diff --git a/.github/workflows/flake8.yml b/.github/workflows/flake8.yml index 2ae9866..5b52020 100644 --- a/.github/workflows/flake8.yml +++ b/.github/workflows/flake8.yml @@ -21,7 +21,8 @@ jobs: uses: TrueBrain/actions-flake8@v2 with: ignore: E203,E701,W503,W504,BLK100 - max_line_length: 118 + exclude: src/agent/test_query_pipeline.py + max_line_length: 185 path: src plugins: flake8-black flake8-isort flake8-quotes error_classes: E,H,I00,Q00 diff --git a/.gitignore b/.gitignore index 8bd26a6..ead74d1 100644 --- a/.gitignore +++ b/.gitignore @@ -2,4 +2,6 @@ prompts/__pycache__ .DS_Store .env __pycache__ -src/query_index \ No newline at end of file +src/query_index +ui/node_modules +ui/.next \ No newline at end of file diff --git a/.vscode/settings.json b/.vscode/settings.json index fb1df91..3e20020 100644 --- a/.vscode/settings.json +++ b/.vscode/settings.json @@ -2,7 +2,7 @@ "git.ignoreLimitWarning": true, "editor.formatOnSave": true, "flake8.args": [ - "--max-line-length=118" + "--max-line-length=185" ], "[python]": { "editor.codeActionsOnSave": { diff --git a/INSTALL.md b/INSTALL.md index 396c77e..753086b 100644 --- a/INSTALL.md +++ b/INSTALL.md @@ -1,4 +1,3 @@ - # Installation Guide This guide provides step-by-step instructions to set up the project after cloning the repository. @@ -52,7 +51,7 @@ curl -fsSL https://ollama.com/install.sh | sh Run the Ollama application: ```bash -ollama run codellama +ollama run llama3.1:8b-instruct-q4_0 ``` ## Step 7: Start the Flask Application @@ -67,5 +66,49 @@ export ATTRIBUTE_API_TTL=172800 python -m flask run ``` -The UI will be available at `http://localhost:5000/` +## Step 8: Start the frontend + +**Change directory:** + +``` +cd ui +``` + +**Create a `.env` file:** + +``` +NEXT_PUBLIC_OLLAMA_URL="http://127.0.0.1:11434" +NEXT_GOAT_NLP_BACKEND="http://localhost:5000" +``` + +**Install dependencies:** + +``` +npm install +``` + +**Start the development server:** + +``` +npm run dev +``` +The UI will be available at `http://localhost:3000/` + +# Testing guide + +Install dev dependencies + +``` +pip install -r requirements-dev.txt +``` + +Run `pytest` +``` +export OLLAMA_HOST_URL=http://127.0.0.1:11434 +export RETRY_COUNT=5 +export GOAT_BASE_URL=https://goat.genomehubs.org/api/v2 +export ATTRIBUTE_API_TTL=172800 + +pytest -W ignore::DeprecationWarning -k test_intent_module +``` diff --git a/pyproject.toml b/pyproject.toml index 6153753..d4bdc42 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,5 +1,5 @@ [tool.black] -line-length = 118 +line-length = 185 target-version = ['py39', 'py310', 'py311', 'py312'] include = '\.pyi?$' required-version = '24.4.2' diff --git a/requirements-dev.txt b/requirements-dev.txt new file mode 100644 index 0000000..c7764ac --- /dev/null +++ b/requirements-dev.txt @@ -0,0 +1,2 @@ +-r requirements.txt +pytest diff --git a/setup.cfg b/setup.cfg index 3016043..cf25ece 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,4 +1,4 @@ [flake8] -max-line-length = 118 +max-line-length = 185 extend-ignore = E203,E701,W503,W504,BLK100 inline-quotes = double \ No newline at end of file diff --git a/src/agent/__init__.py b/src/agent/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/agent/component_helpers.py b/src/agent/component_helpers.py index 69b7b41..3fc01aa 100644 --- a/src/agent/component_helpers.py +++ b/src/agent/component_helpers.py @@ -1,3 +1,4 @@ +import ast import json import logging import os @@ -11,11 +12,13 @@ from llama_index.core.output_parsers.utils import extract_json_str from prompt import ( - ATTRIBUTE_PROMPT, + ATTRIBUTE_CONDITION_PROMPT, + ATTRIBUTE_IDENTIFICATION_PROMPT, ENTITY_PROMPT, INDEX_PROMPT, INTENT_PROMPT, LINEAGE_PROMPT, + MARKDOWN_PROMPT, RANK_PROMPT, RECORD_PROMPT, TIME_PROMPT, @@ -27,6 +30,7 @@ def identify_index(input: str, state: Dict[str, Any]): index_response = Settings.llm.complete(INDEX_PROMPT.format(query=input)).text state["index"] = json.loads(extract_json_str(index_response)) + state["status"] = "Identify Index" if "classification" not in state["index"] or "explanation" not in state["index"]: raise ValueError("Invalid response from model at index identification stage.") @@ -35,6 +39,7 @@ def identify_index(input: str, state: Dict[str, Any]): def identify_entity(input: str, state: Dict[str, Any]): entity_response = Settings.llm.complete(ENTITY_PROMPT.format(query=input)).text state["entity"] = json.loads(extract_json_str(entity_response)) + state["status"] = "Identify Entity" if "entities" not in state["entity"] or "explanation" not in state["entity"]: raise ValueError("Invalid response from model at entity identification stage.") @@ -46,6 +51,7 @@ def identify_rank(input: str, state: Dict[str, Any]): RANK_PROMPT.format(query=input, results=json.dumps(cleaned_taxons, indent=4)) ).text state["rank"] = json.loads(extract_json_str(rank_response)) + state["status"] = "Identify Rank" if "rank" not in state["rank"] or "explanation" not in state["rank"]: raise ValueError("Invalid response from model at rank identification stage.") @@ -56,6 +62,7 @@ def identify_time_frame(input: str, state: Dict[str, Any]): TIME_PROMPT.format(query=input, time=datetime.now().strftime("%Y-%m-%d %H:%M:%S")) ).text state["timeframe"] = json.loads(extract_json_str(time_response)) + state["status"] = "Identify Time Frame" if ( "from_date" not in state["timeframe"] @@ -68,6 +75,7 @@ def identify_time_frame(input: str, state: Dict[str, Any]): def identify_intent(input: str, state: Dict[str, Any]): intent_response = Settings.llm.complete(INTENT_PROMPT.format(query=input)).text state["intent"] = json.loads(extract_json_str(intent_response)) + state["status"] = "Identify Intent" if "intent" not in state["intent"] or "explanation" not in state["intent"]: raise ValueError("Invalid response from model at intent identification stage.") @@ -83,30 +91,72 @@ def attribute_api_call(index: str): return response_parsed if response_parsed["status"]["success"] else None -def identify_attributes(input: str, state: Dict[str, Any]): - +def define_attribute_condition(input: str, state: Dict[str, Any]): attributes = attribute_api_call(state["index"]["classification"]) + + if state["attribute_identification"]["attributes"] == []: + state["attributes"] = {"attributes": [], "explanation": "No attributes identified."} + return + cleaned_attributes = [ { "name": name, - "description": (attribute["description"] if "description" in attribute else None), "constraint": (attribute["constraint"] if "constraint" in attribute else None), - "value_metadata": (attribute["value_metadata"] if "value_metadata" in attribute else None), } for name, attribute in attributes["fields"].items() + if name in state["attribute_identification"]["attributes"] ] attribute_response = Settings.llm.complete( - ATTRIBUTE_PROMPT.format( + ATTRIBUTE_CONDITION_PROMPT.format( attribute_metadata=json.dumps(cleaned_attributes, indent=4), query=input, ) ).text state["attributes"] = json.loads(extract_json_str(attribute_response)) + state["status"] = "Define Attribute Condition" if "attributes" not in state["attributes"] or "explanation" not in state["attributes"]: raise ValueError("Invalid response from model at attribute identification stage.") + for attribute in state["attributes"]["attributes"]: + if attribute["attribute"] not in state["attribute_identification"]["attributes"]: + state["attributes"]["attributes"].pop(attribute) + + +def identify_attributes(input: str, state: Dict[str, Any]): + + attributes = attribute_api_call(state["index"]["classification"]) + + cleaned_attributes = [] + + for name, attribute in attributes["fields"].items(): + cleaned_attribute = {"name": name} + description_added = False + if "description" in attribute: + cleaned_attribute["description"] = attribute["description"] + description_added = True + if "long_description" in attribute: + cleaned_attribute["long_description"] = attribute["long_description"] + description_added = True + if description_added: + cleaned_attributes.append(cleaned_attribute) + + attribute_response = Settings.llm.complete( + ATTRIBUTE_IDENTIFICATION_PROMPT.format( + attribute_metadata=json.dumps(cleaned_attributes, indent=4), + query=input, + ) + ).text + state["attribute_identification"] = ast.literal_eval(extract_json_str(attribute_response)) + state["status"] = "Identify Attributes" + + if ( + "attributes" not in state["attribute_identification"] + or "explanation" not in state["attribute_identification"] + ): + raise ValueError("Invalid response from model at attribute identification stage.") + def construct_query(input: str, state: Dict[str, Any]): query = "" @@ -150,22 +200,43 @@ def construct_query(input: str, state: Dict[str, Any]): condition = attribute["condition"] if condition == "in": query += f'{attribute["attribute"]}({",".join(attribute["value"])}) AND ' + elif condition == "required": + query += f'{attribute["attribute"]} AND ' else: query += f'{attribute["attribute"]}' + f'{attribute["condition"]}' + f'{attribute["value"]} AND ' query = query.removesuffix(" AND ") + state["status"] = "Construct Query" + state["query"] = query def construct_url(input: str, state: Dict[str, Any]): base_url = "https://goat.genomehubs.org/" endpoint = state["intent"]["intent"] + "?" - suffix = f'&result={state["index"]["classification"]}&summaryValues=count&taxonomy=ncbi&offset=0' - suffix += "&fields=assembly_level%2Cassembly_span%2Cgenome_size%2Cchromosome_number%2C" - suffix += "haploid_number&names=common_name&ranks=&includeEstimates=false&size=100" - + if fields := "%2C".join(state.get("attributes", {}).get("attribute", [])): + fields = f"&fields={fields}" + include_estimates = str(not state["rank"]["rank"].endswith("species")).lower() + suffix = f'&result={state["index"]["classification"]}&taxonomy=ncbi' + suffix += f"{fields}&names=common_name&ranks=&includeEstimates={include_estimates}&size=10" + state["status"] = "Construct URL" state["final_url"] = base_url + endpoint + "query=" + urllib.parse.quote(state["query"]) + suffix + state["api_url"] = base_url + "api/v2/" + endpoint + "query=" + urllib.parse.quote(state["query"]) + suffix + + try: + response = requests.get(state["api_url"]) + parsed_response = response.json() + if parsed_response["status"]["success"]: + if state["intent"]["intent"] == "record": + state["api_response"] = parsed_response["records"][0] + for attribute_name, attribute in state["api_response"]["attributes"].items(): + state["api_response"]["attributes"][attribute_name] = attribute["value"] + elif state["intent"]["intent"] == "search": + state["api_response"] = parsed_response["results"] + except Exception as e: + print(str(e)) + pass def identify_record(input: str, state: Dict[str, Any]): @@ -178,6 +249,7 @@ def identify_record(input: str, state: Dict[str, Any]): RECORD_PROMPT.format(query=input, results=json.dumps(cleaned_taxons, indent=4)) ).text state["record"] = json.loads(extract_json_str(taxon_response)) + state["status"] = "Identify Record" if "taxon_id" not in state["record"] or "explanation" not in state["record"]: raise ValueError("Invalid response from model at record identification stage.") @@ -187,6 +259,23 @@ def identify_record(input: str, state: Dict[str, Any]): + str(state["record"]["taxon_id"]) + f"&result={state['index']['classification']}" ) + state["api_url"] = state["final_url"].replace("/record", "/api/v2/record") + + try: + response = requests.get(state["api_url"]) + parsed_response = response.json() + if parsed_response["status"]["success"]: + if state["intent"]["intent"] == "record": + state["api_response"] = parsed_response["records"][0] + for attribute_name, attribute in state["api_response"]["record"]["attributes"].items(): + state["api_response"]["record"]["attributes"][attribute_name] = ( + attribute["value"] if "value" in attribute else "" + ) + elif state["intent"]["intent"] == "search": + state["api_response"] = parsed_response["results"] + except Exception as e: + print(str(e)) + pass def query_entity(state: Dict[str, Any], query_operator="tax_name", include_sub_species=True) -> list: @@ -201,9 +290,13 @@ def query_entity(state: Dict[str, Any], query_operator="tax_name", include_sub_s entities += f"* {entity['singular_form']}," entities += f"* {entity['plural_form']}," - query_url = f'{os.getenv("GOAT_BASE_URL")}/search?query={urllib.parse.quote(f"{query_operator}({entities})")}' + query_url = ( + f'{os.getenv("GOAT_BASE_URL")}/search?query={urllib.parse.quote(f"{query_operator}({entities})")}&size=50' + ) query_url += f"&result={state['index']['classification']}" + state["entity"]["query_url"] = query_url + response = requests.get(query_url) response_parsed = response.json() return [ @@ -218,3 +311,17 @@ def query_entity(state: Dict[str, Any], query_operator="tax_name", include_sub_s } for res in response_parsed["results"] ] + + +def html_explanations(input: str, state: Dict[str, Any]): + cleaned_dictionary = state.copy() + cleaned_dictionary.pop("queue") + cleaned_dictionary.pop("final_url") + cleaned_dictionary.pop("status") + cleaned_dictionary.pop("api_url") + cleaned_dictionary.pop("api_response", None) + index_response = Settings.llm.complete( + MARKDOWN_PROMPT.format(state_dictionary=json.dumps(cleaned_dictionary, indent=4)) + ).text + state["markdown"] = index_response.replace('"', "'") + state["status"] = "Markdown Explanation" diff --git a/src/agent/goat_query_component.py b/src/agent/goat_query_component.py index 43e803e..d6f9bf6 100644 --- a/src/agent/goat_query_component.py +++ b/src/agent/goat_query_component.py @@ -22,8 +22,31 @@ def _run_component(self, **kwargs) -> Dict[str, Any]: exception = None try: self.fn(kwargs["input"]["input"], kwargs["input"]["state"]) + if kwargs["input"]["state"]["status"] == "Markdown Explanation": + kwargs["input"]["state"]["queue"].put( + { + "done": True, + "error": False, + "state": kwargs["input"]["state"]["status"], + "url": kwargs["input"]["state"]["final_url"], + "markdown": kwargs["input"]["state"]["markdown"], + "api_response": kwargs["input"]["state"]["api_response"], + } + ) + else: + kwargs["input"]["state"]["queue"].put( + {"done": False, "error": False, "state": kwargs["input"]["state"]["status"]} + ) except Exception as e: error = True + kwargs["input"]["state"]["queue"].put( + { + "done": False, + "error": True, + "exception": kwargs["input"]["state"]["status"] + " step failed with following error: " + str(e), + "state": "error_state", + } + ) exception = str(e) return { diff --git a/src/agent/query_pipeline.py b/src/agent/query_pipeline.py index 09af2b5..6288496 100644 --- a/src/agent/query_pipeline.py +++ b/src/agent/query_pipeline.py @@ -3,6 +3,8 @@ from agent.component_helpers import ( construct_query, construct_url, + define_attribute_condition, + html_explanations, identify_attributes, identify_entity, identify_index, @@ -21,11 +23,13 @@ "entity": GoatQueryComponent(fn=identify_entity), "rank": GoatQueryComponent(fn=identify_rank), "intent": GoatQueryComponent(fn=identify_intent), - "attribute": GoatQueryComponent(fn=identify_attributes), + "attribute": GoatQueryComponent(fn=define_attribute_condition), + "attribute_identification": GoatQueryComponent(fn=identify_attributes), "time": GoatQueryComponent(fn=identify_time_frame), "query": GoatQueryComponent(fn=construct_query), "url": GoatQueryComponent(fn=construct_url), "record": GoatQueryComponent(fn=identify_record), + "html_explanations": GoatQueryComponent(fn=html_explanations), } ) @@ -37,8 +41,7 @@ "record", condition_fn=lambda x: x["state"]["intent"]["intent"] == "record", ) -qp.add_link( - "entity", "rank", condition_fn=lambda x: x["state"]["intent"]["intent"] != "record" -) -qp.add_chain(["rank", "attribute", "time", "query", "url"]) +qp.add_link("record", "html_explanations") +qp.add_link("entity", "rank", condition_fn=lambda x: x["state"]["intent"]["intent"] != "record") +qp.add_chain(["rank", "attribute_identification", "attribute", "time", "query", "url", "html_explanations"]) # qp.add_chain(["intent", "index", "entity", "rank", "time", "query", "url"]) diff --git a/src/agent/test_query_pipeline.py b/src/agent/test_query_pipeline.py new file mode 100644 index 0000000..20cbad4 --- /dev/null +++ b/src/agent/test_query_pipeline.py @@ -0,0 +1,365 @@ +import os + +import pytest +from dotenv import load_dotenv +from llama_index.core import Settings, set_global_handler +from llama_index.core.query_pipeline import QueryPipeline as QP +from llama_index.llms.ollama import Ollama + +from agent.component_helpers import ( + define_attribute_condition, + identify_attributes, + identify_entity, + identify_index, + identify_intent, + identify_rank, + identify_time_frame, +) +from agent.goat_query_component import GoatQueryComponent + +load_dotenv() + +Settings.llm = Ollama( + model=os.getenv("OLLAMA_MODEL_NAME", "llama3.1:8b-instruct-q4_0"), + base_url=os.getenv("OLLAMA_HOST_URL", "http://127.0.0.1:11434"), + request_timeout=36000.0, +) + +set_global_handler("arize_phoenix") + +QUERIES = [ + ("how many butterfly species do we know?", "taxon", "count", ["Lepidoptera"], "species", None, None, None, None), + ( + "How many assemblies are available for the domestic dog?", + "assembly", + "count", + ["Canis lupus familiaris"], + None, + None, + None, + None, + None, + ), + ( + "Show me all the assemblies for gastropod molluscs", + "assembly", + "search", + ["Gastropod"], + None, + None, + None, + None, + None, + ), + ( + "What are the sequencing status values for bat families?", + "taxon", + "search", + ["Chiroptera"], + "family", + None, + None, + None, + None, + ), + ( + "Does Borneo magnolia have RNA-sequencing?", + "taxon", + "search", + ["Magnolia"], + "species", + "sra_accession", + "required", + None, + None, + ), + ( + "What are the contig N50 values for isopod and grass assemblies?", + "assembly", + "search", + ["Isopoda", "Poaceae"], + None, + "contig_n50", + "required", + None, + None, + ), + ( + "What is the sequencing status of bat families?", + "taxon", + "search", + ["Chiroptera"], + "family", + "sequencing_status", + "required", + None, + None, + ), + ( + "How many genome assemblies for fungi have been updated in August 2023?", + "assembly", + "count", + ["Fungi"], + None, + None, + None, + "2023-08-01", + "2023-08-31", + ), +] + + +@pytest.mark.parametrize( + "input_content, expected_index, _expected_intent, _expected_entities, _expected_rank, _expected_attribute, _expected_attribute_condition, _expected_time_from, _expected_time_to", + QUERIES, +) +def test_index_module( + input_content, + expected_index, + _expected_intent, + _expected_entities, + _expected_rank, + _expected_attribute, + _expected_attribute_condition, + _expected_time_from, + _expected_time_to, +): + # Skip the test if no expected index is provided + if expected_index is None: + pytest.skip("No expected index for this test case") + + # Create a QueryPipeline instance + qp = QP(verbose=True) + + # Add the index module to the QueryPipeline + qp.add_modules({"index": GoatQueryComponent(fn=identify_index)}) + + # Execute the QueryPipeline for the input data + result = qp.run(input={"input": input_content, "state": {}}) + + # Assert the expected index matches the result + assert result["state"]["index"]["classification"] == expected_index + + +@pytest.mark.parametrize( + "input_content, _expected_index, expected_intent, _expected_entities, _expected_rank, _expected_attribute, _expected_attribute_condition, _expected_time_from, _expected_time_to", + QUERIES, +) +def test_intent_module( + input_content, + _expected_index, + expected_intent, + _expected_entities, + _expected_rank, + _expected_attribute, + _expected_attribute_condition, + _expected_time_from, + _expected_time_to, +): + # Skip the test if no expected intent is provided + if expected_intent is None: + pytest.skip("No expected intent for this test case") + + # Create a QueryPipeline instance + qp = QP(verbose=True) + + # Add the intent module to the QueryPipeline + qp.add_modules({"intent": GoatQueryComponent(fn=identify_intent)}) + + # Execute the QueryPipeline for the input data + result = qp.run(input={"input": input_content, "state": {}}) + + # Assert the expected intent matches the result + assert result["state"]["intent"]["intent"] == expected_intent + + +@pytest.mark.parametrize( + "input_content, _expected_index, _expected_intent, expected_entities, _expected_rank, _expected_attribute, _expected_attribute_condition, _expected_time_from, _expected_time_to", + QUERIES, +) +def test_entity_module( + input_content, + _expected_index, + _expected_intent, + expected_entities, + _expected_rank, + _expected_attribute, + _expected_attribute_condition, + _expected_time_from, + _expected_time_to, +): + # Skip the test if no expected entities are provided + if expected_entities is None: + pytest.skip("No expected entities for this test case") + + # Create a QueryPipeline instance + qp = QP(verbose=True) + + # Add the entity module to the QueryPipeline + qp.add_modules({"entity": GoatQueryComponent(fn=identify_entity)}) + + # Execute the QueryPipeline for the input data + result = qp.run(input={"input": input_content, "state": {}}) + + # Assert the expected entity matches the result + entities = result["state"]["entity"]["entities"] + assert len(entities) == len(expected_entities) + for entity in entities: + assert ( + (entity["scientific_name"].lower() in [x.lower() for x in expected_entities]) + or (entity["singular_form"].lower() in [x.lower() for x in expected_entities]) + or (entity["plural_form"].lower() in [x.lower() for x in expected_entities]) + ) + + +@pytest.mark.parametrize( + "input_content, expected_index, expected_intent, expected_entities, expected_rank, _expected_attribute, _expected_attribute_condition, _expected_time_from, _expected_time_to", + QUERIES, +) +def test_rank_module( + input_content, + expected_index, + expected_intent, + expected_entities, + expected_rank, + _expected_attribute, + _expected_attribute_condition, + _expected_time_from, + _expected_time_to, +): + # Skip the test if no expected rank is provided + if expected_rank is None: + pytest.skip("No expected rank for this test case") + + # Create a QueryPipeline instance + qp = QP(verbose=True) + + # Add the rank module to the QueryPipeline + qp.add_modules({"rank": GoatQueryComponent(fn=identify_rank)}) + + # Execute the QueryPipeline for the input data + result = qp.run( + input={ + "input": input_content, + "state": { + "intent": {"intent": expected_intent}, + "index": {"classification": expected_index}, + "entity": { + "entities": [ + {"scientific_name": expected_entity, "singular_form": "", "plural_form": ""} + for expected_entity in expected_entities + ] + }, + }, + } + ) + + # Assert the expected rank matches the result + assert result["state"]["rank"]["rank"] == expected_rank + + +@pytest.mark.parametrize( + "input_content, expected_index, _expected_intent, _expected_entities, _expected_rank, expected_attribute, _expected_attribute_condition, _expected_time_from, _expected_time_to", + QUERIES, +) +def test_attribute_module( + input_content, + expected_index, + _expected_intent, + _expected_entities, + _expected_rank, + expected_attribute, + _expected_attribute_condition, + _expected_time_from, + _expected_time_to, +): + # Skip the test if no expected attribute is provided + if expected_attribute is None: + pytest.skip("No expected attribute for this test case") + + # Create a QueryPipeline instance + qp = QP(verbose=True) + + # Add the attribute module to the QueryPipeline + qp.add_modules({"attribute": GoatQueryComponent(fn=identify_attributes)}) # Corrected function name + + # Execute the QueryPipeline for the input data + result = qp.run(input={"input": input_content, "state": {"index": {"classification": expected_index}}}) + + # Assert the expected attribute matches the result + assert expected_attribute in result["state"]["attribute_identification"]["attributes"] + + +@pytest.mark.parametrize( + "input_content, _expected_index, _expected_intent, _expected_entities, _expected_rank, _expected_attribute, _expected_attribute_condition, expected_time_from, expected_time_to", + QUERIES, +) +def test_time_module( + input_content, + _expected_index, + _expected_intent, + _expected_entities, + _expected_rank, + _expected_attribute, + _expected_attribute_condition, + expected_time_from, + expected_time_to, +): + # Skip the test if no expected time is provided + if expected_time_from is None and expected_time_to is None: + pytest.skip("No expected time for this test case") + + # Create a QueryPipeline instance + qp = QP(verbose=True) + + # Add the time module to the QueryPipeline + qp.add_modules({"time": GoatQueryComponent(fn=identify_time_frame)}) + + # Execute the QueryPipeline for the input data + result = qp.run(input={"input": input_content, "state": {}}) + + # Assert the expected time matches the result + assert ( + result["state"]["timeframe"]["from_date"] == expected_time_from + and result["state"]["timeframe"]["to_date"] == expected_time_to + ) + + +@pytest.mark.parametrize( + "input_content, expected_index, _expected_intent, _expected_entities, _expected_rank, expected_attribute, expected_attribute_condition, _expected_time_from, _expected_time_to", + QUERIES, +) +def test_define_attribute_condition( + input_content, + expected_index, + _expected_intent, + _expected_entities, + _expected_rank, + expected_attribute, + expected_attribute_condition, + _expected_time_from, + _expected_time_to, +): + # Skip the test if no expected attribute is provided + if expected_attribute is None or expected_attribute_condition is None: + pytest.skip("No expected attribute for this test case") + + # Create a QueryPipeline instance + qp = QP(verbose=True) + + # Add the define_attribute_condition module to the QueryPipeline + qp.add_modules({"define_attribute_condition": GoatQueryComponent(fn=define_attribute_condition)}) + + # Execute the QueryPipeline for the input data + result = qp.run( + input={ + "input": input_content, + "state": { + "index": {"classification": expected_index}, + "attribute_identification": {"attributes": [expected_attribute]}, + }, + } + ) + + # Assert the expected attribute condition matches the result + assert result["state"]["attributes"]["attributes"][0]["condition"] == expected_attribute_condition diff --git a/src/app.py b/src/app.py index 54890c3..3375dab 100644 --- a/src/app.py +++ b/src/app.py @@ -1,10 +1,15 @@ +import json import logging import os +import queue import sys +import threading +import time import llama_index.core import phoenix as px -from flask import Flask, render_template, request +from flask import Flask, Response, render_template, request +from flask_cors import CORS from llama_index.core import Settings from llama_index.llms.ollama import Ollama from openinference.instrumentation.llama_index import LlamaIndexInstrumentor @@ -15,7 +20,7 @@ from agent.query_pipeline import qp Settings.llm = Ollama( - model="llama3", + model=os.getenv("OLLAMA_MODEL_NAME", "llama3.1:8b-instruct-q4_0"), base_url=os.getenv("OLLAMA_HOST_URL", "http://127.0.0.1:11434"), request_timeout=36000.0, ) @@ -29,6 +34,7 @@ LlamaIndexInstrumentor().instrument(tracer_provider=tracer_provider) app = Flask("goat_nlp") +CORS(app) handler = logging.StreamHandler(sys.stdout) handler.setFormatter(logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")) @@ -43,18 +49,30 @@ def home(): return render_template("chat.html") -@app.route("/chat", methods=["POST"]) +@app.route("/api/chat", methods=["POST"]) def chat(): - # agent.reset() - for _ in range(os.getenv("RETRY_LIMIT", 3)): - try: - # response = agent.chat(request.form["user_input"]) - response = qp.run(input={"input": request.form["user_input"], "state": {}}) - logger.info(response) - return {"url": str(response["state"]["final_url"]), "json_debug": ""} - except Exception: - continue - return {"url": "", "json_debug": ""} + def stream_response(input): + for _ in range(os.getenv("RETRY_LIMIT", 3)): + state_queue = queue.Queue() + current_state = {"done": False, "error": False, "exception": "", "state": ""} + t1 = threading.Thread( + target=lambda: qp.run(input={"input": input.split("#goat ")[1], "state": {"queue": state_queue}}) + ) + t1.start() + while True: + time.sleep(3) + if not state_queue.empty(): + temp_state = state_queue.get() + if current_state != temp_state: + print("State change") + current_state = temp_state + yield f"{json.dumps(current_state)}\n\n" + if current_state["done"] or current_state["error"]: + break + if current_state["done"]: + break + + return Response(stream_response(request.json["user_input"]), mimetype="text/event-stream") if __name__ == "__main__": diff --git a/src/prompt.py b/src/prompt.py index c562355..1f06dc3 100644 --- a/src/prompt.py +++ b/src/prompt.py @@ -15,6 +15,7 @@ Queries related to **taxon** appear as follows: 1. How many bird species have been collected so far? 2. What mushroom species have RNA seq? +3. What is the distribution of assembly span values across the phylum Chordata? Queries related to **assembly** appear as follows: 1. What are the latest assemblies for the family Canidae? @@ -24,6 +25,9 @@ 1. Find samples with RNA-seq data for tigers 2. Do any samples for cattle include RNA-seq data? +A query looking for values across a taxonomic group that does not mention "assemblies" is most likely to be related +to the taxon index. + Classify the following query into one of the three types: `{query}` @@ -33,13 +37,12 @@ "explanation": "..." }} +*REMEMBER* The classification key in your response SHOULD HAVE ONLY ONE OF THE THREE VALUES. You CANNOT reply with a combination of any values. e.g. "classification": "taxon, assembly", "classification": "taxon/assembly" etc. IS NOT ALLOWED. - -```json - +If the word "assemblies" is mentioned in the query, most likely the classification will be assembly. """ ) @@ -49,18 +52,28 @@ A user is trying to query a genomics database. -We want to identify all the entities in the query. +We want to identify all the taxa in the query. + +A taxon is a living organism present as the subject of the query. -An entity is a word in the query that represents the subject of the query. +For example: +- in the query "How many bird species have been collected so far?", the taxon is "bird". +- in the query "give me a tree of ant families", the taxon is "ant". +- in the query "show me the genome sizes for all species of elephant, cat and yeast?", + there are 3 taxa, "elephant, cat, and yeast". -For example, in the query "How many bird species have been collected so far?", -the entity are "bird". +**REMEMBER**: The query may refer to a subset of a larger group of organisms, for example in +the query "What are the latest assemblies for the bivalve molluscs?", the taxon +is "Bivalvia" and **NOT** "Mollusca" nor a lineage like "Mollusca: Bivalvia". -The identified entity *HAS TO BE* a living organism. +These queries have no taxon: +- "what is the distribution of genome sizes across all classes?" +- "How many samples are there in total?" -For e.g. "genomics", "assembly", "order", etc. are NOT valid entities +**REMEMBER**: The identified taxa **HAVE TO BE** living organisms but should not be a group of +organisms based on taxonomic rank alone. A taxon is **NEVER** the singular or plural form of a taxonomic rank. -You need to return a list containing all the entities in the query along +You need to return a list containing all the taxa in the query along with their singular/plural forms and scientific names. For example, for the query "How many bird species have been collected so far?", @@ -75,12 +88,13 @@ ] ``` +If taxa is not applicable to the query, or the inferred scientific name is either None or an empty string, +return an empty list. + The query given by the user is as follows: `{query}` -If there are no entities in the query, return an empty list. - -Return the entities in the following JSON format: +Return the taxa as a list of entities in the following JSON format: {{ "entities": [ {{ @@ -114,6 +128,8 @@ *User Query:* `{query}` +*Task:* + Look at the results and decide wisely which rank applies to the given query. You need to consider the following 3 important parameters while deciding the rank: @@ -122,15 +138,17 @@ since it is more specific than family and is mentioned in the query. 2. Results - The results contain all possible answers. You need to select the most relevant one from them. 3. Lineage - The lineage of every entry in the result is an array that contains all parents of the entry. - Make sure that the entry that you select contains correct parents in the lineage. + Make sure that the entry that you select an entry that contains correct parents in the lineage. -You need to return the rank and the taxon id of the most relevant entry from the results. +You need to return the singular form of the rank and the taxon id of the most relevant entry from the results. If rank is not applicable to the query, return an empty string for the rank and taxon_id field. -Return the rank in the following JSON format: +*IMPORTANT:* +We do not want a programmatic answer, we only need the rank and the taxon id. +Do not give me python code, your response should simply be a JSON of the following format: {{ "rank": "...", "taxon_id": "...", @@ -195,12 +213,11 @@ "explanation": "..." }} -If there is no time related information in the query, return an empty string -for both from_date and to_date. -If 'from' is not applicable, return an empty string for from_date. -If 'to' is not applicable, return an empty string for to_date. - -```json +*REMEMBER:* +- If there is no time related information in the query, return an empty string + for both from_date and to_date. +- If 'from' is not applicable, return an empty string for from_date. +- If 'to' is not applicable, return an empty string for to_date. """ ) @@ -213,14 +230,32 @@ We need to identify the intent of the query. An intent can be one of the following three types: -- **search**: The user is looking for information. +- **search**: The user is looking for a table of values. - **count**: The user is looking for a count of something. -- **record**: The user is looking for a specific record. +- **record**: The user is looking for a specific taxon, assembly or sample record without any condition or + constraints. +- **tree**: The user is looking for a phylogenetic tree. +- **histogram**: The user is looking for a histogram chart showing the distribution of a **SINGLE** attribute. +- **scatter**: The user is looking for a scatter plot chart showing the distribution of a pair of attributes. Examples for each intent: - search: "What are the latest assemblies for the family Canidae?" +- search: "What are the gene counts for squirrel and mouse assemblies? +- search: "What are the assembly span values for pine and spruce assemblies? - count: "How many bird species have been collected so far?" - record: "What information do we have about the African Elephant?" +- tree: "Show me a tree of all families in the phylum chordata" +- histogram: "What is the distribution of assembly span for species in the cat family?" +- scatter: "What is the relationship between contig scaffold n50 for all domestic dog assemblies" + +**REMEMBER:** +- A user only wants a distribution of values if they use the word "distribution" or "histogram" in their query. +- A user is more likely to want a scatter plot than a histogram if the query refers to a relationship + between attributes. +- The record endpoint is used only when there are no conditions or if the user has NOT asked a specific question. + If the question is generic like "give me info about", "what do we know about", etc., then the intent is record. +- Even if the query mentions a specific taxon, it can have constraints or conditions on it, DO NOT + use the record intent in such cases. The query given by the user is as follows: `{query}` @@ -235,7 +270,7 @@ """ ) -ATTRIBUTE_PROMPT = PromptTemplate( +ATTRIBUTE_IDENTIFICATION_PROMPT = PromptTemplate( """ You are an intelligent assistant who **ONLY ANSWERS IN JSON FORMAT**. @@ -243,47 +278,93 @@ We need to identify any attributes in the query. -These attributes might have some conditions mentioned on them -or they might simply be a "required" field in the output. +*Attribute List:* +`{attribute_metadata}` + +*Query:* +`{query}` + +You need to reply in the following format with a list of attribute names: +{{ + "attributes": ["", "", ...], + "explanation": "The attribute x was chosen because it is mentioned in the query and + x is also the name of the attribute/present in the description of attribute y." +}} + +If there are no attributes in the query, return an empty list. + +**REMEMBER:** +The attributes list in your response must be filled *ONLY* if +the user has *explicitly* mentioned that attribute in the query. + +This means that "ebp_date" (or any other attribute) will not be included in +the list unless the phrase "ebp_date" is given in the query by the user. +For e.g. Does Borneo magnolia have RNA-sequencing? will have "sra_accession" in the attributes list +because RNA-sequencing was mentioned in the query and RNA-seq is mentioned in the description of +the sra_accession attribute. + +**DO NOT** assume that an attribute is **IMPLIED** in the query. +**IN MOST CASES, YOUR RESPONSE WILL BE AN EMPTY LIST.** + +""" +) + +ATTRIBUTE_CONDITION_PROMPT = PromptTemplate( + """ +You are an intelligent assistant who **ONLY ANSWERS IN JSON FORMAT**. + +A user is trying to query a genomics database. -The list of possible attributes and their types/values are as follows: +We have identified some attributes in the query which might have specific conditions mentioned on them +or they might simply be a "required" field in the output. +**Attribute List which needs to be filled with conditions:** `{attribute_metadata}` The query given by the user is as follows: `{query}` -You need to return a list of attributes present in the query along - with the conditions mentioned on them. +Your task is to return the above list of attributes and fill each attribute with conditions. The conditions can be one of the following: ->, <, >=, <=, =, !=, in +>, <, >=, <=, =, !=, in, required If the condition is "in", the value will be a list of values. +If the condition is "required", the value will be null, we just want the attribute to be "present" in the results. You need to reply in the following format: {{ "attributes": [ {{ "attribute": "...", - "condition": "...", - "value": "..." or ["...", "..."] + "condition": "required", + "value": "..." or ["...", "..."] or null }} ], - "explanation": "..." + "explanation": "why the condition was added..." }} -If there are no attributes in the query, return an empty list. - +e.g. +query: "What is the contig N50 value for the family Canidae?" +attributes: ["contig_n50"] -**REMEMBER:** The attributes list in your response must be filled **ONLY** if -the user has **explicitly** mentioned that attribute in the query. +response - +```json +{{ + "attributes": [ + {{ + "attribute": "contig_n50", + "condition": "required", + "value": null + }} + ], + "explanation": "The contig N50 value is required in the output." +}} +``` -This means that "ebp_date" (or any other attribute) will not be included in -the list unless the phrase "ebp_date" is given in the query by the user. +*REMEMBER:* +The result should contain ONLY attributes from the list given above, DO NOT add extra attributes. +DO NOT omit any attributes from the list. +In most cases, the condition will be "required". -**DO NOT** assume that an attribute is **IMPLIED** in the query. -**IN MOST CASES, YOUR RESPONSE WILL BE AN EMPTY LIST.** - -```json """ ) @@ -299,13 +380,16 @@ Make sure that the "rank" of your answer should be the closest match to the user's query. -The query by the user is as follows: -`{query}` - The results from the database are as follows: {results} -You need to return the best taxon from the results in the following JSON format: +The query by the user is as follows: +`{query}` + +*IMPORTANT:* +We do not want a programmatic answer, we only need the best matching taxon id which has the + closest "rank" to the query. +Do not give me python code, your response should simply be a JSON of the following format: {{ "taxon_id": "...", "explanation": "..." @@ -316,3 +400,18 @@ ```json """ ) + +MARKDOWN_PROMPT = PromptTemplate( + """ +You are an intelligent assistant who **ONLY ANSWERS IN MARKDOWN FORMAT**. + +Given a dictionary of data, you need to creatively summarise all the values and their +explanations in a single paragraph. This paragraph should be easy to read and detailed. + +Try to be logical in your summaries, use bold/italic emphasis where necessary. + +The dictionary is as follows: +{state_dictionary} + +""" +) diff --git a/src/templates/chat.html b/src/templates/chat.html index a84fcdf..5d7a70b 100644 --- a/src/templates/chat.html +++ b/src/templates/chat.html @@ -38,6 +38,41 @@ padding: 15px 0; } + details details { + margin-left: 20px; + transition: all 1500ms ease-in-out; + } + + details pre { + margin-left: 20px; + background: rgb(179, 179, 179); + padding: 10px; + transition: all 1500ms ease-in-out; + } + + details { + background: gainsboro; + padding: 2px; + } + + details summary { + cursor: pointer; + transition: all 1500ms ease-in-out; + /* list-style-type: ''; */ + } + + pre { + white-space: pre-wrap; + /* Since CSS 2.1 */ + white-space: -moz-pre-wrap; + /* Mozilla, since 1999 */ + white-space: -pre-wrap; + /* Opera 4-6 */ + white-space: -o-pre-wrap; + /* Opera 7 */ + word-wrap: break-word; + } + #chat_log { flex: 1; padding: 15px; @@ -105,10 +140,54 @@ } }); + function createDebugElement(jsonDebug) { + const debugElement = document.createElement('details'); + const summary = document.createElement('summary'); + summary.textContent = 'Debug'; + debugElement.appendChild(summary); + console.log("hello from outside", jsonDebug) + + for (const key in jsonDebug) { + console.log("hellooooooo") + const detailElement = document.createElement('details'); + const detailSummary = document.createElement('summary'); + detailSummary.textContent = key; + detailElement.appendChild(detailSummary); + + const value = jsonDebug[key]; + if (typeof value === 'object' && value !== null) { + for (const subKey in value) { + const subDetailElement = document.createElement('details'); + const subDetailSummary = document.createElement('summary'); + subDetailSummary.textContent = subKey; + subDetailElement.appendChild(subDetailSummary); + + const subPre = document.createElement('pre'); + subPre.textContent = JSON.stringify(value[subKey], undefined, 4); + subDetailElement.appendChild(subPre); + + detailElement.appendChild(subDetailElement); + } + } else { + const pre = document.createElement('pre'); + pre.textContent = JSON.stringify(value, undefined, 4); + detailElement.appendChild(pre); + } + console.log(detailElement) + debugElement.appendChild(detailElement); + } + + return debugElement; + } + function addMessage(sender, message) { var messageElement; - if (sender == 'bot' && message != 'Bot is typing...' && message != 'Sorry, something went wrong.' && message['url']) - messageElement = $('
GoaT Link!
' + message['json_debug'] + '
'); + if (sender == 'bot' && message != 'Bot is typing...' && message != 'Sorry, something went wrong.' && message['url']) { + + debug_element = createDebugElement(message['json_debug']); + messageElement = $('
GoaT Link!
'); + messageElement.append(debug_element); + } else messageElement = $('
').text(message); $('#chat_log').append(messageElement); @@ -124,6 +203,7 @@ $.ajax({ type: 'POST', url: '/chat', + // url: '/chatDebug', data: { user_input: message }, success: function (response) { $('.bot-message').last().remove(); diff --git a/ui/.eslintrc.json b/ui/.eslintrc.json new file mode 100644 index 0000000..bffb357 --- /dev/null +++ b/ui/.eslintrc.json @@ -0,0 +1,3 @@ +{ + "extends": "next/core-web-vitals" +} diff --git a/ui/.example.env b/ui/.example.env new file mode 100644 index 0000000..25b88a8 --- /dev/null +++ b/ui/.example.env @@ -0,0 +1,2 @@ +NEXT_PUBLIC_OLLAMA_URL="http://localhost:11434" +NEXT_GOAT_NLP_BACKEND="http://localhost:5000" diff --git a/ui/components.json b/ui/components.json new file mode 100644 index 0000000..965b5be --- /dev/null +++ b/ui/components.json @@ -0,0 +1,17 @@ +{ + "$schema": "https://ui.shadcn.com/schema.json", + "style": "new-york", + "rsc": true, + "tsx": true, + "tailwind": { + "config": "tailwind.config.ts", + "css": "src/app/globals.css", + "baseColor": "zinc", + "cssVariables": true, + "prefix": "" + }, + "aliases": { + "components": "@/components", + "utils": "@/lib/utils" + } +} \ No newline at end of file diff --git a/ui/next-env.d.ts b/ui/next-env.d.ts new file mode 100644 index 0000000..4f11a03 --- /dev/null +++ b/ui/next-env.d.ts @@ -0,0 +1,5 @@ +/// +/// + +// NOTE: This file should not be edited +// see https://nextjs.org/docs/basic-features/typescript for more information. diff --git a/ui/next.config.js b/ui/next.config.js new file mode 100644 index 0000000..cff642e --- /dev/null +++ b/ui/next.config.js @@ -0,0 +1,23 @@ +module.exports = { + async headers() { + return [ + { + // matching all API routes + source: "/api/:path*", + headers: [ + { key: "Access-Control-Allow-Credentials", value: "true" }, + { key: "Access-Control-Allow-Origin", value: "*" }, + { + key: "Access-Control-Allow-Methods", + value: "GET,OPTIONS,PATCH,DELETE,POST,PUT", + }, + { + key: "Access-Control-Allow-Headers", + value: + "X-CSRF-Token, X-Requested-With, Accept, Accept-Version, Content-Length, Content-MD5, Content-Type, Date, X-Api-Version", + }, + ], + }, + ]; + }, +}; diff --git a/ui/next.config.mjs b/ui/next.config.mjs new file mode 100644 index 0000000..f6f90c4 --- /dev/null +++ b/ui/next.config.mjs @@ -0,0 +1,29 @@ +/** @type {import('next').NextConfig} */ +const nextConfig = { + output: 'standalone', + webpack: (config, { isServer }) => { + // Fixes npm packages that depend on `fs` module + if (!isServer) { + config.resolve.fallback = { + ...config.resolve.fallback, // if you miss it, all the other options in fallback, specified + // by next.js will be dropped. Doesn't make much sense, but how it is + fs: false, // the solution + module: false, + perf_hooks: false, + }; + } + + return config + }, + typescript: { + // !! WARN !! + // Dangerously allow production builds to successfully complete even if + // your project has type errors. + // !! WARN !! + ignoreBuildErrors: true, + }, +}; + + + +export default nextConfig; diff --git a/ui/package-lock.json b/ui/package-lock.json new file mode 100644 index 0000000..c1fb08c --- /dev/null +++ b/ui/package-lock.json @@ -0,0 +1,10209 @@ +{ + "name": "nextjs-ollama-local-ai", + "version": "0.1.0", + "lockfileVersion": 3, + "requires": true, + "packages": { + "": { + "name": "nextjs-ollama-local-ai", + "version": "0.1.0", + "dependencies": { + "@emoji-mart/data": "^1.1.2", + "@emoji-mart/react": "^1.1.1", + "@hookform/resolvers": "^3.3.4", + "@langchain/community": "^0.0.26", + "@langchain/core": "^0.1.35", + "@radix-ui/react-avatar": "^1.0.4", + "@radix-ui/react-dialog": "^1.0.5", + "@radix-ui/react-dropdown-menu": "^2.0.6", + "@radix-ui/react-icons": "^1.3.0", + "@radix-ui/react-label": "^2.0.2", + "@radix-ui/react-popover": "^1.0.7", + "@radix-ui/react-scroll-area": "^1.0.5", + "@radix-ui/react-select": "^2.0.0", + "@radix-ui/react-slot": "^1.0.2", + "@radix-ui/react-tooltip": 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"^0.1.35", + "@radix-ui/react-avatar": "^1.0.4", + "@radix-ui/react-dialog": "^1.0.5", + "@radix-ui/react-dropdown-menu": "^2.0.6", + "@radix-ui/react-icons": "^1.3.0", + "@radix-ui/react-label": "^2.0.2", + "@radix-ui/react-popover": "^1.0.7", + "@radix-ui/react-scroll-area": "^1.0.5", + "@radix-ui/react-select": "^2.0.0", + "@radix-ui/react-slot": "^1.0.2", + "@radix-ui/react-tooltip": "^1.0.7", + "@types/dom-speech-recognition": "^0.0.4", + "ai": "^2.2.37", + "class-variance-authority": "^0.7.0", + "clsx": "^2.1.0", + "emoji-mart": "^5.5.2", + "framer-motion": "^11.0.3", + "langchain": "^0.1.13", + "lucide-react": "^0.322.0", + "next": "^14.2.3", + "next-themes": "^0.2.1", + "react": "^18", + "react-code-blocks": "^0.1.6", + "react-dom": "^18", + "react-hook-form": "^7.50.1", + "react-markdown": "^9.0.1", + "react-resizable-panels": "^2.0.3", + "react-textarea-autosize": "^8.5.3", + "rehype-raw": "^7.0.0", + "remark-gfm": "^4.0.0", + "sharp": "^0.33.4", + "sonner": "^1.4.0", + "tailwind-merge": "^2.2.1", + "tailwindcss-animate": "^1.0.7", + "uuid": "^9.0.1", + "zod": "^3.22.4" + }, + "devDependencies": { + "@types/node": "^20", + "@types/react": "^18", + "@types/react-dom": "^18", + "@types/uuid": "^9.0.8", + "autoprefixer": "^10.0.1", + "eslint": "^8", + "eslint-config-next": "14.1.0", + "postcss": "^8", + "tailwindcss": "^3.3.0", + "typescript": "^5" + } +} diff --git a/ui/postcss.config.js b/ui/postcss.config.js new file mode 100644 index 0000000..12a703d --- /dev/null +++ b/ui/postcss.config.js @@ -0,0 +1,6 @@ +module.exports = { + plugins: { + tailwindcss: {}, + autoprefixer: {}, + }, +}; diff --git a/ui/public/next.svg b/ui/public/next.svg new file mode 100644 index 0000000..5174b28 --- /dev/null +++ b/ui/public/next.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/ui/public/ollama.png b/ui/public/ollama.png new file mode 100644 index 0000000..89b7582 Binary files /dev/null and b/ui/public/ollama.png differ diff --git a/ui/public/user.jpg b/ui/public/user.jpg new file mode 100644 index 0000000..b1e4d24 Binary files /dev/null and b/ui/public/user.jpg differ diff --git a/ui/public/vercel.svg b/ui/public/vercel.svg new file mode 100644 index 0000000..d2f8422 --- /dev/null +++ b/ui/public/vercel.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/ui/src/app/[id]/page.tsx b/ui/src/app/[id]/page.tsx new file mode 100644 index 0000000..7f65cf3 --- /dev/null +++ b/ui/src/app/[id]/page.tsx @@ -0,0 +1,225 @@ +"use client"; + +import { ChatLayout } from "@/components/chat/chat-layout"; +import { getSelectedModel } from "@/lib/model-helper"; +import { ChatOllama } from "@langchain/community/chat_models/ollama"; +import { AIMessage, HumanMessage } from "@langchain/core/messages"; +import { BytesOutputParser } from "@langchain/core/output_parsers"; +import { ChatRequestOptions } from "ai"; +import { Message, useChat } from "ai/react"; +import React, { useEffect } from "react"; +import { toast } from "sonner"; +import { v4 as uuidv4 } from "uuid"; + +export default function Page({ params }: { params: { id: string } }) { + const { + messages, + input, + handleInputChange, + handleSubmit, + isLoading, + error, + stop, + setMessages, + setInput, + } = useChat({ + onResponse: (response) => { + if (response) { + setLoadingSubmit(false); + } + }, + onError: (error) => { + setLoadingSubmit(false); + toast.error("An error occurred. Please try again."); + }, + }); + const [chatId, setChatId] = React.useState(""); + const [selectedModel, setSelectedModel] = React.useState( + getSelectedModel() + ); + const [ollama, setOllama] = React.useState(); + const env = process.env.NODE_ENV; + const [loadingSubmit, setLoadingSubmit] = React.useState(false); + + useEffect(() => { + if (env === "production") { + console.log("Production mode"); + const newOllama = new ChatOllama({ + baseUrl: process.env.NEXT_PUBLIC_OLLAMA_URL || "http://localhost:11434", + model: selectedModel, + }); + setOllama(newOllama); + } + }, [selectedModel]); + + React.useEffect(() => { + if (params.id) { + const item = localStorage.getItem(`chat_${params.id}`); + if (item) { + setMessages(JSON.parse(item)); + } + } + }, []); + + const addMessage = (Message: any) => { + messages.push(Message); + window.dispatchEvent(new Event("storage")); + setMessages([...messages]); + }; + + // Function to handle chatting with Ollama in production (client side) + const handleSubmitProduction = async ( + e: React.FormEvent + ) => { + e.preventDefault(); + + addMessage({ role: "user", content: input, id: chatId }); + setInput(""); + + if (ollama) { + try { + const parser = new BytesOutputParser(); + + const stream = await ollama + .pipe(parser) + .stream( + (messages as Message[]).map((m) => + m.role == "user" + ? new HumanMessage(m.content) + : new AIMessage(m.content) + ) + ); + + const decoder = new TextDecoder(); + + let responseMessage = ""; + for await (const chunk of stream) { + const decodedChunk = decoder.decode(chunk); + responseMessage += decodedChunk; + setLoadingSubmit(false); + setMessages([ + ...messages, + { role: "assistant", content: responseMessage, id: chatId }, + ]); + } + addMessage({ role: "assistant", content: responseMessage, id: chatId }); + setMessages([...messages]); + + localStorage.setItem(`chat_${params.id}`, JSON.stringify(messages)); + // Trigger the storage event to update the sidebar component + window.dispatchEvent(new Event("storage")); + } catch (error) { + toast.error("An error occurred. Please try again."); + setLoadingSubmit(false); + } + } + }; + + + const runGoatPipeline = async () => { + try { + addMessage({ role: "user", content: input, id: chatId }); + setMessages([...messages]); + let user_input = input; + + setInput(""); + const response = await fetch('http://localhost:5000/api/chat', { + method: 'POST', + headers: { + 'Accept': 'application/json', + 'Content-Type': 'application/json' + }, + body: JSON.stringify({ user_input: user_input }) + }) + const reader = response.body?.getReader() + + if (reader) { + while (true) { + const { done, value } = await reader.read() + if (done) { + break + } + let temp = new TextDecoder().decode(value); + let currentState = JSON.parse(temp) + if (currentState['error']) { + toast.error("Something went wrong, retrying...\nError: " + currentState['error']) + // setLoadingSubmit(false); + // break; + } + else if (currentState['done']) { + addMessage({ role: "assistant", content: currentState['markdown'], id: chatId }); + addMessage({ role: "assistant", content: 'GoaT Link!', id: chatId }); + addMessage({ role: "user", content: "Webpage Details:\nHere is the JSON curated after parsing the above webpage:\n\n" + currentState['api_response'], id: chatId }); + setMessages([...messages]); + setLoadingSubmit(false); + break; + } else { + toast.success(JSON.parse(temp)['state'] + " completed successfully!") + } + } + } + } catch (error) { + toast.error("An error occurred. Please try again."); + setLoadingSubmit(false); + } + } + + + const onSubmit = (e: React.FormEvent) => { + e.preventDefault(); + setLoadingSubmit(true); + + setMessages([...messages]); + + // Prepare the options object with additional body data, to pass the model. + const requestOptions: ChatRequestOptions = { + options: { + body: { + selectedModel: selectedModel, + }, + }, + }; + // console.log(process.env.NODE_ENV) + // console.log("Heeeer") + console.log(input) + if (input.startsWith("#goat")) { + runGoatPipeline() + } else if (env === "production") { + handleSubmitProduction(e); + } else { + // Call the handleSubmit function with the options + handleSubmit(e, requestOptions); + } + + }; + + // When starting a new chat, append the messages to the local storage + React.useEffect(() => { + if (!isLoading && !error && messages.length > 0) { + localStorage.setItem(`chat_${params.id}`, JSON.stringify(messages)); + // Trigger the storage event to update the sidebar component + window.dispatchEvent(new Event("storage")); + } + }, [messages, chatId, isLoading, error]); + + return ( +
+ +
+ ); +} diff --git a/ui/src/app/api/chat/route.ts b/ui/src/app/api/chat/route.ts new file mode 100644 index 0000000..07c7e51 --- /dev/null +++ b/ui/src/app/api/chat/route.ts @@ -0,0 +1,31 @@ +import { StreamingTextResponse, Message } from "ai"; +import { ChatOllama } from "@langchain/community/chat_models/ollama"; +import { AIMessage, HumanMessage } from "@langchain/core/messages"; +import { BytesOutputParser } from "@langchain/core/output_parsers"; + +export const runtime = "edge"; +export const dynamic = "force-dynamic"; + +export async function POST(req: Request) { + const { messages, selectedModel } = await req.json(); + + const model = new ChatOllama({ + baseUrl: process.env.NEXT_PUBLIC_OLLAMA_URL || "http://localhost:11434", + model: selectedModel, + }); + + const parser = new BytesOutputParser(); + + const stream = await model + .pipe(parser) + .stream( + (messages as Message[]).map((m) => + m.role == "user" + ? new HumanMessage(m.content) + : new AIMessage(m.content) + ) + ); + + + return new StreamingTextResponse(stream); +} diff --git a/ui/src/app/api/model/route.ts b/ui/src/app/api/model/route.ts new file mode 100644 index 0000000..04e4c37 --- /dev/null +++ b/ui/src/app/api/model/route.ts @@ -0,0 +1,43 @@ +export async function POST(req: Request) { + const { name } = await req.json(); + + const ollamaUrl = process.env.NEXT_PUBLIC_OLLAMA_URL || "http://localhost:11434"; + + const response = await fetch(ollamaUrl + "/api/pull", { + method: "POST", + body: JSON.stringify({ name }), + }); + + // Create a new ReadableStream from the response body + const stream = new ReadableStream({ + start(controller) { + if (!response.body) { + controller.close(); + return; + } + const reader = response.body.getReader(); + + function pump() { + reader.read().then(({ done, value }) => { + if (done) { + controller.close(); + return; + } + // Enqueue the chunk of data to the controller + controller.enqueue(value); + pump(); + }).catch(error => { + console.error("Error reading response body:", error); + controller.error(error); + }); + } + + pump(); + } + }); + + // Set response headers and return the stream + const headers = new Headers(response.headers); + headers.set("Content-Type", "application/json"); + return new Response(stream, { headers }); +} diff --git a/ui/src/app/api/tags/route.ts b/ui/src/app/api/tags/route.ts new file mode 100644 index 0000000..c393623 --- /dev/null +++ b/ui/src/app/api/tags/route.ts @@ -0,0 +1,9 @@ +export const dynamic = "force-dynamic"; + +export async function GET(req: Request) { + const OLLAMA_URL = process.env.NEXT_PUBLIC_OLLAMA_URL || "http://localhost:11434"; + const res = await fetch( + OLLAMA_URL + "/api/tags" + ); + return new Response(res.body, res); +} diff --git a/ui/src/app/favicon.ico b/ui/src/app/favicon.ico new file mode 100644 index 0000000..718d6fe Binary files /dev/null and b/ui/src/app/favicon.ico differ diff --git a/ui/src/app/globals.css b/ui/src/app/globals.css new file mode 100644 index 0000000..78d22c3 --- /dev/null +++ b/ui/src/app/globals.css @@ -0,0 +1,95 @@ +@tailwind base; +@tailwind components; +@tailwind utilities; + + +@layer base { + :root { + --background: 0 0% 100%; + --foreground: 240 10% 3.9%; + --card: 0 0% 100%; + --card-foreground: 240 10% 3.9%; + --popover: 0 0% 100%; + --popover-foreground: 240 10% 3.9%; + --primary: 240 5.9% 10%; + --primary-foreground: 0 0% 98%; + --secondary: 240 4.8% 95.9%; + --secondary-foreground: 240 5.9% 10%; + --muted: 240 4.8% 95.9%; + --muted-foreground: 240 3.8% 46.1%; + --accent: 240 4.8% 95.9%; + --accent-foreground: 240 5.9% 10%; + --destructive: 0 84.2% 60.2%; + --destructive-foreground: 0 0% 98%; + --border: 240 5.9% 90%; + --input: 240 5.9% 90%; + --ring: 240 5.9% 10%; + --radius: 1rem; + } + + .dark { + --background: 0 0% 9%; + --foreground: 0 0% 98%; + --card: 0 0% 12%; + --card-foreground: 0 0% 98%; + --popover: 0 0% 12%; + --popover-foreground: 0 0% 98%; + --primary: 0 0% 98%; + --primary-foreground: 240 5.9% 10%; + --secondary: 240 3.7% 15.9%; + --secondary-foreground: 0 0% 98%; + --muted: 240 3.7% 15.9%; + --muted-foreground: 240 5% 64.9%; + --accent: 240 3.7% 15.9%; + --accent-foreground: 0 0% 98%; + --destructive: 0 62.8% 30.6%; + --destructive-foreground: 0 0% 98%; + --border: 240 3.7% 15.9%; + --input: 240 3.7% 15.9%; + --ring: 240 4.9% 83.9%; + } +} + +@layer base { + * { + @apply border-border; + } + body { + @apply bg-background text-foreground; + } +} + +#scroller * { + overflow-anchor: none; +} + +#anchor { + overflow-anchor: auto; + height: 1px; +} + +:root { + --scrollbar-thumb-color: #ccc; + --scrollbar-thumb-hover-color: #aaa; +} + +::-webkit-scrollbar { + width: 6px; + height: 6px; +} + +::-webkit-scrollbar-thumb { + background-color: var(--scrollbar-thumb-color); + border-radius: 999px; + transition: width 0.3s, height 0.3s, visibility 0.3s; +} + +::-webkit-scrollbar-thumb:hover { + background-color: var(--scrollbar-thumb-hover-color); +} + +::-webkit-scrollbar-thumb:not(:hover) { + width: 0; + height: 0; + visibility: hidden; +} \ No newline at end of file diff --git a/ui/src/app/hooks/useLocalStorageData.ts b/ui/src/app/hooks/useLocalStorageData.ts new file mode 100644 index 0000000..bff67b7 --- /dev/null +++ b/ui/src/app/hooks/useLocalStorageData.ts @@ -0,0 +1,33 @@ +import { useEffect, useState } from 'react'; + +export const useLocalStorageData = (key: string, initialValue: any) => { + const [data, setData] = useState(initialValue); + + useEffect(() => { + const handleStorageChange = () => { + const value = localStorage.getItem(key); + if (value) { + setData(JSON.parse(value)); + } + }; + + const fetchData = () => { + const value = localStorage.getItem(key); + if (value) { + setData(JSON.parse(value)); + } + }; + + // Initial fetch + fetchData(); + + // Listen for storage changes + window.addEventListener('storage', handleStorageChange); + + return () => { + window.removeEventListener('storage', handleStorageChange); + }; + }, [key]); + + return data; +}; diff --git a/ui/src/app/hooks/useSpeechRecognition.ts b/ui/src/app/hooks/useSpeechRecognition.ts new file mode 100644 index 0000000..52207fd --- /dev/null +++ b/ui/src/app/hooks/useSpeechRecognition.ts @@ -0,0 +1,84 @@ +import { useState, useRef, useEffect } from "react"; + +interface SpeechRecognitionOptions { + interimResults?: boolean; + lang?: string; + continuous?: boolean; +} + +const useSpeechToText = (options: SpeechRecognitionOptions = {}) => { + const [isListening, setIsListening] = useState(false); + const [transcript, setTranscript] = useState(""); + const recognitionRef = useRef(null); + + useEffect(() => { + if (!("webkitSpeechRecognition" in window)) { + console.error("Web Speech API is not supported"); + return; + } + + const recognition = new window.webkitSpeechRecognition(); + recognitionRef.current = recognition; + + recognition.interimResults = options.interimResults || true; + recognition.lang = options.lang || "en-US"; + recognition.continuous = options.continuous || false; + + if ("webkitSpeechGrammarList" in window) { + const grammar = + "#JSGF V1.0; grammar punctuation; public = . | , | ! | ; | : ;"; + const speechRecognitionList = new window.webkitSpeechGrammarList(); + speechRecognitionList.addFromString(grammar, 1); + recognition.grammars = speechRecognitionList; + } + + recognition.onresult = (event: SpeechRecognitionEvent) => { + let text = ""; + + for (let i = 0; i < event.results.length; i++) { + text += event.results[i][0].transcript; + } + + // Always capitalize the first letter + setTranscript(text.charAt(0).toUpperCase() + text.slice(1)); + }; + + recognition.onerror = (event) => { + console.error(event.error); + }; + + recognition.onend = () => { + setIsListening(false); + setTranscript(""); + }; + + return () => { + if (recognitionRef.current) { + recognitionRef.current.stop(); + } + }; + }, []); + + const startListening = () => { + if (recognitionRef.current && !isListening) { + recognitionRef.current.start(); + setIsListening(true); + } + }; + + const stopListening = () => { + if (recognitionRef.current && isListening) { + recognitionRef.current.stop(); + setIsListening(false); + } + }; + + return { + isListening, + transcript, + startListening, + stopListening, + }; +}; + +export default useSpeechToText; diff --git a/ui/src/app/layout.tsx b/ui/src/app/layout.tsx new file mode 100644 index 0000000..2aec7ab --- /dev/null +++ b/ui/src/app/layout.tsx @@ -0,0 +1,36 @@ +import type { Metadata } from "next"; +import { Inter } from "next/font/google"; +import "./globals.css"; +import { ThemeProvider } from "@/providers/theme-provider"; +import { Toaster } from "@/components/ui/sonner" + +const inter = Inter({ subsets: ["latin"] }); + +export const metadata: Metadata = { + title: "GoaT NLP", + description: "Chatbot web interface for GoaT NLP", +}; + +export const viewport = { + width: 'device-width', + initialScale: 1, + maximumScale: 1, + userScalable: 1, +} + +export default function RootLayout({ + children, +}: Readonly<{ + children: React.ReactNode; +}>) { + return ( + + + + {children} + + + + + ); +} diff --git a/ui/src/app/page.tsx b/ui/src/app/page.tsx new file mode 100644 index 0000000..e48c57a --- /dev/null +++ b/ui/src/app/page.tsx @@ -0,0 +1,262 @@ +"use client"; + +import { ChatLayout } from "@/components/chat/chat-layout"; +import { Button } from "@/components/ui/button"; +import { + Dialog, + DialogDescription, + DialogHeader, + DialogTitle, + DialogContent, +} from "@/components/ui/dialog"; +import { Input } from "@/components/ui/input"; +import UsernameForm from "@/components/username-form"; +import { getSelectedModel } from "@/lib/model-helper"; +import { ChatOllama } from "@langchain/community/chat_models/ollama"; +import { AIMessage, HumanMessage } from "@langchain/core/messages"; +import { BytesOutputParser } from "@langchain/core/output_parsers"; +import { ChatRequestOptions } from "ai"; +import { Message, useChat } from "ai/react"; +import React, { useEffect, useRef, useState } from "react"; +import { toast } from "sonner"; +import { v4 as uuidv4 } from "uuid"; + +export default function Home() { + const { + messages, + input, + handleInputChange, + handleSubmit, + isLoading, + error, + stop, + setMessages, + setInput, + } = useChat({ + onResponse: (response) => { + if (response) { + setLoadingSubmit(false); + } + }, + onError: (error) => { + setLoadingSubmit(false); + toast.error("An error occurred. Please try again."); + }, + }); + const [chatId, setChatId] = React.useState(""); + const [selectedModel, setSelectedModel] = React.useState( + getSelectedModel() + ); + const [open, setOpen] = React.useState(false); + const [ollama, setOllama] = useState(); + const env = process.env.NODE_ENV; + const [loadingSubmit, setLoadingSubmit] = React.useState(false); + const formRef = useRef(null); + + useEffect(() => { + if (messages.length < 1) { + // Generate a random id for the chat + console.log("Generating chat id"); + const id = uuidv4(); + setChatId(id); + } + }, [messages]); + + React.useEffect(() => { + if (!isLoading && !error && chatId && messages.length > 0) { + // Save messages to local storage + localStorage.setItem(`chat_${chatId}`, JSON.stringify(messages)); + // Trigger the storage event to update the sidebar component + window.dispatchEvent(new Event("storage")); + } + }, [chatId, isLoading, error]); + + useEffect(() => { + if (env === "production") { + const newOllama = new ChatOllama({ + baseUrl: process.env.NEXT_PUBLIC_OLLAMA_URL || "http://localhost:11434", + model: selectedModel, + }); + setOllama(newOllama); + } + + if (!localStorage.getItem("ollama_user")) { + setOpen(true); + } + }, [selectedModel]); + + const addMessage = (Message: any) => { + messages.push(Message); + window.dispatchEvent(new Event("storage")); + setMessages([...messages]); + }; + + const runGoatPipeline = async () => { + try { + addMessage({ role: "user", content: input, id: chatId }); + setMessages([...messages]); + let user_input = input; + + setInput(""); + const response = await fetch('http://localhost:5000/api/chat', { + method: 'POST', + headers: { + 'Accept': 'application/json', + 'Content-Type': 'application/json' + }, + body: JSON.stringify({ user_input: user_input }) + }) + const reader = response.body?.getReader() + + if (reader) { + while (true) { + const { done, value } = await reader.read() + if (done) { + break + } + let temp = new TextDecoder().decode(value); + let currentState = JSON.parse(temp) + if (currentState['error']) { + toast.error("Something went wrong, retrying...\nError: " + currentState['error']) + // setLoadingSubmit(false); + // break; + } + else if (currentState['done']) { + addMessage({ role: "assistant", content: currentState['markdown'], id: chatId }); + addMessage({ role: "assistant", content: 'GoaT Link!', id: chatId }); + addMessage({ role: "user", content: "Webpage Details:\nHere is the JSON curated after parsing the above webpage:\n\n" + JSON.stringify(currentState['api_response']), id: chatId }); + setMessages([...messages]); + setLoadingSubmit(false); + break; + } else { + toast.success(JSON.parse(temp)['state'] + " completed successfully!") + } + } + } + } catch (error) { + toast.error("An error occurred. Please try again."); + setLoadingSubmit(false); + } + } + + // Function to handle chatting with Ollama in production (client side) + const handleSubmitProduction = async ( + e: React.FormEvent + ) => { + e.preventDefault(); + + addMessage({ role: "user", content: input, id: chatId }); + setInput(""); + + if (ollama) { + try { + const parser = new BytesOutputParser(); + + const stream = await ollama + .pipe(parser) + .stream( + (messages as Message[]).map((m) => + m.role == "user" + ? new HumanMessage(m.content) + : new AIMessage(m.content) + ) + ); + + const decoder = new TextDecoder(); + + let responseMessage = ""; + for await (const chunk of stream) { + const decodedChunk = decoder.decode(chunk); + responseMessage += decodedChunk; + setLoadingSubmit(false); + setMessages([ + ...messages, + { role: "assistant", content: responseMessage, id: chatId }, + ]); + } + addMessage({ role: "assistant", content: responseMessage, id: chatId }); + setMessages([...messages]); + + localStorage.setItem(`chat_${chatId}`, JSON.stringify(messages)); + // Trigger the storage event to update the sidebar component + window.dispatchEvent(new Event("storage")); + } catch (error) { + toast.error("An error occurred. Please try again."); + setLoadingSubmit(false); + } + } + }; + + const onSubmit = (e: React.FormEvent) => { + e.preventDefault(); + setLoadingSubmit(true); + + setMessages([...messages]); + + // Prepare the options object with additional body data, to pass the model. + const requestOptions: ChatRequestOptions = { + options: { + body: { + selectedModel: selectedModel, + }, + }, + }; + // console.log(process.env.NODE_ENV) + // console.log("Heeeer") + console.log(input) + if (input.startsWith("#goat")) { + runGoatPipeline() + } else if (env === "production") { + handleSubmitProduction(e); + } else { + // Call the handleSubmit function with the options + handleSubmit(e, requestOptions); + } + + }; + + const onOpenChange = (isOpen: boolean) => { + const username = localStorage.getItem("ollama_user") + if (username) { + return setOpen(isOpen) + } + + localStorage.setItem("ollama_user", "Anonymous") + window.dispatchEvent(new Event("storage")) + setOpen(isOpen) + } + + return ( +
+ + + + + Welcome to Goat NLP! + + Enter your name to get started. This is just to personalize your + experience. + + + + + +
+ ); +} diff --git a/ui/src/components/chat/chat-bottombar.tsx b/ui/src/components/chat/chat-bottombar.tsx new file mode 100644 index 0000000..289b8c2 --- /dev/null +++ b/ui/src/components/chat/chat-bottombar.tsx @@ -0,0 +1,182 @@ +"use client"; + +import React, { useEffect } from "react"; +import { ChatProps } from "./chat"; +import Link from "next/link"; +import { cn } from "@/lib/utils"; +import { Button, buttonVariants } from "../ui/button"; +import TextareaAutosize from "react-textarea-autosize"; +import { motion, AnimatePresence } from "framer-motion"; +import { ImageIcon, PaperPlaneIcon, StopIcon } from "@radix-ui/react-icons"; +import { Mic, SendHorizonal } from "lucide-react"; +import useSpeechToText from "@/app/hooks/useSpeechRecognition"; + +export default function ChatBottombar({ + messages, + input, + handleInputChange, + handleSubmit, + isLoading, + error, + stop, + formRef, + setInput, +}: ChatProps) { + const [message, setMessage] = React.useState(input); + const [isMobile, setIsMobile] = React.useState(false); + const inputRef = React.useRef(null); + + React.useEffect(() => { + const checkScreenWidth = () => { + setIsMobile(window.innerWidth <= 768); + }; + + // Initial check + checkScreenWidth(); + + // Event listener for screen width changes + window.addEventListener("resize", checkScreenWidth); + + // Cleanup the event listener on component unmount + return () => { + window.removeEventListener("resize", checkScreenWidth); + }; + }, []); + + const handleKeyPress = (e: React.KeyboardEvent) => { + if (e.key === "Enter" && !e.shiftKey) { + e.preventDefault(); + handleSubmit(e as unknown as React.FormEvent); + } + }; + + + + const { isListening, transcript, startListening, stopListening } = + useSpeechToText({ continuous: true }); + + const listen = () => { + isListening ? stopVoiceInput() : startListening(); + }; + + const stopVoiceInput = () => { + setInput && setInput(transcript.length ? transcript : ""); + stopListening(); + }; + + const handleListenClick = () => { + listen(); + }; + + useEffect(() => { + if (inputRef.current) { + inputRef.current.focus(); + } + }, []); + + useEffect(() => { + if (isLoading) { + stopVoiceInput(); + } + }, [isLoading]); + + return ( +
+ +
+
+ {/* */} +
+
+ + {!isLoading ? ( +
+ {isListening ? ( +
+ +
+ ) : ( + + )} + +
+ ) : ( +
+ + +
+ )} + +
+
+
+ ); +} diff --git a/ui/src/components/chat/chat-layout.tsx b/ui/src/components/chat/chat-layout.tsx new file mode 100644 index 0000000..2762d7f --- /dev/null +++ b/ui/src/components/chat/chat-layout.tsx @@ -0,0 +1,130 @@ +"use client"; + +import React, { useEffect, useState } from "react"; +import { + ResizableHandle, + ResizablePanel, + ResizablePanelGroup, +} from "@/components/ui/resizable"; +import { cn } from "@/lib/utils"; +import { Sidebar } from "../sidebar"; +import { Message, useChat } from "ai/react"; +import Chat, { ChatProps } from "./chat"; +import ChatList from "./chat-list"; +import { HamburgerMenuIcon } from "@radix-ui/react-icons"; + +interface ChatLayoutProps { + defaultLayout: number[] | undefined; + defaultCollapsed?: boolean; + navCollapsedSize: number; + chatId: string; + setMessages: (messages: Message[]) => void; +} + +type MergedProps = ChatLayoutProps & ChatProps; + +export function ChatLayout({ + defaultLayout = [30, 160], + defaultCollapsed = false, + navCollapsedSize, + messages, + input, + handleInputChange, + handleSubmit, + isLoading, + error, + stop, + chatId, + setSelectedModel, + loadingSubmit, + formRef, + setMessages, + setInput, +}: MergedProps) { + const [isCollapsed, setIsCollapsed] = React.useState(defaultCollapsed); + const [isMobile, setIsMobile] = useState(false); + + useEffect(() => { + const checkScreenWidth = () => { + setIsMobile(window.innerWidth <= 1023); + }; + + // Initial check + checkScreenWidth(); + + // Event listener for screen width changes + window.addEventListener("resize", checkScreenWidth); + + // Cleanup the event listener on component unmount + return () => { + window.removeEventListener("resize", checkScreenWidth); + }; + }, []); + + return ( + { + document.cookie = `react-resizable-panels:layout=${JSON.stringify( + sizes + )}`; + }} + className="h-screen items-stretch" + > + { + setIsCollapsed(true); + document.cookie = `react-resizable-panels:collapsed=${JSON.stringify( + true + )}`; + }} + onExpand={() => { + setIsCollapsed(false); + document.cookie = `react-resizable-panels:collapsed=${JSON.stringify( + false + )}`; + }} + className={cn( + isCollapsed + ? "min-w-[50px] md:min-w-[70px] transition-all duration-300 ease-in-out" + : "hidden md:block" + )} + > + + + + + + + + ); +} diff --git a/ui/src/components/chat/chat-list.tsx b/ui/src/components/chat/chat-list.tsx new file mode 100644 index 0000000..5f75173 --- /dev/null +++ b/ui/src/components/chat/chat-list.tsx @@ -0,0 +1,249 @@ +import { Message, useChat } from "ai/react"; +import React, { useRef, useEffect } from "react"; +import { motion } from "framer-motion"; +import { cn } from "@/lib/utils"; +import { Avatar, AvatarFallback, AvatarImage } from "../ui/avatar"; +import { ChatProps } from "./chat"; +import Image from "next/image"; +import CodeDisplayBlock from "../code-display-block"; +import Markdown from "react-markdown"; +import remarkGfm from "remark-gfm"; +import rehypeRaw from "rehype-raw"; +import { INITIAL_QUESTIONS } from "@/utils/initial-questions"; +import { Button } from "../ui/button"; + +export default function ChatList({ + messages, + input, + handleInputChange, + handleSubmit, + isLoading, + error, + stop, + loadingSubmit, + formRef, + isMobile, +}: ChatProps) { + const bottomRef = useRef(null); + const [name, setName] = React.useState(""); + const [localStorageIsLoading, setLocalStorageIsLoading] = + React.useState(true); + const [initialQuestions, setInitialQuestions] = React.useState([]); + + const scrollToBottom = () => { + bottomRef.current?.scrollIntoView({ behavior: "smooth", block: "end" }); + }; + + useEffect(() => { + scrollToBottom(); + }, [messages]); + + useEffect(() => { + const username = localStorage.getItem("ollama_user"); + if (username) { + setName(username); + setLocalStorageIsLoading(false); + } + }, []); + + useEffect(() => { + // Fetch 4 initial questions + if (messages.length === 0) { + const questionCount = isMobile ? 2 : 4; + + setInitialQuestions( + INITIAL_QUESTIONS.sort(() => Math.random() - 0.5) + .slice(0, questionCount) + .map((message) => { + return { + id: "1", + role: "user", + content: message.content, + }; + }) + ); + } + }, [isMobile]); + + const onClickQuestion = (value: string, e: React.MouseEvent) => { + e.preventDefault(); + + handleInputChange({ + target: { value }, + } as React.ChangeEvent); + + setTimeout(() => { + formRef.current?.dispatchEvent( + new Event("submit", { + cancelable: true, + bubbles: true, + }) + ); + }, 1); + }; + + if (messages.length === 0) { + return ( +
+
+
+
+ AI +

+ How can I help you today? +

+
+ +
+ {/* Only display 4 random questions */} + {initialQuestions.length > 0 && + initialQuestions.map((message) => { + const delay = Math.random() * 0.25; + + return ( + + + + ); + })} +
+
+
+ ); + } + + return ( +
+
+ {messages.map((message, index) => ( + +
+ {message.role === "user" && ( +
+ + {message.content} + + + + + {name && name.substring(0, 2).toUpperCase()} + + +
+ )} + {message.role === "assistant" && ( +
+ + + + + {/* Check if the message content contains a code block */} + {message.content.split("```").map((part, index) => { + if (index % 2 === 0) { + return ( + + {part} + + ); + } else { + return ( +
+                            
+                          
+ ); + } + })} + {isLoading && + messages.indexOf(message) === messages.length - 1 && ( + + ... + + )} +
+
+ )} +
+
+ ))} + {loadingSubmit && ( +
+ + + +
+
+ + + +
+
+
+ )} +
+
+
+ ); +} diff --git a/ui/src/components/chat/chat-topbar.tsx b/ui/src/components/chat/chat-topbar.tsx new file mode 100644 index 0000000..a8701bb --- /dev/null +++ b/ui/src/components/chat/chat-topbar.tsx @@ -0,0 +1,133 @@ +"use client"; + +import React, { useEffect } from "react"; +import { + Popover, + PopoverContent, + PopoverTrigger, +} from "@/components/ui/popover"; +import { + Sheet, + SheetContent, + SheetDescription, + SheetHeader, + SheetTitle, + SheetTrigger, +} from "@/components/ui/sheet"; + +import { Button } from "../ui/button"; +import { CaretSortIcon, HamburgerMenuIcon } from "@radix-ui/react-icons"; +import { Sidebar } from "../sidebar"; +import { Message } from "ai/react"; +import { getSelectedModel } from "@/lib/model-helper"; + +interface ChatTopbarProps { + setSelectedModel: React.Dispatch>; + isLoading: boolean; + chatId?: string; + messages: Message[]; + setMessages: (messages: Message[]) => void; +} + +export default function ChatTopbar({ + setSelectedModel, + isLoading, + chatId, + messages, + setMessages +}: ChatTopbarProps) { + const [models, setModels] = React.useState([]); + const [open, setOpen] = React.useState(false); + const [sheetOpen, setSheetOpen] = React.useState(false); + const [currentModel, setCurrentModel] = React.useState(null); + + useEffect(() => { + setCurrentModel(getSelectedModel()); + + const env = process.env.NODE_ENV; + + const fetchModels = async () => { + if (env === "production") { + const fetchedModels = await fetch(process.env.NEXT_PUBLIC_OLLAMA_URL + "/api/tags"); + const json = await fetchedModels.json(); + const apiModels = json.models.map((model : any) => model.name); + setModels([...apiModels]); + } + else { + const fetchedModels = await fetch("/api/tags") + const json = await fetchedModels.json(); + const apiModels = json.models.map((model : any) => model.name); + setModels([...apiModels]); + } + } + fetchModels(); + }, []); + + const handleModelChange = (model: string) => { + setCurrentModel(model); + setSelectedModel(model); + if (typeof window !== 'undefined') { + localStorage.setItem("selectedModel", model); + } + setOpen(false); + }; + + const handleCloseSidebar = () => { + setSheetOpen(false); // Close the sidebar + }; + + return ( +
+ + + + + + + + + + + + + + + {models.length > 0 ? ( + models.map((model) => ( + + )) + ) : ( + + )} + + +
+ ); +} diff --git a/ui/src/components/chat/chat.tsx b/ui/src/components/chat/chat.tsx new file mode 100644 index 0000000..3fbbf08 --- /dev/null +++ b/ui/src/components/chat/chat.tsx @@ -0,0 +1,85 @@ +import React from "react"; +import ChatTopbar from "./chat-topbar"; +import ChatList from "./chat-list"; +import ChatBottombar from "./chat-bottombar"; +import { Message, useChat } from "ai/react"; +import { ChatRequestOptions } from "ai"; +import { v4 as uuidv4 } from "uuid"; + +export interface ChatProps { + chatId?: string; + setSelectedModel: React.Dispatch>; + messages: Message[]; + input: string; + handleInputChange: (e: React.ChangeEvent) => void; + handleSubmit: ( + e: React.FormEvent, + chatRequestOptions?: ChatRequestOptions + ) => void; + isLoading: boolean; + loadingSubmit?: boolean; + error: undefined | Error; + stop: () => void; + formRef: React.RefObject; + isMobile?: boolean; + setInput?: React.Dispatch>; + setMessages: (messages: Message[]) => void; +} + +export default function Chat({ + messages, + input, + handleInputChange, + handleSubmit, + isLoading, + error, + stop, + setSelectedModel, + chatId, + loadingSubmit, + formRef, + isMobile, + setInput, + setMessages +}: ChatProps) { + return ( +
+ + + !message.content.startsWith("Webpage Details:"))} + input={input} + handleInputChange={handleInputChange} + handleSubmit={handleSubmit} + isLoading={isLoading} + loadingSubmit={loadingSubmit} + error={error} + stop={stop} + formRef={formRef} + isMobile={isMobile} + setMessages={setMessages} + /> + + +
+ ); +} diff --git a/ui/src/components/code-display-block.tsx b/ui/src/components/code-display-block.tsx new file mode 100644 index 0000000..02fe71b --- /dev/null +++ b/ui/src/components/code-display-block.tsx @@ -0,0 +1,54 @@ +"use client"; +import { CheckIcon, CopyIcon } from "@radix-ui/react-icons"; +import React from "react"; +import { CodeBlock, dracula, github } from "react-code-blocks"; +import { Button } from "./ui/button"; +import { toast } from "sonner"; +import { useTheme } from "next-themes"; + +interface ButtonCodeblockProps { + code: string; + lang: string; +} + +export default function CodeDisplayBlock({ code, lang }: ButtonCodeblockProps) { + const [isCopied, setisCopied] = React.useState(false); + const { theme } = useTheme(); + + const copyToClipboard = () => { + navigator.clipboard.writeText(code); + setisCopied(true); + toast.success("Code copied to clipboard!"); + setTimeout(() => { + setisCopied(false); + }, 1500); + }; + + return ( +
+ + +
+ ); +} diff --git a/ui/src/components/edit-username-form.tsx b/ui/src/components/edit-username-form.tsx new file mode 100644 index 0000000..a857323 --- /dev/null +++ b/ui/src/components/edit-username-form.tsx @@ -0,0 +1,91 @@ +"use client"; + +import { set, z } from "zod"; +import { zodResolver } from "@hookform/resolvers/zod"; +import { useForm } from "react-hook-form"; +import { Button } from "@/components/ui/button"; +import { + Form, + FormControl, + FormDescription, + FormField, + FormItem, + FormLabel, + FormMessage, +} from "@/components/ui/form"; +import { Input } from "@/components/ui/input"; +import React, { useEffect, useState } from "react"; +import { ModeToggle } from "./mode-toggle"; +import { toast } from "sonner" + + +const formSchema = z.object({ + username: z.string().min(2, { + message: "Name must be at least 2 characters.", + }), +}); + +interface EditUsernameFormProps { + setOpen: React.Dispatch>; +} + +export default function EditUsernameForm({ setOpen }: EditUsernameFormProps) { + const [name, setName] = useState(""); + + useEffect(() => { + setName(localStorage.getItem("ollama_user") || "Anonymous"); + }, []); + + const form = useForm>({ + resolver: zodResolver(formSchema), + defaultValues: { + username: "", + }, + }); + + function onSubmit(values: z.infer) { + localStorage.setItem("ollama_user", values.username); + window.dispatchEvent(new Event("storage")); + toast.success("Name updated successfully"); + } + + const handleChange = (e: React.ChangeEvent) => { + e.preventDefault(); + form.setValue("username", e.currentTarget.value); + setName(e.currentTarget.value); + }; + + return ( +
+
+ Theme + +
+ + ( + + Name + +
+ handleChange(e)} + /> + +
+
+ +
+ )} + /> + + + ); +} diff --git a/ui/src/components/emoji-picker.tsx b/ui/src/components/emoji-picker.tsx new file mode 100644 index 0000000..66483e7 --- /dev/null +++ b/ui/src/components/emoji-picker.tsx @@ -0,0 +1,38 @@ +'use client' + +import { + Popover, + PopoverContent, + PopoverTrigger, +} from "@/components/ui/popover" +import { SmileIcon } from "lucide-react"; +import Picker from '@emoji-mart/react'; +import data from "@emoji-mart/data" + +interface EmojiPickerProps { + onChange: (value: string) => void; +} + + +export const EmojiPicker = ({ + onChange +}: EmojiPickerProps) => { + + return ( + + + + + + onChange(emoji.native)} + /> + + + ) +} diff --git a/ui/src/components/mode-toggle.tsx b/ui/src/components/mode-toggle.tsx new file mode 100644 index 0000000..dbabf09 --- /dev/null +++ b/ui/src/components/mode-toggle.tsx @@ -0,0 +1,47 @@ +"use client"; + +import * as React from "react"; +import { ChevronDownIcon, MoonIcon, SunIcon } from "@radix-ui/react-icons"; +import { useTheme } from "next-themes"; + +import { Button } from "@/components/ui/button"; +import { + DropdownMenu, + DropdownMenuContent, + DropdownMenuItem, + DropdownMenuTrigger, +} from "@/components/ui/dropdown-menu"; + +export function ModeToggle() { + const { setTheme, theme } = useTheme(); + + return ( + + + + + + setTheme("light")}> + Light mode + + setTheme("dark")}> + Dark mode + + + + ); +} diff --git a/ui/src/components/pull-model-form.tsx b/ui/src/components/pull-model-form.tsx new file mode 100644 index 0000000..56d679e --- /dev/null +++ b/ui/src/components/pull-model-form.tsx @@ -0,0 +1,186 @@ +"use client"; + +import React, { useState } from "react"; +import { + Form, + FormField, + FormItem, + FormLabel, + FormMessage, +} from "@/components/ui/form"; +import { Button } from "./ui/button"; +import { z } from "zod"; +import { useForm } from "react-hook-form"; +import { zodResolver } from "@hookform/resolvers/zod"; +import { toast } from "sonner"; +import { Loader2Icon } from "lucide-react"; +import { Input } from "./ui/input"; +import { useRouter } from "next/navigation"; + +const formSchema = z.object({ + name: z.string().min(1, { + message: "Please select a model to pull", + }), +}); + +export default function PullModelForm() { + const [isDownloading, setIsDownloading] = useState(false); + const [name, setName] = useState(""); + const router = useRouter(); + const env = process.env.NODE_ENV; + + const form = useForm>({ + resolver: zodResolver(formSchema), + }); + + function onSubmit(data: z.infer) { + // Trim whitespace + data.name = data.name.trim(); + + setIsDownloading(true); + // Send the model name to the server + if (env === "production") { + // Make a post request to localhost + const pullModel = async () => { + const response = await fetch(process.env.NEXT_PUBLIC_OLLAMA_URL + "/api/pull", { + method: "POST", + headers: { + "Content-Type": "application/json", + }, + body: JSON.stringify(data), + }); + const json = await response.json(); + if (json.error) { + toast.error("Error: " + json.error); + setIsDownloading(false); + return; + } else if (json.status === "success") { + toast.success("Model pulled successfully"); + setIsDownloading(false); + return; + } + } + pullModel(); + } else { + fetch("/api/model", { + method: "POST", + headers: { + "Content-Type": "application/json", + }, + body: JSON.stringify(data), + }) + .then((response) => { + // Check if response is successful + if (!response.ok) { + throw new Error("Network response was not ok"); + } + if (!response.body) { + throw new Error("Something went wrong"); + } + // Create a new ReadableStream from the response body + const reader = response.body.getReader(); + + // Read the data in chunks + reader.read().then(function processText({ done, value }) { + if (done) { + setIsDownloading(false); + return; + } + + // Convert the chunk of data to a string + const text = new TextDecoder().decode(value); + + // Split the text into individual JSON objects + const jsonObjects = text.trim().split("\n"); + + jsonObjects.forEach((jsonObject) => { + try { + const responseJson = JSON.parse(jsonObject); + if (responseJson.error) { + // Display an error toast if the response contains an error + toast.error("Error: " + responseJson.error); + setIsDownloading(false); + return; + } else if (responseJson.status === "success") { + // Display a success toast if the response status is success + toast.success("Model pulled successfully"); + setIsDownloading(false); + return; + } + } catch (error) { + toast.error("Error parsing JSON"); + setIsDownloading(false); + return; + } + }); + + // Continue reading the next chunk + reader.read().then(processText); + }); + }) + .catch((error) => { + setIsDownloading(false); + console.error("Error pulling model:", error); + toast.error("Error pulling model"); + }); + } + } + + const handleChange = (e: React.ChangeEvent) => { + e.preventDefault(); + form.setValue("name", e.currentTarget.value); + setName(e.currentTarget.value); + }; + + return ( +
+ + ( + + Model name + handleChange(e)} + /> +

+ Check the{" "} + + library + {" "} + for a list of available models. +

+ +
+ )} + /> +
+ +

+ {isDownloading + ? "This may take a while. You can safely close this modal and continue using the app" + : "Pressing the button will download the specified model to your device."} +

+
+ + + ); +} diff --git a/ui/src/components/pull-model.tsx b/ui/src/components/pull-model.tsx new file mode 100644 index 0000000..b808f85 --- /dev/null +++ b/ui/src/components/pull-model.tsx @@ -0,0 +1,38 @@ +import React, { useEffect } from "react"; +import { Button } from "./ui/button"; +import { + Dialog, + DialogContent, + DialogDescription, + DialogHeader, + DialogTitle, + DialogTrigger, +} from "./ui/dialog"; +import { + Select, + SelectContent, + SelectItem, + SelectTrigger, + SelectValue, +} from "@/components/ui/select"; + +import { DownloadIcon } from "@radix-ui/react-icons"; +import PullModelForm from "./pull-model-form"; + +export default function PullModel() { + + return ( + + +
+ +

Pull model

+
+
+ + Pull Model + + +
+ ); +} diff --git a/ui/src/components/sidebar-skeleton.tsx b/ui/src/components/sidebar-skeleton.tsx new file mode 100644 index 0000000..2ad3472 --- /dev/null +++ b/ui/src/components/sidebar-skeleton.tsx @@ -0,0 +1,33 @@ +import { Skeleton } from "@/components/ui/skeleton"; + +export default function SidebarSkeleton() { + return ( +
+
+ + +
+ +
+ + +
+ +
+ + +
+ +
+ + +
+ +
+ + +
+ +
+ ); +} diff --git a/ui/src/components/sidebar.tsx b/ui/src/components/sidebar.tsx new file mode 100644 index 0000000..3d184d3 --- /dev/null +++ b/ui/src/components/sidebar.tsx @@ -0,0 +1,223 @@ +"use client"; + +import Link from "next/link"; +import { MoreHorizontal, SquarePen, Trash2 } from "lucide-react"; +import { cn } from "@/lib/utils"; +import { Button, buttonVariants } from "@/components/ui/button"; +import { Message } from "ai/react"; +import Image from "next/image"; +import { useEffect, useState } from "react"; +import SidebarSkeleton from "./sidebar-skeleton"; +import { Avatar, AvatarFallback, AvatarImage } from "./ui/avatar"; +import UserSettings from "./user-settings"; +import { useLocalStorageData } from "@/app/hooks/useLocalStorageData"; +import { ScrollArea, Scrollbar } from "@radix-ui/react-scroll-area"; +import PullModel from "./pull-model"; +import { + Dialog, + DialogContent, + DialogDescription, + DialogHeader, + DialogTitle, + DialogTrigger, +} from "./ui/dialog"; +import { + DropdownMenu, + DropdownMenuContent, + DropdownMenuTrigger, +} from "./ui/dropdown-menu"; +import { TrashIcon } from "@radix-ui/react-icons"; +import { useRouter } from "next/navigation"; + +interface SidebarProps { + isCollapsed: boolean; + messages: Message[]; + onClick?: () => void; + isMobile: boolean; + chatId: string; + setMessages: (messages: Message[]) => void; + closeSidebar?: () => void; +} + +export function Sidebar({ + messages, + isCollapsed, + isMobile, + chatId, + setMessages, + closeSidebar +}: SidebarProps) { + const [localChats, setLocalChats] = useState< + { chatId: string; messages: Message[] }[] + >([]); + const localChatss = useLocalStorageData("chat_", []); + const [selectedChatId, setSselectedChatId] = useState(null); + const [isLoading, setIsLoading] = useState(true); + const router = useRouter(); + + useEffect(() => { + if (chatId) { + setSselectedChatId(chatId); + } + + setLocalChats(getLocalstorageChats()); + const handleStorageChange = () => { + setLocalChats(getLocalstorageChats()); + }; + window.addEventListener("storage", handleStorageChange); + return () => { + window.removeEventListener("storage", handleStorageChange); + }; + }, []); + + const getLocalstorageChats = (): { + chatId: string; + messages: Message[]; + }[] => { + const chats = Object.keys(localStorage).filter((key) => + key.startsWith("chat_") + ); + + if (chats.length === 0) { + setIsLoading(false); + } + + // Map through the chats and return an object with chatId and messages + const chatObjects = chats.map((chat) => { + const item = localStorage.getItem(chat); + return item + ? { chatId: chat, messages: JSON.parse(item) } + : { chatId: "", messages: [] }; + }); + + // Sort chats by the createdAt date of the first message of each chat + chatObjects.sort((a, b) => { + const aDate = new Date(a.messages[0].createdAt); + const bDate = new Date(b.messages[0].createdAt); + return bDate.getTime() - aDate.getTime(); + }); + + setIsLoading(false); + return chatObjects; + }; + + const handleDeleteChat = (chatId: string) => { + localStorage.removeItem(chatId); + setLocalChats(getLocalstorageChats()); + }; + + return ( +
+
+ + +
+

Your chats

+ {localChats.length > 0 && ( +
+ {localChats.map(({ chatId, messages }, index) => ( + +
+
+ + {messages.length > 0 ? messages[0].content : ""} + +
+
+ + + + + + + + + + + + Delete chat? + + Are you sure you want to delete this chat? This + action cannot be undone. + +
+ + +
+
+
+
+
+
+ + ))} +
+ )} + {isLoading && } +
+
+ +
+ +
+
+ ); +} diff --git a/ui/src/components/ui/avatar.tsx b/ui/src/components/ui/avatar.tsx new file mode 100644 index 0000000..51e507b --- /dev/null +++ b/ui/src/components/ui/avatar.tsx @@ -0,0 +1,50 @@ +"use client" + +import * as React from "react" +import * as AvatarPrimitive from "@radix-ui/react-avatar" + +import { cn } from "@/lib/utils" + +const Avatar = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +Avatar.displayName = AvatarPrimitive.Root.displayName + +const AvatarImage = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +AvatarImage.displayName = AvatarPrimitive.Image.displayName + +const AvatarFallback = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +AvatarFallback.displayName = AvatarPrimitive.Fallback.displayName + +export { Avatar, AvatarImage, AvatarFallback } diff --git a/ui/src/components/ui/button.tsx b/ui/src/components/ui/button.tsx new file mode 100644 index 0000000..d5b211b --- /dev/null +++ b/ui/src/components/ui/button.tsx @@ -0,0 +1,60 @@ +import * as React from "react"; +import { Slot } from "@radix-ui/react-slot"; +import { cva, type VariantProps } from "class-variance-authority"; + +import { cn } from "@/lib/utils"; + +const buttonVariants = cva( + "inline-flex items-center justify-center whitespace-nowrap rounded-md text-sm font-medium transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-ring disabled:pointer-events-none disabled:opacity-50", + { + variants: { + variant: { + default: + "bg-primary text-primary-foreground shadow hover:bg-primary/90", + destructive: + "bg-destructive text-destructive-foreground shadow-sm hover:bg-destructive/90", + outline: + "border border-input bg-background shadow-sm hover:bg-accent hover:text-accent-foreground", + secondary: + "dark:bg-card/60 bg-accent/20 text-secondary-foreground shadow-sm hover:bg-secondary/60 hover:dark:bg-card/40", + ghost: "hover:bg-accent hover:text-accent-foreground", + link: "text-primary underline-offset-4 hover:underline", + secondaryLink: + "bg-accent/90 dark:bg-secondary/80 text-secondary-foreground shadow-sm dark:hover:bg-secondary hover:bg-accent", + }, + size: { + default: "h-9 px-4 py-2", + sm: "h-8 rounded-md px-3 text-xs", + lg: "h-10 rounded-md px-8", + icon: "h-10 w-10", + iconSm: "h-8 w-8", + }, + }, + defaultVariants: { + variant: "default", + size: "default", + }, + } +); + +export interface ButtonProps + extends React.ButtonHTMLAttributes, + VariantProps { + asChild?: boolean; +} + +const Button = React.forwardRef( + ({ className, variant, size, asChild = false, ...props }, ref) => { + const Comp = asChild ? Slot : "button"; + return ( + + ); + } +); +Button.displayName = "Button"; + +export { Button, buttonVariants }; diff --git a/ui/src/components/ui/card.tsx b/ui/src/components/ui/card.tsx new file mode 100644 index 0000000..77e9fb7 --- /dev/null +++ b/ui/src/components/ui/card.tsx @@ -0,0 +1,76 @@ +import * as React from "react" + +import { cn } from "@/lib/utils" + +const Card = React.forwardRef< + HTMLDivElement, + React.HTMLAttributes +>(({ className, ...props }, ref) => ( +
+)) +Card.displayName = "Card" + +const CardHeader = React.forwardRef< + HTMLDivElement, + React.HTMLAttributes +>(({ className, ...props }, ref) => ( +
+)) +CardHeader.displayName = "CardHeader" + +const CardTitle = React.forwardRef< + HTMLParagraphElement, + React.HTMLAttributes +>(({ className, ...props }, ref) => ( +

+)) +CardTitle.displayName = "CardTitle" + +const CardDescription = React.forwardRef< + HTMLParagraphElement, + React.HTMLAttributes +>(({ className, ...props }, ref) => ( +

+)) +CardDescription.displayName = "CardDescription" + +const CardContent = React.forwardRef< + HTMLDivElement, + React.HTMLAttributes +>(({ className, ...props }, ref) => ( +

+)) +CardContent.displayName = "CardContent" + +const CardFooter = React.forwardRef< + HTMLDivElement, + React.HTMLAttributes +>(({ className, ...props }, ref) => ( +
+)) +CardFooter.displayName = "CardFooter" + +export { Card, CardHeader, CardFooter, CardTitle, CardDescription, CardContent } diff --git a/ui/src/components/ui/dialog.tsx b/ui/src/components/ui/dialog.tsx new file mode 100644 index 0000000..19d2151 --- /dev/null +++ b/ui/src/components/ui/dialog.tsx @@ -0,0 +1,122 @@ +"use client" + +import * as React from "react" +import * as DialogPrimitive from "@radix-ui/react-dialog" +import { Cross2Icon } from "@radix-ui/react-icons" + +import { cn } from "@/lib/utils" + +const Dialog = DialogPrimitive.Root + +const DialogTrigger = DialogPrimitive.Trigger + +const DialogPortal = DialogPrimitive.Portal + +const DialogClose = DialogPrimitive.Close + +const DialogOverlay = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +DialogOverlay.displayName = DialogPrimitive.Overlay.displayName + +const DialogContent = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, children, ...props }, ref) => ( + + + + {children} + + + Close + + + +)) +DialogContent.displayName = DialogPrimitive.Content.displayName + +const DialogHeader = ({ + className, + ...props +}: React.HTMLAttributes) => ( +
+) +DialogHeader.displayName = "DialogHeader" + +const DialogFooter = ({ + className, + ...props +}: React.HTMLAttributes) => ( +
+) +DialogFooter.displayName = "DialogFooter" + +const DialogTitle = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +DialogTitle.displayName = DialogPrimitive.Title.displayName + +const DialogDescription = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +DialogDescription.displayName = DialogPrimitive.Description.displayName + +export { + Dialog, + DialogPortal, + DialogOverlay, + DialogTrigger, + DialogClose, + DialogContent, + DialogHeader, + DialogFooter, + DialogTitle, + DialogDescription, +} diff --git a/ui/src/components/ui/dropdown-menu.tsx b/ui/src/components/ui/dropdown-menu.tsx new file mode 100644 index 0000000..242b07a --- /dev/null +++ b/ui/src/components/ui/dropdown-menu.tsx @@ -0,0 +1,205 @@ +"use client" + +import * as React from "react" +import * as DropdownMenuPrimitive from "@radix-ui/react-dropdown-menu" +import { + CheckIcon, + ChevronRightIcon, + DotFilledIcon, +} from "@radix-ui/react-icons" + +import { cn } from "@/lib/utils" + +const DropdownMenu = DropdownMenuPrimitive.Root + +const DropdownMenuTrigger = DropdownMenuPrimitive.Trigger + +const DropdownMenuGroup = DropdownMenuPrimitive.Group + +const DropdownMenuPortal = DropdownMenuPrimitive.Portal + +const DropdownMenuSub = DropdownMenuPrimitive.Sub + +const DropdownMenuRadioGroup = DropdownMenuPrimitive.RadioGroup + +const DropdownMenuSubTrigger = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef & { + inset?: boolean + } +>(({ className, inset, children, ...props }, ref) => ( + + {children} + + +)) +DropdownMenuSubTrigger.displayName = + DropdownMenuPrimitive.SubTrigger.displayName + +const DropdownMenuSubContent = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +DropdownMenuSubContent.displayName = + DropdownMenuPrimitive.SubContent.displayName + +const DropdownMenuContent = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, sideOffset = 4, ...props }, ref) => ( + + + +)) +DropdownMenuContent.displayName = DropdownMenuPrimitive.Content.displayName + +const DropdownMenuItem = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef & { + inset?: boolean + } +>(({ className, inset, ...props }, ref) => ( + +)) +DropdownMenuItem.displayName = DropdownMenuPrimitive.Item.displayName + +const DropdownMenuCheckboxItem = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, children, checked, ...props }, ref) => ( + + + + + + + {children} + +)) +DropdownMenuCheckboxItem.displayName = + DropdownMenuPrimitive.CheckboxItem.displayName + +const DropdownMenuRadioItem = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, children, ...props }, ref) => ( + + + + + + + {children} + +)) +DropdownMenuRadioItem.displayName = DropdownMenuPrimitive.RadioItem.displayName + +const DropdownMenuLabel = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef & { + inset?: boolean + } +>(({ className, inset, ...props }, ref) => ( + +)) +DropdownMenuLabel.displayName = DropdownMenuPrimitive.Label.displayName + +const DropdownMenuSeparator = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => ( + +)) +DropdownMenuSeparator.displayName = DropdownMenuPrimitive.Separator.displayName + +const DropdownMenuShortcut = ({ + className, + ...props +}: React.HTMLAttributes) => { + return ( + + ) +} +DropdownMenuShortcut.displayName = "DropdownMenuShortcut" + +export { + DropdownMenu, + DropdownMenuTrigger, + DropdownMenuContent, + DropdownMenuItem, + DropdownMenuCheckboxItem, + DropdownMenuRadioItem, + DropdownMenuLabel, + DropdownMenuSeparator, + DropdownMenuShortcut, + DropdownMenuGroup, + DropdownMenuPortal, + DropdownMenuSub, + DropdownMenuSubContent, + DropdownMenuSubTrigger, + DropdownMenuRadioGroup, +} diff --git a/ui/src/components/ui/form.tsx b/ui/src/components/ui/form.tsx new file mode 100644 index 0000000..f6afdaf --- /dev/null +++ b/ui/src/components/ui/form.tsx @@ -0,0 +1,176 @@ +import * as React from "react" +import * as LabelPrimitive from "@radix-ui/react-label" +import { Slot } from "@radix-ui/react-slot" +import { + Controller, + ControllerProps, + FieldPath, + FieldValues, + FormProvider, + useFormContext, +} from "react-hook-form" + +import { cn } from "@/lib/utils" +import { Label } from "@/components/ui/label" + +const Form = FormProvider + +type FormFieldContextValue< + TFieldValues extends FieldValues = FieldValues, + TName extends FieldPath = FieldPath +> = { + name: TName +} + +const FormFieldContext = React.createContext( + {} as FormFieldContextValue +) + +const FormField = < + TFieldValues extends FieldValues = FieldValues, + TName extends FieldPath = FieldPath +>({ + ...props +}: ControllerProps) => { + return ( + + + + ) +} + +const useFormField = () => { + const fieldContext = React.useContext(FormFieldContext) + const itemContext = React.useContext(FormItemContext) + const { getFieldState, formState } = useFormContext() + + const fieldState = getFieldState(fieldContext.name, formState) + + if (!fieldContext) { + throw new Error("useFormField should be used within ") + } + + const { id } = itemContext + + return { + id, + name: fieldContext.name, + formItemId: `${id}-form-item`, + formDescriptionId: `${id}-form-item-description`, + formMessageId: `${id}-form-item-message`, + ...fieldState, + } +} + +type FormItemContextValue = { + id: string +} + +const FormItemContext = React.createContext( + {} as FormItemContextValue +) + +const FormItem = React.forwardRef< + HTMLDivElement, + React.HTMLAttributes +>(({ className, ...props }, ref) => { + const id = React.useId() + + return ( + +
+ + ) +}) +FormItem.displayName = "FormItem" + +const FormLabel = React.forwardRef< + React.ElementRef, + React.ComponentPropsWithoutRef +>(({ className, ...props }, ref) => { + const { error, formItemId } = useFormField() + + return ( +