Update app.py

app.py

@@ -254,11 +254,11 @@ async def generate_plan(history, file_cache):
         
     print("Basic connection test passed")
 
-    try:
-        hf_query_gen_tool_details = await get_hf_tools(hf_token=HF_TOKEN)
-    except Exception as e:
-        hf_query_gen_tool_details = """meta=None nextCursor=None tools=[Tool(name='hf_whoami', description="Hugging Face tools are being used by authenticated user 'bpHigh'", inputSchema={'type': 'object', 'properties': {}, 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='Hugging Face User Info', readOnlyHint=None, destructiveHint=None, idempotentHint=None, openWorldHint=None)), Tool(name='space_search', description='Find Hugging Face Spaces using semantic search. Include links to the Space when presenting the results.', inputSchema={'type': 'object', 'properties': {'query': {'type': 'string', 'minLength': 1, 'maxLength': 50, 'description': 'Semantic Search Query'}, 'limit': {'type': 'number', 'default': 10, 'description': 'Number of results to return'}, 'mcp': {'type': 'boolean', 'default': False, 'description': 'Only return MCP Server enabled Spaces'}}, 'required': ['query'], 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='Hugging Face Space Search', readOnlyHint=True, destructiveHint=False, idempotentHint=None, openWorldHint=True)), Tool(name='model_search', description='Find Machine Learning models hosted on Hugging Face. Returns comprehensive information about matching models including downloads, likes, tags, and direct links. Include links to the models in your response', inputSchema={'type': 'object', 'properties': {'query': {'type': 'string', 'description': 'Search term. Leave blank and specify "sort" and "limit" to get e.g. "Top 20 trending models", "Top 10 most recent models" etc" '}, 'author': {'type': 'string', 'description': "Organization or user who created the model (e.g., 'google', 'meta-llama', 'microsoft')"}, 'task': {'type': 'string', 'description': "Model task type (e.g., 'text-generation', 'image-classification', 'translation')"}, 'library': {'type': 'string', 'description': "Framework the model uses (e.g., 'transformers', 'diffusers', 'timm')"}, 'sort': {'type': 'string', 'enum': ['trendingScore', 'downloads', 'likes', 'createdAt', 'lastModified'], 'description': 'Sort order: trendingScore, downloads , likes, createdAt, lastModified'}, 'limit': {'type': 'number', 'minimum': 1, 'maximum': 100, 'default': 20, 'description': 'Maximum number of results to return'}}, 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='Model Search', readOnlyHint=True, destructiveHint=False, idempotentHint=None, openWorldHint=True)), Tool(name='model_details', description='Get detailed information about a specific model from the Hugging Face Hub.', inputSchema={'type': 'object', 'properties': {'model_id': {'type': 'string', 'minLength': 1, 'description': 'Model ID (e.g., microsoft/DialoGPT-large)'}}, 'required': ['model_id'], 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='Model Details', readOnlyHint=True, destructiveHint=False, idempotentHint=None, openWorldHint=False)), Tool(name='paper_search', description="Find Machine Learning research papers on the Hugging Face hub. Include 'Link to paper' When presenting the results. Consider whether tabulating results matches user intent.", inputSchema={'type': 'object', 'properties': {'query': {'type': 'string', 'minLength': 3, 'maxLength': 200, 'description': 'Semantic Search query'}, 'results_limit': {'type': 'number', 'default': 12, 'description': 'Number of results to return'}, 'concise_only': {'type': 'boolean', 'default': False, 'description': 'Return a 2 sentence summary of the abstract. Use for broad search terms which may return a lot of results. Check with User if unsure.'}}, 'required': ['query'], 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='Paper Search', readOnlyHint=True, destructiveHint=False, idempotentHint=None, openWorldHint=True)), Tool(name='dataset_search', description='Find Datasets hosted on the Hugging Face hub. Returns comprehensive information about matching datasets including downloads, likes, tags, and direct links. Include links to the datasets in your response', inputSchema={'type': 'object', 'properties': {'query': {'type': 'string', 'description': 'Search term. Leave blank and specify "sort" and "limit" to get e.g. "Top 20 trending datasets", "Top 10 most recent datasets" etc" '}, 'author': {'type': 'string', 'description': "Organization or user who created the dataset (e.g., 'google', 'facebook', 'allenai')"}, 'tags': {'type': 'array', 'items': {'type': 'string'}, 'description': "Tags to filter datasets (e.g., ['language:en', 'size_categories:1M<n<10M', 'task_categories:text-classification'])"}, 'sort': {'type': 'string', 'enum': ['trendingScore', 'downloads', 'likes', 'createdAt', 'lastModified'], 'description': 'Sort order: trendingScore, downloads, likes, createdAt, lastModified'}, 'limit': {'type': 'number', 'minimum': 1, 'maximum': 100, 'default': 20, 'description': 'Maximum number of results to return'}}, 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='Dataset Search', readOnlyHint=True, destructiveHint=False, idempotentHint=None, openWorldHint=True)), Tool(name='dataset_details', description='Get detailed information about a specific dataset on Hugging Face Hub.', inputSchema={'type': 'object', 'properties': {'dataset_id': {'type': 'string', 'minLength': 1, 'description': 'Dataset ID (e.g., squad, glue, imdb)'}}, 'required': ['dataset_id'], 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='Dataset Details', readOnlyHint=True, destructiveHint=False, idempotentHint=None, openWorldHint=False)), Tool(name='gr1_evalstate_flux1_schnell', description='Generate an image using the Flux 1 Schnell Image Generator. (from evalstate/flux1_schnell)', inputSchema={'type': 'object', 'properties': {'prompt': {'type': 'string'}, 'seed': {'type': 'number', 'description': 'numeric value between 0 and 2147483647'}, 'randomize_seed': {'type': 'boolean', 'default': True}, 'width': {'type': 'number', 'description': 'numeric value between 256 and 2048', 'default': 1024}, 'height': {'type': 'number', 'description': 'numeric value between 256 and 2048', 'default': 1024}, 'num_inference_steps': {'type': 'number', 'description': 'numeric value between 1 and 50', 'default': 4}}, 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='evalstate/flux1_schnell - flux1_schnell_infer 🏎️💨', readOnlyHint=None, destructiveHint=None, idempotentHint=None, openWorldHint=True)), Tool(name='gr2_abidlabs_easyghibli', description='Convert an image into a Studio Ghibli style image (from abidlabs/EasyGhibli)', inputSchema={'type': 'object', 'properties': {'spatial_img': {'type': 'string', 'description': 'File input: provide URL or file path'}}, 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='abidlabs/EasyGhibli - abidlabs_EasyGhiblisingle_condition_generate_image 🦀', readOnlyHint=None, destructiveHint=None, idempotentHint=None, openWorldHint=True)), Tool(name='gr3_linoyts_framepack_f1', description='FramePack_F1_end_process tool from linoyts/FramePack-F1', inputSchema={'type': 'object', 'properties': {}, 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='linoyts/FramePack-F1 - FramePack_F1_end_process 📹⚡️', readOnlyHint=None, destructiveHint=None, idempotentHint=None, openWorldHint=True))]"""
-        print(str(e))
+    # try:
+    hf_query_gen_tool_details = await get_hf_tools(hf_token=HF_TOKEN)
+    # except Exception as e:
+    #     hf_query_gen_tool_details = """meta=None nextCursor=None tools=[Tool(name='hf_whoami', description="Hugging Face tools are being used by authenticated user 'bpHigh'", inputSchema={'type': 'object', 'properties': {}, 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='Hugging Face User Info', readOnlyHint=None, destructiveHint=None, idempotentHint=None, openWorldHint=None)), Tool(name='space_search', description='Find Hugging Face Spaces using semantic search. Include links to the Space when presenting the results.', inputSchema={'type': 'object', 'properties': {'query': {'type': 'string', 'minLength': 1, 'maxLength': 50, 'description': 'Semantic Search Query'}, 'limit': {'type': 'number', 'default': 10, 'description': 'Number of results to return'}, 'mcp': {'type': 'boolean', 'default': False, 'description': 'Only return MCP Server enabled Spaces'}}, 'required': ['query'], 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='Hugging Face Space Search', readOnlyHint=True, destructiveHint=False, idempotentHint=None, openWorldHint=True)), Tool(name='model_search', description='Find Machine Learning models hosted on Hugging Face. Returns comprehensive information about matching models including downloads, likes, tags, and direct links. Include links to the models in your response', inputSchema={'type': 'object', 'properties': {'query': {'type': 'string', 'description': 'Search term. Leave blank and specify "sort" and "limit" to get e.g. "Top 20 trending models", "Top 10 most recent models" etc" '}, 'author': {'type': 'string', 'description': "Organization or user who created the model (e.g., 'google', 'meta-llama', 'microsoft')"}, 'task': {'type': 'string', 'description': "Model task type (e.g., 'text-generation', 'image-classification', 'translation')"}, 'library': {'type': 'string', 'description': "Framework the model uses (e.g., 'transformers', 'diffusers', 'timm')"}, 'sort': {'type': 'string', 'enum': ['trendingScore', 'downloads', 'likes', 'createdAt', 'lastModified'], 'description': 'Sort order: trendingScore, downloads , likes, createdAt, lastModified'}, 'limit': {'type': 'number', 'minimum': 1, 'maximum': 100, 'default': 20, 'description': 'Maximum number of results to return'}}, 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='Model Search', readOnlyHint=True, destructiveHint=False, idempotentHint=None, openWorldHint=True)), Tool(name='model_details', description='Get detailed information about a specific model from the Hugging Face Hub.', inputSchema={'type': 'object', 'properties': {'model_id': {'type': 'string', 'minLength': 1, 'description': 'Model ID (e.g., microsoft/DialoGPT-large)'}}, 'required': ['model_id'], 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='Model Details', readOnlyHint=True, destructiveHint=False, idempotentHint=None, openWorldHint=False)), Tool(name='paper_search', description="Find Machine Learning research papers on the Hugging Face hub. Include 'Link to paper' When presenting the results. Consider whether tabulating results matches user intent.", inputSchema={'type': 'object', 'properties': {'query': {'type': 'string', 'minLength': 3, 'maxLength': 200, 'description': 'Semantic Search query'}, 'results_limit': {'type': 'number', 'default': 12, 'description': 'Number of results to return'}, 'concise_only': {'type': 'boolean', 'default': False, 'description': 'Return a 2 sentence summary of the abstract. Use for broad search terms which may return a lot of results. Check with User if unsure.'}}, 'required': ['query'], 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='Paper Search', readOnlyHint=True, destructiveHint=False, idempotentHint=None, openWorldHint=True)), Tool(name='dataset_search', description='Find Datasets hosted on the Hugging Face hub. Returns comprehensive information about matching datasets including downloads, likes, tags, and direct links. Include links to the datasets in your response', inputSchema={'type': 'object', 'properties': {'query': {'type': 'string', 'description': 'Search term. Leave blank and specify "sort" and "limit" to get e.g. "Top 20 trending datasets", "Top 10 most recent datasets" etc" '}, 'author': {'type': 'string', 'description': "Organization or user who created the dataset (e.g., 'google', 'facebook', 'allenai')"}, 'tags': {'type': 'array', 'items': {'type': 'string'}, 'description': "Tags to filter datasets (e.g., ['language:en', 'size_categories:1M<n<10M', 'task_categories:text-classification'])"}, 'sort': {'type': 'string', 'enum': ['trendingScore', 'downloads', 'likes', 'createdAt', 'lastModified'], 'description': 'Sort order: trendingScore, downloads, likes, createdAt, lastModified'}, 'limit': {'type': 'number', 'minimum': 1, 'maximum': 100, 'default': 20, 'description': 'Maximum number of results to return'}}, 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='Dataset Search', readOnlyHint=True, destructiveHint=False, idempotentHint=None, openWorldHint=True)), Tool(name='dataset_details', description='Get detailed information about a specific dataset on Hugging Face Hub.', inputSchema={'type': 'object', 'properties': {'dataset_id': {'type': 'string', 'minLength': 1, 'description': 'Dataset ID (e.g., squad, glue, imdb)'}}, 'required': ['dataset_id'], 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='Dataset Details', readOnlyHint=True, destructiveHint=False, idempotentHint=None, openWorldHint=False)), Tool(name='gr1_evalstate_flux1_schnell', description='Generate an image using the Flux 1 Schnell Image Generator. (from evalstate/flux1_schnell)', inputSchema={'type': 'object', 'properties': {'prompt': {'type': 'string'}, 'seed': {'type': 'number', 'description': 'numeric value between 0 and 2147483647'}, 'randomize_seed': {'type': 'boolean', 'default': True}, 'width': {'type': 'number', 'description': 'numeric value between 256 and 2048', 'default': 1024}, 'height': {'type': 'number', 'description': 'numeric value between 256 and 2048', 'default': 1024}, 'num_inference_steps': {'type': 'number', 'description': 'numeric value between 1 and 50', 'default': 4}}, 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='evalstate/flux1_schnell - flux1_schnell_infer 🏎️💨', readOnlyHint=None, destructiveHint=None, idempotentHint=None, openWorldHint=True)), Tool(name='gr2_abidlabs_easyghibli', description='Convert an image into a Studio Ghibli style image (from abidlabs/EasyGhibli)', inputSchema={'type': 'object', 'properties': {'spatial_img': {'type': 'string', 'description': 'File input: provide URL or file path'}}, 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='abidlabs/EasyGhibli - abidlabs_EasyGhiblisingle_condition_generate_image 🦀', readOnlyHint=None, destructiveHint=None, idempotentHint=None, openWorldHint=True)), Tool(name='gr3_linoyts_framepack_f1', description='FramePack_F1_end_process tool from linoyts/FramePack-F1', inputSchema={'type': 'object', 'properties': {}, 'additionalProperties': False, '$schema': 'http://json-schema.org/draft-07/schema#'}, annotations=ToolAnnotations(title='linoyts/FramePack-F1 - FramePack_F1_end_process 📹⚡️', readOnlyHint=None, destructiveHint=None, idempotentHint=None, openWorldHint=True))]"""
+    #     print(str(e))
     # Format the prompt
     formatted_prompt = hf_query_gen_prompt.format(
         Tool_Details=hf_query_gen_tool_details