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Merge pull request #85 from barun-saha/ollama
Browse filesFix bug in offline mode and PPTX templates accessing
- README.md +7 -0
- app.py +5 -2
- requirements.txt +2 -4
README.md
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@@ -88,13 +88,20 @@ Offline LLMs are made available via Ollama. Therefore, a pre-requisite here is t
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In addition, the `RUN_IN_OFFLINE_MODE` environment variable needs to be set to `True` to enable the offline mode. This, for example, can be done using a `.env` file or from the terminal. The typical steps to use SlideDeck AI in offline mode (in a `bash` shell) are as follows:
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```bash
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ollama list # View locally available LLMs
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export RUN_IN_OFFLINE_MODE=True # Enable the offline mode to use Ollama
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git clone https://github.com/barun-saha/slide-deck-ai.git
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cd slide-deck-ai
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python -m venv venv # Create a virtual environment
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source venv/bin/activate # On a Linux system
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pip install -r requirements.txt
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streamlit run ./app.py # Run the application
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```
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In addition, the `RUN_IN_OFFLINE_MODE` environment variable needs to be set to `True` to enable the offline mode. This, for example, can be done using a `.env` file or from the terminal. The typical steps to use SlideDeck AI in offline mode (in a `bash` shell) are as follows:
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```bash
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# Install Git Large File Storage (LFS)
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sudo apt install git-lfs
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git lfs install
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ollama list # View locally available LLMs
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export RUN_IN_OFFLINE_MODE=True # Enable the offline mode to use Ollama
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git clone https://github.com/barun-saha/slide-deck-ai.git
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cd slide-deck-ai
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git lfs pull # Pull the PPTX template files
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python -m venv venv # Create a virtual environment
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source venv/bin/activate # On a Linux system
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pip install -r requirements.txt
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streamlit run ./app.py # Run the application
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```
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app.py
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@@ -159,7 +159,7 @@ with st.sidebar:
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if RUN_IN_OFFLINE_MODE:
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llm_provider_to_use = st.text_input(
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label='2: Enter Ollama model name to use:',
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help=(
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'Specify a correct, locally available LLM, found by running `ollama list`, for'
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' example `mistral:v0.2` and `mistral-nemo:latest`. Having an Ollama-compatible'
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@@ -167,8 +167,11 @@ with st.sidebar:
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)
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)
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api_key_token: str = ''
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else:
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# The LLMs
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llm_provider_to_use = st.sidebar.selectbox(
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label='2: Select a suitable LLM to use:\n\n(Gemini and Mistral-Nemo are recommended)',
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options=[f'{k} ({v["description"]})' for k, v in GlobalConfig.VALID_MODELS.items()],
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if RUN_IN_OFFLINE_MODE:
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llm_provider_to_use = st.text_input(
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label='2: Enter Ollama model name to use (e.g., mistral:v0.2):',
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help=(
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'Specify a correct, locally available LLM, found by running `ollama list`, for'
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' example `mistral:v0.2` and `mistral-nemo:latest`. Having an Ollama-compatible'
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)
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)
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api_key_token: str = ''
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azure_endpoint: str = ''
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azure_deployment: str = ''
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api_version: str = ''
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else:
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# The online LLMs
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llm_provider_to_use = st.sidebar.selectbox(
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label='2: Select a suitable LLM to use:\n\n(Gemini and Mistral-Nemo are recommended)',
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options=[f'{k} ({v["description"]})' for k, v in GlobalConfig.VALID_MODELS.items()],
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requirements.txt
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@@ -17,15 +17,13 @@ langchain-ollama==0.2.1
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langchain-openai==0.3.3
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streamlit~=1.38.0
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python-pptx~=0.
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# metaphor-python
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json5~=0.9.14
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requests~=2.32.3
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transformers>=4.48.0
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torch==2.4.0
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urllib3~=2.2.1
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lxml~=4.9.3
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tqdm~=4.66.5
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numpy
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@@ -38,4 +36,4 @@ anyio==4.4.0
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httpx~=0.27.2
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huggingface-hub~=0.24.5
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ollama~=0.4.
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langchain-openai==0.3.3
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streamlit~=1.38.0
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python-pptx~=1.0.2
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json5~=0.9.14
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requests~=2.32.3
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transformers>=4.48.0
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torch==2.4.0
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lxml~=4.9.3
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tqdm~=4.66.5
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numpy
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httpx~=0.27.2
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huggingface-hub~=0.24.5
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ollama~=0.4.7
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