hack/tools/scripts/llm-key-hunter/results/_cache/content/brevia-ai_brevia-cookiecutter.json

{"repo": "brevia-ai/brevia-cookiecutter", "files": {"{{cookiecutter.project_slug}}/.env": {"2ea3094fd6242f2ac450e8ae3cc6c5ab294b5bc7": {"t": 1785745108.5069945, "n": 3506, "h": "74b58e15e74eb8c2", "c": "### Secrets that must be available as environment variables\n# You can define here secrets used by LLM API services (api keys or access tokens for instance)\n# and by other third party services that need specific env variables.\n# If you don't set these variables, the services that depend on them may not work properly.\n# By using BREVIA_ENV_SECRETS you make sure that these secrets will be available as environment variables.\n# BREVIA_ENV_SECRETS='{\"OPENAI_API_KEY\": \"#########\", \"COHERE_API_KEY\": \"#########\", \"ANTHROPIC_API_KEY\": \"#########\", \"DEEPSEEK_API_KEY\": \"#########\"}'\n\n## OpenAI, Cohere, and other API secrets\n# If these vars are not available as environment variables you may want to add them to BREVIA_ENV_SECRETS (see above)\n# OPENAI_API_KEY=#########\n# COHERE_API_KEY=#########\n# ANTHROPIC_API_KEY=#########\n# DEEPSEEK_API_KEY=#########\n\n## Tracing - Langsmith: if you have an account you need the env vars listed below, edit API_KEY and PROJECT vars\n# If these vars are not available as environment variables you may want to add them to BREVIA_ENV_SECRETS (see above)\n# LANGCHAIN_TRACING_V2=true\n# LANGCHAIN_ENDPOINT=\"https://api.smith.langchain.com\"\n# LANGCHAIN_API_KEY=\"########\"\n# LANGCHAIN_PROJECT=\"My Project\"\n\n### QA vars\n# Completion LLM configuration\n# QA_COMPLETION_LLM='{\"model_provider\": \"openai\", \"model\": \"gpt-4o-mini\", \"temperature\": 0, \"max_tokens\": 200, \"verbose\": true}'\n\n# Followup LLM configuration\n# QA_FOLLOWUP_LLM='{\"model_provider\": \"openai\", \"model\": \"gpt-4o-mini\", \"temperature\": 0, \"max_tokens\": 200, \"verbose\": true}'\n\n# Followup similarity threshold\n# QA_FOLLOWUP_SIM_THRESHOLD=0.735\n\n# Chat history - uncomment to disable session conversation, avoiding chat history loading\n# QA_NO_CHAT_HISTORY=True\n\n# Uncomment to use a custom QA retriever with custom arguments\n# QA_RETRIEVER='{\"retriever\": \"my_project.CustomRetriever\", \"some_var\": \"some_value\"}'\n\n### Security\n# Access tokens secret - if missing no access token validity is checked\n# Generate it with: openssl rand -hex 32\n# TOKENS_SECRET=##########################\n# Comma separated list of valid users - use double quotes!\n# TOKENS_USERS=\"brevia,gustavo\"\n\n## Status\n# Special token used by `GET /status` only\n# STATUS_TOKEN=#############\n\n### Search\n# default number of documents to return in a vector search\n# SEARCH_DOCS_NUM=4\n\n### Embedding\n# Embeddings engine configuration\n# EMBEDDINGS='{\"_type\": \"openai-embeddings\"}'\n\n### Index creation\n# TEXT_CHUNK_SIZE=2000\n# TEXT_CHUNK_OVERLAP=100\n# Uncomment to use a custom splitter with custom arguments\n# TEXT_SPLITTER='{\"splitter\": \"my_project.CustomSplitter\", \"some_var\": \"some_value\"}'\n\n### Summarize\n# Summarization LLM\n# SUMMARIZE_LLM='{\"model_provider\": \"openai\", \"model\": \"gpt-4o-mini\", \"temperature\": 0, \"max_tokens\": 2000}'\n# SUMM_TOKEN_SPLITTER=4000\n# SUMM_TOKEN_OVERLAP=500\n# SUMM_DEFAULT_CHAIN=stuff\n\n### General\n# VERBOSE_MODE=True\n\n### OPENAPI\n# Uncomment to block openapi urls - /docs, /redoc\n# BLOCK_OPENAPI_URLS=True\n\n### Database connection\nPGVECTOR_DRIVER=psycopg2\nPGVECTOR_HOST={{cookiecutter.postgres_host}}\nPGVECTOR_PORT={{cookiecutter.postgres_port}}\nPGVECTOR_DATABASE={{cookiecutter.postgres_database}}\nPGVECTOR_USER={{cookiecutter.postgres_user}}\nPGVECTOR_PASSWORD={{cookiecutter.postgres_password}}\nPGVECTOR_POOL_SIZE=10\n\n### Docker compose\n## Postgres pgvector\n# PGVECTOR_VOLUME_NAME=pgdata\n## PG ADMIN\n# PGADMIN_DEFAULT_EMAIL=admin@admin.com\n# PGADMIN_DEFAULT_PASSWORD=admin\n# PGADMIN_PORT=4000\n# PGADMIN_VOLUME_NAME=pgadmindata\n"}, "72ff3e108172daef4b029767436bb3b308b48328": {"t": 1785747829.3569946, "n": 3506, "h": "74b58e15e74eb8c2", "c": "### Secrets that must be available as environment variables\n# You can define here secrets used by LLM API services (api keys or access tokens for instance)\n# and by other third party services that need specific env variables.\n# If you don't set these variables, the services that depend on them may not work properly.\n# By using BREVIA_ENV_SECRETS you make sure that these secrets will be available as environment variables.\n# BREVIA_ENV_SECRETS='{\"OPENAI_API_KEY\": \"#########\", \"COHERE_API_KEY\": \"#########\", \"ANTHROPIC_API_KEY\": \"#########\", \"DEEPSEEK_API_KEY\": \"#########\"}'\n\n## OpenAI, Cohere, and other API secrets\n# If these vars are not available as environment variables you may want to add them to BREVIA_ENV_SECRETS (see above)\n# OPENAI_API_KEY=#########\n# COHERE_API_KEY=#########\n# ANTHROPIC_API_KEY=#########\n# DEEPSEEK_API_KEY=#########\n\n## Tracing - Langsmith: if you have an account you need the env vars listed below, edit API_KEY and PROJECT vars\n# If these vars are not available as environment variables you may want to add them to BREVIA_ENV_SECRETS (see above)\n# LANGCHAIN_TRACING_V2=true\n# LANGCHAIN_ENDPOINT=\"https://api.smith.langchain.com\"\n# LANGCHAIN_API_KEY=\"########\"\n# LANGCHAIN_PROJECT=\"My Project\"\n\n### QA vars\n# Completion LLM configuration\n# QA_COMPLETION_LLM='{\"model_provider\": \"openai\", \"model\": \"gpt-4o-mini\", \"temperature\": 0, \"max_tokens\": 200, \"verbose\": true}'\n\n# Followup LLM configuration\n# QA_FOLLOWUP_LLM='{\"model_provider\": \"openai\", \"model\": \"gpt-4o-mini\", \"temperature\": 0, \"max_tokens\": 200, \"verbose\": true}'\n\n# Followup similarity threshold\n# QA_FOLLOWUP_SIM_THRESHOLD=0.735\n\n# Chat history - uncomment to disable session conversation, avoiding chat history loading\n# QA_NO_CHAT_HISTORY=True\n\n# Uncomment to use a custom QA retriever with custom arguments\n# QA_RETRIEVER='{\"retriever\": \"my_project.CustomRetriever\", \"some_var\": \"some_value\"}'\n\n### Security\n# Access tokens secret - if missing no access token validity is checked\n# Generate it with: openssl rand -hex 32\n# TOKENS_SECRET=##########################\n# Comma separated list of valid users - use double quotes!\n# TOKENS_USERS=\"brevia,gustavo\"\n\n## Status\n# Special token used by `GET /status` only\n# STATUS_TOKEN=#############\n\n### Search\n# default number of documents to return in a vector search\n# SEARCH_DOCS_NUM=4\n\n### Embedding\n# Embeddings engine configuration\n# EMBEDDINGS='{\"_type\": \"openai-embeddings\"}'\n\n### Index creation\n# TEXT_CHUNK_SIZE=2000\n# TEXT_CHUNK_OVERLAP=100\n# Uncomment to use a custom splitter with custom arguments\n# TEXT_SPLITTER='{\"splitter\": \"my_project.CustomSplitter\", \"some_var\": \"some_value\"}'\n\n### Summarize\n# Summarization LLM\n# SUMMARIZE_LLM='{\"model_provider\": \"openai\", \"model\": \"gpt-4o-mini\", \"temperature\": 0, \"max_tokens\": 2000}'\n# SUMM_TOKEN_SPLITTER=4000\n# SUMM_TOKEN_OVERLAP=500\n# SUMM_DEFAULT_CHAIN=stuff\n\n### General\n# VERBOSE_MODE=True\n\n### OPENAPI\n# Uncomment to block openapi urls - /docs, /redoc\n# BLOCK_OPENAPI_URLS=True\n\n### Database connection\nPGVECTOR_DRIVER=psycopg2\nPGVECTOR_HOST={{cookiecutter.postgres_host}}\nPGVECTOR_PORT={{cookiecutter.postgres_port}}\nPGVECTOR_DATABASE={{cookiecutter.postgres_database}}\nPGVECTOR_USER={{cookiecutter.postgres_user}}\nPGVECTOR_PASSWORD={{cookiecutter.postgres_password}}\nPGVECTOR_POOL_SIZE=10\n\n### Docker compose\n## Postgres pgvector\n# PGVECTOR_VOLUME_NAME=pgdata\n## PG ADMIN\n# PGADMIN_DEFAULT_EMAIL=admin@admin.com\n# PGADMIN_DEFAULT_PASSWORD=admin\n# PGADMIN_PORT=4000\n# PGADMIN_VOLUME_NAME=pgadmindata\n"}, "078e00cee78827c7adeca772b95d482eaea87bb5": {"t": 1785747830.614052, "n": 3425, "h": "e197336098d12af4", "c": "### Secrets that must be available as environment variables\n# You can define here secrets used by LLM API services (api keys or access tokens for instance)\n# and by other third party services that need specific env variables.\n# If you don't set these variables, the services that depend on them may not work properly.\n# By using BREVIA_ENV_SECRETS you make sure that these secrets will be available as environment variables.\nBREVIA_ENV_SECRETS='{\"OPENAI_API_KEY\": \"{{cookiecutter.openai_api_key}}\", \"COHERE_API_KEY\": \"{{cookiecutter.cohere_api_key}}\"}'\n\n## OpenAI, Cohere, and other API secrets\n# If these vars are not available as environment variables you may want to add them to BREVIA_ENV_SECRETS (see above)\n# OPENAI_API_KEY=#########\n# COHERE_API_KEY=#########\n\n## Tracing - Langsmith: if you have an account you need the env vars listed below, edit API_KEY and PROJECT vars\n# If these vars are not available as environment variables you may want to add them to BREVIA_ENV_SECRETS (see above)\n# LANGCHAIN_TRACING_V2=true\n# LANGCHAIN_ENDPOINT=\"https://api.smith.langchain.com\"\n# LANGCHAIN_API_KEY=\"########\"\n# LANGCHAIN_PROJECT=\"My Project\"\n\n### QA vars\n# Completion LLM configuration\n# QA_COMPLETION_LLM='{\"_type\": \"openai-chat\", \"model_name\": \"gpt-4o-mini\", \"temperature\": 0, \"max_tokens\": 200, \"verbose\": true}'\n\n# Followup LLM configuration\n# QA_FOLLOWUP_LLM='{\"_type\": \"openai-chat\", \"model_name\": \"gpt-4o-mini\", \"temperature\": 0, \"max_tokens\": 200, \"verbose\": true}'\n\n# Followup similarity threshold\n# QA_FOLLOWUP_SIM_THRESHOLD=0.735\n\n# Chat history - uncomment to disable session conversation, avoiding chat history loading\n# QA_NO_CHAT_HISTORY=True\n\n# Uncomment to use a custom QA retriever with custom arguments\n# QA_RETRIEVER='{\"retriever\": \"my_project.CustomRetriever\", \"some_var\": \"some_value\"}'\n\n### Security\n# Access tokens secret - if missing no access token validity is checked\n# Generate it with: openssl rand -hex 32\n# TOKENS_SECRET=##########################\n# Comma separated list of valid users - use double quotes!\n# TOKENS_USERS=\"brevia,gustavo\"\n\n## Status\n# Special token used by `GET /status` only\n# STATUS_TOKEN=#############\n\n### Search\n# default number of documents to return in a vector search\n# SEARCH_DOCS_NUM=4\n\n### Embedding\n# Embeddings engine configuration\n# EMBEDDINGS='{\"_type\": \"openai-embeddings\"}'\n\n### Index creation\n# TEXT_CHUNK_SIZE=2000\n# TEXT_CHUNK_OVERLAP=100\n# Uncomment to use a custom splitter with custom arguments\n# TEXT_SPLITTER='{\"splitter\": \"my_project.CustomSplitter\", \"some_var\": \"some_value\"}'\n\n### Summarize\n# Summarization LLM\n# SUMMARIZE_LLM='{\"_type\": \"openai-chat\", \"model_name\": \"gpt-4o-mini\", \"temperature\": 0, \"max_tokens\": 2000}'\n# SUMM_TOKEN_SPLITTER=4000\n# SUMM_TOKEN_OVERLAP=500\n# SUMM_DEFAULT_CHAIN=stuff\n\n### General\n# VERBOSE_MODE=True\n\n### OPENAPI\n# Uncomment to block openapi urls - /docs, /redoc\n# BLOCK_OPENAPI_URLS=True\n\n### Database connection\nPGVECTOR_DRIVER=psycopg2\nPGVECTOR_HOST={{cookiecutter.postgres_host}}\nPGVECTOR_PORT={{cookiecutter.postgres_port}}\nPGVECTOR_DATABASE={{cookiecutter.postgres_database}}\nPGVECTOR_USER={{cookiecutter.postgres_user}}\nPGVECTOR_PASSWORD={{cookiecutter.postgres_password}}\nPGVECTOR_POOL_SIZE=10\n\n### Docker compose\n## Postgres pgvector\n# PGVECTOR_VOLUME_NAME=pgdata\n## PG ADMIN\n# PGADMIN_DEFAULT_EMAIL=admin@admin.com\n# PGADMIN_DEFAULT_PASSWORD=admin\n# PGADMIN_PORT=4000\n# PGADMIN_VOLUME_NAME=pgadmindata\n"}, "6ea2d0ba6072e37b460467fd604af417fb81f1a1": {"t": 1785747831.7242105, "n": 3372, "h": "1bfc3fa666b450ce", "c": "### Secrets that must be available as environment variables\n# You can define here secrets used by LLM API services (api keys or access tokens for instance)\n# and by other third party services that need specific env variables.\n# If you don't set these variables, the services that depend on them may not work properly.\n# By using BREVIA_ENV_SECRETS you make sure that these secrets will be available as environment variables.\nBREVIA_ENV_SECRETS='{\"OPENAI_API_KEY\": \"{{cookiecutter.openai_api_key}}\"}'\n\n## OpenAI, Cohere, and other API secrets\n# If these vars are not available as environment variables you may want to add them to BREVIA_ENV_SECRETS (see above)\n# OPENAI_API_KEY=#########\n# COHERE_API_KEY=#########\n\n## Tracing - Langsmith: if you have an account you need the env vars listed below, edit API_KEY and PROJECT vars\n# If these vars are not available as environment variables you may want to add them to BREVIA_ENV_SECRETS (see above)\n# LANGCHAIN_TRACING_V2=true\n# LANGCHAIN_ENDPOINT=\"https://api.smith.langchain.com\"\n# LANGCHAIN_API_KEY=\"########\"\n# LANGCHAIN_PROJECT=\"My Project\"\n\n### QA vars\n# Completion LLM configuration\n# QA_COMPLETION_LLM='{\"_type\": \"openai-chat\", \"model_name\": \"gpt-4o-mini\", \"temperature\": 0, \"max_tokens\": 200, \"verbose\": true}'\n\n# Followup LLM configuration\n# QA_FOLLOWUP_LLM='{\"_type\": \"openai-chat\", \"model_name\": \"gpt-4o-mini\", \"temperature\": 0, \"max_tokens\": 200, \"verbose\": true}'\n\n# Followup similarity threshold\n# QA_FOLLOWUP_SIM_THRESHOLD=0.735\n\n# Chat history - uncomment to disable session conversation, avoiding chat history loading\n# QA_NO_CHAT_HISTORY=True\n\n# Uncomment to use a custom QA retriever with custom arguments\n# QA_RETRIEVER='{\"retriever\": \"my_project.CustomRetriever\", \"some_var\": \"some_value\"}'\n\n### Security\n# Access tokens secret - if missing no access token validity is checked\n# Generate it with: openssl rand -hex 32\n# TOKENS_SECRET=##########################\n# Comma separated list of valid users - use double quotes!\n# TOKENS_USERS=\"brevia,gustavo\"\n\n## Status\n# Special token used by `GET /status` only\n# STATUS_TOKEN=#############\n\n### Search\n# default number of documents to return in a vector search\n# SEARCH_DOCS_NUM=4\n\n### Embedding\n# Embeddings engine configuration\n# EMBEDDINGS='{\"_type\": \"openai-embeddings\"}'\n\n### Index creation\n# TEXT_CHUNK_SIZE=2000\n# TEXT_CHUNK_OVERLAP=100\n# Uncomment to use a custom splitter with custom arguments\n# TEXT_SPLITTER='{\"splitter\": \"my_project.CustomSplitter\", \"some_var\": \"some_value\"}'\n\n### Summarize\n# Summarization LLM\n# SUMMARIZE_LLM='{\"_type\": \"openai-chat\", \"model_name\": \"gpt-4o-mini\", \"temperature\": 0, \"max_tokens\": 2000}'\n# SUMM_TOKEN_SPLITTER=4000\n# SUMM_TOKEN_OVERLAP=500\n# SUMM_DEFAULT_CHAIN=stuff\n\n### General\n# VERBOSE_MODE=True\n\n### OPENAPI\n# Uncomment to block openapi urls - /docs, /redoc\n# BLOCK_OPENAPI_URLS=True\n\n### Database connection\nPGVECTOR_DRIVER=psycopg2\nPGVECTOR_HOST={{cookiecutter.postgres_host}}\nPGVECTOR_PORT={{cookiecutter.postgres_port}}\nPGVECTOR_DATABASE={{cookiecutter.postgres_database}}\nPGVECTOR_USER={{cookiecutter.postgres_user}}\nPGVECTOR_PASSWORD={{cookiecutter.postgres_password}}\nPGVECTOR_POOL_SIZE=10\n\n### Docker compose\n## Postgres pgvector\n# PGVECTOR_VOLUME_NAME=pgdata\n## PG ADMIN\n# PGADMIN_DEFAULT_EMAIL=admin@admin.com\n# PGADMIN_DEFAULT_PASSWORD=admin\n# PGADMIN_PORT=4000\n# PGADMIN_VOLUME_NAME=pgadmindata\n"}, "21753bcb90e30f7028c5f85535093994b64195a1": {"t": 1785747833.8427598, "n": 2403, "h": "d56f04e0e854310d", "c": "## API conf vars\nOPENAI_API_KEY={{cookiecutter.openai_api_key}}\n\n## QA vars\n# QA completion LLM\nQA_COMPLETION_LLM='{\n    \"_type\": \"openai-chat\",\n    \"model_name\": \"gpt-3.5-turbo-16k\",\n    \"temperature\": 0,\n    \"max_tokens\": 200,\n    \"verbose\": true\n}'\n\n# QA followup LLM\nQA_FOLLOWUP_LLM='{\n    \"_type\": \"openai-chat\",\n    \"model_name\": \"gpt-3.5-turbo-16k\",\n    \"temperature\": 0,\n    \"max_tokens\": 200,\n    \"verbose\": true\n}'\n\nQA_FOLLOWUP_SIM_THRESHOLD=0.735\n# Chat history - uncomment to disable session conversation, avoiding chat history loading\n# QA_NO_CHAT_HISTORY=True\n\n# Access tokens secret - if missing no access token validity is checked\n# Generate it with: openssl rand -hex 32\n# TOKENS_SECRET=##########################\n# Comma separated list of valid users - use double quotes!\n# TOKENS_USERS=\"brevia,gustavo\"\n\n## Status\n# Special token used by `GET /status` only\n# STATUS_TOKEN=#############\n\n## Search\n# default number of documents to return in a vector search\nSEARCH_DOCS_NUM=4\n\n## Embedding\nEMBEDDINGS='{\"_type\": \"openai-embeddings\"}'\n\n## Index creation\nTEXT_CHUNK_SIZE=2000\nTEXT_CHUNK_OVERLAP=100\n\n## Summarize\n# Summarization LLM\nSUMMARIZE_LLM='{\n    \"_type\": \"openai-chat\",\n    \"model_name\": \"gpt-3.5-turbo-16k\",\n    \"temperature\": 0,\n    \"max_tokens\": 2000\n}'\nSUMM_TOKEN_SPLITTER=4000\nSUMM_TOKEN_OVERLAP=500\nSUMM_DEFAULT_CHAIN=stuff\n\n# General\nVERBOSE_MODE=True\n\n# OPENAPI\n# Uncomment to block openapi urls - /docs, /redoc\n# BLOCK_OPENAPI_URLS=True\n\n## Feature flags\n#\n# Uncomment to detect question language with Spacy\n# FEATURE_QA_LANG_DETECT=True\n\n\n## Tracing - Langsmith\n# if you have an account uncomment lines below and edit API_KEY and PROJECT vars\n# LANGCHAIN_TRACING_V2=True\n# LANGCHAIN_ENDPOINT=\"https://api.smith.langchain.com\"\n# LANGCHAIN_API_KEY=\"########\"\n# LANGCHAIN_PROJECT=\"My Project\"\n\n## DB vars\nPGVECTOR_DRIVER=psycopg2\n# host var is used on local development\n# but ignored by docker compose\nPGVECTOR_HOST={{cookiecutter.postgres_host}}\nPGVECTOR_PORT={{cookiecutter.postgres_port}}\nPGVECTOR_DATABASE={{cookiecutter.postgres_database}}\nPGVECTOR_USER={{cookiecutter.postgres_user}}\nPGVECTOR_PASSWORD={{cookiecutter.postgres_password}}\nPGVECTOR_POOL_SIZE=10\n\n## PG ADMIN vars - if used with docker compose\n# PGADMIN_DEFAULT_EMAIL=admin@admin.com\n# PGADMIN_DEFAULT_PASSWORD=admin\n# PGADMIN_PORT=4000\n# # used by docker compose only\n# PGADMIN_VOLUME_NAME=pgadmin-data\n"}, "1c3283d6b5baf575a5ea03f4e1a889576e25c485": {"t": 1785747834.9466808, "n": 1780, "h": "1635d151175dbe7f", "c": "## API conf vars\nOPENAI_API_KEY={{cookiecutter.openai_api_key}}\n\n# FOLLOW-UP question\nQA_FOLLOWUP_MODEL=text-davinci-003\nQA_FOLLOWUP_TEMPERATURE=0\nQA_FOLLOWUP_MAX_TOKENS=200\nQA_FOLLOWUP_SIM_THRESHOLD=0.735\n\n# Temp env var - uncomment to disable session conversation, avoiding chat history loading\n# QA_NO_CHAT_HISTORY=True\n\n# QA\nQA_COMPLETIONS_MODEL=gpt-3.5-turbo\nQA_TEMPERATURE=0\nQA_MAX_TOKENS=2000\n\n# Embedding\n# uncomment to use fake random embedding\n# FAKE_EMBEDDING=True\n\n# Access tokens secret - if missing no access token validity is checked\n# Generate it with: openssl rand -hex 32\n# TOKENS_SECRET=##########################\n# comma separated list of valid users - use double quotes!\n# TOKENS_USERS=\"brevia,gustavo\"\n\n# Search\n# number of documents to return in a vector search\nSEARCH_DOCS_NUM=4\n\n# Index creation\nTEXT_CHUNK_SIZE=1000\nTEXT_CHUNK_OVERLAP=100\n\n# Summarize\nSUMM_COMPLETIONS_MODEL=text-davinci-003\nSUMM_TEMPERATURE=0\nSUMM_TOKENS=1000\nSUMM_TOKEN_SPLITTER=3000\nSUMM_TOKEN_OVERLAP=0\nSUMM_DEFAULT_PROMPT=summarize\nSUMM_NUM_ITEMS=5\n# respond with a fake summary\n# FAKE_SUMMARY=True\n\n# General\nVERBOSE_MODE=True\nPROMPT_LANG=en\n\n## Tracing - enable only if handler is running!!!\n# LANGCHAIN_HANDLER=langchain\n\n## DB vars\nPGVECTOR_DRIVER=psycopg2\n# host var is used on local development\n# but ignored by docker compose\nPGVECTOR_HOST={{cookiecutter.postgres_host}}\nPGVECTOR_PORT={{cookiecutter.postgres_port}}\nPGVECTOR_DATABASE={{cookiecutter.postgres_database}}\nPGVECTOR_USER={{cookiecutter.postgres_user}}\nPGVECTOR_PASSWORD={{cookiecutter.postgres_password}}\nPGVECTOR_POOL_SIZE=10\n\n# used by docker compose only\nPGADMIN_DEFAULT_EMAIL=admin@admin.com\nPGADMIN_DEFAULT_PASSWORD=admin\nPGADMIN_PORT=4000\nPGADMIN_VOLUME_NAME=pgadmin-data\nPGVECTOR_VOLUME_NAME=pgvector-data\n"}}}}