From 2ca63b07a3e7d94c723ec2b72c5522991220c8c6 Mon Sep 17 00:00:00 2001 From: JanPeterDatakind Date: Mon, 22 Apr 2024 14:40:37 -0400 Subject: [PATCH 01/20] Added recipe db + put db creds in .env file --- .env.example | 14 +++ .../recipe-server/db/1-schema.sql | 108 ++++++++++++++++++ .../recipe-server/db/2-demo-data.sql | 41 +++++++ docker-compose.yml | 25 +++- 4 files changed, 185 insertions(+), 3 deletions(-) create mode 100644 actions/actions_plugins/recipe-server/db/1-schema.sql create mode 100644 actions/actions_plugins/recipe-server/db/2-demo-data.sql diff --git a/.env.example b/.env.example index db137b35..d0069c8e 100644 --- a/.env.example +++ b/.env.example @@ -363,6 +363,20 @@ HELP_AND_FAQ_URL=https://librechat.ai # SHOW_BIRTHDAY_ICON=true +#==================================================# +# VectorDB Configuration # +#==================================================# +POSTGRES_DB=mydatabase +POSTGRES_USER=myuser +POSTGRES_PASSWORD=mypassword + + +#==================================================# +# RecipeDB Configuration # +#==================================================# +POSTGRES_RECIPE_DB=mydatabase +POSTGRES_RECIPE_USER=myuser +POSTGRES_RECIPEPASSWORD=mypassword #==================================================# # Others # #==================================================# diff --git a/actions/actions_plugins/recipe-server/db/1-schema.sql b/actions/actions_plugins/recipe-server/db/1-schema.sql new file mode 100644 index 00000000..32fa5933 --- /dev/null +++ b/actions/actions_plugins/recipe-server/db/1-schema.sql @@ -0,0 +1,108 @@ + +CREATE SCHEMA data_recipes; +CREATE SCHEMA data; + +CREATE EXTENSION IF NOT EXISTS "uuid-ossp"; +CREATE EXTENSION IF NOT EXISTS "vector"; + +-- Create Langchain tables. Langchain will do this also, but more convenient to have as part of build. + +DROP TABLE IF EXISTS public.langchain_pg_collection; +CREATE TABLE public.langchain_pg_collection ( + name varchar NULL, + cmetadata json NULL, + uuid uuid NOT NULL, + CONSTRAINT langchain_pg_collection_pkey PRIMARY KEY (uuid) +); + +CREATE TABLE public.langchain_pg_embedding ( + collection_id uuid NULL, + embedding public.vector NULL, + "document" varchar NULL, + cmetadata json NULL, + custom_id varchar NULL, + uuid uuid NOT NULL, + CONSTRAINT langchain_pg_embedding_pkey PRIMARY KEY (uuid) +); + +-- public.langchain_pg_embedding foreign keys +ALTER TABLE public.langchain_pg_embedding ADD CONSTRAINT langchain_pg_embedding_collection_id_fkey FOREIGN KEY (collection_id) REFERENCES public.langchain_pg_collection(uuid) ON DELETE CASCADE; + + +-- Tabular view onto Langchain vector store collection +CREATE VIEW memory_view as +SELECT + le.collection_id, + le.embedding, + le.document, + le.cmetadata, + le.custom_id, + le.uuid, + le.cmetadata->>'intent' AS intent, + le.cmetadata->>'response_format' AS response_format, + le.cmetadata->>'function_response_fields' AS function_response_fields, + le.cmetadata->>'response_text' AS response_text, + le.cmetadata->>'response_image' AS response_image, + le.cmetadata->>'created' AS created, + le.cmetadata->>'source' AS source, + le.cmetadata->>'data_sources' AS data_sources, + le.cmetadata->>'functions_code' AS functions_code, + le.cmetadata->>'calling_code' AS calling_code, + le.cmetadata->>'calling_code_run_status' AS calling_code_run_status, + le.cmetadata->>'calling_code_run_time' AS calling_code_run_time, + le.cmetadata->>'mem_type' AS mem_type +FROM + langchain_pg_embedding le, + langchain_pg_collection lc +where + le.collection_id = lc.uuid and + lc."name" = 'memory_embedding'; + + +CREATE VIEW recipe_view as +SELECT + le.collection_id, + le.embedding, + le.document, + le.cmetadata, + le.custom_id, + le.uuid, + le.cmetadata->>'intent' AS intent, + le.cmetadata->>'created' AS created, + le.cmetadata->>'source' AS source, + le.cmetadata->>'data_sources' AS data_sources, + le.cmetadata->>'functions_code' AS functions_code, + le.cmetadata->>'top_function' AS top_function, + le.cmetadata->>'response_format' AS response_format, + le.cmetadata->>'function_response_fields' AS function_response_fields, + le.cmetadata->>'mem_type' AS mem_type +FROM + langchain_pg_embedding le, + langchain_pg_collection lc +where + le.collection_id = lc.uuid and + lc."name" = 'recipe_embedding'; + +CREATE VIEW helper_function_view as +SELECT + le.collection_id, + le.embedding, + le.document, + le.cmetadata, + le.custom_id, + le.uuid, + le.cmetadata->>'intent' AS intent, + le.cmetadata->>'created' AS created, + le.cmetadata->>'source' AS source, + le.cmetadata->>'data_sources' AS data_sources, + le.cmetadata->>'functions_code' AS functions_code, + le.cmetadata->>'top_function' AS top_function, + le.cmetadata->>'response_format' AS response_format, + le.cmetadata->>'function_response_fields' AS function_response_fields, + le.cmetadata->>'mem_type' AS mem_type +FROM + langchain_pg_embedding le, + langchain_pg_collection lc +where + le.collection_id = lc.uuid and + lc."name" = 'helper_function_embedding'; \ No newline at end of file diff --git a/actions/actions_plugins/recipe-server/db/2-demo-data.sql b/actions/actions_plugins/recipe-server/db/2-demo-data.sql new file mode 100644 index 00000000..bd46a89b --- /dev/null +++ b/actions/actions_plugins/recipe-server/db/2-demo-data.sql @@ -0,0 +1,41 @@ +-- Collection +INSERT INTO public.langchain_pg_collection ("name",cmetadata,uuid) VALUES + ('memory_embedding','null','339fcbd8-5e48-4ea2-8db9-ceb271c20b7d'); + +INSERT INTO public.langchain_pg_collection ("name",cmetadata,uuid) VALUES + ('recipe_embedding','null','4fe46967-7c1f-41e0-af45-16ebdff54616'); + +INSERT INTO public.langchain_pg_collection ("name",cmetadata,uuid) VALUES + ('helper_function_embedding','null','74cd8880-f62f-4107-882d-1cc5684119b8'); + +-- Memories and recipes +INSERT INTO public.langchain_pg_embedding (collection_id,embedding,"document",cmetadata,custom_id,uuid) VALUES + 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you show a visualization of the shapefile for Cameroon?','{"plan": "", "intent": "Plot shapefile for Cameroon", "created": "2024-03-07T19:30:59.050677", "response_format": "None", "function_response_fields": [], "response_text": "", "response_image": 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"data_sources": "[''a__geoBoundaries-adm2-countries_a-c.zip'']", "functions_code": "def plot_cameroon_shapefile(zip_file_location, extract_folder_location):\n import pandas as pd\n import geopandas as gpd\n import matplotlib.pyplot as plt\n import zipfile\n import os\n\n if os.path.exists(extract_folder_location):\n os.rmdir(extract_folder_location)\n os.makedirs(extract_folder_location, exist_ok=True)\n\n with zipfile.ZipFile(zip_file_location, ''r'') as zip_ref:\n zip_ref.extractall(extract_folder_location)\n\n cam_shapefile_path = f\"{extract_folder_location}/cmr_admbnda_adm2.shp\"\n cameroon_gdf = gpd.read_file(cam_shapefile_path)\n\n fig, ax = plt.subplots(figsize=(8, 12))\n cameroon_gdf.boundary.plot(ax=ax, color=''black'')\n cameroon_gdf.plot(ax=ax, color=''lightgrey'')\n plt.title(''Administrative Level 2 Boundaries of Cameroon'')\n plt.xlabel(''Longitude'')\n plt.ylabel(''Latitude'')\n plt.show()", "calling_code": "plot_cameroon_shapefile(''/mnt/data/'', ''/mnt/data/geoBoundariesCMR_ADM2'')", "calling_code_run_status": "OK", "calling_code_run_time": "", "mem_type": "memory", "source": "Chat", "custom_id": "37150026-2d16-4c92-a879-d2f8b985cec6"}','37150026-2d16-4c92-a879-d2f8b985cec6','1b9934c4-cddb-44be-8c3e-a26e11f6c492'), + 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you show a bar chart of food insecurity by state in Cameroon?','{"plan": "", "intent": "plot bar chart for food insecurity by state in Cameroon", "created": "2024-03-07T19:37:12.301936", "response_format": "None", "function_response_fields": "None", "response_text": "", "response_image": 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"data_sources": "[''a__hdx_food_security.csv'']", "functions_code": "def plot_food_insecurity_chart(data_file):\n import pandas as pd\n import matplotlib.pyplot as plt\n\n # Read the food security data\n food_security_df = pd.read_csv(data_file)\n\n # Filter the data for Cameroon using adm0_code ''CMR''\n cmr_food_security_df = food_security_df[food_security_df[''adm0_code''] == ''CMR'']\n\n # Group the food security data by admin1_code (state) and sum up the population_in_phase value\n food_insecurity_by_state = cmr_food_security_df.groupby(''admin1_name'').agg({''population_in_phase'': ''sum''}).reset_index()\n\n # Sort data by population_in_phase in descending order before plotting\n food_insecurity_by_state_sorted = food_insecurity_by_state.sort_values(by=''population_in_phase'', ascending=False)\n\n # Plot a bar chart for food insecurity by state in Cameroon\n plt.figure(figsize=(12, 8))\n plt.bar(food_insecurity_by_state_sorted[''admin1_name''], food_insecurity_by_state_sorted[''population_in_phase''], color=''tomato'')\n plt.xlabel(''State'')\n plt.ylabel(''Population in Phase (Food Insecurity)'')\n plt.title(''Food Insecurity by State in Cameroon'')\n plt.xticks(rotation=90)\n plt.tight_layout() # Adjust layout to make room for the rotated x-axis labels\n plt.show()", "calling_code": "plot_food_insecurity_chart(''/mnt/data/'')", "calling_code_run_status": "OK", "calling_code_run_time": "", "mem_type": "memory", "source": "Chat", "custom_id": "3df638e6-480d-425e-9bc6-09b707abd45f"}','3df638e6-480d-425e-9bc6-09b707abd45f','3d3f95c0-6b18-4814-bac2-c174cdaebd07'), + 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you show a visualization of the distribution of food insecurity in Cameroon?','{"plan": "", "intent": "plot a map of food insecurity in Cameroon", "created": "2024-03-07T19:43:23.539929", "response_format": "None", "function_response_fields": "", "response_text": "", "response_image": 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", "data_sources": "[''a__hdx_food_security.csv'']", "functions_code": "def plot_food_insecurity_map(food_security_data_file, shapefile_zip_file, shapefile_extract_folder): \n food_security_df = pd.read_csv(food_security_data_file) \n cmr_food_security_df = food_security_df[food_security_df[''adm0_code''] == ''CMR''] \n food_insecurity_by_state = cmr_food_security_df.groupby(''adm1_code'').agg({''population_in_phase'': ''sum'', ''population_fraction_in_phase'': ''mean''}).reset_index() \n with zipfile.ZipFile(shapefile_zip_file, ''r'') as zip_ref: \n zip_ref.extractall(shapefile_extract_folder) \n cam_shapefile = f\"{shapefile_extract_folder}/cmr_admbnda_adm2.shp\" \n cam_gdf = gpd.read_file(cam_shapefile) \n cam_gdf_merged = cam_gdf.merge(food_insecurity_by_state, on=''adm1_code'') \n fig, ax = plt.subplots(1, 1, figsize=(12, 12)) \n cam_gdf_merged.plot(column=''population_fraction_in_phase'', ax=ax, legend=True, legend_kwds={''label'': ''Population Fraction in Food Insecurity Phase'', ''orientation'': ''horizontal''}) \n ax.set_title(''Food Insecurity in Cameroon by Admin1'') \n ax.set_axis_off() \n plt.show()", "calling_code": "plot_food_insecurity_map(\"/mnt/data/\", zip_file_location, extract_folder_location)", "calling_code_run_status": "OK", "calling_code_run_time": "", "mem_type": "memory", "source": "Chat", "custom_id": "1b1da8d1-123e-4b81-a303-68887993bcc3"}','1b1da8d1-123e-4b81-a303-68887993bcc3','ad3b9030-8795-4aed-929c-478db965761a'), + 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are the sources of the data in HAPI?','{"intent": "Get information about the sources of the data in HAPI", "data_sources": ["HDX"], "top_function": {"name": "get_hdx_resource", "parameters": {"hdx_id": {"type": "string", "description": "Filter the response by the resource ID, which is a unique and fixed identifier of a Dataset on HDX. A URL in the pattern of `https://data.humdata.org/dataset/[dataset id]/resource/[resource id]` will load the dataset page on HDX.{''type'': ''string'', ''maxLength'': 36, ''description'': ''Filter the response by the resource ID, which is a unique and fixed identifier of a Dataset on HDX. A URL in the pattern of `https://data.humdata.org/dataset/[dataset id]/resource/[resource id]` will load the dataset page on HDX.'', ''title'': ''Hdx Id''}"}, "format": {"type": "string", "description": "Filter the response by the format of the resource on HDX. These are typically file formats, but can also include APIs and web apps.{''type'': ''string'', ''maxLength'': 32, ''description'': ''Filter the response by the format of the resource on HDX. These are typically file formats, but can also include APIs and web apps.'', ''title'': ''Format''}"}, "update_date_min": {"type": "string", "description": "Min date of update date, e.g. 2020-01-01 or 2020-01-01T00:00:00{''anyOf'': [{''type'': ''string'', ''format'': ''date-time''}, {''type'': ''string'', ''format'': ''date''}], ''description'': ''Min date of update date, e.g. 2020-01-01 or 2020-01-01T00:00:00'', ''title'': ''Update Date Min''}. An Example value for this parameter: ''2020-01-01''"}, "update_date_max": {"type": "string", "description": "Max date of update date, e.g. 2020-01-01 or 2020-01-01T00:00:00{''anyOf'': [{''type'': ''string'', ''format'': ''date-time''}, {''type'': ''string'', ''format'': ''date''}], ''description'': ''Max date of update date, e.g. 2020-01-01 or 2020-01-01T00:00:00'', ''title'': ''Update Date Max''}. An Example value for this parameter: ''2024-12-31''"}, "is_hxl": {"type": "boolean", "description": "Filter the response by whether or not the resource contains HXL tags.{''type'': ''boolean'', ''description'': ''Filter the response by whether or not the resource contains HXL tags.'', ''title'': ''Is Hxl''}"}, "dataset_hdx_id": {"type": "string", "description": "Filter the response by the dataset ID, which is a unique and fixed identifier of a Dataset on HDX. A URL in the pattern of `https://data.humdata.org/dataset/[dataset id]` will load the dataset page on HDX. See the dataset endpoint for details. {''type'': ''string'', ''maxLength'': 36, ''description'': ''Filter the response by the dataset ID, which is a unique and fixed identifier of a Dataset on HDX. A URL in the pattern of `https://data.humdata.org/dataset/[dataset id]` will load the dataset page on HDX. See the dataset endpoint for details. '', ''title'': ''Dataset Hdx Id''}"}, "dataset_hdx_stub": {"type": "string", "description": "Filter the response by the URL-safe name of the dataset as displayed on HDX. This name is unique but can change. A URL in the pattern of `https://data.humdata.org/dataset/[dataset name]` will load the dataset page on HDX. See the dataset endpoint for details.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by the URL-safe name of the dataset as displayed on HDX. This name is unique but can change. A URL in the pattern of `https://data.humdata.org/dataset/[dataset name]` will load the dataset page on HDX. See the dataset endpoint for details.'', ''title'': ''Dataset Hdx Stub''}"}, "dataset_title": {"type": "string", "description": "Filter the response by the title of the dataset as it appears in the HDX interface. This name is not unique and can change. See the dataset endpoint for details.{''type'': ''string'', ''maxLength'': 1024, ''description'': ''Filter the response by the title of the dataset as it appears in the HDX interface. This name is not unique and can change. See the dataset endpoint for details.'', ''title'': ''Dataset Title''}"}, "dataset_hdx_provider_stub": {"type": "string", "description": "Filter the response by the code of the provider of the dataset on HDX. A URL in the pattern of `https://data.humdata.org/organization/[org stub]` will load the provider''s page on HDX.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by the code of the provider of the dataset on HDX. A URL in the pattern of `https://data.humdata.org/organization/[org stub]` will load the provider''s page on HDX.'', ''title'': ''Dataset Hdx Provider Stub''}"}, "dataset_hdx_provider_name": {"type": "string", "description": "Filter the response by the display name of the provider of the dataset on HDX.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the display name of the provider of the dataset on HDX.'', ''title'': ''Dataset Hdx Provider Name''}"}, "output_format": {"type": "string", "description": "{''allOf'': [{''$ref'': ''#/components/schemas/OutputFormat''}], ''default'': ''json'', ''title'': ''Output Format''}"}, "limit": {"type": "integer", "description": "Maximum number of records to return. The system will not return more than 10,000 records.{''type'': ''integer'', ''maximum'': 10000, ''minimum'': 0, ''description'': ''Maximum number of records to return. The system will not return more than 10,000 records.'', ''default'': 10000, ''title'': ''Limit''}. An Example value for this parameter: ''1000''"}, "offset": {"type": "integer", "description": "Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.{''type'': ''integer'', ''minimum'': 0, ''description'': ''Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.'', ''default'': 0, ''title'': ''Offset''}"}}}, "functions_code": "\ndef get_hdx_resource(**kwargs):\n return get_api_data(''https://stage.hapi-humdata-org.ahconu.org///api/resource'',**kwargs)\n \n ", "source": "Generated from: https://stage.hapi-humdata-org.ahconu.org/openapi.json", "mem_type": "recipe", "created": "2024-01-31 19:22:50.378978", "response_format": "json", "function_response_fields": [{"name": "hdx_id", "type": "string"}, {"name": "name", "type": "string"}, {"name": "format", "type": "string"}, {"name": "update_date", "type": "string"}, {"name": "is_hxl", "type": "boolean"}, {"name": "download_url", "type": "string"}, {"name": "dataset_hdx_id", "type": "string"}, {"name": "dataset_hdx_stub", "type": "string"}, {"name": "dataset_title", "type": "string"}, {"name": "dataset_hdx_provider_stub", "type": "string"}, {"name": "dataset_hdx_provider_name", "type": "string"}, {"name": "hdx_link", "type": "string"}, {"name": "hdx_api_link", "type": "string"}, {"name": "dataset_hdx_link", "type": "string"}, {"name": "dataset_hdx_api_link", "type": "string"}], "calling_code_run_status": "OK", "calling_code_run_time": 0, "response_image": "", "calling_code": "", "custom_id": "ac6f4812-37b7-4ba9-b356-89562d9a0208"}','ac6f4812-37b7-4ba9-b356-89562d9a0208','05ae6a42-6e01-4d45-82c4-12023628cccd'), + 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is the ISO3 country code for a given country name?','{"intent": "The intent is to retrieve the ISO3 country code for a given country name.", "top_function": {"name": "get_country_code", "parameters": {"type": "object", "properties": {"country_name": {"type": "string", "description": "The name of the country for which the code is desired."}}}}, "functions_code": "# filename: get_country_code.py\n\ndef get_country_code(country_name):\n \"\"\"\n Retrieves the ISO3 country code for a given country name.\n\n Parameters:\n - country_name (str): The name of the country for which the code is desired.\n\n Returns:\n - str: ISO3 country code.\n \"\"\"\n\n # Call the function ''get_hdx_location'' to find the ISO3 country code \n response = get_hdx_location(name=country_name)\n\n if not response:\n print(''No data found for the specified country name.'')\n return None\n\n if ''code'' in response:\n return response[''code'']\n else:\n print(''Country code not found in the response.'')\n return None\n\n", "calling_code_example": " # Define input parameters to the function\n params = {''country_name'': ''Mali''}\n\n # Call the function and print out the country code\n country_code = get_country_code(**params)\n if country_code:\n print(''The country code for Mali is:'', country_code)\n\n", "calling_code_run_status": "OK", "data_sources": ["HDX"], "created": "2024-02-01 00:29:24", "response_format": "string", "mem_type": "recipe", "source": "Recipes Assistant", "function_response_fields": [{"name": "code", "type": "str"}], "custom_id": "bf803eb3-ac8f-4fe8-a13b-5739937b1d38"}','bf803eb3-ac8f-4fe8-a13b-5739937b1d38','e9b7fe67-f917-4247-b59d-62fd89126321'), + 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is the total population for a country?','{"intent": "Get the total population of a country", "top_function": {"name": "get_total_population", "parameters": {"type": "object", "properties": {"country_name": {"type": "string", "description": "The name of the country for which to get the total population."}, "kwargs": {"type": "object", "description": "Additional keyword arguments."}}}}, "functions_code": "# filename: total_population.py\n\nimport json\nimport pandas as pd\n\ndef get_total_population(country_name, **kwargs):\n # Get the ISO3 country code for the given country name\n iso3_code = get_country_code(country_name=country_name)\n \n # Define the parameters for getting the population data\n params = {\n ''location_code'': iso3_code,\n ''output_format'': ''json'',\n ''limit'': 1000\n }\n \n # Fetch population data for the given country code\n population_data = get_hdx_population(**params)\n\n # Calculate the total population\n total_pop = 0\n if population_data: # Check if there is data in the response\n for record in population_data:\n total_pop += record.get(\"population\", 0)\n \n # print the total population and return it\n print(f\"Total population of {country_name} is: {total_pop}\")\n return {''total_population'': total_pop}\n\n\n", "calling_code_example": " country = ''Mali''\n total_population = get_total_population(country_name=country)\n total_population_json = json.dumps(total_population)\n # Print debug information\n print(\"DEBUG INFO - Total population data:\", total_population_json)\n\n", "calling_code_run_status": "OK", "data_sources": ["HDX"], "created": "2024-02-01 00:32:36", "response_format": "string", "mem_type": "recipe", "source": "Recipes Assistant", "function_response_fields": [{"name": "total_population", "type": "integer"}], "custom_id": "3003c3c7-4c6b-4743-b542-2095fd8597eb"}','3003c3c7-4c6b-4743-b542-2095fd8597eb','06895671-8915-4f87-bb03-1a159eabbf21'), + 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a visualization of the distribution of organizations working in different locations affected by a crisis and the humanitarian sectors they are working in.','{"intent": "Retrieve the list of organizations working in different locations affected by a crisis and the humanitarian sectors they are working in", "data_sources": ["HDX"], "top_function": {"name": "get_hdx_3W", "parameters": {"sector_code": {"type": "string", "description": "Filter the response by sector codes, which describe the humanitarian sector to which the operational presence applies. See the sector endpoint for details{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by sector codes, which describe the humanitarian sector to which the operational presence applies. See the sector endpoint for details'', ''title'': ''Sector Code''}"}, "sector_name": {"type": "string", "description": "Filter the response by sector names, which describe the humanitarian sector to which the operational presence applies. See the sector endpoint for details.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by sector names, which describe the humanitarian sector to which the operational presence applies. See the sector endpoint for details.'', ''title'': ''Sector Name''}"}, "org_acronym": {"type": "string", "description": "Filter the response by the acronym of the organization to which the operational presence applies. See the org endpoint for details{''type'': ''string'', ''maxLength'': 32, ''description'': ''Filter the response by the acronym of the organization to which the operational presence applies. See the org endpoint for details'', ''title'': ''Org Acronym''}"}, "org_name": {"type": "string", "description": "Filter the response by the name of the organization to which the operational presence applies. See the org endpoint for details{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the name of the organization to which the operational presence applies. See the org endpoint for details'', ''title'': ''Org Name''}"}, "location_code": {"type": "string", "description": "Filter the response by a location (typically a country). The location codes use the ISO-3 (ISO 3166 alpha-3) codes. See the location endpoint for details.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by a location (typically a country). The location codes use the ISO-3 (ISO 3166 alpha-3) codes. See the location endpoint for details.'', ''title'': ''Location Code''}"}, "location_name": {"type": "string", "description": "Filter the response by a location (typically a country). The location names are based on the ''short name'' from the UN M49 Standard. See the location endpoint for details.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by a location (typically a country). The location names are based on the ''short name'' from the UN M49 Standard. See the location endpoint for details.'', ''title'': ''Location Name''}"}, "admin1_code": {"type": "string", "description": "Filter the response by the 1st subnational administrative divisions. The admin1 codes refer to the p-codes in the Common Operational Datasets. See the admin1 endpoint for details.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by the 1st subnational administrative divisions. The admin1 codes refer to the p-codes in the Common Operational Datasets. See the admin1 endpoint for details.'', ''title'': ''Admin1 Code''}"}, "admin1_name": {"type": "string", "description": "Filter the response by the 1st subnational administrative divisions. The admin1 names refer to the Common Operational Datasets. See the admin1 endpoint for details.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the 1st subnational administrative divisions. The admin1 names refer to the Common Operational Datasets. See the admin1 endpoint for details.'', ''title'': ''Admin1 Name''}"}, "admin2_code": {"type": "string", "description": "Filter the response by the 2nd subnational administrative divisions. The admin2 codes refer to the p-codes in the Common Operational Datasets. See the admin2 endpoint for details.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by the 2nd subnational administrative divisions. The admin2 codes refer to the p-codes in the Common Operational Datasets. See the admin2 endpoint for details.'', ''title'': ''Admin2 Code''}"}, "admin2_name": {"type": "string", "description": "Filter the response by the 1st subnational administrative divisions. The admin2 names refer to the Common Operational Datasets. See the admin2 endpoint for details.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the 1st subnational administrative divisions. The admin2 names refer to the Common Operational Datasets. See the admin2 endpoint for details.'', ''title'': ''Admin2 Name''}"}, "admin_level": {"type": "string", "description": "Filter the response by admin level{''allOf'': [{''$ref'': ''#/components/schemas/AdminLevel''}], ''description'': ''Filter the response by admin level'', ''title'': ''Admin Level''}"}, "resource_update_date_min": {"type": "string", "description": "Filter the repsonse to data updated on or after this date. For example 2020-01-01 or 2020-01-01T00:00:00{''anyOf'': [{''type'': ''string'', ''format'': ''date-time''}, {''type'': ''string'', ''format'': ''date''}], ''description'': ''Filter the repsonse to data updated on or after this date. For example 2020-01-01 or 2020-01-01T00:00:00'', ''title'': ''Resource Update Date Min''}. An Example value for this parameter: ''2020-01-01''"}, "resource_update_date_max": {"type": "string", "description": "Filter the repsonse to data updated on or before this date. For example 2024-12-31 or 2024-12-31T23:59:59{''anyOf'': [{''type'': ''string'', ''format'': ''date-time''}, {''type'': ''string'', ''format'': ''date''}], ''description'': ''Filter the repsonse to data updated on or before this date. For example 2024-12-31 or 2024-12-31T23:59:59'', ''title'': ''Resource Update Date Max''}. An Example value for this parameter: ''2024-12-31''"}, "dataset_hdx_provider_stub": {"type": "string", "description": "Filter the query by the organizations contributing the source data to HDX. If you want to filter by the organization mentioned in the operational presence record, see the org_name and org_acronym parameters below.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the query by the organizations contributing the source data to HDX. If you want to filter by the organization mentioned in the operational presence record, see the org_name and org_acronym parameters below.'', ''title'': ''Dataset Hdx Provider Stub''}"}, "output_format": {"type": "string", "description": "{''allOf'': [{''$ref'': ''#/components/schemas/OutputFormat''}], ''default'': ''json'', ''title'': ''Output Format''}"}, "limit": {"type": "integer", "description": "Maximum number of records to return. The system will not return more than 10,000 records.{''type'': ''integer'', ''maximum'': 10000, ''minimum'': 0, ''description'': ''Maximum number of records to return. The system will not return more than 10,000 records.'', ''default'': 10000, ''title'': ''Limit''}. An Example value for this parameter: ''1000''"}, "offset": {"type": "integer", "description": "Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.{''type'': ''integer'', ''minimum'': 0, ''description'': ''Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.'', ''default'': 0, ''title'': ''Offset''}"}}}, "functions_code": "\ndef get_hdx_3W(**kwargs):\n return get_api_data(''https://stage.hapi-humdata-org.ahconu.org///api/themes/3W'',**kwargs)\n \n ", "source": "Generated from: https://stage.hapi-humdata-org.ahconu.org/openapi.json", "mem_type": "recipe", "created": "2024-01-31 19:22:25.279726", "response_format": "json", "function_response_fields": [{"name": "sector_code", "type": "string"}, {"name": "dataset_hdx_stub", "type": "string"}, {"name": "resource_hdx_id", "type": "string"}, {"name": "org_acronym", "type": "string"}, {"name": "org_name", "type": "string"}, {"name": "sector_name", "type": "string"}, {"name": "location_code", "type": "string"}, {"name": "location_name", "type": "string"}], "calling_code_run_status": "OK", "calling_code_run_time": 0, "response_image": "", "calling_code": "", "custom_id": 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you show a comparison of organizations working in different locations and the humanitarian sectors they are working in?','{"intent": "Retrieve the list of organizations working in different locations and the humanitarian sectors they are working in", "data_sources": ["HDX"], "top_function": {"name": "get_hdx_3w", "parameters": {"sector_code": {"type": "string", "description": "Filter the response by sector codes, which describe the humanitarian sector to which the operational presence applies. See the sector endpoint for details{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by sector codes, which describe the humanitarian sector to which the operational presence applies. See the sector endpoint for details'', ''title'': ''Sector Code''}"}, "sector_name": {"type": "string", "description": "Filter the response by sector names, which describe the humanitarian sector to which the operational presence applies. See the sector endpoint for details.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by sector names, which describe the humanitarian sector to which the operational presence applies. See the sector endpoint for details.'', ''title'': ''Sector Name''}"}, "org_acronym": {"type": "string", "description": "Filter the response by the acronym of the organization to which the operational presence applies. See the org endpoint for details{''type'': ''string'', ''maxLength'': 32, ''description'': ''Filter the response by the acronym of the organization to which the operational presence applies. See the org endpoint for details'', ''title'': ''Org Acronym''}"}, "org_name": {"type": "string", "description": "Filter the response by the name of the organization to which the operational presence applies. See the org endpoint for details{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the name of the organization to which the operational presence applies. See the org endpoint for details'', ''title'': ''Org Name''}"}, "location_code": {"type": "string", "description": "Filter the response by a location (typically a country). The location codes use the ISO-3 (ISO 3166 alpha-3) codes. See the location endpoint for details.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by a location (typically a country). The location codes use the ISO-3 (ISO 3166 alpha-3) codes. See the location endpoint for details.'', ''title'': ''Location Code''}"}, "location_name": {"type": "string", "description": "Filter the response by a location (typically a country). The location names are based on the ''short name'' from the UN M49 Standard. See the location endpoint for details.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by a location (typically a country). The location names are based on the ''short name'' from the UN M49 Standard. See the location endpoint for details.'', ''title'': ''Location Name''}"}, "admin1_code": {"type": "string", "description": "Filter the response by the 1st subnational administrative divisions. The admin1 codes refer to the p-codes in the Common Operational Datasets. See the admin1 endpoint for details.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by the 1st subnational administrative divisions. The admin1 codes refer to the p-codes in the Common Operational Datasets. See the admin1 endpoint for details.'', ''title'': ''Admin1 Code''}"}, "admin1_name": {"type": "string", "description": "Filter the response by the 1st subnational administrative divisions. The admin1 names refer to the Common Operational Datasets. See the admin1 endpoint for details.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the 1st subnational administrative divisions. The admin1 names refer to the Common Operational Datasets. See the admin1 endpoint for details.'', ''title'': ''Admin1 Name''}"}, "admin2_code": {"type": "string", "description": "Filter the response by the 2nd subnational administrative divisions. The admin2 codes refer to the p-codes in the Common Operational Datasets. See the admin2 endpoint for details.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by the 2nd subnational administrative divisions. The admin2 codes refer to the p-codes in the Common Operational Datasets. See the admin2 endpoint for details.'', ''title'': ''Admin2 Code''}"}, "admin2_name": {"type": "string", "description": "Filter the response by the 1st subnational administrative divisions. The admin2 names refer to the Common Operational Datasets. See the admin2 endpoint for details.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the 1st subnational administrative divisions. The admin2 names refer to the Common Operational Datasets. See the admin2 endpoint for details.'', ''title'': ''Admin2 Name''}"}, "admin_level": {"type": "string", "description": "Filter the response by admin level{''allOf'': [{''$ref'': ''#/components/schemas/AdminLevel''}], ''description'': ''Filter the response by admin level'', ''title'': ''Admin Level''}"}, "resource_update_date_min": {"type": "string", "description": "Filter the repsonse to data updated on or after this date. For example 2020-01-01 or 2020-01-01T00:00:00{''anyOf'': [{''type'': ''string'', ''format'': ''date-time''}, {''type'': ''string'', ''format'': ''date''}], ''description'': ''Filter the repsonse to data updated on or after this date. For example 2020-01-01 or 2020-01-01T00:00:00'', ''title'': ''Resource Update Date Min''}. An Example value for this parameter: ''2020-01-01''"}, "resource_update_date_max": {"type": "string", "description": "Filter the repsonse to data updated on or before this date. For example 2024-12-31 or 2024-12-31T23:59:59{''anyOf'': [{''type'': ''string'', ''format'': ''date-time''}, {''type'': ''string'', ''format'': ''date''}], ''description'': ''Filter the repsonse to data updated on or before this date. For example 2024-12-31 or 2024-12-31T23:59:59'', ''title'': ''Resource Update Date Max''}. An Example value for this parameter: ''2024-12-31''"}, "dataset_hdx_provider_stub": {"type": "string", "description": "Filter the query by the organizations contributing the source data to HDX. If you want to filter by the organization mentioned in the operational presence record, see the org_name and org_acronym parameters below.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the query by the organizations contributing the source data to HDX. If you want to filter by the organization mentioned in the operational presence record, see the org_name and org_acronym parameters below.'', ''title'': ''Dataset Hdx Provider Stub''}"}, "output_format": {"type": "string", "description": "{''allOf'': [{''$ref'': ''#/components/schemas/OutputFormat''}], ''default'': ''json'', ''title'': ''Output Format''}"}, "limit": {"type": "integer", "description": "Maximum number of records to return. The system will not return more than 10,000 records.{''type'': ''integer'', ''maximum'': 10000, ''minimum'': 0, ''description'': ''Maximum number of records to return. The system will not return more than 10,000 records.'', ''default'': 10000, ''title'': ''Limit''}. An Example value for this parameter: ''1000''"}, "offset": {"type": "integer", "description": "Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.{''type'': ''integer'', ''minimum'': 0, ''description'': ''Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.'', ''default'': 0, ''title'': ''Offset''}"}}}, "functions_code": "\ndef get_hdx_3w(**kwargs):\n return get_api_data(''https://stage.hapi-humdata-org.ahconu.org///api/themes/3w'',**kwargs)\n \n ", "source": "Generated from: https://stage.hapi-humdata-org.ahconu.org/openapi.json", "mem_type": "recipe", "created": "2024-01-31 19:22:26.728292", "response_format": "json", "function_response_fields": [{"name": "sector_code", "type": "string"}, {"name": "dataset_hdx_stub", "type": "string"}, {"name": "resource_hdx_id", "type": "string"}, {"name": "org_acronym", "type": "string"}, {"name": "org_name", "type": "string"}, {"name": "sector_name", "type": "string"}, {"name": "location_code", "type": "string"}, {"name": "location_name", "type": "string"}, {"name": "admin1_code", "type": "string"}, {"name": "admin1_name", "type": "string"}, {"name": "admin2_code", "type": "string"}, {"name": "admin2_name", "type": "string"}], 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is the population data for baseline populations in the given location/context?','{"intent": "Retrieve baseline population data from the API and return it as a list of populations", "data_sources": ["HDX"], "top_function": {"name": "get_hdx_population", "parameters": {"gender_code": {"type": "string", "description": "Gender code{''type'': ''string'', ''maxLength'': 1, ''description'': ''Gender code'', ''title'': ''Gender Code''}"}, "age_range_code": {"type": "string", "description": "Age range code{''type'': ''string'', ''maxLength'': 32, ''description'': ''Age range code'', ''title'': ''Age Range Code''}"}, "population": {"type": "integer", "description": "Population{''type'': ''integer'', ''description'': ''Population'', ''title'': ''Population''}"}, "dataset_hdx_provider_stub": {"type": "string", "description": "Organization(provider) code{''type'': ''string'', ''maxLength'': 128, ''description'': ''Organization(provider) code'', ''title'': ''Dataset Hdx Provider Stub''}"}, "resource_update_date_min": {"type": "string", "description": "Min date of update date, e.g. 2020-01-01 or 2020-01-01T00:00:00{''anyOf'': [{''type'': ''string'', ''format'': ''date-time''}, {''type'': ''string'', ''format'': ''date''}], ''description'': ''Min date of update date, e.g. 2020-01-01 or 2020-01-01T00:00:00'', ''title'': ''Resource Update Date Min''}. An Example value for this parameter: ''2020-01-01''"}, "resource_update_date_max": {"type": "string", "description": "Max date of update date, e.g. 2020-01-01 or 2020-01-01T00:00:00{''anyOf'': [{''type'': ''string'', ''format'': ''date-time''}, {''type'': ''string'', ''format'': ''date''}], ''description'': ''Max date of update date, e.g. 2020-01-01 or 2020-01-01T00:00:00'', ''title'': ''Resource Update Date Max''}. An Example value for this parameter: ''2024-12-31''"}, "location_code": {"type": "string", "description": "Filter the response by a location (typically a country). The location codes use the ISO-3 (ISO 3166 alpha-3) codes. See the location endpoint for details.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by a location (typically a country). The location codes use the ISO-3 (ISO 3166 alpha-3) codes. See the location endpoint for details.'', ''title'': ''Location Code''}"}, "location_name": {"type": "string", "description": "Filter the response by a location (typically a country). The location names are based on the ''short name'' from the UN M49 Standard. See the location endpoint for details.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by a location (typically a country). The location names are based on the ''short name'' from the UN M49 Standard. See the location endpoint for details.'', ''title'': ''Location Name''}"}, "admin1_name": {"type": "string", "description": "Admin1 name{''type'': ''string'', ''maxLength'': 512, ''description'': ''Admin1 name'', ''title'': ''Admin1 Name''}"}, "admin1_code": {"type": "string", "description": "Admin1 code{''type'': ''string'', ''maxLength'': 128, ''description'': ''Admin1 code'', ''title'': ''Admin1 Code''}"}, "admin2_name": {"type": "string", "description": "Admin2 name{''type'': ''string'', ''maxLength'': 512, ''description'': ''Admin2 name'', ''title'': ''Admin2 Name''}"}, "admin2_code": {"type": "string", "description": "Admin2 code{''type'': ''string'', ''maxLength'': 128, ''description'': ''Admin2 code'', ''title'': ''Admin2 Code''}"}, "admin_level": {"type": "string", "description": "Filter the response by admin level{''allOf'': [{''$ref'': ''#/components/schemas/AdminLevel''}], ''description'': ''Filter the response by admin level'', ''title'': ''Admin Level''}"}, "output_format": {"type": "string", "description": "{''allOf'': [{''$ref'': ''#/components/schemas/OutputFormat''}], ''default'': ''json'', ''title'': ''Output Format''}"}, "limit": {"type": "integer", "description": "Maximum number of records to return. The system will not return more than 10,000 records.{''type'': ''integer'', ''maximum'': 10000, ''minimum'': 0, ''description'': ''Maximum number of records to return. The system will not return more than 10,000 records.'', ''default'': 10000, ''title'': ''Limit''}. An Example value for this parameter: ''1000''"}, "offset": {"type": "integer", "description": "Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.{''type'': ''integer'', ''minimum'': 0, ''description'': ''Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.'', ''default'': 0, ''title'': ''Offset''}"}}}, "functions_code": "\ndef get_hdx_population(**kwargs):\n return get_api_data(''https://stage.hapi-humdata-org.ahconu.org///api/themes/population'',**kwargs)\n \n ", "source": "Generated from: https://stage.hapi-humdata-org.ahconu.org/openapi.json", "mem_type": "recipe", "created": "2024-01-31 19:22:28.700561", "response_format": "json", "function_response_fields": [{"name": "population", "type": "integer"}, {"name": "dataset_hdx_stub", "type": "string"}, {"name": "resource_hdx_id", "type": "string"}, {"name": "location_code", "type": "string"}, {"name": "location_name", "type": "string"}], "calling_code_run_status": "OK", "calling_code_run_time": 0, "response_image": "", "calling_code": "", "custom_id": "73392a46-7f72-41e8-b76d-cb82480b9437"}','73392a46-7f72-41e8-b76d-cb82480b9437','019091c7-16c7-4f11-a0bc-460e55531268'), + 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are the age ranges used for disaggregating population data?','{"intent": "Get the list of age ranges used for disaggregating population data", "data_sources": ["HDX"], "top_function": {"name": "get_hdx_age_range", "parameters": {"code": {"type": "string", "description": "Filter the response by the age range. These are expressed as [start year]-[end year]. The end year is assumed to be inclusive, though that is not always explicit in the source data.{''type'': ''string'', ''maxLength'': 32, ''description'': ''Filter the response by the age range. These are expressed as [start year]-[end year]. The end year is assumed to be inclusive, though that is not always explicit in the source data.'', ''title'': ''Code''}. An Example value for this parameter: ''20-24''"}, "output_format": {"type": "string", "description": "{''allOf'': [{''$ref'': ''#/components/schemas/OutputFormat''}], ''default'': ''json'', ''title'': ''Output Format''}"}, "limit": {"type": "integer", "description": "Maximum number of records to return. The system will not return more than 10,000 records.{''type'': ''integer'', ''maximum'': 10000, ''minimum'': 0, ''description'': ''Maximum number of records to return. The system will not return more than 10,000 records.'', ''default'': 10000, ''title'': ''Limit''}. An Example value for this parameter: ''1000''"}, "offset": {"type": "integer", "description": "Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.{''type'': ''integer'', ''minimum'': 0, ''description'': ''Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.'', ''default'': 0, ''title'': ''Offset''}"}}}, "functions_code": "\ndef get_hdx_age_range(**kwargs):\n return get_api_data(''https://stage.hapi-humdata-org.ahconu.org///api/age_range'',**kwargs)\n \n ", "source": "Generated from: https://stage.hapi-humdata-org.ahconu.org/openapi.json", "mem_type": "recipe", "created": "2024-01-31 19:22:43.337019", "response_format": "json", "function_response_fields": [{"name": "code", "type": "string"}, {"name": "age_min", "type": "integer"}], "calling_code_run_status": "OK", "calling_code_run_time": 0, "response_image": "", "calling_code": "", "custom_id": "4cdf44ad-cb54-4271-8fa5-3263999afa9b"}','4cdf44ad-cb54-4271-8fa5-3263999afa9b','bcb4dea9-9fe7-4bbf-b3e4-651924346d79'); +INSERT INTO public.langchain_pg_embedding (collection_id,embedding,"document",cmetadata,custom_id,uuid) VALUES + 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is the list of second-level administrative divisions for HAPI?','{"intent": "Retrieve the list of second-level administrative divisions available in HAPI", "data_sources": ["HDX"], "top_function": {"name": "get_hdx_admin2", "parameters": {"code": {"type": "string", "description": "Filter the response by the 2nd subnational administrative divisions. The admin2 codes refer to the p-codes in the Common Operational Datasets.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by the 2nd subnational administrative divisions. The admin2 codes refer to the p-codes in the Common Operational Datasets.'', ''title'': ''Code''}"}, "name": {"type": "string", "description": "Filter the response by the 1st subnational administrative divisions. The admin2 names refer to the Common Operational Datasets.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the 1st subnational administrative divisions. The admin2 names refer to the Common Operational Datasets.'', ''title'': ''Name''}"}, "admin1_code": {"type": "string", "description": "Filter the response by the 1st subnational administrative divisions. The admin1 codes refer to the p-codes in the Common Operational Datasets. See the admin1 endpoint for details.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by the 1st subnational administrative divisions. The admin1 codes refer to the p-codes in the Common Operational Datasets. See the admin1 endpoint for details.'', ''title'': ''Admin1 Code''}"}, "admin1_name": {"type": "string", "description": "Filter the response by the 1st subnational administrative divisions. The admin1 names refer to the Common Operational Datasets. See the admin1 endpoint for details.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the 1st subnational administrative divisions. The admin1 names refer to the Common Operational Datasets. See the admin1 endpoint for details.'', ''title'': ''Admin1 Name''}"}, "location_code": {"type": "string", "description": "Filter the response by a location (typically a country). The location codes use the ISO-3 (ISO 3166 alpha-3) codes. See the location endpoint for details.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by a location (typically a country). The location codes use the ISO-3 (ISO 3166 alpha-3) codes. See the location endpoint for details.'', ''title'': ''Location Code''}"}, "location_name": {"type": "string", "description": "Filter the response by a location (typically a country). The location names are based on the ''short name'' from the UN M49 Standard. See the location endpoint for details.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by a location (typically a country). The location names are based on the ''short name'' from the UN M49 Standard. See the location endpoint for details.'', ''title'': ''Location Name''}"}, "output_format": {"type": "string", "description": "{''allOf'': [{''$ref'': ''#/components/schemas/OutputFormat''}], ''default'': ''json'', ''title'': ''Output Format''}"}, "limit": {"type": "integer", "description": "Maximum number of records to return. The system will not return more than 10,000 records.{''type'': ''integer'', ''maximum'': 10000, ''minimum'': 0, ''description'': ''Maximum number of records to return. The system will not return more than 10,000 records.'', ''default'': 10000, ''title'': ''Limit''}. An Example value for this parameter: ''1000''"}, "offset": {"type": "integer", "description": "Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.{''type'': ''integer'', ''minimum'': 0, ''description'': ''Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.'', ''default'': 0, ''title'': ''Offset''}"}}}, "functions_code": "\ndef get_hdx_admin2(**kwargs):\n return get_api_data(''https://stage.hapi-humdata-org.ahconu.org///api/admin2'',**kwargs)\n \n ", "source": "Generated from: https://stage.hapi-humdata-org.ahconu.org/openapi.json", "mem_type": "recipe", "created": "2024-01-31 19:22:34.899544", "response_format": "json", "function_response_fields": [{"name": "code", "type": "string"}, {"name": "name", "type": "string"}, {"name": "admin1_code", "type": "string"}, {"name": "admin1_name", "type": "string"}, {"name": "location_code", "type": "string"}, {"name": "location_name", "type": "string"}], "calling_code_run_status": "OK", "calling_code_run_time": 0, "response_image": "", "calling_code": "", "custom_id": "f3061131-64fc-455e-9b82-c3be06f44fd3"}','f3061131-64fc-455e-9b82-c3be06f44fd3','65c5a91a-bcfc-43ee-ade6-e6f13a1043ac'), + 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is the classification of organizations in HAPI?','{"intent": "Retrieve information about how organizations are classified in HAPI", "data_sources": ["HDX"], "top_function": {"name": "get_hdx_org_type", "parameters": {"code": {"type": "string", "description": "Filter the response by the organization type code.{''type'': ''string'', ''maxLength'': 32, ''description'': ''Filter the response by the organization type code.'', ''title'': ''Code''}. An Example value for this parameter: ''433''"}, "description": {"type": "string", "description": "Filter the response by the organization type description.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the organization type description.'', ''title'': ''Description''}. An Example value for this parameter: ''Donor''"}, "output_format": {"type": "string", "description": "{''allOf'': [{''$ref'': ''#/components/schemas/OutputFormat''}], ''default'': ''json'', ''title'': ''Output Format''}"}, "limit": {"type": "integer", "description": "Maximum number of records to return. The system will not return more than 10,000 records.{''type'': ''integer'', ''maximum'': 10000, ''minimum'': 0, ''description'': ''Maximum number of records to return. The system will not return more than 10,000 records.'', ''default'': 10000, ''title'': ''Limit''}. An Example value for this parameter: ''1000''"}, "offset": {"type": "integer", "description": "Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.{''type'': ''integer'', ''minimum'': 0, ''description'': ''Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.'', ''default'': 0, ''title'': ''Offset''}"}}}, "functions_code": "\ndef get_hdx_org_type(**kwargs):\n return get_api_data(''https://stage.hapi-humdata-org.ahconu.org///api/org_type'',**kwargs)\n \n ", "source": "Generated from: https://stage.hapi-humdata-org.ahconu.org/openapi.json", "mem_type": "recipe", "created": "2024-01-31 19:22:38.833515", "response_format": "json", "function_response_fields": [{"name": "code", "type": "string"}, {"name": "description", "type": "string"}], "calling_code_run_status": "OK", "calling_code_run_time": 0, "response_image": "", "calling_code": "", "custom_id": "1041cd57-a691-4ba5-8600-be1f1e43dcc4"}','1041cd57-a691-4ba5-8600-be1f1e43dcc4','2ff4208f-5451-4a25-b346-bbdcc11dcdd3'), + 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is the list of gender codes used for population data disaggregation?','{"intent": "Retrieve the list of gender codes used for population data disaggregation", "data_sources": ["HDX"], "top_function": {"name": "get_hdx_gender", "parameters": {"code": {"type": "string", "description": "Filter the response by the gender code.{''type'': ''string'', ''maxLength'': 1, ''description'': ''Filter the response by the gender code.'', ''title'': ''Code''}. An Example value for this parameter: ''f''"}, "description": {"type": "string", "description": "Filter the response by the gender description.{''type'': ''string'', ''maxLength'': 256, ''description'': ''Filter the response by the gender description.'', ''title'': ''Description''}. An Example value for this parameter: ''female''"}, "output_format": {"type": "string", "description": "{''allOf'': [{''$ref'': ''#/components/schemas/OutputFormat''}], ''default'': ''json'', ''title'': ''Output Format''}"}, "limit": {"type": "integer", "description": "Maximum number of records to return. The system will not return more than 10,000 records.{''type'': ''integer'', ''maximum'': 10000, ''minimum'': 0, ''description'': ''Maximum number of records to return. The system will not return more than 10,000 records.'', ''default'': 10000, ''title'': ''Limit''}. An Example value for this parameter: ''1000''"}, "offset": {"type": "integer", "description": "Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.{''type'': ''integer'', ''minimum'': 0, ''description'': ''Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.'', ''default'': 0, ''title'': ''Offset''}"}}}, "functions_code": "\ndef get_hdx_gender(**kwargs):\n return get_api_data(''https://stage.hapi-humdata-org.ahconu.org///api/gender'',**kwargs)\n \n ", "source": "Generated from: https://stage.hapi-humdata-org.ahconu.org/openapi.json", "mem_type": "recipe", "created": "2024-01-31 19:22:45.689985", "response_format": "json", "function_response_fields": [{"name": "code", "type": "string"}, {"name": "description", "type": "string"}], "calling_code_run_status": "OK", "calling_code_run_time": 0, "response_image": "", "calling_code": "", "custom_id": "c2103e9a-21f2-4074-b8e9-e6646d5d31b6"}','c2103e9a-21f2-4074-b8e9-e6646d5d31b6','d43c52d1-df82-4002-932f-ead64c0733fe'), + 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you show a visualization of population by admin1 in Venezuela?','{"plan": "", "intent": "Generate a map of population by admin1 in Venezuela", "created": "2024-03-05T10:41:34.216936", "response_format": "None", "function_response_fields": [], "response_text": "", "response_image": 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", "data_sources": "[''d__hdx_population.csv'', ''d__geoBoundaries-adm1-countries_a-z.zip'']", "functions_code": "def generate_population_map(population_data_file, zip_file_extract_folder, zip_file_location_with_shapefiles, venezuela_shapefile):\n import pandas as pd\n import geopandas as gpd\n import matplotlib.pyplot as plt\n import zipfile\n \n # Unzipping the admin level 1 boundaries for Venezuela\n with zipfile.ZipFile(zip_file_location_with_shapefiles, ''r'') as zip_ref:\n zip_ref.extractall(zip_file_extract_folder)\n \n # Load the population data\n population_df = pd.read_csv(population_data_file)\n \n # Filter the population data for Venezuela using its ADM0 code ''VEN''\n venezuela_population_df = population_df[population_df[''adm0_code''] == ''VEN'']\n \n # Group the population by adm1_code and sum up to get the total population per admin1\n venezuela_population_by_admin1 = venezuela_population_df.groupby(''adm1_code'')[''population''].sum().reset_index()\n \n # Load Venezuela''s shapefile using GeoPandas\n venezuela_gdf = gpd.read_file(f''{zip_file_extract_folder}/{venezuela_shapefile}'')\n \n # Merge the population data with the geopandas dataframe using admin1_code\n venezuela_gdf_merged = venezuela_gdf.merge(venezuela_population_by_admin1, left_on=''adm1_code'', right_on=''adm1_code'')\n \n # Plotting the map\n fig, ax = plt.subplots(1, 1, figsize=(10, 10))\n venezuela_gdf_merged.plot(column=''population'', ax=ax, legend=True,\n legend_kwds={''label'': ''Population by Admin1'',\n ''orientation'': ''horizontal''})\n ax.set_title(''Population by Admin1 in Venezuela'')\n \n # Remove axes for clarity\n ax.set_axis_off()\n plt.show()", "calling_code": "generate_population_map(''/mnt/data/'', ''/mnt/data/venezuela_admin1_shp'', ''/mnt/data/'', ''ven_admbnda_adm1.shp'')", "calling_code_run_status": "OK", "calling_code_run_time": "", "mem_type": "memory", "source": "Chat", "custom_id": 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you show a world map of overall risk by country with light gray outlines for all countries?','{"plan": "", "intent": "Plot a world map of overall risk by country with light gray outlines for all countries", "created": "2024-03-05T11:52:08.526423", "response_format": "None", "function_response_fields": "None", "response_text": "", "response_image": 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", "data_sources": "[]", "functions_code": "def plot_world_map(data):\n import geopandas as gpd\n import matplotlib.pyplot as plt\n\n # Load world shapefile data\n world = gpd.read_file(''world.shp'')\n\n # Merge world shapefile with risk data\n world_risk_data = world.merge(data, on=''country'')\n\n # Plotting the map\n fig, ax = plt.subplots(1, 1, figsize=(15, 10))\n world_risk_data.plot(column=''overall_risk'', ax=ax, legend=True,\n missing_kwds={''color'': ''lightgrey''},\n legend_kwds={''label'': ''Overall Risk by Country'', ''orientation'': ''horizontal''})\n ax.set_title(''World Map of Overall Risk by Country'')\n\n # Add light gray outlines for all countries, even if they have no risk data\n world.boundary.plot(color=''lightgray'', linewidth=1, ax=ax)\n\n # Remove axes for better clarity\n ax.set_axis_off()\n\n # Show the plot\n plt.show()", "calling_code": "import pandas as pd\n\n# Load the data\ndata = pd.read_csv(''risk_data.csv'')\n\n# Call the function\nplot_world_map(data)", "calling_code_run_status": "OK", "calling_code_run_time": "", "mem_type": "memory", "source": "Chat", "custom_id": "fc90fb06-eb2b-4fde-bc9c-476f5d97b191"}','fc90fb06-eb2b-4fde-bc9c-476f5d97b191','2514442c-0cd4-4e67-afe5-2cbd4645e750'), + 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is the population for Nigeria?','{"plan": "", "intent": "ask population of Nigeria", "created": "2024-03-06T17:38:09.159482", "response_format": "integer", "function_response_fields": ["nigeria_total_population"], "response_text": "The total population of Nigeria is approximately 204.91 million.", "response_image": "", "data_sources": "[''a__hdx_population.csv'']", "functions_code": "def get_nigeria_population(population_data_file: str, nigeria_code: str) -> int:", "calling_code": "population_data_file = ''/mnt/data/''\n\nget_nigeria_population(population_data_file, ''NGA'')", "calling_code_run_status": "OK", "calling_code_run_time": "", "mem_type": "memory", "source": "Chat", "custom_id": "4a2bb8f1-9bbf-4539-916a-bbd655ca702c"}','4a2bb8f1-9bbf-4539-916a-bbd655ca702c','e6b31bdb-c806-49f9-b691-5d804d0ad033'), + 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are the sources of the data in HDX datasets?','{"intent": "Retrieve information about the sources of the data in HDX datasets", "data_sources": ["HDX"], "top_function": {"name": "get_hdx_dataset", "parameters": {"hdx_id": {"type": "string", "description": "Filter the response by the dataset ID, which is a unique and fixed identifier of a Dataset on HDX. A URL in the pattern of `https://data.humdata.org/dataset/[dataset id]` will load the dataset page on HDX.{''type'': ''string'', ''maxLength'': 36, ''description'': ''Filter the response by the dataset ID, which is a unique and fixed identifier of a Dataset on HDX. A URL in the pattern of `https://data.humdata.org/dataset/[dataset id]` will load the dataset page on HDX.'', ''title'': ''Hdx Id''}"}, "hdx_stub": {"type": "string", "description": "Filter the response by the URL-safe name of the dataset as displayed on HDX. This name is unique but can change. A URL in the pattern of `https://data.humdata.org/dataset/[dataset name]` will load the dataset page on HDX.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by the URL-safe name of the dataset as displayed on HDX. This name is unique but can change. A URL in the pattern of `https://data.humdata.org/dataset/[dataset name]` will load the dataset page on HDX.'', ''title'': ''Hdx Stub''}"}, "title": {"type": "string", "description": "Filter the response by the title of the dataset as it appears in the HDX interface. This name is not unique and can change.{''type'': ''string'', ''maxLength'': 1024, ''description'': ''Filter the response by the title of the dataset as it appears in the HDX interface. This name is not unique and can change.'', ''title'': ''Title''}"}, "hdx_provider_stub": {"type": "string", "description": "Filter the response by the code of the provider of the dataset on HDX. A URL in the pattern of `https://data.humdata.org/organization/[org stub]` will load the provider''s page on HDX.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by the code of the provider of the dataset on HDX. A URL in the pattern of `https://data.humdata.org/organization/[org stub]` will load the provider''s page on HDX.'', ''title'': ''Hdx Provider Stub''}"}, "hdx_provider_name": {"type": "string", "description": "Filter the response by the display name of the provider of the dataset on HDX.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the display name of the provider of the dataset on HDX.'', ''title'': ''Hdx Provider Name''}"}, "output_format": {"type": "string", "description": "{''allOf'': [{''$ref'': ''#/components/schemas/OutputFormat''}], ''default'': ''json'', ''title'': ''Output Format''}"}, "limit": {"type": "integer", "description": "Maximum number of records to return. The system will not return more than 10,000 records.{''type'': ''integer'', ''maximum'': 10000, ''minimum'': 0, ''description'': ''Maximum number of records to return. The system will not return more than 10,000 records.'', ''default'': 10000, ''title'': ''Limit''}. An Example value for this parameter: ''1000''"}, "offset": {"type": "integer", "description": "Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.{''type'': ''integer'', ''minimum'': 0, ''description'': ''Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.'', ''default'': 0, ''title'': ''Offset''}"}}}, "functions_code": "\ndef get_hdx_dataset(**kwargs):\n return get_api_data(''https://stage.hapi-humdata-org.ahconu.org///api/dataset'',**kwargs)\n \n ", "source": "Generated from: https://stage.hapi-humdata-org.ahconu.org/openapi.json", "mem_type": "recipe", "created": "2024-01-31 19:22:48.255188", "response_format": "json", "function_response_fields": [{"name": "hdx_id", "type": "string"}, {"name": "hdx_stub", "type": "string"}, {"name": "title", "type": "string"}, {"name": "hdx_provider_stub", "type": "string"}, {"name": "hdx_provider_name", "type": "string"}, {"name": "hdx_link", "type": "string"}, {"name": "hdx_api_link", "type": "string"}], "calling_code_run_status": "OK", "calling_code_run_time": 0, "response_image": "", "calling_code": "", "custom_id": "cc76cd55-5cb5-455d-becb-5090075ec2ad"}','cc76cd55-5cb5-455d-becb-5090075ec2ad','63037678-9f2a-43fd-a658-3b6c80fc002c'), + 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you show a visualization of the data on a map with specified administrative boundaries and save it as a PNG file?','{"intent": "Plot data on a map with specified administrative boundaries and save the plot as a PNG file", "data_sources": ["HDX"], "top_function": {"name": "plot_data_on_map", "parameters": {"title": {"type": "string", "description": "Title to put on the plot. This mandatory. Should be something like ''Mean of Mali by state''"}, "country": {"type": "string", "description": "Country name to get administrative boundaries geojson for"}, "data": {"type": "string", "description": "The data to be plotted on a map, as a list of dictionaries. Each record should look like this ...\n [\n {\n \"pcode\": \"ML0102\",\n \"metric\": 10000\n },\n {\n \"pcode\": \"ML0103\",\n \"metric\": 20000\n }\n ]\n\n IMPORTANT: each item in the list MUST have fields ''pcode'' and ''metric''\n "}, "admin_level": {"type": "string", "description": "The administration level to get boundaries for, ranging from 1-2"}}}, "functions_code": "def plot_data_on_map(title, data, country, admin_level):\n\n admin_level = admin_level.replace(\"admin\",\"\")\n\n # convert list of json records to dataframe\n data = json.loads(data)\n data = pd.DataFrame.from_records(data)\n print(data.head())\n\n # Read shapefile\n shape_file_location = get_shapefile(country,admin_level)\n shape_file_location = shape_file_location[''file_location'']\n print(shape_file_location)\n\n # Read shapefile\n gdf = gpd.read_file(shape_file_location)\n print(gdf.head())\n #gdf.to_excel(''mali_adm1.xlsx'')\n\n print(f''ADM{admin_level}_PCODE'')\n print(len(gdf[f''ADM{admin_level}_PCODE'']))\n\n # Merge shapefile and population data\n merged = gdf.merge(data, left_on=f''ADM{admin_level}_PCODE'', right_on=''pcode'')\n print(merged.head())\n\n # Plot population data\n fig, ax = plt.subplots(1, figsize=(10, 6))\n ax.axis(''off'')\n ax.set_title(title, fontdict={''fontsize'': ''25'', ''fontweight'' : ''3''})\n merged.plot(column=''metric'', cmap=''Blues'', linewidth=0.8, ax=ax, edgecolor=''0.8'', legend=True)\n #plt.show()\n\n # Save plot to file\n plot_location = f''./data/{country}_adm{admin_level}.png''\n fig.savefig(plot_location, dpi=300)\n\n response = {\n \"file_location\": plot_location\n }\n\n return response\n", "source": "Hardcoded", "mem_type": "helper_function", "created": "2024-01-31 19:22:20.726287", "response_format": "file_location", "function_response_fields": {"name": "file_location", "type": "string"}, "calling_code_run_status": "OK", "calling_code_run_time": 0, "response_image": "", "calling_code": "", 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you provide me with the shape file location for a specific country and administrative level?','{"intent": "Get shape file location for a specific country and admin level", "data_sources": ["HDX"], "top_function": {"name": "get_shapefile", "parameters": {"admin_level": {"description": "Administrative region level", "type": "string", "enum": ["admin1", "admin2"]}, "country": {"description": "Country name", "type": "string"}}}, "functions_code": "def get_shapefile(country, admin_level):\n\n admin_level = admin_level.replace(\"admin\",\"\")\n\n country_code = get_country_code(country)\n\n download_shapefiles(country_code)\n\n shape_file_location = f\"{data_dir}/{country_code}/gadm{ver}_{country_code}_{admin_level}.shp\"\n\n response = {\n \"file_location\": shape_file_location\n }\n\n return response\n\n # Using HDX, but seems to be missing some SHP files\n # Search for shapefiles for the specified country\n #Configuration.create(hdx_site=''prod'', user_agent=''A_Quick_Example'', hdx_read_only=True)\n #datasets = Dataset.search_in_hdx(f''cod shapefile {country} administrative boundaries'')\n #shape_dataset = f''cod-ab-{country_code.lower()}''\n ## Iterate over the results and download the shapefiles\n #for dataset in datasets:\n # if dataset[''name''] == shape_dataset:\n # print(dataset[''name''])\n # resources = dataset.get_resources()\n # for resource in resources:\n # print(resource[''name''], resource[''format''])\n # if ''SHP'' in resource[''format''].lower():\n # url, path = resource.download()\n # print(f''Shapefile downloaded from {url} and saved to {path}'')\n", "source": "Hardcoded", "mem_type": "recipe", "created": "2024-01-31 19:22:23.265929", "response_format": "file_location", "function_response_fields": [{"name": "file_location", "type": "string"}], "calling_code_run_status": "OK", "calling_code_run_time": 0, "response_image": "", "calling_code": "", "custom_id": 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you show a bar chart of the population for Mali by admin 1?','{"plan": "", "intent": "Generate a bar chart of the population in Mali by admin 1", "created": "2024-03-05T02:57:18.017647", "response_format": "None", "function_response_fields": "-", "response_text": "", "response_image": 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"data_sources": "[''d__hdx_population.csv'']", "functions_code": "def generate_population_chart(data_file):\n import pandas as pd\n import matplotlib.pyplot as plt\n\n # Read the Mali population data\n population_df = pd.read_csv(data_file)\n\n # Filter the population data for Mali (adm0_code for Mali is \"MLI\")\n mali_population_df = population_df[population_df[''adm0_code''] == ''MLI'']\n\n # Group the population by admin1_code and sum up to get the total population per admin1\n mali_population_by_admin1 = mali_population_df.groupby(''adm1_code'')[''population''].sum().reset_index()\n\n # Get admin1 names for labels\n mali_population_by_admin1 = mali_population_by_admin1.merge(\n mali_population_df[[''adm1_code'', ''admin1_name'']].drop_duplicates(),\n on=''adm1_code''\n )\n\n # Sort values for better visualization\n mali_population_by_admin1_sorted = mali_population_by_admin1.sort_values(by=''population'', ascending=False)\n\n # Plotting the bar chart\n plt.figure(figsize=(10, 8))\n plt.bar(mali_population_by_admin1_sorted[''admin1_name''], mali_population_by_admin1_sorted[''population''], color=''skyblue'')\n plt.xlabel(''Admin1'')\n plt.ylabel(''Population'')\n plt.title(''Population in Mali by Admin 1'')\n plt.xticks(rotation=90)\n plt.tight_layout() # To ensure labels are not cut off\n plt.show()", "calling_code": "file_path = ''/mnt/data/''\ngenerate_population_chart(file_path)", "calling_code_run_status": "OK", "calling_code_run_time": "", "mem_type": "memory", "source": "Chat", "custom_id": "fd2a2e10-55e4-4e65-9cad-bfc666a0e4a4"}','fd2a2e10-55e4-4e65-9cad-bfc666a0e4a4','5cd81b4c-743f-43a2-a3ba-8a774ba74fc0'); +INSERT INTO public.langchain_pg_embedding (collection_id,embedding,"document",cmetadata,custom_id,uuid) VALUES + 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you show a visualization of population by admin1 in Mali?','{"plan": "", "intent": "Generate a map of population by admin1 in Mali", "created": "2024-03-05T03:01:37.412938", "response_format": "None", "function_response_fields": "None", "response_text": "", "response_image": 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", "data_sources": "[''d__geoBoundaries-adm1-countries_a-z.zip'', ''d__hdx_population.csv'']", "functions_code": "def generate_population_map(population_data_file, zip_file_location, unzip_folder, shape_file):\n import geopandas as gpd\n import zipfile\n import os\n import pandas as pd\n import matplotlib.pyplot as plt\n\n # Unzipping the admin level 1 boundaries\n with zipfile.ZipFile(zip_file_location, ''r'') as zip_ref:\n zip_ref.extractall(unzip_folder)\n\n # Load Mali''s shapefile\n mli_adm1_gdf = gpd.read_file(f''{unzip_folder}/{shape_file}'')\n\n # Read and filter the population data for Mali\n population_df = pd.read_csv(population_data_file)\n mali_population_df = population_df[population_df[''adm0_code''] == ''MLI'']\n\n # Group the population by admin1_code to get the total population per admin1\n mali_population_by_admin1 = mali_population_df.groupby(''adm1_code'')[''population''].sum().reset_index()\n\n # Merge the population data with the geopandas dataframe using admin1_code\n mli_adm1_gdf_merged = mli_adm1_gdf.merge(mali_population_by_admin1, left_on=''adm1_code'', right_on=''adm1_code'')\n\n # Plotting the map\n fig, ax = plt.subplots(1, 1, figsize=(10, 10))\n mli_adm1_gdf_merged.plot(column=''population'', ax=ax, legend=True, \n legend_kwds={''label'': ''Population by Admin1'', \n ''orientation'': ''horizontal''})\n ax.set_title(''Population by Admin1 in Mali'')\n\n # Remove axes for clarity\n ax.set_axis_off()\n\n plt.show()\n", "calling_code": "generate_population_map(''/mnt/data/'', ''/mnt/data/'', ''/mnt/data/geoBoundaries_MLI_adm1'', ''mli_admbnda_adm1.shp'')", "calling_code_run_status": "OK", "calling_code_run_time": "", "mem_type": "memory", "source": "Chat", "custom_id": "4e96b3e9-b9b6-4a17-9355-a92be6a6d3a0"}','4e96b3e9-b9b6-4a17-9355-a92be6a6d3a0','b8086e4b-e4e2-4f0a-bf98-b26adc36b6dc'), + 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you show a map of food security at the administrative level 2 in Chad?','{"created": "2024-03-05T08:12:33.202691", "source": "Chat", "response_format": "image", "calling_code_run_status": "OK", "functions_code": "def generate_food_security_map(food_security_data_file, shapefile_zip_file, shapefile_extract_folder):\n import pandas as pd\n import geopandas as gpd\n import matplotlib.pyplot as plt\n import zipfile\n\n # Read the food security data\n food_security_df = pd.read_csv(food_security_data_file)\n\n # Filter the data for Chad\n chad_food_security_df = food_security_df[food_security_df[''adm0_code''] == ''TCD'']\n\n # Unzipping the admin level 2 boundaries for Chad\n with zipfile.ZipFile(shapefile_zip_file, ''r'') as zip_ref:\n zip_ref.extractall(shapefile_extract_folder)\n\n # Find Chad shapefile for admin level 2 in the unzipped folder\n chad_shapefile = ''tcd_admbnda_adm2.shp''\n\n # Load Chad''s shapefile using GeoPandas\n chad_gdf = gpd.read_file(f''{shapefile_extract_folder}/{chad_shapefile}'')\n\n # Group the food security data by adm2_code\n chad_food_security_by_adm2 = chad_food_security_df.groupby(''adm2_code'').agg({\n ''population_in_phase'': ''sum'',\n ''population_fraction_in_phase'': ''mean'' # We use mean to get an average fraction\n }).reset_index()\n\n # Merge the food security data with the geopandas dataframe using adm2_code\n chad_gdf_merged = chad_gdf.merge(chad_food_security_by_adm2, on=''adm2_code'')\n\n # Plotting the map\n fig, ax = plt.subplots(1, 1, figsize=(12, 12))\n chad_gdf_merged.plot(column=''population_fraction_in_phase'', ax=ax, legend=True,\n legend_kwds={''label'': ''Population Fraction in IPC Phase'',\n ''orientation'': ''horizontal''})\n ax.set_title(''Food Security IPC Phases Fraction in Chad by Admin2'')\n\n # Remove axes for clarity\n ax.set_axis_off()\n\n plt.show()", "intent": "Generate an administrative level 2 map of food security in Chad ", "mem_type": "memory", "response_text": "", "function_response_fields": "[]", "calling_code": "generate_food_security_map(''/mnt/data/'', ''/mnt/data/'', ''/mnt/data/shp_chad_adm2'')", "data_sources": "[''a__hdx_food_security.csv'', ''a__geoBoundaries-adm2-countries_i-z.zip'']", "response_image": 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is the list of organizations represented in the data available in HAPI?','{"intent": "Retrieve a list of organizations represented in the data available in HAPI", "data_sources": ["HDX"], "top_function": {"name": "get_hdx_org", "parameters": {"acronym": {"type": "string", "description": "Filter the response by the standard acronym used to represent the organization. When data is brought into the HAPI database, an attempt is made to standardize the acronyms.{''type'': ''string'', ''maxLength'': 32, ''description'': ''Filter the response by the standard acronym used to represent the organization. When data is brought into the HAPI database, an attempt is made to standardize the acronyms.'', ''title'': ''Acronym''}. An Example value for this parameter: ''unhcr''"}, "name": {"type": "string", "description": "Filter the response by the standard name used to represent the organization. When data is brought into the HAPI database, an attempt is made to standardize the acronyms.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the standard name used to represent the organization. When data is brought into the HAPI database, an attempt is made to standardize the acronyms.'', ''title'': ''Name''}. An Example value for this parameter: ''United Nations High Commissioner for Refugees''"}, "org_type_code": {"type": "string", "description": "Filter the response by the organization type code.{''type'': ''string'', ''maxLength'': 32, ''description'': ''Filter the response by the organization type code.'', ''title'': ''Org Type Code''}"}, "org_type_description": {"type": "string", "description": "Filter the response by the organization type description. See the org type endpoint for details.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the organization type description. See the org type endpoint for details.'', ''title'': ''Org Type Description''}"}, "output_format": {"type": "string", "description": "{''allOf'': [{''$ref'': ''#/components/schemas/OutputFormat''}], ''default'': ''json'', ''title'': ''Output Format''}"}, "limit": {"type": "integer", "description": "Maximum number of records to return. The system will not return more than 10,000 records.{''type'': ''integer'', ''maximum'': 10000, ''minimum'': 0, ''description'': ''Maximum number of records to return. The system will not return more than 10,000 records.'', ''default'': 10000, ''title'': ''Limit''}. An Example value for this parameter: ''1000''"}, "offset": {"type": "integer", "description": "Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.{''type'': ''integer'', ''minimum'': 0, ''description'': ''Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.'', ''default'': 0, ''title'': ''Offset''}"}}}, "functions_code": "\ndef get_hdx_org(**kwargs):\n return get_api_data(''https://stage.hapi-humdata-org.ahconu.org///api/org'',**kwargs)\n \n ", "source": "Generated from: https://stage.hapi-humdata-org.ahconu.org/openapi.json", "mem_type": "recipe", "created": "2024-01-31 19:22:36.871503", "response_format": "json", "function_response_fields": [{"name": "acronym", "type": "string"}, {"name": "name", "type": "string"}], "calling_code_run_status": "OK", "calling_code_run_time": 0, "response_image": "", "calling_code": "", "custom_id": "a019d5ae-81aa-4957-8280-6ecc3e78d472"}','a019d5ae-81aa-4957-8280-6ecc3e78d472','d1f24fe1-d85b-4309-870a-7cbe9a35e8e0'), + 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is the list of locations included in HAPI?','{"intent": "Retrieve the list of locations included in HAPI", "data_sources": ["HDX"], "top_function": {"name": "get_hdx_location", "parameters": {"code": {"type": "string", "description": "Filter the response by a location (typically a country). The location codes use the ISO-3 (ISO 3166 alpha-3) codes.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by a location (typically a country). The location codes use the ISO-3 (ISO 3166 alpha-3) codes.'', ''title'': ''Code''}"}, "name": {"type": "string", "description": "Filter the response by a location (typically a country). The location names are based on the ''short name'' from the UN M49 Standard.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by a location (typically a country). The location names are based on the ''short name'' from the UN M49 Standard.'', ''title'': ''Name''}"}, "output_format": {"type": "string", "description": "{''allOf'': [{''$ref'': ''#/components/schemas/OutputFormat''}], ''default'': ''json'', ''title'': ''Output Format''}"}, "limit": {"type": "integer", "description": "Maximum number of records to return. The system will not return more than 10,000 records.{''type'': ''integer'', ''maximum'': 10000, ''minimum'': 0, ''description'': ''Maximum number of records to return. The system will not return more than 10,000 records.'', ''default'': 10000, ''title'': ''Limit''}. An Example value for this parameter: ''1000''"}, "offset": {"type": "integer", "description": "Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.{''type'': ''integer'', ''minimum'': 0, ''description'': ''Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.'', ''default'': 0, ''title'': ''Offset''}"}}}, "functions_code": "\ndef get_hdx_location(**kwargs):\n return get_api_data(''https://stage.hapi-humdata-org.ahconu.org///api/location'',**kwargs)\n \n ", "source": "Generated from: https://stage.hapi-humdata-org.ahconu.org/openapi.json", "mem_type": "recipe", "created": "2024-01-31 19:22:30.573274", "response_format": "json", "function_response_fields": [{"name": "code", "type": "string"}, {"name": "name", "type": "string"}], "calling_code_run_status": "OK", "calling_code_run_time": 0, "response_image": "", "calling_code": "", "custom_id": "3ce37c7e-1e62-461a-b18a-a3a89c5c68b8"}','3ce37c7e-1e62-461a-b18a-a3a89c5c68b8','605546c6-03d3-41b4-a533-588f9d1517c0'), + 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is the list of first-level subnational administrative divisions available in HAPI?','{"intent": "Retrieve the list of first-level subnational administrative divisions available in HAPI", "data_sources": ["HDX"], "top_function": {"name": "get_hdx_admin1", "parameters": {"code": {"type": "string", "description": "Filter the response by the 1st subnational administrative divisions. The admin1 codes refer to the p-codes in the Common Operational Datasets.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by the 1st subnational administrative divisions. The admin1 codes refer to the p-codes in the Common Operational Datasets.'', ''title'': ''Code''}"}, "name": {"type": "string", "description": "Filter the response by the 1st subnational administrative divisions. The admin1 names refer to the Common Operational Datasets.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the 1st subnational administrative divisions. The admin1 names refer to the Common Operational Datasets.'', ''title'': ''Name''}"}, "location_code": {"type": "string", "description": "Filter the response by a location (typically a country). The location codes use the ISO-3 (ISO 3166 alpha-3) codes. See the location endpoint for details.{''type'': ''string'', ''maxLength'': 128, ''description'': ''Filter the response by a location (typically a country). The location codes use the ISO-3 (ISO 3166 alpha-3) codes. See the location endpoint for details.'', ''title'': ''Location Code''}"}, "location_name": {"type": "string", "description": "Filter the response by a location (typically a country). The location names are based on the ''short name'' from the UN M49 Standard. See the location endpoint for details.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by a location (typically a country). The location names are based on the ''short name'' from the UN M49 Standard. See the location endpoint for details.'', ''title'': ''Location Name''}"}, "output_format": {"type": "string", "description": "{''allOf'': [{''$ref'': ''#/components/schemas/OutputFormat''}], ''default'': ''json'', ''title'': ''Output Format''}"}, "limit": {"type": "integer", "description": "Maximum number of records to return. The system will not return more than 10,000 records.{''type'': ''integer'', ''maximum'': 10000, ''minimum'': 0, ''description'': ''Maximum number of records to return. The system will not return more than 10,000 records.'', ''default'': 10000, ''title'': ''Limit''}. An Example value for this parameter: ''1000''"}, "offset": {"type": "integer", "description": "Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.{''type'': ''integer'', ''minimum'': 0, ''description'': ''Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.'', ''default'': 0, ''title'': ''Offset''}"}}}, "functions_code": "\ndef get_hdx_admin1(**kwargs):\n return get_api_data(''https://stage.hapi-humdata-org.ahconu.org///api/admin1'',**kwargs)\n \n ", "source": "Generated from: https://stage.hapi-humdata-org.ahconu.org/openapi.json", "mem_type": "recipe", "created": "2024-01-31 19:22:33.193684", "response_format": "json", "function_response_fields": [{"name": "code", "type": "string"}, {"name": "name", "type": "string"}, {"name": "location_code", "type": "string"}, {"name": "location_name", "type": "string"}], "calling_code_run_status": "OK", "calling_code_run_time": 0, "response_image": "", "calling_code": "", "custom_id": "d4f13b42-d300-41ba-bc28-01cd02640fc5"}','d4f13b42-d300-41ba-bc28-01cd02640fc5','762fc007-b47f-43c4-897f-b24983d1fdba'), + 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are the impacts of humanitarian response activities on [subject/topic] according to recent data?','{"intent": "Retrieve information about how humanitarian response activities are classified", "data_sources": ["HDX"], "top_function": {"name": "get_hdx_sector", "parameters": {"code": {"type": "string", "description": "Filter the response by the sector code.{''type'': ''string'', ''maxLength'': 32, ''description'': ''Filter the response by the sector code.'', ''title'': ''Code''}. An Example value for this parameter: ''hea''"}, "name": {"type": "string", "description": "Filter the response by the sector name.{''type'': ''string'', ''maxLength'': 512, ''description'': ''Filter the response by the sector name.'', ''title'': ''Name''}. An Example value for this parameter: ''Health''"}, "output_format": {"type": "string", "description": "{''allOf'': [{''$ref'': ''#/components/schemas/OutputFormat''}], ''default'': ''json'', ''title'': ''Output Format''}"}, "limit": {"type": "integer", "description": "Maximum number of records to return. The system will not return more than 10,000 records.{''type'': ''integer'', ''maximum'': 10000, ''minimum'': 0, ''description'': ''Maximum number of records to return. The system will not return more than 10,000 records.'', ''default'': 10000, ''title'': ''Limit''}. An Example value for this parameter: ''1000''"}, "offset": {"type": "integer", "description": "Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.{''type'': ''integer'', ''minimum'': 0, ''description'': ''Number of records to skip in the response. Use in conjunction with the limit parameter to paginate.'', ''default'': 0, ''title'': ''Offset''}"}}}, "functions_code": "\ndef get_hdx_sector(**kwargs):\n return get_api_data(''https://stage.hapi-humdata-org.ahconu.org///api/sector'',**kwargs)\n \n ", "source": "Generated from: https://stage.hapi-humdata-org.ahconu.org/openapi.json", "mem_type": "recipe", "created": "2024-01-31 19:22:41.525873", "response_format": "json", "function_response_fields": [{"name": "code", "type": "string"}, {"name": "name", "type": "string"}], "calling_code_run_status": "OK", "calling_code_run_time": 0, "response_image": "", "calling_code": "", "custom_id": "d47bda9b-f2a9-4aee-afc0-5abc1af4d683"}','d47bda9b-f2a9-4aee-afc0-5abc1af4d683','316de944-c868-4753-888b-33006a1087ad'), + 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is the total population for Mali?','{"plan": "", "intent": "Calculate the total population of Mali", "created": "2024-03-05T17:44:15.629341", "response_format": "integer", "function_response_fields": "total_population", "response_text": "The total population of Mali is 17,839,995.", "response_image": "", "data_sources": "[''a__hdx_population.csv'']", "functions_code": "def calculate_total_population(file_location):\n import pandas as pd\n population_df = pd.read_csv(file_location)\n mali_population_df = population_df[population_df[''adm0_code''] == ''MLI'']\n total_population_mali = mali_population_df[''population''].sum()\n return total_population_mali", "calling_code": "file_location = ''/mnt/data/''\ntotal_population = calculate_total_population(file_location)", "calling_code_run_status": "OK", "calling_code_run_time": "", "mem_type": "memory", "source": "Chat", "custom_id": "56b2a765-ea30-4ab9-b49e-73b5c9f81da0"}','56b2a765-ea30-4ab9-b49e-73b5c9f81da0','a2671181-214b-4806-a8fb-461ea9285f2c'); diff --git a/docker-compose.yml b/docker-compose.yml index b20c19d4..bae0ff16 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -64,12 +64,31 @@ services: #platform: linux/amd64 image: ankane/pgvector:latest environment: - POSTGRES_DB: mydatabase - POSTGRES_USER: myuser - POSTGRES_PASSWORD: mypassword + POSTGRES_DB: ${POSTGRES_DB} + POSTGRES_USER: ${POSTGRES_USER} + POSTGRES_PASSWORD: ${POSTGRES_PASSWORD} restart: always + ports: + - 5432:5432 volumes: - ./ui/recipes_assistant_chat/pgdata2:/var/lib/postgresql/data + env_file: + - .env + data_recipe_db: + #platform: linux/amd64 + image: ankane/pgvector:latest + container_name: datarecipes + environment: + POSTGRES_DB: ${POSTGRES_RECIPE_DB} + POSTGRES_USER: ${POSTGRES_RECIPE_USER} + POSTGRES_PASSWORD: ${POSTGRES_RECIPE_PASSWORD} + restart: always + ports: + - 5439:5432 + volumes: + - ./actions/actions_plugins/recipe-server/db/:/docker-entrypoint-initdb.d + env_file: + - .env rag-api: #platform: linux/amd64 image: ghcr.io/danny-avila/librechat-rag-api-dev-lite:latest From 2571ee04cf3289762a74a31908cb036e7336a4f7 Mon Sep 17 00:00:00 2001 From: JanPeterDatakind Date: Fri, 26 Apr 2024 17:10:58 -0400 Subject: [PATCH 02/20] Added get memory action --- .vscode/settings.json | 3 + actions/Dockerfile | 4 +- .../postgres-universal/actions.py | 68 ++- .../actions_plugins/recipe-server/README.md | 77 ++++ .../actions_plugins/recipe-server/actions.py | 435 ++++++++++++++++++ .../recipe-server/package.yaml | 29 ++ actions/devdata/input_get_memory.json | 4 + actions/package.yaml | 5 + docker-compose.yml | 3 + 9 files changed, 603 insertions(+), 25 deletions(-) create mode 100644 .vscode/settings.json create mode 100644 actions/actions_plugins/recipe-server/README.md create mode 100644 actions/actions_plugins/recipe-server/actions.py create mode 100644 actions/actions_plugins/recipe-server/package.yaml create mode 100644 actions/devdata/input_get_memory.json diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 00000000..677e64ca --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,3 @@ +{ + "python.terminal.activateEnvironment": false +} \ No newline at end of file diff --git a/actions/Dockerfile b/actions/Dockerfile index 1fa0eafd..e15b88a7 100644 --- a/actions/Dockerfile +++ b/actions/Dockerfile @@ -38,9 +38,11 @@ ENV DATA_DB_CONN_STRING=$DATA_DB_CONN_STRING # RUN action-server import --datadir=/action-server/datadir # Load individually RUN action-server import --dir=./actions_plugins/postgres-universal --datadir=/action-server/datadir +RUN action-server import --dir=./actions_plugins/recipe-server --datadir=/action-server/datadir RUN echo "{\"dsn\": \"$DATA_DB_CONN_STRING\"}" > ./actions_plugins/postgres-universal/postgres_connection.json EXPOSE 8080 -CMD ["/usr/bin/supervisord"] \ No newline at end of file +CMD ["/usr/bin/supervisord"] +#CMD ["python", "./actions_plugins/postgres-universal/main.py", "--dsn", "$DATA_DB_CONN_STRING] \ No newline at end of file diff --git a/actions/actions_plugins/postgres-universal/actions.py b/actions/actions_plugins/postgres-universal/actions.py index 2eb254ff..28a5f274 100644 --- a/actions/actions_plugins/postgres-universal/actions.py +++ b/actions/actions_plugins/postgres-universal/actions.py @@ -3,10 +3,11 @@ import psycopg2 from robocorp.actions import action -CONNECTION_FILE_PATH = 'postgres_connection.json' +CONNECTION_FILE_PATH = "postgres_connection.json" MAX_CHARS_TOT = 10000 + class ReadOnlyConnection: def __init__(self, conn_params): self.conn_params = conn_params @@ -24,26 +25,33 @@ def __exit__(self, exc_type, exc_val, exc_tb): self.conn.close() -def truncate_output_with_beginning_clue(output: str, max_chars: int = MAX_CHARS_TOT) -> str: - beginning_clue = "[Cut] " # A very short clue at the beginning to indicate possible truncation +def truncate_output_with_beginning_clue( + output: str, max_chars: int = MAX_CHARS_TOT +) -> str: + beginning_clue = ( + "[Cut] " # A very short clue at the beginning to indicate possible truncation + ) if len(output) > max_chars: - truncated_output = output[:max_chars - len(beginning_clue)] + truncated_output = output[: max_chars - len(beginning_clue)] chars_missed = len(output) - len(truncated_output) truncated_message = f"[+{chars_missed}]" return beginning_clue + truncated_output + truncated_message else: return output + def get_database_schema(conn): schema_info = "Database Schema:\n" with conn.cursor() as cursor: # Retrieve triggers - cursor.execute(""" + cursor.execute( + """ SELECT event_object_table AS table_name, trigger_name FROM information_schema.triggers - """) + """ + ) trigger_records = cursor.fetchall() table_trigger_dict = {} @@ -55,11 +63,13 @@ def get_database_schema(conn): table_trigger_dict[table_name].append(trigger_name) # Retrieve tables - cursor.execute(""" + cursor.execute( + """ SELECT table_name FROM information_schema.tables WHERE table_schema = 'public' - """) + """ + ) tables = cursor.fetchall() for table in tables: @@ -67,14 +77,19 @@ def get_database_schema(conn): schema_info += f"\nTable: {table_name}\n" if table_name in table_trigger_dict.keys(): - schema_info += f"Triggers: {', '.join(table_trigger_dict[table_name])}\n" - + schema_info += ( + f"Triggers: {', '.join(table_trigger_dict[table_name])}\n" + ) + # Get columns and primary key info - cursor.execute(""" + cursor.execute( + """ SELECT column_name, data_type, is_nullable, column_default FROM information_schema.columns WHERE table_name = %s - """, (table_name,)) + """, + (table_name,), + ) columns = cursor.fetchall() for col in columns: @@ -85,17 +100,21 @@ def get_database_schema(conn): schema_info += "\n" # Get primary key info - cursor.execute(""" + cursor.execute( + """ SELECT kcu.column_name FROM information_schema.table_constraints tc JOIN information_schema.key_column_usage kcu ON tc.constraint_name = kcu.constraint_name WHERE tc.table_name = %s AND tc.constraint_type = 'PRIMARY KEY' - """, (table_name,)) + """, + (table_name,), + ) primary_keys = cursor.fetchall() # Get foreign key info - cursor.execute(""" + cursor.execute( + """ SELECT kcu.column_name, ccu.table_name AS foreign_table_name, ccu.column_name AS foreign_column_name FROM information_schema.table_constraints AS tc JOIN information_schema.key_column_usage AS kcu @@ -103,7 +122,9 @@ def get_database_schema(conn): JOIN information_schema.constraint_column_usage AS ccu ON ccu.constraint_name = tc.constraint_name WHERE tc.table_name = %s AND tc.constraint_type = 'FOREIGN KEY' - """, (table_name,)) + """, + (table_name,), + ) foreign_keys = cursor.fetchall() for pk in primary_keys: @@ -114,7 +135,7 @@ def get_database_schema(conn): return schema_info -def truncate_query_results(results, max_chars = MAX_CHARS_TOT): +def truncate_query_results(results, max_chars=MAX_CHARS_TOT): if not results: return "" @@ -142,7 +163,7 @@ def truncate_query_results(results, max_chars = MAX_CHARS_TOT): cell_output = str(cell) # Truncate cell if necessary if len(cell_output) > cell_max: - cell_output = cell_output[:cell_max - 3] + "..." + cell_output = cell_output[: cell_max - 3] + "..." row_output += cell_output + ", " # Remove last comma and space, add newline @@ -151,13 +172,12 @@ def truncate_query_results(results, max_chars = MAX_CHARS_TOT): # Check if we've reached the max characters if len(truncated_output) >= max_chars: # Further truncate and end the loop - truncated_output = truncated_output[:max_chars - 3] + "..." + truncated_output = truncated_output[: max_chars - 3] + "..." break return truncated_output - @action def init_postgres_connection(dsn: str) -> str: """ @@ -170,11 +190,11 @@ def init_postgres_connection(dsn: str) -> str: Returns: str: A textual representation of the database schema. """ - conn_params = {'dsn': dsn} + conn_params = {"dsn": dsn} # Save connection parameters to a file try: - with open(CONNECTION_FILE_PATH, 'w') as file: + with open(CONNECTION_FILE_PATH, "w") as file: json.dump(conn_params, file) with ReadOnlyConnection(conn_params) as conn: schema = get_database_schema(conn) @@ -182,6 +202,7 @@ def init_postgres_connection(dsn: str) -> str: except Exception as e: return f"Failed: {e}" + @action def execute_query(query: str) -> str: """ @@ -196,7 +217,7 @@ def execute_query(query: str) -> str: try: # Read connection parameters from the file if os.path.exists(CONNECTION_FILE_PATH): - with open(CONNECTION_FILE_PATH, 'r') as file: + with open(CONNECTION_FILE_PATH, "r") as file: conn_params = json.load(file) else: return "Connection parameters file not found." @@ -208,4 +229,3 @@ def execute_query(query: str) -> str: return truncate_query_results(results) except Exception as e: return f"An error occurred while executing the query: {e}" - diff --git a/actions/actions_plugins/recipe-server/README.md b/actions/actions_plugins/recipe-server/README.md new file mode 100644 index 00000000..acfc8d37 --- /dev/null +++ b/actions/actions_plugins/recipe-server/README.md @@ -0,0 +1,77 @@ +# Recipe Server Actions + +## Overview +This example simplifies interactions with PostgreSQL databases by allowing users to perform queries through +conversational inputs translated by Large Language Models (LLMs), like OpenAI's GPT. +It focuses on read-only operations to ensure security and prevent unintended data modifications. + +## Key Features +- **Simplified Database Queries**: Execute SQL queries using conversational language without deep SQL knowledge. +- **Secure Read-Only Operations**: Ensures database integrity by restricting actions to read-only transactions. +- **Integration with LLMs**: Designed for seamless integration with LLMs, enabling a conversational interface for database management. + +## Example Use Case: Querying Sales Data + +### Scenario +Imagine you're a sales manager looking to quickly find out this month's top-performing products without writing complex SQL queries. + +### How This Package Helps +Our actions allow you to simply ask, "What are the top-selling products this month?" and handle the rest, fetching and presenting the data in an understandable format. + +### Process +1. **Initiate a Query**: Start by expressing your query through a conversational interface powered by OpenAI's GPT. +2. **Behind-the-Scenes Action**: The system translates your input into a SQL query and fetches the relevant data from your PostgreSQL database. +3. **Data Presentation**: You receive a concise response with the query results, allowing for quick insights without needing to interpret complex data or SQL results. + +## Getting Started + +### Prerequisites +- Access to a PostgreSQL database +- Access to OpenAI's GPT for conversational interfaces + +### Installation +1. Clone this example from this repository to your local machine. + +### Running the Server +Expose the action server to enable integration with external services: +```bash +action-server start --expose +``` + +## Usage + +### Initialize Connection + +To securely establish a connection to your PostgreSQL database, replace `username`, `password`, +`host`, `port`, and `database` with your actual database details: + +**dsn:** `postgresql://username:password@host:port/database` + +To do this securely, go to your Action Server UI http://localhost:8080 and execute the `init_postgres_connection` there. Copy the output from the execution to copy later for LLM use. + +**NOTE:** You can optionally also do this through LLM, but that will reveal the exact connection info to the LLM. + +This action configures the connection and provides a schema overview for LLM to use. + +NOTE: For the dataKind build, I added the creation of the connection file so the end point does not need to be callled. + +### Execute Query +Use OpenAI's GPT to formulate and send your queries. The `execute_query` action will interpret these inputs and perform the necessary SQL queries in a read-only manner. + +## Security and Read-Only Operations +This project prioritizes data integrity, exclusively allowing read-only access to prevent accidental modifications. Our secure approach ensures that your database remains intact while facilitating meaningful data analysis and interaction. + +## Integrating with OpenAI's GPT +To use this project with OpenAI's GPT: + +1. **Configure your Action Server**: Ensure your action server is running and exposed. +2. **Connect to OpenAI's GPT**: Use the public URL and API Authorization Bearer key from your action server to set up the connection in OpenAI's platform. +3. **Create Custom Conversations**: In the GPT editor, set up custom prompts that trigger the actions provided by this server, enabling a seamless conversational interface for database queries. + +### Benefits +- **Accessibility**: Makes database interactions intuitive and accessible for everyone, regardless of their SQL proficiency. +- **Security**: Maintains data safety with strict read-only access. +- **Integration**: Offers straightforward integration with LLMs like OpenAI's GPT, enhancing the user experience through natural language processing. + +By enabling direct, conversational access to PostgreSQL databases, this example democratizes data analysis, +making it accessible and secure for a wide range of users. diff --git a/actions/actions_plugins/recipe-server/actions.py b/actions/actions_plugins/recipe-server/actions.py new file mode 100644 index 00000000..aa2f250b --- /dev/null +++ b/actions/actions_plugins/recipe-server/actions.py @@ -0,0 +1,435 @@ +import ast +import json +import logging +import sys +import os + +from langchain.schema import HumanMessage, SystemMessage +from langchain_community.vectorstores.pgvector import PGVector +from langchain_openai import ( + AzureChatOpenAI, + AzureOpenAIEmbeddings, + ChatOpenAI, + OpenAIEmbeddings, +) +from robocorp.actions import action +from dotenv import load_dotenv + +# Load environment variables from .env file +load_dotenv() + +# Lower numbers are more similar +similarity_cutoff = {"memory": 0.2, "recipe": 0.3, "helper_function": 0.1} + +response_formats = [ + "csv", + "dataframe", + "json", + "file_location", + "integer", + "float", + "string", +] + +prompt_map = { + "memory": """ + You judge matches of user intent with those stored in a database to decide if they are true matches of intent. + When asked to compare two intents, check they are the same, have the same entities and would result in the same outcome. + Be very strict in your judgement. If you are not sure, say no. + A plotting intent is different from a request for just the data. + Intents to generate plots must have the same plot type, data and data aggregation level. + + + Answer with a JSON record ... + + { + "answer": , + "reason": " + } + """, + "recipe": """ + You judge matches of user intent with generic DB intents in the database to see if a DB intent can be used to solve the user's intent. + The requested output format of the user's intent MUST be the same as the output format of the generic DB intent. + For exmaple, if the user's intent is to get a plot, the generic DB intent MUST also be to get a plot. + The level of data aggregation is important, if the user's request differs from the DB intent, then reject it. + + Answer with a JSON record ... + + { + "answer": , + "user_intent_output_format": , + "generic_db_output_format": , + "reason": " + } + """, + "helper_function": """ + You judge matches of user input helper functions and those already in the database + If the user help function matches the database helper function, then it's a match + + Answer with a nested JSON record ... + + { + "answer": , + "reason": " + } + """, + "instructions_intent_from_history": """ + Given a user query, identify the intent of the user query. + + Determine the closest fit and rephrase the intent as one of the following standard sentence structures: + - "What is the [data point] for [subject/topic] in [location/context]?" + - "What are the recent trends in [topic] for [time period]?" + - "Can you show a comparison of [data point] between [subject/topic] and [subject/topic] over [time period]?" + - "Can you show a [type of visualization] of [data point] for [subject/topic] over [time period]?" + - "What does the latest data say about [cause-effect relationship] in [context]?" + - "What are the impacts of [event/condition] on [subject/topic] according to recent data?" + - "Provide a visualization of the distribution of [resources/assistance] in [location]." + - "How has the [data point] changed since [starting year]?" + - "What are the latest figures for [subject/topic]?" + + """, +} + +conn_params = { + "OPENAI_API_TYPE": os.getenv("OPENAI_API_TYPE"), + "OPENAI_API_ENDPOINT": os.getenv("OPENAI_API_ENDPOINT"), + "OPENAI_API_VERSION": os.getenv("OPENAI_API_VERSION_MEMORY"), + "BASE_URL": os.getenv("BASE_URL_MEMORY"), + "MODEL": os.getenv("MODEL"), + "OPENAI_TEXT_COMPLETION_DEPLOYMENT_NAME": os.getenv("OPENAI_TEXT_COMPLETION_DEPLOYMENT_NAME"), + "POSTGRES_DB": os.getenv("POSTGRES_RECIPE_DB"), + "POSTGRES_USER": os.getenv("POSTGRES_RECIPE_USER"), + "POSTGRES_HOST": os.getenv("POSTGRES_RECIPE_HOST"), + "POSTGRES_PORT": os.getenv("POSTGRES_RECIPE_PORT"), + "OPENAI_API_KEY": os.getenv("AZURE_API_KEY"), + "POSTGRES_PASSWORD": os.getenv("POSTGRES_RECIPE_PASSWORD"), +} + +# Setting db to None so that we can initialize it in the first invocation +db = None + + +def call_llm(instructions, prompt, chat): + """ + Call the LLM (Language Learning Model) API with the given instructions and prompt. + + Args: + instructions (str): The instructions to provide to the LLM API. + prompt (str): The prompt to provide to the LLM API. + chat (Langchain Open AI model): Chat model used for AI judging + + Returns: + dict or None: The response from the LLM API as a dictionary, or None if an error occurred. + """ + try: + messages = [ + SystemMessage(content=instructions), + HumanMessage(content=prompt), + ] + response = chat(messages) + print(response) + try: + response = json.loads(response.content) + except Exception as e: + print(f"Error creating json from response {e}") + # Until gpt 3.5 has json output, we'll return just the string for now when prompting fails to create json + response = response.content + return response + except Exception as e: + print(f"Error calling LLM {e}") + + +def initialize_db(mem_type, connection_string, embedding_model): + """ + Initialize the database by creating store tables if they don't exist and returns the initialized database. + + Returns: + dict: The initialized database with store tables for each memory type. + """ + db = {} + + # This will create store tables if they don't exist + collection_name = f"{mem_type}_embedding" + db[mem_type] = PGVector( + collection_name=collection_name, + connection_string=connection_string, + embedding_function=embedding_model, + ) + return db + + +def get_models(conn_params): + """Write short summary. + + Args: + conn_params (_type_): _description_ + + Returns: + _type_: _description_ + """ + api_key = conn_params["OPENAI_API_KEY"] + base_url = conn_params["BASE_URL"] + api_version = conn_params["OPENAI_API_VERSION"] + api_type = conn_params["OPENAI_API_TYPE"] + completion_model = conn_params["OPENAI_TEXT_COMPLETION_DEPLOYMENT_NAME"] + + if api_type == "openai": + print("Using OpenAI API in memory.py") + embedding_model = OpenAIEmbeddings( + api_key=api_key, + # model=completion_model + ) + chat = ChatOpenAI( + # model_name="gpt-3.5-turbo", + model_name="gpt-3.5-turbo-16k", + api_key=api_key, + temperature=1, + max_tokens=1000, + ) + elif api_type == "azure": + print("Using Azure OpenAI API in memory.py") + embedding_model = AzureOpenAIEmbeddings( + api_key=api_key, + deployment=completion_model, + azure_endpoint=base_url, + chunk_size=16, + ) + chat = AzureChatOpenAI( + api_key=api_key, + api_version=api_version, + azure_endpoint=base_url, + model_name="gpt-35-turbo", + # model_name="gpt-4-turbo", + # model="gpt-3-turbo-1106", # Model = should match the deployment name you chose for your 1106-preview model deployment + # response_format={ "type": "json_object" }, + temperature=1, + max_tokens=1000, + ) + else: + print("OPENAI API type not supported") + sys.exit(1) + return embedding_model, chat + + +def get_recipe_memory(intent) -> str: + """Write short summary. + + Args: + intent (_type_): _description_ + + Returns: + str: _description_ + """ + embedding_model, chat = get_models(conn_params) + connection_string = PGVector.connection_string_from_db_params( + driver="psycopg2", + host=conn_params["POSTGRES_HOST"], + port=int(conn_params["POSTGRES_PORT"]), + database=conn_params["POSTGRES_DB"], + user=conn_params["POSTGRES_USER"], + password=conn_params["POSTGRES_PASSWORD"], + ) + mem_type = "memory" + global db + if db is None: + db = initialize_db(mem_type, connection_string, embedding_model) + memory_found, recipe_response = check_memory(intent, mem_type, db, chat) + return memory_found, recipe_response + + +def check_memory(intent, mem_type, db, chat): + """ + Check the memory for a given intent. + + Args: + intent (str): The intent to search for in the memory. + mem_type (str): The type of memory to search in. Can be 'memory', 'recipe', or 'helper_function'. + db (Database): The database object to perform the search on. + chat (Langchain OpenAI model): Chat model + + Returns: + memory_found: Boolean, true if memeory found + result: A dictionary containing the score, content, and metadata of the best match found in the memory. + If no match is found, the dictionary values will be None. + """ + if mem_type not in ["memory", "recipe", "helper_function"]: + print("Memory type not recognised") + sys.exit() + return + r = {"score": None, "content": None, "metadata": None} + print(f"======= Checking {mem_type} for intent: {intent}") + + matches = get_matching_candidates(intent, mem_type, db) + + for m in matches: + score = m["score"] + content = m["content"] + metadata = m["metadata"] + if ( + metadata["calling_code_run_status"] != "ERROR" + and metadata["mem_type"] == mem_type + ): + print(f"\n Reranking candidate: Score: {score} ===> {content} \n") + # Here ask LLM to confirm our match + prompt = f""" + User Intent: + + {intent} + + DB Intent: + + {content} + + """ + + response = call_llm(prompt_map[mem_type], prompt, chat) + print(response) + + if "user_intent_output_format" in response: + if ( + response["user_intent_output_format"] + != response["generic_db_output_format"] + ): + response["answer"] = "no" + response["reason"] = "output formats do not match" + + print("AI Judge of match: ", response) + + if response["answer"].lower() == "yes": + print("We have a match!!!") + r["score"] = score + r["content"] = content + r["metadata"] = metadata + return True, r + + return False, r + + +def get_matching_candidates(intent, mem_type, db, cutoff=None): + """ + Get the matching candidates for a given intent based on similarity search. No LLM judge. + + Args: + intent (str): The intent to search for in the memory. + mem_type (str): The type of memory to search in. Can be 'memory', 'recipe', or 'helper_function'. + db (Database): The database object to perform the search on. + cutoff (float, optional): The similarity cutoff to use for the search. Defaults to similarity_cutoff[mem_type] + + Returns: + list: A list of matching candidates found in the memory. + """ + if mem_type not in ["memory", "recipe", "helper_function"]: + print("Memory type not recognised") + sys.exit() + return + if cutoff is None: + cutoff = similarity_cutoff[mem_type] + print(f"\n\n======= Getting matches for {mem_type} and intent: {intent}\n\n") + docs = db[mem_type].similarity_search_with_score(intent, k=10) + matches = [] + for d in docs: + r = {} + score = d[1] + content = d[0].page_content + metadata = d[0].metadata + print("\n", f"\n\nMatches: Score: {score} ===> {content}\n\n") + if ( + metadata["calling_code_run_status"] != "ERROR" + and metadata["mem_type"] == mem_type + ): + if d[1] < cutoff: + print("\n", " << MATCHED >>") + r["score"] = score + r["content"] = content + r["metadata"] = metadata + matches.append(r) + + return matches + + +def generate_intent_from_history(chat_history: list, remove_code: bool = True) -> dict: + """ + Generate the intent from the user query and chat history. + + Args: + chat_history (str): The chat history. + + Returns: + dict: The generated intent. + + """ + chat = get_models(conn_params)[1] + # Only use last few interactions + buffer = 4 + if len(chat_history) > buffer: + chat_history = chat_history[-buffer:] + + # Remove any code nodes + if remove_code is True: + chat_history2 = [] + for c in chat_history: + chat_history2.append(c) + if "code" in c: + # remove 'code' from dictionary c + c.pop("code") + chat_history = chat_history2 + + prompt = f""" + Given the chat history below, what is the user's intent? + + {chat_history} + + """ + intent = call_llm( + instructions=prompt_map["instructions_intent_from_history"], + prompt=prompt, + chat=chat, + ) + if not isinstance(intent, dict): + intent = {"intent": intent} + print(f"Generated intent: {intent}") + return intent["intent"] + + +@action(is_consequential=True) +def get_memory(user_input, chat_history, generate_intent=True) -> str: + """ + Performs a search in the memory for a given intent and returns the best match found. + + Args: + conn_params (str): The connection parameters for the database. + user_input (str): The user input to search for in the memory. + chat_history (str): The chat history. + generate_intent (str): A flag to indicate whether to generate the intent from the chat history. + + Returns: + str: The 3 best matches found in the memory. + """ + + logging.info("Python HTTP trigger function processed a request.") + # Retrieve the CSV file from the request + + if generate_intent is not None and generate_intent == True: + # chat history is passed from promptflow as a string representation of a list and this has to be converted back to a list for the intent generation to work! + history_list = ast.literal_eval(chat_history) + history_list.append({"inputs": {"question": user_input}}) + user_input = generate_intent_from_history(history_list) + # turn user_input into a proper json record + user_input = json.dumps(user_input) + print(f"\n\n\n\n+++++++++User intent: {user_input}\n\n\n\n") + memory_found, result = get_recipe_memory(user_input) + if memory_found is True: + response_text = result["metadata"]["response_text"] + response_image = result["metadata"]["response_image"] + if response_image is not None and response_image != "": + # result = process_image(response_image) + print(result) + else: + result = response_text + else: + result = "No memory found" + return result diff --git a/actions/actions_plugins/recipe-server/package.yaml b/actions/actions_plugins/recipe-server/package.yaml new file mode 100644 index 00000000..26676d5f --- /dev/null +++ b/actions/actions_plugins/recipe-server/package.yaml @@ -0,0 +1,29 @@ + +# Required: A short name for the action package +name: Get data recipe memory + +# Required: A description of what's in the action package. +description: This action contains logic to derive user intent from a conversation, and check the data recipe server for existing memories to reduce processing times. + +# Required: The current version of this action package. +version: 0.0.1 + +# Required: A link to where the documentation on the package lives. +documentation: https://github.com/robocorp/actions-cookbook/blob/master/example-postgres-universal/README.md + +dependencies: + conda-forge: + - python=3.10.12 + - pip=23.2.1 + - robocorp-truststore=0.8.0 + pypi: + - robocorp=1.6.2 + - robocorp-actions=0.0.7 + - langchain=0.1.16 + - langchain_community=0.0.34 + - langchain_openai=0.1.3 + - psycopg2-binary=2.9.3 + - pgvector=0.2.5 + - python-dotenv=0.19.1 + + diff --git a/actions/devdata/input_get_memory.json b/actions/devdata/input_get_memory.json new file mode 100644 index 00000000..94572db9 --- /dev/null +++ b/actions/devdata/input_get_memory.json @@ -0,0 +1,4 @@ +{ + "user_input": "whats the population of Mali?" , + "chat_history": "[]" +} \ No newline at end of file diff --git a/actions/package.yaml b/actions/package.yaml index 83c46694..873e976e 100644 --- a/actions/package.yaml +++ b/actions/package.yaml @@ -20,4 +20,9 @@ dependencies: - robocorp=1.6.2 - robocorp-actions=0.0.7 - pytz=2024.1 + - langchain=0.1.16 + - langchain_community=0.0.34 + - langchain_openai=0.1.3 + - psycopg2-binary=2.9.3 + - pgvector=0.2.5 diff --git a/docker-compose.yml b/docker-compose.yml index bae0ff16..59fe07dd 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -79,6 +79,7 @@ services: image: ankane/pgvector:latest container_name: datarecipes environment: + #The following is only needed because in the .env file, there are two database configurations and we have to distinguish between them POSTGRES_DB: ${POSTGRES_RECIPE_DB} POSTGRES_USER: ${POSTGRES_RECIPE_USER} POSTGRES_PASSWORD: ${POSTGRES_RECIPE_PASSWORD} @@ -113,6 +114,8 @@ services: - 3001:8080 # Action server portal - 4001:8087 + env_file: + - .env volumes: pgdata2: \ No newline at end of file From f5bfa54c9feb14a97acb0b41ba1a5e4d7654b0ef Mon Sep 17 00:00:00 2001 From: JanPeterDatakind Date: Fri, 26 Apr 2024 18:08:13 -0400 Subject: [PATCH 03/20] Add env variables for connection parameters --- .env.example | 18 +++++++++++++++--- actions/Dockerfile | 3 +-- 2 files changed, 16 insertions(+), 5 deletions(-) diff --git a/.env.example b/.env.example index d0069c8e..3843066f 100644 --- a/.env.example +++ b/.env.example @@ -374,9 +374,21 @@ POSTGRES_PASSWORD=mypassword #==================================================# # RecipeDB Configuration # #==================================================# -POSTGRES_RECIPE_DB=mydatabase -POSTGRES_RECIPE_USER=myuser -POSTGRES_RECIPEPASSWORD=mypassword +POSTGRES_RECIPE_DB=myrecipedatabase +POSTGRES_RECIPE_USER=myrecipeuser +POSTGRES_RECIPE_PASSWORD=myrecipepassword +POSTGRES_RECIPE_HOST=data_recipe_db +POSTGRES_RECIPE_PORT=5432 + +#==================================================# +# Get Memory Action Configuration # +#==================================================# +OPENAI_API_TYPE= +OPENAI_API_ENDPOINT= +OPENAI_API_VERSION_MEMORY= +BASE_URL_MEMORY= +MODEL_MEMORY= +OPENAI_TEXT_COMPLETION_DEPLOYMENT_NAME= #==================================================# # Others # #==================================================# diff --git a/actions/Dockerfile b/actions/Dockerfile index e15b88a7..69dcd082 100644 --- a/actions/Dockerfile +++ b/actions/Dockerfile @@ -44,5 +44,4 @@ RUN echo "{\"dsn\": \"$DATA_DB_CONN_STRING\"}" > ./actions_plugins/postgres-univ EXPOSE 8080 -CMD ["/usr/bin/supervisord"] -#CMD ["python", "./actions_plugins/postgres-universal/main.py", "--dsn", "$DATA_DB_CONN_STRING] \ No newline at end of file +CMD ["/usr/bin/supervisord"] \ No newline at end of file From 2c759b718adf58da512b2ec89fdc21f5a2256e68 Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Mon, 29 Apr 2024 15:12:16 -0600 Subject: [PATCH 04/20] Cleanup script to reset environment --- cleanup.sh | 8 ++++++++ 1 file changed, 8 insertions(+) create mode 100755 cleanup.sh diff --git a/cleanup.sh b/cleanup.sh new file mode 100755 index 00000000..ce0432f1 --- /dev/null +++ b/cleanup.sh @@ -0,0 +1,8 @@ +rm -rf ./ui/recipes_assistant_chat/images/* +rm -rf ./ui/recipes_assistant_chat/logs/* +rm -rf ./ui/recipes_assistant_chat/data-node/* +rm -rf ./ui/recipes_assistant_chat/meili_data_v1.7/* +rm -rf ./ui/recipes_assistant_chat/pgdata2/* +rm -rf ./actions/actions_plugins/recipe-server/db/* + +docker compose down -v \ No newline at end of file From d9c44adbc0a5bcd34f180da3dc11c5170cb01077 Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Mon, 29 Apr 2024 18:20:16 -0600 Subject: [PATCH 05/20] Tidies up docker build for the two new DBs --- .env.example | 41 +++++-- README.md | 5 +- actions/Dockerfile | 4 +- .../postgres-universal/actions.py | 48 ++++---- .../recipe-server/db/1-schema.sql | 4 +- cleanup.sh | 7 +- docker-compose.yml | 32 +++-- ui/recipes_assistant_chat/librechat.yaml | 114 +++++++++--------- 8 files changed, 145 insertions(+), 110 deletions(-) diff --git a/.env.example b/.env.example index 3843066f..7028e485 100644 --- a/.env.example +++ b/.env.example @@ -23,8 +23,31 @@ DOMAIN_SERVER=http://localhost:3080 NO_INDEX=true -# COonection string for where the data DB resides. Can be remote or local DB, in form postgresql://username:password@host:port/database -DATA_DB_CONN_STRING= +# =========== Local Docker containers START ========== +POSTGRES_DATA_HOST=postgres-prototypes.postgres.database.azure.com +POSTGRES_DATA_PORT=5432 +POSTGRES_DATA_DB=hdexpert-alpha +POSTGRES_DATA_USER= +POSTGRES_DATA_PASSWORD= +DATA_DB_CONN_STRING=postgresql://${POSTGRES_DATA_USER}:${POSTGRES_DATA_PASSWORD}@${POSTGRES_DATA_HOST}:${POSTGRES_DATA_PORT}/${POSTGRES_DATA_DB} + +POSTGRES_RECIPE_HOST=recipedb +POSTGRES_RECIPE_PORT=5432 +POSTGRES_RECIPE_DB=recipes +POSTGRES_RECIPE_USER= +POSTGRES_RECIPE_PASSWORD= +RECIPE_DB_CONN_STRING=postgresql://${POSTGRES_RECIPE_USER}:${POSTGRES_RECIPE_PASSWORD}@${POSTGRES_RECIPE_HOST}:${POSTGRES_RECIPE_PORT}/${POSTGRES_RECIPE_DB} +# =========== Local Docker containers END ========== + +#==================================================# +# Get Memory Action Configuration # +#==================================================# +OPENAI_API_TYPE=azure +OPENAI_API_ENDPOINT= +OPENAI_API_VERSION_MEMORY=2024-02-15-preview +BASE_URL_MEMORY= +MODEL_MEMORY=gpt-4-turbo +OPENAI_TEXT_COMPLETION_DEPLOYMENT_NAME=text-embedding-ada-002 #===============# # JSON Logging # @@ -88,22 +111,22 @@ ANTHROPIC_API_KEY=sk-ant-api03-6b0Vg33VrXpxmVALpTlGJu90IvfrIbW5Q8wEamdnk1Es4mg6e # Azure # #============# -AZURE_API_KEY=c3e37d558bea46ca917dd2be40ee69d4 +AZURE_API_KEY= # Note: these variables are DEPRECATED # Use the `librechat.yaml` configuration for `azureOpenAI` instead # You may also continue to use them if you opt out of using the `librechat.yaml` configuration -AZURE_OPENAI_DEFAULT_MODEL=gpt-3.5-turbo # Deprecated -AZURE_OPENAI_MODELS=gpt-35-turbo,gpt-4 +#AZURE_OPENAI_DEFAULT_MODEL=gpt-3.5-turbo # Deprecated +#AZURE_OPENAI_MODELS=gpt-35-turbo,gpt-4 # AZURE_USE_MODEL_AS_DEPLOYMENT_NAME=TRUE # AZURE_API_KEY= # Deprecated -AZURE_OPENAI_API_INSTANCE_NAME=DK-DS-Team -AZURE_OPENAI_API_DEPLOYMENT_NAME=gpt-4 -AZURE_OPENAI_API_VERSION=2023-07-01-preview +#AZURE_OPENAI_API_INSTANCE_NAME=DK-DS-Team +#AZURE_OPENAI_API_DEPLOYMENT_NAME=gpt-4 +#AZURE_OPENAI_API_VERSION=2023-07-01-preview # AZURE_OPENAI_API_COMPLETIONS_DEPLOYMENT_NAME= # Deprecated # AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME= # Deprecated -PLUGINS_USE_AZURE="true" # Deprecated +#PLUGINS_USE_AZURE="true" # Deprecated #============# # BingAI # diff --git a/README.md b/README.md index 750ba59e..5e820f42 100644 --- a/README.md +++ b/README.md @@ -32,7 +32,6 @@ Robocorp AI Actions API - [http://localhost:3001/](http://localhost:3001/) TODO: This will be automated, but for now ... -1. Initialize the DB connection by going to [http://localhost:4001/](http://localhost:4001/) and running action `init_postgres_connection` to set Recipes DB in Azure (TO DO will be changed once we finish ingestion folders) 1. Got to [chat app](http://localhost:3080/) and register a user on the login page 2. Log in 3. Select Assistants, choose HDeXpert SQL @@ -42,6 +41,10 @@ TODO: This will be automated, but for now ... Note: You can reset Libre chat by removing contents of `ui/recipes_assistant_chat/data-node/`. This is sometimes neccesary due to a bug in specifying actions. +## Reseting your environment + +If running locally, you can reset your environment - removing any data for your databases, which means re-registration - by running `./cleanuop.sh`. + ## Testing connection to actions server 1. `exec -it LibreChat /bin/sh` diff --git a/actions/Dockerfile b/actions/Dockerfile index 69dcd082..1c72c3e8 100644 --- a/actions/Dockerfile +++ b/actions/Dockerfile @@ -40,7 +40,9 @@ ENV DATA_DB_CONN_STRING=$DATA_DB_CONN_STRING RUN action-server import --dir=./actions_plugins/postgres-universal --datadir=/action-server/datadir RUN action-server import --dir=./actions_plugins/recipe-server --datadir=/action-server/datadir -RUN echo "{\"dsn\": \"$DATA_DB_CONN_STRING\"}" > ./actions_plugins/postgres-universal/postgres_connection.json +RUN echo "{\"dsn\": \"$DATA_DB_CONN_STRING\"}" > ./actions_plugins/postgres-universal/postgres_data_connection.json + +RUN echo "{\"dsn\": \"$RECIPE_DB_CONN_STRING\"}" > ./actions_plugins/postgres-universal/postgres_recipe_connection.json EXPOSE 8080 diff --git a/actions/actions_plugins/postgres-universal/actions.py b/actions/actions_plugins/postgres-universal/actions.py index 28a5f274..e1f10ae6 100644 --- a/actions/actions_plugins/postgres-universal/actions.py +++ b/actions/actions_plugins/postgres-universal/actions.py @@ -3,7 +3,7 @@ import psycopg2 from robocorp.actions import action -CONNECTION_FILE_PATH = "postgres_connection.json" +CONNECTION_FILE_PATH = "postgres_data_connection.json" MAX_CHARS_TOT = 10000 @@ -178,29 +178,29 @@ def truncate_query_results(results, max_chars=MAX_CHARS_TOT): return truncated_output -@action -def init_postgres_connection(dsn: str) -> str: - """ - Initializes a connection to a PostgreSQL database using the provided Data Source Name (DSN). - - Args: - dsn (str): The connection string for the PostgreSQL database. - This should be in the format 'postgresql://username:password@host:port/database'. - - Returns: - str: A textual representation of the database schema. - """ - conn_params = {"dsn": dsn} - - # Save connection parameters to a file - try: - with open(CONNECTION_FILE_PATH, "w") as file: - json.dump(conn_params, file) - with ReadOnlyConnection(conn_params) as conn: - schema = get_database_schema(conn) - return truncate_output_with_beginning_clue(schema) - except Exception as e: - return f"Failed: {e}" +# @action +# def init_postgres_connection(dsn: str) -> str: +# """ +# Initializes a connection to a PostgreSQL database using the provided Data Source Name (DSN). +# +# Args: +# dsn (str): The connection string for the PostgreSQL database. +# This should be in the format 'postgresql://username:password@host:port/database'. +# +# Returns: +# str: A textual representation of the database schema. +# """ +# conn_params = {"dsn": dsn} +# +# # Save connection parameters to a file +# try: +# with open(CONNECTION_FILE_PATH, "w") as file: +# json.dump(conn_params, file) +# with ReadOnlyConnection(conn_params) as conn: +# schema = get_database_schema(conn) +# return truncate_output_with_beginning_clue(schema) +# except Exception as e: +# return f"Failed: {e}" @action diff --git a/actions/actions_plugins/recipe-server/db/1-schema.sql b/actions/actions_plugins/recipe-server/db/1-schema.sql index 32fa5933..a720e817 100644 --- a/actions/actions_plugins/recipe-server/db/1-schema.sql +++ b/actions/actions_plugins/recipe-server/db/1-schema.sql @@ -1,6 +1,6 @@ -CREATE SCHEMA data_recipes; -CREATE SCHEMA data; +-- CREATE SCHEMA data_recipes; +-- CREATE SCHEMA data; CREATE EXTENSION IF NOT EXISTS "uuid-ossp"; CREATE EXTENSION IF NOT EXISTS "vector"; diff --git a/cleanup.sh b/cleanup.sh index ce0432f1..b845e464 100755 --- a/cleanup.sh +++ b/cleanup.sh @@ -1,8 +1,7 @@ +docker compose down -v + rm -rf ./ui/recipes_assistant_chat/images/* rm -rf ./ui/recipes_assistant_chat/logs/* rm -rf ./ui/recipes_assistant_chat/data-node/* rm -rf ./ui/recipes_assistant_chat/meili_data_v1.7/* -rm -rf ./ui/recipes_assistant_chat/pgdata2/* -rm -rf ./actions/actions_plugins/recipe-server/db/* - -docker compose down -v \ No newline at end of file +rm -rf ./ui/recipes_assistant_chat/pgdata2/* \ No newline at end of file diff --git a/docker-compose.yml b/docker-compose.yml index 59fe07dd..a0fb96db 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -42,7 +42,7 @@ services: target: /app/librechat.yaml mongodb: #platform: linux/amd64 - container_name: chat-mongodb + container_name: haa-mongodb image: mongo restart: always user: "${UID}:${GID}" @@ -51,7 +51,7 @@ services: command: mongod --noauth meilisearch: #platform: linux/amd64 - container_name: chat-meilisearch + container_name: haa-meilisearch image: getmeili/meilisearch:v1.7.3 restart: always user: "${UID}:${GID}" @@ -60,13 +60,14 @@ services: MEILI_NO_ANALYTICS: true volumes: - ./ui/recipes_assistant_chat/meili_data_v1.7:/meili_data - vectordb: + datadb: #platform: linux/amd64 image: ankane/pgvector:latest + container_name: haa-datadb environment: - POSTGRES_DB: ${POSTGRES_DB} - POSTGRES_USER: ${POSTGRES_USER} - POSTGRES_PASSWORD: ${POSTGRES_PASSWORD} + POSTGRES_DB: ${POSTGRES_DATA_DB} + POSTGRES_USER: ${POSTGRES_DATA_USER} + POSTGRES_PASSWORD: ${POSTGRES_DATA_PASSWORD} restart: always ports: - 5432:5432 @@ -74,12 +75,11 @@ services: - ./ui/recipes_assistant_chat/pgdata2:/var/lib/postgresql/data env_file: - .env - data_recipe_db: + recipedb: #platform: linux/amd64 image: ankane/pgvector:latest - container_name: datarecipes + container_name: haa-datarecipes environment: - #The following is only needed because in the .env file, there are two database configurations and we have to distinguish between them POSTGRES_DB: ${POSTGRES_RECIPE_DB} POSTGRES_USER: ${POSTGRES_RECIPE_USER} POSTGRES_PASSWORD: ${POSTGRES_RECIPE_PASSWORD} @@ -93,17 +93,25 @@ services: rag-api: #platform: linux/amd64 image: ghcr.io/danny-avila/librechat-rag-api-dev-lite:latest + container_name: haa-rag-api environment: - DB_HOST: vectordb + DB_HOST: datadb + POSTGRES_DB: ${POSTGRES_DATA_DB} + POSTGRES_USER: ${POSTGRES_DATA_USER} + POSTGRES_PASSWORD: ${POSTGRES_DATA_PASSWORD} RAG_PORT: ${RAG_PORT:-8000} + RAG_OPENAI_API_KEY: ${AZURE_API_KEY} + EMBEDDINGS_PROVIDER: azure + EMBEDDINGS_MODEL: text-embedding-ada-002 + AZURE_OPENAI_ENDPOINT: https://dkopenai2.openai.azure.com/ restart: always depends_on: - - vectordb + - datadb env_file: - .env actions: platform: linux/amd64 - container_name: haa-libre-robo-actions + container_name: haa-robo-actions build: context: . dockerfile: ./actions/Dockerfile diff --git a/ui/recipes_assistant_chat/librechat.yaml b/ui/recipes_assistant_chat/librechat.yaml index bd7b357e..2e4721a1 100644 --- a/ui/recipes_assistant_chat/librechat.yaml +++ b/ui/recipes_assistant_chat/librechat.yaml @@ -62,78 +62,78 @@ endpoints: #retrievalModels: ["gpt-4-turbo-preview"] # (optional) Assistant Capabilities available to all users. Omit the ones you wish to exclude. Defaults to list below. #capabilities: ["code_interpreter", "retrieval", "actions", "tools", "image_vision"] - custom: - # Groq Example - - name: 'groq' - apiKey: '${GROQ_API_KEY}' - baseURL: 'https://api.groq.com/openai/v1/' - models: - default: ['llama2-70b-4096', 'mixtral-8x7b-32768', 'gemma-7b-it'] - fetch: false - titleConvo: true - titleModel: 'mixtral-8x7b-32768' - modelDisplayLabel: 'groq' + # custom: + # # Groq Example + # - name: 'groq' + # apiKey: '${GROQ_API_KEY}' + # baseURL: 'https://api.groq.com/openai/v1/' + # models: + # default: ['llama2-70b-4096', 'mixtral-8x7b-32768', 'gemma-7b-it'] + # fetch: false + # titleConvo: true + # titleModel: 'mixtral-8x7b-32768' + # modelDisplayLabel: 'groq' # Mistral AI Example - - name: 'Mistral' # Unique name for the endpoint - # For `apiKey` and `baseURL`, you can use environment variables that you define. - # recommended environment variables: - apiKey: '${MISTRAL_API_KEY}' - baseURL: 'https://api.mistral.ai/v1' + # - name: 'Mistral' # Unique name for the endpoint + # # For `apiKey` and `baseURL`, you can use environment variables that you define. + # # recommended environment variables: + # apiKey: '${MISTRAL_API_KEY}' + # baseURL: 'https://api.mistral.ai/v1' - # Models configuration - models: - # List of default models to use. At least one value is required. - default: ['mistral-tiny', 'mistral-small', 'mistral-medium'] - # Fetch option: Set to true to fetch models from API. - fetch: true # Defaults to false. + # # Models configuration + # models: + # # List of default models to use. At least one value is required. + # default: ['mistral-tiny', 'mistral-small', 'mistral-medium'] + # # Fetch option: Set to true to fetch models from API. + # fetch: true # Defaults to false. - # Optional configurations + # # Optional configurations - # Title Conversation setting - titleConvo: true # Set to true to enable title conversation + # # Title Conversation setting + # titleConvo: true # Set to true to enable title conversation - # Title Method: Choose between "completion" or "functions". - # titleMethod: "completion" # Defaults to "completion" if omitted. + # # Title Method: Choose between "completion" or "functions". + # # titleMethod: "completion" # Defaults to "completion" if omitted. - # Title Model: Specify the model to use for titles. - titleModel: 'mistral-tiny' # Defaults to "gpt-3.5-turbo" if omitted. + # # Title Model: Specify the model to use for titles. + # titleModel: 'mistral-tiny' # Defaults to "gpt-3.5-turbo" if omitted. - # Summarize setting: Set to true to enable summarization. - # summarize: false + # # Summarize setting: Set to true to enable summarization. + # # summarize: false - # Summary Model: Specify the model to use if summarization is enabled. - # summaryModel: "mistral-tiny" # Defaults to "gpt-3.5-turbo" if omitted. + # # Summary Model: Specify the model to use if summarization is enabled. + # # summaryModel: "mistral-tiny" # Defaults to "gpt-3.5-turbo" if omitted. - # Force Prompt setting: If true, sends a `prompt` parameter instead of `messages`. - # forcePrompt: false + # # Force Prompt setting: If true, sends a `prompt` parameter instead of `messages`. + # # forcePrompt: false - # The label displayed for the AI model in messages. - modelDisplayLabel: 'Mistral' # Default is "AI" when not set. + # # The label displayed for the AI model in messages. + # modelDisplayLabel: 'Mistral' # Default is "AI" when not set. - # Add additional parameters to the request. Default params will be overwritten. - # addParams: - # safe_prompt: true # This field is specific to Mistral AI: https://docs.mistral.ai/api/ + # # Add additional parameters to the request. Default params will be overwritten. + # # addParams: + # # safe_prompt: true # This field is specific to Mistral AI: https://docs.mistral.ai/api/ - # Drop Default params parameters from the request. See default params in guide linked below. - # NOTE: For Mistral, it is necessary to drop the following parameters or you will encounter a 422 Error: - dropParams: ['stop', 'user', 'frequency_penalty', 'presence_penalty'] + # # Drop Default params parameters from the request. See default params in guide linked below. + # # NOTE: For Mistral, it is necessary to drop the following parameters or you will encounter a 422 Error: + # dropParams: ['stop', 'user', 'frequency_penalty', 'presence_penalty'] # OpenRouter Example - - name: 'OpenRouter' - # For `apiKey` and `baseURL`, you can use environment variables that you define. - # recommended environment variables: - # Known issue: you should not use `OPENROUTER_API_KEY` as it will then override the `openAI` endpoint to use OpenRouter as well. - apiKey: '${OPENROUTER_KEY}' - baseURL: 'https://openrouter.ai/api/v1' - models: - default: ['gpt-3.5-turbo'] - fetch: true - titleConvo: true - titleModel: 'gpt-3.5-turbo' - # Recommended: Drop the stop parameter from the request as Openrouter models use a variety of stop tokens. - dropParams: ['stop'] - modelDisplayLabel: 'OpenRouter' + # - name: 'OpenRouter' + # # For `apiKey` and `baseURL`, you can use environment variables that you define. + # # recommended environment variables: + # # Known issue: you should not use `OPENROUTER_API_KEY` as it will then override the `openAI` endpoint to use OpenRouter as well. + # apiKey: '${OPENROUTER_KEY}' + # baseURL: 'https://openrouter.ai/api/v1' + # models: + # default: ['gpt-3.5-turbo'] + # fetch: true + # titleConvo: true + # titleModel: 'gpt-3.5-turbo' + # # Recommended: Drop the stop parameter from the request as Openrouter models use a variety of stop tokens. + # dropParams: ['stop'] + # modelDisplayLabel: 'OpenRouter' # fileConfig: # endpoints: # assistants: From b84c3287cc7d490b004d46c583e8c09fb316dee1 Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Wed, 1 May 2024 17:48:20 -0400 Subject: [PATCH 06/20] Corrected Curl example --- README.md | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 5e820f42..f1a51f7b 100644 --- a/README.md +++ b/README.md @@ -47,11 +47,10 @@ If running locally, you can reset your environment - removing any data for your ## Testing connection to actions server -1. `exec -it LibreChat /bin/sh` +1. `docker exec -it haa-libre-chat /bin/sh` 2. `curl -X POST -H "Content-Type: application/json" \ - -d '{"dsn": "postgresql://username:password@host:port/database"}' \ - "http://actions:8080/api/actions/postgresql-universal-actions/init-postgres-connection/run"` .... replacing with correct postgres credentials` - + -d '{"query": "select 1"}' \ + "http://actions:8080/api/actions/postgresql-universal-actions/execute-query/run"`` ## Deploying to Azure From 81e138b6cc9e0a5d5b5c9eecd1dbecee6309a87b Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Wed, 1 May 2024 17:57:09 -0400 Subject: [PATCH 07/20] Corrected Curl example --- README.md | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index f1a51f7b..f3f71d38 100644 --- a/README.md +++ b/README.md @@ -48,9 +48,12 @@ If running locally, you can reset your environment - removing any data for your ## Testing connection to actions server 1. `docker exec -it haa-libre-chat /bin/sh` -2. `curl -X POST -H "Content-Type: application/json" \ +2. To test the SQL query action, run `curl -X POST -H "Content-Type: application/json" \ -d '{"query": "select 1"}' \ - "http://actions:8080/api/actions/postgresql-universal-actions/execute-query/run"`` + "http://actions:8080/api/actions/postgresql-universal-actions/execute-query/run"` +3. To get get-memory action, run ... `curl -X POST -H "Content-Type: application/json" \ + -d '{"chat_history": "[]", "user_input":"population of Mali", "generate_intent":"true"}' \ + "http://actions:8080/api/actions/get-data-recipe-memory/get-memory/run"`` ## Deploying to Azure From e2af19fe8f288ee97be1eb1d34f46c29905f09d5 Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Wed, 1 May 2024 18:09:39 -0400 Subject: [PATCH 08/20] First version of integration scaffolding --- ingestion/api/hapi/.gitkeep | 0 ingestion/apis.config | 10 +++ ingestion/openapi_ingestion.py | 133 +++++++++++++++++++++++++++++++++ 3 files changed, 143 insertions(+) create mode 100644 ingestion/api/hapi/.gitkeep create mode 100644 ingestion/apis.config create mode 100644 ingestion/openapi_ingestion.py diff --git a/ingestion/api/hapi/.gitkeep b/ingestion/api/hapi/.gitkeep new file mode 100644 index 00000000..e69de29b diff --git a/ingestion/apis.config b/ingestion/apis.config new file mode 100644 index 00000000..5f5d19b0 --- /dev/null +++ b/ingestion/apis.config @@ -0,0 +1,10 @@ +[ + { + "api_name": "hapi", + "api_descr": "New HDX API", + "openapi_def": "https://stage.hapi-humdata-org.ahconu.org/openapi.json", + "excluded_endpoints": [ + "/api/v1/encode_identifier" + ] + } +] \ No newline at end of file diff --git a/ingestion/openapi_ingestion.py b/ingestion/openapi_ingestion.py new file mode 100644 index 00000000..4ba84f33 --- /dev/null +++ b/ingestion/openapi_ingestion.py @@ -0,0 +1,133 @@ +import requests +import json +import os +import time +from urllib.parse import urlencode +import sys +import pandas as pd + +APIS_CONFIG = "apis.config" + +def get_api_def(api): + + api_name = api["api_name"] + api_host = api["openapi_def"].split("/")[2] + openapi_def = api["openapi_def"] + openapi_filename = f"./api/{api_name}/{openapi_def.split('/')[-1]}" + + print(f"Getting {api_name} API definition from {openapi_def} and saving it to {openapi_filename}") + + api = requests.get(openapi_def) + api = json.loads(api.text) + + with open(openapi_filename, "w") as f: + apis_formatted = json.dumps(api, indent=4, sort_keys=True) + f.write(apis_formatted) + + # Needed for some application using openapi's definition + if 'servers' not in api: + api['servers'] = [ + { + "url": f"https:/{api_host}" + } + ] + + return api + +def get_api_data(endpoint, params): + + print('URL', endpoint + '/?' + urlencode(params)) + response = requests.get(endpoint, params=params) + if response.status_code == 200: + data = response.json() + if isinstance(data, list): + return data + else: + return [data] + else: + msg = "No data was returned for endpoint:" + endpoint + print(msg) + return msg + + +def download_data(api_host, openapi_def, excluded_endpoints, save_path): + """ + Downloads data based on the functions specified in the openapi.json definition file. + + TODO: This currently assumes paging per the new HAPI API, and would need work to + extend to other approaches. + + Args: + api_hiost: Host URL + openapi_def (str): The path to the openapi JSON file. + save_path (str): Where to save the data + + """ + + limit = 1000 + offset = 0 + + files = os.listdir(save_path) + for f in files: + if 'openapi.json' not in f: + filename = f"{save_path}/{f}" + os.remove(filename) + + for endpoint in openapi_def["paths"]: + if endpoint in excluded_endpoints: + print(f"Skipping {endpoint}") + continue + print(endpoint) + if "get" not in openapi_def["paths"][endpoint]: + print(f"Skipping endpoint with no 'get' method {endpoint}") + continue + url = f"https://{api_host}/{endpoint}" + print(url) + + data = [] + offset = 0 + output = [] + while len(output) > 0 or offset == 0: + output = get_api_data(url, {'limit':limit, 'offset': offset}) + print(output) + data = data + output + print(len(data), len(output)) + offset = offset + limit + time.sleep(1) + + if len(data) > 0: + endpoint_clean = endpoint.replace("/", "_") + if endpoint_clean[0] == "_": + endpoint_clean = endpoint_clean[1:] + + print(len(data), "Before DF") + df = pd.DataFrame(data) + #df = map_code_cols(df, col_map) + #df = filter_hdx_df(df) + print(df.shape[0], "After DF") + file_name = f"{save_path}/{endpoint_clean}.csv" + df.to_csv(file_name, index=False) + with open(f"{save_path}/{endpoint_clean}_meta.json", "w") as f: + full_meta = openapi_def["paths"][endpoint] + f.write(json.dumps(full_meta, indent=4)) + + print(f"Saved {file_name}") + + +def read_apis_config(): + with open(APIS_CONFIG) as f: + print("Reading apis.config") + apis = json.load(f) + return apis + +def main(): + apis = read_apis_config() + for api in apis: + openapi_def = get_api_def(api) + save_path = f'./api/{api["api_name"]}/' + api_host = api["openapi_def"].split("/")[2] + excluded_endpoints = api["excluded_endpoints"] + download_data(api_host, openapi_def, excluded_endpoints, save_path) + +if __name__ == "__main__": + main() \ No newline at end of file From 638298077f7011e55c32d353fb7b88bff247fb78 Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Wed, 1 May 2024 18:14:02 -0400 Subject: [PATCH 09/20] First version of integration scaffolding --- .gitignore | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index 1e6fa5a3..a2481fb0 100644 --- a/.gitignore +++ b/.gitignore @@ -6,4 +6,5 @@ logs meili_data_v1.7 images pgdata2 -tmp \ No newline at end of file +tmp +api/hapi \ No newline at end of file From 6e0b5125732cdf765a3edf65f8c5007474f039be Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Wed, 1 May 2024 18:14:21 -0400 Subject: [PATCH 10/20] First version of integration scaffolding --- .gitignore | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index a2481fb0..ef6dd2c1 100644 --- a/.gitignore +++ b/.gitignore @@ -7,4 +7,4 @@ meili_data_v1.7 images pgdata2 tmp -api/hapi \ No newline at end of file +integration/api/hapi/* \ No newline at end of file From 05585d418cf96571d9660f18d56175e26887ec61 Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Wed, 1 May 2024 18:14:56 -0400 Subject: [PATCH 11/20] Exclude Date files --- .gitignore | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index ef6dd2c1..5e29cdcc 100644 --- a/.gitignore +++ b/.gitignore @@ -7,4 +7,4 @@ meili_data_v1.7 images pgdata2 tmp -integration/api/hapi/* \ No newline at end of file +ingestion/api/hapi/* \ No newline at end of file From eff233942ba98b162f6532140b74c636e3ef2853 Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Wed, 1 May 2024 18:48:18 -0400 Subject: [PATCH 12/20] Putting prompt under source control to align with integration. This will be revisted under assitant creation --- .../prompts/sql_actions_assistant.jinja | 254 ++++++++++++++++++ 1 file changed, 254 insertions(+) create mode 100644 assistant/recipes_assistant/prompts/sql_actions_assistant.jinja diff --git a/assistant/recipes_assistant/prompts/sql_actions_assistant.jinja b/assistant/recipes_assistant/prompts/sql_actions_assistant.jinja new file mode 100644 index 00000000..68eaee86 --- /dev/null +++ b/assistant/recipes_assistant/prompts/sql_actions_assistant.jinja @@ -0,0 +1,254 @@ +{# prompts/sql_actions_assistant.txt #} + +You are a helpful assistant. +You ONLY get information from the Robocorp actions tools you have been provided. +If someone asks about a country state, that is admin 1. + +ALWAYS perform the get data recipes actions first, and only if no usable result is returned, use other actions +The actions 'url' you should be calling is 'http://actions:8080' + +To get answers about data use your robocorp actions tool to run SQL. +When asked to do a task, first inform the user how you will perform the task +NEVER EVER generate Python using sample data, you MUST always use data you got from calling the SQL action. + +If no data is retuned after trying, inform the user. +adm0_code are 3-leter country ISO codes + +Always display images if you analysis creates one + +Unless the user is asking for data changes over time, add the following clause to all queries to get latest data ... + +`group by + reference_period_start +having + reference_period_start = MAX(reference_period_start)` + +Unless reference_period_start or reference_period_start are part of an output graph, ALWAYS list the ranges of these used when aggregating data. + +Here is a list of tables and their columns ... + +Table, Column, Column Type +hapi_3W adm0_code text +hapi_3W adm1_code text +hapi_3W adm2_code text +hapi_3W admin1_name text +hapi_3W admin2_name text +hapi_3W dataset_hapi_stub text +hapi_3W index bigint +hapi_3W location_name text +hapi_3W org_acronym text +hapi_3W org_name text +hapi_3W reference_period_end text +hapi_3W reference_period_start text +hapi_3W resource_hapi_id text +hapi_3W sector_code text +hapi_3W sector_name text +hapi_admin1 adm0_code text +hapi_admin1 code text +hapi_admin1 index bigint +hapi_admin1 location_name text +hapi_admin1 name text +hapi_admin2 adm0_code text +hapi_admin2 adm1_code text +hapi_admin2 admin1_name text +hapi_admin2 code text +hapi_admin2 index bigint +hapi_admin2 location_name text +hapi_admin2 name text +hapi_age_range age_max double precision +hapi_age_range age_min bigint +hapi_age_range code text +hapi_age_range index bigint +hapi_dataset hapi_api_link text +hapi_dataset hapi_id text +hapi_dataset hapi_link text +hapi_dataset hapi_provider_name text +hapi_dataset hapi_provider_stub text +hapi_dataset hapi_stub text +hapi_dataset index bigint +hapi_dataset title text +hapi_food_security adm0_code text +hapi_food_security adm1_code text +hapi_food_security adm2_code text +hapi_food_security admin1_name text +hapi_food_security admin2_name text +hapi_food_security dataset_hapi_provider_stub text +hapi_food_security dataset_hapi_stub text +hapi_food_security index bigint +hapi_food_security ipc_phase_code text +hapi_food_security ipc_phase_name text +hapi_food_security ipc_type_code text +hapi_food_security location_name text +hapi_food_security population_fraction_in_phase double precision +hapi_food_security population_in_phase bigint +hapi_food_security reference_period_end text +hapi_food_security reference_period_start text +hapi_food_security resource_hapi_id text +hapi_gender code text +hapi_gender description text +hapi_gender index bigint +hapi_humanitarian_needs adm0_code text +hapi_humanitarian_needs adm1_code text +hapi_humanitarian_needs adm2_code text +hapi_humanitarian_needs admin1_name text +hapi_humanitarian_needs admin2_name text +hapi_humanitarian_needs age_range_code double precision +hapi_humanitarian_needs dataset_hapi_provider_stub text +hapi_humanitarian_needs dataset_hapi_stub text +hapi_humanitarian_needs disabled_marker double precision +hapi_humanitarian_needs gender_code double precision +hapi_humanitarian_needs index bigint +hapi_humanitarian_needs location_name text +hapi_humanitarian_needs population bigint +hapi_humanitarian_needs population_group_code double precision +hapi_humanitarian_needs population_status_code text +hapi_humanitarian_needs reference_period_end text +hapi_humanitarian_needs reference_period_start text +hapi_humanitarian_needs resource_hapi_id text +hapi_humanitarian_needs sector_code double precision +hapi_humanitarian_needs sector_name double precision +hapi_location code text +hapi_location index bigint +hapi_location name text +hapi_national_risk adm0_code text +hapi_national_risk coping_capacity_risk double precision +hapi_national_risk dataset_hapi_provider_stub text +hapi_national_risk dataset_hapi_stub text +hapi_national_risk global_rank bigint +hapi_national_risk hazard_exposure_risk double precision +hapi_national_risk index bigint +hapi_national_risk location_name text +hapi_national_risk meta_avg_recentness_years double precision +hapi_national_risk meta_missing_indicators_pct double precision +hapi_national_risk overall_risk double precision +hapi_national_risk reference_period_end text +hapi_national_risk reference_period_start text +hapi_national_risk resource_hapi_id text +hapi_national_risk risk_class bigint +hapi_national_risk vulnerability_risk double precision +hapi_org acronym text +hapi_org index bigint +hapi_org name text +hapi_org org_type_code bigint +hapi_org org_type_description text +hapi_org_type code bigint +hapi_org_type description text +hapi_org_type index bigint +hapi_population adm0_code text +hapi_population adm1_code text +hapi_population adm2_code text +hapi_population admin1_name text +hapi_population admin2_name text +hapi_population age_range_code text +hapi_population dataset_hapi_stub text +hapi_population gender_code text +hapi_population index bigint +hapi_population location_name text +hapi_population population bigint +hapi_population reference_period_end text +hapi_population reference_period_start text +hapi_population resource_hapi_id text +hapi_population_group code text +hapi_population_group description text +hapi_population_group index bigint +hapi_population_status code text +hapi_population_status description text +hapi_population_status index bigint +hapi_resource dataset_hapi_api_link text +hapi_resource dataset_hapi_id text +hapi_resource dataset_hapi_link text +hapi_resource dataset_hapi_provider_name text +hapi_resource dataset_hapi_provider_stub text +hapi_resource dataset_hapi_stub text +hapi_resource dataset_title text +hapi_resource download_url text +hapi_resource format text +hapi_resource hapi_api_link text +hapi_resource hapi_id text +hapi_resource hapi_link text +hapi_resource index bigint +hapi_resource is_hxl boolean +hapi_resource name text +hapi_resource update_date text +hapi_sector code text +hapi_sector index bigint +hapi_sector name text +hapi_shape_files ADM0_AR text +hapi_shape_files ADM0_EN text +hapi_shape_files ADM0_ES text +hapi_shape_files ADM0_FR text +hapi_shape_files ADM0_HT text +hapi_shape_files ADM0_MY text +hapi_shape_files ADM0_PT text +hapi_shape_files ADM0_RU text +hapi_shape_files ADM0_UA text +hapi_shape_files ADM1ALT1AR text +hapi_shape_files ADM1ALT1EN text +hapi_shape_files ADM1ALT1ES text +hapi_shape_files ADM1ALT1FR text +hapi_shape_files ADM1ALT1HT text +hapi_shape_files ADM1ALT1PT text +hapi_shape_files ADM1ALT2AR text +hapi_shape_files ADM1ALT2EN text +hapi_shape_files ADM1ALT2ES text +hapi_shape_files ADM1ALT2FR text +hapi_shape_files ADM1ALT2HT text +hapi_shape_files ADM1ALT2PT text +hapi_shape_files ADM1_ALTPC text +hapi_shape_files ADM1_AR text +hapi_shape_files ADM1_EN text +hapi_shape_files ADM1_ES text +hapi_shape_files ADM1_FR text +hapi_shape_files ADM1_HT text +hapi_shape_files ADM1_MY text +hapi_shape_files ADM1_PT text +hapi_shape_files ADM1_REF text +hapi_shape_files ADM1_RU text +hapi_shape_files ADM1_UA text +hapi_shape_files ADM2ALT1AR text +hapi_shape_files ADM2ALT1EN text +hapi_shape_files ADM2ALT1ES text +hapi_shape_files ADM2ALT1FR text +hapi_shape_files ADM2ALT1HT text +hapi_shape_files ADM2ALT1PT text +hapi_shape_files ADM2ALT2AR text +hapi_shape_files ADM2ALT2EN text +hapi_shape_files ADM2ALT2ES text +hapi_shape_files ADM2ALT2FR text +hapi_shape_files ADM2ALT2HT text +hapi_shape_files ADM2ALT2PT text +hapi_shape_files ADM2_AR text +hapi_shape_files ADM2_EN text +hapi_shape_files ADM2_ES text +hapi_shape_files ADM2_FR text +hapi_shape_files ADM2_HT text +hapi_shape_files ADM2_MY text +hapi_shape_files ADM2_PT text +hapi_shape_files ADM2_REF text +hapi_shape_files ADM2_RU text +hapi_shape_files ADM2_UA text +hapi_shape_files AREA_SQKM double precision +hapi_shape_files OBJECTID double precision +hapi_shape_files SD_EN text +hapi_shape_files SD_PCODE text +hapi_shape_files Shape_Area double precision +hapi_shape_files Shape_Leng double precision +hapi_shape_files ValidTo text +hapi_shape_files adm0_code text +hapi_shape_files adm1_code text +hapi_shape_files adm2_code text +hapi_shape_files admin0Name text +hapi_shape_files admin1Al_1 text +hapi_shape_files admin1AltN text +hapi_shape_files admin1Na_1 text +hapi_shape_files admin1Name text +hapi_shape_files admin1RefN text +hapi_shape_files admin2Al_1 text +hapi_shape_files admin2AltN text +hapi_shape_files admin2Na_1 text +hapi_shape_files admin2Name text +hapi_shape_files admin2RefN text +hapi_shape_files date text +hapi_shape_files geometry USER-DEFINED +hapi_shape_files validOn text +hapi_shape_files validTo text \ No newline at end of file From 3b6ceecc3f3f6e1796b93b234f1e4deb51f07c8f Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Wed, 1 May 2024 18:53:29 -0400 Subject: [PATCH 13/20] Renaming --- ingestion/ingest.py | 244 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 244 insertions(+) create mode 100644 ingestion/ingest.py diff --git a/ingestion/ingest.py b/ingestion/ingest.py new file mode 100644 index 00000000..ad1add67 --- /dev/null +++ b/ingestion/ingest.py @@ -0,0 +1,244 @@ +import requests +import json +import os +import time +from urllib.parse import urlencode +import sys +import pandas as pd +from dotenv import load_dotenv +from sqlalchemy import create_engine + +APIS_CONFIG = "apis.config" + +def get_api_def(api): + + api_name = api["api_name"] + api_host = api["openapi_def"].split("/")[2] + openapi_def = api["openapi_def"] + openapi_filename = f"./api/{api_name}/{openapi_def.split('/')[-1]}" + + print(f"Getting {api_name} API definition from {openapi_def} and saving it to {openapi_filename}") + + api = requests.get(openapi_def) + api = json.loads(api.text) + + with open(openapi_filename, "w") as f: + apis_formatted = json.dumps(api, indent=4, sort_keys=True) + f.write(apis_formatted) + + # Needed for some application using openapi's definition + if 'servers' not in api: + api['servers'] = [ + { + "url": f"https:/{api_host}" + } + ] + + return api + +def get_api_data(endpoint, params): + + print('URL', endpoint + '/?' + urlencode(params)) + response = requests.get(endpoint, params=params) + if response.status_code == 200: + data = response.json() + if isinstance(data, list): + return data + else: + return [data] + else: + msg = "No data was returned for endpoint:" + endpoint + print(msg) + return msg + + +def download_openapi_data(api_host, openapi_def, excluded_endpoints, save_path): + """ + Downloads data based on the functions specified in the openapi.json definition file. + + TODO: This currently assumes paging per the new HAPI API, and would need work to + extend to other approaches. + + Args: + api_hiost: Host URL + openapi_def (str): The path to the openapi JSON file. + save_path (str): Where to save the data + + """ + + limit = 1000 + offset = 0 + + files = os.listdir(save_path) + for f in files: + if 'openapi.json' not in f: + filename = f"{save_path}/{f}" + os.remove(filename) + + for endpoint in openapi_def["paths"]: + if endpoint in excluded_endpoints: + print(f"Skipping {endpoint}") + continue + print(endpoint) + if "get" not in openapi_def["paths"][endpoint]: + print(f"Skipping endpoint with no 'get' method {endpoint}") + continue + url = f"https://{api_host}/{endpoint}" + print(url) + + data = [] + offset = 0 + output = [] + while len(output) > 0 or offset == 0: + output = get_api_data(url, {'limit':limit, 'offset': offset}) + print(output) + data = data + output + print(len(data), len(output)) + offset = offset + limit + time.sleep(1) + + if len(data) > 0: + endpoint_clean = endpoint.replace("/", "_") + if endpoint_clean[0] == "_": + endpoint_clean = endpoint_clean[1:] + + print(len(data), "Before DF") + df = pd.DataFrame(data) + #df = map_code_cols(df, col_map) + #df = filter_hdx_df(df) + print(df.shape[0], "After DF") + file_name = f"{save_path}/{endpoint_clean}.csv" + df.to_csv(file_name, index=False) + with open(f"{save_path}/{endpoint_clean}_meta.json", "w") as f: + full_meta = openapi_def["paths"][endpoint] + f.write(json.dumps(full_meta, indent=4)) + + print(f"Saved {file_name}") + + +def read_apis_config(): + with open(APIS_CONFIG) as f: + print("Reading apis.config") + apis = json.load(f) + return apis + +def connect_to_db(): + """ + Connects to the PostgreSQL database using the environment variables for host, port, database, user, and password. + + Returns: + sqlalchemy.engine.base.Engine: The database connection engine. + """ + + load_dotenv("../.env") + + host = os.getenv("POSTGRES_DATA_HOST") + host = 'localhost' + port = os.getenv("POSTGRES_DATA_PORT") + database = os.getenv("POSTGRES_DATA_DB") + user = os.getenv("POSTGRES_DATA_USER") + password = os.getenv("POSTGRES_DATA_PASSWORD") + conn_str = f"postgresql://{user}:{password}@{host}:{port}/{database}" + print(conn_str) + try: + conn = create_engine(conn_str) + return conn + except Exception as error: + print("--------------- Error while connecting to PostgreSQL", error) + + +def sanitize_name(name): + """ + Sanitizes the given name by removing '.csv', replacing '-' with '_', removing 'a__', + removing 'd__', and replacing '.' with '_'. + + Args: + name (str): The name to be sanitized. + + Returns: + str: The sanitized name. + """ + table_name = ( + name.replace(".csv", "") + .replace("-", "_") + .replace("a__", "") + .replace("d__", "") + .replace(".", "_") + .replace("api_v1_themes_", "") + .replace("api_v1_", "") + ) + + return table_name + + +def upload_csv_files(files_dir, conn, api_name): + """ + Uploads CSV files from a directory to a SQLite database. + + Args: + files_dir (str): The directory path where the CSV files are located. + conn (sqlite3.Connection): The SQLite database connection object. + api_name (str): Name of the api, eg hapi + + Returns: + None + """ + datafiles = os.listdir(files_dir) + for f in datafiles: + if f.endswith(".csv"): + df = pd.read_csv(f"{files_dir}/{f}") + table = f"{api_name}_{sanitize_name(f)}" + print(f"Creating table {table} from {f}") + df.to_sql(table, conn, if_exists="replace") + + +def upload_shape_files(files_dir, conn): + """ + Uploads shape files from a directory to a PostgreSQL database. + + Args: + files_dir (str): The directory path where the shape files are located. + conn (psycopg2.extensions.connection): The PostgreSQL database connection. + + Returns: + None + """ + if not os.path.exists("./tmp"): + os.makedirs("./tmp") + else: + for f in os.listdir("./tmp"): + os.remove(f"./tmp/{f}") + for f in os.listdir(files_dir): + if f.endswith(".zip"): + print(f"Unzipping {f}") + os.system(f"unzip {files_dir}/{f} -d ./tmp") + df_list = [] + for f in os.listdir("./tmp"): + if f.endswith(".shp"): + df = gpd.read_file(f"./tmp/{f}") + table = sanitize_name(f) + print(f"Processing table {table} from {f}") + df_list.append(df) + all_shapes = pd.concat(df_list, ignore_index=True) + print(all_shapes.shape) + all_shapes.to_postgis("hdx_shape_files", conn, if_exists="replace") + + +def main(): + apis = read_apis_config() + conn = connect_to_db() + for api in apis: + openapi_def = get_api_def(api) + api_name = api["api_name"] + save_path = f'./api/{api_name}/' + api_host = api["openapi_def"].split("/")[2] + excluded_endpoints = api["excluded_endpoints"] + + # Extract data from remote APIs which are defined in apis.config + #download_openapi_data(api_host, openapi_def, excluded_endpoints, save_path) + + # Upload CSV files to the database + upload_csv_files(save_path, conn, api_name) + +if __name__ == "__main__": + main() \ No newline at end of file From e1a5d7272b358d4166256fb492f938a7b21bbb2c Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Wed, 1 May 2024 18:53:47 -0400 Subject: [PATCH 14/20] Renaming --- ingestion/openapi_ingestion.py | 133 --------------------------------- 1 file changed, 133 deletions(-) delete mode 100644 ingestion/openapi_ingestion.py diff --git a/ingestion/openapi_ingestion.py b/ingestion/openapi_ingestion.py deleted file mode 100644 index 4ba84f33..00000000 --- a/ingestion/openapi_ingestion.py +++ /dev/null @@ -1,133 +0,0 @@ -import requests -import json -import os -import time -from urllib.parse import urlencode -import sys -import pandas as pd - -APIS_CONFIG = "apis.config" - -def get_api_def(api): - - api_name = api["api_name"] - api_host = api["openapi_def"].split("/")[2] - openapi_def = api["openapi_def"] - openapi_filename = f"./api/{api_name}/{openapi_def.split('/')[-1]}" - - print(f"Getting {api_name} API definition from {openapi_def} and saving it to {openapi_filename}") - - api = requests.get(openapi_def) - api = json.loads(api.text) - - with open(openapi_filename, "w") as f: - apis_formatted = json.dumps(api, indent=4, sort_keys=True) - f.write(apis_formatted) - - # Needed for some application using openapi's definition - if 'servers' not in api: - api['servers'] = [ - { - "url": f"https:/{api_host}" - } - ] - - return api - -def get_api_data(endpoint, params): - - print('URL', endpoint + '/?' + urlencode(params)) - response = requests.get(endpoint, params=params) - if response.status_code == 200: - data = response.json() - if isinstance(data, list): - return data - else: - return [data] - else: - msg = "No data was returned for endpoint:" + endpoint - print(msg) - return msg - - -def download_data(api_host, openapi_def, excluded_endpoints, save_path): - """ - Downloads data based on the functions specified in the openapi.json definition file. - - TODO: This currently assumes paging per the new HAPI API, and would need work to - extend to other approaches. - - Args: - api_hiost: Host URL - openapi_def (str): The path to the openapi JSON file. - save_path (str): Where to save the data - - """ - - limit = 1000 - offset = 0 - - files = os.listdir(save_path) - for f in files: - if 'openapi.json' not in f: - filename = f"{save_path}/{f}" - os.remove(filename) - - for endpoint in openapi_def["paths"]: - if endpoint in excluded_endpoints: - print(f"Skipping {endpoint}") - continue - print(endpoint) - if "get" not in openapi_def["paths"][endpoint]: - print(f"Skipping endpoint with no 'get' method {endpoint}") - continue - url = f"https://{api_host}/{endpoint}" - print(url) - - data = [] - offset = 0 - output = [] - while len(output) > 0 or offset == 0: - output = get_api_data(url, {'limit':limit, 'offset': offset}) - print(output) - data = data + output - print(len(data), len(output)) - offset = offset + limit - time.sleep(1) - - if len(data) > 0: - endpoint_clean = endpoint.replace("/", "_") - if endpoint_clean[0] == "_": - endpoint_clean = endpoint_clean[1:] - - print(len(data), "Before DF") - df = pd.DataFrame(data) - #df = map_code_cols(df, col_map) - #df = filter_hdx_df(df) - print(df.shape[0], "After DF") - file_name = f"{save_path}/{endpoint_clean}.csv" - df.to_csv(file_name, index=False) - with open(f"{save_path}/{endpoint_clean}_meta.json", "w") as f: - full_meta = openapi_def["paths"][endpoint] - f.write(json.dumps(full_meta, indent=4)) - - print(f"Saved {file_name}") - - -def read_apis_config(): - with open(APIS_CONFIG) as f: - print("Reading apis.config") - apis = json.load(f) - return apis - -def main(): - apis = read_apis_config() - for api in apis: - openapi_def = get_api_def(api) - save_path = f'./api/{api["api_name"]}/' - api_host = api["openapi_def"].split("/")[2] - excluded_endpoints = api["excluded_endpoints"] - download_data(api_host, openapi_def, excluded_endpoints, save_path) - -if __name__ == "__main__": - main() \ No newline at end of file From e36a797cf2b10bdd003a9a5b76329ee97cc9b872 Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Wed, 1 May 2024 18:58:47 -0400 Subject: [PATCH 15/20] Various tweaks --- .../prompts/sql_actions_assistant.jinja | 148 +++++++++--------- ingestion/ingest.py | 4 +- 2 files changed, 77 insertions(+), 75 deletions(-) diff --git a/assistant/recipes_assistant/prompts/sql_actions_assistant.jinja b/assistant/recipes_assistant/prompts/sql_actions_assistant.jinja index 68eaee86..069963d1 100644 --- a/assistant/recipes_assistant/prompts/sql_actions_assistant.jinja +++ b/assistant/recipes_assistant/prompts/sql_actions_assistant.jinja @@ -12,7 +12,7 @@ When asked to do a task, first inform the user how you will perform the task NEVER EVER generate Python using sample data, you MUST always use data you got from calling the SQL action. If no data is retuned after trying, inform the user. -adm0_code are 3-leter country ISO codes +location_code are 3-leter country ISO codes Always display images if you analysis creates one @@ -28,9 +28,9 @@ Unless reference_period_start or reference_period_start are part of an output gr Here is a list of tables and their columns ... Table, Column, Column Type -hapi_3W adm0_code text -hapi_3W adm1_code text -hapi_3W adm2_code text +hapi_3W admin0_code text +hapi_3W admin1_code text +hapi_3W admin2_code text hapi_3W admin1_name text hapi_3W admin2_name text hapi_3W dataset_hapi_stub text @@ -43,13 +43,13 @@ hapi_3W reference_period_start text hapi_3W resource_hapi_id text hapi_3W sector_code text hapi_3W sector_name text -hapi_admin1 adm0_code text +hapi_admin1 admin0_code text hapi_admin1 code text hapi_admin1 index bigint hapi_admin1 location_name text hapi_admin1 name text -hapi_admin2 adm0_code text -hapi_admin2 adm1_code text +hapi_admin2 admin0_code text +hapi_admin2 admin1_code text hapi_admin2 admin1_name text hapi_admin2 code text hapi_admin2 index bigint @@ -67,9 +67,9 @@ hapi_dataset hapi_provider_stub text hapi_dataset hapi_stub text hapi_dataset index bigint hapi_dataset title text -hapi_food_security adm0_code text -hapi_food_security adm1_code text -hapi_food_security adm2_code text +hapi_food_security admin0_code text +hapi_food_security admin1_code text +hapi_food_security admin2_code text hapi_food_security admin1_name text hapi_food_security admin2_name text hapi_food_security dataset_hapi_provider_stub text @@ -87,9 +87,9 @@ hapi_food_security resource_hapi_id text hapi_gender code text hapi_gender description text hapi_gender index bigint -hapi_humanitarian_needs adm0_code text -hapi_humanitarian_needs adm1_code text -hapi_humanitarian_needs adm2_code text +hapi_humanitarian_needs admin0_code text +hapi_humanitarian_needs admin1_code text +hapi_humanitarian_needs admin2_code text hapi_humanitarian_needs admin1_name text hapi_humanitarian_needs admin2_name text hapi_humanitarian_needs age_range_code double precision @@ -110,7 +110,7 @@ hapi_humanitarian_needs sector_name double precision hapi_location code text hapi_location index bigint hapi_location name text -hapi_national_risk adm0_code text +hapi_national_risk admin0_code text hapi_national_risk coping_capacity_risk double precision hapi_national_risk dataset_hapi_provider_stub text hapi_national_risk dataset_hapi_stub text @@ -134,9 +134,9 @@ hapi_org org_type_description text hapi_org_type code bigint hapi_org_type description text hapi_org_type index bigint -hapi_population adm0_code text -hapi_population adm1_code text -hapi_population adm2_code text +hapi_population admin0_code text +hapi_population admin1_code text +hapi_population admin2_code text hapi_population admin1_name text hapi_population admin2_name text hapi_population age_range_code text @@ -173,60 +173,60 @@ hapi_resource update_date text hapi_sector code text hapi_sector index bigint hapi_sector name text -hapi_shape_files ADM0_AR text -hapi_shape_files ADM0_EN text -hapi_shape_files ADM0_ES text -hapi_shape_files ADM0_FR text -hapi_shape_files ADM0_HT text -hapi_shape_files ADM0_MY text -hapi_shape_files ADM0_PT text -hapi_shape_files ADM0_RU text -hapi_shape_files ADM0_UA text -hapi_shape_files ADM1ALT1AR text -hapi_shape_files ADM1ALT1EN text -hapi_shape_files ADM1ALT1ES text -hapi_shape_files ADM1ALT1FR text -hapi_shape_files ADM1ALT1HT text -hapi_shape_files ADM1ALT1PT text -hapi_shape_files ADM1ALT2AR text -hapi_shape_files ADM1ALT2EN text -hapi_shape_files ADM1ALT2ES text -hapi_shape_files ADM1ALT2FR text -hapi_shape_files ADM1ALT2HT text -hapi_shape_files ADM1ALT2PT text -hapi_shape_files ADM1_ALTPC text -hapi_shape_files ADM1_AR text -hapi_shape_files ADM1_EN text -hapi_shape_files ADM1_ES text -hapi_shape_files ADM1_FR text -hapi_shape_files ADM1_HT text -hapi_shape_files ADM1_MY text -hapi_shape_files ADM1_PT text -hapi_shape_files ADM1_REF text -hapi_shape_files ADM1_RU text -hapi_shape_files ADM1_UA text -hapi_shape_files ADM2ALT1AR text -hapi_shape_files ADM2ALT1EN text -hapi_shape_files ADM2ALT1ES text -hapi_shape_files ADM2ALT1FR text -hapi_shape_files ADM2ALT1HT text -hapi_shape_files ADM2ALT1PT text -hapi_shape_files ADM2ALT2AR text -hapi_shape_files ADM2ALT2EN text -hapi_shape_files ADM2ALT2ES text -hapi_shape_files ADM2ALT2FR text -hapi_shape_files ADM2ALT2HT text -hapi_shape_files ADM2ALT2PT text -hapi_shape_files ADM2_AR text -hapi_shape_files ADM2_EN text -hapi_shape_files ADM2_ES text -hapi_shape_files ADM2_FR text -hapi_shape_files ADM2_HT text -hapi_shape_files ADM2_MY text -hapi_shape_files ADM2_PT text -hapi_shape_files ADM2_REF text -hapi_shape_files ADM2_RU text -hapi_shape_files ADM2_UA text +hapi_shape_files admin0_AR text +hapi_shape_files admin0_EN text +hapi_shape_files admin0_ES text +hapi_shape_files admin0_FR text +hapi_shape_files admin0_HT text +hapi_shape_files admin0_MY text +hapi_shape_files admin0_PT text +hapi_shape_files admin0_RU text +hapi_shape_files admin0_UA text +hapi_shape_files admin1ALT1AR text +hapi_shape_files admin1ALT1EN text +hapi_shape_files admin1ALT1ES text +hapi_shape_files admin1ALT1FR text +hapi_shape_files admin1ALT1HT text +hapi_shape_files admin1ALT1PT text +hapi_shape_files admin1ALT2AR text +hapi_shape_files admin1ALT2EN text +hapi_shape_files admin1ALT2ES text +hapi_shape_files admin1ALT2FR text +hapi_shape_files admin1ALT2HT text +hapi_shape_files admin1ALT2PT text +hapi_shape_files admin1_ALTPC text +hapi_shape_files admin1_AR text +hapi_shape_files admin1_EN text +hapi_shape_files admin1_ES text +hapi_shape_files admin1_FR text +hapi_shape_files admin1_HT text +hapi_shape_files admin1_MY text +hapi_shape_files admin1_PT text +hapi_shape_files admin1_REF text +hapi_shape_files admin1_RU text +hapi_shape_files admin1_UA text +hapi_shape_files admin2ALT1AR text +hapi_shape_files admin2ALT1EN text +hapi_shape_files admin2ALT1ES text +hapi_shape_files admin2ALT1FR text +hapi_shape_files admin2ALT1HT text +hapi_shape_files admin2ALT1PT text +hapi_shape_files admin2ALT2AR text +hapi_shape_files admin2ALT2EN text +hapi_shape_files admin2ALT2ES text +hapi_shape_files admin2ALT2FR text +hapi_shape_files admin2ALT2HT text +hapi_shape_files admin2ALT2PT text +hapi_shape_files admin2_AR text +hapi_shape_files admin2_EN text +hapi_shape_files admin2_ES text +hapi_shape_files admin2_FR text +hapi_shape_files admin2_HT text +hapi_shape_files admin2_MY text +hapi_shape_files admin2_PT text +hapi_shape_files admin2_REF text +hapi_shape_files admin2_RU text +hapi_shape_files admin2_UA text hapi_shape_files AREA_SQKM double precision hapi_shape_files OBJECTID double precision hapi_shape_files SD_EN text @@ -234,9 +234,9 @@ hapi_shape_files SD_PCODE text hapi_shape_files Shape_Area double precision hapi_shape_files Shape_Leng double precision hapi_shape_files ValidTo text -hapi_shape_files adm0_code text -hapi_shape_files adm1_code text -hapi_shape_files adm2_code text +hapi_shape_files admin0_code text +hapi_shape_files admin1_code text +hapi_shape_files admin2_code text hapi_shape_files admin0Name text hapi_shape_files admin1Al_1 text hapi_shape_files admin1AltN text diff --git a/ingestion/ingest.py b/ingestion/ingest.py index ad1add67..71dccb76 100644 --- a/ingestion/ingest.py +++ b/ingestion/ingest.py @@ -238,7 +238,9 @@ def main(): #download_openapi_data(api_host, openapi_def, excluded_endpoints, save_path) # Upload CSV files to the database - upload_csv_files(save_path, conn, api_name) + #upload_csv_files(save_path, conn, api_name) + + # Upload metadata file here if __name__ == "__main__": main() \ No newline at end of file From 40360579acb15b6782c1e1bb0d6213d147d613f3 Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Wed, 1 May 2024 19:07:31 -0400 Subject: [PATCH 16/20] Implementing hokey code mapping for now --- .../prompts/sql_actions_assistant.jinja | 204 +++++++++--------- 1 file changed, 102 insertions(+), 102 deletions(-) diff --git a/assistant/recipes_assistant/prompts/sql_actions_assistant.jinja b/assistant/recipes_assistant/prompts/sql_actions_assistant.jinja index 069963d1..7cf27c36 100644 --- a/assistant/recipes_assistant/prompts/sql_actions_assistant.jinja +++ b/assistant/recipes_assistant/prompts/sql_actions_assistant.jinja @@ -12,7 +12,7 @@ When asked to do a task, first inform the user how you will perform the task NEVER EVER generate Python using sample data, you MUST always use data you got from calling the SQL action. If no data is retuned after trying, inform the user. -location_code are 3-leter country ISO codes +adm0_code are 3-leter country ISO codes Always display images if you analysis creates one @@ -28,11 +28,11 @@ Unless reference_period_start or reference_period_start are part of an output gr Here is a list of tables and their columns ... Table, Column, Column Type -hapi_3W admin0_code text -hapi_3W admin1_code text -hapi_3W admin2_code text -hapi_3W admin1_name text -hapi_3W admin2_name text +hapi_3W adm0_code text +hapi_3W adm1_code text +hapi_3W adm2_code text +hapi_3W adm1_name text +hapi_3W adm2_name text hapi_3W dataset_hapi_stub text hapi_3W index bigint hapi_3W location_name text @@ -43,18 +43,18 @@ hapi_3W reference_period_start text hapi_3W resource_hapi_id text hapi_3W sector_code text hapi_3W sector_name text -hapi_admin1 admin0_code text -hapi_admin1 code text -hapi_admin1 index bigint -hapi_admin1 location_name text -hapi_admin1 name text -hapi_admin2 admin0_code text -hapi_admin2 admin1_code text -hapi_admin2 admin1_name text -hapi_admin2 code text -hapi_admin2 index bigint -hapi_admin2 location_name text -hapi_admin2 name text +hapi_adm1 adm0_code text +hapi_adm1 code text +hapi_adm1 index bigint +hapi_adm1 location_name text +hapi_adm1 name text +hapi_adm2 adm0_code text +hapi_adm2 adm1_code text +hapi_adm2 adm1_name text +hapi_adm2 code text +hapi_adm2 index bigint +hapi_adm2 location_name text +hapi_adm2 name text hapi_age_range age_max double precision hapi_age_range age_min bigint hapi_age_range code text @@ -67,11 +67,11 @@ hapi_dataset hapi_provider_stub text hapi_dataset hapi_stub text hapi_dataset index bigint hapi_dataset title text -hapi_food_security admin0_code text -hapi_food_security admin1_code text -hapi_food_security admin2_code text -hapi_food_security admin1_name text -hapi_food_security admin2_name text +hapi_food_security adm0_code text +hapi_food_security adm1_code text +hapi_food_security adm2_code text +hapi_food_security adm1_name text +hapi_food_security adm2_name text hapi_food_security dataset_hapi_provider_stub text hapi_food_security dataset_hapi_stub text hapi_food_security index bigint @@ -87,11 +87,11 @@ hapi_food_security resource_hapi_id text hapi_gender code text hapi_gender description text hapi_gender index bigint -hapi_humanitarian_needs admin0_code text -hapi_humanitarian_needs admin1_code text -hapi_humanitarian_needs admin2_code text -hapi_humanitarian_needs admin1_name text -hapi_humanitarian_needs admin2_name text +hapi_humanitarian_needs adm0_code text +hapi_humanitarian_needs adm1_code text +hapi_humanitarian_needs adm2_code text +hapi_humanitarian_needs adm1_name text +hapi_humanitarian_needs adm2_name text hapi_humanitarian_needs age_range_code double precision hapi_humanitarian_needs dataset_hapi_provider_stub text hapi_humanitarian_needs dataset_hapi_stub text @@ -110,7 +110,7 @@ hapi_humanitarian_needs sector_name double precision hapi_location code text hapi_location index bigint hapi_location name text -hapi_national_risk admin0_code text +hapi_national_risk adm0_code text hapi_national_risk coping_capacity_risk double precision hapi_national_risk dataset_hapi_provider_stub text hapi_national_risk dataset_hapi_stub text @@ -134,11 +134,11 @@ hapi_org org_type_description text hapi_org_type code bigint hapi_org_type description text hapi_org_type index bigint -hapi_population admin0_code text -hapi_population admin1_code text -hapi_population admin2_code text -hapi_population admin1_name text -hapi_population admin2_name text +hapi_population adm0_code text +hapi_population adm1_code text +hapi_population adm2_code text +hapi_population adm1_name text +hapi_population adm2_name text hapi_population age_range_code text hapi_population dataset_hapi_stub text hapi_population gender_code text @@ -173,60 +173,60 @@ hapi_resource update_date text hapi_sector code text hapi_sector index bigint hapi_sector name text -hapi_shape_files admin0_AR text -hapi_shape_files admin0_EN text -hapi_shape_files admin0_ES text -hapi_shape_files admin0_FR text -hapi_shape_files admin0_HT text -hapi_shape_files admin0_MY text -hapi_shape_files admin0_PT text -hapi_shape_files admin0_RU text -hapi_shape_files admin0_UA text -hapi_shape_files admin1ALT1AR text -hapi_shape_files admin1ALT1EN text -hapi_shape_files admin1ALT1ES text -hapi_shape_files admin1ALT1FR text -hapi_shape_files admin1ALT1HT text -hapi_shape_files admin1ALT1PT text -hapi_shape_files admin1ALT2AR text -hapi_shape_files admin1ALT2EN text -hapi_shape_files admin1ALT2ES text -hapi_shape_files admin1ALT2FR text -hapi_shape_files admin1ALT2HT text -hapi_shape_files admin1ALT2PT text -hapi_shape_files admin1_ALTPC text -hapi_shape_files admin1_AR text -hapi_shape_files admin1_EN text -hapi_shape_files admin1_ES text -hapi_shape_files admin1_FR text -hapi_shape_files admin1_HT text -hapi_shape_files admin1_MY text -hapi_shape_files admin1_PT text -hapi_shape_files admin1_REF text -hapi_shape_files admin1_RU text -hapi_shape_files admin1_UA text -hapi_shape_files admin2ALT1AR text -hapi_shape_files admin2ALT1EN text -hapi_shape_files admin2ALT1ES text -hapi_shape_files admin2ALT1FR text -hapi_shape_files admin2ALT1HT text -hapi_shape_files admin2ALT1PT text -hapi_shape_files admin2ALT2AR text -hapi_shape_files admin2ALT2EN text -hapi_shape_files admin2ALT2ES text -hapi_shape_files admin2ALT2FR text -hapi_shape_files admin2ALT2HT text -hapi_shape_files admin2ALT2PT text -hapi_shape_files admin2_AR text -hapi_shape_files admin2_EN text -hapi_shape_files admin2_ES text -hapi_shape_files admin2_FR text -hapi_shape_files admin2_HT text -hapi_shape_files admin2_MY text -hapi_shape_files admin2_PT text -hapi_shape_files admin2_REF text -hapi_shape_files admin2_RU text -hapi_shape_files admin2_UA text +hapi_shape_files adm0_AR text +hapi_shape_files adm0_EN text +hapi_shape_files adm0_ES text +hapi_shape_files adm0_FR text +hapi_shape_files adm0_HT text +hapi_shape_files adm0_MY text +hapi_shape_files adm0_PT text +hapi_shape_files adm0_RU text +hapi_shape_files adm0_UA text +hapi_shape_files adm1ALT1AR text +hapi_shape_files adm1ALT1EN text +hapi_shape_files adm1ALT1ES text +hapi_shape_files adm1ALT1FR text +hapi_shape_files adm1ALT1HT text +hapi_shape_files adm1ALT1PT text +hapi_shape_files adm1ALT2AR text +hapi_shape_files adm1ALT2EN text +hapi_shape_files adm1ALT2ES text +hapi_shape_files adm1ALT2FR text +hapi_shape_files adm1ALT2HT text +hapi_shape_files adm1ALT2PT text +hapi_shape_files adm1_ALTPC text +hapi_shape_files adm1_AR text +hapi_shape_files adm1_EN text +hapi_shape_files adm1_ES text +hapi_shape_files adm1_FR text +hapi_shape_files adm1_HT text +hapi_shape_files adm1_MY text +hapi_shape_files adm1_PT text +hapi_shape_files adm1_REF text +hapi_shape_files adm1_RU text +hapi_shape_files adm1_UA text +hapi_shape_files adm2ALT1AR text +hapi_shape_files adm2ALT1EN text +hapi_shape_files adm2ALT1ES text +hapi_shape_files adm2ALT1FR text +hapi_shape_files adm2ALT1HT text +hapi_shape_files adm2ALT1PT text +hapi_shape_files adm2ALT2AR text +hapi_shape_files adm2ALT2EN text +hapi_shape_files adm2ALT2ES text +hapi_shape_files adm2ALT2FR text +hapi_shape_files adm2ALT2HT text +hapi_shape_files adm2ALT2PT text +hapi_shape_files adm2_AR text +hapi_shape_files adm2_EN text +hapi_shape_files adm2_ES text +hapi_shape_files adm2_FR text +hapi_shape_files adm2_HT text +hapi_shape_files adm2_MY text +hapi_shape_files adm2_PT text +hapi_shape_files adm2_REF text +hapi_shape_files adm2_RU text +hapi_shape_files adm2_UA text hapi_shape_files AREA_SQKM double precision hapi_shape_files OBJECTID double precision hapi_shape_files SD_EN text @@ -234,20 +234,20 @@ hapi_shape_files SD_PCODE text hapi_shape_files Shape_Area double precision hapi_shape_files Shape_Leng double precision hapi_shape_files ValidTo text -hapi_shape_files admin0_code text -hapi_shape_files admin1_code text -hapi_shape_files admin2_code text -hapi_shape_files admin0Name text -hapi_shape_files admin1Al_1 text -hapi_shape_files admin1AltN text -hapi_shape_files admin1Na_1 text -hapi_shape_files admin1Name text -hapi_shape_files admin1RefN text -hapi_shape_files admin2Al_1 text -hapi_shape_files admin2AltN text -hapi_shape_files admin2Na_1 text -hapi_shape_files admin2Name text -hapi_shape_files admin2RefN text +hapi_shape_files adm0_code text +hapi_shape_files adm1_code text +hapi_shape_files adm2_code text +hapi_shape_files adm0Name text +hapi_shape_files adm1Al_1 text +hapi_shape_files adm1AltN text +hapi_shape_files adm1Na_1 text +hapi_shape_files adm1Name text +hapi_shape_files adm1RefN text +hapi_shape_files adm2Al_1 text +hapi_shape_files adm2AltN text +hapi_shape_files adm2Na_1 text +hapi_shape_files adm2Name text +hapi_shape_files adm2RefN text hapi_shape_files date text hapi_shape_files geometry USER-DEFINED hapi_shape_files validOn text From a1313487083deee2822026b7c090ca2de5800af6 Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Wed, 1 May 2024 19:16:52 -0400 Subject: [PATCH 17/20] Add test so ingestion can be run inside docker out outside --- ingestion/ingest.py | 92 +++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 88 insertions(+), 4 deletions(-) diff --git a/ingestion/ingest.py b/ingestion/ingest.py index 71dccb76..0d696b55 100644 --- a/ingestion/ingest.py +++ b/ingestion/ingest.py @@ -10,6 +10,27 @@ APIS_CONFIG = "apis.config" +# We use this to map column names to be the same in all files +# Note that shapefile geopandas columns must be less than 10 characters +# TODO, move this to API config +admin0_code_name = "adm0_code" +admin1_code_name = "adm1_code" +admin2_code_name = "adm2_code" +admin3_code_name = "adm3_code" +col_map = { + "location_code": admin0_code_name, + "admin1_code": admin1_code_name, + "admin2_code": admin2_code_name, + "admin3_code": admin3_code_name, + "ADM0_PCODE": admin0_code_name, + "ADM1_PCODE": admin1_code_name, + "ADM2_PCODE": admin2_code_name, + "ADM3_PCODE": admin3_code_name, + "admin0Pcod": admin0_code_name, + "admin1Pcod": admin1_code_name, + "admin2Pcod": admin2_code_name, +} + def get_api_def(api): api_name = api["api_name"] @@ -104,8 +125,6 @@ def download_openapi_data(api_host, openapi_def, excluded_endpoints, save_path): print(len(data), "Before DF") df = pd.DataFrame(data) - #df = map_code_cols(df, col_map) - #df = filter_hdx_df(df) print(df.shape[0], "After DF") file_name = f"{save_path}/{endpoint_clean}.csv" df.to_csv(file_name, index=False) @@ -122,6 +141,9 @@ def read_apis_config(): apis = json.load(f) return apis +def is_running_in_docker(): + return os.path.exists('/.dockerenv') + def connect_to_db(): """ Connects to the PostgreSQL database using the environment variables for host, port, database, user, and password. @@ -132,7 +154,11 @@ def connect_to_db(): load_dotenv("../.env") - host = os.getenv("POSTGRES_DATA_HOST") + if is_running_in_docker(): + host = os.getenv("POSTGRES_DATA_HOST") + else: + host = 'localhost' + host = 'localhost' port = os.getenv("POSTGRES_DATA_PORT") database = os.getenv("POSTGRES_DATA_DB") @@ -187,6 +213,11 @@ def upload_csv_files(files_dir, conn, api_name): for f in datafiles: if f.endswith(".csv"): df = pd.read_csv(f"{files_dir}/{f}") + df = map_code_cols(df, col_map) + # TODO: This is a temporary workaround to account for HAPI having + # aggregate and disaggregated data in the same tables, where the hierarchy differs by country + if api_name == "hapi": + df = filter_hdx_df(df) table = f"{api_name}_{sanitize_name(f)}" print(f"Creating table {table} from {f}") df.to_sql(table, conn, if_exists="replace") @@ -224,6 +255,59 @@ def upload_shape_files(files_dir, conn): all_shapes.to_postgis("hdx_shape_files", conn, if_exists="replace") +def map_code_cols(df, col_map): + """ + Map columns in a DataFrame to a new set of column names. + + Args: + df (pandas.DataFrame): The DataFrame to be mapped. + col_map (dict): A dictionary containing the mapping of old column names to new column names. + + Returns: + pandas.DataFrame: The mapped DataFrame. + """ + for c in col_map: + if c in df.columns: + df.rename(columns={c: col_map[c]}, inplace=True) + + return df + +def filter_hdx_df(df, **kwargs): + """ + Filter a pandas DataFrame by removing columns where all values are null and removing rows where any value is null. + Hack to get around the fact HDX mixes total values in with disaggregated values in the API + + Args: + df (pandas.DataFrame): The DataFrame to be filtered. + **kwargs: Additional keyword arguments. + + Returns: + pandas.DataFrame: The filtered DataFrame. + """ + df_orig = df.copy() + + if df.shape[0] == 0: + return df_orig + + dfs = [] + if admin0_code_name in df.columns: + for country in df[admin0_code_name].unique(): + df2 = df.copy() + df2 = df2[df2[admin0_code_name] == country] + + # Remove any columns where all null + df2 = df2.dropna(axis=1, how="all") + + # Remove any rows where one of the values is null + df2 = df2.dropna(axis=0, how="any") + + dfs.append(df.iloc[df2.index]) + + df = pd.concat(dfs) + + return df + + def main(): apis = read_apis_config() conn = connect_to_db() @@ -238,7 +322,7 @@ def main(): #download_openapi_data(api_host, openapi_def, excluded_endpoints, save_path) # Upload CSV files to the database - #upload_csv_files(save_path, conn, api_name) + upload_csv_files(save_path, conn, api_name) # Upload metadata file here From 0e7775c61b6b6209123cbe39a265cd4c0ca089e7 Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Wed, 1 May 2024 19:21:43 -0400 Subject: [PATCH 18/20] Add test so ingestion can be run inside docker out outside --- ingestion/ingest.py | 43 +++++++++++++++++++++++++------------------ 1 file changed, 25 insertions(+), 18 deletions(-) diff --git a/ingestion/ingest.py b/ingestion/ingest.py index 0d696b55..1ea7795e 100644 --- a/ingestion/ingest.py +++ b/ingestion/ingest.py @@ -13,22 +13,29 @@ # We use this to map column names to be the same in all files # Note that shapefile geopandas columns must be less than 10 characters # TODO, move this to API config -admin0_code_name = "adm0_code" -admin1_code_name = "adm1_code" -admin2_code_name = "adm2_code" -admin3_code_name = "adm3_code" +admin0_code = "adm0_code" +admin1_code = "adm1_code" +admin2_code = "adm2_code" +admin3_code = "adm3_code" +admin0_name = "adm0_name" +admin1_name = "adm1_name" +admin2_name = "adm2_name" +admin3_name = "adm3_name" col_map = { - "location_code": admin0_code_name, - "admin1_code": admin1_code_name, - "admin2_code": admin2_code_name, - "admin3_code": admin3_code_name, - "ADM0_PCODE": admin0_code_name, - "ADM1_PCODE": admin1_code_name, - "ADM2_PCODE": admin2_code_name, - "ADM3_PCODE": admin3_code_name, - "admin0Pcod": admin0_code_name, - "admin1Pcod": admin1_code_name, - "admin2Pcod": admin2_code_name, + "location_code": admin0_code, + "admin1_code": admin1_code, + "admin2_code": admin2_code, + "admin3_code": admin3_code, + "admin1_name": admin1_name, + "admin2_name": admin2_name, + "admin3_name": admin3_name, + "ADM0_PCODE": admin0_code, + "ADM1_PCODE": admin1_code, + "ADM2_PCODE": admin2_code, + "ADM3_PCODE": admin3_code, + "admin0Pcod": admin0_code, + "admin1Pcod": admin1_code, + "admin2Pcod": admin2_code, } def get_api_def(api): @@ -290,10 +297,10 @@ def filter_hdx_df(df, **kwargs): return df_orig dfs = [] - if admin0_code_name in df.columns: - for country in df[admin0_code_name].unique(): + if admin0_code in df.columns: + for country in df[admin0_code].unique(): df2 = df.copy() - df2 = df2[df2[admin0_code_name] == country] + df2 = df2[df2[admin0_code] == country] # Remove any columns where all null df2 = df2.dropna(axis=1, how="all") From bff79d515a4ee3d6be21d046026b52a5091fc1a1 Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Thu, 2 May 2024 16:09:17 -0400 Subject: [PATCH 19/20] Full upload of HAPI and supporting shapefiles from HDX --- README.md | 10 +- docker-compose.yml | 17 ++- ingestion/Dockerfile | 19 +++ ingestion/api/{hapi => hdx}/.gitkeep | 0 ingestion/ingest.py | 111 ++++++++++---- ingestion/requirements.txt | 11 ++ ingestion/shapefiles.py | 212 +++++++++++++++++++++++++++ 7 files changed, 349 insertions(+), 31 deletions(-) create mode 100644 ingestion/Dockerfile rename ingestion/api/{hapi => hdx}/.gitkeep (100%) create mode 100644 ingestion/requirements.txt create mode 100644 ingestion/shapefiles.py diff --git a/README.md b/README.md index f3f71d38..ba4a28ce 100644 --- a/README.md +++ b/README.md @@ -34,10 +34,12 @@ TODO: This will be automated, but for now ... 1. Got to [chat app](http://localhost:3080/) and register a user on the login page 2. Log in -3. Select Assistants, choose HDeXpert SQL -4. Under actions, create a new action and use the function definition from [here](http://localhost:4001/openapi.json). You'll need to remove the comments at the top and change the host to be 'url' in 'servers' to be "http://actions:8080" -5. Save the action -6. Update the agent +3. `docker exec -it haa-ingestion /bin/bash` +4. `python3 ingest.py` +5. Select Assistants, choose HDeXpert SQL +6. Under actions, create a new action and use the function definition from [here](http://localhost:4001/openapi.json). You'll need to remove the comments at the top and change the host to be 'url' in 'servers' to be "http://actions:8080" +7. Save the action +8. Update the agent Note: You can reset Libre chat by removing contents of `ui/recipes_assistant_chat/data-node/`. This is sometimes neccesary due to a bug in specifying actions. diff --git a/docker-compose.yml b/docker-compose.yml index a0fb96db..aad60410 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -62,7 +62,7 @@ services: - ./ui/recipes_assistant_chat/meili_data_v1.7:/meili_data datadb: #platform: linux/amd64 - image: ankane/pgvector:latest + image: postgis/postgis:12-3.4 container_name: haa-datadb environment: POSTGRES_DB: ${POSTGRES_DATA_DB} @@ -124,6 +124,21 @@ services: - 4001:8087 env_file: - .env + ingestion: + #platform: linux/amd64 + container_name: haa-ingestion + build: + context: . + dockerfile: ./ingestion/Dockerfile + depends_on: + - datadb + restart: always + env_file: + - .env + volumes: + - type: bind + source: ./ingestion + target: /app volumes: pgdata2: \ No newline at end of file diff --git a/ingestion/Dockerfile b/ingestion/Dockerfile new file mode 100644 index 00000000..8a969b80 --- /dev/null +++ b/ingestion/Dockerfile @@ -0,0 +1,19 @@ +FROM python:3.11.4 + +WORKDIR /app + +COPY ./ingestion/requirements.txt ./ + +RUN apt-get update && apt-get install -y --no-install-recommends \ + libgeos-dev \ + && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* + +RUN apt-get update && apt-get install -y --no-install-recommends \ + libgdal-dev \ + && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* + +RUN pip install --no-cache-dir -r requirements.txt + +COPY ./ingestion . + +CMD [ "tail", "-f" , "/dev/null" ] \ No newline at end of file diff --git a/ingestion/api/hapi/.gitkeep b/ingestion/api/hdx/.gitkeep similarity index 100% rename from ingestion/api/hapi/.gitkeep rename to ingestion/api/hdx/.gitkeep diff --git a/ingestion/ingest.py b/ingestion/ingest.py index 1ea7795e..f4724fc0 100644 --- a/ingestion/ingest.py +++ b/ingestion/ingest.py @@ -6,7 +6,11 @@ import sys import pandas as pd from dotenv import load_dotenv -from sqlalchemy import create_engine +from sqlalchemy import create_engine, text +import geopandas as gpd +import shutil + +from shapefiles import download_hdx_boundaries APIS_CONFIG = "apis.config" @@ -162,17 +166,15 @@ def connect_to_db(): load_dotenv("../.env") if is_running_in_docker(): + print("Running in Docker ...") host = os.getenv("POSTGRES_DATA_HOST") else: host = 'localhost' - - host = 'localhost' port = os.getenv("POSTGRES_DATA_PORT") database = os.getenv("POSTGRES_DATA_DB") user = os.getenv("POSTGRES_DATA_USER") password = os.getenv("POSTGRES_DATA_PASSWORD") conn_str = f"postgresql://{user}:{password}@{host}:{port}/{database}" - print(conn_str) try: conn = create_engine(conn_str) return conn @@ -203,10 +205,31 @@ def sanitize_name(name): return table_name +def get_cols_string(table, conn): + """ + Get the columns of a table as a string. + + Args: + table (str): The table name. + conn (sqlalchemy.engine.base.Connection): The database connection object. -def upload_csv_files(files_dir, conn, api_name): + Returns: + str: The columns of the table as a string. + """ + cols = "" + with conn.connect() as connection: + statement = text(f"SELECT column_name, data_type FROM information_schema.columns WHERE table_name = '{table}'") + result = connection.execute(statement) + cols = result.fetchall() + cols_str = "" + for c in cols: + cols_str += f"{c[0]} ({c[1]}); " + return cols_str + +def upload_openapi_csv_files(files_dir, conn, api_name): """ - Uploads CSV files from a directory to a SQLite database. + Uploads CSV files from a directory to Postgres. It assumes files_dir contains CSV files as + well as a metadata json file for each CSV file. Args: files_dir (str): The directory path where the CSV files are located. @@ -217,6 +240,7 @@ def upload_csv_files(files_dir, conn, api_name): None """ datafiles = os.listdir(files_dir) + table_metadata = [] for f in datafiles: if f.endswith(".csv"): df = pd.read_csv(f"{files_dir}/{f}") @@ -227,10 +251,37 @@ def upload_csv_files(files_dir, conn, api_name): df = filter_hdx_df(df) table = f"{api_name}_{sanitize_name(f)}" print(f"Creating table {table} from {f}") - df.to_sql(table, conn, if_exists="replace") - - -def upload_shape_files(files_dir, conn): + df.to_sql(table, conn, if_exists="replace", index=False) + + # Collate metadata + meta_file = f"{files_dir}/{f.replace('.csv', '_meta.json')}" + if os.path.exists(meta_file): + with open(meta_file) as mf: + meta = json.load(mf) + r = {} + r["api_name"] = api_name + r["table_name"] = table + r["summary"] = str(meta["get"]["tags"]) + r["columns"] = get_cols_string(table, conn) + r["api_description"] = meta["get"]["summary"] + if 'description' in meta["get"]: + r["api_description"] += f' : {meta["get"]["description"]}' + r["api_definition"] = str(meta) + r["file_name"] = f + table_metadata.append(r) + + # We could also use Postgres comments, but this is simpler for LLM agents for now + table_metadata = pd.DataFrame(table_metadata) + table_metadata.to_sql("table_metadata", conn, if_exists="replace", index=False) + +def empty_folder(folder): + for f in os.listdir(folder): + try: + os.remove(f"{folder}/{f}") + except IsADirectoryError: + shutil.rmtree(f"{folder}/{f}") + +def upload_hdx_shape_files(files_dir, conn): """ Uploads shape files from a directory to a PostgreSQL database. @@ -241,26 +292,27 @@ def upload_shape_files(files_dir, conn): Returns: None """ - if not os.path.exists("./tmp"): - os.makedirs("./tmp") - else: - for f in os.listdir("./tmp"): - os.remove(f"./tmp/{f}") - for f in os.listdir(files_dir): - if f.endswith(".zip"): - print(f"Unzipping {f}") - os.system(f"unzip {files_dir}/{f} -d ./tmp") + + shape_files_table = "hdx_shape_files" + df_list = [] - for f in os.listdir("./tmp"): + for f in os.listdir(files_dir): if f.endswith(".shp"): - df = gpd.read_file(f"./tmp/{f}") + df = gpd.read_file(f"{files_dir}/{f}") table = sanitize_name(f) print(f"Processing table {table} from {f}") df_list.append(df) all_shapes = pd.concat(df_list, ignore_index=True) print(all_shapes.shape) - all_shapes.to_postgis("hdx_shape_files", conn, if_exists="replace") + all_shapes.to_postgis(shape_files_table, conn, if_exists="replace") + + # Updatre + cols = get_cols_string(shape_files_table, conn) + with conn.connect() as connection: + statement = text(f"INSERT INTO table_metadata (api_name, table_name, summary, columns, api_description, api_definition, file_name) VALUES ('hdx', '{shape_files_table}', \ + 'HDX Shape Files', '{cols}', 'HDX Shape Files', 'HDX Shape Files', 'HDX Shape Files')") + connection.execute(statement) def map_code_cols(df, col_map): """ @@ -319,6 +371,7 @@ def main(): apis = read_apis_config() conn = connect_to_db() for api in apis: + openapi_def = get_api_def(api) api_name = api["api_name"] save_path = f'./api/{api_name}/' @@ -326,12 +379,18 @@ def main(): excluded_endpoints = api["excluded_endpoints"] # Extract data from remote APIs which are defined in apis.config - #download_openapi_data(api_host, openapi_def, excluded_endpoints, save_path) + download_openapi_data(api_host, openapi_def, excluded_endpoints, save_path) + + # Download shapefiles from HDX + download_hdx_boundaries(datafile="./api/hapi/api_v1_themes_population.csv", \ + datafile_country_col='location_code', target_dir="./api/hdx/",\ + col_map=col_map, map_code_cols=map_code_cols) - # Upload CSV files to the database - upload_csv_files(save_path, conn, api_name) + # Upload CSV files to the database, with supporting metadata + upload_openapi_csv_files(save_path, conn, api_name) - # Upload metadata file here + # Upload shapefiles to the database + upload_hdx_shape_files('./api/hdx', conn) if __name__ == "__main__": main() \ No newline at end of file diff --git a/ingestion/requirements.txt b/ingestion/requirements.txt new file mode 100644 index 00000000..8e7a5e9e --- /dev/null +++ b/ingestion/requirements.txt @@ -0,0 +1,11 @@ +geoalchemy2==0.14.6 +geopandas==0.10.2 +hdx-python-api==6.2.1 +hdx-python-country==3.6.4 +hdx-python-utilities==3.6.5 +psycopg2_binary==2.9.9 +python-dotenv==1.0.0 +pandas==1.5.3 +requests==2.31.0 +sqlalchemy==2.0.29 + diff --git a/ingestion/shapefiles.py b/ingestion/shapefiles.py new file mode 100644 index 00000000..169509f5 --- /dev/null +++ b/ingestion/shapefiles.py @@ -0,0 +1,212 @@ +import os +import pandas as pd +from dotenv import load_dotenv +from hdx.api.configuration import Configuration +from hdx.data.dataset import Dataset +from hdx.utilities.easy_logging import setup_logging +import geopandas as gpd +import glob +import shutil +import zipfile + +def get_hdx_config(): + """ + Get the HDX configuration for connecting to HDX API + + Returns: + None + """ + try: + Configuration.create( + hdx_site="prod", user_agent="HAPI-test1", hdx_read_only=True + ) + except Exception as e: + if str(e) == "Configuration already created!": + print("DEBUG: HDX Configuration already created. Continuing...") + else: + print(f"DEBUG: Exception: {e}") + return {"file_location": ""} + return Configuration + +def get_hdx_shapefile(country_code, admin_level): + """ + Retrieves the shapefile for the specified country and administrative level. + + Args: + country_code (str): The 3-letter ISO name of the country, eg MLI + admin_level (str): The administrative level. + + Returns: + dict: A dictionary containing the file location of the shapefile. + + Raises: + None + """ + admin_level = admin_level.replace("admin", "") + + data_dir = "./tmp" + datasets = Dataset.search_in_hdx( + f"cod shapefile {country_code} administrative boundaries" + ) + shape_dataset = f"cod-ab-{country_code.lower()}" + response = "" + # Iterate over the results and download the shapefiles + for dataset in datasets: + if dataset["name"] == shape_dataset: + print(dataset["name"]) + resources = dataset.get_resources() + for resource in resources: + print(resource["name"], resource["format"]) + if "shp" in resource["format"].lower(): + url, path = resource.download() + new_loc = f"{data_dir}/{country_code}.zip" + shutil.move(path, new_loc) + print(f"Shapefile downloaded from {url} and saved to {new_loc}") + + with zipfile.ZipFile(new_loc, "r") as zip_ref: + zip_ref.extractall(f"{data_dir}") + + # Remove extra files + for file in os.listdir(data_dir): + if "zip" in file or "ALL" in file or "pdf" in file: + os.remove(os.path.join(data_dir, file)) + + # Tidy up, we will be zipping this folder. The zipfiles from HDX have differing unpacked layout + files = glob.glob("./tmp/*/*") + for f in files: + if not os.path.isfile(f"./tmp/{f.split('/')[-1]}"): + print(f"Moving {f} to ./tmp") + shutil.move(f, "./tmp") + else: + os.remove(f) + dirs = glob.glob("./tmp/*/") + for d in dirs: + os.rmdir(d) + files = glob.glob("./tmp/*.zip") + for f in files: + os.remove(f) + + return response + +def normalize_hdx_boundaries(datafile, col_map, map_code_cols, datafile_country_col): + """ + HDX Boundaries have inconsistent naming conventions and pcode variable names. This function + attempts to standardize them for easier use in HDeXpert. + + Args: + datafile (str): Path to the data file containing location codes. Default is "./data/hdx_population.csv". + files_prefix (str): The prefix to use for the files. + col_map (dict): A dictionary of column names mapping, used to rename columns to standard names. + map_code_cols (function): A function to map the code columns to standard names. + datafile_country_col (str): The column name in the data file containing the country codes. + + Returns: + None + """ + + output_dir = "./tmp/normalized/" + if not os.path.exists(output_dir): + os.makedirs(output_dir) + + files = glob.glob(f"{output_dir}/*") + for f in files: + os.remove(f) + + df = pd.read_csv(datafile) + print(df.columns) + countries = df[datafile_country_col].unique() + countries = [c.lower() for c in countries] + # TODO: Remove Columbia, it's too big + countries = [c for c in countries if "col" not in c] + for country in countries: + for admin in ["adm1", "adm2"]: + # list off .shp files starting with country_code + match_str = f"./tmp/{country}*{admin}*.shp" + shp_file = glob.glob(match_str) + if len(shp_file) > 0: + print(shp_file) + if len(shp_file) > 0: + if len(shp_file) > 1: + print(f"Multiple shape files found for {country} {admin}") + shp_file = [f for f in shp_file if f"{admin}.shp" in f] + shp_file = shp_file[0] + gdf = gpd.read_file(shp_file) + gdf = map_code_cols(gdf, col_map) + shp_file = shp_file.split(admin)[0] + admin + ".shp" + shp_file = shp_file.replace("./tmp", "") + shp_file = f"{output_dir}/{shp_file[1:]}" + gdf.to_file(shp_file) + return output_dir + + +def download_hdx_boundaries(datafile="./api/hapi/hapi_population.csv", datafile_country_col='location_code', \ + target_dir="./api/hdx/", col_map={}, map_code_cols=None): + + """ + Downloads HDX boundaries for all countries and administrative levels. + + We may use this in some form, but it doesn't seem to have pcodes or admin codes. TODO. + + Args: + datafile (str): Path to the data file containing location codes. Default is "./data/hdx_population.csv". + datafile_country_col (str): The column name in the data file containing the country codes. + files_prefix (str): The prefix to use for the files. + col_map (dict): A dictionary of column names mapping, used to rename columns to standard names. + map_code_cols (function): A function to map the code columns to standard names. + + Returns: + None + """ + tmp_dir = "./tmp" + if not os.path.exists(tmp_dir): + os.makedirs(tmp_dir) + + # Create connection to HDX + get_hdx_config() + + df = pd.read_csv(datafile) + countries = df[datafile_country_col].unique() + countries = [c.lower() for c in countries] + # TODO: Remove Columbia, it's too big + #countries = [c for c in countries if "col" not in c] + + for country in countries: + for admin in ["admin1", "admin2"]: + print(country, admin) + get_hdx_shapefile(country, admin) + + # Align field names with other datasets + output_dir = normalize_hdx_boundaries(datafile, col_map, map_code_cols, datafile_country_col) + + # Copy normalized files to target_dir + files = glob.glob(f"{output_dir}/*") + for f in files: + shutil.copy(f, target_dir) + + # Split shape files into zip files by country letter range and admin level. These + # Are useful for assistants + for admin in ["adm0", "adm1", "adm2"]: + files = glob.glob(f"{output_dir}/*{admin}*") + if len(files) > 0: + if admin != "adm2": + ranges = ["a-z"] + else: + ranges = ["a-c", "d-h", "i-z"] + for letter_range in ranges: + letters = letter_range.split("-") + letters = [chr(i) for i in range(ord(letters[0]), ord(letters[1]) + 1)] + country_sublist = [c for c in countries if c[0].lower() in letters] + + zipfile_path = f"{target_dir}/geoBoundaries-{admin}-countries_{letter_range}.zip" + + with zipfile.ZipFile(zipfile_path, 'w') as zipf: + # Iterate over all files in the output directory + for foldername, subfolders, filenames in os.walk(output_dir): + for filename in filenames: + # Check if the file matches the pattern + if any(admin in filename for admin in country_sublist): + # Get the full file path + file_path = os.path.join(foldername, filename) + # Add the file to the zip file + zipf.write(file_path, arcname=os.path.relpath(file_path, output_dir)) + From b1a7829af939a48261066bfe8af604d0778ef779 Mon Sep 17 00:00:00 2001 From: Matthew Harris Date: Thu, 2 May 2024 16:10:19 -0400 Subject: [PATCH 20/20] Full upload of HAPI and supporting shapefiles from HDX --- .gitignore | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index 5e29cdcc..006dbf4e 100644 --- a/.gitignore +++ b/.gitignore @@ -7,4 +7,5 @@ meili_data_v1.7 images pgdata2 tmp -ingestion/api/hapi/* \ No newline at end of file +ingestion/api/hapi/* +ingestion/api/hdx/* \ No newline at end of file