diff --git a/.github/workflows/ghcr_deploy.yml b/.github/workflows/ghcr_deploy.yml index 58cda02c31b..4045056e3a2 100644 --- a/.github/workflows/ghcr_deploy.yml +++ b/.github/workflows/ghcr_deploy.yml @@ -25,6 +25,11 @@ jobs: if: github.repository == 'BerriAI/litellm' runs-on: ubuntu-latest steps: + - + name: Checkout + uses: actions/checkout@v4 + with: + ref: ${{ github.event.inputs.commit_hash }} - name: Set up QEMU uses: docker/setup-qemu-action@v3 @@ -41,12 +46,14 @@ jobs: name: Build and push uses: docker/build-push-action@v5 with: + context: . push: true tags: litellm/litellm:${{ github.event.inputs.tag || 'latest' }} - name: Build and push litellm-database image uses: docker/build-push-action@v5 with: + context: . push: true file: Dockerfile.database tags: litellm/litellm-database:${{ github.event.inputs.tag || 'latest' }} @@ -54,6 +61,7 @@ jobs: name: Build and push litellm-spend-logs image uses: docker/build-push-action@v5 with: + context: . push: true file: ./litellm-js/spend-logs/Dockerfile tags: litellm/litellm-spend_logs:${{ github.event.inputs.tag || 'latest' }} @@ -68,6 +76,8 @@ jobs: steps: - name: Checkout repository uses: actions/checkout@v4 + with: + ref: ${{ github.event.inputs.commit_hash }} # Uses the `docker/login-action` action to log in to the Container registry registry using the account and password that will publish the packages. Once published, the packages are scoped to the account defined here. - name: Log in to the Container registry uses: docker/login-action@65b78e6e13532edd9afa3aa52ac7964289d1a9c1 @@ -92,7 +102,7 @@ jobs: - name: Build and push Docker image uses: docker/build-push-action@4976231911ebf5f32aad765192d35f942aa48cb8 with: - context: https://github.com/BerriAI/litellm.git#${{ github.event.inputs.commit_hash}} + context: . push: true tags: ${{ steps.meta.outputs.tags }}-${{ github.event.inputs.tag || 'latest' }}, ${{ steps.meta.outputs.tags }}-${{ github.event.inputs.release_type }} # if a tag is provided, use that, otherwise use the release tag, and if neither is available, use 'latest' labels: ${{ steps.meta.outputs.labels }} @@ -106,6 +116,8 @@ jobs: steps: - name: Checkout repository uses: actions/checkout@v4 + with: + ref: ${{ github.event.inputs.commit_hash }} - name: Log in to the Container registry uses: docker/login-action@65b78e6e13532edd9afa3aa52ac7964289d1a9c1 @@ -128,7 +140,7 @@ jobs: - name: Build and push Database Docker image uses: docker/build-push-action@f2a1d5e99d037542a71f64918e516c093c6f3fc4 with: - context: https://github.com/BerriAI/litellm.git#${{ github.event.inputs.commit_hash}} + context: . file: Dockerfile.database push: true tags: ${{ steps.meta-database.outputs.tags }}-${{ github.event.inputs.tag || 'latest' }}, ${{ steps.meta-database.outputs.tags }}-${{ github.event.inputs.release_type }} @@ -143,6 +155,8 @@ jobs: steps: - name: Checkout repository uses: actions/checkout@v4 + with: + ref: ${{ github.event.inputs.commit_hash }} - name: Log in to the Container registry uses: docker/login-action@65b78e6e13532edd9afa3aa52ac7964289d1a9c1 @@ -165,7 +179,7 @@ jobs: - name: Build and push Database Docker image uses: docker/build-push-action@f2a1d5e99d037542a71f64918e516c093c6f3fc4 with: - context: https://github.com/BerriAI/litellm.git#${{ github.event.inputs.commit_hash}} + context: . file: ./litellm-js/spend-logs/Dockerfile push: true tags: ${{ steps.meta-spend-logs.outputs.tags }}-${{ github.event.inputs.tag || 'latest' }}, ${{ steps.meta-spend-logs.outputs.tags }}-${{ github.event.inputs.release_type }} @@ -176,6 +190,8 @@ jobs: steps: - name: Checkout repository uses: actions/checkout@v4 + with: + ref: ${{ github.event.inputs.commit_hash }} - name: Log in to the Container registry uses: docker/login-action@65b78e6e13532edd9afa3aa52ac7964289d1a9c1 diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index cc41d85f145..f31d0d05793 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -1,4 +1,19 @@ repos: +- repo: local + hooks: + # - id: mypy + # name: mypy + # entry: python3 -m mypy --ignore-missing-imports + # language: system + # types: [python] + # files: ^litellm/ + - id: isort + name: isort + entry: isort + language: system + types: [python] + files: litellm/.*\.py + exclude: ^litellm/__init__.py$ - repo: https://github.com/psf/black rev: 24.2.0 hooks: @@ -16,11 +31,10 @@ repos: name: Check if files match entry: python3 ci_cd/check_files_match.py language: system -- repo: local - hooks: - - id: mypy - name: mypy - entry: python3 -m mypy --ignore-missing-imports - language: system - types: [python] - files: ^litellm/ \ No newline at end of file + # - id: check-file-length + # name: Check file length + # entry: python check_file_length.py + # args: ["10000"] # set your desired maximum number of lines + # language: python + # files: litellm/.*\.py + # exclude: ^litellm/tests/ \ No newline at end of file diff --git a/check_file_length.py b/check_file_length.py new file mode 100644 index 00000000000..f23b79add25 --- /dev/null +++ b/check_file_length.py @@ -0,0 +1,28 @@ +import sys + + +def check_file_length(max_lines, filenames): + bad_files = [] + for filename in filenames: + with open(filename, "r") as file: + lines = file.readlines() + if len(lines) > max_lines: + bad_files.append((filename, len(lines))) + return bad_files + + +if __name__ == "__main__": + max_lines = int(sys.argv[1]) + filenames = sys.argv[2:] + + bad_files = check_file_length(max_lines, filenames) + if bad_files: + bad_files.sort( + key=lambda x: x[1], reverse=True + ) # Sort files by length in descending order + for filename, length in bad_files: + print(f"{filename}: {length} lines") + + sys.exit(1) + else: + sys.exit(0) diff --git a/docs/my-website/docs/completion/input.md b/docs/my-website/docs/completion/input.md index 6ad412af8f7..e9ea8f50ef9 100644 --- a/docs/my-website/docs/completion/input.md +++ b/docs/my-website/docs/completion/input.md @@ -162,7 +162,7 @@ def completion( - `function`: *object* - Required. -- `tool_choice`: *string or object (optional)* - Controls which (if any) function is called by the model. none means the model will not call a function and instead generates a message. auto means the model can pick between generating a message or calling a function. Specifying a particular function via {"type: "function", "function": {"name": "my_function"}} forces the model to call that function. +- `tool_choice`: *string or object (optional)* - Controls which (if any) function is called by the model. none means the model will not call a function and instead generates a message. auto means the model can pick between generating a message or calling a function. Specifying a particular function via `{"type: "function", "function": {"name": "my_function"}}` forces the model to call that function. - `none` is the default when no functions are present. `auto` is the default if functions are present. diff --git a/docs/my-website/docs/debugging/hosted_debugging.md b/docs/my-website/docs/debugging/hosted_debugging.md index 5c98ac6f568..e69de29bb2d 100644 --- a/docs/my-website/docs/debugging/hosted_debugging.md +++ b/docs/my-website/docs/debugging/hosted_debugging.md @@ -1,90 +0,0 @@ -import Image from '@theme/IdealImage'; -import QueryParamReader from '../../src/components/queryParamReader.js' - -# [Beta] Monitor Logs in Production - -:::note - -This is in beta. Expect frequent updates, as we improve based on your feedback. - -::: - -LiteLLM provides an integration to let you monitor logs in production. - -👉 Jump to our sample LiteLLM Dashboard: https://admin.litellm.ai/ - - -Dashboard - -## Debug your first logs - - Open In Colab - - - -### 1. Get your LiteLLM Token - -Go to [admin.litellm.ai](https://admin.litellm.ai/) and copy the code snippet with your unique token - -Usage - -### 2. Set up your environment - -**Add it to your .env** - -```python -import os - -os.env["LITELLM_TOKEN"] = "e24c4c06-d027-4c30-9e78-18bc3a50aebb" # replace with your unique token - -``` - -**Turn on LiteLLM Client** -```python -import litellm -litellm.client = True -``` - -### 3. Make a normal `completion()` call -```python -import litellm -from litellm import completion -import os - -# set env variables -os.environ["LITELLM_TOKEN"] = "e24c4c06-d027-4c30-9e78-18bc3a50aebb" # replace with your unique token -os.environ["OPENAI_API_KEY"] = "openai key" - -litellm.use_client = True # enable logging dashboard -messages = [{ "content": "Hello, how are you?","role": "user"}] - -# openai call -response = completion(model="gpt-3.5-turbo", messages=messages) -``` - -Your `completion()` call print with a link to your session dashboard (https://admin.litellm.ai/) - -In the above case it would be: [`admin.litellm.ai/e24c4c06-d027-4c30-9e78-18bc3a50aebb`](https://admin.litellm.ai/e24c4c06-d027-4c30-9e78-18bc3a50aebb) - -Click on your personal dashboard link. Here's how you can find it 👇 - -Dashboard - -[👋 Tell us if you need better privacy controls](https://calendly.com/d/4mp-gd3-k5k/berriai-1-1-onboarding-litellm-hosted-version?month=2023-08) - -### 3. Review request log - -Oh! Looks like our request was made successfully. Let's click on it and see exactly what got sent to the LLM provider. - - - - -Ah! So we can see that this request was made to a **Baseten** (see litellm_params > custom_llm_provider) for a model with ID - **7qQNLDB** (see model). The message sent was - `"Hey, how's it going?"` and the response received was - `"As an AI language model, I don't have feelings or emotions, but I can assist you with your queries. How can I assist you today?"` - -Dashboard Log Row - -:::info - -🎉 Congratulations! You've successfully debugger your first log! - -::: \ No newline at end of file diff --git a/docs/my-website/docs/observability/langfuse_integration.md b/docs/my-website/docs/observability/langfuse_integration.md index 07970f599d8..0fb411dd3f0 100644 --- a/docs/my-website/docs/observability/langfuse_integration.md +++ b/docs/my-website/docs/observability/langfuse_integration.md @@ -122,6 +122,7 @@ response = completion( metadata={ "generation_name": "ishaan-test-generation", # set langfuse Generation Name "generation_id": "gen-id22", # set langfuse Generation ID + "parent_observation_id": "obs-id9" # set langfuse Parent Observation ID "version": "test-generation-version" # set langfuse Generation Version "trace_user_id": "user-id2", # set langfuse Trace User ID "session_id": "session-1", # set langfuse Session ID @@ -190,9 +191,10 @@ The following parameters can be updated on a continuation of a trace by passing #### Generation Specific Parameters -* `generation_id` - Identifier for the generation, auto-generated by default -* `generation_name` - Identifier for the generation, auto-generated by default -* `prompt` - Langfuse prompt object used for the generation, defaults to None +* `generation_id` - Identifier for the generation, auto-generated by default +* `generation_name` - Identifier for the generation, auto-generated by default +* `parent_observation_id` - Identifier for the parent observation, defaults to `None` +* `prompt` - Langfuse prompt object used for the generation, defaults to `None` Any other key value pairs passed into the metadata not listed in the above spec for a `litellm` completion will be added as a metadata key value pair for the generation. diff --git a/docs/my-website/docs/observability/promptlayer_integration.md b/docs/my-website/docs/observability/promptlayer_integration.md index a48dd91057d..ffc0a32ec08 100644 --- a/docs/my-website/docs/observability/promptlayer_integration.md +++ b/docs/my-website/docs/observability/promptlayer_integration.md @@ -1,3 +1,5 @@ +import Image from '@theme/IdealImage'; + # Promptlayer Tutorial Promptlayer is a platform for prompt engineers. Log OpenAI requests. Search usage history. Track performance. Visually manage prompt templates. diff --git a/docs/my-website/docs/providers/text_completion_openai.md b/docs/my-website/docs/providers/text_completion_openai.md index 842b56aec95..d790c01fe0b 100644 --- a/docs/my-website/docs/providers/text_completion_openai.md +++ b/docs/my-website/docs/providers/text_completion_openai.md @@ -1,3 +1,6 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + # OpenAI (Text Completion) LiteLLM supports OpenAI text completion models diff --git a/docs/my-website/docs/providers/togetherai.md b/docs/my-website/docs/providers/togetherai.md index 1021f5ba84e..e069ea69dda 100644 --- a/docs/my-website/docs/providers/togetherai.md +++ b/docs/my-website/docs/providers/togetherai.md @@ -208,7 +208,7 @@ print(response) Instead of using the `custom_llm_provider` arg to specify which provider you're using (e.g. together ai), you can just pass the provider name as part of the model name, and LiteLLM will parse it out. -Expected format: / +Expected format: `/` e.g. completion(model="together_ai/togethercomputer/Llama-2-7B-32K-Instruct", ...) diff --git a/docs/my-website/docs/proxy/alerting.md b/docs/my-website/docs/proxy/alerting.md index 402de410c92..08030f47846 100644 --- a/docs/my-website/docs/proxy/alerting.md +++ b/docs/my-website/docs/proxy/alerting.md @@ -1,3 +1,5 @@ +import Image from '@theme/IdealImage'; + # 🚨 Alerting / Webhooks Get alerts for: @@ -15,6 +17,11 @@ Get alerts for: - **Spend** Weekly & Monthly spend per Team, Tag +Works across: +- [Slack](#quick-start) +- [Discord](#advanced---using-discord-webhooks) +- [Microsoft Teams](#advanced---using-ms-teams-webhooks) + ## Quick Start Set up a slack alert channel to receive alerts from proxy. @@ -25,41 +32,33 @@ Get a slack webhook url from https://api.slack.com/messaging/webhooks You can also use Discord Webhooks, see [here](#using-discord-webhooks) -### Step 2: Update config.yaml -- Set `SLACK_WEBHOOK_URL` in your proxy env to enable Slack alerts. -- Just for testing purposes, let's save a bad key to our proxy. +Set `SLACK_WEBHOOK_URL` in your proxy env to enable Slack alerts. + +```bash +export SLACK_WEBHOOK_URL="https://hooks.slack.com/services/<>/<>/<>" +``` + +### Step 2: Setup Proxy ```yaml -model_list: - model_name: "azure-model" - litellm_params: - model: "azure/gpt-35-turbo" - api_key: "my-bad-key" # 👈 bad key - general_settings: alerting: ["slack"] alerting_threshold: 300 # sends alerts if requests hang for 5min+ and responses take 5min+ - -environment_variables: - SLACK_WEBHOOK_URL: "https://hooks.slack.com/services/<>/<>/<>" - SLACK_DAILY_REPORT_FREQUENCY: "86400" # 24 hours; Optional: defaults to 12 hours ``` - -### Step 3: Start proxy - +Start proxy ```bash $ litellm --config /path/to/config.yaml ``` -## Testing Alerting is Setup Correctly -Make a GET request to `/health/services`, expect to see a test slack alert in your provided webhook slack channel +### Step 3: Test it! -```shell -curl -X GET 'http://localhost:4000/health/services?service=slack' \ - -H 'Authorization: Bearer sk-1234' + +```bash +curl -X GET 'http://0.0.0.0:4000/health/services?service=slack' \ +-H 'Authorization: Bearer sk-1234' ``` ## Advanced - Redacting Messages from Alerts @@ -77,7 +76,34 @@ litellm_settings: ``` +## Advanced - Add Metadata to alerts +Add alerting metadata to proxy calls for debugging. + +```python +import openai +client = openai.OpenAI( + api_key="anything", + base_url="http://0.0.0.0:4000" +) + +# request sent to model set on litellm proxy, `litellm --model` +response = client.chat.completions.create( + model="gpt-3.5-turbo", + messages = [], + extra_body={ + "metadata": { + "alerting_metadata": { + "hello": "world" + } + } + } +) +``` + +**Expected Response** + + ## Advanced - Opting into specific alert types @@ -108,6 +134,48 @@ AlertType = Literal[ ``` +## Advanced - Using MS Teams Webhooks + +MS Teams provides a slack compatible webhook url that you can use for alerting + +##### Quick Start + +1. [Get a webhook url](https://learn.microsoft.com/en-us/microsoftteams/platform/webhooks-and-connectors/how-to/add-incoming-webhook?tabs=newteams%2Cdotnet#create-an-incoming-webhook) for your Microsoft Teams channel + +2. Add it to your .env + +```bash +SLACK_WEBHOOK_URL="https://berriai.webhook.office.com/webhookb2/...6901/IncomingWebhook/b55fa0c2a48647be8e6effedcd540266/e04b1092-4a3e-44a2-ab6b-29a0a4854d1d" +``` + +3. Add it to your litellm config + +```yaml +model_list: + model_name: "azure-model" + litellm_params: + model: "azure/gpt-35-turbo" + api_key: "my-bad-key" # 👈 bad key + +general_settings: + alerting: ["slack"] + alerting_threshold: 300 # sends alerts if requests hang for 5min+ and responses take 5min+ +``` + +4. Run health check! + +Call the proxy `/health/services` endpoint to test if your alerting connection is correctly setup. + +```bash +curl --location 'http://0.0.0.0:4000/health/services?service=slack' \ +--header 'Authorization: Bearer sk-1234' +``` + + +**Expected Response** + + + ## Advanced - Using Discord Webhooks Discord provides a slack compatible webhook url that you can use for alerting @@ -139,7 +207,6 @@ environment_variables: SLACK_WEBHOOK_URL: "https://discord.com/api/webhooks/1240030362193760286/cTLWt5ATn1gKmcy_982rl5xmYHsrM1IWJdmCL1AyOmU9JdQXazrp8L1_PYgUtgxj8x4f/slack" ``` -That's it ! You're ready to go ! ## Advanced - [BETA] Webhooks for Budget Alerts diff --git a/docs/my-website/docs/proxy/deploy.md b/docs/my-website/docs/proxy/deploy.md index a3c8590b5f4..8767417f5aa 100644 --- a/docs/my-website/docs/proxy/deploy.md +++ b/docs/my-website/docs/proxy/deploy.md @@ -669,7 +669,7 @@ Once the stack is created, get the DatabaseURL of the Database resource, copy th #### 3. Connect to the EC2 Instance and deploy litellm on the EC2 container From the EC2 console, connect to the instance created by the stack (e.g., using SSH). -Run the following command, replacing with the value you copied in step 2 +Run the following command, replacing `` with the value you copied in step 2 ```shell docker run --name litellm-proxy \ diff --git a/docs/my-website/docs/proxy/email.md b/docs/my-website/docs/proxy/email.md index 2551f4359b1..7db52910754 100644 --- a/docs/my-website/docs/proxy/email.md +++ b/docs/my-website/docs/proxy/email.md @@ -5,6 +5,7 @@ import Image from '@theme/IdealImage'; Send an Email to your users when: - A Proxy API Key is created for them - Their API Key crosses it's Budget +- All Team members of a LiteLLM Team -> when the team crosses it's budget diff --git a/docs/my-website/docs/proxy/model_management.md b/docs/my-website/docs/proxy/model_management.md index 0a236185f98..61d7e088239 100644 --- a/docs/my-website/docs/proxy/model_management.md +++ b/docs/my-website/docs/proxy/model_management.md @@ -1,3 +1,6 @@ +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + # Model Management Add new models + Get model info without restarting proxy. diff --git a/docs/my-website/docs/proxy/perf.md b/docs/my-website/docs/proxy/perf.md index 947ff0462db..a9c901445f8 100644 --- a/docs/my-website/docs/proxy/perf.md +++ b/docs/my-website/docs/proxy/perf.md @@ -1,3 +1,5 @@ +import Image from '@theme/IdealImage'; + # LiteLLM Proxy Performance ### Throughput - 30% Increase diff --git a/docs/my-website/docs/proxy/prometheus.md b/docs/my-website/docs/proxy/prometheus.md index b1fb62ad51a..2c7481f4c6e 100644 --- a/docs/my-website/docs/proxy/prometheus.md +++ b/docs/my-website/docs/proxy/prometheus.md @@ -1,4 +1,4 @@ -# Grafana, Prometheus metrics [BETA] +# 📈 Prometheus metrics [BETA] LiteLLM Exposes a `/metrics` endpoint for Prometheus to Poll @@ -54,6 +54,13 @@ http://localhost:4000/metrics | `litellm_total_tokens` | input + output tokens per `"user", "key", "model", "team", "end-user"` | | `litellm_llm_api_failed_requests_metric` | Number of failed LLM API requests per `"user", "key", "model", "team", "end-user"` | +### Budget Metrics +| Metric Name | Description | +|----------------------|--------------------------------------| +| `litellm_remaining_team_budget_metric` | Remaining Budget for Team (A team created on LiteLLM) | +| `litellm_remaining_api_key_budget_metric` | Remaining Budget for API Key (A key Created on LiteLLM)| + + ## Monitor System Health To monitor the health of litellm adjacent services (redis / postgres), do: diff --git a/docs/my-website/docs/proxy/reliability.md b/docs/my-website/docs/proxy/reliability.md index d4ab1a2c75c..a2d24da69b8 100644 --- a/docs/my-website/docs/proxy/reliability.md +++ b/docs/my-website/docs/proxy/reliability.md @@ -409,6 +409,28 @@ print(response) +### Content Policy Fallbacks + +Fallback across providers (e.g. from Azure OpenAI to Anthropic) if you hit content policy violation errors. + +```yaml +model_list: + - model_name: gpt-3.5-turbo-small + litellm_params: + model: azure/chatgpt-v-2 + api_base: os.environ/AZURE_API_BASE + api_key: os.environ/AZURE_API_KEY + api_version: "2023-07-01-preview" + + - model_name: claude-opus + litellm_params: + model: claude-3-opus-20240229 + api_key: os.environ/ANTHROPIC_API_KEY + +litellm_settings: + content_policy_fallbacks: [{"gpt-3.5-turbo-small": ["claude-opus"]}] +``` + ### EU-Region Filtering (Pre-Call Checks) **Before call is made** check if a call is within model context window with **`enable_pre_call_checks: true`**. diff --git a/docs/my-website/docs/proxy/self_serve.md b/docs/my-website/docs/proxy/self_serve.md index 568e6541a62..27fefc7f4f7 100644 --- a/docs/my-website/docs/proxy/self_serve.md +++ b/docs/my-website/docs/proxy/self_serve.md @@ -123,4 +123,18 @@ LiteLLM Enterprise: Enable [SSO login](./ui.md#setup-ssoauth-for-ui) 4. User can now create their own keys - \ No newline at end of file + + + +## Advanced +### Setting custom logout URLs + +Set `PROXY_LOGOUT_URL` in your .env if you want users to get redirected to a specific URL when they click logout + +``` +export PROXY_LOGOUT_URL="https://www.google.com" +``` + + + + diff --git a/docs/my-website/docs/proxy/team_budgets.md b/docs/my-website/docs/proxy/team_budgets.md new file mode 100644 index 00000000000..54f5efddffd --- /dev/null +++ b/docs/my-website/docs/proxy/team_budgets.md @@ -0,0 +1,123 @@ +import Image from '@theme/IdealImage'; +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + +# 💰 Setting Team Budgets + +Track spend, set budgets for your Internal Team + +## Setting Monthly Team Budgets + +### 1. Create a team +- Set `max_budget=000000001` ($ value the team is allowed to spend) +- Set `budget_duration="1d"` (How frequently the budget should update) + + +Create a new team and set `max_budget` and `budget_duration` +```shell +curl -X POST 'http://0.0.0.0:4000/team/new' \ + -H 'Authorization: Bearer sk-1234' \ + -H 'Content-Type: application/json' \ + -d '{ + "team_alias": "QA Prod Bot", + "max_budget": 0.000000001, + "budget_duration": "1d" + }' +``` + +Response +```shell +{ + "team_alias": "QA Prod Bot", + "team_id": "de35b29e-6ca8-4f47-b804-2b79d07aa99a", + "max_budget": 0.0001, + "budget_duration": "1d", + "budget_reset_at": "2024-06-14T22:48:36.594000Z" +} +``` + + + +Possible values for `budget_duration` + +| `budget_duration` | When Budget will reset | +| --- | --- | +| `budget_duration="1s"` | every 1 second | +| `budget_duration="1m"` | every 1 min | +| `budget_duration="1h"` | every 1 hour | +| `budget_duration="1d"` | every 1 day | +| `budget_duration="1mo"` | every 1 month | + + +### 2. Create a key for the `team` + +Create a key for `team_id="de35b29e-6ca8-4f47-b804-2b79d07aa99a"` from Step 1 + +💡 **The Budget for Team="QA Prod Bot" budget will apply to this team** + +```shell +curl -X POST 'http://0.0.0.0:4000/key/generate' \ + -H 'Authorization: Bearer sk-1234' \ + -H 'Content-Type: application/json' \ + -d '{"team_id": "de35b29e-6ca8-4f47-b804-2b79d07aa99a"}' +``` + +Response + +```shell +{"team_id":"de35b29e-6ca8-4f47-b804-2b79d07aa99a", "key":"sk-5qtncoYjzRcxMM4bDRktNQ"} +``` + + +### 3. Test It + +Use the key from step 2 and run this Request twice +```shell +curl -X POST 'http://0.0.0.0:4000/chat/completions' \ + -H 'Authorization: Bearer sk-mso-JSykEGri86KyOvgxBw' \ + -H 'Content-Type: application/json' \ + -d ' { + "model": "llama3", + "messages": [ + { + "role": "user", + "content": "hi" + } + ] + }' +``` + +On the 2nd response - expect to see the following exception + +```shell +{ + "error": { + "message": "Budget has been exceeded! Current cost: 3.5e-06, Max budget: 1e-09", + "type": "auth_error", + "param": null, + "code": 400 + } +} +``` + +## Advanced + +### Prometheus metrics for `remaining_budget` + +[More info about Prometheus metrics here](https://docs.litellm.ai/docs/proxy/prometheus) + +You'll need the following in your proxy config.yaml + +```yaml +litellm_settings: + success_callback: ["prometheus"] + failure_callback: ["prometheus"] +``` + +Expect to see this metric on prometheus to track the Remaining Budget for the team + +```shell +litellm_remaining_team_budget_metric{team_alias="QA Prod Bot",team_id="de35b29e-6ca8-4f47-b804-2b79d07aa99a"} 9.699999999999992e-06 +``` + + diff --git a/docs/my-website/docs/proxy/users.md b/docs/my-website/docs/proxy/users.md index 77fbcb44481..dca9f190e13 100644 --- a/docs/my-website/docs/proxy/users.md +++ b/docs/my-website/docs/proxy/users.md @@ -413,6 +413,52 @@ curl 'http://0.0.0.0:4000/key/generate' \ +### Reset Budgets + +Reset budgets across keys/internal users/teams/customers + +`budget_duration`: Budget is reset at the end of specified duration. If not set, budget is never reset. You can set duration as seconds ("30s"), minutes ("30m"), hours ("30h"), days ("30d"). + + + + +```bash +curl 'http://0.0.0.0:4000/user/new' \ +--header 'Authorization: Bearer ' \ +--header 'Content-Type: application/json' \ +--data-raw '{ + "max_budget": 10, + "budget_duration": 10s, # 👈 KEY CHANGE +}' +``` + + + +```bash +curl 'http://0.0.0.0:4000/key/generate' \ +--header 'Authorization: Bearer ' \ +--header 'Content-Type: application/json' \ +--data-raw '{ + "max_budget": 10, + "budget_duration": 10s, # 👈 KEY CHANGE +}' +``` + + + + +```bash +curl 'http://0.0.0.0:4000/team/new' \ +--header 'Authorization: Bearer ' \ +--header 'Content-Type: application/json' \ +--data-raw '{ + "max_budget": 10, + "budget_duration": 10s, # 👈 KEY CHANGE +}' +``` + + + ## Set Rate Limits You can set: diff --git a/docs/my-website/docs/routing.md b/docs/my-website/docs/routing.md index d91912644fc..63fac94562b 100644 --- a/docs/my-website/docs/routing.md +++ b/docs/my-website/docs/routing.md @@ -790,85 +790,205 @@ If the error is a context window exceeded error, fall back to a larger model gro Fallbacks are done in-order - ["gpt-3.5-turbo, "gpt-4", "gpt-4-32k"], will do 'gpt-3.5-turbo' first, then 'gpt-4', etc. -You can also set 'default_fallbacks', in case a specific model group is misconfigured / bad. +You can also set `default_fallbacks`, in case a specific model group is misconfigured / bad. + +There are 3 types of fallbacks: +- `content_policy_fallbacks`: For litellm.ContentPolicyViolationError - LiteLLM maps content policy violation errors across providers [**See Code**](https://github.com/BerriAI/litellm/blob/89a43c872a1e3084519fb9de159bf52f5447c6c4/litellm/utils.py#L8495C27-L8495C54) +- `context_window_fallbacks`: For litellm.ContextWindowExceededErrors - LiteLLM maps context window error messages across providers [**See Code**](https://github.com/BerriAI/litellm/blob/89a43c872a1e3084519fb9de159bf52f5447c6c4/litellm/utils.py#L8469) +- `fallbacks`: For all remaining errors - e.g. litellm.RateLimitError + +**Content Policy Violation Fallback** + +Key change: ```python -from litellm import Router - -model_list = [ - { # list of model deployments - "model_name": "azure/gpt-3.5-turbo", # openai model name - "litellm_params": { # params for litellm completion/embedding call - "model": "azure/chatgpt-v-2", - "api_key": "bad-key", - "api_version": os.getenv("AZURE_API_VERSION"), - "api_base": os.getenv("AZURE_API_BASE") - }, - "tpm": 240000, - "rpm": 1800 - }, - { # list of model deployments - "model_name": "azure/gpt-3.5-turbo-context-fallback", # openai model name - "litellm_params": { # params for litellm completion/embedding call - "model": "azure/chatgpt-v-2", - "api_key": "bad-key", - "api_version": os.getenv("AZURE_API_VERSION"), - "api_base": os.getenv("AZURE_API_BASE") - }, - "tpm": 240000, - "rpm": 1800 - }, - { - "model_name": "azure/gpt-3.5-turbo", # openai model name - "litellm_params": { # params for litellm completion/embedding call - "model": "azure/chatgpt-functioncalling", - "api_key": "bad-key", - "api_version": os.getenv("AZURE_API_VERSION"), - "api_base": os.getenv("AZURE_API_BASE") - }, - "tpm": 240000, - "rpm": 1800 - }, - { - "model_name": "gpt-3.5-turbo", # openai model name - "litellm_params": { # params for litellm completion/embedding call - "model": "gpt-3.5-turbo", - "api_key": os.getenv("OPENAI_API_KEY"), - }, - "tpm": 1000000, - "rpm": 9000 - }, - { - "model_name": "gpt-3.5-turbo-16k", # openai model name - "litellm_params": { # params for litellm completion/embedding call - "model": "gpt-3.5-turbo-16k", - "api_key": os.getenv("OPENAI_API_KEY"), - }, - "tpm": 1000000, - "rpm": 9000 - } -] - - -router = Router(model_list=model_list, - fallbacks=[{"azure/gpt-3.5-turbo": ["gpt-3.5-turbo"]}], - default_fallbacks=["gpt-3.5-turbo-16k"], - context_window_fallbacks=[{"azure/gpt-3.5-turbo-context-fallback": ["gpt-3.5-turbo-16k"]}, {"gpt-3.5-turbo": ["gpt-3.5-turbo-16k"]}], - set_verbose=True) - - -user_message = "Hello, whats the weather in San Francisco??" -messages = [{"content": user_message, "role": "user"}] - -# normal fallback call -response = router.completion(model="azure/gpt-3.5-turbo", messages=messages) - -# context window fallback call -response = router.completion(model="azure/gpt-3.5-turbo-context-fallback", messages=messages) - -print(f"response: {response}") +content_policy_fallbacks=[{"claude-2": ["my-fallback-model"]}] ``` + + + +```python +from litellm import Router + +router = Router( + model_list=[ + { + "model_name": "claude-2", + "litellm_params": { + "model": "claude-2", + "api_key": "", + "mock_response": Exception("content filtering policy"), + }, + }, + { + "model_name": "my-fallback-model", + "litellm_params": { + "model": "claude-2", + "api_key": "", + "mock_response": "This works!", + }, + }, + ], + content_policy_fallbacks=[{"claude-2": ["my-fallback-model"]}], # 👈 KEY CHANGE + # fallbacks=[..], # [OPTIONAL] + # context_window_fallbacks=[..], # [OPTIONAL] +) + +response = router.completion( + model="claude-2", + messages=[{"role": "user", "content": "Hey, how's it going?"}], +) +``` + + + +In your proxy config.yaml just add this line 👇 + +```yaml +router_settings: + content_policy_fallbacks=[{"claude-2": ["my-fallback-model"]}] +``` + +Start proxy + +```bash +litellm --config /path/to/config.yaml + +# RUNNING on http://0.0.0.0:4000 +``` + + + + +**Context Window Exceeded Fallback** + +Key change: + +```python +context_window_fallbacks=[{"claude-2": ["my-fallback-model"]}] +``` + + + + +```python +from litellm import Router + +router = Router( + model_list=[ + { + "model_name": "claude-2", + "litellm_params": { + "model": "claude-2", + "api_key": "", + "mock_response": Exception("prompt is too long"), + }, + }, + { + "model_name": "my-fallback-model", + "litellm_params": { + "model": "claude-2", + "api_key": "", + "mock_response": "This works!", + }, + }, + ], + context_window_fallbacks=[{"claude-2": ["my-fallback-model"]}], # 👈 KEY CHANGE + # fallbacks=[..], # [OPTIONAL] + # content_policy_fallbacks=[..], # [OPTIONAL] +) + +response = router.completion( + model="claude-2", + messages=[{"role": "user", "content": "Hey, how's it going?"}], +) +``` + + + +In your proxy config.yaml just add this line 👇 + +```yaml +router_settings: + context_window_fallbacks=[{"claude-2": ["my-fallback-model"]}] +``` + +Start proxy + +```bash +litellm --config /path/to/config.yaml + +# RUNNING on http://0.0.0.0:4000 +``` + + + + +**Regular Fallbacks** + +Key change: + +```python +fallbacks=[{"claude-2": ["my-fallback-model"]}] +``` + + + + +```python +from litellm import Router + +router = Router( + model_list=[ + { + "model_name": "claude-2", + "litellm_params": { + "model": "claude-2", + "api_key": "", + "mock_response": Exception("this is a rate limit error"), + }, + }, + { + "model_name": "my-fallback-model", + "litellm_params": { + "model": "claude-2", + "api_key": "", + "mock_response": "This works!", + }, + }, + ], + fallbacks=[{"claude-2": ["my-fallback-model"]}], # 👈 KEY CHANGE + # context_window_fallbacks=[..], # [OPTIONAL] + # content_policy_fallbacks=[..], # [OPTIONAL] +) + +response = router.completion( + model="claude-2", + messages=[{"role": "user", "content": "Hey, how's it going?"}], +) +``` + + + +In your proxy config.yaml just add this line 👇 + +```yaml +router_settings: + fallbacks=[{"claude-2": ["my-fallback-model"]}] +``` + +Start proxy + +```bash +litellm --config /path/to/config.yaml + +# RUNNING on http://0.0.0.0:4000 +``` + + + + ### Caching In production, we recommend using a Redis cache. For quickly testing things locally, we also support simple in-memory caching. diff --git a/docs/my-website/docs/tutorials/TogetherAI_liteLLM.md b/docs/my-website/docs/tutorials/TogetherAI_liteLLM.md index 08e8d56f067..dd9dd288672 100644 --- a/docs/my-website/docs/tutorials/TogetherAI_liteLLM.md +++ b/docs/my-website/docs/tutorials/TogetherAI_liteLLM.md @@ -23,9 +23,13 @@ https://api.together.xyz/playground/chat?model=togethercomputer%2Fllama-2-70b-ch model_name = "together_ai/togethercomputer/llama-2-70b-chat" response = completion(model=model_name, messages=messages) print(response) +``` + + ``` {'choices': [{'finish_reason': 'stop', 'index': 0, 'message': {'role': 'assistant', 'content': "\n\nI'm not able to provide real-time weather information. However, I can suggest"}}], 'created': 1691629657.9288375, 'model': 'togethercomputer/llama-2-70b-chat', 'usage': {'prompt_tokens': 9, 'completion_tokens': 17, 'total_tokens': 26}} +``` LiteLLM handles the prompt formatting for Together AI's Llama2 models as well, converting your message to the diff --git a/docs/my-website/img/alerting_metadata.png b/docs/my-website/img/alerting_metadata.png new file mode 100644 index 00000000000..e75f0c72bfe Binary files /dev/null and b/docs/my-website/img/alerting_metadata.png differ diff --git a/docs/my-website/img/ms_teams_alerting.png b/docs/my-website/img/ms_teams_alerting.png new file mode 100644 index 00000000000..42ec6f784fb Binary files /dev/null and b/docs/my-website/img/ms_teams_alerting.png differ diff --git a/docs/my-website/img/ui_logout.png b/docs/my-website/img/ui_logout.png new file mode 100644 index 00000000000..1b45ed06495 Binary files /dev/null and b/docs/my-website/img/ui_logout.png differ diff --git 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"resolved": "https://registry.npmjs.org/xdg-basedir/-/xdg-basedir-5.1.0.tgz", + "integrity": "sha512-GCPAHLvrIH13+c0SuacwvRYj2SxJXQ4kaVTT5xgL3kPrz56XxkF21IGhjSE1+W0aw7gpBWRGXLCPnPby6lSpmQ==", "engines": { - "node": ">=8" + "node": ">=12" + }, + "funding": { + "url": "https://github.com/sponsors/sindresorhus" } }, "node_modules/xml-js": { diff --git a/docs/my-website/package.json b/docs/my-website/package.json index e8be813ba89..ca1ef13fbd8 100644 --- a/docs/my-website/package.json +++ b/docs/my-website/package.json @@ -14,17 +14,17 @@ "write-heading-ids": "docusaurus write-heading-ids" }, "dependencies": { - "@docusaurus/core": "2.4.1", - "@docusaurus/plugin-google-gtag": "^2.4.1", - "@docusaurus/plugin-ideal-image": "^2.4.1", - "@docusaurus/preset-classic": "2.4.1", + "@docusaurus/core": "3.1.1", + "@docusaurus/plugin-google-gtag": "3.1.1", + "@docusaurus/plugin-ideal-image": "3.1.1", + "@docusaurus/preset-classic": "3.1.1", "@mdx-js/react": "^1.6.22", "clsx": "^1.2.1", "docusaurus": 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index e96d90e26f4..9bfeb6642b9 100644 --- a/docs/my-website/yarn.lock +++ b/docs/my-website/yarn.lock @@ -29,114 +29,131 @@ resolved "https://registry.npmjs.org/@algolia/autocomplete-shared/-/autocomplete-shared-1.9.3.tgz" integrity sha512-Wnm9E4Ye6Rl6sTTqjoymD+l8DjSTHsHboVRYrKgEt8Q7UHm9nYbqhN/i0fhUYA3OAEH7WA8x3jfpnmJm3rKvaQ== -"@algolia/cache-browser-local-storage@4.19.1": - version "4.19.1" - resolved "https://registry.npmjs.org/@algolia/cache-browser-local-storage/-/cache-browser-local-storage-4.19.1.tgz" - integrity sha512-FYAZWcGsFTTaSAwj9Std8UML3Bu8dyWDncM7Ls8g+58UOe4XYdlgzXWbrIgjaguP63pCCbMoExKr61B+ztK3tw== +"@algolia/cache-browser-local-storage@4.23.3": + version "4.23.3" + resolved "https://registry.npmjs.org/@algolia/cache-browser-local-storage/-/cache-browser-local-storage-4.23.3.tgz" + integrity sha512-vRHXYCpPlTDE7i6UOy2xE03zHF2C8MEFjPN2v7fRbqVpcOvAUQK81x3Kc21xyb5aSIpYCjWCZbYZuz8Glyzyyg== dependencies: - "@algolia/cache-common" "4.19.1" + "@algolia/cache-common" "4.23.3" 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dependencies: microevent.ts "~0.1.1" -wrap-ansi@^7.0.0: - version "7.0.0" - resolved "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-7.0.0.tgz" - integrity sha512-YVGIj2kamLSTxw6NsZjoBxfSwsn0ycdesmc4p+Q21c5zPuZ1pl+NfxVdxPtdHvmNVOQ6XSYG4AUtyt/Fi7D16Q== - dependencies: - ansi-styles "^4.0.0" - string-width "^4.1.0" - strip-ansi "^6.0.0" - -wrap-ansi@^8.0.1: +wrap-ansi@^8.0.1, wrap-ansi@^8.1.0: version "8.1.0" resolved "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-8.1.0.tgz" integrity sha512-si7QWI6zUMq56bESFvagtmzMdGOtoxfR+Sez11Mobfc7tm+VkUckk9bW2UeffTGVUbOksxmSw0AA2gs8g71NCQ== @@ -13056,7 +13985,7 @@ wrappy@1: resolved "https://registry.npmjs.org/wrappy/-/wrappy-1.0.2.tgz" integrity sha512-l4Sp/DRseor9wL6EvV2+TuQn63dMkPjZ/sp9XkghTEbV9KlPS1xUsZ3u7/IQO4wxtcFB4bgpQPRcR3QCvezPcQ== -write-file-atomic@^3.0.0: +write-file-atomic@^3.0.3: version "3.0.3" resolved "https://registry.npmjs.org/write-file-atomic/-/write-file-atomic-3.0.3.tgz" integrity 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sha512-V50KMwwzqJV0NpZIZFwfOD5/lyny3WlSzRiXgA0G7VUnRlqttta1L6UQIHzd6EuBY/cHGfwTIck7w1yH6Q5zUw== + +zwitch@^2.0.0: + version "2.0.4" + resolved "https://registry.npmjs.org/zwitch/-/zwitch-2.0.4.tgz" + integrity sha512-bXE4cR/kVZhKZX/RjPEflHaKVhUVl85noU3v6b8apfQEc1x4A+zBxjZ4lN8LqGd6WZ3dl98pY4o717VFmoPp+A== diff --git a/enterprise/utils.py b/enterprise/utils.py index b8f660927b5..baff3b1b022 100644 --- a/enterprise/utils.py +++ b/enterprise/utils.py @@ -122,236 +122,6 @@ async def ui_get_spend_by_tags( return {"spend_per_tag": ui_tags} -async def view_spend_logs_from_clickhouse( - api_key=None, user_id=None, request_id=None, start_date=None, end_date=None -): - verbose_logger.debug("Reading logs from Clickhouse") - import os - - # if user has setup clickhouse - # TODO: Move this to be a helper function - # querying clickhouse for this data - import clickhouse_connect - from datetime import datetime - - port = os.getenv("CLICKHOUSE_PORT") - if port is not None and isinstance(port, str): - port = int(port) - - client = clickhouse_connect.get_client( - host=os.getenv("CLICKHOUSE_HOST"), - port=port, - username=os.getenv("CLICKHOUSE_USERNAME", ""), - password=os.getenv("CLICKHOUSE_PASSWORD", ""), - ) - if ( - start_date is not None - and isinstance(start_date, str) - and end_date is not None - and isinstance(end_date, str) - ): - # Convert the date strings to datetime objects - start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") - end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") - - # get top spend per day - response = client.query( - f""" - SELECT - toDate(startTime) AS day, - sum(spend) AS total_spend - FROM - spend_logs - WHERE - toDate(startTime) BETWEEN toDate('2024-02-01') AND toDate('2024-02-29') - GROUP BY - day - ORDER BY - total_spend - """ - ) - - results = [] - result_rows = list(response.result_rows) - for response in result_rows: - current_row = {} - current_row["users"] = {"example": 0.0} - current_row["models"] = {} - - current_row["spend"] = float(response[1]) - current_row["startTime"] = str(response[0]) - - # stubbed api_key - current_row[""] = 0.0 # type: ignore - results.append(current_row) - - return results - else: - # check if spend logs exist, if it does then return last 10 logs, sorted in descending order of startTime - response = client.query( - """ - SELECT - * - FROM - default.spend_logs - ORDER BY - startTime DESC - LIMIT - 10 - """ - ) - - # get size of spend logs - num_rows = client.query("SELECT count(*) FROM default.spend_logs") - num_rows = num_rows.result_rows[0][0] - - # safely access num_rows.result_rows[0][0] - if num_rows is None: - num_rows = 0 - - raw_rows = list(response.result_rows) - response_data = { - "logs": raw_rows, - "log_count": num_rows, - } - return response_data - - -def _create_clickhouse_material_views(client=None, table_names=[]): - # Create Materialized Views if they don't exist - # Materialized Views send new inserted rows to the aggregate tables - - verbose_logger.debug("Clickhouse: Creating Materialized Views") - if "daily_aggregated_spend_per_model_mv" not in table_names: - verbose_logger.debug("Clickhouse: Creating daily_aggregated_spend_per_model_mv") - client.command( - """ - CREATE MATERIALIZED VIEW daily_aggregated_spend_per_model_mv - TO daily_aggregated_spend_per_model - AS - SELECT - toDate(startTime) as day, - sumState(spend) AS DailySpend, - model as model - FROM spend_logs - GROUP BY - day, model - """ - ) - if "daily_aggregated_spend_per_api_key_mv" not in table_names: - verbose_logger.debug( - "Clickhouse: Creating daily_aggregated_spend_per_api_key_mv" - ) - client.command( - """ - CREATE MATERIALIZED VIEW daily_aggregated_spend_per_api_key_mv - TO daily_aggregated_spend_per_api_key - AS - SELECT - toDate(startTime) as day, - sumState(spend) AS DailySpend, - api_key as api_key - FROM spend_logs - GROUP BY - day, api_key - """ - ) - if "daily_aggregated_spend_per_user_mv" not in table_names: - verbose_logger.debug("Clickhouse: Creating daily_aggregated_spend_per_user_mv") - client.command( - """ - CREATE MATERIALIZED VIEW daily_aggregated_spend_per_user_mv - TO daily_aggregated_spend_per_user - AS - SELECT - toDate(startTime) as day, - sumState(spend) AS DailySpend, - user as user - FROM spend_logs - GROUP BY - day, user - """ - ) - if "daily_aggregated_spend_mv" not in table_names: - verbose_logger.debug("Clickhouse: Creating daily_aggregated_spend_mv") - client.command( - """ - CREATE MATERIALIZED VIEW daily_aggregated_spend_mv - TO daily_aggregated_spend - AS - SELECT - toDate(startTime) as day, - sumState(spend) AS DailySpend - FROM spend_logs - GROUP BY - day - """ - ) - - -def _create_clickhouse_aggregate_tables(client=None, table_names=[]): - # Basic Logging works without this - this is only used for low latency reporting apis - verbose_logger.debug("Clickhouse: Creating Aggregate Tables") - - # Create Aggregeate Tables if they don't exist - if "daily_aggregated_spend_per_model" not in table_names: - verbose_logger.debug("Clickhouse: Creating daily_aggregated_spend_per_model") - client.command( - """ - CREATE TABLE daily_aggregated_spend_per_model - ( - `day` Date, - `DailySpend` AggregateFunction(sum, Float64), - `model` String - ) - ENGINE = SummingMergeTree() - ORDER BY (day, model); - """ - ) - if "daily_aggregated_spend_per_api_key" not in table_names: - verbose_logger.debug("Clickhouse: Creating daily_aggregated_spend_per_api_key") - client.command( - """ - CREATE TABLE daily_aggregated_spend_per_api_key - ( - `day` Date, - `DailySpend` AggregateFunction(sum, Float64), - `api_key` String - ) - ENGINE = SummingMergeTree() - ORDER BY (day, api_key); - """ - ) - if "daily_aggregated_spend_per_user" not in table_names: - verbose_logger.debug("Clickhouse: Creating daily_aggregated_spend_per_user") - client.command( - """ - CREATE TABLE daily_aggregated_spend_per_user - ( - `day` Date, - `DailySpend` AggregateFunction(sum, Float64), - `user` String - ) - ENGINE = SummingMergeTree() - ORDER BY (day, user); - """ - ) - if "daily_aggregated_spend" not in table_names: - verbose_logger.debug("Clickhouse: Creating daily_aggregated_spend") - client.command( - """ - CREATE TABLE daily_aggregated_spend - ( - `day` Date, - `DailySpend` AggregateFunction(sum, Float64), - ) - ENGINE = SummingMergeTree() - ORDER BY (day); - """ - ) - return - - def _forecast_daily_cost(data: list): import requests # type: ignore from datetime import datetime, timedelta diff --git a/litellm/__init__.py b/litellm/__init__.py index 91fa253e71f..353d7ac5b64 100644 --- a/litellm/__init__.py +++ b/litellm/__init__.py @@ -73,7 +73,7 @@ token: Optional[str] = ( ) telemetry = True max_tokens = 256 # OpenAI Defaults -drop_params = False +drop_params = bool(os.getenv("LITELLM_DROP_PARAMS", False)) modify_params = False retry = True ### AUTH ### @@ -240,6 +240,7 @@ num_retries: Optional[int] = None # per model endpoint default_fallbacks: Optional[List] = None fallbacks: Optional[List] = None context_window_fallbacks: Optional[List] = None +content_policy_fallbacks: Optional[List] = None allowed_fails: int = 0 num_retries_per_request: Optional[int] = ( None # for the request overall (incl. fallbacks + model retries) @@ -714,6 +715,7 @@ openai_image_generation_models = ["dall-e-2", "dall-e-3"] from .timeout import timeout from .cost_calculator import completion_cost +from litellm.litellm_core_utils.litellm_logging import Logging from .utils import ( client, exception_type, @@ -722,12 +724,10 @@ from .utils import ( token_counter, create_pretrained_tokenizer, create_tokenizer, - cost_per_token, supports_function_calling, supports_parallel_function_calling, supports_vision, get_litellm_params, - Logging, acreate, get_model_list, get_max_tokens, @@ -747,9 +747,10 @@ from .utils import ( get_first_chars_messages, ModelResponse, ImageResponse, - ImageObject, get_provider_fields, ) + +from .types.utils import ImageObject from .llms.huggingface_restapi import HuggingfaceConfig from .llms.anthropic import AnthropicConfig from .llms.databricks import DatabricksConfig, DatabricksEmbeddingConfig @@ -826,4 +827,4 @@ from .router import Router from .assistants.main import * from .batches.main import * from .scheduler import * -from .cost_calculator import response_cost_calculator +from .cost_calculator import response_cost_calculator, cost_per_token diff --git a/litellm/_logging.py b/litellm/_logging.py index ab7a08f976b..52a445b49e4 100644 --- a/litellm/_logging.py +++ b/litellm/_logging.py @@ -3,10 +3,17 @@ from logging import Formatter import traceback set_verbose = False + +if set_verbose is True: + logging.warning( + "`litellm.set_verbose` is deprecated. Please set `os.environ['LITELLM_LOG'] = 'DEBUG'` for debug logs." + ) json_logs = bool(os.getenv("JSON_LOGS", False)) # Create a handler for the logger (you may need to adapt this based on your needs) +log_level = os.getenv("LITELLM_LOG", "ERROR") +numeric_level: str = getattr(logging, log_level.upper()) handler = logging.StreamHandler() -handler.setLevel(logging.DEBUG) +handler.setLevel(numeric_level) class JsonFormatter(Formatter): diff --git a/litellm/caching.py b/litellm/caching.py index 497dd2371c5..6b58cf52766 100644 --- a/litellm/caching.py +++ b/litellm/caching.py @@ -1192,7 +1192,7 @@ class S3Cache(BaseCache): return cached_response except botocore.exceptions.ClientError as e: if e.response["Error"]["Code"] == "NoSuchKey": - verbose_logger.error( + verbose_logger.debug( f"S3 Cache: The specified key '{key}' does not exist in the S3 bucket." ) return None diff --git a/litellm/cost_calculator.py b/litellm/cost_calculator.py index d1e2dab526d..c84df53e86d 100644 --- a/litellm/cost_calculator.py +++ b/litellm/cost_calculator.py @@ -1,6 +1,6 @@ # What is this? ## File for 'response_cost' calculation in Logging -from typing import Optional, Union, Literal, List +from typing import Optional, Union, Literal, List, Tuple import litellm._logging from litellm.utils import ( ModelResponse, @@ -9,7 +9,6 @@ from litellm.utils import ( TranscriptionResponse, TextCompletionResponse, CallTypes, - cost_per_token, print_verbose, CostPerToken, token_counter, @@ -18,6 +17,224 @@ import litellm from litellm import verbose_logger +def _cost_per_token_custom_pricing_helper( + prompt_tokens=0, + completion_tokens=0, + response_time_ms=None, + ### CUSTOM PRICING ### + custom_cost_per_token: Optional[CostPerToken] = None, + custom_cost_per_second: Optional[float] = None, +) -> Optional[Tuple[float, float]]: + """Internal helper function for calculating cost, if custom pricing given""" + if custom_cost_per_token is None and custom_cost_per_second is None: + return None + + if custom_cost_per_token is not None: + input_cost = custom_cost_per_token["input_cost_per_token"] * prompt_tokens + output_cost = custom_cost_per_token["output_cost_per_token"] * completion_tokens + return input_cost, output_cost + elif custom_cost_per_second is not None: + output_cost = custom_cost_per_second * response_time_ms / 1000 # type: ignore + return 0, output_cost + + return None + + +def cost_per_token( + model: str = "", + prompt_tokens=0, + completion_tokens=0, + response_time_ms=None, + custom_llm_provider=None, + region_name=None, + ### CUSTOM PRICING ### + custom_cost_per_token: Optional[CostPerToken] = None, + custom_cost_per_second: Optional[float] = None, +) -> Tuple[float, float]: + """ + Calculates the cost per token for a given model, prompt tokens, and completion tokens. + + Parameters: + model (str): The name of the model to use. Default is "" + prompt_tokens (int): The number of tokens in the prompt. + completion_tokens (int): The number of tokens in the completion. + response_time (float): The amount of time, in milliseconds, it took the call to complete. + custom_llm_provider (str): The llm provider to whom the call was made (see init.py for full list) + custom_cost_per_token: Optional[CostPerToken]: the cost per input + output token for the llm api call. + custom_cost_per_second: Optional[float]: the cost per second for the llm api call. + + Returns: + tuple: A tuple containing the cost in USD dollars for prompt tokens and completion tokens, respectively. + """ + if model is None: + raise Exception("Invalid arg. Model cannot be none.") + ## CUSTOM PRICING ## + response_cost = _cost_per_token_custom_pricing_helper( + prompt_tokens=prompt_tokens, + completion_tokens=completion_tokens, + response_time_ms=response_time_ms, + custom_cost_per_second=custom_cost_per_second, + custom_cost_per_token=custom_cost_per_token, + ) + if response_cost is not None: + return response_cost[0], response_cost[1] + + # given + prompt_tokens_cost_usd_dollar: float = 0 + completion_tokens_cost_usd_dollar: float = 0 + model_cost_ref = litellm.model_cost + model_with_provider = model + if custom_llm_provider is not None: + model_with_provider = custom_llm_provider + "/" + model + if region_name is not None: + model_with_provider_and_region = ( + f"{custom_llm_provider}/{region_name}/{model}" + ) + if ( + model_with_provider_and_region in model_cost_ref + ): # use region based pricing, if it's available + model_with_provider = model_with_provider_and_region + + model_without_prefix = model + model_parts = model.split("/") + if len(model_parts) > 1: + model_without_prefix = model_parts[1] + else: + model_without_prefix = model + """ + Code block that formats model to lookup in litellm.model_cost + Option1. model = "bedrock/ap-northeast-1/anthropic.claude-instant-v1". This is the most accurate since it is region based. Should always be option 1 + Option2. model = "openai/gpt-4" - model = provider/model + Option3. model = "anthropic.claude-3" - model = model + """ + if ( + model_with_provider in model_cost_ref + ): # Option 2. use model with provider, model = "openai/gpt-4" + model = model_with_provider + elif model in model_cost_ref: # Option 1. use model passed, model="gpt-4" + model = model + elif ( + model_without_prefix in model_cost_ref + ): # Option 3. if user passed model="bedrock/anthropic.claude-3", use model="anthropic.claude-3" + model = model_without_prefix + + # see this https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models + print_verbose(f"Looking up model={model} in model_cost_map") + if model in model_cost_ref: + print_verbose(f"Success: model={model} in model_cost_map") + print_verbose( + f"prompt_tokens={prompt_tokens}; completion_tokens={completion_tokens}" + ) + if ( + model_cost_ref[model].get("input_cost_per_token", None) is not None + and model_cost_ref[model].get("output_cost_per_token", None) is not None + ): + ## COST PER TOKEN ## + prompt_tokens_cost_usd_dollar = ( + model_cost_ref[model]["input_cost_per_token"] * prompt_tokens + ) + completion_tokens_cost_usd_dollar = ( + model_cost_ref[model]["output_cost_per_token"] * completion_tokens + ) + elif ( + model_cost_ref[model].get("output_cost_per_second", None) is not None + and response_time_ms is not None + ): + print_verbose( + f"For model={model} - output_cost_per_second: {model_cost_ref[model].get('output_cost_per_second')}; response time: {response_time_ms}" + ) + ## COST PER SECOND ## + prompt_tokens_cost_usd_dollar = 0 + completion_tokens_cost_usd_dollar = ( + model_cost_ref[model]["output_cost_per_second"] + * response_time_ms + / 1000 + ) + elif ( + model_cost_ref[model].get("input_cost_per_second", None) is not None + and response_time_ms is not None + ): + print_verbose( + f"For model={model} - input_cost_per_second: {model_cost_ref[model].get('input_cost_per_second')}; response time: {response_time_ms}" + ) + ## COST PER SECOND ## + prompt_tokens_cost_usd_dollar = ( + model_cost_ref[model]["input_cost_per_second"] * response_time_ms / 1000 + ) + completion_tokens_cost_usd_dollar = 0.0 + print_verbose( + f"Returned custom cost for model={model} - prompt_tokens_cost_usd_dollar: {prompt_tokens_cost_usd_dollar}, completion_tokens_cost_usd_dollar: {completion_tokens_cost_usd_dollar}" + ) + return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar + elif "ft:gpt-3.5-turbo" in model: + print_verbose(f"Cost Tracking: {model} is an OpenAI FinteTuned LLM") + # fuzzy match ft:gpt-3.5-turbo:abcd-id-cool-litellm + prompt_tokens_cost_usd_dollar = ( + model_cost_ref["ft:gpt-3.5-turbo"]["input_cost_per_token"] * prompt_tokens + ) + completion_tokens_cost_usd_dollar = ( + model_cost_ref["ft:gpt-3.5-turbo"]["output_cost_per_token"] + * completion_tokens + ) + return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar + elif "ft:davinci-002" in model: + print_verbose(f"Cost Tracking: {model} is an OpenAI FinteTuned LLM") + # fuzzy match ft:davinci-002:abcd-id-cool-litellm + prompt_tokens_cost_usd_dollar = ( + model_cost_ref["ft:davinci-002"]["input_cost_per_token"] * prompt_tokens + ) + completion_tokens_cost_usd_dollar = ( + model_cost_ref["ft:davinci-002"]["output_cost_per_token"] + * completion_tokens + ) + return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar + elif "ft:babbage-002" in model: + print_verbose(f"Cost Tracking: {model} is an OpenAI FinteTuned LLM") + # fuzzy match ft:babbage-002:abcd-id-cool-litellm + prompt_tokens_cost_usd_dollar = ( + model_cost_ref["ft:babbage-002"]["input_cost_per_token"] * prompt_tokens + ) + completion_tokens_cost_usd_dollar = ( + model_cost_ref["ft:babbage-002"]["output_cost_per_token"] + * completion_tokens + ) + return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar + elif model in litellm.azure_llms: + verbose_logger.debug(f"Cost Tracking: {model} is an Azure LLM") + model = litellm.azure_llms[model] + verbose_logger.debug( + f"applying cost={model_cost_ref[model]['input_cost_per_token']} for prompt_tokens={prompt_tokens}" + ) + prompt_tokens_cost_usd_dollar = ( + model_cost_ref[model]["input_cost_per_token"] * prompt_tokens + ) + verbose_logger.debug( + f"applying cost={model_cost_ref[model]['output_cost_per_token']} for completion_tokens={completion_tokens}" + ) + completion_tokens_cost_usd_dollar = ( + model_cost_ref[model]["output_cost_per_token"] * completion_tokens + ) + return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar + elif model in litellm.azure_embedding_models: + verbose_logger.debug(f"Cost Tracking: {model} is an Azure Embedding Model") + model = litellm.azure_embedding_models[model] + prompt_tokens_cost_usd_dollar = ( + model_cost_ref[model]["input_cost_per_token"] * prompt_tokens + ) + completion_tokens_cost_usd_dollar = ( + model_cost_ref[model]["output_cost_per_token"] * completion_tokens + ) + return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar + else: + # if model is not in model_prices_and_context_window.json. Raise an exception-let users know + error_str = f"Model not in model_prices_and_context_window.json. You passed model={model}. Register pricing for model - https://docs.litellm.ai/docs/proxy/custom_pricing\n" + raise litellm.exceptions.NotFoundError( # type: ignore + message=error_str, + model=model, + llm_provider="", + ) + + # Extract the number of billion parameters from the model name # only used for together_computer LLMs def get_model_params_and_category(model_name) -> str: diff --git a/litellm/exceptions.py b/litellm/exceptions.py index edc17133d52..9674d48b120 100644 --- a/litellm/exceptions.py +++ b/litellm/exceptions.py @@ -26,7 +26,7 @@ class AuthenticationError(openai.AuthenticationError): # type: ignore num_retries: Optional[int] = None, ): self.status_code = 401 - self.message = message + self.message = "litellm.AuthenticationError: {}".format(message) self.llm_provider = llm_provider self.model = model self.litellm_debug_info = litellm_debug_info @@ -72,7 +72,7 @@ class NotFoundError(openai.NotFoundError): # type: ignore num_retries: Optional[int] = None, ): self.status_code = 404 - self.message = message + self.message = "litellm.NotFoundError: {}".format(message) self.model = model self.llm_provider = llm_provider self.litellm_debug_info = litellm_debug_info @@ -117,7 +117,7 @@ class BadRequestError(openai.BadRequestError): # type: ignore num_retries: Optional[int] = None, ): self.status_code = 400 - self.message = message + self.message = "litellm.BadRequestError: {}".format(message) self.model = model self.llm_provider = llm_provider self.litellm_debug_info = litellm_debug_info @@ -162,7 +162,7 @@ class UnprocessableEntityError(openai.UnprocessableEntityError): # type: ignore num_retries: Optional[int] = None, ): self.status_code = 422 - self.message = message + self.message = "litellm.UnprocessableEntityError: {}".format(message) self.model = model self.llm_provider = llm_provider self.litellm_debug_info = litellm_debug_info @@ -204,7 +204,7 @@ class Timeout(openai.APITimeoutError): # type: ignore request=request ) # Call the base class constructor with the parameters it needs self.status_code = 408 - self.message = message + self.message = "litellm.Timeout: {}".format(message) self.model = model self.llm_provider = llm_provider self.litellm_debug_info = litellm_debug_info @@ -241,7 +241,7 @@ class PermissionDeniedError(openai.PermissionDeniedError): # type:ignore num_retries: Optional[int] = None, ): self.status_code = 403 - self.message = message + self.message = "litellm.PermissionDeniedError: {}".format(message) self.llm_provider = llm_provider self.model = model self.litellm_debug_info = litellm_debug_info @@ -280,7 +280,7 @@ class RateLimitError(openai.RateLimitError): # type: ignore num_retries: Optional[int] = None, ): self.status_code = 429 - self.message = message + self.message = "litellm.RateLimitError: {}".format(message) self.llm_provider = llm_provider self.model = model self.litellm_debug_info = litellm_debug_info @@ -324,19 +324,21 @@ class ContextWindowExceededError(BadRequestError): # type: ignore message, model, llm_provider, - response: httpx.Response, + response: Optional[httpx.Response] = None, litellm_debug_info: Optional[str] = None, ): self.status_code = 400 - self.message = message + self.message = "litellm.ContextWindowExceededError: {}".format(message) self.model = model self.llm_provider = llm_provider self.litellm_debug_info = litellm_debug_info + request = httpx.Request(method="POST", url="https://api.openai.com/v1") + self.response = response or httpx.Response(status_code=400, request=request) super().__init__( message=self.message, model=self.model, # type: ignore llm_provider=self.llm_provider, # type: ignore - response=response, + response=self.response, litellm_debug_info=self.litellm_debug_info, ) # Call the base class constructor with the parameters it needs @@ -368,7 +370,7 @@ class RejectedRequestError(BadRequestError): # type: ignore litellm_debug_info: Optional[str] = None, ): self.status_code = 400 - self.message = message + self.message = "litellm.RejectedRequestError: {}".format(message) self.model = model self.llm_provider = llm_provider self.litellm_debug_info = litellm_debug_info @@ -407,19 +409,21 @@ class ContentPolicyViolationError(BadRequestError): # type: ignore message, model, llm_provider, - response: httpx.Response, + response: Optional[httpx.Response] = None, litellm_debug_info: Optional[str] = None, ): self.status_code = 400 - self.message = message + self.message = "litellm.ContentPolicyViolationError: {}".format(message) self.model = model self.llm_provider = llm_provider self.litellm_debug_info = litellm_debug_info + request = httpx.Request(method="POST", url="https://api.openai.com/v1") + self.response = response or httpx.Response(status_code=500, request=request) super().__init__( message=self.message, model=self.model, # type: ignore llm_provider=self.llm_provider, # type: ignore - response=response, + response=self.response, litellm_debug_info=self.litellm_debug_info, ) # Call the base class constructor with the parameters it needs @@ -452,7 +456,7 @@ class ServiceUnavailableError(openai.APIStatusError): # type: ignore num_retries: Optional[int] = None, ): self.status_code = 503 - self.message = message + self.message = "litellm.ServiceUnavailableError: {}".format(message) self.llm_provider = llm_provider self.model = model self.litellm_debug_info = litellm_debug_info @@ -501,7 +505,7 @@ class InternalServerError(openai.InternalServerError): # type: ignore num_retries: Optional[int] = None, ): self.status_code = 500 - self.message = message + self.message = "litellm.InternalServerError: {}".format(message) self.llm_provider = llm_provider self.model = model self.litellm_debug_info = litellm_debug_info @@ -552,7 +556,7 @@ class APIError(openai.APIError): # type: ignore num_retries: Optional[int] = None, ): self.status_code = status_code - self.message = message + self.message = "litellm.APIError: {}".format(message) self.llm_provider = llm_provider self.model = model self.litellm_debug_info = litellm_debug_info @@ -589,7 +593,7 @@ class APIConnectionError(openai.APIConnectionError): # type: ignore max_retries: Optional[int] = None, num_retries: Optional[int] = None, ): - self.message = message + self.message = "litellm.APIConnectionError: {}".format(message) self.llm_provider = llm_provider self.model = model self.status_code = 500 @@ -626,7 +630,7 @@ class APIResponseValidationError(openai.APIResponseValidationError): # type: ig max_retries: Optional[int] = None, num_retries: Optional[int] = None, ): - self.message = message + self.message = "litellm.APIResponseValidationError: {}".format(message) self.llm_provider = llm_provider self.model = model request = httpx.Request(method="POST", url="https://api.openai.com/v1") diff --git a/litellm/integrations/clickhouse.py b/litellm/integrations/clickhouse.py index f8b6b1bbf07..eff1836ef1d 100644 --- a/litellm/integrations/clickhouse.py +++ b/litellm/integrations/clickhouse.py @@ -226,14 +226,6 @@ def _start_clickhouse(): response = client.query("DESCRIBE default.spend_logs") verbose_logger.debug(f"spend logs schema ={response.result_rows}") - # RUN Enterprise Clickhouse Setup - # TLDR: For Enterprise - we create views / aggregate tables for low latency reporting APIs - from litellm.proxy.enterprise.utils import _create_clickhouse_aggregate_tables - from litellm.proxy.enterprise.utils import _create_clickhouse_material_views - - _create_clickhouse_aggregate_tables(client=client, table_names=table_names) - _create_clickhouse_material_views(client=client, table_names=table_names) - class ClickhouseLogger: # Class variables or attributes diff --git a/litellm/integrations/email_alerting.py b/litellm/integrations/email_alerting.py new file mode 100644 index 00000000000..434efb63b07 --- /dev/null +++ b/litellm/integrations/email_alerting.py @@ -0,0 +1,136 @@ +""" +Functions for sending Email Alerts +""" + +import os +from typing import Optional, List +from litellm.proxy._types import WebhookEvent +import asyncio +from litellm._logging import verbose_logger, verbose_proxy_logger + +# we use this for the email header, please send a test email if you change this. verify it looks good on email +LITELLM_LOGO_URL = "https://litellm-listing.s3.amazonaws.com/litellm_logo.png" +LITELLM_SUPPORT_CONTACT = "support@berri.ai" + + +async def get_all_team_member_emails(team_id: Optional[str] = None) -> list: + verbose_logger.debug( + "Email Alerting: Getting all team members for team_id=%s", team_id + ) + if team_id is None: + return [] + from litellm.proxy.proxy_server import premium_user, prisma_client + + if prisma_client is None: + raise Exception("Not connected to DB!") + + team_row = await prisma_client.db.litellm_teamtable.find_unique( + where={ + "team_id": team_id, + } + ) + + if team_row is None: + return [] + + _team_members = team_row.members_with_roles + verbose_logger.debug( + "Email Alerting: Got team members for team_id=%s Team Members: %s", + team_id, + _team_members, + ) + _team_member_user_ids: List[str] = [] + for member in _team_members: + if member and isinstance(member, dict) and member.get("user_id") is not None: + _team_member_user_ids.append(member.get("user_id")) + + sql_query = """ + SELECT user_email + FROM "LiteLLM_UserTable" + WHERE user_id = ANY($1::TEXT[]); + """ + + _result = await prisma_client.db.query_raw(sql_query, _team_member_user_ids) + + verbose_logger.debug("Email Alerting: Got all Emails for team, emails=%s", _result) + + if _result is None: + return [] + + emails = [] + for user in _result: + if user and isinstance(user, dict) and user.get("user_email", None) is not None: + emails.append(user.get("user_email")) + return emails + + +async def send_team_budget_alert(webhook_event: WebhookEvent) -> bool: + """ + Send an Email Alert to All Team Members when the Team Budget is crossed + Returns -> True if sent, False if not. + """ + from litellm.proxy.utils import send_email + + from litellm.proxy.proxy_server import premium_user, prisma_client + + _team_id = webhook_event.team_id + team_alias = webhook_event.team_alias + verbose_logger.debug( + "Email Alerting: Sending Team Budget Alert for team=%s", team_alias + ) + + email_logo_url = os.getenv("SMTP_SENDER_LOGO", os.getenv("EMAIL_LOGO_URL", None)) + email_support_contact = os.getenv("EMAIL_SUPPORT_CONTACT", None) + + # await self._check_if_using_premium_email_feature( + # premium_user, email_logo_url, email_support_contact + # ) + + if email_logo_url is None: + email_logo_url = LITELLM_LOGO_URL + if email_support_contact is None: + email_support_contact = LITELLM_SUPPORT_CONTACT + recipient_emails = await get_all_team_member_emails(_team_id) + recipient_emails_str: str = ",".join(recipient_emails) + verbose_logger.debug( + "Email Alerting: Sending team budget alert to %s", recipient_emails_str + ) + + event_name = webhook_event.event_message + max_budget = webhook_event.max_budget + email_html_content = "Alert from LiteLLM Server" + + if recipient_emails_str is None: + verbose_proxy_logger.error( + "Email Alerting: Trying to send email alert to no recipient, got recipient_emails=%s", + recipient_emails_str, + ) + + email_html_content = f""" + LiteLLM Logo


+ + Budget Crossed for Team {team_alias}

+ + Your Teams LLM API usage has crossed it's budget of ${max_budget} , current spend is ${webhook_event.spend}

+ + API requests will be rejected until either (a) you increase your budget or (b) your budget gets reset

+ + If you have any questions, please send an email to {email_support_contact}

+ + Best,
+ The LiteLLM team
+ """ + + email_event = { + "to": recipient_emails_str, + "subject": f"LiteLLM {event_name} for Team {team_alias}", + "html": email_html_content, + } + + await send_email( + receiver_email=email_event["to"], + subject=email_event["subject"], + html=email_event["html"], + ) + + return False diff --git a/litellm/integrations/langfuse.py b/litellm/integrations/langfuse.py index 7fe2e9f2275..3c8f8c85cc6 100644 --- a/litellm/integrations/langfuse.py +++ b/litellm/integrations/langfuse.py @@ -528,6 +528,10 @@ class LangFuseLogger: "version": clean_metadata.pop("version", None), } + parent_observation_id = metadata.get("parent_observation_id", None) + if parent_observation_id is not None: + generation_params["parent_observation_id"] = parent_observation_id + if supports_prompt: user_prompt = clean_metadata.pop("prompt", None) if user_prompt is None: diff --git a/litellm/integrations/prometheus.py b/litellm/integrations/prometheus.py index c97fce0d837..4f0ffa387e8 100644 --- a/litellm/integrations/prometheus.py +++ b/litellm/integrations/prometheus.py @@ -8,6 +8,7 @@ import traceback import datetime, subprocess, sys import litellm, uuid from litellm._logging import print_verbose, verbose_logger +from typing import Optional, Union class PrometheusLogger: @@ -17,33 +18,76 @@ class PrometheusLogger: **kwargs, ): try: - from prometheus_client import Counter + from prometheus_client import Counter, Gauge self.litellm_llm_api_failed_requests_metric = Counter( name="litellm_llm_api_failed_requests_metric", documentation="Total number of failed LLM API calls via litellm", - labelnames=["end_user", "hashed_api_key", "model", "team", "team_alias", "user"], + labelnames=[ + "end_user", + "hashed_api_key", + "model", + "team", + "team_alias", + "user", + ], ) self.litellm_requests_metric = Counter( name="litellm_requests_metric", documentation="Total number of LLM calls to litellm", - labelnames=["end_user", "hashed_api_key", "model", "team", "team_alias", "user"], + labelnames=[ + "end_user", + "hashed_api_key", + "model", + "team", + "team_alias", + "user", + ], ) # Counter for spend self.litellm_spend_metric = Counter( "litellm_spend_metric", "Total spend on LLM requests", - labelnames=["end_user", "hashed_api_key", "model", "team", "team_alias", "user"], + labelnames=[ + "end_user", + "hashed_api_key", + "model", + "team", + "team_alias", + "user", + ], ) # Counter for total_output_tokens self.litellm_tokens_metric = Counter( "litellm_total_tokens", "Total number of input + output tokens from LLM requests", - labelnames=["end_user", "hashed_api_key", "model", "team", "team_alias", "user"], + labelnames=[ + "end_user", + "hashed_api_key", + "model", + "team", + "team_alias", + "user", + ], ) + + # Remaining Budget for Team + self.litellm_remaining_team_budget_metric = Gauge( + "litellm_remaining_team_budget_metric", + "Remaining budget for team", + labelnames=["team_id", "team_alias"], + ) + + # Remaining Budget for API Key + self.litellm_remaining_api_key_budget_metric = Gauge( + "litellm_remaining_api_key_budget_metric", + "Remaining budget for api key", + labelnames=["hashed_api_key", "api_key_alias"], + ) + except Exception as e: print_verbose(f"Got exception on init prometheus client {str(e)}") raise e @@ -51,7 +95,9 @@ class PrometheusLogger: async def _async_log_event( self, kwargs, response_obj, start_time, end_time, print_verbose, user_id ): - self.log_event(kwargs, response_obj, start_time, end_time, print_verbose) + self.log_event( + kwargs, response_obj, start_time, end_time, user_id, print_verbose + ) def log_event( self, kwargs, response_obj, start_time, end_time, user_id, print_verbose @@ -72,12 +118,36 @@ class PrometheusLogger: "user_api_key_user_id", None ) user_api_key = litellm_params.get("metadata", {}).get("user_api_key", None) + user_api_key_alias = litellm_params.get("metadata", {}).get( + "user_api_key_alias", None + ) user_api_team = litellm_params.get("metadata", {}).get( "user_api_key_team_id", None ) user_api_team_alias = litellm_params.get("metadata", {}).get( "user_api_key_team_alias", None ) + + _team_spend = litellm_params.get("metadata", {}).get( + "user_api_key_team_spend", None + ) + _team_max_budget = litellm_params.get("metadata", {}).get( + "user_api_key_team_max_budget", None + ) + _remaining_team_budget = safe_get_remaining_budget( + max_budget=_team_max_budget, spend=_team_spend + ) + + _api_key_spend = litellm_params.get("metadata", {}).get( + "user_api_key_spend", None + ) + _api_key_max_budget = litellm_params.get("metadata", {}).get( + "user_api_key_max_budget", None + ) + _remaining_api_key_budget = safe_get_remaining_budget( + max_budget=_api_key_max_budget, spend=_api_key_spend + ) + if response_obj is not None: tokens_used = response_obj.get("usage", {}).get("total_tokens", 0) else: @@ -97,19 +167,47 @@ class PrometheusLogger: user_api_key = hash_token(user_api_key) self.litellm_requests_metric.labels( - end_user_id, user_api_key, model, user_api_team, user_api_team_alias, user_id + end_user_id, + user_api_key, + model, + user_api_team, + user_api_team_alias, + user_id, ).inc() self.litellm_spend_metric.labels( - end_user_id, user_api_key, model, user_api_team, user_api_team_alias, user_id + end_user_id, + user_api_key, + model, + user_api_team, + user_api_team_alias, + user_id, ).inc(response_cost) self.litellm_tokens_metric.labels( - end_user_id, user_api_key, model, user_api_team, user_api_team_alias, user_id + end_user_id, + user_api_key, + model, + user_api_team, + user_api_team_alias, + user_id, ).inc(tokens_used) + self.litellm_remaining_team_budget_metric.labels( + user_api_team, user_api_team_alias + ).set(_remaining_team_budget) + + self.litellm_remaining_api_key_budget_metric.labels( + user_api_key, user_api_key_alias + ).set(_remaining_api_key_budget) + ### FAILURE INCREMENT ### if "exception" in kwargs: self.litellm_llm_api_failed_requests_metric.labels( - end_user_id, user_api_key, model, user_api_team, user_api_team_alias, user_id + end_user_id, + user_api_key, + model, + user_api_team, + user_api_team_alias, + user_id, ).inc() except Exception as e: verbose_logger.error( @@ -117,3 +215,15 @@ class PrometheusLogger: ) verbose_logger.debug(traceback.format_exc()) pass + + +def safe_get_remaining_budget( + max_budget: Optional[float], spend: Optional[float] +) -> float: + if max_budget is None: + return float("inf") + + if spend is None: + return max_budget + + return max_budget - spend diff --git a/litellm/integrations/slack_alerting.py b/litellm/integrations/slack_alerting.py index 21415fb6d6f..c1f94febe2f 100644 --- a/litellm/integrations/slack_alerting.py +++ b/litellm/integrations/slack_alerting.py @@ -330,6 +330,7 @@ class SlackAlerting(CustomLogger): messages = "Message not logged. litellm.redact_messages_in_exceptions=True" request_info = f"\nRequest Model: `{model}`\nAPI Base: `{api_base}`\nMessages: `{messages}`" slow_message = f"`Responses are slow - {round(time_difference_float,2)}s response time > Alerting threshold: {self.alerting_threshold}s`" + alerting_metadata: dict = {} if time_difference_float > self.alerting_threshold: # add deployment latencies to alert if ( @@ -337,7 +338,7 @@ class SlackAlerting(CustomLogger): and "litellm_params" in kwargs and "metadata" in kwargs["litellm_params"] ): - _metadata = kwargs["litellm_params"]["metadata"] + _metadata: dict = kwargs["litellm_params"]["metadata"] request_info = litellm.utils._add_key_name_and_team_to_alert( request_info=request_info, metadata=_metadata ) @@ -349,10 +350,14 @@ class SlackAlerting(CustomLogger): request_info += ( f"\nAvailable Deployment Latencies\n{_deployment_latency_map}" ) + + if "alerting_metadata" in _metadata: + alerting_metadata = _metadata["alerting_metadata"] await self.send_alert( message=slow_message + request_info, level="Low", alert_type="llm_too_slow", + alerting_metadata=alerting_metadata, ) async def async_update_daily_reports( @@ -540,7 +545,12 @@ class SlackAlerting(CustomLogger): message += f"\n\nNext Run is at: `{time.time() + self.alerting_args.daily_report_frequency}`s" # send alert - await self.send_alert(message=message, level="Low", alert_type="daily_reports") + await self.send_alert( + message=message, + level="Low", + alert_type="daily_reports", + alerting_metadata={}, + ) return True @@ -582,6 +592,7 @@ class SlackAlerting(CustomLogger): await asyncio.sleep( self.alerting_threshold ) # Set it to 5 minutes - i'd imagine this might be different for streaming, non-streaming, non-completion (embedding + img) requests + alerting_metadata: dict = {} if ( request_data is not None and request_data.get("litellm_status", "") != "success" @@ -606,7 +617,7 @@ class SlackAlerting(CustomLogger): ): # In hanging requests sometime it has not made it to the point where the deployment is passed to the `request_data`` # in that case we fallback to the api base set in the request metadata - _metadata = request_data["metadata"] + _metadata: dict = request_data["metadata"] _api_base = _metadata.get("api_base", "") request_info = litellm.utils._add_key_name_and_team_to_alert( @@ -615,6 +626,9 @@ class SlackAlerting(CustomLogger): if _api_base is None: _api_base = "" + + if "alerting_metadata" in _metadata: + alerting_metadata = _metadata["alerting_metadata"] request_info += f"\nAPI Base: `{_api_base}`" # only alert hanging responses if they have not been marked as success alerting_message = ( @@ -640,6 +654,7 @@ class SlackAlerting(CustomLogger): message=alerting_message + request_info, level="Medium", alert_type="llm_requests_hanging", + alerting_metadata=alerting_metadata, ) async def failed_tracking_alert(self, error_message: str): @@ -650,7 +665,10 @@ class SlackAlerting(CustomLogger): result = await _cache.async_get_cache(key=_cache_key) if result is None: await self.send_alert( - message=message, level="High", alert_type="budget_alerts" + message=message, + level="High", + alert_type="budget_alerts", + alerting_metadata={}, ) await _cache.async_set_cache( key=_cache_key, @@ -680,7 +698,7 @@ class SlackAlerting(CustomLogger): return if "budget_alerts" not in self.alert_types: return - _id: str = "default_id" # used for caching + _id: Optional[str] = "default_id" # used for caching user_info_json = user_info.model_dump(exclude_none=True) for k, v in user_info_json.items(): user_info_str = "\n{}: {}\n".format(k, v) @@ -751,6 +769,7 @@ class SlackAlerting(CustomLogger): level="High", alert_type="budget_alerts", user_info=webhook_event, + alerting_metadata={}, ) await _cache.async_set_cache( key=_cache_key, @@ -769,7 +788,13 @@ class SlackAlerting(CustomLogger): response_cost: Optional[float], max_budget: Optional[float], ): - if end_user_id is not None and token is not None and response_cost is not None: + if ( + self.alerting is not None + and "webhook" in self.alerting + and end_user_id is not None + and token is not None + and response_cost is not None + ): # log customer spend event = WebhookEvent( spend=response_cost, @@ -941,7 +966,10 @@ class SlackAlerting(CustomLogger): ) # send minor alert await self.send_alert( - message=msg, level="Medium", alert_type="outage_alerts" + message=msg, + level="Medium", + alert_type="outage_alerts", + alerting_metadata={}, ) # set to true outage_value["minor_alert_sent"] = True @@ -963,7 +991,12 @@ class SlackAlerting(CustomLogger): ) # send minor alert - await self.send_alert(message=msg, level="High", alert_type="outage_alerts") + await self.send_alert( + message=msg, + level="High", + alert_type="outage_alerts", + alerting_metadata={}, + ) # set to true outage_value["major_alert_sent"] = True @@ -1062,7 +1095,10 @@ class SlackAlerting(CustomLogger): ) # send minor alert await self.send_alert( - message=msg, level="Medium", alert_type="outage_alerts" + message=msg, + level="Medium", + alert_type="outage_alerts", + alerting_metadata={}, ) # set to true outage_value["minor_alert_sent"] = True @@ -1081,7 +1117,10 @@ class SlackAlerting(CustomLogger): ) # send minor alert await self.send_alert( - message=msg, level="High", alert_type="outage_alerts" + message=msg, + level="High", + alert_type="outage_alerts", + alerting_metadata={}, ) # set to true outage_value["major_alert_sent"] = True @@ -1143,7 +1182,10 @@ Model Info: """ alert_val = self.send_alert( - message=message, level="Low", alert_type="new_model_added" + message=message, + level="Low", + alert_type="new_model_added", + alerting_metadata={}, ) if alert_val is not None and asyncio.iscoroutine(alert_val): @@ -1159,6 +1201,9 @@ Model Info: Currently only implemented for budget alerts Returns -> True if sent, False if not. + + Raises Exception + - if WEBHOOK_URL is not set """ webhook_url = os.getenv("WEBHOOK_URL", None) @@ -1297,7 +1342,9 @@ Model Info: verbose_proxy_logger.error("Error sending email alert %s", str(e)) return False - async def send_email_alert_using_smtp(self, webhook_event: WebhookEvent) -> bool: + async def send_email_alert_using_smtp( + self, webhook_event: WebhookEvent, alert_type: str + ) -> bool: """ Sends structured Email alert to an SMTP server @@ -1306,7 +1353,6 @@ Model Info: Returns -> True if sent, False if not. """ from litellm.proxy.utils import send_email - from litellm.proxy.proxy_server import premium_user, prisma_client email_logo_url = os.getenv( @@ -1360,6 +1406,10 @@ Model Info: subject=email_event["subject"], html=email_event["html"], ) + if webhook_event.event_group == "team": + from litellm.integrations.email_alerting import send_team_budget_alert + + await send_team_budget_alert(webhook_event=webhook_event) return False @@ -1368,6 +1418,7 @@ Model Info: message: str, level: Literal["Low", "Medium", "High"], alert_type: Literal[AlertType], + alerting_metadata: dict, user_info: Optional[WebhookEvent] = None, **kwargs, ): @@ -1401,7 +1452,9 @@ Model Info: and user_info is not None ): # only send budget alerts over Email - await self.send_email_alert_using_smtp(webhook_event=user_info) + await self.send_email_alert_using_smtp( + webhook_event=user_info, alert_type=alert_type + ) if "slack" not in self.alerting: return @@ -1425,6 +1478,9 @@ Model Info: if kwargs: for key, value in kwargs.items(): formatted_message += f"\n\n{key}: `{value}`\n\n" + if alerting_metadata: + for key, value in alerting_metadata.items(): + formatted_message += f"\n\n*Alerting Metadata*: \n{key}: `{value}`\n\n" if _proxy_base_url is not None: formatted_message += f"\n\nProxy URL: `{_proxy_base_url}`" @@ -1440,7 +1496,7 @@ Model Info: slack_webhook_url = os.getenv("SLACK_WEBHOOK_URL", None) if slack_webhook_url is None: - raise Exception("Missing SLACK_WEBHOOK_URL from environment") + raise ValueError("Missing SLACK_WEBHOOK_URL from environment") payload = {"text": formatted_message} headers = {"Content-type": "application/json"} @@ -1453,7 +1509,7 @@ Model Info: pass else: verbose_proxy_logger.debug( - "Error sending slack alert. Error=", response.text + "Error sending slack alert. Error={}".format(response.text) ) async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): @@ -1622,6 +1678,7 @@ Model Info: message=_weekly_spend_message, level="Low", alert_type="spend_reports", + alerting_metadata={}, ) except Exception as e: verbose_proxy_logger.error("Error sending weekly spend report", e) @@ -1673,6 +1730,7 @@ Model Info: message=_spend_message, level="Low", alert_type="spend_reports", + alerting_metadata={}, ) except Exception as e: verbose_proxy_logger.error("Error sending weekly spend report", e) diff --git a/litellm/litellm_core_utils/core_helpers.py b/litellm/litellm_core_utils/core_helpers.py new file mode 100644 index 00000000000..7b911895d10 --- /dev/null +++ b/litellm/litellm_core_utils/core_helpers.py @@ -0,0 +1,41 @@ +# What is this? +## Helper utilities for the model response objects + + +def map_finish_reason( + finish_reason: str, +): # openai supports 5 stop sequences - 'stop', 'length', 'function_call', 'content_filter', 'null' + # anthropic mapping + if finish_reason == "stop_sequence": + return "stop" + # cohere mapping - https://docs.cohere.com/reference/generate + elif finish_reason == "COMPLETE": + return "stop" + elif finish_reason == "MAX_TOKENS": # cohere + vertex ai + return "length" + elif finish_reason == "ERROR_TOXIC": + return "content_filter" + elif ( + finish_reason == "ERROR" + ): # openai currently doesn't support an 'error' finish reason + return "stop" + # huggingface mapping https://huggingface.github.io/text-generation-inference/#/Text%20Generation%20Inference/generate_stream + elif finish_reason == "eos_token" or finish_reason == "stop_sequence": + return "stop" + elif ( + finish_reason == "FINISH_REASON_UNSPECIFIED" or finish_reason == "STOP" + ): # vertex ai - got from running `print(dir(response_obj.candidates[0].finish_reason))`: ['FINISH_REASON_UNSPECIFIED', 'MAX_TOKENS', 'OTHER', 'RECITATION', 'SAFETY', 'STOP',] + return "stop" + elif finish_reason == "SAFETY": # vertex ai + return "content_filter" + elif finish_reason == "STOP": # vertex ai + return "stop" + elif finish_reason == "end_turn" or finish_reason == "stop_sequence": # anthropic + return "stop" + elif finish_reason == "max_tokens": # anthropic + return "length" + elif finish_reason == "tool_use": # anthropic + return "tool_calls" + elif finish_reason == "content_filtered": + return "content_filter" + return finish_reason diff --git a/litellm/litellm_core_utils/litellm_logging.py b/litellm/litellm_core_utils/litellm_logging.py new file mode 100644 index 00000000000..f99303abb48 --- /dev/null +++ b/litellm/litellm_core_utils/litellm_logging.py @@ -0,0 +1,1780 @@ +# What is this? +## Common Utility file for Logging handler +# Logging function -> log the exact model details + what's being sent | Non-Blocking +from litellm.types.utils import CallTypes +from typing import Optional +import datetime +from litellm import ( + verbose_logger, + json_logs, + log_raw_request_response, + turn_off_message_logging, +) +import traceback +import litellm +import copy +import sys +import uuid +import os +from litellm.integrations.custom_logger import CustomLogger +import json +import time +from litellm.litellm_core_utils.redact_messages import ( + redact_message_input_output_from_logging, +) +from litellm.utils import ( + _get_base_model_from_metadata, + supabaseClient, + liteDebuggerClient, + promptLayerLogger, + weightsBiasesLogger, + langsmithLogger, + logfireLogger, + capture_exception, + add_breadcrumb, + lunaryLogger, + prometheusLogger, + print_verbose, + customLogger, + prompt_token_calculator, +) +from litellm.types.utils import ( + ModelResponse, + EmbeddingResponse, + ImageResponse, + TranscriptionResponse, + TextCompletionResponse, +) +import subprocess +from ..integrations.traceloop import TraceloopLogger +from ..integrations.athina import AthinaLogger +from ..integrations.helicone import HeliconeLogger +from ..integrations.aispend import AISpendLogger +from ..integrations.berrispend import BerriSpendLogger +from ..integrations.supabase import Supabase +from ..integrations.lunary import LunaryLogger +from ..integrations.prompt_layer import PromptLayerLogger +from ..integrations.langsmith import LangsmithLogger +from ..integrations.logfire_logger import LogfireLogger, LogfireLevel +from ..integrations.weights_biases import WeightsBiasesLogger +from ..integrations.custom_logger import CustomLogger +from ..integrations.langfuse import LangFuseLogger +from ..integrations.openmeter import OpenMeterLogger +from ..integrations.lago import LagoLogger +from ..integrations.datadog import DataDogLogger +from ..integrations.prometheus import PrometheusLogger +from ..integrations.prometheus_services import PrometheusServicesLogger +from ..integrations.dynamodb import DyanmoDBLogger +from ..integrations.s3 import S3Logger +from ..integrations.clickhouse import ClickhouseLogger +from ..integrations.greenscale import GreenscaleLogger +from ..integrations.litedebugger import LiteDebugger + + +class Logging: + global supabaseClient, liteDebuggerClient, promptLayerLogger, weightsBiasesLogger, langsmithLogger, logfireLogger, capture_exception, add_breadcrumb, lunaryLogger, logfireLogger, prometheusLogger, slack_app + custom_pricing: bool = False + stream_options = None + + def __init__( + self, + model, + messages, + stream, + call_type, + start_time, + litellm_call_id, + function_id, + dynamic_success_callbacks=None, + dynamic_failure_callbacks=None, + dynamic_async_success_callbacks=None, + langfuse_public_key=None, + langfuse_secret=None, + ): + if call_type not in [item.value for item in CallTypes]: + allowed_values = ", ".join([item.value for item in CallTypes]) + raise ValueError( + f"Invalid call_type {call_type}. Allowed values: {allowed_values}" + ) + if messages is not None: + if isinstance(messages, str): + messages = [ + {"role": "user", "content": messages} + ] # convert text completion input to the chat completion format + elif ( + isinstance(messages, list) + and len(messages) > 0 + and isinstance(messages[0], str) + ): + new_messages = [] + for m in messages: + new_messages.append({"role": "user", "content": m}) + messages = new_messages + self.model = model + self.messages = messages + self.stream = stream + self.start_time = start_time # log the call start time + self.call_type = call_type + self.litellm_call_id = litellm_call_id + self.function_id = function_id + self.streaming_chunks = [] # for generating complete stream response + self.sync_streaming_chunks = [] # for generating complete stream response + self.model_call_details = {} + self.dynamic_input_callbacks = [] # [TODO] callbacks set for just that call + self.dynamic_failure_callbacks = dynamic_failure_callbacks + self.dynamic_success_callbacks = ( + dynamic_success_callbacks # callbacks set for just that call + ) + self.dynamic_async_success_callbacks = ( + dynamic_async_success_callbacks # callbacks set for just that call + ) + ## DYNAMIC LANGFUSE KEYS ## + self.langfuse_public_key = langfuse_public_key + self.langfuse_secret = langfuse_secret + ## TIME TO FIRST TOKEN LOGGING ## + self.completion_start_time: Optional[datetime.datetime] = None + + def update_environment_variables( + self, model, user, optional_params, litellm_params, **additional_params + ): + self.optional_params = optional_params + self.model = model + self.user = user + self.litellm_params = litellm_params + self.logger_fn = litellm_params.get("logger_fn", None) + verbose_logger.debug(f"self.optional_params: {self.optional_params}") + + self.model_call_details = { + "model": self.model, + "messages": self.messages, + "optional_params": self.optional_params, + "litellm_params": self.litellm_params, + "start_time": self.start_time, + "stream": self.stream, + "user": user, + "call_type": str(self.call_type), + "litellm_call_id": self.litellm_call_id, + "completion_start_time": self.completion_start_time, + **self.optional_params, + **additional_params, + } + + ## check if stream options is set ## - used by CustomStreamWrapper for easy instrumentation + if "stream_options" in additional_params: + self.stream_options = additional_params["stream_options"] + ## check if custom pricing set ## + if ( + litellm_params.get("input_cost_per_token") is not None + or litellm_params.get("input_cost_per_second") is not None + or litellm_params.get("output_cost_per_token") is not None + or litellm_params.get("output_cost_per_second") is not None + ): + self.custom_pricing = True + + def _pre_call(self, input, api_key, model=None, additional_args={}): + """ + Common helper function across the sync + async pre-call function + """ + self.model_call_details["input"] = input + self.model_call_details["api_key"] = api_key + self.model_call_details["additional_args"] = additional_args + self.model_call_details["log_event_type"] = "pre_api_call" + if ( + model + ): # if model name was changes pre-call, overwrite the initial model call name with the new one + self.model_call_details["model"] = model + + def pre_call(self, input, api_key, model=None, additional_args={}): + # Log the exact input to the LLM API + litellm.error_logs["PRE_CALL"] = locals() + try: + self._pre_call( + input=input, + api_key=api_key, + model=model, + additional_args=additional_args, + ) + + # User Logging -> if you pass in a custom logging function + headers = additional_args.get("headers", {}) + if headers is None: + headers = {} + data = additional_args.get("complete_input_dict", {}) + api_base = additional_args.get("api_base", "") + self.model_call_details["litellm_params"]["api_base"] = str( + api_base + ) # used for alerting + masked_headers = { + k: ( + (v[:-44] + "*" * 44) + if (isinstance(v, str) and len(v) > 44) + else "*****" + ) + for k, v in headers.items() + } + formatted_headers = " ".join( + [f"-H '{k}: {v}'" for k, v in masked_headers.items()] + ) + + verbose_logger.debug(f"PRE-API-CALL ADDITIONAL ARGS: {additional_args}") + + curl_command = "\n\nPOST Request Sent from LiteLLM:\n" + curl_command += "curl -X POST \\\n" + curl_command += f"{api_base} \\\n" + curl_command += ( + f"{formatted_headers} \\\n" if formatted_headers.strip() != "" else "" + ) + curl_command += f"-d '{str(data)}'\n" + if additional_args.get("request_str", None) is not None: + # print the sagemaker / bedrock client request + curl_command = "\nRequest Sent from LiteLLM:\n" + curl_command += additional_args.get("request_str", None) + elif api_base == "": + curl_command = self.model_call_details + + if json_logs: + verbose_logger.debug( + "POST Request Sent from LiteLLM", + extra={"api_base": {api_base}, **masked_headers}, + ) + else: + verbose_logger.debug(f"\033[92m{curl_command}\033[0m\n") + # log raw request to provider (like LangFuse) -- if opted in. + if log_raw_request_response is True: + try: + # [Non-blocking Extra Debug Information in metadata] + _litellm_params = self.model_call_details.get("litellm_params", {}) + _metadata = _litellm_params.get("metadata", {}) or {} + if ( + turn_off_message_logging is not None + and turn_off_message_logging is True + ): + _metadata["raw_request"] = ( + "redacted by litellm. \ + 'litellm.turn_off_message_logging=True'" + ) + else: + _metadata["raw_request"] = str(curl_command) + except Exception as e: + _metadata["raw_request"] = ( + "Unable to Log \ + raw request: {}".format( + str(e) + ) + ) + if self.logger_fn and callable(self.logger_fn): + try: + self.logger_fn( + self.model_call_details + ) # Expectation: any logger function passed in by the user should accept a dict object + except Exception as e: + verbose_logger.error( + "LiteLLM.LoggingError: [Non-Blocking] Exception occurred while logging {}\n{}".format( + str(e), traceback.format_exc() + ) + ) + # Input Integration Logging -> If you want to log the fact that an attempt to call the model was made + callbacks = litellm.input_callback + self.dynamic_input_callbacks + for callback in callbacks: + try: + if callback == "supabase": + verbose_logger.debug("reaches supabase for logging!") + model = self.model_call_details["model"] + messages = self.model_call_details["input"] + verbose_logger.debug(f"supabaseClient: {supabaseClient}") + supabaseClient.input_log_event( + model=model, + messages=messages, + end_user=self.model_call_details.get("user", "default"), + litellm_call_id=self.litellm_params["litellm_call_id"], + print_verbose=print_verbose, + ) + elif callback == "sentry" and add_breadcrumb: + try: + details_to_log = copy.deepcopy(self.model_call_details) + except: + details_to_log = self.model_call_details + if litellm.turn_off_message_logging: + # make a copy of the _model_Call_details and log it + details_to_log.pop("messages", None) + details_to_log.pop("input", None) + details_to_log.pop("prompt", None) + + add_breadcrumb( + category="litellm.llm_call", + message=f"Model Call Details pre-call: {details_to_log}", + level="info", + ) + elif isinstance(callback, CustomLogger): # custom logger class + callback.log_pre_api_call( + model=self.model, + messages=self.messages, + kwargs=self.model_call_details, + ) + elif callable(callback): # custom logger functions + customLogger.log_input_event( + model=self.model, + messages=self.messages, + kwargs=self.model_call_details, + print_verbose=print_verbose, + callback_func=callback, + ) + except Exception as e: + verbose_logger.error( + "litellm.Logging.pre_call(): Exception occured - {}\n{}".format( + str(e), traceback.format_exc() + ) + ) + verbose_logger.debug( + f"LiteLLM.Logging: is sentry capture exception initialized {capture_exception}" + ) + if capture_exception: # log this error to sentry for debugging + capture_exception(e) + except Exception: + verbose_logger.error( + "LiteLLM.LoggingError: [Non-Blocking] Exception occurred while logging {}\n{}".format( + str(e), traceback.format_exc() + ) + ) + verbose_logger.error( + f"LiteLLM.Logging: is sentry capture exception initialized {capture_exception}" + ) + if capture_exception: # log this error to sentry for debugging + capture_exception(e) + + def post_call( + self, original_response, input=None, api_key=None, additional_args={} + ): + # Log the exact result from the LLM API, for streaming - log the type of response received + litellm.error_logs["POST_CALL"] = locals() + if isinstance(original_response, dict): + original_response = json.dumps(original_response) + try: + self.model_call_details["input"] = input + self.model_call_details["api_key"] = api_key + self.model_call_details["original_response"] = original_response + self.model_call_details["additional_args"] = additional_args + self.model_call_details["log_event_type"] = "post_api_call" + + verbose_logger.debug( + "RAW RESPONSE:\n{}\n\n".format( + self.model_call_details.get( + "original_response", self.model_call_details + ) + ), + ) + if self.logger_fn and callable(self.logger_fn): + try: + self.logger_fn( + self.model_call_details + ) # Expectation: any logger function passed in by the user should accept a dict object + except Exception as e: + verbose_logger.debug( + "LiteLLM.LoggingError: [Non-Blocking] Exception occurred while logging {}\n{}".format( + str(e), traceback.format_exc() + ) + ) + original_response = redact_message_input_output_from_logging( + litellm_logging_obj=self, result=original_response + ) + # Input Integration Logging -> If you want to log the fact that an attempt to call the model was made + + callbacks = litellm.input_callback + self.dynamic_input_callbacks + for callback in callbacks: + try: + if callback == "sentry" and add_breadcrumb: + verbose_logger.debug("reaches sentry breadcrumbing") + try: + details_to_log = copy.deepcopy(self.model_call_details) + except: + details_to_log = self.model_call_details + if litellm.turn_off_message_logging: + # make a copy of the _model_Call_details and log it + details_to_log.pop("messages", None) + details_to_log.pop("input", None) + details_to_log.pop("prompt", None) + + add_breadcrumb( + category="litellm.llm_call", + message=f"Model Call Details post-call: {details_to_log}", + level="info", + ) + elif isinstance(callback, CustomLogger): # custom logger class + callback.log_post_api_call( + kwargs=self.model_call_details, + response_obj=None, + start_time=self.start_time, + end_time=None, + ) + except Exception as e: + verbose_logger.error( + "LiteLLM.LoggingError: [Non-Blocking] Exception occurred while post-call logging with integrations {}\n{}".format( + str(e), traceback.format_exc() + ) + ) + verbose_logger.debug( + f"LiteLLM.Logging: is sentry capture exception initialized {capture_exception}" + ) + if capture_exception: # log this error to sentry for debugging + capture_exception(e) + except Exception as e: + verbose_logger.error( + "LiteLLM.LoggingError: [Non-Blocking] Exception occurred while logging {}\n{}".format( + str(e), traceback.format_exc() + ) + ) + + def _success_handler_helper_fn( + self, result=None, start_time=None, end_time=None, cache_hit=None + ): + try: + if start_time is None: + start_time = self.start_time + if end_time is None: + end_time = datetime.datetime.now() + if self.completion_start_time is None: + self.completion_start_time = end_time + self.model_call_details["completion_start_time"] = ( + self.completion_start_time + ) + self.model_call_details["log_event_type"] = "successful_api_call" + self.model_call_details["end_time"] = end_time + self.model_call_details["cache_hit"] = cache_hit + ## if model in model cost map - log the response cost + ## else set cost to None + verbose_logger.debug(f"Model={self.model};") + if ( + result is not None + and ( + isinstance(result, ModelResponse) + or isinstance(result, EmbeddingResponse) + or isinstance(result, ImageResponse) + or isinstance(result, TranscriptionResponse) + or isinstance(result, TextCompletionResponse) + ) + and self.stream != True + ): # handle streaming separately + self.model_call_details["response_cost"] = ( + litellm.response_cost_calculator( + response_object=result, + model=self.model, + cache_hit=self.model_call_details.get("cache_hit", False), + custom_llm_provider=self.model_call_details.get( + "custom_llm_provider", None + ), + base_model=_get_base_model_from_metadata( + model_call_details=self.model_call_details + ), + call_type=self.call_type, + optional_params=self.optional_params, + ) + ) + else: # streaming chunks + image gen. + self.model_call_details["response_cost"] = None + + if ( + litellm.max_budget + and self.stream == False + and result is not None + and "content" in result + ): + time_diff = (end_time - start_time).total_seconds() + float_diff = float(time_diff) + litellm._current_cost += litellm.completion_cost( + model=self.model, + prompt="", + completion=result["content"], + total_time=float_diff, + ) + + return start_time, end_time, result + except Exception as e: + raise Exception(f"[Non-Blocking] LiteLLM.Success_Call Error: {str(e)}") + + def success_handler( + self, result=None, start_time=None, end_time=None, cache_hit=None, **kwargs + ): + verbose_logger.debug( + f"Logging Details LiteLLM-Success Call: Cache_hit={cache_hit}" + ) + start_time, end_time, result = self._success_handler_helper_fn( + start_time=start_time, + end_time=end_time, + result=result, + cache_hit=cache_hit, + ) + # print(f"original response in success handler: {self.model_call_details['original_response']}") + try: + verbose_logger.debug(f"success callbacks: {litellm.success_callback}") + ## BUILD COMPLETE STREAMED RESPONSE + complete_streaming_response = None + if self.stream and isinstance(result, ModelResponse): + if ( + result.choices[0].finish_reason is not None + ): # if it's the last chunk + self.sync_streaming_chunks.append(result) + # print_verbose(f"final set of received chunks: {self.sync_streaming_chunks}") + try: + complete_streaming_response = litellm.stream_chunk_builder( + self.sync_streaming_chunks, + messages=self.model_call_details.get("messages", None), + start_time=start_time, + end_time=end_time, + ) + except Exception as e: + verbose_logger.error( + "LiteLLM.LoggingError: [Non-Blocking] Exception occurred while building complete streaming response in success logging {}\n{}".format( + str(e), traceback.format_exc() + ), + log_level="ERROR", + ) + complete_streaming_response = None + else: + self.sync_streaming_chunks.append(result) + + if complete_streaming_response is not None: + verbose_logger.debug( + f"Logging Details LiteLLM-Success Call streaming complete" + ) + self.model_call_details["complete_streaming_response"] = ( + complete_streaming_response + ) + self.model_call_details["response_cost"] = ( + litellm.response_cost_calculator( + response_object=complete_streaming_response, + model=self.model, + cache_hit=self.model_call_details.get("cache_hit", False), + custom_llm_provider=self.model_call_details.get( + "custom_llm_provider", None + ), + base_model=_get_base_model_from_metadata( + model_call_details=self.model_call_details + ), + call_type=self.call_type, + optional_params=self.optional_params, + ) + ) + if self.dynamic_success_callbacks is not None and isinstance( + self.dynamic_success_callbacks, list + ): + callbacks = self.dynamic_success_callbacks + ## keep the internal functions ## + for callback in litellm.success_callback: + if ( + isinstance(callback, CustomLogger) + and "_PROXY_" in callback.__class__.__name__ + ): + callbacks.append(callback) + else: + callbacks = litellm.success_callback + + result = redact_message_input_output_from_logging( + result=result, litellm_logging_obj=self + ) + + for callback in callbacks: + try: + litellm_params = self.model_call_details.get("litellm_params", {}) + if litellm_params.get("no-log", False) == True: + # proxy cost tracking cal backs should run + if not ( + isinstance(callback, CustomLogger) + and "_PROXY_" in callback.__class__.__name__ + ): + print_verbose("no-log request, skipping logging") + continue + if callback == "lite_debugger": + print_verbose("reaches lite_debugger for logging!") + print_verbose(f"liteDebuggerClient: {liteDebuggerClient}") + print_verbose( + f"liteDebuggerClient details function {self.call_type} and stream set to {self.stream}" + ) + liteDebuggerClient.log_event( + end_user=kwargs.get("user", "default"), + response_obj=result, + start_time=start_time, + end_time=end_time, + litellm_call_id=self.litellm_call_id, + print_verbose=print_verbose, + call_type=self.call_type, + stream=self.stream, + ) + if callback == "promptlayer": + print_verbose("reaches promptlayer for logging!") + promptLayerLogger.log_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + ) + if callback == "supabase": + print_verbose("reaches supabase for logging!") + kwargs = self.model_call_details + + # this only logs streaming once, complete_streaming_response exists i.e when stream ends + if self.stream: + if "complete_streaming_response" not in kwargs: + continue + else: + print_verbose("reaches supabase for streaming logging!") + result = kwargs["complete_streaming_response"] + + model = kwargs["model"] + messages = kwargs["messages"] + optional_params = kwargs.get("optional_params", {}) + litellm_params = kwargs.get("litellm_params", {}) + supabaseClient.log_event( + model=model, + messages=messages, + end_user=optional_params.get("user", "default"), + response_obj=result, + start_time=start_time, + end_time=end_time, + litellm_call_id=litellm_params.get( + "litellm_call_id", str(uuid.uuid4()) + ), + print_verbose=print_verbose, + ) + if callback == "wandb": + print_verbose("reaches wandb for logging!") + weightsBiasesLogger.log_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + ) + if callback == "langsmith": + print_verbose("reaches langsmith for logging!") + if self.stream: + if "complete_streaming_response" not in kwargs: + continue + else: + print_verbose( + "reaches langsmith for streaming logging!" + ) + result = kwargs["complete_streaming_response"] + langsmithLogger.log_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + ) + if callback == "logfire": + global logfireLogger + verbose_logger.debug("reaches logfire for success logging!") + kwargs = {} + for k, v in self.model_call_details.items(): + if ( + k != "original_response" + ): # copy.deepcopy raises errors as this could be a coroutine + kwargs[k] = v + + # this only logs streaming once, complete_streaming_response exists i.e when stream ends + if self.stream: + if "complete_streaming_response" not in kwargs: + continue + else: + print_verbose("reaches logfire for streaming logging!") + result = kwargs["complete_streaming_response"] + + logfireLogger.log_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + level=LogfireLevel.INFO.value, + ) + + if callback == "lunary": + print_verbose("reaches lunary for logging!") + model = self.model + kwargs = self.model_call_details + + input = kwargs.get("messages", kwargs.get("input", None)) + + type = ( + "embed" + if self.call_type == CallTypes.embedding.value + else "llm" + ) + + # this only logs streaming once, complete_streaming_response exists i.e when stream ends + if self.stream: + if "complete_streaming_response" not in kwargs: + continue + else: + result = kwargs["complete_streaming_response"] + + lunaryLogger.log_event( + type=type, + kwargs=kwargs, + event="end", + model=model, + input=input, + user_id=kwargs.get("user", None), + # user_props=self.model_call_details.get("user_props", None), + extra=kwargs.get("optional_params", {}), + response_obj=result, + start_time=start_time, + end_time=end_time, + run_id=self.litellm_call_id, + print_verbose=print_verbose, + ) + if callback == "helicone": + print_verbose("reaches helicone for logging!") + model = self.model + messages = self.model_call_details["input"] + heliconeLogger.log_success( + model=model, + messages=messages, + response_obj=result, + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + ) + if callback == "langfuse": + global langFuseLogger + verbose_logger.debug("reaches langfuse for success logging!") + kwargs = {} + for k, v in self.model_call_details.items(): + if ( + k != "original_response" + ): # copy.deepcopy raises errors as this could be a coroutine + kwargs[k] = v + # this only logs streaming once, complete_streaming_response exists i.e when stream ends + if self.stream: + verbose_logger.debug( + f"is complete_streaming_response in kwargs: {kwargs.get('complete_streaming_response', None)}" + ) + if complete_streaming_response is None: + continue + else: + print_verbose("reaches langfuse for streaming logging!") + result = kwargs["complete_streaming_response"] + if langFuseLogger is None or ( + ( + self.langfuse_public_key is not None + and self.langfuse_public_key + != langFuseLogger.public_key + ) + and ( + self.langfuse_public_key is not None + and self.langfuse_public_key + != langFuseLogger.public_key + ) + ): + langFuseLogger = LangFuseLogger( + langfuse_public_key=self.langfuse_public_key, + langfuse_secret=self.langfuse_secret, + ) + langFuseLogger.log_event( + kwargs=kwargs, + response_obj=result, + start_time=start_time, + end_time=end_time, + user_id=kwargs.get("user", None), + print_verbose=print_verbose, + ) + if callback == "datadog": + global dataDogLogger + verbose_logger.debug("reaches datadog for success logging!") + kwargs = {} + for k, v in self.model_call_details.items(): + if ( + k != "original_response" + ): # copy.deepcopy raises errors as this could be a coroutine + kwargs[k] = v + # this only logs streaming once, complete_streaming_response exists i.e when stream ends + if self.stream: + verbose_logger.debug( + f"datadog: is complete_streaming_response in kwargs: {kwargs.get('complete_streaming_response', None)}" + ) + if complete_streaming_response is None: + continue + else: + print_verbose("reaches datadog for streaming logging!") + result = kwargs["complete_streaming_response"] + dataDogLogger.log_event( + kwargs=kwargs, + response_obj=result, + start_time=start_time, + end_time=end_time, + user_id=kwargs.get("user", None), + print_verbose=print_verbose, + ) + if callback == "prometheus": + verbose_logger.debug("reaches prometheus for success logging!") + kwargs = {} + for k, v in self.model_call_details.items(): + if ( + k != "original_response" + ): # copy.deepcopy raises errors as this could be a coroutine + kwargs[k] = v + # this only logs streaming once, complete_streaming_response exists i.e when stream ends + if self.stream: + verbose_logger.debug( + f"prometheus: is complete_streaming_response in kwargs: {kwargs.get('complete_streaming_response', None)}" + ) + if complete_streaming_response is None: + continue + else: + print_verbose( + "reaches prometheus for streaming logging!" + ) + result = kwargs["complete_streaming_response"] + prometheusLogger.log_event( + kwargs=kwargs, + response_obj=result, + start_time=start_time, + end_time=end_time, + user_id=kwargs.get("user", None), + print_verbose=print_verbose, + ) + if callback == "generic": + global genericAPILogger + verbose_logger.debug("reaches langfuse for success logging!") + kwargs = {} + for k, v in self.model_call_details.items(): + if ( + k != "original_response" + ): # copy.deepcopy raises errors as this could be a coroutine + kwargs[k] = v + # this only logs streaming once, complete_streaming_response exists i.e when stream ends + if self.stream: + verbose_logger.debug( + f"is complete_streaming_response in kwargs: {kwargs.get('complete_streaming_response', None)}" + ) + if complete_streaming_response is None: + continue + else: + print_verbose("reaches langfuse for streaming logging!") + result = kwargs["complete_streaming_response"] + if genericAPILogger is None: + genericAPILogger = GenericAPILogger() + genericAPILogger.log_event( + kwargs=kwargs, + response_obj=result, + start_time=start_time, + end_time=end_time, + user_id=kwargs.get("user", None), + print_verbose=print_verbose, + ) + if callback == "clickhouse": + global clickHouseLogger + verbose_logger.debug("reaches clickhouse for success logging!") + kwargs = {} + for k, v in self.model_call_details.items(): + if ( + k != "original_response" + ): # copy.deepcopy raises errors as this could be a coroutine + kwargs[k] = v + # this only logs streaming once, complete_streaming_response exists i.e when stream ends + if self.stream: + verbose_logger.debug( + f"is complete_streaming_response in kwargs: {kwargs.get('complete_streaming_response', None)}" + ) + if complete_streaming_response is None: + continue + else: + print_verbose( + "reaches clickhouse for streaming logging!" + ) + result = kwargs["complete_streaming_response"] + if clickHouseLogger is None: + clickHouseLogger = ClickhouseLogger() + clickHouseLogger.log_event( + kwargs=kwargs, + response_obj=result, + start_time=start_time, + end_time=end_time, + user_id=kwargs.get("user", None), + print_verbose=print_verbose, + ) + if callback == "greenscale": + kwargs = {} + for k, v in self.model_call_details.items(): + if ( + k != "original_response" + ): # copy.deepcopy raises errors as this could be a coroutine + kwargs[k] = v + # this only logs streaming once, complete_streaming_response exists i.e when stream ends + if self.stream: + verbose_logger.debug( + f"is complete_streaming_response in kwargs: {kwargs.get('complete_streaming_response', None)}" + ) + if complete_streaming_response is None: + continue + else: + print_verbose( + "reaches greenscale for streaming logging!" + ) + result = kwargs["complete_streaming_response"] + + greenscaleLogger.log_event( + kwargs=kwargs, + response_obj=result, + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + ) + if callback == "cache" and litellm.cache is not None: + # this only logs streaming once, complete_streaming_response exists i.e when stream ends + print_verbose("success_callback: reaches cache for logging!") + kwargs = self.model_call_details + if self.stream: + if "complete_streaming_response" not in kwargs: + print_verbose( + f"success_callback: reaches cache for logging, there is no complete_streaming_response. Kwargs={kwargs}\n\n" + ) + pass + else: + print_verbose( + "success_callback: reaches cache for logging, there is a complete_streaming_response. Adding to cache" + ) + result = kwargs["complete_streaming_response"] + # only add to cache once we have a complete streaming response + litellm.cache.add_cache(result, **kwargs) + if callback == "athina": + deep_copy = {} + for k, v in self.model_call_details.items(): + deep_copy[k] = v + athinaLogger.log_event( + kwargs=deep_copy, + response_obj=result, + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + ) + if callback == "traceloop": + deep_copy = {} + for k, v in self.model_call_details.items(): + if k != "original_response": + deep_copy[k] = v + traceloopLogger.log_event( + kwargs=deep_copy, + response_obj=result, + start_time=start_time, + end_time=end_time, + user_id=kwargs.get("user", None), + print_verbose=print_verbose, + ) + if callback == "s3": + global s3Logger + if s3Logger is None: + s3Logger = S3Logger() + if self.stream: + if "complete_streaming_response" in self.model_call_details: + print_verbose( + "S3Logger Logger: Got Stream Event - Completed Stream Response" + ) + s3Logger.log_event( + kwargs=self.model_call_details, + response_obj=self.model_call_details[ + "complete_streaming_response" + ], + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + ) + else: + print_verbose( + "S3Logger Logger: Got Stream Event - No complete stream response as yet" + ) + else: + s3Logger.log_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + ) + if ( + callback == "openmeter" + and self.model_call_details.get("litellm_params", {}).get( + "acompletion", False + ) + == False + and self.model_call_details.get("litellm_params", {}).get( + "aembedding", False + ) + == False + and self.model_call_details.get("litellm_params", {}).get( + "aimage_generation", False + ) + == False + and self.model_call_details.get("litellm_params", {}).get( + "atranscription", False + ) + == False + ): + global openMeterLogger + if openMeterLogger is None: + print_verbose("Instantiates openmeter client") + openMeterLogger = OpenMeterLogger() + if self.stream and complete_streaming_response is None: + openMeterLogger.log_stream_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + ) + else: + if self.stream and complete_streaming_response: + self.model_call_details["complete_response"] = ( + self.model_call_details.get( + "complete_streaming_response", {} + ) + ) + result = self.model_call_details["complete_response"] + openMeterLogger.log_success_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + ) + + if ( + isinstance(callback, CustomLogger) + and self.model_call_details.get("litellm_params", {}).get( + "acompletion", False + ) + == False + and self.model_call_details.get("litellm_params", {}).get( + "aembedding", False + ) + == False + and self.model_call_details.get("litellm_params", {}).get( + "aimage_generation", False + ) + == False + and self.model_call_details.get("litellm_params", {}).get( + "atranscription", False + ) + == False + ): # custom logger class + if self.stream and complete_streaming_response is None: + callback.log_stream_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + ) + else: + if self.stream and complete_streaming_response: + self.model_call_details["complete_response"] = ( + self.model_call_details.get( + "complete_streaming_response", {} + ) + ) + result = self.model_call_details["complete_response"] + callback.log_success_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + ) + if ( + callable(callback) == True + and self.model_call_details.get("litellm_params", {}).get( + "acompletion", False + ) + == False + and self.model_call_details.get("litellm_params", {}).get( + "aembedding", False + ) + == False + and self.model_call_details.get("litellm_params", {}).get( + "aimage_generation", False + ) + == False + and self.model_call_details.get("litellm_params", {}).get( + "atranscription", False + ) + == False + ): # custom logger functions + print_verbose( + f"success callbacks: Running Custom Callback Function" + ) + customLogger.log_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + callback_func=callback, + ) + + except Exception as e: + print_verbose( + f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while success logging with integrations {traceback.format_exc()}" + ) + print_verbose( + f"LiteLLM.Logging: is sentry capture exception initialized {capture_exception}" + ) + if capture_exception: # log this error to sentry for debugging + capture_exception(e) + except: + verbose_logger.error( + "LiteLLM.LoggingError: [Non-Blocking] Exception occurred while success logging {}\n{}".format( + str(e), traceback.format_exc() + ), + ) + + async def async_success_handler( + self, result=None, start_time=None, end_time=None, cache_hit=None, **kwargs + ): + """ + Implementing async callbacks, to handle asyncio event loop issues when custom integrations need to use async functions. + """ + print_verbose("Logging Details LiteLLM-Async Success Call") + start_time, end_time, result = self._success_handler_helper_fn( + start_time=start_time, end_time=end_time, result=result, cache_hit=cache_hit + ) + ## BUILD COMPLETE STREAMED RESPONSE + complete_streaming_response = None + if self.stream: + if result.choices[0].finish_reason is not None: # if it's the last chunk + self.streaming_chunks.append(result) + # verbose_logger.debug(f"final set of received chunks: {self.streaming_chunks}") + try: + complete_streaming_response = litellm.stream_chunk_builder( + self.streaming_chunks, + messages=self.model_call_details.get("messages", None), + start_time=start_time, + end_time=end_time, + ) + except Exception as e: + print_verbose( + "Error occurred building stream chunk in success logging: {}\n{}".format( + str(e), traceback.format_exc() + ), + log_level="ERROR", + ) + complete_streaming_response = None + else: + self.streaming_chunks.append(result) + if complete_streaming_response is not None: + print_verbose("Async success callbacks: Got a complete streaming response") + self.model_call_details["async_complete_streaming_response"] = ( + complete_streaming_response + ) + try: + if self.model_call_details.get("cache_hit", False) is True: + self.model_call_details["response_cost"] = 0.0 + else: + # check if base_model set on azure + base_model = _get_base_model_from_metadata( + model_call_details=self.model_call_details + ) + # base_model defaults to None if not set on model_info + self.model_call_details["response_cost"] = litellm.completion_cost( + completion_response=complete_streaming_response, + model=base_model, + ) + verbose_logger.debug( + f"Model={self.model}; cost={self.model_call_details['response_cost']}" + ) + except litellm.NotFoundError as e: + verbose_logger.error( + f"Model={self.model} not found in completion cost map. Setting 'response_cost' to None" + ) + self.model_call_details["response_cost"] = None + + if self.dynamic_async_success_callbacks is not None and isinstance( + self.dynamic_async_success_callbacks, list + ): + callbacks = self.dynamic_async_success_callbacks + ## keep the internal functions ## + for callback in litellm._async_success_callback: + callback_name = "" + if isinstance(callback, CustomLogger): + callback_name = callback.__class__.__name__ + if callable(callback): + callback_name = callback.__name__ + if "_PROXY_" in callback_name: + callbacks.append(callback) + else: + callbacks = litellm._async_success_callback + + result = redact_message_input_output_from_logging( + result=result, litellm_logging_obj=self + ) + + for callback in callbacks: + # check if callback can run for this request + litellm_params = self.model_call_details.get("litellm_params", {}) + if litellm_params.get("no-log", False) == True: + # proxy cost tracking cal backs should run + if not ( + isinstance(callback, CustomLogger) + and "_PROXY_" in callback.__class__.__name__ + ): + print_verbose("no-log request, skipping logging") + continue + try: + if kwargs.get("no-log", False) == True: + print_verbose("no-log request, skipping logging") + continue + if callback == "cache" and litellm.cache is not None: + # set_cache once complete streaming response is built + print_verbose("async success_callback: reaches cache for logging!") + kwargs = self.model_call_details + if self.stream: + if "async_complete_streaming_response" not in kwargs: + print_verbose( + f"async success_callback: reaches cache for logging, there is no async_complete_streaming_response. Kwargs={kwargs}\n\n" + ) + pass + else: + print_verbose( + "async success_callback: reaches cache for logging, there is a async_complete_streaming_response. Adding to cache" + ) + result = kwargs["async_complete_streaming_response"] + # only add to cache once we have a complete streaming response + if litellm.cache is not None and not isinstance( + litellm.cache.cache, S3Cache + ): + await litellm.cache.async_add_cache(result, **kwargs) + else: + litellm.cache.add_cache(result, **kwargs) + if callback == "openmeter": + global openMeterLogger + if self.stream == True: + if ( + "async_complete_streaming_response" + in self.model_call_details + ): + await openMeterLogger.async_log_success_event( + kwargs=self.model_call_details, + response_obj=self.model_call_details[ + "async_complete_streaming_response" + ], + start_time=start_time, + end_time=end_time, + ) + else: + await openMeterLogger.async_log_stream_event( # [TODO]: move this to being an async log stream event function + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + ) + else: + await openMeterLogger.async_log_success_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + ) + if isinstance(callback, CustomLogger): # custom logger class + if self.stream == True: + if ( + "async_complete_streaming_response" + in self.model_call_details + ): + await callback.async_log_success_event( + kwargs=self.model_call_details, + response_obj=self.model_call_details[ + "async_complete_streaming_response" + ], + start_time=start_time, + end_time=end_time, + ) + else: + await callback.async_log_stream_event( # [TODO]: move this to being an async log stream event function + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + ) + else: + await callback.async_log_success_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + ) + if callable(callback): # custom logger functions + if self.stream: + if ( + "async_complete_streaming_response" + in self.model_call_details + ): + await customLogger.async_log_event( + kwargs=self.model_call_details, + response_obj=self.model_call_details[ + "async_complete_streaming_response" + ], + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + callback_func=callback, + ) + else: + await customLogger.async_log_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + callback_func=callback, + ) + if callback == "dynamodb": + global dynamoLogger + if dynamoLogger is None: + dynamoLogger = DyanmoDBLogger() + if self.stream: + if ( + "async_complete_streaming_response" + in self.model_call_details + ): + print_verbose( + "DynamoDB Logger: Got Stream Event - Completed Stream Response" + ) + await dynamoLogger._async_log_event( + kwargs=self.model_call_details, + response_obj=self.model_call_details[ + "async_complete_streaming_response" + ], + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + ) + else: + print_verbose( + "DynamoDB Logger: Got Stream Event - No complete stream response as yet" + ) + else: + await dynamoLogger._async_log_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + ) + except Exception as e: + verbose_logger.error( + f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while success logging {traceback.format_exc()}" + ) + pass + + def _failure_handler_helper_fn( + self, exception, traceback_exception, start_time=None, end_time=None + ): + if start_time is None: + start_time = self.start_time + if end_time is None: + end_time = datetime.datetime.now() + + # on some exceptions, model_call_details is not always initialized, this ensures that we still log those exceptions + if not hasattr(self, "model_call_details"): + self.model_call_details = {} + + self.model_call_details["log_event_type"] = "failed_api_call" + self.model_call_details["exception"] = exception + self.model_call_details["traceback_exception"] = traceback_exception + self.model_call_details["end_time"] = end_time + self.model_call_details.setdefault("original_response", None) + return start_time, end_time + + def failure_handler( + self, exception, traceback_exception, start_time=None, end_time=None + ): + verbose_logger.debug( + f"Logging Details LiteLLM-Failure Call: {litellm.failure_callback}" + ) + try: + start_time, end_time = self._failure_handler_helper_fn( + exception=exception, + traceback_exception=traceback_exception, + start_time=start_time, + end_time=end_time, + ) + callbacks = [] # init this to empty incase it's not created + + if self.dynamic_failure_callbacks is not None and isinstance( + self.dynamic_failure_callbacks, list + ): + callbacks = self.dynamic_failure_callbacks + ## keep the internal functions ## + for callback in litellm.failure_callback: + if ( + isinstance(callback, CustomLogger) + and "_PROXY_" in callback.__class__.__name__ + ): + callbacks.append(callback) + else: + callbacks = litellm.failure_callback + + result = None # result sent to all loggers, init this to None incase it's not created + + result = redact_message_input_output_from_logging( + result=result, litellm_logging_obj=self + ) + for callback in callbacks: + try: + if callback == "lite_debugger": + print_verbose("reaches lite_debugger for logging!") + print_verbose(f"liteDebuggerClient: {liteDebuggerClient}") + result = { + "model": self.model, + "created": time.time(), + "error": traceback_exception, + "usage": { + "prompt_tokens": prompt_token_calculator( + self.model, messages=self.messages + ), + "completion_tokens": 0, + }, + } + liteDebuggerClient.log_event( + model=self.model, + messages=self.messages, + end_user=self.model_call_details.get("user", "default"), + response_obj=result, + start_time=start_time, + end_time=end_time, + litellm_call_id=self.litellm_call_id, + print_verbose=print_verbose, + call_type=self.call_type, + stream=self.stream, + ) + if callback == "lunary": + print_verbose("reaches lunary for logging error!") + + model = self.model + + input = self.model_call_details["input"] + + _type = ( + "embed" + if self.call_type == CallTypes.embedding.value + else "llm" + ) + + lunaryLogger.log_event( + type=_type, + event="error", + user_id=self.model_call_details.get("user", "default"), + model=model, + input=input, + error=traceback_exception, + run_id=self.litellm_call_id, + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + ) + if callback == "sentry": + print_verbose("sending exception to sentry") + if capture_exception: + capture_exception(exception) + else: + print_verbose( + f"capture exception not initialized: {capture_exception}" + ) + elif callback == "supabase": + print_verbose("reaches supabase for logging!") + print_verbose(f"supabaseClient: {supabaseClient}") + result = { + "model": model, + "created": time.time(), + "error": traceback_exception, + "usage": { + "prompt_tokens": prompt_token_calculator( + model, messages=self.messages + ), + "completion_tokens": 0, + }, + } + supabaseClient.log_event( + model=self.model, + messages=self.messages, + end_user=self.model_call_details.get("user", "default"), + response_obj=result, + start_time=start_time, + end_time=end_time, + litellm_call_id=self.model_call_details["litellm_call_id"], + print_verbose=print_verbose, + ) + if callable(callback): # custom logger functions + customLogger.log_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + callback_func=callback, + ) + if ( + isinstance(callback, CustomLogger) + and self.model_call_details.get("litellm_params", {}).get( + "acompletion", False + ) + == False + and self.model_call_details.get("litellm_params", {}).get( + "aembedding", False + ) + == False + ): # custom logger class + callback.log_failure_event( + start_time=start_time, + end_time=end_time, + response_obj=result, + kwargs=self.model_call_details, + ) + if callback == "langfuse": + global langFuseLogger + verbose_logger.debug("reaches langfuse for logging failure") + kwargs = {} + for k, v in self.model_call_details.items(): + if ( + k != "original_response" + ): # copy.deepcopy raises errors as this could be a coroutine + kwargs[k] = v + # this only logs streaming once, complete_streaming_response exists i.e when stream ends + if langFuseLogger is None or ( + ( + self.langfuse_public_key is not None + and self.langfuse_public_key + != langFuseLogger.public_key + ) + and ( + self.langfuse_public_key is not None + and self.langfuse_public_key + != langFuseLogger.public_key + ) + ): + langFuseLogger = LangFuseLogger( + langfuse_public_key=self.langfuse_public_key, + langfuse_secret=self.langfuse_secret, + ) + langFuseLogger.log_event( + start_time=start_time, + end_time=end_time, + response_obj=None, + user_id=kwargs.get("user", None), + print_verbose=print_verbose, + status_message=str(exception), + level="ERROR", + kwargs=self.model_call_details, + ) + if callback == "traceloop": + traceloopLogger.log_event( + start_time=start_time, + end_time=end_time, + response_obj=None, + user_id=kwargs.get("user", None), + print_verbose=print_verbose, + status_message=str(exception), + level="ERROR", + kwargs=self.model_call_details, + ) + if callback == "prometheus": + global prometheusLogger + verbose_logger.debug("reaches prometheus for success logging!") + kwargs = {} + for k, v in self.model_call_details.items(): + if ( + k != "original_response" + ): # copy.deepcopy raises errors as this could be a coroutine + kwargs[k] = v + kwargs["exception"] = str(exception) + prometheusLogger.log_event( + kwargs=kwargs, + response_obj=result, + start_time=start_time, + end_time=end_time, + user_id=kwargs.get("user", None), + print_verbose=print_verbose, + ) + + if callback == "logfire": + verbose_logger.debug("reaches logfire for failure logging!") + kwargs = {} + for k, v in self.model_call_details.items(): + if ( + k != "original_response" + ): # copy.deepcopy raises errors as this could be a coroutine + kwargs[k] = v + kwargs["exception"] = exception + + logfireLogger.log_event( + kwargs=kwargs, + response_obj=result, + start_time=start_time, + end_time=end_time, + level=LogfireLevel.ERROR.value, + print_verbose=print_verbose, + ) + except Exception as e: + print_verbose( + f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while failure logging with integrations {str(e)}" + ) + print_verbose( + f"LiteLLM.Logging: is sentry capture exception initialized {capture_exception}" + ) + if capture_exception: # log this error to sentry for debugging + capture_exception(e) + except Exception as e: + verbose_logger.error( + "LiteLLM.LoggingError: [Non-Blocking] Exception occurred while failure logging {}\n{}".format( + str(e), traceback.format_exc() + ) + ) + + async def async_failure_handler( + self, exception, traceback_exception, start_time=None, end_time=None + ): + """ + Implementing async callbacks, to handle asyncio event loop issues when custom integrations need to use async functions. + """ + start_time, end_time = self._failure_handler_helper_fn( + exception=exception, + traceback_exception=traceback_exception, + start_time=start_time, + end_time=end_time, + ) + result = None # result sent to all loggers, init this to None incase it's not created + for callback in litellm._async_failure_callback: + try: + if isinstance(callback, CustomLogger): # custom logger class + await callback.async_log_failure_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + ) # type: ignore + if callable(callback): # custom logger functions + await customLogger.async_log_event( + kwargs=self.model_call_details, + response_obj=result, + start_time=start_time, + end_time=end_time, + print_verbose=print_verbose, + callback_func=callback, + ) + except Exception as e: + verbose_logger.error( + "LiteLLM.LoggingError: [Non-Blocking] Exception occurred while success \ + logging {}\n{}\nCallback={}".format( + str(e), traceback.format_exc(), callback + ) + ) + + +def set_callbacks(callback_list, function_id=None): + """ + Globally sets the callback client + """ + global sentry_sdk_instance, capture_exception, add_breadcrumb, posthog, slack_app, alerts_channel, traceloopLogger, athinaLogger, heliconeLogger, aispendLogger, berrispendLogger, supabaseClient, liteDebuggerClient, lunaryLogger, promptLayerLogger, langFuseLogger, customLogger, weightsBiasesLogger, langsmithLogger, logfireLogger, dynamoLogger, s3Logger, dataDogLogger, prometheusLogger, greenscaleLogger, openMeterLogger + + try: + for callback in callback_list: + print_verbose(f"init callback list: {callback}") + if callback == "sentry": + try: + import sentry_sdk + except ImportError: + print_verbose("Package 'sentry_sdk' is missing. Installing it...") + subprocess.check_call( + [sys.executable, "-m", "pip", "install", "sentry_sdk"] + ) + import sentry_sdk + sentry_sdk_instance = sentry_sdk + sentry_trace_rate = ( + os.environ.get("SENTRY_API_TRACE_RATE") + if "SENTRY_API_TRACE_RATE" in os.environ + else "1.0" + ) + sentry_sdk_instance.init( + dsn=os.environ.get("SENTRY_DSN"), + traces_sample_rate=float(sentry_trace_rate), + ) + capture_exception = sentry_sdk_instance.capture_exception + add_breadcrumb = sentry_sdk_instance.add_breadcrumb + elif callback == "posthog": + try: + from posthog import Posthog + except ImportError: + print_verbose("Package 'posthog' is missing. Installing it...") + subprocess.check_call( + [sys.executable, "-m", "pip", "install", "posthog"] + ) + from posthog import Posthog + posthog = Posthog( + project_api_key=os.environ.get("POSTHOG_API_KEY"), + host=os.environ.get("POSTHOG_API_URL"), + ) + elif callback == "slack": + try: + from slack_bolt import App + except ImportError: + print_verbose("Package 'slack_bolt' is missing. Installing it...") + subprocess.check_call( + [sys.executable, "-m", "pip", "install", "slack_bolt"] + ) + from slack_bolt import App + slack_app = App( + token=os.environ.get("SLACK_API_TOKEN"), + signing_secret=os.environ.get("SLACK_API_SECRET"), + ) + alerts_channel = os.environ["SLACK_API_CHANNEL"] + print_verbose(f"Initialized Slack App: {slack_app}") + elif callback == "traceloop": + traceloopLogger = TraceloopLogger() + elif callback == "athina": + athinaLogger = AthinaLogger() + print_verbose("Initialized Athina Logger") + elif callback == "helicone": + heliconeLogger = HeliconeLogger() + elif callback == "lunary": + lunaryLogger = LunaryLogger() + elif callback == "promptlayer": + promptLayerLogger = PromptLayerLogger() + elif callback == "langfuse": + langFuseLogger = LangFuseLogger() + elif callback == "openmeter": + openMeterLogger = OpenMeterLogger() + elif callback == "datadog": + dataDogLogger = DataDogLogger() + elif callback == "prometheus": + if prometheusLogger is None: + prometheusLogger = PrometheusLogger() + elif callback == "dynamodb": + dynamoLogger = DyanmoDBLogger() + elif callback == "s3": + s3Logger = S3Logger() + elif callback == "wandb": + weightsBiasesLogger = WeightsBiasesLogger() + elif callback == "langsmith": + langsmithLogger = LangsmithLogger() + elif callback == "logfire": + logfireLogger = LogfireLogger() + elif callback == "aispend": + aispendLogger = AISpendLogger() + elif callback == "berrispend": + berrispendLogger = BerriSpendLogger() + elif callback == "supabase": + print_verbose("instantiating supabase") + supabaseClient = Supabase() + elif callback == "greenscale": + greenscaleLogger = GreenscaleLogger() + print_verbose("Initialized Greenscale Logger") + elif callback == "lite_debugger": + print_verbose("instantiating lite_debugger") + if function_id: + liteDebuggerClient = LiteDebugger(email=function_id) + elif litellm.token: + liteDebuggerClient = LiteDebugger(email=litellm.token) + elif litellm.email: + liteDebuggerClient = LiteDebugger(email=litellm.email) + else: + liteDebuggerClient = LiteDebugger(email=str(uuid.uuid4())) + elif callable(callback): + customLogger = CustomLogger() + except Exception as e: + raise e diff --git a/litellm/litellm_core_utils/redact_messages.py b/litellm/litellm_core_utils/redact_messages.py new file mode 100644 index 00000000000..8f270d8bec0 --- /dev/null +++ b/litellm/litellm_core_utils/redact_messages.py @@ -0,0 +1,71 @@ +# +-----------------------------------------------+ +# | | +# | Give Feedback / Get Help | +# | https://github.com/BerriAI/litellm/issues/new | +# | | +# +-----------------------------------------------+ +# +# Thank you users! We ❤️ you! - Krrish & Ishaan + +import copy +from typing import TYPE_CHECKING, Any +import litellm + +if TYPE_CHECKING: + from litellm.litellm_core_utils.litellm_logging import ( + Logging as _LiteLLMLoggingObject, + ) + + LiteLLMLoggingObject = _LiteLLMLoggingObject +else: + LiteLLMLoggingObject = Any + + +def redact_message_input_output_from_logging( + litellm_logging_obj: LiteLLMLoggingObject, result +): + """ + Removes messages, prompts, input, response from logging. This modifies the data in-place + only redacts when litellm.turn_off_message_logging == True + """ + # check if user opted out of logging message/response to callbacks + if litellm.turn_off_message_logging is not True: + return result + + # remove messages, prompts, input, response from logging + litellm_logging_obj.model_call_details["messages"] = [ + {"role": "user", "content": "redacted-by-litellm"} + ] + litellm_logging_obj.model_call_details["prompt"] = "" + litellm_logging_obj.model_call_details["input"] = "" + + # response cleaning + # ChatCompletion Responses + if ( + litellm_logging_obj.stream is True + and "complete_streaming_response" in litellm_logging_obj.model_call_details + ): + _streaming_response = litellm_logging_obj.model_call_details[ + "complete_streaming_response" + ] + for choice in _streaming_response.choices: + if isinstance(choice, litellm.Choices): + choice.message.content = "redacted-by-litellm" + elif isinstance(choice, litellm.utils.StreamingChoices): + choice.delta.content = "redacted-by-litellm" + else: + if result is not None: + if isinstance(result, litellm.ModelResponse): + # only deep copy litellm.ModelResponse + _result = copy.deepcopy(result) + if hasattr(_result, "choices") and _result.choices is not None: + for choice in _result.choices: + if isinstance(choice, litellm.Choices): + choice.message.content = "redacted-by-litellm" + elif isinstance(choice, litellm.utils.StreamingChoices): + choice.delta.content = "redacted-by-litellm" + + return _result + + # by default return result + return result diff --git a/litellm/llms/anthropic.py b/litellm/llms/anthropic.py index 8e469a8f48c..808813c05e3 100644 --- a/litellm/llms/anthropic.py +++ b/litellm/llms/anthropic.py @@ -5,10 +5,16 @@ import requests, copy # type: ignore import time from functools import partial from typing import Callable, Optional, List, Union -from litellm.utils import ModelResponse, Usage, map_finish_reason, CustomStreamWrapper +import litellm.litellm_core_utils +from litellm.utils import ModelResponse, Usage, CustomStreamWrapper +from litellm.litellm_core_utils.core_helpers import map_finish_reason import litellm from .prompt_templates.factory import prompt_factory, custom_prompt -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + _get_async_httpx_client, + _get_httpx_client, +) from .base import BaseLLM import httpx # type: ignore from litellm.types.llms.anthropic import AnthropicMessagesToolChoice @@ -171,7 +177,7 @@ async def make_call( logging_obj, ): if client is None: - client = AsyncHTTPHandler() # Create a new client if none provided + client = _get_async_httpx_client() # Create a new client if none provided response = await client.post(api_base, headers=headers, data=data, stream=True) @@ -201,7 +207,7 @@ class AnthropicChatCompletion(BaseLLM): response: Union[requests.Response, httpx.Response], model_response: ModelResponse, stream: bool, - logging_obj: litellm.utils.Logging, + logging_obj: litellm.litellm_core_utils.litellm_logging.Logging, optional_params: dict, api_key: str, data: Union[dict, str], @@ -316,7 +322,7 @@ class AnthropicChatCompletion(BaseLLM): response: Union[requests.Response, httpx.Response], model_response: ModelResponse, stream: bool, - logging_obj: litellm.utils.Logging, + logging_obj: litellm.litellm_core_utils.litellm_logging.Logging, optional_params: dict, api_key: str, data: Union[dict, str], @@ -463,9 +469,7 @@ class AnthropicChatCompletion(BaseLLM): logger_fn=None, headers={}, ) -> Union[ModelResponse, CustomStreamWrapper]: - async_handler = AsyncHTTPHandler( - timeout=httpx.Timeout(timeout=600.0, connect=5.0) - ) + async_handler = _get_async_httpx_client() response = await async_handler.post(api_base, headers=headers, json=data) if stream and _is_function_call: return self.process_streaming_response( diff --git a/litellm/llms/base.py b/litellm/llms/base.py index 8c2f5101e16..0222d2366ca 100644 --- a/litellm/llms/base.py +++ b/litellm/llms/base.py @@ -2,7 +2,7 @@ import litellm import httpx, requests from typing import Optional, Union -from litellm.utils import Logging +from litellm.litellm_core_utils.litellm_logging import Logging class BaseLLM: diff --git a/litellm/llms/bedrock.py b/litellm/llms/bedrock.py index 4314032e76d..73fa1802378 100644 --- a/litellm/llms/bedrock.py +++ b/litellm/llms/bedrock.py @@ -5,12 +5,10 @@ import time, uuid from typing import Callable, Optional, Any, Union, List import litellm from litellm.utils import ( - ModelResponse, get_secret, - Usage, - ImageResponse, - map_finish_reason, ) +from litellm.litellm_core_utils.core_helpers import map_finish_reason +from litellm.types.utils import ImageResponse, ModelResponse, Usage from .prompt_templates.factory import ( prompt_factory, custom_prompt, @@ -633,7 +631,11 @@ def init_bedrock_client( config = boto3.session.Config() ### CHECK STS ### - if aws_web_identity_token is not None and aws_role_name is not None and aws_session_name is not None: + if ( + aws_web_identity_token is not None + and aws_role_name is not None + and aws_session_name is not None + ): oidc_token = get_secret(aws_web_identity_token) if oidc_token is None: @@ -642,9 +644,7 @@ def init_bedrock_client( status_code=401, ) - sts_client = boto3.client( - "sts" - ) + sts_client = boto3.client("sts") # https://docs.aws.amazon.com/STS/latest/APIReference/API_AssumeRoleWithWebIdentity.html # https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sts/client/assume_role_with_web_identity.html diff --git a/litellm/llms/bedrock_httpx.py b/litellm/llms/bedrock_httpx.py index 84b61d4cbd1..510bf7c7c67 100644 --- a/litellm/llms/bedrock_httpx.py +++ b/litellm/llms/bedrock_httpx.py @@ -22,13 +22,12 @@ from typing import ( from litellm.utils import ( ModelResponse, Usage, - map_finish_reason, CustomStreamWrapper, - Message, - Choices, get_secret, - Logging, ) +from litellm.litellm_core_utils.core_helpers import map_finish_reason +from litellm.litellm_core_utils.litellm_logging import Logging +from litellm.types.utils import Message, Choices import litellm, uuid from .prompt_templates.factory import ( prompt_factory, @@ -41,7 +40,12 @@ from .prompt_templates.factory import ( _bedrock_converse_messages_pt, _bedrock_tools_pt, ) -from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler +from litellm.llms.custom_httpx.http_handler import ( + AsyncHTTPHandler, + HTTPHandler, + _get_async_httpx_client, + _get_httpx_client, +) from .base import BaseLLM import httpx # type: ignore from .bedrock import BedrockError, convert_messages_to_prompt, ModelResponseIterator @@ -57,6 +61,7 @@ from litellm.caching import DualCache iam_cache = DualCache() + class AmazonCohereChatConfig: """ Reference - https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-cohere-command-r-plus.html @@ -167,7 +172,7 @@ async def make_call( logging_obj, ): if client is None: - client = AsyncHTTPHandler() # Create a new client if none provided + client = _get_async_httpx_client() # Create a new client if none provided response = await client.post(api_base, headers=headers, data=data, stream=True) @@ -198,7 +203,7 @@ def make_sync_call( logging_obj, ): if client is None: - client = HTTPHandler() # Create a new client if none provided + client = _get_httpx_client() # Create a new client if none provided response = client.post(api_base, headers=headers, data=data, stream=True) @@ -327,13 +332,19 @@ class BedrockLLM(BaseLLM): ) = params_to_check ### CHECK STS ### - if aws_web_identity_token is not None and aws_role_name is not None and aws_session_name is not None: - iam_creds_cache_key = json.dumps({ - "aws_web_identity_token": aws_web_identity_token, - "aws_role_name": aws_role_name, - "aws_session_name": aws_session_name, - "aws_region_name": aws_region_name, - }) + if ( + aws_web_identity_token is not None + and aws_role_name is not None + and aws_session_name is not None + ): + iam_creds_cache_key = json.dumps( + { + "aws_web_identity_token": aws_web_identity_token, + "aws_role_name": aws_role_name, + "aws_session_name": aws_session_name, + "aws_region_name": aws_region_name, + } + ) iam_creds_dict = iam_cache.get_cache(iam_creds_cache_key) if iam_creds_dict is None: @@ -348,7 +359,7 @@ class BedrockLLM(BaseLLM): sts_client = boto3.client( "sts", region_name=aws_region_name, - endpoint_url=f"https://sts.{aws_region_name}.amazonaws.com" + endpoint_url=f"https://sts.{aws_region_name}.amazonaws.com", ) # https://docs.aws.amazon.com/STS/latest/APIReference/API_AssumeRoleWithWebIdentity.html @@ -362,12 +373,18 @@ class BedrockLLM(BaseLLM): iam_creds_dict = { "aws_access_key_id": sts_response["Credentials"]["AccessKeyId"], - "aws_secret_access_key": sts_response["Credentials"]["SecretAccessKey"], + "aws_secret_access_key": sts_response["Credentials"][ + "SecretAccessKey" + ], "aws_session_token": sts_response["Credentials"]["SessionToken"], "region_name": aws_region_name, } - iam_cache.set_cache(key=iam_creds_cache_key, value=json.dumps(iam_creds_dict), ttl=3600 - 60) + iam_cache.set_cache( + key=iam_creds_cache_key, + value=json.dumps(iam_creds_dict), + ttl=3600 - 60, + ) session = boto3.Session(**iam_creds_dict) @@ -976,7 +993,7 @@ class BedrockLLM(BaseLLM): if isinstance(timeout, float) or isinstance(timeout, int): timeout = httpx.Timeout(timeout) _params["timeout"] = timeout - self.client = HTTPHandler(**_params) # type: ignore + self.client = _get_httpx_client(_params) # type: ignore else: self.client = client if (stream is not None and stream == True) and provider != "ai21": @@ -1058,7 +1075,7 @@ class BedrockLLM(BaseLLM): if isinstance(timeout, float) or isinstance(timeout, int): timeout = httpx.Timeout(timeout) _params["timeout"] = timeout - client = AsyncHTTPHandler(**_params) # type: ignore + client = _get_async_httpx_client(_params) # type: ignore else: client = client # type: ignore @@ -1433,13 +1450,19 @@ class BedrockConverseLLM(BaseLLM): ) = params_to_check ### CHECK STS ### - if aws_web_identity_token is not None and aws_role_name is not None and aws_session_name is not None: - iam_creds_cache_key = json.dumps({ - "aws_web_identity_token": aws_web_identity_token, - "aws_role_name": aws_role_name, - "aws_session_name": aws_session_name, - "aws_region_name": aws_region_name, - }) + if ( + aws_web_identity_token is not None + and aws_role_name is not None + and aws_session_name is not None + ): + iam_creds_cache_key = json.dumps( + { + "aws_web_identity_token": aws_web_identity_token, + "aws_role_name": aws_role_name, + "aws_session_name": aws_session_name, + "aws_region_name": aws_region_name, + } + ) iam_creds_dict = iam_cache.get_cache(iam_creds_cache_key) if iam_creds_dict is None: @@ -1454,7 +1477,7 @@ class BedrockConverseLLM(BaseLLM): sts_client = boto3.client( "sts", region_name=aws_region_name, - endpoint_url=f"https://sts.{aws_region_name}.amazonaws.com" + endpoint_url=f"https://sts.{aws_region_name}.amazonaws.com", ) # https://docs.aws.amazon.com/STS/latest/APIReference/API_AssumeRoleWithWebIdentity.html @@ -1468,12 +1491,18 @@ class BedrockConverseLLM(BaseLLM): iam_creds_dict = { "aws_access_key_id": sts_response["Credentials"]["AccessKeyId"], - "aws_secret_access_key": sts_response["Credentials"]["SecretAccessKey"], + "aws_secret_access_key": sts_response["Credentials"][ + "SecretAccessKey" + ], "aws_session_token": sts_response["Credentials"]["SessionToken"], "region_name": aws_region_name, } - iam_cache.set_cache(key=iam_creds_cache_key, value=json.dumps(iam_creds_dict), ttl=3600 - 60) + iam_cache.set_cache( + key=iam_creds_cache_key, + value=json.dumps(iam_creds_dict), + ttl=3600 - 60, + ) session = boto3.Session(**iam_creds_dict) @@ -1575,7 +1604,7 @@ class BedrockConverseLLM(BaseLLM): if isinstance(timeout, float) or isinstance(timeout, int): timeout = httpx.Timeout(timeout) _params["timeout"] = timeout - client = AsyncHTTPHandler(**_params) # type: ignore + client = _get_async_httpx_client(_params) # type: ignore else: client = client # type: ignore @@ -1847,7 +1876,7 @@ class BedrockConverseLLM(BaseLLM): if isinstance(timeout, float) or isinstance(timeout, int): timeout = httpx.Timeout(timeout) _params["timeout"] = timeout - client = HTTPHandler(**_params) # type: ignore + client = _get_httpx_client(_params) # type: ignore else: client = client try: diff --git a/litellm/llms/custom_httpx/http_handler.py b/litellm/llms/custom_httpx/http_handler.py index 5ec9c79bb2d..a3c5865fa37 100644 --- a/litellm/llms/custom_httpx/http_handler.py +++ b/litellm/llms/custom_httpx/http_handler.py @@ -12,6 +12,15 @@ class AsyncHTTPHandler: timeout: Optional[Union[float, httpx.Timeout]] = None, concurrent_limit=1000, ): + self.timeout = timeout + self.client = self.create_client( + timeout=timeout, concurrent_limit=concurrent_limit + ) + + def create_client( + self, timeout: Optional[Union[float, httpx.Timeout]], concurrent_limit: int + ) -> httpx.AsyncClient: + async_proxy_mounts = None # Check if the HTTP_PROXY and HTTPS_PROXY environment variables are set and use them accordingly. http_proxy = os.getenv("HTTP_PROXY", None) @@ -39,7 +48,8 @@ class AsyncHTTPHandler: if timeout is None: timeout = _DEFAULT_TIMEOUT # Create a client with a connection pool - self.client = httpx.AsyncClient( + + return httpx.AsyncClient( timeout=timeout, limits=httpx.Limits( max_connections=concurrent_limit, @@ -83,11 +93,48 @@ class AsyncHTTPHandler: response = await self.client.send(req, stream=stream) response.raise_for_status() return response + except httpx.RemoteProtocolError: + # Retry the request with a new session if there is a connection error + new_client = self.create_client(timeout=self.timeout, concurrent_limit=1) + try: + return await self.single_connection_post_request( + url=url, + client=new_client, + data=data, + json=json, + params=params, + headers=headers, + stream=stream, + ) + finally: + await new_client.aclose() except httpx.HTTPStatusError as e: raise e except Exception as e: raise e + async def single_connection_post_request( + self, + url: str, + client: httpx.AsyncClient, + data: Optional[Union[dict, str]] = None, # type: ignore + json: Optional[dict] = None, + params: Optional[dict] = None, + headers: Optional[dict] = None, + stream: bool = False, + ): + """ + Making POST request for a single connection client. + + Used for retrying connection client errors. + """ + req = client.build_request( + "POST", url, data=data, json=json, params=params, headers=headers # type: ignore + ) + response = await client.send(req, stream=stream) + response.raise_for_status() + return response + def __del__(self) -> None: try: asyncio.get_running_loop().create_task(self.close()) @@ -172,3 +219,60 @@ class HTTPHandler: self.close() except Exception: pass + + +def _get_async_httpx_client(params: Optional[dict] = None) -> AsyncHTTPHandler: + """ + Retrieves the async HTTP client from the cache + If not present, creates a new client + + Caches the new client and returns it. + """ + _params_key_name = "" + if params is not None: + for key, value in params.items(): + try: + _params_key_name += f"{key}_{value}" + except Exception: + pass + + _cache_key_name = "async_httpx_client" + _params_key_name + if _cache_key_name in litellm.in_memory_llm_clients_cache: + return litellm.in_memory_llm_clients_cache[_cache_key_name] + + if params is not None: + _new_client = AsyncHTTPHandler(**params) + else: + _new_client = AsyncHTTPHandler( + timeout=httpx.Timeout(timeout=600.0, connect=5.0) + ) + litellm.in_memory_llm_clients_cache[_cache_key_name] = _new_client + return _new_client + + +def _get_httpx_client(params: Optional[dict] = None) -> HTTPHandler: + """ + Retrieves the HTTP client from the cache + If not present, creates a new client + + Caches the new client and returns it. + """ + _params_key_name = "" + if params is not None: + for key, value in params.items(): + try: + _params_key_name += f"{key}_{value}" + except Exception: + pass + + _cache_key_name = "httpx_client" + _params_key_name + if _cache_key_name in litellm.in_memory_llm_clients_cache: + return litellm.in_memory_llm_clients_cache[_cache_key_name] + + if params is not None: + _new_client = HTTPHandler(**params) + else: + _new_client = HTTPHandler(timeout=httpx.Timeout(timeout=600.0, connect=5.0)) + + litellm.in_memory_llm_clients_cache[_cache_key_name] = _new_client + return _new_client diff --git a/litellm/llms/databricks.py b/litellm/llms/databricks.py index 4fe47525935..1ab09246b06 100644 --- a/litellm/llms/databricks.py +++ b/litellm/llms/databricks.py @@ -10,10 +10,10 @@ from typing import Callable, Optional, List, Union, Tuple, Literal from litellm.utils import ( ModelResponse, Usage, - map_finish_reason, CustomStreamWrapper, EmbeddingResponse, ) +from litellm.litellm_core_utils.core_helpers import map_finish_reason import litellm from .prompt_templates.factory import prompt_factory, custom_prompt from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler @@ -289,7 +289,7 @@ class DatabricksChatCompletion(BaseLLM): response: Union[requests.Response, httpx.Response], model_response: ModelResponse, stream: bool, - logging_obj: litellm.utils.Logging, + logging_obj: litellm.litellm_core_utils.litellm_logging.Logging, optional_params: dict, api_key: str, data: Union[dict, str], diff --git a/litellm/llms/predibase.py b/litellm/llms/predibase.py index 66c28acee4e..8ad294457ec 100644 --- a/litellm/llms/predibase.py +++ b/litellm/llms/predibase.py @@ -12,11 +12,11 @@ from typing import Callable, Optional, List, Literal, Union from litellm.utils import ( ModelResponse, Usage, - map_finish_reason, CustomStreamWrapper, Message, Choices, ) +from litellm.litellm_core_utils.core_helpers import map_finish_reason import litellm from .prompt_templates.factory import prompt_factory, custom_prompt from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler @@ -198,7 +198,7 @@ class PredibaseChatCompletion(BaseLLM): response: Union[requests.Response, httpx.Response], model_response: ModelResponse, stream: bool, - logging_obj: litellm.utils.Logging, + logging_obj: litellm.litellm_core_utils.litellm_logging.Logging, optional_params: dict, api_key: str, data: Union[dict, str], diff --git a/litellm/llms/triton.py b/litellm/llms/triton.py index 711186b3fba..d647c9c43bc 100644 --- a/litellm/llms/triton.py +++ b/litellm/llms/triton.py @@ -4,7 +4,6 @@ from enum import Enum import requests, copy # type: ignore import time from typing import Callable, Optional, List -from litellm.utils import ModelResponse, Usage, map_finish_reason, CustomStreamWrapper import litellm from .prompt_templates.factory import prompt_factory, custom_prompt from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler diff --git a/litellm/llms/vertex_ai.py b/litellm/llms/vertex_ai.py index 67a8a451916..60d3d589797 100644 --- a/litellm/llms/vertex_ai.py +++ b/litellm/llms/vertex_ai.py @@ -5,7 +5,8 @@ import requests # type: ignore import time from typing import Callable, Optional, Union, List, Literal, Any from pydantic import BaseModel -from litellm.utils import ModelResponse, Usage, CustomStreamWrapper, map_finish_reason +from litellm.utils import ModelResponse, Usage, CustomStreamWrapper +from litellm.litellm_core_utils.core_helpers import map_finish_reason import litellm, uuid import httpx, inspect # type: ignore from litellm.types.llms.vertex_ai import * diff --git a/litellm/llms/vertex_ai_anthropic.py b/litellm/llms/vertex_ai_anthropic.py index 0652942801c..fd43d43786b 100644 --- a/litellm/llms/vertex_ai_anthropic.py +++ b/litellm/llms/vertex_ai_anthropic.py @@ -6,7 +6,8 @@ from enum import Enum import requests, copy # type: ignore import time, uuid from typing import Callable, Optional, List -from litellm.utils import ModelResponse, Usage, map_finish_reason, CustomStreamWrapper +from litellm.utils import ModelResponse, Usage, CustomStreamWrapper +from litellm.litellm_core_utils.core_helpers import map_finish_reason import litellm from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler from .prompt_templates.factory import ( diff --git a/litellm/llms/vertex_httpx.py b/litellm/llms/vertex_httpx.py index b1c38f0bc5a..c9e48f3e175 100644 --- a/litellm/llms/vertex_httpx.py +++ b/litellm/llms/vertex_httpx.py @@ -8,7 +8,10 @@ from enum import Enum import requests # type: ignore import time from typing import Callable, Optional, Union, List, Any, Tuple -from litellm.utils import ModelResponse, Usage, CustomStreamWrapper, map_finish_reason +import litellm.litellm_core_utils +import litellm.litellm_core_utils.litellm_logging +from litellm.utils import ModelResponse, Usage, CustomStreamWrapper +from litellm.litellm_core_utils.core_helpers import map_finish_reason import litellm, uuid import httpx, inspect # type: ignore from litellm.llms.custom_httpx.http_handler import AsyncHTTPHandler, HTTPHandler @@ -320,7 +323,7 @@ class VertexLLM(BaseLLM): model: str, response: httpx.Response, model_response: ModelResponse, - logging_obj: litellm.utils.Logging, + logging_obj: litellm.litellm_core_utils.litellm_logging.Logging, optional_params: dict, api_key: str, data: Union[dict, str], diff --git a/litellm/main.py b/litellm/main.py index 31cb8e364f3..77fe38fd2d8 100644 --- a/litellm/main.py +++ b/litellm/main.py @@ -368,7 +368,9 @@ async def acompletion( return response except Exception as e: verbose_logger.error( - "litellm.acompletion(): Exception occured - {}".format(str(e)) + "litellm.acompletion(): Exception occured - {}\n{}".format( + str(e), traceback.format_exc() + ) ) verbose_logger.debug(traceback.format_exc()) custom_llm_provider = custom_llm_provider or "openai" @@ -399,6 +401,7 @@ def mock_completion( stream: Optional[bool] = False, mock_response: Union[str, Exception] = "This is a mock request", logging=None, + custom_llm_provider=None, **kwargs, ): """ @@ -436,7 +439,7 @@ def mock_completion( raise litellm.APIError( status_code=getattr(mock_response, "status_code", 500), # type: ignore message=getattr(mock_response, "text", str(mock_response)), - llm_provider=getattr(mock_response, "llm_provider", "openai"), # type: ignore + llm_provider=getattr(mock_response, "llm_provider", custom_llm_provider or "openai"), # type: ignore model=model, # type: ignore request=httpx.Request(method="POST", url="https://api.openai.com/v1/"), ) @@ -905,6 +908,7 @@ def completion( logging=logging, acompletion=acompletion, mock_delay=kwargs.get("mock_delay", None), + custom_llm_provider=custom_llm_provider, ) if custom_llm_provider == "azure": # azure configs diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json index 385dc2ead02..98da8d69c0c 100644 --- a/litellm/model_prices_and_context_window_backup.json +++ b/litellm/model_prices_and_context_window_backup.json @@ -3347,6 +3347,24 @@ "litellm_provider": "deepinfra", "mode": "chat" }, + "deepinfra/meta-llama/Meta-Llama-3-8B-Instruct": { + "max_tokens": 8191, + "max_input_tokens": 8191, + "max_output_tokens": 4096, + "input_cost_per_token": 0.00000008, + "output_cost_per_token": 0.00000008, + "litellm_provider": "deepinfra", + "mode": "chat" + }, + "deepinfra/meta-llama/Meta-Llama-3-70B-Instruct": { + "max_tokens": 8191, + "max_input_tokens": 8191, + "max_output_tokens": 4096, + "input_cost_per_token": 0.00000059, + "output_cost_per_token": 0.00000079, + "litellm_provider": "deepinfra", + "mode": "chat" + }, "deepinfra/01-ai/Yi-34B-200K": { "max_tokens": 4096, "max_input_tokens": 200000, diff --git a/litellm/proxy/_experimental/out/404.html b/litellm/proxy/_experimental/out/404.html index e97c72fc132..e648c625ed2 100644 --- a/litellm/proxy/_experimental/out/404.html +++ b/litellm/proxy/_experimental/out/404.html @@ -1 +1 @@ -404: This page could not be found.LiteLLM Dashboard

404

This page could not be found.

\ No newline at end of file +404: This page could not be found.LiteLLM Dashboard

404

This page could not be found.

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assistant that im using to make a test request to."\n ),\n HumanMessage(\n content="test from litellm. tell me why it\'s amazing in 1 sentence"\n ),\n]\nresponse = chat(messages)\n\nprint(response)\n\n ')})})]})]})]})})]})}}},function(e){e.O(0,[936,294,131,684,759,777,971,69,744],function(){return e(e.s=20661)}),_N_E=e.O()}]); \ No newline at end of file diff --git a/ui/litellm-dashboard/out/_next/static/chunks/webpack-496e007a0280178b.js b/litellm/proxy/_experimental/out/_next/static/chunks/webpack-6f7793f21bbb2fbe.js similarity index 98% rename from ui/litellm-dashboard/out/_next/static/chunks/webpack-496e007a0280178b.js rename to litellm/proxy/_experimental/out/_next/static/chunks/webpack-6f7793f21bbb2fbe.js index a08c6655b71..359d51f19ba 100644 --- a/ui/litellm-dashboard/out/_next/static/chunks/webpack-496e007a0280178b.js +++ b/litellm/proxy/_experimental/out/_next/static/chunks/webpack-6f7793f21bbb2fbe.js @@ -1 +1 @@ -!function(){"use strict";var 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2b20547565e..15b8bc93e69 100644 --- a/litellm/proxy/_super_secret_config.yaml +++ b/litellm/proxy/_super_secret_config.yaml @@ -11,7 +11,7 @@ model_list: - model_name: fake-openai-endpoint litellm_params: model: predibase/llama-3-8b-instruct - api_base: "http://0.0.0.0:8081" + api_base: "http://0.0.0.0:8000" api_key: os.environ/PREDIBASE_API_KEY tenant_id: os.environ/PREDIBASE_TENANT_ID max_retries: 0 @@ -55,7 +55,16 @@ model_list: model: textembedding-gecko-multilingual@001 vertex_project: my-project-9d5c vertex_location: us-central1 - +- model_name: lbl/command-r-plus + litellm_params: + model: openai/lbl/command-r-plus + api_key: "os.environ/VLLM_API_KEY" + api_base: http://vllm-command:8000/v1 + rpm: 1000 + input_cost_per_token: 0 + output_cost_per_token: 0 + model_info: + max_input_tokens: 80920 assistant_settings: custom_llm_provider: openai litellm_params: @@ -68,9 +77,10 @@ router_settings: litellm_settings: success_callback: ["langfuse"] failure_callback: ["langfuse"] + cache: true -# general_settings: -# alerting: ["email"] +general_settings: + alerting: ["slack"] # key_management_system: "aws_kms" # key_management_settings: # hosted_keys: ["LITELLM_MASTER_KEY"] diff --git a/litellm/proxy/_types.py b/litellm/proxy/_types.py index ccc8ed34792..9a284783918 100644 --- a/litellm/proxy/_types.py +++ b/litellm/proxy/_types.py @@ -1358,10 +1358,11 @@ class CallInfo(LiteLLMBase): spend: float max_budget: Optional[float] = None - token: str = Field(description="Hashed value of that key") + token: Optional[str] = Field(default=None, description="Hashed value of that key") customer_id: Optional[str] = None user_id: Optional[str] = None team_id: Optional[str] = None + team_alias: Optional[str] = None user_email: Optional[str] = None key_alias: Optional[str] = None projected_exceeded_date: Optional[str] = None @@ -1574,3 +1575,44 @@ class ManagementEndpointLoggingPayload(LiteLLMBase): exception: Optional[Any] = None start_time: Optional[datetime] = None end_time: Optional[datetime] = None + + +class ProxyException(Exception): + # NOTE: DO NOT MODIFY THIS + # This is used to map exactly to OPENAI Exceptions + def __init__( + self, + message: str, + type: str, + param: Optional[str], + code: Optional[int], + ): + self.message = message + self.type = type + self.param = param + self.code = code + + # rules for proxyExceptions + # Litellm router.py returns "No healthy deployment available" when there are no deployments available + # Should map to 429 errors https://github.com/BerriAI/litellm/issues/2487 + if ( + "No healthy deployment available" in self.message + or "No deployments available" in self.message + ): + self.code = 429 + + def to_dict(self) -> dict: + """Converts the ProxyException instance to a dictionary.""" + return { + "message": self.message, + "type": self.type, + "param": self.param, + "code": self.code, + } + + +class CommonProxyErrors(enum.Enum): + db_not_connected_error = "DB not connected" + no_llm_router = "No models configured on proxy" + not_allowed_access = "Admin-only endpoint. Not allowed to access this." + not_premium_user = "You must be a LiteLLM Enterprise user to use this feature. If you have a license please set `LITELLM_LICENSE` in your env. If you want to obtain a license meet with us here: https://calendly.com/d/4mp-gd3-k5k/litellm-1-1-onboarding-chat" diff --git a/litellm/proxy/auth/user_api_key_auth.py b/litellm/proxy/auth/user_api_key_auth.py new file mode 100644 index 00000000000..c79b0a8f95c --- /dev/null +++ b/litellm/proxy/auth/user_api_key_auth.py @@ -0,0 +1,1237 @@ +""" +This file handles authentication for the LiteLLM Proxy. + +it checks if the user passed a valid API Key to the LiteLLM Proxy + +Returns a UserAPIKeyAuth object if the API key is valid + +""" + +import json +from datetime import datetime, timedelta, timezone +from typing import Optional +import secrets +from uuid import uuid4 + +import fastapi +from fastapi import Request +from pydantic import BaseModel +import litellm +import traceback +import asyncio +from fastapi import ( + FastAPI, + Request, + HTTPException, + status, + Path, + Depends, + Header, + Response, + Form, + UploadFile, + File, +) +from fastapi.responses import ( + StreamingResponse, + FileResponse, + ORJSONResponse, + JSONResponse, +) +from fastapi.openapi.utils import get_openapi +from fastapi.responses import RedirectResponse +from fastapi.middleware.cors import CORSMiddleware +from fastapi.staticfiles import StaticFiles +from fastapi.security.api_key import APIKeyHeader +from litellm.proxy._types import * +from litellm._logging import verbose_logger, verbose_proxy_logger + +from litellm.proxy.auth.auth_checks import ( + common_checks, + get_end_user_object, + get_org_object, + get_team_object, + get_user_object, + allowed_routes_check, + get_actual_routes, + log_to_opentelemetry, +) + +from litellm.proxy.utils import _to_ns +from litellm.proxy.common_utils.http_parsing_utils import _read_request_body + + +api_key_header = APIKeyHeader( + name="Authorization", auto_error=False, description="Bearer token" +) +azure_api_key_header = APIKeyHeader( + name="API-Key", + auto_error=False, + description="Some older versions of the openai Python package will send an API-Key header with just the API key ", +) + + +def _get_bearer_token( + api_key: str, +): + if api_key.startswith("Bearer "): # ensure Bearer token passed in + api_key = api_key.replace("Bearer ", "") # extract the token + else: + api_key = "" + return api_key + + +async def user_api_key_auth( + request: Request, + api_key: str = fastapi.Security(api_key_header), + azure_api_key_header: str = fastapi.Security(azure_api_key_header), +) -> UserAPIKeyAuth: + + from litellm.proxy.proxy_server import ( + litellm_proxy_admin_name, + common_checks, + master_key, + prisma_client, + llm_model_list, + user_custom_auth, + custom_db_client, + general_settings, + proxy_logging_obj, + open_telemetry_logger, + user_api_key_cache, + jwt_handler, + allowed_routes_check, + get_actual_routes, + ) + + try: + if isinstance(api_key, str): + passed_in_key = api_key + api_key = _get_bearer_token(api_key=api_key) + + elif isinstance(azure_api_key_header, str): + api_key = azure_api_key_header + + parent_otel_span: Optional[Span] = None + if open_telemetry_logger is not None: + parent_otel_span = open_telemetry_logger.tracer.start_span( + name="Received Proxy Server Request", + start_time=_to_ns(datetime.now()), + context=open_telemetry_logger.get_traceparent_from_header( + headers=request.headers + ), + ) + ### USER-DEFINED AUTH FUNCTION ### + if user_custom_auth is not None: + response = await user_custom_auth(request=request, api_key=api_key) + return UserAPIKeyAuth.model_validate(response) + + ### LITELLM-DEFINED AUTH FUNCTION ### + #### IF JWT #### + """ + LiteLLM supports using JWTs. + + Enable this in proxy config, by setting + ``` + general_settings: + enable_jwt_auth: true + ``` + """ + route: str = request.url.path + + if route in LiteLLMRoutes.public_routes.value: + # check if public endpoint + return UserAPIKeyAuth(user_role=LitellmUserRoles.INTERNAL_USER_VIEW_ONLY) + + if general_settings.get("enable_jwt_auth", False) == True: + is_jwt = jwt_handler.is_jwt(token=api_key) + verbose_proxy_logger.debug("is_jwt: %s", is_jwt) + if is_jwt: + # check if valid token + jwt_valid_token: dict = await jwt_handler.auth_jwt(token=api_key) + # get scopes + scopes = jwt_handler.get_scopes(token=jwt_valid_token) + + # check if admin + is_admin = jwt_handler.is_admin(scopes=scopes) + # if admin return + if is_admin: + # check allowed admin routes + is_allowed = allowed_routes_check( + user_role=LitellmUserRoles.PROXY_ADMIN, + user_route=route, + litellm_proxy_roles=jwt_handler.litellm_jwtauth, + ) + if is_allowed: + return UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, + parent_otel_span=parent_otel_span, + ) + else: + allowed_routes: List[Any] = ( + jwt_handler.litellm_jwtauth.admin_allowed_routes + ) + actual_routes = get_actual_routes(allowed_routes=allowed_routes) + raise Exception( + f"Admin not allowed to access this route. Route={route}, Allowed Routes={actual_routes}" + ) + # get team id + team_id = jwt_handler.get_team_id( + token=jwt_valid_token, default_value=None + ) + + if team_id is None and jwt_handler.is_required_team_id() == True: + raise Exception( + f"No team id passed in. Field checked in jwt token - '{jwt_handler.litellm_jwtauth.team_id_jwt_field}'" + ) + + team_object: Optional[LiteLLM_TeamTable] = None + if team_id is not None: + # check allowed team routes + is_allowed = allowed_routes_check( + user_role=LitellmUserRoles.TEAM, + user_route=route, + litellm_proxy_roles=jwt_handler.litellm_jwtauth, + ) + if is_allowed == False: + allowed_routes = jwt_handler.litellm_jwtauth.team_allowed_routes # type: ignore + actual_routes = get_actual_routes(allowed_routes=allowed_routes) + raise Exception( + f"Team not allowed to access this route. Route={route}, Allowed Routes={actual_routes}" + ) + + # check if team in db + team_object = await get_team_object( + team_id=team_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + ) + + # [OPTIONAL] track spend for an org id - `LiteLLM_OrganizationTable` + org_id = jwt_handler.get_org_id( + token=jwt_valid_token, default_value=None + ) + if org_id is not None: + _ = await get_org_object( + org_id=org_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + ) + # [OPTIONAL] track spend against an internal employee - `LiteLLM_UserTable` + user_object = None + user_id = jwt_handler.get_user_id( + token=jwt_valid_token, default_value=None + ) + if user_id is not None: + # get the user object + user_object = await get_user_object( + user_id=user_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + user_id_upsert=jwt_handler.is_upsert_user_id(), + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + ) + + # [OPTIONAL] track spend against an external user - `LiteLLM_EndUserTable` + end_user_object = None + end_user_id = jwt_handler.get_end_user_id( + token=jwt_valid_token, default_value=None + ) + if end_user_id is not None: + # get the end-user object + end_user_object = await get_end_user_object( + end_user_id=end_user_id, + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + ) + + global_proxy_spend = None + if litellm.max_budget > 0: # user set proxy max budget + # check cache + global_proxy_spend = await user_api_key_cache.async_get_cache( + key="{}:spend".format(litellm_proxy_admin_name) + ) + if global_proxy_spend is None and prisma_client is not None: + # get from db + sql_query = """SELECT SUM(spend) as total_spend FROM "MonthlyGlobalSpend";""" + + response = await prisma_client.db.query_raw(query=sql_query) + + global_proxy_spend = response[0]["total_spend"] + + await user_api_key_cache.async_set_cache( + key="{}:spend".format(litellm_proxy_admin_name), + value=global_proxy_spend, + ) + if global_proxy_spend is not None: + user_info = CallInfo( + user_id=litellm_proxy_admin_name, + max_budget=litellm.max_budget, + spend=global_proxy_spend, + token=jwt_valid_token["token"], + ) + asyncio.create_task( + proxy_logging_obj.budget_alerts( + type="proxy_budget", + user_info=user_info, + ) + ) + # get the request body + request_data = await _read_request_body(request=request) + + # run through common checks + _ = common_checks( + request_body=request_data, + team_object=team_object, + user_object=user_object, + end_user_object=end_user_object, + general_settings=general_settings, + global_proxy_spend=global_proxy_spend, + route=route, + ) + + # return UserAPIKeyAuth object + return UserAPIKeyAuth( + api_key=None, + team_id=team_object.team_id if team_object is not None else None, + team_tpm_limit=( + team_object.tpm_limit if team_object is not None else None + ), + team_rpm_limit=( + team_object.rpm_limit if team_object is not None else None + ), + team_models=team_object.models if team_object is not None else [], + user_role=LitellmUserRoles.INTERNAL_USER, + user_id=user_id, + org_id=org_id, + parent_otel_span=parent_otel_span, + ) + #### ELSE #### + if master_key is None: + if isinstance(api_key, str): + return UserAPIKeyAuth( + api_key=api_key, + user_role=LitellmUserRoles.PROXY_ADMIN, + parent_otel_span=parent_otel_span, + ) + else: + return UserAPIKeyAuth( + user_role=LitellmUserRoles.PROXY_ADMIN, + parent_otel_span=parent_otel_span, + ) + elif api_key is None: # only require api key if master key is set + raise Exception("No api key passed in.") + elif api_key == "": + # missing 'Bearer ' prefix + raise Exception( + f"Malformed API Key passed in. Ensure Key has `Bearer ` prefix. Passed in: {passed_in_key}" + ) + + if route == "/user/auth": + if general_settings.get("allow_user_auth", False) == True: + return UserAPIKeyAuth() + else: + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail="'allow_user_auth' not set or set to False", + ) + + ## Check END-USER OBJECT + request_data = await _read_request_body(request=request) + _end_user_object = None + end_user_params = {} + if "user" in request_data: + try: + _end_user_object = await get_end_user_object( + end_user_id=request_data["user"], + prisma_client=prisma_client, + user_api_key_cache=user_api_key_cache, + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + ) + if _end_user_object is not None: + end_user_params["allowed_model_region"] = ( + _end_user_object.allowed_model_region + ) + if _end_user_object.litellm_budget_table is not None: + budget_info = _end_user_object.litellm_budget_table + end_user_params["end_user_id"] = _end_user_object.user_id + if budget_info.tpm_limit is not None: + end_user_params["end_user_tpm_limit"] = ( + budget_info.tpm_limit + ) + if budget_info.rpm_limit is not None: + end_user_params["end_user_rpm_limit"] = ( + budget_info.rpm_limit + ) + if budget_info.max_budget is not None: + end_user_params["end_user_max_budget"] = ( + budget_info.max_budget + ) + except Exception as e: + if isinstance(e, litellm.BudgetExceededError): + raise e + verbose_proxy_logger.debug( + "Unable to find user in db. Error - {}".format(str(e)) + ) + pass + + ### CHECK IF ADMIN ### + # note: never string compare api keys, this is vulenerable to a time attack. Use secrets.compare_digest instead + ### CHECK IF ADMIN ### + # note: never string compare api keys, this is vulenerable to a time attack. Use secrets.compare_digest instead + ## Check CACHE + valid_token: Optional[UserAPIKeyAuth] = user_api_key_cache.get_cache( + key=hash_token(api_key) + ) + if ( + valid_token is not None + and isinstance(valid_token, UserAPIKeyAuth) + and valid_token.user_role == LitellmUserRoles.PROXY_ADMIN + ): + # update end-user params on valid token + valid_token.end_user_id = end_user_params.get("end_user_id") + valid_token.end_user_tpm_limit = end_user_params.get("end_user_tpm_limit") + valid_token.end_user_rpm_limit = end_user_params.get("end_user_rpm_limit") + valid_token.allowed_model_region = end_user_params.get( + "allowed_model_region" + ) + valid_token.parent_otel_span = parent_otel_span + + return valid_token + + try: + is_master_key_valid = secrets.compare_digest(api_key, master_key) # type: ignore + except Exception as e: + is_master_key_valid = False + + ## VALIDATE MASTER KEY ## + try: + assert isinstance(master_key, str) + except Exception as e: + raise HTTPException( + status_code=500, + detail={ + "Master key must be a valid string. Current type={}".format( + type(master_key) + ) + }, + ) + + if is_master_key_valid: + _user_api_key_obj = UserAPIKeyAuth( + api_key=master_key, + user_role=LitellmUserRoles.PROXY_ADMIN, + user_id=litellm_proxy_admin_name, + parent_otel_span=parent_otel_span, + **end_user_params, + ) + await user_api_key_cache.async_set_cache( + key=hash_token(master_key), value=_user_api_key_obj + ) + + return _user_api_key_obj + + ## IF it's not a master key + ## Route should not be in master_key_only_routes + if route in LiteLLMRoutes.master_key_only_routes.value: + raise Exception( + f"Tried to access route={route}, which is only for MASTER KEY" + ) + + ## Check DB + if isinstance( + api_key, str + ): # if generated token, make sure it starts with sk-. + assert api_key.startswith("sk-") # prevent token hashes from being used + + if ( + prisma_client is None and custom_db_client is None + ): # if both master key + user key submitted, and user key != master key, and no db connected, raise an error + raise Exception("No connected db.") + + ## check for cache hit (In-Memory Cache) + original_api_key = api_key # (Patch: For DynamoDB Backwards Compatibility) + _user_role = None + if api_key.startswith("sk-"): + api_key = hash_token(token=api_key) + valid_token: Optional[UserAPIKeyAuth] = user_api_key_cache.get_cache( # type: ignore + key=api_key + ) + if valid_token is None: + ## check db + verbose_proxy_logger.debug("api key: %s", api_key) + if prisma_client is not None: + _valid_token: Optional[BaseModel] = await prisma_client.get_data( + token=api_key, + table_name="combined_view", + parent_otel_span=parent_otel_span, + proxy_logging_obj=proxy_logging_obj, + ) + if _valid_token is not None: + valid_token = UserAPIKeyAuth( + **_valid_token.model_dump(exclude_none=True) + ) + verbose_proxy_logger.debug("Token from db: %s", valid_token) + elif valid_token is not None and isinstance(valid_token, UserAPIKeyAuth): + verbose_proxy_logger.debug("API Key Cache Hit!") + + # update end-user params on valid token + # These can change per request - it's important to update them here + valid_token.end_user_id = end_user_params.get("end_user_id") + valid_token.end_user_tpm_limit = end_user_params.get("end_user_tpm_limit") + valid_token.end_user_rpm_limit = end_user_params.get("end_user_rpm_limit") + valid_token.allowed_model_region = end_user_params.get( + "allowed_model_region" + ) + + user_id_information: Optional[List] = None + if valid_token is not None: + # Got Valid Token from Cache, DB + # Run checks for + # 1. If token can call model + # 2. If user_id for this token is in budget + # 3. If the user spend within their own team is within budget + # 4. If 'user' passed to /chat/completions, /embeddings endpoint is in budget + # 5. If token is expired + # 6. If token spend is under Budget for the token + # 7. If token spend per model is under budget per model + # 8. If token spend is under team budget + # 9. If team spend is under team budget + + # Check 1. If token can call model + _model_alias_map = {} + if ( + hasattr(valid_token, "team_model_aliases") + and valid_token.team_model_aliases is not None + ): + _model_alias_map = { + **valid_token.aliases, + **valid_token.team_model_aliases, + } + else: + _model_alias_map = {**valid_token.aliases} + litellm.model_alias_map = _model_alias_map + config = valid_token.config + if config != {}: + model_list = config.get("model_list", []) + llm_model_list = model_list + verbose_proxy_logger.debug( + f"\n new llm router model list {llm_model_list}" + ) + if ( + len(valid_token.models) == 0 + ): # assume an empty model list means all models are allowed to be called + pass + elif ( + isinstance(valid_token.models, list) + and "all-team-models" in valid_token.models + ): + # Do not do any validation at this step + # the validation will occur when checking the team has access to this model + pass + else: + try: + data = await request.json() + except json.JSONDecodeError: + data = {} # Provide a default value, such as an empty dictionary + model = data.get("model", None) + if model in litellm.model_alias_map: + model = litellm.model_alias_map[model] + + ## check if model in allowed model names + verbose_proxy_logger.debug( + f"LLM Model List pre access group check: {llm_model_list}" + ) + from collections import defaultdict + + access_groups = defaultdict(list) + if llm_model_list is not None: + for m in llm_model_list: + for group in m.get("model_info", {}).get("access_groups", []): + model_name = m["model_name"] + access_groups[group].append(model_name) + + models_in_current_access_groups = [] + if ( + len(access_groups) > 0 + ): # check if token contains any model access groups + for idx, m in enumerate( + valid_token.models + ): # loop token models, if any of them are an access group add the access group + if m in access_groups: + # if it is an access group we need to remove it from valid_token.models + models_in_group = access_groups[m] + models_in_current_access_groups.extend(models_in_group) + + # Filter out models that are access_groups + filtered_models = [ + m for m in valid_token.models if m not in access_groups + ] + + filtered_models += models_in_current_access_groups + verbose_proxy_logger.debug( + f"model: {model}; allowed_models: {filtered_models}" + ) + if ( + model is not None + and model not in filtered_models + and "*" not in filtered_models + ): + raise ValueError( + f"API Key not allowed to access model. This token can only access models={valid_token.models}. Tried to access {model}" + ) + valid_token.models = filtered_models + verbose_proxy_logger.debug( + f"filtered allowed_models: {filtered_models}; valid_token.models: {valid_token.models}" + ) + + # Check 2. If user_id for this token is in budget + if valid_token.user_id is not None: + user_id_list = [valid_token.user_id] + for id in user_id_list: + value = user_api_key_cache.get_cache(key=id) + if value is not None: + if user_id_information is None: + user_id_information = [] + user_id_information.append(value) + if user_id_information is None or ( + isinstance(user_id_information, list) + and len(user_id_information) < 1 + ): + if prisma_client is not None: + user_id_information = await prisma_client.get_data( + user_id_list=[ + valid_token.user_id, + ], + table_name="user", + query_type="find_all", + ) + if user_id_information is not None: + for _id in user_id_information: + await user_api_key_cache.async_set_cache( + key=_id["user_id"], + value=_id, + ) + + verbose_proxy_logger.debug( + f"user_id_information: {user_id_information}" + ) + + if user_id_information is not None: + if isinstance(user_id_information, list): + ## Check if user in budget + for _user in user_id_information: + if _user is None: + continue + assert isinstance(_user, dict) + # check if user is admin # + + # Token exists, not expired now check if its in budget for the user + user_max_budget = _user.get("max_budget", None) + user_current_spend = _user.get("spend", None) + + verbose_proxy_logger.debug( + f"user_id: {_user.get('user_id', None)}; user_max_budget: {user_max_budget}; user_current_spend: {user_current_spend}" + ) + + if ( + user_max_budget is not None + and user_current_spend is not None + ): + call_info = CallInfo( + token=valid_token.token, + spend=user_current_spend, + max_budget=user_max_budget, + user_id=_user.get("user_id", None), + user_email=_user.get("user_email", None), + key_alias=valid_token.key_alias, + ) + asyncio.create_task( + proxy_logging_obj.budget_alerts( + type="user_budget", + user_info=call_info, + ) + ) + + _user_id = _user.get("user_id", None) + if user_current_spend > user_max_budget: + raise litellm.BudgetExceededError( + current_cost=user_current_spend, + max_budget=user_max_budget, + ) + else: + # Token exists, not expired now check if its in budget for the user + user_max_budget = getattr( + user_id_information, "max_budget", None + ) + user_current_spend = getattr(user_id_information, "spend", None) + + if ( + user_max_budget is not None + and user_current_spend is not None + ): + call_info = CallInfo( + token=valid_token.token, + spend=user_current_spend, + max_budget=user_max_budget, + user_id=getattr(user_id_information, "user_id", None), + user_email=getattr( + user_id_information, "user_email", None + ), + key_alias=valid_token.key_alias, + ) + asyncio.create_task( + proxy_logging_obj.budget_alerts( + type="user_budget", + user_info=call_info, + ) + ) + + if user_current_spend > user_max_budget: + raise litellm.BudgetExceededError( + current_cost=user_current_spend, + max_budget=user_max_budget, + ) + + # Check 3. Check if user is in their team budget + if valid_token.team_member_spend is not None: + if prisma_client is not None: + + _cache_key = f"{valid_token.team_id}_{valid_token.user_id}" + + team_member_info = await user_api_key_cache.async_get_cache( + key=_cache_key + ) + if team_member_info is None: + # read from DB + _user_id = valid_token.user_id + _team_id = valid_token.team_id + + if _user_id is not None and _team_id is not None: + team_member_info = await prisma_client.db.litellm_teammembership.find_first( + where={ + "user_id": _user_id, + "team_id": _team_id, + }, # type: ignore + include={"litellm_budget_table": True}, + ) + await user_api_key_cache.async_set_cache( + key=_cache_key, + value=team_member_info, + ) + + if ( + team_member_info is not None + and team_member_info.litellm_budget_table is not None + ): + team_member_budget = ( + team_member_info.litellm_budget_table.max_budget + ) + if team_member_budget is not None and team_member_budget > 0: + if valid_token.team_member_spend > team_member_budget: + raise litellm.BudgetExceededError( + current_cost=valid_token.team_member_spend, + max_budget=team_member_budget, + ) + + # Check 3. If token is expired + if valid_token.expires is not None: + current_time = datetime.now(timezone.utc) + expiry_time = datetime.fromisoformat(valid_token.expires) + if ( + expiry_time.tzinfo is None + or expiry_time.tzinfo.utcoffset(expiry_time) is None + ): + expiry_time = expiry_time.replace(tzinfo=timezone.utc) + verbose_proxy_logger.debug( + f"Checking if token expired, expiry time {expiry_time} and current time {current_time}" + ) + if expiry_time < current_time: + # Token exists but is expired. + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail=f"Authentication Error - Expired Key. Key Expiry time {expiry_time} and current time {current_time}", + ) + + # Check 4. Token Spend is under budget + if valid_token.spend is not None and valid_token.max_budget is not None: + + #################################### + # collect information for alerting # + #################################### + + user_email: Optional[str] = None + # Check if the token has any user id information + if user_id_information is not None and len(user_id_information) > 0: + specific_user_id_information = user_id_information[0] + _user_email = specific_user_id_information.get("user_email", None) + if _user_email is not None: + user_email = str(_user_email) + + call_info = CallInfo( + token=valid_token.token, + spend=valid_token.spend, + max_budget=valid_token.max_budget, + user_id=valid_token.user_id, + team_id=valid_token.team_id, + user_email=user_email, + key_alias=valid_token.key_alias, + ) + asyncio.create_task( + proxy_logging_obj.budget_alerts( + type="token_budget", + user_info=call_info, + ) + ) + + #################################### + # collect information for alerting # + #################################### + + if valid_token.spend >= valid_token.max_budget: + raise litellm.BudgetExceededError( + current_cost=valid_token.spend, + max_budget=valid_token.max_budget, + ) + + # Check 5. Token Model Spend is under Model budget + max_budget_per_model = valid_token.model_max_budget + current_model = request_data.get("model", None) + + if ( + max_budget_per_model is not None + and isinstance(max_budget_per_model, dict) + and len(max_budget_per_model) > 0 + and prisma_client is not None + and current_model is not None + and valid_token.token is not None + ): + ## GET THE SPEND FOR THIS MODEL + twenty_eight_days_ago = datetime.now() - timedelta(days=28) + model_spend = await prisma_client.db.litellm_spendlogs.group_by( + by=["model"], + sum={"spend": True}, + where={ + "AND": [ + {"api_key": valid_token.token}, + {"startTime": {"gt": twenty_eight_days_ago}}, + {"model": current_model}, + ] + }, # type: ignore + ) + if ( + len(model_spend) > 0 + and max_budget_per_model.get(current_model, None) is not None + ): + if ( + model_spend[0]["model"] == current_model + and model_spend[0]["_sum"]["spend"] + >= max_budget_per_model[current_model] + ): + current_model_spend = model_spend[0]["_sum"]["spend"] + current_model_budget = max_budget_per_model[current_model] + raise litellm.BudgetExceededError( + current_cost=current_model_spend, + max_budget=current_model_budget, + ) + + # Check 6. Team spend is under Team budget + if ( + hasattr(valid_token, "team_spend") + and valid_token.team_spend is not None + and hasattr(valid_token, "team_max_budget") + and valid_token.team_max_budget is not None + ): + call_info = CallInfo( + token=valid_token.token, + spend=valid_token.team_spend, + max_budget=valid_token.team_max_budget, + user_id=valid_token.user_id, + team_id=valid_token.team_id, + team_alias=valid_token.team_alias, + ) + asyncio.create_task( + proxy_logging_obj.budget_alerts( + type="team_budget", + user_info=call_info, + ) + ) + + if valid_token.team_spend >= valid_token.team_max_budget: + raise litellm.BudgetExceededError( + current_cost=valid_token.team_spend, + max_budget=valid_token.team_max_budget, + ) + + # Check 8: Additional Common Checks across jwt + key auth + _team_obj = LiteLLM_TeamTable( + team_id=valid_token.team_id, + max_budget=valid_token.team_max_budget, + spend=valid_token.team_spend, + tpm_limit=valid_token.team_tpm_limit, + rpm_limit=valid_token.team_rpm_limit, + blocked=valid_token.team_blocked, + models=valid_token.team_models, + ) + + user_api_key_cache.set_cache( + key=valid_token.team_id, value=_team_obj + ) # save team table in cache - used for tpm/rpm limiting - tpm_rpm_limiter.py + + global_proxy_spend = None + if ( + litellm.max_budget > 0 and prisma_client is not None + ): # user set proxy max budget + # check cache + global_proxy_spend = await user_api_key_cache.async_get_cache( + key="{}:spend".format(litellm_proxy_admin_name) + ) + if global_proxy_spend is None: + # get from db + sql_query = """SELECT SUM(spend) as total_spend FROM "MonthlyGlobalSpend";""" + + response = await prisma_client.db.query_raw(query=sql_query) + + global_proxy_spend = response[0]["total_spend"] + await user_api_key_cache.async_set_cache( + key="{}:spend".format(litellm_proxy_admin_name), + value=global_proxy_spend, + ) + + if global_proxy_spend is not None: + call_info = CallInfo( + token=valid_token.token, + spend=global_proxy_spend, + max_budget=litellm.max_budget, + user_id=litellm_proxy_admin_name, + team_id=valid_token.team_id, + ) + asyncio.create_task( + proxy_logging_obj.budget_alerts( + type="proxy_budget", + user_info=call_info, + ) + ) + _ = common_checks( + request_body=request_data, + team_object=_team_obj, + user_object=None, + end_user_object=_end_user_object, + general_settings=general_settings, + global_proxy_spend=global_proxy_spend, + route=route, + ) + # Token passed all checks + if valid_token is None: + raise HTTPException(401, detail="Invalid API key") + if valid_token.token is None: + raise HTTPException(401, detail="Invalid API key, no token associated") + api_key = valid_token.token + + # Add hashed token to cache + await user_api_key_cache.async_set_cache( + key=api_key, + value=valid_token, + ) + valid_token_dict = valid_token.model_dump(exclude_none=True) + valid_token_dict.pop("token", None) + + if _end_user_object is not None: + valid_token_dict.update(end_user_params) + + _user_role = _get_user_role(user_id_information=user_id_information) + + if not _is_user_proxy_admin(user_id_information): # if non-admin + if route in LiteLLMRoutes.openai_routes.value: + pass + elif request["route"].name in LiteLLMRoutes.openai_route_names.value: + pass + elif ( + route in LiteLLMRoutes.info_routes.value + ): # check if user allowed to call an info route + if route == "/key/info": + # check if user can access this route + query_params = request.query_params + key = query_params.get("key") + if key is not None and hash_token(token=key) != api_key: + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail="user not allowed to access this key's info", + ) + elif route == "/user/info": + # check if user can access this route + query_params = request.query_params + user_id = query_params.get("user_id") + verbose_proxy_logger.debug( + f"user_id: {user_id} & valid_token.user_id: {valid_token.user_id}" + ) + if user_id != valid_token.user_id: + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail="key not allowed to access this user's info. user_id={}, key's user_id={}".format( + user_id, valid_token.user_id + ), + ) + elif route == "/model/info": + # /model/info just shows models user has access to + pass + elif route == "/team/info": + # check if key can access this team's info + query_params = request.query_params + team_id = query_params.get("team_id") + if team_id != valid_token.team_id: + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail="key not allowed to access this team's info", + ) + elif ( + _has_user_setup_sso() + and route in LiteLLMRoutes.sso_only_routes.value + ): + pass + elif ( + route in LiteLLMRoutes.global_spend_tracking_routes.value + and getattr(valid_token, "permissions", None) is not None + and "get_spend_routes" in getattr(valid_token, "permissions", []) + ): + + pass + elif _user_role == LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY: + if route in LiteLLMRoutes.openai_routes.value: + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail=f"user not allowed to access this OpenAI routes, role= {_user_role}", + ) + if route in LiteLLMRoutes.management_routes.value: + # the Admin Viewer is only allowed to call /user/update for their own user_id and can only update + if route == "/user/update": + + # Check the Request params are valid for PROXY_ADMIN_VIEW_ONLY + if request_data is not None and isinstance( + request_data, dict + ): + _params_updated = request_data.keys() + for param in _params_updated: + if param not in ["user_email", "password"]: + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail=f"user not allowed to access this route, role= {_user_role}. Trying to access: {route} and updating invalid param: {param}. only user_email and password can be updated", + ) + else: + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, + detail=f"user not allowed to access this route, role= {_user_role}. Trying to access: {route}", + ) + elif ( + _user_role == LitellmUserRoles.INTERNAL_USER + and route in LiteLLMRoutes.internal_user_routes.value + ): + pass + else: + user_role = "unknown" + user_id = "unknown" + if ( + user_id_information is not None + and isinstance(user_id_information, list) + and len(user_id_information) > 0 + ): + _user = user_id_information[0] + user_role = _user.get("user_role", "unknown") + user_id = _user.get("user_id", "unknown") + raise Exception( + f"Only proxy admin can be used to generate, delete, update info for new keys/users/teams. Route={route}. Your role={user_role}. Your user_id={user_id}" + ) + + # check if token is from litellm-ui, litellm ui makes keys to allow users to login with sso. These keys can only be used for LiteLLM UI functions + # sso/login, ui/login, /key functions and /user functions + # this will never be allowed to call /chat/completions + token_team = getattr(valid_token, "team_id", None) + + if token_team is not None and token_team == "litellm-dashboard": + # this token is only used for managing the ui + allowed_routes = [ + "/sso", + "/login", + "/key/generate", + "/key/update", + "/key/info", + "/config", + "/spend", + "/user", + "/model/info", + "/v2/model/info", + "/v2/key/info", + "/models", + "/v1/models", + "/global/spend", + "/global/spend/logs", + "/global/spend/keys", + "/global/spend/models", + "/global/predict/spend/logs", + "/global/activity", + "/health/services", + ] + LiteLLMRoutes.info_routes.value + # check if the current route startswith any of the allowed routes + if ( + route is not None + and isinstance(route, str) + and any( + route.startswith(allowed_route) for allowed_route in allowed_routes + ) + ): + # Do something if the current route starts with any of the allowed routes + pass + else: + if user_id_information is not None and _is_user_proxy_admin( + user_id_information + ): + return UserAPIKeyAuth( + api_key=api_key, + user_role=LitellmUserRoles.PROXY_ADMIN, + parent_otel_span=parent_otel_span, + **valid_token_dict, + ) + elif ( + _has_user_setup_sso() + and route in LiteLLMRoutes.sso_only_routes.value + ): + return UserAPIKeyAuth( + api_key=api_key, + user_role=_user_role, + parent_otel_span=parent_otel_span, + **valid_token_dict, + ) + else: + raise Exception( + f"This key is made for LiteLLM UI, Tried to access route: {route}. Not allowed" + ) + if valid_token is None: + # No token was found when looking up in the DB + raise Exception("Invalid proxy server token passed") + if valid_token_dict is not None: + if user_id_information is not None and _is_user_proxy_admin( + user_id_information + ): + return UserAPIKeyAuth( + api_key=api_key, + user_role=LitellmUserRoles.PROXY_ADMIN, + parent_otel_span=parent_otel_span, + **valid_token_dict, + ) + elif _has_user_setup_sso() and route in LiteLLMRoutes.sso_only_routes.value: + return UserAPIKeyAuth( + api_key=api_key, + user_role=LitellmUserRoles.INTERNAL_USER, + parent_otel_span=parent_otel_span, + **valid_token_dict, + ) + else: + return UserAPIKeyAuth( + api_key=api_key, + user_role=LitellmUserRoles.INTERNAL_USER, + parent_otel_span=parent_otel_span, + **valid_token_dict, + ) + else: + raise Exception() + except Exception as e: + verbose_proxy_logger.error( + "litellm.proxy.proxy_server.user_api_key_auth(): Exception occured - {}".format( + str(e) + ) + ) + + # Log this exception to OTEL + if open_telemetry_logger is not None: + await open_telemetry_logger.async_post_call_failure_hook( + original_exception=e, + user_api_key_dict=UserAPIKeyAuth(parent_otel_span=parent_otel_span), + ) + + verbose_proxy_logger.debug(traceback.format_exc()) + if isinstance(e, litellm.BudgetExceededError): + raise ProxyException( + message=e.message, type="auth_error", param=None, code=400 + ) + if isinstance(e, HTTPException): + raise ProxyException( + message=getattr(e, "detail", f"Authentication Error({str(e)})"), + type="auth_error", + param=getattr(e, "param", "None"), + code=getattr(e, "status_code", status.HTTP_401_UNAUTHORIZED), + ) + elif isinstance(e, ProxyException): + raise e + raise ProxyException( + message="Authentication Error, " + str(e), + type="auth_error", + param=getattr(e, "param", "None"), + code=status.HTTP_401_UNAUTHORIZED, + ) + + +def _has_user_setup_sso(): + """ + Check if the user has set up single sign-on (SSO) by verifying the presence of Microsoft client ID, Google client ID, and UI username environment variables. + Returns a boolean indicating whether SSO has been set up. + """ + microsoft_client_id = os.getenv("MICROSOFT_CLIENT_ID", None) + google_client_id = os.getenv("GOOGLE_CLIENT_ID", None) + ui_username = os.getenv("UI_USERNAME", None) + + sso_setup = ( + (microsoft_client_id is not None) + or (google_client_id is not None) + or (ui_username is not None) + ) + + return sso_setup + + +def _is_user_proxy_admin(user_id_information: Optional[list]): + if user_id_information is None: + return False + + if len(user_id_information) == 0 or user_id_information[0] is None: + return False + + _user = user_id_information[0] + if ( + _user.get("user_role", None) is not None + and _user.get("user_role") == LitellmUserRoles.PROXY_ADMIN.value + ): + return True + + # if user_id_information contains litellm-proxy-budget + # get first user_id that is not litellm-proxy-budget + for user in user_id_information: + if user.get("user_id") != "litellm-proxy-budget": + _user = user + break + + if ( + _user.get("user_role", None) is not None + and _user.get("user_role") == LitellmUserRoles.PROXY_ADMIN.value + ): + return True + + return False + + +def _get_user_role(user_id_information: Optional[list]): + if user_id_information is None: + return None + + if len(user_id_information) == 0 or user_id_information[0] is None: + return None + + _user = user_id_information[0] + return _user.get("user_role") diff --git a/litellm/proxy/caching_routes.py b/litellm/proxy/caching_routes.py new file mode 100644 index 00000000000..bad747793f9 --- /dev/null +++ b/litellm/proxy/caching_routes.py @@ -0,0 +1,194 @@ +from typing import Optional +from fastapi import Depends, Request, APIRouter +from fastapi import HTTPException +import copy +import litellm +from litellm._logging import verbose_proxy_logger +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth + + +router = APIRouter( + prefix="/cache", + tags=["caching"], +) + + +@router.get( + "/ping", + dependencies=[Depends(user_api_key_auth)], +) +async def cache_ping(): + """ + Endpoint for checking if cache can be pinged + """ + try: + litellm_cache_params = {} + specific_cache_params = {} + + if litellm.cache is None: + raise HTTPException( + status_code=503, detail="Cache not initialized. litellm.cache is None" + ) + + for k, v in vars(litellm.cache).items(): + try: + if k == "cache": + continue + litellm_cache_params[k] = str(copy.deepcopy(v)) + except Exception: + litellm_cache_params[k] = "" + for k, v in vars(litellm.cache.cache).items(): + try: + specific_cache_params[k] = str(v) + except Exception: + specific_cache_params[k] = "" + if litellm.cache.type == "redis": + # ping the redis cache + ping_response = await litellm.cache.ping() + verbose_proxy_logger.debug( + "/cache/ping: ping_response: " + str(ping_response) + ) + # making a set cache call + # add cache does not return anything + await litellm.cache.async_add_cache( + result="test_key", + model="test-model", + messages=[{"role": "user", "content": "test from litellm"}], + ) + verbose_proxy_logger.debug("/cache/ping: done with set_cache()") + return { + "status": "healthy", + "cache_type": litellm.cache.type, + "ping_response": True, + "set_cache_response": "success", + "litellm_cache_params": litellm_cache_params, + "redis_cache_params": specific_cache_params, + } + else: + return { + "status": "healthy", + "cache_type": litellm.cache.type, + "litellm_cache_params": litellm_cache_params, + } + except Exception as e: + raise HTTPException( + status_code=503, + detail=f"Service Unhealthy ({str(e)}).Cache parameters: {litellm_cache_params}.specific_cache_params: {specific_cache_params}", + ) + + +@router.post( + "/delete", + tags=["caching"], + dependencies=[Depends(user_api_key_auth)], +) +async def cache_delete(request: Request): + """ + Endpoint for deleting a key from the cache. All responses from litellm proxy have `x-litellm-cache-key` in the headers + + Parameters: + - **keys**: *Optional[List[str]]* - A list of keys to delete from the cache. Example {"keys": ["key1", "key2"]} + + ```shell + curl -X POST "http://0.0.0.0:4000/cache/delete" \ + -H "Authorization: Bearer sk-1234" \ + -d '{"keys": ["key1", "key2"]}' + ``` + + """ + try: + if litellm.cache is None: + raise HTTPException( + status_code=503, detail="Cache not initialized. litellm.cache is None" + ) + + request_data = await request.json() + keys = request_data.get("keys", None) + + if litellm.cache.type == "redis": + await litellm.cache.delete_cache_keys(keys=keys) + return { + "status": "success", + } + else: + raise HTTPException( + status_code=500, + detail=f"Cache type {litellm.cache.type} does not support deleting a key. only `redis` is supported", + ) + except Exception as e: + raise HTTPException( + status_code=500, + detail=f"Cache Delete Failed({str(e)})", + ) + + +@router.get( + "/redis/info", + dependencies=[Depends(user_api_key_auth)], +) +async def cache_redis_info(): + """ + Endpoint for getting /redis/info + """ + try: + if litellm.cache is None: + raise HTTPException( + status_code=503, detail="Cache not initialized. litellm.cache is None" + ) + if litellm.cache.type == "redis": + client_list = litellm.cache.cache.client_list() + redis_info = litellm.cache.cache.info() + num_clients = len(client_list) + return { + "num_clients": num_clients, + "clients": client_list, + "info": redis_info, + } + else: + raise HTTPException( + status_code=500, + detail=f"Cache type {litellm.cache.type} does not support flushing", + ) + except Exception as e: + raise HTTPException( + status_code=503, + detail=f"Service Unhealthy ({str(e)})", + ) + + +@router.post( + "/flushall", + tags=["caching"], + dependencies=[Depends(user_api_key_auth)], +) +async def cache_flushall(): + """ + A function to flush all items from the cache. (All items will be deleted from the cache with this) + Raises HTTPException if the cache is not initialized or if the cache type does not support flushing. + Returns a dictionary with the status of the operation. + + Usage: + ``` + curl -X POST http://0.0.0.0:4000/cache/flushall -H "Authorization: Bearer sk-1234" + ``` + """ + try: + if litellm.cache is None: + raise HTTPException( + status_code=503, detail="Cache not initialized. litellm.cache is None" + ) + if litellm.cache.type == "redis": + litellm.cache.cache.flushall() + return { + "status": "success", + } + else: + raise HTTPException( + status_code=500, + detail=f"Cache type {litellm.cache.type} does not support flushing", + ) + except Exception as e: + raise HTTPException( + status_code=503, + detail=f"Service Unhealthy ({str(e)})", + ) diff --git a/litellm/proxy/common_utils/management_endpoint_utils.py b/litellm/proxy/common_utils/management_endpoint_utils.py deleted file mode 100644 index 006f6aaae39..00000000000 --- a/litellm/proxy/common_utils/management_endpoint_utils.py +++ /dev/null @@ -1,90 +0,0 @@ -from datetime import datetime -from functools import wraps -from litellm.proxy._types import UserAPIKeyAuth, ManagementEndpointLoggingPayload -from litellm.proxy.common_utils.http_parsing_utils import _read_request_body -from fastapi import Request - - -def management_endpoint_wrapper(func): - """ - This wrapper does the following: - - 1. Log I/O, Exceptions to OTEL - 2. Create an Audit log for success calls - """ - - @wraps(func) - async def wrapper(*args, **kwargs): - start_time = datetime.now() - - try: - result = await func(*args, **kwargs) - end_time = datetime.now() - - if kwargs is None: - kwargs = {} - user_api_key_dict: UserAPIKeyAuth = ( - kwargs.get("user_api_key_dict") or UserAPIKeyAuth() - ) - parent_otel_span = user_api_key_dict.parent_otel_span - if parent_otel_span is not None: - from litellm.proxy.proxy_server import open_telemetry_logger - - if open_telemetry_logger is not None: - _http_request: Request = kwargs.get("http_request") - - _route = _http_request.url.path - _request_body: dict = await _read_request_body( - request=_http_request - ) - _response = dict(result) if result is not None else None - - logging_payload = ManagementEndpointLoggingPayload( - route=_route, - request_data=_request_body, - response=_response, - start_time=start_time, - end_time=end_time, - ) - - await open_telemetry_logger.async_management_endpoint_success_hook( - logging_payload=logging_payload, - parent_otel_span=parent_otel_span, - ) - - return result - except Exception as e: - end_time = datetime.now() - - if kwargs is None: - kwargs = {} - user_api_key_dict: UserAPIKeyAuth = ( - kwargs.get("user_api_key_dict") or UserAPIKeyAuth() - ) - parent_otel_span = user_api_key_dict.parent_otel_span - if parent_otel_span is not None: - from litellm.proxy.proxy_server import open_telemetry_logger - - if open_telemetry_logger is not None: - _http_request: Request = kwargs.get("http_request") - _route = _http_request.url.path - _request_body: dict = await _read_request_body( - request=_http_request - ) - logging_payload = ManagementEndpointLoggingPayload( - route=_route, - request_data=_request_body, - response=None, - start_time=start_time, - end_time=end_time, - exception=e, - ) - - await open_telemetry_logger.async_management_endpoint_failure_hook( - logging_payload=logging_payload, - parent_otel_span=parent_otel_span, - ) - - raise e - - return wrapper diff --git a/litellm/proxy/health_endpoints/_health_endpoints.py b/litellm/proxy/health_endpoints/_health_endpoints.py new file mode 100644 index 00000000000..fbb1c1a5f2c --- /dev/null +++ b/litellm/proxy/health_endpoints/_health_endpoints.py @@ -0,0 +1,478 @@ +from typing import Optional, Literal +import litellm +import os +import asyncio +import fastapi +import traceback +from datetime import datetime, timedelta +from fastapi import Depends, Request, APIRouter, Header, status +from litellm.proxy.health_check import perform_health_check +from fastapi import HTTPException +import copy +from litellm._logging import verbose_proxy_logger +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy._types import ( + UserAPIKeyAuth, + ProxyException, + WebhookEvent, + CallInfo, +) + +#### Health ENDPOINTS #### + +router = APIRouter() + + +@router.get( + "/test", + tags=["health"], + dependencies=[Depends(user_api_key_auth)], +) +async def test_endpoint(request: Request): + """ + [DEPRECATED] use `/health/liveliness` instead. + + A test endpoint that pings the proxy server to check if it's healthy. + + Parameters: + request (Request): The incoming request. + + Returns: + dict: A dictionary containing the route of the request URL. + """ + # ping the proxy server to check if its healthy + return {"route": request.url.path} + + +@router.get( + "/health/services", + tags=["health"], + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, +) +async def health_services_endpoint( + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), + service: Literal[ + "slack_budget_alerts", "langfuse", "slack", "openmeter", "webhook", "email" + ] = fastapi.Query(description="Specify the service being hit."), +): + """ + Hidden endpoint. + + Used by the UI to let user check if slack alerting is working as expected. + """ + try: + from litellm.proxy.proxy_server import ( + proxy_logging_obj, + prisma_client, + general_settings, + ) + + if service is None: + raise HTTPException( + status_code=400, detail={"error": "Service must be specified."} + ) + if service not in [ + "slack_budget_alerts", + "email", + "langfuse", + "slack", + "openmeter", + "webhook", + ]: + raise HTTPException( + status_code=400, + detail={ + "error": f"Service must be in list. Service={service}. List={['slack_budget_alerts']}" + }, + ) + + if service == "openmeter": + _ = await litellm.acompletion( + model="openai/litellm-mock-response-model", + messages=[{"role": "user", "content": "Hey, how's it going?"}], + user="litellm:/health/services", + mock_response="This is a mock response", + ) + return { + "status": "success", + "message": "Mock LLM request made - check openmeter.", + } + + if service == "langfuse": + from litellm.integrations.langfuse import LangFuseLogger + + langfuse_logger = LangFuseLogger() + langfuse_logger.Langfuse.auth_check() + _ = litellm.completion( + model="openai/litellm-mock-response-model", + messages=[{"role": "user", "content": "Hey, how's it going?"}], + user="litellm:/health/services", + mock_response="This is a mock response", + ) + return { + "status": "success", + "message": "Mock LLM request made - check langfuse.", + } + + if service == "webhook": + user_info = CallInfo( + token=user_api_key_dict.token or "", + spend=1, + max_budget=0, + user_id=user_api_key_dict.user_id, + key_alias=user_api_key_dict.key_alias, + team_id=user_api_key_dict.team_id, + ) + await proxy_logging_obj.budget_alerts( + type="user_budget", + user_info=user_info, + ) + + if service == "slack" or service == "slack_budget_alerts": + if "slack" in general_settings.get("alerting", []): + # test_message = f"""\n🚨 `ProjectedLimitExceededError` 💸\n\n`Key Alias:` litellm-ui-test-alert \n`Expected Day of Error`: 28th March \n`Current Spend`: $100.00 \n`Projected Spend at end of month`: $1000.00 \n`Soft Limit`: $700""" + # check if user has opted into unique_alert_webhooks + if ( + proxy_logging_obj.slack_alerting_instance.alert_to_webhook_url + is not None + ): + for ( + alert_type + ) in proxy_logging_obj.slack_alerting_instance.alert_to_webhook_url: + """ + "llm_exceptions", + "llm_too_slow", + "llm_requests_hanging", + "budget_alerts", + "db_exceptions", + """ + # only test alert if it's in active alert types + if ( + proxy_logging_obj.slack_alerting_instance.alert_types + is not None + and alert_type + not in proxy_logging_obj.slack_alerting_instance.alert_types + ): + continue + test_message = "default test message" + if alert_type == "llm_exceptions": + test_message = f"LLM Exception test alert" + elif alert_type == "llm_too_slow": + test_message = f"LLM Too Slow test alert" + elif alert_type == "llm_requests_hanging": + test_message = f"LLM Requests Hanging test alert" + elif alert_type == "budget_alerts": + test_message = f"Budget Alert test alert" + elif alert_type == "db_exceptions": + test_message = f"DB Exception test alert" + elif alert_type == "outage_alerts": + test_message = f"Outage Alert Exception test alert" + elif alert_type == "daily_reports": + test_message = f"Daily Reports test alert" + + await proxy_logging_obj.alerting_handler( + message=test_message, level="Low", alert_type=alert_type + ) + else: + await proxy_logging_obj.alerting_handler( + message="This is a test slack alert message", + level="Low", + alert_type="budget_alerts", + ) + + if prisma_client is not None: + asyncio.create_task( + proxy_logging_obj.slack_alerting_instance.send_monthly_spend_report() + ) + asyncio.create_task( + proxy_logging_obj.slack_alerting_instance.send_weekly_spend_report() + ) + + alert_types = ( + proxy_logging_obj.slack_alerting_instance.alert_types or [] + ) + alert_types = list(alert_types) + return { + "status": "success", + "alert_types": alert_types, + "message": "Mock Slack Alert sent, verify Slack Alert Received on your channel", + } + else: + raise HTTPException( + status_code=422, + detail={ + "error": '"{}" not in proxy config: general_settings. Unable to test this.'.format( + service + ) + }, + ) + if service == "email": + webhook_event = WebhookEvent( + event="key_created", + event_group="key", + event_message="Test Email Alert", + token=user_api_key_dict.token or "", + key_alias="Email Test key (This is only a test alert key. DO NOT USE THIS IN PRODUCTION.)", + spend=0, + max_budget=0, + user_id=user_api_key_dict.user_id, + user_email=os.getenv("TEST_EMAIL_ADDRESS"), + team_id=user_api_key_dict.team_id, + ) + + # use create task - this can take 10 seconds. don't keep ui users waiting for notification to check their email + asyncio.create_task( + proxy_logging_obj.slack_alerting_instance.send_key_created_or_user_invited_email( + webhook_event=webhook_event + ) + ) + + return { + "status": "success", + "message": "Mock Email Alert sent, verify Email Alert Received", + } + + except Exception as e: + verbose_proxy_logger.error( + "litellm.proxy.proxy_server.health_services_endpoint(): Exception occured - {}".format( + str(e) + ) + ) + verbose_proxy_logger.debug(traceback.format_exc()) + if isinstance(e, HTTPException): + raise ProxyException( + message=getattr(e, "detail", f"Authentication Error({str(e)})"), + type="auth_error", + param=getattr(e, "param", "None"), + code=getattr(e, "status_code", status.HTTP_500_INTERNAL_SERVER_ERROR), + ) + elif isinstance(e, ProxyException): + raise e + raise ProxyException( + message="Authentication Error, " + str(e), + type="auth_error", + param=getattr(e, "param", "None"), + code=status.HTTP_500_INTERNAL_SERVER_ERROR, + ) + + +@router.get("/health", tags=["health"], dependencies=[Depends(user_api_key_auth)]) +async def health_endpoint( + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), + model: Optional[str] = fastapi.Query( + None, description="Specify the model name (optional)" + ), +): + """ + 🚨 USE `/health/liveliness` to health check the proxy 🚨 + + See more 👉 https://docs.litellm.ai/docs/proxy/health + + + Check the health of all the endpoints in config.yaml + + To run health checks in the background, add this to config.yaml: + ``` + general_settings: + # ... other settings + background_health_checks: True + ``` + else, the health checks will be run on models when /health is called. + """ + from litellm.proxy.proxy_server import ( + health_check_results, + use_background_health_checks, + user_model, + llm_model_list, + ) + + try: + if llm_model_list is None: + # if no router set, check if user set a model using litellm --model ollama/llama2 + if user_model is not None: + healthy_endpoints, unhealthy_endpoints = await perform_health_check( + model_list=[], cli_model=user_model + ) + return { + "healthy_endpoints": healthy_endpoints, + "unhealthy_endpoints": unhealthy_endpoints, + "healthy_count": len(healthy_endpoints), + "unhealthy_count": len(unhealthy_endpoints), + } + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail={"error": "Model list not initialized"}, + ) + _llm_model_list = copy.deepcopy(llm_model_list) + ### FILTER MODELS FOR ONLY THOSE USER HAS ACCESS TO ### + if len(user_api_key_dict.models) > 0: + allowed_model_names = user_api_key_dict.models + else: + allowed_model_names = [] # + if use_background_health_checks: + return health_check_results + else: + healthy_endpoints, unhealthy_endpoints = await perform_health_check( + _llm_model_list, model + ) + + return { + "healthy_endpoints": healthy_endpoints, + "unhealthy_endpoints": unhealthy_endpoints, + "healthy_count": len(healthy_endpoints), + "unhealthy_count": len(unhealthy_endpoints), + } + except Exception as e: + verbose_proxy_logger.error( + "litellm.proxy.proxy_server.py::health_endpoint(): Exception occured - {}".format( + str(e) + ) + ) + verbose_proxy_logger.debug(traceback.format_exc()) + raise e + + +db_health_cache = {"status": "unknown", "last_updated": datetime.now()} + + +def _db_health_readiness_check(): + from litellm.proxy.proxy_server import prisma_client + + global db_health_cache + + # Note - Intentionally don't try/except this so it raises an exception when it fails + + # if timedelta is less than 2 minutes return DB Status + time_diff = datetime.now() - db_health_cache["last_updated"] + if db_health_cache["status"] != "unknown" and time_diff < timedelta(minutes=2): + return db_health_cache + prisma_client.health_check() + db_health_cache = {"status": "connected", "last_updated": datetime.now()} + return db_health_cache + + +@router.get( + "/active/callbacks", + tags=["health"], + dependencies=[Depends(user_api_key_auth)], +) +async def active_callbacks(): + """ + Returns a list of active callbacks on litellm.callbacks, litellm.input_callback, litellm.failure_callback, litellm.success_callback + """ + from litellm.proxy.proxy_server import proxy_logging_obj, general_settings + + _alerting = str(general_settings.get("alerting")) + # get success callbacks + + litellm_callbacks = [str(x) for x in litellm.callbacks] + litellm_input_callbacks = [str(x) for x in litellm.input_callback] + litellm_failure_callbacks = [str(x) for x in litellm.failure_callback] + litellm_success_callbacks = [str(x) for x in litellm.success_callback] + litellm_async_success_callbacks = [str(x) for x in litellm._async_success_callback] + litellm_async_failure_callbacks = [str(x) for x in litellm._async_failure_callback] + litellm_async_input_callbacks = [str(x) for x in litellm._async_input_callback] + + all_litellm_callbacks = ( + litellm_callbacks + + litellm_input_callbacks + + litellm_failure_callbacks + + litellm_success_callbacks + + litellm_async_success_callbacks + + litellm_async_failure_callbacks + + litellm_async_input_callbacks + ) + + alerting = proxy_logging_obj.alerting + _num_alerting = 0 + if alerting and isinstance(alerting, list): + _num_alerting = len(alerting) + + return { + "alerting": _alerting, + "litellm.callbacks": litellm_callbacks, + "litellm.input_callback": litellm_input_callbacks, + "litellm.failure_callback": litellm_failure_callbacks, + "litellm.success_callback": litellm_success_callbacks, + "litellm._async_success_callback": litellm_async_success_callbacks, + "litellm._async_failure_callback": litellm_async_failure_callbacks, + "litellm._async_input_callback": litellm_async_input_callbacks, + "all_litellm_callbacks": all_litellm_callbacks, + "num_callbacks": len(all_litellm_callbacks), + "num_alerting": _num_alerting, + } + + +@router.get( + "/health/readiness", + tags=["health"], + dependencies=[Depends(user_api_key_auth)], +) +async def health_readiness(): + """ + Unprotected endpoint for checking if worker can receive requests + """ + from litellm.proxy.proxy_server import proxy_logging_obj, prisma_client, version + + try: + # get success callback + success_callback_names = [] + + try: + # this was returning a JSON of the values in some of the callbacks + # all we need is the callback name, hence we do str(callback) + success_callback_names = [str(x) for x in litellm.success_callback] + except: + # don't let this block the /health/readiness response, if we can't convert to str -> return litellm.success_callback + success_callback_names = litellm.success_callback + + # check Cache + cache_type = None + if litellm.cache is not None: + from litellm.caching import RedisSemanticCache + + cache_type = litellm.cache.type + + if isinstance(litellm.cache.cache, RedisSemanticCache): + # ping the cache + # TODO: @ishaan-jaff - we should probably not ping the cache on every /health/readiness check + try: + index_info = await litellm.cache.cache._index_info() + except Exception as e: + index_info = "index does not exist - error: " + str(e) + cache_type = {"type": cache_type, "index_info": index_info} + + # check DB + if prisma_client is not None: # if db passed in, check if it's connected + db_health_status = _db_health_readiness_check() + return { + "status": "healthy", + "db": "connected", + "cache": cache_type, + "litellm_version": version, + "success_callbacks": success_callback_names, + **db_health_status, + } + else: + return { + "status": "healthy", + "db": "Not connected", + "cache": cache_type, + "litellm_version": version, + "success_callbacks": success_callback_names, + } + except Exception as e: + raise HTTPException(status_code=503, detail=f"Service Unhealthy ({str(e)})") + + +@router.get( + "/health/liveliness", + tags=["health"], + dependencies=[Depends(user_api_key_auth)], +) +async def health_liveliness(): + """ + Unprotected endpoint for checking if worker is alive + """ + return "I'm alive!" diff --git a/litellm/proxy/hooks/parallel_request_limiter.py b/litellm/proxy/hooks/parallel_request_limiter.py index 4ba7a2229ba..a17fcb2c972 100644 --- a/litellm/proxy/hooks/parallel_request_limiter.py +++ b/litellm/proxy/hooks/parallel_request_limiter.py @@ -10,18 +10,17 @@ from datetime import datetime class _PROXY_MaxParallelRequestsHandler(CustomLogger): - user_api_key_cache = None # Class variables or attributes - def __init__(self): - pass + def __init__(self, internal_usage_cache: DualCache): + self.internal_usage_cache = internal_usage_cache def print_verbose(self, print_statement): try: verbose_proxy_logger.debug(print_statement) if litellm.set_verbose: print(print_statement) # noqa - except: + except Exception: pass async def check_key_in_limits( @@ -35,7 +34,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): rpm_limit: int, request_count_api_key: str, ): - current = cache.get_cache( + current = await self.internal_usage_cache.async_get_cache( key=request_count_api_key ) # {"current_requests": 1, "current_tpm": 1, "current_rpm": 10} if current is None: @@ -49,7 +48,9 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): "current_tpm": 0, "current_rpm": 0, } - cache.set_cache(request_count_api_key, new_val) + await self.internal_usage_cache.async_set_cache( + request_count_api_key, new_val + ) elif ( int(current["current_requests"]) < max_parallel_requests and current["current_tpm"] < tpm_limit @@ -61,7 +62,9 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): "current_tpm": current["current_tpm"], "current_rpm": current["current_rpm"], } - cache.set_cache(request_count_api_key, new_val) + await self.internal_usage_cache.async_set_cache( + request_count_api_key, new_val + ) else: raise HTTPException( status_code=429, @@ -75,7 +78,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): data: dict, call_type: str, ): - self.print_verbose(f"Inside Max Parallel Request Pre-Call Hook") + self.print_verbose("Inside Max Parallel Request Pre-Call Hook") api_key = user_api_key_dict.api_key max_parallel_requests = user_api_key_dict.max_parallel_requests if max_parallel_requests is None: @@ -90,7 +93,6 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): if rpm_limit is None: rpm_limit = sys.maxsize - self.user_api_key_cache = cache # save the api key cache for updating the value # ------------ # Setup values # ------------ @@ -98,7 +100,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): if global_max_parallel_requests is not None: # get value from cache _key = "global_max_parallel_requests" - current_global_requests = await cache.async_get_cache( + current_global_requests = await self.internal_usage_cache.async_get_cache( key=_key, local_only=True ) # check if below limit @@ -111,7 +113,9 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): ) # if below -> increment else: - await cache.async_increment_cache(key=_key, value=1, local_only=True) + await self.internal_usage_cache.async_increment_cache( + key=_key, value=1, local_only=True + ) current_date = datetime.now().strftime("%Y-%m-%d") current_hour = datetime.now().strftime("%H") @@ -123,7 +127,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): # CHECK IF REQUEST ALLOWED for key - current = cache.get_cache( + current = await self.internal_usage_cache.async_get_cache( key=request_count_api_key ) # {"current_requests": 1, "current_tpm": 1, "current_rpm": 10} self.print_verbose(f"current: {current}") @@ -143,7 +147,9 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): "current_tpm": 0, "current_rpm": 0, } - cache.set_cache(request_count_api_key, new_val) + await self.internal_usage_cache.async_set_cache( + request_count_api_key, new_val + ) elif ( int(current["current_requests"]) < max_parallel_requests and current["current_tpm"] < tpm_limit @@ -155,7 +161,9 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): "current_tpm": current["current_tpm"], "current_rpm": current["current_rpm"], } - cache.set_cache(request_count_api_key, new_val) + await self.internal_usage_cache.async_set_cache( + request_count_api_key, new_val + ) else: raise HTTPException( status_code=429, detail="Max parallel request limit reached." @@ -164,7 +172,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): # check if REQUEST ALLOWED for user_id user_id = user_api_key_dict.user_id if user_id is not None: - _user_id_rate_limits = await self.user_api_key_cache.async_get_cache( + _user_id_rate_limits = await self.internal_usage_cache.async_get_cache( key=user_id ) # get user tpm/rpm limits @@ -256,7 +264,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): try: - self.print_verbose(f"INSIDE parallel request limiter ASYNC SUCCESS LOGGING") + self.print_verbose("INSIDE parallel request limiter ASYNC SUCCESS LOGGING") global_max_parallel_requests = kwargs["litellm_params"]["metadata"].get( "global_max_parallel_requests", None ) @@ -269,9 +277,6 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): ) user_api_key_end_user_id = kwargs.get("user") - if self.user_api_key_cache is None: - return - # ------------ # Setup values # ------------ @@ -280,7 +285,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): # get value from cache _key = "global_max_parallel_requests" # decrement - await self.user_api_key_cache.async_increment_cache( + await self.internal_usage_cache.async_increment_cache( key=_key, value=-1, local_only=True ) @@ -303,7 +308,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): f"{user_api_key}::{precise_minute}::request_count" ) - current = self.user_api_key_cache.get_cache( + current = await self.internal_usage_cache.async_get_cache( key=request_count_api_key ) or { "current_requests": 1, @@ -320,7 +325,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): self.print_verbose( f"updated_value in success call: {new_val}, precise_minute: {precise_minute}" ) - self.user_api_key_cache.set_cache( + await self.internal_usage_cache.async_set_cache( request_count_api_key, new_val, ttl=60 ) # store in cache for 1 min. @@ -337,7 +342,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): f"{user_api_key_user_id}::{precise_minute}::request_count" ) - current = self.user_api_key_cache.get_cache( + current = await self.internal_usage_cache.async_get_cache( key=request_count_api_key ) or { "current_requests": 1, @@ -354,7 +359,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): self.print_verbose( f"updated_value in success call: {new_val}, precise_minute: {precise_minute}" ) - self.user_api_key_cache.set_cache( + await self.internal_usage_cache.async_set_cache( request_count_api_key, new_val, ttl=60 ) # store in cache for 1 min. @@ -371,7 +376,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): f"{user_api_key_team_id}::{precise_minute}::request_count" ) - current = self.user_api_key_cache.get_cache( + current = await self.internal_usage_cache.async_get_cache( key=request_count_api_key ) or { "current_requests": 1, @@ -388,7 +393,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): self.print_verbose( f"updated_value in success call: {new_val}, precise_minute: {precise_minute}" ) - self.user_api_key_cache.set_cache( + await self.internal_usage_cache.async_set_cache( request_count_api_key, new_val, ttl=60 ) # store in cache for 1 min. @@ -405,7 +410,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): f"{user_api_key_end_user_id}::{precise_minute}::request_count" ) - current = self.user_api_key_cache.get_cache( + current = await self.internal_usage_cache.async_get_cache( key=request_count_api_key ) or { "current_requests": 1, @@ -422,7 +427,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): self.print_verbose( f"updated_value in success call: {new_val}, precise_minute: {precise_minute}" ) - self.user_api_key_cache.set_cache( + await self.internal_usage_cache.async_set_cache( request_count_api_key, new_val, ttl=60 ) # store in cache for 1 min. @@ -442,9 +447,6 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): if user_api_key is None: return - if self.user_api_key_cache is None: - return - ## decrement call count if call failed if "Max parallel request limit reached" in str(kwargs["exception"]): pass # ignore failed calls due to max limit being reached @@ -457,12 +459,12 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): # get value from cache _key = "global_max_parallel_requests" current_global_requests = ( - await self.user_api_key_cache.async_get_cache( + await self.internal_usage_cache.async_get_cache( key=_key, local_only=True ) ) # decrement - await self.user_api_key_cache.async_increment_cache( + await self.internal_usage_cache.async_increment_cache( key=_key, value=-1, local_only=True ) @@ -478,7 +480,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): # ------------ # Update usage # ------------ - current = self.user_api_key_cache.get_cache( + current = await self.internal_usage_cache.async_get_cache( key=request_count_api_key ) or { "current_requests": 1, @@ -493,7 +495,7 @@ class _PROXY_MaxParallelRequestsHandler(CustomLogger): } self.print_verbose(f"updated_value in failure call: {new_val}") - self.user_api_key_cache.set_cache( + await self.internal_usage_cache.async_set_cache( request_count_api_key, new_val, ttl=60 ) # save in cache for up to 1 min. except Exception as e: diff --git a/litellm/proxy/litellm_pre_call_utils.py b/litellm/proxy/litellm_pre_call_utils.py index d8dc798f089..5aca61a96c8 100644 --- a/litellm/proxy/litellm_pre_call_utils.py +++ b/litellm/proxy/litellm_pre_call_utils.py @@ -104,6 +104,15 @@ async def add_litellm_data_to_request( data["metadata"]["user_api_key_team_alias"] = getattr( user_api_key_dict, "team_alias", None ) + + # Team spend, budget - used by prometheus.py + data["metadata"]["user_api_key_team_max_budget"] = user_api_key_dict.team_max_budget + data["metadata"]["user_api_key_team_spend"] = user_api_key_dict.team_spend + + # API Key spend, budget - used by prometheus.py + data["metadata"]["user_api_key_spend"] = user_api_key_dict.spend + data["metadata"]["user_api_key_max_budget"] = user_api_key_dict.max_budget + data["metadata"]["user_api_key_metadata"] = user_api_key_dict.metadata _headers = dict(request.headers) _headers.pop( diff --git a/litellm/proxy/management_endpoints/key_management_endpoints.py b/litellm/proxy/management_endpoints/key_management_endpoints.py new file mode 100644 index 00000000000..94d377f78fe --- /dev/null +++ b/litellm/proxy/management_endpoints/key_management_endpoints.py @@ -0,0 +1,926 @@ +""" +KEY MANAGEMENT + +All /key management endpoints + +/key/generate +/key/info +/key/update +/key/delete +""" + +import copy +import json +import uuid +import re +import traceback +import asyncio +import secrets +from typing import Optional, List +import fastapi +from fastapi import Depends, Request, APIRouter, Header, status +from fastapi import HTTPException +import litellm +from datetime import datetime, timedelta, timezone +from litellm._logging import verbose_proxy_logger +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy._types import * + +router = APIRouter() + + +@router.post( + "/key/generate", + tags=["key management"], + dependencies=[Depends(user_api_key_auth)], + response_model=GenerateKeyResponse, +) +async def generate_key_fn( + data: GenerateKeyRequest, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), + litellm_changed_by: Optional[str] = Header( + None, + description="The litellm-changed-by header enables tracking of actions performed by authorized users on behalf of other users, providing an audit trail for accountability", + ), +): + """ + Generate an API key based on the provided data. + + Docs: https://docs.litellm.ai/docs/proxy/virtual_keys + + Parameters: + - duration: Optional[str] - Specify the length of time the token is valid for. You can set duration as seconds ("30s"), minutes ("30m"), hours ("30h"), days ("30d"). + - key_alias: Optional[str] - User defined key alias + - team_id: Optional[str] - The team id of the key + - user_id: Optional[str] - The user id of the key + - models: Optional[list] - Model_name's a user is allowed to call. (if empty, key is allowed to call all models) + - aliases: Optional[dict] - Any alias mappings, on top of anything in the config.yaml model list. - https://docs.litellm.ai/docs/proxy/virtual_keys#managing-auth---upgradedowngrade-models + - config: Optional[dict] - any key-specific configs, overrides config in config.yaml + - spend: Optional[int] - Amount spent by key. Default is 0. Will be updated by proxy whenever key is used. https://docs.litellm.ai/docs/proxy/virtual_keys#managing-auth---tracking-spend + - send_invite_email: Optional[bool] - Whether to send an invite email to the user_id, with the generate key + - max_budget: Optional[float] - Specify max budget for a given key. + - max_parallel_requests: Optional[int] - Rate limit a user based on the number of parallel requests. Raises 429 error, if user's parallel requests > x. + - metadata: Optional[dict] - Metadata for key, store information for key. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" } + - permissions: Optional[dict] - key-specific permissions. Currently just used for turning off pii masking (if connected). Example - {"pii": false} + - model_max_budget: Optional[dict] - key-specific model budget in USD. Example - {"text-davinci-002": 0.5, "gpt-3.5-turbo": 0.5}. IF null or {} then no model specific budget. + + Examples: + + 1. Allow users to turn on/off pii masking + + ```bash + curl --location 'http://0.0.0.0:8000/key/generate' \ + --header 'Authorization: Bearer sk-1234' \ + --header 'Content-Type: application/json' \ + --data '{ + "permissions": {"allow_pii_controls": true} + }' + ``` + + Returns: + - key: (str) The generated api key + - expires: (datetime) Datetime object for when key expires. + - user_id: (str) Unique user id - used for tracking spend across multiple keys for same user id. + """ + try: + from litellm.proxy.proxy_server import ( + user_custom_key_generate, + prisma_client, + litellm_proxy_admin_name, + general_settings, + proxy_logging_obj, + create_audit_log_for_update, + ) + + verbose_proxy_logger.debug("entered /key/generate") + + if user_custom_key_generate is not None: + result = await user_custom_key_generate(data) + decision = result.get("decision", True) + message = result.get("message", "Authentication Failed - Custom Auth Rule") + if not decision: + raise HTTPException( + status_code=status.HTTP_403_FORBIDDEN, detail=message + ) + # check if user set default key/generate params on config.yaml + if litellm.default_key_generate_params is not None: + for elem in data: + key, value = elem + if value is None and key in [ + "max_budget", + "user_id", + "team_id", + "max_parallel_requests", + "tpm_limit", + "rpm_limit", + "budget_duration", + ]: + setattr( + data, key, litellm.default_key_generate_params.get(key, None) + ) + elif key == "models" and value == []: + setattr(data, key, litellm.default_key_generate_params.get(key, [])) + elif key == "metadata" and value == {}: + setattr(data, key, litellm.default_key_generate_params.get(key, {})) + + # check if user set default key/generate params on config.yaml + if litellm.upperbound_key_generate_params is not None: + for elem in data: + # if key in litellm.upperbound_key_generate_params, use the min of value and litellm.upperbound_key_generate_params[key] + key, value = elem + if ( + value is not None + and getattr(litellm.upperbound_key_generate_params, key, None) + is not None + ): + # if value is float/int + if key in [ + "max_budget", + "max_parallel_requests", + "tpm_limit", + "rpm_limit", + ]: + if value > getattr(litellm.upperbound_key_generate_params, key): + raise HTTPException( + status_code=400, + detail={ + "error": f"{key} is over max limit set in config - user_value={value}; max_value={getattr(litellm.upperbound_key_generate_params, key)}" + }, + ) + elif key == "budget_duration": + # budgets are in 1s, 1m, 1h, 1d, 1m (30s, 30m, 30h, 30d, 30m) + # compare the duration in seconds and max duration in seconds + upperbound_budget_duration = _duration_in_seconds( + duration=getattr( + litellm.upperbound_key_generate_params, key + ) + ) + user_set_budget_duration = _duration_in_seconds(duration=value) + if user_set_budget_duration > upperbound_budget_duration: + raise HTTPException( + status_code=400, + detail={ + "error": f"Budget duration is over max limit set in config - user_value={user_set_budget_duration}; max_value={upperbound_budget_duration}" + }, + ) + + # TODO: @ishaan-jaff: Migrate all budget tracking to use LiteLLM_BudgetTable + _budget_id = None + if prisma_client is not None and data.soft_budget is not None: + # create the Budget Row for the LiteLLM Verification Token + budget_row = LiteLLM_BudgetTable( + soft_budget=data.soft_budget, + model_max_budget=data.model_max_budget or {}, + ) + new_budget = prisma_client.jsonify_object( + budget_row.json(exclude_none=True) + ) + + _budget = await prisma_client.db.litellm_budgettable.create( + data={ + **new_budget, # type: ignore + "created_by": user_api_key_dict.user_id or litellm_proxy_admin_name, + "updated_by": user_api_key_dict.user_id or litellm_proxy_admin_name, + } + ) + _budget_id = getattr(_budget, "budget_id", None) + data_json = data.json() # type: ignore + # if we get max_budget passed to /key/generate, then use it as key_max_budget. Since generate_key_helper_fn is used to make new users + if "max_budget" in data_json: + data_json["key_max_budget"] = data_json.pop("max_budget", None) + if _budget_id is not None: + data_json["budget_id"] = _budget_id + + if "budget_duration" in data_json: + data_json["key_budget_duration"] = data_json.pop("budget_duration", None) + + response = await generate_key_helper_fn( + request_type="key", **data_json, table_name="key" + ) + + response["soft_budget"] = ( + data.soft_budget + ) # include the user-input soft budget in the response + + if data.send_invite_email is True: + if "email" not in general_settings.get("alerting", []): + raise ValueError( + "Email alerting not setup on config.yaml. Please set `alerting=['email']. \nDocs: https://docs.litellm.ai/docs/proxy/email`" + ) + event = WebhookEvent( + event="key_created", + event_group="key", + event_message=f"API Key Created", + token=response.get("token", ""), + spend=response.get("spend", 0.0), + max_budget=response.get("max_budget", 0.0), + user_id=response.get("user_id", None), + team_id=response.get("team_id", "Default Team"), + key_alias=response.get("key_alias", None), + ) + + # If user configured email alerting - send an Email letting their end-user know the key was created + asyncio.create_task( + proxy_logging_obj.slack_alerting_instance.send_key_created_or_user_invited_email( + webhook_event=event, + ) + ) + + # Enterprise Feature - Audit Logging. Enable with litellm.store_audit_logs = True + if litellm.store_audit_logs is True: + _updated_values = json.dumps(response, default=str) + asyncio.create_task( + create_audit_log_for_update( + request_data=LiteLLM_AuditLogs( + id=str(uuid.uuid4()), + updated_at=datetime.now(timezone.utc), + changed_by=litellm_changed_by + or user_api_key_dict.user_id + or litellm_proxy_admin_name, + changed_by_api_key=user_api_key_dict.api_key, + table_name=LitellmTableNames.KEY_TABLE_NAME, + object_id=response.get("token_id", ""), + action="created", + updated_values=_updated_values, + before_value=None, + ) + ) + ) + + return GenerateKeyResponse(**response) + except Exception as e: + verbose_proxy_logger.error( + "litellm.proxy.proxy_server.generate_key_fn(): Exception occured - {}".format( + str(e) + ) + ) + verbose_proxy_logger.debug(traceback.format_exc()) + if isinstance(e, HTTPException): + raise ProxyException( + message=getattr(e, "detail", f"Authentication Error({str(e)})"), + type="auth_error", + param=getattr(e, "param", "None"), + code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), + ) + elif isinstance(e, ProxyException): + raise e + raise ProxyException( + message="Authentication Error, " + str(e), + type="auth_error", + param=getattr(e, "param", "None"), + code=status.HTTP_400_BAD_REQUEST, + ) + + +@router.post( + "/key/update", tags=["key management"], dependencies=[Depends(user_api_key_auth)] +) +async def update_key_fn( + request: Request, + data: UpdateKeyRequest, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), + litellm_changed_by: Optional[str] = Header( + None, + description="The litellm-changed-by header enables tracking of actions performed by authorized users on behalf of other users, providing an audit trail for accountability", + ), +): + """ + Update an existing key + """ + from litellm.proxy.proxy_server import ( + user_custom_key_generate, + prisma_client, + litellm_proxy_admin_name, + general_settings, + proxy_logging_obj, + create_audit_log_for_update, + user_api_key_cache, + ) + + try: + data_json: dict = data.json() + key = data_json.pop("key") + # get the row from db + if prisma_client is None: + raise Exception("Not connected to DB!") + + existing_key_row = await prisma_client.get_data( + token=data.key, table_name="key", query_type="find_unique" + ) + + if existing_key_row is None: + raise HTTPException( + status_code=404, + detail={"error": f"Team not found, passed team_id={data.team_id}"}, + ) + + # get non default values for key + non_default_values = {} + for k, v in data_json.items(): + if v is not None and v not in ( + [], + {}, + 0, + ): # models default to [], spend defaults to 0, we should not reset these values + non_default_values[k] = v + + if "duration" in non_default_values: + duration = non_default_values.pop("duration") + duration_s = _duration_in_seconds(duration=duration) + expires = datetime.now(timezone.utc) + timedelta(seconds=duration_s) + non_default_values["expires"] = expires + + response = await prisma_client.update_data( + token=key, data={**non_default_values, "token": key} + ) + + # Delete - key from cache, since it's been updated! + # key updated - a new model could have been added to this key. it should not block requests after this is done + user_api_key_cache.delete_cache(key) + hashed_token = hash_token(key) + user_api_key_cache.delete_cache(hashed_token) + + # Enterprise Feature - Audit Logging. Enable with litellm.store_audit_logs = True + if litellm.store_audit_logs is True: + _updated_values = json.dumps(data_json, default=str) + + _before_value = existing_key_row.json(exclude_none=True) + _before_value = json.dumps(_before_value, default=str) + + asyncio.create_task( + create_audit_log_for_update( + request_data=LiteLLM_AuditLogs( + id=str(uuid.uuid4()), + updated_at=datetime.now(timezone.utc), + changed_by=litellm_changed_by + or user_api_key_dict.user_id + or litellm_proxy_admin_name, + changed_by_api_key=user_api_key_dict.api_key, + table_name=LitellmTableNames.KEY_TABLE_NAME, + object_id=data.key, + action="updated", + updated_values=_updated_values, + before_value=_before_value, + ) + ) + ) + + return {"key": key, **response["data"]} + # update based on remaining passed in values + except Exception as e: + if isinstance(e, HTTPException): + raise ProxyException( + message=getattr(e, "detail", f"Authentication Error({str(e)})"), + type="auth_error", + param=getattr(e, "param", "None"), + code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), + ) + elif isinstance(e, ProxyException): + raise e + raise ProxyException( + message="Authentication Error, " + str(e), + type="auth_error", + param=getattr(e, "param", "None"), + code=status.HTTP_400_BAD_REQUEST, + ) + + +@router.post( + "/key/delete", tags=["key management"], dependencies=[Depends(user_api_key_auth)] +) +async def delete_key_fn( + data: KeyRequest, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), + litellm_changed_by: Optional[str] = Header( + None, + description="The litellm-changed-by header enables tracking of actions performed by authorized users on behalf of other users, providing an audit trail for accountability", + ), +): + """ + Delete a key from the key management system. + + Parameters:: + - keys (List[str]): A list of keys or hashed keys to delete. Example {"keys": ["sk-QWrxEynunsNpV1zT48HIrw", "837e17519f44683334df5291321d97b8bf1098cd490e49e215f6fea935aa28be"]} + + Returns: + - deleted_keys (List[str]): A list of deleted keys. Example {"deleted_keys": ["sk-QWrxEynunsNpV1zT48HIrw", "837e17519f44683334df5291321d97b8bf1098cd490e49e215f6fea935aa28be"]} + + + Raises: + HTTPException: If an error occurs during key deletion. + """ + try: + from litellm.proxy.proxy_server import ( + user_custom_key_generate, + prisma_client, + litellm_proxy_admin_name, + general_settings, + proxy_logging_obj, + create_audit_log_for_update, + user_api_key_cache, + ) + + keys = data.keys + if len(keys) == 0: + raise ProxyException( + message=f"No keys provided, passed in: keys={keys}", + type="auth_error", + param="keys", + code=status.HTTP_400_BAD_REQUEST, + ) + + ## only allow user to delete keys they own + user_id = user_api_key_dict.user_id + verbose_proxy_logger.debug( + f"user_api_key_dict.user_role: {user_api_key_dict.user_role}" + ) + if ( + user_api_key_dict.user_role is not None + and user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN + ): + user_id = None # unless they're admin + + # Enterprise Feature - Audit Logging. Enable with litellm.store_audit_logs = True + # we do this after the first for loop, since first for loop is for validation. we only want this inserted after validation passes + if litellm.store_audit_logs is True: + # make an audit log for each team deleted + for key in data.keys: + key_row = await prisma_client.get_data( # type: ignore + token=key, table_name="key", query_type="find_unique" + ) + + key_row = key_row.json(exclude_none=True) + _key_row = json.dumps(key_row, default=str) + + asyncio.create_task( + create_audit_log_for_update( + request_data=LiteLLM_AuditLogs( + id=str(uuid.uuid4()), + updated_at=datetime.now(timezone.utc), + changed_by=litellm_changed_by + or user_api_key_dict.user_id + or litellm_proxy_admin_name, + changed_by_api_key=user_api_key_dict.api_key, + table_name=LitellmTableNames.KEY_TABLE_NAME, + object_id=key, + action="deleted", + updated_values="{}", + before_value=_key_row, + ) + ) + ) + + number_deleted_keys = await delete_verification_token( + tokens=keys, user_id=user_id + ) + verbose_proxy_logger.debug( + f"/key/delete - deleted_keys={number_deleted_keys['deleted_keys']}" + ) + + try: + assert len(keys) == number_deleted_keys["deleted_keys"] + except Exception as e: + raise HTTPException( + status_code=400, + detail={ + "error": f"Not all keys passed in were deleted. This probably means you don't have access to delete all the keys passed in. Keys passed in={len(keys)}, Deleted keys ={number_deleted_keys['deleted_keys']}" + }, + ) + + for key in keys: + user_api_key_cache.delete_cache(key) + # remove hash token from cache + hashed_token = hash_token(key) + user_api_key_cache.delete_cache(hashed_token) + + verbose_proxy_logger.debug( + f"/keys/delete - cache after delete: {user_api_key_cache.in_memory_cache.cache_dict}" + ) + + return {"deleted_keys": keys} + except Exception as e: + if isinstance(e, HTTPException): + raise ProxyException( + message=getattr(e, "detail", f"Authentication Error({str(e)})"), + type="auth_error", + param=getattr(e, "param", "None"), + code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), + ) + elif isinstance(e, ProxyException): + raise e + raise ProxyException( + message="Authentication Error, " + str(e), + type="auth_error", + param=getattr(e, "param", "None"), + code=status.HTTP_400_BAD_REQUEST, + ) + + +@router.post( + "/v2/key/info", tags=["key management"], dependencies=[Depends(user_api_key_auth)] +) +async def info_key_fn_v2( + data: Optional[KeyRequest] = None, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + Retrieve information about a list of keys. + + **New endpoint**. Currently admin only. + Parameters: + keys: Optional[list] = body parameter representing the key(s) in the request + user_api_key_dict: UserAPIKeyAuth = Dependency representing the user's API key + Returns: + Dict containing the key and its associated information + + Example Curl: + ``` + curl -X GET "http://0.0.0.0:8000/key/info" \ + -H "Authorization: Bearer sk-1234" \ + -d {"keys": ["sk-1", "sk-2", "sk-3"]} + ``` + """ + from litellm.proxy.proxy_server import ( + user_custom_key_generate, + prisma_client, + litellm_proxy_admin_name, + general_settings, + proxy_logging_obj, + create_audit_log_for_update, + ) + + try: + if prisma_client is None: + raise Exception( + f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + ) + if data is None: + raise HTTPException( + status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, + detail={"message": "Malformed request. No keys passed in."}, + ) + + key_info = await prisma_client.get_data( + token=data.keys, table_name="key", query_type="find_all" + ) + filtered_key_info = [] + for k in key_info: + try: + k = k.model_dump() # noqa + except: + # if using pydantic v1 + k = k.dict() + filtered_key_info.append(k) + return {"key": data.keys, "info": filtered_key_info} + + except Exception as e: + if isinstance(e, HTTPException): + raise ProxyException( + message=getattr(e, "detail", f"Authentication Error({str(e)})"), + type="auth_error", + param=getattr(e, "param", "None"), + code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), + ) + elif isinstance(e, ProxyException): + raise e + raise ProxyException( + message="Authentication Error, " + str(e), + type="auth_error", + param=getattr(e, "param", "None"), + code=status.HTTP_400_BAD_REQUEST, + ) + + +@router.get( + "/key/info", tags=["key management"], dependencies=[Depends(user_api_key_auth)] +) +async def info_key_fn( + key: Optional[str] = fastapi.Query( + default=None, description="Key in the request parameters" + ), + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + Retrieve information about a key. + Parameters: + key: Optional[str] = Query parameter representing the key in the request + user_api_key_dict: UserAPIKeyAuth = Dependency representing the user's API key + Returns: + Dict containing the key and its associated information + + Example Curl: + ``` + curl -X GET "http://0.0.0.0:8000/key/info?key=sk-02Wr4IAlN3NvPXvL5JVvDA" \ +-H "Authorization: Bearer sk-1234" + ``` + + Example Curl - if no key is passed, it will use the Key Passed in Authorization Header + ``` + curl -X GET "http://0.0.0.0:8000/key/info" \ +-H "Authorization: Bearer sk-02Wr4IAlN3NvPXvL5JVvDA" + ``` + """ + from litellm.proxy.proxy_server import ( + user_custom_key_generate, + prisma_client, + litellm_proxy_admin_name, + general_settings, + proxy_logging_obj, + create_audit_log_for_update, + ) + + try: + if prisma_client is None: + raise Exception( + f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + ) + if key == None: + key = user_api_key_dict.api_key + key_info = await prisma_client.get_data(token=key) + ## REMOVE HASHED TOKEN INFO BEFORE RETURNING ## + try: + key_info = key_info.model_dump() # noqa + except: + # if using pydantic v1 + key_info = key_info.dict() + key_info.pop("token") + return {"key": key, "info": key_info} + except Exception as e: + if isinstance(e, HTTPException): + raise ProxyException( + message=getattr(e, "detail", f"Authentication Error({str(e)})"), + type="auth_error", + param=getattr(e, "param", "None"), + code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), + ) + elif isinstance(e, ProxyException): + raise e + raise ProxyException( + message="Authentication Error, " + str(e), + type="auth_error", + param=getattr(e, "param", "None"), + code=status.HTTP_400_BAD_REQUEST, + ) + + +def _duration_in_seconds(duration: str): + match = re.match(r"(\d+)([smhd]?)", duration) + if not match: + raise ValueError("Invalid duration format") + + value, unit = match.groups() + value = int(value) + + if unit == "s": + return value + elif unit == "m": + return value * 60 + elif unit == "h": + return value * 3600 + elif unit == "d": + return value * 86400 + else: + raise ValueError("Unsupported duration unit") + + +async def generate_key_helper_fn( + request_type: Literal[ + "user", "key" + ], # identifies if this request is from /user/new or /key/generate + duration: Optional[str], + models: list, + aliases: dict, + config: dict, + spend: float, + key_max_budget: Optional[float] = None, # key_max_budget is used to Budget Per key + key_budget_duration: Optional[str] = None, + budget_id: Optional[float] = None, # budget id <-> LiteLLM_BudgetTable + soft_budget: Optional[ + float + ] = None, # soft_budget is used to set soft Budgets Per user + max_budget: Optional[float] = None, # max_budget is used to Budget Per user + budget_duration: Optional[str] = None, # max_budget is used to Budget Per user + token: Optional[str] = None, + user_id: Optional[str] = None, + team_id: Optional[str] = None, + user_email: Optional[str] = None, + user_role: Optional[str] = None, + max_parallel_requests: Optional[int] = None, + metadata: Optional[dict] = {}, + tpm_limit: Optional[int] = None, + rpm_limit: Optional[int] = None, + query_type: Literal["insert_data", "update_data"] = "insert_data", + update_key_values: Optional[dict] = None, + key_alias: Optional[str] = None, + allowed_cache_controls: Optional[list] = [], + permissions: Optional[dict] = {}, + model_max_budget: Optional[dict] = {}, + teams: Optional[list] = None, + organization_id: Optional[str] = None, + table_name: Optional[Literal["key", "user"]] = None, + send_invite_email: Optional[bool] = None, +): + from litellm.proxy.proxy_server import ( + prisma_client, + custom_db_client, + litellm_proxy_budget_name, + premium_user, + ) + + if prisma_client is None and custom_db_client is None: + raise Exception( + f"Connect Proxy to database to generate keys - https://docs.litellm.ai/docs/proxy/virtual_keys " + ) + + if token is None: + token = f"sk-{secrets.token_urlsafe(16)}" + + if duration is None: # allow tokens that never expire + expires = None + else: + duration_s = _duration_in_seconds(duration=duration) + expires = datetime.now(timezone.utc) + timedelta(seconds=duration_s) + + if key_budget_duration is None: # one-time budget + key_reset_at = None + else: + duration_s = _duration_in_seconds(duration=key_budget_duration) + key_reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) + + if budget_duration is None: # one-time budget + reset_at = None + else: + duration_s = _duration_in_seconds(duration=budget_duration) + reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) + + aliases_json = json.dumps(aliases) + config_json = json.dumps(config) + permissions_json = json.dumps(permissions) + metadata_json = json.dumps(metadata) + model_max_budget_json = json.dumps(model_max_budget) + user_role = user_role + tpm_limit = tpm_limit + rpm_limit = rpm_limit + allowed_cache_controls = allowed_cache_controls + + try: + # Create a new verification token (you may want to enhance this logic based on your needs) + user_data = { + "max_budget": max_budget, + "user_email": user_email, + "user_id": user_id, + "team_id": team_id, + "organization_id": organization_id, + "user_role": user_role, + "spend": spend, + "models": models, + "max_parallel_requests": max_parallel_requests, + "tpm_limit": tpm_limit, + "rpm_limit": rpm_limit, + "budget_duration": budget_duration, + "budget_reset_at": reset_at, + "allowed_cache_controls": allowed_cache_controls, + } + if teams is not None: + user_data["teams"] = teams + key_data = { + "token": token, + "key_alias": key_alias, + "expires": expires, + "models": models, + "aliases": aliases_json, + "config": config_json, + "spend": spend, + "max_budget": key_max_budget, + "user_id": user_id, + "team_id": team_id, + "max_parallel_requests": max_parallel_requests, + "metadata": metadata_json, + "tpm_limit": tpm_limit, + "rpm_limit": rpm_limit, + "budget_duration": key_budget_duration, + "budget_reset_at": key_reset_at, + "allowed_cache_controls": allowed_cache_controls, + "permissions": permissions_json, + "model_max_budget": model_max_budget_json, + "budget_id": budget_id, + } + + if ( + litellm.get_secret("DISABLE_KEY_NAME", False) == True + ): # allow user to disable storing abbreviated key name (shown in UI, to help figure out which key spent how much) + pass + else: + key_data["key_name"] = f"sk-...{token[-4:]}" + saved_token = copy.deepcopy(key_data) + if isinstance(saved_token["aliases"], str): + saved_token["aliases"] = json.loads(saved_token["aliases"]) + if isinstance(saved_token["config"], str): + saved_token["config"] = json.loads(saved_token["config"]) + if isinstance(saved_token["metadata"], str): + saved_token["metadata"] = json.loads(saved_token["metadata"]) + if isinstance(saved_token["permissions"], str): + if ( + "get_spend_routes" in saved_token["permissions"] + and premium_user != True + ): + raise ValueError( + "get_spend_routes permission is only available for LiteLLM Enterprise users" + ) + + saved_token["permissions"] = json.loads(saved_token["permissions"]) + if isinstance(saved_token["model_max_budget"], str): + saved_token["model_max_budget"] = json.loads( + saved_token["model_max_budget"] + ) + + if saved_token.get("expires", None) is not None and isinstance( + saved_token["expires"], datetime + ): + saved_token["expires"] = saved_token["expires"].isoformat() + if prisma_client is not None: + if ( + table_name is None or table_name == "user" + ): # do not auto-create users for `/key/generate` + ## CREATE USER (If necessary) + if query_type == "insert_data": + user_row = await prisma_client.insert_data( + data=user_data, table_name="user" + ) + ## use default user model list if no key-specific model list provided + if len(user_row.models) > 0 and len(key_data["models"]) == 0: # type: ignore + key_data["models"] = user_row.models + elif query_type == "update_data": + user_row = await prisma_client.update_data( + data=user_data, + table_name="user", + update_key_values=update_key_values, + ) + if user_id == litellm_proxy_budget_name or ( + table_name is not None and table_name == "user" + ): + # do not create a key for litellm_proxy_budget_name or if table name is set to just 'user' + # we only need to ensure this exists in the user table + # the LiteLLM_VerificationToken table will increase in size if we don't do this check + return user_data + + ## CREATE KEY + verbose_proxy_logger.debug("prisma_client: Creating Key= %s", key_data) + create_key_response = await prisma_client.insert_data( + data=key_data, table_name="key" + ) + key_data["token_id"] = getattr(create_key_response, "token", None) + except Exception as e: + verbose_proxy_logger.error( + "litellm.proxy.proxy_server.generate_key_helper_fn(): Exception occured - {}".format( + str(e) + ) + ) + verbose_proxy_logger.debug(traceback.format_exc()) + if isinstance(e, HTTPException): + raise e + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail={"error": "Internal Server Error."}, + ) + + # Add budget related info in key_data - this ensures it's returned + key_data["budget_id"] = budget_id + + if request_type == "user": + # if this is a /user/new request update the key_date with user_data fields + key_data.update(user_data) + return key_data + + +async def delete_verification_token(tokens: List, user_id: Optional[str] = None): + from litellm.proxy.proxy_server import prisma_client, litellm_proxy_admin_name + + try: + if prisma_client: + # Assuming 'db' is your Prisma Client instance + # check if admin making request - don't filter by user-id + if user_id == litellm_proxy_admin_name: + deleted_tokens = await prisma_client.delete_data(tokens=tokens) + # else + else: + deleted_tokens = await prisma_client.delete_data( + tokens=tokens, user_id=user_id + ) + _num_deleted_tokens = deleted_tokens.get("deleted_keys", 0) + if _num_deleted_tokens != len(tokens): + raise Exception( + "Failed to delete all tokens. Tried to delete tokens that don't belong to user: " + + str(user_id) + ) + else: + raise Exception("DB not connected. prisma_client is None") + except Exception as e: + verbose_proxy_logger.error( + "litellm.proxy.proxy_server.delete_verification_token(): Exception occured - {}".format( + str(e) + ) + ) + verbose_proxy_logger.debug(traceback.format_exc()) + raise e + return deleted_tokens diff --git a/litellm/proxy/management_endpoints/team_endpoints.py b/litellm/proxy/management_endpoints/team_endpoints.py new file mode 100644 index 00000000000..50244ee23a4 --- /dev/null +++ b/litellm/proxy/management_endpoints/team_endpoints.py @@ -0,0 +1,899 @@ +from typing import Optional, List +import fastapi +from fastapi import Depends, Request, APIRouter, Header, status +from fastapi import HTTPException +import copy +import json +import uuid +import litellm +import asyncio +from datetime import datetime, timedelta, timezone +from litellm._logging import verbose_proxy_logger +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +from litellm.proxy._types import ( + UserAPIKeyAuth, + LiteLLM_TeamTable, + LiteLLM_ModelTable, + LitellmUserRoles, + NewTeamRequest, + TeamMemberAddRequest, + UpdateTeamRequest, + BlockTeamRequest, + DeleteTeamRequest, + Member, + LitellmTableNames, + LiteLLM_AuditLogs, + TeamMemberDeleteRequest, + ProxyException, + CommonProxyErrors, +) +from litellm.proxy.management_helpers.utils import ( + add_new_member, + management_endpoint_wrapper, +) + +router = APIRouter() + + +#### TEAM MANAGEMENT #### +@router.post( + "/team/new", + tags=["team management"], + dependencies=[Depends(user_api_key_auth)], + response_model=LiteLLM_TeamTable, +) +@management_endpoint_wrapper +async def new_team( + data: NewTeamRequest, + http_request: Request, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), + litellm_changed_by: Optional[str] = Header( + None, + description="The litellm-changed-by header enables tracking of actions performed by authorized users on behalf of other users, providing an audit trail for accountability", + ), +): + """ + Allow users to create a new team. Apply user permissions to their team. + + 👉 [Detailed Doc on setting team budgets](https://docs.litellm.ai/docs/proxy/team_budgets) + + + Parameters: + - team_alias: Optional[str] - User defined team alias + - team_id: Optional[str] - The team id of the user. If none passed, we'll generate it. + - members_with_roles: List[{"role": "admin" or "user", "user_id": ""}] - A list of users and their roles in the team. Get user_id when making a new user via `/user/new`. + - metadata: Optional[dict] - Metadata for team, store information for team. Example metadata = {"extra_info": "some info"} + - tpm_limit: Optional[int] - The TPM (Tokens Per Minute) limit for this team - all keys with this team_id will have at max this TPM limit + - rpm_limit: Optional[int] - The RPM (Requests Per Minute) limit for this team - all keys associated with this team_id will have at max this RPM limit + - max_budget: Optional[float] - The maximum budget allocated to the team - all keys for this team_id will have at max this max_budget + - budget_duration: Optional[str] - The duration of the budget for the team. Doc [here](https://docs.litellm.ai/docs/proxy/team_budgets) + - models: Optional[list] - A list of models associated with the team - all keys for this team_id will have at most, these models. If empty, assumes all models are allowed. + - blocked: bool - Flag indicating if the team is blocked or not - will stop all calls from keys with this team_id. + + Returns: + - team_id: (str) Unique team id - used for tracking spend across multiple keys for same team id. + + _deprecated_params: + - admins: list - A list of user_id's for the admin role + - users: list - A list of user_id's for the user role + + Example Request: + ``` + curl --location 'http://0.0.0.0:4000/team/new' \ + + --header 'Authorization: Bearer sk-1234' \ + + --header 'Content-Type: application/json' \ + + --data '{ + "team_alias": "my-new-team_2", + "members_with_roles": [{"role": "admin", "user_id": "user-1234"}, + {"role": "user", "user_id": "user-2434"}] + }' + + ``` + + ``` + curl --location 'http://0.0.0.0:4000/team/new' \ + + --header 'Authorization: Bearer sk-1234' \ + + --header 'Content-Type: application/json' \ + + --data '{ + "team_alias": "QA Prod Bot", + "max_budget": 0.000000001, + "budget_duration": "1d" + }' + + ``` + """ + from litellm.proxy.proxy_server import ( + prisma_client, + litellm_proxy_admin_name, + create_audit_log_for_update, + _duration_in_seconds, + ) + + if prisma_client is None: + raise HTTPException(status_code=500, detail={"error": "No db connected"}) + + if data.team_id is None: + data.team_id = str(uuid.uuid4()) + else: + # Check if team_id exists already + _existing_team_id = await prisma_client.get_data( + team_id=data.team_id, table_name="team", query_type="find_unique" + ) + if _existing_team_id is not None: + raise HTTPException( + status_code=400, + detail={ + "error": f"Team id = {data.team_id} already exists. Please use a different team id." + }, + ) + + if ( + user_api_key_dict.user_role is None + or user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN + ): # don't restrict proxy admin + if ( + data.tpm_limit is not None + and user_api_key_dict.tpm_limit is not None + and data.tpm_limit > user_api_key_dict.tpm_limit + ): + raise HTTPException( + status_code=400, + detail={ + "error": f"tpm limit higher than user max. User tpm limit={user_api_key_dict.tpm_limit}. User role={user_api_key_dict.user_role}" + }, + ) + + if ( + data.rpm_limit is not None + and user_api_key_dict.rpm_limit is not None + and data.rpm_limit > user_api_key_dict.rpm_limit + ): + raise HTTPException( + status_code=400, + detail={ + "error": f"rpm limit higher than user max. User rpm limit={user_api_key_dict.rpm_limit}. User role={user_api_key_dict.user_role}" + }, + ) + + if ( + data.max_budget is not None + and user_api_key_dict.max_budget is not None + and data.max_budget > user_api_key_dict.max_budget + ): + raise HTTPException( + status_code=400, + detail={ + "error": f"max budget higher than user max. User max budget={user_api_key_dict.max_budget}. User role={user_api_key_dict.user_role}" + }, + ) + + if data.models is not None and len(user_api_key_dict.models) > 0: + for m in data.models: + if m not in user_api_key_dict.models: + raise HTTPException( + status_code=400, + detail={ + "error": f"Model not in allowed user models. User allowed models={user_api_key_dict.models}. User id={user_api_key_dict.user_id}" + }, + ) + + if user_api_key_dict.user_id is not None: + creating_user_in_list = False + for member in data.members_with_roles: + if member.user_id == user_api_key_dict.user_id: + creating_user_in_list = True + + if creating_user_in_list == False: + data.members_with_roles.append( + Member(role="admin", user_id=user_api_key_dict.user_id) + ) + + ## ADD TO MODEL TABLE + _model_id = None + if data.model_aliases is not None and isinstance(data.model_aliases, dict): + litellm_modeltable = LiteLLM_ModelTable( + model_aliases=json.dumps(data.model_aliases), + created_by=user_api_key_dict.user_id or litellm_proxy_admin_name, + updated_by=user_api_key_dict.user_id or litellm_proxy_admin_name, + ) + model_dict = await prisma_client.db.litellm_modeltable.create( + {**litellm_modeltable.json(exclude_none=True)} # type: ignore + ) # type: ignore + + _model_id = model_dict.id + + ## ADD TO TEAM TABLE + complete_team_data = LiteLLM_TeamTable( + **data.json(), + model_id=_model_id, + ) + + # If budget_duration is set, set `budget_reset_at` + if complete_team_data.budget_duration is not None: + duration_s = _duration_in_seconds(duration=complete_team_data.budget_duration) + reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) + complete_team_data.budget_reset_at = reset_at + + team_row = await prisma_client.insert_data( + data=complete_team_data.json(exclude_none=True), table_name="team" + ) + + ## ADD TEAM ID TO USER TABLE ## + for user in complete_team_data.members_with_roles: + ## add team id to user row ## + await prisma_client.update_data( + user_id=user.user_id, + data={"user_id": user.user_id, "teams": [team_row.team_id]}, + update_key_values_custom_query={ + "teams": { + "push ": [team_row.team_id], + } + }, + ) + + # Enterprise Feature - Audit Logging. Enable with litellm.store_audit_logs = True + if litellm.store_audit_logs is True: + _updated_values = complete_team_data.json(exclude_none=True) + + _updated_values = json.dumps(_updated_values, default=str) + + asyncio.create_task( + create_audit_log_for_update( + request_data=LiteLLM_AuditLogs( + id=str(uuid.uuid4()), + updated_at=datetime.now(timezone.utc), + changed_by=litellm_changed_by + or user_api_key_dict.user_id + or litellm_proxy_admin_name, + changed_by_api_key=user_api_key_dict.api_key, + table_name=LitellmTableNames.TEAM_TABLE_NAME, + object_id=data.team_id, + action="created", + updated_values=_updated_values, + before_value=None, + ) + ) + ) + + try: + return team_row.model_dump() + except Exception as e: + return team_row.dict() + + +@router.post( + "/team/update", tags=["team management"], dependencies=[Depends(user_api_key_auth)] +) +@management_endpoint_wrapper +async def update_team( + data: UpdateTeamRequest, + http_request: Request, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), + litellm_changed_by: Optional[str] = Header( + None, + description="The litellm-changed-by header enables tracking of actions performed by authorized users on behalf of other users, providing an audit trail for accountability", + ), +): + """ + Use `/team/member_add` AND `/team/member/delete` to add/remove new team members + + You can now update team budget / rate limits via /team/update + + Parameters: + - team_id: str - The team id of the user. Required param. + - team_alias: Optional[str] - User defined team alias + - metadata: Optional[dict] - Metadata for team, store information for team. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" } + - tpm_limit: Optional[int] - The TPM (Tokens Per Minute) limit for this team - all keys with this team_id will have at max this TPM limit + - rpm_limit: Optional[int] - The RPM (Requests Per Minute) limit for this team - all keys associated with this team_id will have at max this RPM limit + - max_budget: Optional[float] - The maximum budget allocated to the team - all keys for this team_id will have at max this max_budget + - budget_duration: Optional[str] - The duration of the budget for the team. Doc [here](https://docs.litellm.ai/docs/proxy/team_budgets) + - models: Optional[list] - A list of models associated with the team - all keys for this team_id will have at most, these models. If empty, assumes all models are allowed. + - blocked: bool - Flag indicating if the team is blocked or not - will stop all calls from keys with this team_id. + + Example - update team TPM Limit + + ``` + curl --location 'http://0.0.0.0:8000/team/update' \ + + --header 'Authorization: Bearer sk-1234' \ + + --header 'Content-Type: application/json' \ + + --data-raw '{ + "team_id": "litellm-test-client-id-new", + "tpm_limit": 100 + }' + ``` + + Example - Update Team `max_budget` budget + ``` + curl --location 'http://0.0.0.0:8000/team/update' \ + + --header 'Authorization: Bearer sk-1234' \ + + --header 'Content-Type: application/json' \ + + --data-raw '{ + "team_id": "litellm-test-client-id-new", + "max_budget": 10 + }' + ``` + """ + from litellm.proxy.proxy_server import ( + prisma_client, + litellm_proxy_admin_name, + create_audit_log_for_update, + _duration_in_seconds, + ) + + if prisma_client is None: + raise HTTPException(status_code=500, detail={"error": "No db connected"}) + + if data.team_id is None: + raise HTTPException(status_code=400, detail={"error": "No team id passed in"}) + verbose_proxy_logger.debug("/team/update - %s", data) + + existing_team_row = await prisma_client.get_data( + team_id=data.team_id, table_name="team", query_type="find_unique" + ) + if existing_team_row is None: + raise HTTPException( + status_code=404, + detail={"error": f"Team not found, passed team_id={data.team_id}"}, + ) + + updated_kv = data.json(exclude_none=True) + + # Check budget_duration and budget_reset_at + if data.budget_duration is not None: + duration_s = _duration_in_seconds(duration=data.budget_duration) + reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) + + # set the budget_reset_at in DB + updated_kv["budget_reset_at"] = reset_at + + team_row = await prisma_client.update_data( + update_key_values=updated_kv, + data=updated_kv, + table_name="team", + team_id=data.team_id, + ) + + # Enterprise Feature - Audit Logging. Enable with litellm.store_audit_logs = True + if litellm.store_audit_logs is True: + _before_value = existing_team_row.json(exclude_none=True) + _before_value = json.dumps(_before_value, default=str) + _after_value: str = json.dumps(updated_kv, default=str) + + asyncio.create_task( + create_audit_log_for_update( + request_data=LiteLLM_AuditLogs( + id=str(uuid.uuid4()), + updated_at=datetime.now(timezone.utc), + changed_by=litellm_changed_by + or user_api_key_dict.user_id + or litellm_proxy_admin_name, + changed_by_api_key=user_api_key_dict.api_key, + table_name=LitellmTableNames.TEAM_TABLE_NAME, + object_id=data.team_id, + action="updated", + updated_values=_after_value, + before_value=_before_value, + ) + ) + ) + + return team_row + + +@router.post( + "/team/member_add", + tags=["team management"], + dependencies=[Depends(user_api_key_auth)], +) +@management_endpoint_wrapper +async def team_member_add( + data: TeamMemberAddRequest, + http_request: Request, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + [BETA] + + Add new members (either via user_email or user_id) to a team + + If user doesn't exist, new user row will also be added to User Table + + ``` + + curl -X POST 'http://0.0.0.0:4000/team/member_add' \ + -H 'Authorization: Bearer sk-1234' \ + -H 'Content-Type: application/json' \ + -d '{"team_id": "45e3e396-ee08-4a61-a88e-16b3ce7e0849", "member": {"role": "user", "user_id": "krrish247652@berri.ai"}}' + + ``` + """ + from litellm.proxy.proxy_server import ( + prisma_client, + litellm_proxy_admin_name, + create_audit_log_for_update, + _duration_in_seconds, + ) + + if prisma_client is None: + raise HTTPException(status_code=500, detail={"error": "No db connected"}) + + if data.team_id is None: + raise HTTPException(status_code=400, detail={"error": "No team id passed in"}) + + if data.member is None: + raise HTTPException( + status_code=400, detail={"error": "No member/members passed in"} + ) + + existing_team_row = await prisma_client.db.litellm_teamtable.find_unique( + where={"team_id": data.team_id} + ) + if existing_team_row is None: + raise HTTPException( + status_code=404, + detail={ + "error": f"Team not found for team_id={getattr(data, 'team_id', None)}" + }, + ) + + complete_team_data = LiteLLM_TeamTable(**existing_team_row.model_dump()) + + if isinstance(data.member, Member): + # add to team db + new_member = data.member + + complete_team_data.members_with_roles.append(new_member) + + elif isinstance(data.member, List): + # add to team db + new_members = data.member + + complete_team_data.members_with_roles.extend(new_members) + + # ADD MEMBER TO TEAM + _db_team_members = [m.model_dump() for m in complete_team_data.members_with_roles] + updated_team = await prisma_client.db.litellm_teamtable.update( + where={"team_id": data.team_id}, + data={"members_with_roles": json.dumps(_db_team_members)}, # type: ignore + ) + + if isinstance(data.member, Member): + await add_new_member( + new_member=data.member, + max_budget_in_team=data.max_budget_in_team, + prisma_client=prisma_client, + user_api_key_dict=user_api_key_dict, + litellm_proxy_admin_name=litellm_proxy_admin_name, + team_id=data.team_id, + ) + elif isinstance(data.member, List): + tasks: List = [] + for m in data.member: + await add_new_member( + new_member=m, + max_budget_in_team=data.max_budget_in_team, + prisma_client=prisma_client, + user_api_key_dict=user_api_key_dict, + litellm_proxy_admin_name=litellm_proxy_admin_name, + team_id=data.team_id, + ) + await asyncio.gather(*tasks) + + return updated_team + + +@router.post( + "/team/member_delete", + tags=["team management"], + dependencies=[Depends(user_api_key_auth)], +) +@management_endpoint_wrapper +async def team_member_delete( + data: TeamMemberDeleteRequest, + http_request: Request, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + [BETA] + + delete members (either via user_email or user_id) from a team + + If user doesn't exist, an exception will be raised + ``` + curl -X POST 'http://0.0.0.0:8000/team/update' \ + + -H 'Authorization: Bearer sk-1234' \ + + -H 'Content-Type: application/json' \ + + -D '{ + "team_id": "45e3e396-ee08-4a61-a88e-16b3ce7e0849", + "user_id": "krrish247652@berri.ai" + }' + ``` + """ + from litellm.proxy.proxy_server import ( + prisma_client, + litellm_proxy_admin_name, + create_audit_log_for_update, + _duration_in_seconds, + ) + + if prisma_client is None: + raise HTTPException(status_code=500, detail={"error": "No db connected"}) + + if data.team_id is None: + raise HTTPException(status_code=400, detail={"error": "No team id passed in"}) + + if data.user_id is None and data.user_email is None: + raise HTTPException( + status_code=400, + detail={"error": "Either user_id or user_email needs to be passed in"}, + ) + + _existing_team_row = await prisma_client.db.litellm_teamtable.find_unique( + where={"team_id": data.team_id} + ) + + if _existing_team_row is None: + raise HTTPException( + status_code=400, + detail={"error": "Team id={} does not exist in db".format(data.team_id)}, + ) + existing_team_row = LiteLLM_TeamTable(**_existing_team_row.model_dump()) + + ## DELETE MEMBER FROM TEAM + new_team_members: List[Member] = [] + for m in existing_team_row.members_with_roles: + if ( + data.user_id is not None + and m.user_id is not None + and data.user_id == m.user_id + ): + continue + elif ( + data.user_email is not None + and m.user_email is not None + and data.user_email == m.user_email + ): + continue + new_team_members.append(m) + existing_team_row.members_with_roles = new_team_members + + _db_new_team_members: List[dict] = [m.model_dump() for m in new_team_members] + + _ = await prisma_client.db.litellm_teamtable.update( + where={ + "team_id": data.team_id, + }, + data={"members_with_roles": json.dumps(_db_new_team_members)}, # type: ignore + ) + + ## DELETE TEAM ID from USER ROW, IF EXISTS ## + # get user row + key_val = {} + if data.user_id is not None: + key_val["user_id"] = data.user_id + elif data.user_email is not None: + key_val["user_email"] = data.user_email + existing_user_rows = await prisma_client.db.litellm_usertable.find_many( + where=key_val # type: ignore + ) + + if existing_user_rows is not None and ( + isinstance(existing_user_rows, list) and len(existing_user_rows) > 0 + ): + for existing_user in existing_user_rows: + team_list = [] + if data.team_id in existing_user.teams: + team_list = existing_user.teams + team_list.remove(data.team_id) + await prisma_client.db.litellm_usertable.update( + where={ + "user_id": existing_user.user_id, + }, + data={"teams": {"set": team_list}}, + ) + + return existing_team_row + + +@router.post( + "/team/delete", tags=["team management"], dependencies=[Depends(user_api_key_auth)] +) +@management_endpoint_wrapper +async def delete_team( + data: DeleteTeamRequest, + http_request: Request, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), + litellm_changed_by: Optional[str] = Header( + None, + description="The litellm-changed-by header enables tracking of actions performed by authorized users on behalf of other users, providing an audit trail for accountability", + ), +): + """ + delete team and associated team keys + + ``` + curl --location 'http://0.0.0.0:8000/team/delete' \ + + --header 'Authorization: Bearer sk-1234' \ + + --header 'Content-Type: application/json' \ + + --data-raw '{ + "team_ids": ["45e3e396-ee08-4a61-a88e-16b3ce7e0849"] + }' + ``` + """ + from litellm.proxy.proxy_server import ( + prisma_client, + litellm_proxy_admin_name, + create_audit_log_for_update, + _duration_in_seconds, + ) + + if prisma_client is None: + raise HTTPException(status_code=500, detail={"error": "No db connected"}) + + if data.team_ids is None: + raise HTTPException(status_code=400, detail={"error": "No team id passed in"}) + + # check that all teams passed exist + for team_id in data.team_ids: + team_row = await prisma_client.get_data( # type: ignore + team_id=team_id, table_name="team", query_type="find_unique" + ) + if team_row is None: + raise HTTPException( + status_code=404, + detail={"error": f"Team not found, passed team_id={team_id}"}, + ) + + # Enterprise Feature - Audit Logging. Enable with litellm.store_audit_logs = True + # we do this after the first for loop, since first for loop is for validation. we only want this inserted after validation passes + if litellm.store_audit_logs is True: + # make an audit log for each team deleted + for team_id in data.team_ids: + team_row = await prisma_client.get_data( # type: ignore + team_id=team_id, table_name="team", query_type="find_unique" + ) + + _team_row = team_row.json(exclude_none=True) + + asyncio.create_task( + create_audit_log_for_update( + request_data=LiteLLM_AuditLogs( + id=str(uuid.uuid4()), + updated_at=datetime.now(timezone.utc), + changed_by=litellm_changed_by + or user_api_key_dict.user_id + or litellm_proxy_admin_name, + changed_by_api_key=user_api_key_dict.api_key, + table_name=LitellmTableNames.TEAM_TABLE_NAME, + object_id=team_id, + action="deleted", + updated_values="{}", + before_value=_team_row, + ) + ) + ) + + # End of Audit logging + + ## DELETE ASSOCIATED KEYS + await prisma_client.delete_data(team_id_list=data.team_ids, table_name="key") + ## DELETE TEAMS + deleted_teams = await prisma_client.delete_data( + team_id_list=data.team_ids, table_name="team" + ) + return deleted_teams + + +@router.get( + "/team/info", tags=["team management"], dependencies=[Depends(user_api_key_auth)] +) +@management_endpoint_wrapper +async def team_info( + http_request: Request, + team_id: str = fastapi.Query( + default=None, description="Team ID in the request parameters" + ), +): + """ + get info on team + related keys + + ``` + curl --location 'http://localhost:4000/team/info' \ + --header 'Authorization: Bearer sk-1234' \ + --header 'Content-Type: application/json' \ + --data '{ + "teams": ["",..] + }' + ``` + """ + from litellm.proxy.proxy_server import ( + prisma_client, + litellm_proxy_admin_name, + create_audit_log_for_update, + _duration_in_seconds, + ) + + try: + if prisma_client is None: + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail={ + "error": f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + }, + ) + if team_id is None: + raise HTTPException( + status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, + detail={"message": "Malformed request. No team id passed in."}, + ) + + team_info = await prisma_client.get_data( + team_id=team_id, table_name="team", query_type="find_unique" + ) + if team_info is None: + raise HTTPException( + status_code=status.HTTP_404_NOT_FOUND, + detail={"message": f"Team not found, passed team id: {team_id}."}, + ) + + ## GET ALL KEYS ## + keys = await prisma_client.get_data( + team_id=team_id, + table_name="key", + query_type="find_all", + expires=datetime.now(), + ) + + if team_info is None: + ## make sure we still return a total spend ## + spend = 0 + for k in keys: + spend += getattr(k, "spend", 0) + team_info = {"spend": spend} + + ## REMOVE HASHED TOKEN INFO before returning ## + for key in keys: + try: + key = key.model_dump() # noqa + except: + # if using pydantic v1 + key = key.dict() + key.pop("token", None) + return {"team_id": team_id, "team_info": team_info, "keys": keys} + + except Exception as e: + if isinstance(e, HTTPException): + raise ProxyException( + message=getattr(e, "detail", f"Authentication Error({str(e)})"), + type="auth_error", + param=getattr(e, "param", "None"), + code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), + ) + elif isinstance(e, ProxyException): + raise e + raise ProxyException( + message="Authentication Error, " + str(e), + type="auth_error", + param=getattr(e, "param", "None"), + code=status.HTTP_400_BAD_REQUEST, + ) + + +@router.post( + "/team/block", tags=["team management"], dependencies=[Depends(user_api_key_auth)] +) +@management_endpoint_wrapper +async def block_team( + data: BlockTeamRequest, + http_request: Request, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + Blocks all calls from keys with this team id. + """ + from litellm.proxy.proxy_server import ( + prisma_client, + litellm_proxy_admin_name, + create_audit_log_for_update, + _duration_in_seconds, + ) + + if prisma_client is None: + raise Exception("No DB Connected.") + + record = await prisma_client.db.litellm_teamtable.update( + where={"team_id": data.team_id}, data={"blocked": True} # type: ignore + ) + + return record + + +@router.post( + "/team/unblock", tags=["team management"], dependencies=[Depends(user_api_key_auth)] +) +@management_endpoint_wrapper +async def unblock_team( + data: BlockTeamRequest, + http_request: Request, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + Blocks all calls from keys with this team id. + """ + from litellm.proxy.proxy_server import ( + prisma_client, + litellm_proxy_admin_name, + create_audit_log_for_update, + _duration_in_seconds, + ) + + if prisma_client is None: + raise Exception("No DB Connected.") + + record = await prisma_client.db.litellm_teamtable.update( + where={"team_id": data.team_id}, data={"blocked": False} # type: ignore + ) + + return record + + +@router.get( + "/team/list", tags=["team management"], dependencies=[Depends(user_api_key_auth)] +) +@management_endpoint_wrapper +async def list_team( + http_request: Request, + user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), +): + """ + [Admin-only] List all available teams + + ``` + curl --location --request GET 'http://0.0.0.0:4000/team/list' \ + --header 'Authorization: Bearer sk-1234' + ``` + """ + from litellm.proxy.proxy_server import ( + prisma_client, + litellm_proxy_admin_name, + create_audit_log_for_update, + _duration_in_seconds, + ) + + if user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN: + raise HTTPException( + status_code=401, + detail={ + "error": "Admin-only endpoint. Your user role={}".format( + user_api_key_dict.user_role + ) + }, + ) + + if prisma_client is None: + raise HTTPException( + status_code=400, + detail={"error": CommonProxyErrors.db_not_connected_error.value}, + ) + + response = await prisma_client.db.litellm_teamtable.find_many() + + return response diff --git a/litellm/proxy/management_helpers/utils.py b/litellm/proxy/management_helpers/utils.py index 6c035d3ef80..1cf22480b00 100644 --- a/litellm/proxy/management_helpers/utils.py +++ b/litellm/proxy/management_helpers/utils.py @@ -1,5 +1,11 @@ # What is this? ## Helper utils for the management endpoints (keys/users/teams) +from datetime import datetime +from functools import wraps +from litellm.proxy._types import UserAPIKeyAuth, ManagementEndpointLoggingPayload +from litellm.proxy.common_utils.http_parsing_utils import _read_request_body +from litellm._logging import verbose_logger +from fastapi import Request from litellm.proxy._types import LiteLLM_TeamTable, Member, UserAPIKeyAuth from litellm.proxy.utils import PrismaClient @@ -61,3 +67,110 @@ async def add_new_member( "budget_id": _budget_id, } ) + + +def management_endpoint_wrapper(func): + """ + This wrapper does the following: + + 1. Log I/O, Exceptions to OTEL + 2. Create an Audit log for success calls + """ + + @wraps(func) + async def wrapper(*args, **kwargs): + start_time = datetime.now() + + try: + result = await func(*args, **kwargs) + end_time = datetime.now() + try: + if kwargs is None: + kwargs = {} + user_api_key_dict: UserAPIKeyAuth = ( + kwargs.get("user_api_key_dict") or UserAPIKeyAuth() + ) + _http_request: Request = kwargs.get("http_request") + parent_otel_span = user_api_key_dict.parent_otel_span + if parent_otel_span is not None: + from litellm.proxy.proxy_server import open_telemetry_logger + + if open_telemetry_logger is not None: + if _http_request: + _route = _http_request.url.path + _request_body: dict = await _read_request_body( + request=_http_request + ) + _response = dict(result) if result is not None else None + + logging_payload = ManagementEndpointLoggingPayload( + route=_route, + request_data=_request_body, + response=_response, + start_time=start_time, + end_time=end_time, + ) + + await open_telemetry_logger.async_management_endpoint_success_hook( + logging_payload=logging_payload, + parent_otel_span=parent_otel_span, + ) + + if _http_request: + _route = _http_request.url.path + # Flush user_api_key cache if this was an update/delete call to /key, /team, or /user + if _route in [ + "/key/update", + "/key/delete", + "/team/update", + "/team/delete", + "/user/update", + "/user/delete", + "/customer/update", + "/customer/delete", + ]: + from litellm.proxy.proxy_server import user_api_key_cache + + user_api_key_cache.flush_cache() + except Exception as e: + # Non-Blocking Exception + verbose_logger.debug("Error in management endpoint wrapper: %s", str(e)) + pass + + return result + except Exception as e: + end_time = datetime.now() + + if kwargs is None: + kwargs = {} + user_api_key_dict: UserAPIKeyAuth = ( + kwargs.get("user_api_key_dict") or UserAPIKeyAuth() + ) + parent_otel_span = user_api_key_dict.parent_otel_span + if parent_otel_span is not None: + from litellm.proxy.proxy_server import open_telemetry_logger + + if open_telemetry_logger is not None: + _http_request: Request = kwargs.get("http_request") + if _http_request: + _route = _http_request.url.path + _request_body: dict = await _read_request_body( + request=_http_request + ) + logging_payload = ManagementEndpointLoggingPayload( + route=_route, + request_data=_request_body, + response=None, + start_time=start_time, + end_time=end_time, + exception=e, + ) + + await open_telemetry_logger.async_management_endpoint_failure_hook( + logging_payload=logging_payload, + parent_otel_span=parent_otel_span, + ) + + raise e + + return wrapper diff --git a/litellm/proxy/proxy_config.yaml b/litellm/proxy/proxy_config.yaml index a21378f31e4..27d49a33dd5 100644 --- a/litellm/proxy/proxy_config.yaml +++ b/litellm/proxy/proxy_config.yaml @@ -20,10 +20,13 @@ model_list: general_settings: master_key: sk-1234 + alerting: ["slack", "email"] litellm_settings: - callbacks: ["otel"] + success_callback: ["prometheus"] + failure_callback: ["prometheus"] store_audit_logs: true + turn_off_message_logging: true redact_messages_in_exceptions: True enforced_params: - user diff --git a/litellm/proxy/proxy_server.py b/litellm/proxy/proxy_server.py index 3e979c07874..64a2cbb2fef 100644 --- a/litellm/proxy/proxy_server.py +++ b/litellm/proxy/proxy_server.py @@ -90,7 +90,6 @@ from litellm.types.llms.openai import ( HttpxBinaryResponseContent, ) from litellm.proxy.litellm_pre_call_utils import add_litellm_data_to_request -from litellm.proxy.management_helpers.utils import add_new_member from litellm.proxy.utils import ( PrismaClient, DBClient, @@ -104,14 +103,11 @@ from litellm.proxy.utils import ( html_form, missing_keys_html_form, _is_valid_team_configs, - _is_user_proxy_admin, - _get_user_role, _is_projected_spend_over_limit, _get_projected_spend_over_limit, update_spend, encrypt_value, decrypt_value, - _to_ns, get_error_message_str, ) from litellm.proxy.common_utils.http_parsing_utils import _read_request_body @@ -151,6 +147,7 @@ from litellm.proxy.auth.model_checks import ( get_key_models, get_team_models, ) +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth from litellm.proxy.hooks.prompt_injection_detection import ( _OPTIONAL_PromptInjectionDetection, ) @@ -164,14 +161,25 @@ from litellm.proxy.auth.auth_checks import ( get_actual_routes, log_to_opentelemetry, ) -from litellm.proxy.common_utils.management_endpoint_utils import ( - management_endpoint_wrapper, -) from litellm.llms.custom_httpx.httpx_handler import HTTPHandler from litellm.exceptions import RejectedRequestError from litellm.integrations.slack_alerting import SlackAlertingArgs, SlackAlerting from litellm.scheduler import Scheduler, FlowItem, DefaultPriorities +## Import All Misc routes here ## +from litellm.proxy.caching_routes import router as caching_router +from litellm.proxy.management_endpoints.team_endpoints import router as team_router +from litellm.proxy.spend_reporting_endpoints.spend_management_endpoints import ( + router as spend_management_router, +) +from litellm.proxy.management_endpoints.key_management_endpoints import ( + router as key_management_router, + _duration_in_seconds, + generate_key_helper_fn, + delete_verification_token, +) +from litellm.proxy.health_endpoints._health_endpoints import router as health_router + try: from litellm._version import version except: @@ -275,51 +283,10 @@ if os.getenv("DOCS_FILTERED", "False") == "True" and premium_user: app.openapi = custom_openapi # type: ignore -class ProxyException(Exception): - # NOTE: DO NOT MODIFY THIS - # This is used to map exactly to OPENAI Exceptions - def __init__( - self, - message: str, - type: str, - param: Optional[str], - code: Optional[int], - ): - self.message = message - self.type = type - self.param = param - self.code = code - - # rules for proxyExceptions - # Litellm router.py returns "No healthy deployment available" when there are no deployments available - # Should map to 429 errors https://github.com/BerriAI/litellm/issues/2487 - if ( - "No healthy deployment available" in self.message - or "No deployments available" in self.message - ): - self.code = 429 - - def to_dict(self) -> dict: - """Converts the ProxyException instance to a dictionary.""" - return { - "message": self.message, - "type": self.type, - "param": self.param, - "code": self.code, - } - - class UserAPIKeyCacheTTLEnum(enum.Enum): in_memory_cache_ttl = 60 # 1 min ttl ## configure via `general_settings::user_api_key_cache_ttl: ` -class CommonProxyErrors(enum.Enum): - db_not_connected_error = "DB not connected" - no_llm_router = "No models configured on proxy" - not_allowed_access = "Admin-only endpoint. Not allowed to access this." - not_premium_user = "You must be a LiteLLM Enterprise user to use this feature. If you have a license please set `LITELLM_LICENSE` in your env. If you want to obtain a license meet with us here: https://calendly.com/d/4mp-gd3-k5k/litellm-1-1-onboarding-chat" - - @app.exception_handler(ProxyException) async def openai_exception_handler(request: Request, exc: ProxyException): # NOTE: DO NOT MODIFY THIS, its crucial to map to Openai exceptions @@ -371,14 +338,6 @@ app.add_middleware( from typing import Dict -api_key_header = APIKeyHeader( - name="Authorization", auto_error=False, description="Bearer token" -) -azure_api_key_header = APIKeyHeader( - name="API-Key", - auto_error=False, - description="Some older versions of the openai Python package will send an API-Key header with just the API key ", -) user_api_base = None user_model = None user_debug = False @@ -437,16 +396,6 @@ db_writer_client: Optional[HTTPHandler] = None ### logger ### -def _get_bearer_token( - api_key: str, -): - if api_key.startswith("Bearer "): # ensure Bearer token passed in - api_key = api_key.replace("Bearer ", "") # extract the token - else: - api_key = "" - return api_key - - def _get_pydantic_json_dict(pydantic_obj: BaseModel) -> dict: try: return pydantic_obj.model_dump() # type: ignore @@ -518,1074 +467,6 @@ async def check_request_disconnection(request: Request, llm_api_call_task): ) -async def user_api_key_auth( - request: Request, - api_key: str = fastapi.Security(api_key_header), - azure_api_key_header: str = fastapi.Security(azure_api_key_header), -) -> UserAPIKeyAuth: - global master_key, prisma_client, llm_model_list, user_custom_auth, custom_db_client, general_settings, proxy_logging_obj - try: - if isinstance(api_key, str): - passed_in_key = api_key - api_key = _get_bearer_token(api_key=api_key) - - elif isinstance(azure_api_key_header, str): - api_key = azure_api_key_header - - parent_otel_span: Optional[Span] = None - if open_telemetry_logger is not None: - parent_otel_span = open_telemetry_logger.tracer.start_span( - name="Received Proxy Server Request", - start_time=_to_ns(datetime.now()), - context=open_telemetry_logger.get_traceparent_from_header( - headers=request.headers - ), - ) - ### USER-DEFINED AUTH FUNCTION ### - if user_custom_auth is not None: - response = await user_custom_auth(request=request, api_key=api_key) - return UserAPIKeyAuth.model_validate(response) - - ### LITELLM-DEFINED AUTH FUNCTION ### - #### IF JWT #### - """ - LiteLLM supports using JWTs. - - Enable this in proxy config, by setting - ``` - general_settings: - enable_jwt_auth: true - ``` - """ - route: str = request.url.path - - if route in LiteLLMRoutes.public_routes.value: - # check if public endpoint - return UserAPIKeyAuth(user_role=LitellmUserRoles.INTERNAL_USER_VIEW_ONLY) - - if general_settings.get("enable_jwt_auth", False) == True: - is_jwt = jwt_handler.is_jwt(token=api_key) - verbose_proxy_logger.debug("is_jwt: %s", is_jwt) - if is_jwt: - # check if valid token - jwt_valid_token: dict = await jwt_handler.auth_jwt(token=api_key) - # get scopes - scopes = jwt_handler.get_scopes(token=jwt_valid_token) - - # check if admin - is_admin = jwt_handler.is_admin(scopes=scopes) - # if admin return - if is_admin: - # check allowed admin routes - is_allowed = allowed_routes_check( - user_role=LitellmUserRoles.PROXY_ADMIN, - user_route=route, - litellm_proxy_roles=jwt_handler.litellm_jwtauth, - ) - if is_allowed: - return UserAPIKeyAuth( - user_role=LitellmUserRoles.PROXY_ADMIN, - parent_otel_span=parent_otel_span, - ) - else: - allowed_routes = ( - jwt_handler.litellm_jwtauth.admin_allowed_routes - ) - actual_routes = get_actual_routes(allowed_routes=allowed_routes) - raise Exception( - f"Admin not allowed to access this route. Route={route}, Allowed Routes={actual_routes}" - ) - # get team id - team_id = jwt_handler.get_team_id( - token=jwt_valid_token, default_value=None - ) - - if team_id is None and jwt_handler.is_required_team_id() == True: - raise Exception( - f"No team id passed in. Field checked in jwt token - '{jwt_handler.litellm_jwtauth.team_id_jwt_field}'" - ) - - team_object: Optional[LiteLLM_TeamTable] = None - if team_id is not None: - # check allowed team routes - is_allowed = allowed_routes_check( - user_role=LitellmUserRoles.TEAM, - user_route=route, - litellm_proxy_roles=jwt_handler.litellm_jwtauth, - ) - if is_allowed == False: - allowed_routes = jwt_handler.litellm_jwtauth.team_allowed_routes # type: ignore - actual_routes = get_actual_routes(allowed_routes=allowed_routes) - raise Exception( - f"Team not allowed to access this route. Route={route}, Allowed Routes={actual_routes}" - ) - - # check if team in db - team_object = await get_team_object( - team_id=team_id, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - parent_otel_span=parent_otel_span, - proxy_logging_obj=proxy_logging_obj, - ) - - # [OPTIONAL] track spend for an org id - `LiteLLM_OrganizationTable` - org_id = jwt_handler.get_org_id( - token=jwt_valid_token, default_value=None - ) - if org_id is not None: - _ = await get_org_object( - org_id=org_id, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - parent_otel_span=parent_otel_span, - proxy_logging_obj=proxy_logging_obj, - ) - # [OPTIONAL] track spend against an internal employee - `LiteLLM_UserTable` - user_object = None - user_id = jwt_handler.get_user_id( - token=jwt_valid_token, default_value=None - ) - if user_id is not None: - # get the user object - user_object = await get_user_object( - user_id=user_id, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - user_id_upsert=jwt_handler.is_upsert_user_id(), - parent_otel_span=parent_otel_span, - proxy_logging_obj=proxy_logging_obj, - ) - - # [OPTIONAL] track spend against an external user - `LiteLLM_EndUserTable` - end_user_object = None - end_user_id = jwt_handler.get_end_user_id( - token=jwt_valid_token, default_value=None - ) - if end_user_id is not None: - # get the end-user object - end_user_object = await get_end_user_object( - end_user_id=end_user_id, - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - parent_otel_span=parent_otel_span, - proxy_logging_obj=proxy_logging_obj, - ) - - global_proxy_spend = None - if litellm.max_budget > 0: # user set proxy max budget - # check cache - global_proxy_spend = await user_api_key_cache.async_get_cache( - key="{}:spend".format(litellm_proxy_admin_name) - ) - if global_proxy_spend is None and prisma_client is not None: - # get from db - sql_query = """SELECT SUM(spend) as total_spend FROM "MonthlyGlobalSpend";""" - - response = await prisma_client.db.query_raw(query=sql_query) - - global_proxy_spend = response[0]["total_spend"] - - await user_api_key_cache.async_set_cache( - key="{}:spend".format(litellm_proxy_admin_name), - value=global_proxy_spend, - ) - if global_proxy_spend is not None: - user_info = CallInfo( - user_id=litellm_proxy_admin_name, - max_budget=litellm.max_budget, - spend=global_proxy_spend, - token=jwt_valid_token["token"], - ) - asyncio.create_task( - proxy_logging_obj.budget_alerts( - type="proxy_budget", - user_info=user_info, - ) - ) - # get the request body - request_data = await _read_request_body(request=request) - - # run through common checks - _ = common_checks( - request_body=request_data, - team_object=team_object, - user_object=user_object, - end_user_object=end_user_object, - general_settings=general_settings, - global_proxy_spend=global_proxy_spend, - route=route, - ) - - # return UserAPIKeyAuth object - return UserAPIKeyAuth( - api_key=None, - team_id=team_object.team_id if team_object is not None else None, - team_tpm_limit=( - team_object.tpm_limit if team_object is not None else None - ), - team_rpm_limit=( - team_object.rpm_limit if team_object is not None else None - ), - team_models=team_object.models if team_object is not None else [], - user_role=LitellmUserRoles.INTERNAL_USER, - user_id=user_id, - org_id=org_id, - parent_otel_span=parent_otel_span, - ) - #### ELSE #### - if master_key is None: - if isinstance(api_key, str): - return UserAPIKeyAuth( - api_key=api_key, - user_role=LitellmUserRoles.PROXY_ADMIN, - parent_otel_span=parent_otel_span, - ) - else: - return UserAPIKeyAuth( - user_role=LitellmUserRoles.PROXY_ADMIN, - parent_otel_span=parent_otel_span, - ) - elif api_key is None: # only require api key if master key is set - raise Exception("No api key passed in.") - elif api_key == "": - # missing 'Bearer ' prefix - raise Exception( - f"Malformed API Key passed in. Ensure Key has `Bearer ` prefix. Passed in: {passed_in_key}" - ) - - if route == "/user/auth": - if general_settings.get("allow_user_auth", False) == True: - return UserAPIKeyAuth() - else: - raise HTTPException( - status_code=status.HTTP_403_FORBIDDEN, - detail="'allow_user_auth' not set or set to False", - ) - - ## Check END-USER OBJECT - request_data = await _read_request_body(request=request) - _end_user_object = None - end_user_params = {} - if "user" in request_data: - try: - _end_user_object = await get_end_user_object( - end_user_id=request_data["user"], - prisma_client=prisma_client, - user_api_key_cache=user_api_key_cache, - parent_otel_span=parent_otel_span, - proxy_logging_obj=proxy_logging_obj, - ) - if _end_user_object is not None: - end_user_params["allowed_model_region"] = ( - _end_user_object.allowed_model_region - ) - if _end_user_object.litellm_budget_table is not None: - budget_info = _end_user_object.litellm_budget_table - end_user_params["end_user_id"] = _end_user_object.user_id - if budget_info.tpm_limit is not None: - end_user_params["end_user_tpm_limit"] = ( - budget_info.tpm_limit - ) - if budget_info.rpm_limit is not None: - end_user_params["end_user_rpm_limit"] = ( - budget_info.rpm_limit - ) - if budget_info.max_budget is not None: - end_user_params["end_user_max_budget"] = ( - budget_info.max_budget - ) - except Exception as e: - if isinstance(e, litellm.BudgetExceededError): - raise e - verbose_proxy_logger.debug( - "Unable to find user in db. Error - {}".format(str(e)) - ) - pass - - ### CHECK IF ADMIN ### - # note: never string compare api keys, this is vulenerable to a time attack. Use secrets.compare_digest instead - ### CHECK IF ADMIN ### - # note: never string compare api keys, this is vulenerable to a time attack. Use secrets.compare_digest instead - ## Check CACHE - valid_token: Optional[UserAPIKeyAuth] = user_api_key_cache.get_cache( - key=hash_token(api_key) - ) - if ( - valid_token is not None - and isinstance(valid_token, UserAPIKeyAuth) - and valid_token.user_role == LitellmUserRoles.PROXY_ADMIN - ): - # update end-user params on valid token - valid_token.end_user_id = end_user_params.get("end_user_id") - valid_token.end_user_tpm_limit = end_user_params.get("end_user_tpm_limit") - valid_token.end_user_rpm_limit = end_user_params.get("end_user_rpm_limit") - valid_token.allowed_model_region = end_user_params.get( - "allowed_model_region" - ) - valid_token.parent_otel_span = parent_otel_span - - return valid_token - - try: - is_master_key_valid = secrets.compare_digest(api_key, master_key) # type: ignore - except Exception as e: - is_master_key_valid = False - - ## VALIDATE MASTER KEY ## - try: - assert isinstance(master_key, str) - except Exception as e: - raise HTTPException( - status_code=500, - detail={ - "Master key must be a valid string. Current type={}".format( - type(master_key) - ) - }, - ) - - if is_master_key_valid: - _user_api_key_obj = UserAPIKeyAuth( - api_key=master_key, - user_role=LitellmUserRoles.PROXY_ADMIN, - user_id=litellm_proxy_admin_name, - parent_otel_span=parent_otel_span, - **end_user_params, - ) - await user_api_key_cache.async_set_cache( - key=hash_token(master_key), value=_user_api_key_obj - ) - - return _user_api_key_obj - - ## IF it's not a master key - ## Route should not be in master_key_only_routes - if route in LiteLLMRoutes.master_key_only_routes.value: - raise Exception( - f"Tried to access route={route}, which is only for MASTER KEY" - ) - - ## Check DB - if isinstance( - api_key, str - ): # if generated token, make sure it starts with sk-. - assert api_key.startswith("sk-") # prevent token hashes from being used - - if ( - prisma_client is None and custom_db_client is None - ): # if both master key + user key submitted, and user key != master key, and no db connected, raise an error - raise Exception("No connected db.") - - ## check for cache hit (In-Memory Cache) - original_api_key = api_key # (Patch: For DynamoDB Backwards Compatibility) - _user_role = None - if api_key.startswith("sk-"): - api_key = hash_token(token=api_key) - valid_token: Optional[UserAPIKeyAuth] = user_api_key_cache.get_cache( # type: ignore - key=api_key - ) - if valid_token is None: - ## check db - verbose_proxy_logger.debug("api key: %s", api_key) - if prisma_client is not None: - _valid_token: Optional[BaseModel] = await prisma_client.get_data( - token=api_key, - table_name="combined_view", - parent_otel_span=parent_otel_span, - proxy_logging_obj=proxy_logging_obj, - ) - if _valid_token is not None: - valid_token = UserAPIKeyAuth( - **_valid_token.model_dump(exclude_none=True) - ) - verbose_proxy_logger.debug("Token from db: %s", valid_token) - elif valid_token is not None and isinstance(valid_token, UserAPIKeyAuth): - verbose_proxy_logger.debug("API Key Cache Hit!") - - # update end-user params on valid token - # These can change per request - it's important to update them here - valid_token.end_user_id = end_user_params.get("end_user_id") - valid_token.end_user_tpm_limit = end_user_params.get("end_user_tpm_limit") - valid_token.end_user_rpm_limit = end_user_params.get("end_user_rpm_limit") - valid_token.allowed_model_region = end_user_params.get( - "allowed_model_region" - ) - - user_id_information: Optional[List] = None - if valid_token is not None: - # Got Valid Token from Cache, DB - # Run checks for - # 1. If token can call model - # 2. If user_id for this token is in budget - # 3. If the user spend within their own team is within budget - # 4. If 'user' passed to /chat/completions, /embeddings endpoint is in budget - # 5. If token is expired - # 6. If token spend is under Budget for the token - # 7. If token spend per model is under budget per model - # 8. If token spend is under team budget - # 9. If team spend is under team budget - - # Check 1. If token can call model - _model_alias_map = {} - if ( - hasattr(valid_token, "team_model_aliases") - and valid_token.team_model_aliases is not None - ): - _model_alias_map = { - **valid_token.aliases, - **valid_token.team_model_aliases, - } - else: - _model_alias_map = {**valid_token.aliases} - litellm.model_alias_map = _model_alias_map - config = valid_token.config - if config != {}: - model_list = config.get("model_list", []) - llm_model_list = model_list - verbose_proxy_logger.debug( - f"\n new llm router model list {llm_model_list}" - ) - if ( - len(valid_token.models) == 0 - ): # assume an empty model list means all models are allowed to be called - pass - elif ( - isinstance(valid_token.models, list) - and "all-team-models" in valid_token.models - ): - # Do not do any validation at this step - # the validation will occur when checking the team has access to this model - pass - else: - try: - data = await request.json() - except json.JSONDecodeError: - data = {} # Provide a default value, such as an empty dictionary - model = data.get("model", None) - if model in litellm.model_alias_map: - model = litellm.model_alias_map[model] - - ## check if model in allowed model names - verbose_proxy_logger.debug( - f"LLM Model List pre access group check: {llm_model_list}" - ) - from collections import defaultdict - - access_groups = defaultdict(list) - if llm_model_list is not None: - for m in llm_model_list: - for group in m.get("model_info", {}).get("access_groups", []): - model_name = m["model_name"] - access_groups[group].append(model_name) - - models_in_current_access_groups = [] - if ( - len(access_groups) > 0 - ): # check if token contains any model access groups - for idx, m in enumerate( - valid_token.models - ): # loop token models, if any of them are an access group add the access group - if m in access_groups: - # if it is an access group we need to remove it from valid_token.models - models_in_group = access_groups[m] - models_in_current_access_groups.extend(models_in_group) - - # Filter out models that are access_groups - filtered_models = [ - m for m in valid_token.models if m not in access_groups - ] - - filtered_models += models_in_current_access_groups - verbose_proxy_logger.debug( - f"model: {model}; allowed_models: {filtered_models}" - ) - if ( - model is not None - and model not in filtered_models - and "*" not in filtered_models - ): - raise ValueError( - f"API Key not allowed to access model. This token can only access models={valid_token.models}. Tried to access {model}" - ) - valid_token.models = filtered_models - verbose_proxy_logger.debug( - f"filtered allowed_models: {filtered_models}; valid_token.models: {valid_token.models}" - ) - - # Check 2. If user_id for this token is in budget - if valid_token.user_id is not None: - user_id_list = [valid_token.user_id] - for id in user_id_list: - value = user_api_key_cache.get_cache(key=id) - if value is not None: - if user_id_information is None: - user_id_information = [] - user_id_information.append(value) - if user_id_information is None or ( - isinstance(user_id_information, list) - and len(user_id_information) < 1 - ): - if prisma_client is not None: - user_id_information = await prisma_client.get_data( - user_id_list=[ - valid_token.user_id, - ], - table_name="user", - query_type="find_all", - ) - if user_id_information is not None: - for _id in user_id_information: - await user_api_key_cache.async_set_cache( - key=_id["user_id"], - value=_id, - ) - - verbose_proxy_logger.debug( - f"user_id_information: {user_id_information}" - ) - - if user_id_information is not None: - if isinstance(user_id_information, list): - ## Check if user in budget - for _user in user_id_information: - if _user is None: - continue - assert isinstance(_user, dict) - # check if user is admin # - - # Token exists, not expired now check if its in budget for the user - user_max_budget = _user.get("max_budget", None) - user_current_spend = _user.get("spend", None) - - verbose_proxy_logger.debug( - f"user_id: {_user.get('user_id', None)}; user_max_budget: {user_max_budget}; user_current_spend: {user_current_spend}" - ) - - if ( - user_max_budget is not None - and user_current_spend is not None - ): - call_info = CallInfo( - token=valid_token.token, - spend=user_current_spend, - max_budget=user_max_budget, - user_id=_user.get("user_id", None), - user_email=_user.get("user_email", None), - key_alias=valid_token.key_alias, - ) - asyncio.create_task( - proxy_logging_obj.budget_alerts( - type="user_budget", - user_info=call_info, - ) - ) - - _user_id = _user.get("user_id", None) - if user_current_spend > user_max_budget: - raise litellm.BudgetExceededError( - current_cost=user_current_spend, - max_budget=user_max_budget, - ) - else: - # Token exists, not expired now check if its in budget for the user - user_max_budget = getattr( - user_id_information, "max_budget", None - ) - user_current_spend = getattr(user_id_information, "spend", None) - - if ( - user_max_budget is not None - and user_current_spend is not None - ): - call_info = CallInfo( - token=valid_token.token, - spend=user_current_spend, - max_budget=user_max_budget, - user_id=getattr(user_id_information, "user_id", None), - user_email=getattr( - user_id_information, "user_email", None - ), - key_alias=valid_token.key_alias, - ) - asyncio.create_task( - proxy_logging_obj.budget_alerts( - type="user_budget", - user_info=call_info, - ) - ) - - if user_current_spend > user_max_budget: - raise litellm.BudgetExceededError( - current_cost=user_current_spend, - max_budget=user_max_budget, - ) - - # Check 3. Check if user is in their team budget - if valid_token.team_member_spend is not None: - if prisma_client is not None: - - _cache_key = f"{valid_token.team_id}_{valid_token.user_id}" - - team_member_info = await user_api_key_cache.async_get_cache( - key=_cache_key - ) - if team_member_info is None: - team_member_info = ( - await prisma_client.db.litellm_teammembership.find_first( - where={ - "user_id": valid_token.user_id, - "team_id": valid_token.team_id, - }, # type: ignore - include={"litellm_budget_table": True}, - ) - ) - await user_api_key_cache.async_set_cache( - key=_cache_key, - value=team_member_info, - ) - - if ( - team_member_info is not None - and team_member_info.litellm_budget_table is not None - ): - team_member_budget = ( - team_member_info.litellm_budget_table.max_budget - ) - if team_member_budget is not None and team_member_budget > 0: - if valid_token.team_member_spend > team_member_budget: - raise litellm.BudgetExceededError( - current_cost=valid_token.team_member_spend, - max_budget=team_member_budget, - ) - - # Check 3. If token is expired - if valid_token.expires is not None: - current_time = datetime.now(timezone.utc) - expiry_time = datetime.fromisoformat(valid_token.expires) - if ( - expiry_time.tzinfo is None - or expiry_time.tzinfo.utcoffset(expiry_time) is None - ): - expiry_time = expiry_time.replace(tzinfo=timezone.utc) - verbose_proxy_logger.debug( - f"Checking if token expired, expiry time {expiry_time} and current time {current_time}" - ) - if expiry_time < current_time: - # Token exists but is expired. - raise HTTPException( - status_code=status.HTTP_403_FORBIDDEN, - detail=f"Authentication Error - Expired Key. Key Expiry time {expiry_time} and current time {current_time}", - ) - - # Check 4. Token Spend is under budget - if valid_token.spend is not None and valid_token.max_budget is not None: - - #################################### - # collect information for alerting # - #################################### - - user_email: Optional[str] = None - # Check if the token has any user id information - if user_id_information is not None and len(user_id_information) > 0: - specific_user_id_information = user_id_information[0] - _user_email = specific_user_id_information.get("user_email", None) - if _user_email is not None: - user_email = str(_user_email) - - call_info = CallInfo( - token=valid_token.token, - spend=valid_token.spend, - max_budget=valid_token.max_budget, - user_id=valid_token.user_id, - team_id=valid_token.team_id, - user_email=user_email, - key_alias=valid_token.key_alias, - ) - asyncio.create_task( - proxy_logging_obj.budget_alerts( - type="token_budget", - user_info=call_info, - ) - ) - - #################################### - # collect information for alerting # - #################################### - - if valid_token.spend >= valid_token.max_budget: - raise litellm.BudgetExceededError( - current_cost=valid_token.spend, - max_budget=valid_token.max_budget, - ) - - # Check 5. Token Model Spend is under Model budget - max_budget_per_model = valid_token.model_max_budget - - if ( - max_budget_per_model is not None - and isinstance(max_budget_per_model, dict) - and len(max_budget_per_model) > 0 - ): - current_model = request_data.get("model") - ## GET THE SPEND FOR THIS MODEL - twenty_eight_days_ago = datetime.now() - timedelta(days=28) - model_spend = await prisma_client.db.litellm_spendlogs.group_by( - by=["model"], - sum={"spend": True}, - where={ - "AND": [ - {"api_key": valid_token.token}, - {"startTime": {"gt": twenty_eight_days_ago}}, - {"model": current_model}, - ] - }, # type: ignore - ) - if ( - len(model_spend) > 0 - and max_budget_per_model.get(current_model, None) is not None - ): - if ( - model_spend[0]["model"] == current_model - and model_spend[0]["_sum"]["spend"] - >= max_budget_per_model[current_model] - ): - current_model_spend = model_spend[0]["_sum"]["spend"] - current_model_budget = max_budget_per_model[current_model] - raise litellm.BudgetExceededError( - current_cost=current_model_spend, - max_budget=current_model_budget, - ) - - # Check 6. Team spend is under Team budget - if ( - hasattr(valid_token, "team_spend") - and valid_token.team_spend is not None - and hasattr(valid_token, "team_max_budget") - and valid_token.team_max_budget is not None - ): - call_info = CallInfo( - token=valid_token.token, - spend=valid_token.team_spend, - max_budget=valid_token.team_max_budget, - user_id=valid_token.user_id, - ) - asyncio.create_task( - proxy_logging_obj.budget_alerts( - type="team_budget", - user_info=call_info, - ) - ) - - if valid_token.team_spend >= valid_token.team_max_budget: - raise litellm.BudgetExceededError( - current_cost=valid_token.team_spend, - max_budget=valid_token.team_max_budget, - ) - - # Check 8: Additional Common Checks across jwt + key auth - _team_obj = LiteLLM_TeamTable( - team_id=valid_token.team_id, - max_budget=valid_token.team_max_budget, - spend=valid_token.team_spend, - tpm_limit=valid_token.team_tpm_limit, - rpm_limit=valid_token.team_rpm_limit, - blocked=valid_token.team_blocked, - models=valid_token.team_models, - ) - - user_api_key_cache.set_cache( - key=valid_token.team_id, value=_team_obj - ) # save team table in cache - used for tpm/rpm limiting - tpm_rpm_limiter.py - - global_proxy_spend = None - if ( - litellm.max_budget > 0 and prisma_client is not None - ): # user set proxy max budget - # check cache - global_proxy_spend = await user_api_key_cache.async_get_cache( - key="{}:spend".format(litellm_proxy_admin_name) - ) - if global_proxy_spend is None: - # get from db - sql_query = """SELECT SUM(spend) as total_spend FROM "MonthlyGlobalSpend";""" - - response = await prisma_client.db.query_raw(query=sql_query) - - global_proxy_spend = response[0]["total_spend"] - await user_api_key_cache.async_set_cache( - key="{}:spend".format(litellm_proxy_admin_name), - value=global_proxy_spend, - ) - - if global_proxy_spend is not None: - call_info = CallInfo( - token=valid_token.token, - spend=global_proxy_spend, - max_budget=litellm.max_budget, - user_id=litellm_proxy_admin_name, - team_id=valid_token.team_id, - ) - asyncio.create_task( - proxy_logging_obj.budget_alerts( - type="proxy_budget", - user_info=call_info, - ) - ) - _ = common_checks( - request_body=request_data, - team_object=_team_obj, - user_object=None, - end_user_object=_end_user_object, - general_settings=general_settings, - global_proxy_spend=global_proxy_spend, - route=route, - ) - # Token passed all checks - api_key = valid_token.token - - # Add hashed token to cache - await user_api_key_cache.async_set_cache( - key=api_key, - value=valid_token, - ) - valid_token_dict = valid_token.model_dump(exclude_none=True) - valid_token_dict.pop("token", None) - - if _end_user_object is not None: - valid_token_dict.update(end_user_params) - - _user_role = _get_user_role(user_id_information=user_id_information) - - if not _is_user_proxy_admin(user_id_information): # if non-admin - if route in LiteLLMRoutes.openai_routes.value: - pass - elif request["route"].name in LiteLLMRoutes.openai_route_names.value: - pass - elif ( - route in LiteLLMRoutes.info_routes.value - ): # check if user allowed to call an info route - if route == "/key/info": - # check if user can access this route - query_params = request.query_params - key = query_params.get("key") - if key is not None and hash_token(token=key) != api_key: - raise HTTPException( - status_code=status.HTTP_403_FORBIDDEN, - detail="user not allowed to access this key's info", - ) - elif route == "/user/info": - # check if user can access this route - query_params = request.query_params - user_id = query_params.get("user_id") - verbose_proxy_logger.debug( - f"user_id: {user_id} & valid_token.user_id: {valid_token.user_id}" - ) - if user_id != valid_token.user_id: - raise HTTPException( - status_code=status.HTTP_403_FORBIDDEN, - detail="key not allowed to access this user's info. user_id={}, key's user_id={}".format( - user_id, valid_token.user_id - ), - ) - elif route == "/model/info": - # /model/info just shows models user has access to - pass - elif route == "/team/info": - # check if key can access this team's info - query_params = request.query_params - team_id = query_params.get("team_id") - if team_id != valid_token.team_id: - raise HTTPException( - status_code=status.HTTP_403_FORBIDDEN, - detail="key not allowed to access this team's info", - ) - elif ( - _has_user_setup_sso() - and route in LiteLLMRoutes.sso_only_routes.value - ): - pass - elif ( - route in LiteLLMRoutes.global_spend_tracking_routes.value - and getattr(valid_token, "permissions", None) is not None - and "get_spend_routes" in getattr(valid_token, "permissions", None) - ): - - pass - elif _user_role == LitellmUserRoles.PROXY_ADMIN_VIEW_ONLY: - if route in LiteLLMRoutes.openai_routes.value: - raise HTTPException( - status_code=status.HTTP_403_FORBIDDEN, - detail=f"user not allowed to access this OpenAI routes, role= {_user_role}", - ) - if route in LiteLLMRoutes.management_routes.value: - # the Admin Viewer is only allowed to call /user/update for their own user_id and can only update - if route == "/user/update": - - # Check the Request params are valid for PROXY_ADMIN_VIEW_ONLY - if request_data is not None and isinstance( - request_data, dict - ): - _params_updated = request_data.keys() - for param in _params_updated: - if param not in ["user_email", "password"]: - raise HTTPException( - status_code=status.HTTP_403_FORBIDDEN, - detail=f"user not allowed to access this route, role= {_user_role}. Trying to access: {route} and updating invalid param: {param}. only user_email and password can be updated", - ) - else: - raise HTTPException( - status_code=status.HTTP_403_FORBIDDEN, - detail=f"user not allowed to access this route, role= {_user_role}. Trying to access: {route}", - ) - elif ( - _user_role == LitellmUserRoles.INTERNAL_USER - and route in LiteLLMRoutes.internal_user_routes.value - ): - pass - else: - user_role = "unknown" - user_id = "unknown" - if ( - user_id_information is not None - and isinstance(user_id_information, list) - and len(user_id_information) > 0 - ): - _user = user_id_information[0] - user_role = _user.get("user_role", "unknown") - user_id = _user.get("user_id", "unknown") - raise Exception( - f"Only proxy admin can be used to generate, delete, update info for new keys/users/teams. Route={route}. Your role={user_role}. Your user_id={user_id}" - ) - - # check if token is from litellm-ui, litellm ui makes keys to allow users to login with sso. These keys can only be used for LiteLLM UI functions - # sso/login, ui/login, /key functions and /user functions - # this will never be allowed to call /chat/completions - token_team = getattr(valid_token, "team_id", None) - - if token_team is not None and token_team == "litellm-dashboard": - # this token is only used for managing the ui - allowed_routes = [ - "/sso", - "/login", - "/key/generate", - "/key/update", - "/key/info", - "/config", - "/spend", - "/user", - "/model/info", - "/v2/model/info", - "/v2/key/info", - "/models", - "/v1/models", - "/global/spend", - "/global/spend/logs", - "/global/spend/keys", - "/global/spend/models", - "/global/predict/spend/logs", - "/global/activity", - "/health/services", - ] + LiteLLMRoutes.info_routes.value - # check if the current route startswith any of the allowed routes - if ( - route is not None - and isinstance(route, str) - and any( - route.startswith(allowed_route) for allowed_route in allowed_routes - ) - ): - # Do something if the current route starts with any of the allowed routes - pass - else: - if user_id_information is not None and _is_user_proxy_admin( - user_id_information - ): - return UserAPIKeyAuth( - api_key=api_key, - user_role=LitellmUserRoles.PROXY_ADMIN, - parent_otel_span=parent_otel_span, - **valid_token_dict, - ) - elif ( - _has_user_setup_sso() - and route in LiteLLMRoutes.sso_only_routes.value - ): - return UserAPIKeyAuth( - api_key=api_key, - user_role=_user_role, - parent_otel_span=parent_otel_span, - **valid_token_dict, - ) - else: - raise Exception( - f"This key is made for LiteLLM UI, Tried to access route: {route}. Not allowed" - ) - if valid_token is None: - # No token was found when looking up in the DB - raise Exception("Invalid proxy server token passed") - if valid_token_dict is not None: - if user_id_information is not None and _is_user_proxy_admin( - user_id_information - ): - return UserAPIKeyAuth( - api_key=api_key, - user_role=LitellmUserRoles.PROXY_ADMIN, - parent_otel_span=parent_otel_span, - **valid_token_dict, - ) - elif _has_user_setup_sso() and route in LiteLLMRoutes.sso_only_routes.value: - return UserAPIKeyAuth( - api_key=api_key, - user_role=LitellmUserRoles.INTERNAL_USER, - parent_otel_span=parent_otel_span, - **valid_token_dict, - ) - else: - return UserAPIKeyAuth( - api_key=api_key, - user_role=LitellmUserRoles.INTERNAL_USER, - parent_otel_span=parent_otel_span, - **valid_token_dict, - ) - else: - raise Exception() - except Exception as e: - verbose_proxy_logger.error( - "litellm.proxy.proxy_server.user_api_key_auth(): Exception occured - {}".format( - str(e) - ) - ) - - # Log this exception to OTEL - if open_telemetry_logger is not None: - await open_telemetry_logger.async_post_call_failure_hook( - original_exception=e, - user_api_key_dict=UserAPIKeyAuth(parent_otel_span=parent_otel_span), - ) - - verbose_proxy_logger.debug(traceback.format_exc()) - if isinstance(e, litellm.BudgetExceededError): - raise ProxyException( - message=e.message, type="auth_error", param=None, code=400 - ) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({str(e)})"), - type="auth_error", - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_401_UNAUTHORIZED), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type="auth_error", - param=getattr(e, "param", "None"), - code=status.HTTP_401_UNAUTHORIZED, - ) - - def prisma_setup(database_url: Optional[str]): global prisma_client, proxy_logging_obj, user_api_key_cache @@ -2853,6 +1734,7 @@ class ProxyConfig: use_azure_key_vault = general_settings.get("use_azure_key_vault", False) load_from_azure_key_vault(use_azure_key_vault=use_azure_key_vault) ### ALERTING ### + proxy_logging_obj.update_values( alerting=general_settings.get("alerting", None), alerting_threshold=general_settings.get("alerting_threshold", 600), @@ -3381,263 +2263,6 @@ class ProxyConfig: proxy_config = ProxyConfig() -def _duration_in_seconds(duration: str): - match = re.match(r"(\d+)([smhd]?)", duration) - if not match: - raise ValueError("Invalid duration format") - - value, unit = match.groups() - value = int(value) - - if unit == "s": - return value - elif unit == "m": - return value * 60 - elif unit == "h": - return value * 3600 - elif unit == "d": - return value * 86400 - else: - raise ValueError("Unsupported duration unit") - - -async def generate_key_helper_fn( - request_type: Literal[ - "user", "key" - ], # identifies if this request is from /user/new or /key/generate - duration: Optional[str], - models: list, - aliases: dict, - config: dict, - spend: float, - key_max_budget: Optional[float] = None, # key_max_budget is used to Budget Per key - key_budget_duration: Optional[str] = None, - budget_id: Optional[float] = None, # budget id <-> LiteLLM_BudgetTable - soft_budget: Optional[ - float - ] = None, # soft_budget is used to set soft Budgets Per user - max_budget: Optional[float] = None, # max_budget is used to Budget Per user - budget_duration: Optional[str] = None, # max_budget is used to Budget Per user - token: Optional[str] = None, - user_id: Optional[str] = None, - team_id: Optional[str] = None, - user_email: Optional[str] = None, - user_role: Optional[str] = None, - max_parallel_requests: Optional[int] = None, - metadata: Optional[dict] = {}, - tpm_limit: Optional[int] = None, - rpm_limit: Optional[int] = None, - query_type: Literal["insert_data", "update_data"] = "insert_data", - update_key_values: Optional[dict] = None, - key_alias: Optional[str] = None, - allowed_cache_controls: Optional[list] = [], - permissions: Optional[dict] = {}, - model_max_budget: Optional[dict] = {}, - teams: Optional[list] = None, - organization_id: Optional[str] = None, - table_name: Optional[Literal["key", "user"]] = None, - send_invite_email: Optional[bool] = None, -): - global prisma_client, custom_db_client, user_api_key_cache, litellm_proxy_admin_name, premium_user - - if prisma_client is None and custom_db_client is None: - raise Exception( - f"Connect Proxy to database to generate keys - https://docs.litellm.ai/docs/proxy/virtual_keys " - ) - - if token is None: - token = f"sk-{secrets.token_urlsafe(16)}" - - if duration is None: # allow tokens that never expire - expires = None - else: - duration_s = _duration_in_seconds(duration=duration) - expires = datetime.now(timezone.utc) + timedelta(seconds=duration_s) - - if key_budget_duration is None: # one-time budget - key_reset_at = None - else: - duration_s = _duration_in_seconds(duration=key_budget_duration) - key_reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) - - if budget_duration is None: # one-time budget - reset_at = None - else: - duration_s = _duration_in_seconds(duration=budget_duration) - reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) - - aliases_json = json.dumps(aliases) - config_json = json.dumps(config) - permissions_json = json.dumps(permissions) - metadata_json = json.dumps(metadata) - model_max_budget_json = json.dumps(model_max_budget) - user_role = user_role - tpm_limit = tpm_limit - rpm_limit = rpm_limit - allowed_cache_controls = allowed_cache_controls - - try: - # Create a new verification token (you may want to enhance this logic based on your needs) - user_data = { - "max_budget": max_budget, - "user_email": user_email, - "user_id": user_id, - "team_id": team_id, - "organization_id": organization_id, - "user_role": user_role, - "spend": spend, - "models": models, - "max_parallel_requests": max_parallel_requests, - "tpm_limit": tpm_limit, - "rpm_limit": rpm_limit, - "budget_duration": budget_duration, - "budget_reset_at": reset_at, - "allowed_cache_controls": allowed_cache_controls, - } - if teams is not None: - user_data["teams"] = teams - key_data = { - "token": token, - "key_alias": key_alias, - "expires": expires, - "models": models, - "aliases": aliases_json, - "config": config_json, - "spend": spend, - "max_budget": key_max_budget, - "user_id": user_id, - "team_id": team_id, - "max_parallel_requests": max_parallel_requests, - "metadata": metadata_json, - "tpm_limit": tpm_limit, - "rpm_limit": rpm_limit, - "budget_duration": key_budget_duration, - "budget_reset_at": key_reset_at, - "allowed_cache_controls": allowed_cache_controls, - "permissions": permissions_json, - "model_max_budget": model_max_budget_json, - "budget_id": budget_id, - } - - if ( - litellm.get_secret("DISABLE_KEY_NAME", False) == True - ): # allow user to disable storing abbreviated key name (shown in UI, to help figure out which key spent how much) - pass - else: - key_data["key_name"] = f"sk-...{token[-4:]}" - saved_token = copy.deepcopy(key_data) - if isinstance(saved_token["aliases"], str): - saved_token["aliases"] = json.loads(saved_token["aliases"]) - if isinstance(saved_token["config"], str): - saved_token["config"] = json.loads(saved_token["config"]) - if isinstance(saved_token["metadata"], str): - saved_token["metadata"] = json.loads(saved_token["metadata"]) - if isinstance(saved_token["permissions"], str): - if ( - "get_spend_routes" in saved_token["permissions"] - and premium_user != True - ): - raise ValueError( - "get_spend_routes permission is only available for LiteLLM Enterprise users" - ) - - saved_token["permissions"] = json.loads(saved_token["permissions"]) - if isinstance(saved_token["model_max_budget"], str): - saved_token["model_max_budget"] = json.loads( - saved_token["model_max_budget"] - ) - - if saved_token.get("expires", None) is not None and isinstance( - saved_token["expires"], datetime - ): - saved_token["expires"] = saved_token["expires"].isoformat() - if prisma_client is not None: - if ( - table_name is None or table_name == "user" - ): # do not auto-create users for `/key/generate` - ## CREATE USER (If necessary) - if query_type == "insert_data": - user_row = await prisma_client.insert_data( - data=user_data, table_name="user" - ) - ## use default user model list if no key-specific model list provided - if len(user_row.models) > 0 and len(key_data["models"]) == 0: # type: ignore - key_data["models"] = user_row.models - elif query_type == "update_data": - user_row = await prisma_client.update_data( - data=user_data, - table_name="user", - update_key_values=update_key_values, - ) - if user_id == litellm_proxy_budget_name or ( - table_name is not None and table_name == "user" - ): - # do not create a key for litellm_proxy_budget_name or if table name is set to just 'user' - # we only need to ensure this exists in the user table - # the LiteLLM_VerificationToken table will increase in size if we don't do this check - return user_data - - ## CREATE KEY - verbose_proxy_logger.debug("prisma_client: Creating Key= %s", key_data) - create_key_response = await prisma_client.insert_data( - data=key_data, table_name="key" - ) - key_data["token_id"] = getattr(create_key_response, "token", None) - except Exception as e: - verbose_proxy_logger.error( - "litellm.proxy.proxy_server.generate_key_helper_fn(): Exception occured - {}".format( - str(e) - ) - ) - verbose_proxy_logger.debug(traceback.format_exc()) - if isinstance(e, HTTPException): - raise e - raise HTTPException( - status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, - detail={"error": "Internal Server Error."}, - ) - - # Add budget related info in key_data - this ensures it's returned - key_data["budget_id"] = budget_id - - if request_type == "user": - # if this is a /user/new request update the key_date with user_data fields - key_data.update(user_data) - return key_data - - -async def delete_verification_token(tokens: List, user_id: Optional[str] = None): - global prisma_client - try: - if prisma_client: - # Assuming 'db' is your Prisma Client instance - # check if admin making request - don't filter by user-id - if user_id == litellm_proxy_admin_name: - deleted_tokens = await prisma_client.delete_data(tokens=tokens) - # else - else: - deleted_tokens = await prisma_client.delete_data( - tokens=tokens, user_id=user_id - ) - _num_deleted_tokens = deleted_tokens.get("deleted_keys", 0) - if _num_deleted_tokens != len(tokens): - raise Exception( - "Failed to delete all tokens. Tried to delete tokens that don't belong to user: " - + str(user_id) - ) - else: - raise Exception("DB not connected. prisma_client is None") - except Exception as e: - verbose_proxy_logger.error( - "litellm.proxy.proxy_server.delete_verification_token(): Exception occured - {}".format( - str(e) - ) - ) - verbose_proxy_logger.debug(traceback.format_exc()) - raise e - return deleted_tokens - - def save_worker_config(**data): import json @@ -3964,6 +2589,11 @@ async def startup_event(): db_writer_client = HTTPHandler() + ## UPDATE INTERNAL USAGE CACHE ## + proxy_logging_obj.update_values( + redis_cache=redis_usage_cache + ) # used by parallel request limiter for rate limiting keys across instances + proxy_logging_obj._init_litellm_callbacks() # INITIALIZE LITELLM CALLBACKS ON SERVER STARTUP <- do this to catch any logging errors on startup, not when calls are being made if "daily_reports" in proxy_logging_obj.slack_alerting_instance.alert_types: @@ -5877,231 +4507,6 @@ async def run_thread( ) -###################################################################### - -# /v1/batches Endpoints - - -###################################################################### -@router.post( - "/v1/batches", - dependencies=[Depends(user_api_key_auth)], - tags=["batch"], -) -@router.post( - "/batches", - dependencies=[Depends(user_api_key_auth)], - tags=["batch"], -) -async def create_batch( - request: Request, - fastapi_response: Response, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), -): - """ - Create large batches of API requests for asynchronous processing. - This is the equivalent of POST https://api.openai.com/v1/batch - Supports Identical Params as: https://platform.openai.com/docs/api-reference/batch - - Example Curl - ``` - curl http://localhost:4000/v1/batches \ - -H "Authorization: Bearer sk-1234" \ - -H "Content-Type: application/json" \ - -d '{ - "input_file_id": "file-abc123", - "endpoint": "/v1/chat/completions", - "completion_window": "24h" - }' - ``` - """ - global proxy_logging_obj - data: Dict = {} - try: - # Use orjson to parse JSON data, orjson speeds up requests significantly - form_data = await request.form() - data = {key: value for key, value in form_data.items() if key != "file"} - - # Include original request and headers in the data - data = await add_litellm_data_to_request( - data=data, - request=request, - general_settings=general_settings, - user_api_key_dict=user_api_key_dict, - version=version, - proxy_config=proxy_config, - ) - - _create_batch_data = CreateBatchRequest(**data) - - # for now use custom_llm_provider=="openai" -> this will change as LiteLLM adds more providers for acreate_batch - response = await litellm.acreate_batch( - custom_llm_provider="openai", **_create_batch_data - ) - - ### ALERTING ### - data["litellm_status"] = "success" # used for alerting - - ### RESPONSE HEADERS ### - hidden_params = getattr(response, "_hidden_params", {}) or {} - model_id = hidden_params.get("model_id", None) or "" - cache_key = hidden_params.get("cache_key", None) or "" - api_base = hidden_params.get("api_base", None) or "" - - fastapi_response.headers.update( - get_custom_headers( - user_api_key_dict=user_api_key_dict, - model_id=model_id, - cache_key=cache_key, - api_base=api_base, - version=version, - model_region=getattr(user_api_key_dict, "allowed_model_region", ""), - ) - ) - - return response - except Exception as e: - data["litellm_status"] = "fail" # used for alerting - await proxy_logging_obj.post_call_failure_hook( - user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data - ) - verbose_proxy_logger.error( - "litellm.proxy.proxy_server.create_batch(): Exception occured - {}".format( - str(e) - ) - ) - verbose_proxy_logger.debug(traceback.format_exc()) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "message", str(e.detail)), - type=getattr(e, "type", "None"), - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - else: - error_msg = f"{str(e)}" - raise ProxyException( - message=getattr(e, "message", error_msg), - type=getattr(e, "type", "None"), - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", 500), - ) - - -@router.get( - "/v1/batches{batch_id}", - dependencies=[Depends(user_api_key_auth)], - tags=["batch"], -) -@router.get( - "/batches{batch_id}", - dependencies=[Depends(user_api_key_auth)], - tags=["batch"], -) -async def retrieve_batch( - request: Request, - fastapi_response: Response, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), - batch_id: str = Path( - title="Batch ID to retrieve", description="The ID of the batch to retrieve" - ), -): - """ - Retrieves a batch. - This is the equivalent of GET https://api.openai.com/v1/batches/{batch_id} - Supports Identical Params as: https://platform.openai.com/docs/api-reference/batch/retrieve - - Example Curl - ``` - curl http://localhost:4000/v1/batches/batch_abc123 \ - -H "Authorization: Bearer sk-1234" \ - -H "Content-Type: application/json" \ - - ``` - """ - global proxy_logging_obj - data: Dict = {} - try: - # Use orjson to parse JSON data, orjson speeds up requests significantly - form_data = await request.form() - data = {key: value for key, value in form_data.items() if key != "file"} - - # Include original request and headers in the data - data = await add_litellm_data_to_request( - data=data, - request=request, - general_settings=general_settings, - user_api_key_dict=user_api_key_dict, - version=version, - proxy_config=proxy_config, - ) - - _retrieve_batch_request = RetrieveBatchRequest( - batch_id=batch_id, - ) - - # for now use custom_llm_provider=="openai" -> this will change as LiteLLM adds more providers for acreate_batch - response = await litellm.aretrieve_batch( - custom_llm_provider="openai", **_retrieve_batch_request - ) - - ### ALERTING ### - data["litellm_status"] = "success" # used for alerting - - ### RESPONSE HEADERS ### - hidden_params = getattr(response, "_hidden_params", {}) or {} - model_id = hidden_params.get("model_id", None) or "" - cache_key = hidden_params.get("cache_key", None) or "" - api_base = hidden_params.get("api_base", None) or "" - - fastapi_response.headers.update( - get_custom_headers( - user_api_key_dict=user_api_key_dict, - model_id=model_id, - cache_key=cache_key, - api_base=api_base, - version=version, - model_region=getattr(user_api_key_dict, "allowed_model_region", ""), - ) - ) - - return response - except Exception as e: - data["litellm_status"] = "fail" # used for alerting - await proxy_logging_obj.post_call_failure_hook( - user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data - ) - verbose_proxy_logger.error( - "litellm.proxy.proxy_server.retrieve_batch(): Exception occured - {}".format( - str(e) - ) - ) - verbose_proxy_logger.debug(traceback.format_exc()) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "message", str(e.detail)), - type=getattr(e, "type", "None"), - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - else: - error_traceback = traceback.format_exc() - error_msg = f"{str(e)}" - raise ProxyException( - message=getattr(e, "message", error_msg), - type=getattr(e, "type", "None"), - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", 500), - ) - - -###################################################################### - -# END OF /v1/batches Endpoints Implementation - -###################################################################### - - ###################################################################### # /v1/files Endpoints @@ -6450,2391 +4855,6 @@ async def supported_openai_params(model: str): ) -#### KEY MANAGEMENT #### - - -@router.post( - "/key/generate", - tags=["key management"], - dependencies=[Depends(user_api_key_auth)], - response_model=GenerateKeyResponse, -) -async def generate_key_fn( - data: GenerateKeyRequest, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), - litellm_changed_by: Optional[str] = Header( - None, - description="The litellm-changed-by header enables tracking of actions performed by authorized users on behalf of other users, providing an audit trail for accountability", - ), -): - """ - Generate an API key based on the provided data. - - Docs: https://docs.litellm.ai/docs/proxy/virtual_keys - - Parameters: - - duration: Optional[str] - Specify the length of time the token is valid for. You can set duration as seconds ("30s"), minutes ("30m"), hours ("30h"), days ("30d"). - - key_alias: Optional[str] - User defined key alias - - team_id: Optional[str] - The team id of the key - - user_id: Optional[str] - The user id of the key - - models: Optional[list] - Model_name's a user is allowed to call. (if empty, key is allowed to call all models) - - aliases: Optional[dict] - Any alias mappings, on top of anything in the config.yaml model list. - https://docs.litellm.ai/docs/proxy/virtual_keys#managing-auth---upgradedowngrade-models - - config: Optional[dict] - any key-specific configs, overrides config in config.yaml - - spend: Optional[int] - Amount spent by key. Default is 0. Will be updated by proxy whenever key is used. https://docs.litellm.ai/docs/proxy/virtual_keys#managing-auth---tracking-spend - - send_invite_email: Optional[bool] - Whether to send an invite email to the user_id, with the generate key - - max_budget: Optional[float] - Specify max budget for a given key. - - max_parallel_requests: Optional[int] - Rate limit a user based on the number of parallel requests. Raises 429 error, if user's parallel requests > x. - - metadata: Optional[dict] - Metadata for key, store information for key. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" } - - permissions: Optional[dict] - key-specific permissions. Currently just used for turning off pii masking (if connected). Example - {"pii": false} - - model_max_budget: Optional[dict] - key-specific model budget in USD. Example - {"text-davinci-002": 0.5, "gpt-3.5-turbo": 0.5}. IF null or {} then no model specific budget. - - Examples: - - 1. Allow users to turn on/off pii masking - - ```bash - curl --location 'http://0.0.0.0:8000/key/generate' \ - --header 'Authorization: Bearer sk-1234' \ - --header 'Content-Type: application/json' \ - --data '{ - "permissions": {"allow_pii_controls": true} - }' - ``` - - Returns: - - key: (str) The generated api key - - expires: (datetime) Datetime object for when key expires. - - user_id: (str) Unique user id - used for tracking spend across multiple keys for same user id. - """ - try: - global user_custom_key_generate - verbose_proxy_logger.debug("entered /key/generate") - - if user_custom_key_generate is not None: - result = await user_custom_key_generate(data) - decision = result.get("decision", True) - message = result.get("message", "Authentication Failed - Custom Auth Rule") - if not decision: - raise HTTPException( - status_code=status.HTTP_403_FORBIDDEN, detail=message - ) - # check if user set default key/generate params on config.yaml - if litellm.default_key_generate_params is not None: - for elem in data: - key, value = elem - if value is None and key in [ - "max_budget", - "user_id", - "team_id", - "max_parallel_requests", - "tpm_limit", - "rpm_limit", - "budget_duration", - ]: - setattr( - data, key, litellm.default_key_generate_params.get(key, None) - ) - elif key == "models" and value == []: - setattr(data, key, litellm.default_key_generate_params.get(key, [])) - elif key == "metadata" and value == {}: - setattr(data, key, litellm.default_key_generate_params.get(key, {})) - - # check if user set default key/generate params on config.yaml - if litellm.upperbound_key_generate_params is not None: - for elem in data: - # if key in litellm.upperbound_key_generate_params, use the min of value and litellm.upperbound_key_generate_params[key] - key, value = elem - if ( - value is not None - and getattr(litellm.upperbound_key_generate_params, key, None) - is not None - ): - # if value is float/int - if key in [ - "max_budget", - "max_parallel_requests", - "tpm_limit", - "rpm_limit", - ]: - if value > getattr(litellm.upperbound_key_generate_params, key): - raise HTTPException( - status_code=400, - detail={ - "error": f"{key} is over max limit set in config - user_value={value}; max_value={getattr(litellm.upperbound_key_generate_params, key)}" - }, - ) - elif key == "budget_duration": - # budgets are in 1s, 1m, 1h, 1d, 1m (30s, 30m, 30h, 30d, 30m) - # compare the duration in seconds and max duration in seconds - upperbound_budget_duration = _duration_in_seconds( - duration=getattr( - litellm.upperbound_key_generate_params, key - ) - ) - user_set_budget_duration = _duration_in_seconds(duration=value) - if user_set_budget_duration > upperbound_budget_duration: - raise HTTPException( - status_code=400, - detail={ - "error": f"Budget duration is over max limit set in config - user_value={user_set_budget_duration}; max_value={upperbound_budget_duration}" - }, - ) - - # TODO: @ishaan-jaff: Migrate all budget tracking to use LiteLLM_BudgetTable - _budget_id = None - if prisma_client is not None and data.soft_budget is not None: - # create the Budget Row for the LiteLLM Verification Token - budget_row = LiteLLM_BudgetTable( - soft_budget=data.soft_budget, - model_max_budget=data.model_max_budget or {}, - ) - new_budget = prisma_client.jsonify_object( - budget_row.json(exclude_none=True) - ) - - _budget = await prisma_client.db.litellm_budgettable.create( - data={ - **new_budget, # type: ignore - "created_by": user_api_key_dict.user_id or litellm_proxy_admin_name, - "updated_by": user_api_key_dict.user_id or litellm_proxy_admin_name, - } - ) - _budget_id = getattr(_budget, "budget_id", None) - data_json = data.json() # type: ignore - # if we get max_budget passed to /key/generate, then use it as key_max_budget. Since generate_key_helper_fn is used to make new users - if "max_budget" in data_json: - data_json["key_max_budget"] = data_json.pop("max_budget", None) - if _budget_id is not None: - data_json["budget_id"] = _budget_id - - if "budget_duration" in data_json: - data_json["key_budget_duration"] = data_json.pop("budget_duration", None) - - response = await generate_key_helper_fn( - request_type="key", **data_json, table_name="key" - ) - - response["soft_budget"] = ( - data.soft_budget - ) # include the user-input soft budget in the response - - if data.send_invite_email is True: - if "email" not in general_settings.get("alerting", []): - raise ValueError( - "Email alerting not setup on config.yaml. Please set `alerting=['email']. \nDocs: https://docs.litellm.ai/docs/proxy/email`" - ) - event = WebhookEvent( - event="key_created", - event_group="key", - event_message=f"API Key Created", - token=response.get("token", ""), - spend=response.get("spend", 0.0), - max_budget=response.get("max_budget", 0.0), - user_id=response.get("user_id", None), - team_id=response.get("team_id", "Default Team"), - key_alias=response.get("key_alias", None), - ) - - # If user configured email alerting - send an Email letting their end-user know the key was created - asyncio.create_task( - proxy_logging_obj.slack_alerting_instance.send_key_created_or_user_invited_email( - webhook_event=event, - ) - ) - - # Enterprise Feature - Audit Logging. Enable with litellm.store_audit_logs = True - if litellm.store_audit_logs is True: - _updated_values = json.dumps(response) - asyncio.create_task( - create_audit_log_for_update( - request_data=LiteLLM_AuditLogs( - id=str(uuid.uuid4()), - updated_at=datetime.now(timezone.utc), - changed_by=litellm_changed_by - or user_api_key_dict.user_id - or litellm_proxy_admin_name, - changed_by_api_key=user_api_key_dict.api_key, - table_name=LitellmTableNames.KEY_TABLE_NAME, - object_id=response.get("token_id", ""), - action="created", - updated_values=_updated_values, - before_value=None, - ) - ) - ) - - return GenerateKeyResponse(**response) - except Exception as e: - verbose_proxy_logger.error( - "litellm.proxy.proxy_server.generate_key_fn(): Exception occured - {}".format( - str(e) - ) - ) - verbose_proxy_logger.debug(traceback.format_exc()) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({str(e)})"), - type="auth_error", - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type="auth_error", - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) - - -@router.post( - "/key/update", tags=["key management"], dependencies=[Depends(user_api_key_auth)] -) -async def update_key_fn( - request: Request, - data: UpdateKeyRequest, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), - litellm_changed_by: Optional[str] = Header( - None, - description="The litellm-changed-by header enables tracking of actions performed by authorized users on behalf of other users, providing an audit trail for accountability", - ), -): - """ - Update an existing key - """ - global prisma_client - try: - data_json: dict = data.json() - key = data_json.pop("key") - # get the row from db - if prisma_client is None: - raise Exception("Not connected to DB!") - - existing_key_row = await prisma_client.get_data( - token=data.key, table_name="key", query_type="find_unique" - ) - - if existing_key_row is None: - raise HTTPException( - status_code=404, - detail={"error": f"Team not found, passed team_id={data.team_id}"}, - ) - - # get non default values for key - non_default_values = {} - for k, v in data_json.items(): - if v is not None and v not in ( - [], - {}, - 0, - ): # models default to [], spend defaults to 0, we should not reset these values - non_default_values[k] = v - - if "duration" in non_default_values: - duration = non_default_values.pop("duration") - duration_s = _duration_in_seconds(duration=duration) - expires = datetime.now(timezone.utc) + timedelta(seconds=duration_s) - non_default_values["expires"] = expires - - response = await prisma_client.update_data( - token=key, data={**non_default_values, "token": key} - ) - - # Delete - key from cache, since it's been updated! - # key updated - a new model could have been added to this key. it should not block requests after this is done - user_api_key_cache.delete_cache(key) - hashed_token = hash_token(key) - user_api_key_cache.delete_cache(hashed_token) - - # Enterprise Feature - Audit Logging. Enable with litellm.store_audit_logs = True - if litellm.store_audit_logs is True: - _updated_values = json.dumps(data_json) - - _before_value = existing_key_row.json(exclude_none=True) - _before_value = json.dumps(_before_value) - - asyncio.create_task( - create_audit_log_for_update( - request_data=LiteLLM_AuditLogs( - id=str(uuid.uuid4()), - updated_at=datetime.now(timezone.utc), - changed_by=litellm_changed_by - or user_api_key_dict.user_id - or litellm_proxy_admin_name, - changed_by_api_key=user_api_key_dict.api_key, - table_name=LitellmTableNames.KEY_TABLE_NAME, - object_id=data.key, - action="updated", - updated_values=_updated_values, - before_value=_before_value, - ) - ) - ) - - return {"key": key, **response["data"]} - # update based on remaining passed in values - except Exception as e: - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({str(e)})"), - type="auth_error", - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type="auth_error", - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) - - -@router.post( - "/key/delete", tags=["key management"], dependencies=[Depends(user_api_key_auth)] -) -async def delete_key_fn( - data: KeyRequest, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), - litellm_changed_by: Optional[str] = Header( - None, - description="The litellm-changed-by header enables tracking of actions performed by authorized users on behalf of other users, providing an audit trail for accountability", - ), -): - """ - Delete a key from the key management system. - - Parameters:: - - keys (List[str]): A list of keys or hashed keys to delete. Example {"keys": ["sk-QWrxEynunsNpV1zT48HIrw", "837e17519f44683334df5291321d97b8bf1098cd490e49e215f6fea935aa28be"]} - - Returns: - - deleted_keys (List[str]): A list of deleted keys. Example {"deleted_keys": ["sk-QWrxEynunsNpV1zT48HIrw", "837e17519f44683334df5291321d97b8bf1098cd490e49e215f6fea935aa28be"]} - - - Raises: - HTTPException: If an error occurs during key deletion. - """ - try: - global user_api_key_cache - keys = data.keys - if len(keys) == 0: - raise ProxyException( - message=f"No keys provided, passed in: keys={keys}", - type="auth_error", - param="keys", - code=status.HTTP_400_BAD_REQUEST, - ) - - ## only allow user to delete keys they own - user_id = user_api_key_dict.user_id - verbose_proxy_logger.debug( - f"user_api_key_dict.user_role: {user_api_key_dict.user_role}" - ) - if ( - user_api_key_dict.user_role is not None - and user_api_key_dict.user_role == LitellmUserRoles.PROXY_ADMIN - ): - user_id = None # unless they're admin - - # Enterprise Feature - Audit Logging. Enable with litellm.store_audit_logs = True - # we do this after the first for loop, since first for loop is for validation. we only want this inserted after validation passes - if litellm.store_audit_logs is True: - # make an audit log for each team deleted - for key in data.keys: - key_row = await prisma_client.get_data( # type: ignore - token=key, table_name="key", query_type="find_unique" - ) - - key_row = key_row.json(exclude_none=True) - _key_row = json.dumps(key_row) - - asyncio.create_task( - create_audit_log_for_update( - request_data=LiteLLM_AuditLogs( - id=str(uuid.uuid4()), - updated_at=datetime.now(timezone.utc), - changed_by=litellm_changed_by - or user_api_key_dict.user_id - or litellm_proxy_admin_name, - changed_by_api_key=user_api_key_dict.api_key, - table_name=LitellmTableNames.KEY_TABLE_NAME, - object_id=key, - action="deleted", - updated_values="{}", - before_value=_key_row, - ) - ) - ) - - number_deleted_keys = await delete_verification_token( - tokens=keys, user_id=user_id - ) - verbose_proxy_logger.debug( - f"/key/delete - deleted_keys={number_deleted_keys['deleted_keys']}" - ) - - try: - assert len(keys) == number_deleted_keys["deleted_keys"] - except Exception as e: - raise HTTPException( - status_code=400, - detail={ - "error": f"Not all keys passed in were deleted. This probably means you don't have access to delete all the keys passed in. Keys passed in={len(keys)}, Deleted keys ={number_deleted_keys['deleted_keys']}" - }, - ) - - for key in keys: - user_api_key_cache.delete_cache(key) - # remove hash token from cache - hashed_token = hash_token(key) - user_api_key_cache.delete_cache(hashed_token) - - verbose_proxy_logger.debug( - f"/keys/delete - cache after delete: {user_api_key_cache.in_memory_cache.cache_dict}" - ) - - return {"deleted_keys": keys} - except Exception as e: - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({str(e)})"), - type="auth_error", - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type="auth_error", - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) - - -@router.post( - "/v2/key/info", tags=["key management"], dependencies=[Depends(user_api_key_auth)] -) -async def info_key_fn_v2( - data: Optional[KeyRequest] = None, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), -): - """ - Retrieve information about a list of keys. - - **New endpoint**. Currently admin only. - Parameters: - keys: Optional[list] = body parameter representing the key(s) in the request - user_api_key_dict: UserAPIKeyAuth = Dependency representing the user's API key - Returns: - Dict containing the key and its associated information - - Example Curl: - ``` - curl -X GET "http://0.0.0.0:8000/key/info" \ - -H "Authorization: Bearer sk-1234" \ - -d {"keys": ["sk-1", "sk-2", "sk-3"]} - ``` - """ - global prisma_client - try: - if prisma_client is None: - raise Exception( - f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - ) - if data is None: - raise HTTPException( - status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, - detail={"message": "Malformed request. No keys passed in."}, - ) - - key_info = await prisma_client.get_data( - token=data.keys, table_name="key", query_type="find_all" - ) - filtered_key_info = [] - for k in key_info: - try: - k = k.model_dump() # noqa - except: - # if using pydantic v1 - k = k.dict() - filtered_key_info.append(k) - return {"key": data.keys, "info": filtered_key_info} - - except Exception as e: - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({str(e)})"), - type="auth_error", - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type="auth_error", - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) - - -@router.get( - "/key/info", tags=["key management"], dependencies=[Depends(user_api_key_auth)] -) -async def info_key_fn( - key: Optional[str] = fastapi.Query( - default=None, description="Key in the request parameters" - ), - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), -): - """ - Retrieve information about a key. - Parameters: - key: Optional[str] = Query parameter representing the key in the request - user_api_key_dict: UserAPIKeyAuth = Dependency representing the user's API key - Returns: - Dict containing the key and its associated information - - Example Curl: - ``` - curl -X GET "http://0.0.0.0:8000/key/info?key=sk-02Wr4IAlN3NvPXvL5JVvDA" \ --H "Authorization: Bearer sk-1234" - ``` - - Example Curl - if no key is passed, it will use the Key Passed in Authorization Header - ``` - curl -X GET "http://0.0.0.0:8000/key/info" \ --H "Authorization: Bearer sk-02Wr4IAlN3NvPXvL5JVvDA" - ``` - """ - global prisma_client - try: - if prisma_client is None: - raise Exception( - f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - ) - if key == None: - key = user_api_key_dict.api_key - key_info = await prisma_client.get_data(token=key) - ## REMOVE HASHED TOKEN INFO BEFORE RETURNING ## - try: - key_info = key_info.model_dump() # noqa - except: - # if using pydantic v1 - key_info = key_info.dict() - key_info.pop("token") - return {"key": key, "info": key_info} - except Exception as e: - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({str(e)})"), - type="auth_error", - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type="auth_error", - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) - - -#### SPEND MANAGEMENT ##### - - -@router.get( - "/spend/keys", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], -) -async def spend_key_fn(): - """ - View all keys created, ordered by spend - - Example Request: - ``` - curl -X GET "http://0.0.0.0:8000/spend/keys" \ --H "Authorization: Bearer sk-1234" - ``` - """ - global prisma_client - try: - if prisma_client is None: - raise Exception( - f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - ) - - key_info = await prisma_client.get_data(table_name="key", query_type="find_all") - return key_info - - except Exception as e: - raise HTTPException( - status_code=status.HTTP_400_BAD_REQUEST, - detail={"error": str(e)}, - ) - - -@router.get( - "/spend/users", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], -) -async def spend_user_fn( - user_id: Optional[str] = fastapi.Query( - default=None, - description="Get User Table row for user_id", - ), -): - """ - View all users created, ordered by spend - - Example Request: - ``` - curl -X GET "http://0.0.0.0:8000/spend/users" \ --H "Authorization: Bearer sk-1234" - ``` - - View User Table row for user_id - ``` - curl -X GET "http://0.0.0.0:8000/spend/users?user_id=1234" \ --H "Authorization: Bearer sk-1234" - ``` - """ - global prisma_client - try: - if prisma_client is None: - raise Exception( - f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - ) - - if user_id is not None: - user_info = await prisma_client.get_data( - table_name="user", query_type="find_unique", user_id=user_id - ) - return [user_info] - else: - user_info = await prisma_client.get_data( - table_name="user", query_type="find_all" - ) - - return user_info - - except Exception as e: - raise HTTPException( - status_code=status.HTTP_400_BAD_REQUEST, - detail={"error": str(e)}, - ) - - -@router.get( - "/spend/tags", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], - responses={ - 200: {"model": List[LiteLLM_SpendLogs]}, - }, -) -async def view_spend_tags( - start_date: Optional[str] = fastapi.Query( - default=None, - description="Time from which to start viewing key spend", - ), - end_date: Optional[str] = fastapi.Query( - default=None, - description="Time till which to view key spend", - ), -): - """ - LiteLLM Enterprise - View Spend Per Request Tag - - Example Request: - ``` - curl -X GET "http://0.0.0.0:8000/spend/tags" \ --H "Authorization: Bearer sk-1234" - ``` - - Spend with Start Date and End Date - ``` - curl -X GET "http://0.0.0.0:8000/spend/tags?start_date=2022-01-01&end_date=2022-02-01" \ --H "Authorization: Bearer sk-1234" - ``` - """ - - from enterprise.utils import get_spend_by_tags - - global prisma_client - try: - if prisma_client is None: - raise Exception( - f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - ) - - # run the following SQL query on prisma - """ - SELECT - jsonb_array_elements_text(request_tags) AS individual_request_tag, - COUNT(*) AS log_count, - SUM(spend) AS total_spend - FROM "LiteLLM_SpendLogs" - GROUP BY individual_request_tag; - """ - response = await get_spend_by_tags( - start_date=start_date, end_date=end_date, prisma_client=prisma_client - ) - - return response - except Exception as e: - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"/spend/tags Error({str(e)})"), - type="internal_error", - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_500_INTERNAL_SERVER_ERROR), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="/spend/tags Error" + str(e), - type="internal_error", - param=getattr(e, "param", "None"), - code=status.HTTP_500_INTERNAL_SERVER_ERROR, - ) - - -@router.get( - "/global/activity", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], - responses={ - 200: {"model": List[LiteLLM_SpendLogs]}, - }, -) -async def get_global_activity( - start_date: Optional[str] = fastapi.Query( - default=None, - description="Time from which to start viewing spend", - ), - end_date: Optional[str] = fastapi.Query( - default=None, - description="Time till which to view spend", - ), -): - """ - Get number of API Requests, total tokens through proxy - - { - "daily_data": [ - const chartdata = [ - { - date: 'Jan 22', - api_requests: 10, - total_tokens: 2000 - }, - { - date: 'Jan 23', - api_requests: 10, - total_tokens: 12 - }, - ], - "sum_api_requests": 20, - "sum_total_tokens": 2012 - } - """ - from collections import defaultdict - - if start_date is None or end_date is None: - raise HTTPException( - status_code=status.HTTP_400_BAD_REQUEST, - detail={"error": "Please provide start_date and end_date"}, - ) - - start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") - end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") - - global prisma_client, llm_router - try: - if prisma_client is None: - raise Exception( - f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - ) - - sql_query = """ - SELECT - date_trunc('day', "startTime") AS date, - COUNT(*) AS api_requests, - SUM(total_tokens) AS total_tokens - FROM "LiteLLM_SpendLogs" - WHERE "startTime" BETWEEN $1::date AND $2::date + interval '1 day' - GROUP BY date_trunc('day', "startTime") - """ - db_response = await prisma_client.db.query_raw( - sql_query, start_date_obj, end_date_obj - ) - - if db_response is None: - return [] - - sum_api_requests = 0 - sum_total_tokens = 0 - daily_data = [] - for row in db_response: - # cast date to datetime - _date_obj = datetime.fromisoformat(row["date"]) - row["date"] = _date_obj.strftime("%b %d") - - daily_data.append(row) - sum_api_requests += row.get("api_requests", 0) - sum_total_tokens += row.get("total_tokens", 0) - - # sort daily_data by date - daily_data = sorted(daily_data, key=lambda x: x["date"]) - - data_to_return = { - "daily_data": daily_data, - "sum_api_requests": sum_api_requests, - "sum_total_tokens": sum_total_tokens, - } - - return data_to_return - - except Exception as e: - raise HTTPException( - status_code=status.HTTP_400_BAD_REQUEST, - detail={"error": str(e)}, - ) - - -@router.get( - "/global/activity/model", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], - responses={ - 200: {"model": List[LiteLLM_SpendLogs]}, - }, -) -async def get_global_activity_model( - start_date: Optional[str] = fastapi.Query( - default=None, - description="Time from which to start viewing spend", - ), - end_date: Optional[str] = fastapi.Query( - default=None, - description="Time till which to view spend", - ), -): - """ - Get number of API Requests, total tokens through proxy - Grouped by MODEL - - [ - { - "model": "gpt-4", - "daily_data": [ - const chartdata = [ - { - date: 'Jan 22', - api_requests: 10, - total_tokens: 2000 - }, - { - date: 'Jan 23', - api_requests: 10, - total_tokens: 12 - }, - ], - "sum_api_requests": 20, - "sum_total_tokens": 2012 - - }, - { - "model": "azure/gpt-4-turbo", - "daily_data": [ - const chartdata = [ - { - date: 'Jan 22', - api_requests: 10, - total_tokens: 2000 - }, - { - date: 'Jan 23', - api_requests: 10, - total_tokens: 12 - }, - ], - "sum_api_requests": 20, - "sum_total_tokens": 2012 - - }, - ] - """ - from collections import defaultdict - - if start_date is None or end_date is None: - raise HTTPException( - status_code=status.HTTP_400_BAD_REQUEST, - detail={"error": "Please provide start_date and end_date"}, - ) - - start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") - end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") - - global prisma_client, llm_router, premium_user - try: - if prisma_client is None: - raise Exception( - f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - ) - - sql_query = """ - SELECT - model_group, - date_trunc('day', "startTime") AS date, - COUNT(*) AS api_requests, - SUM(total_tokens) AS total_tokens - FROM "LiteLLM_SpendLogs" - WHERE "startTime" BETWEEN $1::date AND $2::date + interval '1 day' - GROUP BY model_group, date_trunc('day', "startTime") - """ - db_response = await prisma_client.db.query_raw( - sql_query, start_date_obj, end_date_obj - ) - if db_response is None: - return [] - - model_ui_data: dict = ( - {} - ) # {"gpt-4": {"daily_data": [], "sum_api_requests": 0, "sum_total_tokens": 0}} - - for row in db_response: - _model = row["model_group"] - if _model not in model_ui_data: - model_ui_data[_model] = { - "daily_data": [], - "sum_api_requests": 0, - "sum_total_tokens": 0, - } - _date_obj = datetime.fromisoformat(row["date"]) - row["date"] = _date_obj.strftime("%b %d") - - model_ui_data[_model]["daily_data"].append(row) - model_ui_data[_model]["sum_api_requests"] += row.get("api_requests", 0) - model_ui_data[_model]["sum_total_tokens"] += row.get("total_tokens", 0) - - # sort mode ui data by sum_api_requests -> get top 10 models - model_ui_data = dict( - sorted( - model_ui_data.items(), - key=lambda x: x[1]["sum_api_requests"], - reverse=True, - )[:10] - ) - - response = [] - for model, data in model_ui_data.items(): - _sort_daily_data = sorted(data["daily_data"], key=lambda x: x["date"]) - - response.append( - { - "model": model, - "daily_data": _sort_daily_data, - "sum_api_requests": data["sum_api_requests"], - "sum_total_tokens": data["sum_total_tokens"], - } - ) - - return response - - except Exception as e: - raise HTTPException( - status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, - detail={"error": str(e)}, - ) - - -@router.get( - "/global/activity/exceptions/deployment", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], - responses={ - 200: {"model": List[LiteLLM_SpendLogs]}, - }, -) -async def get_global_activity_exceptions_per_deployment( - model_group: str = fastapi.Query( - description="Filter by model group", - ), - start_date: Optional[str] = fastapi.Query( - default=None, - description="Time from which to start viewing spend", - ), - end_date: Optional[str] = fastapi.Query( - default=None, - description="Time till which to view spend", - ), -): - """ - Get number of 429 errors - Grouped by deployment - - [ - { - "deployment": "https://azure-us-east-1.openai.azure.com/", - "daily_data": [ - const chartdata = [ - { - date: 'Jan 22', - num_rate_limit_exceptions: 10 - }, - { - date: 'Jan 23', - num_rate_limit_exceptions: 12 - }, - ], - "sum_num_rate_limit_exceptions": 20, - - }, - { - "deployment": "https://azure-us-east-1.openai.azure.com/", - "daily_data": [ - const chartdata = [ - { - date: 'Jan 22', - num_rate_limit_exceptions: 10, - }, - { - date: 'Jan 23', - num_rate_limit_exceptions: 12 - }, - ], - "sum_num_rate_limit_exceptions": 20, - - }, - ] - """ - from collections import defaultdict - - if start_date is None or end_date is None: - raise HTTPException( - status_code=status.HTTP_400_BAD_REQUEST, - detail={"error": "Please provide start_date and end_date"}, - ) - - start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") - end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") - - global prisma_client, llm_router, premium_user - try: - if prisma_client is None: - raise Exception( - f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - ) - - sql_query = """ - SELECT - api_base, - date_trunc('day', "startTime")::date AS date, - COUNT(*) AS num_rate_limit_exceptions - FROM - "LiteLLM_ErrorLogs" - WHERE - "startTime" >= $1::date - AND "startTime" < ($2::date + INTERVAL '1 day') - AND model_group = $3 - AND status_code = '429' - GROUP BY - api_base, - date_trunc('day', "startTime") - ORDER BY - date; - """ - db_response = await prisma_client.db.query_raw( - sql_query, start_date_obj, end_date_obj, model_group - ) - if db_response is None: - return [] - - model_ui_data: dict = ( - {} - ) # {"gpt-4": {"daily_data": [], "sum_api_requests": 0, "sum_total_tokens": 0}} - - for row in db_response: - _model = row["api_base"] - if _model not in model_ui_data: - model_ui_data[_model] = { - "daily_data": [], - "sum_num_rate_limit_exceptions": 0, - } - _date_obj = datetime.fromisoformat(row["date"]) - row["date"] = _date_obj.strftime("%b %d") - - model_ui_data[_model]["daily_data"].append(row) - model_ui_data[_model]["sum_num_rate_limit_exceptions"] += row.get( - "num_rate_limit_exceptions", 0 - ) - - # sort mode ui data by sum_api_requests -> get top 10 models - model_ui_data = dict( - sorted( - model_ui_data.items(), - key=lambda x: x[1]["sum_num_rate_limit_exceptions"], - reverse=True, - )[:10] - ) - - response = [] - for model, data in model_ui_data.items(): - _sort_daily_data = sorted(data["daily_data"], key=lambda x: x["date"]) - - response.append( - { - "api_base": model, - "daily_data": _sort_daily_data, - "sum_num_rate_limit_exceptions": data[ - "sum_num_rate_limit_exceptions" - ], - } - ) - - return response - - except Exception as e: - raise HTTPException( - status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, - detail={"error": str(e)}, - ) - - -@router.get( - "/global/activity/exceptions", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], - responses={ - 200: {"model": List[LiteLLM_SpendLogs]}, - }, -) -async def get_global_activity_exceptions( - model_group: str = fastapi.Query( - description="Filter by model group", - ), - start_date: Optional[str] = fastapi.Query( - default=None, - description="Time from which to start viewing spend", - ), - end_date: Optional[str] = fastapi.Query( - default=None, - description="Time till which to view spend", - ), -): - """ - Get number of API Requests, total tokens through proxy - - { - "daily_data": [ - const chartdata = [ - { - date: 'Jan 22', - num_rate_limit_exceptions: 10, - }, - { - date: 'Jan 23', - num_rate_limit_exceptions: 10, - }, - ], - "sum_api_exceptions": 20, - } - """ - from collections import defaultdict - - if start_date is None or end_date is None: - raise HTTPException( - status_code=status.HTTP_400_BAD_REQUEST, - detail={"error": "Please provide start_date and end_date"}, - ) - - start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") - end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") - - global prisma_client, llm_router - try: - if prisma_client is None: - raise Exception( - f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - ) - - sql_query = """ - SELECT - date_trunc('day', "startTime")::date AS date, - COUNT(*) AS num_rate_limit_exceptions - FROM - "LiteLLM_ErrorLogs" - WHERE - "startTime" >= $1::date - AND "startTime" < ($2::date + INTERVAL '1 day') - AND model_group = $3 - AND status_code = '429' - GROUP BY - date_trunc('day', "startTime") - ORDER BY - date; - """ - db_response = await prisma_client.db.query_raw( - sql_query, start_date_obj, end_date_obj, model_group - ) - - if db_response is None: - return [] - - sum_num_rate_limit_exceptions = 0 - daily_data = [] - for row in db_response: - # cast date to datetime - _date_obj = datetime.fromisoformat(row["date"]) - row["date"] = _date_obj.strftime("%b %d") - - daily_data.append(row) - sum_num_rate_limit_exceptions += row.get("num_rate_limit_exceptions", 0) - - # sort daily_data by date - daily_data = sorted(daily_data, key=lambda x: x["date"]) - - data_to_return = { - "daily_data": daily_data, - "sum_num_rate_limit_exceptions": sum_num_rate_limit_exceptions, - } - - return data_to_return - - except Exception as e: - raise HTTPException( - status_code=status.HTTP_400_BAD_REQUEST, - detail={"error": str(e)}, - ) - - -@router.get( - "/global/spend/provider", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], - include_in_schema=False, - responses={ - 200: {"model": List[LiteLLM_SpendLogs]}, - }, -) -async def get_global_spend_provider( - start_date: Optional[str] = fastapi.Query( - default=None, - description="Time from which to start viewing spend", - ), - end_date: Optional[str] = fastapi.Query( - default=None, - description="Time till which to view spend", - ), -): - """ - Get breakdown of spend per provider - [ - { - "provider": "Azure OpenAI", - "spend": 20 - }, - { - "provider": "OpenAI", - "spend": 10 - }, - { - "provider": "VertexAI", - "spend": 30 - } - ] - """ - from collections import defaultdict - - if start_date is None or end_date is None: - raise HTTPException( - status_code=status.HTTP_400_BAD_REQUEST, - detail={"error": "Please provide start_date and end_date"}, - ) - - start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") - end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") - - global prisma_client, llm_router - try: - if prisma_client is None: - raise Exception( - f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - ) - - sql_query = """ - - SELECT - model_id, - SUM(spend) AS spend - FROM "LiteLLM_SpendLogs" - WHERE "startTime" BETWEEN $1::date AND $2::date AND length(model_id) > 0 - GROUP BY model_id - """ - - db_response = await prisma_client.db.query_raw( - sql_query, start_date_obj, end_date_obj - ) - if db_response is None: - return [] - - ################################### - # Convert model_id -> to Provider # - ################################### - - # we use the in memory router for this - ui_response = [] - provider_spend_mapping: defaultdict = defaultdict(int) - for row in db_response: - _model_id = row["model_id"] - _provider = "Unknown" - if llm_router is not None: - _deployment = llm_router.get_deployment(model_id=_model_id) - if _deployment is not None: - try: - _, _provider, _, _ = litellm.get_llm_provider( - model=_deployment.litellm_params.model, - custom_llm_provider=_deployment.litellm_params.custom_llm_provider, - api_base=_deployment.litellm_params.api_base, - litellm_params=_deployment.litellm_params, - ) - provider_spend_mapping[_provider] += row["spend"] - except: - pass - - for provider, spend in provider_spend_mapping.items(): - ui_response.append({"provider": provider, "spend": spend}) - - return ui_response - - except Exception as e: - raise HTTPException( - status_code=status.HTTP_400_BAD_REQUEST, - detail={"error": str(e)}, - ) - - -@router.get( - "/global/spend/report", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], - responses={ - 200: {"model": List[LiteLLM_SpendLogs]}, - }, -) -async def get_global_spend_report( - start_date: Optional[str] = fastapi.Query( - default=None, - description="Time from which to start viewing spend", - ), - end_date: Optional[str] = fastapi.Query( - default=None, - description="Time till which to view spend", - ), - group_by: Optional[Literal["team", "customer"]] = fastapi.Query( - default="team", - description="Group spend by internal team or customer", - ), -): - """ - Get Daily Spend per Team, based on specific startTime and endTime. Per team, view usage by each key, model - [ - { - "group-by-day": "2024-05-10", - "teams": [ - { - "team_name": "team-1" - "spend": 10, - "keys": [ - "key": "1213", - "usage": { - "model-1": { - "cost": 12.50, - "input_tokens": 1000, - "output_tokens": 5000, - "requests": 100 - }, - "audio-modelname1": { - "cost": 25.50, - "seconds": 25, - "requests": 50 - }, - } - } - ] - ] - } - """ - if start_date is None or end_date is None: - raise HTTPException( - status_code=status.HTTP_400_BAD_REQUEST, - detail={"error": "Please provide start_date and end_date"}, - ) - - start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") - end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") - - global prisma_client - try: - if prisma_client is None: - raise Exception( - f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - ) - - if group_by == "team": - # first get data from spend logs -> SpendByModelApiKey - # then read data from "SpendByModelApiKey" to format the response obj - sql_query = """ - - WITH SpendByModelApiKey AS ( - SELECT - date_trunc('day', sl."startTime") AS group_by_day, - COALESCE(tt.team_alias, 'Unassigned Team') AS team_name, - sl.model, - sl.api_key, - SUM(sl.spend) AS model_api_spend, - SUM(sl.total_tokens) AS model_api_tokens - FROM - "LiteLLM_SpendLogs" sl - LEFT JOIN - "LiteLLM_TeamTable" tt - ON - sl.team_id = tt.team_id - WHERE - sl."startTime" BETWEEN $1::date AND $2::date - GROUP BY - date_trunc('day', sl."startTime"), - tt.team_alias, - sl.model, - sl.api_key - ) - SELECT - group_by_day, - jsonb_agg(jsonb_build_object( - 'team_name', team_name, - 'total_spend', total_spend, - 'metadata', metadata - )) AS teams - FROM ( - SELECT - group_by_day, - team_name, - SUM(model_api_spend) AS total_spend, - jsonb_agg(jsonb_build_object( - 'model', model, - 'api_key', api_key, - 'spend', model_api_spend, - 'total_tokens', model_api_tokens - )) AS metadata - FROM - SpendByModelApiKey - GROUP BY - group_by_day, - team_name - ) AS aggregated - GROUP BY - group_by_day - ORDER BY - group_by_day; - """ - - db_response = await prisma_client.db.query_raw( - sql_query, start_date_obj, end_date_obj - ) - if db_response is None: - return [] - - return db_response - - elif group_by == "customer": - sql_query = """ - - WITH SpendByModelApiKey AS ( - SELECT - date_trunc('day', sl."startTime") AS group_by_day, - sl.end_user AS customer, - sl.model, - sl.api_key, - SUM(sl.spend) AS model_api_spend, - SUM(sl.total_tokens) AS model_api_tokens - FROM - "LiteLLM_SpendLogs" sl - WHERE - sl."startTime" BETWEEN $1::date AND $2::date - GROUP BY - date_trunc('day', sl."startTime"), - customer, - sl.model, - sl.api_key - ) - SELECT - group_by_day, - jsonb_agg(jsonb_build_object( - 'customer', customer, - 'total_spend', total_spend, - 'metadata', metadata - )) AS customers - FROM - ( - SELECT - group_by_day, - customer, - SUM(model_api_spend) AS total_spend, - jsonb_agg(jsonb_build_object( - 'model', model, - 'api_key', api_key, - 'spend', model_api_spend, - 'total_tokens', model_api_tokens - )) AS metadata - FROM - SpendByModelApiKey - GROUP BY - group_by_day, - customer - ) AS aggregated - GROUP BY - group_by_day - ORDER BY - group_by_day; - """ - - db_response = await prisma_client.db.query_raw( - sql_query, start_date_obj, end_date_obj - ) - if db_response is None: - return [] - - return db_response - - except Exception as e: - raise HTTPException( - status_code=status.HTTP_400_BAD_REQUEST, - detail={"error": str(e)}, - ) - - -@router.get( - "/global/spend/all_tag_names", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], - include_in_schema=False, - responses={ - 200: {"model": List[LiteLLM_SpendLogs]}, - }, -) -async def global_get_all_tag_names(): - try: - if prisma_client is None: - raise Exception( - f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - ) - - sql_query = """ - SELECT DISTINCT - jsonb_array_elements_text(request_tags) AS individual_request_tag - FROM "LiteLLM_SpendLogs"; - """ - - db_response = await prisma_client.db.query_raw(sql_query) - if db_response is None: - return [] - - _tag_names = [] - for row in db_response: - _tag_names.append(row.get("individual_request_tag")) - - return {"tag_names": _tag_names} - - except Exception as e: - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"/spend/all_tag_names Error({str(e)})"), - type="internal_error", - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_500_INTERNAL_SERVER_ERROR), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="/spend/all_tag_names Error" + str(e), - type="internal_error", - param=getattr(e, "param", "None"), - code=status.HTTP_500_INTERNAL_SERVER_ERROR, - ) - - -@router.get( - "/global/spend/tags", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], - include_in_schema=False, - responses={ - 200: {"model": List[LiteLLM_SpendLogs]}, - }, -) -async def global_view_spend_tags( - start_date: Optional[str] = fastapi.Query( - default=None, - description="Time from which to start viewing key spend", - ), - end_date: Optional[str] = fastapi.Query( - default=None, - description="Time till which to view key spend", - ), - tags: Optional[str] = fastapi.Query( - default=None, - description="comman separated tags to filter on", - ), -): - """ - LiteLLM Enterprise - View Spend Per Request Tag. Used by LiteLLM UI - - Example Request: - ``` - curl -X GET "http://0.0.0.0:4000/spend/tags" \ --H "Authorization: Bearer sk-1234" - ``` - - Spend with Start Date and End Date - ``` - curl -X GET "http://0.0.0.0:4000/spend/tags?start_date=2022-01-01&end_date=2022-02-01" \ --H "Authorization: Bearer sk-1234" - ``` - """ - - from enterprise.utils import ui_get_spend_by_tags - - global prisma_client - try: - if prisma_client is None: - raise Exception( - f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - ) - - if end_date is None or start_date is None: - raise ProxyException( - message="Please provide start_date and end_date", - type="bad_request", - param=None, - code=status.HTTP_400_BAD_REQUEST, - ) - response = await ui_get_spend_by_tags( - start_date=start_date, - end_date=end_date, - tags_str=tags, - prisma_client=prisma_client, - ) - - return response - except Exception as e: - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"/spend/tags Error({str(e)})"), - type="internal_error", - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_500_INTERNAL_SERVER_ERROR), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="/spend/tags Error" + str(e), - type="internal_error", - param=getattr(e, "param", "None"), - code=status.HTTP_500_INTERNAL_SERVER_ERROR, - ) - - -async def _get_spend_report_for_time_range( - start_date: str, - end_date: str, -): - global prisma_client - if prisma_client is None: - verbose_proxy_logger.error( - f"Database not connected. Connect a database to your proxy for weekly, monthly spend reports" - ) - return None - - try: - sql_query = """ - SELECT - t.team_alias, - SUM(s.spend) AS total_spend - FROM - "LiteLLM_SpendLogs" s - LEFT JOIN - "LiteLLM_TeamTable" t ON s.team_id = t.team_id - WHERE - s."startTime"::DATE >= $1::date AND s."startTime"::DATE <= $2::date - GROUP BY - t.team_alias - ORDER BY - total_spend DESC; - """ - response = await prisma_client.db.query_raw(sql_query, start_date, end_date) - - # get spend per tag for today - sql_query = """ - SELECT - jsonb_array_elements_text(request_tags) AS individual_request_tag, - SUM(spend) AS total_spend - FROM "LiteLLM_SpendLogs" - WHERE "startTime"::DATE >= $1::date AND "startTime"::DATE <= $2::date - GROUP BY individual_request_tag - ORDER BY total_spend DESC; - """ - - spend_per_tag = await prisma_client.db.query_raw( - sql_query, start_date, end_date - ) - - return response, spend_per_tag - except Exception as e: - verbose_proxy_logger.error( - "Exception in _get_daily_spend_reports {}".format(str(e)) - ) # noqa - - -@router.post( - "/spend/calculate", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], - responses={ - 200: { - "cost": { - "description": "The calculated cost", - "example": 0.0, - "type": "float", - } - } - }, -) -async def calculate_spend(request: Request): - """ - Accepts all the params of completion_cost. - - Calculate spend **before** making call: - - Note: If you see a spend of $0.0 you need to set custom_pricing for your model: https://docs.litellm.ai/docs/proxy/custom_pricing - - ``` - curl --location 'http://localhost:4000/spend/calculate' - --header 'Authorization: Bearer sk-1234' - --header 'Content-Type: application/json' - --data '{ - "model": "anthropic.claude-v2", - "messages": [{"role": "user", "content": "Hey, how'''s it going?"}] - }' - ``` - - Calculate spend **after** making call: - - ``` - curl --location 'http://localhost:4000/spend/calculate' - --header 'Authorization: Bearer sk-1234' - --header 'Content-Type: application/json' - --data '{ - "completion_response": { - "id": "chatcmpl-123", - "object": "chat.completion", - "created": 1677652288, - "model": "gpt-3.5-turbo-0125", - "system_fingerprint": "fp_44709d6fcb", - "choices": [{ - "index": 0, - "message": { - "role": "assistant", - "content": "Hello there, how may I assist you today?" - }, - "logprobs": null, - "finish_reason": "stop" - }] - "usage": { - "prompt_tokens": 9, - "completion_tokens": 12, - "total_tokens": 21 - } - } - }' - ``` - """ - from litellm import completion_cost - - data = await request.json() - if "completion_response" in data: - data["completion_response"] = litellm.ModelResponse( - **data["completion_response"] - ) - return {"cost": completion_cost(**data)} - - -@router.get( - "/spend/logs", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], - responses={ - 200: {"model": List[LiteLLM_SpendLogs]}, - }, -) -async def view_spend_logs( - api_key: Optional[str] = fastapi.Query( - default=None, - description="Get spend logs based on api key", - ), - user_id: Optional[str] = fastapi.Query( - default=None, - description="Get spend logs based on user_id", - ), - request_id: Optional[str] = fastapi.Query( - default=None, - description="request_id to get spend logs for specific request_id. If none passed then pass spend logs for all requests", - ), - start_date: Optional[str] = fastapi.Query( - default=None, - description="Time from which to start viewing key spend", - ), - end_date: Optional[str] = fastapi.Query( - default=None, - description="Time till which to view key spend", - ), -): - """ - View all spend logs, if request_id is provided, only logs for that request_id will be returned - - Example Request for all logs - ``` - curl -X GET "http://0.0.0.0:8000/spend/logs" \ --H "Authorization: Bearer sk-1234" - ``` - - Example Request for specific request_id - ``` - curl -X GET "http://0.0.0.0:8000/spend/logs?request_id=chatcmpl-6dcb2540-d3d7-4e49-bb27-291f863f112e" \ --H "Authorization: Bearer sk-1234" - ``` - - Example Request for specific api_key - ``` - curl -X GET "http://0.0.0.0:8000/spend/logs?api_key=sk-Fn8Ej39NkBQmUagFEoUWPQ" \ --H "Authorization: Bearer sk-1234" - ``` - - Example Request for specific user_id - ``` - curl -X GET "http://0.0.0.0:8000/spend/logs?user_id=ishaan@berri.ai" \ --H "Authorization: Bearer sk-1234" - ``` - """ - global prisma_client - try: - verbose_proxy_logger.debug("inside view_spend_logs") - if prisma_client is None: - raise Exception( - f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - ) - spend_logs = [] - if ( - start_date is not None - and isinstance(start_date, str) - and end_date is not None - and isinstance(end_date, str) - ): - # Convert the date strings to datetime objects - start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") - end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") - - filter_query = { - "startTime": { - "gte": start_date_obj, # Greater than or equal to Start Date - "lte": end_date_obj, # Less than or equal to End Date - } - } - - if api_key is not None and isinstance(api_key, str): - filter_query["api_key"] = api_key # type: ignore - elif request_id is not None and isinstance(request_id, str): - filter_query["request_id"] = request_id # type: ignore - elif user_id is not None and isinstance(user_id, str): - filter_query["user"] = user_id # type: ignore - - # SQL query - response = await prisma_client.db.litellm_spendlogs.group_by( - by=["api_key", "user", "model", "startTime"], - where=filter_query, # type: ignore - sum={ - "spend": True, - }, - ) - - if ( - isinstance(response, list) - and len(response) > 0 - and isinstance(response[0], dict) - ): - result: dict = {} - for record in response: - dt_object = datetime.strptime( - str(record["startTime"]), "%Y-%m-%dT%H:%M:%S.%fZ" - ) # type: ignore - date = dt_object.date() - if date not in result: - result[date] = {"users": {}, "models": {}} - api_key = record["api_key"] - user_id = record["user"] - model = record["model"] - result[date]["spend"] = ( - result[date].get("spend", 0) + record["_sum"]["spend"] - ) - result[date][api_key] = ( - result[date].get(api_key, 0) + record["_sum"]["spend"] - ) - result[date]["users"][user_id] = ( - result[date]["users"].get(user_id, 0) + record["_sum"]["spend"] - ) - result[date]["models"][model] = ( - result[date]["models"].get(model, 0) + record["_sum"]["spend"] - ) - return_list = [] - final_date = None - for k, v in sorted(result.items()): - return_list.append({**v, "startTime": k}) - final_date = k - - end_date_date = end_date_obj.date() - if final_date is not None and final_date < end_date_date: - current_date = final_date + timedelta(days=1) - while current_date <= end_date_date: - # Represent current_date as string because original response has it this way - return_list.append( - { - "startTime": current_date, - "spend": 0, - "users": {}, - "models": {}, - } - ) # If no data, will stay as zero - current_date += timedelta(days=1) # Move on to the next day - - return return_list - - return response - - elif api_key is not None and isinstance(api_key, str): - if api_key.startswith("sk-"): - hashed_token = prisma_client.hash_token(token=api_key) - else: - hashed_token = api_key - spend_log = await prisma_client.get_data( - table_name="spend", - query_type="find_all", - key_val={"key": "api_key", "value": hashed_token}, - ) - if isinstance(spend_log, list): - return spend_log - else: - return [spend_log] - elif request_id is not None: - spend_log = await prisma_client.get_data( - table_name="spend", - query_type="find_unique", - key_val={"key": "request_id", "value": request_id}, - ) - return [spend_log] - elif user_id is not None: - spend_log = await prisma_client.get_data( - table_name="spend", - query_type="find_all", - key_val={"key": "user", "value": user_id}, - ) - if isinstance(spend_log, list): - return spend_log - else: - return [spend_log] - else: - spend_logs = await prisma_client.get_data( - table_name="spend", query_type="find_all" - ) - - return spend_log - - return None - - except Exception as e: - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"/spend/logs Error({str(e)})"), - type="internal_error", - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_500_INTERNAL_SERVER_ERROR), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="/spend/logs Error" + str(e), - type="internal_error", - param=getattr(e, "param", "None"), - code=status.HTTP_500_INTERNAL_SERVER_ERROR, - ) - - -@router.post( - "/global/spend/reset", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], -) -async def global_spend_reset(): - """ - ADMIN ONLY / MASTER KEY Only Endpoint - - Globally reset spend for All API Keys and Teams, maintain LiteLLM_SpendLogs - - 1. LiteLLM_SpendLogs will maintain the logs on spend, no data gets deleted from there - 2. LiteLLM_VerificationTokens spend will be set = 0 - 3. LiteLLM_TeamTable spend will be set = 0 - - """ - global prisma_client - if prisma_client is None: - raise ProxyException( - message="Prisma Client is not initialized", - type="internal_error", - param="None", - code=status.HTTP_401_UNAUTHORIZED, - ) - - await prisma_client.db.litellm_verificationtoken.update_many( - data={"spend": 0.0}, where={} - ) - await prisma_client.db.litellm_teamtable.update_many(data={"spend": 0.0}, where={}) - - return { - "message": "Spend for all API Keys and Teams reset successfully", - "status": "success", - } - - -@router.get( - "/global/spend/logs", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], -) -async def global_spend_logs( - api_key: str = fastapi.Query( - default=None, - description="API Key to get global spend (spend per day for last 30d). Admin-only endpoint", - ) -): - """ - [BETA] This is a beta endpoint. It will change. - - Use this to get global spend (spend per day for last 30d). Admin-only endpoint - - More efficient implementation of /spend/logs, by creating a view over the spend logs table. - """ - global prisma_client - if prisma_client is None: - raise ProxyException( - message="Prisma Client is not initialized", - type="internal_error", - param="None", - code=status.HTTP_500_INTERNAL_SERVER_ERROR, - ) - if api_key is None: - sql_query = """SELECT * FROM "MonthlyGlobalSpend" ORDER BY "date";""" - - response = await prisma_client.db.query_raw(query=sql_query) - - return response - else: - sql_query = """ - SELECT * FROM "MonthlyGlobalSpendPerKey" - WHERE "api_key" = $1 - ORDER BY "date"; - """ - - response = await prisma_client.db.query_raw(sql_query, api_key) - - return response - return - - -@router.get( - "/global/spend", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], -) -async def global_spend(): - """ - [BETA] This is a beta endpoint. It will change. - - View total spend across all proxy keys - """ - global prisma_client - total_spend = 0.0 - total_proxy_budget = 0.0 - - if prisma_client is None: - raise HTTPException(status_code=500, detail={"error": "No db connected"}) - sql_query = """SELECT SUM(spend) as total_spend FROM "MonthlyGlobalSpend";""" - response = await prisma_client.db.query_raw(query=sql_query) - if response is not None: - if isinstance(response, list) and len(response) > 0: - total_spend = response[0].get("total_spend", 0.0) - - return {"spend": total_spend, "max_budget": litellm.max_budget} - - -@router.get( - "/global/spend/keys", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], -) -async def global_spend_keys( - limit: int = fastapi.Query( - default=None, - description="Number of keys to get. Will return Top 'n' keys.", - ) -): - """ - [BETA] This is a beta endpoint. It will change. - - Use this to get the top 'n' keys with the highest spend, ordered by spend. - """ - global prisma_client - - if prisma_client is None: - raise HTTPException(status_code=500, detail={"error": "No db connected"}) - sql_query = f"""SELECT * FROM "Last30dKeysBySpend" LIMIT {limit};""" - - response = await prisma_client.db.query_raw(query=sql_query) - - return response - - -@router.get( - "/global/spend/teams", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], -) -async def global_spend_per_team(): - """ - [BETA] This is a beta endpoint. It will change. - - Use this to get daily spend, grouped by `team_id` and `date` - """ - global prisma_client - - if prisma_client is None: - raise HTTPException(status_code=500, detail={"error": "No db connected"}) - sql_query = """ - SELECT - t.team_alias as team_alias, - DATE(s."startTime") AS spend_date, - SUM(s.spend) AS total_spend - FROM - "LiteLLM_SpendLogs" s - LEFT JOIN - "LiteLLM_TeamTable" t ON s.team_id = t.team_id - WHERE - s."startTime" >= CURRENT_DATE - INTERVAL '30 days' - GROUP BY - t.team_alias, - DATE(s."startTime") - ORDER BY - spend_date; - """ - response = await prisma_client.db.query_raw(query=sql_query) - - # transform the response for the Admin UI - spend_by_date = {} - team_aliases = set() - total_spend_per_team = {} - for row in response: - row_date = row["spend_date"] - if row_date is None: - continue - team_alias = row["team_alias"] - if team_alias is None: - team_alias = "Unassigned" - team_aliases.add(team_alias) - if row_date in spend_by_date: - # get the team_id for this entry - # get the spend for this entry - spend = row["total_spend"] - spend = round(spend, 2) - current_date_entries = spend_by_date[row_date] - current_date_entries[team_alias] = spend - else: - spend = row["total_spend"] - spend = round(spend, 2) - spend_by_date[row_date] = {team_alias: spend} - - if team_alias in total_spend_per_team: - total_spend_per_team[team_alias] += spend - else: - total_spend_per_team[team_alias] = spend - - total_spend_per_team_ui = [] - # order the elements in total_spend_per_team by spend - total_spend_per_team = dict( - sorted(total_spend_per_team.items(), key=lambda item: item[1], reverse=True) - ) - for team_id in total_spend_per_team: - # only add first 10 elements to total_spend_per_team_ui - if len(total_spend_per_team_ui) >= 10: - break - if team_id is None: - team_id = "Unassigned" - total_spend_per_team_ui.append( - {"team_id": team_id, "total_spend": total_spend_per_team[team_id]} - ) - - # sort spend_by_date by it's key (which is a date) - - response_data = [] - for key in spend_by_date: - value = spend_by_date[key] - response_data.append({"date": key, **value}) - - return { - "daily_spend": response_data, - "teams": list(team_aliases), - "total_spend_per_team": total_spend_per_team_ui, - } - - -@router.get( - "/global/all_end_users", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], - include_in_schema=False, -) -async def global_view_all_end_users(): - """ - [BETA] This is a beta endpoint. It will change. - - Use this to just get all the unique `end_users` - """ - global prisma_client - - if prisma_client is None: - raise HTTPException(status_code=500, detail={"error": "No db connected"}) - - sql_query = """ - SELECT DISTINCT end_user FROM "LiteLLM_SpendLogs" - """ - - db_response = await prisma_client.db.query_raw(query=sql_query) - if db_response is None: - return [] - - _end_users = [] - for row in db_response: - _end_users.append(row["end_user"]) - - return {"end_users": _end_users} - - -@router.post( - "/global/spend/end_users", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], -) -async def global_spend_end_users(data: Optional[GlobalEndUsersSpend] = None): - """ - [BETA] This is a beta endpoint. It will change. - - Use this to get the top 'n' keys with the highest spend, ordered by spend. - """ - global prisma_client - - if prisma_client is None: - raise HTTPException(status_code=500, detail={"error": "No db connected"}) - - """ - Gets the top 100 end-users for a given api key - """ - startTime = None - endTime = None - selected_api_key = None - if data is not None: - startTime = data.startTime - endTime = data.endTime - selected_api_key = data.api_key - - startTime = startTime or datetime.now() - timedelta(days=30) - endTime = endTime or datetime.now() - - sql_query = """ -SELECT end_user, COUNT(*) AS total_count, SUM(spend) AS total_spend -FROM "LiteLLM_SpendLogs" -WHERE "startTime" >= $1::timestamp - AND "startTime" < $2::timestamp - AND ( - CASE - WHEN $3::TEXT IS NULL THEN TRUE - ELSE api_key = $3 - END - ) -GROUP BY end_user -ORDER BY total_spend DESC -LIMIT 100 - """ - response = await prisma_client.db.query_raw( - sql_query, startTime, endTime, selected_api_key - ) - - return response - - -@router.get( - "/global/spend/models", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], -) -async def global_spend_models( - limit: int = fastapi.Query( - default=None, - description="Number of models to get. Will return Top 'n' models.", - ) -): - """ - [BETA] This is a beta endpoint. It will change. - - Use this to get the top 'n' keys with the highest spend, ordered by spend. - """ - global prisma_client - - if prisma_client is None: - raise HTTPException(status_code=500, detail={"error": "No db connected"}) - - sql_query = f"""SELECT * FROM "Last30dModelsBySpend" LIMIT {limit};""" - - response = await prisma_client.db.query_raw(query=sql_query) - - return response - - -@router.post( - "/global/predict/spend/logs", - tags=["Budget & Spend Tracking"], - dependencies=[Depends(user_api_key_auth)], -) -async def global_predict_spend_logs(request: Request): - from enterprise.utils import _forecast_daily_cost - - data = await request.json() - data = data.get("data") - return _forecast_daily_cost(data) - - #### INTERNAL USER MANAGEMENT #### @router.post( "/user/new", @@ -8884,6 +4904,8 @@ async def new_user(data: NewUserRequest): # Admin UI Logic # if team_id passed add this user to the team if data_json.get("team_id", None) is not None: + from litellm.proxy.management_endpoints.team_endpoints import team_member_add + await team_member_add( data=TeamMemberAddRequest( team_id=data_json.get("team_id", None), @@ -8894,7 +4916,7 @@ async def new_user(data: NewUserRequest): ), ), http_request=Request( - scope={"type": "http"}, + scope={"type": "http", "path": "/user/new"}, ), ) @@ -9919,217 +5941,6 @@ async def delete_end_user( pass -#### TEAM MANAGEMENT #### - - -@router.post( - "/team/new", - tags=["team management"], - dependencies=[Depends(user_api_key_auth)], - response_model=LiteLLM_TeamTable, -) -@management_endpoint_wrapper -async def new_team( - data: NewTeamRequest, - http_request: Request, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), - litellm_changed_by: Optional[str] = Header( - None, - description="The litellm-changed-by header enables tracking of actions performed by authorized users on behalf of other users, providing an audit trail for accountability", - ), -): - """ - Allow users to create a new team. Apply user permissions to their team. - - [ASK FOR HELP](https://github.com/BerriAI/litellm/issues) - - Parameters: - - team_alias: Optional[str] - User defined team alias - - team_id: Optional[str] - The team id of the user. If none passed, we'll generate it. - - members_with_roles: List[{"role": "admin" or "user", "user_id": ""}] - A list of users and their roles in the team. Get user_id when making a new user via `/user/new`. - - metadata: Optional[dict] - Metadata for team, store information for team. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" } - - tpm_limit: Optional[int] - The TPM (Tokens Per Minute) limit for this team - all keys with this team_id will have at max this TPM limit - - rpm_limit: Optional[int] - The RPM (Requests Per Minute) limit for this team - all keys associated with this team_id will have at max this RPM limit - - max_budget: Optional[float] - The maximum budget allocated to the team - all keys for this team_id will have at max this max_budget - - models: Optional[list] - A list of models associated with the team - all keys for this team_id will have at most, these models. If empty, assumes all models are allowed. - - blocked: bool - Flag indicating if the team is blocked or not - will stop all calls from keys with this team_id. - - Returns: - - team_id: (str) Unique team id - used for tracking spend across multiple keys for same team id. - - _deprecated_params: - - admins: list - A list of user_id's for the admin role - - users: list - A list of user_id's for the user role - - Example Request: - ``` - curl --location 'http://0.0.0.0:4000/team/new' \ - - --header 'Authorization: Bearer sk-1234' \ - - --header 'Content-Type: application/json' \ - - --data '{ - "team_alias": "my-new-team_2", - "members_with_roles": [{"role": "admin", "user_id": "user-1234"}, - {"role": "user", "user_id": "user-2434"}] - }' - - ``` - """ - global prisma_client - - if prisma_client is None: - raise HTTPException(status_code=500, detail={"error": "No db connected"}) - - if data.team_id is None: - data.team_id = str(uuid.uuid4()) - else: - # Check if team_id exists already - _existing_team_id = await prisma_client.get_data( - team_id=data.team_id, table_name="team", query_type="find_unique" - ) - if _existing_team_id is not None: - raise HTTPException( - status_code=400, - detail={ - "error": f"Team id = {data.team_id} already exists. Please use a different team id." - }, - ) - - if ( - user_api_key_dict.user_role is None - or user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN - ): # don't restrict proxy admin - if ( - data.tpm_limit is not None - and user_api_key_dict.tpm_limit is not None - and data.tpm_limit > user_api_key_dict.tpm_limit - ): - raise HTTPException( - status_code=400, - detail={ - "error": f"tpm limit higher than user max. User tpm limit={user_api_key_dict.tpm_limit}. User role={user_api_key_dict.user_role}" - }, - ) - - if ( - data.rpm_limit is not None - and user_api_key_dict.rpm_limit is not None - and data.rpm_limit > user_api_key_dict.rpm_limit - ): - raise HTTPException( - status_code=400, - detail={ - "error": f"rpm limit higher than user max. User rpm limit={user_api_key_dict.rpm_limit}. User role={user_api_key_dict.user_role}" - }, - ) - - if ( - data.max_budget is not None - and user_api_key_dict.max_budget is not None - and data.max_budget > user_api_key_dict.max_budget - ): - raise HTTPException( - status_code=400, - detail={ - "error": f"max budget higher than user max. User max budget={user_api_key_dict.max_budget}. User role={user_api_key_dict.user_role}" - }, - ) - - if data.models is not None and len(user_api_key_dict.models) > 0: - for m in data.models: - if m not in user_api_key_dict.models: - raise HTTPException( - status_code=400, - detail={ - "error": f"Model not in allowed user models. User allowed models={user_api_key_dict.models}. User id={user_api_key_dict.user_id}" - }, - ) - - if user_api_key_dict.user_id is not None: - creating_user_in_list = False - for member in data.members_with_roles: - if member.user_id == user_api_key_dict.user_id: - creating_user_in_list = True - - if creating_user_in_list == False: - data.members_with_roles.append( - Member(role="admin", user_id=user_api_key_dict.user_id) - ) - - ## ADD TO MODEL TABLE - _model_id = None - if data.model_aliases is not None and isinstance(data.model_aliases, dict): - litellm_modeltable = LiteLLM_ModelTable( - model_aliases=json.dumps(data.model_aliases), - created_by=user_api_key_dict.user_id or litellm_proxy_admin_name, - updated_by=user_api_key_dict.user_id or litellm_proxy_admin_name, - ) - model_dict = await prisma_client.db.litellm_modeltable.create( - {**litellm_modeltable.json(exclude_none=True)} # type: ignore - ) # type: ignore - - _model_id = model_dict.id - - ## ADD TO TEAM TABLE - complete_team_data = LiteLLM_TeamTable( - **data.json(), - model_id=_model_id, - ) - - # If budget_duration is set, set `budget_reset_at` - if complete_team_data.budget_duration is not None: - duration_s = _duration_in_seconds(duration=complete_team_data.budget_duration) - reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) - complete_team_data.budget_reset_at = reset_at - - team_row = await prisma_client.insert_data( - data=complete_team_data.json(exclude_none=True), table_name="team" - ) - - ## ADD TEAM ID TO USER TABLE ## - for user in complete_team_data.members_with_roles: - ## add team id to user row ## - await prisma_client.update_data( - user_id=user.user_id, - data={"user_id": user.user_id, "teams": [team_row.team_id]}, - update_key_values_custom_query={ - "teams": { - "push ": [team_row.team_id], - } - }, - ) - - # Enterprise Feature - Audit Logging. Enable with litellm.store_audit_logs = True - if litellm.store_audit_logs is True: - _updated_values = complete_team_data.json(exclude_none=True) - _updated_values = json.dumps(_updated_values) - - asyncio.create_task( - create_audit_log_for_update( - request_data=LiteLLM_AuditLogs( - id=str(uuid.uuid4()), - updated_at=datetime.now(timezone.utc), - changed_by=litellm_changed_by - or user_api_key_dict.user_id - or litellm_proxy_admin_name, - changed_by_api_key=user_api_key_dict.api_key, - table_name=LitellmTableNames.TEAM_TABLE_NAME, - object_id=data.team_id, - action="created", - updated_values=_updated_values, - before_value=None, - ) - ) - ) - - try: - return team_row.model_dump() - except Exception as e: - return team_row.dict() - - async def create_audit_log_for_update(request_data: LiteLLM_AuditLogs): if premium_user is not True: return @@ -10162,577 +5973,6 @@ async def create_audit_log_for_update(request_data: LiteLLM_AuditLogs): return -@router.post( - "/team/update", tags=["team management"], dependencies=[Depends(user_api_key_auth)] -) -@management_endpoint_wrapper -async def update_team( - data: UpdateTeamRequest, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), - litellm_changed_by: Optional[str] = Header( - None, - description="The litellm-changed-by header enables tracking of actions performed by authorized users on behalf of other users, providing an audit trail for accountability", - ), -): - """ - Use `/team/member_add` AND `/team/member/delete` to add/remove new team members - - You can now update team budget / rate limits via /team/update - - Parameters: - - team_id: str - The team id of the user. Required param. - - team_alias: Optional[str] - User defined team alias - - metadata: Optional[dict] - Metadata for team, store information for team. Example metadata = {"team": "core-infra", "app": "app2", "email": "ishaan@berri.ai" } - - tpm_limit: Optional[int] - The TPM (Tokens Per Minute) limit for this team - all keys with this team_id will have at max this TPM limit - - rpm_limit: Optional[int] - The RPM (Requests Per Minute) limit for this team - all keys associated with this team_id will have at max this RPM limit - - max_budget: Optional[float] - The maximum budget allocated to the team - all keys for this team_id will have at max this max_budget - - models: Optional[list] - A list of models associated with the team - all keys for this team_id will have at most, these models. If empty, assumes all models are allowed. - - blocked: bool - Flag indicating if the team is blocked or not - will stop all calls from keys with this team_id. - - Example - update team TPM Limit - - ``` - curl --location 'http://0.0.0.0:8000/team/update' \ - - --header 'Authorization: Bearer sk-1234' \ - - --header 'Content-Type: application/json' \ - - --data-raw '{ - "team_id": "litellm-test-client-id-new", - "tpm_limit": 100 - }' - ``` - """ - global prisma_client - - if prisma_client is None: - raise HTTPException(status_code=500, detail={"error": "No db connected"}) - - if data.team_id is None: - raise HTTPException(status_code=400, detail={"error": "No team id passed in"}) - verbose_proxy_logger.debug("/team/update - %s", data) - - existing_team_row = await prisma_client.get_data( - team_id=data.team_id, table_name="team", query_type="find_unique" - ) - if existing_team_row is None: - raise HTTPException( - status_code=404, - detail={"error": f"Team not found, passed team_id={data.team_id}"}, - ) - - updated_kv = data.json(exclude_none=True) - - # Check budget_duration and budget_reset_at - if data.budget_duration is not None: - duration_s = _duration_in_seconds(duration=data.budget_duration) - reset_at = datetime.now(timezone.utc) + timedelta(seconds=duration_s) - - # set the budget_reset_at in DB - updated_kv["budget_reset_at"] = reset_at - - team_row = await prisma_client.update_data( - update_key_values=updated_kv, - data=updated_kv, - table_name="team", - team_id=data.team_id, - ) - - # Enterprise Feature - Audit Logging. Enable with litellm.store_audit_logs = True - if litellm.store_audit_logs is True: - _before_value = existing_team_row.json(exclude_none=True) - _before_value = json.dumps(_before_value) - _after_value: str = json.dumps(updated_kv) - - asyncio.create_task( - create_audit_log_for_update( - request_data=LiteLLM_AuditLogs( - id=str(uuid.uuid4()), - updated_at=datetime.now(timezone.utc), - changed_by=litellm_changed_by - or user_api_key_dict.user_id - or litellm_proxy_admin_name, - changed_by_api_key=user_api_key_dict.api_key, - table_name=LitellmTableNames.TEAM_TABLE_NAME, - object_id=data.team_id, - action="updated", - updated_values=_after_value, - before_value=_before_value, - ) - ) - ) - - return team_row - - -@router.post( - "/team/member_add", - tags=["team management"], - dependencies=[Depends(user_api_key_auth)], -) -@management_endpoint_wrapper -async def team_member_add( - data: TeamMemberAddRequest, - http_request: Request, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), -): - """ - [BETA] - - Add new members (either via user_email or user_id) to a team - - If user doesn't exist, new user row will also be added to User Table - - ``` - - curl -X POST 'http://0.0.0.0:4000/team/member_add' \ - -H 'Authorization: Bearer sk-1234' \ - -H 'Content-Type: application/json' \ - -d '{"team_id": "45e3e396-ee08-4a61-a88e-16b3ce7e0849", "member": {"role": "user", "user_id": "krrish247652@berri.ai"}}' - - ``` - """ - if prisma_client is None: - raise HTTPException(status_code=500, detail={"error": "No db connected"}) - - if data.team_id is None: - raise HTTPException(status_code=400, detail={"error": "No team id passed in"}) - - if data.member is None: - raise HTTPException( - status_code=400, detail={"error": "No member/members passed in"} - ) - - existing_team_row = await prisma_client.db.litellm_teamtable.find_unique( - where={"team_id": data.team_id} - ) - if existing_team_row is None: - raise HTTPException( - status_code=404, - detail={ - "error": f"Team not found for team_id={getattr(data, 'team_id', None)}" - }, - ) - - complete_team_data = LiteLLM_TeamTable(**existing_team_row.model_dump()) - - if isinstance(data.member, Member): - # add to team db - new_member = data.member - - complete_team_data.members_with_roles.append(new_member) - - elif isinstance(data.member, List): - # add to team db - new_members = data.member - - complete_team_data.members_with_roles.extend(new_members) - - # ADD MEMBER TO TEAM - _db_team_members = [m.model_dump() for m in complete_team_data.members_with_roles] - updated_team = await prisma_client.db.litellm_teamtable.update( - where={"team_id": data.team_id}, - data={"members_with_roles": json.dumps(_db_team_members)}, # type: ignore - ) - - if isinstance(data.member, Member): - await add_new_member( - new_member=data.member, - max_budget_in_team=data.max_budget_in_team, - prisma_client=prisma_client, - user_api_key_dict=user_api_key_dict, - litellm_proxy_admin_name=litellm_proxy_admin_name, - team_id=data.team_id, - ) - elif isinstance(data.member, List): - tasks: List = [] - for m in data.member: - await add_new_member( - new_member=m, - max_budget_in_team=data.max_budget_in_team, - prisma_client=prisma_client, - user_api_key_dict=user_api_key_dict, - litellm_proxy_admin_name=litellm_proxy_admin_name, - team_id=data.team_id, - ) - await asyncio.gather(*tasks) - - return updated_team - - -@router.post( - "/team/member_delete", - tags=["team management"], - dependencies=[Depends(user_api_key_auth)], -) -@management_endpoint_wrapper -async def team_member_delete( - data: TeamMemberDeleteRequest, - http_request: Request, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), -): - """ - [BETA] - - delete members (either via user_email or user_id) from a team - - If user doesn't exist, an exception will be raised - ``` - curl -X POST 'http://0.0.0.0:8000/team/update' \ - - -H 'Authorization: Bearer sk-1234' \ - - -H 'Content-Type: application/json' \ - - -D '{ - "team_id": "45e3e396-ee08-4a61-a88e-16b3ce7e0849", - "user_id": "krrish247652@berri.ai" - }' - ``` - """ - if prisma_client is None: - raise HTTPException(status_code=500, detail={"error": "No db connected"}) - - if data.team_id is None: - raise HTTPException(status_code=400, detail={"error": "No team id passed in"}) - - if data.user_id is None and data.user_email is None: - raise HTTPException( - status_code=400, - detail={"error": "Either user_id or user_email needs to be passed in"}, - ) - - _existing_team_row = await prisma_client.db.litellm_teamtable.find_unique( - where={"team_id": data.team_id} - ) - - if _existing_team_row is None: - raise HTTPException( - status_code=400, - detail={"error": "Team id={} does not exist in db".format(data.team_id)}, - ) - existing_team_row = LiteLLM_TeamTable(**_existing_team_row.model_dump()) - - ## DELETE MEMBER FROM TEAM - new_team_members: List[Member] = [] - for m in existing_team_row.members_with_roles: - if ( - data.user_id is not None - and m.user_id is not None - and data.user_id == m.user_id - ): - continue - elif ( - data.user_email is not None - and m.user_email is not None - and data.user_email == m.user_email - ): - continue - new_team_members.append(m) - existing_team_row.members_with_roles = new_team_members - - _db_new_team_members: List[dict] = [m.model_dump() for m in new_team_members] - - _ = await prisma_client.db.litellm_teamtable.update( - where={ - "team_id": data.team_id, - }, - data={"members_with_roles": json.dumps(_db_new_team_members)}, # type: ignore - ) - - ## DELETE TEAM ID from USER ROW, IF EXISTS ## - # get user row - key_val = {} - if data.user_id is not None: - key_val["user_id"] = data.user_id - elif data.user_email is not None: - key_val["user_email"] = data.user_email - existing_user_rows = await prisma_client.db.litellm_usertable.find_many( - where=key_val # type: ignore - ) - - if existing_user_rows is not None and ( - isinstance(existing_user_rows, list) and len(existing_user_rows) > 0 - ): - for existing_user in existing_user_rows: - team_list = [] - if data.team_id in existing_user.teams: - team_list = existing_user.teams - team_list.remove(data.team_id) - await prisma_client.db.litellm_usertable.update( - where={ - "user_id": existing_user.user_id, - }, - data={"teams": {"set": team_list}}, - ) - - return existing_team_row - - -@router.post( - "/team/delete", tags=["team management"], dependencies=[Depends(user_api_key_auth)] -) -@management_endpoint_wrapper -async def delete_team( - data: DeleteTeamRequest, - http_request: Request, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), - litellm_changed_by: Optional[str] = Header( - None, - description="The litellm-changed-by header enables tracking of actions performed by authorized users on behalf of other users, providing an audit trail for accountability", - ), -): - """ - delete team and associated team keys - - ``` - curl --location 'http://0.0.0.0:8000/team/delete' \ - - --header 'Authorization: Bearer sk-1234' \ - - --header 'Content-Type: application/json' \ - - --data-raw '{ - "team_ids": ["45e3e396-ee08-4a61-a88e-16b3ce7e0849"] - }' - ``` - """ - global prisma_client - - if prisma_client is None: - raise HTTPException(status_code=500, detail={"error": "No db connected"}) - - if data.team_ids is None: - raise HTTPException(status_code=400, detail={"error": "No team id passed in"}) - - # check that all teams passed exist - for team_id in data.team_ids: - team_row = await prisma_client.get_data( # type: ignore - team_id=team_id, table_name="team", query_type="find_unique" - ) - if team_row is None: - raise HTTPException( - status_code=404, - detail={"error": f"Team not found, passed team_id={team_id}"}, - ) - - # Enterprise Feature - Audit Logging. Enable with litellm.store_audit_logs = True - # we do this after the first for loop, since first for loop is for validation. we only want this inserted after validation passes - if litellm.store_audit_logs is True: - # make an audit log for each team deleted - for team_id in data.team_ids: - team_row = await prisma_client.get_data( # type: ignore - team_id=team_id, table_name="team", query_type="find_unique" - ) - - _team_row = team_row.json(exclude_none=True) - - asyncio.create_task( - create_audit_log_for_update( - request_data=LiteLLM_AuditLogs( - id=str(uuid.uuid4()), - updated_at=datetime.now(timezone.utc), - changed_by=litellm_changed_by - or user_api_key_dict.user_id - or litellm_proxy_admin_name, - changed_by_api_key=user_api_key_dict.api_key, - table_name=LitellmTableNames.TEAM_TABLE_NAME, - object_id=team_id, - action="deleted", - updated_values="{}", - before_value=_team_row, - ) - ) - ) - - # End of Audit logging - - ## DELETE ASSOCIATED KEYS - await prisma_client.delete_data(team_id_list=data.team_ids, table_name="key") - ## DELETE TEAMS - deleted_teams = await prisma_client.delete_data( - team_id_list=data.team_ids, table_name="team" - ) - return deleted_teams - - -@router.get( - "/team/info", tags=["team management"], dependencies=[Depends(user_api_key_auth)] -) -@management_endpoint_wrapper -async def team_info( - http_request: Request, - team_id: str = fastapi.Query( - default=None, description="Team ID in the request parameters" - ), -): - """ - get info on team + related keys - - ``` - curl --location 'http://localhost:4000/team/info' \ - --header 'Authorization: Bearer sk-1234' \ - --header 'Content-Type: application/json' \ - --data '{ - "teams": ["",..] - }' - ``` - """ - global prisma_client - try: - if prisma_client is None: - raise HTTPException( - status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, - detail={ - "error": f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" - }, - ) - if team_id is None: - raise HTTPException( - status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, - detail={"message": "Malformed request. No team id passed in."}, - ) - - team_info = await prisma_client.get_data( - team_id=team_id, table_name="team", query_type="find_unique" - ) - if team_info is None: - raise HTTPException( - status_code=status.HTTP_404_NOT_FOUND, - detail={"message": f"Team not found, passed team id: {team_id}."}, - ) - - ## GET ALL KEYS ## - keys = await prisma_client.get_data( - team_id=team_id, - table_name="key", - query_type="find_all", - expires=datetime.now(), - ) - - if team_info is None: - ## make sure we still return a total spend ## - spend = 0 - for k in keys: - spend += getattr(k, "spend", 0) - team_info = {"spend": spend} - - ## REMOVE HASHED TOKEN INFO before returning ## - for key in keys: - try: - key = key.model_dump() # noqa - except: - # if using pydantic v1 - key = key.dict() - key.pop("token", None) - return {"team_id": team_id, "team_info": team_info, "keys": keys} - - except Exception as e: - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({str(e)})"), - type="auth_error", - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type="auth_error", - param=getattr(e, "param", "None"), - code=status.HTTP_400_BAD_REQUEST, - ) - - -@router.post( - "/team/block", tags=["team management"], dependencies=[Depends(user_api_key_auth)] -) -@management_endpoint_wrapper -async def block_team( - data: BlockTeamRequest, - http_request: Request, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), -): - """ - Blocks all calls from keys with this team id. - """ - global prisma_client - - if prisma_client is None: - raise Exception("No DB Connected.") - - record = await prisma_client.db.litellm_teamtable.update( - where={"team_id": data.team_id}, data={"blocked": True} # type: ignore - ) - - return record - - -@router.post( - "/team/unblock", tags=["team management"], dependencies=[Depends(user_api_key_auth)] -) -@management_endpoint_wrapper -async def unblock_team( - data: BlockTeamRequest, - http_request: Request, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), -): - """ - Blocks all calls from keys with this team id. - """ - global prisma_client - - if prisma_client is None: - raise Exception("No DB Connected.") - - record = await prisma_client.db.litellm_teamtable.update( - where={"team_id": data.team_id}, data={"blocked": False} # type: ignore - ) - - return record - - -@router.get( - "/team/list", tags=["team management"], dependencies=[Depends(user_api_key_auth)] -) -@management_endpoint_wrapper -async def list_team( - http_request: Request, - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), -): - """ - [Admin-only] List all available teams - - ``` - curl --location --request GET 'http://0.0.0.0:4000/team/list' \ - --header 'Authorization: Bearer sk-1234' - ``` - """ - global prisma_client - - if user_api_key_dict.user_role != LitellmUserRoles.PROXY_ADMIN: - raise HTTPException( - status_code=401, - detail={ - "error": "Admin-only endpoint. Your user role={}".format( - user_api_key_dict.user_role - ) - }, - ) - - if prisma_client is None: - raise HTTPException( - status_code=400, - detail={"error": CommonProxyErrors.db_not_connected_error.value}, - ) - - response = await prisma_client.db.litellm_teamtable.find_many() - - return response - - #### ORGANIZATION MANAGEMENT #### @@ -11402,7 +6642,7 @@ async def model_info_v2( for _model in all_models: # provided model_info in config.yaml model_info = _model.get("model_info", {}) - if debug == True: + if debug is True: _openai_client = "None" if llm_router is not None: _openai_client = ( @@ -11427,7 +6667,7 @@ async def model_info_v2( litellm_model = litellm_params.get("model", None) try: litellm_model_info = litellm.get_model_info(model=litellm_model) - except: + except Exception: litellm_model_info = {} # 3rd pass on the model, try seeing if we can find model but without the "/" in model cost map if litellm_model_info == {}: @@ -11438,8 +6678,10 @@ async def model_info_v2( if len(split_model) > 0: litellm_model = split_model[-1] try: - litellm_model_info = litellm.get_model_info(model=litellm_model) - except: + litellm_model_info = litellm.get_model_info( + model=litellm_model, custom_llm_provider=split_model[0] + ) + except Exception: litellm_model_info = {} for k, v in litellm_model_info.items(): if k not in model_info: @@ -11950,7 +7192,9 @@ async def model_info_v1( if len(split_model) > 0: litellm_model = split_model[-1] try: - litellm_model_info = litellm.get_model_info(model=litellm_model) + litellm_model_info = litellm.get_model_info( + model=litellm_model, custom_llm_provider=split_model[0] + ) except: litellm_model_info = {} for k, v in litellm_model_info.items(): @@ -12217,6 +7461,7 @@ async def alerting_settings( "/queue/chat/completions", tags=["experimental"], dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, ) async def async_queue_request( request: Request, @@ -12328,18 +7573,10 @@ async def async_queue_request( ) -@router.get( - "/ollama_logs", dependencies=[Depends(user_api_key_auth)], tags=["experimental"] -) -async def retrieve_server_log(request: Request): - filepath = os.path.expanduser("~/.ollama/logs/server.log") - return FileResponse(filepath) - - #### LOGIN ENDPOINTS #### -@app.get("/sso/key/generate", tags=["experimental"]) +@app.get("/sso/key/generate", tags=["experimental"], include_in_schema=False) async def google_login(request: Request): """ Create Proxy API Keys using Google Workspace SSO. Requires setting PROXY_BASE_URL in .env @@ -12575,7 +7812,8 @@ async def login(request: Request): if secrets.compare_digest(username, ui_username) and secrets.compare_digest( password, ui_password ): - user_role = "app_owner" + # Non SSO -> If user is using UI_USERNAME and UI_PASSWORD they are Proxy admin + user_role = LitellmUserRoles.PROXY_ADMIN user_id = username key_user_id = user_id if ( @@ -12583,7 +7821,6 @@ async def login(request: Request): and os.environ["PROXY_ADMIN_ID"] == user_id ) or user_id == "admin": # checks if user is admin - user_role = "app_admin" key_user_id = os.getenv("PROXY_ADMIN_ID", "default_user_id") # Admin is Authe'd in - generate key for the UI to access Proxy @@ -12592,7 +7829,7 @@ async def login(request: Request): await user_update( data=UpdateUserRequest( user_id=key_user_id, - user_role=LitellmUserRoles.PROXY_ADMIN, + user_role=user_role, ) ) if os.getenv("DATABASE_URL") is not None: @@ -12620,7 +7857,7 @@ async def login(request: Request): "user_id": user_id, "key": key, "user_email": user_id, - "user_role": "app_admin", # this is the path without sso - we can assume only admins will use this + "user_role": user_role, # this is the path without sso - we can assume only admins will use this "login_method": "username_password", "premium_user": premium_user, }, @@ -12630,8 +7867,15 @@ async def login(request: Request): litellm_dashboard_ui += "?userID=" + user_id + "&token=" + jwt_token return RedirectResponse(url=litellm_dashboard_ui, status_code=303) elif _user_row is not None: + """ + When sharing invite links + + -> if the user has no role in the DB assume they are only a viewer + """ user_id = getattr(_user_row, "user_id", "unknown") - user_role = getattr(_user_row, "user_role", "unknown") + user_role = getattr( + _user_row, "user_role", LitellmUserRoles.INTERNAL_USER_VIEW_ONLY + ) user_email = getattr(_user_row, "user_email", "unknown") _password = getattr(_user_row, "password", "unknown") @@ -12933,7 +8177,7 @@ def get_image(): return FileResponse(logo_path, media_type="image/jpeg") -@app.get("/sso/callback", tags=["experimental"]) +@app.get("/sso/callback", tags=["experimental"], include_in_schema=False) async def auth_callback(request: Request): """Verify login""" global general_settings, ui_access_mode, premium_user @@ -13238,6 +8482,7 @@ async def auth_callback(request: Request): tags=["Invite Links"], dependencies=[Depends(user_api_key_auth)], response_model=InvitationModel, + include_in_schema=False, ) async def new_invitation( data: InvitationNew, user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth) @@ -13302,6 +8547,7 @@ async def new_invitation( tags=["Invite Links"], dependencies=[Depends(user_api_key_auth)], response_model=InvitationModel, + include_in_schema=False, ) async def invitation_info( invitation_id: str, user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth) @@ -13353,6 +8599,7 @@ async def invitation_info( tags=["Invite Links"], dependencies=[Depends(user_api_key_auth)], response_model=InvitationModel, + include_in_schema=False, ) async def invitation_update( data: InvitationUpdate, @@ -13413,6 +8660,7 @@ async def invitation_update( tags=["Invite Links"], dependencies=[Depends(user_api_key_auth)], response_model=InvitationModel, + include_in_schema=False, ) async def invitation_delete( data: InvitationDelete, @@ -13465,6 +8713,7 @@ async def invitation_delete( "/config/update", tags=["config.yaml"], dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, ) async def update_config(config_info: ConfigYAML): """ @@ -13622,6 +8871,7 @@ Keep it more precise, to prevent overwrite other values unintentially "/config/field/update", tags=["config.yaml"], dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, ) async def update_config_general_settings( data: ConfigFieldUpdate, @@ -13700,6 +8950,7 @@ async def update_config_general_settings( tags=["config.yaml"], dependencies=[Depends(user_api_key_auth)], response_model=ConfigFieldInfo, + include_in_schema=False, ) async def get_config_general_settings( field_name: str, @@ -13760,6 +9011,7 @@ async def get_config_general_settings( "/config/list", tags=["config.yaml"], dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, ) async def get_config_list( config_type: Literal["general_settings"], @@ -13836,6 +9088,7 @@ async def get_config_list( "/config/field/delete", tags=["config.yaml"], dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, ) async def delete_config_general_settings( data: ConfigFieldDelete, @@ -14091,6 +9344,7 @@ async def get_config(): "/config/yaml", tags=["config.yaml"], dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, ) async def config_yaml_endpoint(config_info: ConfigYAML): """ @@ -14112,631 +9366,6 @@ async def config_yaml_endpoint(config_info: ConfigYAML): return {"hello": "world"} -#### BASIC ENDPOINTS #### -@router.get( - "/test", - tags=["health"], - dependencies=[Depends(user_api_key_auth)], -) -async def test_endpoint(request: Request): - """ - [DEPRECATED] use `/health/liveliness` instead. - - A test endpoint that pings the proxy server to check if it's healthy. - - Parameters: - request (Request): The incoming request. - - Returns: - dict: A dictionary containing the route of the request URL. - """ - # ping the proxy server to check if its healthy - return {"route": request.url.path} - - -@router.get( - "/health/services", - tags=["health"], - dependencies=[Depends(user_api_key_auth)], - include_in_schema=False, -) -async def health_services_endpoint( - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), - service: Literal[ - "slack_budget_alerts", "langfuse", "slack", "openmeter", "webhook", "email" - ] = fastapi.Query(description="Specify the service being hit."), -): - """ - Hidden endpoint. - - Used by the UI to let user check if slack alerting is working as expected. - """ - try: - global general_settings, proxy_logging_obj - - if service is None: - raise HTTPException( - status_code=400, detail={"error": "Service must be specified."} - ) - if service not in [ - "slack_budget_alerts", - "email", - "langfuse", - "slack", - "openmeter", - "webhook", - ]: - raise HTTPException( - status_code=400, - detail={ - "error": f"Service must be in list. Service={service}. List={['slack_budget_alerts']}" - }, - ) - - if service == "openmeter": - _ = await litellm.acompletion( - model="openai/litellm-mock-response-model", - messages=[{"role": "user", "content": "Hey, how's it going?"}], - user="litellm:/health/services", - mock_response="This is a mock response", - ) - return { - "status": "success", - "message": "Mock LLM request made - check openmeter.", - } - - if service == "langfuse": - from litellm.integrations.langfuse import LangFuseLogger - - langfuse_logger = LangFuseLogger() - langfuse_logger.Langfuse.auth_check() - _ = litellm.completion( - model="openai/litellm-mock-response-model", - messages=[{"role": "user", "content": "Hey, how's it going?"}], - user="litellm:/health/services", - mock_response="This is a mock response", - ) - return { - "status": "success", - "message": "Mock LLM request made - check langfuse.", - } - - if service == "webhook": - user_info = CallInfo( - token=user_api_key_dict.token or "", - spend=1, - max_budget=0, - user_id=user_api_key_dict.user_id, - key_alias=user_api_key_dict.key_alias, - team_id=user_api_key_dict.team_id, - ) - await proxy_logging_obj.budget_alerts( - type="user_budget", - user_info=user_info, - ) - - if service == "slack" or service == "slack_budget_alerts": - if "slack" in general_settings.get("alerting", []): - # test_message = f"""\n🚨 `ProjectedLimitExceededError` 💸\n\n`Key Alias:` litellm-ui-test-alert \n`Expected Day of Error`: 28th March \n`Current Spend`: $100.00 \n`Projected Spend at end of month`: $1000.00 \n`Soft Limit`: $700""" - # check if user has opted into unique_alert_webhooks - if ( - proxy_logging_obj.slack_alerting_instance.alert_to_webhook_url - is not None - ): - for ( - alert_type - ) in proxy_logging_obj.slack_alerting_instance.alert_to_webhook_url: - """ - "llm_exceptions", - "llm_too_slow", - "llm_requests_hanging", - "budget_alerts", - "db_exceptions", - """ - # only test alert if it's in active alert types - if ( - proxy_logging_obj.slack_alerting_instance.alert_types - is not None - and alert_type - not in proxy_logging_obj.slack_alerting_instance.alert_types - ): - continue - test_message = "default test message" - if alert_type == "llm_exceptions": - test_message = f"LLM Exception test alert" - elif alert_type == "llm_too_slow": - test_message = f"LLM Too Slow test alert" - elif alert_type == "llm_requests_hanging": - test_message = f"LLM Requests Hanging test alert" - elif alert_type == "budget_alerts": - test_message = f"Budget Alert test alert" - elif alert_type == "db_exceptions": - test_message = f"DB Exception test alert" - elif alert_type == "outage_alerts": - test_message = f"Outage Alert Exception test alert" - elif alert_type == "daily_reports": - test_message = f"Daily Reports test alert" - - await proxy_logging_obj.alerting_handler( - message=test_message, level="Low", alert_type=alert_type - ) - else: - await proxy_logging_obj.alerting_handler( - message="This is a test slack alert message", - level="Low", - alert_type="budget_alerts", - ) - - if prisma_client is not None: - asyncio.create_task( - proxy_logging_obj.slack_alerting_instance.send_monthly_spend_report() - ) - asyncio.create_task( - proxy_logging_obj.slack_alerting_instance.send_weekly_spend_report() - ) - - alert_types = ( - proxy_logging_obj.slack_alerting_instance.alert_types or [] - ) - alert_types = list(alert_types) - return { - "status": "success", - "alert_types": alert_types, - "message": "Mock Slack Alert sent, verify Slack Alert Received on your channel", - } - else: - raise HTTPException( - status_code=422, - detail={ - "error": '"{}" not in proxy config: general_settings. Unable to test this.'.format( - service - ) - }, - ) - if service == "email": - webhook_event = WebhookEvent( - event="key_created", - event_group="key", - event_message="Test Email Alert", - token=user_api_key_dict.token or "", - key_alias="Email Test key (This is only a test alert key. DO NOT USE THIS IN PRODUCTION.)", - spend=0, - max_budget=0, - user_id=user_api_key_dict.user_id, - user_email=os.getenv("TEST_EMAIL_ADDRESS"), - team_id=user_api_key_dict.team_id, - ) - - # use create task - this can take 10 seconds. don't keep ui users waiting for notification to check their email - asyncio.create_task( - proxy_logging_obj.slack_alerting_instance.send_key_created_or_user_invited_email( - webhook_event=webhook_event - ) - ) - - return { - "status": "success", - "message": "Mock Email Alert sent, verify Email Alert Received", - } - - except Exception as e: - verbose_proxy_logger.error( - "litellm.proxy.proxy_server.health_services_endpoint(): Exception occured - {}".format( - str(e) - ) - ) - verbose_proxy_logger.debug(traceback.format_exc()) - if isinstance(e, HTTPException): - raise ProxyException( - message=getattr(e, "detail", f"Authentication Error({str(e)})"), - type="auth_error", - param=getattr(e, "param", "None"), - code=getattr(e, "status_code", status.HTTP_500_INTERNAL_SERVER_ERROR), - ) - elif isinstance(e, ProxyException): - raise e - raise ProxyException( - message="Authentication Error, " + str(e), - type="auth_error", - param=getattr(e, "param", "None"), - code=status.HTTP_500_INTERNAL_SERVER_ERROR, - ) - - -@router.get("/health", tags=["health"], dependencies=[Depends(user_api_key_auth)]) -async def health_endpoint( - user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth), - model: Optional[str] = fastapi.Query( - None, description="Specify the model name (optional)" - ), -): - """ - 🚨 USE `/health/liveliness` to health check the proxy 🚨 - - See more 👉 https://docs.litellm.ai/docs/proxy/health - - - Check the health of all the endpoints in config.yaml - - To run health checks in the background, add this to config.yaml: - ``` - general_settings: - # ... other settings - background_health_checks: True - ``` - else, the health checks will be run on models when /health is called. - """ - global health_check_results, use_background_health_checks, user_model, llm_model_list - try: - if llm_model_list is None: - # if no router set, check if user set a model using litellm --model ollama/llama2 - if user_model is not None: - healthy_endpoints, unhealthy_endpoints = await perform_health_check( - model_list=[], cli_model=user_model - ) - return { - "healthy_endpoints": healthy_endpoints, - "unhealthy_endpoints": unhealthy_endpoints, - "healthy_count": len(healthy_endpoints), - "unhealthy_count": len(unhealthy_endpoints), - } - raise HTTPException( - status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, - detail={"error": "Model list not initialized"}, - ) - _llm_model_list = copy.deepcopy(llm_model_list) - ### FILTER MODELS FOR ONLY THOSE USER HAS ACCESS TO ### - if len(user_api_key_dict.models) > 0: - allowed_model_names = user_api_key_dict.models - else: - allowed_model_names = [] # - if use_background_health_checks: - return health_check_results - else: - healthy_endpoints, unhealthy_endpoints = await perform_health_check( - _llm_model_list, model - ) - - return { - "healthy_endpoints": healthy_endpoints, - "unhealthy_endpoints": unhealthy_endpoints, - "healthy_count": len(healthy_endpoints), - "unhealthy_count": len(unhealthy_endpoints), - } - except Exception as e: - verbose_proxy_logger.error( - "litellm.proxy.proxy_server.py::health_endpoint(): Exception occured - {}".format( - str(e) - ) - ) - verbose_proxy_logger.debug(traceback.format_exc()) - raise e - - -db_health_cache = {"status": "unknown", "last_updated": datetime.now()} - - -def _db_health_readiness_check(): - global db_health_cache, prisma_client - - # Note - Intentionally don't try/except this so it raises an exception when it fails - - # if timedelta is less than 2 minutes return DB Status - time_diff = datetime.now() - db_health_cache["last_updated"] - if db_health_cache["status"] != "unknown" and time_diff < timedelta(minutes=2): - return db_health_cache - prisma_client.health_check() - db_health_cache = {"status": "connected", "last_updated": datetime.now()} - return db_health_cache - - -@router.get( - "/active/callbacks", - tags=["health"], - dependencies=[Depends(user_api_key_auth)], -) -async def active_callbacks(): - """ - Returns a list of active callbacks on litellm.callbacks, litellm.input_callback, litellm.failure_callback, litellm.success_callback - """ - global proxy_logging_obj - _alerting = str(general_settings.get("alerting")) - # get success callbacks - - litellm_callbacks = [str(x) for x in litellm.callbacks] - litellm_input_callbacks = [str(x) for x in litellm.input_callback] - litellm_failure_callbacks = [str(x) for x in litellm.failure_callback] - litellm_success_callbacks = [str(x) for x in litellm.success_callback] - litellm_async_success_callbacks = [str(x) for x in litellm._async_success_callback] - litellm_async_failure_callbacks = [str(x) for x in litellm._async_failure_callback] - litellm_async_input_callbacks = [str(x) for x in litellm._async_input_callback] - - all_litellm_callbacks = ( - litellm_callbacks - + litellm_input_callbacks - + litellm_failure_callbacks - + litellm_success_callbacks - + litellm_async_success_callbacks - + litellm_async_failure_callbacks - + litellm_async_input_callbacks - ) - - alerting = proxy_logging_obj.alerting - _num_alerting = 0 - if alerting and isinstance(alerting, list): - _num_alerting = len(alerting) - - return { - "alerting": _alerting, - "litellm.callbacks": litellm_callbacks, - "litellm.input_callback": litellm_input_callbacks, - "litellm.failure_callback": litellm_failure_callbacks, - "litellm.success_callback": litellm_success_callbacks, - "litellm._async_success_callback": litellm_async_success_callbacks, - "litellm._async_failure_callback": litellm_async_failure_callbacks, - "litellm._async_input_callback": litellm_async_input_callbacks, - "all_litellm_callbacks": all_litellm_callbacks, - "num_callbacks": len(all_litellm_callbacks), - "num_alerting": _num_alerting, - } - - -@router.get( - "/health/readiness", - tags=["health"], - dependencies=[Depends(user_api_key_auth)], -) -async def health_readiness(): - """ - Unprotected endpoint for checking if worker can receive requests - """ - global general_settings - try: - # get success callback - success_callback_names = [] - - try: - # this was returning a JSON of the values in some of the callbacks - # all we need is the callback name, hence we do str(callback) - success_callback_names = [str(x) for x in litellm.success_callback] - except: - # don't let this block the /health/readiness response, if we can't convert to str -> return litellm.success_callback - success_callback_names = litellm.success_callback - - # check Cache - cache_type = None - if litellm.cache is not None: - from litellm.caching import RedisSemanticCache - - cache_type = litellm.cache.type - - if isinstance(litellm.cache.cache, RedisSemanticCache): - # ping the cache - # TODO: @ishaan-jaff - we should probably not ping the cache on every /health/readiness check - try: - index_info = await litellm.cache.cache._index_info() - except Exception as e: - index_info = "index does not exist - error: " + str(e) - cache_type = {"type": cache_type, "index_info": index_info} - - # check DB - if prisma_client is not None: # if db passed in, check if it's connected - db_health_status = _db_health_readiness_check() - return { - "status": "healthy", - "db": "connected", - "cache": cache_type, - "litellm_version": version, - "success_callbacks": success_callback_names, - **db_health_status, - } - else: - return { - "status": "healthy", - "db": "Not connected", - "cache": cache_type, - "litellm_version": version, - "success_callbacks": success_callback_names, - } - except Exception as e: - raise HTTPException(status_code=503, detail=f"Service Unhealthy ({str(e)})") - - -@router.get( - "/health/liveliness", - tags=["health"], - dependencies=[Depends(user_api_key_auth)], -) -async def health_liveliness(): - """ - Unprotected endpoint for checking if worker is alive - """ - return "I'm alive!" - - -@router.get( - "/cache/ping", - tags=["caching"], - dependencies=[Depends(user_api_key_auth)], -) -async def cache_ping(): - """ - Endpoint for checking if cache can be pinged - """ - try: - litellm_cache_params = {} - specific_cache_params = {} - - if litellm.cache is None: - raise HTTPException( - status_code=503, detail="Cache not initialized. litellm.cache is None" - ) - - for k, v in vars(litellm.cache).items(): - try: - if k == "cache": - continue - litellm_cache_params[k] = str(copy.deepcopy(v)) - except Exception: - litellm_cache_params[k] = "" - for k, v in vars(litellm.cache.cache).items(): - try: - specific_cache_params[k] = str(v) - except Exception: - specific_cache_params[k] = "" - if litellm.cache.type == "redis": - # ping the redis cache - ping_response = await litellm.cache.ping() - verbose_proxy_logger.debug( - "/cache/ping: ping_response: " + str(ping_response) - ) - # making a set cache call - # add cache does not return anything - await litellm.cache.async_add_cache( - result="test_key", - model="test-model", - messages=[{"role": "user", "content": "test from litellm"}], - ) - verbose_proxy_logger.debug("/cache/ping: done with set_cache()") - return { - "status": "healthy", - "cache_type": litellm.cache.type, - "ping_response": True, - "set_cache_response": "success", - "litellm_cache_params": litellm_cache_params, - "redis_cache_params": specific_cache_params, - } - else: - return { - "status": "healthy", - "cache_type": litellm.cache.type, - "litellm_cache_params": litellm_cache_params, - } - except Exception as e: - raise HTTPException( - status_code=503, - detail=f"Service Unhealthy ({str(e)}).Cache parameters: {litellm_cache_params}.specific_cache_params: {specific_cache_params}", - ) - - -@router.post( - "/cache/delete", - tags=["caching"], - dependencies=[Depends(user_api_key_auth)], -) -async def cache_delete(request: Request): - """ - Endpoint for deleting a key from the cache. All responses from litellm proxy have `x-litellm-cache-key` in the headers - - Parameters: - - **keys**: *Optional[List[str]]* - A list of keys to delete from the cache. Example {"keys": ["key1", "key2"]} - - ```shell - curl -X POST "http://0.0.0.0:4000/cache/delete" \ - -H "Authorization: Bearer sk-1234" \ - -d '{"keys": ["key1", "key2"]}' - ``` - - """ - try: - if litellm.cache is None: - raise HTTPException( - status_code=503, detail="Cache not initialized. litellm.cache is None" - ) - - request_data = await request.json() - keys = request_data.get("keys", None) - - if litellm.cache.type == "redis": - await litellm.cache.delete_cache_keys(keys=keys) - return { - "status": "success", - } - else: - raise HTTPException( - status_code=500, - detail=f"Cache type {litellm.cache.type} does not support deleting a key. only `redis` is supported", - ) - except Exception as e: - raise HTTPException( - status_code=500, - detail=f"Cache Delete Failed({str(e)})", - ) - - -@router.get( - "/cache/redis/info", - tags=["caching"], - dependencies=[Depends(user_api_key_auth)], -) -async def cache_redis_info(): - """ - Endpoint for getting /redis/info - """ - try: - if litellm.cache is None: - raise HTTPException( - status_code=503, detail="Cache not initialized. litellm.cache is None" - ) - if litellm.cache.type == "redis": - client_list = litellm.cache.cache.client_list() - redis_info = litellm.cache.cache.info() - num_clients = len(client_list) - return { - "num_clients": num_clients, - "clients": client_list, - "info": redis_info, - } - else: - raise HTTPException( - status_code=500, - detail=f"Cache type {litellm.cache.type} does not support flushing", - ) - except Exception as e: - raise HTTPException( - status_code=503, - detail=f"Service Unhealthy ({str(e)})", - ) - - -@router.post( - "/cache/flushall", - tags=["caching"], - dependencies=[Depends(user_api_key_auth)], -) -async def cache_flushall(): - """ - A function to flush all items from the cache. (All items will be deleted from the cache with this) - Raises HTTPException if the cache is not initialized or if the cache type does not support flushing. - Returns a dictionary with the status of the operation. - - Usage: - ``` - curl -X POST http://0.0.0.0:4000/cache/flushall -H "Authorization: Bearer sk-1234" - ``` - """ - try: - if litellm.cache is None: - raise HTTPException( - status_code=503, detail="Cache not initialized. litellm.cache is None" - ) - if litellm.cache.type == "redis": - litellm.cache.cache.flushall() - return { - "status": "success", - } - else: - raise HTTPException( - status_code=500, - detail=f"Cache type {litellm.cache.type} does not support flushing", - ) - except Exception as e: - raise HTTPException( - status_code=503, - detail=f"Service Unhealthy ({str(e)})", - ) - - @router.get( "/get/litellm_model_cost_map", include_in_schema=False, @@ -14781,7 +9410,11 @@ async def get_routes(): #### TEST ENDPOINTS #### -@router.get("/token/generate", dependencies=[Depends(user_api_key_auth)]) +@router.get( + "/token/generate", + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, +) async def token_generate(): """ Test endpoint. Admin-only access. Meant for generating admin tokens with specific claims and testing if they work for creating keys, etc. @@ -14801,24 +9434,6 @@ async def token_generate(): return {"token": token} -def _has_user_setup_sso(): - """ - Check if the user has set up single sign-on (SSO) by verifying the presence of Microsoft client ID, Google client ID, and UI username environment variables. - Returns a boolean indicating whether SSO has been set up. - """ - microsoft_client_id = os.getenv("MICROSOFT_CLIENT_ID", None) - google_client_id = os.getenv("GOOGLE_CLIENT_ID", None) - ui_username = os.getenv("UI_USERNAME", None) - - sso_setup = ( - (microsoft_client_id is not None) - or (google_client_id is not None) - or (ui_username is not None) - ) - - return sso_setup - - @router.on_event("shutdown") async def shutdown_event(): global prisma_client, master_key, user_custom_auth, user_custom_key_generate @@ -14867,3 +9482,8 @@ def cleanup_router_config_variables(): app.include_router(router) +app.include_router(health_router) +app.include_router(key_management_router) +app.include_router(team_router) +app.include_router(spend_management_router) +app.include_router(caching_router) diff --git a/litellm/proxy/spend_reporting_endpoints/spend_management_endpoints.py b/litellm/proxy/spend_reporting_endpoints/spend_management_endpoints.py new file mode 100644 index 00000000000..901a926456d --- /dev/null +++ b/litellm/proxy/spend_reporting_endpoints/spend_management_endpoints.py @@ -0,0 +1,1829 @@ +#### SPEND MANAGEMENT ##### +from typing import Optional, List +import litellm +from litellm._logging import verbose_proxy_logger +from datetime import datetime, timedelta, timezone +from litellm.proxy.auth.user_api_key_auth import user_api_key_auth +import fastapi +from fastapi import Depends, Request, APIRouter, Header, status +from fastapi import HTTPException +from litellm.proxy._types import * + +router = APIRouter() + + +@router.get( + "/spend/keys", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, +) +async def spend_key_fn(): + """ + View all keys created, ordered by spend + + Example Request: + ``` + curl -X GET "http://0.0.0.0:8000/spend/keys" \ +-H "Authorization: Bearer sk-1234" + ``` + """ + + from litellm.proxy.proxy_server import prisma_client + + try: + if prisma_client is None: + raise Exception( + f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + ) + + key_info = await prisma_client.get_data(table_name="key", query_type="find_all") + return key_info + + except Exception as e: + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail={"error": str(e)}, + ) + + +@router.get( + "/spend/users", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, +) +async def spend_user_fn( + user_id: Optional[str] = fastapi.Query( + default=None, + description="Get User Table row for user_id", + ), +): + """ + View all users created, ordered by spend + + Example Request: + ``` + curl -X GET "http://0.0.0.0:8000/spend/users" \ +-H "Authorization: Bearer sk-1234" + ``` + + View User Table row for user_id + ``` + curl -X GET "http://0.0.0.0:8000/spend/users?user_id=1234" \ +-H "Authorization: Bearer sk-1234" + ``` + """ + from litellm.proxy.proxy_server import prisma_client + + try: + if prisma_client is None: + raise Exception( + f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + ) + + if user_id is not None: + user_info = await prisma_client.get_data( + table_name="user", query_type="find_unique", user_id=user_id + ) + return [user_info] + else: + user_info = await prisma_client.get_data( + table_name="user", query_type="find_all" + ) + + return user_info + + except Exception as e: + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail={"error": str(e)}, + ) + + +@router.get( + "/spend/tags", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + responses={ + 200: {"model": List[LiteLLM_SpendLogs]}, + }, +) +async def view_spend_tags( + start_date: Optional[str] = fastapi.Query( + default=None, + description="Time from which to start viewing key spend", + ), + end_date: Optional[str] = fastapi.Query( + default=None, + description="Time till which to view key spend", + ), +): + """ + LiteLLM Enterprise - View Spend Per Request Tag + + Example Request: + ``` + curl -X GET "http://0.0.0.0:8000/spend/tags" \ +-H "Authorization: Bearer sk-1234" + ``` + + Spend with Start Date and End Date + ``` + curl -X GET "http://0.0.0.0:8000/spend/tags?start_date=2022-01-01&end_date=2022-02-01" \ +-H "Authorization: Bearer sk-1234" + ``` + """ + + from enterprise.utils import get_spend_by_tags + from litellm.proxy.proxy_server import prisma_client + + try: + if prisma_client is None: + raise Exception( + f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + ) + + # run the following SQL query on prisma + """ + SELECT + jsonb_array_elements_text(request_tags) AS individual_request_tag, + COUNT(*) AS log_count, + SUM(spend) AS total_spend + FROM "LiteLLM_SpendLogs" + GROUP BY individual_request_tag; + """ + response = await get_spend_by_tags( + start_date=start_date, end_date=end_date, prisma_client=prisma_client + ) + + return response + except Exception as e: + if isinstance(e, HTTPException): + raise ProxyException( + message=getattr(e, "detail", f"/spend/tags Error({str(e)})"), + type="internal_error", + param=getattr(e, "param", "None"), + code=getattr(e, "status_code", status.HTTP_500_INTERNAL_SERVER_ERROR), + ) + elif isinstance(e, ProxyException): + raise e + raise ProxyException( + message="/spend/tags Error" + str(e), + type="internal_error", + param=getattr(e, "param", "None"), + code=status.HTTP_500_INTERNAL_SERVER_ERROR, + ) + + +@router.get( + "/global/activity", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + responses={ + 200: {"model": List[LiteLLM_SpendLogs]}, + }, + include_in_schema=False, +) +async def get_global_activity( + start_date: Optional[str] = fastapi.Query( + default=None, + description="Time from which to start viewing spend", + ), + end_date: Optional[str] = fastapi.Query( + default=None, + description="Time till which to view spend", + ), +): + """ + Get number of API Requests, total tokens through proxy + + { + "daily_data": [ + const chartdata = [ + { + date: 'Jan 22', + api_requests: 10, + total_tokens: 2000 + }, + { + date: 'Jan 23', + api_requests: 10, + total_tokens: 12 + }, + ], + "sum_api_requests": 20, + "sum_total_tokens": 2012 + } + """ + from collections import defaultdict + + if start_date is None or end_date is None: + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail={"error": "Please provide start_date and end_date"}, + ) + + start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") + end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") + + from litellm.proxy.proxy_server import prisma_client, llm_router + + try: + if prisma_client is None: + raise Exception( + f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + ) + + sql_query = """ + SELECT + date_trunc('day', "startTime") AS date, + COUNT(*) AS api_requests, + SUM(total_tokens) AS total_tokens + FROM "LiteLLM_SpendLogs" + WHERE "startTime" BETWEEN $1::date AND $2::date + interval '1 day' + GROUP BY date_trunc('day', "startTime") + """ + db_response = await prisma_client.db.query_raw( + sql_query, start_date_obj, end_date_obj + ) + + if db_response is None: + return [] + + sum_api_requests = 0 + sum_total_tokens = 0 + daily_data = [] + for row in db_response: + # cast date to datetime + _date_obj = datetime.fromisoformat(row["date"]) + row["date"] = _date_obj.strftime("%b %d") + + daily_data.append(row) + sum_api_requests += row.get("api_requests", 0) + sum_total_tokens += row.get("total_tokens", 0) + + # sort daily_data by date + daily_data = sorted(daily_data, key=lambda x: x["date"]) + + data_to_return = { + "daily_data": daily_data, + "sum_api_requests": sum_api_requests, + "sum_total_tokens": sum_total_tokens, + } + + return data_to_return + + except Exception as e: + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail={"error": str(e)}, + ) + + +@router.get( + "/global/activity/model", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + responses={ + 200: {"model": List[LiteLLM_SpendLogs]}, + }, + include_in_schema=False, +) +async def get_global_activity_model( + start_date: Optional[str] = fastapi.Query( + default=None, + description="Time from which to start viewing spend", + ), + end_date: Optional[str] = fastapi.Query( + default=None, + description="Time till which to view spend", + ), +): + """ + Get number of API Requests, total tokens through proxy - Grouped by MODEL + + [ + { + "model": "gpt-4", + "daily_data": [ + const chartdata = [ + { + date: 'Jan 22', + api_requests: 10, + total_tokens: 2000 + }, + { + date: 'Jan 23', + api_requests: 10, + total_tokens: 12 + }, + ], + "sum_api_requests": 20, + "sum_total_tokens": 2012 + + }, + { + "model": "azure/gpt-4-turbo", + "daily_data": [ + const chartdata = [ + { + date: 'Jan 22', + api_requests: 10, + total_tokens: 2000 + }, + { + date: 'Jan 23', + api_requests: 10, + total_tokens: 12 + }, + ], + "sum_api_requests": 20, + "sum_total_tokens": 2012 + + }, + ] + """ + from collections import defaultdict + + if start_date is None or end_date is None: + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail={"error": "Please provide start_date and end_date"}, + ) + + start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") + end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") + + from litellm.proxy.proxy_server import prisma_client, llm_router, premium_user + + try: + if prisma_client is None: + raise Exception( + f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + ) + + sql_query = """ + SELECT + model_group, + date_trunc('day', "startTime") AS date, + COUNT(*) AS api_requests, + SUM(total_tokens) AS total_tokens + FROM "LiteLLM_SpendLogs" + WHERE "startTime" BETWEEN $1::date AND $2::date + interval '1 day' + GROUP BY model_group, date_trunc('day', "startTime") + """ + db_response = await prisma_client.db.query_raw( + sql_query, start_date_obj, end_date_obj + ) + if db_response is None: + return [] + + model_ui_data: dict = ( + {} + ) # {"gpt-4": {"daily_data": [], "sum_api_requests": 0, "sum_total_tokens": 0}} + + for row in db_response: + _model = row["model_group"] + if _model not in model_ui_data: + model_ui_data[_model] = { + "daily_data": [], + "sum_api_requests": 0, + "sum_total_tokens": 0, + } + _date_obj = datetime.fromisoformat(row["date"]) + row["date"] = _date_obj.strftime("%b %d") + + model_ui_data[_model]["daily_data"].append(row) + model_ui_data[_model]["sum_api_requests"] += row.get("api_requests", 0) + model_ui_data[_model]["sum_total_tokens"] += row.get("total_tokens", 0) + + # sort mode ui data by sum_api_requests -> get top 10 models + model_ui_data = dict( + sorted( + model_ui_data.items(), + key=lambda x: x[1]["sum_api_requests"], + reverse=True, + )[:10] + ) + + response = [] + for model, data in model_ui_data.items(): + _sort_daily_data = sorted(data["daily_data"], key=lambda x: x["date"]) + + response.append( + { + "model": model, + "daily_data": _sort_daily_data, + "sum_api_requests": data["sum_api_requests"], + "sum_total_tokens": data["sum_total_tokens"], + } + ) + + return response + + except Exception as e: + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail={"error": str(e)}, + ) + + +@router.get( + "/global/activity/exceptions/deployment", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + responses={ + 200: {"model": List[LiteLLM_SpendLogs]}, + }, + include_in_schema=False, +) +async def get_global_activity_exceptions_per_deployment( + model_group: str = fastapi.Query( + description="Filter by model group", + ), + start_date: Optional[str] = fastapi.Query( + default=None, + description="Time from which to start viewing spend", + ), + end_date: Optional[str] = fastapi.Query( + default=None, + description="Time till which to view spend", + ), +): + """ + Get number of 429 errors - Grouped by deployment + + [ + { + "deployment": "https://azure-us-east-1.openai.azure.com/", + "daily_data": [ + const chartdata = [ + { + date: 'Jan 22', + num_rate_limit_exceptions: 10 + }, + { + date: 'Jan 23', + num_rate_limit_exceptions: 12 + }, + ], + "sum_num_rate_limit_exceptions": 20, + + }, + { + "deployment": "https://azure-us-east-1.openai.azure.com/", + "daily_data": [ + const chartdata = [ + { + date: 'Jan 22', + num_rate_limit_exceptions: 10, + }, + { + date: 'Jan 23', + num_rate_limit_exceptions: 12 + }, + ], + "sum_num_rate_limit_exceptions": 20, + + }, + ] + """ + from collections import defaultdict + + if start_date is None or end_date is None: + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail={"error": "Please provide start_date and end_date"}, + ) + + start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") + end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") + + from litellm.proxy.proxy_server import prisma_client, llm_router, premium_user + + try: + if prisma_client is None: + raise Exception( + f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + ) + + sql_query = """ + SELECT + api_base, + date_trunc('day', "startTime")::date AS date, + COUNT(*) AS num_rate_limit_exceptions + FROM + "LiteLLM_ErrorLogs" + WHERE + "startTime" >= $1::date + AND "startTime" < ($2::date + INTERVAL '1 day') + AND model_group = $3 + AND status_code = '429' + GROUP BY + api_base, + date_trunc('day', "startTime") + ORDER BY + date; + """ + db_response = await prisma_client.db.query_raw( + sql_query, start_date_obj, end_date_obj, model_group + ) + if db_response is None: + return [] + + model_ui_data: dict = ( + {} + ) # {"gpt-4": {"daily_data": [], "sum_api_requests": 0, "sum_total_tokens": 0}} + + for row in db_response: + _model = row["api_base"] + if _model not in model_ui_data: + model_ui_data[_model] = { + "daily_data": [], + "sum_num_rate_limit_exceptions": 0, + } + _date_obj = datetime.fromisoformat(row["date"]) + row["date"] = _date_obj.strftime("%b %d") + + model_ui_data[_model]["daily_data"].append(row) + model_ui_data[_model]["sum_num_rate_limit_exceptions"] += row.get( + "num_rate_limit_exceptions", 0 + ) + + # sort mode ui data by sum_api_requests -> get top 10 models + model_ui_data = dict( + sorted( + model_ui_data.items(), + key=lambda x: x[1]["sum_num_rate_limit_exceptions"], + reverse=True, + )[:10] + ) + + response = [] + for model, data in model_ui_data.items(): + _sort_daily_data = sorted(data["daily_data"], key=lambda x: x["date"]) + + response.append( + { + "api_base": model, + "daily_data": _sort_daily_data, + "sum_num_rate_limit_exceptions": data[ + "sum_num_rate_limit_exceptions" + ], + } + ) + + return response + + except Exception as e: + raise HTTPException( + status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, + detail={"error": str(e)}, + ) + + +@router.get( + "/global/activity/exceptions", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + responses={ + 200: {"model": List[LiteLLM_SpendLogs]}, + }, + include_in_schema=False, +) +async def get_global_activity_exceptions( + model_group: str = fastapi.Query( + description="Filter by model group", + ), + start_date: Optional[str] = fastapi.Query( + default=None, + description="Time from which to start viewing spend", + ), + end_date: Optional[str] = fastapi.Query( + default=None, + description="Time till which to view spend", + ), +): + """ + Get number of API Requests, total tokens through proxy + + { + "daily_data": [ + const chartdata = [ + { + date: 'Jan 22', + num_rate_limit_exceptions: 10, + }, + { + date: 'Jan 23', + num_rate_limit_exceptions: 10, + }, + ], + "sum_api_exceptions": 20, + } + """ + from collections import defaultdict + + if start_date is None or end_date is None: + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail={"error": "Please provide start_date and end_date"}, + ) + + start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") + end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") + + from litellm.proxy.proxy_server import prisma_client, llm_router + + try: + if prisma_client is None: + raise Exception( + f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + ) + + sql_query = """ + SELECT + date_trunc('day', "startTime")::date AS date, + COUNT(*) AS num_rate_limit_exceptions + FROM + "LiteLLM_ErrorLogs" + WHERE + "startTime" >= $1::date + AND "startTime" < ($2::date + INTERVAL '1 day') + AND model_group = $3 + AND status_code = '429' + GROUP BY + date_trunc('day', "startTime") + ORDER BY + date; + """ + db_response = await prisma_client.db.query_raw( + sql_query, start_date_obj, end_date_obj, model_group + ) + + if db_response is None: + return [] + + sum_num_rate_limit_exceptions = 0 + daily_data = [] + for row in db_response: + # cast date to datetime + _date_obj = datetime.fromisoformat(row["date"]) + row["date"] = _date_obj.strftime("%b %d") + + daily_data.append(row) + sum_num_rate_limit_exceptions += row.get("num_rate_limit_exceptions", 0) + + # sort daily_data by date + daily_data = sorted(daily_data, key=lambda x: x["date"]) + + data_to_return = { + "daily_data": daily_data, + "sum_num_rate_limit_exceptions": sum_num_rate_limit_exceptions, + } + + return data_to_return + + except Exception as e: + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail={"error": str(e)}, + ) + + +@router.get( + "/global/spend/provider", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, + responses={ + 200: {"model": List[LiteLLM_SpendLogs]}, + }, +) +async def get_global_spend_provider( + start_date: Optional[str] = fastapi.Query( + default=None, + description="Time from which to start viewing spend", + ), + end_date: Optional[str] = fastapi.Query( + default=None, + description="Time till which to view spend", + ), +): + """ + Get breakdown of spend per provider + [ + { + "provider": "Azure OpenAI", + "spend": 20 + }, + { + "provider": "OpenAI", + "spend": 10 + }, + { + "provider": "VertexAI", + "spend": 30 + } + ] + """ + from collections import defaultdict + + if start_date is None or end_date is None: + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail={"error": "Please provide start_date and end_date"}, + ) + + start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") + end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") + + from litellm.proxy.proxy_server import prisma_client, llm_router + + try: + if prisma_client is None: + raise Exception( + f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + ) + + sql_query = """ + + SELECT + model_id, + SUM(spend) AS spend + FROM "LiteLLM_SpendLogs" + WHERE "startTime" BETWEEN $1::date AND $2::date AND length(model_id) > 0 + GROUP BY model_id + """ + + db_response = await prisma_client.db.query_raw( + sql_query, start_date_obj, end_date_obj + ) + if db_response is None: + return [] + + ################################### + # Convert model_id -> to Provider # + ################################### + + # we use the in memory router for this + ui_response = [] + provider_spend_mapping: defaultdict = defaultdict(int) + for row in db_response: + _model_id = row["model_id"] + _provider = "Unknown" + if llm_router is not None: + _deployment = llm_router.get_deployment(model_id=_model_id) + if _deployment is not None: + try: + _, _provider, _, _ = litellm.get_llm_provider( + model=_deployment.litellm_params.model, + custom_llm_provider=_deployment.litellm_params.custom_llm_provider, + api_base=_deployment.litellm_params.api_base, + litellm_params=_deployment.litellm_params, + ) + provider_spend_mapping[_provider] += row["spend"] + except: + pass + + for provider, spend in provider_spend_mapping.items(): + ui_response.append({"provider": provider, "spend": spend}) + + return ui_response + + except Exception as e: + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail={"error": str(e)}, + ) + + +@router.get( + "/global/spend/report", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + responses={ + 200: {"model": List[LiteLLM_SpendLogs]}, + }, +) +async def get_global_spend_report( + start_date: Optional[str] = fastapi.Query( + default=None, + description="Time from which to start viewing spend", + ), + end_date: Optional[str] = fastapi.Query( + default=None, + description="Time till which to view spend", + ), + group_by: Optional[Literal["team", "customer"]] = fastapi.Query( + default="team", + description="Group spend by internal team or customer", + ), +): + """ + Get Daily Spend per Team, based on specific startTime and endTime. Per team, view usage by each key, model + [ + { + "group-by-day": "2024-05-10", + "teams": [ + { + "team_name": "team-1" + "spend": 10, + "keys": [ + "key": "1213", + "usage": { + "model-1": { + "cost": 12.50, + "input_tokens": 1000, + "output_tokens": 5000, + "requests": 100 + }, + "audio-modelname1": { + "cost": 25.50, + "seconds": 25, + "requests": 50 + }, + } + } + ] + ] + } + """ + if start_date is None or end_date is None: + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail={"error": "Please provide start_date and end_date"}, + ) + + start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") + end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") + + from litellm.proxy.proxy_server import prisma_client + + try: + if prisma_client is None: + raise Exception( + f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + ) + + if group_by == "team": + # first get data from spend logs -> SpendByModelApiKey + # then read data from "SpendByModelApiKey" to format the response obj + sql_query = """ + + WITH SpendByModelApiKey AS ( + SELECT + date_trunc('day', sl."startTime") AS group_by_day, + COALESCE(tt.team_alias, 'Unassigned Team') AS team_name, + sl.model, + sl.api_key, + SUM(sl.spend) AS model_api_spend, + SUM(sl.total_tokens) AS model_api_tokens + FROM + "LiteLLM_SpendLogs" sl + LEFT JOIN + "LiteLLM_TeamTable" tt + ON + sl.team_id = tt.team_id + WHERE + sl."startTime" BETWEEN $1::date AND $2::date + GROUP BY + date_trunc('day', sl."startTime"), + tt.team_alias, + sl.model, + sl.api_key + ) + SELECT + group_by_day, + jsonb_agg(jsonb_build_object( + 'team_name', team_name, + 'total_spend', total_spend, + 'metadata', metadata + )) AS teams + FROM ( + SELECT + group_by_day, + team_name, + SUM(model_api_spend) AS total_spend, + jsonb_agg(jsonb_build_object( + 'model', model, + 'api_key', api_key, + 'spend', model_api_spend, + 'total_tokens', model_api_tokens + )) AS metadata + FROM + SpendByModelApiKey + GROUP BY + group_by_day, + team_name + ) AS aggregated + GROUP BY + group_by_day + ORDER BY + group_by_day; + """ + + db_response = await prisma_client.db.query_raw( + sql_query, start_date_obj, end_date_obj + ) + if db_response is None: + return [] + + return db_response + + elif group_by == "customer": + sql_query = """ + + WITH SpendByModelApiKey AS ( + SELECT + date_trunc('day', sl."startTime") AS group_by_day, + sl.end_user AS customer, + sl.model, + sl.api_key, + SUM(sl.spend) AS model_api_spend, + SUM(sl.total_tokens) AS model_api_tokens + FROM + "LiteLLM_SpendLogs" sl + WHERE + sl."startTime" BETWEEN $1::date AND $2::date + GROUP BY + date_trunc('day', sl."startTime"), + customer, + sl.model, + sl.api_key + ) + SELECT + group_by_day, + jsonb_agg(jsonb_build_object( + 'customer', customer, + 'total_spend', total_spend, + 'metadata', metadata + )) AS customers + FROM + ( + SELECT + group_by_day, + customer, + SUM(model_api_spend) AS total_spend, + jsonb_agg(jsonb_build_object( + 'model', model, + 'api_key', api_key, + 'spend', model_api_spend, + 'total_tokens', model_api_tokens + )) AS metadata + FROM + SpendByModelApiKey + GROUP BY + group_by_day, + customer + ) AS aggregated + GROUP BY + group_by_day + ORDER BY + group_by_day; + """ + + db_response = await prisma_client.db.query_raw( + sql_query, start_date_obj, end_date_obj + ) + if db_response is None: + return [] + + return db_response + + except Exception as e: + raise HTTPException( + status_code=status.HTTP_400_BAD_REQUEST, + detail={"error": str(e)}, + ) + + +@router.get( + "/global/spend/all_tag_names", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, + responses={ + 200: {"model": List[LiteLLM_SpendLogs]}, + }, +) +async def global_get_all_tag_names(): + try: + from litellm.proxy.proxy_server import prisma_client + + if prisma_client is None: + raise Exception( + f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + ) + + sql_query = """ + SELECT DISTINCT + jsonb_array_elements_text(request_tags) AS individual_request_tag + FROM "LiteLLM_SpendLogs"; + """ + + db_response = await prisma_client.db.query_raw(sql_query) + if db_response is None: + return [] + + _tag_names = [] + for row in db_response: + _tag_names.append(row.get("individual_request_tag")) + + return {"tag_names": _tag_names} + + except Exception as e: + if isinstance(e, HTTPException): + raise ProxyException( + message=getattr(e, "detail", f"/spend/all_tag_names Error({str(e)})"), + type="internal_error", + param=getattr(e, "param", "None"), + code=getattr(e, "status_code", status.HTTP_500_INTERNAL_SERVER_ERROR), + ) + elif isinstance(e, ProxyException): + raise e + raise ProxyException( + message="/spend/all_tag_names Error" + str(e), + type="internal_error", + param=getattr(e, "param", "None"), + code=status.HTTP_500_INTERNAL_SERVER_ERROR, + ) + + +@router.get( + "/global/spend/tags", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, + responses={ + 200: {"model": List[LiteLLM_SpendLogs]}, + }, +) +async def global_view_spend_tags( + start_date: Optional[str] = fastapi.Query( + default=None, + description="Time from which to start viewing key spend", + ), + end_date: Optional[str] = fastapi.Query( + default=None, + description="Time till which to view key spend", + ), + tags: Optional[str] = fastapi.Query( + default=None, + description="comman separated tags to filter on", + ), +): + """ + LiteLLM Enterprise - View Spend Per Request Tag. Used by LiteLLM UI + + Example Request: + ``` + curl -X GET "http://0.0.0.0:4000/spend/tags" \ +-H "Authorization: Bearer sk-1234" + ``` + + Spend with Start Date and End Date + ``` + curl -X GET "http://0.0.0.0:4000/spend/tags?start_date=2022-01-01&end_date=2022-02-01" \ +-H "Authorization: Bearer sk-1234" + ``` + """ + + from enterprise.utils import ui_get_spend_by_tags + + from litellm.proxy.proxy_server import prisma_client + + try: + if prisma_client is None: + raise Exception( + f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + ) + + if end_date is None or start_date is None: + raise ProxyException( + message="Please provide start_date and end_date", + type="bad_request", + param=None, + code=status.HTTP_400_BAD_REQUEST, + ) + response = await ui_get_spend_by_tags( + start_date=start_date, + end_date=end_date, + tags_str=tags, + prisma_client=prisma_client, + ) + + return response + except Exception as e: + if isinstance(e, HTTPException): + raise ProxyException( + message=getattr(e, "detail", f"/spend/tags Error({str(e)})"), + type="internal_error", + param=getattr(e, "param", "None"), + code=getattr(e, "status_code", status.HTTP_500_INTERNAL_SERVER_ERROR), + ) + elif isinstance(e, ProxyException): + raise e + raise ProxyException( + message="/spend/tags Error" + str(e), + type="internal_error", + param=getattr(e, "param", "None"), + code=status.HTTP_500_INTERNAL_SERVER_ERROR, + ) + + +async def _get_spend_report_for_time_range( + start_date: str, + end_date: str, +): + from litellm.proxy.proxy_server import prisma_client + + if prisma_client is None: + verbose_proxy_logger.error( + f"Database not connected. Connect a database to your proxy for weekly, monthly spend reports" + ) + return None + + try: + sql_query = """ + SELECT + t.team_alias, + SUM(s.spend) AS total_spend + FROM + "LiteLLM_SpendLogs" s + LEFT JOIN + "LiteLLM_TeamTable" t ON s.team_id = t.team_id + WHERE + s."startTime"::DATE >= $1::date AND s."startTime"::DATE <= $2::date + GROUP BY + t.team_alias + ORDER BY + total_spend DESC; + """ + response = await prisma_client.db.query_raw(sql_query, start_date, end_date) + + # get spend per tag for today + sql_query = """ + SELECT + jsonb_array_elements_text(request_tags) AS individual_request_tag, + SUM(spend) AS total_spend + FROM "LiteLLM_SpendLogs" + WHERE "startTime"::DATE >= $1::date AND "startTime"::DATE <= $2::date + GROUP BY individual_request_tag + ORDER BY total_spend DESC; + """ + + spend_per_tag = await prisma_client.db.query_raw( + sql_query, start_date, end_date + ) + + return response, spend_per_tag + except Exception as e: + verbose_proxy_logger.error( + "Exception in _get_daily_spend_reports {}".format(str(e)) + ) # noqa + + +@router.post( + "/spend/calculate", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + responses={ + 200: { + "cost": { + "description": "The calculated cost", + "example": 0.0, + "type": "float", + } + } + }, +) +async def calculate_spend(request: Request): + """ + Accepts all the params of completion_cost. + + Calculate spend **before** making call: + + Note: If you see a spend of $0.0 you need to set custom_pricing for your model: https://docs.litellm.ai/docs/proxy/custom_pricing + + ``` + curl --location 'http://localhost:4000/spend/calculate' + --header 'Authorization: Bearer sk-1234' + --header 'Content-Type: application/json' + --data '{ + "model": "anthropic.claude-v2", + "messages": [{"role": "user", "content": "Hey, how'''s it going?"}] + }' + ``` + + Calculate spend **after** making call: + + ``` + curl --location 'http://localhost:4000/spend/calculate' + --header 'Authorization: Bearer sk-1234' + --header 'Content-Type: application/json' + --data '{ + "completion_response": { + "id": "chatcmpl-123", + "object": "chat.completion", + "created": 1677652288, + "model": "gpt-3.5-turbo-0125", + "system_fingerprint": "fp_44709d6fcb", + "choices": [{ + "index": 0, + "message": { + "role": "assistant", + "content": "Hello there, how may I assist you today?" + }, + "logprobs": null, + "finish_reason": "stop" + }] + "usage": { + "prompt_tokens": 9, + "completion_tokens": 12, + "total_tokens": 21 + } + } + }' + ``` + """ + from litellm import completion_cost + + data = await request.json() + if "completion_response" in data: + data["completion_response"] = litellm.ModelResponse( + **data["completion_response"] + ) + return {"cost": completion_cost(**data)} + + +@router.get( + "/spend/logs", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + responses={ + 200: {"model": List[LiteLLM_SpendLogs]}, + }, +) +async def view_spend_logs( + api_key: Optional[str] = fastapi.Query( + default=None, + description="Get spend logs based on api key", + ), + user_id: Optional[str] = fastapi.Query( + default=None, + description="Get spend logs based on user_id", + ), + request_id: Optional[str] = fastapi.Query( + default=None, + description="request_id to get spend logs for specific request_id. If none passed then pass spend logs for all requests", + ), + start_date: Optional[str] = fastapi.Query( + default=None, + description="Time from which to start viewing key spend", + ), + end_date: Optional[str] = fastapi.Query( + default=None, + description="Time till which to view key spend", + ), +): + """ + View all spend logs, if request_id is provided, only logs for that request_id will be returned + + Example Request for all logs + ``` + curl -X GET "http://0.0.0.0:8000/spend/logs" \ +-H "Authorization: Bearer sk-1234" + ``` + + Example Request for specific request_id + ``` + curl -X GET "http://0.0.0.0:8000/spend/logs?request_id=chatcmpl-6dcb2540-d3d7-4e49-bb27-291f863f112e" \ +-H "Authorization: Bearer sk-1234" + ``` + + Example Request for specific api_key + ``` + curl -X GET "http://0.0.0.0:8000/spend/logs?api_key=sk-Fn8Ej39NkBQmUagFEoUWPQ" \ +-H "Authorization: Bearer sk-1234" + ``` + + Example Request for specific user_id + ``` + curl -X GET "http://0.0.0.0:8000/spend/logs?user_id=ishaan@berri.ai" \ +-H "Authorization: Bearer sk-1234" + ``` + """ + from litellm.proxy.proxy_server import prisma_client + + try: + verbose_proxy_logger.debug("inside view_spend_logs") + if prisma_client is None: + raise Exception( + f"Database not connected. Connect a database to your proxy - https://docs.litellm.ai/docs/simple_proxy#managing-auth---virtual-keys" + ) + spend_logs = [] + if ( + start_date is not None + and isinstance(start_date, str) + and end_date is not None + and isinstance(end_date, str) + ): + # Convert the date strings to datetime objects + start_date_obj = datetime.strptime(start_date, "%Y-%m-%d") + end_date_obj = datetime.strptime(end_date, "%Y-%m-%d") + + filter_query = { + "startTime": { + "gte": start_date_obj, # Greater than or equal to Start Date + "lte": end_date_obj, # Less than or equal to End Date + } + } + + if api_key is not None and isinstance(api_key, str): + filter_query["api_key"] = api_key # type: ignore + elif request_id is not None and isinstance(request_id, str): + filter_query["request_id"] = request_id # type: ignore + elif user_id is not None and isinstance(user_id, str): + filter_query["user"] = user_id # type: ignore + + # SQL query + response = await prisma_client.db.litellm_spendlogs.group_by( + by=["api_key", "user", "model", "startTime"], + where=filter_query, # type: ignore + sum={ + "spend": True, + }, + ) + + if ( + isinstance(response, list) + and len(response) > 0 + and isinstance(response[0], dict) + ): + result: dict = {} + for record in response: + dt_object = datetime.strptime( + str(record["startTime"]), "%Y-%m-%dT%H:%M:%S.%fZ" + ) # type: ignore + date = dt_object.date() + if date not in result: + result[date] = {"users": {}, "models": {}} + api_key = record["api_key"] + user_id = record["user"] + model = record["model"] + result[date]["spend"] = ( + result[date].get("spend", 0) + record["_sum"]["spend"] + ) + result[date][api_key] = ( + result[date].get(api_key, 0) + record["_sum"]["spend"] + ) + result[date]["users"][user_id] = ( + result[date]["users"].get(user_id, 0) + record["_sum"]["spend"] + ) + result[date]["models"][model] = ( + result[date]["models"].get(model, 0) + record["_sum"]["spend"] + ) + return_list = [] + final_date = None + for k, v in sorted(result.items()): + return_list.append({**v, "startTime": k}) + final_date = k + + end_date_date = end_date_obj.date() + if final_date is not None and final_date < end_date_date: + current_date = final_date + timedelta(days=1) + while current_date <= end_date_date: + # Represent current_date as string because original response has it this way + return_list.append( + { + "startTime": current_date, + "spend": 0, + "users": {}, + "models": {}, + } + ) # If no data, will stay as zero + current_date += timedelta(days=1) # Move on to the next day + + return return_list + + return response + + elif api_key is not None and isinstance(api_key, str): + if api_key.startswith("sk-"): + hashed_token = prisma_client.hash_token(token=api_key) + else: + hashed_token = api_key + spend_log = await prisma_client.get_data( + table_name="spend", + query_type="find_all", + key_val={"key": "api_key", "value": hashed_token}, + ) + if isinstance(spend_log, list): + return spend_log + else: + return [spend_log] + elif request_id is not None: + spend_log = await prisma_client.get_data( + table_name="spend", + query_type="find_unique", + key_val={"key": "request_id", "value": request_id}, + ) + return [spend_log] + elif user_id is not None: + spend_log = await prisma_client.get_data( + table_name="spend", + query_type="find_all", + key_val={"key": "user", "value": user_id}, + ) + if isinstance(spend_log, list): + return spend_log + else: + return [spend_log] + else: + spend_logs = await prisma_client.get_data( + table_name="spend", query_type="find_all" + ) + + return spend_log + + return None + + except Exception as e: + if isinstance(e, HTTPException): + raise ProxyException( + message=getattr(e, "detail", f"/spend/logs Error({str(e)})"), + type="internal_error", + param=getattr(e, "param", "None"), + code=getattr(e, "status_code", status.HTTP_500_INTERNAL_SERVER_ERROR), + ) + elif isinstance(e, ProxyException): + raise e + raise ProxyException( + message="/spend/logs Error" + str(e), + type="internal_error", + param=getattr(e, "param", "None"), + code=status.HTTP_500_INTERNAL_SERVER_ERROR, + ) + + +@router.post( + "/global/spend/reset", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], +) +async def global_spend_reset(): + """ + ADMIN ONLY / MASTER KEY Only Endpoint + + Globally reset spend for All API Keys and Teams, maintain LiteLLM_SpendLogs + + 1. LiteLLM_SpendLogs will maintain the logs on spend, no data gets deleted from there + 2. LiteLLM_VerificationTokens spend will be set = 0 + 3. LiteLLM_TeamTable spend will be set = 0 + + """ + from litellm.proxy.proxy_server import prisma_client + + if prisma_client is None: + raise ProxyException( + message="Prisma Client is not initialized", + type="internal_error", + param="None", + code=status.HTTP_401_UNAUTHORIZED, + ) + + await prisma_client.db.litellm_verificationtoken.update_many( + data={"spend": 0.0}, where={} + ) + await prisma_client.db.litellm_teamtable.update_many(data={"spend": 0.0}, where={}) + + return { + "message": "Spend for all API Keys and Teams reset successfully", + "status": "success", + } + + +@router.get( + "/global/spend/logs", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, +) +async def global_spend_logs( + api_key: str = fastapi.Query( + default=None, + description="API Key to get global spend (spend per day for last 30d). Admin-only endpoint", + ) +): + """ + [BETA] This is a beta endpoint. It will change. + + Use this to get global spend (spend per day for last 30d). Admin-only endpoint + + More efficient implementation of /spend/logs, by creating a view over the spend logs table. + """ + from litellm.proxy.proxy_server import prisma_client + + if prisma_client is None: + raise ProxyException( + message="Prisma Client is not initialized", + type="internal_error", + param="None", + code=status.HTTP_500_INTERNAL_SERVER_ERROR, + ) + if api_key is None: + sql_query = """SELECT * FROM "MonthlyGlobalSpend" ORDER BY "date";""" + + response = await prisma_client.db.query_raw(query=sql_query) + + return response + else: + sql_query = """ + SELECT * FROM "MonthlyGlobalSpendPerKey" + WHERE "api_key" = $1 + ORDER BY "date"; + """ + + response = await prisma_client.db.query_raw(sql_query, api_key) + + return response + return + + +@router.get( + "/global/spend", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, +) +async def global_spend(): + """ + [BETA] This is a beta endpoint. It will change. + + View total spend across all proxy keys + """ + from litellm.proxy.proxy_server import prisma_client + + total_spend = 0.0 + total_proxy_budget = 0.0 + + if prisma_client is None: + raise HTTPException(status_code=500, detail={"error": "No db connected"}) + sql_query = """SELECT SUM(spend) as total_spend FROM "MonthlyGlobalSpend";""" + response = await prisma_client.db.query_raw(query=sql_query) + if response is not None: + if isinstance(response, list) and len(response) > 0: + total_spend = response[0].get("total_spend", 0.0) + + return {"spend": total_spend, "max_budget": litellm.max_budget} + + +@router.get( + "/global/spend/keys", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, +) +async def global_spend_keys( + limit: int = fastapi.Query( + default=None, + description="Number of keys to get. Will return Top 'n' keys.", + ) +): + """ + [BETA] This is a beta endpoint. It will change. + + Use this to get the top 'n' keys with the highest spend, ordered by spend. + """ + from litellm.proxy.proxy_server import prisma_client + + if prisma_client is None: + raise HTTPException(status_code=500, detail={"error": "No db connected"}) + sql_query = f"""SELECT * FROM "Last30dKeysBySpend" LIMIT {limit};""" + + response = await prisma_client.db.query_raw(query=sql_query) + + return response + + +@router.get( + "/global/spend/teams", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, +) +async def global_spend_per_team(): + """ + [BETA] This is a beta endpoint. It will change. + + Use this to get daily spend, grouped by `team_id` and `date` + """ + from litellm.proxy.proxy_server import prisma_client + + if prisma_client is None: + raise HTTPException(status_code=500, detail={"error": "No db connected"}) + sql_query = """ + SELECT + t.team_alias as team_alias, + DATE(s."startTime") AS spend_date, + SUM(s.spend) AS total_spend + FROM + "LiteLLM_SpendLogs" s + LEFT JOIN + "LiteLLM_TeamTable" t ON s.team_id = t.team_id + WHERE + s."startTime" >= CURRENT_DATE - INTERVAL '30 days' + GROUP BY + t.team_alias, + DATE(s."startTime") + ORDER BY + spend_date; + """ + response = await prisma_client.db.query_raw(query=sql_query) + + # transform the response for the Admin UI + spend_by_date = {} + team_aliases = set() + total_spend_per_team = {} + for row in response: + row_date = row["spend_date"] + if row_date is None: + continue + team_alias = row["team_alias"] + if team_alias is None: + team_alias = "Unassigned" + team_aliases.add(team_alias) + if row_date in spend_by_date: + # get the team_id for this entry + # get the spend for this entry + spend = row["total_spend"] + spend = round(spend, 2) + current_date_entries = spend_by_date[row_date] + current_date_entries[team_alias] = spend + else: + spend = row["total_spend"] + spend = round(spend, 2) + spend_by_date[row_date] = {team_alias: spend} + + if team_alias in total_spend_per_team: + total_spend_per_team[team_alias] += spend + else: + total_spend_per_team[team_alias] = spend + + total_spend_per_team_ui = [] + # order the elements in total_spend_per_team by spend + total_spend_per_team = dict( + sorted(total_spend_per_team.items(), key=lambda item: item[1], reverse=True) + ) + for team_id in total_spend_per_team: + # only add first 10 elements to total_spend_per_team_ui + if len(total_spend_per_team_ui) >= 10: + break + if team_id is None: + team_id = "Unassigned" + total_spend_per_team_ui.append( + {"team_id": team_id, "total_spend": total_spend_per_team[team_id]} + ) + + # sort spend_by_date by it's key (which is a date) + + response_data = [] + for key in spend_by_date: + value = spend_by_date[key] + response_data.append({"date": key, **value}) + + return { + "daily_spend": response_data, + "teams": list(team_aliases), + "total_spend_per_team": total_spend_per_team_ui, + } + + +@router.get( + "/global/all_end_users", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, +) +async def global_view_all_end_users(): + """ + [BETA] This is a beta endpoint. It will change. + + Use this to just get all the unique `end_users` + """ + from litellm.proxy.proxy_server import prisma_client + + if prisma_client is None: + raise HTTPException(status_code=500, detail={"error": "No db connected"}) + + sql_query = """ + SELECT DISTINCT end_user FROM "LiteLLM_SpendLogs" + """ + + db_response = await prisma_client.db.query_raw(query=sql_query) + if db_response is None: + return [] + + _end_users = [] + for row in db_response: + _end_users.append(row["end_user"]) + + return {"end_users": _end_users} + + +@router.post( + "/global/spend/end_users", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, +) +async def global_spend_end_users(data: Optional[GlobalEndUsersSpend] = None): + """ + [BETA] This is a beta endpoint. It will change. + + Use this to get the top 'n' keys with the highest spend, ordered by spend. + """ + from litellm.proxy.proxy_server import prisma_client + + if prisma_client is None: + raise HTTPException(status_code=500, detail={"error": "No db connected"}) + + """ + Gets the top 100 end-users for a given api key + """ + startTime = None + endTime = None + selected_api_key = None + if data is not None: + startTime = data.startTime + endTime = data.endTime + selected_api_key = data.api_key + + startTime = startTime or datetime.now() - timedelta(days=30) + endTime = endTime or datetime.now() + + sql_query = """ +SELECT end_user, COUNT(*) AS total_count, SUM(spend) AS total_spend +FROM "LiteLLM_SpendLogs" +WHERE "startTime" >= $1::timestamp + AND "startTime" < $2::timestamp + AND ( + CASE + WHEN $3::TEXT IS NULL THEN TRUE + ELSE api_key = $3 + END + ) +GROUP BY end_user +ORDER BY total_spend DESC +LIMIT 100 + """ + response = await prisma_client.db.query_raw( + sql_query, startTime, endTime, selected_api_key + ) + + return response + + +@router.get( + "/global/spend/models", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, +) +async def global_spend_models( + limit: int = fastapi.Query( + default=None, + description="Number of models to get. Will return Top 'n' models.", + ) +): + """ + [BETA] This is a beta endpoint. It will change. + + Use this to get the top 'n' keys with the highest spend, ordered by spend. + """ + from litellm.proxy.proxy_server import prisma_client + + if prisma_client is None: + raise HTTPException(status_code=500, detail={"error": "No db connected"}) + + sql_query = f"""SELECT * FROM "Last30dModelsBySpend" LIMIT {limit};""" + + response = await prisma_client.db.query_raw(query=sql_query) + + return response + + +@router.post( + "/global/predict/spend/logs", + tags=["Budget & Spend Tracking"], + dependencies=[Depends(user_api_key_auth)], + include_in_schema=False, +) +async def global_predict_spend_logs(request: Request): + from enterprise.utils import _forecast_daily_cost + + data = await request.json() + data = data.get("data") + return _forecast_daily_cost(data) diff --git a/litellm/proxy/utils.py b/litellm/proxy/utils.py index 54782c0887e..badc77546a2 100644 --- a/litellm/proxy/utils.py +++ b/litellm/proxy/utils.py @@ -1,4 +1,4 @@ -from typing import Optional, List, Any, Literal, Union, TYPE_CHECKING +from typing import Optional, List, Any, Literal, Union, TYPE_CHECKING, Tuple import os import subprocess import hashlib @@ -12,6 +12,8 @@ import litellm import backoff import traceback from pydantic import BaseModel +import litellm.litellm_core_utils +import litellm.litellm_core_utils.litellm_logging from litellm.proxy._types import ( UserAPIKeyAuth, DynamoDBArgs, @@ -162,8 +164,12 @@ class ProxyLogging: ## INITIALIZE LITELLM CALLBACKS ## self.call_details: dict = {} self.call_details["user_api_key_cache"] = user_api_key_cache - self.internal_usage_cache = DualCache() - self.max_parallel_request_limiter = _PROXY_MaxParallelRequestsHandler() + self.internal_usage_cache = DualCache( + default_in_memory_ttl=1 + ) # ping redis cache every 1s + self.max_parallel_request_limiter = _PROXY_MaxParallelRequestsHandler( + self.internal_usage_cache + ) self.max_budget_limiter = _PROXY_MaxBudgetLimiter() self.cache_control_check = _PROXY_CacheControlCheck() self.alerting: Optional[List] = None @@ -189,39 +195,45 @@ class ProxyLogging: def update_values( self, - alerting: Optional[List], - alerting_threshold: Optional[float], - redis_cache: Optional[RedisCache], + alerting: Optional[List] = None, + alerting_threshold: Optional[float] = None, + redis_cache: Optional[RedisCache] = None, alert_types: Optional[List[AlertType]] = None, alerting_args: Optional[dict] = None, ): - self.alerting = alerting + updated_slack_alerting: bool = False + if self.alerting is not None: + self.alerting = alerting + updated_slack_alerting = True if alerting_threshold is not None: self.alerting_threshold = alerting_threshold + updated_slack_alerting = True if alert_types is not None: self.alert_types = alert_types + updated_slack_alerting = True - self.slack_alerting_instance.update_values( - alerting=self.alerting, - alerting_threshold=self.alerting_threshold, - alert_types=self.alert_types, - alerting_args=alerting_args, - ) + if updated_slack_alerting is True: + self.slack_alerting_instance.update_values( + alerting=self.alerting, + alerting_threshold=self.alerting_threshold, + alert_types=self.alert_types, + alerting_args=alerting_args, + ) - if ( - self.alerting is not None - and "slack" in self.alerting - and "daily_reports" in self.alert_types - ): - # NOTE: ENSURE we only add callbacks when alerting is on - # We should NOT add callbacks when alerting is off - litellm.callbacks.append(self.slack_alerting_instance) # type: ignore + if ( + self.alerting is not None + and "slack" in self.alerting + and "daily_reports" in self.alert_types + ): + # NOTE: ENSURE we only add callbacks when alerting is on + # We should NOT add callbacks when alerting is off + litellm.callbacks.append(self.slack_alerting_instance) # type: ignore if redis_cache is not None: self.internal_usage_cache.redis_cache = redis_cache def _init_litellm_callbacks(self): - print_verbose(f"INITIALIZING LITELLM CALLBACKS!") + print_verbose("INITIALIZING LITELLM CALLBACKS!") self.service_logging_obj = ServiceLogging() litellm.callbacks.append(self.max_parallel_request_limiter) litellm.callbacks.append(self.max_budget_limiter) @@ -256,7 +268,9 @@ class ProxyLogging: + litellm.failure_callback ) ) - litellm.utils.set_callbacks(callback_list=callback_list) + litellm.litellm_core_utils.litellm_logging.set_callbacks( + callback_list=callback_list + ) # The actual implementation of the function async def pre_call_hook( @@ -321,7 +335,9 @@ class ProxyLogging: return data except Exception as e: if "litellm_logging_obj" in data: - logging_obj: litellm.utils.Logging = data["litellm_logging_obj"] + logging_obj: litellm.litellm_core_utils.litellm_logging.Logging = data[ + "litellm_logging_obj" + ] ## ASYNC FAILURE HANDLER ## error_message = "" @@ -445,6 +461,7 @@ class ProxyLogging: formatted_message += f"\n\nProxy URL: `{_proxy_base_url}`" extra_kwargs = {} + alerting_metadata = {} if request_data is not None: _url = self.slack_alerting_instance._add_langfuse_trace_id_to_alert( request_data=request_data @@ -452,7 +469,12 @@ class ProxyLogging: if _url is not None: extra_kwargs["🪢 Langfuse Trace"] = _url formatted_message += "\n\n🪢 Langfuse Trace: {}".format(_url) - + if ( + "metadata" in request_data + and request_data["metadata"].get("alerting_metadata", None) is not None + and isinstance(request_data["metadata"]["alerting_metadata"], dict) + ): + alerting_metadata = request_data["metadata"]["alerting_metadata"] for client in self.alerting: if client == "slack": await self.slack_alerting_instance.send_alert( @@ -460,6 +482,7 @@ class ProxyLogging: level=level, alert_type=alert_type, user_info=None, + alerting_metadata=alerting_metadata, **extra_kwargs, ) elif client == "sentry": @@ -500,7 +523,7 @@ class ProxyLogging: ) if hasattr(self, "service_logging_obj"): - self.service_logging_obj.async_service_failure_hook( + await self.service_logging_obj.async_service_failure_hook( service=ServiceTypes.DB, duration=duration, error=error_message, @@ -1950,6 +1973,9 @@ async def send_email(receiver_email, subject, html): email_message["From"] = sender_email email_message["To"] = receiver_email email_message["Subject"] = subject + verbose_proxy_logger.debug( + "sending email from %s to %s", sender_email, receiver_email + ) # Attach the body to the email email_message.attach(MIMEText(html, "html")) @@ -2093,14 +2119,42 @@ def get_logging_payload( raise e -def _duration_in_seconds(duration: str): - match = re.match(r"(\d+)([smhd]?)", duration) +def _extract_from_regex(duration: str) -> Tuple[int, str]: + match = re.match(r"(\d+)(mo|[smhd]?)", duration) + if not match: raise ValueError("Invalid duration format") value, unit = match.groups() value = int(value) + return value, unit + + +def get_last_day_of_month(year, month): + # Handle December case + if month == 12: + return 31 + # Next month is January, so subtract a day from March 1st + next_month = datetime(year=year, month=month + 1, day=1) + last_day_of_month = (next_month - timedelta(days=1)).day + return last_day_of_month + + +def _duration_in_seconds(duration: str) -> int: + """ + Parameters: + - duration: + - "s" - seconds + - "m" - minutes + - "h" - hours + - "d" - days + - "mo" - months + + Returns time in seconds till when budget needs to be reset + """ + value, unit = _extract_from_regex(duration=duration) + if unit == "s": return value elif unit == "m": @@ -2109,6 +2163,38 @@ def _duration_in_seconds(duration: str): return value * 3600 elif unit == "d": return value * 86400 + elif unit == "mo": + now = time.time() + current_time = datetime.fromtimestamp(now) + + if current_time.month == 12: + target_year = current_time.year + 1 + target_month = 1 + else: + target_year = current_time.year + target_month = current_time.month + value + + # Determine the day to set for next month + target_day = current_time.day + last_day_of_target_month = get_last_day_of_month(target_year, target_month) + + if target_day > last_day_of_target_month: + target_day = last_day_of_target_month + + next_month = datetime( + year=target_year, + month=target_month, + day=target_day, + hour=current_time.hour, + minute=current_time.minute, + second=current_time.second, + microsecond=current_time.microsecond, + ) + + # Calculate the duration until the first day of the next month + duration_until_next_month = next_month - current_time + return int(duration_until_next_month.total_seconds()) + else: raise ValueError("Unsupported duration unit") @@ -2674,47 +2760,6 @@ def _is_valid_team_configs(team_id=None, team_config=None, request_data=None): return -def _is_user_proxy_admin(user_id_information: Optional[list]): - if user_id_information is None: - return False - - if len(user_id_information) == 0 or user_id_information[0] is None: - return False - - _user = user_id_information[0] - if ( - _user.get("user_role", None) is not None - and _user.get("user_role") == LitellmUserRoles.PROXY_ADMIN.value - ): - return True - - # if user_id_information contains litellm-proxy-budget - # get first user_id that is not litellm-proxy-budget - for user in user_id_information: - if user.get("user_id") != "litellm-proxy-budget": - _user = user - break - - if ( - _user.get("user_role", None) is not None - and _user.get("user_role") == LitellmUserRoles.PROXY_ADMIN.value - ): - return True - - return False - - -def _get_user_role(user_id_information: Optional[list]): - if user_id_information is None: - return None - - if len(user_id_information) == 0 or user_id_information[0] is None: - return None - - _user = user_id_information[0] - return _user.get("user_role") - - def encrypt_value(value: str, master_key: str): import hashlib import nacl.secret diff --git a/litellm/router.py b/litellm/router.py index 4d7a36a3865..cd6c9c16eb1 100644 --- a/litellm/router.py +++ b/litellm/router.py @@ -66,6 +66,7 @@ from litellm.types.llms.openai import ( ) from litellm.scheduler import Scheduler, FlowItem from typing import Iterable +from litellm.router_utils.handle_error import send_llm_exception_alert class Router: @@ -108,6 +109,7 @@ class Router: ] = None, # generic fallbacks, works across all deployments fallbacks: List = [], context_window_fallbacks: List = [], + content_policy_fallbacks: List = [], model_group_alias: Optional[dict] = {}, enable_pre_call_checks: bool = False, retry_after: int = 0, # min time to wait before retrying a failed request @@ -311,6 +313,12 @@ class Router: self.context_window_fallbacks = ( context_window_fallbacks or litellm.context_window_fallbacks ) + + _content_policy_fallbacks = ( + content_policy_fallbacks or litellm.content_policy_fallbacks + ) + self.validate_fallbacks(fallback_param=_content_policy_fallbacks) + self.content_policy_fallbacks = _content_policy_fallbacks self.total_calls: defaultdict = defaultdict( int ) # dict to store total calls made to each model @@ -576,6 +584,14 @@ class Router: return response except Exception as e: + asyncio.create_task( + send_llm_exception_alert( + litellm_router_instance=self, + request_kwargs=kwargs, + error_traceback_str=traceback.format_exc(), + original_exception=e, + ) + ) raise e async def _acompletion( @@ -1097,6 +1113,14 @@ class Router: return response except Exception as e: + asyncio.create_task( + send_llm_exception_alert( + litellm_router_instance=self, + request_kwargs=kwargs, + error_traceback_str=traceback.format_exc(), + original_exception=e, + ) + ) raise e async def _aimage_generation(self, prompt: str, model: str, **kwargs): @@ -1221,6 +1245,14 @@ class Router: return response except Exception as e: + asyncio.create_task( + send_llm_exception_alert( + litellm_router_instance=self, + request_kwargs=kwargs, + error_traceback_str=traceback.format_exc(), + original_exception=e, + ) + ) raise e async def _atranscription(self, file: BinaryIO, model: str, **kwargs): @@ -1387,6 +1419,14 @@ class Router: return response except Exception as e: + asyncio.create_task( + send_llm_exception_alert( + litellm_router_instance=self, + request_kwargs=kwargs, + error_traceback_str=traceback.format_exc(), + original_exception=e, + ) + ) raise e async def amoderation(self, model: str, input: str, **kwargs): @@ -1402,6 +1442,14 @@ class Router: return response except Exception as e: + asyncio.create_task( + send_llm_exception_alert( + litellm_router_instance=self, + request_kwargs=kwargs, + error_traceback_str=traceback.format_exc(), + original_exception=e, + ) + ) raise e async def _amoderation(self, model: str, input: str, **kwargs): @@ -1546,6 +1594,14 @@ class Router: return response except Exception as e: + asyncio.create_task( + send_llm_exception_alert( + litellm_router_instance=self, + request_kwargs=kwargs, + error_traceback_str=traceback.format_exc(), + original_exception=e, + ) + ) raise e async def _atext_completion(self, model: str, prompt: str, **kwargs): @@ -1741,6 +1797,14 @@ class Router: response = await self.async_function_with_fallbacks(**kwargs) return response except Exception as e: + asyncio.create_task( + send_llm_exception_alert( + litellm_router_instance=self, + request_kwargs=kwargs, + error_traceback_str=traceback.format_exc(), + original_exception=e, + ) + ) raise e async def _aembedding(self, input: Union[str, List], model: str, **kwargs): @@ -1998,6 +2062,9 @@ class Router: context_window_fallbacks = kwargs.get( "context_window_fallbacks", self.context_window_fallbacks ) + content_policy_fallbacks = kwargs.get( + "content_policy_fallbacks", self.content_policy_fallbacks + ) try: if mock_testing_fallbacks is not None and mock_testing_fallbacks == True: raise Exception( @@ -2016,7 +2083,10 @@ class Router: if ( hasattr(e, "status_code") and e.status_code == 400 # type: ignore - and not isinstance(e, litellm.ContextWindowExceededError) + and not ( + isinstance(e, litellm.ContextWindowExceededError) + or isinstance(e, litellm.ContentPolicyViolationError) + ) ): # don't retry a malformed request raise e if ( @@ -2034,6 +2104,39 @@ class Router: if fallback_model_group is None: raise original_exception + for mg in fallback_model_group: + """ + Iterate through the model groups and try calling that deployment + """ + try: + kwargs["model"] = mg + kwargs.setdefault("metadata", {}).update( + {"model_group": mg} + ) # update model_group used, if fallbacks are done + response = await self.async_function_with_retries( + *args, **kwargs + ) + verbose_router_logger.info( + "Successful fallback b/w models." + ) + return response + except Exception as e: + pass + elif ( + isinstance(e, litellm.ContentPolicyViolationError) + and content_policy_fallbacks is not None + ): + fallback_model_group = None + for ( + item + ) in content_policy_fallbacks: # [{"gpt-3.5-turbo": ["gpt-4"]}] + if list(item.keys())[0] == model_group: + fallback_model_group = item[model_group] + break + + if fallback_model_group is None: + raise original_exception + for mg in fallback_model_group: """ Iterate through the model groups and try calling that deployment @@ -2114,6 +2217,9 @@ class Router: context_window_fallbacks = kwargs.pop( "context_window_fallbacks", self.context_window_fallbacks ) + content_policy_fallbacks = kwargs.pop( + "content_policy_fallbacks", self.content_policy_fallbacks + ) num_retries = kwargs.pop("num_retries") @@ -2141,6 +2247,7 @@ class Router: healthy_deployments=_healthy_deployments, context_window_fallbacks=context_window_fallbacks, regular_fallbacks=fallbacks, + content_policy_fallbacks=content_policy_fallbacks, ) # decides how long to sleep before retry @@ -2206,10 +2313,12 @@ class Router: error: Exception, healthy_deployments: Optional[List] = None, context_window_fallbacks: Optional[List] = None, + content_policy_fallbacks: Optional[List] = None, regular_fallbacks: Optional[List] = None, ): """ 1. raise an exception for ContextWindowExceededError if context_window_fallbacks is not None + 2. raise an exception for ContentPolicyViolationError if content_policy_fallbacks is not None 2. raise an exception for RateLimitError if - there are no fallbacks @@ -2219,13 +2328,19 @@ class Router: if healthy_deployments is not None and isinstance(healthy_deployments, list): _num_healthy_deployments = len(healthy_deployments) - ### CHECK IF RATE LIMIT / CONTEXT WINDOW ERROR w/ fallbacks available / Bad Request Error + ### CHECK IF RATE LIMIT / CONTEXT WINDOW ERROR / CONTENT POLICY VIOLATION ERROR w/ fallbacks available / Bad Request Error if ( isinstance(error, litellm.ContextWindowExceededError) and context_window_fallbacks is not None ): raise error + if ( + isinstance(error, litellm.ContentPolicyViolationError) + and content_policy_fallbacks is not None + ): + raise error + # Error we should only retry if there are other deployments if isinstance(error, openai.RateLimitError): if ( @@ -2256,6 +2371,9 @@ class Router: context_window_fallbacks = kwargs.get( "context_window_fallbacks", self.context_window_fallbacks ) + content_policy_fallbacks = kwargs.get( + "content_policy_fallbacks", self.content_policy_fallbacks + ) try: if mock_testing_fallbacks is not None and mock_testing_fallbacks == True: raise Exception( @@ -2271,7 +2389,10 @@ class Router: if ( hasattr(e, "status_code") and e.status_code == 400 # type: ignore - and not isinstance(e, litellm.ContextWindowExceededError) + and not ( + isinstance(e, litellm.ContextWindowExceededError) + or isinstance(e, litellm.ContentPolicyViolationError) + ) ): # don't retry a malformed request raise e @@ -2294,6 +2415,37 @@ class Router: if fallback_model_group is None: raise original_exception + for mg in fallback_model_group: + """ + Iterate through the model groups and try calling that deployment + """ + try: + ## LOGGING + kwargs = self.log_retry(kwargs=kwargs, e=original_exception) + kwargs["model"] = mg + kwargs.setdefault("metadata", {}).update( + {"model_group": mg} + ) # update model_group used, if fallbacks are done + response = self.function_with_fallbacks(*args, **kwargs) + return response + except Exception as e: + pass + elif ( + isinstance(e, litellm.ContentPolicyViolationError) + and content_policy_fallbacks is not None + ): + fallback_model_group = None + + for ( + item + ) in content_policy_fallbacks: # [{"gpt-3.5-turbo": ["gpt-4"]}] + if list(item.keys())[0] == model_group: + fallback_model_group = item[model_group] + break + + if fallback_model_group is None: + raise original_exception + for mg in fallback_model_group: """ Iterate through the model groups and try calling that deployment @@ -2400,6 +2552,9 @@ class Router: context_window_fallbacks = kwargs.pop( "context_window_fallbacks", self.context_window_fallbacks ) + content_policy_fallbacks = kwargs.pop( + "content_policy_fallbacks", self.content_policy_fallbacks + ) try: # if the function call is successful, no exception will be raised and we'll break out of the loop @@ -2419,6 +2574,7 @@ class Router: healthy_deployments=_healthy_deployments, context_window_fallbacks=context_window_fallbacks, regular_fallbacks=fallbacks, + content_policy_fallbacks=content_policy_fallbacks, ) # decides how long to sleep before retry @@ -4570,6 +4726,8 @@ class Router: default_webhook_url=router_alerting_config.webhook_url, ) + self.slack_alerting_logger = _slack_alerting_logger + litellm.callbacks.append(_slack_alerting_logger) litellm.success_callback.append( _slack_alerting_logger.response_taking_too_long_callback diff --git a/litellm/router_utils/handle_error.py b/litellm/router_utils/handle_error.py new file mode 100644 index 00000000000..d848fd82b10 --- /dev/null +++ b/litellm/router_utils/handle_error.py @@ -0,0 +1,53 @@ +import asyncio +import traceback +from typing import TYPE_CHECKING, Any + +if TYPE_CHECKING: + from litellm.router import Router as _Router + + LitellmRouter = _Router +else: + LitellmRouter = Any + + +async def send_llm_exception_alert( + litellm_router_instance: LitellmRouter, + request_kwargs: dict, + error_traceback_str: str, + original_exception, +): + """ + Sends a Slack / MS Teams alert for the LLM API call failure. + + Parameters: + litellm_router_instance (_Router): The LitellmRouter instance. + original_exception (Any): The original exception that occurred. + + Returns: + None + """ + if litellm_router_instance is None: + return + + if not hasattr(litellm_router_instance, "slack_alerting_logger"): + return + + if litellm_router_instance.slack_alerting_logger is None: + return + + if "proxy_server_request" in request_kwargs: + # Do not send any alert if it's a request from litellm proxy server request + # the proxy is already instrumented to send LLM API call failures + return + + litellm_debug_info = getattr(original_exception, "litellm_debug_info", None) + exception_str = str(original_exception) + if litellm_debug_info is not None: + exception_str += litellm_debug_info + exception_str += f"\n\n{error_traceback_str[:2000]}" + + await litellm_router_instance.slack_alerting_logger.send_alert( + message=f"LLM API call failed: `{exception_str}`", + level="High", + alert_type="llm_exceptions", + ) diff --git a/litellm/tests/test_alerting.py b/litellm/tests/test_alerting.py index 9dfec3dcfab..643b59cc1ee 100644 --- a/litellm/tests/test_alerting.py +++ b/litellm/tests/test_alerting.py @@ -25,6 +25,9 @@ import pytest from litellm.router import AlertingConfig, Router from litellm.proxy._types import CallInfo from openai import APIError +from litellm.router import AlertingConfig +import litellm +import os @pytest.mark.parametrize( @@ -159,6 +162,29 @@ async def test_response_taking_too_long_callback(slack_alerting): mock_send_alert.assert_awaited_once() +@pytest.mark.asyncio +async def test_alerting_metadata(slack_alerting): + """ + Test alerting_metadata is propogated correctly for response taking too long + """ + start_time = datetime.now() + end_time = start_time + timedelta(seconds=301) + kwargs = { + "model": "test_model", + "messages": "test_messages", + "litellm_params": {"metadata": {"alerting_metadata": {"hello": "world"}}}, + } + with patch.object(slack_alerting, "send_alert", new=AsyncMock()) as mock_send_alert: + + ## RESPONSE TAKING TOO LONG + await slack_alerting.response_taking_too_long_callback( + kwargs, None, start_time, end_time + ) + mock_send_alert.assert_awaited_once() + + assert "hello" in mock_send_alert.call_args[1]["alerting_metadata"] + + # Test for budget crossed @pytest.mark.asyncio async def test_budget_alerts_crossed(slack_alerting): @@ -204,7 +230,9 @@ async def test_send_alert(slack_alerting): slack_alerting.async_http_handler, "post", new=AsyncMock() ) as mock_post: mock_post.return_value.status_code = 200 - await slack_alerting.send_alert("Test message", "Low", "budget_alerts") + await slack_alerting.send_alert( + "Test message", "Low", "budget_alerts", alerting_metadata={} + ) mock_post.assert_awaited_once() @@ -263,7 +291,7 @@ async def test_daily_reports_completion(slack_alerting): await asyncio.sleep(3) response_val = await slack_alerting.send_daily_reports(router=router) - assert response_val == True + assert response_val is True mock_send_alert.assert_awaited_once() @@ -288,7 +316,7 @@ async def test_daily_reports_completion(slack_alerting): await asyncio.sleep(3) response_val = await slack_alerting.send_daily_reports(router=router) - assert response_val == True + assert response_val is True mock_send_alert.assert_awaited() @@ -743,3 +771,37 @@ async def test_region_outage_alerting_called( mock_send_alert.assert_called_once() else: mock_send_alert.assert_not_called() + + +@pytest.mark.asyncio +@pytest.mark.skip(reason="test only needs to run locally ") +async def test_alerting(): + router = litellm.Router( + model_list=[ + { + "model_name": "gpt-3.5-turbo", + "litellm_params": { + "model": "gpt-3.5-turbo", + "api_key": "bad_key", + }, + } + ], + debug_level="DEBUG", + set_verbose=True, + alerting_config=AlertingConfig( + alerting_threshold=10, # threshold for slow / hanging llm responses (in seconds). Defaults to 300 seconds + webhook_url=os.getenv( + "SLACK_WEBHOOK_URL" + ), # webhook you want to send alerts to + ), + ) + try: + await router.acompletion( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "Hey, how's it going?"}], + ) + + except: + pass + finally: + await asyncio.sleep(3) diff --git a/litellm/tests/test_blocked_user_list.py b/litellm/tests/test_blocked_user_list.py index 3c277a2d48d..f49084d03b4 100644 --- a/litellm/tests/test_blocked_user_list.py +++ b/litellm/tests/test_blocked_user_list.py @@ -29,19 +29,22 @@ import pytest, logging, asyncio import litellm, asyncio from litellm.proxy.proxy_server import ( new_user, - generate_key_fn, user_api_key_auth, user_update, + user_info, + block_user, +) +from litellm.proxy.management_endpoints.key_management_endpoints import ( delete_key_fn, info_key_fn, update_key_fn, generate_key_fn, generate_key_helper_fn, +) +from litellm.proxy.spend_reporting_endpoints.spend_management_endpoints import ( spend_user_fn, spend_key_fn, view_spend_logs, - user_info, - block_user, ) from litellm.proxy.utils import PrismaClient, ProxyLogging, hash_token from litellm._logging import verbose_proxy_logger diff --git a/litellm/tests/test_completion.py b/litellm/tests/test_completion.py index 1e9014ef4a6..91144684660 100644 --- a/litellm/tests/test_completion.py +++ b/litellm/tests/test_completion.py @@ -16,7 +16,7 @@ from litellm.llms.prompt_templates.factory import anthropic_messages_pt from unittest.mock import patch, MagicMock from litellm.llms.custom_httpx.http_handler import HTTPHandler, AsyncHTTPHandler -# litellm.num_retries = 3 +# litellm.num_retries =3 litellm.cache = None litellm.success_callback = [] user_message = "Write a short poem about the sky" diff --git a/litellm/tests/test_completion_cost.py b/litellm/tests/test_completion_cost.py index c0be350f919..3f728885474 100644 --- a/litellm/tests/test_completion_cost.py +++ b/litellm/tests/test_completion_cost.py @@ -13,7 +13,7 @@ from litellm import ( open_ai_chat_completion_models, TranscriptionResponse, ) -from litellm.utils import CustomLogger +from litellm.litellm_core_utils.litellm_logging import CustomLogger import pytest, asyncio diff --git a/litellm/tests/test_get_model_info.py b/litellm/tests/test_get_model_info.py index ec6843df80b..3fd6a6d22f6 100644 --- a/litellm/tests/test_get_model_info.py +++ b/litellm/tests/test_get_model_info.py @@ -7,6 +7,7 @@ sys.path.insert( ) # Adds the parent directory to the system path import litellm from litellm import get_model_info +import pytest def test_get_model_info_simple_model_name(): @@ -23,3 +24,16 @@ def test_get_model_info_custom_llm_with_model_name(): """ model = "anthropic/claude-3-opus-20240229" litellm.get_model_info(model) + + +def test_get_model_info_custom_llm_with_same_name_vllm(): + """ + Tests if {custom_llm_provider}/{model_name} name given, and model exists in model info, the object is returned + """ + model = "command-r-plus" + provider = "openai" # vllm is openai-compatible + try: + litellm.get_model_info(model, custom_llm_provider=provider) + pytest.fail("Expected get model info to fail for an unmapped model/provider") + except Exception: + pass diff --git a/litellm/tests/test_jwt.py b/litellm/tests/test_jwt.py index 17de5729118..a2edbcc2f86 100644 --- a/litellm/tests/test_jwt.py +++ b/litellm/tests/test_jwt.py @@ -14,6 +14,7 @@ sys.path.insert( import pytest from litellm.proxy._types import LiteLLM_JWTAuth, LiteLLMRoutes from litellm.proxy.auth.handle_jwt import JWTHandler +from litellm.proxy.management_endpoints.team_endpoints import new_team from litellm.caching import DualCache from datetime import datetime, timedelta from fastapi import Request @@ -218,7 +219,7 @@ async def test_team_token_output(prisma_client, audience): from cryptography.hazmat.backends import default_backend from fastapi import Request from starlette.datastructures import URL - from litellm.proxy.proxy_server import user_api_key_auth, new_team + from litellm.proxy.proxy_server import user_api_key_auth from litellm.proxy._types import NewTeamRequest, UserAPIKeyAuth import litellm import uuid @@ -399,7 +400,6 @@ async def test_user_token_output( from starlette.datastructures import URL from litellm.proxy.proxy_server import ( user_api_key_auth, - new_team, new_user, user_info, ) @@ -623,7 +623,7 @@ async def test_allowed_routes_admin(prisma_client, audience): from cryptography.hazmat.backends import default_backend from fastapi import Request from starlette.datastructures import URL - from litellm.proxy.proxy_server import user_api_key_auth, new_team + from litellm.proxy.proxy_server import user_api_key_auth from litellm.proxy._types import NewTeamRequest, UserAPIKeyAuth import litellm import uuid diff --git a/litellm/tests/test_key_generate_prisma.py b/litellm/tests/test_key_generate_prisma.py index 21ffbdb5470..cf93cfae911 100644 --- a/litellm/tests/test_key_generate_prisma.py +++ b/litellm/tests/test_key_generate_prisma.py @@ -38,22 +38,9 @@ import pytest, logging, asyncio import litellm, asyncio from litellm.proxy.proxy_server import ( new_user, - generate_key_fn, user_api_key_auth, user_update, - delete_key_fn, - info_key_fn, - update_key_fn, - generate_key_fn, - generate_key_helper_fn, - spend_user_fn, - spend_key_fn, - view_spend_logs, user_info, - team_info, - info_key_fn, - new_team, - update_team, chat_completion, completion, embeddings, @@ -63,6 +50,23 @@ from litellm.proxy.proxy_server import ( model_list, LitellmUserRoles, ) +from litellm.proxy.management_endpoints.key_management_endpoints import ( + delete_key_fn, + info_key_fn, + update_key_fn, + generate_key_fn, + generate_key_helper_fn, +) +from litellm.proxy.management_endpoints.team_endpoints import ( + team_info, + new_team, + update_team, +) +from litellm.proxy.spend_reporting_endpoints.spend_management_endpoints import ( + spend_user_fn, + spend_key_fn, + view_spend_logs, +) from litellm.proxy.utils import PrismaClient, ProxyLogging, hash_token, update_spend from litellm._logging import verbose_proxy_logger @@ -1779,7 +1783,7 @@ async def test_upperbound_key_params(prisma_client): def test_get_bearer_token(): - from litellm.proxy.proxy_server import _get_bearer_token + from litellm.proxy.auth.user_api_key_auth import _get_bearer_token # Test valid Bearer token api_key = "Bearer valid_token" @@ -2217,6 +2221,7 @@ async def test_create_update_team(prisma_client): tpm_limit=30, rpm_limit=30, ), + http_request=Request(scope={"type": "http"}), user_api_key_dict=UserAPIKeyAuth( user_role=LitellmUserRoles.PROXY_ADMIN, api_key="sk-1234", @@ -2308,3 +2313,4 @@ async def test_enforced_params(prisma_client): "Authentication Error, BadRequest please pass param=[metadata][generation_name] in request body" in e.message ) + general_settings.pop("enforced_params") diff --git a/litellm/tests/test_parallel_request_limiter.py b/litellm/tests/test_parallel_request_limiter.py index 94652c2a674..06817fa87b9 100644 --- a/litellm/tests/test_parallel_request_limiter.py +++ b/litellm/tests/test_parallel_request_limiter.py @@ -40,7 +40,9 @@ async def test_global_max_parallel_requests(): _api_key = hash_token("sk-12345") user_api_key_dict = UserAPIKeyAuth(api_key=_api_key, max_parallel_requests=100) local_cache = DualCache() - parallel_request_handler = MaxParallelRequestsHandler() + parallel_request_handler = MaxParallelRequestsHandler( + internal_usage_cache=local_cache + ) for _ in range(3): try: @@ -68,7 +70,9 @@ async def test_pre_call_hook(): _api_key = hash_token("sk-12345") user_api_key_dict = UserAPIKeyAuth(api_key=_api_key, max_parallel_requests=1) local_cache = DualCache() - parallel_request_handler = MaxParallelRequestsHandler() + parallel_request_handler = MaxParallelRequestsHandler( + internal_usage_cache=local_cache + ) await parallel_request_handler.async_pre_call_hook( user_api_key_dict=user_api_key_dict, cache=local_cache, data={}, call_type="" @@ -81,10 +85,12 @@ async def test_pre_call_hook(): request_count_api_key = f"{_api_key}::{precise_minute}::request_count" print( - parallel_request_handler.user_api_key_cache.get_cache(key=request_count_api_key) + parallel_request_handler.internal_usage_cache.get_cache( + key=request_count_api_key + ) ) assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_requests"] == 1 @@ -101,7 +107,9 @@ async def test_pre_call_hook_rpm_limits(): api_key=_api_key, max_parallel_requests=1, tpm_limit=9, rpm_limit=1 ) local_cache = DualCache() - parallel_request_handler = MaxParallelRequestsHandler() + parallel_request_handler = MaxParallelRequestsHandler( + internal_usage_cache=local_cache + ) await parallel_request_handler.async_pre_call_hook( user_api_key_dict=user_api_key_dict, cache=local_cache, data={}, call_type="" @@ -148,7 +156,9 @@ async def test_pre_call_hook_team_rpm_limits(): team_id=_team_id, ) local_cache = DualCache() - parallel_request_handler = MaxParallelRequestsHandler() + parallel_request_handler = MaxParallelRequestsHandler( + internal_usage_cache=local_cache + ) await parallel_request_handler.async_pre_call_hook( user_api_key_dict=user_api_key_dict, cache=local_cache, data={}, call_type="" @@ -194,7 +204,9 @@ async def test_pre_call_hook_tpm_limits(): api_key=_api_key, max_parallel_requests=1, tpm_limit=9, rpm_limit=10 ) local_cache = DualCache() - parallel_request_handler = MaxParallelRequestsHandler() + parallel_request_handler = MaxParallelRequestsHandler( + internal_usage_cache=local_cache + ) await parallel_request_handler.async_pre_call_hook( user_api_key_dict=user_api_key_dict, cache=local_cache, data={}, call_type="" @@ -244,7 +256,9 @@ async def test_pre_call_hook_user_tpm_limits(): res = dict(user_api_key_dict) print("dict user", res) - parallel_request_handler = MaxParallelRequestsHandler() + parallel_request_handler = MaxParallelRequestsHandler( + internal_usage_cache=local_cache + ) await parallel_request_handler.async_pre_call_hook( user_api_key_dict=user_api_key_dict, cache=local_cache, data={}, call_type="" @@ -287,7 +301,9 @@ async def test_success_call_hook(): _api_key = hash_token("sk-12345") user_api_key_dict = UserAPIKeyAuth(api_key=_api_key, max_parallel_requests=1) local_cache = DualCache() - parallel_request_handler = MaxParallelRequestsHandler() + parallel_request_handler = MaxParallelRequestsHandler( + internal_usage_cache=local_cache + ) await parallel_request_handler.async_pre_call_hook( user_api_key_dict=user_api_key_dict, cache=local_cache, data={}, call_type="" @@ -300,7 +316,7 @@ async def test_success_call_hook(): request_count_api_key = f"{_api_key}::{precise_minute}::request_count" assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_requests"] == 1 @@ -313,7 +329,7 @@ async def test_success_call_hook(): ) assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_requests"] == 0 @@ -329,7 +345,9 @@ async def test_failure_call_hook(): _api_key = hash_token(_api_key) user_api_key_dict = UserAPIKeyAuth(api_key=_api_key, max_parallel_requests=1) local_cache = DualCache() - parallel_request_handler = MaxParallelRequestsHandler() + parallel_request_handler = MaxParallelRequestsHandler( + internal_usage_cache=local_cache + ) await parallel_request_handler.async_pre_call_hook( user_api_key_dict=user_api_key_dict, cache=local_cache, data={}, call_type="" @@ -342,7 +360,7 @@ async def test_failure_call_hook(): request_count_api_key = f"{_api_key}::{precise_minute}::request_count" assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_requests"] == 1 @@ -358,7 +376,7 @@ async def test_failure_call_hook(): ) assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_requests"] == 0 @@ -423,7 +441,7 @@ async def test_normal_router_call(): request_count_api_key = f"{_api_key}::{precise_minute}::request_count" assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_requests"] == 1 @@ -440,7 +458,7 @@ async def test_normal_router_call(): print(f"response: {response}") assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_requests"] == 0 @@ -504,7 +522,7 @@ async def test_normal_router_tpm_limit(): print("Test: Checking current_requests for precise_minute=", precise_minute) assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_requests"] == 1 @@ -522,7 +540,7 @@ async def test_normal_router_tpm_limit(): try: assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_tpm"] > 0 @@ -583,7 +601,7 @@ async def test_streaming_router_call(): request_count_api_key = f"{_api_key}::{precise_minute}::request_count" assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_requests"] == 1 @@ -601,7 +619,7 @@ async def test_streaming_router_call(): continue await asyncio.sleep(1) # success is done in a separate thread assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_requests"] == 0 @@ -661,7 +679,7 @@ async def test_streaming_router_tpm_limit(): request_count_api_key = f"{_api_key}::{precise_minute}::request_count" assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_requests"] == 1 @@ -680,7 +698,7 @@ async def test_streaming_router_tpm_limit(): await asyncio.sleep(5) # success is done in a separate thread assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_tpm"] > 0 @@ -738,7 +756,7 @@ async def test_bad_router_call(): request_count_api_key = f"{_api_key}::{precise_minute}::request_count" assert ( - parallel_request_handler.user_api_key_cache.get_cache( # type: ignore + parallel_request_handler.internal_usage_cache.get_cache( # type: ignore key=request_count_api_key )["current_requests"] == 1 @@ -755,7 +773,7 @@ async def test_bad_router_call(): except: pass assert ( - parallel_request_handler.user_api_key_cache.get_cache( # type: ignore + parallel_request_handler.internal_usage_cache.get_cache( # type: ignore key=request_count_api_key )["current_requests"] == 0 @@ -814,7 +832,7 @@ async def test_bad_router_tpm_limit(): request_count_api_key = f"{_api_key}::{precise_minute}::request_count" assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_requests"] == 1 @@ -833,7 +851,7 @@ async def test_bad_router_tpm_limit(): await asyncio.sleep(1) # success is done in a separate thread assert ( - parallel_request_handler.user_api_key_cache.get_cache( + parallel_request_handler.internal_usage_cache.get_cache( key=request_count_api_key )["current_tpm"] == 0 diff --git a/litellm/tests/test_proxy_server.py b/litellm/tests/test_proxy_server.py index 114b96872f6..d8bfb522975 100644 --- a/litellm/tests/test_proxy_server.py +++ b/litellm/tests/test_proxy_server.py @@ -26,7 +26,7 @@ logging.basicConfig( from fastapi.testclient import TestClient from fastapi import FastAPI from litellm.proxy.proxy_server import ( - router, + app, save_worker_config, initialize, ) # Replace with the actual module where your FastAPI router is defined @@ -119,9 +119,6 @@ def client_no_auth(fake_env_vars): config_fp = f"{filepath}/test_configs/test_config_no_auth.yaml" # initialize can get run in parallel, it sets specific variables for the fast api app, sinc eit gets run in parallel different tests use the wrong variables asyncio.run(initialize(config=config_fp, debug=True)) - app = FastAPI() - app.include_router(router) # Include your router in the test app - return TestClient(app) @@ -426,6 +423,10 @@ def test_add_new_model(client_no_auth): def test_health(client_no_auth): global headers import time + from litellm._logging import verbose_logger, verbose_proxy_logger + import logging + + verbose_proxy_logger.setLevel(logging.DEBUG) try: response = client_no_auth.get("/health") diff --git a/litellm/tests/test_router_debug_logs.py b/litellm/tests/test_router_debug_logs.py index c01b6eecb98..09590e5ac66 100644 --- a/litellm/tests/test_router_debug_logs.py +++ b/litellm/tests/test_router_debug_logs.py @@ -81,7 +81,7 @@ def test_async_fallbacks(caplog): # Define the expected log messages # - error request, falling back notice, success notice expected_logs = [ - "litellm.acompletion(model=gpt-3.5-turbo)\x1b[31m Exception AuthenticationError: OpenAIException - Error code: 401 - {'error': {'message': 'Incorrect API key provided: bad-key. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}\x1b[0m", + "litellm.acompletion(model=gpt-3.5-turbo)\x1b[31m Exception litellm.AuthenticationError: AuthenticationError: OpenAIException - Error code: 401 - {'error': {'message': 'Incorrect API key provided: bad-key. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}}\x1b[0m", "Falling back to model_group = azure/gpt-3.5-turbo", "litellm.acompletion(model=azure/chatgpt-v-2)\x1b[32m 200 OK\x1b[0m", "Successful fallback b/w models.", diff --git a/litellm/tests/test_router_fallbacks.py b/litellm/tests/test_router_fallbacks.py index c6e0e541115..545eb23db3a 100644 --- a/litellm/tests/test_router_fallbacks.py +++ b/litellm/tests/test_router_fallbacks.py @@ -1109,3 +1109,59 @@ async def test_client_side_fallbacks_list(sync_mode): assert isinstance(response, litellm.ModelResponse) assert response.model is not None and response.model == "gpt-4o" + + +@pytest.mark.parametrize("sync_mode", [True, False]) +@pytest.mark.asyncio +async def test_router_content_policy_fallbacks(sync_mode): + os.environ["LITELLM_LOG"] = "DEBUG" + router = Router( + model_list=[ + { + "model_name": "claude-2", + "litellm_params": { + "model": "claude-2", + "api_key": "", + "mock_response": Exception("content filtering policy"), + }, + }, + { + "model_name": "my-fallback-model", + "litellm_params": { + "model": "claude-2", + "api_key": "", + "mock_response": "This works!", + }, + }, + { + "model_name": "my-general-model", + "litellm_params": { + "model": "claude-2", + "api_key": "", + "mock_response": Exception("Should not have called this."), + }, + }, + { + "model_name": "my-context-window-model", + "litellm_params": { + "model": "claude-2", + "api_key": "", + "mock_response": Exception("Should not have called this."), + }, + }, + ], + content_policy_fallbacks=[{"claude-2": ["my-fallback-model"]}], + fallbacks=[{"claude-2": ["my-general-model"]}], + context_window_fallbacks=[{"claude-2": ["my-context-window-model"]}], + ) + + if sync_mode is True: + response = router.completion( + model="claude-2", + messages=[{"role": "user", "content": "Hey, how's it going?"}], + ) + else: + response = await router.acompletion( + model="claude-2", + messages=[{"role": "user", "content": "Hey, how's it going?"}], + ) diff --git a/litellm/tests/test_spend_logs.py b/litellm/tests/test_spend_logs.py index 0a02edc88c8..b56bb5e2e40 100644 --- a/litellm/tests/test_spend_logs.py +++ b/litellm/tests/test_spend_logs.py @@ -63,7 +63,7 @@ def test_spend_logs_payload(): "user_api_key_team_id": None, "user_api_key_team_alias": None, "user_api_key_metadata": {}, - "spend_logs_metadata": {}, + "spend_logs_metadata": {"hello": "world"}, "headers": { "content-type": "application/json", "user-agent": "PostmanRuntime/7.32.3", diff --git a/litellm/tests/test_update_spend.py b/litellm/tests/test_update_spend.py index 529e90e3c8b..d4f5662e13a 100644 --- a/litellm/tests/test_update_spend.py +++ b/litellm/tests/test_update_spend.py @@ -26,19 +26,22 @@ import pytest, logging, asyncio import litellm, asyncio from litellm.proxy.proxy_server import ( new_user, - generate_key_fn, user_api_key_auth, user_update, + user_info, + block_user, +) +from litellm.proxy.spend_reporting_endpoints.spend_management_endpoints import ( + spend_user_fn, + spend_key_fn, + view_spend_logs, +) +from litellm.proxy.management_endpoints.key_management_endpoints import ( delete_key_fn, info_key_fn, update_key_fn, generate_key_fn, generate_key_helper_fn, - spend_user_fn, - spend_key_fn, - view_spend_logs, - user_info, - block_user, ) from litellm.proxy.utils import PrismaClient, ProxyLogging, hash_token, update_spend from litellm._logging import verbose_proxy_logger diff --git a/litellm/tests/test_utils.py b/litellm/tests/test_utils.py index 491283eeda8..bf84ba994dd 100644 --- a/litellm/tests/test_utils.py +++ b/litellm/tests/test_utils.py @@ -3,6 +3,7 @@ from unittest import mock from dotenv import load_dotenv import copy +from datetime import datetime load_dotenv() import os @@ -25,6 +26,11 @@ from litellm.utils import ( get_max_tokens, get_supported_openai_params, ) +from litellm.proxy.utils import ( + _duration_in_seconds, + _extract_from_regex, + get_last_day_of_month, +) # Assuming your trim_messages, shorten_message_to_fit_limit, and get_token_count functions are all in a module named 'message_utils' @@ -395,3 +401,105 @@ def test_get_supported_openai_params() -> None: # Unmapped provider assert get_supported_openai_params("nonexistent") is None + + +def test_redact_msgs_from_logs(): + """ + Tests that turn_off_message_logging does not modify the response_obj + + On the proxy some users were seeing the redaction impact client side responses + """ + from litellm.litellm_core_utils.redact_messages import ( + redact_message_input_output_from_logging, + ) + from litellm.litellm_core_utils.litellm_logging import Logging + + litellm.turn_off_message_logging = True + + response_obj = litellm.ModelResponse( + choices=[ + { + "finish_reason": "stop", + "index": 0, + "message": { + "content": "I'm LLaMA, an AI assistant developed by Meta AI that can understand and respond to human input in a conversational manner.", + "role": "assistant", + }, + } + ] + ) + + _redacted_response_obj = redact_message_input_output_from_logging( + result=response_obj, + litellm_logging_obj=Logging( + model="gpt-3.5-turbo", + messages=[{"role": "user", "content": "hi"}], + stream=False, + call_type="acompletion", + litellm_call_id="1234", + start_time=datetime.now(), + function_id="1234", + ), + ) + + # Assert the response_obj content is NOT modified + assert ( + response_obj.choices[0].message.content + == "I'm LLaMA, an AI assistant developed by Meta AI that can understand and respond to human input in a conversational manner." + ) + + litellm.turn_off_message_logging = False + print("Test passed") + + +@pytest.mark.parametrize( + "duration, unit", + [("7s", "s"), ("7m", "m"), ("7h", "h"), ("7d", "d"), ("7mo", "mo")], +) +def test_extract_from_regex(duration, unit): + value, _unit = _extract_from_regex(duration=duration) + + assert value == 7 + assert _unit == unit + + +def test_duration_in_seconds(): + """ + Test if duration int is correctly calculated for different str + """ + import time + + now = time.time() + current_time = datetime.fromtimestamp(now) + + if current_time.month == 12: + target_year = current_time.year + 1 + target_month = 1 + else: + target_year = current_time.year + target_month = current_time.month + 1 + + # Determine the day to set for next month + target_day = current_time.day + last_day_of_target_month = get_last_day_of_month(target_year, target_month) + + if target_day > last_day_of_target_month: + target_day = last_day_of_target_month + + next_month = datetime( + year=target_year, + month=target_month, + day=target_day, + hour=current_time.hour, + minute=current_time.minute, + second=current_time.second, + microsecond=current_time.microsecond, + ) + + # Calculate the duration until the first day of the next month + duration_until_next_month = next_month - current_time + expected_duration = int(duration_until_next_month.total_seconds()) + + value = _duration_in_seconds(duration="1mo") + + assert value - expected_duration < 2 diff --git a/litellm/types/utils.py b/litellm/types/utils.py index 1fbb375d309..29d21143e15 100644 --- a/litellm/types/utils.py +++ b/litellm/types/utils.py @@ -3,6 +3,16 @@ from typing_extensions import TypedDict from enum import Enum from typing_extensions import override, Required, Dict from .llms.openai import ChatCompletionUsageBlock, ChatCompletionToolCallChunk +from ..litellm_core_utils.core_helpers import map_finish_reason +from openai._models import BaseModel as OpenAIObject +from pydantic import ConfigDict +import uuid +import json +import time + + +def _generate_id(): # private helper function + return "chatcmpl-" + str(uuid.uuid4()) class LiteLLMCommonStrings(Enum): @@ -48,3 +58,904 @@ class GenericStreamingChunk(TypedDict): finish_reason: Required[str] usage: Optional[ChatCompletionUsageBlock] index: int + + +from enum import Enum + + +class CallTypes(Enum): + embedding = "embedding" + aembedding = "aembedding" + completion = "completion" + acompletion = "acompletion" + atext_completion = "atext_completion" + text_completion = "text_completion" + image_generation = "image_generation" + aimage_generation = "aimage_generation" + moderation = "moderation" + amoderation = "amoderation" + atranscription = "atranscription" + transcription = "transcription" + aspeech = "aspeech" + speech = "speech" + + +class TopLogprob(OpenAIObject): + token: str + """The token.""" + + bytes: Optional[List[int]] = None + """A list of integers representing the UTF-8 bytes representation of the token. + + Useful in instances where characters are represented by multiple tokens and + their byte representations must be combined to generate the correct text + representation. Can be `null` if there is no bytes representation for the token. + """ + + logprob: float + """The log probability of this token, if it is within the top 20 most likely + tokens. + + Otherwise, the value `-9999.0` is used to signify that the token is very + unlikely. + """ + + +class ChatCompletionTokenLogprob(OpenAIObject): + token: str + """The token.""" + + bytes: Optional[List[int]] = None + """A list of integers representing the UTF-8 bytes representation of the token. + + Useful in instances where characters are represented by multiple tokens and + their byte representations must be combined to generate the correct text + representation. Can be `null` if there is no bytes representation for the token. + """ + + logprob: float + """The log probability of this token, if it is within the top 20 most likely + tokens. + + Otherwise, the value `-9999.0` is used to signify that the token is very + unlikely. + """ + + top_logprobs: List[TopLogprob] + """List of the most likely tokens and their log probability, at this token + position. + + In rare cases, there may be fewer than the number of requested `top_logprobs` + returned. + """ + + +class ChoiceLogprobs(OpenAIObject): + content: Optional[List[ChatCompletionTokenLogprob]] = None + """A list of message content tokens with log probability information.""" + + +class FunctionCall(OpenAIObject): + arguments: str + name: Optional[str] = None + + +class Function(OpenAIObject): + arguments: str + name: Optional[str] = None + + def __init__( + self, + arguments: Union[Dict, str], + name: Optional[str] = None, + **params, + ): + if isinstance(arguments, Dict): + arguments = json.dumps(arguments) + else: + arguments = arguments + + name = name + + # Build a dictionary with the structure your BaseModel expects + data = {"arguments": arguments, "name": name, **params} + + super(Function, self).__init__(**data) + + def __contains__(self, key): + # Define custom behavior for the 'in' operator + return hasattr(self, key) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + +class ChatCompletionDeltaToolCall(OpenAIObject): + id: Optional[str] = None + function: Function + type: Optional[str] = None + index: int + + +class HiddenParams(OpenAIObject): + original_response: Optional[str] = None + model_id: Optional[str] = None # used in Router for individual deployments + api_base: Optional[str] = None # returns api base used for making completion call + + model_config = ConfigDict(extra="allow", protected_namespaces=()) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + def json(self, **kwargs): + try: + return self.model_dump() # noqa + except: + # if using pydantic v1 + return self.dict() + + +class ChatCompletionMessageToolCall(OpenAIObject): + def __init__( + self, + function: Union[Dict, Function], + id: Optional[str] = None, + type: Optional[str] = None, + **params, + ): + super(ChatCompletionMessageToolCall, self).__init__(**params) + if isinstance(function, Dict): + self.function = Function(**function) + else: + self.function = function + + if id is not None: + self.id = id + else: + self.id = f"{uuid.uuid4()}" + + if type is not None: + self.type = type + else: + self.type = "function" + + def __contains__(self, key): + # Define custom behavior for the 'in' operator + return hasattr(self, key) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + +class Message(OpenAIObject): + def __init__( + self, + content: Optional[str] = "default", + role="assistant", + logprobs=None, + function_call=None, + tool_calls=None, + **params, + ): + super(Message, self).__init__(**params) + self.content = content + self.role = role + if function_call is not None: + self.function_call = FunctionCall(**function_call) + + if tool_calls is not None: + self.tool_calls = [] + for tool_call in tool_calls: + self.tool_calls.append(ChatCompletionMessageToolCall(**tool_call)) + + if logprobs is not None: + self._logprobs = ChoiceLogprobs(**logprobs) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + def json(self, **kwargs): + try: + return self.model_dump() # noqa + except: + # if using pydantic v1 + return self.dict() + + +class Delta(OpenAIObject): + def __init__( + self, + content=None, + role=None, + function_call=None, + tool_calls=None, + **params, + ): + super(Delta, self).__init__(**params) + self.content = content + self.role = role + + if function_call is not None and isinstance(function_call, dict): + self.function_call = FunctionCall(**function_call) + else: + self.function_call = function_call + if tool_calls is not None and isinstance(tool_calls, list): + self.tool_calls = [] + for tool_call in tool_calls: + if isinstance(tool_call, dict): + if tool_call.get("index", None) is None: + tool_call["index"] = 0 + self.tool_calls.append(ChatCompletionDeltaToolCall(**tool_call)) + elif isinstance(tool_call, ChatCompletionDeltaToolCall): + self.tool_calls.append(tool_call) + else: + self.tool_calls = tool_calls + + def __contains__(self, key): + # Define custom behavior for the 'in' operator + return hasattr(self, key) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + +class Choices(OpenAIObject): + def __init__( + self, + finish_reason=None, + index=0, + message: Optional[Union[Message, dict]] = None, + logprobs=None, + enhancements=None, + **params, + ): + super(Choices, self).__init__(**params) + if finish_reason is not None: + self.finish_reason = map_finish_reason( + finish_reason + ) # set finish_reason for all responses + else: + self.finish_reason = "stop" + self.index = index + if message is None: + self.message = Message() + else: + if isinstance(message, Message): + self.message = message + elif isinstance(message, dict): + self.message = Message(**message) + if logprobs is not None: + self.logprobs = logprobs + if enhancements is not None: + self.enhancements = enhancements + + def __contains__(self, key): + # Define custom behavior for the 'in' operator + return hasattr(self, key) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + +class Usage(OpenAIObject): + def __init__( + self, prompt_tokens=None, completion_tokens=None, total_tokens=None, **params + ): + super(Usage, self).__init__(**params) + if prompt_tokens: + self.prompt_tokens = prompt_tokens + if completion_tokens: + self.completion_tokens = completion_tokens + if total_tokens: + self.total_tokens = total_tokens + + def __contains__(self, key): + # Define custom behavior for the 'in' operator + return hasattr(self, key) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + +class StreamingChoices(OpenAIObject): + def __init__( + self, + finish_reason=None, + index=0, + delta: Optional[Delta] = None, + logprobs=None, + enhancements=None, + **params, + ): + super(StreamingChoices, self).__init__(**params) + if finish_reason: + self.finish_reason = finish_reason + else: + self.finish_reason = None + self.index = index + if delta is not None: + if isinstance(delta, Delta): + self.delta = delta + elif isinstance(delta, dict): + self.delta = Delta(**delta) + else: + self.delta = Delta() + if enhancements is not None: + self.enhancements = enhancements + + if logprobs is not None and isinstance(logprobs, dict): + self.logprobs = ChoiceLogprobs(**logprobs) + else: + self.logprobs = logprobs # type: ignore + + def __contains__(self, key): + # Define custom behavior for the 'in' operator + return hasattr(self, key) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + +class ModelResponse(OpenAIObject): + id: str + """A unique identifier for the completion.""" + + choices: List[Union[Choices, StreamingChoices]] + """The list of completion choices the model generated for the input prompt.""" + + created: int + """The Unix timestamp (in seconds) of when the completion was created.""" + + model: Optional[str] = None + """The model used for completion.""" + + object: str + """The object type, which is always "text_completion" """ + + system_fingerprint: Optional[str] = None + """This fingerprint represents the backend configuration that the model runs with. + + Can be used in conjunction with the `seed` request parameter to understand when + backend changes have been made that might impact determinism. + """ + + _hidden_params: dict = {} + + def __init__( + self, + id=None, + choices=None, + created=None, + model=None, + object=None, + system_fingerprint=None, + usage=None, + stream=None, + stream_options=None, + response_ms=None, + hidden_params=None, + **params, + ): + if stream is not None and stream is True: + object = "chat.completion.chunk" + if choices is not None and isinstance(choices, list): + new_choices = [] + for choice in choices: + if isinstance(choice, StreamingChoices): + _new_choice = choice + elif isinstance(choice, dict): + _new_choice = StreamingChoices(**choice) + new_choices.append(_new_choice) + choices = new_choices + else: + choices = [StreamingChoices()] + else: + object = "chat.completion" + if choices is not None and isinstance(choices, list): + new_choices = [] + for choice in choices: + if isinstance(choice, Choices): + _new_choice = choice + elif isinstance(choice, dict): + _new_choice = Choices(**choice) + new_choices.append(_new_choice) + choices = new_choices + else: + choices = [Choices()] + if id is None: + id = _generate_id() + else: + id = id + if created is None: + created = int(time.time()) + else: + created = created + model = model + if usage is not None: + if isinstance(usage, dict): + usage = Usage(**usage) + else: + usage = usage + elif stream is None or stream is False: + usage = Usage() + if hidden_params: + self._hidden_params = hidden_params + + init_values = { + "id": id, + "choices": choices, + "created": created, + "model": model, + "object": object, + "system_fingerprint": system_fingerprint, + } + + if usage is not None: + init_values["usage"] = usage + + super().__init__( + **init_values, + **params, + ) + + def __contains__(self, key): + # Define custom behavior for the 'in' operator + return hasattr(self, key) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + def json(self, **kwargs): + try: + return self.model_dump() # noqa + except: + # if using pydantic v1 + return self.dict() + + +class Embedding(OpenAIObject): + embedding: Union[list, str] = [] + index: int + object: str + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + +class EmbeddingResponse(OpenAIObject): + model: Optional[str] = None + """The model used for embedding.""" + + data: Optional[List] = None + """The actual embedding value""" + + object: str + """The object type, which is always "embedding" """ + + usage: Optional[Usage] = None + """Usage statistics for the embedding request.""" + + _hidden_params: dict = {} + + def __init__( + self, + model=None, + usage=None, + stream=False, + response_ms=None, + data=None, + **params, + ): + object = "list" + if response_ms: + _response_ms = response_ms + else: + _response_ms = None + if data: + data = data + else: + data = None + + if usage: + usage = usage + else: + usage = Usage() + + model = model + super().__init__(model=model, object=object, data=data, usage=usage) + + def __contains__(self, key): + # Define custom behavior for the 'in' operator + return hasattr(self, key) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + def json(self, **kwargs): + try: + return self.model_dump() # noqa + except: + # if using pydantic v1 + return self.dict() + + +class Logprobs(OpenAIObject): + text_offset: List[int] + token_logprobs: List[float] + tokens: List[str] + top_logprobs: List[Dict[str, float]] + + +class TextChoices(OpenAIObject): + def __init__(self, finish_reason=None, index=0, text=None, logprobs=None, **params): + super(TextChoices, self).__init__(**params) + if finish_reason: + self.finish_reason = map_finish_reason(finish_reason) + else: + self.finish_reason = None + self.index = index + if text is not None: + self.text = text + else: + self.text = None + if logprobs is None: + self.logprobs = None + else: + if isinstance(logprobs, dict): + self.logprobs = Logprobs(**logprobs) + else: + self.logprobs = logprobs + + def __contains__(self, key): + # Define custom behavior for the 'in' operator + return hasattr(self, key) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + def json(self, **kwargs): + try: + return self.model_dump() # noqa + except: + # if using pydantic v1 + return self.dict() + + +class TextCompletionResponse(OpenAIObject): + """ + { + "id": response["id"], + "object": "text_completion", + "created": response["created"], + "model": response["model"], + "choices": [ + { + "text": response["choices"][0]["message"]["content"], + "index": response["choices"][0]["index"], + "logprobs": transformed_logprobs, + "finish_reason": response["choices"][0]["finish_reason"] + } + ], + "usage": response["usage"] + } + """ + + id: str + object: str + created: int + model: Optional[str] + choices: List[TextChoices] + usage: Optional[Usage] + _response_ms: Optional[int] = None + _hidden_params: HiddenParams + + def __init__( + self, + id=None, + choices=None, + created=None, + model=None, + usage=None, + stream=False, + response_ms=None, + object=None, + **params, + ): + if stream: + object = "text_completion.chunk" + choices = [TextChoices()] + else: + object = "text_completion" + if choices is not None and isinstance(choices, list): + new_choices = [] + for choice in choices: + if isinstance(choice, TextChoices): + _new_choice = choice + elif isinstance(choice, dict): + _new_choice = TextChoices(**choice) + new_choices.append(_new_choice) + choices = new_choices + else: + choices = [TextChoices()] + if object is not None: + object = object + if id is None: + id = _generate_id() + else: + id = id + if created is None: + created = int(time.time()) + else: + created = created + + model = model + if usage: + usage = usage + else: + usage = Usage() + + super(TextCompletionResponse, self).__init__( + id=id, + object=object, + created=created, + model=model, + choices=choices, + usage=usage, + **params, + ) + + if response_ms: + self._response_ms = response_ms + else: + self._response_ms = None + self._hidden_params = HiddenParams() + + def __contains__(self, key): + # Define custom behavior for the 'in' operator + return hasattr(self, key) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + +class ImageObject(OpenAIObject): + """ + Represents the url or the content of an image generated by the OpenAI API. + + Attributes: + b64_json: The base64-encoded JSON of the generated image, if response_format is b64_json. + url: The URL of the generated image, if response_format is url (default). + revised_prompt: The prompt that was used to generate the image, if there was any revision to the prompt. + + https://platform.openai.com/docs/api-reference/images/object + """ + + b64_json: Optional[str] = None + url: Optional[str] = None + revised_prompt: Optional[str] = None + + def __init__(self, b64_json=None, url=None, revised_prompt=None): + super().__init__(b64_json=b64_json, url=url, revised_prompt=revised_prompt) + + def __contains__(self, key): + # Define custom behavior for the 'in' operator + return hasattr(self, key) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + def json(self, **kwargs): + try: + return self.model_dump() # noqa + except: + # if using pydantic v1 + return self.dict() + + +class ImageResponse(OpenAIObject): + created: Optional[int] = None + + data: Optional[List[ImageObject]] = None + + usage: Optional[dict] = None + + _hidden_params: dict = {} + + def __init__(self, created=None, data=None, response_ms=None): + if response_ms: + _response_ms = response_ms + else: + _response_ms = None + if data: + data = data + else: + data = None + + if created: + created = created + else: + created = None + + super().__init__(data=data, created=created) + self.usage = {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0} + + def __contains__(self, key): + # Define custom behavior for the 'in' operator + return hasattr(self, key) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + def json(self, **kwargs): + try: + return self.model_dump() # noqa + except: + # if using pydantic v1 + return self.dict() + + +class TranscriptionResponse(OpenAIObject): + text: Optional[str] = None + + _hidden_params: dict = {} + + def __init__(self, text=None): + super().__init__(text=text) + + def __contains__(self, key): + # Define custom behavior for the 'in' operator + return hasattr(self, key) + + def get(self, key, default=None): + # Custom .get() method to access attributes with a default value if the attribute doesn't exist + return getattr(self, key, default) + + def __getitem__(self, key): + # Allow dictionary-style access to attributes + return getattr(self, key) + + def __setitem__(self, key, value): + # Allow dictionary-style assignment of attributes + setattr(self, key, value) + + def json(self, **kwargs): + try: + return self.model_dump() # noqa + except: + # if using pydantic v1 + return self.dict() diff --git a/litellm/utils.py b/litellm/utils.py index dbde3c1a1a1..6bc33d73d75 100644 --- a/litellm/utils.py +++ b/litellm/utils.py @@ -6,6 +6,9 @@ # +-----------------------------------------------+ # # Thank you users! We ❤️ you! - Krrish & Ishaan + +# What is this? +## Generic utils.py file. Problem-specific utils (e.g. 'cost calculation), should all be in `litellm_core_utils/`. import sys, re, binascii, struct import litellm import dotenv, json, traceback, threading, base64, ast @@ -18,7 +21,7 @@ from functools import wraps, lru_cache import datetime, time import tiktoken import uuid -from pydantic import BaseModel, ConfigDict +from pydantic import BaseModel import aiohttp import textwrap import logging @@ -32,9 +35,32 @@ from dataclasses import ( ) import os import litellm._service_logger # for storing API inputs, outputs, and metadata +import litellm.litellm_core_utils +from litellm.litellm_core_utils.core_helpers import map_finish_reason from litellm.llms.custom_httpx.http_handler import HTTPHandler, AsyncHTTPHandler from litellm.caching import DualCache -from litellm.types.utils import CostPerToken, ProviderField, ModelInfo +from litellm.types.utils import ( + CostPerToken, + ProviderField, + ModelInfo, + CallTypes, + ModelResponse, + EmbeddingResponse, + ImageResponse, + TranscriptionResponse, + TextCompletionResponse, + ChatCompletionDeltaToolCall, + Message, + Delta, + Choices, + Usage, + StreamingChoices, + Embedding, + TextChoices, +) +from litellm.litellm_core_utils.redact_messages import ( + redact_message_input_output_from_logging, +) oidc_cache = DualCache() @@ -68,32 +94,9 @@ from .types.llms.openai import ( ChatCompletionToolCallFunctionChunk, ChatCompletionDeltaToolCallChunk, ) -from .integrations.traceloop import TraceloopLogger -from .integrations.athina import AthinaLogger -from .integrations.helicone import HeliconeLogger -from .integrations.aispend import AISpendLogger -from .integrations.berrispend import BerriSpendLogger -from .integrations.supabase import Supabase -from .integrations.lunary import LunaryLogger -from .integrations.prompt_layer import PromptLayerLogger -from .integrations.langsmith import LangsmithLogger -from .integrations.logfire_logger import LogfireLogger, LogfireLevel -from .integrations.weights_biases import WeightsBiasesLogger -from .integrations.custom_logger import CustomLogger -from .integrations.langfuse import LangFuseLogger -from .integrations.openmeter import OpenMeterLogger -from .integrations.lago import LagoLogger -from .integrations.datadog import DataDogLogger -from .integrations.prometheus import PrometheusLogger -from .integrations.prometheus_services import PrometheusServicesLogger -from .integrations.dynamodb import DyanmoDBLogger -from .integrations.s3 import S3Logger -from .integrations.clickhouse import ClickhouseLogger -from .integrations.greenscale import GreenscaleLogger -from .integrations.litedebugger import LiteDebugger + from .proxy._types import KeyManagementSystem from openai import OpenAIError as OriginalError -from openai._models import BaseModel as OpenAIObject from .caching import S3Cache, RedisSemanticCache, RedisCache from .exceptions import ( AuthenticationError, @@ -176,6 +179,8 @@ local_cache: Optional[Dict[str, str]] = {} last_fetched_at = None last_fetched_at_keys = None ######## Model Response ######################### + + # All liteLLM Model responses will be in this format, Follows the OpenAI Format # https://docs.litellm.ai/docs/completion/output # { @@ -206,944 +211,19 @@ class UnsupportedParamsError(Exception): ) # Call the base class constructor with the parameters it needs -def _generate_id(): # private helper function - return "chatcmpl-" + str(uuid.uuid4()) - - -def map_finish_reason( - finish_reason: str, -): # openai supports 5 stop sequences - 'stop', 'length', 'function_call', 'content_filter', 'null' - # anthropic mapping - if finish_reason == "stop_sequence": - return "stop" - # cohere mapping - https://docs.cohere.com/reference/generate - elif finish_reason == "COMPLETE": - return "stop" - elif finish_reason == "MAX_TOKENS": # cohere + vertex ai - return "length" - elif finish_reason == "ERROR_TOXIC": - return "content_filter" - elif ( - finish_reason == "ERROR" - ): # openai currently doesn't support an 'error' finish reason - return "stop" - # huggingface mapping https://huggingface.github.io/text-generation-inference/#/Text%20Generation%20Inference/generate_stream - elif finish_reason == "eos_token" or finish_reason == "stop_sequence": - return "stop" - elif ( - finish_reason == "FINISH_REASON_UNSPECIFIED" or finish_reason == "STOP" - ): # vertex ai - got from running `print(dir(response_obj.candidates[0].finish_reason))`: ['FINISH_REASON_UNSPECIFIED', 'MAX_TOKENS', 'OTHER', 'RECITATION', 'SAFETY', 'STOP',] - return "stop" - elif finish_reason == "SAFETY": # vertex ai - return "content_filter" - elif finish_reason == "STOP": # vertex ai - return "stop" - elif finish_reason == "end_turn" or finish_reason == "stop_sequence": # anthropic - return "stop" - elif finish_reason == "max_tokens": # anthropic - return "length" - elif finish_reason == "tool_use": # anthropic - return "tool_calls" - elif finish_reason == "content_filtered": - return "content_filter" - return finish_reason - - -class TopLogprob(OpenAIObject): - token: str - """The token.""" - - bytes: Optional[List[int]] = None - """A list of integers representing the UTF-8 bytes representation of the token. - - Useful in instances where characters are represented by multiple tokens and - their byte representations must be combined to generate the correct text - representation. Can be `null` if there is no bytes representation for the token. - """ - - logprob: float - """The log probability of this token, if it is within the top 20 most likely - tokens. - - Otherwise, the value `-9999.0` is used to signify that the token is very - unlikely. - """ - - -class ChatCompletionTokenLogprob(OpenAIObject): - token: str - """The token.""" - - bytes: Optional[List[int]] = None - """A list of integers representing the UTF-8 bytes representation of the token. - - Useful in instances where characters are represented by multiple tokens and - their byte representations must be combined to generate the correct text - representation. Can be `null` if there is no bytes representation for the token. - """ - - logprob: float - """The log probability of this token, if it is within the top 20 most likely - tokens. - - Otherwise, the value `-9999.0` is used to signify that the token is very - unlikely. - """ - - top_logprobs: List[TopLogprob] - """List of the most likely tokens and their log probability, at this token - position. - - In rare cases, there may be fewer than the number of requested `top_logprobs` - returned. - """ - - -class ChoiceLogprobs(OpenAIObject): - content: Optional[List[ChatCompletionTokenLogprob]] = None - """A list of message content tokens with log probability information.""" - - -class FunctionCall(OpenAIObject): - arguments: str - name: Optional[str] = None - - -class Function(OpenAIObject): - arguments: str - name: Optional[str] = None - - def __init__( - self, - arguments: Union[Dict, str], - name: Optional[str] = None, - **params, - ): - if isinstance(arguments, Dict): - arguments = json.dumps(arguments) - else: - arguments = arguments - - name = name - - # Build a dictionary with the structure your BaseModel expects - data = {"arguments": arguments, "name": name, **params} - - super(Function, self).__init__(**data) - - def __contains__(self, key): - # Define custom behavior for the 'in' operator - return hasattr(self, key) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - -class ChatCompletionDeltaToolCall(OpenAIObject): - id: Optional[str] = None - function: Function - type: Optional[str] = None - index: int - - -class HiddenParams(OpenAIObject): - original_response: Optional[str] = None - model_id: Optional[str] = None # used in Router for individual deployments - api_base: Optional[str] = None # returns api base used for making completion call - - model_config = ConfigDict(extra="allow", protected_namespaces=()) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - def json(self, **kwargs): - try: - return self.model_dump() # noqa - except: - # if using pydantic v1 - return self.dict() - - -class ChatCompletionMessageToolCall(OpenAIObject): - def __init__( - self, - function: Union[Dict, Function], - id: Optional[str] = None, - type: Optional[str] = None, - **params, - ): - super(ChatCompletionMessageToolCall, self).__init__(**params) - if isinstance(function, Dict): - self.function = Function(**function) - else: - self.function = function - - if id is not None: - self.id = id - else: - self.id = f"{uuid.uuid4()}" - - if type is not None: - self.type = type - else: - self.type = "function" - - def __contains__(self, key): - # Define custom behavior for the 'in' operator - return hasattr(self, key) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - -class Message(OpenAIObject): - def __init__( - self, - content: Optional[str] = "default", - role="assistant", - logprobs=None, - function_call=None, - tool_calls=None, - **params, - ): - super(Message, self).__init__(**params) - self.content = content - self.role = role - if function_call is not None: - self.function_call = FunctionCall(**function_call) - - if tool_calls is not None: - self.tool_calls = [] - for tool_call in tool_calls: - self.tool_calls.append(ChatCompletionMessageToolCall(**tool_call)) - - if logprobs is not None: - self._logprobs = ChoiceLogprobs(**logprobs) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - def json(self, **kwargs): - try: - return self.model_dump() # noqa - except: - # if using pydantic v1 - return self.dict() - - -class Delta(OpenAIObject): - def __init__( - self, - content=None, - role=None, - function_call=None, - tool_calls=None, - **params, - ): - super(Delta, self).__init__(**params) - self.content = content - self.role = role - - if function_call is not None and isinstance(function_call, dict): - self.function_call = FunctionCall(**function_call) - else: - self.function_call = function_call - if tool_calls is not None and isinstance(tool_calls, list): - self.tool_calls = [] - for tool_call in tool_calls: - if isinstance(tool_call, dict): - if tool_call.get("index", None) is None: - tool_call["index"] = 0 - self.tool_calls.append(ChatCompletionDeltaToolCall(**tool_call)) - elif isinstance(tool_call, ChatCompletionDeltaToolCall): - self.tool_calls.append(tool_call) - else: - self.tool_calls = tool_calls - - def __contains__(self, key): - # Define custom behavior for the 'in' operator - return hasattr(self, key) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - -class Choices(OpenAIObject): - def __init__( - self, - finish_reason=None, - index=0, - message: Optional[Union[Message, dict]] = None, - logprobs=None, - enhancements=None, - **params, - ): - super(Choices, self).__init__(**params) - if finish_reason is not None: - self.finish_reason = map_finish_reason( - finish_reason - ) # set finish_reason for all responses - else: - self.finish_reason = "stop" - self.index = index - if message is None: - self.message = Message() - else: - if isinstance(message, Message): - self.message = message - elif isinstance(message, dict): - self.message = Message(**message) - if logprobs is not None: - self.logprobs = logprobs - if enhancements is not None: - self.enhancements = enhancements - - def __contains__(self, key): - # Define custom behavior for the 'in' operator - return hasattr(self, key) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - -class Usage(OpenAIObject): - def __init__( - self, prompt_tokens=None, completion_tokens=None, total_tokens=None, **params - ): - super(Usage, self).__init__(**params) - if prompt_tokens: - self.prompt_tokens = prompt_tokens - if completion_tokens: - self.completion_tokens = completion_tokens - if total_tokens: - self.total_tokens = total_tokens - - def __contains__(self, key): - # Define custom behavior for the 'in' operator - return hasattr(self, key) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - -class StreamingChoices(OpenAIObject): - def __init__( - self, - finish_reason=None, - index=0, - delta: Optional[Delta] = None, - logprobs=None, - enhancements=None, - **params, - ): - super(StreamingChoices, self).__init__(**params) - if finish_reason: - self.finish_reason = finish_reason - else: - self.finish_reason = None - self.index = index - if delta is not None: - if isinstance(delta, Delta): - self.delta = delta - elif isinstance(delta, dict): - self.delta = Delta(**delta) - else: - self.delta = Delta() - if enhancements is not None: - self.enhancements = enhancements - - if logprobs is not None and isinstance(logprobs, dict): - self.logprobs = ChoiceLogprobs(**logprobs) - else: - self.logprobs = logprobs # type: ignore - - def __contains__(self, key): - # Define custom behavior for the 'in' operator - return hasattr(self, key) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - -class ModelResponse(OpenAIObject): - id: str - """A unique identifier for the completion.""" - - choices: List[Union[Choices, StreamingChoices]] - """The list of completion choices the model generated for the input prompt.""" - - created: int - """The Unix timestamp (in seconds) of when the completion was created.""" - - model: Optional[str] = None - """The model used for completion.""" - - object: str - """The object type, which is always "text_completion" """ - - system_fingerprint: Optional[str] = None - """This fingerprint represents the backend configuration that the model runs with. - - Can be used in conjunction with the `seed` request parameter to understand when - backend changes have been made that might impact determinism. - """ - - _hidden_params: dict = {} - - def __init__( - self, - id=None, - choices=None, - created=None, - model=None, - object=None, - system_fingerprint=None, - usage=None, - stream=None, - stream_options=None, - response_ms=None, - hidden_params=None, - **params, - ): - if stream is not None and stream == True: - object = "chat.completion.chunk" - if choices is not None and isinstance(choices, list): - new_choices = [] - for choice in choices: - if isinstance(choice, StreamingChoices): - _new_choice = choice - elif isinstance(choice, dict): - _new_choice = StreamingChoices(**choice) - new_choices.append(_new_choice) - choices = new_choices - else: - choices = [StreamingChoices()] - else: - if model in litellm.open_ai_embedding_models: - object = "embedding" - else: - object = "chat.completion" - if choices is not None and isinstance(choices, list): - new_choices = [] - for choice in choices: - if isinstance(choice, Choices): - _new_choice = choice - elif isinstance(choice, dict): - _new_choice = Choices(**choice) - new_choices.append(_new_choice) - choices = new_choices - else: - choices = [Choices()] - if id is None: - id = _generate_id() - else: - id = id - if created is None: - created = int(time.time()) - else: - created = created - model = model - if usage is not None: - if isinstance(usage, dict): - usage = Usage(**usage) - else: - usage = usage - elif stream is None or stream == False: - usage = Usage() - if hidden_params: - self._hidden_params = hidden_params - - init_values = { - "id": id, - "choices": choices, - "created": created, - "model": model, - "object": object, - "system_fingerprint": system_fingerprint, - } - - if usage is not None: - init_values["usage"] = usage - - super().__init__( - **init_values, - **params, - ) - - def __contains__(self, key): - # Define custom behavior for the 'in' operator - return hasattr(self, key) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - def json(self, **kwargs): - try: - return self.model_dump() # noqa - except: - # if using pydantic v1 - return self.dict() - - -class Embedding(OpenAIObject): - embedding: Union[list, str] = [] - index: int - object: str - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - -class EmbeddingResponse(OpenAIObject): - model: Optional[str] = None - """The model used for embedding.""" - - data: Optional[List] = None - """The actual embedding value""" - - object: str - """The object type, which is always "embedding" """ - - usage: Optional[Usage] = None - """Usage statistics for the embedding request.""" - - _hidden_params: dict = {} - - def __init__( - self, - model=None, - usage=None, - stream=False, - response_ms=None, - data=None, - **params, - ): - object = "list" - if response_ms: - _response_ms = response_ms - else: - _response_ms = None - if data: - data = data - else: - data = None - - if usage: - usage = usage - else: - usage = Usage() - - model = model - super().__init__(model=model, object=object, data=data, usage=usage) - - def __contains__(self, key): - # Define custom behavior for the 'in' operator - return hasattr(self, key) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - def json(self, **kwargs): - try: - return self.model_dump() # noqa - except: - # if using pydantic v1 - return self.dict() - - -class Logprobs(OpenAIObject): - text_offset: List[int] - token_logprobs: List[float] - tokens: List[str] - top_logprobs: List[Dict[str, float]] - - -class TextChoices(OpenAIObject): - def __init__(self, finish_reason=None, index=0, text=None, logprobs=None, **params): - super(TextChoices, self).__init__(**params) - if finish_reason: - self.finish_reason = map_finish_reason(finish_reason) - else: - self.finish_reason = None - self.index = index - if text is not None: - self.text = text - else: - self.text = None - if logprobs is None: - self.logprobs = None - else: - if isinstance(logprobs, dict): - self.logprobs = Logprobs(**logprobs) - else: - self.logprobs = logprobs - - def __contains__(self, key): - # Define custom behavior for the 'in' operator - return hasattr(self, key) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - def json(self, **kwargs): - try: - return self.model_dump() # noqa - except: - # if using pydantic v1 - return self.dict() - - -class TextCompletionResponse(OpenAIObject): - """ - { - "id": response["id"], - "object": "text_completion", - "created": response["created"], - "model": response["model"], - "choices": [ - { - "text": response["choices"][0]["message"]["content"], - "index": response["choices"][0]["index"], - "logprobs": transformed_logprobs, - "finish_reason": response["choices"][0]["finish_reason"] - } - ], - "usage": response["usage"] - } - """ - - id: str - object: str - created: int - model: Optional[str] - choices: List[TextChoices] - usage: Optional[Usage] - _response_ms: Optional[int] = None - _hidden_params: HiddenParams - - def __init__( - self, - id=None, - choices=None, - created=None, - model=None, - usage=None, - stream=False, - response_ms=None, - object=None, - **params, - ): - if stream: - object = "text_completion.chunk" - choices = [TextChoices()] - else: - object = "text_completion" - if choices is not None and isinstance(choices, list): - new_choices = [] - for choice in choices: - if isinstance(choice, TextChoices): - _new_choice = choice - elif isinstance(choice, dict): - _new_choice = TextChoices(**choice) - new_choices.append(_new_choice) - choices = new_choices - else: - choices = [TextChoices()] - if object is not None: - object = object - if id is None: - id = _generate_id() - else: - id = id - if created is None: - created = int(time.time()) - else: - created = created - - model = model - if usage: - usage = usage - else: - usage = Usage() - - super(TextCompletionResponse, self).__init__( - id=id, - object=object, - created=created, - model=model, - choices=choices, - usage=usage, - **params, - ) - - if response_ms: - self._response_ms = response_ms - else: - self._response_ms = None - self._hidden_params = HiddenParams() - - def __contains__(self, key): - # Define custom behavior for the 'in' operator - return hasattr(self, key) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - -class ImageObject(OpenAIObject): - """ - Represents the url or the content of an image generated by the OpenAI API. - - Attributes: - b64_json: The base64-encoded JSON of the generated image, if response_format is b64_json. - url: The URL of the generated image, if response_format is url (default). - revised_prompt: The prompt that was used to generate the image, if there was any revision to the prompt. - - https://platform.openai.com/docs/api-reference/images/object - """ - - b64_json: Optional[str] = None - url: Optional[str] = None - revised_prompt: Optional[str] = None - - def __init__(self, b64_json=None, url=None, revised_prompt=None): - super().__init__(b64_json=b64_json, url=url, revised_prompt=revised_prompt) - - def __contains__(self, key): - # Define custom behavior for the 'in' operator - return hasattr(self, key) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - def json(self, **kwargs): - try: - return self.model_dump() # noqa - except: - # if using pydantic v1 - return self.dict() - - -class ImageResponse(OpenAIObject): - created: Optional[int] = None - - data: Optional[List[ImageObject]] = None - - usage: Optional[dict] = None - - _hidden_params: dict = {} - - def __init__(self, created=None, data=None, response_ms=None): - if response_ms: - _response_ms = response_ms - else: - _response_ms = None - if data: - data = data - else: - data = None - - if created: - created = created - else: - created = None - - super().__init__(data=data, created=created) - self.usage = {"prompt_tokens": 0, "completion_tokens": 0, "total_tokens": 0} - - def __contains__(self, key): - # Define custom behavior for the 'in' operator - return hasattr(self, key) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - def json(self, **kwargs): - try: - return self.model_dump() # noqa - except: - # if using pydantic v1 - return self.dict() - - -class TranscriptionResponse(OpenAIObject): - text: Optional[str] = None - - _hidden_params: dict = {} - - def __init__(self, text=None): - super().__init__(text=text) - - def __contains__(self, key): - # Define custom behavior for the 'in' operator - return hasattr(self, key) - - def get(self, key, default=None): - # Custom .get() method to access attributes with a default value if the attribute doesn't exist - return getattr(self, key, default) - - def __getitem__(self, key): - # Allow dictionary-style access to attributes - return getattr(self, key) - - def __setitem__(self, key, value): - # Allow dictionary-style assignment of attributes - setattr(self, key, value) - - def json(self, **kwargs): - try: - return self.model_dump() # noqa - except: - # if using pydantic v1 - return self.dict() - - ############################################################ def print_verbose( print_statement, logger_only: bool = False, - log_level: Literal["DEBUG", "INFO"] = "DEBUG", + log_level: Literal["DEBUG", "INFO", "ERROR"] = "DEBUG", ): try: if log_level == "DEBUG": verbose_logger.debug(print_statement) elif log_level == "INFO": verbose_logger.info(print_statement) + elif log_level == "ERROR": + verbose_logger.error(print_statement) if litellm.set_verbose == True and logger_only == False: print(print_statement) # noqa except: @@ -1151,1617 +231,6 @@ def print_verbose( ####### LOGGING ################### -from enum import Enum - - -class CallTypes(Enum): - embedding = "embedding" - aembedding = "aembedding" - completion = "completion" - acompletion = "acompletion" - atext_completion = "atext_completion" - text_completion = "text_completion" - image_generation = "image_generation" - aimage_generation = "aimage_generation" - moderation = "moderation" - amoderation = "amoderation" - atranscription = "atranscription" - transcription = "transcription" - aspeech = "aspeech" - speech = "speech" - - -# Logging function -> log the exact model details + what's being sent | Non-BlockingP -class Logging: - global supabaseClient, liteDebuggerClient, promptLayerLogger, weightsBiasesLogger, langsmithLogger, logfireLogger, capture_exception, add_breadcrumb, lunaryLogger - - custom_pricing: bool = False - stream_options = None - - def __init__( - self, - model, - messages, - stream, - call_type, - start_time, - litellm_call_id, - function_id, - dynamic_success_callbacks=None, - dynamic_failure_callbacks=None, - dynamic_async_success_callbacks=None, - langfuse_public_key=None, - langfuse_secret=None, - ): - if call_type not in [item.value for item in CallTypes]: - allowed_values = ", ".join([item.value for item in CallTypes]) - raise ValueError( - f"Invalid call_type {call_type}. Allowed values: {allowed_values}" - ) - if messages is not None: - if isinstance(messages, str): - messages = [ - {"role": "user", "content": messages} - ] # convert text completion input to the chat completion format - elif ( - isinstance(messages, list) - and len(messages) > 0 - and isinstance(messages[0], str) - ): - new_messages = [] - for m in messages: - new_messages.append({"role": "user", "content": m}) - messages = new_messages - self.model = model - self.messages = messages - self.stream = stream - self.start_time = start_time # log the call start time - self.call_type = call_type - self.litellm_call_id = litellm_call_id - self.function_id = function_id - self.streaming_chunks = [] # for generating complete stream response - self.sync_streaming_chunks = [] # for generating complete stream response - self.model_call_details = {} - self.dynamic_input_callbacks = [] # [TODO] callbacks set for just that call - self.dynamic_failure_callbacks = dynamic_failure_callbacks - self.dynamic_success_callbacks = ( - dynamic_success_callbacks # callbacks set for just that call - ) - self.dynamic_async_success_callbacks = ( - dynamic_async_success_callbacks # callbacks set for just that call - ) - ## DYNAMIC LANGFUSE KEYS ## - self.langfuse_public_key = langfuse_public_key - self.langfuse_secret = langfuse_secret - ## TIME TO FIRST TOKEN LOGGING ## - self.completion_start_time: Optional[datetime.datetime] = None - - def update_environment_variables( - self, model, user, optional_params, litellm_params, **additional_params - ): - self.optional_params = optional_params - self.model = model - self.user = user - self.litellm_params = litellm_params - self.logger_fn = litellm_params.get("logger_fn", None) - print_verbose(f"self.optional_params: {self.optional_params}") - - self.model_call_details = { - "model": self.model, - "messages": self.messages, - "optional_params": self.optional_params, - "litellm_params": self.litellm_params, - "start_time": self.start_time, - "stream": self.stream, - "user": user, - "call_type": str(self.call_type), - "litellm_call_id": self.litellm_call_id, - "completion_start_time": self.completion_start_time, - **self.optional_params, - **additional_params, - } - - ## check if stream options is set ## - used by CustomStreamWrapper for easy instrumentation - if "stream_options" in additional_params: - self.stream_options = additional_params["stream_options"] - ## check if custom pricing set ## - if ( - litellm_params.get("input_cost_per_token") is not None - or litellm_params.get("input_cost_per_second") is not None - or litellm_params.get("output_cost_per_token") is not None - or litellm_params.get("output_cost_per_second") is not None - ): - self.custom_pricing = True - - def _pre_call(self, input, api_key, model=None, additional_args={}): - """ - Common helper function across the sync + async pre-call function - """ - # print_verbose(f"logging pre call for model: {self.model} with call type: {self.call_type}") - self.model_call_details["input"] = input - self.model_call_details["api_key"] = api_key - self.model_call_details["additional_args"] = additional_args - self.model_call_details["log_event_type"] = "pre_api_call" - if ( - model - ): # if model name was changes pre-call, overwrite the initial model call name with the new one - self.model_call_details["model"] = model - - def pre_call(self, input, api_key, model=None, additional_args={}): - # Log the exact input to the LLM API - litellm.error_logs["PRE_CALL"] = locals() - try: - self._pre_call( - input=input, - api_key=api_key, - model=model, - additional_args=additional_args, - ) - - # User Logging -> if you pass in a custom logging function - headers = additional_args.get("headers", {}) - if headers is None: - headers = {} - data = additional_args.get("complete_input_dict", {}) - api_base = additional_args.get("api_base", "") - self.model_call_details["litellm_params"]["api_base"] = str( - api_base - ) # used for alerting - masked_headers = { - k: ( - (v[:-44] + "*" * 44) - if (isinstance(v, str) and len(v) > 44) - else "*****" - ) - for k, v in headers.items() - } - formatted_headers = " ".join( - [f"-H '{k}: {v}'" for k, v in masked_headers.items()] - ) - - verbose_logger.debug(f"PRE-API-CALL ADDITIONAL ARGS: {additional_args}") - - curl_command = "\n\nPOST Request Sent from LiteLLM:\n" - curl_command += "curl -X POST \\\n" - curl_command += f"{api_base} \\\n" - curl_command += ( - f"{formatted_headers} \\\n" if formatted_headers.strip() != "" else "" - ) - curl_command += f"-d '{str(data)}'\n" - if additional_args.get("request_str", None) is not None: - # print the sagemaker / bedrock client request - curl_command = "\nRequest Sent from LiteLLM:\n" - curl_command += additional_args.get("request_str", None) - elif api_base == "": - curl_command = self.model_call_details - - # only print verbose if verbose logger is not set - if verbose_logger.level == 0: - # this means verbose logger was not switched on - user is in litellm.set_verbose=True - print_verbose(f"\033[92m{curl_command}\033[0m\n") - - if litellm.json_logs: - verbose_logger.debug( - "POST Request Sent from LiteLLM", - extra={"api_base": {api_base}, **masked_headers}, - ) - else: - verbose_logger.debug(f"\033[92m{curl_command}\033[0m\n") - # log raw request to provider (like LangFuse) -- if opted in. - if litellm.log_raw_request_response is True: - try: - # [Non-blocking Extra Debug Information in metadata] - _litellm_params = self.model_call_details.get("litellm_params", {}) - _metadata = _litellm_params.get("metadata", {}) or {} - if ( - litellm.turn_off_message_logging is not None - and litellm.turn_off_message_logging is True - ): - _metadata["raw_request"] = ( - "redacted by litellm. \ - 'litellm.turn_off_message_logging=True'" - ) - else: - _metadata["raw_request"] = str(curl_command) - except Exception as e: - _metadata["raw_request"] = ( - "Unable to Log \ - raw request: {}".format( - str(e) - ) - ) - if self.logger_fn and callable(self.logger_fn): - try: - self.logger_fn( - self.model_call_details - ) # Expectation: any logger function passed in by the user should accept a dict object - except Exception as e: - print_verbose( - f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while logging {traceback.format_exc()}" - ) - # Input Integration Logging -> If you want to log the fact that an attempt to call the model was made - callbacks = litellm.input_callback + self.dynamic_input_callbacks - for callback in callbacks: - try: - if callback == "supabase": - print_verbose("reaches supabase for logging!") - model = self.model_call_details["model"] - messages = self.model_call_details["input"] - print_verbose(f"supabaseClient: {supabaseClient}") - supabaseClient.input_log_event( - model=model, - messages=messages, - end_user=self.model_call_details.get("user", "default"), - litellm_call_id=self.litellm_params["litellm_call_id"], - print_verbose=print_verbose, - ) - elif callback == "sentry" and add_breadcrumb: - try: - details_to_log = copy.deepcopy(self.model_call_details) - except: - details_to_log = self.model_call_details - if litellm.turn_off_message_logging: - # make a copy of the _model_Call_details and log it - details_to_log.pop("messages", None) - details_to_log.pop("input", None) - details_to_log.pop("prompt", None) - - add_breadcrumb( - category="litellm.llm_call", - message=f"Model Call Details pre-call: {details_to_log}", - level="info", - ) - elif isinstance(callback, CustomLogger): # custom logger class - callback.log_pre_api_call( - model=self.model, - messages=self.messages, - kwargs=self.model_call_details, - ) - elif callable(callback): # custom logger functions - customLogger.log_input_event( - model=self.model, - messages=self.messages, - kwargs=self.model_call_details, - print_verbose=print_verbose, - callback_func=callback, - ) - except Exception as e: - verbose_logger.error( - "litellm.Logging.pre_call(): Exception occured - {}".format( - str(e) - ) - ) - verbose_logger.debug( - f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while input logging with integrations {traceback.format_exc()}" - ) - print_verbose( - f"LiteLLM.Logging: is sentry capture exception initialized {capture_exception}" - ) - if capture_exception: # log this error to sentry for debugging - capture_exception(e) - except: - print_verbose( - f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while logging {traceback.format_exc()}" - ) - print_verbose( - f"LiteLLM.Logging: is sentry capture exception initialized {capture_exception}" - ) - if capture_exception: # log this error to sentry for debugging - capture_exception(e) - - def post_call( - self, original_response, input=None, api_key=None, additional_args={} - ): - # Log the exact result from the LLM API, for streaming - log the type of response received - litellm.error_logs["POST_CALL"] = locals() - if isinstance(original_response, dict): - original_response = json.dumps(original_response) - try: - self.model_call_details["input"] = input - self.model_call_details["api_key"] = api_key - self.model_call_details["original_response"] = original_response - self.model_call_details["additional_args"] = additional_args - self.model_call_details["log_event_type"] = "post_api_call" - # User Logging -> if you pass in a custom logging function - print_verbose( - f"RAW RESPONSE:\n{self.model_call_details.get('original_response', self.model_call_details)}\n\n", - log_level="DEBUG", - ) - if self.logger_fn and callable(self.logger_fn): - try: - self.logger_fn( - self.model_call_details - ) # Expectation: any logger function passed in by the user should accept a dict object - except Exception as e: - print_verbose( - f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while logging {traceback.format_exc()}" - ) - self.redact_message_input_output_from_logging(result=original_response) - # Input Integration Logging -> If you want to log the fact that an attempt to call the model was made - - callbacks = litellm.input_callback + self.dynamic_input_callbacks - for callback in callbacks: - try: - if callback == "lite_debugger": - print_verbose("reaches litedebugger for post-call logging!") - print_verbose(f"liteDebuggerClient: {liteDebuggerClient}") - liteDebuggerClient.post_call_log_event( - original_response=original_response, - litellm_call_id=self.litellm_params["litellm_call_id"], - print_verbose=print_verbose, - call_type=self.call_type, - stream=self.stream, - ) - elif callback == "sentry" and add_breadcrumb: - print_verbose("reaches sentry breadcrumbing") - try: - details_to_log = copy.deepcopy(self.model_call_details) - except: - details_to_log = self.model_call_details - if litellm.turn_off_message_logging: - # make a copy of the _model_Call_details and log it - details_to_log.pop("messages", None) - details_to_log.pop("input", None) - details_to_log.pop("prompt", None) - - add_breadcrumb( - category="litellm.llm_call", - message=f"Model Call Details post-call: {details_to_log}", - level="info", - ) - elif isinstance(callback, CustomLogger): # custom logger class - callback.log_post_api_call( - kwargs=self.model_call_details, - response_obj=None, - start_time=self.start_time, - end_time=None, - ) - except Exception as e: - print_verbose( - f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while post-call logging with integrations {traceback.format_exc()}" - ) - print_verbose( - f"LiteLLM.Logging: is sentry capture exception initialized {capture_exception}" - ) - if capture_exception: # log this error to sentry for debugging - capture_exception(e) - except: - print_verbose( - f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while logging {traceback.format_exc()}" - ) - pass - - def _success_handler_helper_fn( - self, result=None, start_time=None, end_time=None, cache_hit=None - ): - try: - if start_time is None: - start_time = self.start_time - if end_time is None: - end_time = datetime.datetime.now() - if self.completion_start_time is None: - self.completion_start_time = end_time - self.model_call_details["completion_start_time"] = ( - self.completion_start_time - ) - self.model_call_details["log_event_type"] = "successful_api_call" - self.model_call_details["end_time"] = end_time - self.model_call_details["cache_hit"] = cache_hit - ## if model in model cost map - log the response cost - ## else set cost to None - verbose_logger.debug(f"Model={self.model};") - if ( - result is not None - and ( - isinstance(result, ModelResponse) - or isinstance(result, EmbeddingResponse) - or isinstance(result, ImageResponse) - or isinstance(result, TranscriptionResponse) - or isinstance(result, TextCompletionResponse) - ) - and self.stream != True - ): # handle streaming separately - self.model_call_details["response_cost"] = ( - litellm.response_cost_calculator( - response_object=result, - model=self.model, - cache_hit=self.model_call_details.get("cache_hit", False), - custom_llm_provider=self.model_call_details.get( - "custom_llm_provider", None - ), - base_model=_get_base_model_from_metadata( - model_call_details=self.model_call_details - ), - call_type=self.call_type, - optional_params=self.optional_params, - ) - ) - else: # streaming chunks + image gen. - self.model_call_details["response_cost"] = None - - if ( - litellm.max_budget - and self.stream == False - and result is not None - and "content" in result - ): - time_diff = (end_time - start_time).total_seconds() - float_diff = float(time_diff) - litellm._current_cost += litellm.completion_cost( - model=self.model, - prompt="", - completion=result["content"], - total_time=float_diff, - ) - - return start_time, end_time, result - except Exception as e: - raise Exception(f"[Non-Blocking] LiteLLM.Success_Call Error: {str(e)}") - - def success_handler( - self, result=None, start_time=None, end_time=None, cache_hit=None, **kwargs - ): - print_verbose(f"Logging Details LiteLLM-Success Call: {cache_hit}") - start_time, end_time, result = self._success_handler_helper_fn( - start_time=start_time, - end_time=end_time, - result=result, - cache_hit=cache_hit, - ) - # print(f"original response in success handler: {self.model_call_details['original_response']}") - try: - print_verbose(f"success callbacks: {litellm.success_callback}") - ## BUILD COMPLETE STREAMED RESPONSE - complete_streaming_response = None - if self.stream and isinstance(result, ModelResponse): - if ( - result.choices[0].finish_reason is not None - ): # if it's the last chunk - self.sync_streaming_chunks.append(result) - # print_verbose(f"final set of received chunks: {self.sync_streaming_chunks}") - try: - complete_streaming_response = litellm.stream_chunk_builder( - self.sync_streaming_chunks, - messages=self.model_call_details.get("messages", None), - start_time=start_time, - end_time=end_time, - ) - except Exception as e: - complete_streaming_response = None - else: - self.sync_streaming_chunks.append(result) - - if complete_streaming_response is not None: - print_verbose( - f"Logging Details LiteLLM-Success Call streaming complete" - ) - self.model_call_details["complete_streaming_response"] = ( - complete_streaming_response - ) - self.model_call_details["response_cost"] = ( - litellm.response_cost_calculator( - response_object=complete_streaming_response, - model=self.model, - cache_hit=self.model_call_details.get("cache_hit", False), - custom_llm_provider=self.model_call_details.get( - "custom_llm_provider", None - ), - base_model=_get_base_model_from_metadata( - model_call_details=self.model_call_details - ), - call_type=self.call_type, - optional_params=self.optional_params, - ) - ) - if self.dynamic_success_callbacks is not None and isinstance( - self.dynamic_success_callbacks, list - ): - callbacks = self.dynamic_success_callbacks - ## keep the internal functions ## - for callback in litellm.success_callback: - if ( - isinstance(callback, CustomLogger) - and "_PROXY_" in callback.__class__.__name__ - ): - callbacks.append(callback) - else: - callbacks = litellm.success_callback - - self.redact_message_input_output_from_logging(result=result) - - for callback in callbacks: - try: - litellm_params = self.model_call_details.get("litellm_params", {}) - if litellm_params.get("no-log", False) == True: - # proxy cost tracking cal backs should run - if not ( - isinstance(callback, CustomLogger) - and "_PROXY_" in callback.__class__.__name__ - ): - print_verbose("no-log request, skipping logging") - continue - if callback == "lite_debugger": - print_verbose("reaches lite_debugger for logging!") - print_verbose(f"liteDebuggerClient: {liteDebuggerClient}") - print_verbose( - f"liteDebuggerClient details function {self.call_type} and stream set to {self.stream}" - ) - liteDebuggerClient.log_event( - end_user=kwargs.get("user", "default"), - response_obj=result, - start_time=start_time, - end_time=end_time, - litellm_call_id=self.litellm_call_id, - print_verbose=print_verbose, - call_type=self.call_type, - stream=self.stream, - ) - if callback == "promptlayer": - print_verbose("reaches promptlayer for logging!") - promptLayerLogger.log_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - ) - if callback == "supabase": - print_verbose("reaches supabase for logging!") - kwargs = self.model_call_details - - # this only logs streaming once, complete_streaming_response exists i.e when stream ends - if self.stream: - if "complete_streaming_response" not in kwargs: - continue - else: - print_verbose("reaches supabase for streaming logging!") - result = kwargs["complete_streaming_response"] - - model = kwargs["model"] - messages = kwargs["messages"] - optional_params = kwargs.get("optional_params", {}) - litellm_params = kwargs.get("litellm_params", {}) - supabaseClient.log_event( - model=model, - messages=messages, - end_user=optional_params.get("user", "default"), - response_obj=result, - start_time=start_time, - end_time=end_time, - litellm_call_id=litellm_params.get( - "litellm_call_id", str(uuid.uuid4()) - ), - print_verbose=print_verbose, - ) - if callback == "wandb": - print_verbose("reaches wandb for logging!") - weightsBiasesLogger.log_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - ) - if callback == "langsmith": - print_verbose("reaches langsmith for logging!") - if self.stream: - if "complete_streaming_response" not in kwargs: - continue - else: - print_verbose( - "reaches langsmith for streaming logging!" - ) - result = kwargs["complete_streaming_response"] - langsmithLogger.log_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - ) - if callback == "logfire": - global logfireLogger - verbose_logger.debug("reaches logfire for success logging!") - kwargs = {} - for k, v in self.model_call_details.items(): - if ( - k != "original_response" - ): # copy.deepcopy raises errors as this could be a coroutine - kwargs[k] = v - - # this only logs streaming once, complete_streaming_response exists i.e when stream ends - if self.stream: - if "complete_streaming_response" not in kwargs: - continue - else: - print_verbose("reaches logfire for streaming logging!") - result = kwargs["complete_streaming_response"] - - logfireLogger.log_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - level=LogfireLevel.INFO.value, - ) - - if callback == "lunary": - print_verbose("reaches lunary for logging!") - model = self.model - kwargs = self.model_call_details - - input = kwargs.get("messages", kwargs.get("input", None)) - - type = ( - "embed" - if self.call_type == CallTypes.embedding.value - else "llm" - ) - - # this only logs streaming once, complete_streaming_response exists i.e when stream ends - if self.stream: - if "complete_streaming_response" not in kwargs: - continue - else: - result = kwargs["complete_streaming_response"] - - lunaryLogger.log_event( - type=type, - kwargs=kwargs, - event="end", - model=model, - input=input, - user_id=kwargs.get("user", None), - # user_props=self.model_call_details.get("user_props", None), - extra=kwargs.get("optional_params", {}), - response_obj=result, - start_time=start_time, - end_time=end_time, - run_id=self.litellm_call_id, - print_verbose=print_verbose, - ) - if callback == "helicone": - print_verbose("reaches helicone for logging!") - model = self.model - messages = self.model_call_details["input"] - heliconeLogger.log_success( - model=model, - messages=messages, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - ) - if callback == "langfuse": - global langFuseLogger - verbose_logger.debug("reaches langfuse for success logging!") - kwargs = {} - for k, v in self.model_call_details.items(): - if ( - k != "original_response" - ): # copy.deepcopy raises errors as this could be a coroutine - kwargs[k] = v - # this only logs streaming once, complete_streaming_response exists i.e when stream ends - if self.stream: - verbose_logger.debug( - f"is complete_streaming_response in kwargs: {kwargs.get('complete_streaming_response', None)}" - ) - if complete_streaming_response is None: - continue - else: - print_verbose("reaches langfuse for streaming logging!") - result = kwargs["complete_streaming_response"] - if langFuseLogger is None or ( - ( - self.langfuse_public_key is not None - and self.langfuse_public_key - != langFuseLogger.public_key - ) - and ( - self.langfuse_public_key is not None - and self.langfuse_public_key - != langFuseLogger.public_key - ) - ): - langFuseLogger = LangFuseLogger( - langfuse_public_key=self.langfuse_public_key, - langfuse_secret=self.langfuse_secret, - ) - langFuseLogger.log_event( - kwargs=kwargs, - response_obj=result, - start_time=start_time, - end_time=end_time, - user_id=kwargs.get("user", None), - print_verbose=print_verbose, - ) - if callback == "datadog": - global dataDogLogger - verbose_logger.debug("reaches datadog for success logging!") - kwargs = {} - for k, v in self.model_call_details.items(): - if ( - k != "original_response" - ): # copy.deepcopy raises errors as this could be a coroutine - kwargs[k] = v - # this only logs streaming once, complete_streaming_response exists i.e when stream ends - if self.stream: - verbose_logger.debug( - f"datadog: is complete_streaming_response in kwargs: {kwargs.get('complete_streaming_response', None)}" - ) - if complete_streaming_response is None: - continue - else: - print_verbose("reaches datadog for streaming logging!") - result = kwargs["complete_streaming_response"] - dataDogLogger.log_event( - kwargs=kwargs, - response_obj=result, - start_time=start_time, - end_time=end_time, - user_id=kwargs.get("user", None), - print_verbose=print_verbose, - ) - if callback == "prometheus": - global prometheusLogger - verbose_logger.debug("reaches prometheus for success logging!") - kwargs = {} - for k, v in self.model_call_details.items(): - if ( - k != "original_response" - ): # copy.deepcopy raises errors as this could be a coroutine - kwargs[k] = v - # this only logs streaming once, complete_streaming_response exists i.e when stream ends - if self.stream: - verbose_logger.debug( - f"prometheus: is complete_streaming_response in kwargs: {kwargs.get('complete_streaming_response', None)}" - ) - if complete_streaming_response is None: - continue - else: - print_verbose( - "reaches prometheus for streaming logging!" - ) - result = kwargs["complete_streaming_response"] - prometheusLogger.log_event( - kwargs=kwargs, - response_obj=result, - start_time=start_time, - end_time=end_time, - user_id=kwargs.get("user", None), - print_verbose=print_verbose, - ) - if callback == "generic": - global genericAPILogger - verbose_logger.debug("reaches langfuse for success logging!") - kwargs = {} - for k, v in self.model_call_details.items(): - if ( - k != "original_response" - ): # copy.deepcopy raises errors as this could be a coroutine - kwargs[k] = v - # this only logs streaming once, complete_streaming_response exists i.e when stream ends - if self.stream: - verbose_logger.debug( - f"is complete_streaming_response in kwargs: {kwargs.get('complete_streaming_response', None)}" - ) - if complete_streaming_response is None: - continue - else: - print_verbose("reaches langfuse for streaming logging!") - result = kwargs["complete_streaming_response"] - if genericAPILogger is None: - genericAPILogger = GenericAPILogger() - genericAPILogger.log_event( - kwargs=kwargs, - response_obj=result, - start_time=start_time, - end_time=end_time, - user_id=kwargs.get("user", None), - print_verbose=print_verbose, - ) - if callback == "clickhouse": - global clickHouseLogger - verbose_logger.debug("reaches clickhouse for success logging!") - kwargs = {} - for k, v in self.model_call_details.items(): - if ( - k != "original_response" - ): # copy.deepcopy raises errors as this could be a coroutine - kwargs[k] = v - # this only logs streaming once, complete_streaming_response exists i.e when stream ends - if self.stream: - verbose_logger.debug( - f"is complete_streaming_response in kwargs: {kwargs.get('complete_streaming_response', None)}" - ) - if complete_streaming_response is None: - continue - else: - print_verbose( - "reaches clickhouse for streaming logging!" - ) - result = kwargs["complete_streaming_response"] - if clickHouseLogger is None: - clickHouseLogger = ClickhouseLogger() - clickHouseLogger.log_event( - kwargs=kwargs, - response_obj=result, - start_time=start_time, - end_time=end_time, - user_id=kwargs.get("user", None), - print_verbose=print_verbose, - ) - if callback == "greenscale": - kwargs = {} - for k, v in self.model_call_details.items(): - if ( - k != "original_response" - ): # copy.deepcopy raises errors as this could be a coroutine - kwargs[k] = v - # this only logs streaming once, complete_streaming_response exists i.e when stream ends - if self.stream: - verbose_logger.debug( - f"is complete_streaming_response in kwargs: {kwargs.get('complete_streaming_response', None)}" - ) - if complete_streaming_response is None: - continue - else: - print_verbose( - "reaches greenscale for streaming logging!" - ) - result = kwargs["complete_streaming_response"] - - greenscaleLogger.log_event( - kwargs=kwargs, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - ) - if callback == "cache" and litellm.cache is not None: - # this only logs streaming once, complete_streaming_response exists i.e when stream ends - print_verbose("success_callback: reaches cache for logging!") - kwargs = self.model_call_details - if self.stream: - if "complete_streaming_response" not in kwargs: - print_verbose( - f"success_callback: reaches cache for logging, there is no complete_streaming_response. Kwargs={kwargs}\n\n" - ) - pass - else: - print_verbose( - "success_callback: reaches cache for logging, there is a complete_streaming_response. Adding to cache" - ) - result = kwargs["complete_streaming_response"] - # only add to cache once we have a complete streaming response - litellm.cache.add_cache(result, **kwargs) - if callback == "athina": - deep_copy = {} - for k, v in self.model_call_details.items(): - deep_copy[k] = v - athinaLogger.log_event( - kwargs=deep_copy, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - ) - if callback == "traceloop": - deep_copy = {} - for k, v in self.model_call_details.items(): - if k != "original_response": - deep_copy[k] = v - traceloopLogger.log_event( - kwargs=deep_copy, - response_obj=result, - start_time=start_time, - end_time=end_time, - user_id=kwargs.get("user", None), - print_verbose=print_verbose, - ) - if callback == "s3": - global s3Logger - if s3Logger is None: - s3Logger = S3Logger() - if self.stream: - if "complete_streaming_response" in self.model_call_details: - print_verbose( - "S3Logger Logger: Got Stream Event - Completed Stream Response" - ) - s3Logger.log_event( - kwargs=self.model_call_details, - response_obj=self.model_call_details[ - "complete_streaming_response" - ], - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - ) - else: - print_verbose( - "S3Logger Logger: Got Stream Event - No complete stream response as yet" - ) - else: - s3Logger.log_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - ) - if ( - callback == "openmeter" - and self.model_call_details.get("litellm_params", {}).get( - "acompletion", False - ) - == False - and self.model_call_details.get("litellm_params", {}).get( - "aembedding", False - ) - == False - and self.model_call_details.get("litellm_params", {}).get( - "aimage_generation", False - ) - == False - and self.model_call_details.get("litellm_params", {}).get( - "atranscription", False - ) - == False - ): - global openMeterLogger - if openMeterLogger is None: - print_verbose("Instantiates openmeter client") - openMeterLogger = OpenMeterLogger() - if self.stream and complete_streaming_response is None: - openMeterLogger.log_stream_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - ) - else: - if self.stream and complete_streaming_response: - self.model_call_details["complete_response"] = ( - self.model_call_details.get( - "complete_streaming_response", {} - ) - ) - result = self.model_call_details["complete_response"] - openMeterLogger.log_success_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - ) - - if ( - isinstance(callback, CustomLogger) - and self.model_call_details.get("litellm_params", {}).get( - "acompletion", False - ) - == False - and self.model_call_details.get("litellm_params", {}).get( - "aembedding", False - ) - == False - and self.model_call_details.get("litellm_params", {}).get( - "aimage_generation", False - ) - == False - and self.model_call_details.get("litellm_params", {}).get( - "atranscription", False - ) - == False - ): # custom logger class - if self.stream and complete_streaming_response is None: - callback.log_stream_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - ) - else: - if self.stream and complete_streaming_response: - self.model_call_details["complete_response"] = ( - self.model_call_details.get( - "complete_streaming_response", {} - ) - ) - result = self.model_call_details["complete_response"] - callback.log_success_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - ) - if ( - callable(callback) == True - and self.model_call_details.get("litellm_params", {}).get( - "acompletion", False - ) - == False - and self.model_call_details.get("litellm_params", {}).get( - "aembedding", False - ) - == False - and self.model_call_details.get("litellm_params", {}).get( - "aimage_generation", False - ) - == False - and self.model_call_details.get("litellm_params", {}).get( - "atranscription", False - ) - == False - ): # custom logger functions - print_verbose( - f"success callbacks: Running Custom Callback Function" - ) - customLogger.log_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - callback_func=callback, - ) - - except Exception as e: - print_verbose( - f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while success logging with integrations {traceback.format_exc()}" - ) - print_verbose( - f"LiteLLM.Logging: is sentry capture exception initialized {capture_exception}" - ) - if capture_exception: # log this error to sentry for debugging - capture_exception(e) - except: - print_verbose( - f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while success logging {traceback.format_exc()}" - ) - pass - - async def async_success_handler( - self, result=None, start_time=None, end_time=None, cache_hit=None, **kwargs - ): - """ - Implementing async callbacks, to handle asyncio event loop issues when custom integrations need to use async functions. - """ - print_verbose(f"Logging Details LiteLLM-Async Success Call") - start_time, end_time, result = self._success_handler_helper_fn( - start_time=start_time, end_time=end_time, result=result, cache_hit=cache_hit - ) - ## BUILD COMPLETE STREAMED RESPONSE - complete_streaming_response = None - if self.stream: - if result.choices[0].finish_reason is not None: # if it's the last chunk - self.streaming_chunks.append(result) - # verbose_logger.debug(f"final set of received chunks: {self.streaming_chunks}") - try: - complete_streaming_response = litellm.stream_chunk_builder( - self.streaming_chunks, - messages=self.model_call_details.get("messages", None), - start_time=start_time, - end_time=end_time, - ) - except Exception as e: - print_verbose( - f"Error occurred building stream chunk: {traceback.format_exc()}" - ) - complete_streaming_response = None - else: - self.streaming_chunks.append(result) - if complete_streaming_response is not None: - print_verbose("Async success callbacks: Got a complete streaming response") - self.model_call_details["async_complete_streaming_response"] = ( - complete_streaming_response - ) - try: - if self.model_call_details.get("cache_hit", False) == True: - self.model_call_details["response_cost"] = 0.0 - else: - # check if base_model set on azure - base_model = _get_base_model_from_metadata( - model_call_details=self.model_call_details - ) - # base_model defaults to None if not set on model_info - self.model_call_details["response_cost"] = litellm.completion_cost( - completion_response=complete_streaming_response, - model=base_model, - ) - verbose_logger.debug( - f"Model={self.model}; cost={self.model_call_details['response_cost']}" - ) - except litellm.NotFoundError as e: - verbose_logger.debug( - f"Model={self.model} not found in completion cost map." - ) - self.model_call_details["response_cost"] = None - - if self.dynamic_async_success_callbacks is not None and isinstance( - self.dynamic_async_success_callbacks, list - ): - callbacks = self.dynamic_async_success_callbacks - ## keep the internal functions ## - for callback in litellm._async_success_callback: - callback_name = "" - if isinstance(callback, CustomLogger): - callback_name = callback.__class__.__name__ - if callable(callback): - callback_name = callback.__name__ - if "_PROXY_" in callback_name: - callbacks.append(callback) - else: - callbacks = litellm._async_success_callback - - self.redact_message_input_output_from_logging(result=result) - - for callback in callbacks: - # check if callback can run for this request - litellm_params = self.model_call_details.get("litellm_params", {}) - if litellm_params.get("no-log", False) == True: - # proxy cost tracking cal backs should run - if not ( - isinstance(callback, CustomLogger) - and "_PROXY_" in callback.__class__.__name__ - ): - print_verbose("no-log request, skipping logging") - continue - try: - if kwargs.get("no-log", False) == True: - print_verbose("no-log request, skipping logging") - continue - if callback == "cache" and litellm.cache is not None: - # set_cache once complete streaming response is built - print_verbose("async success_callback: reaches cache for logging!") - kwargs = self.model_call_details - if self.stream: - if "async_complete_streaming_response" not in kwargs: - print_verbose( - f"async success_callback: reaches cache for logging, there is no async_complete_streaming_response. Kwargs={kwargs}\n\n" - ) - pass - else: - print_verbose( - "async success_callback: reaches cache for logging, there is a async_complete_streaming_response. Adding to cache" - ) - result = kwargs["async_complete_streaming_response"] - # only add to cache once we have a complete streaming response - if litellm.cache is not None and not isinstance( - litellm.cache.cache, S3Cache - ): - await litellm.cache.async_add_cache(result, **kwargs) - else: - litellm.cache.add_cache(result, **kwargs) - if callback == "openmeter": - global openMeterLogger - if self.stream == True: - if ( - "async_complete_streaming_response" - in self.model_call_details - ): - await openMeterLogger.async_log_success_event( - kwargs=self.model_call_details, - response_obj=self.model_call_details[ - "async_complete_streaming_response" - ], - start_time=start_time, - end_time=end_time, - ) - else: - await openMeterLogger.async_log_stream_event( # [TODO]: move this to being an async log stream event function - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - ) - else: - await openMeterLogger.async_log_success_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - ) - if isinstance(callback, CustomLogger): # custom logger class - if self.stream == True: - if ( - "async_complete_streaming_response" - in self.model_call_details - ): - await callback.async_log_success_event( - kwargs=self.model_call_details, - response_obj=self.model_call_details[ - "async_complete_streaming_response" - ], - start_time=start_time, - end_time=end_time, - ) - else: - await callback.async_log_stream_event( # [TODO]: move this to being an async log stream event function - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - ) - else: - await callback.async_log_success_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - ) - if callable(callback): # custom logger functions - if self.stream: - if ( - "async_complete_streaming_response" - in self.model_call_details - ): - await customLogger.async_log_event( - kwargs=self.model_call_details, - response_obj=self.model_call_details[ - "async_complete_streaming_response" - ], - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - callback_func=callback, - ) - else: - await customLogger.async_log_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - callback_func=callback, - ) - if callback == "dynamodb": - global dynamoLogger - if dynamoLogger is None: - dynamoLogger = DyanmoDBLogger() - if self.stream: - if ( - "async_complete_streaming_response" - in self.model_call_details - ): - print_verbose( - "DynamoDB Logger: Got Stream Event - Completed Stream Response" - ) - await dynamoLogger._async_log_event( - kwargs=self.model_call_details, - response_obj=self.model_call_details[ - "async_complete_streaming_response" - ], - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - ) - else: - print_verbose( - "DynamoDB Logger: Got Stream Event - No complete stream response as yet" - ) - else: - await dynamoLogger._async_log_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - ) - except Exception as e: - verbose_logger.error( - f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while success logging {traceback.format_exc()}" - ) - pass - - def _failure_handler_helper_fn( - self, exception, traceback_exception, start_time=None, end_time=None - ): - if start_time is None: - start_time = self.start_time - if end_time is None: - end_time = datetime.datetime.now() - - # on some exceptions, model_call_details is not always initialized, this ensures that we still log those exceptions - if not hasattr(self, "model_call_details"): - self.model_call_details = {} - - self.model_call_details["log_event_type"] = "failed_api_call" - self.model_call_details["exception"] = exception - self.model_call_details["traceback_exception"] = traceback_exception - self.model_call_details["end_time"] = end_time - self.model_call_details.setdefault("original_response", None) - return start_time, end_time - - def failure_handler( - self, exception, traceback_exception, start_time=None, end_time=None - ): - print_verbose( - f"Logging Details LiteLLM-Failure Call: {litellm.failure_callback}" - ) - try: - start_time, end_time = self._failure_handler_helper_fn( - exception=exception, - traceback_exception=traceback_exception, - start_time=start_time, - end_time=end_time, - ) - callbacks = [] # init this to empty incase it's not created - - if self.dynamic_failure_callbacks is not None and isinstance( - self.dynamic_failure_callbacks, list - ): - callbacks = self.dynamic_failure_callbacks - ## keep the internal functions ## - for callback in litellm.failure_callback: - if ( - isinstance(callback, CustomLogger) - and "_PROXY_" in callback.__class__.__name__ - ): - callbacks.append(callback) - else: - callbacks = litellm.failure_callback - - result = None # result sent to all loggers, init this to None incase it's not created - - self.redact_message_input_output_from_logging(result=result) - for callback in callbacks: - try: - if callback == "lite_debugger": - print_verbose("reaches lite_debugger for logging!") - print_verbose(f"liteDebuggerClient: {liteDebuggerClient}") - result = { - "model": self.model, - "created": time.time(), - "error": traceback_exception, - "usage": { - "prompt_tokens": prompt_token_calculator( - self.model, messages=self.messages - ), - "completion_tokens": 0, - }, - } - liteDebuggerClient.log_event( - model=self.model, - messages=self.messages, - end_user=self.model_call_details.get("user", "default"), - response_obj=result, - start_time=start_time, - end_time=end_time, - litellm_call_id=self.litellm_call_id, - print_verbose=print_verbose, - call_type=self.call_type, - stream=self.stream, - ) - if callback == "lunary": - print_verbose("reaches lunary for logging error!") - - model = self.model - - input = self.model_call_details["input"] - - _type = ( - "embed" - if self.call_type == CallTypes.embedding.value - else "llm" - ) - - lunaryLogger.log_event( - type=_type, - event="error", - user_id=self.model_call_details.get("user", "default"), - model=model, - input=input, - error=traceback_exception, - run_id=self.litellm_call_id, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - ) - if callback == "sentry": - print_verbose("sending exception to sentry") - if capture_exception: - capture_exception(exception) - else: - print_verbose( - f"capture exception not initialized: {capture_exception}" - ) - if callable(callback): # custom logger functions - customLogger.log_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - callback_func=callback, - ) - if ( - isinstance(callback, CustomLogger) - and self.model_call_details.get("litellm_params", {}).get( - "acompletion", False - ) - == False - and self.model_call_details.get("litellm_params", {}).get( - "aembedding", False - ) - == False - ): # custom logger class - callback.log_failure_event( - start_time=start_time, - end_time=end_time, - response_obj=result, - kwargs=self.model_call_details, - ) - if callback == "langfuse": - global langFuseLogger - verbose_logger.debug("reaches langfuse for logging failure") - kwargs = {} - for k, v in self.model_call_details.items(): - if ( - k != "original_response" - ): # copy.deepcopy raises errors as this could be a coroutine - kwargs[k] = v - # this only logs streaming once, complete_streaming_response exists i.e when stream ends - if langFuseLogger is None or ( - ( - self.langfuse_public_key is not None - and self.langfuse_public_key - != langFuseLogger.public_key - ) - and ( - self.langfuse_public_key is not None - and self.langfuse_public_key - != langFuseLogger.public_key - ) - ): - langFuseLogger = LangFuseLogger( - langfuse_public_key=self.langfuse_public_key, - langfuse_secret=self.langfuse_secret, - ) - langFuseLogger.log_event( - start_time=start_time, - end_time=end_time, - response_obj=None, - user_id=kwargs.get("user", None), - print_verbose=print_verbose, - status_message=str(exception), - level="ERROR", - kwargs=self.model_call_details, - ) - if callback == "traceloop": - traceloopLogger.log_event( - start_time=start_time, - end_time=end_time, - response_obj=None, - user_id=kwargs.get("user", None), - print_verbose=print_verbose, - status_message=str(exception), - level="ERROR", - kwargs=self.model_call_details, - ) - if callback == "prometheus": - global prometheusLogger - verbose_logger.debug("reaches prometheus for success logging!") - kwargs = {} - for k, v in self.model_call_details.items(): - if ( - k != "original_response" - ): # copy.deepcopy raises errors as this could be a coroutine - kwargs[k] = v - kwargs["exception"] = str(exception) - prometheusLogger.log_event( - kwargs=kwargs, - response_obj=result, - start_time=start_time, - end_time=end_time, - user_id=kwargs.get("user", None), - print_verbose=print_verbose, - ) - - if callback == "logfire": - global logfireLogger - verbose_logger.debug("reaches logfire for failure logging!") - kwargs = {} - for k, v in self.model_call_details.items(): - if ( - k != "original_response" - ): # copy.deepcopy raises errors as this could be a coroutine - kwargs[k] = v - kwargs["exception"] = exception - - logfireLogger.log_event( - kwargs=kwargs, - response_obj=result, - start_time=start_time, - end_time=end_time, - level=LogfireLevel.ERROR.value, - print_verbose=print_verbose, - ) - except Exception as e: - print_verbose( - f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while failure logging with integrations {str(e)}" - ) - print_verbose( - f"LiteLLM.Logging: is sentry capture exception initialized {capture_exception}" - ) - if capture_exception: # log this error to sentry for debugging - capture_exception(e) - except Exception as e: - print_verbose( - f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while failure logging {traceback.format_exc()}" - ) - pass - - async def async_failure_handler( - self, exception, traceback_exception, start_time=None, end_time=None - ): - """ - Implementing async callbacks, to handle asyncio event loop issues when custom integrations need to use async functions. - """ - start_time, end_time = self._failure_handler_helper_fn( - exception=exception, - traceback_exception=traceback_exception, - start_time=start_time, - end_time=end_time, - ) - result = None # result sent to all loggers, init this to None incase it's not created - for callback in litellm._async_failure_callback: - try: - if isinstance(callback, CustomLogger): # custom logger class - await callback.async_log_failure_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - ) # type: ignore - if callable(callback): # custom logger functions - await customLogger.async_log_event( - kwargs=self.model_call_details, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - callback_func=callback, - ) - except Exception as e: - print_verbose( - f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while success logging {traceback.format_exc()}" - ) - - def redact_message_input_output_from_logging(self, result): - """ - Removes messages, prompts, input, response from logging. This modifies the data in-place - only redacts when litellm.turn_off_message_logging == True - """ - # check if user opted out of logging message/response to callbacks - if litellm.turn_off_message_logging is True: - # remove messages, prompts, input, response from logging - self.model_call_details["messages"] = [ - {"role": "user", "content": "redacted-by-litellm"} - ] - self.model_call_details["prompt"] = "" - self.model_call_details["input"] = "" - - # response cleaning - # ChatCompletion Responses - if self.stream and "complete_streaming_response" in self.model_call_details: - _streaming_response = self.model_call_details[ - "complete_streaming_response" - ] - for choice in _streaming_response.choices: - if isinstance(choice, litellm.Choices): - choice.message.content = "redacted-by-litellm" - elif isinstance(choice, litellm.utils.StreamingChoices): - choice.delta.content = "redacted-by-litellm" - else: - if result is not None: - if isinstance(result, litellm.ModelResponse): - if hasattr(result, "choices") and result.choices is not None: - for choice in result.choices: - if isinstance(choice, litellm.Choices): - choice.message.content = "redacted-by-litellm" - elif isinstance(choice, litellm.utils.StreamingChoices): - choice.delta.content = "redacted-by-litellm" def exception_logging( @@ -2858,6 +327,11 @@ def _init_custom_logger_compatible_class( def function_setup( original_function: str, rules_obj, start_time, *args, **kwargs ): # just run once to check if user wants to send their data anywhere - PostHog/Sentry/Slack/etc. + ### NOTICES ### + if litellm.set_verbose is True: + verbose_logger.warning( + "`litellm.set_verbose` is deprecated. Please set `os.environ['LITELLM_LOG'] = 'DEBUG'` for debug logs." + ) try: global callback_list, add_breadcrumb, user_logger_fn, Logging function_id = kwargs["id"] if "id" in kwargs else None @@ -2898,7 +372,9 @@ def function_setup( + litellm.failure_callback ) ) - set_callbacks(callback_list=callback_list, function_id=function_id) + litellm.litellm_core_utils.litellm_logging.set_callbacks( + callback_list=callback_list, function_id=function_id + ) ## ASYNC CALLBACKS if len(litellm.input_callback) > 0: removed_async_items = [] @@ -3043,7 +519,7 @@ def function_setup( ): messages = kwargs.get("input", "speech") stream = True if "stream" in kwargs and kwargs["stream"] == True else False - logging_obj = Logging( + logging_obj = litellm.litellm_core_utils.litellm_logging.Logging( model=model, messages=messages, stream=stream, @@ -3201,7 +677,7 @@ def client(original_function): ) if previous_models is not None: if litellm.num_retries_per_request <= len(previous_models): - raise Exception(f"Max retries per request hit!") + raise Exception("Max retries per request hit!") # [OPTIONAL] CHECK CACHE print_verbose( @@ -3446,6 +922,7 @@ def client(original_function): isinstance(e, litellm.exceptions.ContextWindowExceededError) and context_window_fallback_dict and model in context_window_fallback_dict + and not _is_litellm_router_call ): if len(args) > 0: args[0] = context_window_fallback_dict[model] @@ -3460,11 +937,6 @@ def client(original_function): logging_obj.failure_handler( e, traceback_exception, start_time, end_time ) # DO NOT MAKE THREADED - router retry fallback relies on this! - my_thread = threading.Thread( - target=handle_failure, - args=(e, traceback_exception, start_time, end_time, args, kwargs), - ) # don't interrupt execution of main thread - my_thread.start() if hasattr(e, "message"): if ( liteDebuggerClient and liteDebuggerClient.dashboard_url != None @@ -3568,7 +1040,7 @@ def client(original_function): if cached_result is not None and not isinstance( cached_result, list ): - print_verbose(f"Cache Hit!") + print_verbose("Cache Hit!", log_level="INFO") cache_hit = True end_time = datetime.datetime.now() ( @@ -4332,229 +1804,6 @@ def token_counter( return num_tokens -def _cost_per_token_custom_pricing_helper( - prompt_tokens=0, - completion_tokens=0, - response_time_ms=None, - ### CUSTOM PRICING ### - custom_cost_per_token: Optional[CostPerToken] = None, - custom_cost_per_second: Optional[float] = None, -) -> Optional[Tuple[float, float]]: - """Internal helper function for calculating cost, if custom pricing given""" - if custom_cost_per_token is None and custom_cost_per_second is None: - return None - - if custom_cost_per_token is not None: - input_cost = custom_cost_per_token["input_cost_per_token"] * prompt_tokens - output_cost = custom_cost_per_token["output_cost_per_token"] * completion_tokens - return input_cost, output_cost - elif custom_cost_per_second is not None: - output_cost = custom_cost_per_second * response_time_ms / 1000 # type: ignore - return 0, output_cost - - return None - - -def cost_per_token( - model: str = "", - prompt_tokens=0, - completion_tokens=0, - response_time_ms=None, - custom_llm_provider=None, - region_name=None, - ### CUSTOM PRICING ### - custom_cost_per_token: Optional[CostPerToken] = None, - custom_cost_per_second: Optional[float] = None, -) -> Tuple[float, float]: - """ - Calculates the cost per token for a given model, prompt tokens, and completion tokens. - - Parameters: - model (str): The name of the model to use. Default is "" - prompt_tokens (int): The number of tokens in the prompt. - completion_tokens (int): The number of tokens in the completion. - response_time (float): The amount of time, in milliseconds, it took the call to complete. - custom_llm_provider (str): The llm provider to whom the call was made (see init.py for full list) - custom_cost_per_token: Optional[CostPerToken]: the cost per input + output token for the llm api call. - custom_cost_per_second: Optional[float]: the cost per second for the llm api call. - - Returns: - tuple: A tuple containing the cost in USD dollars for prompt tokens and completion tokens, respectively. - """ - if model is None: - raise Exception("Invalid arg. Model cannot be none.") - ## CUSTOM PRICING ## - response_cost = _cost_per_token_custom_pricing_helper( - prompt_tokens=prompt_tokens, - completion_tokens=completion_tokens, - response_time_ms=response_time_ms, - custom_cost_per_second=custom_cost_per_second, - custom_cost_per_token=custom_cost_per_token, - ) - if response_cost is not None: - return response_cost[0], response_cost[1] - - # given - prompt_tokens_cost_usd_dollar: float = 0 - completion_tokens_cost_usd_dollar: float = 0 - model_cost_ref = litellm.model_cost - model_with_provider = model - if custom_llm_provider is not None: - model_with_provider = custom_llm_provider + "/" + model - if region_name is not None: - model_with_provider_and_region = ( - f"{custom_llm_provider}/{region_name}/{model}" - ) - if ( - model_with_provider_and_region in model_cost_ref - ): # use region based pricing, if it's available - model_with_provider = model_with_provider_and_region - - model_without_prefix = model - model_parts = model.split("/") - if len(model_parts) > 1: - model_without_prefix = model_parts[1] - else: - model_without_prefix = model - """ - Code block that formats model to lookup in litellm.model_cost - Option1. model = "bedrock/ap-northeast-1/anthropic.claude-instant-v1". This is the most accurate since it is region based. Should always be option 1 - Option2. model = "openai/gpt-4" - model = provider/model - Option3. model = "anthropic.claude-3" - model = model - """ - if ( - model_with_provider in model_cost_ref - ): # Option 2. use model with provider, model = "openai/gpt-4" - model = model_with_provider - elif model in model_cost_ref: # Option 1. use model passed, model="gpt-4" - model = model - elif ( - model_without_prefix in model_cost_ref - ): # Option 3. if user passed model="bedrock/anthropic.claude-3", use model="anthropic.claude-3" - model = model_without_prefix - - # see this https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models - print_verbose(f"Looking up model={model} in model_cost_map") - if model in model_cost_ref: - print_verbose(f"Success: model={model} in model_cost_map") - print_verbose( - f"prompt_tokens={prompt_tokens}; completion_tokens={completion_tokens}" - ) - if ( - model_cost_ref[model].get("input_cost_per_token", None) is not None - and model_cost_ref[model].get("output_cost_per_token", None) is not None - ): - ## COST PER TOKEN ## - prompt_tokens_cost_usd_dollar = ( - model_cost_ref[model]["input_cost_per_token"] * prompt_tokens - ) - completion_tokens_cost_usd_dollar = ( - model_cost_ref[model]["output_cost_per_token"] * completion_tokens - ) - elif ( - model_cost_ref[model].get("output_cost_per_second", None) is not None - and response_time_ms is not None - ): - print_verbose( - f"For model={model} - output_cost_per_second: {model_cost_ref[model].get('output_cost_per_second')}; response time: {response_time_ms}" - ) - ## COST PER SECOND ## - prompt_tokens_cost_usd_dollar = 0 - completion_tokens_cost_usd_dollar = ( - model_cost_ref[model]["output_cost_per_second"] - * response_time_ms - / 1000 - ) - elif ( - model_cost_ref[model].get("input_cost_per_second", None) is not None - and response_time_ms is not None - ): - print_verbose( - f"For model={model} - input_cost_per_second: {model_cost_ref[model].get('input_cost_per_second')}; response time: {response_time_ms}" - ) - ## COST PER SECOND ## - prompt_tokens_cost_usd_dollar = ( - model_cost_ref[model]["input_cost_per_second"] * response_time_ms / 1000 - ) - completion_tokens_cost_usd_dollar = 0.0 - print_verbose( - f"Returned custom cost for model={model} - prompt_tokens_cost_usd_dollar: {prompt_tokens_cost_usd_dollar}, completion_tokens_cost_usd_dollar: {completion_tokens_cost_usd_dollar}" - ) - return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar - elif "ft:gpt-3.5-turbo" in model: - print_verbose(f"Cost Tracking: {model} is an OpenAI FinteTuned LLM") - # fuzzy match ft:gpt-3.5-turbo:abcd-id-cool-litellm - prompt_tokens_cost_usd_dollar = ( - model_cost_ref["ft:gpt-3.5-turbo"]["input_cost_per_token"] * prompt_tokens - ) - completion_tokens_cost_usd_dollar = ( - model_cost_ref["ft:gpt-3.5-turbo"]["output_cost_per_token"] - * completion_tokens - ) - return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar - elif "ft:davinci-002" in model: - print_verbose(f"Cost Tracking: {model} is an OpenAI FinteTuned LLM") - # fuzzy match ft:davinci-002:abcd-id-cool-litellm - prompt_tokens_cost_usd_dollar = ( - model_cost_ref["ft:davinci-002"]["input_cost_per_token"] * prompt_tokens - ) - completion_tokens_cost_usd_dollar = ( - model_cost_ref["ft:davinci-002"]["output_cost_per_token"] - * completion_tokens - ) - return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar - elif "ft:babbage-002" in model: - print_verbose(f"Cost Tracking: {model} is an OpenAI FinteTuned LLM") - # fuzzy match ft:babbage-002:abcd-id-cool-litellm - prompt_tokens_cost_usd_dollar = ( - model_cost_ref["ft:babbage-002"]["input_cost_per_token"] * prompt_tokens - ) - completion_tokens_cost_usd_dollar = ( - model_cost_ref["ft:babbage-002"]["output_cost_per_token"] - * completion_tokens - ) - return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar - elif model in litellm.azure_llms: - verbose_logger.debug(f"Cost Tracking: {model} is an Azure LLM") - model = litellm.azure_llms[model] - verbose_logger.debug( - f"applying cost={model_cost_ref[model]['input_cost_per_token']} for prompt_tokens={prompt_tokens}" - ) - prompt_tokens_cost_usd_dollar = ( - model_cost_ref[model]["input_cost_per_token"] * prompt_tokens - ) - verbose_logger.debug( - f"applying cost={model_cost_ref[model]['output_cost_per_token']} for completion_tokens={completion_tokens}" - ) - completion_tokens_cost_usd_dollar = ( - model_cost_ref[model]["output_cost_per_token"] * completion_tokens - ) - return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar - elif model in litellm.azure_embedding_models: - verbose_logger.debug(f"Cost Tracking: {model} is an Azure Embedding Model") - model = litellm.azure_embedding_models[model] - prompt_tokens_cost_usd_dollar = ( - model_cost_ref[model]["input_cost_per_token"] * prompt_tokens - ) - completion_tokens_cost_usd_dollar = ( - model_cost_ref[model]["output_cost_per_token"] * completion_tokens - ) - return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar - else: - # if model is not in model_prices_and_context_window.json. Raise an exception-let users know - error_str = f"Model not in model_prices_and_context_window.json. You passed model={model}. Register pricing for model - https://docs.litellm.ai/docs/proxy/custom_pricing\n" - raise litellm.exceptions.NotFoundError( # type: ignore - message=error_str, - model=model, - response=httpx.Response( - status_code=404, - content=error_str, - request=httpx.Request(method="cost_per_token", url="https://github.com/BerriAI/litellm"), # type: ignore - ), - llm_provider="", - ) - - def supports_httpx_timeout(custom_llm_provider: str) -> bool: """ Helper function to know if a provider implementation supports httpx timeout @@ -6963,13 +4212,14 @@ def get_max_tokens(model: str): ) -def get_model_info(model: str) -> ModelInfo: +def get_model_info(model: str, custom_llm_provider: Optional[str] = None) -> ModelInfo: """ Get a dict for the maximum tokens (context window), input_cost_per_token, output_cost_per_token for a given model. Parameters: - model (str): The name of the model. + - model (str): The name of the model. + - custom_llm_provider (str | null): the provider used for the model. If provided, used to check if the litellm model info is for that provider. Returns: dict: A dictionary containing the following information: @@ -7023,12 +4273,14 @@ def get_model_info(model: str) -> ModelInfo: if model in azure_llms: model = azure_llms[model] ########################## - # Get custom_llm_provider - split_model, custom_llm_provider = model, "" - try: - split_model, custom_llm_provider, _, _ = get_llm_provider(model=model) - except: - pass + if custom_llm_provider is None: + # Get custom_llm_provider + try: + split_model, custom_llm_provider, _, _ = get_llm_provider(model=model) + except: + pass + else: + split_model = model ######################### supported_openai_params = litellm.get_supported_openai_params( @@ -7053,10 +4305,20 @@ def get_model_info(model: str) -> ModelInfo: if model in litellm.model_cost: _model_info = litellm.model_cost[model] _model_info["supported_openai_params"] = supported_openai_params + if ( + "litellm_provider" in _model_info + and _model_info["litellm_provider"] != custom_llm_provider + ): + raise Exception return _model_info if split_model in litellm.model_cost: _model_info = litellm.model_cost[split_model] _model_info["supported_openai_params"] = supported_openai_params + if ( + "litellm_provider" in _model_info + and _model_info["litellm_provider"] != custom_llm_provider + ): + raise Exception return _model_info else: raise ValueError( @@ -7509,264 +4771,6 @@ def validate_environment(model: Optional[str] = None) -> dict: return {"keys_in_environment": keys_in_environment, "missing_keys": missing_keys} -def set_callbacks(callback_list, function_id=None): - global sentry_sdk_instance, capture_exception, add_breadcrumb, posthog, slack_app, alerts_channel, traceloopLogger, athinaLogger, heliconeLogger, aispendLogger, berrispendLogger, supabaseClient, liteDebuggerClient, lunaryLogger, promptLayerLogger, langFuseLogger, customLogger, weightsBiasesLogger, langsmithLogger, logfireLogger, dynamoLogger, s3Logger, dataDogLogger, prometheusLogger, greenscaleLogger, openMeterLogger - - try: - for callback in callback_list: - print_verbose(f"init callback list: {callback}") - if callback == "sentry": - try: - import sentry_sdk - except ImportError: - print_verbose("Package 'sentry_sdk' is missing. Installing it...") - subprocess.check_call( - [sys.executable, "-m", "pip", "install", "sentry_sdk"] - ) - import sentry_sdk - sentry_sdk_instance = sentry_sdk - sentry_trace_rate = ( - os.environ.get("SENTRY_API_TRACE_RATE") - if "SENTRY_API_TRACE_RATE" in os.environ - else "1.0" - ) - sentry_sdk_instance.init( - dsn=os.environ.get("SENTRY_DSN"), - traces_sample_rate=float(sentry_trace_rate), - ) - capture_exception = sentry_sdk_instance.capture_exception - add_breadcrumb = sentry_sdk_instance.add_breadcrumb - elif callback == "posthog": - try: - from posthog import Posthog - except ImportError: - print_verbose("Package 'posthog' is missing. Installing it...") - subprocess.check_call( - [sys.executable, "-m", "pip", "install", "posthog"] - ) - from posthog import Posthog - posthog = Posthog( - project_api_key=os.environ.get("POSTHOG_API_KEY"), - host=os.environ.get("POSTHOG_API_URL"), - ) - elif callback == "slack": - try: - from slack_bolt import App - except ImportError: - print_verbose("Package 'slack_bolt' is missing. Installing it...") - subprocess.check_call( - [sys.executable, "-m", "pip", "install", "slack_bolt"] - ) - from slack_bolt import App - slack_app = App( - token=os.environ.get("SLACK_API_TOKEN"), - signing_secret=os.environ.get("SLACK_API_SECRET"), - ) - alerts_channel = os.environ["SLACK_API_CHANNEL"] - print_verbose(f"Initialized Slack App: {slack_app}") - elif callback == "traceloop": - traceloopLogger = TraceloopLogger() - elif callback == "athina": - athinaLogger = AthinaLogger() - print_verbose("Initialized Athina Logger") - elif callback == "helicone": - heliconeLogger = HeliconeLogger() - elif callback == "lunary": - lunaryLogger = LunaryLogger() - elif callback == "promptlayer": - promptLayerLogger = PromptLayerLogger() - elif callback == "langfuse": - langFuseLogger = LangFuseLogger() - elif callback == "openmeter": - openMeterLogger = OpenMeterLogger() - elif callback == "datadog": - dataDogLogger = DataDogLogger() - elif callback == "prometheus": - if prometheusLogger is None: - prometheusLogger = PrometheusLogger() - elif callback == "dynamodb": - dynamoLogger = DyanmoDBLogger() - elif callback == "s3": - s3Logger = S3Logger() - elif callback == "wandb": - weightsBiasesLogger = WeightsBiasesLogger() - elif callback == "langsmith": - langsmithLogger = LangsmithLogger() - elif callback == "logfire": - logfireLogger = LogfireLogger() - elif callback == "aispend": - aispendLogger = AISpendLogger() - elif callback == "berrispend": - berrispendLogger = BerriSpendLogger() - elif callback == "supabase": - print_verbose(f"instantiating supabase") - supabaseClient = Supabase() - elif callback == "greenscale": - greenscaleLogger = GreenscaleLogger() - print_verbose("Initialized Greenscale Logger") - elif callback == "lite_debugger": - print_verbose(f"instantiating lite_debugger") - if function_id: - liteDebuggerClient = LiteDebugger(email=function_id) - elif litellm.token: - liteDebuggerClient = LiteDebugger(email=litellm.token) - elif litellm.email: - liteDebuggerClient = LiteDebugger(email=litellm.email) - else: - liteDebuggerClient = LiteDebugger(email=str(uuid.uuid4())) - elif callable(callback): - customLogger = CustomLogger() - except Exception as e: - raise e - - -# NOTE: DEPRECATING this in favor of using failure_handler() in Logging: -def handle_failure(exception, traceback_exception, start_time, end_time, args, kwargs): - global sentry_sdk_instance, capture_exception, add_breadcrumb, posthog, slack_app, alerts_channel, aispendLogger, berrispendLogger, supabaseClient, liteDebuggerClient, lunaryLogger - try: - # print_verbose(f"handle_failure args: {args}") - # print_verbose(f"handle_failure kwargs: {kwargs}") - - success_handler = additional_details.pop("success_handler", None) - failure_handler = additional_details.pop("failure_handler", None) - - additional_details["Event_Name"] = additional_details.pop( - "failed_event_name", "litellm.failed_query" - ) - print_verbose(f"self.failure_callback: {litellm.failure_callback}") - for callback in litellm.failure_callback: - try: - if callback == "slack": - slack_msg = "" - if len(kwargs) > 0: - for key in kwargs: - slack_msg += f"{key}: {kwargs[key]}\n" - if len(args) > 0: - for i, arg in enumerate(args): - slack_msg += f"LiteLLM_Args_{str(i)}: {arg}" - for detail in additional_details: - slack_msg += f"{detail}: {additional_details[detail]}\n" - slack_msg += f"Traceback: {traceback_exception}" - truncated_slack_msg = textwrap.shorten( - slack_msg, width=512, placeholder="..." - ) - slack_app.client.chat_postMessage( - channel=alerts_channel, text=truncated_slack_msg - ) - elif callback == "sentry": - capture_exception(exception) - elif callback == "posthog": - print_verbose( - f"inside posthog, additional_details: {len(additional_details.keys())}" - ) - ph_obj = {} - if len(kwargs) > 0: - ph_obj = kwargs - if len(args) > 0: - for i, arg in enumerate(args): - ph_obj["litellm_args_" + str(i)] = arg - for detail in additional_details: - ph_obj[detail] = additional_details[detail] - event_name = additional_details["Event_Name"] - print_verbose(f"ph_obj: {ph_obj}") - print_verbose(f"PostHog Event Name: {event_name}") - if "user_id" in additional_details: - posthog.capture( - additional_details["user_id"], event_name, ph_obj - ) - else: # PostHog calls require a unique id to identify a user - https://posthog.com/docs/libraries/python - unique_id = str(uuid.uuid4()) - posthog.capture(unique_id, event_name) - print_verbose(f"successfully logged to PostHog!") - elif callback == "berrispend": - print_verbose("reaches berrispend for logging!") - model = args[0] if len(args) > 0 else kwargs["model"] - messages = args[1] if len(args) > 1 else kwargs["messages"] - result = { - "model": model, - "created": time.time(), - "error": traceback_exception, - "usage": { - "prompt_tokens": prompt_token_calculator( - model, messages=messages - ), - "completion_tokens": 0, - }, - } - berrispendLogger.log_event( - model=model, - messages=messages, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - ) - elif callback == "aispend": - print_verbose("reaches aispend for logging!") - model = args[0] if len(args) > 0 else kwargs["model"] - messages = args[1] if len(args) > 1 else kwargs["messages"] - result = { - "model": model, - "created": time.time(), - "usage": { - "prompt_tokens": prompt_token_calculator( - model, messages=messages - ), - "completion_tokens": 0, - }, - } - aispendLogger.log_event( - model=model, - response_obj=result, - start_time=start_time, - end_time=end_time, - print_verbose=print_verbose, - ) - elif callback == "supabase": - print_verbose("reaches supabase for logging!") - print_verbose(f"supabaseClient: {supabaseClient}") - model = args[0] if len(args) > 0 else kwargs["model"] - messages = args[1] if len(args) > 1 else kwargs["messages"] - result = { - "model": model, - "created": time.time(), - "error": traceback_exception, - "usage": { - "prompt_tokens": prompt_token_calculator( - model, messages=messages - ), - "completion_tokens": 0, - }, - } - supabaseClient.log_event( - model=model, - messages=messages, - end_user=kwargs.get("user", "default"), - response_obj=result, - start_time=start_time, - end_time=end_time, - litellm_call_id=kwargs["litellm_call_id"], - print_verbose=print_verbose, - ) - except: - print_verbose( - f"Error Occurred while logging failure: {traceback.format_exc()}" - ) - pass - - if failure_handler and callable(failure_handler): - call_details = { - "exception": exception, - "additional_details": additional_details, - } - failure_handler(call_details) - pass - except Exception as e: - # LOGGING - exception_logging(logger_fn=user_logger_fn, exception=e) - pass - - async def convert_to_streaming_response_async(response_object: Optional[dict] = None): """ Asynchronously converts a response object to a streaming response. @@ -8417,7 +5421,7 @@ def exception_type( extra_information = _add_key_name_and_team_to_alert( request_info=extra_information, metadata=_metadata ) - except: + except Exception: # DO NOT LET this Block raising the original exception pass @@ -8634,32 +5638,33 @@ def exception_type( ), ) elif custom_llm_provider == "anthropic": # one of the anthropics - if hasattr(original_exception, "message"): - if ( - "prompt is too long" in original_exception.message - or "prompt: length" in original_exception.message - ): - exception_mapping_worked = True - raise ContextWindowExceededError( - message=original_exception.message, - model=model, - llm_provider="anthropic", - response=original_exception.response, - ) - if "Invalid API Key" in original_exception.message: - exception_mapping_worked = True - raise AuthenticationError( - message=original_exception.message, - model=model, - llm_provider="anthropic", - response=original_exception.response, - ) + if "prompt is too long" in error_str or "prompt: length" in error_str: + exception_mapping_worked = True + raise ContextWindowExceededError( + message=error_str, + model=model, + llm_provider="anthropic", + ) + if "Invalid API Key" in error_str: + exception_mapping_worked = True + raise AuthenticationError( + message=error_str, + model=model, + llm_provider="anthropic", + ) + if "content filtering policy" in error_str: + exception_mapping_worked = True + raise ContentPolicyViolationError( + message=error_str, + model=model, + llm_provider="anthropic", + ) if hasattr(original_exception, "status_code"): print_verbose(f"status_code: {original_exception.status_code}") if original_exception.status_code == 401: exception_mapping_worked = True raise AuthenticationError( - message=f"AnthropicException - {original_exception.message}", + message=f"AnthropicException - {error_str}", llm_provider="anthropic", model=model, response=original_exception.response, @@ -8670,7 +5675,7 @@ def exception_type( ): exception_mapping_worked = True raise BadRequestError( - message=f"AnthropicException - {original_exception.message}", + message=f"AnthropicException - {error_str}", model=model, llm_provider="anthropic", response=original_exception.response, @@ -8678,14 +5683,14 @@ def exception_type( elif original_exception.status_code == 408: exception_mapping_worked = True raise Timeout( - message=f"AnthropicException - {original_exception.message}", + message=f"AnthropicException - {error_str}", model=model, llm_provider="anthropic", ) elif original_exception.status_code == 429: exception_mapping_worked = True raise RateLimitError( - message=f"AnthropicException - {original_exception.message}", + message=f"AnthropicException - {error_str}", llm_provider="anthropic", model=model, response=original_exception.response, @@ -8694,7 +5699,7 @@ def exception_type( exception_mapping_worked = True raise APIError( status_code=500, - message=f"AnthropicException - {original_exception.message}. Handle with `litellm.APIError`.", + message=f"AnthropicException - {error_str}. Handle with `litellm.APIError`.", llm_provider="anthropic", model=model, request=original_exception.request, @@ -9953,6 +6958,9 @@ def exception_type( response=original_exception.response, ) else: # ensure generic errors always return APIConnectionError= + """ + For unmapped exceptions - raise the exception with traceback - https://github.com/BerriAI/litellm/issues/4201 + """ exception_mapping_worked = True if hasattr(original_exception, "request"): raise APIConnectionError( @@ -9963,7 +6971,9 @@ def exception_type( ) else: raise APIConnectionError( - message=f"{str(original_exception)}", + message="{}\n{}".format( + str(original_exception), traceback.format_exc() + ), llm_provider=custom_llm_provider, model=model, request=httpx.Request( @@ -9989,7 +6999,15 @@ def exception_type( if exception_mapping_worked: raise e else: - raise original_exception + raise APIConnectionError( + message="{}\n{}".format(original_exception, traceback.format_exc()), + llm_provider="", + model="", + request=httpx.Request( + method="POST", + url="https://www.litellm.ai/", + ), + ) def get_or_generate_uuid(): diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json index 385dc2ead02..98da8d69c0c 100644 --- a/model_prices_and_context_window.json +++ b/model_prices_and_context_window.json @@ -3347,6 +3347,24 @@ "litellm_provider": "deepinfra", "mode": "chat" }, + "deepinfra/meta-llama/Meta-Llama-3-8B-Instruct": { + "max_tokens": 8191, + "max_input_tokens": 8191, + "max_output_tokens": 4096, + "input_cost_per_token": 0.00000008, + "output_cost_per_token": 0.00000008, + "litellm_provider": "deepinfra", + "mode": "chat" + }, + "deepinfra/meta-llama/Meta-Llama-3-70B-Instruct": { + "max_tokens": 8191, + "max_input_tokens": 8191, + "max_output_tokens": 4096, + "input_cost_per_token": 0.00000059, + "output_cost_per_token": 0.00000079, + "litellm_provider": "deepinfra", + "mode": "chat" + }, "deepinfra/01-ai/Yi-34B-200K": { "max_tokens": 4096, "max_input_tokens": 200000, diff --git a/poetry.lock b/poetry.lock index ac946690c09..750def10168 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2174,7 +2174,6 @@ files = [ {file = "PyYAML-6.0.1-cp311-cp311-win_amd64.whl", hash = "sha256:bf07ee2fef7014951eeb99f56f39c9bb4af143d8aa3c21b1677805985307da34"}, {file = "PyYAML-6.0.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:855fb52b0dc35af121542a76b9a84f8d1cd886ea97c84703eaa6d88e37a2ad28"}, {file = "PyYAML-6.0.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:40df9b996c2b73138957fe23a16a4f0ba614f4c0efce1e9406a184b6d07fa3a9"}, - {file = "PyYAML-6.0.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a08c6f0fe150303c1c6b71ebcd7213c2858041a7e01975da3a99aed1e7a378ef"}, {file = "PyYAML-6.0.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6c22bec3fbe2524cde73d7ada88f6566758a8f7227bfbf93a408a9d86bcc12a0"}, {file = "PyYAML-6.0.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8d4e9c88387b0f5c7d5f281e55304de64cf7f9c0021a3525bd3b1c542da3b0e4"}, {file = "PyYAML-6.0.1-cp312-cp312-win32.whl", hash = "sha256:d483d2cdf104e7c9fa60c544d92981f12ad66a457afae824d146093b8c294c54"}, @@ -3198,4 +3197,4 @@ proxy = ["PyJWT", "apscheduler", "backoff", "cryptography", "fastapi", "fastapi- [metadata] lock-version = "2.0" python-versions = ">=3.8.1,<4.0, !=3.9.7" -content-hash = "73054c657782120d170dc168ef07b494a916f1f810ff9c2b0ac878bd857a9dac" +content-hash = "62156f0fa65f39f36576ef6ed91d773658399757111dd4b0660e1ce2a58ea7b2" diff --git a/pyproject.toml b/pyproject.toml index 462ebb6426e..5a6fd15ad24 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "litellm" -version = "1.40.10" +version = "1.40.15" description = "Library to easily interface with LLM API providers" authors = ["BerriAI"] license = "MIT" @@ -26,6 +26,7 @@ click = "*" jinja2 = "^3.1.2" aiohttp = "*" requests = "^2.31.0" +pydantic = "^2.0.0" uvicorn = {version = "^0.22.0", optional = true} gunicorn = {version = "^22.0.0", optional = true} @@ -85,7 +86,7 @@ requires = ["poetry-core", "wheel"] build-backend = "poetry.core.masonry.api" [tool.commitizen] -version = "1.40.10" +version = "1.40.15" version_files = [ "pyproject.toml:^version" ] diff --git a/requirements.txt b/requirements.txt index 07dc7e347cf..ab755fec335 100644 --- a/requirements.txt +++ b/requirements.txt @@ -27,7 +27,7 @@ pyjwt[crypto]==2.8.0 python-multipart==0.0.9 # admin UI Pillow==10.3.0 azure-ai-contentsafety==1.0.0 # for azure content safety -azure-identity==1.15.0 # for azure content safety +azure-identity==1.16.1 # for azure content safety opentelemetry-api==1.25.0 opentelemetry-sdk==1.25.0 opentelemetry-exporter-otlp==1.25.0 @@ -43,5 +43,5 @@ certifi==2023.7.22 # [TODO] clean up aiohttp==3.9.0 # for network calls aioboto3==12.3.0 # for async sagemaker calls tenacity==8.2.3 # for retrying requests, when litellm.num_retries set -pydantic==2.7.1 # openai req. +pydantic==2.7.1 # proxy + openai req. #### \ No newline at end of file diff --git a/ui/litellm-dashboard/out/404.html b/ui/litellm-dashboard/out/404.html index e97c72fc132..e648c625ed2 100644 --- a/ui/litellm-dashboard/out/404.html +++ b/ui/litellm-dashboard/out/404.html @@ -1 +1 @@ -404: This page could not be found.LiteLLM Dashboard

404

This page could not be found.

\ No newline at end of file +404: This page could not be found.LiteLLM Dashboard

404

This page could not be found.

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deployment_name="azure-embedding-model",\n azure_endpoint="http://0.0.0.0:4000",\n api_key="sk-1234",\n api_version="2023-07-01-preview",\n)\n\n\ndocuments = SimpleDirectoryReader("llama_index_data").load_data()\nservice_context = ServiceContext.from_defaults(llm=llm, embed_model=embed_model)\nindex = VectorStoreIndex.from_documents(documents, service_context=service_context)\n\nquery_engine = index.as_query_engine()\nresponse = query_engine.query("What did the author do growing up?")\nprint(response)\n\n ')})}),(0,t.jsx)(u.Z,{children:(0,t.jsx)(_.Z,{language:"python",children:'\nfrom langchain.chat_models import ChatOpenAI\nfrom langchain.prompts.chat import (\n ChatPromptTemplate,\n HumanMessagePromptTemplate,\n SystemMessagePromptTemplate,\n)\nfrom langchain.schema import HumanMessage, SystemMessage\n\nchat = ChatOpenAI(\n openai_api_base="http://0.0.0.0:4000",\n model = "'.concat(P.model_group,'",\n temperature=0.1\n)\n\nmessages = [\n SystemMessage(\n content="You are a helpful 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80efdd2cfc6..100478a2106 100644 --- a/ui/litellm-dashboard/package-lock.json +++ b/ui/litellm-dashboard/package-lock.json @@ -1550,11 +1550,11 @@ } }, "node_modules/braces": { - "version": "3.0.2", - "resolved": "https://registry.npmjs.org/braces/-/braces-3.0.2.tgz", - "integrity": "sha512-b8um+L1RzM3WDSzvhm6gIz1yfTbBt6YTlcEKAvsmqCZZFw46z626lVj9j1yEPW33H5H+lBQpZMP1k8l+78Ha0A==", + "version": "3.0.3", + "resolved": "https://registry.npmjs.org/braces/-/braces-3.0.3.tgz", + "integrity": "sha512-yQbXgO/OSZVD2IsiLlro+7Hf6Q18EJrKSEsdoMzKePKXct3gvD8oLcOQdIzGupr5Fj+EDe8gO/lxc1BzfMpxvA==", "dependencies": { - "fill-range": "^7.0.1" + "fill-range": "^7.1.1" }, "engines": { "node": ">=8" @@ -2862,9 +2862,9 @@ } }, "node_modules/fill-range": { - "version": "7.0.1", - "resolved": "https://registry.npmjs.org/fill-range/-/fill-range-7.0.1.tgz", - "integrity": "sha512-qOo9F+dMUmC2Lcb4BbVvnKJxTPjCm+RRpe4gDuGrzkL7mEVl/djYSu2OdQ2Pa302N4oqkSg9ir6jaLWJ2USVpQ==", + "version": "7.1.1", + "resolved": "https://registry.npmjs.org/fill-range/-/fill-range-7.1.1.tgz", + "integrity": "sha512-YsGpe3WHLK8ZYi4tWDg2Jy3ebRz2rXowDxnld4bkQB00cc/1Zw9AWnC0i9ztDJitivtQvaI9KaLyKrc+hBW0yg==", "dependencies": { "to-regex-range": "^5.0.1" }, diff --git a/ui/litellm-dashboard/src/components/budgets/budget_modal.tsx b/ui/litellm-dashboard/src/components/budgets/budget_modal.tsx index 2c32d88bd09..551e8d37a02 100644 --- a/ui/litellm-dashboard/src/components/budgets/budget_modal.tsx +++ b/ui/litellm-dashboard/src/components/budgets/budget_modal.tsx @@ -122,6 +122,7 @@ const BudgetModal: React.FC = ({ > diff --git a/ui/litellm-dashboard/src/components/budgets/budget_panel.tsx b/ui/litellm-dashboard/src/components/budgets/budget_panel.tsx index c52ca163188..4d2752a9b59 100644 --- a/ui/litellm-dashboard/src/components/budgets/budget_panel.tsx +++ b/ui/litellm-dashboard/src/components/budgets/budget_panel.tsx @@ -6,6 +6,7 @@ import React, { useState, useEffect } from "react"; import BudgetSettings from "./budget_settings"; import BudgetModal from "./budget_modal"; +import EditBudgetModal from "./edit_budget_modal"; import { Table, TableBody, @@ -43,7 +44,7 @@ interface BudgetSettingsPageProps { accessToken: string | null; } -interface budgetItem { +export interface budgetItem { budget_id: string; max_budget: string | null; rpm_limit: number | null; @@ -52,6 +53,8 @@ interface budgetItem { const BudgetPanel: React.FC = ({ accessToken }) => { const [isModalVisible, setIsModalVisible] = useState(false); + const [isEditModalVisible, setIsEditModalVisible] = useState(false); + const [selectedBudget, setSelectedBudget] = useState(null); const [budgetList, setBudgetList] = useState([]); useEffect(() => { if (!accessToken) { @@ -62,6 +65,15 @@ const BudgetPanel: React.FC = ({ accessToken }) => { }); }, [accessToken]); + + const handleEditCall = async (budget_id: string, index: number) => { + if (accessToken == null) { + return; + } + setSelectedBudget(budgetList[index]) + setIsEditModalVisible(true) + }; + const handleDeleteCall = async (budget_id: string, index: number) => { if (accessToken == null) { return; @@ -94,6 +106,15 @@ const BudgetPanel: React.FC = ({ accessToken }) => { setIsModalVisible={setIsModalVisible} setBudgetList={setBudgetList} /> + { + selectedBudget && + } Create a budget to assign to customers. @@ -119,6 +140,11 @@ const BudgetPanel: React.FC = ({ accessToken }) => { {value.rpm_limit ? value.rpm_limit : "n/a"} + handleEditCall(value.budget_id, index)} + /> >; + setBudgetList: React.Dispatch>; + existingBudget: budgetItem +} +const EditBudgetModal: React.FC = ({ + isModalVisible, + accessToken, + setIsModalVisible, + setBudgetList, + existingBudget +}) => { + const [form] = Form.useForm(); + const handleOk = () => { + setIsModalVisible(false); + form.resetFields(); + }; + + const handleCancel = () => { + setIsModalVisible(false); + form.resetFields(); + }; + + const handleCreate = async (formValues: Record) => { + if (accessToken == null || accessToken == undefined) { + return; + } + try { + message.info("Making API Call"); + // setIsModalVisible(true); + const response = await budgetCreateCall(accessToken, formValues); + console.log("key create Response:", response); + setBudgetList((prevData) => + prevData ? [...prevData, response] : [response] + ); // Check if prevData is null + message.success("API Key Created"); + form.resetFields(); + } catch (error) { + console.error("Error creating the key:", error); + message.error(`Error creating the key: ${error}`, 20); + } + }; + + return ( + +
+ <> + + + + + + + + + + + + + Optional Settings + + + + + + + + + + + + +
+ Edit Budget +
+ + + ); +}; + +export default EditBudgetModal; diff --git a/ui/litellm-dashboard/src/components/create_key_button.tsx b/ui/litellm-dashboard/src/components/create_key_button.tsx index 83e8d926474..75edb2ef3bc 100644 --- a/ui/litellm-dashboard/src/components/create_key_button.tsx +++ b/ui/litellm-dashboard/src/components/create_key_button.tsx @@ -261,6 +261,7 @@ const CreateKey: React.FC = ({ > diff --git a/ui/litellm-dashboard/src/components/model_dashboard.tsx b/ui/litellm-dashboard/src/components/model_dashboard.tsx index e18f4233eb7..fb189b8c446 100644 --- a/ui/litellm-dashboard/src/components/model_dashboard.tsx +++ b/ui/litellm-dashboard/src/components/model_dashboard.tsx @@ -1531,7 +1531,7 @@ const ModelDashboard: React.FC = ({ 
                               {model.input_cost
                                 ? model.input_cost
-                                : model.litellm_params.input_cost_per_token
+                                : model.litellm_params.input_cost_per_token != null && model.litellm_params.input_cost_per_token != undefined
                                   ? (
                                       Number(
                                         model.litellm_params
@@ -2080,6 +2080,24 @@ const ModelDashboard: React.FC = ({
                 
               
             
+            
+            
+
+            All Exceptions for {selectedModelGroup}
+             
+             
+                          
+      
+            
+
 
             
                 
@@ -2098,15 +2116,7 @@ const ModelDashboard: React.FC = ({
- {/* */} - + diff --git a/ui/litellm-dashboard/src/components/teams.tsx b/ui/litellm-dashboard/src/components/teams.tsx index 9e5758a283d..8b4b803b563 100644 --- a/ui/litellm-dashboard/src/components/teams.tsx +++ b/ui/litellm-dashboard/src/components/teams.tsx @@ -151,6 +151,17 @@ const Team: React.FC = ({ + + + daily + weekly + monthly + + @@ -427,7 +438,7 @@ const Team: React.FC = ({ overflow: "hidden", }} > - {team["max_budget"] ? team["max_budget"] : "No limit"} + {team["max_budget"] !== null && team["max_budget"] !== undefined ? team["max_budget"] : "No limit"} = ({ + + + daily + weekly + monthly + + = ({ showLegend={true} index="date" categories={uniqueTeamIds} - yAxisWidth={80} - colors={["blue", "green", "yellow", "red", "purple"]} - + yAxisWidth={80} stack={true} />