You would come across the RulePolicy configuration of Rasa if you ever land up on this Rasa documentation page: https://rasa.com/docs/rasa/policies/ The page for Forms says:Usage
To use forms with Rasa Open Source you need to make sure that the Rule Policy is added to your policy configuration. For example: policies: - name: RulePolicy To find out the lack of proper logging and getting to understand the erroneous situation that this policy can land you in, do the following. Do a "$ rasa init" to initialize a project. Add the following code to the "config.yml": policies: - name: RulePolicy Next, do: $ rasa train $ rasa interactiveNext we are going to show chat logs 'with the RulePolicy configuration' and 'without the RulePolicy configuration'
Without the RulePolicy configuration (this is the default setting you get from '$ rasa init')
(base) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop/ws/jupyter/rasa/project2$ rasa interactive 2022-10-04 00:09:02 INFO numexpr.utils - NumExpr defaulting to 4 threads. The configuration for policies and pipeline was chosen automatically. It was written into the config file at 'config.yml'. /home/ashish/.local/lib/python3.8/site-packages/matplotlib/__init__.py:169: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead. if LooseVersion(module.__version__) < minver: /home/ashish/anaconda3/envs/rasa_py38/lib/python3.8/site-packages/setuptools/_distutils/version.py:346: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead. other = LooseVersion(other) /home/ashish/.local/lib/python3.8/site-packages/tensorflow_addons/utils/ensure_tf_install.py:47: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead. min_version = LooseVersion(INCLUSIVE_MIN_TF_VERSION) 2022-10-04 00:09:09 INFO rasa.engine.training.hooks - Restored component 'CountVectorsFeaturizer' from cache. 2022-10-04 00:09:09 INFO rasa.engine.training.hooks - Restored component 'CountVectorsFeaturizer' from cache. 2022-10-04 00:09:09 INFO rasa.engine.training.hooks - Restored component 'DIETClassifier' from cache. 2022-10-04 00:09:09 INFO rasa.engine.training.hooks - Restored component 'EntitySynonymMapper' from cache. 2022-10-04 00:09:09 INFO rasa.engine.training.hooks - Restored component 'LexicalSyntacticFeaturizer' from cache. 2022-10-04 00:09:09 INFO rasa.engine.training.hooks - Restored component 'MemoizationPolicy' from cache. 2022-10-04 00:09:09 INFO rasa.engine.training.hooks - Restored component 'RegexFeaturizer' from cache. 2022-10-04 00:09:09 INFO rasa.engine.training.hooks - Restored component 'ResponseSelector' from cache. 2022-10-04 00:09:09 INFO rasa.engine.training.hooks - Restored component 'RulePolicy' from cache. 2022-10-04 00:09:09 INFO rasa.engine.training.hooks - Restored component 'TEDPolicy' from cache. 2022-10-04 00:09:09 INFO rasa.engine.training.hooks - Restored component 'UnexpecTEDIntentPolicy' from cache. Your Rasa model is trained and saved at 'models/20221004-000906-cream-hoops.tar.gz'. /home/ashish/.local/lib/python3.8/site-packages/colorclass/codes.py:5: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working from collections import Mapping /home/ashish/.local/lib/python3.8/site-packages/sanic_cors/extension.py:39: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead. SANIC_VERSION = LooseVersion(sanic_version) 2022-10-04 00:09:24 INFO rasa.core.processor - Loading model models/20221004-000906-cream-hoops.tar.gz... 2022-10-04 00:09:51 WARNING rasa.shared.utils.common - The UnexpecTED Intent Policy is currently experimental and might change or be removed in the future 🔬 Please share your feedback on it in the forum (https://forum.rasa.com) to help us make this feature ready for production. 2022-10-04 00:10:04 INFO root - Rasa server is up and running. Processed story blocks: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 1446.98it/s, # trackers=1] Processed rules: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2095.58it/s, # trackers=1] Bot loaded. Visualisation at http://localhost:5006/visualization.html . Type a message and press enter (press 'Ctrl-c' to exit). ? Your input -> hi ? Your NLU model classified 'hi' with intent 'greet' and there are no entities, is this correct? Yes ------ Chat History # Bot You ──────────────────────────────────────────── 1 action_listen ──────────────────────────────────────────── 2 hi intent: greet 1.00 Current slots: session_started_metadata: None ------ ? The bot wants to run 'utter_greet', correct? Yes /home/ashish/.local/lib/python3.8/site-packages/rasa/server.py:860: FutureWarning: The "POST /conversations/<conversation_id>/execute" endpoint is deprecated. Inserting actions to the tracker externally should be avoided. Actions should be predicted by the policies only. rasa.shared.utils.io.raise_warning( ------ Chat History # Bot You ──────────────────────────────────────────────── 1 action_listen ──────────────────────────────────────────────── 2 hi intent: greet 1.00 ──────────────────────────────────────────────── 3 utter_greet 1.00 Hey! How are you? ------ Current slots: session_started_metadata: None ? The bot wants to run 'action_listen', correct? Yes ? Your input -> great ? Your NLU model classified 'great' with intent 'mood_great' and there are no entities, is this correct? Yes ------ Chat History ------ # Bot You ────────────────────────────────────────────────────── 1 action_listen ────────────────────────────────────────────────────── 2 hi intent: greet 1.00 ────────────────────────────────────────────────────── 3 utter_greet 1.00 Hey! How are you? action_listen 1.00 ────────────────────────────────────────────────────── 4 great intent: mood_great 1.00 Current slots: session_started_metadata: None ? The bot wants to run 'utter_happy', correct? Yes ------ Chat History # Bot You ────────────────────────────────────────────────────── 1 action_listen ────────────────────────────────────────────────────── 2 hi intent: greet 1.00 ────────────────────────────────────────────────────── 3 utter_greet 1.00 Hey! How are you? action_listen 1.00 ────────────────────────────────────────────────────── 4 great intent: mood_great 1.00 ────────────────────────────────────────────────────── 5 utter_happy 1.00 Great, carry on! ------ Current slots: session_started_metadata: None ? The bot wants to run 'action_listen', correct? Yes ? Your input ->Logs with the RulePolicy configuration
Erroneous Logs (Part 1)
(base) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop/ws/jupyter/rasa/project2$ rasa interactive 2022-10-03 23:35:00 INFO numexpr.utils - NumExpr defaulting to 4 threads. The configuration for pipeline was chosen automatically. It was written into the config file at 'config.yml'. /home/ashish/.local/lib/python3.8/site-packages/matplotlib/__init__.py:169: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead. if LooseVersion(module.__version__) < minver: /home/ashish/anaconda3/envs/rasa_py38/lib/python3.8/site-packages/setuptools/_distutils/version.py:346: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead. other = LooseVersion(other) /home/ashish/.local/lib/python3.8/site-packages/tensorflow_addons/utils/ensure_tf_install.py:47: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead. min_version = LooseVersion(INCLUSIVE_MIN_TF_VERSION) 2022-10-03 23:35:08 INFO rasa.engine.training.hooks - Restored component 'CountVectorsFeaturizer' from cache. 2022-10-03 23:35:08 INFO rasa.engine.training.hooks - Restored component 'CountVectorsFeaturizer' from cache. 2022-10-03 23:35:08 INFO rasa.engine.training.hooks - Restored component 'DIETClassifier' from cache. 2022-10-03 23:35:08 INFO rasa.engine.training.hooks - Restored component 'EntitySynonymMapper' from cache. 2022-10-03 23:35:08 INFO rasa.engine.training.hooks - Restored component 'LexicalSyntacticFeaturizer' from cache. 2022-10-03 23:35:08 INFO rasa.engine.training.hooks - Restored component 'RegexFeaturizer' from cache. 2022-10-03 23:35:08 INFO rasa.engine.training.hooks - Restored component 'ResponseSelector' from cache. 2022-10-03 23:35:08 INFO rasa.engine.training.hooks - Restored component 'RulePolicy' from cache. Your Rasa model is trained and saved at 'models/20221003-233504-energetic-palace.tar.gz'. /home/ashish/.local/lib/python3.8/site-packages/colorclass/codes.py:5: DeprecationWarning: Using or importing the ABCs from 'collections' instead of from 'collections.abc' is deprecated since Python 3.3, and in 3.10 it will stop working from collections import Mapping /home/ashish/.local/lib/python3.8/site-packages/sanic_cors/extension.py:39: DeprecationWarning: distutils Version classes are deprecated. Use packaging.version instead. SANIC_VERSION = LooseVersion(sanic_version) 2022-10-03 23:35:20 INFO rasa.core.processor - Loading model models/20221003-233504-energetic-palace.tar.gz... 2022-10-03 23:35:33 INFO root - Rasa server is up and running. Processed story blocks: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 1607.63it/s, # trackers=1] Processed rules: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2113.53it/s, # trackers=1] Bot loaded. Visualisation at http://localhost:5006/visualization.html . Type a message and press enter (press 'Ctrl-c' to exit). ? Your input -> hi ? Your NLU model classified 'hi' with intent 'greet' and there are no entities, is this correct? Yes ------ Chat History # Bot You ──────────────────────────────────────────── 1 action_listen ──────────────────────────────────────────── 2 hi intent: greet 1.00 ------ Current slots: session_started_metadata: None ? The bot wants to run 'action_default_fallback', correct? (Y/n) Cancelled by user ? Do you want to stop? (Use arrow keys) Cancelled by user ? Export stories to (if file exists, this will append the stories) data/stories.yml Cancelled by user 2022-10-03 23:36:09 INFO rasa.core.training.interactive - Killing Sanic server now.Erroneous Logs (Part 2)
? Your input -> hi ? Your NLU model classified 'hi' with intent 'greet' and there are no entities, is this correct? Yes ------ Chat History # Bot You ──────────────────────────────────────────── 1 action_listen ──────────────────────────────────────────── 2 hi intent: greet 1.00 Current slots: session_started_metadata: None ------ ? The bot wants to run 'action_default_fallback', correct? Yes /home/ashish/.local/lib/python3.8/site-packages/rasa/server.py:860: FutureWarning: The "POST /conversations/<conversation_id>/execute" endpoint is deprecated. Inserting actions to the tracker externally should be avoided. Actions should be predicted by the policies only. rasa.shared.utils.io.raise_warning( ------ Chat History # Bot You ──────────────────────────────────── 1 action_listen ------ Current slots: session_started_metadata: None ? The bot wants to run 'action_default_fallback', correct? Yes ------ Chat History ------ # Bot You ──────────────────────────────────── 1 action_listen Current slots: session_started_metadata: None ? The bot wants to run 'action_default_fallback', correct? Yes ------What is this "action_default_fallback"?
The answer comes from Rasa Documentation:Policy Priority
In the case that two policies predict with equal confidence (for example, the Memoization and Rule Policies might both predict with confidence 1), the priority of the policies is considered. Rasa Open Source policies have default priorities that are set to ensure the expected outcome in the case of a tie. They look like this, where higher numbers have higher priority: 6 - RulePolicy 3 - MemoizationPolicy or AugmentedMemoizationPolicy 2 - UnexpecTEDIntentPolicy 1 - TEDPolicyRule Policy
The RulePolicy is a policy that handles conversation parts that follow a fixed behavior (e.g. business logic). It makes predictions based on any rules you have in your training data. See the Rules documentation for further information on how to define rules. The RulePolicy has the following configuration options: File: config.yml policies: - name: "RulePolicy" core_fallback_threshold: 0.3 core_fallback_action_name: action_default_fallback enable_fallback_prediction: true restrict_rules: true check_for_contradictions: true The values shown above are the default settings. Ref: https://rasa.com/docs/rasa/policies
Showing posts with label Rasa. Show all posts
Showing posts with label Rasa. Show all posts
Monday, October 3, 2022
The RulePolicy of Rasa (Oct 2022)
Monday, September 19, 2022
Installing Rasa 3.2.8 on Ubuntu using Conda
Contents of env.yml
name: rasa_py38 channels: - conda-forge dependencies: - python=3.8 - pip - spacy (base) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ conda env create -f env.yml Collecting package metadata (repodata.json): done Solving environment: done ==> WARNING: A newer version of conda exists. <== current version: 4.12.0 latest version: 4.14.0 Please update conda by running $ conda update -n base -c defaults conda Downloading and Extracting Packages libsqlite-3.39.3 | 789 KB | ### | 100% numpy-1.23.3 | 7.1 MB | ### | 100% dataclasses-0.8 | 10 KB | ### | 100% pathy-0.6.2 | 38 KB | ### | 100% srsly-2.4.4 | 540 KB | ### | 100% sqlite-3.39.3 | 789 KB | ### | 100% python-3.8.13 | 25.1 MB | ### | 100% markupsafe-2.1.1 | 22 KB | ### | 100% spacy-loggers-1.0.3 | 13 KB | ### | 100% cython-blis-0.7.8 | 9.0 MB | ### | 100% cymem-2.0.6 | 42 KB | ### | 100% cffi-1.15.1 | 229 KB | ### | 100% click-8.1.3 | 146 KB | ### | 100% langcodes-3.3.0 | 156 KB | ### | 100% cryptography-37.0.4 | 1.5 MB | ### | 100% tqdm-4.64.1 | 82 KB | ### | 100% shellingham-1.5.0 | 12 KB | ### | 100% brotlipy-0.7.0 | 342 KB | ### | 100% spacy-3.4.1 | 6.4 MB | ### | 100% preshed-3.0.7 | 122 KB | ### | 100% wasabi-0.10.0 | 26 KB | ### | 100% python_abi-3.8 | 4 KB | ### | 100% libzlib-1.2.12 | 65 KB | ### | 100% smart_open-5.2.1 | 43 KB | ### | 100% thinc-8.1.0 | 904 KB | ### | 100% typer-0.4.2 | 45 KB | ### | 100% pydantic-1.9.2 | 2.4 MB | ### | 100% spacy-legacy-3.0.10 | 20 KB | ### | 100% catalogue-2.0.8 | 32 KB | ### | 100% murmurhash-1.0.8 | 27 KB | ### | 100% libopenblas-0.3.21 | 10.1 MB | ### | 100% Preparing transaction: done Verifying transaction: done Executing transaction: done # # To activate this environment, use # # $ conda activate rasa_py38 # # To deactivate an active environment, use # # $ conda deactivate (base) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ (base) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ conda activate rasa_py38 (rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ conda install ipykernel jupyterlab -c conda-forge Collecting package metadata (current_repodata.json): done Solving environment: done ==> WARNING: A newer version of conda exists. <== current version: 4.12.0 latest version: 4.14.0 Please update conda by running $ conda update -n base -c defaults conda ## Package Plan ## environment location: /home/ashish/anaconda3/envs/rasa_py38 added / updated specs: - ipykernel - jupyterlab The following packages will be downloaded: package | build ---------------------------|----------------- argon2-cffi-bindings-21.2.0| py38h0a891b7_2 34 KB conda-forge debugpy-1.6.3 | py38hfa26641_0 2.0 MB conda-forge importlib-metadata-4.11.4 | py38h578d9bd_0 33 KB conda-forge ipykernel-6.15.3 | pyh210e3f2_0 99 KB conda-forge ipython-8.5.0 | pyh41d4057_1 552 KB conda-forge jsonschema-4.16.0 | pyhd8ed1ab_0 65 KB conda-forge jupyter_core-4.11.1 | py38h578d9bd_0 81 KB conda-forge jupyterlab-3.4.7 | pyhd8ed1ab_0 5.9 MB conda-forge lxml-4.9.1 | py38h0a891b7_0 1.4 MB conda-forge nbclient-0.6.8 | pyhd8ed1ab_0 65 KB conda-forge nbformat-5.5.0 | pyhd8ed1ab_0 105 KB conda-forge prompt-toolkit-3.0.31 | pyha770c72_0 254 KB conda-forge psutil-5.9.2 | py38h0a891b7_0 346 KB conda-forge pyrsistent-0.18.1 | py38h0a891b7_1 92 KB conda-forge pyzmq-24.0.0 | py38hfc09fa9_0 499 KB conda-forge terminado-0.15.0 | py38h578d9bd_0 28 KB conda-forge tomli-2.0.1 | pyhd8ed1ab_0 16 KB conda-forge tornado-6.2 | py38h0a891b7_0 653 KB conda-forge traitlets-5.4.0 | pyhd8ed1ab_0 85 KB conda-forge ------------------------------------------------------------ Total: 12.3 MB The following NEW packages will be INSTALLED: anyio conda-forge/noarch::anyio-3.6.1-pyhd8ed1ab_1 argon2-cffi conda-forge/noarch::argon2-cffi-21.3.0-pyhd8ed1ab_0 argon2-cffi-bindi~ conda-forge/linux-64::argon2-cffi-bindings-21.2.0-py38h0a891b7_2 asttokens conda-forge/noarch::asttokens-2.0.8-pyhd8ed1ab_0 attrs conda-forge/noarch::attrs-22.1.0-pyh71513ae_1 babel conda-forge/noarch::babel-2.10.3-pyhd8ed1ab_0 backcall conda-forge/noarch::backcall-0.2.0-pyh9f0ad1d_0 backports conda-forge/noarch::backports-1.0-py_2 backports.functoo~ conda-forge/noarch::backports.functools_lru_cache-1.6.4-pyhd8ed1ab_0 beautifulsoup4 conda-forge/noarch::beautifulsoup4-4.11.1-pyha770c72_0 bleach conda-forge/noarch::bleach-5.0.1-pyhd8ed1ab_0 debugpy conda-forge/linux-64::debugpy-1.6.3-py38hfa26641_0 decorator conda-forge/noarch::decorator-5.1.1-pyhd8ed1ab_0 defusedxml conda-forge/noarch::defusedxml-0.7.1-pyhd8ed1ab_0 entrypoints conda-forge/noarch::entrypoints-0.4-pyhd8ed1ab_0 executing conda-forge/noarch::executing-1.0.0-pyhd8ed1ab_0 flit-core conda-forge/noarch::flit-core-3.7.1-pyhd8ed1ab_0 icu conda-forge/linux-64::icu-70.1-h27087fc_0 importlib-metadata conda-forge/linux-64::importlib-metadata-4.11.4-py38h578d9bd_0 importlib_metadata conda-forge/noarch::importlib_metadata-4.11.4-hd8ed1ab_0 importlib_resourc~ conda-forge/noarch::importlib_resources-5.9.0-pyhd8ed1ab_0 ipykernel conda-forge/noarch::ipykernel-6.15.3-pyh210e3f2_0 ipython conda-forge/noarch::ipython-8.5.0-pyh41d4057_1 ipython_genutils conda-forge/noarch::ipython_genutils-0.2.0-py_1 jedi conda-forge/noarch::jedi-0.18.1-pyhd8ed1ab_2 json5 conda-forge/noarch::json5-0.9.5-pyh9f0ad1d_0 jsonschema conda-forge/noarch::jsonschema-4.16.0-pyhd8ed1ab_0 jupyter_client conda-forge/noarch::jupyter_client-7.3.5-pyhd8ed1ab_0 jupyter_core conda-forge/linux-64::jupyter_core-4.11.1-py38h578d9bd_0 jupyter_server conda-forge/noarch::jupyter_server-1.18.1-pyhd8ed1ab_0 jupyterlab conda-forge/noarch::jupyterlab-3.4.7-pyhd8ed1ab_0 jupyterlab_pygmen~ conda-forge/noarch::jupyterlab_pygments-0.2.2-pyhd8ed1ab_0 jupyterlab_server conda-forge/noarch::jupyterlab_server-2.15.1-pyhd8ed1ab_0 libiconv conda-forge/linux-64::libiconv-1.16-h516909a_0 libsodium conda-forge/linux-64::libsodium-1.0.18-h36c2ea0_1 libxml2 conda-forge/linux-64::libxml2-2.9.14-h22db469_4 libxslt conda-forge/linux-64::libxslt-1.1.35-h8affb1d_0 lxml conda-forge/linux-64::lxml-4.9.1-py38h0a891b7_0 matplotlib-inline conda-forge/noarch::matplotlib-inline-0.1.6-pyhd8ed1ab_0 mistune conda-forge/noarch::mistune-2.0.4-pyhd8ed1ab_0 nbclassic conda-forge/noarch::nbclassic-0.4.3-pyhd8ed1ab_0 nbclient conda-forge/noarch::nbclient-0.6.8-pyhd8ed1ab_0 nbconvert conda-forge/noarch::nbconvert-7.0.0-pyhd8ed1ab_0 nbconvert-core conda-forge/noarch::nbconvert-core-7.0.0-pyhd8ed1ab_0 nbconvert-pandoc conda-forge/noarch::nbconvert-pandoc-7.0.0-pyhd8ed1ab_0 nbformat conda-forge/noarch::nbformat-5.5.0-pyhd8ed1ab_0 nest-asyncio conda-forge/noarch::nest-asyncio-1.5.5-pyhd8ed1ab_0 notebook conda-forge/noarch::notebook-6.4.12-pyha770c72_0 notebook-shim conda-forge/noarch::notebook-shim-0.1.0-pyhd8ed1ab_0 pandoc conda-forge/linux-64::pandoc-2.19.2-ha770c72_0 pandocfilters conda-forge/noarch::pandocfilters-1.5.0-pyhd8ed1ab_0 parso conda-forge/noarch::parso-0.8.3-pyhd8ed1ab_0 pexpect conda-forge/noarch::pexpect-4.8.0-pyh9f0ad1d_2 pickleshare conda-forge/noarch::pickleshare-0.7.5-py_1003 pkgutil-resolve-n~ conda-forge/noarch::pkgutil-resolve-name-1.3.10-pyhd8ed1ab_0 prometheus_client conda-forge/noarch::prometheus_client-0.14.1-pyhd8ed1ab_0 prompt-toolkit conda-forge/noarch::prompt-toolkit-3.0.31-pyha770c72_0 psutil conda-forge/linux-64::psutil-5.9.2-py38h0a891b7_0 ptyprocess conda-forge/noarch::ptyprocess-0.7.0-pyhd3deb0d_0 pure_eval conda-forge/noarch::pure_eval-0.2.2-pyhd8ed1ab_0 pygments conda-forge/noarch::pygments-2.13.0-pyhd8ed1ab_0 pyrsistent conda-forge/linux-64::pyrsistent-0.18.1-py38h0a891b7_1 python-dateutil conda-forge/noarch::python-dateutil-2.8.2-pyhd8ed1ab_0 python-fastjsonsc~ conda-forge/noarch::python-fastjsonschema-2.16.1-pyhd8ed1ab_0 pytz conda-forge/noarch::pytz-2022.2.1-pyhd8ed1ab_0 pyzmq conda-forge/linux-64::pyzmq-24.0.0-py38hfc09fa9_0 send2trash conda-forge/noarch::send2trash-1.8.0-pyhd8ed1ab_0 six conda-forge/noarch::six-1.16.0-pyh6c4a22f_0 sniffio conda-forge/noarch::sniffio-1.3.0-pyhd8ed1ab_0 soupsieve conda-forge/noarch::soupsieve-2.3.2.post1-pyhd8ed1ab_0 stack_data conda-forge/noarch::stack_data-0.5.0-pyhd8ed1ab_0 terminado conda-forge/linux-64::terminado-0.15.0-py38h578d9bd_0 tinycss2 conda-forge/noarch::tinycss2-1.1.1-pyhd8ed1ab_0 tomli conda-forge/noarch::tomli-2.0.1-pyhd8ed1ab_0 tornado conda-forge/linux-64::tornado-6.2-py38h0a891b7_0 traitlets conda-forge/noarch::traitlets-5.4.0-pyhd8ed1ab_0 wcwidth conda-forge/noarch::wcwidth-0.2.5-pyh9f0ad1d_2 webencodings conda-forge/noarch::webencodings-0.5.1-py_1 websocket-client conda-forge/noarch::websocket-client-1.4.1-pyhd8ed1ab_0 zeromq conda-forge/linux-64::zeromq-4.3.4-h9c3ff4c_1 zipp conda-forge/noarch::zipp-3.8.1-pyhd8ed1ab_0 Proceed ([y]/n)? y Downloading and Extracting Packages traitlets-5.4.0 | 85 KB | ### | 100% nbclient-0.6.8 | 65 KB | ### | 100% ipykernel-6.15.3 | 99 KB | ### | 100% tomli-2.0.1 | 16 KB | ### | 100% ipython-8.5.0 | 552 KB | ### | 100% jsonschema-4.16.0 | 65 KB | ### | 100% jupyter_core-4.11.1 | 81 KB | ### | 100% psutil-5.9.2 | 346 KB | ### | 100% lxml-4.9.1 | 1.4 MB | ### | 100% jupyterlab-3.4.7 | 5.9 MB | ### | 100% terminado-0.15.0 | 28 KB | ### | 100% nbformat-5.5.0 | 105 KB | ### | 100% argon2-cffi-bindings | 34 KB | ### | 100% debugpy-1.6.3 | 2.0 MB | ### | 100% pyrsistent-0.18.1 | 92 KB | ### | 100% importlib-metadata-4 | 33 KB | ### | 100% pyzmq-24.0.0 | 499 KB | ### | 100% tornado-6.2 | 653 KB | ### | 100% prompt-toolkit-3.0.3 | 254 KB | ### | 100% Preparing transaction: done Verifying transaction: done Executing transaction: done (rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ (rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ python -m ipykernel install --user --name rasa_py38 Installed kernelspec rasa_py38 in /home/ashish/.local/share/jupyter/kernels/rasa_py38 (rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ pip3 install rasa --user Collecting rasa Downloading 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Stored in directory: /home/ashish/.cache/pip/wheels/27/ab/59/a3f84ec019a2a87ad812a2dc15945f763e5684aecfb059d9ec Building wheel for mattermostwrapper (setup.py) ... done Created wheel for mattermostwrapper: filename=mattermostwrapper-2.2-py3-none-any.whl size=2448 sha256=671230d2ec1c13e72ee8b2f53cd09e8a800d5db87dc166a6c2eb6ac019a89a7c Stored in directory: /home/ashish/.cache/pip/wheels/1a/d3/89/63aef88b581e7acc2c48812e6160a2bae57b6ef180f6e1f293 Building wheel for pyTelegramBotAPI (setup.py) ... done Created wheel for pyTelegramBotAPI: filename=pyTelegramBotAPI-4.7.0-py3-none-any.whl size=192810 sha256=388f48b689f2b9f8f5ab4253a9a1a0c0caba6a9869dacffe2f60077cab1a69ea Stored in directory: /home/ashish/.cache/pip/wheels/f7/29/1d/113c046ac93c2896159bb2c33673efe140b3642f21a06c4ac5 Building wheel for randomname (setup.py) ... done Created wheel for randomname: filename=randomname-0.1.5-py3-none-any.whl size=58808 sha256=b4ef46a33c316f83d0947ae923af542f7963176dffcd821789ce9af5b5d6393e Stored in directory: /home/ashish/.cache/pip/wheels/46/0a/9d/32f2d10d4fae6ddfbdeb504d949ccd70d666382a277e7c1bd5 Building wheel for twilio (setup.py) ... done Created wheel for twilio: filename=twilio-6.50.1-py2.py3-none-any.whl size=1208682 sha256=bc11ed67ebb0cd32e27e90ea4db4232206f01c9c0ed5909773b04b4b9e20391d Stored in directory: /home/ashish/.cache/pip/wheels/85/db/cc/c5c9ef20439073ba2a5403f5ce292446d3a01547007927df87 Building wheel for docopt (setup.py) ... done Created wheel for docopt: filename=docopt-0.6.2-py2.py3-none-any.whl size=13706 sha256=659b1afa51fb6f8497374a399b9e1c36a423a1fead4fa7999ccd1440917d65c2 Stored in directory: /home/ashish/.cache/pip/wheels/56/ea/58/ead137b087d9e326852a851351d1debf4ada529b6ac0ec4e8c Building wheel for fire (setup.py) ... done Created wheel for fire: filename=fire-0.4.0-py2.py3-none-any.whl size=115926 sha256=ecb49e817db0442d3d91f76c263f923d22f9c308f2fb6b2f170a80b3ceef5ac0 Stored in directory: /home/ashish/.cache/pip/wheels/1f/10/06/2a990ee4d73a8479fe2922445e8a876d38cfbfed052284c6a1 Building wheel for future (setup.py) ... done Created wheel for future: filename=future-0.18.2-py3-none-any.whl size=491058 sha256=cca1f0c0a3dfd4ada8c1534891271c9122c30f91097627fc9495f64eed6ae3d1 Stored in directory: /home/ashish/.cache/pip/wheels/8e/70/28/3d6ccd6e315f65f245da085482a2e1c7d14b90b30f239e2cf4 Successfully built aio-pika mattermostwrapper pyTelegramBotAPI randomname twilio docopt fire future Installing collected packages: typing-extensions, types-cryptography, tensorflow-estimator, tensorboard-plugin-wit, sanic-routing, pytz, python-crfsuite, pyasn1, msgpack, libclang, keras, kafka-python, flatbuffers, docopt, chardet, wrapt, werkzeug, websockets, uvloop, ujson, tzlocal, typing-utils, typeguard, toolz, threadpoolctl, terminaltables, termcolor, tensorflow-io-gcs-filesystem, tensorboard-data-server, tarsafe, tabulate, sentry-sdk, ruamel.yaml.clib, rsa, regex, redis, pyyaml, python-engineio, pymongo, PyJWT, pydot, pyasn1-modules, psycopg2-binary, protobuf, prompt-toolkit, pillow, pamqp, packaging, oauthlib, numpy, networkx, multidict, locket, kiwisolver, jsonpickle, joblib, jmespath, humanfriendly, httptools, grpcio, greenlet, google-pasta, gast, future, fsspec, dnspython, cycler, colorhash, colorclass, cloudpickle, cachetools, bidict, attrs, async-timeout, astunparse, aiofiles, absl-py, yarl, twilio, tensorflow_hub, tensorflow-addons, SQLAlchemy, sklearn-crfsuite, scipy, sanic-jwt, sanic, ruamel.yaml, rocketchat_API, requests-toolbelt, requests-oauthlib, questionary, python-socketio, pyTelegramBotAPI, partd, opt-einsum, mattermostwrapper, matplotlib, markdown, keras-preprocessing, jsonschema, h5py, google-auth, fire, fbmessenger, coloredlogs, CacheControl, botocore, apscheduler, webexteamssdk, scikit-learn, sanic-cors, s3transfer, randomname, pykwalify, google-auth-oauthlib, dask, aiormq, aiohttp, tensorboard, slackclient, rasa-sdk, boto3, aio-pika, tensorflow, tensorflow-text, rasa WARNING: The script chardetect is installed in '/home/ashish/.local/bin' which is not on PATH. 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Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. WARNING: The script jsonschema is installed in '/home/ashish/.local/bin' which is not on PATH. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. WARNING: The script coloredlogs is installed in '/home/ashish/.local/bin' which is not on PATH. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. WARNING: The script doesitcache is installed in '/home/ashish/.local/bin' which is not on PATH. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. WARNING: The script randomname is installed in '/home/ashish/.local/bin' which is not on PATH. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. WARNING: The script pykwalify is installed in '/home/ashish/.local/bin' which is not on PATH. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. WARNING: The script google-oauthlib-tool is installed in '/home/ashish/.local/bin' which is not on PATH. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. WARNING: The script tensorboard is installed in '/home/ashish/.local/bin' which is not on PATH. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. WARNING: The scripts estimator_ckpt_converter, import_pb_to_tensorboard, saved_model_cli, tensorboard, tf_upgrade_v2, tflite_convert, toco and toco_from_protos are installed in '/home/ashish/.local/bin' which is not on PATH. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. WARNING: The script rasa is installed in '/home/ashish/.local/bin' which is not on PATH. Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location. Successfully installed CacheControl-0.12.11 PyJWT-2.5.0 SQLAlchemy-1.4.41 absl-py-0.13.0 aio-pika-8.2.1 aiofiles-22.1.0 aiohttp-3.7.4 aiormq-6.4.2 apscheduler-3.7.0 astunparse-1.6.3 async-timeout-3.0.1 attrs-21.2.0 bidict-0.22.0 boto3-1.24.75 botocore-1.27.75 cachetools-4.2.4 chardet-3.0.4 cloudpickle-1.6.0 colorclass-2.2.2 coloredlogs-15.0.1 colorhash-1.0.4 cycler-0.11.0 dask-2022.2.0 dnspython-1.16.0 docopt-0.6.2 fbmessenger-6.0.0 fire-0.4.0 flatbuffers-2.0.7 fsspec-2022.8.2 future-0.18.2 gast-0.4.0 google-auth-1.35.0 google-auth-oauthlib-0.4.6 google-pasta-0.2.0 greenlet-1.1.3 grpcio-1.49.0 h5py-3.7.0 httptools-0.5.0 humanfriendly-10.0 jmespath-1.0.1 joblib-1.0.1 jsonpickle-2.0.0 jsonschema-4.4.0 kafka-python-2.0.2 keras-2.7.0 keras-preprocessing-1.1.2 kiwisolver-1.4.4 libclang-14.0.6 locket-1.0.0 markdown-3.4.1 matplotlib-3.3.4 mattermostwrapper-2.2 msgpack-1.0.4 multidict-5.2.0 networkx-2.6.3 numpy-1.19.5 oauthlib-3.2.1 opt-einsum-3.3.0 packaging-20.9 pamqp-3.2.1 partd-1.3.0 pillow-9.2.0 prompt-toolkit-3.0.28 protobuf-3.19.5 psycopg2-binary-2.9.3 pyTelegramBotAPI-4.7.0 pyasn1-0.4.8 pyasn1-modules-0.2.8 pydot-1.4.2 pykwalify-1.8.0 pymongo-3.10.1 python-crfsuite-0.9.8 python-engineio-4.3.4 python-socketio-5.7.1 pytz-2021.3 pyyaml-6.0 questionary-1.10.0 randomname-0.1.5 rasa-3.2.8 rasa-sdk-3.2.1 redis-3.5.3 regex-2022.4.24 requests-oauthlib-1.3.1 requests-toolbelt-0.9.1 rocketchat_API-1.25.0 rsa-4.9 ruamel.yaml-0.16.13 ruamel.yaml.clib-0.2.6 s3transfer-0.6.0 sanic-21.12.2 sanic-cors-2.0.1 sanic-jwt-1.8.0 sanic-routing-0.7.2 scikit-learn-0.24.2 scipy-1.7.3 sentry-sdk-1.3.1 sklearn-crfsuite-0.3.6 slackclient-2.9.4 tabulate-0.8.10 tarsafe-0.0.3 tensorboard-2.10.0 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.1 tensorflow-2.7.4 tensorflow-addons-0.15.0 tensorflow-estimator-2.7.0 tensorflow-io-gcs-filesystem-0.27.0 tensorflow-text-2.7.3 tensorflow_hub-0.12.0 termcolor-2.0.1 terminaltables-3.1.10 threadpoolctl-3.1.0 toolz-0.12.0 twilio-6.50.1 typeguard-2.13.3 types-cryptography-3.3.23 typing-extensions-3.10.0.2 typing-utils-0.1.0 tzlocal-2.1 ujson-5.5.0 uvloop-0.17.0 webexteamssdk-1.6.1 websockets-10.3 werkzeug-2.2.2 wrapt-1.14.1 yarl-1.8.1 (rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ (rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ pip show rasa Name: rasa Version: 3.2.8 Summary: Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants Home-page: https://rasa.com Author: Rasa Technologies GmbH Author-email: hi@rasa.com License: Apache-2.0 Location: /home/ashish/.local/lib/python3.8/site-packages Requires: absl-py, aio-pika, aiohttp, apscheduler, attrs, boto3, CacheControl, cloudpickle, colorclass, coloredlogs, colorhash, dask, fbmessenger, google-auth, joblib, jsonpickle, jsonschema, kafka-python, matplotlib, mattermostwrapper, networkx, numpy, packaging, prompt-toolkit, psycopg2-binary, pydot, PyJWT, pykwalify, pymongo, pyTelegramBotAPI, python-dateutil, python-engineio, python-socketio, pytz, questionary, randomname, rasa-sdk, redis, regex, requests, rocketchat_API, ruamel.yaml, sanic, sanic-cors, sanic-jwt, sanic-routing, scikit-learn, scipy, sentry-sdk, setuptools, sklearn-crfsuite, slackclient, SQLAlchemy, tarsafe, tensorflow, tensorflow-addons, tensorflow-text, tensorflow_hub, terminaltables, tqdm, twilio, typing-extensions, typing-utils, ujson, webexteamssdk Required-by:Fix the PATH variable to enable RASA CLI
(rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ rasa rasa: command not found (rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ (rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ sudo nano ~/.bashrc [sudo] password for ashish: (rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ (rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ (rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ source ~/.bashrc (base) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ conda activate rasa_py38 (rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ rasa usage: rasa [-h] [--version] {init,run,shell,train,interactive,telemetry,test,visualize,data,export,x,evaluate} ... Rasa command line interface. Rasa allows you to build your own conversational assistants 🤖. The 'rasa' command allows you to easily run most common commands like creating a new bot, training or evaluating models. positional arguments: {init,run,shell,train,interactive,telemetry,test,visualize,data,export,x,evaluate} Rasa commands init Creates a new project, with example training data, actions, and config files. run Starts a Rasa server with your trained model. shell Loads your trained model and lets you talk to your assistant on the command line. train Trains a Rasa model using your NLU data and stories. interactive Starts an interactive learning session to create new training data for a Rasa model by chatting. telemetry Configuration of Rasa Open Source telemetry reporting. test Tests Rasa models using your test NLU data and stories. visualize Visualize stories. data Utils for the Rasa training files. export Export conversations using an event broker. evaluate Tools for evaluating models. optional arguments: -h, --help show this help message and exit --version Print installed Rasa versionThe Fix of PATH Variable
(rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$ echo $PATH /home/ashish/.local/bin:/home/ashish/anaconda3/envs/rasa_py38/bin:/home/ashish/anaconda3/condabin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/snap/bin (rasa_py38) ashish@ashish-Lenovo-ideapad-130-15IKB:~/Desktop$
Tuesday, March 30, 2021
Issues in RASA CLI installation in Conda Env using YML file (and workarounds) (less logs)
We do not have "rasa" available in "conda-forge" channel:
(erasa4) CMD>conda install rasa -c conda-forge
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
PackagesNotFoundError: The following packages are not available from current channels:
- rasa
Current channels:
- https://conda.anaconda.org/conda-forge/win-64
- https://conda.anaconda.org/conda-forge/noarch
- https://repo.anaconda.com/pkgs/main/win-64
- https://repo.anaconda.com/pkgs/main/noarch
- https://repo.anaconda.com/pkgs/r/win-64
- https://repo.anaconda.com/pkgs/r/noarch
- https://repo.anaconda.com/pkgs/msys2/win-64
- https://repo.anaconda.com/pkgs/msys2/noarch
To search for alternate channels that may provide the conda package you're
looking for, navigate to
https://anaconda.org
and use the search bar at the top of the page.
-- -- -- -- --
ERRONEOUS CODE in FILE "env.yml"
name: erasa5
channels:
- conda-forge
dependencies:
- spacy
- python=3.8
- pip
- pip:
- rasa
- rasa-core
ERROR:
/ Pip subprocess error:
WARNING: Retrying (Retry(total=4, connect=None, read=None, redirect=None, status=None)) after connection broken by 'ProtocolError('Connection aborted.', ConnectionResetError(10054, 'An existing connection was forcibly closed by the remote host', None, 10054, None))': /simple/joblib/
ERROR: Could not install packages due to an OSError: [WinError 5] Access is denied: 'e:\\anaconda3\\envs\\erasa5\\scripts\\tqdm.exe'
Consider using the `--user` option or check the permissions.
failed
CondaEnvException: Pip failed
Complete Logs
(base) CMD>conda env create -f env.yml
Collecting package metadata (repodata.json): done
Solving environment: done
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
Installing pip dependencies: / Ran pip subprocess with arguments:
['e:\\Anaconda3\\envs\\erasa5\\python.exe', '-m', 'pip', 'install', '-U', '-r', 'C:\\Users\\ashish\\Desktop\\condaenv.170xtvti.requirements.txt']
Pip subprocess output:
...
Installing collected packages: sniffio, ..., rasa-core, rasa
Attempting uninstall: attrs
Found existing installation: attrs 20.3.0
Uninstalling attrs-20.3.0:
Successfully uninstalled attrs-20.3.0
Attempting uninstall: multidict
Found existing installation: multidict 5.1.0
Uninstalling multidict-5.1.0:
Successfully uninstalled multidict-5.1.0
Attempting uninstall: pytz
Found existing installation: pytz 2021.1
Uninstalling pytz-2021.1:
Successfully uninstalled pytz-2021.1
Attempting uninstall: numpy
Found existing installation: numpy 1.20.0
Uninstalling numpy-1.20.0:
Successfully uninstalled numpy-1.20.0
Attempting uninstall: tqdm
Found existing installation: tqdm 4.56.0
Uninstalling tqdm-4.56.0:
Pip subprocess error:
ERROR: Could not install packages due to an OSError: [WinError 5] Access is denied: 'e:\\anaconda3\\envs\\erasa5\\scripts\\tqdm.exe'
Consider using the `--user` option or check the permissions.
failed
CondaEnvException: Pip failed
(base) CMD>
-- -- -- -- --
We have a separate environment where we installed 'RASA_CORE' and 'RASA_NLU' separately, and here also we see that 'RASA' PYPI package (for RASA CLI) is failing to install.
ENV.YML for erasa4:
name: erasa4
channels:
- conda-forge
dependencies:
- spacy
- python=3.8
- pip
- pip:
- rasa-core
(base) CMD>conda activate erasa4
Issues:
(erasa4) CMD>pip show rasa_core
Name: rasa-core
Version: 0.8.6
Summary: Machine learning based dialogue engine for conversational software.
Home-page: https://rasa.ai
Author: Rasa Technologies GmbH
Author-email: hi@rasa.ai
License: UNKNOWN
Location: e:\anaconda3\envs\erasa4\lib\site-packages
Requires: pandoc, ..., tqdm
Required-by:
(erasa4) CMD>pip show rasa_nlu
Name: rasa-nlu
Version: 0.11.5
Summary: Rasa NLU a natural language parser for bots
Home-page: https://rasa.com
Author: Alan Nichol
Author-email: alan@rasa.ai
License: UNKNOWN
Location: e:\anaconda3\envs\erasa4\lib\site-packages
Requires: future, numpy, simplejson, jsonschema, requests, cloudpickle, matplotlib, pathlib, klein, boto3, gevent, six, typing, tqdm
Required-by: rasa-core
(erasa4) CMD>pip show rasa
WARNING: Package(s) not found: rasa
-- -- -- -- --
ERROR
(erasa4) CMD>rasa
'rasa' is not recognized as an internal or external command, operable program or batch file.
(erasa4) CMD>rasa init
'rasa' is not recognized as an internal or external command, operable program or batch file.
RASA fails to install for all users.
(erasa4) CMD>pip3 install rasa
Collecting rasa
Using cached rasa-2.2.9-py3-none-any.whl (689 kB)
...
Installing collected packages: sniffio, ..., rasa
Attempting uninstall: multidict
Found existing installation: multidict 5.1.0
Uninstalling multidict-5.1.0:
Successfully uninstalled multidict-5.1.0
Attempting uninstall: yarl
Found existing installation: yarl 1.6.3
Uninstalling yarl-1.6.3:
Successfully uninstalled yarl-1.6.3
Attempting uninstall: numpy
Found existing installation: numpy 1.19.5
Uninstalling numpy-1.19.5:
Successfully uninstalled numpy-1.19.5
Attempting uninstall: attrs
Found existing installation: attrs 20.3.0
Uninstalling attrs-20.3.0:
Successfully uninstalled attrs-20.3.0
Attempting uninstall: absl-py
Found existing installation: absl-py 0.11.0
Uninstalling absl-py-0.11.0:
Successfully uninstalled absl-py-0.11.0
Attempting uninstall: tqdm
Found existing installation: tqdm 4.56.0
Uninstalling tqdm-4.56.0:
ERROR: Could not install packages due to an OSError: [WinError 5] Access is denied: 'e:\\anaconda3\\envs\\erasa4\\scripts\\tqdm.exe'
Consider using the `--user` option or check the permissions.
(erasa4) CMD>
-- -- -- -- --
To install RASA CLI (and overcome the installation issue in "erasa4" environment) we have to open the terminal and run the "pip3 install rasa --user" command there:
(erasa4) CMD>pip3 install rasa --user
Collecting rasa
Using cached rasa-2.2.9-py3-none-any.whl (689 kB)
...
Installing collected packages: tqdm, ..., rasa
WARNING: The script tqdm.exe is installed in 'C:\Users\ashish\AppData\Roaming\Python\Python38\Scripts' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
WARNING: The script tabulate.exe is installed in 'C:\Users\ashish\AppData\Roaming\Python\Python38\Scripts' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
WARNING: The script coloredlogs.exe is installed in 'C:\Users\ashish\AppData\Roaming\Python\Python38\Scripts' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
WARNING: The scripts make_image_classifier.exe and make_nearest_neighbour_index.exe are installed in 'C:\Users\ashish\AppData\Roaming\Python\Python38\Scripts' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
WARNING: The scripts estimator_ckpt_converter.exe, saved_model_cli.exe, tensorboard.exe, tf_upgrade_v2.exe, tflite_convert.exe, toco.exe and toco_from_protos.exe are installed in 'C:\Users\ashish\AppData\Roaming\Python\Python38\Scripts' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
WARNING: The script pykwalify.exe is installed in 'C:\Users\ashish\AppData\Roaming\Python\Python38\Scripts' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
WARNING: The script rasa.exe is installed in 'C:\Users\ashish\AppData\Roaming\Python\Python38\Scripts' which is not on PATH.
Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
rasa-core 0.8.6 requires fbmessenger<5.0.0, but you have fbmessenger 6.0.0 which is incompatible.
rasa-core 0.8.6 requires pykwalify<=1.6.0, but you have pykwalify 1.7.0 which is incompatible.
Successfully installed PyJWT-2.0.1 SQLAlchemy-1.3.23 aio-pika-6.7.1 aiohttp-3.6.3 ... webexteamssdk-1.6
(erasa4) CMD>
(erasa4) CMD>pip show rasa
Name: rasa
Version: 2.2.9
Summary: Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
Home-page: https://rasa.com
Author: Rasa Technologies GmbH
Author-email: hi@rasa.com
License: Apache-2.0
Location: c:\users\ashish\appdata\roaming\python\python38\site-packages
Requires: pykwalify, ..., tensorflow-probability
Required-by:
-- -- -- -- --
(erasa4) CMD>rasa
2021-02-03 14:50:58.305729: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
2021-02-03 14:50:58.313121: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
usage: rasa [-h] [--version] {init,run,shell,train,interactive,telemetry,test,visualize,data,export,x} ...
Rasa command line interface. Rasa allows you to build your own conversational assistants 🤖. The 'rasa' command allows you to easily run most common commands like creating a new bot, training or evaluating models.
positional arguments:
{init,run,shell,train,interactive,telemetry,test,visualize,data,export,x}
Rasa commands
init Creates a new project, with example training data, actions, and config files.
run Starts a Rasa server with your trained model.
shell Loads your trained model and lets you talk to your assistant on the command line.
train Trains a Rasa model using your NLU data and stories.
interactive Starts an interactive learning session to create new training data for a Rasa model by chatting.
telemetry Configuration of Rasa Open Source telemetry reporting.
test Tests Rasa models using your test NLU data and stories.
visualize Visualize stories.
data Utils for the Rasa training files.
export Export conversations using an event broker.
optional arguments:
-h, --help show this help message and exit
--version Print installed Rasa version
(erasa4) CMD>
-- -- -- -- --
ALSO, WE SHARE BELOW THE LOGS WHILE DOING INSTALLATION FROM TERMINAL WITHOUT USING YML FILE
(base) CMD>conda create -n temp_rasa python=3.8
Collecting package metadata (current_repodata.json): done
Solving environment: done
## Package Plan ##
environment location: e:\Anaconda3\envs\temp_rasa
added / updated specs:
- python=3.8
The following packages will be downloaded:
package | build
---------------------------|-----------------
certifi-2020.12.5 | py38haa95532_0 141 KB
pip-20.3.3 | py38haa95532_0 1.8 MB
setuptools-52.0.0 | py38haa95532_0 726 KB
------------------------------------------------------------
Total: 2.6 MB
The following NEW packages will be INSTALLED:
ca-certificates pkgs/main/win-64::ca-certificates-2021.1.19-haa95532_0
certifi pkgs/main/win-64::certifi-2020.12.5-py38haa95532_0
openssl pkgs/main/win-64::openssl-1.1.1i-h2bbff1b_0
pip pkgs/main/win-64::pip-20.3.3-py38haa95532_0
python pkgs/main/win-64::python-3.8.5-h5fd99cc_1
setuptools pkgs/main/win-64::setuptools-52.0.0-py38haa95532_0
sqlite pkgs/main/win-64::sqlite-3.33.0-h2a8f88b_0
vc pkgs/main/win-64::vc-14.2-h21ff451_1
vs2015_runtime pkgs/main/win-64::vs2015_runtime-14.27.29016-h5e58377_2
wheel pkgs/main/noarch::wheel-0.36.2-pyhd3eb1b0_0
wincertstore pkgs/main/win-64::wincertstore-0.2-py38_0
zlib pkgs/main/win-64::zlib-1.2.11-h62dcd97_4
Proceed ([y]/n)? y
Downloading and Extracting Packages
certifi-2020.12.5 | 141 KB | ### | 100%
setuptools-52.0.0 | 726 KB | ### | 100%
pip-20.3.3 | 1.8 MB | ### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use
#
# $ conda activate temp_rasa
#
# To deactivate an active environment, use
#
# $ conda deactivate
(temp_rasa) CMD>pip install rasa
Requirement already satisfied: rasa in c:\users\ashish\appdata\roaming\python\python38\site-packages (2.2.9)
...
Installing collected packages: sniffio, ..., apscheduler
Successfully installed PyYAML-5.4.1 absl-py-0.10.0 aiofiles-0.6.0 ... yarl-1.5.1
(temp_rasa) CMD>
(temp_rasa) CMD>pip show rasa
Name: rasa
Version: 2.2.9
Summary: Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
Home-page: https://rasa.com
Author: Rasa Technologies GmbH
Author-email: hi@rasa.com
License: Apache-2.0
Location: c:\users\ashish\appdata\roaming\python\python38\site-packages
Requires: sanic-cors, ..., colorhash
Required-by:
(temp_rasa) CMD>rasa
2021-02-03 15:19:23.023468: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
2021-02-03 15:19:23.030147: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
usage: rasa [-h] [--version] {init,run,shell,train,interactive,telemetry,test,visualize,data,export,x} ...
Rasa command line interface. Rasa allows you to build your own conversational assistants 🤖. The 'rasa' command allows you to easily run most common commands like creating a new bot, training or evaluating models.
positional arguments:
{init,run,shell,train,interactive,telemetry,test,visualize,data,export,x}
Rasa commands
init Creates a new project, with example training data, actions, and config files.
run Starts a Rasa server with your trained model.
shell Loads your trained model and lets you talk to your assistant on the command line.
train Trains a Rasa model using your NLU data and stories.
interactive Starts an interactive learning session to create new training data for a Rasa model by chatting.
telemetry Configuration of Rasa Open Source telemetry reporting.
test Tests Rasa models using your test NLU data and stories.
visualize Visualize stories.
data Utils for the Rasa training files.
export Export conversations using an event broker.
optional arguments:
-h, --help show this help message and exit
--version Print installed Rasa version
(temp_rasa) CMD>
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