pipeline = pipeline(
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  "text-generation",
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+ model="unsloth/DeepSeek-V3",
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  trust_remote_code=True
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  )
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  return engineer_pipeline
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  @st.cache_resource
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  def load_model_analyst():
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+ # Analyst: DeepSeek-V5 via pipeline
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  analyst_pipeline = pipeline(
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  "text-generation",
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+ model="unsloth/DeepSeek-V3",
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  trust_remote_code=True
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  )
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  return analyst_pipeline
 
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  # Summarize the final plan
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  with st.spinner("Generating the final plan..."):
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+ final_plan = summarize_conversation