From c88997cd2c7a82c0b9c32f7c94c68283694e408f Mon Sep 17 00:00:00 2001 From: Kyo Lee Date: Fri, 29 Sep 2023 05:17:46 +0000 Subject: [PATCH 1/3] [Release] Version 0.1.1 What's changed: - Update the version of ChromaDB to 4.13. - Re-generate the `poetry.lock` file. - Update Python scripts to migrate ChromaDB from 3.21 to 4.13 (See https://docs.trychroma.com/migration). - Updated README to clarify when to delete an existing vector database. - Update the chatbot UI template to use "PaLM" to refer to the AI model. Sept 28, 2023 --- demos/palm/python/docs-agent/README.md | 11 +- .../chatbot/templates/chatui/result.html | 2 +- demos/palm/python/docs-agent/chroma.py | 7 +- demos/palm/python/docs-agent/poetry.lock | 3716 ++++++++--------- demos/palm/python/docs-agent/pyproject.toml | 5 +- .../scripts/markdown_to_plain_text.py | 5 +- .../scripts/populate_vector_database.py | 15 +- .../scripts/test_vector_database.py | 4 +- 8 files changed, 1790 insertions(+), 1975 deletions(-) diff --git a/demos/palm/python/docs-agent/README.md b/demos/palm/python/docs-agent/README.md index 582fc9be1..a343dd044 100644 --- a/demos/palm/python/docs-agent/README.md +++ b/demos/palm/python/docs-agent/README.md @@ -487,15 +487,16 @@ To convert Markdown files to plain text files: ### 2. Populate a new vector database -**Important**: If the `vector_stores/chroma` directory already exists, delete -(or move) the `chroma` directory before populating a new vector database. Also, -if the Docs Agent chat app is already running using this `chroma` directory, shut down -the app before deleting the directory. - Once you have plain text files processed and stored in the `output_path` directory, you can run the `populat_vector_database.py` script to populate a vector database with the contents of the plain text files and their embeddings (and metadata). +**Important**: For a clean setup, if the `vector_stores/chroma` directory already +exists, delete (or move) the `chroma` directory before populating a new vector +database. (Otherwise, new entries will be added to your existing vector database.) +Also, if the Docs Agent chat app is already running using this `chroma` directory, +shut down the app before deleting the directory. + To populate a new vector database: 1. Go to the Docs Agent project directory, for example: diff --git a/demos/palm/python/docs-agent/chatbot/templates/chatui/result.html b/demos/palm/python/docs-agent/chatbot/templates/chatui/result.html index a61396cb9..3dd0446fc 100644 --- a/demos/palm/python/docs-agent/chatbot/templates/chatui/result.html +++ b/demos/palm/python/docs-agent/chatbot/templates/chatui/result.html @@ -38,7 +38,7 @@

Question:

{{ question | replace("+", " ") | replace("%3F", "?")}}

 -

Bard's response:

+

PaLM's response:

{{ response_in_html | safe }} diff --git a/demos/palm/python/docs-agent/chroma.py b/demos/palm/python/docs-agent/chroma.py index aecc6f940..403ce462b 100644 --- a/demos/palm/python/docs-agent/chroma.py +++ b/demos/palm/python/docs-agent/chroma.py @@ -42,12 +42,7 @@ class Chroma: """Chroma wrapper""" def __init__(self, chroma_dir) -> None: - self.client = chromadb.Client( - Settings( - chroma_db_impl="duckdb+parquet", - persist_directory=chroma_dir, - ) - ) + self.client = chromadb.PersistentClient(path=chroma_dir) def list_collections(self): return self.client.list_collections() diff --git a/demos/palm/python/docs-agent/poetry.lock b/demos/palm/python/docs-agent/poetry.lock index fba9000e0..6220b567d 100644 --- a/demos/palm/python/docs-agent/poetry.lock +++ b/demos/palm/python/docs-agent/poetry.lock @@ -11,25 +11,37 @@ files = [ {file = "absl_py-1.4.0-py3-none-any.whl", hash = "sha256:0d3fe606adfa4f7db64792dd4c7aee4ee0c38ab75dfd353b7a83ed3e957fcb47"}, ] +[[package]] +name = "annotated-types" +version = "0.5.0" +description = "Reusable constraint types to use with typing.Annotated" +optional = false +python-versions = ">=3.7" +files = [ + {file = "annotated_types-0.5.0-py3-none-any.whl", hash = "sha256:58da39888f92c276ad970249761ebea80ba544b77acddaa1a4d6cf78287d45fd"}, + {file = "annotated_types-0.5.0.tar.gz", hash = "sha256:47cdc3490d9ac1506ce92c7aaa76c579dc3509ff11e098fc867e5130ab7be802"}, +] + [[package]] name = "anyio" -version = "3.6.2" +version = "3.7.1" description = "High level compatibility layer for multiple asynchronous event loop implementations" optional = false -python-versions = ">=3.6.2" +python-versions = ">=3.7" files = [ - 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b/demos/palm/python/docs-agent/pyproject.toml index 9cc8489b6..60ac1fbbf 100644 --- a/demos/palm/python/docs-agent/pyproject.toml +++ b/demos/palm/python/docs-agent/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "docs-agent" -version = "0.1.0" +version = "0.1.1" description = "" authors = ["Docs Agent contributors"] readme = "README.md" @@ -11,7 +11,7 @@ rich = "^13.3.5" Markdown = "^3.4.3" beautifulsoup4 = "^4.12.2" protobuf = ">=3.20" -chromadb = "^0.3.21" +chromadb = "==0.4.13" sentence-transformers = "^2.2.2" ratelimit = "^2.2.1" absl-py = "^1.4.0" @@ -21,6 +21,7 @@ google-generativeai = "^0.1.0" grpcio = "^1.57.0" grpcio-tools = "^1.57.0" uuid = "^1.30" +pytz = ">=2020.1" [tool.poetry.group.dev.dependencies] ipython = "^8.13.2" diff --git a/demos/palm/python/docs-agent/scripts/markdown_to_plain_text.py b/demos/palm/python/docs-agent/scripts/markdown_to_plain_text.py index cd9ac1549..8f1585dd7 100644 --- a/demos/palm/python/docs-agent/scripts/markdown_to_plain_text.py +++ b/demos/palm/python/docs-agent/scripts/markdown_to_plain_text.py @@ -153,6 +153,9 @@ def process_page_and_section_titles(markdown_text): page_title = data["title"] markdown_text = data.content metadata = data.metadata + if "URL" in data: + final_url = data["URL"] + metadata["URL"] = final_url for line in markdown_text.split("\n"): new_line = "" skip_this_line = False @@ -173,7 +176,7 @@ def process_page_and_section_titles(markdown_text): # Detect Markdown heading levels if heading == "#": page_title = captured_title.strip() - metadata = {"title": page_title} + metadata["title"] = page_title subsection_title = "" section_title = "" elif heading == "##": diff --git a/demos/palm/python/docs-agent/scripts/populate_vector_database.py b/demos/palm/python/docs-agent/scripts/populate_vector_database.py index ce4f9414e..51eeb0ce8 100644 --- a/demos/palm/python/docs-agent/scripts/populate_vector_database.py +++ b/demos/palm/python/docs-agent/scripts/populate_vector_database.py @@ -108,10 +108,7 @@ MODEL = os.path.join(BASE_DIR, "models/all-mpnet-base-v2") emb_fn = embedding_functions.SentenceTransformerEmbeddingFunction(model_name=MODEL) -chroma_client = chromadb.Client( - Settings(chroma_db_impl="duckdb+parquet", persist_directory=LOCAL_VECTOR_DB_DIR) -) - +chroma_client = chromadb.PersistentClient(path=LOCAL_VECTOR_DB_DIR) # Create embed function for PaLM # API call limit to 5 qps @@ -175,6 +172,8 @@ def embed_function(texts: Documents) -> Embeddings: # Using the full path avoids mismatches full_file_name = FULL_BASE_DIR + clean_filename + file metadata_dict_extra = {} + # Flag to see if there is a predefined URL from frontmatter + final_url = False # Reads the metadata associated with files for key in index: if full_file_name in index[key]: @@ -197,6 +196,10 @@ def embed_function(texts: Documents) -> Embeddings: index[key][full_file_name]["metadata"], delimiter="_" ) metadata_dict_extra = dict(metadata_dict_extra) + # Extracts user specified URL + if "URL" in metadata_dict_extra: + final_url = True + final_url_value = metadata_dict_extra["URL"] else: metadata_dict_extra = {} if "UUID" in index[key][full_file_name]: @@ -216,6 +219,9 @@ def embed_function(texts: Documents) -> Embeddings: # Remove .md at the end of URLs by default. match3 = re.search(r"(.*)\.md$", url) url = match3[1] + # Replaces the URL if it comes from frontmatter + if (final_url): + url = final_url_value # Creates a dictionary with basic metadata values # (i.e. source, URL, and md_hash) metadata_dict_main = { @@ -287,7 +293,6 @@ def embed_function(texts: Documents) -> Embeddings: print("[Warning] Empty file!") print("") auto.close() -chroma_client.persist() # results = collection.query( # query_texts=["What are some differences between apples and oranges?"], # n_results=3, diff --git a/demos/palm/python/docs-agent/scripts/test_vector_database.py b/demos/palm/python/docs-agent/scripts/test_vector_database.py index e87d4735f..075bda6e3 100644 --- a/demos/palm/python/docs-agent/scripts/test_vector_database.py +++ b/demos/palm/python/docs-agent/scripts/test_vector_database.py @@ -83,9 +83,7 @@ def embed_palm(texts: Documents) -> Embeddings: ai_console = Console(width=160) ai_console.rule("Fold") -chroma_client = chromadb.Client( - Settings(chroma_db_impl="duckdb+parquet", persist_directory=LOCAL_VECTOR_DB_DIR) -) +chroma_client = chromadb.PersistentClient(path=LOCAL_VECTOR_DB_DIR) if EMBEDDINGS_TYPE == "PALM": PALM_EMBEDDING_MODEL = "models/embedding-gecko-001" From 7ea6bb69c88a31699a1d0904276ddb0432fab839 Mon Sep 17 00:00:00 2001 From: Kyo Lee Date: Fri, 6 Oct 2023 20:55:12 +0000 Subject: [PATCH 2/3] [Release] version 0.1.2 What's changed: - Refactored the `chatbot/chatui.py` to consolidate methods into `ask_model()`. - Updated the element names in the `result.html` template. - Cleaned up the code related to reading and replacing custom error messages. - Added more comments describing each prompt in the `ask_model()` method. - Moved the role of `condition.txt` to `config.yaml`. - Updated the Docs Agent module to read custom prompt text from `config.yaml`. - Removed the `condition.txt` file. - Re-generated the `poetry.lock` file to be up to date. October 6, 2023 --- demos/palm/python/docs-agent/README.md | 32 +- .../palm/python/docs-agent/chatbot/chatui.py | 227 ++- .../chatbot/templates/chatui/result.html | 8 +- demos/palm/python/docs-agent/condition.txt | 2 - demos/palm/python/docs-agent/config.yaml | 74 +- demos/palm/python/docs-agent/docs_agent.py | 60 +- demos/palm/python/docs-agent/poetry.lock | 1345 +++++++++-------- demos/palm/python/docs-agent/pyproject.toml | 2 +- 8 files changed, 926 insertions(+), 824 deletions(-) delete mode 100644 demos/palm/python/docs-agent/condition.txt diff --git a/demos/palm/python/docs-agent/README.md b/demos/palm/python/docs-agent/README.md index a343dd044..f05c08dac 100644 --- a/demos/palm/python/docs-agent/README.md +++ b/demos/palm/python/docs-agent/README.md @@ -57,7 +57,7 @@ content from the source documents given user questions. Once the most relevant content is returned, the Docs Agent server uses the prompt structure shown in Figure 3 to augment the user question with a preset **condition** and a list of **context**. (When the Docs Agent server starts, the condition value is read from the -[`condition.txt`][condition-txt] file.) Then the Docs Agent server sends this prompt to a +[`config.yaml`][condition-txt] file.) Then the Docs Agent server sends this prompt to a PaLM 2 model using the PaLM API and receives a response generated by the model. ![Docs Agent prompt strcture](docs/images/docs-agent-prompt-structure-01.png) @@ -202,16 +202,16 @@ by the PaLM model: - Additional condition (for fact-checking): ``` - Compare the following body of text to the context provided in this prompt and write - a short message that warns the readers about which part of the text below they - should consider fact-checking for themselves? (please keep your response concise and - mention only one important point): + Can you compare the following text to the context provided in this prompt and write + a short message that warns the readers about which part of the text they should + consider fact-checking? (Please keep your response concise and focus on only + one important item.) ``` - Previously generated response ``` - + Text: ``` This "fact-checking" prompt returns a response similar to the following example: @@ -542,15 +542,7 @@ allowing you to easily bring up and destory the Flask app instance. To customize settings in the Docs Agent chat app, do the following: -1. (**Optional**) Update the `condition.txt` file to provide a more specific prompt condition - for your custom dataset, for example: - - ``` - You are a helpful chatbot answering questions from developers working on Flutter apps. - Read the following context first and answer the question at the end: - ``` - -2. Edit the `config.yaml` file to update the following field: +1. Edit the `config.yaml` file to update the following field: ``` product_name: "My product" @@ -563,6 +555,14 @@ To customize settings in the Docs Agent chat app, do the following: product_name: "Flutter" ``` +2. (**Optional**) Edit the `config.yaml` file to provide a more specific prompt + condition for your custom dataset, for example: + + ``` + condition_text: "You are a helpful chatbot answering questions from developers working on + Flutter apps. Read the following context first and answer the question at the end:" + ``` + ### 2. Launch the Docs Agent chat app To launch the Docs Agent chat app, do the following: @@ -636,7 +636,7 @@ Meggin Kearney (`@Meggin`), and Kyo Lee (`@kyolee415`). [set-up-docs-agent]: #set-up-docs-agent [markdown-to-plain-text]: ./scripts/markdown_to_plain_text.py [populate-vector-database]: ./scripts/populate_vector_database.py -[condition-txt]: ./condition.txt +[condition-txt]: ./config.yaml [context-source-01]: http://eventhorizontelescope.org [fact-check-section]: #using-a-palm-2-model-to-fact-check-its-own-response [related-questions-section]: #using-a-palm-2-model-to-suggest-related-questions diff --git a/demos/palm/python/docs-agent/chatbot/chatui.py b/demos/palm/python/docs-agent/chatbot/chatui.py index c0f0a3322..4b6c64bcf 100644 --- a/demos/palm/python/docs-agent/chatbot/chatui.py +++ b/demos/palm/python/docs-agent/chatbot/chatui.py @@ -112,152 +112,115 @@ def rewrite(): return redirect(url_for("chatui.index")) +# Render a response page when the user asks a question +# using input text box. @bp.route("/result", methods=["GET", "POST"]) def result(): if request.method == "POST": - uuid_value = uuid.uuid1() - question_captured = request.form["question"] - query_result = docs_agent.query_vector_store(question_captured) - context = markdown.markdown(query_result.fetch_formatted(Format.CONTEXT)) - context_with_prefix = docs_agent.add_instruction_to_context(context) - response_in_markdown = docs_agent.ask_text_model_with_context( - context_with_prefix, question_captured - ) - if response_in_markdown is None: - response_in_markdown = ( - "The PaLM API is not able to answer this question at the moment. " - "Try to rephrase the question and ask again." - ) - response_in_html = markdown.markdown(response_in_markdown) - metadatas = markdown.markdown( - query_result.fetch_formatted(Format.CLICKABLE_URL) - ) - fact_checked_answer_in_markdown = docs_agent.ask_text_model_to_fact_check( - context_with_prefix, response_in_markdown - ) - if fact_checked_answer_in_markdown is None: - fact_checked_answer_in_markdown = ( - "The PaLM API is not able to answer this question at the moment. " - "Try to rephrase the question and ask again." - ) - fact_checked_answer_in_html = markdown.markdown(fact_checked_answer_in_markdown) - new_question = ( - "What are 5 questions developers might ask after reading the context?" - ) - related_questions = markdown.markdown( - docs_agent.ask_text_model_with_context(response_in_markdown, new_question) - ) - soup = BeautifulSoup(related_questions, "html.parser") - for item in soup.find_all("li"): - if item.string is not None: - link = soup.new_tag( - "a", - href=url_for( - "chatui.question", ask=urllib.parse.quote_plus(item.string) - ), - ) - link.string = item.string - item.string = "" - item.append(link) - related_questions = soup - fact_link = markdown.markdown( - query_result.fetch_nearest_formatted(Format.CLICKABLE_URL) - ) - server_url = request.url_root.replace("http", "https") - # Log the question and response to the log file. - log_question(uuid_value, question_captured, response_in_markdown) - return render_template( - "chatui/index.html", - question=question_captured, - context=context, - context_with_prefix=context_with_prefix, - response_in_markdown=response_in_markdown, - response_in_html=response_in_html, - product=product, - metadatas=metadatas, - fact_checked_answer=fact_checked_answer_in_html, - fact_link=fact_link, - related_questions=related_questions, - server_url=server_url, - uuid=uuid_value, - ) + question = request.form["question"] + return ask_model(question) else: return redirect(url_for("chatui.index")) +# Render a response page when the user clicks a question +# from the related questions list. @bp.route("/question/", methods=["GET", "POST"]) def question(ask): if request.method == "GET": - uuid_value = uuid.uuid1() - question_captured = urllib.parse.unquote_plus(ask) - query_result = docs_agent.query_vector_store(question_captured) - context = markdown.markdown(query_result.fetch_formatted(Format.CONTEXT)) - context_with_prefix = docs_agent.add_instruction_to_context(context) - response_in_markdown = docs_agent.ask_text_model_with_context( - context_with_prefix, question_captured - ) - if response_in_markdown is None: - response_in_markdown = ( - "The PaLM API is not able to answer this question at the moment. " - "Try to rephrase the question and ask again." - ) - response_in_html = markdown.markdown(response_in_markdown) - metadatas = markdown.markdown( - query_result.fetch_formatted(Format.CLICKABLE_URL) - ) - fact_checked_answer_in_markdown = docs_agent.ask_text_model_to_fact_check( - context_with_prefix, response_in_markdown - ) - if fact_checked_answer_in_markdown is None: - fact_checked_answer_in_markdown = ( - "The PaLM API is not able to answer this question at the moment. " - "Try to rephrase the question and ask again." - ) - fact_checked_answer_in_html = markdown.markdown(fact_checked_answer_in_markdown) - new_question = ( - "What are 5 questions developers might ask after reading the context?" - ) - related_questions = markdown.markdown( - docs_agent.ask_text_model_with_context(response_in_markdown, new_question) - ) - soup = BeautifulSoup(related_questions, "html.parser") - for item in soup.find_all("li"): - if item.string is not None: - link = soup.new_tag( - "a", - href=url_for( - "chatui.question", ask=urllib.parse.quote_plus(item.string) - ), - ) - link.string = item.string - item.string = "" - item.append(link) - related_questions = soup - fact_link = markdown.markdown( - query_result.fetch_nearest_formatted(Format.CLICKABLE_URL) - ) - server_url = request.url_root.replace("http", "https") - # Log the question and response to the log file. - log_question(uuid_value, question_captured, response_in_markdown) - return render_template( - "chatui/index.html", - question=question_captured, - context=context, - context_with_prefix=context_with_prefix, - response_in_markdown=response_in_markdown, - response_in_html=response_in_html, - product=product, - metadatas=metadatas, - fact_checked_answer=fact_checked_answer_in_html, - fact_link=fact_link, - related_questions=related_questions, - server_url=server_url, - uuid=uuid_value, - ) + question = urllib.parse.unquote_plus(ask) + return ask_model(question) else: return redirect(url_for("chatui.index")) +# Construct a set of prompts using the user question, send the prompts to +# the lanaguage model, receive responses, and present them into a page. +def ask_model(question): + ### PROMPT 1: AUGMENT THE USER QUESTION WITH CONTEXT. + # 1. Use the question to retrieve a list of related contents from the database. + # 2. Convert the list of related contents into plain Markdown text (context). + # 3. Add the custom condition text to the context. + # 4. Send the prompt (condition + context + question) to the language model. + query_result = docs_agent.query_vector_store(question) + context = markdown.markdown(query_result.fetch_formatted(Format.CONTEXT)) + context_with_prefix = docs_agent.add_instruction_to_context(context) + response = docs_agent.ask_text_model_with_context(context_with_prefix, question) + + ### PROMPT 2: FACT-CHECK THE PREVIOUS RESPONSE. + fact_checked_response = docs_agent.ask_text_model_to_fact_check( + context_with_prefix, response + ) + + ### PROMPT 3: GET 5 RELATED QUESTIONS. + # 1. Prepare a new question asking the model to come up with 5 related questions. + # 2. Ask the language model with the new question. + # 3. Parse the model's response into a list in HTML format. + new_question = ( + "What are 5 questions developers might ask after reading the context?" + ) + new_response = markdown.markdown( + docs_agent.ask_text_model_with_context(response, new_question) + ) + related_questions = parse_related_questions_response_to_html_list(new_response) + + ### RETRIEVE SOURCE URLS. + # - Construct clickable URLs using the returned related contents above. + # - Extract the URL of the top related content for the fact-check message. + clickable_urls = markdown.markdown( + query_result.fetch_formatted(Format.CLICKABLE_URL) + ) + fact_check_url = markdown.markdown( + query_result.fetch_nearest_formatted(Format.CLICKABLE_URL) + ) + + ### PREPARE OTHER ELEMENTS NEEDED BY UI. + # - Create a uuid for this request. + # - Convert the first response from the model into HTML for rendering. + # - Convert the fact-check response from the model into HTML for rendering. + # - A workaround to get the server's URL to work with the rewrite and like features. + new_uuid = uuid.uuid1() + response_in_html = markdown.markdown(response) + fact_checked_response_in_html = markdown.markdown(fact_checked_response) + server_url = request.url_root.replace("http", "https") + + ### LOG THIS REQUEST. + log_question(new_uuid, question, response) + + return render_template( + "chatui/index.html", + question=question, + context=context, + response=response, + response_in_html=response_in_html, + clickable_urls=clickable_urls, + fact_checked_response_in_html=fact_checked_response_in_html, + fact_check_url=fact_check_url, + related_questions=related_questions, + product=product, + server_url=server_url, + uuid=new_uuid, + ) + + +# Parse a response containing a list of related questions from the language model +# and convert it into an HTML-based list. +def parse_related_questions_response_to_html_list(response): + soup = BeautifulSoup(response, "html.parser") + for item in soup.find_all("li"): + if item.string is not None: + link = soup.new_tag( + "a", + href=url_for( + "chatui.question", ask=urllib.parse.quote_plus(item.string) + ), + ) + link.string = item.string + item.string = "" + item.append(link) + return soup + + # Log the question and response to the server's log file. def log_question(uid, user_question, response): date_format = "%m/%d/%Y %H:%M:%S %Z" diff --git a/demos/palm/python/docs-agent/chatbot/templates/chatui/result.html b/demos/palm/python/docs-agent/chatbot/templates/chatui/result.html index 3dd0446fc..d02d95425 100644 --- a/demos/palm/python/docs-agent/chatbot/templates/chatui/result.html +++ b/demos/palm/python/docs-agent/chatbot/templates/chatui/result.html @@ -8,9 +8,9 @@

PaLM's answer

{{ response_in_html | safe }}

Important:

- {{ fact_checked_answer | safe }} + {{ fact_checked_response_in_html | safe }}

To verify this information, please check out:

- {{ fact_link | safe }} + {{ fact_check_url | safe }}

Related questions

@@ -25,7 +25,7 @@

{{ context | safe }}

Reference:

- {{ metadatas | safe }} + {{ clickable_urls | safe }}

@@ -43,7 +43,7 @@

PaLM's response:

{{ response_in_html | safe }}

Rewrite:

- +
diff --git a/demos/palm/python/docs-agent/condition.txt b/demos/palm/python/docs-agent/condition.txt deleted file mode 100644 index f28fbd493..000000000 --- a/demos/palm/python/docs-agent/condition.txt +++ /dev/null @@ -1,2 +0,0 @@ -You are a helpful chatbot answering questions from users. Read the following context first -and answer the question at the end: diff --git a/demos/palm/python/docs-agent/config.yaml b/demos/palm/python/docs-agent/config.yaml index 13ee5b35b..5b10185bb 100644 --- a/demos/palm/python/docs-agent/config.yaml +++ b/demos/palm/python/docs-agent/config.yaml @@ -14,32 +14,43 @@ # limitations under the License. # -# Configuration file for Docs Agent +### Configuration for Docs Agent ### -# `product_name` is the name of your product that appears on the chatbot UI. +### Docs Agent environment +# +# product_name: The name of your product to appears on the chatbot UI. +# +# output_path: The directory where plain text files will be stored +# after documentation source files are processed by +# the `markdown-to-plain-text.py` script. +# Use a relative path to Doc Agent' home directory. +# +# vector_db_dir: The directory where dataset collections for the Chroma +# vector database are stored. +# +# collection_name: The name used to identify a dataset collection by +# the Chroma vector database. +# product_name: "My product" - -# `output_path` is the directory where the plain text files will be saved -# after Markdown files are processed by `markdown-to-plain-text.py`. It is -# relative to the Doc Agent repo folder. output_path: "data/plain_docs" - -# `vector_db_dir` is the directory that stores artifacts for the Chroma vector -# database. vector_db_dir: "vector_stores/chroma" - -# `collection_name` is the name used by the Chroma vector database to identify -# your dataset collection. collection_name: "docs_collection" -# You can list a number of input sources under the `input` field: -# `path` (Required): The directory where the source Markdown files are -# stored. -# `url_prefix` (Required): The prefix of the URL used to create URLs for the -# source files. If URLs don't exist for the source -# files, you still need to provide a mock string. -# `exclude_path` (Optional): The sub-directory to be excluded from the `path` -# directory when processing source files. + +### Documentation sources +# +# List your documentation sources under the `input` field: +# +# path (Required): The directory where the source Markdown files +# are stored. +# +# url_prefix (Required): The prefix used to create URLs for the source +# files. Even if URLs don't exist for the source, +# you still need to provide a mock string. +# +# exclude_path (Optional): The sub-directory to be excluded from the `path` +# directory when processing source files. +# input: - path: "data/example/markdown-src-01" url_prefix: "https://example.com/markdown-src-01" @@ -47,3 +58,26 @@ input: url_prefix: "https://example.com/makrdown-src-02" exclude_path: "/reference/changelogs/" + +### Docs Agent prompts +# +# condition_text: The condition added at the top of each prompt to +# language models. +# +# fact_check_question: The additional condition used in promopts when asking +# language models to "fact check" their own responses. +# +# model_error_message: The error message returned to the user when language +# models are unable to provide responses. +# +condition_text: "You are a helpful chatbot answering questions from users. Read +the following context firstand answer the question at the end:" + +fact_check_question: "Can you compare the following text to the context provided +in this prompt and write a short message that warns the readers about which part +of the text they should consider fact-checking? (Please keep your response +concise and focus on only one important item.)" + +model_error_message: "PaLM is not able to answer this question at the +moment. Rephrase the question and try asking again." + diff --git a/demos/palm/python/docs-agent/docs_agent.py b/demos/palm/python/docs-agent/docs_agent.py index dde2bb19f..1fe383d38 100644 --- a/demos/palm/python/docs-agent/docs_agent.py +++ b/demos/palm/python/docs-agent/docs_agent.py @@ -27,19 +27,19 @@ from scripts import read_config -### Set up the PaLM API key from the environment ### +# Set up the PaLM API key from the environment. API_KEY = os.getenv("PALM_API_KEY") if API_KEY is None: sys.exit("Please set the environment variable PALM_API_KEY to be your API key.") -### Select your PaLM API endpoint ### +# Select your PaLM API endpoint. PALM_API_ENDPOINT = "generativelanguage.googleapis.com" palm = PaLM(api_key=API_KEY, api_endpoint=PALM_API_ENDPOINT) BASE_DIR = os.path.dirname(os.path.abspath(__file__)) -### Set up the path to the chroma vector database ### +# Set up the path to the chroma vector database. LOCAL_VECTOR_DB_DIR = os.path.join(BASE_DIR, "vector_stores/chroma") COLLECTION_NAME = "docs_collection" @@ -48,35 +48,17 @@ config_values = read_config.ReadConfig() LOCAL_VECTOR_DB_DIR = config_values.returnConfigValue("vector_db_dir") COLLECTION_NAME = config_values.returnConfigValue("collection_name") + CONDITION_TEXT = config_values.returnConfigValue("condition_text") + FACT_CHECK_QUESTION = config_values.returnConfigValue("fact_check_question") + MODEL_ERROR_MESSAGE = config_values.returnConfigValue("model_error_message") -### Set up the path to the `condition.txt` file that holds custom condition text. ### -CONDITION_FILE = os.path.join(BASE_DIR, "condition.txt") - -### Select the number of contents to be used for providing context +# Select the number of contents to be used for providing context. NUM_RETURNS = 5 class DocsAgent: """DocsAgent class""" - prompt_condition = ( - "Answer the question below as truthfully as possible, " - "and if you're unsure of the answer, say \"Sorry, I don't know.\"" - ) - text_model_error_response = ( - "I'm a large language model. " - "I'm currently not able to help you with that question. " - "You may rephrase your question with more specifics and try again." - ) - chat_model_error_response = ( - "I'm a large language model. " - "I'm currently not able to help you with that question." - ) - palm_none_response = ( - "PaLM is not able to answer this question at the moment. " - "You may rephrase the question and ask again." - ) - def __init__(self): # Initialize the Chroma vector database logging.info( @@ -84,8 +66,10 @@ def __init__(self): ) self.chroma = Chroma(LOCAL_VECTOR_DB_DIR) self.collection = self.chroma.get_collection(COLLECTION_NAME) - # Update PaLM's condition string - self.update_condition_from_file() + # Update PaLM's custom prompt strings + self.prompt_condition = CONDITION_TEXT + self.fact_check_question = FACT_CHECK_QUESTION + self.model_error_message = MODEL_ERROR_MESSAGE # Use this method for talking to PaLM (Text) def ask_text_model_with_context(self, context, question): @@ -98,11 +82,11 @@ def ask_text_model_with_context(self, context, question): temperature=0.0, ) except google.api_core.exceptions.InvalidArgument: - return self.text_model_error_response + return self.model_error_message if response.result is None: print("Block reason: " + str(response.filters)) print("Safety feedback: " + str(response.safety_feedback)) - return self.palm_none_response + return self.model_error_message return response.result # Use this method for talking to PaLM (Chat) @@ -114,7 +98,7 @@ def ask_chat_model_with_context(self, context, question): temperature=0.05, ) except google.api_core.exceptions.InvalidArgument: - return self.chat_model_error_response + return self.model_error_message if response.last is None: return self.palm_none_response @@ -122,15 +106,7 @@ def ask_chat_model_with_context(self, context, question): # Use this method for asking PaLM (Text) for fact-checking def ask_text_model_to_fact_check(self, context, prev_response): - question = ( - "Can you compare the following body of text " - "to the context provided in this prompt and " - "write a short message that warns the readers about " - "which part of the text below they should consider " - "fact-checking for themselves? " - "(please keep your response concise and mention " - "only one important point):\n\n" - ) + question = self.fact_check_question + "\n\nText: " question += prev_response return self.ask_text_model_with_context(context, question) @@ -143,9 +119,3 @@ def add_instruction_to_context(self, context): new_context = "" new_context += self.prompt_condition + "\n" + context return new_context - - # Update the condition string for PaLM from the `condition.txt` file - def update_condition_from_file(self): - with open(CONDITION_FILE, "r", encoding="utf-8") as text_file: - self.prompt_condition = text_file.read() - text_file.close() diff --git a/demos/palm/python/docs-agent/poetry.lock b/demos/palm/python/docs-agent/poetry.lock index 6220b567d..b1c17c48c 100644 --- a/demos/palm/python/docs-agent/poetry.lock +++ b/demos/palm/python/docs-agent/poetry.lock @@ -275,86 +275,101 @@ files = [ [[package]] name = "charset-normalizer" -version = "3.2.0" +version = "3.3.0" description = "The Real First Universal Charset Detector. 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library." optional = false python-versions = ">=3.8" files = [ - {file = "werkzeug-2.3.7-py3-none-any.whl", hash = "sha256:effc12dba7f3bd72e605ce49807bbe692bd729c3bb122a3b91747a6ae77df528"}, - {file = "werkzeug-2.3.7.tar.gz", hash = "sha256:2b8c0e447b4b9dbcc85dd97b6eeb4dcbaf6c8b6c3be0bd654e25553e0a2157d8"}, + {file = "werkzeug-3.0.0-py3-none-any.whl", hash = "sha256:cbb2600f7eabe51dbc0502f58be0b3e1b96b893b05695ea2b35b43d4de2d9962"}, + {file = "werkzeug-3.0.0.tar.gz", hash = "sha256:3ffff4dcc32db52ef3cc94dff3000a3c2846890f3a5a51800a27b909c5e770f0"}, ] [package.dependencies] diff --git a/demos/palm/python/docs-agent/pyproject.toml b/demos/palm/python/docs-agent/pyproject.toml index 60ac1fbbf..9f9c86d23 100644 --- a/demos/palm/python/docs-agent/pyproject.toml +++ b/demos/palm/python/docs-agent/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "docs-agent" -version = "0.1.1" +version = "0.1.2" description = "" authors = ["Docs Agent contributors"] readme = "README.md" From 95e8493909cb56ef3e6caeeddb4ab5f98260f9fe Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Sat, 21 Oct 2023 03:10:41 +0000 Subject: [PATCH 3/3] Bump react-devtools-core from 4.28.0 to 4.28.4 in /demos/palm/web/textfx Bumps [react-devtools-core](https://github.com/facebook/react/tree/HEAD/packages/react-devtools-core) from 4.28.0 to 4.28.4. - [Release notes](https://github.com/facebook/react/releases) - [Changelog](https://github.com/facebook/react/blob/main/CHANGELOG.md) - [Commits](https://github.com/facebook/react/commits/HEAD/packages/react-devtools-core) --- updated-dependencies: - dependency-name: react-devtools-core dependency-type: indirect ... Signed-off-by: dependabot[bot] --- demos/palm/web/textfx/package-lock.json | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/demos/palm/web/textfx/package-lock.json b/demos/palm/web/textfx/package-lock.json index 801e36648..3d5001be6 100644 --- a/demos/palm/web/textfx/package-lock.json +++ b/demos/palm/web/textfx/package-lock.json @@ -10873,9 +10873,9 @@ } }, "node_modules/react-devtools-core": { - "version": "4.28.0", - "resolved": "https://registry.npmjs.org/react-devtools-core/-/react-devtools-core-4.28.0.tgz", - "integrity": "sha512-E3C3X1skWBdBzwpOUbmXG8SgH6BtsluSMe+s6rRcujNKG1DGi8uIfhdhszkgDpAsMoE55hwqRUzeXCmETDBpTg==", + "version": "4.28.4", + "resolved": "https://registry.npmjs.org/react-devtools-core/-/react-devtools-core-4.28.4.tgz", + "integrity": "sha512-IUZKLv3CimeM07G3vX4H4loxVpByrzq3HvfTX7v9migalwvLs9ZY5D3S3pKR33U+GguYfBBdMMZyToFhsSE/iQ==", "peer": true, "dependencies": { "shell-quote": "^1.6.1", @@ -20765,9 +20765,9 @@ } }, "react-devtools-core": { - "version": "4.28.0", - "resolved": "https://registry.npmjs.org/react-devtools-core/-/react-devtools-core-4.28.0.tgz", - "integrity": "sha512-E3C3X1skWBdBzwpOUbmXG8SgH6BtsluSMe+s6rRcujNKG1DGi8uIfhdhszkgDpAsMoE55hwqRUzeXCmETDBpTg==", + "version": "4.28.4", + "resolved": "https://registry.npmjs.org/react-devtools-core/-/react-devtools-core-4.28.4.tgz", + "integrity": "sha512-IUZKLv3CimeM07G3vX4H4loxVpByrzq3HvfTX7v9migalwvLs9ZY5D3S3pKR33U+GguYfBBdMMZyToFhsSE/iQ==", "peer": true, "requires": { "shell-quote": "^1.6.1",