mirror of
https://github.com/BerriAI/litellm.git
synced 2026-09-09 22:31:41 +00:00
Merge branch 'BerriAI:main' into kowyo/fix-ollama-think
This commit is contained in:
Kowyo
GitHub
commit
89aad0e21f
230 changed files with 2468 additions and 681 deletions
|
|
@ -676,18 +676,16 @@ jobs:
|
|||
working_directory: ~/project
|
||||
steps:
|
||||
- checkout
|
||||
- run:
|
||||
name: Install PostgreSQL
|
||||
command: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install postgresql postgresql-contrib
|
||||
echo 'export PATH=/usr/lib/postgresql/*/bin:$PATH' >> $BASH_ENV
|
||||
- setup_google_dns
|
||||
- run:
|
||||
name: Show git commit hash
|
||||
command: |
|
||||
echo "Git commit hash: $CIRCLE_SHA1"
|
||||
|
||||
- run:
|
||||
name: Install PostgreSQL
|
||||
command: |
|
||||
sudo apt-get update
|
||||
sudo apt-get install -y postgresql-14 postgresql-contrib-14
|
||||
- restore_cache:
|
||||
keys:
|
||||
- v1-dependencies-{{ checksum ".circleci/requirements.txt" }}
|
||||
|
|
@ -2375,6 +2373,25 @@ jobs:
|
|||
pip install "pytest-mock==3.12.0"
|
||||
pip install "pytest-asyncio==0.21.1"
|
||||
pip install "assemblyai==0.37.0"
|
||||
- run:
|
||||
name: Install dockerize
|
||||
command: |
|
||||
wget https://github.com/jwilder/dockerize/releases/download/v0.6.1/dockerize-linux-amd64-v0.6.1.tar.gz
|
||||
sudo tar -C /usr/local/bin -xzvf dockerize-linux-amd64-v0.6.1.tar.gz
|
||||
rm dockerize-linux-amd64-v0.6.1.tar.gz
|
||||
- run:
|
||||
name: Start PostgreSQL Database
|
||||
command: |
|
||||
docker run -d \
|
||||
--name postgres-db \
|
||||
-e POSTGRES_USER=postgres \
|
||||
-e POSTGRES_PASSWORD=postgres \
|
||||
-e POSTGRES_DB=circle_test \
|
||||
-p 5432:5432 \
|
||||
postgres:14
|
||||
- run:
|
||||
name: Wait for PostgreSQL to be ready
|
||||
command: dockerize -wait tcp://localhost:5432 -timeout 1m
|
||||
- run:
|
||||
name: Build Docker image
|
||||
command: docker build -t my-app:latest -f ./docker/Dockerfile.database .
|
||||
|
|
@ -2385,10 +2402,11 @@ jobs:
|
|||
command: |
|
||||
docker run -d \
|
||||
-p 4000:4000 \
|
||||
-e DATABASE_URL=$CLEAN_STORE_MODEL_IN_DB_DATABASE_URL \
|
||||
-e DATABASE_URL=postgresql://postgres:postgres@host.docker.internal:5432/circle_test \
|
||||
-e STORE_MODEL_IN_DB="True" \
|
||||
-e LITELLM_MASTER_KEY="sk-1234" \
|
||||
-e LITELLM_LICENSE=$LITELLM_LICENSE \
|
||||
--add-host host.docker.internal:host-gateway \
|
||||
--name my-app \
|
||||
-v $(pwd)/litellm/proxy/example_config_yaml/store_model_db_config.yaml:/app/config.yaml \
|
||||
my-app:latest \
|
||||
|
|
@ -2418,7 +2436,16 @@ jobs:
|
|||
python -m pytest -vv tests/store_model_in_db_tests -x --junitxml=test-results/junit.xml --durations=5
|
||||
no_output_timeout:
|
||||
120m
|
||||
# Clean up first container
|
||||
- run:
|
||||
name: Stop and remove containers
|
||||
command: |
|
||||
docker stop my-app || true
|
||||
docker rm my-app || true
|
||||
docker stop postgres-db || true
|
||||
docker rm postgres-db || true
|
||||
when: always
|
||||
- store_test_results:
|
||||
path: test-results
|
||||
|
||||
proxy_build_from_pip_tests:
|
||||
# Change from docker to machine executor
|
||||
|
|
|
|||
|
|
@ -68,8 +68,11 @@ run_grype_scans() {
|
|||
|
||||
# Allowlist of CVEs to be ignored in failure threshold/reporting
|
||||
# - CVE-2025-8869: Not applicable on Python >=3.13 (PEP 706 implemented); pip fallback unused; no OS-level fix
|
||||
# - GHSA-4xh5-x5gv-qwph: GitHub Security Advisory alias for CVE-2025-8869
|
||||
ALLOWED_CVES=(
|
||||
"CVE-2025-8869"
|
||||
"GHSA-4xh5-x5gv-qwph"
|
||||
"CVE-2025-8291" # no fix available as of Oct 11, 2025
|
||||
)
|
||||
|
||||
# Build JSON array of allowlisted CVE IDs for jq
|
||||
|
|
@ -77,6 +80,26 @@ run_grype_scans() {
|
|||
|
||||
echo "Checking for vulnerabilities with CVSS score >= 4.0..."
|
||||
echo "Allowlisted CVEs (ignored in threshold): ${ALLOWED_CVES[*]}"
|
||||
echo ""
|
||||
|
||||
# Show all high-severity vulnerabilities for transparency
|
||||
TOTAL_HIGH_SEVERITY=$(grype litellm:latest -o json | jq -r '
|
||||
.matches[]
|
||||
| select(.vulnerability.cvss[]?.metrics.baseScore >= 4.0)
|
||||
| .vulnerability.id' | wc -l)
|
||||
|
||||
if [ "$TOTAL_HIGH_SEVERITY" -gt 0 ]; then
|
||||
echo "Total vulnerabilities found with CVSS >= 4.0: $TOTAL_HIGH_SEVERITY"
|
||||
echo ""
|
||||
echo "All high-severity vulnerabilities (including allowlisted):"
|
||||
grype litellm:latest -o json | jq --argjson allow "$ALLOWED_IDS_JSON" -r '
|
||||
["Package", "Version", "Vulnerability ID", "CVSS Score", "Allowlisted"],
|
||||
(.matches[]
|
||||
| select(.vulnerability.cvss[]?.metrics.baseScore >= 4.0)
|
||||
| [.artifact.name, .artifact.version, .vulnerability.id, .vulnerability.cvss[0].metrics.baseScore, (if (.vulnerability.id as $id | $allow | index($id)) then "YES" else "NO" end)])
|
||||
| @tsv' | column -t -s $'\t'
|
||||
echo ""
|
||||
fi
|
||||
|
||||
HIGH_SEVERITY_COUNT=$(grype litellm:latest -o json | jq --argjson allow "$ALLOWED_IDS_JSON" -r '
|
||||
.matches[]
|
||||
|
|
@ -85,8 +108,17 @@ run_grype_scans() {
|
|||
| .vulnerability.id' | wc -l)
|
||||
|
||||
if [ "$HIGH_SEVERITY_COUNT" -gt 0 ]; then
|
||||
echo "ERROR: Found $HIGH_SEVERITY_COUNT vulnerabilities with CVSS score >= 4.0 in litellm:latest"
|
||||
echo ""
|
||||
echo "=========================================="
|
||||
echo "ERROR: Security Scan Failed"
|
||||
echo "=========================================="
|
||||
echo "Found $HIGH_SEVERITY_COUNT non-allowlisted vulnerabilities with CVSS score >= 4.0 in litellm:latest"
|
||||
echo ""
|
||||
echo "These vulnerabilities are NOT in the allowlist and must be addressed."
|
||||
echo "Current allowlisted CVEs: ${ALLOWED_CVES[*]}"
|
||||
echo ""
|
||||
echo "Detailed vulnerability report:"
|
||||
echo ""
|
||||
grype litellm:latest -o json | jq --argjson allow "$ALLOWED_IDS_JSON" -r '
|
||||
["Package", "Version", "Vulnerability ID", "CVSS Score", "Severity", "Fix Version", "Description"],
|
||||
(.matches[]
|
||||
|
|
@ -94,6 +126,19 @@ run_grype_scans() {
|
|||
| select((.vulnerability.id as $id | $allow | index($id) | not))
|
||||
| [.artifact.name, .artifact.version, .vulnerability.id, .vulnerability.cvss[0].metrics.baseScore, .vulnerability.severity, (.vulnerability.fix.versions[0] // "No fix available"), .vulnerability.description])
|
||||
| @tsv' | column -t -s $'\t'
|
||||
echo ""
|
||||
echo "=========================================="
|
||||
echo "Action Required:"
|
||||
echo "=========================================="
|
||||
echo "1. If a fix is available, update the package to the fixed version"
|
||||
echo "2. If the vulnerability is not applicable or has no fix:"
|
||||
echo " - Add the CVE/GHSA ID to ALLOWED_CVES array in ci_cd/security_scans.sh"
|
||||
echo " - Add a comment explaining why it's safe to ignore"
|
||||
echo ""
|
||||
echo "Note: Some vulnerabilities may have multiple IDs (CVE-XXXX and GHSA-XXXX)."
|
||||
echo "Add all relevant IDs to the allowlist if they refer to the same issue."
|
||||
echo "=========================================="
|
||||
echo ""
|
||||
exit 1
|
||||
else
|
||||
echo "No high-severity vulnerabilities (CVSS >= 4.0) found in litellm:latest"
|
||||
|
|
|
|||
|
|
@ -180,11 +180,11 @@ 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.
|
||||
|
||||
- `parallel_tool_calls`: *boolean (optional)* - Whether to enable parallel function calling during tool use.. OpenAI default is true.
|
||||
- `parallel_tool_calls`: *boolean (optional)* - Whether to enable parallel function calling during tool use. OpenAI default is true.
|
||||
|
||||
- `frequency_penalty`: *number or null (optional)* - It is used to penalize new tokens based on their frequency in the text so far.
|
||||
|
||||
|
|
|
|||
|
|
@ -1204,6 +1204,8 @@ mcp_servers:
|
|||
scopes: ["public_repo", "user:email"]
|
||||
```
|
||||
|
||||
[**See Claude Code Tutorial**](./tutorials/claude_responses_api#connecting-mcp-servers)
|
||||
|
||||
## Using your MCP with client side credentials
|
||||
|
||||
Use this if you want to pass a client side authentication token to LiteLLM to then pass to your MCP to auth to your MCP.
|
||||
|
|
|
|||
|
|
@ -339,6 +339,72 @@ curl -X POST 'http://0.0.0.0:4000/chat/completions' \
|
|||
| fine tuned `gpt-3.5-turbo-1106` | `response = completion(model="ft:gpt-3.5-turbo-1106", messages=messages)` |
|
||||
| fine tuned `gpt-3.5-turbo-0613` | `response = completion(model="ft:gpt-3.5-turbo-0613", messages=messages)` |
|
||||
|
||||
## Getting Reasoning Content in `/chat/completions`
|
||||
|
||||
GPT-5 models return reasoning content when called via the Responses API. You can call these models via the `/chat/completions` endpoint by using the `openai/responses/` prefix.
|
||||
|
||||
<Tabs>
|
||||
<TabItem value="sdk" label="SDK">
|
||||
```python
|
||||
response = litellm.completion(
|
||||
model="openai/responses/gpt-5-mini", # tells litellm to call the model via the Responses API
|
||||
messages=[{"role": "user", "content": "What is the capital of France?"}],
|
||||
reasoning_effort="low",
|
||||
)
|
||||
```
|
||||
</TabItem>
|
||||
|
||||
<TabItem value="proxy" label="PROXY">
|
||||
```bash
|
||||
curl -X POST 'http://0.0.0.0:4000/chat/completions' \
|
||||
-H 'Content-Type: application/json' \
|
||||
-H 'Authorization: Bearer sk-1234' \
|
||||
-d '{
|
||||
"model": "openai/responses/gpt-5-mini",
|
||||
"messages": [{"role": "user", "content": "What is the capital of France?"}],
|
||||
"reasoning_effort": "low"
|
||||
}'
|
||||
```
|
||||
</TabItem>
|
||||
</Tabs>
|
||||
|
||||
Expected Response:
|
||||
```json
|
||||
{
|
||||
"id": "chatcmpl-6382a222-43c9-40c4-856b-22e105d88075",
|
||||
"created": 1760146746,
|
||||
"model": "gpt-5-mini",
|
||||
"object": "chat.completion",
|
||||
"system_fingerprint": null,
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "stop",
|
||||
"index": 0,
|
||||
"message": {
|
||||
"content": "Paris",
|
||||
"role": "assistant",
|
||||
"tool_calls": null,
|
||||
"function_call": null,
|
||||
"reasoning_content": "**Identifying the capital**\n\nThe user wants me to think of the capital of France and write it down. That's pretty straightforward: it's Paris. There aren't any safety issues to consider here. I think it would be best to keep it concise, so maybe just \"Paris\" would suffice. I feel confident that I should just stick to that without adding anything else. So, let's write it down!",
|
||||
"provider_specific_fields": null
|
||||
}
|
||||
}
|
||||
],
|
||||
"usage": {
|
||||
"completion_tokens": 7,
|
||||
"prompt_tokens": 18,
|
||||
"total_tokens": 25,
|
||||
"completion_tokens_details": null,
|
||||
"prompt_tokens_details": {
|
||||
"audio_tokens": null,
|
||||
"cached_tokens": 0,
|
||||
"text_tokens": null,
|
||||
"image_tokens": null
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
```
|
||||
|
||||
## OpenAI Chat Completion to Responses API Bridge
|
||||
|
||||
|
|
|
|||
|
|
@ -780,8 +780,8 @@ router_settings:
|
|||
| USE_AWS_KMS | Flag to enable AWS Key Management Service for encryption
|
||||
| USE_PRISMA_MIGRATE | Flag to use prisma migrate instead of prisma db push. Recommended for production environments.
|
||||
| WEBHOOK_URL | URL for receiving webhooks from external services
|
||||
| SPEND_LOG_RUN_LOOPS | Constant for setting how many runs of 1000 batch deletes should spend_log_cleanup task run |
|
||||
| SPEND_LOG_CLEANUP_BATCH_SIZE | Number of logs deleted per batch during cleanup. Default is 1000 |
|
||||
| COROUTINE_CHECKER_MAX_SIZE_IN_MEMORY | Maximum size for CoroutineChecker in-memory cache. Default is 1000 |
|
||||
DEFAULT_SHARED_HEALTH_CHECK_TTL | Time-to-live in seconds for cached health check results in shared health check mode. Default is 300 (5 minutes)
|
||||
DEFAULT_SHARED_HEALTH_CHECK_LOCK_TTL | Time-to-live in seconds for health check lock in shared health check mode. Default is 60 (1 minute)
|
||||
| SPEND_LOG_RUN_LOOPS | Constant for setting how many runs of 1000 batch deletes should spend_log_cleanup task run
|
||||
| SPEND_LOG_CLEANUP_BATCH_SIZE | Number of logs deleted per batch during cleanup. Default is 1000
|
||||
| COROUTINE_CHECKER_MAX_SIZE_IN_MEMORY | Maximum size for CoroutineChecker in-memory cache. Default is 1000
|
||||
| DEFAULT_SHARED_HEALTH_CHECK_TTL | Time-to-live in seconds for cached health check results in shared health check mode. Default is 300 (5 minutes)
|
||||
| DEFAULT_SHARED_HEALTH_CHECK_LOCK_TTL | Time-to-live in seconds for health check lock in shared health check mode. Default is 60 (1 minute)
|
||||
|
|
@ -1,5 +1,6 @@
|
|||
import Tabs from '@theme/Tabs';
|
||||
import TabItem from '@theme/TabItem';
|
||||
import Image from '@theme/IdealImage';
|
||||
|
||||
# Virtual Keys
|
||||
Track Spend, and control model access via virtual keys for the proxy
|
||||
|
|
@ -66,50 +67,6 @@ curl 'http://0.0.0.0:4000/key/generate' \
|
|||
--data-raw '{"models": ["gpt-3.5-turbo", "gpt-4"], "metadata": {"user": "ishaan@berri.ai"}}'
|
||||
```
|
||||
|
||||
## 🔁 Scheduled Key Rotations (NEW in v1.77.5)
|
||||
|
||||
LiteLLM can now rotate **virtual keys automatically** on a schedule you define.
|
||||
|
||||
### How it works
|
||||
1. When creating a virtual key you set `rotation_schedule` – a [cron expression](https://crontab.guru/).
|
||||
2. LiteLLM stores the schedule in the DB and runs a background job that regenerates the key at the specified time.
|
||||
3. Existing key string is invalidated; a **notification webhook** (if configured) is sent with the new key value.
|
||||
|
||||
### Create a key with rotation
|
||||
|
||||
```bash
|
||||
curl 'http://0.0.0.0:4000/key/generate' \
|
||||
-H 'Authorization: Bearer <your-master-key>' \
|
||||
-H 'Content-Type: application/json' \
|
||||
-d '{
|
||||
"models": ["gpt-4o"],
|
||||
"rotation_schedule": "0 0 * * SUN", # rotate every Sunday at 00:00 UTC
|
||||
"webhook_url": "https://example.com/key-rotated"
|
||||
}'
|
||||
```
|
||||
|
||||
### Enable globally via env
|
||||
|
||||
Set these env vars when starting the proxy:
|
||||
|
||||
| Variable | Description | Default |
|
||||
|----------|-------------|---------|
|
||||
| `LITELLM_KEY_ROTATION_ENABLED` | Enable the rotation worker | `false` |
|
||||
| `LITELLM_KEY_ROTATION_CHECK_INTERVAL_SECONDS` | How often to scan for keys to rotate | `86400` |
|
||||
|
||||
### Webhook payload
|
||||
|
||||
```json
|
||||
{
|
||||
"event": "virtual_key.rotated",
|
||||
"old_key_id": "sk-abc...",
|
||||
"new_key": "sk-def...",
|
||||
"rotation_time": "2025-10-05T00:00:00Z"
|
||||
}
|
||||
```
|
||||
|
||||
If no `webhook_url` is provided the new key value is returned in the response of the `/key/rotate` REST call instead.
|
||||
|
||||
## Spend Tracking
|
||||
|
||||
Get spend per:
|
||||
|
|
@ -604,6 +561,94 @@ curl 'http://localhost:4000/key/sk-1234/regenerate' \
|
|||
[**👉 API REFERENCE DOCS**](https://litellm-api.up.railway.app/#/key%20management/regenerate_key_fn_key__key__regenerate_post)
|
||||
|
||||
|
||||
### Scheduled Key Rotations
|
||||
|
||||
LiteLLM can rotate **virtual keys automatically** based on time intervals you define.
|
||||
|
||||
#### Prerequisites
|
||||
|
||||
1. **Database connection required** - Key rotation requires a connected database to track rotation schedules
|
||||
2. **Enable the rotation worker** - Set environment variable `LITELLM_KEY_ROTATION_ENABLED=true`
|
||||
3. **Configure check interval** - Optionally set `LITELLM_KEY_ROTATION_CHECK_INTERVAL_SECONDS` (default: 86400 seconds / 24 hours)
|
||||
|
||||
#### How it works
|
||||
|
||||
1. When creating a virtual key, set `auto_rotate: true` and `rotation_interval` (duration string)
|
||||
2. LiteLLM calculates the next rotation time as `now + rotation_interval` and stores it in the database
|
||||
3. A background job periodically checks for keys where the rotation time has passed
|
||||
4. When a key is due for rotation, LiteLLM automatically regenerates it and invalidates the old key string
|
||||
5. The new rotation time is calculated and the cycle continues
|
||||
|
||||
#### Create a key with auto rotation
|
||||
|
||||
**API**
|
||||
```bash
|
||||
curl 'http://0.0.0.0:4000/key/generate' \
|
||||
-H 'Authorization: Bearer <your-master-key>' \
|
||||
-H 'Content-Type: application/json' \
|
||||
-d '{
|
||||
"models": ["gpt-4o"],
|
||||
"auto_rotate": true,
|
||||
"rotation_interval": "30d"
|
||||
}'
|
||||
```
|
||||
|
||||
**LiteLLM UI**
|
||||
|
||||
On the LiteLLM UI, Navigate to the Keys page and click on `Generate Key` > `Key Lifecycle` > `Enable Auto Rotation`
|
||||
<Image
|
||||
img={require('../../img/key_r.png')}
|
||||
style={{width: '30%', display: 'block', margin: '0'}}
|
||||
/>
|
||||
|
||||
**Valid rotation_interval formats:**
|
||||
- `"30s"` - 30 seconds
|
||||
- `"30m"` - 30 minutes
|
||||
- `"30h"` - 30 hours
|
||||
- `"30d"` - 30 days
|
||||
- `"90d"` - 90 days
|
||||
|
||||
#### Update existing key to enable rotation
|
||||
|
||||
**API**
|
||||
|
||||
```bash
|
||||
curl 'http://0.0.0.0:4000/key/update' \
|
||||
-H 'Authorization: Bearer <your-master-key>' \
|
||||
-H 'Content-Type: application/json' \
|
||||
-d '{
|
||||
"key": "sk-existing-key",
|
||||
"auto_rotate": true,
|
||||
"rotation_interval": "90d"
|
||||
}'
|
||||
```
|
||||
|
||||
**LiteLLM UI**
|
||||
|
||||
On the LiteLLM UI, Navigate to the Keys page. Select the key you want to update and click on `Edit Settings` > `Auto-Rotation Settings`
|
||||
|
||||
<Image
|
||||
img={require('../../img/key_u.png')}
|
||||
style={{width: '30%', display: 'block', margin: '0'}}
|
||||
/>
|
||||
|
||||
#### Environment variables
|
||||
|
||||
Set these environment variables when starting the proxy:
|
||||
|
||||
| Variable | Description | Default |
|
||||
|----------|-------------|---------|
|
||||
| `LITELLM_KEY_ROTATION_ENABLED` | Enable the rotation worker | `false` |
|
||||
| `LITELLM_KEY_ROTATION_CHECK_INTERVAL_SECONDS` | How often to scan for keys to rotate (in seconds) | `86400` (24 hours) |
|
||||
|
||||
**Example:**
|
||||
```bash
|
||||
export LITELLM_KEY_ROTATION_ENABLED=true
|
||||
export LITELLM_KEY_ROTATION_CHECK_INTERVAL_SECONDS=3600 # Check every hour
|
||||
|
||||
litellm --config config.yaml
|
||||
```
|
||||
|
||||
### Temporary Budget Increase
|
||||
|
||||
Use the `/key/update` endpoint to increase the budget of an existing key.
|
||||
|
|
|
|||
|
|
@ -105,7 +105,7 @@ LITELLM_MASTER_KEY gives claude access to all proxy models, whereas a virtual ke
|
|||
Alternatively, use the Anthropic pass-through endpoint:
|
||||
|
||||
```bash
|
||||
export ANTHROPIC_BASE_URL="http://0.0.0.0:4000/anthropic"
|
||||
export ANTHROPIC_BASE_URL="http://0.0.0.0:4000"
|
||||
export ANTHROPIC_AUTH_TOKEN="$LITELLM_MASTER_KEY"
|
||||
```
|
||||
|
||||
|
|
@ -209,4 +209,81 @@ claude --model claude-bedrock
|
|||
</TabItem>
|
||||
</Tabs>
|
||||
|
||||
<Image img={require('../../img/release_notes/claude_code_demo.png')} style={{ width: '500px', height: 'auto' }} />
|
||||
<Image img={require('../../img/release_notes/claude_code_demo.png')} style={{ width: '500px', height: 'auto' }} />
|
||||
|
||||
|
||||
## Connecting MCP Servers
|
||||
|
||||
You can also connect MCP servers to Claude Code via LiteLLM Proxy.
|
||||
|
||||
:::note
|
||||
|
||||
Limitations:
|
||||
|
||||
- Currently, only HTTP MCP servers are supported
|
||||
- Does not work in Cursor IDE yet.
|
||||
|
||||
:::
|
||||
|
||||
1. Add the MCP server to your `config.yaml`
|
||||
|
||||
In this example, we'll add the Github MCP server to our `config.yaml`
|
||||
|
||||
```yaml title="config.yaml" showLineNumbers
|
||||
mcp_servers:
|
||||
github_mcp:
|
||||
url: "https://api.githubcopilot.com/mcp"
|
||||
auth_type: oauth2
|
||||
authorization_url: https://github.com/login/oauth/authorize
|
||||
token_url: https://github.com/login/oauth/access_token
|
||||
client_id: os.environ/GITHUB_OAUTH_CLIENT_ID
|
||||
client_secret: os.environ/GITHUB_OAUTH_CLIENT_SECRET
|
||||
scopes: ["public_repo", "user:email"]
|
||||
```
|
||||
|
||||
2. Start LiteLLM Proxy
|
||||
|
||||
```bash
|
||||
litellm --config /path/to/config.yaml
|
||||
|
||||
# RUNNING on http://0.0.0.0:4000
|
||||
```
|
||||
|
||||
3. Use the MCP server in Claude Code
|
||||
|
||||
```bash
|
||||
claude mcp add --transport http litellm_proxy http://0.0.0.0:4000 --header "Authorization: Bearer sk-LITELLM_VIRTUAL_KEY"
|
||||
```
|
||||
|
||||
4. Authenticate via Claude Code
|
||||
|
||||
a. Start Claude Code
|
||||
|
||||
```bash
|
||||
claude
|
||||
```
|
||||
|
||||
b. Authenticate via Claude Code
|
||||
|
||||
```bash
|
||||
/mcp
|
||||
```
|
||||
|
||||
c. Select the MCP server
|
||||
|
||||
```bash
|
||||
> litellm_proxy
|
||||
```
|
||||
|
||||
d. Start Oauth flow via Claude Code
|
||||
|
||||
```bash
|
||||
> 1. Authenticate
|
||||
2. Reconnect
|
||||
3. Disable
|
||||
```
|
||||
|
||||
e. Once completed, you should see this success message:
|
||||
|
||||
<Image img={require('../../img/oauth_2_success.png')} style={{ width: '500px', height: 'auto' }} />
|
||||
|
||||
|
|
|
|||
BIN
docs/my-website/img/key_r.png
Normal file
BIN
docs/my-website/img/key_r.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 125 KiB |
BIN
docs/my-website/img/key_u.png
Normal file
BIN
docs/my-website/img/key_u.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 216 KiB |
BIN
docs/my-website/img/mcp_updates.jpg
Normal file
BIN
docs/my-website/img/mcp_updates.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 913 KiB |
BIN
docs/my-website/img/oauth_2_success.png
Normal file
BIN
docs/my-website/img/oauth_2_success.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 67 KiB |
BIN
docs/my-website/img/release_notes/1_78_0_perf.png
Normal file
BIN
docs/my-website/img/release_notes/1_78_0_perf.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 134 KiB |
BIN
docs/my-website/img/release_notes/tool_control.png
Normal file
BIN
docs/my-website/img/release_notes/tool_control.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 798 KiB |
|
|
@ -57,19 +57,6 @@ pip install litellm==1.77.5
|
|||
|
||||
---
|
||||
|
||||
### Scheduled Key Rotations
|
||||
|
||||
<Image img={require('../../img/release_notes/schedule_key_rotations.png')} style={{ width: '800px', height: 'auto' }} />
|
||||
|
||||
<br/>
|
||||
|
||||
This release brings support for scheduling virtual key rotations on LiteLLM AI Gateway.
|
||||
|
||||
This is great for Proxy Admins looking to enforce Enterprise Grade security for use cases going through LiteLLM AI Gateway.
|
||||
|
||||
From this release you can enforce Virtual Keys to rotate on a schedule of your choice e.g every 15 days/30 days/60 days etc.
|
||||
|
||||
---
|
||||
### Performance Improvements - 54% RPS Improvement
|
||||
|
||||
<Image img={require('../../img/release_notes/perf_77_5.png')} style={{ width: '800px', height: 'auto' }} />
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
---
|
||||
title: "[Preview] v1.77.7-stable - Claude Sonnet 4.5"
|
||||
title: "v1.77.7-stable - 2.9x Lower Median Latency"
|
||||
slug: "v1-77-7"
|
||||
date: 2025-10-04T10:00:00
|
||||
authors:
|
||||
|
|
@ -15,7 +15,7 @@ authors:
|
|||
title: Backend Performance Engineer
|
||||
url: https://www.linkedin.com/in/alexsander-baptista/
|
||||
image_url: https://media.licdn.com/dms/image/v2/D5603AQGXnziu4kqNCQ/profile-displayphoto-crop_800_800/B56ZkxEcuOKEAI-/0/1757464874550?e=1762387200&v=beta&t=9SNXLsWhx8OnYPAMQ9fqAr02oevDYEAL2vMYg2f9ieg
|
||||
- name: Achintya Srivastava
|
||||
- name: Achintya Rajan
|
||||
title: Fullstack Engineer
|
||||
url: https://www.linkedin.com/in/achintya-rajan/
|
||||
image_url: https://media.licdn.com/dms/image/v2/D5603AQGdkEeyJTdljw/profile-displayphoto-shrink_800_800/profile-displayphoto-shrink_800_800/0/1716271140869?e=1762387200&v=beta&t=9gOoLPeqR2E5z3KSX61EUj3HVZXmgo87vhVuSHeffjc
|
||||
|
|
@ -103,6 +103,31 @@ View the complete configuration: [gist.github.com/AlexsanderHamir/config.yaml](h
|
|||
|
||||
View the complete load testing script: [gist.github.com/AlexsanderHamir/no_cache_hits.py](https://gist.github.com/AlexsanderHamir/42c33d7a4dc7a57f56a78b560dee3a42)
|
||||
|
||||
### MCP OAuth 2.0 Support
|
||||
|
||||
<Image img={require('../../img/mcp_updates.jpg')} style={{ width: '800px', height: 'auto' }} />
|
||||
|
||||
<br/>
|
||||
|
||||
This release adds support for OAuth 2.0 Client Credentials for MCP servers. This is great for **Internal Dev Tools** use-cases, as it enables your users to call MCP servers, with their own credentials. E.g. Allowing your developers to call the Github MCP, with their own credentials.
|
||||
|
||||
[Set it up today on Claude Code](../../docs/tutorials/claude_responses_api#connecting-mcp-servers)
|
||||
|
||||
### Scheduled Key Rotations
|
||||
|
||||
<Image img={require('../../img/release_notes/schedule_key_rotations.png')} style={{ width: '800px', height: 'auto' }} />
|
||||
|
||||
<br/>
|
||||
|
||||
This release brings support for scheduling virtual key rotations on LiteLLM AI Gateway.
|
||||
|
||||
From this release you can enforce Virtual Keys to rotate on a schedule of your choice e.g every 15 days/30 days/60 days etc.
|
||||
|
||||
This is great for Proxy Admins who need to enforce security policies for production workloads.
|
||||
|
||||
[Get Started](../../docs/proxy/virtual_keys#scheduled-key-rotations)
|
||||
|
||||
|
||||
## New Models / Updated Models
|
||||
|
||||
#### New Model Support
|
||||
|
|
|
|||
394
docs/my-website/release_notes/v1.78.0-stable/index.md
Normal file
394
docs/my-website/release_notes/v1.78.0-stable/index.md
Normal file
|
|
@ -0,0 +1,394 @@
|
|||
---
|
||||
title: "[Preview] v1.78.0-stable - MCP Gateway: Control Tool Access by Team, Key"
|
||||
slug: "v1-78-0"
|
||||
date: 2025-10-11T10:00:00
|
||||
authors:
|
||||
- name: Krrish Dholakia
|
||||
title: CEO, LiteLLM
|
||||
url: https://www.linkedin.com/in/krish-d/
|
||||
image_url: https://pbs.twimg.com/profile_images/1298587542745358340/DZv3Oj-h_400x400.jpg
|
||||
- name: Ishaan Jaff
|
||||
title: CTO, LiteLLM
|
||||
url: https://www.linkedin.com/in/reffajnaahsi/
|
||||
image_url: https://pbs.twimg.com/profile_images/1613813310264340481/lz54oEiB_400x400.jpg
|
||||
- name: Alexsander Hamir
|
||||
title: Backend Performance Engineer
|
||||
url: https://www.linkedin.com/in/alexsander-baptista/
|
||||
image_url: https://media.licdn.com/dms/image/v2/D5603AQGXnziu4kqNCQ/profile-displayphoto-crop_800_800/B56ZkxEcuOKEAI-/0/1757464874550?e=1762387200&v=beta&t=9SNXLsWhx8OnYPAMQ9fqAr02oevDYEAL2vMYg2f9ieg
|
||||
- name: Achintya Rajan
|
||||
title: Fullstack Engineer
|
||||
url: https://www.linkedin.com/in/achintya-rajan/
|
||||
image_url: https://media.licdn.com/dms/image/v2/D5603AQGdkEeyJTdljw/profile-displayphoto-shrink_800_800/profile-displayphoto-shrink_800_800/0/1716271140869?e=1762387200&v=beta&t=9gOoLPeqR2E5z3KSX61EUj3HVZXmgo87vhVuSHeffjc
|
||||
- name: Sameer Kankute
|
||||
title: Backend Engineer (LLM Translation)
|
||||
url: https://www.linkedin.com/in/sameer-kankute/
|
||||
image_url: https://media.licdn.com/dms/image/v2/D4D03AQHB_loQYd5gjg/profile-displayphoto-shrink_800_800/profile-displayphoto-shrink_800_800/0/1719137160975?e=1762387200&v=beta&t=0jbuX-f4eSnDxBY3olI6meuYr-LMbObhFmFbRcKF5mY
|
||||
|
||||
hide_table_of_contents: false
|
||||
---
|
||||
|
||||
import Image from '@theme/IdealImage';
|
||||
import Tabs from '@theme/Tabs';
|
||||
import TabItem from '@theme/TabItem';
|
||||
|
||||
## Deploy this version
|
||||
|
||||
<Tabs>
|
||||
<TabItem value="docker" label="Docker">
|
||||
|
||||
``` showLineNumbers title="docker run litellm"
|
||||
docker run \
|
||||
-e STORE_MODEL_IN_DB=True \
|
||||
-p 4000:4000 \
|
||||
ghcr.io/berriai/litellm:v1.78.0.rc.1
|
||||
```
|
||||
|
||||
</TabItem>
|
||||
|
||||
<TabItem value="pip" label="Pip">
|
||||
|
||||
``` showLineNumbers title="pip install litellm"
|
||||
pip install litellm==1.78.0.rc.1
|
||||
```
|
||||
|
||||
</TabItem>
|
||||
</Tabs>
|
||||
|
||||
---
|
||||
|
||||
## Key Highlights
|
||||
|
||||
- **MCP Gateway - Control Tool Access by Team, Key** - Control MCP tool access by team/key.
|
||||
- **Performance Improvements** - 70% Lower p99 Latency
|
||||
- **GPT-5 Pro & GPT-Image-1-Mini** - Day 0 support for OpenAI's GPT-5 Pro (400K context) and gpt-image-1-mini image generation
|
||||
- **EnkryptAI Guardrails** - New guardrail integration for content moderation
|
||||
- **Tag-Based Budgets** - Support for setting budgets based on request tags
|
||||
|
||||
---
|
||||
|
||||
### MCP Gateway - Control Tool Access by Team, Key
|
||||
|
||||
<Image
|
||||
img={require('../../img/release_notes/tool_control.png')}
|
||||
style={{width: '100%', display: 'block', margin: '2rem auto'}}
|
||||
/>
|
||||
|
||||
<br/>
|
||||
|
||||
Proxy admins can now control MCP tool access by team or key. This makes it easy to grant different teams selective access to tools from the same MCP server.
|
||||
|
||||
For example, you can now give your Engineering team access to `list_repositories`, `create_issue`, and `search_code` tools, while Sales only gets `search_code` and `close_issue` tools.
|
||||
|
||||
This makes it easier for Proxy Admins to govern MCP Tool Access.
|
||||
|
||||
[Get Started](../../docs/mcp_control#set-allowed-tools-for-a-key-team-or-organization)
|
||||
|
||||
---
|
||||
|
||||
## Performance - 70% Lower p99 Latency
|
||||
|
||||
<Image img={require('../../img/release_notes/1_78_0_perf.png')} style={{ width: '800px', height: 'auto' }} />
|
||||
|
||||
<br/>
|
||||
|
||||
This release cuts p99 latency by 70% on LiteLLM AI Gateway, making it even better for low-latency use cases.
|
||||
|
||||
These gains come from two key enhancements:
|
||||
|
||||
**Reliable Sessions**
|
||||
|
||||
Added support for shared sessions with aiohttp. The shared_session parameter is now consistently used across all calls, enabling connection pooling.
|
||||
|
||||
**Faster Routing**
|
||||
|
||||
A new `model_name_to_deployment_indices` hash map replaces O(n) list scans in `_get_all_deployments()` with O(1) hash lookups, boosting routing performance and scalability.
|
||||
|
||||
As a result, performance improved across all latency percentiles:
|
||||
|
||||
- **Median latency:** 110 ms → **100 ms** (−9.1%)
|
||||
- **p95 latency:** 440 ms → **150 ms** (−65.9%)
|
||||
- **p99 latency:** 810 ms → **240 ms** (−70.4%)
|
||||
- **Average latency:** 310 ms → **111.73 ms** (−64.0%)
|
||||
|
||||
### **Test Setup**
|
||||
|
||||
**Locust**
|
||||
|
||||
- **Concurrent users:** 1,000
|
||||
- **Ramp-up:** 500
|
||||
|
||||
**System Specs**
|
||||
|
||||
- **Database was used**
|
||||
- **CPU:** 4 vCPUs
|
||||
- **Memory:** 8 GB RAM
|
||||
- **LiteLLM Workers:** 4
|
||||
- **Instances**: 4
|
||||
|
||||
**Configuration (config.yaml)**
|
||||
|
||||
View the complete configuration: [gist.github.com/AlexsanderHamir/config.yaml](https://gist.github.com/AlexsanderHamir/53f7d554a5d2afcf2c4edb5b6be68ff4)
|
||||
|
||||
**Load Script (no_cache_hits.py)**
|
||||
|
||||
View the complete load testing script: [gist.github.com/AlexsanderHamir/no_cache_hits.py](https://gist.github.com/AlexsanderHamir/42c33d7a4dc7a57f56a78b560dee3a42)
|
||||
|
||||
---
|
||||
|
||||
## New Models / Updated Models
|
||||
|
||||
#### New Model Support
|
||||
|
||||
| Provider | Model | Context Window | Input ($/1M tokens) | Output ($/1M tokens) | Features |
|
||||
| -------- | ----- | -------------- | ------------------- | -------------------- | -------- |
|
||||
| OpenAI | `gpt-5-pro` | 400K | $15.00 | $120.00 | Responses API, reasoning, vision, function calling, prompt caching, web search |
|
||||
| OpenAI | `gpt-5-pro-2025-10-06` | 400K | $15.00 | $120.00 | Responses API, reasoning, vision, function calling, prompt caching, web search |
|
||||
| OpenAI | `gpt-image-1-mini` | - | $2.00/img | - | Image generation and editing |
|
||||
| OpenAI | `gpt-realtime-mini` | 128K | $0.60 | $2.40 | Realtime audio, function calling |
|
||||
| Azure AI | `azure_ai/Phi-4-mini-reasoning` | 131K | $0.08 | $0.32 | Function calling |
|
||||
| Azure AI | `azure_ai/Phi-4-reasoning` | 32K | $0.125 | $0.50 | Function calling, reasoning |
|
||||
| Azure AI | `azure_ai/MAI-DS-R1` | 128K | $1.35 | $5.40 | Reasoning, function calling |
|
||||
| Bedrock | `au.anthropic.claude-sonnet-4-5-20250929-v1:0` | 200K | $3.30 | $16.50 | Chat, reasoning, vision, function calling, prompt caching |
|
||||
| Bedrock | `global.anthropic.claude-sonnet-4-5-20250929-v1:0` | 200K | $3.00 | $15.00 | Chat, reasoning, vision, function calling, prompt caching |
|
||||
| Bedrock | `global.anthropic.claude-sonnet-4-20250514-v1:0` | 1M | $3.00 | $15.00 | Chat, reasoning, vision, function calling, prompt caching |
|
||||
| Bedrock | `cohere.embed-v4:0` | 128K | $0.12 | - | Embeddings, image input support |
|
||||
| OCI | `oci/cohere.command-latest` | 128K | $1.56 | $1.56 | Function calling |
|
||||
| OCI | `oci/cohere.command-a-03-2025` | 256K | $1.56 | $1.56 | Function calling |
|
||||
| OCI | `oci/cohere.command-plus-latest` | 128K | $1.56 | $1.56 | Function calling |
|
||||
| Together AI | `together_ai/moonshotai/Kimi-K2-Instruct-0905` | 262K | $1.00 | $3.00 | Function calling |
|
||||
| Together AI | `together_ai/Qwen/Qwen3-Next-80B-A3B-Instruct` | 262K | $0.15 | $1.50 | Function calling |
|
||||
| Together AI | `together_ai/Qwen/Qwen3-Next-80B-A3B-Thinking` | 262K | $0.15 | $1.50 | Function calling |
|
||||
| Vertex AI | MedGemma models | Varies | Varies | Varies | Medical-focused Gemma models on custom endpoints |
|
||||
| Watson X | 27 new foundation models | Varies | Varies | Varies | Granite, Llama, Mistral families |
|
||||
|
||||
#### Features
|
||||
|
||||
- **[OpenAI](../../docs/providers/openai)**
|
||||
- Add GPT-5 Pro model configuration and documentation - [PR #15258](https://github.com/BerriAI/litellm/pull/15258)
|
||||
- Add stop parameter to non-supported params for GPT-5 - [PR #15244](https://github.com/BerriAI/litellm/pull/15244)
|
||||
- Day 0 Support, Add gpt-image-1-mini - [PR #15259](https://github.com/BerriAI/litellm/pull/15259)
|
||||
- Add gpt-realtime-mini support - [PR #15283](https://github.com/BerriAI/litellm/pull/15283)
|
||||
- Add gpt-5-pro-2025-10-06 to model costs - [PR #15344](https://github.com/BerriAI/litellm/pull/15344)
|
||||
- Minimal fix: gpt5 models should not go on cooldown when called with temperature!=1 - [PR #15330](https://github.com/BerriAI/litellm/pull/15330)
|
||||
|
||||
- **[Snowflake Cortex](../../docs/providers/snowflake)**
|
||||
- Add function calling support for Snowflake Cortex REST API - [PR #15221](https://github.com/BerriAI/litellm/pull/15221)
|
||||
|
||||
- **[Gemini](../../docs/providers/gemini)**
|
||||
- Fix header forwarding for Gemini/Vertex AI providers in proxy mode - [PR #15231](https://github.com/BerriAI/litellm/pull/15231)
|
||||
|
||||
- **[Azure](../../docs/providers/azure)**
|
||||
- Removed stop param from unsupported azure models - [PR #15229](https://github.com/BerriAI/litellm/pull/15229)
|
||||
- Fix(azure/responses): remove invalid status param from azure call - [PR #15253](https://github.com/BerriAI/litellm/pull/15253)
|
||||
- Add new Azure AI models with pricing details - [PR #15387](https://github.com/BerriAI/litellm/pull/15387)
|
||||
- AzureAD Default credentials - select credential type based on environment - [PR #14470](https://github.com/BerriAI/litellm/pull/14470)
|
||||
|
||||
- **[Bedrock](../../docs/providers/bedrock)**
|
||||
- Add Global Cross-Region Inference - [PR #15210](https://github.com/BerriAI/litellm/pull/15210)
|
||||
- Add Cohere Embed v4 support for AWS Bedrock - [PR #15298](https://github.com/BerriAI/litellm/pull/15298)
|
||||
- Fix(bedrock): include cacheWriteInputTokens in prompt_tokens calculation - [PR #15292](https://github.com/BerriAI/litellm/pull/15292)
|
||||
- Add Bedrock AU Cross-Region Inference for Claude Sonnet 4.5 - [PR #15402](https://github.com/BerriAI/litellm/pull/15402)
|
||||
- Converse → /v1/messages streaming doesn't handle parallel tool calls with Claude models - [PR #15315](https://github.com/BerriAI/litellm/pull/15315)
|
||||
|
||||
- **[Vertex AI](../../docs/providers/vertex)**
|
||||
- Implement Context Caching for Vertex AI provider - [PR #15226](https://github.com/BerriAI/litellm/pull/15226)
|
||||
- Support for Vertex AI Gemma Models on Custom Endpoints - [PR #15397](https://github.com/BerriAI/litellm/pull/15397)
|
||||
- VertexAI - gemma model family support (custom endpoints) - [PR #15419](https://github.com/BerriAI/litellm/pull/15419)
|
||||
- VertexAI Gemma model family streaming support + Added MedGemma - [PR #15427](https://github.com/BerriAI/litellm/pull/15427)
|
||||
|
||||
- **[OCI](../../docs/providers/oci)**
|
||||
- Add OCI Cohere support with tool calling and streaming capabilities - [PR #15365](https://github.com/BerriAI/litellm/pull/15365)
|
||||
|
||||
- **[Watson X](../../docs/providers/watsonx)**
|
||||
- Add Watson X foundation model definitions to model_prices_and_context_window.json - [PR #15219](https://github.com/BerriAI/litellm/pull/15219)
|
||||
- Watsonx - Apply correct prompt templates for openai/gpt-oss model family - [PR #15341](https://github.com/BerriAI/litellm/pull/15341)
|
||||
|
||||
- **[OpenRouter](../../docs/providers/openrouter)**
|
||||
- Fix - (openrouter): move cache_control to content blocks for claude/gemini - [PR #15345](https://github.com/BerriAI/litellm/pull/15345)
|
||||
- Fix - OpenRouter cache_control to only apply to last content block - [PR #15395](https://github.com/BerriAI/litellm/pull/15395)
|
||||
|
||||
- **[Together AI](../../docs/providers/togetherai)**
|
||||
- Add new together models - [PR #15383](https://github.com/BerriAI/litellm/pull/15383)
|
||||
|
||||
### Bug Fixes
|
||||
|
||||
- **General**
|
||||
- Bug fix: gpt-5-chat-latest has incorrect max_input_tokens value - [PR #15116](https://github.com/BerriAI/litellm/pull/15116)
|
||||
- Fix reasoning response ID - [PR #15265](https://github.com/BerriAI/litellm/pull/15265)
|
||||
- Fix issue with parsing assistant messages - [PR #15320](https://github.com/BerriAI/litellm/pull/15320)
|
||||
- Fix litellm_param based costing - [PR #15336](https://github.com/BerriAI/litellm/pull/15336)
|
||||
- Fix lint errors - [PR #15406](https://github.com/BerriAI/litellm/pull/15406)
|
||||
|
||||
---
|
||||
|
||||
## LLM API Endpoints
|
||||
|
||||
#### Features
|
||||
|
||||
- **[Responses API](../../docs/response_api)**
|
||||
- Added streaming support for response api streaming image generation - [PR #15269](https://github.com/BerriAI/litellm/pull/15269)
|
||||
- Add native Responses API support for litellm_proxy provider - [PR #15347](https://github.com/BerriAI/litellm/pull/15347)
|
||||
- Temporarily relax ResponsesAPIResponse parsing to support custom backends (e.g., vLLM) - [PR #15362](https://github.com/BerriAI/litellm/pull/15362)
|
||||
|
||||
- **[Files API](../../docs/files_api)**
|
||||
- Feat(files): add @client decorator to file operations - [PR #15339](https://github.com/BerriAI/litellm/pull/15339)
|
||||
|
||||
- **[/generateContent](../../docs/providers/gemini)**
|
||||
- Fix gemini cli by actually streaming the response - [PR #15264](https://github.com/BerriAI/litellm/pull/15264)
|
||||
|
||||
- **[Azure Passthrough](../../docs/pass_through/azure)**
|
||||
- Azure - passthrough support with router models - [PR #15240](https://github.com/BerriAI/litellm/pull/15240)
|
||||
|
||||
#### Bugs
|
||||
|
||||
- **General**
|
||||
- Fix x-litellm-cache-key header not being returned on cache hit - [PR #15348](https://github.com/BerriAI/litellm/pull/15348)
|
||||
|
||||
---
|
||||
|
||||
## Management Endpoints / UI
|
||||
|
||||
#### Features
|
||||
|
||||
- **Proxy CLI Auth**
|
||||
- Proxy CLI - dont store existing key in the URL, store it in the state param - [PR #15290](https://github.com/BerriAI/litellm/pull/15290)
|
||||
|
||||
- **Models + Endpoints**
|
||||
- Make PATCH `/model/{model_id}/update` handle `team_id` consistently with POST `/model/new` - [PR #15297](https://github.com/BerriAI/litellm/pull/15297)
|
||||
- Feature: adds Infinity as a provider in the UI - [PR #15285](https://github.com/BerriAI/litellm/pull/15285)
|
||||
- Fix: model + endpoints page crash when config file contains router_settings.model_group_alias - [PR #15308](https://github.com/BerriAI/litellm/pull/15308)
|
||||
- Models & Endpoints Initial Refactor - [PR #15435](https://github.com/BerriAI/litellm/pull/15435)
|
||||
- Litellm UI API Reference page updates - [PR #15438](https://github.com/BerriAI/litellm/pull/15438)
|
||||
|
||||
- **Teams**
|
||||
- Teams page: new column "Your Role" on the teams table - [PR #15384](https://github.com/BerriAI/litellm/pull/15384)
|
||||
- LiteLLM Dashboard Teams UI refactor - [PR #15418](https://github.com/BerriAI/litellm/pull/15418)
|
||||
|
||||
- **UI Infrastructure**
|
||||
- Added prettier to autoformat frontend - [PR #15215](https://github.com/BerriAI/litellm/pull/15215)
|
||||
- Adds turbopack to the npm run dev command in UI to build faster during development - [PR #15250](https://github.com/BerriAI/litellm/pull/15250)
|
||||
- (perf) fix: Replaces bloated key list calls with lean key aliases endpoint - [PR #15252](https://github.com/BerriAI/litellm/pull/15252)
|
||||
- Potentially fixes a UI spasm issue with an expired cookie - [PR #15309](https://github.com/BerriAI/litellm/pull/15309)
|
||||
- LiteLLM UI Refactor Infrastructure - [PR #15236](https://github.com/BerriAI/litellm/pull/15236)
|
||||
- Enforces removal of unused imports from UI - [PR #15416](https://github.com/BerriAI/litellm/pull/15416)
|
||||
- Fix: usage page >> Model Activity >> spend per day graph: y-axis clipping on large spend values - [PR #15389](https://github.com/BerriAI/litellm/pull/15389)
|
||||
- Updates guardrail provider logos - [PR #15421](https://github.com/BerriAI/litellm/pull/15421)
|
||||
|
||||
- **Admin Settings**
|
||||
- Fix: Router settings do not update despite success message - [PR #15249](https://github.com/BerriAI/litellm/pull/15249)
|
||||
- Fix: Prevents DB from accidentally overriding config file values if they are empty in DB - [PR #15340](https://github.com/BerriAI/litellm/pull/15340)
|
||||
|
||||
- **SSO**
|
||||
- SSO - support EntraID app roles - [PR #15351](https://github.com/BerriAI/litellm/pull/15351)
|
||||
|
||||
---
|
||||
|
||||
## Logging / Guardrail / Prompt Management Integrations
|
||||
|
||||
#### Features
|
||||
|
||||
- **[PostHog](../../docs/observability/posthog)**
|
||||
- Feat: posthog per request api key - [PR #15379](https://github.com/BerriAI/litellm/pull/15379)
|
||||
|
||||
#### Guardrails
|
||||
|
||||
- **[EnkryptAI](../../docs/proxy/guardrails)**
|
||||
- Add EnkryptAI Guardrails on LiteLLM - [PR #15390](https://github.com/BerriAI/litellm/pull/15390)
|
||||
|
||||
---
|
||||
|
||||
## Spend Tracking, Budgets and Rate Limiting
|
||||
|
||||
- **Tag Management**
|
||||
- Tag Management - Add support for setting tag based budgets - [PR #15433](https://github.com/BerriAI/litellm/pull/15433)
|
||||
|
||||
- **Dynamic Rate Limiter v3**
|
||||
- QA/Fixes - Dynamic Rate Limiter v3 - final QA - [PR #15311](https://github.com/BerriAI/litellm/pull/15311)
|
||||
- Fix dynamic Rate limiter v3 - inserting litellm_model_saturation - [PR #15394](https://github.com/BerriAI/litellm/pull/15394)
|
||||
|
||||
- **Shared Health Check**
|
||||
- Implement Shared Health Check State Across Pods - [PR #15380](https://github.com/BerriAI/litellm/pull/15380)
|
||||
|
||||
---
|
||||
|
||||
## MCP Gateway
|
||||
|
||||
- **Tool Control**
|
||||
- MCP Gateway - UI - Select allowed tools for Key, Teams - [PR #15241](https://github.com/BerriAI/litellm/pull/15241)
|
||||
- MCP Gateway - Backend - Allow storing allowed tools by team/key - [PR #15243](https://github.com/BerriAI/litellm/pull/15243)
|
||||
- MCP Gateway - Fine-grained Database Object Storage Control - [PR #15255](https://github.com/BerriAI/litellm/pull/15255)
|
||||
- MCP Gateway - Litellm mcp fixes team control - [PR #15304](https://github.com/BerriAI/litellm/pull/15304)
|
||||
- MCP Gateway - QA/Fixes - Ensure Team/Key level enforcement works for MCPs - [PR #15305](https://github.com/BerriAI/litellm/pull/15305)
|
||||
- Feature: Include server_name in /v1/mcp/server/health endpoint response - [PR #15431](https://github.com/BerriAI/litellm/pull/15431)
|
||||
|
||||
- **OpenAPI Integration**
|
||||
- MCP - support converting OpenAPI specs to MCP servers - [PR #15343](https://github.com/BerriAI/litellm/pull/15343)
|
||||
- MCP - specify allowed params per tool - [PR #15346](https://github.com/BerriAI/litellm/pull/15346)
|
||||
|
||||
- **Configuration**
|
||||
- MCP - support setting CA_BUNDLE_PATH - [PR #15253](https://github.com/BerriAI/litellm/pull/15253)
|
||||
- Fix: Ensure MCP client stays open during tool call - [PR #15391](https://github.com/BerriAI/litellm/pull/15391)
|
||||
- Remove hardcoded "public" schema in migration.sql - [PR #15363](https://github.com/BerriAI/litellm/pull/15363)
|
||||
|
||||
---
|
||||
|
||||
## Performance / Loadbalancing / Reliability improvements
|
||||
|
||||
- **Router Optimizations**
|
||||
- Fix - Router: add model_name index for O(1) deployment lookups - [PR #15113](https://github.com/BerriAI/litellm/pull/15113)
|
||||
- Refactor Utils: extract inner function from client - [PR #15234](https://github.com/BerriAI/litellm/pull/15234)
|
||||
- Fix Networking: remove limitations - [PR #15302](https://github.com/BerriAI/litellm/pull/15302)
|
||||
|
||||
- **Session Management**
|
||||
- Fix - Sessions not being shared - [PR #15388](https://github.com/BerriAI/litellm/pull/15388)
|
||||
- Fix: remove panic from hot path - [PR #15396](https://github.com/BerriAI/litellm/pull/15396)
|
||||
- Fix - shared session parsing and usage issue - [PR #15440](https://github.com/BerriAI/litellm/pull/15440)
|
||||
- Fix: handle closed aiohttp sessions - [PR #15442](https://github.com/BerriAI/litellm/pull/15442)
|
||||
- Fix: prevent session leaks when recreating aiohttp sessions - [PR #15443](https://github.com/BerriAI/litellm/pull/15443)
|
||||
|
||||
- **SSL/TLS Performance**
|
||||
- Perf: optimize SSL/TLS handshake performance with prioritized cipher - [PR #15398](https://github.com/BerriAI/litellm/pull/15398)
|
||||
|
||||
- **Dependencies**
|
||||
- Upgrades tenacity version to 8.5.0 - [PR #15303](https://github.com/BerriAI/litellm/pull/15303)
|
||||
|
||||
- **Data Masking**
|
||||
- Fix - SensitiveDataMasker converts lists to string - [PR #15420](https://github.com/BerriAI/litellm/pull/15420)
|
||||
|
||||
---
|
||||
|
||||
|
||||
## General AI Gateway Improvements
|
||||
|
||||
#### Security
|
||||
|
||||
- **General**
|
||||
- Fix: redact AWS credentials when redact_user_api_key_info enabled - [PR #15321](https://github.com/BerriAI/litellm/pull/15321)
|
||||
|
||||
---
|
||||
|
||||
## Documentation Updates
|
||||
|
||||
- **Provider Documentation**
|
||||
- Update doc: perf update - [PR #15211](https://github.com/BerriAI/litellm/pull/15211)
|
||||
- Add W&B Inference documentation - [PR #15278](https://github.com/BerriAI/litellm/pull/15278)
|
||||
|
||||
- **Deployment**
|
||||
- Deletion of docker-compose buggy comment that cause `config.yaml` based startup fail - [PR #15425](https://github.com/BerriAI/litellm/pull/15425)
|
||||
|
||||
---
|
||||
|
||||
## New Contributors
|
||||
|
||||
* @Gal-bloch made their first contribution in [PR #15219](https://github.com/BerriAI/litellm/pull/15219)
|
||||
* @lcfyi made their first contribution in [PR #15315](https://github.com/BerriAI/litellm/pull/15315)
|
||||
* @ashengstd made their first contribution in [PR #15362](https://github.com/BerriAI/litellm/pull/15362)
|
||||
* @vkolehmainen made their first contribution in [PR #15363](https://github.com/BerriAI/litellm/pull/15363)
|
||||
* @jlan-nl made their first contribution in [PR #15330](https://github.com/BerriAI/litellm/pull/15330)
|
||||
* @BCook98 made their first contribution in [PR #15402](https://github.com/BerriAI/litellm/pull/15402)
|
||||
* @PabloGmz96 made their first contribution in [PR #15425](https://github.com/BerriAI/litellm/pull/15425)
|
||||
|
||||
---
|
||||
|
||||
## **[Full Changelog](https://github.com/BerriAI/litellm/compare/v1.77.7.rc.1...v1.78.0.rc.1)**
|
||||
|
||||
|
|
@ -94,10 +94,10 @@ const sidebars = {
|
|||
|
||||
{
|
||||
type: "category",
|
||||
label: "LiteLLM Proxy Server",
|
||||
label: "LiteLLM AI Gateway",
|
||||
link: {
|
||||
type: "generated-index",
|
||||
title: "LiteLLM Proxy Server (LLM Gateway)",
|
||||
title: "LiteLLM AI Gateway (LLM Proxy)",
|
||||
description: `OpenAI Proxy Server (LLM Gateway) to call 100+ LLMs in a unified interface & track spend, set budgets per virtual key/user`,
|
||||
slug: "/simple_proxy",
|
||||
},
|
||||
|
|
|
|||
|
|
@ -36,6 +36,8 @@ async def apply_guardrail(
|
|||
if active_guardrail is None:
|
||||
raise Exception(f"Guardrail {request.guardrail_name} not found")
|
||||
|
||||
return await active_guardrail.apply_guardrail(
|
||||
response_text = await active_guardrail.apply_guardrail(
|
||||
text=request.text, language=request.language, entities=request.entities
|
||||
)
|
||||
|
||||
return ApplyGuardrailResponse(response_text=response_text)
|
||||
|
|
|
|||
BIN
litellm-proxy-extras/dist/litellm_proxy_extras-0.2.26-py3-none-any.whl
vendored
Normal file
BIN
litellm-proxy-extras/dist/litellm_proxy_extras-0.2.26-py3-none-any.whl
vendored
Normal file
Binary file not shown.
BIN
litellm-proxy-extras/dist/litellm_proxy_extras-0.2.26.tar.gz
vendored
Normal file
BIN
litellm-proxy-extras/dist/litellm_proxy_extras-0.2.26.tar.gz
vendored
Normal file
Binary file not shown.
|
|
@ -0,0 +1,18 @@
|
|||
-- CreateTable
|
||||
CREATE TABLE "LiteLLM_TagTable" (
|
||||
"tag_name" TEXT NOT NULL,
|
||||
"description" TEXT,
|
||||
"models" TEXT[],
|
||||
"model_info" JSONB,
|
||||
"spend" DOUBLE PRECISION NOT NULL DEFAULT 0.0,
|
||||
"budget_id" TEXT,
|
||||
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
|
||||
"created_by" TEXT,
|
||||
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
|
||||
|
||||
CONSTRAINT "LiteLLM_TagTable_pkey" PRIMARY KEY ("tag_name")
|
||||
);
|
||||
|
||||
-- AddForeignKey
|
||||
ALTER TABLE "LiteLLM_TagTable" ADD CONSTRAINT "LiteLLM_TagTable_budget_id_fkey" FOREIGN KEY ("budget_id") REFERENCES "LiteLLM_BudgetTable"("budget_id") ON DELETE SET NULL ON UPDATE CASCADE;
|
||||
|
||||
|
|
@ -1,6 +1,6 @@
|
|||
[tool.poetry]
|
||||
name = "litellm-proxy-extras"
|
||||
version = "0.2.25"
|
||||
version = "0.2.26"
|
||||
description = "Additional files for the LiteLLM Proxy. Reduces the size of the main litellm package."
|
||||
authors = ["BerriAI"]
|
||||
readme = "README.md"
|
||||
|
|
@ -22,7 +22,7 @@ requires = ["poetry-core"]
|
|||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.commitizen]
|
||||
version = "0.2.25"
|
||||
version = "0.2.26"
|
||||
version_files = [
|
||||
"pyproject.toml:version",
|
||||
"../requirements.txt:litellm-proxy-extras==",
|
||||
|
|
|
|||
|
|
@ -18,13 +18,15 @@ from typing import (
|
|||
cast,
|
||||
)
|
||||
|
||||
from openai.types.responses.tool_param import FunctionToolParam
|
||||
|
||||
from litellm import ModelResponse
|
||||
from litellm._logging import verbose_logger
|
||||
from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator
|
||||
from litellm.llms.base_llm.bridges.completion_transformation import (
|
||||
CompletionTransformationBridge,
|
||||
)
|
||||
from litellm.types.llms.openai import Reasoning
|
||||
from litellm.types.llms.openai import ChatCompletionToolParamFunctionChunk, Reasoning
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from openai.types.responses import ResponseInputImageParam
|
||||
|
|
@ -50,6 +52,47 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
|
|||
def __init__(self):
|
||||
pass
|
||||
|
||||
def _handle_raw_dict_response_item(
|
||||
self, item: Dict[str, Any], index: int
|
||||
) -> Tuple[Optional[Any], int]:
|
||||
"""
|
||||
Handle raw dict response items from Responses API (e.g., GPT-5 Codex format).
|
||||
|
||||
Args:
|
||||
item: Raw dict response item with 'type' field
|
||||
index: Current choice index
|
||||
|
||||
Returns:
|
||||
Tuple of (Choice object or None, updated index)
|
||||
"""
|
||||
from litellm.types.utils import Choices, Message
|
||||
|
||||
item_type = item.get("type")
|
||||
|
||||
# Ignore reasoning items for now
|
||||
if item_type == "reasoning":
|
||||
return None, index
|
||||
|
||||
# Handle message items with output_text content
|
||||
if item_type == "message":
|
||||
content_list = item.get("content", [])
|
||||
for content_item in content_list:
|
||||
if isinstance(content_item, dict):
|
||||
content_type = content_item.get("type")
|
||||
if content_type == "output_text":
|
||||
response_text = content_item.get("text", "")
|
||||
msg = Message(
|
||||
role=item.get("role", "assistant"),
|
||||
content=response_text if response_text else ""
|
||||
)
|
||||
choice = Choices(
|
||||
message=msg, finish_reason="stop", index=index
|
||||
)
|
||||
return choice, index + 1
|
||||
|
||||
# Unknown or unsupported type
|
||||
return None, index
|
||||
|
||||
def convert_chat_completion_messages_to_responses_api(
|
||||
self, messages: List["AllMessageValues"]
|
||||
) -> Tuple[List[Any], Optional[str]]:
|
||||
|
|
@ -201,6 +244,11 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
|
|||
if value is not None:
|
||||
if key == "instructions" and instructions:
|
||||
request_data["instructions"] = instructions
|
||||
elif key == "stream_options" and isinstance(value, dict):
|
||||
request_data["stream_options"] = value.get("include_obfuscation")
|
||||
elif key == "user": # string can't be longer than 64 characters
|
||||
if isinstance(value, str) and len(value) <= 64:
|
||||
request_data["user"] = value
|
||||
else:
|
||||
request_data[key] = value
|
||||
|
||||
|
|
@ -221,7 +269,6 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
|
|||
json_mode: Optional[bool] = None,
|
||||
) -> "ModelResponse":
|
||||
"""Transform Responses API response to chat completion response"""
|
||||
|
||||
from openai.types.responses import (
|
||||
ResponseFunctionToolCall,
|
||||
ResponseOutputMessage,
|
||||
|
|
@ -240,19 +287,35 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
|
|||
|
||||
choices: List[Choices] = []
|
||||
index = 0
|
||||
|
||||
reasoning_content: Optional[str] = None
|
||||
|
||||
for item in raw_response.output:
|
||||
|
||||
if isinstance(item, ResponseReasoningItem):
|
||||
pass # ignore for now.
|
||||
|
||||
for content in item.summary:
|
||||
response_text = getattr(content, "text", "")
|
||||
reasoning_content = response_text if response_text else ""
|
||||
|
||||
elif isinstance(item, ResponseOutputMessage):
|
||||
for content in item.content:
|
||||
response_text = getattr(content, "text", "")
|
||||
msg = Message(
|
||||
role=item.role, content=response_text if response_text else ""
|
||||
role=item.role,
|
||||
content=response_text if response_text else "",
|
||||
reasoning_content=reasoning_content,
|
||||
)
|
||||
|
||||
choices.append(
|
||||
Choices(message=msg, finish_reason="stop", index=index)
|
||||
Choices(
|
||||
message=msg,
|
||||
finish_reason="stop",
|
||||
index=index,
|
||||
)
|
||||
)
|
||||
|
||||
reasoning_content = None # flush reasoning content
|
||||
index += 1
|
||||
elif isinstance(item, ResponseFunctionToolCall):
|
||||
msg = Message(
|
||||
|
|
@ -267,12 +330,19 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
|
|||
"type": "function",
|
||||
}
|
||||
],
|
||||
reasoning_content=reasoning_content,
|
||||
)
|
||||
|
||||
choices.append(
|
||||
Choices(message=msg, finish_reason="tool_calls", index=index)
|
||||
)
|
||||
reasoning_content = None # flush reasoning content
|
||||
index += 1
|
||||
elif isinstance(item, dict):
|
||||
# Handle raw dict responses (e.g., from GPT-5 Codex)
|
||||
choice, index = self._handle_raw_dict_response_item(item=item, index=index)
|
||||
if choice is not None:
|
||||
choices.append(choice)
|
||||
else:
|
||||
pass # don't fail request if item in list is not supported
|
||||
|
||||
|
|
@ -447,9 +517,25 @@ class LiteLLMResponsesTransformationHandler(CompletionTransformationBridge):
|
|||
self, tools: List[Dict[str, Any]]
|
||||
) -> List["ALL_RESPONSES_API_TOOL_PARAMS"]:
|
||||
"""Convert chat completion tools to responses API tools format"""
|
||||
responses_tools = []
|
||||
responses_tools: List["ALL_RESPONSES_API_TOOL_PARAMS"] = []
|
||||
for tool in tools:
|
||||
responses_tools.append(tool)
|
||||
# convert function tool from chat completion to responses API format
|
||||
if tool.get("type") == "function":
|
||||
function_tool = cast(
|
||||
ChatCompletionToolParamFunctionChunk, tool.get("function")
|
||||
)
|
||||
responses_tools.append(
|
||||
FunctionToolParam(
|
||||
name=function_tool["name"],
|
||||
parameters=function_tool.get("parameters"),
|
||||
strict=function_tool.get("strict"),
|
||||
type="function",
|
||||
description=function_tool.get("description"),
|
||||
)
|
||||
)
|
||||
else:
|
||||
responses_tools.append(tool) # type: ignore
|
||||
|
||||
return cast(List["ALL_RESPONSES_API_TOOL_PARAMS"], responses_tools)
|
||||
|
||||
def _map_reasoning_effort(self, reasoning_effort: str) -> Optional[Reasoning]:
|
||||
|
|
|
|||
|
|
@ -11,11 +11,10 @@ For batching specific details see CustomBatchLogger class
|
|||
|
||||
import asyncio
|
||||
import os
|
||||
from litellm._uuid import uuid
|
||||
from typing import Any, Dict, Optional
|
||||
|
||||
from typing import Any, Dict, Optional, Tuple
|
||||
|
||||
from litellm._logging import verbose_logger
|
||||
from litellm._uuid import uuid
|
||||
from litellm.integrations.custom_batch_logger import CustomBatchLogger
|
||||
from litellm.llms.custom_httpx.http_handler import (
|
||||
_get_httpx_client,
|
||||
|
|
@ -74,6 +73,8 @@ class PostHogLogger(CustomBatchLogger):
|
|||
)
|
||||
|
||||
api_key, api_url = self._get_credentials_for_request(kwargs)
|
||||
if api_key is None or api_url is None:
|
||||
raise Exception("PostHog credentials not found in kwargs")
|
||||
event_payload = self.create_posthog_event_payload(kwargs)
|
||||
|
||||
headers = {
|
||||
|
|
@ -275,7 +276,7 @@ class PostHogLogger(CustomBatchLogger):
|
|||
|
||||
return self._safe_uuid()
|
||||
|
||||
def _get_credentials_for_request(self, kwargs: Dict[str, Any]) -> tuple[str, str]:
|
||||
def _get_credentials_for_request(self, kwargs: Dict[str, Any]) -> Tuple[Optional[str], Optional[str]]:
|
||||
"""
|
||||
Get PostHog credentials for this request.
|
||||
|
||||
|
|
|
|||
|
|
@ -133,7 +133,6 @@ class LiteLLMMessagesToCompletionTransformationHandler:
|
|||
**kwargs,
|
||||
) -> Union[AnthropicMessagesResponse, AsyncIterator]:
|
||||
"""Handle non-Anthropic models asynchronously using the adapter"""
|
||||
|
||||
completion_kwargs = (
|
||||
LiteLLMMessagesToCompletionTransformationHandler._prepare_completion_kwargs(
|
||||
max_tokens=max_tokens,
|
||||
|
|
|
|||
|
|
@ -672,6 +672,10 @@ class BaseAzureLLM(BaseOpenAILLM):
|
|||
) -> dict:
|
||||
litellm_params = litellm_params or GenericLiteLLMParams()
|
||||
|
||||
# Check if api-key is already in headers; if so, use it
|
||||
if "api-key" in headers:
|
||||
return headers
|
||||
|
||||
api_key = (
|
||||
litellm_params.api_key
|
||||
or litellm.api_key
|
||||
|
|
|
|||
|
|
@ -1,4 +1,4 @@
|
|||
from typing import TYPE_CHECKING, Any, Dict, Literal, Optional, Tuple
|
||||
from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Tuple, Union
|
||||
|
||||
import httpx
|
||||
from openai.types.responses import ResponseReasoningItem
|
||||
|
|
@ -41,12 +41,10 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig):
|
|||
|
||||
def _handle_reasoning_item(self, item: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""
|
||||
Handle reasoning items specifically to filter out status=None using OpenAI's model.
|
||||
Handle reasoning items to filter out the status field.
|
||||
Issue: https://github.com/BerriAI/litellm/issues/13484
|
||||
OpenAI API does not accept ReasoningItem(status=None), so we need to:
|
||||
1. Check if the item is a reasoning type
|
||||
2. Create a ResponseReasoningItem object with the item data
|
||||
3. Convert it back to dict with exclude_none=True to filter None values
|
||||
|
||||
Azure OpenAI API does not accept 'status' field in reasoning input items.
|
||||
"""
|
||||
if item.get("type") == "reasoning":
|
||||
try:
|
||||
|
|
@ -82,6 +80,32 @@ class AzureOpenAIResponsesAPIConfig(OpenAIResponsesAPIConfig):
|
|||
}
|
||||
return filtered_item
|
||||
return item
|
||||
|
||||
def _validate_input_param(
|
||||
self, input: Union[str, ResponseInputParam]
|
||||
) -> Union[str, ResponseInputParam]:
|
||||
"""
|
||||
Override parent method to also filter out 'status' field from message items.
|
||||
Azure OpenAI API does not accept 'status' field in input messages.
|
||||
"""
|
||||
from typing import cast
|
||||
|
||||
# First call parent's validation
|
||||
validated_input = super()._validate_input_param(input)
|
||||
|
||||
# Then filter out status from message items
|
||||
if isinstance(validated_input, list):
|
||||
filtered_input: List[Any] = []
|
||||
for item in validated_input:
|
||||
if isinstance(item, dict) and item.get("type") == "message":
|
||||
# Filter out status field from message items
|
||||
filtered_item = {k: v for k, v in item.items() if k != "status"}
|
||||
filtered_input.append(filtered_item)
|
||||
else:
|
||||
filtered_input.append(item)
|
||||
return cast(ResponseInputParam, filtered_input)
|
||||
|
||||
return validated_input
|
||||
|
||||
def transform_responses_api_request(
|
||||
self,
|
||||
|
|
|
|||
|
|
@ -210,6 +210,7 @@ class AzureAIEmbedding(OpenAIChatCompletion):
|
|||
client=None,
|
||||
aembedding=None,
|
||||
max_retries: Optional[int] = None,
|
||||
shared_session=None,
|
||||
) -> EmbeddingResponse:
|
||||
"""
|
||||
- Separate image url from text
|
||||
|
|
@ -275,6 +276,7 @@ class AzureAIEmbedding(OpenAIChatCompletion):
|
|||
else None
|
||||
),
|
||||
aembedding=aembedding,
|
||||
shared_session=shared_session,
|
||||
)
|
||||
|
||||
text_embedding_responses = response.data
|
||||
|
|
|
|||
|
|
@ -13,13 +13,13 @@ from typing import (
|
|||
cast,
|
||||
)
|
||||
|
||||
from litellm._logging import verbose_logger
|
||||
import httpx # type: ignore
|
||||
|
||||
import litellm
|
||||
import litellm.litellm_core_utils
|
||||
import litellm.types
|
||||
import litellm.types.utils
|
||||
from litellm._logging import verbose_logger
|
||||
from litellm.litellm_core_utils.realtime_streaming import RealTimeStreaming
|
||||
from litellm.llms.base_llm.anthropic_messages.transformation import (
|
||||
BaseAnthropicMessagesConfig,
|
||||
|
|
@ -239,7 +239,7 @@ class BaseLLMHTTPHandler:
|
|||
json_mode: bool = False,
|
||||
signed_json_body: Optional[bytes] = None,
|
||||
shared_session: Optional["ClientSession"] = None,
|
||||
):
|
||||
):
|
||||
if client is None:
|
||||
verbose_logger.debug(
|
||||
f"Creating HTTP client with shared_session: {id(shared_session) if shared_session else None}"
|
||||
|
|
@ -1533,6 +1533,7 @@ class BaseLLMHTTPHandler:
|
|||
data=data,
|
||||
fake_stream=fake_stream,
|
||||
)
|
||||
|
||||
response = sync_httpx_client.post(
|
||||
url=api_base,
|
||||
headers=headers,
|
||||
|
|
|
|||
|
|
@ -161,6 +161,10 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
|
|||
) -> ResponsesAPIResponse:
|
||||
"""No transform applied since outputs are in OpenAI spec already"""
|
||||
try:
|
||||
logging_obj.post_call(
|
||||
original_response=raw_response.text,
|
||||
additional_args={"complete_input_dict": {}},
|
||||
)
|
||||
raw_response_json = raw_response.json()
|
||||
raw_response_json["created_at"] = _safe_convert_created_field(
|
||||
raw_response_json["created_at"]
|
||||
|
|
@ -169,7 +173,13 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
|
|||
raise OpenAIError(
|
||||
message=raw_response.text, status_code=raw_response.status_code
|
||||
)
|
||||
return ResponsesAPIResponse.model_construct(**raw_response_json)
|
||||
try:
|
||||
return ResponsesAPIResponse(**raw_response_json)
|
||||
except Exception:
|
||||
verbose_logger.debug(
|
||||
f"Error constructing ResponsesAPIResponse: {raw_response_json}, using model_construct"
|
||||
)
|
||||
return ResponsesAPIResponse.model_construct(**raw_response_json)
|
||||
|
||||
def validate_environment(
|
||||
self, headers: dict, model: str, litellm_params: Optional[GenericLiteLLMParams]
|
||||
|
|
|
|||
|
|
@ -4841,7 +4841,7 @@
|
|||
"input_cost_per_token_above_200k_tokens": 6e-06,
|
||||
"litellm_provider": "anthropic",
|
||||
"max_input_tokens": 1000000,
|
||||
"max_output_tokens": 1000000,
|
||||
"max_output_tokens": 64000,
|
||||
"max_tokens": 1000000,
|
||||
"mode": "chat",
|
||||
"output_cost_per_token": 1.5e-05,
|
||||
|
|
@ -13074,34 +13074,6 @@
|
|||
"supports_vision": true,
|
||||
"supports_web_search": true
|
||||
},
|
||||
"gpt-5-codex": {
|
||||
"cache_read_input_token_cost": 1.25e-07,
|
||||
"input_cost_per_token": 1.25e-06,
|
||||
"litellm_provider": "openai",
|
||||
"max_input_tokens": 400000,
|
||||
"max_output_tokens": 128000,
|
||||
"max_tokens": 128000,
|
||||
"mode": "chat",
|
||||
"output_cost_per_token": 1e-05,
|
||||
"supported_endpoints": [
|
||||
"/v1/responses"
|
||||
],
|
||||
"supported_modalities": [
|
||||
"text",
|
||||
"image"
|
||||
],
|
||||
"supported_output_modalities": [
|
||||
"text"
|
||||
],
|
||||
"supports_function_calling": true,
|
||||
"supports_native_streaming": true,
|
||||
"supports_parallel_function_calling": true,
|
||||
"supports_prompt_caching": true,
|
||||
"supports_reasoning": true,
|
||||
"supports_response_schema": true,
|
||||
"supports_system_messages": true,
|
||||
"supports_tool_choice": true
|
||||
},
|
||||
"gpt-5-2025-08-07": {
|
||||
"cache_read_input_token_cost": 1.25e-07,
|
||||
"cache_read_input_token_cost_flex": 6.25e-08,
|
||||
|
|
@ -19710,6 +19682,22 @@
|
|||
"mode": "embedding",
|
||||
"output_cost_per_token": 0.0
|
||||
},
|
||||
"together_ai/baai/bge-base-en-v1.5": {
|
||||
"input_cost_per_token": 8e-09,
|
||||
"litellm_provider": "together_ai",
|
||||
"max_input_tokens": 512,
|
||||
"mode": "embedding",
|
||||
"output_cost_per_token": 0.0,
|
||||
"output_vector_size": 768
|
||||
},
|
||||
"together_ai/BAAI/bge-base-en-v1.5": {
|
||||
"input_cost_per_token": 8e-09,
|
||||
"litellm_provider": "together_ai",
|
||||
"max_input_tokens": 512,
|
||||
"mode": "embedding",
|
||||
"output_cost_per_token": 0.0,
|
||||
"output_vector_size": 768
|
||||
},
|
||||
"together-ai-up-to-4b": {
|
||||
"input_cost_per_token": 1e-07,
|
||||
"litellm_provider": "together_ai",
|
||||
|
|
@ -20212,12 +20200,12 @@
|
|||
},
|
||||
"us.anthropic.claude-sonnet-4-5-20250929-v1:0": {
|
||||
"cache_creation_input_token_cost": 4.125e-06,
|
||||
"cache_read_input_token_cost": 33e-07,
|
||||
"input_cost_per_token": 33e-06,
|
||||
"input_cost_per_token_above_200k_tokens": 66e-06,
|
||||
"cache_read_input_token_cost": 3.3e-07,
|
||||
"input_cost_per_token": 3.3e-06,
|
||||
"input_cost_per_token_above_200k_tokens": 6.6e-06,
|
||||
"output_cost_per_token_above_200k_tokens": 2.475e-05,
|
||||
"cache_creation_input_token_cost_above_200k_tokens": 8.25e-06,
|
||||
"cache_read_input_token_cost_above_200k_tokens": 66e-07,
|
||||
"cache_read_input_token_cost_above_200k_tokens": 6.6e-07,
|
||||
"litellm_provider": "bedrock_converse",
|
||||
"max_input_tokens": 200000,
|
||||
"max_output_tokens": 64000,
|
||||
|
|
|
|||
|
|
@ -355,12 +355,12 @@ class MCPServerManager:
|
|||
)
|
||||
|
||||
# Update tool name to server name mapping (for both prefixed and base names)
|
||||
self.tool_name_to_mcp_server_name_mapping[
|
||||
base_tool_name
|
||||
] = server_prefix
|
||||
self.tool_name_to_mcp_server_name_mapping[
|
||||
prefixed_tool_name
|
||||
] = server_prefix
|
||||
self.tool_name_to_mcp_server_name_mapping[base_tool_name] = (
|
||||
server_prefix
|
||||
)
|
||||
self.tool_name_to_mcp_server_name_mapping[prefixed_tool_name] = (
|
||||
server_prefix
|
||||
)
|
||||
|
||||
registered_count += 1
|
||||
verbose_logger.debug(
|
||||
|
|
@ -1276,7 +1276,7 @@ class MCPServerManager:
|
|||
get_prisma_client_or_throw,
|
||||
)
|
||||
|
||||
verbose_logger.info("Loading MCP servers from database into registry...")
|
||||
verbose_logger.debug("Loading MCP servers from database into registry...")
|
||||
|
||||
# perform authz check to filter the mcp servers user has access to
|
||||
prisma_client = get_prisma_client_or_throw(
|
||||
|
|
@ -1292,7 +1292,9 @@ class MCPServerManager:
|
|||
)
|
||||
self.add_update_server(server)
|
||||
|
||||
verbose_logger.info(f"Registry now contains {len(self.get_registry())} servers")
|
||||
verbose_logger.debug(
|
||||
f"Registry now contains {len(self.get_registry())} servers"
|
||||
)
|
||||
|
||||
def get_mcp_server_by_id(self, server_id: str) -> Optional[MCPServer]:
|
||||
"""
|
||||
|
|
|
|||
|
|
@ -1,12 +1,18 @@
|
|||
import json
|
||||
from typing import Any, Callable, Dict, List, Optional
|
||||
|
||||
from mcp.types import Tool as MCPToolSDKTool
|
||||
from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional
|
||||
|
||||
from litellm._logging import verbose_logger
|
||||
from litellm.proxy.types_utils.utils import get_instance_fn
|
||||
from litellm.types.mcp_server.tool_registry import MCPTool
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from mcp.types import Tool as MCPToolSDKTool
|
||||
else:
|
||||
try:
|
||||
from mcp.types import Tool as MCPToolSDKTool
|
||||
except ImportError:
|
||||
MCPToolSDKTool = None # type: ignore
|
||||
|
||||
|
||||
class MCPToolRegistry:
|
||||
"""
|
||||
|
|
@ -55,7 +61,11 @@ class MCPToolRegistry:
|
|||
|
||||
def convert_tools_to_mcp_sdk_tool_type(
|
||||
self, tools: List[MCPTool]
|
||||
) -> List[MCPToolSDKTool]:
|
||||
) -> List["MCPToolSDKTool"]:
|
||||
if MCPToolSDKTool is None:
|
||||
raise ImportError(
|
||||
"MCP SDK is not installed. Please install it with: pip install 'litellm[proxy]'"
|
||||
)
|
||||
return [
|
||||
MCPToolSDKTool(
|
||||
name=tool.name,
|
||||
|
|
|
|||
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|
@ -0,0 +1 @@
|
|||
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|
||||
|
|
@ -1 +0,0 @@
|
|||
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|
||||
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|
|
@ -0,0 +1 @@
|
|||
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|
||||
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Add table
Reference in a new issue