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[agents] Add support for AstraDB Collections (Astra Vector DB, using …
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java/lib/* |
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examples/applications/webcrawler-astra-vector-db/README.md
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# Indexing a WebSite | ||
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This sample application shows how to use the WebCrawler Source Connector and Astra Vector DB. | ||
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## Collections | ||
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This application creates a collection named "documents" in your DB. | ||
You can change the name of the collection in the file `configuration.yaml`. | ||
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## Configure access to the Vector Database | ||
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Export some ENV variables in order to configure access to the database: | ||
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``` | ||
export ASTRA_VECTOR_DB_TOKEN=AstraCS:... | ||
export ASTRA_VECTOR_DB_ENDPOINT=https://....astra.datastax.com | ||
``` | ||
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You can find the credentials in the Astra DB console. | ||
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The examples/secrets/secrets.yaml resolves those environment variables for you. | ||
When you go in production you are supposed to create a dedicated secrets.yaml file for each environment. | ||
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## Configure the pipeline | ||
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You can edit the file `crawler.yaml` and configure the list of the allowed web domains, this is required in order to not let the crawler escape outside your data. | ||
Configure the list of seed URLs, for instance with your home page. | ||
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The default configuration in this example will crawl the LangStream website. | ||
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## Deploy the LangStream application | ||
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``` | ||
./bin/langstream docker run test -app examples/applications/webcrawler-astra-vector-db -s examples/secrets/secrets.yaml | ||
``` | ||
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## Talk with the Chat bot | ||
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If the application launches successfully, you can talk with the chat bot using UI. | ||
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You can also use the CLI: | ||
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``` | ||
./bin/langstream gateway chat test -cg bot-output -pg user-input -p sessionId=$(uuidgen) | ||
``` |
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examples/applications/webcrawler-astra-vector-db/chatbot.yaml
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# | ||
# Copyright DataStax, Inc. | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
# | ||
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topics: | ||
- name: "questions-topic" | ||
creation-mode: create-if-not-exists | ||
- name: "answers-topic" | ||
creation-mode: create-if-not-exists | ||
- name: "log-topic" | ||
creation-mode: create-if-not-exists | ||
errors: | ||
on-failure: "skip" | ||
pipeline: | ||
- name: "convert-to-structure" | ||
type: "document-to-json" | ||
input: "questions-topic" | ||
configuration: | ||
text-field: "question" | ||
- name: "compute-embeddings" | ||
type: "compute-ai-embeddings" | ||
configuration: | ||
model: "${secrets.open-ai.embeddings-model}" # This needs to match the name of the model deployment, not the base model | ||
embeddings-field: "value.question_embeddings" | ||
text: "{{ value.question }}" | ||
flush-interval: 0 | ||
- name: "lookup-related-documents" | ||
type: "query-vector-db" | ||
configuration: | ||
datasource: "AstraDatasource" | ||
query: | | ||
{ | ||
"collection-name": "${globals.collection-name}", | ||
"limit": 20, | ||
"vector": ? | ||
} | ||
fields: | ||
- "value.question_embeddings" | ||
output-field: "value.related_documents" | ||
- name: "re-rank documents with MMR" | ||
type: "re-rank" | ||
configuration: | ||
max: 5 # keep only the top 5 documents, because we have an hard limit on the prompt size | ||
field: "value.related_documents" | ||
query-text: "value.question" | ||
query-embeddings: "value.question_embeddings" | ||
output-field: "value.related_documents" | ||
text-field: "record.text" | ||
embeddings-field: "record.vector" | ||
algorithm: "MMR" | ||
lambda: 0.5 | ||
k1: 1.2 | ||
b: 0.75 | ||
- name: "ai-chat-completions" | ||
type: "ai-chat-completions" | ||
configuration: | ||
model: "${secrets.open-ai.chat-completions-model}" # This needs to be set to the model deployment name, not the base name | ||
# on the log-topic we add a field with the answer | ||
completion-field: "value.answer" | ||
# we are also logging the prompt we sent to the LLM | ||
log-field: "value.prompt" | ||
# here we configure the streaming behavior | ||
# as soon as the LLM answers with a chunk we send it to the answers-topic | ||
stream-to-topic: "answers-topic" | ||
# on the streaming answer we send the answer as whole message | ||
# the 'value' syntax is used to refer to the whole value of the message | ||
stream-response-completion-field: "value" | ||
# we want to stream the answer as soon as we have 20 chunks | ||
# in order to reduce latency for the first message the agent sends the first message | ||
# with 1 chunk, then with 2 chunks....up to the min-chunks-per-message value | ||
# eventually we want to send bigger messages to reduce the overhead of each message on the topic | ||
min-chunks-per-message: 20 | ||
messages: | ||
- role: system | ||
content: | | ||
An user is going to perform a questions, The documents below may help you in answering to their questions. | ||
Please try to leverage them in your answer as much as possible. | ||
Take into consideration that the user is always asking questions about the LangStream project. | ||
If you provide code or YAML snippets, please explicitly state that they are examples. | ||
Do not provide information that is not related to the LangStream project. | ||
Documents: | ||
{{# value.related_documents}} | ||
{{ text}} | ||
{{/ value.related_documents}} | ||
- role: user | ||
content: "{{ value.question}}" | ||
- name: "cleanup-response" | ||
type: "drop-fields" | ||
output: "log-topic" | ||
configuration: | ||
fields: | ||
- "question_embeddings" | ||
- "related_documents" |
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examples/applications/webcrawler-astra-vector-db/configuration.yaml
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# | ||
# | ||
# Copyright DataStax, Inc. | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
# | ||
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configuration: | ||
defaults: | ||
globals: | ||
collection-name: "documents" | ||
resources: | ||
- type: "open-ai-configuration" | ||
name: "OpenAI Azure configuration" | ||
configuration: | ||
url: "${secrets.open-ai.url}" | ||
access-key: "${secrets.open-ai.access-key}" | ||
provider: "${secrets.open-ai.provider}" | ||
- type: "datasource" | ||
name: "AstraDatasource" | ||
configuration: | ||
service: "astra-vector-db" | ||
token: "${secrets.astra-vector-db.token}" | ||
endpoint: "${secrets.astra-vector-db.endpoint}" |
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examples/applications/webcrawler-astra-vector-db/crawler.yaml
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# | ||
# Copyright DataStax, Inc. | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
# | ||
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name: "Crawl a website" | ||
topics: | ||
- name: "chunks-topic" | ||
creation-mode: create-if-not-exists | ||
resources: | ||
size: 2 | ||
pipeline: | ||
- name: "Crawl the WebSite" | ||
type: "webcrawler-source" | ||
configuration: | ||
seed-urls: ["https://docs.langstream.ai/"] | ||
allowed-domains: ["https://docs.langstream.ai"] | ||
forbidden-paths: [] | ||
min-time-between-requests: 500 | ||
reindex-interval-seconds: 3600 | ||
max-error-count: 5 | ||
max-urls: 1000 | ||
max-depth: 50 | ||
handle-robots-file: true | ||
user-agent: "" # this is computed automatically, but you can override it | ||
scan-html-documents: true | ||
http-timeout: 10000 | ||
handle-cookies: true | ||
max-unflushed-pages: 100 | ||
# store data directly on the agent disk, no need for external S3 storage | ||
state-storage: disk | ||
- name: "Extract text" | ||
type: "text-extractor" | ||
- name: "Normalise text" | ||
type: "text-normaliser" | ||
configuration: | ||
make-lowercase: true | ||
trim-spaces: true | ||
- name: "Detect language" | ||
type: "language-detector" | ||
configuration: | ||
property: "language" | ||
- name: "Split into chunks" | ||
type: "text-splitter" | ||
configuration: | ||
splitter_type: "RecursiveCharacterTextSplitter" | ||
chunk_size: 400 | ||
separators: ["\n\n", "\n", " ", ""] | ||
keep_separator: false | ||
chunk_overlap: 100 | ||
length_function: "cl100k_base" | ||
- name: "Convert to structured data" | ||
type: "document-to-json" | ||
configuration: | ||
text-field: text | ||
copy-properties: true | ||
- name: "prepare-structure" | ||
type: "compute" | ||
configuration: | ||
fields: | ||
- name: "value.filename" | ||
expression: "properties.url" | ||
type: STRING | ||
- name: "value.chunk_id" | ||
expression: "properties.chunk_id" | ||
type: STRING | ||
- name: "value.language" | ||
expression: "properties.language" | ||
type: STRING | ||
- name: "value.chunk_num_tokens" | ||
expression: "properties.chunk_num_tokens" | ||
type: STRING | ||
- name: "compute-embeddings" | ||
id: "step1" | ||
type: "compute-ai-embeddings" | ||
output: "chunks-topic" | ||
configuration: | ||
model: "${secrets.open-ai.embeddings-model}" | ||
embeddings-field: "value.embeddings_vector" | ||
text: "{{ value.text }}" | ||
batch-size: 10 | ||
flush-interval: 500 |
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examples/applications/webcrawler-astra-vector-db/gateways.yaml
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# | ||
# | ||
# Copyright DataStax, Inc. | ||
# | ||
# Licensed under the Apache License, Version 2.0 (the "License"); | ||
# you may not use this file except in compliance with the License. | ||
# You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, software | ||
# distributed under the License is distributed on an "AS IS" BASIS, | ||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
# See the License for the specific language governing permissions and | ||
# limitations under the License. | ||
# | ||
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gateways: | ||
- id: "user-input" | ||
type: produce | ||
topic: "questions-topic" | ||
parameters: | ||
- sessionId | ||
produceOptions: | ||
headers: | ||
- key: langstream-client-session-id | ||
valueFromParameters: sessionId | ||
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- id: "bot-output" | ||
type: consume | ||
topic: "answers-topic" | ||
parameters: | ||
- sessionId | ||
consumeOptions: | ||
filters: | ||
headers: | ||
- key: langstream-client-session-id | ||
valueFromParameters: sessionId | ||
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- id: "llm-debug" | ||
type: consume | ||
topic: "log-topic" |
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