Add support for Cohere

app.py

@@ -138,11 +138,11 @@ with st.sidebar:
     api_key_token = st.text_input(
         label=(
             '3: Paste your API key/access token:\n\n'
-            '*Optional* if an HF Mistral LLM is selected from the list but still encouraged.\n\n'
+            '*Mandatory* for Cohere and Gemini LLMs.'
+            ' *Optional* for HF Mistral LLMs but still encouraged.\n\n'
         ),
         type='password',
     )
-    st.caption('(Wrong HF access token will lead to validation error)')
 
 
 def build_ui():
@@ -152,9 +152,9 @@ def build_ui():
 
     st.title(APP_TEXT['app_name'])
     st.subheader(APP_TEXT['caption'])
-    # st.markdown(
-    #     '![Visitors](https://api.visitorbadge.io/api/visitors?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2Fbarunsaha%2Fslide-deck-ai&countColor=%23263759)'  # noqa: E501
-    # )
+    st.markdown(
+        '![Visitors](https://api.visitorbadge.io/api/visitors?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2Fbarunsaha%2Fslide-deck-ai&countColor=%23263759)'  # noqa: E501
+    )
 
     with st.expander('Usage Policies and Limitations'):
         st.text(APP_TEXT['tos'] + '\n\n' + APP_TEXT['tos2'])
@@ -267,7 +267,9 @@ def set_up_chat_ui():
             handle_error(
                 f'An unexpected error occurred while generating the content: {ex}'
                 '\nPlease try again later, possibly with different inputs.'
-                ' Alternatively, try selecting a different LLM from the dropdown list.',
+                ' Alternatively, try selecting a different LLM from the dropdown list.'
+                ' If you are using Cohere or Gemini models, make sure that you have provided'
+                ' a correct API key.',
                 True
             )
             return

global_config.py

@@ -17,10 +17,16 @@ class GlobalConfig:
     A data class holding the configurations.
     """
 
-    PROVIDER_HUGGING_FACE = 'hf'
+    PROVIDER_COHERE = 'co'
     PROVIDER_GOOGLE_GEMINI = 'gg'
-    VALID_PROVIDERS = {PROVIDER_HUGGING_FACE, PROVIDER_GOOGLE_GEMINI}
+    PROVIDER_HUGGING_FACE = 'hf'
+    VALID_PROVIDERS = {PROVIDER_COHERE, PROVIDER_GOOGLE_GEMINI, PROVIDER_HUGGING_FACE}
     VALID_MODELS = {
+        '[co]command-r-08-2024': {
+            'description': 'simpler, slower',
+            'max_new_tokens': 4096,
+            'paid': True,
+        },
         '[gg]gemini-1.5-flash-002': {
             'description': 'faster response',
             'max_new_tokens': 8192,
@@ -39,10 +45,11 @@ class GlobalConfig:
     }
     LLM_PROVIDER_HELP = (
         'LLM provider codes:\n\n'
+        '- **[co]**: Cohere\n'
         '- **[gg]**: Google Gemini API\n'
         '- **[hf]**: Hugging Face Inference Endpoint\n'
     )
-    DEFAULT_MODEL_INDEX = 1
+    DEFAULT_MODEL_INDEX = 2
     LLM_MODEL_TEMPERATURE = 0.2
     LLM_MODEL_MIN_OUTPUT_LENGTH = 100
     LLM_MODEL_MAX_INPUT_LENGTH = 400  # characters

helpers/llm_helper.py

@@ -9,7 +9,6 @@ from typing import Tuple, Union
 import requests
 from requests.adapters import HTTPAdapter
 from urllib3.util import Retry
-from langchain_community.llms.huggingface_endpoint import HuggingFaceEndpoint
 from langchain_core.language_models import BaseLLM
 
 sys.path.append('..')
@@ -22,6 +21,8 @@ HF_API_HEADERS = {'Authorization': f'Bearer {GlobalConfig.HUGGINGFACEHUB_API_TOK
 REQUEST_TIMEOUT = 35
 
 logger = logging.getLogger(__name__)
+logging.getLogger('httpx').setLevel(logging.WARNING)
+logging.getLogger('httpcore').setLevel(logging.WARNING)
 
 retries = Retry(
     total=5,
@@ -93,6 +94,8 @@ def get_langchain_llm(
     """
 
     if provider == GlobalConfig.PROVIDER_HUGGING_FACE:
+        from langchain_community.llms.huggingface_endpoint import HuggingFaceEndpoint
+
         logger.debug('Getting LLM via HF endpoint: %s', model)
         return HuggingFaceEndpoint(
             repo_id=model,
@@ -111,6 +114,7 @@ def get_langchain_llm(
         from google.generativeai.types.safety_types import HarmBlockThreshold, HarmCategory
         from langchain_google_genai import GoogleGenerativeAI
 
+        logger.debug('Getting LLM via Google Gemini: %s', model)
         return GoogleGenerativeAI(
             model=model,
             temperature=GlobalConfig.LLM_MODEL_TEMPERATURE,
@@ -128,11 +132,25 @@ def get_langchain_llm(
             }
         )
 
+    if provider == GlobalConfig.PROVIDER_COHERE:
+        from langchain_cohere.llms import Cohere
+
+        logger.debug('Getting LLM via Cohere: %s', model)
+        return Cohere(
+            temperature=GlobalConfig.LLM_MODEL_TEMPERATURE,
+            max_tokens=max_new_tokens,
+            timeout_seconds=None,
+            max_retries=2,
+            cohere_api_key=api_key,
+            streaming=True,
+        )
+
     return None
 
 
 if __name__ == '__main__':
     inputs = [
+        '[co]Cohere',
         '[hf]mistralai/Mistral-7B-Instruct-v0.2',
         '[gg]gemini-1.5-flash-002'
     ]

helpers/pptx_helper.py

@@ -115,37 +115,42 @@ def generate_powerpoint_presentation(
 
     # Add content in a loop
     for a_slide in parsed_data['slides']:
-        is_processing_done = _handle_icons_ideas(
-            presentation=presentation,
-            slide_json=a_slide,
-            slide_width_inch=slide_width_inch,
-            slide_height_inch=slide_height_inch
-        )
-
-        if not is_processing_done:
-            is_processing_done = _handle_double_col_layout(
+        try:
+            is_processing_done = _handle_icons_ideas(
                 presentation=presentation,
                 slide_json=a_slide,
                 slide_width_inch=slide_width_inch,
                 slide_height_inch=slide_height_inch
             )
 
-        if not is_processing_done:
-            is_processing_done = _handle_step_by_step_process(
-                presentation=presentation,
-                slide_json=a_slide,
-                slide_width_inch=slide_width_inch,
-                slide_height_inch=slide_height_inch
-            )
+            if not is_processing_done:
+                is_processing_done = _handle_double_col_layout(
+                    presentation=presentation,
+                    slide_json=a_slide,
+                    slide_width_inch=slide_width_inch,
+                    slide_height_inch=slide_height_inch
+                )
 
-        if not is_processing_done:
-            _handle_default_display(
-                presentation=presentation,
-                slide_json=a_slide,
-                slide_width_inch=slide_width_inch,
-                slide_height_inch=slide_height_inch
+            if not is_processing_done:
+                is_processing_done = _handle_step_by_step_process(
+                    presentation=presentation,
+                    slide_json=a_slide,
+                    slide_width_inch=slide_width_inch,
+                    slide_height_inch=slide_height_inch
+                )
+
+            if not is_processing_done:
+                _handle_default_display(
+                    presentation=presentation,
+                    slide_json=a_slide,
+                    slide_width_inch=slide_width_inch,
+                    slide_height_inch=slide_height_inch
             )
 
+        except Exception:
+            # In case of any unforeseen error, try to salvage what is available
+            continue
+
     # The thank-you slide
     last_slide_layout = presentation.slide_layouts[0]
     slide = presentation.slides.add_slide(last_slide_layout)

requirements.txt

@@ -11,6 +11,7 @@ langchain~=0.3.7
 langchain-core~=0.3.0
 langchain-community==0.3.0
 langchain-google-genai==2.0.6
+langchain-cohere==0.3.3
 streamlit~=1.38.0
 
 python-pptx